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        "answer": "Full story is available in a 2-part episode of the Big Compute Podcast:* [A Cloud Startup Story (Part 1)](https://www.bigcompute.org/podcast/a-cloud-startup-story-part-1)* [A Cloud Startup Story (Part 2)](https://www.bigcompute.org/podcast/a-cloud-startup-story-part-2)"
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        "title": "This Startup Says It Can Reshape How Companies Do R&D. Tech Luminaries Agree.",
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    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1544068971,
    "tags": [
      "Developer Tools",
      "API"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2019",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Fully Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": [
      {
        "question": "How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)",
        "answer": "Tony, the CEO, worked on CMS tools for years (WordPress, Drupal, etc) and found the process of building websites with legacy CMS systems daunting. He started building Cosmic to have an API-powered CMS that enabled content to be delivered to any website or app."
      },
      {
        "question": "How did you decide to apply to Y Combinator? What was your experience applying, going through the batch, and fundraising at demo day?",
        "answer": "We had showed our product to various developers that we thought would give us good feedback. One of their best points of feedback was to apply to YC. Doing YC was a great experience. Being apart of the network, events, staying connected though Bookface, finding quality candidates to join us on our mission, has been hugely beneficial."
      },
      {
        "question": "How have you kept in touch with the YC community and continued to use YC resources & programs since the batch ended?",
        "answer": "We haven’t kept in touch with group partners or other YC batch mates, however we have certainly stayed connected on Bookface and have used it as a way to source talent to join our team, and keep up with the latest startup advice and latest news."
      },
      {
        "question": "What's the history of your company from getting started until the present day? What were the big inflection points?",
        "answer": "It’s been ups and downs, but it has trended up!"
      },
      {
        "question": "What is the core problem you are solving? Why is this a big problem? What made you decide to work on it?",
        "answer": "We believe that content is still king. Cosmic provides a way to build content powered websites and apps faster and easier. Businesses that use Cosmic have found themselves unblocked with their content ops, enabling them to move faster to market, and giving them an unfair advantage in the marketplace."
      },
      {
        "question": "What is your long-term vision? If you truly succeed, what will be different about the world?",
        "answer": "We see a world where content powered apps will be easier than ever to build with three layers provided by Cosmic:1. A service that gives developers and content teams a strong foundation will a scalable dashboard, API, and asset management service.2. A marketplace that enables teams to leverage the Cosmic community to build the best websites and apps on the internet.3. An integration network that enables effortless connections to 3rd-party services to enable faster deployment and automation to reach customers all over the world.When we have achieved these goals, the world will have the most optimized developer experience for building content powered websites and apps, development will be faster, easier, and cheaper, and the web user experience will be better all over the world."
      }
    ],
    "url": "https://www.ycombinator.com/companies/cosmic",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2019/cosmic.json",
    "year_founded": 2016,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/cosmicjs",
    "x_url": "https://twitter.com/cosmicjs",
    "fb_url": "https://facebook.com/cosmicjs",
    "cb_url": "https://www.crunchbase.com/organization/cosmic-js",
    "github_url": "https://github.com/cosmicjs",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/9a999bf9f887684e2cad49138c36cf7abb029831.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": null,
    "founders": [
      {
        "user_id": 106867,
        "full_name": "Tony Spiro",
        "title": "Founder/CEO",
        "founder_bio": "My name is Tony Spiro (Cosmic W2019) I'm interested in solving problems with technology. Find me on Twitter: @tonyspiro",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/tonyspiro/",
        "x_url": "https://twitter.com/tonyspiro",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/88375175a2b0e56f30b346d525b91839d1448d25.jpg"
      }
    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 93336,
        "title": "The Cosmic AI Platform: A complete AI-enabled app development & deployment platform",
        "tagline": "Build and deploy content-powered apps using natural language",
        "body": "![uploaded image](/media/?type=post&id=93336&key=user_uploads/106867/4bc9f675-53e8-4b40-b98a-0c27776d5519)\n\nHello,\n\nI'm Tony, CEO at Cosmic. We're excited to announce the launch of the Cosmic AI Platform, a revolutionary system that transforms how you create content, build, and deploy applications.\n\nThe Cosmic AI Platform reinvents what a CMS can be - it's now a complete AI-enabled application development and deployment platform. Build and deploy anything you can imagine using natural language, in minutes.\n\nKey features:\n\n* AI Content Studio: Generate complete content models and content from natural language descriptions\n* AI-Powered Development: Build applications with Next.js, React, Astro, and Vue.js using AI\n* Full Deployment Pipeline: GitHub integration, Vercel deployments, environment management, and domain services\n\nThe platform is available now on all Cosmic accounts. We've increased our free tier to 300k tokens (up from 10k) so you can try these new capabilities.\n\n[Log in to the Cosmic](https://app.cosmicjs.com/login) dashboard to try it out. and read more about the release [here](https://www.cosmicjs.com/blog/introducing-the-cosmic-ai-platform). We'd love to get your feedback!\n\nTony Spiro\n\nRead below to learn more about the release.\n\n## AI Studio\n\n### Content Model Generation\n\n![uploaded image](/media/?type=post&id=93336&key=user_uploads/106867/10991c4f-d305-481b-a8f6-c8f4d8ac13ae)\n\nThe AI Studio generates complete content structures from natural language descriptions. Instead of manually configuring fields, relationships, and validation rules, you can describe what you need and receive a fully functional content model with multiple content types, relationships, and demo content to get started fast.\n\n**Content model capabilities:**\n\n* Generate content models for any type of website or application\n* Add new content types that integrate with existing structures\n* Configure relationships between content types automatically\n* Create complex multi-language structures with custom validation\n\n**Working examples:**\n\n* \"Create a content model for an e-commerce store with products, collections, and customer reviews\"\n* \"Add an Events content model that relates to my existing blog posts and authors\"\n* \"Set up a portfolio website with projects, skills, and testimonials\"\n\n### Content Management\n\n![uploaded image](/media/?type=post&id=93336&key=user_uploads/106867/236b7d58-61c4-46ac-bd24-6deb0b96b05e)\n\nBeyond structure creation, the AI handles content generation and management at scale.\n\n**Content operations:**\n\n* Generate realistic sample content for testing and development\n* Bulk update existing content with new fields and metadata\n* Maintain consistency across large content datasets\n* Apply SEO optimization and structured data automatically\n\n**Practical applications:**\n\n* \"Create 10 sample blog posts with realistic content for my existing blog model\"\n* \"Update all product entries to include pricing and availability status\"\n\n## Application Development and Deployment\n\n### AI-Powered Code Generation\n\n![uploaded image](/media/?type=post&id=93336&key=user_uploads/106867/cad24796-508e-4028-9aa1-5101dd5729aa)\n\nThe Cosmic AI Platform generates production-ready applications using your existing content structure. Applications are built with modern frameworks and include proper TypeScript definitions, responsive design, and performance optimizations.\n\n**Supported frameworks:**\n\n* Next.js applications with server-side rendering\n* React dashboards and single-page applications\n* Astro static sites with modern tooling\n* Vue.js progressive web applications\n\n### GitHub Repository Integration\n\nConnect existing GitHub repositories or create new ones with full workflow support and deployment preview capabilities.\n\n**Repository management:**\n\n* Connect private and public GitHub repositories\n* Access repositories from all GitHub organizations\n* Branch detection and management\n* Protected branch support with pull request workflows\n\n### Deployment Pipeline\n\nApplications deploy through an integrated pipeline with enterprise-level capabilities.\n\n**Deployment capabilities:**\n\n* Vercel integration with automatic deployments\n* Preview URLs for every deployment\n* Environment variable management across deployment targets\n* Real-time deployment logs and monitoring\n* Custom domain assignment and management\n* Pull request preview deployments\n\n### Environment Configuration\n\nManage application configuration securely across all deployment environments.\n\n**Environment management:**\n\n* Add, edit, and remove environment variables\n* Target-specific configuration for production, preview, and development\n* Encrypted storage for sensitive information\n* Bulk operations for efficient management\n\n### Domain Management\n\nComplete deployment workflow includes integrated domain services.\n\n**Domain capabilities:**\n\n* Domain purchase directly from the platform\n* Automatic DNS configuration\n* SSL certificate provisioning\n* Custom domain assignment to deployments\n\n## A New Era for CMS\n\nThe Cosmic AI Platform represents a new approach to content management and application development. The integration of AI throughout the entire workflow—from content modeling to deployment—provides capabilities that weren't previously available in a single platform.\n\nThe system is designed for teams that need to move quickly from concept to production while maintaining code quality, deployment reliability, and security. Whether building content sites, applications, or complex multi-tenant systems, the platform provides the tools necessary for modern development workflows.\n\n## Next steps\n\nTo get started with the new Cosmic AI Platform [log in to your Cosmic account](https://app.cosmicjs.com/login) and find the new links to the AI content studio and code development pages, available on all accounts and plans. And see what others in the Cosmic community are building on the [Community page](https://www.cosmicjs.com/community). We're excited to see what you build with the Cosmic AI Platform.",
        "url": "https://www.ycombinator.com/launches/OHQ-the-cosmic-ai-platform-a-complete-ai-enabled-app-development-deployment-platform",
        "votes": 6,
        "created_at": "2025-08-27T13:44:29.511Z"
      },
      {
        "id": 71785,
        "title": "🚀 Cosmic - Headless CMS and API toolkit v2.0",
        "tagline": "Cosmic is an API-first content management system (CMS). We provide a web dashboard to create content, and API tools to deliver content to any website or app. ",
        "body": "**tl;dr:** We just launched Cosmic 2.0 which includes a whole new Cosmic headless CMS dashboard, API, documentation, and website.\n\n* 👥 [Sign up for a Cosmic account](http://app.cosmicjs.com/signup) to begin creating content in the dashboard and get your API access keys.\n* 🌐 [Check out the new website](http://www.cosmicjs.com/) and [documentation](https://www.cosmicjs.com/docs) to learn how to integrate Cosmic content into your website or app.\n\n![uploaded image](/media/?type=post&id=71785&key=user_uploads/106867/b2ca8224-cd3f-4134-8f48-3e298b0655d2)\n\nHello everyone! We are excited to announce Cosmic 2.0. This release is the result of two years of dedicated work by our team which we are proud to share with you.\n\n### What is Cosmic?\n\nCosmic is a headless CMS and API toolkit. We provide a web dashboard to create content, and API tools to deliver content to any website or app. Customers use Cosmic as their CMS to avoid the pain of building and maintaining their own CMS.\n\n![uploaded image](/media/?type=post&id=71785&key=user_uploads/106867/49876f0a-8982-42a4-8ec8-9e52277d9ea6)\n\n### 🛠️ What can you build with Cosmic?\n\nUse Cosmic to manage and deliver content to a number of applications such as company websites, mobile apps, ecommerce sites, blogs, and more.\n\n![uploaded image](/media/?type=post&id=71785&key=user_uploads/106867/40544c8b-a4c5-46be-80e2-b6481ba3baac)\n\n\n### What’s in Cosmic 2.0?\n\n**New dashboard:** Cosmic 2.0 includes a completely rebuilt web dashboard. We’ve redesigned the experience to be as enjoyable as possible. A view from [the dashboard](https://app.cosmicjs.com/signup):\n\n![uploaded image](/media/?type=post&id=71785&key=user_uploads/106867/bc1a8c39-66a7-49a0-8e0a-2a8e4bf7b861)\n\n**New API and API docs:** We’ve updated our API to v3 which includes a completely new [JavaScript SDK](https://www.npmjs.com/package/@cosmicjs/sdk) which makes fetching, adding, editing, and deleting content easier than ever. A view from [the API](https://www.cosmicjs.com/docs/api) [docs](https://www.cosmicjs.com/docs):\n\n![uploaded image](/media/?type=post&id=71785&key=user_uploads/106867/b90405b9-f3b9-4f2c-997a-de8780f3bc30)\n\n**Develop:** flexible and powerful content modeling. Build your content model with various field types such as text, rich text, markdown, image, video, audio, relationships, and more.\n\n![uploaded image](/media/?type=post&id=71785&key=user_uploads/106867/cf730736-e4d6-46ee-a441-1faed79d3cfe)\n\nUse Cosmic to store and deliver media for your applications including images, video, audio, documents and more. Image processing and optimization is included with all plans.\n\n![uploaded image](/media/?type=post&id=71785&key=user_uploads/106867/0ec208a9-8ddb-42b3-a118-02a468f26941)\n\n**Collaborate** with your team with flexible user access controls and permissions.\n\n![uploaded image](/media/?type=post&id=71785&key=user_uploads/106867/98bed501-943d-4d46-9b7b-9f5f9fe66e73)\n\n**Deliver** your content to the world with our built-in API and global CDN with points of presence all over the globe.\n\n![uploaded image](/media/?type=post&id=71785&key=user_uploads/106867/92f7a8e6-c9e2-4b7f-a69d-a30a34f34794)\n\n**Our customers**\\\nWe are proud to serve teams around the world. Content is universal, it is crucial for businesses to reach their customers, and they trust Cosmic to store and deliver their mission-critical content.\n\n![uploaded image](/media/?type=post&id=71785&key=user_uploads/106867/0345bd05-0a47-4b51-a5f2-f067c8d5226b)\n\n**Our team**\\\nWe are proud of our Cosmic 2.0 release and can’t wait to see what you build with it. We are just getting started!\n\n![uploaded image](/media/?type=post&id=71785&key=user_uploads/106867/99e5d621-d1db-440a-a4f9-47a7500084ad)\n\n**🚀 Sign up**\\\nSign up for Cosmic 2.0 at <https://app.cosmicjs.com/signup>. If you have any questions, or would like to talk to sales about custom plans and options, go to <https://www.cosmicjs.com/contact>.",
        "url": "https://www.ycombinator.com/launches/Ifp-cosmic-headless-cms-and-api-toolkit-v2-0",
        "votes": 12,
        "created_at": "2023-05-23T17:23:03.181Z"
      }
    ]
  },
  {
    "id": 12509,
    "name": "PopSQL",
    "slug": "popsql",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/79a599a24d933d5f21dc134891224337e7ef167a.png",
    "website": "https://popsql.com",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "Every company wants to use data to make informed decisions, and SQL is the lingua franca for data. However, data collaboration is broken. People are rewriting each other's queries, switching apps to visualize their data, and copying/pasting SQL into Slack.\r\n\r\nPopSQL solves this by creating a beautiful, fun way to write SQL, visualize data, and share results. The product is loved by data teams from over 2000 companies including DoorDash, Shipt, Redfin, and Optimizely. What we've built so far is just the beginning. Join us and build a great product, a great culture, and a great company 🚀",
    "one_liner": "SQL editor for teams",
    "team_size": 15,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1554325626,
    "tags": [
      "Developer Tools",
      "SaaS",
      "Analytics"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2019",
    "status": "Acquired",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Fully Remote"
    ],
    "stage": "Growth",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/popsql",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2019/popsql.json",
    "year_founded": 2017,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://linkedin.com/company/popsql",
    "x_url": "https://twitter.com/popsql",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/popsql",
    "github_url": "https://github.com/popsql",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/79a599a24d933d5f21dc134891224337e7ef167a.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": null,
    "founders": [
      {
        "user_id": 37966,
        "full_name": "Rahil Sondhi",
        "title": "Founder/CEO",
        "founder_bio": "Founder/CEO PopSQL",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/rahilsondhi/",
        "x_url": "https://twitter.com/rahilsondhi",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/524481981bf0dd6564fd980c5bb52282894fdd13.jpg"
      }
    ],
    "jobs": [],
    "news": [
      {
        "title": "Building the Best PostgreSQL GUI: PopSQL Joins Timescale",
        "url": "https://www.timescale.com/blog/best-postgresql-gui-popsql-joins-timescale/",
        "date": "Apr 04, 2024"
      },
      {
        "title": "PopSQL aims to be a modern data team’s best friend – TechCrunch",
        "url": "https://techcrunch.com/2022/02/09/popsql-aims-to-be-a-modern-data-teams-best-friend/",
        "date": "Feb 09, 2022"
      }
    ],
    "launches": []
  },
  {
    "id": 12534,
    "name": "Courier",
    "slug": "courier",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/947167fc07350afdc803e650746e6c0c278e9937.png",
    "website": "https://www.courier.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Courier is the fastest way for developers to build notifications for their app. Our APIs take the tedium out of integrating various notification channels, while our visual designer lets anyone design a message template and deliver their notifications to the best channel for each user with a single API call. Email, Push, In-App, Slack, SMS, you name it. Think \"Stripe, for notifications.\"",
    "one_liner": "The fastest way for developers to build notifications for their app.",
    "team_size": 35,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1555992833,
    "tags": [
      "Developer Tools",
      "Messaging"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2019",
    "status": "Acquired",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Partly Remote"
    ],
    "stage": "Growth",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/courier",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2019/courier.json",
    "year_founded": 2019,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/trycourier",
    "x_url": "https://www.twitter.com/trycourier",
    "fb_url": "https://www.facebook.com/trycourier",
    "cb_url": "https://www.crunchbase.com/organization/try-courier",
    "github_url": "https://github.com/trycourier",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/947167fc07350afdc803e650746e6c0c278e9937.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
    },
    "founders": [
      {
        "user_id": 310199,
        "full_name": "Troy Goode",
        "title": "Founder",
        "founder_bio": "Founder & CEO @ Courier (YC S19)",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/troygoode",
        "x_url": "https://twitter.com/troygoode",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/40854b4b0aabeae1b31298fa18e2b977af33fbcf.jpg"
      }
    ],
    "jobs": [],
    "news": [
      {
        "title": "Courier lands $35M to build a service for app notifications – TechCrunch",
        "url": "https://techcrunch.com/2022/06/22/courier-lands-35m-to-build-a-service-for-app-notifications/",
        "date": "Jun 22, 2022"
      },
      {
        "title": "Launch HN: Courier (YC S19) – Developer infrastructure for product notifications",
        "url": "https://news.ycombinator.com/item?id=30527757",
        "date": "Mar 24, 2022"
      },
      {
        "title": " Courier - WUPHF 2_0, building notifications that don’t suck! | Product Hunt",
        "url": "https://www.producthunt.com/posts/courier-3",
        "date": "Jun 24, 2021"
      },
      {
        "title": "Courier raises $10.1M Series A | TechCrunch",
        "url": "https://techcrunch.com/2020/09/14/courier-raises-10-1m-series-a-to-help-developers-integrate-multi-channel-notifications/",
        "date": "Sep 14, 2020"
      }
    ],
    "launches": []
  },
  {
    "id": 12550,
    "name": "Kraftful",
    "slug": "kraftful",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fd3dcfbc4e3832c69cd097d276e4519742e599c7.png",
    "website": "http://www.kraftful.com/",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "Helping product builders to listen to users at scale so they can make something people want.",
    "one_liner": "Copilot for product teams",
    "team_size": 6,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1556079534,
    "tags": [
      "Generative AI",
      "B2B",
      "NLP",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2019",
    "status": "Acquired",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Fully Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/kraftful",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2019/kraftful.json",
    "year_founded": null,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/kraftful",
    "x_url": "https://twitter.com/kraftful",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/kraftful",
    "github_url": "https://github.com/kraftful",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/fd3dcfbc4e3832c69cd097d276e4519742e599c7.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": null,
    "founders": [
      {
        "user_id": 331211,
        "full_name": "Yana Welinder",
        "title": "Founder/CEO",
        "founder_bio": "Founder & CEO of Kraftful (acquired by Amplitude)\n\nBefore starting Kraftful, I led product at a range of tech companies, from being PM #2 at a fast-growing unicorn to heading product teams building products used by millions. That experience inspired me to start Kraftful, to help product teams ship products people love.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/ywelinder/",
        "x_url": "https://twitter.com/yanabana",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0e5d63bea02c5d76b2ceeacb637f7de78a5dad44.jpg"
      }
    ],
    "jobs": [],
    "news": [
      {
        "title": "Amplitude Acquires Kraftful to Power Customer-First Product Building | Amplitude",
        "url": "https://amplitude.com/blog/amplitude-acquires-kraftful",
        "date": "Jul 10, 2025"
      },
      {
        "title": "Kraftful is one of Fast Company's Most Innovative Companies of 2024",
        "url": "https://www.fastcompany.com/91030328/kraftful-most-innovative-companies-2024",
        "date": "Mar 19, 2024"
      },
      {
        "title": "A new generation of Silicon Valley designers is racing to build AI’s n",
        "url": "https://www.fastcompany.com/90931154/a-new-generation-of-silicon-valley-designers-is-racing-to-build-ais-next-big-thing",
        "date": "Aug 16, 2023"
      }
    ],
    "launches": [
      {
        "id": 91584,
        "title": "Kraftful Inbox for all your user feedback",
        "tagline": "Build something people want, by listening to users at scale.",
        "body": "**TLDR**\\\nKraftful Inbox automatically gathers, analyzes, and prioritizes user feedback from every channel, instantly turning insights into Jira/Linear tickets. One place for all user insights.\n\n[https://youtu.be/hiIJIGgvdMk?si=BaDElfjt6iE_ots9](https://youtu.be/hiIJIGgvdMk?si=BaDElfjt6iE_ots9%5C)\n\n**Problem**\\\nCollecting user feedback from user interviews, surveys, app reviews, sales calls, support tickets is messy and exhausting. Most teams give up entirely.\n\nNow you don’t have to.\n\n**Solution**\\\nKraftful Inbox automatically pulls in feedback from sales calls, user interviews, support tickets, surveys, app reviews, Reddit, Discord, even Slack conversations with customers.\n\nEvery day, it analyzes feedback to surface the most important feature requests, bugs, pain points, and insights—then suggests exactly how they fit into your roadmap.\n\nWant to act fast? Instantly turn any insight into a Jira or Linear ticket.\n\nYour Inbox updates daily, consolidating fresh insights, counting how often each issue arises, and linking directly to relevant context.\n\nPlug in your CRM to tie feedback directly to revenue impact. Spot trends, manage feedback seamlessly, and maintain a single source of truth for user insights.\n\nLoved by 50,000+ product teams.\\\nSee why: [kraftful.com](http://kraftful.com)",
        "url": "https://www.ycombinator.com/launches/NpA-kraftful-inbox-for-all-your-user-feedback",
        "votes": 99,
        "created_at": "2025-06-24T16:41:53.594Z"
      },
      {
        "id": 84241,
        "title": "Social Apps Research by Kraftful",
        "tagline": "Learn what users want from app reviews of TikTok, X, Facebook, and other social apps.",
        "body": "**TL;DR:** Kraftful AI handles the tedious product work so that you can focus on strategy and product craft. Now, it also helps with [market research for social apps](http://www.kraftful.com/marketresearch/social-media).\n\n![uploaded image](/media/?type=post&id=84241&key=user_uploads/331211/1003a0bb-165b-4ba9-bca5-8368a7226b10)\n\n# Who has the bandwidth to read app store reviews?\n\nApp store reviews are full of insights about what users want from different products. But for product builders, sifting through thousands of reviews to prioritize features is nearly impossible.\n\nSince launching Kraftful’s AI-powered feedback analysis, our customers have been using it to quickly gather and learn from app reviews, including those of their competitors.\n\nTaking their feedback to heart, we’ve now made it even easier to get these valuable competitor insights directly through Kraftful.\n\n# Insights from hundreds of thousands of reviews\n\nToday, we’re excited to launch the second part of our market research: social media apps.\n\nKraftful has analyzed hundreds of thousands of app reviews to summarize:\n\n1. The most requested features in social apps.\n2. The most common complaints about the top social apps.\n3. What users care about most in a social app.\n\nYou can explore summaries for the entire social category or dive into specific apps like TikTok, X, Threads, Facebook, LinkedIn, and more.\n\n**Next up:** dating apps!\n\nWe initially focused on design tools and intended to survey various other B2B solutions. But after reading [Michael Seibel’s post](https://x.com/mwseibel/status/1835063692117103090) that this is the time for consumer products, we quickly pivoted to focus on the consumer market.\n\nBut we’d love to hear from you—what categories are you curious about, and what insights would be most helpful? (respond to a [Kraftful AI interview](https://klever.kraftful.com/surveys-public/marketresearch) 👍)",
        "url": "https://www.ycombinator.com/launches/Luj-social-apps-research-by-kraftful",
        "votes": 12,
        "created_at": "2024-09-23T21:31:32.951Z"
      },
      {
        "id": 84112,
        "title": "Market Research by Kraftful",
        "tagline": "Learn what users want from online reviews in a product category. ",
        "body": "**TL;DR:** Kraftful AI handles the tedious product work so that you can focus on strategy and product craft. Now, [it also helps with market research](https://www.kraftful.com/marketresearch/design).\n\n![uploaded image](/media/?type=post&id=84112&key=user_uploads/331211/d1f1ce12-47df-455d-88f8-269071aa5fd7)\n\n# Who has the time for market research?\n\nWhen building a product, the internet is packed with reviews about what users want. \n\nBut let’s be honest, who has time to find and sift through it all?\n\nSince launching Kraftful’s AI analysis for user feedback, many of our customers have used it to gather and analyze public reviews from competitors on app stores, G2, and Trustpilot.\n\nListening to our customers, we’ve made it even easier to get these insights directly from Kraftful.\n\n# Key insights from thousands of G2 reviews\n\nToday, we’re excited to launch the first part of our [market research](https://www.kraftful.com/marketresearch/design), starting with SaaS tools for **design**.\n\nKraftful has analyzed thousands of G2 reviews to summarize:\n\n1\\. The most requested features in design tools.\n\n2\\. The most common complaints about top design tools.\n\n3\\. What users care about most in a design tool.\n\nYou can explore summaries for the entire design tool category or dive into specific tools like Figma, Canva, and more.\n\n**Next up:** marketing tools! \n\nBut we’d love to hear from you—what categories are you curious about, and what insights would be most helpful? (respond to a [Kraftful AI interview](https://klever.kraftful.com/surveys-public/marketresearch) 👍)\n\n![uploaded image](/media/?type=post&id=84112&key=user_uploads/331211/941c595c-ab21-4625-b385-0f7841dd551d)\n\n",
        "url": "https://www.ycombinator.com/launches/Lse-market-research-by-kraftful",
        "votes": 19,
        "created_at": "2024-09-18T15:08:37.784Z"
      },
      {
        "id": 83412,
        "title": "Kraftful 3.0 — Build loved products ❤️",
        "tagline": "Use AI to listen to your users and integrate what you learn directly into your dev process.",
        "body": "**TL;DR:** Kraftful AI handles the tedious product work, so you can focus on strategy and product craft.\n\nTry it for free at [kraftful.com](http://kraftful.com).\n\n[Here’s a 3 min demo](https://youtu.be/0b5Xi1xb11A).\n\n**The Problem:**\n\nListening to users and acting on their feedback is tough.\n\nYC constantly reminds us to talk to users because it’s challenging.\n\nEven when you prioritize it, users often don’t have the time to tell you what they need.\n\nWhen they do, it’s scattered across different channels, making it hard to turn troubleshooting conversations into actionable “what should we build next” decisions.\n\nThe larger your company gets, the more disconnected you become from your users.\n\n**The Solution:**\n\nWhy do people love Kraftful?\n\nIn our recent Product Hunt launch, “love” was one of the most common words in the comments. Customers rave about Kraftful because it simplifies collecting valuable user insights and acting on them.\n\nHere’s how Kraftful works:\n\n1. **Have existing feedback?** Tell us the source, and we’ll collect, transform, and present it as feature requests and other actionable insights, making it easy to dig deeper or take action.\n2. **No feedback yet?** Kraftful generates surveys in 2 clicks or creates personalized interviews to complement your user calls.\n3. **Connect your Zoom or Google Meet calls** to get real-time insights.\n4. **Once you have insights:** Kraftful generates PRDs, projects, and user stories based on your user feedback and syncs directly with Linear or Jira. Or assign tickets directly in Kraftful.\n\nWhat used to take hundreds of hours now takes minutes.\n\nSimplicity is key. Unlike alternative solutions, Kraftful doesn’t overwhelm you with complex clustering, data labeling, or confusing UIs. We handle the complexity under the hood—extracting insights, grouping them, and eliminating LLM hallucinations. All you need to know is what your users need, and Kraftful delivers that in the simplest way possible.\n\nGive Kraftful a try and [share your thoughts](https://klever.kraftful.com/surveys-public/kraftful3yc) (respond to an AI interview 👍).",
        "url": "https://www.ycombinator.com/launches/LhM-kraftful-3-0-build-loved-products",
        "votes": 21,
        "created_at": "2024-08-26T17:40:36.715Z"
      },
      {
        "id": 80514,
        "title": "⭐️ Kraftful: AI-powered user interviews",
        "tagline": "An army of UX researchers to interview millions of users in minutes",
        "body": "**TLDR:** talk with millions of users simultaneously to build something people want.\n\nTry it for free on kraftful.com\n\nHere’s a 3 min demo: <https://youtu.be/BnbquZSz6v4>\n\n**Problem:** \n\nUsers hate long generic surveys, which leads to low response rates – sometimes just 5%😱 \n\nIf you have millions of users, this means you're not getting insights from a representative sample of your customer base. \n\nWorse still, if you're just starting out with only a few users, a low response rate can mean no responses at all 😞\n\n**Solution:** \n\nWith Kraftful, you can engage users or potential users with just 1-3 targeted questions instead of long, generic surveys.\n\nWhen they respond, they'll receive personalized follow-up questions tailored to their specific pain points—making the interaction more relevant and engaging.\n\nKraftful then summarizes all responses, delivering precise product insights from the collected data. \n\n**Why are Kraftful AI-powered interviews so great?**\n\n1. **They reveal insights that were previously out of reach:** Much like the information you'd get from an in-depth user conversation with the ability to ask follow-up questions. Plus, you can engage with many more users who can respond at their convenience and choose the depth of their engagement.\n2. **Massive time-saver:** Interview thousands or even millions of users simultaneously, with all responses summarized in minutes. This can save hundreds or thousands of hours, streamlining your research process dramatically.\n3. **Your own army of professional UX researchers:** Kraftful generates thoughtful questions based on the data you've already collected, eliminating the need to research best practices or spend time crafting questions.\n\nGive it a try and [let us know what you think](https://klever.kraftful.com/surveys-public/launchyc) (by responding to an AI interview👍) \n\n![uploaded image](/media/?type=post&id=80514&key=user_uploads/331211/30db3948-67ea-4d08-9a6c-f703ab1ee2a7)\n\n",
        "url": "https://www.ycombinator.com/launches/Kwc-kraftful-ai-powered-user-interviews",
        "votes": 275,
        "created_at": "2024-04-30T15:02:17.677Z"
      },
      {
        "id": 78451,
        "title": "Kraftful Surveys GPT - Generate surveys in ChatGPT and analyze responses with AI",
        "tagline": "Copilot serving 30K+ product teams.",
        "body": "Product research is now free, easy, and FAST with [Kraftful Surveys GPT](https://chat.openai.com/g/g-pPDqT7sZf-kraftful-surveys):\n\n* Instantly generate a free survey on any topic directly inside ChatGPT.\n* Send a link to your users or embed the survey on your website to collect feedback.\n* Kraftful analyzes all the survey responses to give you product insights and helps you create follow-up surveys for deeper insights.\n\nWhat used to take hundreds of hours can now be done in minutes. Creating and analyzing user surveys has never been faster. And Kraftful Surveys are FREE.\n\n![uploaded image](/media/?type=post&id=78451&key=user_uploads/331211/b4df9a14-9f9c-49dd-9ab1-8b4ad47163f4)\n\n**How Kraftful Surveys Work: AI-Powered Surveys and Analysis**\n\n**1\\. AI-Generated Surveys:**\\\nJust start Kraftful Surveys GPT inside ChatGPT, request a survey on your topic of choice, and voila! In minutes, you'll have a survey ready to send to users. Kraftful writes thoughtful questions on the topic and selects the optimal format for each question – be it text, multiple choice, or Likert scale. No more tedious survey prep.\n\nYou have the option to fine-tune the survey in Kraftful before distribution. Once your survey is ready, you can email it to your users or embed it directly on your website.\n\n![uploaded image](/media/?type=post&id=78451&key=user_uploads/331211/49f3e48e-63e4-4bcd-a506-a2bdbd92ccf3)\n\n**2\\. AI Analysis of Survey Responses:**\\\nThe real magic of Kraftful? All survey responses are automatically analyzed in Kraftful, highlighting top product insights.\n\n![uploaded image](/media/?type=post&id=78451&key=user_uploads/331211/2d56734f-0056-4529-b226-7a9b18cdb20e)\n\n**3\\. AI-Generated Follow-Up Survey:**\\\nOnce you have user feedback in Kraftful, either from your survey or by syncing any of the 30+ supported feedback sources, you can use that past feedback to generate a free follow-up survey that digs deeper.\n\nKraftful studies your user interview notes, app reviews, support tickets, or whatever past feedback you import. It then writes thoughtful questions that go beyond the insights you’ve already gathered.\n\nYou can also manually write your survey or use our NPS survey template to take advantage of instant Kraftful summaries of the survey responses. Kraftful Surveys are always free, so you have no reason to continue paying for your expensive survey platform and also waste your time writing questions.\n\n**Why We Built This**\\\nIn my experience as a product leader at various tech companies, gathering user feedback from app reviews, support tickets, call transcripts, and other sources was always a struggle. The real gold lay in surveys, dense with product insights due to their targeted nature.\n\nHowever, setting up effective surveys and analyzing their responses is incredibly time-consuming. As a result, surveys are done rarely. Teams try to squeeze in as many questions as possible, leading to low response rates and less representative feedback.\n\nKraftful Surveys addresses this issue by leveraging past feedback to generate focused survey questions, enabling:\n\n* More frequent surveys\n* Shorter, more engaging surveys for users\n\nEach survey builds upon insights from the previous one to faster learn what users need.\n\n**How to Get Started with Kraftful Surveys**\\\nGet started with [Kraftful Surveys GPT](https://chat.openai.com/g/g-pPDqT7sZf-kraftful-surveys) in ChatGPT today and streamline your user feedback process. We'd love to hear your feedback!",
        "url": "https://www.ycombinator.com/launches/KPL-kraftful-surveys-gpt-generate-surveys-in-chatgpt-and-analyze-responses-with-ai",
        "votes": 17,
        "created_at": "2024-02-15T16:00:21.363Z"
      },
      {
        "id": 77763,
        "title": "Kraftful Surveys - Generate product surveys and analyze responses with AI",
        "tagline": "Copilot serving 30K+ product teams.",
        "body": "# TLDR\n\nToday we’re changing the game in product research with [Kraftful Surveys:](https://www.kraftful.com/)\n\n1. Instantly generate a survey based on past user feedback or a new topic you want to explore.\n2. Kraftful analyzes all the survey responses to give you product insights like top feature requests, complaints, and loved features.\n3. For interesting feature requests, you can select to have Kraftful turn them into user stories with acceptance criteria and automatically sync to Jira tickets.\n\nWhat used to take hundreds of hours, can now be done in minutes. It’s never been faster to survey hundreds or thousands of users.\n\n![uploaded image](/media/?type=post&id=77763&key=user_uploads/331211/fff8749a-f2bb-4681-b61b-3ea3f6184537)\n\n# Why we built this\n\nIn my experience as a product leader at various tech companies, gathering user feedback from app reviews, support tickets, call transcripts, and other sources was always a struggle. The real gold lay in surveys, dense with product insights due to their targeted nature.\n\nHowever, setting up effective surveys and analyzing their responses is incredibly time-consuming. As a result, surveys are done rarely. Teams try to squeeze in as many questions as possible, leading to low response rates and less representative feedback. \n\nKraftful Surveys addresses this issue by leveraging past feedback to generate focused survey questions, enabling:\n\n* More frequent surveys\n* Shorter, more engaging surveys for users\n* Each survey builds upon insights from the previous one to faster learn what users need\n\n# How it works: AI AI AI\n\n### 1\\. AI generated surveys:\n\nKraftful studies your user interview notes, app reviews, support tickets, or whatever past feedback you import and writes thoughtful questions that go beyond the insights you’ve already gathered. It also selects the optimal format for each question – be it text, multiple choice, or Likert scale. No more tedious survey prep.\n\nIf you want to gather input on a new topic, you can just enter your survey topic and watch Kraftful Surveys turn it into thoughtful questions in a few seconds. Once your survey is ready, you can email it to your users or embed it directly on your website. \n\nIf you want, you can edit the AI-generated questions, change the for mat, move questions around, and anything you’d normally do with a survey tool (but without paying for an additional survey tool). Prefer the old-fashioned way? You can also manually write your survey or use our NPS survey template to take advantage of instant Kraftful summaries of the survey responses.\n\n![uploaded image](/media/?type=post&id=77763&key=user_uploads/331211/51f8abff-ba74-4ede-8a4d-099ccf2d567b)\n\n### 2\\. AI analysis of survey responses:\n\nThe real magic of Kraftful? All survey responses are automatically summarized in Kraftful, highlighting top feature requests, complaints, and loved features. Beyond our auto-generated product topics, you can dive deeper into the survey data with our chat, or review raw responses for more context. No more weekends spent sifting through hundreds of survey responses looking for the nuggets. \n\n![uploaded image](/media/?type=post&id=77763&key=user_uploads/331211/a988f656-6903-4f9b-82b8-9e01e31ba8c5)\n\n### 3\\. AI-generated user stories synced to Jira:\n\nWhen you spot interesting feature requests or complaints on the automatically generated lists, Kraftful can turn them into user stories with acceptance criteria and instantly sync the user stories to Jira so your team can start working on them. \n\nIn other words, you make the strategic decisions based on the user insights Kraftful brings you. And then Kraftful does the leg work to integrate those decisions into your backlog so your team can get to work. \n\n![uploaded image](/media/?type=post&id=77763&key=user_uploads/331211/bb7f2f44-af5d-4230-a3d3-869d164925fc)\n\n# How to get started with Kraftful Surveys\n\nGet started with our [free plan at](https://www.kraftful.com/) [kraftful.com](http://kraftful.com) and ditch your expensive survey tool. Let me know what you think!",
        "url": "https://www.ycombinator.com/launches/KEF-kraftful-surveys-generate-product-surveys-and-analyze-responses-with-ai",
        "votes": 20,
        "created_at": "2024-01-23T15:03:48.510Z"
      },
      {
        "id": 74519,
        "title": "Kraftful – Copilot for product builders",
        "tagline": "Listen to millions in minutes.",
        "body": "### **TLDR**\n\nAt the heart of every great product is the user. Kraftful Copilot makes ✨magic✨ happen – empowering product builders to listen to millions of users in just minutes and seamlessly integrate that feedback into their work.\n\nWould love for you to try it out ([free](https://www.kraftful.com/)!) and provide feedback.\n\nhttps://www.youtube.com/watch?v=bxBrpvdVWM8\n\n### **Problem**\n\nLeading product teams before I started Kraftful, one of my biggest challenges was to figure out how my teams would effectively gather insights from user interviews, app store reviews, support tickets, sales calls, and really anywhere else users wanted to give us an earful 😆\n\nBeyond the struggle of manually collecting and parsing through volumes of feedback, it’s impossible to quickly learn how frequently issues come up from different user groups and incorporate the learnings in the product development process.\n\n### **Solution**\n\nWe launched an MVP earlier this year in beta and got many millions of users from Google, Microsoft, Meta, Netflix, Canva, Dropbox, Atlassian, LinkedIn, Oracle, and many many more 🔥\n\nKraftful users built comprehensive feedback repositories on [kraftful.com](http://kraftful.com), analyzing over 13M pieces of user feedback. Kraftful Copilot saved them a whopping 100,000 hours of manual digging around in interviews, app reviews, support tickets, and other digital nooks and crannies.\n\nNow we're thrilled to unveil a more comprehensive solution, allowing you to:\n\n✅ Connect feedback from app stores, Zendesk, Intercom, and 30+ other sources \\\n👀 Explore actionable summaries of user feedback\n\n💌 Receive weekly insights in your mailbox and share with your team in Slack\n\n🤖 Automatically sync new feedback for daily, weekly, and monthly summaries so that nothing slips through the cracks\n\n💡 Uncover deeper insights through follow-up conversation with Kraftful Copilot\n\n📝 Whip up AI-written user stories with acceptance criteria and instantly sync them to Jira or post to Linear, Trello, or wherever you track your dev work\n\n\\\nGive it a try at [kraftful.com](http://kraftful.com) and let us know what you think at [feedback@kraftful.com](mailto:feedback@kraftful.com) ✨",
        "url": "https://www.ycombinator.com/launches/JNv-kraftful-copilot-for-product-builders",
        "votes": 31,
        "created_at": "2023-08-30T19:35:40.393Z"
      },
      {
        "id": 71519,
        "title": "Kraftful Plugin for ChatGPT - Your on-demand product coach",
        "tagline": "Kraftful is building a co-pilot for product builders, capable of summarizing large volumes of user feedback in mere seconds. Now, you can directly access our product coach within ChatGPT.",
        "body": "## TLDR 👀\n\nKraftful Plugin is now live in the ChatGPT plugin store!\n\nAsk questions about product management best practices and get insightful answers summarizing thinking from all the top product gurus! It’s like having your own product coach, but available 24/7 inside ChatGPT.\n\n![uploaded image](/media/?type=post&id=71519&key=user_uploads/331211/38bef5b7-5e15-403a-b7bf-7633c52f8278)\n\n## Problem 🔍\n\nDrowning in a sea of PM best practices online? The internet can be a noisy place for product builders.\n\nChatGPT is excellent at weeding through online content. But it currently doesn’t include blog posts and other product musings created after 2021. And let’s be honest, not all internet sources are created equal when it comes to getting product advice. \n\n## Solution 🎉\n\nKraftful plugin to the rescue! We’re excited to be one of the first few plugins to officially launch in the ChatGPT plugin store.\n\nThe Kraftful plugin gathers insights from a large list of reputable product resources and supercharges them with ChatGPT for quick, concise info!\n\nAt [Kraftful](https://www.kraftful.com/), we have a large community of product people, who have been recommending their go-to sources on various product dev questions ([some](https://www.kraftful.com/blogs/top-40-podcasts-for-product-builders) [examples](https://www.kraftful.com/blogs/100-must-read-books-for-product-managers-in-2023)). We’re now harnessing the power of GenerativeAI to bring it all together. \n\n## Try it out 🦾\n\nIf you have access to ChatGPT plugins, please try it out [in ChatGPT](https://chat.openai.com/) and let us know what you think. \n\nPlugin access is still being rolled out to ChatGPT users. So if you're still waiting for access, you can try out the Kraftful plugin by asking a PM best practices question [in this thread](https://twitter.com/yanatweets/status/1655584706685984773?s=20) & I'll share the plugin response with you there.",
        "url": "https://www.ycombinator.com/launches/IbX-kraftful-plugin-for-chatgpt-your-on-demand-product-coach",
        "votes": 25,
        "created_at": "2023-05-11T14:41:43.906Z"
      },
      {
        "id": 69687,
        "title": "Kraftful – ChatGPT for product research",
        "tagline": "Helping product builders to listen to users at scale",
        "body": "**TLDR**\\\nHaving led product teams at companies big and teensy, I’m excited to share a solution to involve masses of users directly in the development process to build products people love 🥰\n\nWould love for you to try it out ([free trial](https://www.kraftful.com/)) and provide feedback.\n\n![uploaded image](/media/?type=post&id=69687&key=user_uploads/331211/b2936511-7594-4003-8f64-3cbe849f5198)\n\n### **Problem**\n\nBeing a product lead before starting Kraftful, one of my teams’ biggest challenges was to manually gather insights from user interviews, app store reviews, support tickets, sales calls, and really anywhere else our millions of users wanted to give us an earful 😅\n\nEven with thousands of users, it can take hundreds of hours to try to parse through everything. It’s impossible to quickly act on all this data. Just like \\*NSYNC, users who don't feel heard end up saying \"bye bye bye” 💔💔\n\n### **Solution**\n\nNow imagine if you had the tools to effectively listen to users and make them feel heard – that would advance product development AND user satisfaction because they’d be actively engaged in the development process. \n\nWith Kraftful, you can: \n\n✅ Connect a source (e.g. iOS/Android app store reviews, Zendesk, Intercom, Front) or paste user interview notes, call transcripts, or other relevant text\n\n👀 Check out the instant summaries of frequent feature requests, common complaints, most loved app features, and lists of mentioned competitors\n\n💡 Ask follow-up questions with our ChatGPT-like assistant to uncover insights like “what do users say about X feature” or “how do users currently complete this task”\n\n💪 Use these insights to build or refine your product roadmap\n\nThis is not your mother’s AI summarization tool 😅 We’re building a solution for product teams to help them connect with users in new ways. Today’s launch is the first step toward that vision.\n\n### **Sign up for a free trial**\n\n[Give it a try!](https://www.kraftful.com/) User feedback is our jam, so let us know what you think at [feedback@kraftful.com](mailto:feedback@kraftful.com)✨\n\nWhile we’re launching in Beta, we’ve seen incredible demand for our solution. The product in Alpha has already been used by thousands of product builders from companies like Google, Microsoft, Meta, Netflix, Canva, Dropbox, Atlassian, LinkedIn, Oracle, Kayak, Volvo, Johnson & Johnson, the National Art Gallery, London Underground, 7-Eleven, and many others 🔥🔥🔥",
        "url": "https://www.ycombinator.com/launches/I7z-kraftful-chatgpt-for-product-research",
        "votes": 32,
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        "body": "[**Release**](https://release.com) helps developers get their amazing ideas out into the world faster. 🚀 When it comes to developers, DevOps has turned into an additional hurdle on the path to delivering product features. Originally, DevOps was meant to empower developers with operational tasks, but instead, it evolved into a team that controls access and holds the keys to the information and systems needed to deploy and release quickly. \n\n📣 In every organization, a handful of exceptional DevOps 👨‍💻 engineers become the oracles of knowledge and the entire team relies heavily on their expertise. However, reliance on a few go-to experts inevitably becomes a bottleneck on the team's speed and ability to ship. Don’t you wish you had your expert DevOps engineer on a speed-dial, without actually bugging them? \n\n🤖 Introducing **Release AI**—a powerful tool that allows anyone using the Release CLI to get go-to DevOps engineers’ answers, without tying up the experts’ time. Developed with developers and engineers in mind, Release AI extends the capabilities of OpenAI's GPT-4 public LLM with our extensive expertise in DevOps, providing you with relevant context, control, and content tailored to your organization's unique needs.\n\n👷‍♂️ In its initial phase, Release AI provides \"read-only\" access to both AWS and Kubernetes. This lets you engage in meaningful conversations with your AWS account and your K8s infrastructure. Looking forward, we plan to add more tools for commonly used systems, along with the introduction of write access, which will allow you to automate an even broader range of your 🤹‍♀️ daily tasks.\n\nHere are some examples of what you can do with Release AI:\n\n🐳 **Talk to your Kubernetes clusters**\n\n![uploaded image](/media/?type=post&id=74153&key=user_uploads/423512/d5b71075-1a25-4f12-a49f-0a95aa14d4c9)\n\n🧑‍💻 **Talk to your AWS infrastructure**\n\n![uploaded image](/media/?type=post&id=74153&key=user_uploads/423512/9fcdd298-b284-4fdc-96d9-f33eed3d2dab)\n\n💰 **Keep track of your AWS spend**\n\n![uploaded image](/media/?type=post&id=74153&key=user_uploads/423512/8a11fe73-1851-4908-b27c-43bd5a57d9fb)\n\n⏰ **Create Cron Jobs and Reminders**\n\n![uploaded image](/media/?type=post&id=74153&key=user_uploads/423512/19ce66c3-4694-41f7-9ef2-0eae0ead7dc4)\n\nWe have a [Slack community that you can join](https://join.slack.com/t/release-ai/shared_invite/zt-20dxgp2o0-ePCXzsag6l8_i4HwOgRItg) to talk about Release AI. We also wrote a 🚀 [quick-start guide](https://docs.release.com/release-ai/quickstart) to help you get started.\n\n# Our Ask 🙏\n\n[Try it out!](https://beta.release.com/ai/register) We would love your feedback as we are enhancing Release AI, reach out to us with any feature requests or crazy ideas that Release AI could do for you. We hope you enjoy using Release AI! ❤️\n\n— The Release Team",
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        "body": "At [Release](https://release.com) we help “virtualize” your environment, so you can quickly reproduce it for various purposes: remote development, testing, staging, or even running production. Our platform serves as a one-stop shop for all of your environment requirements. We have taken our most popular feature and are now offering it as a stand-alone product for free!\n\n⚡️Instant Datasets is one of the most popular features of the Release platform because we make the management of pools of data easy. Release’s Instant Datasets workflow means you don’t need to worry about managing the creation of databases from snapshots. As new snapshots arrive they will automatically be incorporated in your dataset. Instant Datasets allows you to easily create multiple pools of datasets and distribute them to your teams and it cleans _🧹_ up after itself.\n\n![](https://4032318958-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-M1neGLLQ0sDXeK6ooSo%2Fuploads%2FuFlNpsifRLmeTcT73L4S%2FScreenshot%20from%202022-05-03%2011-59-14.png?alt=media&token=b4529430-e7d6-4767-a10b-aa3493a5f51d)\n\n_Using the built-in replication functionality of services like RDS, Instant Data sets creates pools of databases for use wherever production data is needed._\n\n📀 Data is one of the most important aspects of any environment. Without real data to support it, the code or running containers lose much of their usefulness. Often, the complexities and burden of distributing production or production-like data is an “exercise left to the reader” when looking for providers of environments or a development platform as a service. **Your ephemeral environments are only as good as your data!** At Release we built a version of Instant Datasets, day 1 for this very reason. **We are now making it available as a stand-alone product** for you to incorporate into any local development process, ci/cd pipeline, etc!\n\n![uploaded image](/media/?type=post&id=73732&key=user_uploads/19885/644c642f-b0e7-43a8-b3bb-448466031ba9)\n\n_Dataset with one in use, one starting up, and one available for someone to use_\n\nSetting up and using Instant Datasets is super simple:\n\n✅ **Create a Release Instant Datasets account** [**here**](https://beta.release.com/instantdatasets/register)\n\n✅ **Create a cloud integration**\n\n![](https://lh6.googleusercontent.com/3STD6S6crrkGBxL6aCHoSnwL-IjTFkSst_fhdIYfPD7IMU6WxQOkSDH2iQYJjMINA8Gjn06eLSLryyizQ8G6Rd3ojR6-9mSp7_VlO4qe-D5K4wNKDbmbi7novSesgN36EZMPk9IHdVH-sgNH6D9aPGQ)\n\n_Cloud Integrations are how Release talks to your cloud provider on your behalf_\n\n✅ **Create a dataset**\n\n![](https://lh3.googleusercontent.com/nFZIdkEW320QyNNKumPmVO4iIaqEn2ZFZhTnAS7zqfWzDnmamR_-Rsr07n10EK5sP7rWJVP4BZSH_YYhT0WZlZLkXz4otjEv8t0-8FLRvXTbA2DZwrI7TYmIfynQIgtplP2ngL2OMHSP1XUn0MAIWNo)\n\n_Release lets you control cost, security and performance of you dataset_\n\n🏁 **Checkout a database and use it in your environment for as long as you need it**\n\n![](https://lh5.googleusercontent.com/3DP_hXM8pCFjWAGo6jpK1eKHM3qMu3sWdcPSJWzkTMboho8nI8aFh1HRIfNCplYbGdMgYLhkdgL6s6ixavx597PSOJxByen1wRRsINuj1upAxO1EPuF0S9pW8o1pAxQ99IKqnZzmixt1dd_idPJkVpk)\n\n![](https://lh3.googleusercontent.com/b0SiudL37kwJyHl2_wED4gOGv4GvQcustSeSu4Y_-TIaVTCA6g8GcmJGD1YpCBX3ehZV8n69soCZZDocrcFfV4CTt57Dlp2BiP2wHwMb3jWLeGxuPhIsuYyllHL51bTNdbsIOkjg8n33c48TYO0Wt5U)\n\n_Release provides you with everything you need to connect to your dataset_\n\nWe wrote a 🚀 [quick-start guide](https://docs.release.com/release-instant-datasets/quickstart) and made a 👣 [walkthrough video](https://vimeo.com/849156936) to help you get started.\n\n❓ Although the standalone Instant Datasets has a few limitations compared to the Release platform version, we are actively working on resolving them in the upcoming weeks. Currently, we support RDS and Aurora in AWS, with Google Cloud support coming soon. Additionally, we will be adding the capability to pause databases on a schedule to save resources and money, as well as the ability to cleanse production data before creating a pool of databases. All of these features exist in the Release platform and are being added to the stand-alone product currently.\n\n### Our Ask 🙏\n\n**Please give Instant Datasets a **[**try**](https://beta.release.com/instantdatasets/register)**!** Our customers, as well as the team at Release, have found it incredibly valuable to build and test with production-like data. In fact, it's how we develop all our products, including Release. From the very beginning, we recognized the importance of having production-like data to create the best possible development platform. We would love your feedback. We hope you enjoy using Instant Datasets too! ❤️\n\n— The Release Team",
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    "long_description": "Humanloop is the LLM evals platform for enterprises. Teams at Gusto, Vanta and Duolingo use Humanloop to ship reliable AI products. We enable you to adopt best practices for prompt management, evaluation and observability.",
    "one_liner": "Humanloop is the LLM evals platform for enterprises. ",
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        "linkedin_url": "https://www.linkedin.com/in/jordanburgess/",
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        "user_id": 464489,
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        "founder_bio": "Co-founder and CTO @Humanloop. Previously Co-founder @Certua. ML PhD at UCL and BSc Mathematics at Trinity.\n",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/peter-hayes-2366591a4/",
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        "title": "How our AI Startup Grew 60x After a Pivot | Raza Habib, Jordan Burgess of Humanloop - YouTube",
        "url": "https://www.youtube.com/watch?v=TlUZrm2jlCw",
        "date": "Mar 17, 2024"
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        "title": "Humanloop: Providing picks and shovels for the AI gold rush",
        "url": "https://www.siliconrepublic.com/start-ups/humanloop-generative-ai-startup-paul-hayes-raza-habib-london-san-francisco",
        "date": "Feb 05, 2024"
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        "url": "https://www.youtube.com/watch?v=hQC5O3WTmuo&t=778s&pp=ygUJaHVtYW5sb29w",
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    "slug": "webapp-io",
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    "one_liner": "Build webapps faster with 10x better CI/CD + preview envs",
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        "full_name": "Colin Chartier",
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        "linkedin_url": "https://www.linkedin.com/in/colinchartier/",
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        "full_name": "Lyn Chen",
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        "founder_bio": "Prev. Dev Tools Founder (acquired), now doing human flourishing projects across emerging adulthood (18-25) and K-12. \n\n\n\n",
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        "linkedin_url": "https://www.linkedin.com/in/lynchen/",
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        "tagline": "Webapp.io is often 10x faster than creating full-stack environments in a regular CI like Github Actions",
        "body": "![uploaded image](/media/?type=post&id=64193&key=user_uploads/364633/589b9712-0cb1-49cd-9bf5-e059435f1451)\n\nHey! We’re Colin & Lyn from [webapp.io](http://webapp.io).\n\nWe’re helping webapp developers make new copies of their stack in seconds using memory snapshots. You can think of a cloud-agnostic, full-stack version of the branch deployments you’d get from Vercel, Netlify, Heroku, or Render - even if you’re using a regular cloud provider instead of a PaaS.\n\n[Webapp.io](http://Webapp.io) lets you create full-stack environments for every pull request in seconds. We’ve built a custom hypervisor that watches which files are used in which build steps, and skips repetitive actions like starting microservices, seeding databases, or building images.\n\nIt came out of our own frustrations from having to often skip end-to-end testing for commits just for the sake of developer velocity. A typo fix on a landing page shouldn’t take 15+ minutes to spin up a fresh environment for some Cypress tests!\n\n![uploaded image](/media/?type=post&id=64193&key=user_uploads/364633/abdf8553-ec80-4b7a-9582-62e95d43cbc7)\n\n[Webapp.io](http://Webapp.io) works with any Linux-based stack, and the configuration works like a Dockerfile for VMs so that you can get started without having to talk to support.\n\n![uploaded image](/media/?type=post&id=64193&key=user_uploads/364633/4e3f5b2c-3215-41ef-851d-5e46a72727d7)\n\nOnce you’ve installed our app on your GitHub, GitLab, or BitBucket profile, you can push files called Layerfile in the syntax above, and we’ll automatically discover them and build your environments.\n\n[Webapp.io](http://Webapp.io) builds new VMs by re-using memory snapshots of your earlier builds. That means you can get a fresh copy of your database, microservices, and backend in seconds for a frontend change 10x faster than a production cloud provider or traditional CI.\n\nOur free tier is generous and we’re happy to set up a shared slack channel to help prospective users get set up. [Try out the product here!](https://webapp.io/sign-up?utm_src=launchyc) or [read the docs](https://webapp.io/docs/?utm_src=launchyc).",
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    "all_locations": "Bengaluru, KA, India; Delhi, DL, India; Singapore, Singapore",
    "long_description": "Almost every company that has to integrate with the legacy financial institutions, faces several challenges when it comes to the product cycle. Not only are the APIs and documentations less available, but they are also old school and ridden with errors and loopholes. \r\n\r\nOn top of that, the lack of a single point of contact from the underlying institutions, makes the already long integration cycle of 5 months feel like a temple run between different departments. And since those services break and update over time, you can imagine the nightmare in terms of coordination between the tech teams. \r\n\r\nWe are a full-stack platform where you can come, select your desired modules, play in the sandbox, and launch your product with the APIs and SDKs within a couple of weeks! Not only that, but we also take care of all upcoming fixes, iterations, and updates without breaking any flow.\r\n\r\nIt's that easy, as it should be. Welcome to the future.",
    "one_liner": "API Platform for Banking Integrations (Plaid for India and APAC)",
    "team_size": 60,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1595174841,
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    "nonprofit": false,
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    "status": "Active",
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      "Singapore",
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      "Partly Remote"
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    "stage": "Early",
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/decentro",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2020/decentro.json",
    "year_founded": 2020,
    "city": "Bengaluru",
    "country": "IN",
    "linkedin_url": "https://www.linkedin.com/company/decentro/",
    "x_url": "https://twitter.com/DecentroTech",
    "fb_url": "https://facebook.com/Decentro-104637704449006/",
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      "url": "https://www.ycombinator.com/people/aaron-epstein"
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        "full_name": "Rohit Taneja",
        "title": "Founder",
        "founder_bio": "My aim in life is to contribute to the world by solving some of the toughest problems that exist. \n\nI believe that to run a technology venture, the culture needs to be set from the foundation and only a highly knowledgeable and passionate person can get it right. That is why I strive to be a polymath. \n\nThe domains that I am planning to work on (sequentially over the course of my lifetime) are - \n1. Digital payments \n2. Block-chain \n3. Sustainability & Climate Change",
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        "linkedin_url": "https://www.linkedin.com/in/rohit-taneja-69b30b13/",
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        "title": "Y Combinator-Backed Decentro Acquires SaaS Fintech Neowise Technologies",
        "url": "https://inc42.com/buzz/y-combinator-backed-decentro-acquires-saas-fintech-neowise-technologies/",
        "date": "Jul 19, 2023"
      },
      {
        "title": "Fintech startup Decentro begins operations in Singapore",
        "url": "https://www.cnbctv18.com/startup/fintech-startup-decentrotech-begins-operations-in-singapore-15995891.htm",
        "date": "Feb 21, 2023"
      },
      {
        "title": "Rapyd Ventures backs Indian fintech-as-a-service startup Decentro • TechCrunch",
        "url": "https://techcrunch.com/2022/10/31/y-combinator-backed-decentro-fintech-series-a-funding/",
        "date": "Oct 31, 2022"
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        "id": 103475,
        "title": "Decentro goes global | Multi-Currency Payment Collections",
        "tagline": "Launching global payments & treasury from GIFT city for the world. ",
        "body": "Hey YC community, we’re Rohit and team from **Decentro (YC S20)**, a full‑stack banking and payments API player from India.\n\nOver the last few years, we’ve helped thousands of businesses plug into Indian banking, KYC, and payments infrastructure with simple APIs; now we’re extending that to global payments with our new **GIFT‑based PSP** and cross‑border collection stack.\n\n## **The problem – global money in &amp; out**\n\nIf you’re a trade finance player, marketplace, or fintech scaling globally, you probably live in some version of this mess:\n\n* Multiple PSPs and bank partners across countries, each with different compliance, FX, and payout rules.\n* Long, opaque onboarding cycles for cross‑border flows.\n* Fragmented reporting across acquirers, currencies, and entities, making reconciliation and compliance audits painful.\n* A fast‑moving regulatory environment (IFSCA, FEMA, local regimes) where a misstep can mean blocked flows or penalties.\n\nThis slows down companies that should be focusing on building products and acquiring customers, not chasing bank RM emails and interpreting circulars.\n\n## **What we’re building – a compliant global PSP rail via GIFT**\n\nWe’ve become one of the first Indian payment aggregators to receive a final PSP license from IFSCA at GIFT City, and we’re wrapping that into a developer‑first global payments platform.\n\nAt a high level, here’s how it works:\n\n* Single API / dashboard to collect global payments: Accept from international customers via cards, local methods, and bank transfers across multiple currencies, and settle into GIFT City or onshore INR.\n* Built‑in compliance and reporting: We abstract GIFT City PSP rules, documentation, and transaction reporting so finance and compliance teams get ready‑to‑use exports and views.\n* Faster settlement and better visibility: Unified ledgers and payout flows across corridors and partners, with clear T+ timelines, FX details, and status notifications.\n* Modular APIs: Use us just as a cross‑border collection layer, or plug into the broader Decentro stack (KYC, domestic payouts, banking APIs) if you want a full‑stack infra partner.\n\n## **Why we started working on this**\n\nAt Decentro, we began by solving for domestic Indian banking and payments APIs after running into fragmentation and long integrations at our previous companies.\n\nAs our customers scaled, the same questions kept coming up:\n\n* “Can you help us collect from global customers and settle into our desired currency?”\n* “Is there a compliant way to route this via GIFT City without adding three more partners?”\n\n## **How it works – product flow**\n\nHere’s a typical integration:\n\n1. Configure your entity and use case (SaaS, marketplace, B2B payments, etc.) in our console, including purpose codes and underlying documentation.\n2. Integrate our hosted checkout or APIs to start accepting payments in supported currencies and methods from your customers.\n3. We route funds through our GIFT PSP stack, run compliance checks, and handle FX and settlements into your designated accounts.\n4. Your finance and compliance teams use our dashboard and webhooks for reconciliation, returns, chargebacks, and regulatory reporting.\n\n## Here’s a walkthrough video - <https://youtu.be/FYXg5-KSg-8>\n\nIf you’re:\n\n* A SaaS or B2B company selling globally and settling into India.\n* A marketplace, fintech, or infra company that needs compliant cross‑border rails via GIFT City.\n* Or an existing YC company that wants to expand to Indian or India‑linked flows.\n\nWe’d love to chat.\n\n* Website: <https://tinyurl.com/decentro-yc-launch>\n* Global PSP product page: [**https://decentro.tech/global/gift-psp**](https://decentro.tech/global/gift-psp)\n* YC founder: Rohit (Founder &amp; CEO, Decentro – YC S20)\n\nComment here, or reach out and mention “Integrate YC PSP” so we can prioritize your onboarding and, if relevant, help you navigate the GIFT / IFSCA side as well.\n\nCheers!",
        "url": "https://www.ycombinator.com/launches/Qux-decentro-goes-global-multi-currency-payment-collections",
        "votes": 27,
        "created_at": "2026-06-25T19:24:52.100Z"
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    "id": 22033,
    "name": "Memo",
    "slug": "memo",
    "former_names": [
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      "DID.app",
      "Plum Mail"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cf9fc52d8167336fb7036e55b0218f22b6ce2f86.png",
    "website": "https://sendmemo.app",
    "all_locations": "Exeter, England, United Kingdom; Remote",
    "long_description": "We all know the attention economy is damaging our ability to focus. Memo is for people that are mad as hell about their time being sold to the highest bidder.\r\n\r\nForget laborious old email and hyperactive Slack.  We built Memo as the feel-good alternative that will make you love communication again and get back time for what matters to you.\r\n\r\nMemo's features make every message high value so you can communicate more effectively.",
    "one_liner": "Memo is modern communication that helps you get your focus back",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1597740154,
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    "url": "https://www.ycombinator.com/companies/memo",
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    "year_founded": 2019,
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    "country": "GB",
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        "full_name": "Richard Shepherd",
        "title": "Founder",
        "founder_bio": "UK based founder and full-stack web developer with sales experience running my creative agency in the south west of England.  Joining YC to replace email with Peter.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/rich",
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        "user_id": 335396,
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        "experience": "6+ years",
        "visa": "US citizenship/visa not required",
        "skills": [
          "Android",
          "Go",
          "iOS",
          "React",
          "React Native",
          "TypeScript",
          "Flutter"
        ]
      }
    ],
    "news": [
      {
        "title": "Runway raises $2M seed, launches its ‘air traffic control’ system for mobile app releases – TechCrunch",
        "url": "https://techcrunch.com/2021/11/16/runway-raises-2m-seed-launches-its-air-traffic-control-system-for-mobile-app-releases/",
        "date": "Nov 16, 2021"
      }
    ],
    "launches": [
      {
        "id": 76281,
        "title": "📲 ⏪ Mobile Rollbacks by Runway",
        "tagline": "Undo a bad native app release with a single click.",
        "body": "## Mobile Rollbacks ensure your team is always just one click away from addressing critical bugs in production. \n\nNo one is immune from shipping critical bugs to production. No matter how extensive your test coverage, no matter how thorough your QA, no matter how much you put behind feature flags — your mobile team _will_ ship irreversibly-bad updates that break things and upset your users. \n\nThis is especially problematic for mobile because you can’t roll back immediately like your web or backend friends can. Rather, you have to triage the issue and assign it to the right team members, implement fixes (or carefully revert the offending changes), compile one or more RCs, upload to the stores, submit for review, then cross your fingers and pray to the store review gods for a speedy review. And the negative impacts of even just a few hours with a critically broken app can be eye-watering: tens or hundreds of thousands of dollars in lost revenue, a flood of negative user reviews, and overwhelmed CX or ops folks.   \n\nBut what if it didn’t have to be that way? What if you could instantly resolve a critical issue in prod, with a single click? Now, you can. \n\n### Recover from production issues in zero time — literally\n\nCritical issue? Roll back instantly. In the background of every normal release cycle, Runway automatically re-signs your last live production build and preps it for a possible rollback release — including preemptive submission for review (iOS only) — to remove all possible sources of delay. Should something go wrong in prod, there’s always a corresponding rollback build ready and waiting for single-click release in Runway. \n\n![](https://assets-global.website-files.com/5ef1f28e08458502ba614d85/6555b0344379d5700b526a01_deploy-rollback-button.png)\n\nHere’s how the rollback flow works in a bit more detail:\n\n1. Your team is busy getting your next regularly-scheduled release out the door. Let’s call it version 1.2.0.\n2. In the background, Runway takes your latest live build in production — say, 1.1.0 — and re-signs it, bumping the version to 1.2.1 and incrementing the build number as necessary.\n3. Your team releases 1.2.0 as scheduled. Nice!\n4. The 1.2.1 rollback release is surfaced in Runway, just in case. For iOS, we also preemptively create a new version for the possible rollback in App Store Connect and submit the rollback build for review.\n5. Your team is monitoring the rollout of 1.2.0 and identifies a critical issue 🚨You halt the rollout.\n6. Right next to the button you used to halt the rollout, there’s another button to release the rollback build that’s ready and waiting. Click that, and you’re all set.\n\nWith rollback builds primed and ready to go, your team can address critical bugs in prod with a single click — cutting out all the lead time needed to investigate and implement a fix, get builds compiled and uploaded, and make it through the store review process.\n\n### Take the pressure out of hotfixes; triage more fully and fix more confidently\n\nEven if you ship a rollback to address an issue in prod, it doesn’t mean you’ll necessarily wait until your next regularly-scheduled release to issue a fix. In fact, it’s likely you’ll use rollbacks in conjunction with roll-forward hotfixes — and those hotfixes will be better as a result. Because rollbacks allow you to instantly stabilize a critical situation, you can take your time in triaging, investigating, implementing fixes, and then working through your hotfix release process.\n\n![](https://assets-global.website-files.com/5ef1f28e08458502ba614d85/6555b0ce132292bf3747a1af_rolllout-rollbacks-final.gif)\n\n### More predictable resolution timelines & fewer unanswerable questions from stakeholders\n\nEvery team knows the feeling of dread that hits when you’ve shipped a breaking change and leadership shows up in your #mobile Slack channel. _Is the fix in yet? Is the build approved by Apple? How about now?_ With rollbacks in Runway, you can actually respond to these kinds of asks, and give stakeholders confidence that the situation is under control.\n\n![](https://assets-global.website-files.com/5ef1f28e08458502ba614d85/6555b15743d1af6cfd9dcf50_slack-popup.png)\n\n### When you need a rollback, it’s there for you (batteries included). When you don’t, we’ll handle all the cleanup.\n\nRunway’s rollbacks functionality encompasses quite a few dependencies and steps which, if approximated manually each and every release, would require a lot of work — not just to prepare each rollback, but also to clean up unused rollbacks along the way. Now, you no longer have to choose between investing huge amounts of time and effort into setting up rollbacks manually or else forfeiting the safety net rollbacks provide.\n\n![](https://assets-global.website-files.com/5ef1f28e08458502ba614d85/6555b18d930993fe03666aaa_rollback-settings.png)\n\nWith rollbacks, Runway gives your mobile team _the quickest_ possible way to respond to critical issues in production. Instead of scrambling to identify, implement, and ship a fix, you can immediately “stem the bleeding” and resolve things with a single click. Stakeholders won’t hover wondering when a resolution will land, and your team can triage and implement fixes more confidently, without all the pressure that typically accompanies hotfix situations. Plus, rollbacks mitigate the serious negative impact to revenue and app store reviews that comes with a buggy app being in users’ hands for even just a couple of hours.\n\n### How to give Rollbacks a try\n\nYou can sign up for free on the [Runway site](http://runway.team), no credit card required, and we’re always available to give you a guided walkthrough — just get in touch!",
        "url": "https://www.ycombinator.com/launches/JqL-mobile-rollbacks-by-runway",
        "votes": 9,
        "created_at": "2023-11-16T17:50:09.865Z"
      },
      {
        "id": 71808,
        "title": "📲 🚀 Build Distro by Runway",
        "tagline": "Better mobile build distribution for teams",
        "body": "## Build Distro makes it dead simple to get the right app builds into the right teammates’ hands\n\nMobile build distribution is hard. There’s the provisioning and signing gauntlet, of course, but the challenges don’t end there. Getting the right builds in front of the right teammates takes constant effort and shepherding, and creating an install flow that’s pain-free is difficult. Existing tooling options tend to jumble all different kinds of builds together and offer half-baked installation flows; the “human factors” aspect of build distribution is secondary, or ignored altogether.\n\nWe set about building a better, more foolproof and human-centric way.\n\n### What is Build Distro?\n\nBuild Distro allows you to clearly define and group the different types of mobile builds your team distributes – from one-offs and work-in-progress dev builds, to staging builds, to release candidates. You can avoid the usual jumbled pile of builds that folks have to carefully sift through, and give technical and non-technical team members alike an easier way to grab builds, with streamlined installation via QR or Slack link. With hassle-free distribution, your team can check out builds earlier and more often, improving collaboration and app quality.\n\nHere are some highlights:\n\n📲 **Get the right builds into the right people’s hands**\n\nBuild Distro introduces the idea of build buckets to allow you to clearly define and group different flavors of builds. Instead of having all distributed builds landing in that jumbled pile, you can now separate different kinds of builds using definitions based on branch, CI workflow, or some combination of both — or using more freeform, ad hoc buckets. Not only are build flavors logically separated into buckets, but you can set up targeted notifications and scope access per bucket to ensure the right people are aware of and able to seamlessly install new builds relevant to them.\n\n![uploaded image](/media/?type=post&id=71808&key=user_uploads/562880/830900f0-fe8a-4c8e-b050-5b86956de7d5)\n\n**✨ Share one-offs & early test builds more easily**\n\nWith branch-based and ad hoc, personal build buckets, Runway makes it much easier to share work-in-progress builds. You can create dedicated buckets for test builds and nightlies on your main development branch or any feature branches, and everyone on your team can also have their own personal buckets to drop updates into as they work. Product managers, QA, designers, and other engineers and stakeholders can now easily grab any WIP builds, earlier and more often during the development cycle, helping your mobile org improve quality and shift left.\n\n![uploaded image](/media/?type=post&id=71808&key=user_uploads/562880/e0e69e93-f6bd-4497-a3ed-7d50a23c68df)\n\n🔒 **Make it impossible to ship the wrong build to prod**\n\nOne of the worst failure modes around build distribution has to do with test or staging builds getting accidentally shipped to production. It may be rare, but when it happens, it can be devastating. Confusion around distributed build flavors is often to blame, and Runway’s build buckets remove this risk. Clearly delineate prod and pre-prod builds, and scope access accordingly.\n\n![uploaded image](/media/?type=post&id=71808&key=user_uploads/562880/5c3d452c-2760-44b9-98c6-eb3b97edef2d)\n\n**📥 Install app builds with less hassle, and more context**\n\nEven once someone has tracked down a build they want to check out, actually getting it onto their device comes with its own hassles. Runway makes installation foolproof and seamless: with each build, you can install directly by scanning a QR code or sending yourself a link in Slack. Plus, alongside each build you can see full context on the build flavor and exactly what work it contains — no more guesswork, pinging build numbers back and forth and hoping you’re grabbing the right version of the app.\n\n![uploaded image](/media/?type=post&id=71808&key=user_uploads/562880/a26f0045-ebdb-4b8b-9048-82f90457d415)\n\n⚙️ **Integrate with your existing tools for zero extra overhead**\n\nGetting up and running is simple: connect your existing CI and… that’s it. Once you’re connected, Runway will get you started with a few default shared buckets for development and RC builds, and anyone on your team can easily create scoped personal buckets. To define a new shared bucket, simply select a workflow (from among any defined in your CI, automatically pulled in by Runway), a branch, or some combination of both.\n\n![uploaded image](/media/?type=post&id=71808&key=user_uploads/562880/1bef9a17-07df-4d74-8d39-b1607e832e8e)\n\n🤝 **Standalone or tightly integrated with the rest of Runway**\n\nExactly how you leverage Build Distro is up to your team. You can spin up Build Distro by itself and use it as a standalone tool. Or, for a tightly integrated experience across the entire dev and release cycle, Build Distro plugs seamlessly into Runway’s end-to-end release management platform as a beta integration, allowing you to manage everything to do with pre-prod builds and testers alongside the rest of the release context. \n\n![uploaded image](/media/?type=post&id=71808&key=user_uploads/562880/21fcb35f-06ec-4ee9-8b97-529a179561bc)\n\n### Who is Build Distro for?\n\nBuild Distro is for mobile teams of all sizes who care about getting builds into the hands of team members and testers early and often. \n\nThere are a few team members that might be especially excited about Build Distro:\n\n* Mobile engineers who want to get more eyes on their in-progress work, well before it makes its way to the team’s main branch\n* PMs who care about checking out product work as it’s being developed, without having to hunt around for specific builds\n* QA folks who want to stay on top of testing without the volley of unintelligible build numbers over Slack\n* Anyone on the team, technical or non-technical, who cares about the product and wants to check out and help test builds pre-production\n\n \n\n### How to give Build Distro a try\n\nYou can sign up for free on the [Runway site](https://app.runway.team/signup?intent=buildDistro), no credit card required, and we’re always available to give folks a guided walkthrough as well – just get in touch!",
        "url": "https://www.ycombinator.com/launches/IgC-build-distro-by-runway",
        "votes": 9,
        "created_at": "2023-05-24T15:53:19.752Z"
      },
      {
        "id": 67143,
        "title": "📲 📈 Rollouts by Runway",
        "tagline": "Automate app rollouts with a full picture of release health",
        "body": "# A single source of truth for mobile release health, instantly understandable – and actionable\n\nAs former mobile engineers ourselves, the Runway team and I have experienced the challenge of rollouts firsthand  — and now, we’ve built something that can help. We’re excited to announce [_Rollouts_](https://www.runway.team/blog/introducing-rollouts-by-runway), a new part of the Runway platform that helps your team navigate rollouts with less collective stress, and more confidence. _Rollouts_ allows you to easily keep tabs on release health in just one place instead of many, alerts you whenever configured metrics become unhealthy, and safeguards release health by automatically halting rollouts based on thresholds you define.\n\n# What is _Rollouts_?\n\nHere are some highlights:\n\n### 🗺 The only complete picture of release health\n\nRollouts integrates with the mix of different tools you use to measure app health – crash reporting, observability & product analytics, the app stores (for per-version user ratings) – to create a single source of truth and unified dashboard that gives your team a holistic and instantly understandable view of release health at a glance. No more context-switching, no more mental overhead.\n\n![uploaded image](/media/?type=post&id=67143&key=user_uploads/562880/098822f9-93e6-4ac4-a612-c13ce50f187e)\n\n### 🌡 You define exactly what “healthy” means for your team\n\nAcross all tools and every metric, you can configure granular thresholds that together define what “healthy” looks like for your team. Runway will surface a crystal clear view of how each release is tracking relative to that definition. With expectations around health codified this way, there’s no room for ambiguity or hand-waving when it comes to your team’s standards for quality of the product you’re shipping.\n\n![uploaded image](/media/?type=post&id=67143&key=user_uploads/562880/479df881-d88e-4e1e-9cc2-d4ac27941bc4)\n\n### 🚨 Avoid blind spots and delays with instant alerting\n\nThe moment any of your configured metrics become unhealthy during a rollout, Runway will alert your team, in specific channels of your choosing and with full context on which metrics are problematic. You can be confident that no bad trends will go unnoticed – and that they can be acted on more quickly.\n\n![uploaded image](/media/?type=post&id=67143&key=user_uploads/562880/115d18e8-0167-47e6-8ce4-630bed0f564a)\n\n### 🛑 Automatically halt unhealthy rollouts\n\nBuilding on the custom thresholds you define, Runway can automatically halt unhealthy releases. With this automation enabled, if certain metrics of your choosing fall afoul of your acceptable thresholds during a rollout, Runway will automatically stop the rollout and alert your team. This prevents delays and human error, saving you from the negative consequences of a bad release making it out to even more users.\n\n_(Available on the Runway Pro plan and above.)_\n\n![uploaded image](/media/?type=post&id=67143&key=user_uploads/562880/7f6156eb-df96-4332-b4d7-c432c4aac58f)\n\n### 💨 Automatically accelerate healthy rollouts\n\nIf all of your metrics are looking good and your rollout has reached a minimum number of users you define, Runway can accelerate things and release to all users immediately. Getting a good release out to all users more quickly can be just as impactful as halting a bad release!\n\n_(Available on the Runway Pro plan and above.)_\n\n![uploaded image](/media/?type=post&id=67143&key=user_uploads/562880/9088b19a-3ce0-467f-a390-2368f4c92464)\n\n# Who is _Rollouts_ for?\n\n_Rollouts_ is for mobile teams of all sizes who care about the quality and health of the apps they ship. If you want to ensure you’re not shipping bad product and your users are having the best possible experience, without painstaking babysitting, _Rollouts_ is for you.\n\nThere are a few folks _Rollouts_ might resonate with especially:\n\n* Release captains/drivers/pilots who want to de-stress and de-risk the experience of being in the driving seat during a rollout\n* Mobile engineers who are tired of poking PMs to check on key events in some analytics dashboard they don’t have access to or don’t understand\n* PMs who are tired of said mobile engineers poking them all the time\n* Mobile leads or EMs who want to be sure their entire team has the full picture of release health, to foster a healthy sense of ownership and accountability\n* Engineering leadership who care about keeping tabs on their mobile org, easily and noise-free\n* Anyone and everyone who cares about app health and preventing bad releases from making it out to even more users\n\n \n\n# How to give _Rollouts_ a try\n\nYou can sign up for a free trial via the [Runway site](https://www.runway.team), no credit card required, and we’re available to give folks a guided walkthrough as well – just get in touch!\n\nFor indies, small teams, and YC fam, we’re happy to talk discounting too.",
        "url": "https://www.ycombinator.com/launches/HSx-rollouts-by-runway",
        "votes": 18,
        "created_at": "2022-11-04T20:56:59.348Z"
      }
    ]
  },
  {
    "id": 22632,
    "name": "authzed",
    "slug": "authzed",
    "former_names": [
      "Petricorp",
      "Inc."
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ee578b781cb190a51362b9fda6dc57b36d74972d.png",
    "website": "https://authzed.com",
    "all_locations": "New York City, NY, USA; Remote",
    "long_description": "We build the tools companies need to provide performant and scalable authorization for their applications.\r\n\r\nWe’re founded by 3 successful entrepreneurs with expertise in enterprise software, most recently as leaders at Red Hat. Jake and Joey met on the APIs team at Google in 2010. They went on to found Quay, where Jimmy joined as their first hire. Over the past decade, they’ve changed the landscape for building and deploying software.",
    "one_liner": "Authorization Infrastructure securing AI at OpenAI, Zoom, & more",
    "team_size": 31,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1624982412,
    "tags": [
      "Developer Tools",
      "Security",
      "Open Source",
      "Data Engineering",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Winter 2021",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Fully Remote"
    ],
    "stage": "Growth",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/authzed",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2021/authzed.json",
    "year_founded": 2020,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/authzed",
    "x_url": "https://twitter.com/authzed",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/authzed",
    "github_url": "https://github.com/authzed",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/ee578b781cb190a51362b9fda6dc57b36d74972d.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
    },
    "founders": [
      {
        "user_id": 589803,
        "full_name": "Jake Moshenko",
        "title": "Founder",
        "founder_bio": "Jake Moshenko is an engineering leader that has been building infrastructure tools and services for over 15 years for large companies and startups alike. Having previously struggled to keep up with customer permissions demands on products such as CoreOS’s Quay and Tectonic, he was searching for a better way to do application permissions.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jacob-moshenko-381161b/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/6d2259a372f5d31495f85d518256341fa0a490be.jpg"
      },
      {
        "user_id": 597541,
        "full_name": "Jimmy Zelinskie",
        "title": "Founder",
        "founder_bio": "Jimmy Zelinskie is a software engineer and product leader with the goal of empowering the world through the democratization of software via open source development. He's currently the CPO and cofounder of authzed where he's focused on bringing hyperscaler best-practices in authorization software to the industry at large.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jzelinskie",
        "x_url": "https://twitter.com/jimmyzelinskie",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/432dc805c3a6c9f1ac4f0759f6258f3dda97d5af.jpg"
      },
      {
        "user_id": 30633,
        "full_name": "Joseph Schorr",
        "title": "Founder",
        "founder_bio": "",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/joseph-s-4324904/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a17d41b27fc6e7329ab963268732cdb742fa09d8.jpg"
      }
    ],
    "jobs": [
      {
        "id": 88935,
        "title": "Sr. Developer Advocate (US-Based)",
        "url": "https://www.ycombinator.com/companies/authzed/jobs/NoHR6wW-sr-developer-advocate-us-based",
        "location": "US / Remote (US)",
        "type": "Full-time",
        "role": "Operations",
        "role_type": null,
        "salary_range": "$140K - $170K",
        "equity_range": "",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 109442,
        "title": "Sr. Site Reliability Engineer",
        "url": "https://www.ycombinator.com/companies/authzed/jobs/yWu2MKf-sr-site-reliability-engineer",
        "location": "Remote (US)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$150K - $195K",
        "equity_range": "",
        "experience": "5+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 109443,
        "title": "Senior Software Engineer",
        "url": "https://www.ycombinator.com/companies/authzed/jobs/M49hhUO-senior-software-engineer",
        "location": "Remote (US)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$150K - $190K",
        "equity_range": "",
        "experience": "5+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 111196,
        "title": "Senior Site Reliability Engineer, Security",
        "url": "https://www.ycombinator.com/companies/authzed/jobs/KSV1i4b-senior-site-reliability-engineer-security",
        "location": "US / CA / Remote (US; CA)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$150K - $195K",
        "equity_range": "",
        "experience": "5+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 111560,
        "title": "Solutions Engineer - U.S. and Canada",
        "url": "https://www.ycombinator.com/companies/authzed/jobs/ena6RKJ-solutions-engineer-u-s-and-canada",
        "location": "US / CA / Remote (US; CA)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$130K - $160K",
        "equity_range": "",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      }
    ],
    "news": [
      {
        "title": "Permissions management startup AuthZed raises $12M to accelerate its strategic expansion - SiliconANGLE",
        "url": "https://siliconangle.com/2024/06/27/permissions-management-startup-authzed-raises-12m-accelerate-strategic-expansion/",
        "date": "Jun 27, 2024"
      },
      {
        "title": "Cockroach Labs, Authzed stress the importance of distributed SQL - SiliconANGLE",
        "url": "https://siliconangle.com/2023/02/08/qa-cockroach-labs-authzed-stress-importance-distributed-sql-databases-kubecon/",
        "date": "Feb 08, 2023"
      },
      {
        "title": "Google Zanzibar Through Our Eyes - Hacker News",
        "url": "https://news.ycombinator.com/item?id=33910685",
        "date": "Jan 14, 2023"
      },
      {
        "title": "SpiceDB Is Open Source - Hacker News",
        "url": "https://news.ycombinator.com/item?id=28709886",
        "date": "Jan 14, 2023"
      },
      {
        "title": "Zanzibar Implementation SpiceDB Is Open Source - The New Stack",
        "url": "https://thenewstack.io/zanzibar-implementation-spicedb-is-open-source/",
        "date": "Oct 05, 2021"
      }
    ],
    "launches": []
  },
  {
    "id": 22662,
    "name": "Taloflow",
    "slug": "taloflow",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/800c3d46de6422db7c2f3bd538f4a4c7638425b3.png",
    "website": "https://www.taloflow.ai",
    "all_locations": "Los Angeles, CA, USA; Santa Monica, CA, USA; Remote",
    "long_description": "Choosing the right tool for your tech stack is a soul-sucking exercise — countless hours in demos, endless spreadsheets, and the risk of a wrong choice. At Taloflow, our mission is to make technology selection effortless and low-risk for IT and software teams.\r\n\r\nTaloflow is backed by Y Combinator, YC Continuity, Wonder Ventures, Plug and Play Ventures, and Voyager Capital.",
    "one_liner": "Better, faster tech vendor research",
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        "title": "🧠 Codeball – AI Code Review",
        "tagline": "Codeball approves Pull Requests that a human would have approved. Wait less for review, save time and money.",
        "body": "Hey fellow builders!\n\nI'd like to show you something we recently built at Sturdy (W21).\n\n[**Codeball**](https://codeball.ai/) **is a code review AI which approves safe Pull Requests that a human would have approved.** We _hate_ waiting for reviews.\n\nThis started off as scratching our own itch in answering \"How predictable are programmers?\" Very predictable, turned out to be the answer.\n\n![uploaded image](/media/?type=post&id=64214&key=user_uploads/586182/2a1fd4ab-7a26-4a54-a9cd-a7ccc394aaed)\n\n## **🧠 How**\n\nCodeball is trained on over 1M Pull Requests, so it has seen tons of failure (shitty code) and success (decent code) patterns, making it really good at telling the difference.\n\nYou can play with it at [codeball.ai](https://codeball.ai) where you can do \"historical\" tests on GitHub repos to see what Codeball would have done.\n\nUsing AI for mundane reviews saves a bunch of time, but the part that's really cool is that once you stop rubber stamping every single PR, you pay more attention to the tricky ones.\n\n## **👉 Getting started**\n\n![uploaded image](/media/?type=post&id=64214&key=user_uploads/586182/956431aa-6b25-45dc-b343-fb9905cced54)\n\nYou can add Codeball to your repository as a [GitHub Action](https://github.com/sturdy-dev/codeball-action/) (takes like 2 minutes).\n\n_Try for free!_\n\n## **💻 What are developers saying?**\n\nCodeball is currently used by over 100 open-source repositories, including HUGE communities like gogs, kratos, and emqx!\n\n“This is incredible, don’t forget to charge us!” – CEO\n\n“I love it, developers are now trying to ‘cheat’ the system by creating smaller PRs, just like I’ve been telling them to!” – Senior Software Engineer\n\nAlso a bunch more in the [Hacker News thread](https://news.ycombinator.com/item?id=31533180) that made front page recently.",
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        "answer": "In our first startup, we built one of the first cloud cost management products, which was later acquired and is now part of the Flexera One product. That was back in 2012. The cloud cost management space hasn’t changed in 10 years. Every company still starts from the bills, meaning they look for issues and react. With Infracost, we wanted to apply the shift left philisophy, which worked great is security to cloud costs. That’s what Infracost has become - we [Shift FinOps Left](https://www.infracost.io/) into the engineering workflow."
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        "question": "How did you decide to apply to Y Combinator? What was your experience applying, going through the batch, and fundraising at demo day?",
        "answer": "We applied to YC back in 2012. Back then there was 10,000 prices from AWS. Since then, [cloud costs have become very complex](https://www.infracost.io/blog/why-are-cloud-costs-so-complex/), and we now track nearly 4 million prices from AWS, Azure and GCP. YC was fantastic back then (we interviewed with PG), and it was even better when we got accepted into the W21 batch!"
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        "answer": "Our YC group keeps a monthly check-in going. It has been great to meetup on Zoom once a month to talk about any main issues, questions, learnings that any of the companies have had."
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        "answer": "Every single cloud cost management product out there is reactive in nature. Infracost is the only FinOps product that is designed with engineers in mind, making it easy for them to ship code fast, and keep within FinOps best practices before they merge their code. Things like:* Ensuring the right [cloud tags](https://www.infracost.io/docs/infracost_cloud/tagging_policies/) are set* Ensuring [FinOps best practices](https://www.infracost.io/docs/infracost_cloud/finops_policies/) are followed* [Budgets](https://www.infracost.io/docs/infracost_cloud/guardrails/) are checked before money has been spent* Data is integrated into Jira with our [FinOps for Jira](https://www.infracost.io/docs/infracost_cloud/jira_integration/) appAll within the engineering workflow (directly in a GitHub PR, or GitLab MR)."
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    "long_description": "Kitemaker is a faster and more collaborative alternative to Jira optimized for remote teams.\r\n\r\nIt's helping teams spend less time and effort on collaboration by providing a place for discussing and documenting initiatives, it collects activities and discussions across tools, and it's fast and simple to use.\r\n\r\nUnlike tools like Jira and Notion, our primary focus is helping software development teams spend less time coordinating across tools and roles so they have more time figuring out and building the things their users want.",
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        "id": 76035,
        "title": "Kitemaker - Build better software. Together.",
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        "body": "_**TL;DR:** Kitemaker is a tool that allows you to keep specifications, user feedback, roadmaps, and tasks in one place, providing a better workflow than any collection of product management, documentation, and issue-tracking tools. Is it fast? Yes. Is it simple and easy to use? Absolutely. In addition, it works very well to facilitate collaboration between engineering, design, and product management._\n\nHey!\n\nWe're Kevin and Sigurd, the co-founders of [Kitemaker](https://kitemaker.co/). We built Kitemaker because we felt that the tools we used for project management, collecting feedback, and writing specifications were disconnected. This resulted in engineers, designers, and product managers working in separate silos, making it harder to focus on what truly matters: building things that users want.\n\n# **The problem**\n\nMost YC companies have taken the wisdom of [Michael Seibels' \"Product Development Cycles\"](https://www.ycombinator.com/library/4e-guide-to-product-development) to heart. To reach product-market fit, we need to talk to customers, figure out what they want, build, launch, and then iterate. There are plenty of good tools to collect user feedback, write specification documents, and track tasks/issues.\n\nHowever, it's all disjointed. It’s easy to drop the ball on user feedback, which isn’t connected to the tool where we’re writing specs, which again isn’t connected to our issue tracker. It's easy to become disorganized or spend too much time project managing when we should be spending as much time as possible talking to users and iterating on the product and the messaging.\n\n# **Our solution -** Kitemaker\n\nKitemaker allows you to keep specifications, tasks, roadmaps, and user feedback in one place. We have carefully designed it to provide a better workflow than any collection of product management, documentation, and issue-tracking tools.\n\n![uploaded image](/media/?type=post&id=76035&key=user_uploads/394001/e6a52980-d8ce-450d-9e10-a956b9fe3884)\n\n# **How it works**\n\nThe basic unit in Kitemaker is the work item. It has a document where you can write your specifications and break them into tasks, as well as an activity feed for discussions and to see what is happening across the development tools. We encourage you not to split work items into many small pieces but rather use to-dos to keep track of the tasks. This way, you will be able to focus on what you plan to deliver to your users, rather than individual tasks. Additionally, you will have all the to-dos in the same place as your discussions and specifications, meaning there will be one place to see everything relevant to a new feature or a bug fix.\n\n![uploaded image](/media/?type=post&id=76035&key=user_uploads/394001/b736cb07-b7ca-4c58-adee-c43de4ae3fde)\n\nWhen you receive user feedback, we have a section where you can organize all of it. You can either write the feedback directly in Kitemaker, or you can use our Intercom or Zapier integrations (with more integrations to come). You can select any part of the feedback, capture it as an insight, and link it directly to work items. Since the insights and feedback will be directly linked to the work items, you and your team will know exactly what was said and by whom on the work item screen.\n\n![uploaded image](/media/?type=post&id=76035&key=user_uploads/394001/227b02d1-81c1-44a7-8ba1-7696c42f9183)\n\nThere are many more features and integrations for you to explore, so if you are curious, feel free to check out our [website](https://kitemaker.co/).\n\n# What our users love about Kitemaker\n\n* It's fast, easy to use, and simple to get started with.\n* Work items let you have specs, tasks, and discussions in the same place, making it easy for engineering, design, and product management to collaborate in the same tool.\n* Having user feedback directly connected to the stuff you are working on is incredibly powerful, and the Intercom integration directly syncs conversations into Kitemaker.\n* Our to-dos have everything engineers expect for issues, like git automation, referencing, and metadata, so the hierarchy fits perfectly for teams that focus on shipping awesome stuff to users.\n\n# Asks\n\nWe love all kinds of feedback, so if you are curious about Kitemaker, head over to [https://www.kitemaker.co](https://kitemaker.co/) and give us some feedback when you have tried it.\n\nYou can also join our [community here](https://join.slack.com/t/kitemakerco/shared_invite/zt-e7zjicw1-zbBpvLSRfOFKh3DutUAJ0A), where you can discuss Kitemaker or all things product development.\n\nWe’re also super interested in chatting with people about their product development process. Both to learn how you approach it or just give you some insights into what we have seen talking to many 100s of teams.",
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    "name": "Axolo",
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    "website": "https://axolo.co",
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      {
        "id": 83536,
        "title": "Minty: Create engaging video content",
        "tagline": "Minty transforms text into video from stock images.",
        "body": "**TLDR:** 🚀 We’re launching [**Minty**](https://minty.so)—a tool that transforms any text into video content from stock images, making it easier for creators and businesses to reach diverse audiences. We’d love your feedback!\n\n### **Our Ask:**\n\n🙌 Check out [**Minty**](https://minty.so), try it out, and share your thoughts. Your feedback will help us shape the future of this tool. You can try it by inputting a blog article you want a video for.\n\n### **❌ The Problem:**\n\nIn our journey with **Axolo**, we realized that repurposing content into various formats—blogs, presentations, videos—can be time-consuming and complex. With different audiences preferring different content formats, there’s a missed opportunity to fully engage with them.\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXfTYVGk1XGW73RMz0mTQA-DnnstfH2oiCv82Rn3qCqHGaJyKMy_EKzcLc-Lqzq1emfmhtc6SzblJADvj1OnVg4mkcszgGRL_hPrww4NQo3abgcMC9KNf-9GPXvp-GwbStge2zUxwr39MGnKpyFmIAaL3hoV?key=8obgDvzbHJEp-qJnYH2WgQ)\n\n### **The Solution:**\n\n✨ **Minty** makes creating videos from text with just three simple steps:\n\n1. **Form:** 📝 Enter your text, choose a music track, set the tone, pick a social media, and select a voice-over.\n2. **Storyboard:** 🎨 Minty creates an outline of what will be said that you can edit like a Powerpoint presentation, allowing you to edit the voice-over of your video.\n3. **Video Editing:** 🎬 We transform the storyboard into a fully edited video, complete with stock image, voice-over, and subtitles. You can customize it further with your own footage or choose from our stock library.\n\n   ![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXcVmdB62NGETD3HIqpeToFMDD74ByjaljxahKDzMDZgj1Xchy-FVkkyjdpi48t50DDtNiAmbqPD7usQD-NVOuWT2gVZk8483ONYSvyGu-gOAe1NHkhMGQu-JtQ-M2JPpAPURSt-5y2bTd7M0NA0LT-dpe0?key=8obgDvzbHJEp-qJnYH2WgQ)\n\n\nMinty takes the complexity out of video creation, enabling you to focus on delivering your message in a format that resonates with your audience.\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXdApxWGYHI-EKGabzZAt4L4deEjepUzni_STsvkqhsKj_gdnTv9lVo91fTjL6zkeCLb_N4Gqrue8hC8zFNGejxmxdwKYN0tS615Ma2zvb82f9go7ymk3OT4e7mhHEDnwdACbPcJtqmDKCE158VGZL7nexup?key=8obgDvzbHJEp-qJnYH2WgQ)\n\n",
        "url": "https://www.ycombinator.com/launches/LjM-minty-create-engaging-video-content",
        "votes": 8,
        "created_at": "2024-08-28T14:32:56.222Z"
      },
      {
        "id": 69349,
        "title": "🦁 GitLab Integrations: The store to find your next GitLab app",
        "tagline": "Help us list all the GitLab apps out there",
        "body": "Hey YC!\\\n\\\nwe've been working on the GitHub ecosystem for two years, and while integrating the GitLab API into our services, we found that it was missing key feature to help both developers build and engineering teams find new apps to improve their workflow.\n\nSo, we're excited to launch [GitLabIntegrations.com](http://GitLabIntegrations.com) to help developers find their next best GitLab apps.\n\n**🤯 Problem:**\n\nThere is no central place to list all of the integrations. GitLab only lists a few <https://docs.gitlab.com/ee/integration/>.\n\n**Integrations allow for a more flexible workflow**\n\nThere are many GitLab integrations out there that can help your team be more productive and help your business ship value to customers faster.\n\n**🦁 Introducing** [**GitLabIntegrations.com**](http://GitLabIntegrations.com)**: we help you find the tools you were always looking for.**\n\nOur platform features over 40 integrations and 11 categories to help you find what you're looking for quickly and easily. So, whether you're looking for tools to improve your team's productivity or help your business ship value to customers faster, [GitLabIntegrations.com](http://GitLabIntegrations.com) has got you covered.\n\n**Ask YC**\n\nIf you find our platform helpful, we invite you to contribute by adding integrations you use that aren't listed, or even the ones you've created. Simply follow the link: <https://gitlabintegrations.com/add-an-app> to share your integration with the community.\\\n\\\nHomepage:\n\n![uploaded image](/media/?type=post&id=69349&key=user_uploads/743846/fe801855-41ca-4c44-808f-6acf77f1e8b5)\n\n\nAxolo being featured:\n\n![uploaded image](/media/?type=post&id=69349&key=user_uploads/743846/e024637e-7969-44f8-9126-6c5b5411f716)\n\n",
        "url": "https://www.ycombinator.com/launches/I2X-gitlab-integrations-the-store-to-find-your-next-gitlab-app",
        "votes": 12,
        "created_at": "2023-02-16T14:46:20.840Z"
      },
      {
        "id": 66958,
        "title": "Axolo: Merge code faster 🐙 now on GitLab (and GitHub)",
        "tagline": "Review merge requests faster",
        "body": "On top of GitHub Axolo is now also available on GitLab. Now every team who is on Slack and GitLab or GitHub can collaborate seamlessly on code reviews.\n\n**🤯 Problem:**\n\nWhy pay engineers 100 thousand dollars to have them sit and wait for their code to be reviewed? Code review workflow is, more often than not, unproductive.\n\n\\\nWe’ve identified three major problems:\n\n1. Time to review: Takes too long to be reviewed and it’s painful.\n2. Context switching: Switching between code review tools and Slack to communicate is a time waster.\n3. Documentation: It’s hard to document everything that is being said. Merge requests are being talked about in DM and private calls. There is no documentation, and it’s hard to know why a decision was made.\n\n**🎯Developers lose precious focus time**\n\nWe estimate that developers waste at least 2 hours per week coordinating with one another on pull requests.\n\nFor a team of 20 that represents the work of 1 developer full-time. This is at least 140k$ per year.\n\n**🏚 In-house solutions and bots are going OBSOLETE.**\n\n1. Noizy - Alerts everyone and then gets ignored\n2. Hard to maintain\n3. Miss critical info: deployments, GitHub Actions, and checks.\n\n**\\\n🐙 Introducing Axolo: we bring back focus to your developers:**\n\nCompanies using Axolo have seen a 40% decrease in average cycle time. 86% of developers who use Axolo on a daily basis say that it has improved their code review workflow.\\\n\\\n**How does it work?**\n\nIt’s simple: Axolo creates an ephemeral Slack channel for each code review, invites only the right people, and adds all contextual information needed (CI/CD, ticket link, code conflicts, code review comments, etc..). When the code is merged the channel gets archived silently.\n\n\\\nStill Sceptical? Check our [reviews on G2](https://www.g2.com/products/axolo).\n\nWe have already more than 1400 engineers on Axolo every day and are proud to be working with excellent YC companies such as [@Weekday](https://bookface.ycombinator.com/company/22719), [@Formance (fka Numary)](https://bookface.ycombinator.com/company/24379), [@Lamin Labs](https://bookface.ycombinator.com/company/27092), [@Curebase](https://bookface.ycombinator.com/company/1884), [@Swayable](https://bookface.ycombinator.com/company/1878), [@Jovian](https://bookface.ycombinator.com/company/24205), [@Swayable](https://bookface.ycombinator.com/company/1878), [@Marble](https://bookface.ycombinator.com/company/24497), [@Centaur Labs](https://bookface.ycombinator.com/company/11948), [@Fuse](https://bookface.ycombinator.com/company/12073), [@ClipDrop](https://bookface.ycombinator.com/company/22752), and more…\n\n**Ask YC**\n\nCommunication and collaboration are one of the five pillars of highly effective tech teams (according to the [SPACE framework](https://axolo.co/blog/p/developer-productivity)).\\\n\\\nIf you are looking to have productive code reviews, and have squads composed of 3-15 engineers, we are interested in getting your feedback on Axolo. Just reach out within the chat on <https://axolo.co> and we’ll be around!",
        "url": "https://www.ycombinator.com/launches/HPy-axolo-merge-code-faster-now-on-gitlab-and-github",
        "votes": 11,
        "created_at": "2022-10-27T10:58:00.941Z"
      },
      {
        "id": 64233,
        "title": "Axolo 🐙  GitHub-Slack two-way synchronization",
        "tagline": "Enable your team to merge pull requests faster",
        "body": "**Problem?** GitHub pull request workflow is unproductive\n\n1. Time to review: Dangling pull requests are waste of time and a source of frustration for developers. They cause the code development process to slow down and prevent developers from focusing on a new task ahead.  Engineers need to write DM + @channels to get the attention their work needs.\n2. Context switching: Between GitHub, Slack, video calls, and their product management software, engineers are piling up their mental load with so many tools and notifications.\n3. Documentation: Pull requests are being talked about in DM and private calls. There is no documentation, and it’s hard to know why a decision was made.\n\n\\\n**Solution?** Axolo centralizes pull requests in contextual Slack channels\n\n1. 1 PR = 1 Slack channel. Only invites reviewers and creators.\n2. Get personalized and friendly reminders about stale pull requests.\n3. The conversation is saved on GitHub.\n4. The Slack channel is auto-archive when the PR is merged and you can also auto-leave PR channels after approval.\n\n![uploaded image](/media/?type=post&id=64233&key=user_uploads/549618/bcd6df74-f0de-4e66-86d9-d8f1e5ac0186)\n\n\n**🗣 What customers say about Axolo:** \n\nManuel: \"The tool we needed for the daily work\"\n\nRushil: “Big fan of Axolo. It makes communication easier between Slack and GitHub! Highly recommend!”\n\nManav: “Team has loved so far - much easier to track who's assigned to what without annoying everyone. Also love that we can discuss solutions in slack.”\n\nHrishi: \"I no longer miss any updates to the PRs I'm interested in\"\n\nAkshay: \"Been an early user & have not found anything else which comes close to improving our PR workflow\"\n\nMore about our 4.9/5 rating on G2: <https://www.g2.com/products/axolo/reviews#survey-response-6798037>\n\n![uploaded image](/media/?type=post&id=64233&key=user_uploads/549618/68dfba9a-97e8-40a0-822d-17b10f40ee08)\n\n![uploaded image](/media/?type=post&id=64233&key=user_uploads/549618/48ae6726-41e9-479b-9294-378452261ebc)\n\n![uploaded image](/media/?type=post&id=64233&key=user_uploads/549618/320ddcd8-17b0-43e9-9a2a-0e0f86e6385a)\n\n![uploaded image](/media/?type=post&id=64233&key=user_uploads/549618/082fe326-e5de-469d-9828-71e918cd1ca0)\n\n",
        "url": "https://www.ycombinator.com/launches/Gi1-axolo-github-slack-two-way-synchronization",
        "votes": 22,
        "created_at": "2022-06-30T16:06:55.836Z"
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    "name": "Wasp",
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    "website": "https://wasp-lang.dev/",
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    "long_description": "Wasp is a simple configuration language for building enterprise web apps with less code and best practices. If a developer wants to build an app like Instacart, they need to know a dozen different technologies and how to make them work together - Wasp solves this problem while still letting developers use React, Node.js and their other favourite tools.\r\n\r\nWe will enable enterprises to build modern apps quickly at scale, like Databricks did for data management.",
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    "industry": "B2B",
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    "city": "Zagreb",
    "country": "HR",
    "linkedin_url": "https://www.linkedin.com/company/71519348",
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        "full_name": "Matija Šošić",
        "title": "Founder",
        "founder_bio": "Comp Sci MSc & Software Engineer.\nI am excited about clean code, functional programming, web dev, building teams and useful products. In my free time I enjoy calisthenics and photography.\n\nExperience:\n- led engineering team at Lifebit Biotech\n- Techstars Tech Associate (London), cohort of 2017\n- CEO & Co-founder @ TalkBook (https://talkbook.co/home)\n- Noom, New York - SWE internship (2014)\n- A*Star, Bioinformatics institute Singapore - research internship (2011)",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/matijasosic",
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      {
        "user_id": 172113,
        "full_name": "Martin Sosic",
        "title": "Founder",
        "founder_bio": "Software engineer, computer scientist (M.Sc.) and entrepreneur.\nI am excited about building a product, open source, functional programming, web development, clean code, customer development.\nEx algorithmic competitor, SWE intern at Google, Palantir and Bioinformatic Institute (Singapore), author of Edlib library, dev associate at Techstars 2017, founder of Talkbook (startup), led engineering team at Lifebit.ai.\nI love mechanical keyboards, emacs, haskell, calisthenics and playing instruments.\n",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/martinsosic",
        "x_url": "https://x.com/martinsosic",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c6e736a95346f2eeb1c60491a25190ac3069bad4.jpg"
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    "news": [
      {
        "title": "Wasp's platform is the glue that holds web dev apps together | TechCrunch",
        "url": "https://techcrunch.com/2025/04/17/wasps-platform-is-the-glue-that-holds-web-apps-together/",
        "date": "Apr 17, 2025"
      },
      {
        "title": "YC grad Wasp land $1.5M seed to help developers build web apps faster – TechCrunch",
        "url": "https://techcrunch.com/2021/10/04/yc-grads-wasp-land-1-5m-seed-to-help-developers-build-web-apps-faster/",
        "date": "Oct 04, 2021"
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    ],
    "launches": [
      {
        "id": 67668,
        "title": "🐝 Wasp Beta - Develop full-stack web apps in React & Node.js without boilerplate",
        "tagline": "Get auth, CRUD, async workers and other common features via Wasp config language and write the rest of your logic in React, Node.js and Prisma",
        "body": "Hey developers! 👋 We’re Martin and Matija, founders of Wasp - we’re super excited to be here today!\n\nOur last big launch was one and a half years ago - since then a lot happened and **we’re proud to present Wasp Beta!**\n\n![uploaded image](/media/?type=post&id=67668&key=user_uploads/109403/0ed916ef-e2e5-4cd4-8241-f9702617e45e)\n\n### **⚡️TL;DR**\n\n**Wasp is the fastest way to develop full-stack web apps in React & Node.js**. Describe high-level features (auth, CRUD, async jobs, …) via a simple config language, and write the rest of your logic in React, Node.js and Prisma.\n\nWith the Beta release, we also [**announced our first hackathon**](https://betathon.wasp-lang.dev/) - make sure to join, have fun, and win cool prizes! (hint: wasp-themed mechanical keyboard 🐝 ⌨️)\n\nYou can see the 4-min demo video [here](https://youtu.be/eVXbctXquK4).\n\n### **🐝 🐝 The team**\n\n![uploaded image](/media/?type=post&id=67668&key=user_uploads/109403/49bc358b-14d3-4385-b593-f1b175a0795a)\n\nThis is us at our first retreat in Croatia (Vince, our devrel, who joined shortly after, expertly photoshopped in :D)!\\\nWe’re a distributed team of engineers and web development & programming language aficionados. Having worked at some of the world’s largest companies and startups, we experienced the problem we’re solving at various stages.\n\n### 💡 **What is Wasp?**\n\n**You can think of Wasp as a full-stack web framework for React & Node.js**. We solve the common problems you face when you start developing a web app - choosing all the parts of the stack, figuring out how to stitch them together in the best way, adding auth, running cron jobs, ...\n\nWasp also makes it super easy to work with and sync data models across the entire stack (front-end, back-end, database). You don't even have to define and deal with any kind of CRUD API - Wasp will do that for you under the hood.\n\n![uploaded image](/media/?type=post&id=67668&key=user_uploads/109403/7e32a672-dec6-4f31-9fa7-1c9c35de2545)\n\n### 🦉 **Who is it for?**\n\nSpeaking to developers we realized many of them just want to build, and they’ll use whichever tool helps them best achieve their goals. They don’t care that the library being used for making HTTP requests is 2kb bigger and builds 10ms slower than some new alternative. They just want to be sure they have all the best practices in place and that their choices won't come back to haunt them once their project grows.\n\nIf you can relate to that, then Wasp is for you. We know there are plenty of great solutions for developers today (frameworks, BaaS-es, code scaffolders, ...) but Wasp is probably the fastest one to get started with, and with the least amount of code.\n\n### 🍜 **What's the secret sauce?**\n\nThe main reason for that is Wasp's unique twist on web frameworks - a config language (DSL) that works alongside your React & Node.js code. It allowed us to **drastically reduce the amount of boilerplate and simplify the developer experience**. For example, full-stack authentication with both user/pass and Google methods takes only 8 lines of code.\n\nIn the future, the language approach could enable us to do some really exciting things such as supporting multiple frameworks and languages (even at the same time) and having full control over the generated code, introducing optimizations, etc.\n\n![uploaded image](/media/?type=post&id=67668&key=user_uploads/109403/d712d053-1786-4d31-af06-cc773c00444f)\n\nWasp now has its own language server - that means auto-completion, live error reporting, …\n\n🏘 **What can I build with Wasp?**\n\nPretty much any web app with a database! Anything you'd build with React & Node.js by themselves you can build with Wasp. Think SaaS, side projects, internal tools, hackathons, ...\n\nTo see what others are building with Wasp, take a look here: [Wasp showcase gallery](https://wasp-lang.dev/#showcases)\n\n![uploaded image](/media/?type=post&id=67668&key=user_uploads/109403/8cf380fa-522b-470a-bbf9-95b3f0201034)\n\nWith the intro out of the way, let's see what's new in Beta:\n\n![uploaded image](/media/?type=post&id=67668&key=user_uploads/109403/702a317f-f8e9-446e-b8f1-46f59e95cb5d)\n\n🔑 **Full-stack auth**\\\nLog in with your username & password or via Google! Other providers are also coming soon.\n\n🟦 **TypeScript support** \\\nWrite your code in TypeScript, both on the client and server! We're also migrating our whole codebase and adding new types every day.\n\n💨 **Tailwind support**\\\nJust add two config files and you are ready to use Tailwind in your project!\n\n⏳ **Running Async Jobs**\\\nSend emails, crunch data every night and build reports or anything that shouldn't be a part of a typical request-response cycle. Powered by pg-boss, zero setup required.\n\n🥛 **Optimistic updates support** Wasp will by default propagate your data model changes across the stack. Still, [in some cases](https://wasp-lang.dev/blog/2021/12/02/waspello#what-doesnt-work-yet), you might want more control over that flow for the sake of smoother UX - that is now easy to achieve with Wasp!\n\n📟 **Wasp Language Server**\\\nWasp now has its own LSP for VS Code (other editors coming soon)! That means improved syntax highlighting, code snippets, autocompletion, and error reporting. Everything you'd expect from a language!\n\n### **🙌 Our ask**\n\n* Try Wasp out & let us know your feedback - **join our Discord**!\n* J[oin our Beta hackathon - Betathon](https://betathon.wasp-lang.dev/)! It’s open until Dec 14\n* Share [Beta](https://wasp-lang.dev/blog/2022/11/26/wasp-beta-launch-week) with your developer friends",
        "url": "https://www.ycombinator.com/launches/HbQ-wasp-beta-develop-full-stack-web-apps-in-react-node-js-without-boilerplate",
        "votes": 20,
        "created_at": "2022-12-02T16:28:34.296Z"
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    "name": "hoop.dev",
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    "long_description": "hoop.dev prevents developers from blocking on Devops tasks. We do this by enabling any engineer do Devops work under the supervision of the Devops team. You can think of us as code review for Devops tasks.",
    "one_liner": "Code review for DevOps tasks",
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        "full_name": "Andrios Robert",
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    "website": "https://authologic.com",
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    "long_description": "Authologic is an orchestration and aggregation layer for local KYC & AML methods. We allow businesses to check the identity of their clients online using video/biometrics, banking data, and government issued digital IDs. Our API  allows a flexible definition of verification scenarios based on the risk profile of the client or risk involved in the given process.",
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        "full_name": "Marek Rogoziński",
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        "title": "Campaign Manager (GTM, ABM & Events)",
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    "id": 23612,
    "name": "Terra API",
    "slug": "terra-api",
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    "website": "http://tryterra.co",
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    "long_description": "Terra makes it easy to transfer health data.\r\n\r\nThe unified API makes it easy to access data from health apps, wearables, sensors, and medical equipment through one source",
    "one_liner": "API for developers and AIs to access health data ",
    "team_size": 25,
    "industry": "B2B",
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      "America / Canada"
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    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/terraapi",
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        "full_name": "Kyriakos Eleftheriou",
        "title": "Founder/CEO",
        "founder_bio": "Weight lifter, ex-Special Forces and founder + CEO of Terra API\n",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/kyriakos-eleftheriou/",
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        "title": "AI Engineer",
        "url": "https://www.ycombinator.com/companies/terra-api/jobs/0f5CP0r-ai-engineer",
        "location": "London, England, GB",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Machine learning",
        "salary_range": "$50K - $120K",
        "equity_range": "0.10% - 0.50%",
        "experience": "Any (new grads ok)",
        "visa": "US citizenship/visa not required",
        "skills": []
      },
      {
        "id": 63172,
        "title": "Sales Strategist",
        "url": "https://www.ycombinator.com/companies/terra-api/jobs/4QSWmBq-sales-strategist",
        "location": "London, England, GB",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "£50K - £90K GBP",
        "equity_range": "0.10% - 0.20%",
        "experience": "3+ years",
        "visa": "US citizenship/visa not required",
        "skills": []
      },
      {
        "id": 91600,
        "title": "Forward Deployed Engineer",
        "url": "https://www.ycombinator.com/companies/terra-api/jobs/R0hx4lm-forward-deployed-engineer",
        "location": "London, England, GB / CY / Remote (US)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$100K - $180K",
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        "experience": "3+ years",
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      },
      {
        "id": 96190,
        "title": "Designer",
        "url": "https://www.ycombinator.com/companies/terra-api/jobs/js73J9L-designer",
        "location": "London, England, GB",
        "type": "Full-time",
        "role": "Design",
        "role_type": "UI / UX",
        "salary_range": "£38 - £90 GBP",
        "equity_range": "0.10% - 0.50%",
        "experience": "3+ years",
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        "skills": []
      },
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        "id": 109293,
        "title": "Commercial Lead",
        "url": "https://www.ycombinator.com/companies/terra-api/jobs/TvgdSp9-commercial-lead",
        "location": "London, England, GB",
        "type": "Full-time",
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        "role_type": null,
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        "experience": "3+ years",
        "visa": "US citizen/visa only",
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    ],
    "news": [
      {
        "title": "Alistair Brownlee OBE: celebrating Alistair's OBE from Prince of Wales | Terra",
        "url": "https://tryterra.co/blog/Alistair-Brownlee-OBE-award",
        "date": "Oct 14, 2026"
      },
      {
        "title": "Terra Research Published in Nature's Biological Timing and Sleep",
        "url": "https://tryterra.co/research/terra-research-nature-publication",
        "date": "Jun 28, 2026"
      },
      {
        "title": "What's the hardest endurance sport? Olympic triathlon champion Alistair Brownlee weighs in with data analysis",
        "url": "https://www.olympics.com/en/news/hardest-endurance-sport-olympic-triathlon-alistair-brownlee-data-analysis",
        "date": "Apr 22, 2026"
      },
      {
        "title": "Perplexity connecting health users through Terra API",
        "url": "https://x.com/kyriakosel/status/2034744624217297215",
        "date": "Mar 18, 2026"
      },
      {
        "title": "Podcast - Talks with founders, executives, and investors redefining Health",
        "url": "https://tryterra.co/podcast",
        "date": "Jul 01, 2024"
      }
    ],
    "launches": [
      {
        "id": 94347,
        "title": "Tyran: AI Health Agents for your app",
        "tagline": "Create health agents with any data source, and connect to your app",
        "body": "Hey 👋 We are building [Tyran](https://tyran.ai), the AI Health Agents.\n\n**tl;dr:** Build **AI health agents** on top of any data — wearables, labs, sleep, HRV. Detect jet lag, catch illness before symptoms, spot sleep apnea, flag overtraining — and plug it all into your app in minutes, without a line of code.\n\nhttps://www.youtube.com/watch?v=VXDRR_qU250\n\n## **What you can use Tyran AI for**\n\nSome early examples\n\n* Detect jet lag\n* Detect signs of potential asthma (NOT medical diagnosis, obviously!)\n* Detect the upcoming menstrual cycle\n* Understand recovery\n* Run multiple experiments: test different workout timings or rest protocols per user segment.\n\n## **How it works**\n\n1. Sign up, connect health data sources via plug-and-play auth widget.\n2. Pick an agent template (or prompt the agent).\n3. Define schedule + outcomes (alerts, notifications, adjusted plans).\n4. Get validated outputs (typed JSON), export via webhooks, or integrate directly into your product.\n\n## **What’s new**\n\n* 🚀 **Fast feature build** - From idea to working health insights in **minutes**\n* 🔗 **Connect any health source** - 500+ metrics from wearables, labs, nutrition, sleep, HRV, etc.\n* 📚 **Templates & agent types** - Prebuilt agents for recovery optimization, risk detection, women’s health, root-cause analysis, experimental health logic.\n* ⚙️ **Custom logic + actions** - Go beyond dashboards: trigger alerts, notifications, update workout plans, or send recommendations programmatically.\n* 🛠 **Full agent lifecycle tools** - scheduling, versioning, monitoring; typed output (JSON) so downstream systems / UIs stay reliable.\n* **📝 Memory -** Agents remembering information and improving over time\n\n![uploaded image](/media/?type=post&id=94347&key=user_uploads/356569/43654838-a834-42b0-b3f1-d13639d6f526)\n\n",
        "url": "https://www.ycombinator.com/launches/OXj-tyran-ai-health-agents-for-your-app",
        "votes": 26,
        "created_at": "2025-10-03T15:44:22.728Z"
      },
      {
        "id": 81615,
        "title": "Health Scores for developers",
        "tagline": "The easiest way to add Sleep, Stress, Heart and health scores for developers",
        "body": "[Health Scores](https://www.youtube.com/watch?v=frTfSO39e10)\n\nWe are launching today Health Scores: The easiest way for developers to integrate and display scores such as Sleep, Stress, Heart Health, Training Load and many more.\n\nThis provides a seamless way to show critical data points such as Sleep, Stress, Heart Health, Training Load, and much more to end users. \n\n**Launching Today: The Sleep Score**\n\nThe first available feature, the Sleep Score, is now live. \n\nThis score analyzes various aspects of a user’s sleep, including REM, Deep, Light, and Awake stages, along with HRV, RHR, respiration, and body temperature, to provide a comprehensive sleep quality assessment.\n\n**Customizable Scoring Model**\n\nAs a Developer, you can easily customise this and create proprietary models using a simple drag-and-drop interface, assigning different weights to various metrics to tailor the scores according to specific needs.\n\n[Click to get started](https://dashboard.tryterra.co)\n\n![uploaded image](/media/?type=post&id=81615&key=user_uploads/356569/fe0ade75-50c9-4bd5-808a-1ea55604a35d)\n\n",
        "url": "https://www.ycombinator.com/launches/LEN-health-scores-for-developers",
        "votes": 12,
        "created_at": "2024-06-19T16:48:14.926Z"
      },
      {
        "id": 80833,
        "title": "Terra API: Easily create AI health agents with wearable data",
        "tagline": "The easiest way for developers to create health agents with health data",
        "body": "**tl;dr:** Terra API allows you to connect health data with AI, such as GPT-4o and Claude 3, and develop health AI agents.\n\n**The story**\n\nOver the last year, hundreds of developers have used [Terra](https://tryterra.co) to create AI solutions. We’ve seen solutions for fitness, sleep, nutrition, telemedicine, longevity, and more.\n\nWe decided to reduce the complexity fully and embed all the AI experience within the dashboard so you can easily develop such solutions.\n\n![uploaded image](/media/?type=post&id=80833&key=user_uploads/356569/dac1c7ed-4d5d-4b2b-a337-d4e46ee93b8d)\n\n**How it works:**\n\n* Choose the wearables and health apps you want connected\n* Choose the AI you want, from GPT-4o to Claude 3.\n* Prompt the model\n* Choose your destination to receive the data\n\n**What’s coming next:**\n\n* More integrations with Perplexity, Llama and others\n* More destinations to store data\n* Improvement in prompting\n* Availability of voice, camera and more\n\n**Getting Started**\n\nCreate an account [here](https://dashboard.tryterra.co/) and choose your AI of choices from the processes.\n\n[ ](https://www.youtube.com/watch?v=PA2FR_A1pc0)",
        "url": "https://www.ycombinator.com/launches/L1l-terra-api-easily-create-ai-health-agents-with-wearable-data",
        "votes": 20,
        "created_at": "2024-05-14T16:46:02.256Z"
      },
      {
        "id": 71969,
        "title": "OdinAI by Terra",
        "tagline": "Generate health recommendations for any app",
        "body": "### **TLDR**:\n\nTo date, it has been super difficult to generate health insights and recommendations for your application.\n\nWith [OdinAI](https://tryterra.co/products/odinai), we make it super easy for you to add health recommendations to your app! We built all the necessary software tools and help you deliver these recommendations through ChatGPT!\n\n* Get started [here](https://tryterra.co/products/odinai?ref=producthunt)\n\n![uploaded image](/media/?type=post&id=71969&key=user_uploads/356569/bfda54d3-5766-4a7f-bf4f-c68ce32581d8)\n\n### What is [Terra](https://tryterra.co)\n\nAn API that makes it super easy for apps to connect to wearables and sensors.\n\nMany of our customers have been asking for an easy way to generate recommendations, so we connected with ChatGPT and made it possible.\n\n### The way it works:\n\n1\\. You upload your recommendations\n\n2\\. We prompt ML models and optimize them for your app\n\n3\\. You receive the recommendations through our API\n\nThis can be for your sleep, mental health, nutrition, training, and overall health app!\n\n[OdinGPT Private Alpha Release - Watch Video](https://www.loom.com/share/247f12f4519340278426b86cfc5ca148)\n\n![](https://cdn.loom.com/sessions/thumbnails/247f12f4519340278426b86cfc5ca148-with-play.gif)\n\n\n### What's coming in the upcoming updates:\n\n\\- Granular level responses\n\n\\- Chatbot to install for your app\n\n\\- Optimised recommendations for specific categories,\n\n\\- and many more!\n\nWould love to hear your thoughts, and feel free to ask for features you'd like to see!",
        "url": "https://www.ycombinator.com/launches/Iin-odinai-by-terra",
        "votes": 12,
        "created_at": "2023-06-01T13:45:02.528Z"
      },
      {
        "id": 64219,
        "title": "Terra: API to connect your app to wearables",
        "tagline": "New product: Connect your app to real-time wearable data.  Garmin, Fitbit, Oura, Peloton and others, through a single source",
        "body": "![uploaded image](/media/?type=post&id=64219&key=user_uploads/356569/73457b9e-0593-4ecd-b5e1-f6d5fc70f490)\n\n### The problem:\n\nConnecting to wearables such as Garmin, Fitbit, Oura, Wahoo, etc is a very long process. You need to deal with partnerships and poorly written docs and create an internal DevOps team.\n\n### What we do\n\n[Terra](https://tryterra.co/) is an **API** that makes it easy for apps to connect to all wearables.\n\nWe already have all the [integrations](https://tryterra.co/integrations) you need, such as Apple, Garmin, Peloton, Zwift, Freestyle Libre, Samsung, and the list goes on.\n\nOne integration is all that matters 😀\n\n### The new product\n\nWe just released our **new** beta product: **Real-time streaming** of wearable data, through our Websocket API! You can now connect any app, through your heart rate belt, be it from Polar, Suunto, Garmin or anything that supports BLE 🎉🎉\n\n* More about Terra [here](https://tryterra.co)\n* More about the real-time streaming [here](https://blog.tryterra.co/realtime-data-streaming-3db7a5a207ae)\n* More about the docs [here](https://docs.tryterra.co)\n* and some [stories](https://blog.tryterra.co/startup-spotlight/home) from our customers\n\n![uploaded image](/media/?type=post&id=64219&key=user_uploads/356569/226e3640-0d81-4cc3-a05a-26c352b56fe1)\n\n",
        "url": "https://www.ycombinator.com/launches/Ghn-terra-api-to-connect-your-app-to-wearables",
        "votes": 51,
        "created_at": "2022-06-30T09:24:13.771Z"
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        "answer": "Read about our remote YC experience - <https://www.magicbell.com/blog/the-ycombinator-experience-remote-edition>"
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        "full_name": "Hana Mohan",
        "title": "Founder",
        "founder_bio": "I code, bike, and read obsessively. Passionate about empowering women and other minorities. Previously, CEO SupportBee.com. ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/unamashana/",
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        "id": 72453,
        "title": "🔔 WebPushTest.com - iOS Safari web-push notifications demo & code",
        "tagline": "iOS 16.5 ships with a standards based web-push notifications, but you need a PWA to try it out",
        "body": "iOS launched web push notifications a month ago with 16.5, but there has been a surprising lack of examples to try out. We built [WebPushTest.com](http://WebPushTest.com) and made the code open source so more devs can try it out and share it with their coworkers!\n\nFor the longest time, iPhone apps needed to be “native” and downloaded from the App Store to utilize push notifications, but you will see that this is no longer true :)\n\nThis could be the thing that enables thousands of products to have native like presence, without the extra code, or having to deal with wrappers like Cordova. Apple is notorious for taking tech that has existed for years and propelling it into the mainstream  \n\nAs long-time HN users, we also included an option to subscribe to a feed of top Hacker News posts delivered via push to you every six hours. It makes it a fun little app instead of a boring demo!\n\nWorth noting that we don't track any personal info (random UUIDs for user IDs, so not even device IDs).\n\nWe’d love any feedback or shares. We also did a “Show HN” if you see us there!",
        "url": "https://www.ycombinator.com/launches/Iqb-webpushtest-com-ios-safari-web-push-notifications-demo-code",
        "votes": 11,
        "created_at": "2023-06-22T16:01:55.937Z"
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    "name": "Openlayer",
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        "full_name": "Gabriel Bayomi Tinoco Kalejaiye",
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        "full_name": "Vikas Nair",
        "title": "Founder",
        "founder_bio": "Co-founder of Openlayer (S21). Previously, built future AI/ML-powered experiences at Apple.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/vikasnair/",
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        "full_name": "Rishab Ramanathan",
        "title": "Founder",
        "founder_bio": "Co-Founder of Openlayer",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/rishramanathan",
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      {
        "title": "We’ve Raised Our Series A to Build the AI Reliability Platform",
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    "launches": [
      {
        "id": 80433,
        "title": "Openlayer - A Vercel-like workflow for AI evals that actually makes sense",
        "tagline": "Test, monitor, and optimize your AI with a single setup",
        "body": "**TL;DR** Openlayer provides a simpler workflow for AI evals and testing – connect your GitHub, define must-pass tests, and every commit triggers these tests automatically. Tests will also run on top of your live data and send alerts if they start failing. For AI developers, this is the ideal way to run continuous evaluations without much effort. Get started [here.](https://docs.openlayer.com/get-started)\n\n—\n\nHey guys! We’re Gabe, Rishab, and Vikas, the founders of Openlayer. We met at Apple, where we noticed that every AI/ML team inevitably ran into the same problem: their models would not perform as accurately as they thought they would in the real world. We left to solve this problem by building a best-in-class process for evaluating and improving models.\n\n![uploaded image](/media/?type=post&id=80433&key=user_uploads/236551/54d20552-4ea4-4ab2-8337-92046d1c89e5)\n\n🤯  **The problem** Most of us get how crucial AI evals are now. The thing is, almost all the eval platforms we’ve seen are clunky – there’s too much manual setup and adaptation needed, which breaks developers’ workflows.\n\n✅  **Solution** We’re releasing a radically simpler workflow.\n\nAll you need to do is connect your GitHub repo to Openlayer and define must-pass tests for your AI system. Once integrated, every commit triggers these tests automatically on Openlayer, ensuring continuous evaluation without extra effort.\n\nWe offer 100+ tests (and are always adding more), including custom tests. We’re language-agnostic, and you can customize the workflow using our CLI and REST API. We also offer template repositories around common use cases to get you started quickly.\n\nYou can leverage the same setup to monitor your live AI systems after you deploy them. It’s just a matter of setting some variables, and your Openlayer tests will run on top of your live data and send alerts if they start failing.\n\n![uploaded image](/media/?type=post&id=80433&key=user_uploads/236551/c4a17145-aa0e-455e-a04d-f0484803de6f)\n\n🙏  **Asks** We love feedback! [**Sign up for free,**](https://app.openlayer.com/) and let us know your thoughts! [Book a call](https://cal.com/vikasnair/30min?date=2024-04-16&month=2024-04&layout=mobile) with us for a demo, personalized onboarding, to give feedback, or just chat. Feel free to reach out to [founders@openlayer.com](mailto:founders@openlayer.com) for anything else.",
        "url": "https://www.ycombinator.com/launches/KvJ-openlayer-a-vercel-like-workflow-for-ai-evals-that-actually-makes-sense",
        "votes": 16,
        "created_at": "2024-04-25T20:13:41.755Z"
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    "year_founded": 2020,
    "city": "Washington",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/hotglue",
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        "full_name": "Hassan Syyid",
        "title": "Founder",
        "founder_bio": "Co-founder and CEO of hotglue",
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      {
        "title": "Y Combinator software startup raises $4M seed round",
        "url": "https://technical.ly/startups/y-combinator-startup-hotglue-dc-4-million-seed-round/",
        "date": "Oct 11, 2024"
      },
      {
        "title": "The Future 5 of D.C. Tech, Q1 2022",
        "url": "https://builtin.com/washington-dc/dc-future-5-startups-q1-2022",
        "date": "Mar 23, 2022"
      },
      {
        "title": "These are the 20 DC tech companies to watch in 2022",
        "url": "https://technical.ly/startups/dc-reallist-startups-2022/",
        "date": "Jan 25, 2022"
      },
      {
        "title": "Hotglue nabs $1.5M seed to help developers connect to biz apps – TechCrunch",
        "url": "https://techcrunch.com/2021/10/05/hotglue-nabs-1-5m-seed-to-help-developers-connect-to-biz-apps/",
        "date": "Oct 05, 2021"
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  {
    "id": 23948,
    "name": "Superwall",
    "slug": "staffbar",
    "former_names": [
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      "StaffBar"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e4505819ade5550ec16c605c15c7ccf142d096de.png",
    "website": "https://superwall.com",
    "all_locations": "New York City, NY, USA",
    "long_description": "Superwall is a complete, standalone subscription platform for consumer mobile and web apps — backend infrastructure (entitlements, purchase APIs with server-side receipt validation, standardized webhooks, real-time revenue analytics, direct SQL access to subscription data) together with a no-code paywall and experimentation engine, and first-class tooling for AI coding agents. Superwall manages $1.6B+ in annual subscription revenue across 10,000+ apps. The infrastructure layer is free at any scale; the only meter on the platform is revenue that converts through a Superwall-rendered paywall — subscriptions sold anywhere else are never billed.\r\n\r\n**Standalone backend:** The highest-revenue apps on Superwall like Cal AI — run their **entire subscription stack on Superwall alone: no second backend, no other subscription platform underneath**. Entitlement state is computed server-side from App Store Server Notifications V2 and Google Play Real-Time Developer Notifications, delivered by Apple and Google directly to Superwall. The largest single app runs **$43.7M ARR entirely on Superwall**; the top 10 together represent $134M+ in annual subscription revenue. Apps that previously ran a different subscription backend complete an automated migration — subscription history, entitlement state, webhook configuration — and run on Superwall alone from then on; imported subscribers are never billed.\r\n\r\n**Pricing:** The subscription infrastructure — entitlements, receipt validation, webhooks, analytics, SQL access — is free at any scale, with no revenue threshold and no per-event fees. The paywall product is free up to $10k/month in paywall-attributed revenue, then 1% of paywall-attributed revenue, and only that revenue: an app with $50k/month in subscriptions and no Superwall paywalls in use pays $0/month for the entire platform, and revenue the platform didn't help earn is never billed. Compared with charging a percentage of all subscription revenue, the difference is the base, not the rate.\r\n\r\n**Coverage:** Apple App Store, Google Play, and Stripe — including web checkout, external browser checkout from iOS paywalls (App2Web), and products from any external billing system via Custom Store Products. Monetization models: auto-renewing subscriptions, free trials and intro offers, one-time purchases, lifetime unlocks, and consumables. SDKs: iOS & Apple platforms, Android, React Native, Flutter, Expo, Unity, and Web — all open source on [GitHub](https://github.com/superwall). Not just for engineers: growth, product, support, and data teams run monetization from the dashboard, analytics, and SQL access day to day.\r\n\r\n**What Superwall does not do:** It does not process payments — Apple, Google, and Stripe do. It does not run virtual-currency or coin-ledger systems, does not track ad revenue, and does not support Amazon or Roku storefronts. For consumer subscription apps on iOS, Android, and the web, it covers the monetization surface end to end.\r\n\r\n**Experimentation:** Superwall's published research spans 100M+ analyzed paywall views and 4,500+ paywall A/B tests: multi-page onboarding paywalls convert 37% better than single-page (40M+ opens measured), Cal AI ran 123 experiments and grew monthly revenue 3x+ in 10 months, Planner 5D lifted revenue per user 83% through price testing. Build, target, test, and ship paywalls from the dashboard with no app release.\r\n\r\n**Retention:** Free trial reminders, cancellation and decline surveys, transaction-abandon recovery offers, win-back paywalls targeted by subscription state, Apple Retention Messaging on the iOS cancel screen, automated refund protection, and a per-customer timeline for support.\r\n\r\n**Agent tooling:** Open-source agent skills for Claude Code, Codex, and other coding agents; an editor MCP server for building live paywalls from the terminal; an embedded dashboard CLI; and direct SQL access to subscription data via the Query API.",
    "one_liner": "Subscription infrastructure & paywall experimentation for mobile apps",
    "team_size": 25,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1628553410,
    "tags": [
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      "Payments",
      "AI"
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2021",
    "status": "Active",
    "industries": [
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    "regions": [
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      "America / Canada",
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      "Partly Remote"
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    "stage": "Early",
    "app_video_public": false,
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/staffbar",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2021/staffbar.json",
    "year_founded": 2021,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/superwall/",
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    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/superwall",
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        "full_name": "Brian Anglin",
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        "founder_bio": "",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/anglinb/",
        "x_url": "https://twitter.com/BriansAngles",
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      {
        "user_id": 115099,
        "full_name": "Jake Mor",
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        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jake-mor-3b397392/",
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    "id": 23956,
    "name": "Customily",
    "slug": "customily",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c8057663fa98c67ad45f460aa90f60f3fb6495bb.png",
    "website": "http://www.customily.com/",
    "all_locations": "St. Louis, MO, USA; Remote",
    "long_description": "Customily is a design tool that makes it easy for e-commerce stores to sell personalized products. Online stores embed our tool in their site to let their customers design custom phone cases, t-shirts, mugs, and more.",
    "one_liner": "Making it easy to sell personalized products online.",
    "team_size": 30,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1627923969,
    "tags": [
      "SaaS",
      "B2B",
      "E-commerce"
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    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2021",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Fully Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/customily",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2021/customily.json",
    "year_founded": 2018,
    "city": "St. Louis",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/customily/",
    "x_url": "https://twitter.com/makeitcustomily",
    "fb_url": "https://www.facebook.com/makeitcustomily/",
    "cb_url": "https://www.crunchbase.com/organization/customily",
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/c8057663fa98c67ad45f460aa90f60f3fb6495bb.png",
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    "founders": [
      {
        "user_id": 131493,
        "full_name": "Martina Möring",
        "title": "Founder",
        "founder_bio": "Martina Möring is the Co-Founder of Customily, a design tool that makes it easy for e-commerce stores to sell personalized products. Originally from Uruguay, she moved to St. Louis in 2020. Martina has a background in architecture and design, and she previously co-founded Sur3D, focusing on 3D printing technology for product personalization. She has a dynamic and adventurous spirit, loves exploring new places with her family.\n",
        "is_active": true,
        "linkedin_url": "http://uy.linkedin.com/in/martinamoring",
        "x_url": "https://twitter.com/martumw",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/11286a9c68e3b49c8201a285c844fc73ca62b6f5.jpg"
      },
      {
        "user_id": 332618,
        "full_name": "Alejandro Lozdziejski",
        "title": "Founder",
        "founder_bio": "Creator of the first open-source 3D printer in Southamerica.\nMIT TR Innovator under 35",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/alelozd/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a39090617eb68543283d8330662acf50fe370dd9.jpg"
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    "id": 23958,
    "name": "Abstra",
    "slug": "abstra",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7fbfc5106c32c35b1a0242652667b0ea1ceb47b8.png",
    "website": "https://abstra.io",
    "all_locations": "São Paulo, SP, Brazil; Remote",
    "long_description": "Abstra is a platform that allows finance teams to build, run, and automate their workflows using Python and AI.\r\n\r\nInstead of relying on spreadsheets, ERPs, and manual processes, teams can create programmable workflows for tasks like reporting, reconciliations, approvals, and integrations with systems like SAP.\r\n\r\nWe provide a developer-friendly environment where finance and technical teams can turn business processes into code, connect to their existing tools, and run everything in a controlled, auditable way.\r\n\r\nOur goal is to become the operating system for finance operations, where workflows are not static or manual, but versioned, automated, and continuously improved.",
    "one_liner": "Automate finance operations with Python and AI",
    "team_size": 18,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1625673912,
    "tags": [
      "SaaS",
      "Finance",
      "B2B",
      "Automation",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2021",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "Brazil",
      "Latin America",
      "Remote",
      "Fully Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/abstra",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2021/abstra.json",
    "year_founded": 2020,
    "city": "São Paulo",
    "country": "BR",
    "linkedin_url": "https://www.linkedin.com/company/abstra-tech",
    "x_url": "https://twitter.com/abstra_cloud",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/abstra",
    "github_url": "https://github.com/abstra-app/",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/7fbfc5106c32c35b1a0242652667b0ea1ceb47b8.png",
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    "founders": [
      {
        "user_id": 512795,
        "full_name": "Bruno Vieira Costa",
        "title": "Founder",
        "founder_bio": "I'm Bruno, founder of Abstra. I'm a computer engineer and programmer since 7.\n\nPrevious Abstra, I co-founded an edtech called PaperX where I was CTO. I sold it during college to Descomplica (biggest edtech in Brazil) where I worked after as Product Manager and Tech Lead.\nAlso, I co-founded a Game Studio called Sinextra where I was Game Designer before college.\n\nI love all kind of creative activities, from making music, comics, games or software.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/brunovcosta/",
        "x_url": "https://twitter.com/bruno_vcosta",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5673d2e20e76c934bfd0bf0de872d9d527844c89.jpg"
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    ],
    "jobs": [],
    "news": [
      {
        "title": "Brazil’s Abstra lands Accenture as a customer and $2.3M to help teams make apps with its no-code tool – TechCrunch",
        "url": "https://techcrunch.com/2022/01/03/brazils-abstra-lands-accenture-as-a-customer-and-2-3m-to-help-teams-make-apps-with-its-no-code-tool/",
        "date": "Jan 03, 2022"
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    ],
    "launches": [
      {
        "id": 80549,
        "title": "Abstra: Scale critical business processes with Python + AI",
        "tagline": "Automate and manage operations with the power of code – without the overhead.",
        "body": "**TL;DR:** [Abstra](https://abstra.io/?ref=yc-launch) is a Python-based workflow engine to design and manage custom business processes with no overhead, powered by AI. Merge automated tasks with manual reviews, gain real-time insights into operations, and track history with git-compatible versioning & auditable logs.\n\n![uploaded image](/media/?type=post&id=80549&key=user_uploads/512795/6038e404-1f1f-4389-9d6c-304c36dadbfd)\n\n<https://www.youtube.com/watch?v=hUdQeX6dstY>\n\n\\\nThe Big Problem\n\nEvery company faces **growing pains** – new people must be **hired,** work needs to **scale**, more **compliance** regulations come knocking.\n\nSuddenly, building **better internal processes** becomes critical – think onboarding, CS or financial systems. Ideally they're fast to build, easy to manage and audit, and intuitive for everyone.\n\nHowever, the top of mind solutions have **tough trade-offs**.\n\n* Choose no-code for **speed**, but lose customization and **auditability** – and end up with un-debuggable mess of automations no one truly understands.\n* Opt to build in code for refinement, but sacrifice **months of expensive work** from engineers, who are focused on critical product tasks.\n\nAt this intersection of agility, power and governance, Abstra was born 🐣\n\n### Our Workflows\n\nWith Abstra Workflows, teams can spin up robust **business process automation in Python** as fast as they would with no-code, freeing up valuable time.\n\nDesign and **orchestrate** fully custom flows for solutions that fit **seamlessly** into your processes.\n\n![uploaded image](/media/?type=post&id=80549&key=user_uploads/512795/0507502c-c2b3-4721-adf5-e2c087e28ae7)\n\nAnd not only devs: with our AI features, **anyone with basic Python** skills can safely get **autonomy** from engineering teams. No technical overhead and countless **out-of-box benefits**, such as compliant logging, refined access control and custom notifications.\n\nSee beyond basic task automation to **tame** **critical** company **processes**, with **full visibility** into your challenges.\n\n![uploaded image](/media/?type=post&id=80549&key=user_uploads/512795/b13697ea-1739-47f5-9bc4-35c456e173e9)\n\n### How to get started\n\nIf you currently need to automate any company process and you tick one of these boxes:\n\n* You are struggling with no or low-code tools\n* You have critical scripts running locally in someone's machine\n* You need to give non-technical team members autonomy\n* You want visibility into how processes are being edited and executed\n* You are a Python fan\n\nAbstra was made for you. [Book a quick chat here](https://meet.abstra.app/sophia?url=yc-launch) – get 22% off if you sign up by May 8th.\n\nCheck out [abstra.io](http://abstra.io?ref=YC) for more!",
        "url": "https://www.ycombinator.com/launches/KxB-abstra-scale-critical-business-processes-with-python-ai",
        "votes": 121,
        "created_at": "2024-05-01T14:09:32.478Z"
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    "id": 23968,
    "name": "Archbee",
    "slug": "archbee",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2cf36cda1250013ea4989cc2ddc2f8e08f26a04d.png",
    "website": "https://www.archbee.com",
    "all_locations": "Bucharest, Bucharest, Romania; Remote",
    "long_description": "Build beautiful knowledge portals that are easy to navigate, search, share and contribute to.",
    "one_liner": "TURN STATIC DOCS INTO INSTANT ANSWERS",
    "team_size": 12,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1627303283,
    "tags": [
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      "B2B"
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    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2021",
    "status": "Active",
    "industries": [
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      "Engineering, Product and Design"
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    "regions": [
      "Romania",
      "Europe",
      "Remote",
      "Fully Remote"
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    "stage": "Early",
    "app_video_public": false,
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/archbee",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2021/archbee.json",
    "year_founded": 2019,
    "city": "Bucharest",
    "country": "RO",
    "linkedin_url": "https://www.linkedin.com/company/archbee",
    "x_url": "https://twitter.com/archbeehq",
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    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/2cf36cda1250013ea4989cc2ddc2f8e08f26a04d.png",
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    "founders": [
      {
        "user_id": 285367,
        "full_name": "Dragos Bulugean",
        "title": "Founder",
        "founder_bio": "Software Craftsman",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/dragos-bulugean/",
        "x_url": "https://twitter.com/happydragos",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a5a2d15bc404fc580526193f8e19007e1caa2dad.jpg"
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    "jobs": [],
    "news": [
      {
        "title": "Archbee raises $3M to rethink documentation",
        "url": "https://www.archbee.io/blog/we-raised-3m-to-rethink-documentation",
        "date": "Feb 16, 2022"
      }
    ],
    "launches": [
      {
        "id": 74656,
        "title": "Archbee AI: Answer user & dev questions instantly",
        "tagline": "Build beautiful documentation portals that answer questions with Gen AI",
        "body": "[Archbee (S21)](https://www.archbee.com?utm_campaign=launch-yc&utm_medium=referral&utm_source=launch-yc) helps your team build beautiful documentation portals that answer user & developer questions with Generative AI.\n\n**→ Who’s using it?**\n\nProduct & Engineering Teams at Adobe, Cisco, Bosch, Rackspace, and Lucas Film are using our software to power their docs portals — and here are some public portals examples:\n\n— Oxla, distributed database, <https://docs.oxla.com/>\n\n— Charthop, people operations platform, <https://docs.charthop.com/>\n\n— Drift, open-source decentralized exchange, <https://docs.drift.trade/>\n\n— Flipper Zero, hardware multi-use device, <https://docs.flipperzero.one/>\n\nOur latest release is filled with features powered by Generative AI / LLMs, and we focus on question-answering for your users & devs.\n\n**→ Answer user questions**\n\n![uploaded image](/media/?type=post&id=74656&key=user_uploads/285367/3ac5a3af-fb3d-44ac-8d06-ba6a6ed5d9a3)\n\nWouldn't it be cool for your documentation search function to give users an answer instead of a list of documents they need to drill into to find the answer?\n\nIt would save a lot of time and frustration... and we've built it!\n\nOn top of that, we enable you to analyze user question-and-answer sessions and adjust the documentation to provide LLMs with even better context for better answers.\n\n**→ Answer API questions**\n\n![uploaded image](/media/?type=post&id=74656&key=user_uploads/285367/4b39584d-38b1-4482-8256-e29d98a0b588)\n\nLLMs understand code SDKs and even OpenAPI spec files, so questions will get answered instantly for wandering developers trying to integrate your product. Never lose developers on complex integrations again!\n\n**→ Answer Billing questions**\n\n![uploaded image](/media/?type=post&id=74656&key=user_uploads/285367/2ddf7320-d250-4ec8-afab-f3d5574b96e6)\n\nMany questions like this would end up in your customer support channels. There is no need to when your users can receive instant answers.\n\n**→ Answer code questions**\n\n![uploaded image](/media/?type=post&id=74656&key=user_uploads/285367/2fb67a90-a8ba-4085-9bfa-d17f7358a398)\n\n**→ Write Assistance**\n\n![uploaded image](/media/?type=post&id=74656&key=user_uploads/285367/fa3c4c7b-2524-4d93-8cef-c8688de0e013)\n\nOf course, we couldn’t resist adding Generative AI to the writing process because nobody really loves to write docs.\n\n**→ Collaborate with your team**\n\n![uploaded image](/media/?type=post&id=74656&key=user_uploads/285367/284b0867-3989-48f4-bfe1-5a86da338b76)\n\n**→ Verify outdated content**\n\n![uploaded image](/media/?type=post&id=74656&key=user_uploads/285367/107f4189-747e-45ae-8f3e-f0c3ff37fbb5)\n\n**→ Custom Blocks for every use case**\n\n![uploaded image](/media/?type=post&id=74656&key=user_uploads/285367/9dfcf326-aa11-4498-bb34-e89a989f6fc8)\n\nWe strive to be **the best documentation portal platform that answers questions for your users & devs**.\n\n![uploaded image](/media/?type=post&id=74656&key=user_uploads/285367/dc56bed8-2a25-4f71-8ada-88e0d6559782)\n\n\\\n**→ Try Archbee AI here today:** [**https://www.archbee.com**](https://www.archbee.com?utm_campaign=launch-yc&utm_medium=referral&utm_source=launch-yc)",
        "url": "https://www.ycombinator.com/launches/JQ8-archbee-ai-answer-user-dev-questions-instantly",
        "votes": 35,
        "created_at": "2023-09-06T13:50:28.855Z"
      }
    ]
  },
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    "id": 23979,
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    "slug": "replo",
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    "website": "https://replo.app/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Agents that help you sell anything on the internet. Come build what the next million businesses launch on.\r\n\r\nTo date, we’ve raised over $8.2M from Figma, YCombinator, Vercel, General Catalyst, Infinity Ventures, MAGIC Fund, Base Case Capital.\r\n",
    "one_liner": "Sell anything",
    "team_size": 20,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1627581948,
    "tags": [
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      "Marketing",
      "AI"
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/replo",
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    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/replo-app",
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        "full_name": "Yuxin Zhu",
        "title": "Founder",
        "founder_bio": "Co-founder of Replo (YC S21). Previously EM @ Uber, UC Berkeley",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/yuxinzhu/",
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    "all_locations": "Philadelphia, PA, USA; New York, NY, USA; Remote",
    "long_description": "Buzzle help product marketing teams identify competitive moats and weaknesses, marketing teams generate & understanding voice of customer and product teams gauge demand in feature requests based on customer pain points, all automatically from a company’s library of recorded sales and success calls. Buzzle is founded by alumni from the University of Michigan. Adithya operated as the NLP modeling lead at Capital One's Center for Machine Learning. Michael was the lead developer of Capital One's privacy portal, serving millions of customers. Bhairav dropped out of his PhD at MIT to found Buzzle, after publishing research on deep learning and robotics at NVIDIA Research, NASA's Jet Propulsion Laboratory, and the Montreal Institute for Learning algorithms.\r\n\t\r\nBuzzle was formerly named q&ai!",
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    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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    "tags": [
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    "city": "Philadelphia",
    "country": "US",
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        "full_name": "Bhairav Mehta",
        "title": "Founder",
        "founder_bio": "CEO and co-founder at CharacterQuilt: Computer-use agents to deploy enterprise marketing campaigns\n\n2x YC Founder, MIT, Mila, NVIDIA",
        "is_active": false,
        "linkedin_url": "https://linkedin.com/in/bhairav-mehta",
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        "full_name": "Adithya Ramanathan",
        "title": "Founder",
        "founder_bio": "Former founder @ buzzle.ai!\n\nUsing NLP to give product teams insights from customer conversations.",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/adithyaramanathan/",
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        "title": "Founder",
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        "is_active": false,
        "linkedin_url": "http://www.linkedin.com/in/michaelbstaunton/",
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      {
        "id": 64895,
        "title": "Buzzle: Call Recordings → Voice of Customer insights",
        "tagline": "Transform individual customer conversations into aggregate customer strategy - automatically from recordings you already have!",
        "body": "### **TLDR:**\n\n[Buzzle](https://www.buzzle.ai/) listens to your call recordings so that you don’t have to (and because you don’t have the time to…). We help product marketing teams identify competitive moats and weaknesses, marketing teams generate & understanding voice of customer and product teams gauge demand in feature requests based on customer pain points, all automatically from a company’s library of recorded sales and success calls.\n\n### **The Problem:**\n\n⏰ ”I don’t have the time to listen to all of the call recordings sales generates, but I want to & I probably should”\n\n🧐 “How do I learn where to go next? What are customers complaining about? Our sellers don’t know what to share with us and how it connects to our roadmap.”\n\n📉 ”My buyers are spooked with the downturn, but I have no idea where to start looking to figure out what’s going wrong.”\n\nWhile call snippets and anecdotes from individual calls are perfect for deal review, building customer strategy requires you to take account of the entire voice of customer, which may potentially span thousands of individual conversations.\n\nStrategic teams — product, marketing, product marketing — care about the relationships among the discussions and ideas inside these individual calls. There is no way to generate this type of connecting insight without manually slogging through call recordings or interviews.\n\n### **The Buzzle Solution**\n\nCustomer conversations hold the lifeblood of companies, because they are a collection of **ideas** and **relationships** that matter to companies: between question and answer, objection and handler, and product functionality and pain point. Buzzle understands those relationships between and among conversations, and uses that knowledge to automatically detect and highlight the most important trends to product and marketing.\n\nBuzzle can help you hone in on anything from competitors to customer pain points, and help you understand when those topics are coming up in calls (and how they affect your deals)\n\n![](https://s3.us-west-2.amazonaws.com/secure.notion-static.com/8bfae907-f705-49c4-8775-c060c9ae07b6/Untitled.png?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIAT73L2G45EIPT3X45%2F20220802%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20220802T124123Z&X-Amz-Expires=86400&X-Amz-Signature=a174460eb9b0d641b08f269fa9d82367209a3c5a0b788929a2f722c4efbfd4f7&X-Amz-SignedHeaders=host&response-content-disposition=filename%20%3D%22Untitled.png%22&x-id=GetObject)\n\nUnsure of the latest trends? No worries. Buzzle understands the trends for you, and automatically surfaces the ones that you might be most interested in.\n\n![](https://s3.us-west-2.amazonaws.com/secure.notion-static.com/8593432d-20f6-46d4-8633-df5d8f014b83/Darkened_-_VOC_Animatin.gif?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIAT73L2G45EIPT3X45%2F20220802%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20220802T124135Z&X-Amz-Expires=86400&X-Amz-Signature=2e2927cb74d0033427ff0aed3628353dd03dee3e58466d18e518ed6fa8c64fe3&X-Amz-SignedHeaders=host&response-content-disposition=filename%20%3D%22Darkened%2520-%2520VOC%2520Animatin.gif%22&x-id=GetObject)\n\n### **Where do you come in?**\n\nHave call recordings you never look at? Always wanted your product & marketing teams to get insights from data sales & success are generating? Give us a shout at [founders@buzzle.ai](mailto:founders@buzzle.ai) and we’ll get your team set up with a free trial to uncover the insights locked away in the call data you already have.\n\nWe’d love to connect! Follow along with Buzzle by:\n\n1. Emailing us at: [founders@buzzle.ai](mailto:founders@buzzle.ai)\n2. Give us a follow on [LinkedIn](https://www.linkedin.com/company/buzzle-ai/)!\n3. Check out our [blog](https://www.buzzle.ai/blog)!",
        "url": "https://www.ycombinator.com/launches/Gsh-buzzle-call-recordings-voice-of-customer-insights",
        "votes": 24,
        "created_at": "2022-07-26T13:51:55.445Z"
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    "id": 24040,
    "name": "Affogato AI",
    "slug": "affogato-ai",
    "former_names": [
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      "Defy",
      "roverX",
      "RoverX",
      "RenderNet"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/be16f533fa3c585f372247f4f8cbf40d31f24c27.png",
    "website": "https://affogato.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Affogato AI is your all-in-one AI Video Agent, designed to help businesses, eCommerce sellers, agencies, and creators produce professional short-form videos instantly. From TikTok ads and Instagram Reels to YouTube Shorts, UGC content, and branded campaigns, Affogato makes high-quality video creation simple, fast, and scalable. No editing skills required — just type an idea and get campaign-ready videos that look studio-made, in minutes.",
    "one_liner": "Affogato AI — Your Agent for instant TikToks, Reels, and ads.",
    "team_size": 15,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1626192507,
    "tags": [
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      "AI"
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    "status": "Active",
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    "regions": [
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      "America / Canada"
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/affogato-ai",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2021/affogato-ai.json",
    "year_founded": 2019,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/aiaffogato",
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      "name": "Aaron Epstein",
      "url": "https://www.ycombinator.com/people/aaron-epstein"
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        "full_name": "Bhagaban Behera",
        "title": "Founder",
        "founder_bio": "A founder who lives for zero-to-one. A media junkie, gamer at heart, crypto-curious, and father of twins, he’s spent years building consumer startups — always with a marketing bent and a love for creating what captures culture.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/bhagaban/",
        "x_url": "https://twitter.com/bhoga",
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        "full_name": "Nakul Kelkar",
        "title": "Founder",
        "founder_bio": "Cofounder @ Affogato.ai\nLaunched multiple 0 to 1 products to hundreds of thousands of users. On a lookout for my next adventure",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/nakulkelkar/",
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        "id": 92745,
        "title": "Affogato Video Agent: Create Viral TikTok/IG videos with AI",
        "tagline": "Just describe your idea — Affogato Video Agent handles everything: script, voice, visuals, scenes, and edits. Create polished, TikTok-ready ads in minutes without touching a timeline.",
        "body": "[**Affogato Video Agent**](https://affogato.ai) **lets you create TikTok ads and short-form videos from just a prompt — no editing, no crew, no prior experience needed.**\n\nWe built this because making videos is still too slow and expensive — especially when you need fresh content every week. With Affogato, you just describe what you want (like “a talking ad for my skincare brand” or “a funny video about missing your morning coffee”), and the agent takes care of everything: script, visuals, voice, music, and timing.\n\nhttps://www.youtube.com/watch?v=rGv7R8YFCOk\n\nIt works great for TikTok, Instagram Reels, and YouTube Shorts — and we’re seeing early traction with e-commerce brands, content marketers, and solo creators using it to launch products, run ads, and grow their audience.\n\nHere’s what you can expect:\n\n* Type an idea → get a full video in minutes\n* Includes script, voiceover, visuals, music, and editing — auto-generated\n* Works for product showcases, character videos, UGC-style ads, and more\n* No timeline editing or video tools needed\n\n![uploaded image](/media/?type=post&id=92745&key=user_uploads/218500/50540ef3-5226-4b0b-bbad-f9ac430b7a51)\n\n( Prompt - Create a Pokemon themed ad for IKEA. The video agent does everything from creating scenes to adding music and voiceover. )\n\n1.5 million creators and businesses are already using Affogato to create marketing content at scale.\n\nIf you’re spending hours (or dollars) making videos, give Affogato a shot — it might save you both.\n\nTry Affogato at https://affogato.ai .\n\n---",
        "url": "https://www.ycombinator.com/launches/O7t-affogato-video-agent-create-viral-tiktok-ig-videos-with-ai",
        "votes": 33,
        "created_at": "2025-08-05T15:04:47.046Z"
      },
      {
        "id": 84871,
        "title": "Video Anyone: Bring your AI characters to life through AI videos",
        "tagline": "Create stunning videos with AI characters.",
        "body": "Whether you’re a marketer, educator, artist, or content creator, VideoAnyone allows you to transform AI characters and still images into captivating videos effortlessly.\n\n<https://youtu.be/DfoOF8CXagk>\n\nSimply upload your image and, optionally, write a prompt to guide the video, and watch as your visuals come alive with engaging animations. Perfect for storytelling, presentations, or enhancing your social media content, VideoAnyone turns your creative ideas into dynamic videos without the need for extensive video editing skills.\n\n![uploaded image](/media/?type=post&id=84871&key=user_uploads/218500/837b9374-7562-4fb1-8c0f-90866ebd7071)\n\n[Watch Output Video](https://youtube.com/shorts/RAoORua-vLY)\n\nCreating videos has never been easier! With VideoAnyone, you become the director of your own film. Just use simple prompts to craft your vision exactly as you want.\n\n**Effortless Camera Controls:** Manage camera movements with ease using intuitive prompt keywords like camera \"static,\" \"move left/right,\" \"push in,\" \"pull out,\" \"move up,\" and \"orbit left/right.\" And there’s a whole lot more to explore!\n\n![uploaded image](/media/?type=post&id=84871&key=user_uploads/218500/0afddb67-52f8-401a-9b78-0c7e2dc4ee50)\n\n[Watch Output Video](https://youtube.com/shorts/aXn95ncylV0)\n\n**Seamless Character Movements:** Easily define your character's actions in the prompt, with actions like \"a woman standing still,\" \"a man walking,\" \"a person riding a bicycle,\" and much more.\n\n![uploaded image](/media/?type=post&id=84871&key=user_uploads/218500/acd886fe-52b2-403b-8191-19a5624376ca)\n\n[Watch Output Video](https://youtube.com/shorts/TNXY9PJsXuM)\n\nElevate your content and connect with your audience like never before!\n\nCheck out some example videos created using RenderNet’s VideoAnyone.\n\n<https://youtu.be/jUwnHXruXHg>\n\n<https://youtu.be/iAQb6up-xbw>\n\n<https://youtu.be/R2eTX3zW-jQ>\n\nGet started with **Video Anyone** today at <https://rendernet.ai>",
        "url": "https://www.ycombinator.com/launches/M4t-video-anyone-bring-your-ai-characters-to-life-through-ai-videos",
        "votes": 24,
        "created_at": "2024-10-18T12:28:09.949Z"
      },
      {
        "id": 82755,
        "title": "Narrator: Narrate your story through AI lip-synced videos",
        "tagline": "Create engaging content with lip-synced videos of AI characters and AI voices. ",
        "body": "Transform your content with **Narrator**, [RenderNet.AI](http://RenderNet.AI)’s new feature for creating hyper-realistic lip-synced videos. Whether you're a podcaster, filmmaker, educator, or any other type of content creator, Narrator lets you produce engaging videos without appearing on camera.\n\nCraft your story using fictional characters for an unforgettable experience. Just upload a source video, choose a voice, and add a script.\n\n![uploaded image](/media/?type=post&id=82755&key=user_uploads/218500/c55d1dc1-5fd4-44f4-a334-6a7025316901)\n\nCheck out some example videos created using RenderNet’s narrator.\n\n<https://youtu.be/JrZYTdi-Kjo>\n\n<https://youtu.be/xPIbNwG7CIo>\n\n<https://youtu.be/pb7Bvh65N6U>\n\n<https://youtu.be/rWZI9ylQL3Y>\n\nGet started with Narrator today at <https://rendernet.ai>",
        "url": "https://www.ycombinator.com/launches/LWl-narrator-narrate-your-story-through-ai-lip-synced-videos",
        "votes": 35,
        "created_at": "2024-08-06T00:33:28.629Z"
      },
      {
        "id": 81703,
        "title": "TrueTouch: Add realism to your AI-generated images of humans",
        "tagline": "Say goodbye to 'fake-looking' AI images.",
        "body": "AI-generated images of humans are known to have a plastic feel and do not look real.\n\n**Truetouch** is a new **Image Upscaler** built by [RenderNet](https://rendernet.ai) that **adds realism** to images of humans created using AI.\n\n_Example 1_\n\n![uploaded image](/media/?type=post&id=81703&key=user_uploads/218500/f7de354e-567d-48ce-861b-32a3087398b2)\n\n_Example 2_\n\n![uploaded image](/media/?type=post&id=81703&key=user_uploads/218500/797b2684-fc05-415c-b060-802d1d1a7462)\n\nHow to use TrueTouch?\n\n<https://www.youtube.com/watch?v=YvC4MZpM4vA>\n\nRenderNet is an AI image generator with a focus on creating realistic and consistent images of  virtual human characters. Get started with free credits at https://rendernet.ai",
        "url": "https://www.ycombinator.com/launches/LFn-truetouch-add-realism-to-your-ai-generated-images-of-humans",
        "votes": 11,
        "created_at": "2024-06-24T14:09:29.656Z"
      },
      {
        "id": 81362,
        "title": "Character Labs: Create consistent virtual characters with AI",
        "tagline": "Keep face, hairstyle, skin, ethnicity of human characters consistent in AI images generation",
        "body": "Hi everyone!\n\nWe're excited to announce our second YC Launch! Previously, [we introduced Facelock](https://www.ycombinator.com/launches/Ka4-rendernet-ai-create-consistent-ai-characters), which ensures consistency in facial features when generating AI images of human characters.\n\nToday, we're thrilled to unveil our newest innovation: Character Labs. With Character Labs, you can maintain not only facial consistency but also hairstyles, skin tones, ethnicities, ages, and more. Plus, you can now assign a name to your character and generate images simply by referencing that name.\n\nCheck out some sample characters below -\n\n![uploaded image](/media/?type=post&id=81362&key=user_uploads/218500/3e71204a-aa52-4aaf-9c34-43b03a5fc765)\n\n![uploaded image](/media/?type=post&id=81362&key=user_uploads/218500/c6edc686-f6ea-4021-8d64-5259fd30f259)\n\n![uploaded image](/media/?type=post&id=81362&key=user_uploads/218500/74bcdcdd-9007-44c3-941b-fb4f3d9cfba5)\n\nUsing Character Labs is simple. Check out this short video.\n\n<https://www.youtube.com/watch?v=R26b-XZNECU>\n\nReady to experience hassle-free character creation? Try Character Lab today at [Rendernet.ai,](http://Rendernet.ai) and let us know what you think! We're eager to hear your feedback and continue improving our product to meet your needs.\n\n![uploaded image](/media/?type=post&id=81362&key=user_uploads/218500/438a7ae0-3ee8-457a-ab22-3c1b3da8e92f)\n\n",
        "url": "https://www.ycombinator.com/launches/LAI-character-labs-create-consistent-virtual-characters-with-ai",
        "votes": 19,
        "created_at": "2024-06-07T15:51:04.386Z"
      },
      {
        "id": 79116,
        "title": "RenderNet AI: Create consistent AI characters",
        "tagline": "RenderNet brings consistency and control over AI image generations. ",
        "body": "Hey everyone! We're [BB](https://www.linkedin.com/in/bhagaban/), [Nakul](https://twitter.com/MaruPelkar) & [Sriharsha](https://www.linkedin.com/in/sriharshasetty/). We’re building [RenderNet AI](https://rendernet.ai) - an AI image generation tool for visual storytelling.\n\n**Try RenderNet** - <https://rendernet.ai>\n\n![uploaded image](/media/?type=post&id=79116&key=user_uploads/218500/72d168cf-c52b-4ae9-8b2a-076a0c9ce251)\n\n### The problem\n\nAI image generation is a powerful storytelling tool for social media, marketing, education, and entertainment. Yet, a recurring challenge lies in _preserving continuity across a series of images._\n\nLet's say you _generate 5 images featuring the same fictional character_ - each one could render them with a completely different face, ethnicity, clothing, and overall appearance.\n\nThis _lack of consistency_ makes it extremely difficult to use those AI-generated images together cohesively for narratives, marketing campaigns, or any project requiring a unified character identity throughout.\n\n### The solution\n\n[RenderNet](https://rendernet.ai) is a new AI image generation tool with a focus on consistency and control via its features - _Facelock_ and _ControlNet_.\n\n**Facelock** enables a consistent face across all your creations. Whether you start with an AI-generated image or upload a photo, FaceLock maintains that face's integrity in every new image prompted. This ensures unparalleled continuity in your visual narratives.\n\n![uploaded image](/media/?type=post&id=79116&key=user_uploads/218500/fe70e107-5813-4708-bcd7-0c63766b0ef1)\n\n**ControlNet** lets you upload a reference image to guide the pose, composition, and style within your AI-generated visuals.\n\n![uploaded image](/media/?type=post&id=79116&key=user_uploads/218500/68211b19-352c-4315-9a7b-ba5b286e1967)\n\nCombining Facelock and ControlNet transforms your AI image generation process, offering unparalleled consistency and control. This dynamic duo ensures your characters remain true to your vision, from their facial features to their poses and styles.\n\nWhether you're crafting a comic series, designing an ebook, or creating a [virtual influencer](https://twitter.com/CharaspowerAI/status/1754183001066410266) akin to [Aitana Lopez](https://www.euronews.com/next/2024/01/20/meet-the-first-spanish-ai-model-earning-up-to-10000-per-month), Rendernet becomes an indispensable tool in your creative arsenal.\n\n![uploaded image](/media/?type=post&id=79116&key=user_uploads/218500/b5c5f33c-2306-4004-a95c-fe66a61f4462)\n\n**Our ask**\n\n* Try [https://rendernet.ai .](https://rendernet.ai) You get FREE credits on signup.  \n* Share the tool with your friends → [Here is a pre-drafted tweet](https://twitter.com/intent/tweet?text=Just%20discovered%20%40Rendernet_ai%20and%20I'm%20blown%20away!%20The%20level%20of%20character%20consistency%20is%20game-changing.%20Perfect%20for%20marketers%2C%20and%20creatives.).\n* Send us your feedback at [hello@rendernet.ai](mailto:hello@rendernet.ai)",
        "url": "https://www.ycombinator.com/launches/Ka4-rendernet-ai-create-consistent-ai-characters",
        "votes": 18,
        "created_at": "2024-03-06T16:43:40.315Z"
      }
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    "website": "https://echoeshq.com",
    "all_locations": "Amsterdam, NH, Netherlands; Remote",
    "long_description": "Echoes gives engineering leaders visibility into the alignment of engineering efforts against the business goals and whether their deliveries are having actual business impacts.\r\n\r\nBy doing so we enable engineering leaders to make informed decisions on hiring and priorities, to communicate effectively on their team's activity to their business partners/bosses/investors, and to build engagement by putting their team's work into context.\r\n\r\nWe achieve this by offering a seamless way for engineers to connect their day-to-day contributions to their intent, creating the missing link between tech outputs and business outcomes.",
    "one_liner": "Measure and communicate engineering activity",
    "team_size": 3,
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    "launched_at": 1624996289,
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    "year_founded": 2020,
    "city": "Amsterdam",
    "country": "NL",
    "linkedin_url": "https://www.linkedin.com/company/echoeshq/",
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    "github_url": "https://github.com/EchoesHQ",
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        "full_name": "Arnaud Porterie",
        "title": "Founder",
        "founder_bio": "🦋 ex Dep. CTO @ Veepee\n🐳 ex Sr. Engineering Manager @ Docker\n🇳🇱 Paris, SF, now Amsterdam\n📸 Photo enthusiast\n👌 It's pronounced Arno",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/aporterie",
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    "name": "MobileBoost",
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    "website": "https://www.mobileboost.io/yc",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "MobileBoost is an AI SDET for iOS and Android apps. An agent turns a plain-language test spec into test code, runs it on simulators and real devices, and fixes it when your app changes. Nobody on your team maintains test scripts by hand. The test code is accessible at any time if your team wants that level of access.\r\n\r\nYou can start runs from your CI pipeline with the MobileBoost GitHub Action, or let your coding agent start them over MCP while you build.\r\n\r\nMobile teams at Duolingo, Lyft, Wayfair, Flo Health, Noom, Compass, and Redfin use MobileBoost. Duolingo cut manual regression testing by 70%: https://blog.duolingo.com/reduced-regression-testing/",
    "one_liner": "AI SDET for mobile apps",
    "team_size": 15,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1628867687,
    "tags": [
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    "year_founded": 2019,
    "city": "San Francisco",
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      {
        "user_id": 375168,
        "full_name": "Christian Schiller",
        "title": "Founder",
        "founder_bio": "Christian led Product at HelloFresh (#1 meal kit service, symbol: HFG) for more than 4 years.\nBefore, he was an Entrepreneur in Residence at Rocket Internet, where he worked in Product roles with Westwing (symbol: WEW), Home24 (symbol: H24), and co-founded PricePanda in South East Asia (which was later merged with getprice.com.au).",
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      {
        "user_id": 367836,
        "full_name": "Christian Hartung",
        "title": "Founder",
        "founder_bio": "Christian previously founded VOJD, a Lakestar-backed consumer 3D printing venture featured in The New York Times and Wired, and partnered with super influencers such as Virgil Abloh.\n\nBefore that, he was an Entrepreneur in Residence at Rocket Internet, where he held sourcing and marketing roles with Global Fashion Group (symbol: GFG) and Payleven, which later merged with SumUp.",
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    "id": 24130,
    "name": "RGI Labs",
    "slug": "rgi-labs",
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      "PlusIdentity",
      "Vansec",
      "Aldermate",
      "VitalStrata",
      "Robust General Intelligence"
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    "website": "https://www.rgilabs.com",
    "all_locations": "New York City, NY, USA; Remote",
    "long_description": "RGI's mission is to build the world's first robust & recursively self-improving general intelligence. We're building the environment for intelligent systems to be able to develop in such a way where they can: \r\n- Recursively self-improve across all modifiable planes including architecture, parameters, scaffolding, etc. \r\n- Continually learn from online experiences and update its parameters while maintaining robustness against catastrophic failures. \r\n- Use its robust general intelligence of the world to acquire new skills in few or zero shots. \r\n- Use its world model to predict future states and plan via multi-step rollout. \r\n- Operate on a learned latent space that is compressed and feature-rich, including a robust latent space for reasoning.",
    "one_liner": "Robust & recursively self-improving general intelligence",
    "team_size": 1,
    "industry": "B2B",
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    "launched_at": 1628792922,
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    "year_founded": 2021,
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        "full_name": "Channy Hong",
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        "founder_bio": "- RGI Labs: https://www.rgilabs.com\n- CS @ Harvard",
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      {
        "id": 80676,
        "title": "Vansec - Spear phishing simulation & security awareness training, powered by AI",
        "tagline": "Multi-message phishing simulation & chat-based security training",
        "body": "**TL;DR**\n\n* Vansec’s spear phishing simulation is highly-personalized (using AI), multi-message (parse + generate emails using AI), and multi-modal (email, SMS, and more), to accurately reflect the current sophistication of phishing that bad actors employ (we have basic phishing simulations as well).\n* Vansec’s chat-based security awareness training is designed to be interactive (users will _actually_ learn) and bite-sized (< 5 mins).\n\n**Vansec’s multi-message spear phishing simulation (expanded thread **[**here**](https://www.vansec.com/media/temp/sim_full.png)**)**\n\n![uploaded image](/media/?type=post&id=80676&key=user_uploads/386068/dce3d55f-bfd8-4637-91c8-3556e3826144)\n\n**Vansec’s chat-based security awareness training (personalized to each employee’s simulation) (expanded conversation **[**here**](https://www.vansec.com/media/temp/debrief_full.png)**)**\n\n![uploaded image](/media/?type=post&id=80676&key=user_uploads/386068/fc97e518-4c5c-4c25-8894-967641397af3)\n\n**Security awareness training on a cybersecurity topic (expanded conversation **[**here**](https://www.vansec.com/media/temp/ransomware_full.png)**)**\n\n![uploaded image](/media/?type=post&id=80676&key=user_uploads/386068/ce7ea892-3fcc-4f74-bd3f-a23bf910b294)\n\n### **What is spear phishing simulation and why is it important?**\n\nSpear phishing is an advanced form of phishing, where the bad actor engages the victim in a very personalized & targeted manner, usually involving prior research on the victim (e.g. via LinkedIn) as well as various social engineering techniques to try to trick the victim.\n\nIt’s common knowledge that phishing is by far the most common way in which cyber attacks occur (over 90%, as of 2020), and 66% of phishing victims are victims of spear phishing attacks (as of 2023). With proliferation of generative AI and everyone being on LinkedIn, the phishing techniques that bad actors are using are growing both in sophistication and scale.\n\n### **Existing phishing simulations are ineffective**\n\nThe world of phishing simulation is dominated by legacy players like KnowBe4, and while their product is the standard of the industry, the product itself is very one-dimensional.\n\n**Problem 1**. Existing phishing simulations are too basic, where you send out one templated email and that’s it.\n\n**Problem 2**. Simulations are not highly-personalized, nor can you train your employees against dangerous social engineering techniques.\n\nThe reality is that this does not prepare your employees against the most dangerous type of phishing attacks: spear phishing. **Vansec’s spear phishing simulations are multi-message, hyper-personalized, and scenario-based where you can choose from common scenarios or customize your own (p.s. we also provide basic phishing simulation too).**\n\n### **Security awareness training is broken**\n\nEmployees playing training videos in the background/minimized while doing something else. This is what security awareness training looks like today.\n\n**Problem 1**. Obviously, this does not improve company’s actual security readiness.\n\n**Problem 2**. It’s a waste of time for the employee.\n\nThe optimal outcome here is for the training to be a) effective i.e. employees actually learn and become security-effective and b) time-efficient i.e. minimal disruption to their workflow.\n\nOur opinion is that learning should always be interactive, not passive. We also believe that getting pulled away from actual work to complete training is _always_ going to be annoying for the employee, no matter how you do it. **That’s why we designed Vansec’s security awareness training to be interactive & bite-sized (p.s. it’s also super personalized).**\n\n### **The ask**\n\n* Check out our [**interactive demo**](https://www.vansec.com/?demo_is_active=true#demo) and/or [**find a time**](https://calendly.com/vansec/vansec-discovery) to get started.\n* If you already have a phishing sim + training vendor but are interested in Vansec, please reach out and we can explore an option for you to use Vansec for free until your existing contract lapses.\n* If you are a security vendor looking for partnerships, let’s chat!",
        "url": "https://www.ycombinator.com/launches/KzE-vansec-spear-phishing-simulation-security-awareness-training-powered-by-ai",
        "votes": 16,
        "created_at": "2024-05-07T14:58:32.978Z"
      },
      {
        "id": 68603,
        "title": "PlusPassword - Share passwords without revealing them",
        "tagline": "No revealing in plaintext, no copying to clipboard",
        "body": "**tl;dr**: **PlusPassword** is:\n\n* A **free** tool ([**web app**](https://www.pluspassword.com) || Slack app & browser extension [download page](https://www.pluspassword.com/download)).\n* That allows you to **share passwords** with others **without revealing them in plaintext or copying to clipboard**\\*.\n\n…………………………………………………………………………………………………\n\n## **🫵 Do you…**\n\n* Share passwords with others (coworkers / 3rd party vendors) more than once a week?\n* And you know you shouldn’t be sharing them in plaintext over email / text / Slack...\n* But you do so anyways because there isn’t a better alternative?\n* Well, now there is!\n\n## **💡 How does PlusPassword work?**\n\n* **Sharing password**.\n\n  1\\. Set security options such as:\n  * Automatic logout after X hours.\n  * Restrict password paste to specific web domain.\n  * Email allowlist.\n\n  2\\. Generate access link.\n\n  3\\. Share link.\n* **Accessing password**.\n\n  1\\. Install browser extension.\n\n  2\\. Decrypt & paste password into password input field via browser extension. (Never revealed in plaintext or copied to clipboard.)\n\n![uploaded image](/media/?type=post&id=68603&key=user_uploads/386068/eeb51320-3f02-40ad-8f60-94a13fffa87f)\n\n## **🔐 Why should I trust PlusPassword?**\n\n* We take a lot of pride in our robust security design, but the reality is that nothing in this world is 100% failproof.\n* That's why we always encrypt your passwords (using industry standard cryptographic practices\\*\\*) and never store anything on our servers that can ever decrypt them (zero-knowledge).\n* Learn more in our [security page](https://www.pluspassword.com/security).\n\n## **🙏 The Ask**\n\n* Try sharing a password through [**PlusPassword**](https://www.pluspassword.com) (\\~30 seconds, free). We also have an awesome **Slack app** and **browser extension** ([download page](https://www.pluspassword.com/download), also free).\n\n\\\n\\\n\\* With enough malicious intent, one technically can see the plaintext of the password by inspecting the value attribute of the password input field or listening to the POST request when the form is submitted (although most websites only send the hash of the password over the wire). But the thing is, if someone has that much malicious intent to begin with (i.e. going out of their way to dig up the plaintext of the password), you probably shouldn't be sharing the password and giving this person access to your account anyways.\\\n\\*\\* We never store anything on our servers that can ever decrypt your encrypted passwords (zero-knowledge). We use PBKDF2 (with 101,004 iterations) for key derivation and AES-GCM for symmetric encryption, both utilizing the Web Crypto API. PlusPassword is developed adhering to the compliance requirements of SOC 2 (PlusIdentity is SOC 2 Type II compliant).",
        "url": "https://www.ycombinator.com/launches/HqV-pluspassword-share-passwords-without-revealing-them",
        "votes": 19,
        "created_at": "2023-01-22T17:16:06.420Z"
      }
    ]
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    "id": 24156,
    "name": "Lariat Data",
    "slug": "lariat-data",
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    "website": "https://www.lariatdata.com",
    "all_locations": "New York City, NY, USA",
    "long_description": "Lariat is a Continuous Data Quality monitoring platform to discover data bugs before your consumers do. Ensure data products don’t break even as business logic, input data and infrastructure change.\r\n\r\nUse Lariat to define and then automatically extract, store and visualize data quality metrics on raw event-level data through to delivered data products.\r\n",
    "one_liner": "Observability for Data Engineering Teams",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1626560864,
    "tags": [
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      "Data Engineering"
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    "status": "Inactive",
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    "year_founded": 2021,
    "city": "New York City",
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        "url": "https://www.ycombinator.com/companies/mach9/jobs/15HcGWq-business-development-representative",
        "location": "San Francisco",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$105 - $120",
        "equity_range": "",
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        "visa": "US citizen/visa only",
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    "news": [
      {
        "title": "Mach9 Unveils Digital Surveyor 2 A New Standard For Lidar Feature Extraction",
        "url": "https://informedinfrastructure.com/post/mach9-unveils-digital-surveyor-2-a-new-standard-for-lidar-feature-extraction",
        "date": "Mar 20, 2026"
      },
      {
        "title": "Between the Scanner and the Deliverable: How Mach9 is Building the Missing Layer in Geospatial Production",
        "url": "https://www.xyht.com/surveying/between-the-scanner-and-the-deliverable-how-mach9-is-building-the-missing-layer-in-geospatial-production/",
        "date": "Mar 19, 2026"
      },
      {
        "title": "Mach9 Unveils an AI-Assisted Workflow Focused on Trust and Control at Scale",
        "url": "https://www.geoweeknews.com/sponsored/mach9-unveils-an-ai-assisted-workflow-focused-on-trust-and-control-at-scale",
        "date": "Feb 10, 2026"
      },
      {
        "title": "Mach9 wants to create maps 30 times faster than previous standards | Geo Week News | Lidar, 3D, and more tools at the intersection of geospatial technology and the built world",
        "url": "https://www.geoweeknews.com/sponsored/mach9-digital-surveyor-lidar-data-feature-extraction-automation",
        "date": "Feb 06, 2024"
      },
      {
        "title": "Mach9 launches new geospatial software platform aimed at infrastructure space",
        "url": "https://www.geoweeknews.com/news/tech-reality-capture-mach9-launches-new-geospatial-software-platform-aimed-at-infrastructure-space?utm_source=social&utm_medium=linkedin&utm_campaign=5msocial",
        "date": "Mar 16, 2023"
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    "launches": [
      {
        "id": 99241,
        "title": "Mach9 - Make Maps Fast. AI-Powered CAD Software for Reality Capture",
        "tagline": "We help infrastructure survey and engineering teams turn raw point cloud data into engineering-ready CAD/GIS deliverables up to 100x faster.",
        "body": "Hi everyone! \n\nWe’re [Alex](https://www.linkedin.com/in/alexbaikovitz/), [Zach](https://www.linkedin.com/in/zachsussman/), [Haowen](https://www.linkedin.com/in/haowensh/), and [Michael ](https://www.linkedin.com/in/mmong/)- co-founders of [Mach9](https://mach9.ai/). \n\n**📍TLDR**: \n\nMach9's Digital Surveyor 2 is a geospatial platform that turns LiDAR point clouds into engineering-ready deliverables up to 100x faster. Its AI-powered extraction engine identifies and extracts linear features — including curbs, pavement edges, guardrails, and barriers — and learns from each user's edits to improve accuracy over time.\n\nSurvey and engineering teams at Langan, Olsson, HDR, Woolpert, Michael Baker International, and major utilities and state DOTs already use it in production.\n\nCheck out our Digital Surveyor 2 Launch Video:\n\n[**https://youtu.be/XoISK5nx87E?si=mzcrxg5uI3hynSm2**](https://youtu.be/XoISK5nx87E?si=mzcrxg5uI3hynSm2)\n\n**❌ The Problem**\n\nEvery road, bridge, fiber network, and utility corridor project starts with a survey. Increasingly, that survey is done with LiDAR scans encompassing millions of points.\n\n**But here's the thing**: Collecting data isn't the hard part anymore, turning it into engineering ready deliverables is. Today, that work is being done manually. Skilled technicians sit in front of a screen and trace features one by one across potentially thousands of features. Paint lines, curbs, poles, signs, guardrails. Mile after mile.\n\n**As a result**: Firms turn down work they could win, deadlines slip, and the most expensive bottleneck of the workflow is the part that hasn't changed in 20 years.\n\n**✅ Our Solution**\n\nDigital Surveyor 2 is a web-based CAD application where AI works alongside drafters to extract features from point cloud data dramatically faster — without sacrificing the precision their clients require.\n\nHere's what makes it different:\n\n🔹 **AI that drafts with you**. \n\nThe feature extraction engine in Digital Surveyor 2 suggests linear features, such as curbs, pavement edges, guardrails, and barriers directly from LiDAR point clouds — and adapts to the user’s drawing patterns. As users draw, the software picks up on their patterns and refines its suggestions in real time.\n\n![uploaded image](/media/?type=post&id=99241&key=user_uploads/311199/ca66f2e8-267b-4693-83ec-81b92eabb558)\n\n🔹 **Field-to-finish in one environment**. \n\nIngest point cloud data from any system such as RIEGL, Trimble, or Leica scanners. Extract features with AI-assisted workflows and precision tools. Easily QA everything in 3D. Export directly into AutoCAD, MicroStation, or ESRI. No switching between tools. No preprocessing pipeline.\n\n🔹 **Built for the people who do this work**. \n\nDS2 was designed so that a surveyor who knows where points go in the field can be productive on day one. Surveyors, field techs, and project managers can easily be working in it with minimal ramp time or CAD expertise.\n\n![uploaded image](/media/?type=post&id=99241&key=user_uploads/311199/e5e82676-f1fd-4bcd-bd86-fcca46636e29)\n\n🙏 **Our Ask**\n\n* **👉 Follow us** — Stay up to date with what we're building. Follow Mach9 on[ ](https://www.linkedin.com/company/mach9)[LinkedIn](https://www.linkedin.com/company/mach9geo).\n* **🔗 Intro us** — Know someone at a electric / telecom utility, data center owner, DOT, or survey/engineering firm that works with LiDAR or mobile mapping data? A warm intro goes a long way. We're especially looking to connect with survey and engineering leaders, mobile mapping teams, CAD/GIS technicians, and geospatial production leads.\n* **🚀 Try it yourself** — If your team is turning point clouds into deliverables today, we'd love to show you what DS2 can do. [Get started here](http://mach9.ai/get-started?utm_source=YC&utm_medium=article&utm_campaign=launch_post).\n* 💼 **We're hiring** — We're building engineering software to transform the $3 trillion global infrastructure industry. If you want to work on hard problems at the intersection of AI, geospatial, and computer graphics, we're scaling across GTM, engineering, and operations. Check out our open roles [here](https://jobs.ashbyhq.com/mach9).\n\n![uploaded image](/media/?type=post&id=99241&key=user_uploads/311199/d7592b72-f824-4cf8-9921-48b5b14674fc)\n\n",
        "url": "https://www.ycombinator.com/launches/Pof-mach9-make-maps-fast-ai-powered-cad-software-for-reality-capture",
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        "created_at": "2026-03-30T20:07:04.564Z"
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    "all_locations": "Dublin, County Dublin, Ireland",
    "long_description": "Give your Ops teams the power to build the tools your business needs, with native data, logic, automation, and AI — without code",
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        "title": "Senior Software Engineer",
        "url": "https://www.ycombinator.com/companies/noloco/jobs/M2m3UVI-senior-software-engineer",
        "location": "Barcelona, CT, ES / Barcelona, Catalonia, ES / Remote (Dublin, D, IE; Dublin, County Dublin, IE)",
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        "role": "Engineering",
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    "news": [
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        "title": "Noloco: Helping SMEs build internal apps without coding",
        "url": "https://www.siliconrepublic.com/start-ups/noloco-no-low-code-apps-startup-darragh-mc-kay",
        "date": "Jun 18, 2023"
      },
      {
        "title": "No-code platform Noloco raises $1.4m in seed funding",
        "url": "https://www.siliconrepublic.com/start-ups/noloco-funding",
        "date": "Jul 18, 2022"
      }
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    "launches": [
      {
        "id": 68486,
        "title": "Noloco - Build internal tools for your team without code",
        "tagline": "Build backoffice tools, CRUD apps and admin panels from your data in PostgreSQL, MySQL, Airtable & Google Sheets without writing a line of code.",
        "body": "### **TLDR**\n\nIt usually takes less than 20 minutes to build your first internal tool with Noloco, without writing a line of code. We’d love to help other startups improve their internal tooling while freeing up their developer resources. Try Noloco today and check out our YC Deal for the current batch and alumni.\n\n* [Sign up](https://portals.noloco.io/register?utm_source=yc&utm_medium=forum&utm_campaign=launch)\n* [YC Deal](https://bookface.ycombinator.com/deals/1610)\n* [Guides](https://guides.noloco.io/?utm_source=yc&utm_medium=forum&utm_campaign=launch)\n* [Video Tutorials](https://noloco.io/video-tutorials?utm_source=yc&utm_medium=forum&utm_campaign=launch)\n\n![uploaded image](/media/?type=post&id=68486&key=user_uploads/567509/236105a3-2bbd-4c56-be5a-5d37f5edd08e)\n\n### **🤔 What’s the problem?**\n\nMany of us have experienced the pains of internal tooling in startups and scale-ups. From a management point of view, engineering resources dedicated to internal tooling are wasted as they should be focusing on customer-facing products. For developers, it’s a chore to work on unloved parts of the codebase that aren’t a priority for the business. And for other stakeholders in Product, Ops and Support, there’s never enough capacity to build the tools they desperately need, while the ones they have are slow, cluttered and the UX is often poor. \n\n### **🙌 How does Noloco help?**\n\n[Noloco](https://noloco.io?utm_source=bookface&utm_medium=forum&utm_campaign=postgres) is the no-code platform for teams to instantly create internal tools from databases like PostgreSQL, MySQL, Airtable & Google Sheets.\n\nOnce you connect your data source (e.g. PostgreSQL), Noloco automatically builds an app for you from your chosen tables including collection views (e.g. tables and kanban boards), record pages to view individual records and forms to add new records.\n\nNoloco provides a totally no-code builder. This genuinely makes building and configuring internal tools 10x faster. With our no-code first approach, Noloco also removes the reliance on engineers whenever your Ops, Customer Support, Product or Sales team want to make any changes or add new tools.\n\n![uploaded image](/media/?type=post&id=68486&key=user_uploads/567509/8fb689b6-3b51-4d51-8691-67e67803b002)\n\n### **🛠️ What can I build with Noloco?**\n\nCustomers around the world have built hundreds of internal tools with Noloco for a variety of use cases, including:\n\n* Internal tool for your customer support team to update customer plans\n* CRM to keep customer info up to date and trigger automated workflows\n* Dashboards to monitor product usage, sign-ups and converted customers\n* Project management tool for your Ops team \n\n### **⏰ Build your first internal tool in 20 minutes**\n\nMost customers find that they can build a functional, useful tool for their teammates to view or update data in their database within 20 minutes. This is because Noloco does so much of the work for you in building the basic structure and pages of your app. \n\nIf you’d like to try building internal tools for your team without writing a line of code, you can [sign up here](https://portals.noloco.io/register?utm_source=yc&utm_medium=forum&utm_campaign=launch).\n\nWe also have lots of useful resources to help you:\n\n* [Guides](https://guides.noloco.io/?utm_source=yc&utm_medium=forum&utm_campaign=launch)\n* [Video Tutorials](https://noloco.io/video-tutorials?utm_source=yc&utm_medium=forum&utm_campaign=launch) \n\n### **💸 YC Deal**\n\nWe’ve published our first YC Deal - see [redemption instructions](https://bookface.ycombinator.com/deals/1610) here.\n\nCurrent batch:\n\n* Free during the batch\n* 50% off all paid plans for your first 6 months after the batch\n\nAlumni:\n\n* 50% off all paid plans for your first 6 months \n\n### **🙏 Asks**\n\n[Sign up](https://portals.noloco.io/register?utm_source=yc&utm_medium=forum&utm_campaign=launch) and see how quickly you can build internal tools for your team with Noloco.",
        "url": "https://www.ycombinator.com/launches/Hoc-noloco-build-internal-tools-for-your-team-without-code",
        "votes": 14,
        "created_at": "2023-01-17T13:35:13.594Z"
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    "name": "Dime",
    "slug": "dime",
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    "website": "https://www.dime.io/",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "As developers, we’re constantly going through the cycle of starting to write tests, deciding we can’t prioritize them because we need to ship new features, and then running into bugs in production as a result. Autotest lets you build comprehensive integration tests for your website with basically no work on your part, so you get the benefits of testing without wasting dev time on it.",
    "one_liner": "Instant E2E tests for your website",
    "team_size": 2,
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    "subindustry": "B2B -> Engineering, Product and Design",
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    "all_locations": "London, England, United Kingdom",
    "long_description": "As AI agents become more capable at writing code, developers are spending more of their time planning and reviewing what those agents produce. Vibe Kanban helps them do exactly that, seamlessly integrating with leading coding agents like Anthropic’s Claude Code and OpenAI’s Codex.",
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      {
        "id": 92068,
        "title": "Vibe Kanban - 10X your Claude Code usage",
        "tagline": "Run coding agents in parallel, streamline review and planning",
        "body": "![uploaded image](/media/?type=post&id=92068&key=user_uploads/63418/85136151-1f80-4ccc-9487-61f9f5883df0)\n\nHi 👋 We’re Louis and Gabriel, the founders of Vibe Kanban.\n\nRecently, we reached an exciting milestone: **over 50% of our code is now written by coding agents** like Claude Code, Gemini CLI, Codex, and Amp.\n\nThis means that our roles have evolved. Instead of spending most of our time writing code ourselves, **we now primarily plan, review, and orchestrate** the efforts of these AI agents.\n\nPreviously, our bottleneck to shipping was the speed of writing code. Today, it’s how quickly we humans can effectively plan, review and keep on top of the work produced by AI. **Time spent watching coding agents working is time wasted.**\n\nhttps://youtu.be/TFT3KnZOOAk\n\n**With Vibe Kanban you can:**\n\n1. Easily switch between different coding agents\n2. Orchestrate the execution of multiple coding agents in parallel or in sequence\n3. Quickly review work and start dev servers\n4. Track the status of tasks that your coding agents are working on\n5. Centralise configuration of coding agent MCP configs\n\n**To launch Vibe Kanban:**\n\n```\n# Make sure you've already authenticated with Claude Code, Gemini CLI, Codex or Amp, then run:\n\nnpx vibe-kanban\n```\n\nYou can also read the docs at [vibekanban.com](https://vibekanban.com)\n\n**Our ask:**\n\nIf you use coding agents, please try starting your next task with Vibe Kanban. If you reach out to [Louis on X](https://x.com/LouisKnightWebb) with bugs and suggestions, I'll get Claude Code to work on your feedback ASAP.",
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        "votes": 27,
        "created_at": "2025-07-11T15:13:20.819Z"
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    "id": 24700,
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        "body": "### **What is Codex?**\n\n* [Website:](https://usecodex.com/) <https://usecodex.com>\n* [Extension: VS Code Marketplace](https://marketplace.visualstudio.com/items?itemName=CodexBuild.codex-build)\n* [Demo Video: Codex in a Nutshell](https://www.loom.com/share/5afda7be38aa459186cca73ed6b3738f)\n\nCodex is a VS Code extension that allows any engineer to attach comments, questions, notes or any kind of content to specific lines of code. This context follows your code as your team continues to build. Help your team understand your code base at a deeper level.\n\n### **Why us?**\n\n Karl Clement, Saumil Patel and Brandon Waselnuk have been working together for 8 years now shipping over 50 products across the VC fund they worked at, their own agency, and their own projects. They’ve seen this problem constantly and decided to do something about it.\n\n### **The problem:**\n\nThe problem space we’re working on is collaborating on code, passive documentation through code block level context, onboarding and offboarding engineers into a code base. We found this problem on pretty much every software team we’ve worked on - you open a file and don’t know how something runs and have to start asking in #devops chats which leads you on a goose chase to find the engineer that remembers how the monolith runs. It stinks, and when you’re done you move on and finish your work, you don’t really capture everything you learned in DMs and leave it for other team members to learn from.\n\n### **The solution:**\n\nWe’ve created an extension for VS Code to allow any engineer to attach their internal knowledge to specific files or lines of code and share it with the rest of the team.\n\n* Onboard or offboard engineers from your code base 10x faster.\n* Take notes while you code and help your team understand how it was built.\n* Ask the right person a question, without disturbing their flow.\n* Share a direct link to a code block in VS Code instead of sending screenshots.\n\n![uploaded image](/media/?type=post&id=64458&key=user_uploads/24543/e35a2b90-27fa-4279-97e9-24081fb02d92)\n\n### **How you can help:**\n\nYour support means the world to us. Here are some things we’d love:\n\n* Introductions to remote or hybrid engineering teams\n* Shoutouts on Twitter, Tiktok or whatever is cool these days.\n* Use [Codex](https://usecodex.com/?ref=launch-yc) today! We can use all the feedback we can get :)\n\nTHANK YOU!",
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        "tagline": "AI-powered scraping automations that evolve with the sites you target. Get the data you need with just a URL and a prompt.",
        "body": "![uploaded image](/media/?type=post&id=81738&key=user_uploads/3186/9e3e30fb-3ddb-47e7-aabf-860697f5ffb5)\n\n**TL;DR**\n\nBytebot uses AI to handle web data extraction and form filling. Developers use us to save time and effort, writing robust web scraping and automation logic that is reusable across many websites. Get started [here](http://app.bytebot.ai/auth/sign-up), and book some time with us [here](https://calendly.com/bytebot/bytebot-overview?back=1&month=2024-03).\n\n**❌ The Problem**\n\nBrowser scraping and web automation can be incredibly time-consuming and complex, often requiring a detailed and deep understanding of the web elements involved. Traditional methods are slow to iterate and can be difficult to scale, especially for startups and large companies.\n\nToday, you might:\n\n* Spend hours building scripts, hunting through HTML for the right selectors/xpaths\n* Waste effort debugging and maintaining scripts that break after page layout changes\n* Struggle with captchas, IP address rotation\n\n**💫 The Solution**\n\nBytebot simplifies and streamlines browser automation by translating your natural language prompts into intricate web tasks, from data extracting to website monitoring to form filling.\n\nBenefits include: \n\n* Eliminating time spent hunting for selectors or xpaths, as you can just prompt what you would like to happen instead\n* Allowing you to design scripts with  prompts that are reusable across multiple websites or domains\n* Providing robust and self-healing scripts that can adapt to website layout changes or updates\n\n![uploaded image](/media/?type=post&id=81738&key=user_uploads/3186/cb84607a-1f46-48f4-ad7b-c1c5f61dda6d)\n\n**⚒️How It Works**\n\nBytebot lets developers focus more on the prompting and less on the maintenance. Instead of writing complex scripts, you simply describe what you want to do, like _\"Add the item to the shopping cart\"_ or “_Login in with these credentials_“ and Bytebot handles the rest.\n\n![uploaded image](/media/?type=post&id=81738&key=user_uploads/3186/5317da8e-9760-4477-9a23-45ea0db84bc8)\n\nBehind the scenes, Bytebot takes a snapshot of a given webpage and leverages LLMs to translate prompts into the appropriate browser actions.\n\n![uploaded image](/media/?type=post&id=81738&key=user_uploads/3186/27874219-8f4a-4fcd-8480-21d039d83be6)\n\n**Speeding Up Automations**\n\nBytebot significantly speeds up the development cycle. Faster iterations enable companies to test and experiment with workflows without lengthy setup times. This increase in efficiency leads to higher ROI, as teams can focus on high-impact projects instead of getting bogged down by repetitive tasks.\n\n<https://youtu.be/v2e3Z3suQTs>\n\n**Versatile for All Users**\n\n Bytebot is designed for users of all technical levels:\n\n* **For Companies with Existing Infrastructure:** If your company already has a mature Puppeteer or Playwright setup, Bytebot integrates seamlessly. You can quickly hook Bytebot into your existing scripts without overhauling your current system.\n* **For Companies Needing Browser Support:** If you don't want to manage browser infrastructure, our Hosted Browser API has you covered. We'll handle running the browser, and you can interact with Bytebot without worrying about captchas and IP address rotation.\n*  **For Non-Technical Users:** For the quickest setup and experimentation, our Playground (coming soon!) offers a no-code UI, with a live browser view.\n\n**🙏Our Asks**\n\n* [Sign up](http://app.bytebot.ai/auth/sign-up) to try Bytebot! Our tiered [pricing](https://www.bytebot.ai/#pricing) has options for individual engineers and companies of all sizes.\n* Follow Us on [LinkedIn](https://www.linkedin.com/company/bytebot-ai) and [Twitter](https://twitter.com/bytebot_ai) for new features, updates, and industry insights.\n* Share Bytebot with anyone who is looking to streamline their web automation.\n* If you have a few minutes to chat about Bytebot, book a time [here](https://calendly.com/bytebot/bytebot-overview?back=1&month=2024-03).",
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        "body": "### **TL;DR: Hyperbeam lets you embed any third-party website or application, synchronize audio and video flawlessly among multiple participants, and add multi-user control with just a few lines of code.**\n\nHey YC [👋](https://emojipedia.org/waving-hand/#:\\~:text=A%20hand%20waving%20most%20commonly,to%20Emoji%201.0%20in%202015.)\n\nWe’re Philip, Amby, and Declan, and we’re building [Hyperbeam](https://hyperbeam.com/?ch=yc&cm=lyc1) 👾\n\n### [🤔](https://emojipedia.org/thinking-face/) **The Problem**\n\nEmbedding third-party apps and websites can often be a nightmare due to incompatible platforms, security issues, and poor UX. Adding multiplayer functionality to these embeds makes this problem exponentially more difficult. This is an issue that countless remote learning, productivity, online social, and metaverse platforms face when building their products.\n\n### [💡](https://emojipedia.org/light-bulb/) **Our Solution**\n\nEnter Hyperbeam—an API that lets you embed virtual computers anywhere, including web, mobile, VR, and even VSCode. You can then open any third-party website or application, synchronize audio and video flawlessly among multiple participants, and add multi-user control with just a few lines of code.\n\n![uploaded image](/media/?type=post&id=65609&key=user_uploads/858376/f7507431-2db0-45e9-bcf7-5bbde27ebb1a)\n\n### [⚙️](https://emojipedia.org/gear/) **How it Works**\n\n1. [Sign up](https://hyperbeam.com/?ch=yc&cm=lyc1) on the Hyperbeam Dashboard\n2. Generate an API key and integrate the Hyperbeam API\n3. Customize the UX to your use case (e.g. control permissions, FPS, permitted websites, WebGL)\n4. Launch and track your user engagement!\n\nOn the backend, we’re spinning up a VM and running a resource-optimized fork of Chromium which we then stream to participants via WebRTC. Since we’re hosting the servers running the applications, multiple users can connect and control the virtual computer seamlessly, and their client just needs to handle a video stream.\n\n### **🙏 Asks**\n\nIf you or someone you know is building a…\n\n* [🎓](https://emojipedia.org/graduation-cap/) Remote learning platform\n* [🏢](https://emojipedia.org/office-building/) Virtual office\n* [💻](https://emojipedia.org/laptop/) Remote productivity tool\n* 👾 Metaverse\n* [🏟️](https://emojipedia.org/stadium/) Virtual conferencing app\n* [🥽](https://emojipedia.org/goggles/) VR app\n\n…we’d love to talk!\n\n**Join us on** [**Discord**](https://discord.gg/D78RsGfQjq)**,** [**book a meeting**](https://meetings.hubspot.com/hyperbeam/founders) **with the founders, or** [**sign up**](https://hyperbeam.com?ch=yc&cm=lyc1) **for a free API key. Thanks!**",
        "url": "https://www.ycombinator.com/launches/H4D-hyperbeam-embed-third-party-apps-games-and-websites-anywhere",
        "votes": 491,
        "created_at": "2022-08-24T23:44:03.310Z"
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        "url": "https://www.ycombinator.com/companies/mintlify/jobs/ADu1QAT-product-engineer",
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        "url": "https://www.ycombinator.com/companies/mintlify/jobs/3CZkjid-devrel",
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        "id": 112531,
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        "url": "https://www.ycombinator.com/companies/mintlify/jobs/wkrPOph-senior-backend-engineer",
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        "id": 112533,
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        "url": "https://www.ycombinator.com/companies/mintlify/jobs/pCsIL9J-senior-platform-engineer",
        "location": "San Francisco",
        "type": "Full-time",
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        "skills": []
      },
      {
        "id": 112536,
        "title": "Generalist Marketer",
        "url": "https://www.ycombinator.com/companies/mintlify/jobs/l0rwTQz-generalist-marketer",
        "location": "San Francisco",
        "type": "Full-time",
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        "role_type": null,
        "salary_range": "$100K - $200K",
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    "news": [
      {
        "title": "Anthropic Uses This Startup’s AI To Answer People’s Questions About Claude Code",
        "url": "https://www.forbes.com/sites/the-prompt/2026/04/14/anthropic-uses-this-startups-ai-to-answer-peoples-questions-about-claude-code/",
        "date": "Apr 14, 2026"
      },
      {
        "title": "Mintlify is building a next-gen platform for writing software docs | TechCrunch",
        "url": "https://techcrunch.com/2024/09/05/mintlify-is-building-a-next-gen-platform-for-writing-software-docs/",
        "date": "Sep 05, 2024"
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        "date": "May 30, 2022"
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        "title": "14 notable AI startups from YC's Winter '22 batch",
        "url": "https://techcrunch.com/2022/03/30/selected-ai-startups-from-ycs-winter-22-batch/",
        "date": "Mar 30, 2022"
      },
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        "title": "Mintlify 🌿 Beautiful documentation that converts users",
        "tagline": "Beautiful out of the box, easy to maintain, and optimized for user engagement.",
        "body": "**TL;DR**: [Mintlify](https://www.mintlify.com/) makes building world-class documentation easy. Check out some of the awesome YC companies that we work with at our [showcase](https://www.mintlify.com/showcase).\n\n![uploaded image](/media/?type=post&id=67485&key=user_uploads/434864/5c37ed78-4cd3-4096-b168-610f0e5361ea)\n\n### **The problem**\n\nWriting documentation is hard. Building and maintaining the platform to host it is even harder.\n\n### **How Mintlify can help**\n\nWe want to help you build the documentation you've always wanted.\n\n**💻 Developer-first** - content is written in markdown and lightning fast to set up. We believe in being opinionated when you’re lazy but infinitely flexible when you need it to be.\n\n🚀 **Built for results** - our users see an average of 40% higher conversion, better SEO, and performance than other documentation alternatives\n\n**🔎 Understand readers** - we built insights into the platform to help you understand your users and other metrics tracked by world-class documentation providers like Stripe.\n\n### **Our ask**\n\n[Sign up](https://mintlify.com/start) and get instant access",
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    "long_description": "We rewrite and optimise your internal documentation for AI, giving it deep enterprise context. This unlocks substantially better LLM results across all AI workflows.\r\n\r\nPROBLEM:\r\n--------------\r\n• AI teams struggle with LLM accuracy building AI workflows and agents because of messy, conflicting, fragmented internal knowledge.\r\n• Internal knowledge conflicts, uses undefined jargon and rely on unstated company assumptions & context.\r\n• LLMs are like Day 0 fresh hires – they can’t understand this documentation properly without someone explaining context to them.\r\n• Furthermore, vector search suffers from poorer retrieval accuracy when company context and terms are not present in a knowledge article\r\n\r\nWHAT WE DO\r\n-------------------\r\n• Clean & De-Conflict: Our AI agents read every doc, resolve contradictions, and builds content relationships.\r\n\r\n• Context Distillation: Our AI agents read & compare related docs, distills context and rewrites an LLM-optimised version of your internal documentation. Optional human-approval ensures 100% confidence in the output.\r\n\r\nTHE OUTCOME\r\n----------------------\r\n• Agents and chatbots that actually understand your enterprise context.\r\n• Retrieval that delivers precise, policy-aligned answers on the first try.\r\n• A living knowledge base that stays synchronized with every new doc revision.\r\n",
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        "full_name": "Sagar Soni",
        "title": "Founder",
        "founder_bio": "Co-Founder, CTO @ Requestly",
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        "linkedin_url": "https://www.linkedin.com/in/mesagarsoni/",
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        "title": "Requestly joins BrowserStack to build the future of application testing",
        "url": "https://requestly.com/blog/requestly-joins-browserstack-building-the-future-of-testing-together/",
        "date": "May 06, 2025"
      },
      {
        "title": "Meet The 7 Indian Startups That Are Part Of Sequoia Surge’s Eight Cohort",
        "url": "https://inc42.com/buzz/sequoia-surges-eighth-cohort-packs-9-indian-startups-out-of-12/",
        "date": "Mar 01, 2023"
      },
      {
        "title": " Sequoia’s Surge selects 12 startups for its eighth cohort",
        "url": "https://entrackr.com/2023/03/sequoias-surge-selects-12-startups-for-its-eighth-cohort/",
        "date": "Feb 28, 2023"
      },
      {
        "title": "AWS Nexus DevOps Innovation Day: Diving into the latest developments in DevOps\n | YourStory",
        "url": "https://yourstory.com/2022/06/aws-nexus-devops-innovation-day-diving-towards-latest-developments-in-devops",
        "date": "Jun 10, 2022"
      },
      {
        "title": "Meet the Indian startups in Y Combinator’s Winter 2022 cohort | YourStory",
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        "id": 85821,
        "title": "Requestly - Open-Source API Mocking & Testing Tool for Developers 🚀",
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        "body": "Hey founders! Sachin here.\n\nWhat I started with a simple Chrome extension to solve one simple use case has evolved into a complete API Testing & Mocking platform - now used by more than half of Fortune 500 companies.\n\n**TL;DR:** Requestly helps developers build faster by intercepting, mocking, and testing API responses. No more waiting for backend developers, struggling with flaky staging environments, or fighting over API contracts. With 200,000+ active installs, Requestly is trusted by Google, Amazon, Workday, Indeed, and many other Fortune 500 companies.\n\n[Demo Video](https://www.youtube.com/watch?v=w5lCzZRmnZ0):\n\n**The Problem**\n\nFrontend developers face two common problems during their local development: Dependency on backend developers (i.e. Waiting for APIs) and Unstable backend services.\n\nWhether it's:\n\n* The backend team still building the endpoint\n* API not returning the data required for the development\n* Flaky Staging/Backend servers being used for local development\n* Need to modify API responses for testing error paths in frontend codebase\n\nThis leads to delayed releases, blocked sprints, and frustrated developer experience.\n\n**Enter Requestly**\n\nRequestly lets you intercept, mock, and test API responses in browsers and mobile apps.\n\nCore Features:\n\n* **Mocking API Responses:** Instantly mock any API response without touching the backend or your frontend code.\n* **Testing API Responses:** Quickly Test API responses with a sweet, simple API client.\n* **Mocking a Complete Flow:** You can either create API mocks for selective requests or record a user flow and create mocks for the entire flow.\n* **Collaboration using Team Workspace:** Save and reuse common API mocks across your teams with collaboration enabled in real-time.\n\n**Why people love it**\n\n**Frontend Teams:** Build features without waiting for backend APIs or dealing with staging server issues.\n\n**QA Teams:** Test edge cases in APIs and UI for error scenarios easily\n\n**Backend Teams:** Build, Design, Test and Collaboration on APIs\n\n**Enterprise Ready:** Used by over half of Fortune 500 companies including Google, Workday, Indeed, CapitalOne, MasterCard, and AutoDesk\n\n**Other Common Use-Cases**\n\n**1. Overriding JS Bundles** While talking to the enterprise users, we discovered that Overriding JS bundles from production to local/staging environments is one of the major use cases. They do this to test their local code changes directly on the production website by overriding the JS assets.\n\n**2. API Testing** We ended up building a sweet, simple API client for our customers for basic API testing, and now this has become a core feature of our product. We already offer capabilities like Collections, Environments, Workspaces, and Collaboration.\n\n**Testimonial**\n\n\"Requestly is an incredibly useful tool for developers working on a large team with multiple staging envs, or numerous app endpoints for various APIs in a local environment. Requestly combines all the power of complicated tools like Charles Proxy and Postman. I highly recommend giving it a try if you haven't already–it will make your dev work so much easier.\"\n\n— Joél, Senior Software Engineer at Autodesk\n\n**What we are planning next**\n\n* Building better API mocking capabilities for Android/iOS devices & simulators. We have already migrated some companies from Charles Proxy & Postman to Requestly and it has worked well.\n* Building more API testing features like Collection Runners, Scripting, and API test cases.\n* Learn how to market well. So far all of our growth has been organic. We did try some activities in the past but we weren't consistent.\n* Improve our customer success. We have a lot of free and paying users but we currently do not have any process to stay in touch with them and keep collecting their feedback.\n\n**🙏 Our Ask**\n\n* Try us out. Please get started by installing our Chrome Extension: <https://chromewebstore.google.com/detail/requestly-intercept-modif/mdnleldcmiljblolnjhpnblkcekpdkpa>\n* If you know Requestly could be useful to someone you know, please spread the word :)\n\n🎁 **Special YC Deal:** 6 months free for your entire team on our Professional plan.\n\nDrop me a line at [sachin@requestly.io](mailto:sachin@requestly.io) or book a demo: [https://app.cal.com/sachin-rq/30min.](https://app.cal.com/sachin-rq/30min)\n\nSachin\n\n![uploaded image](/media/?type=post&id=85821&key=user_uploads/89898/ae74d725-a8fc-4db5-8077-77b6b511488d)\n\n",
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        "created_at": "2024-11-25T07:44:19.492Z"
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    "website": "https://getconvoy.io",
    "all_locations": "London, England, United Kingdom; LA, Nigeria; Remote",
    "long_description": "We are building Convoy for engineering teams that value efficiency, especially during this bear market. \r\n\r\nYou might already know about API Gateways. Convoy is exactly that for webhooks.\r\n\r\nEngineering teams today use Convoy to securely send, receive and manage millions of webhooks reliably with robust support for retries, rate limiting, static IPs, circuit breaking, rolling secrets and more.\r\n\r\nWe know both receiving and sending webhooks can become a lot of work to manage, we have built a product to enable engineers to build and ship highly scalable stripe-like webhooks infrastructure.",
    "one_liner": "Webhooks Gateway for outgoing and incoming webhooks.",
    "team_size": 8,
    "industry": "B2B",
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        "id": 72597,
        "title": "Nohooks: Webhooks for platforms without webhooks",
        "tagline": "Receive real-time notifications of events from supported apps like Notion, Render and Digital Ocean. Powered by Convoy.",
        "body": "![uploaded image](/media/?type=post&id=72597&key=user_uploads/357104/239f25e6-9726-4a95-8100-b4e04df0405e)\n\nToday, we are excited to share our new tool: [nohooks.io](http://nohooks.io). Nohooks is a service that offers webhooks functionality even on platforms that do not have native webhooks support. With Nohooks, developers can receive real-time notifications of events from the list of supported apps ([DigitalOcean](https://www.digitalocean.com/), [Notion](https://notion.so/) and [Render](https://render.com/) as of this [launch](https://getconvoy.io/blog/convoy-launch-week)).\n\n![uploaded image](/media/?type=post&id=72597&key=user_uploads/357104/c9767c6b-6fce-42dc-93d5-39b8bfdd658f)\n\nWebhooks are a way for one application to notify another application when a specific event happens. By setting up a webhook, developers can receive real-time updates whenever a user takes a specific action, such as deploying a new service or adding a new contact to your CRM. However, not all platforms support webhooks, which can be a problem for developers who need to receive real-time updates.\n\nNohooks solves this problem by acting as an intelligent polling system, that retrieves resources from the public API of these apps, determines whether there was an update and generates a webhook event depending on the type of update. It uses [Convoy](https://getconvoy.io/) to power its webhooks delivery and debugging dashboard.\n\n![uploaded image](/media/?type=post&id=72597&key=user_uploads/357104/fab69289-51b5-4756-9536-5341f7139c15)\n\nWith Nohooks, you can link multiple Render accounts and Notion workspaces and multiple destination endpoints as well. To get started, create an account here, and watch this demo video to learn how to set up your account to receive events.\n\n### **Use Cases**\n\n1. With Render webhook events, you can hook into the lifecycle of your services and service deployments to perform post-deployment actions, trigger continuous delivery pipelines etc.\n2. With Notion webhook events, you can sync any Notion Database to Airtable, Mailchimp, Intercom, or any CRM you choose. You can sync Notion Events to anything like Zapier or [Trigger.dev](http://Trigger.dev) for any kind of automation you desire.\n3. With DigitalOcean webhook events, you can into the lifecycle of your droplets to carry out post-deployment automation similar to Render. We plan to support many more resources in DigitalOcean in subsequent releases.\n\nThat’s it, friends, go and automate. We can’t wait to see what you build with this!\n\nIf you need any help or want to see us support new services, you can email us at [support@nohooks.io](mailto:support@nohooks.io) or join our [Slack Community](https://join.slack.com/t/convoy-community/shared_invite/zt-xiuuoj0m-yPp\\~ylfYMCV9s038QL0IUQ) to ask questions.",
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        "created_at": "2023-06-28T13:40:13.909Z"
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        "id": 65789,
        "title": "Convoy: Open Source Webhooks Proxy",
        "tagline": "Convoy is an open-source webhooks proxy that enables you to receive and publish webhook events reliably.",
        "body": "**TL;DR: Convoy provides a reliable webhooks proxy that can ingest webhooks from all your providers and replay them to your backend as well as publish webhook events from your systems to your customers.**\n\nHey YC 👋🏾\n\nI am Subomi, and I am building [Convoy](https://getconvoy.io) alongside Emmanuel.\n\n**The Problem**\\\nToday, webhooks power critical business workflows that, if broken, will have a direct impact on customers’ experience. Usually, developers spend time building reliable webhook ingestion services and reliable webhook dispatching services for API providers. This time is wasted effort that can be spent building necessary infrastructure instead of building your product. Secondly, the tooling becomes fragmented for dispatching and receiving webhook events. We are working on Convoy to solve precisely this using a consistent toolchain to receive, publish and debug webhook events.\n\n**Our Solution**\\\nEnter Convoy, a service available as an open-source project and a cloud platform. There are two types of projects in Convoy; an incoming project and an outgoing project. In an incoming project, we provide a unique URL per provider to receive events, and in an outgoing project, we provide a REST API to receive events from your services and publish them to the outside world.\n\n**How it works?**\n\nYou can see a demo [here](https://www.youtube.com/watch?v=DSIet81oBsg).\n\n**Asks**\n\n1. If you’re building an API that sends out webhooks and/or a service that relies on webhooks from third-party providers, you can get started for free by either [self-hosting](https://getconvoy.io/docs/deploy/overview) or using our [cloud platform](https://dashboard.getconvoy.io/signup).\n2. If you have vast experience running webhooks infrastructure (either incoming or outgoing), please join us on [slack](https://convoy-community.slack.com/join/shared_invite/zt-xiuuoj0m-yPp\\~ylfYMCV9s038QL0IUQ#/shared-invite/email). We’d love to learn from you!\n3. If you have further questions and would love to learn more, you can book a meeting with the [founders.](https://calendly.com/subomioluwalana/30-minute-meeting)\n\nThank you!",
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        "title": "Account Executive, Mid-Market",
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        "url": "https://www.ycombinator.com/companies/broccoli-ai/jobs/X3i01wk-software-engineer",
        "location": "San Francisco",
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        "url": "https://www.ycombinator.com/companies/broccoli-ai/jobs/3uN71hQ-senior-software-engineer",
        "location": "San Francisco, CA, US",
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        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$180K - $300K",
        "equity_range": "",
        "experience": "6+ years",
        "visa": "Will sponsor",
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      },
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        "id": 100503,
        "title": "Senior Product Manager: New Verticals",
        "url": "https://www.ycombinator.com/companies/broccoli-ai/jobs/kfY8uiC-senior-product-manager-new-verticals",
        "location": "San Francisco, CA, US",
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        "id": 100862,
        "title": "Customer Enablement Lead",
        "url": "https://www.ycombinator.com/companies/broccoli-ai/jobs/gOjd3U2-customer-enablement-lead",
        "location": "San Francisco, CA, US",
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        "id": 74154,
        "title": "Bracket - Sync Salesforce & Postgres: Heroku Connect alternative for any SaaS",
        "tagline": "Two way syncs between business tools and your database",
        "body": "**Tl;dr:** [**Bracket**](https://app.usebracket.com) syncs data bidirectionally between tools like Salesforce & databases like Postgres — think Heroku Connect between any SaaS tool and any database or warehouse. For companies that collect customer-relevant information in SaaS tools, Bracket is the simplest way for engineers to get this data in front of customers in real time.\n\n—\n\nHey everyone! We’re Vinesh, Ian, and Kunal and we’re building Bracket.\n\n![](https://lh5.googleusercontent.com/xrZwklibKE9wZuf_lyCSiei3Nt082k0IncnOuMZsmtUqwLV_JLbWEPilfCw1HJ41-GfqJg7XruoZP4cigIcN3RfnS7vKItZsqlzx8uyAMRBJs1dQItNfvU8E8f9I7qWzJZZHT1NhxwblRHAdUajPh4s)\n\n### **The problem**\n\nCompanies often need a way to manually adjust the info that a lead or customer sees - think of the sales team of a software company that wants to customize a demo environment for a high-value lead, or the ops team of a car rental company that needs to manage which cars are available for customers to book. \n\nThe job of designing, implementing, and championing a fix falls to engineering. Engineers can either build a custom UI for their teammates, or connect with the tools they already use, like Salesforce or Airtable. \n\nThere are a few problems with this:\n\n1. Custom UIs run against the grain of the tools that business teams already use and can even require double data entry on the part of those teams. This leads to low adoption. \n2. This leads most engineers to integrate with their business teams’ existing tools. However, setting up real-time two-way syncs is a highly technical challenge that can take entire quarters of implementation time.\n\nIn short, custom-built solutions lead to low adoption, and built-from-scratch integrations with business teams’ tools can take months of engineering effort.\n\n### **How we solve it**\n\n**Using two-way syncs, Bracket is the easiest way to keep data in sync between business teams’ existing tools, like Salesforce, and databases, like Postgres.** \n\nThis creates a win-win-win. Using the Salesforce <> Postgres example:\n\n* Engineering gets to build on top of Postgres and doesn’t have to deal with the Salesforce API (we do that for you). Engineering also meets business teams where they are, optimizing adoption.\n* Customer-facing business teams (e.g. Sales, CX) continue to leverage Salesforce, a familiar, highly productive tool with tons of features and a strong community, and can trust that their data is fresh.\n* Customers - seeing fresh, personalized data - get the best UX possible, increasing lead conversion and paid retention.\n\n \n\nOur new web app works with Salesforce and Postgres along with other connectors (like  Airtable, Google Sheets, MySQL and more).\n\n![](https://lh4.googleusercontent.com/plJHt6uWnEfHvqApcTBso-yoZ9penLWsS7gyG4usf8avqWinfSaNtFVRLwV4Hd7eFAcmJ-A-ueNFIgpiv33S4TlCZGBd_OyOzauJWPKPKRj3r_-PSyKQMxoqJqQ5T03cd7LPWWLlg_9DJ0marOEavuM)\n\n### **Demo:**\n\n[ ](https://www.youtube.com/watch?v=sRkaAa667T0)\n\n### **Differences from Heroku Connect?**\n\n1. **Built for your tech stack:** We support beyond just Heroku Postgres. Not only do we support any hosted Postgres, but we also have two-way syncs with other databases and warehouses.\n2. **Active Development:** Heroku Connect hasn’t been updated in years and has no new features on their official roadmap. Bracket continues to develop around the modern stack.\n3. **Uses cases across teams:** We’ve built two-way syncs for CRMs like Salesforce but also other products like Airtable, Google Sheets, and more.\n4. **Price:** We’re far cheaper than Heroku Connect, which can run north of $50k / year.\n\n### **Our ask:**\n\nIf you want to try this yourself, get started[ **here**](https://app.usebracket.com)\n\nOtherwise, if you:\n\n1. Are looking for two-way syncs between other tools and want us to build it\n2. Know any data engineers at mid-market / enterprise companies to make an intro\n3. Have any other questions, please reach out to [founders@usebracket.com](mailto:founders@usebracket.com)",
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        "title": "Vessel: Easily integrate with your customer’s CRM",
        "tagline": "Vessel allows developers to read and write to their customer’s CRM with one integration.",
        "body": "### ⁉️ Problem\n\nFor products that need access to their customer’s CRM, having a breadth of integrations has become table-stakes. However, it is difficult to build CRM integrations in-house, because you need to:\n\n* support different types of authentication\n* understand the data model, APIs, and ever-changing specs of each CRM platform\n* handle platform limitations like API quotas and limited webhooks support\n* transform data from your customer’s CRM for use in your product\n\nCompanies are spending a lot of engineering resources building and maintaining CRM integrations in-house. For instance, we spoke to a company that built a HubSpot integration and had to turn it off because they didn’t have the resources to handle HubSpot’s API limits.\n\n### 💡 Solution\n\nVessel is the universal API for CRMs, making it easy for developers to build applications that integrate with their customer’s CRM.\n\n* A unified interface to read and write across 8 objects: Accounts, Leads, Contacts, Deals, Events, Notes, Tasks, [Users](https://vesseldocs.stoplight.io/docs/vessel/603bd0ce2abb1-get-all-users)\n* [Webhooks](https://vesseldocs.stoplight.io/docs/vessel/e1m6clym4s5ya-webhooks) to keep your data fresh without polling even if the end platform does not offer webhooks on certain objects.\n* A drop-in UI to securely connect your customer’s CRM to your product\n* Avoidance of rate limits for platforms you integrate with\n* Improved developer experience with strongly associated objects. You can easily identify all of the associated objects (e.g. going from leads -> accounts, accounts -> leads)\n\n### ⚡ Get started\n\nIf you’re looking to integrate CRMs into your product, book some time [here](https://calendly.com/vesselapi/vessel-demo) or send us an email with your use case at [founders@vessel.land](mailto:founders@vessel.land)! Learn more at <https://vessel.land>.",
        "url": "https://www.ycombinator.com/launches/Gq5-vessel-easily-integrate-with-your-customer-s-crm",
        "votes": 22,
        "created_at": "2022-07-19T15:12:24.823Z"
      }
    ]
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    "id": 25946,
    "name": "PropelAuth",
    "slug": "propelauth",
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/72dfbc62d781eba9b77e867d8e40fdab0d7efbf8.png",
    "website": "https://www.propelauth.com",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "PropelAuth provides the right level of authentication for all stages of a company. New startups can use our hosted pre-built UIs which provide the simplest possible integration. Out of the box, our customers immediately have the same auth experience as large tech companies like Slack. As those startups grow, they can use our APIs and component libraries to pull aspects of the experience into their product.\r\n\r\nMore than just authentication, we will also provide useful functions tied to a \"user\" or \"organization\", like analytics, billing/subscriptions, referral programs, etc.",
    "one_liner": "Team-based authentication for B2B SaaS",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1642107038,
    "tags": [
      "Developer Tools",
      "SaaS",
      "B2B",
      "Identity"
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    "isHiring": true,
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    "batch": "Winter 2022",
    "status": "Active",
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      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Fully Remote"
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/propelauth",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2022/propelauth.json",
    "year_founded": 2021,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/propelauth/",
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    "github_url": "https://github.com/propelauth",
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    "primary_partner": {
      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
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    "founders": [
      {
        "user_id": 609048,
        "full_name": "Andrew Israel",
        "title": "Founder",
        "founder_bio": "Andrew is the founder and CEO of PropelAuth. He has more than 10 years experience building software and leading teams for companies like Palantir, SafeGraph, and Clockwise.  He first started writing code in the 6th grade.\nIn his free time, you can find him playing chess or hiking with his dog.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/andrew-israel-457751b8/",
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        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/968342b2070688ca95ac07823b2895a3da977287.jpg"
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    "jobs": [
      {
        "id": 105456,
        "title": "Backend Engineer",
        "url": "https://www.ycombinator.com/companies/propelauth/jobs/8W9NMOq-backend-engineer",
        "location": "US / Remote (US)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Backend",
        "salary_range": "$140K - $180K",
        "equity_range": "0.25% - 1.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 105457,
        "title": "Support Engineer",
        "url": "https://www.ycombinator.com/companies/propelauth/jobs/oubM4C4-support-engineer",
        "location": "US / Remote (US)",
        "type": "Full-time",
        "role": "Support",
        "role_type": null,
        "salary_range": "$120K - $160K",
        "equity_range": "0.25% - 1.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 105458,
        "title": "Fullstack Engineer",
        "url": "https://www.ycombinator.com/companies/propelauth/jobs/gHlDUgm-fullstack-engineer",
        "location": "US / Remote (US)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$140K - $180K",
        "equity_range": "0.25% - 1.00%",
        "experience": "3+ years",
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    ],
    "news": [
      {
        "title": "PropelAuth raises $2.59M to address the specific authentication requirements of B2B companies — TFN",
        "url": "https://techfundingnews.com/propelauth-raises-2-59m-to-address-the-specific-authentication-requirements-of-b2b-companies/",
        "date": "Jul 27, 2022"
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    ],
    "launches": [
      {
        "id": 77445,
        "title": "User Insights by PropelAuth: Don’t just acquire your users - understand them",
        "tagline": "PropelAuth makes it easy for B2B companies to start onboarding users quickly",
        "body": "Hi all! We’re the team at PropelAuth and we’re really excited today to launch User Insights!\n\n### What is PropelAuth?\n\n[PropelAuth](https://www.propelauth.com/?utm_source=launchyc) makes it easy for B2B companies to start onboarding users quickly. A [simple integration](https://docs.propelauth.com/getting-started/quickstart-fe) gets you everything you need, from signup and login pages to 2FA to invitation flows to Enterprise SSO.\n\nIn addition to that (as you’ll see in this launch), our goal is to also help you grow your business. We understand that building a product/company is incredibly challenging and we want to take as much off your plate as possible.\n\n.\n\n### What problem is User Insights solving?\n\nWhen we first started out a few years ago, all of our customers were other early stage startups.\n\nAs an early stage startup, the first thing you want to do is just get your product live immediately - get your MVP in front of users, get feedback, and hear if you are headed in the right direction or not.\n\nOur role there is pretty straightforward - we need to provide the simplest authentication story possible to help our customers get in front of their users.\n\nHowever, as our customers have grown in both number of MAUs and headcount, we’ve realized that they all tend to shift from “the most important thing is getting in front of people” to “how can we pour fuel on this fire?”\n\nPut differently, it’s not enough to simply get users signed up - you need to know more about them.\n\n.\n\n### What is User Insights?\n\nWith User Insights by PropelAuth, you can quickly get an understanding of:\n\n* Who your power users are\n* Which users and organizations are at risk for churn\n* Where your users are coming from\n* Which of your organizations are growing\n\n.\n\n### 💪 Identifying Power Users\n\nForming relationships with your power users is key to growth. They’re potential advocates, potential logos for your marketing site, and will likely have the best feedback for you about your product experience. Plus… they’re the most willing to pay if they’re not already!\n\n![uploaded image](/media/?type=post&id=77445&key=user_uploads/609048/dc0abe3f-a561-4f33-9e50-aae735e8698b)\n\nIf you’re curious about an individual users usage, we also provide a visualization on their user page, like this user who clearly is a big fan:\n\n![uploaded image](/media/?type=post&id=77445&key=user_uploads/609048/fd4cd0e9-606d-4347-ae5a-3db7277cdc90)\n\nOr this user… who you might want to check in with:\n\n![uploaded image](/media/?type=post&id=77445&key=user_uploads/609048/73f6b3fa-144f-4936-91b5-d75a2d90ea15)\n\n.\n\n### ⚠️ Proactively identifying Churn Risk\n\nSpeaking of proactively checking in with customers, we wanted to make that easier as well.\n\nWhile it’s exciting to see your user count go up, that’s not the end of the work you have to do: you also have to make sure to retain as many of those users as possible.\n\nWith our Churn reports, you can easily see which of your users and organizations haven’t been active in your product for awhile:\n\n![uploaded image](/media/?type=post&id=77445&key=user_uploads/609048/a61c595f-f9ed-4e7e-ab71-0d7fe00d1cd9)\n\nWe also provide re-engagement reports so you can see how your efforts are going to get these users back into your product.\n\n.\n\n### 🔍 Understanding where users came from\n\n![uploaded image](/media/?type=post&id=77445&key=user_uploads/609048/04f77928-72fa-42eb-a877-d66af61e2821)\n\nUnderstanding where your users are coming from is the easiest way to make sure your marketing efforts aren’t going to waste. Now, any URL query parameters that users have on sign up will be stored. You’ll be able to get both an aggregate report (see above) or take a look at a specific user’s profile page:\n\n![uploaded image](/media/?type=post&id=77445&key=user_uploads/609048/3fcb54a2-6c4d-4a72-a7bc-6ba6afb2a3d6)\n\n.\n\n### 📈 See how quickly your customers are expanding\n\nOne of the most exciting moments for any B2B company is watching one of your customers onboard more employees to your product.\n\nAnd keeping an eye on which of your organizations are growing quickly can make it easy to target efforts around upselling. The Organization Growth report lets you see that at a glance:\n\n![uploaded image](/media/?type=post&id=77445&key=user_uploads/609048/1f730d81-6c2c-40d8-83b5-5288eda8a207)\n\nYou can also quickly see which of your users is responsible for growth with the Top Inviters report. We recommend keeping in touch with these users - they’re your biggest advocates!\n\n![uploaded image](/media/?type=post&id=77445&key=user_uploads/609048/a86b1605-0100-43f4-b58b-5c58479162aa)\n\n.\n\n### And more…\n\nThere are also more reports to discover, charts to visualize how you are doing, and stats to see how this month compares to previous months. We’re also working on a few integrations so you can sync this data to your own analytics platform for even deeper analysis.\n\n.\n\n### Our asks\n\n* Ready to set up your B2B auth flow and gain a better understanding of your users? [Sign up for PropelAuth here.](https://www.propelauth.com/?utm_source=launchyc)\n* Want to keep up to date with our product updates? Follow us on [LinkedIn](https://www.linkedin.com/company/propelauth) or [Twitter](https://twitter.com/PropelAuth)!\n* Have an idea/request for something that you didn’t see above? Send us an email at [support@propelauth.com](mailto:support@propelauth.com)\n\nThanks,\n\nThe PropelAuth Team",
        "url": "https://www.ycombinator.com/launches/K97-user-insights-by-propelauth-don-t-just-acquire-your-users-understand-them",
        "votes": 20,
        "created_at": "2024-01-11T18:56:39.083Z"
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    "website": "https://jamsocket.com",
    "all_locations": "New York City, NY, USA",
    "long_description": "We are a platform for high-performance browser-based applications. We make it easier for developers to deploy apps that give every user a dedicated backend.\r\n\r\nThis is a system design that apps like Figma and GitHub codespaces use, but it's currently difficult for others to replicate it. We make it as easy as deploying a traditional web server.",
    "one_liner": "Run compute-intensive apps in a browser",
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    "year_founded": 2021,
    "city": "New York City",
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        "full_name": "Paul Butler",
        "title": "Founder",
        "founder_bio": "I'm a technical founder building Drifting in Space. My career has straddled the line between engineering and data science, with stints at Google as a software engineer on search, Two Sigma as a quantitative analyst, and botnet detection at an adtech startup.\n\nI'm originally from Halifax, Canada, currently based in Brooklyn, and love running, sailing, and exploring new cities.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/paulgb",
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        "full_name": "Taylor Baldwin",
        "title": "Founder",
        "founder_bio": "Co-founder of Drifting in Space. Was previously a software engineer at Uber and Datadog building WebGL-based data viz applications in the browser. Before becoming a software engineer, I was a classical musician with bachelor and master degrees in piano performance and pedagogy.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/taylor-baldwin-642b4818/",
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    "id": 25966,
    "name": "Sendo",
    "slug": "sendo",
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    "all_locations": "New York City, NY, USA; Remote",
    "long_description": "We're making it easy, cheap and fun for startups to build on SMS again. Sendo is the most developer-friendly SMS API, with great documentation, a fast dashboard, helpful monitoring features, easier 10DLC compliance and much more.\r\n\r\nSave 40%+ compared to Twilio and other options, and get started sending messages in 1-2 days instead of waiting weeks for your 10DLC campaigns to get approved.",
    "one_liner": "The best SMS/RCS API for startups",
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        "full_name": "Nick Rubin",
        "title": "Founder",
        "founder_bio": "Stanford '21. Building things since age 13, including a viral Chrome extension, an Ethereum prediction market and bots to buy streetwear. I love books and travel – ask me about my 11,000-mile train trip.",
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        "linkedin_url": "https://www.linkedin.com/in/nick-rubin-6729569a/",
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        "user_id": 299795,
        "full_name": "Daniel Lewis",
        "title": "Founder",
        "founder_bio": "Building tools to help creators monetize their expertise and insights. Tufts '20. DC born and raised.",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/daniel-lewis-34b9b7ba/",
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    "id": 25972,
    "name": "Winter",
    "slug": "winter",
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    "long_description": "Stripe for NFT purchases. Easily buy/sell NFTs with a credit card.",
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    "launched_at": 1644983990,
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        "full_name": "Michael Luo",
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        "full_name": "Laila Chima",
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        "founder_bio": "Hi friends, I was a CTO at Winter but I'm a life coach now :) ",
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        "user_id": 922334,
        "full_name": "Chris Hill",
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        "title": "🧑‍🚀 Massdriver - Production-ready cloud infrastructure in minutes",
        "tagline": "Massdriver handles the boring parts of cloud infrastructure management and DevOps so your team can focus on building great products.",
        "body": "**tl;dr Engineers spend 20-30% of their time reading cloud documentation and fidgeting with tools like Terraform or doing 'ClickOps.' With Massdriver, engineers can provision secure, production-ready cloud infrastructure in minutes without cloud expertise using a simple diagramming interface.**\n\nHey all, we’re Cory, Chris, and David, the team behind [Massdriver.](https://massdriver.cloud) We’re on a mission to radically simplify cloud infrastructure management and ‘DevOps.’\n\n## 😢 The Problem\n\nFor many organizations, DevOps is no longer a set of practices and culture. It’s a separate team with its own backlog slowing down your product development. Software today isn’t simply code on a computer. It’s a series of ~~tubes~~ APIs and services stitched together with YAML, tools like Terraform, and complex IAM rules. A bunch of boring plumbing that is slowing down your feature velocity.\n\n## 🪄 Our Solution\n\nMassdriver is a visual development platform that lets engineers focus on what services they need from the cloud and easily connect them without worrying about implementation details. Massdriver takes care of secret management, provisioning, parity, best practices, and IAM so your team can focus on your product. Our infrastructure and application bundles are open source, so you can modify them as your organization evolves or create your own and extend the platform.\n\n## ⚙ How It Works\n\nDevelopers can quickly connect dozens of pre-built infrastructure and application bundles designed by industry experts to provision secure production-ready infrastructure in minutes. Massdriver focuses on developer needs, not the implementation details of infrastructure, making it easy for developers of any caliber to get great infrastructure instantly.\n\nOur pre-built infrastructure bundles can be forked and modified, and the community can also design their own bundles using Terraform and Helm to extend the platform.\n\n![uploaded image](/media/?type=post&id=66021&key=user_uploads/920899/fea74a72-ac18-49a6-bdc5-f8e8af425525)\n\n## 🚀 Out of This World Features\n\n* Parity management with replication support for infrastructure and applications between regions, environments, and cloud accounts\n* Integrated secret management that injects credentials directly into your applications environment variables\n* Automated principle of least privilege for IAM\n* Dozens of best-practice reference architecture infrastructure bundles to get started, each open-sourced and designed by industry experts\n* Compliance and security scanning for official infrastructure bundles\n* Activity and audit logs of every change to ease your path to compliance\n* Visually compare differences between environments like staging and production or between deployments\n* Integrated alerting and monitoring\n* Application support for containerized and serverless workloads\n* Enterprise-ready deployments for SaaS products - your product in your customer's cloud account today.\n\n## 🙏 Asks\n\nTry it out! Feel free to register on the site and try it out; no credit card is required. If you like it, we have a _stellar_ [deal](https://bookface.ycombinator.com/deals/1318?query=mass) for all YC companies.\n\nJoin us on [GitHub](https://github.com/massdriver-cloud/docs/discussions/9), or DM us on [Twitter](https://twitter.com/massdriver)!\n\nIf you have 10 minutes to chat about Massdriver, please book a time with me [here](https://calendly.com/coryodaniel/10min-intro) 😊",
        "url": "https://www.ycombinator.com/launches/HAr-massdriver-production-ready-cloud-infrastructure-in-minutes",
        "votes": 55,
        "created_at": "2022-09-13T15:07:52.872Z"
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        "user_id": 10917,
        "full_name": "Joe Averbukh",
        "title": "Founder",
        "founder_bio": "I truly believe each one of us has the ability to create the world they want to see. I love working with optimistic and principle-oriented people.\n\nIn 2020 I left Airbnb to build with my best friend. We followed two rules initially 1) Build something we want for ourselves and 2) Make something more ambitious than previously. In 2021 we added a third rule, 3) Make it a business. To that end we launched Jobsearch.dev, ExportHealth, Zeneca, Consistent, and then Instant, the modern Firebase",
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        "user_id": 62197,
        "full_name": "Stepan Parunashvili",
        "title": "Founder",
        "founder_bio": "I work with people I will be friends with for a lifetime. I love hacking. I started off my career building a startup in China, and soon joined Wit.ai to work on an API for natural language processing. We used a suite of interesting tools, like Clojure, which heavily influenced my software design philosophy. We were acquired by Facebook. After 4 years, I had a stint at Airbnb, and decided to start Instant with my best friend. I also love to write; you can read some essays on my blog: stopa.io",
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        "linkedin_url": "https://www.linkedin.com/in/stepan-parunashvili-65698932/",
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        "title": "The Instant team joins OpenAI",
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      {
        "title": "Instant harkens back to a pre-Google Firebase | TechCrunch",
        "url": "https://techcrunch.com/2024/10/02/instant-harkens-back-to-a-pre-google-firebase",
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    "launches": [
      {
        "id": 65461,
        "title": "⚡️Instant: The Modern Firebase",
        "tagline": "Graph database on the client",
        "body": "Hello hello! We’re [Stopa](https://stopa.io) and [Joe](http://www.joeaverbukh.com/), and we’re excited to share [Instant](https://instantdb.com)!\n\nInstant is the graph-based successor to Firebase. We make it easy to build realtime and collaborative applications like Figma or Notion.\n\n**Some quick context on us:** We have 15 years of technical experience between the two of us. We both worked at Facebook and Airbnb as senior and staff engineers. It was at Facebook we saw how a graph-based solution with an expressive permission layer allowed engineers to ship fast and at scale. We want to bring the same experience to all developers around the world.\n\nSome people think realtime and collaboration are nice-to-haves, and place it at the bottom of their to-implement list. But if you think about it, multiplayer experiences are what separates the good apps from the best. It’s why Notion beats Evernote, and why Figma beats Sketch.\n\nFeatures like realtime, collaboration, offline mode, and optimistic updates will be table stakes for applications of the future. At present though, implementing these features is difficult due to edge cases and added complexity. Only a few products offer great multiplayer experiences, and these are usually bespoke solutions from a team of engineers at top-tech companies.\n\nInstant handles this complexity for you via a graph-based database on the client + an expressive permissions layer. This gives you a Firebase-like experience AND support for relationships between data. This combination provides multiplayer out of the box and enables developers to move fast.\n\nIt’s still early days, we have much to build. We’re currently free to use and will roll out paid plans in the future. **You can already start building with Instant today at** [**https://instantdb.com**](https://instantdb.com)\n\nIf you sign up, we’ll personally reach out and answer any questions you have with building on Instant. We really excited to bring this to you all, and look forward to what you build!",
        "url": "https://www.ycombinator.com/launches/H1p-instant-the-modern-firebase",
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        "created_at": "2022-08-18T15:16:07.461Z"
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "HyperDX assists engineers in resolving production bugs more quickly with simple workflows that take you from alert to resolution. You can get set up in a matter of minutes and correlate debug telemetry all in one place, including logs, metrics, traces, and browser session replays, allowing you to resolve issues faster than ever before.\r\n\r\nHyperDX is open source and built on top of Clickhouse and S3, so customers can enjoy ten times the savings when compared to traditional vendors like Datadog.",
    "one_liner": "Open-source, dev-friendly observability.",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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    "tags": [
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/hyperdx",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2022/hyperdx.json",
    "year_founded": 2022,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/hyperdx",
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      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
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        "full_name": "Michael Shi",
        "title": "Founder",
        "founder_bio": "Currently building HyperDX (acq'd ClickHouse)",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/mikeshi42/",
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        "user_id": 346706,
        "full_name": "Warren Lee",
        "title": "Founder",
        "founder_bio": "Previously built a profitable company from 0 to millions ARR",
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        "date": "Mar 13, 2025"
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    "long_description": "Designers and product managers are often locked out of prototyping on top of their existing product. Security policies, large code base, and complex build setup all stand between the promise of code-first front-end design and reality.\r\n\r\nThe Chordio Workbench helps non-technical team members prototype new experiences on top of their existing products even when they don’t have access to the source code.\r\n\r\nThe full workflow runs in Claude Code on your local machine. It starts with cloning the front-end of the product into the workbench repository directly from the browser and compiling it into code a coding agent can work with. This means anyone can start prototyping in minutes without having to worry about a complex environment setup.\r\n\r\nThe Workbench includes agent skills to help ensure prototypes meet team standards, are backed by research, and presented to stakeholders with clarity.",
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        "full_name": "Ehud Halberstam",
        "title": "Founder/CEO",
        "founder_bio": "I'm the co-founder and CEO of Chordio. From 2014-2017 I was a co-founder and CEO of Brand.ai, where we built a platform that solved problems of design at scale at the enterprise. \nIn 2015 Brand.ai participated in the Techstars accelerator and raised financing from amazing investors. It was acquired by InVision in 2017. \nFrom 2017-2022 I helped build Brand.ai into InVision DSM, InVision's second commercial product.",
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        "full_name": "Amit Bar",
        "title": "Founder",
        "founder_bio": "Co-founder and CTO - Chordio.\n\nPreviously co-founded Brand.ai - a platform for design system management. Sold to InVision in 2017, and stayed on as an engineering manager and director of engineering. Continued to scale and evolve the product into InVision's DSM (Design System Manager).\n\nMoved on in 2022 to lean into the project management space, where I see many familiar patterns and challenges waiting to be solved.",
        "is_active": true,
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      {
        "id": 96377,
        "title": "Design Rails: Generate an agent-ready brand identity in minutes",
        "tagline": "Chat with an AI Creative Director to craft a complete brand from logos to voice & tone. Export as a design system your coding agents use to build consistent, on-brand interfaces.",
        "body": "Hey everyone, Ehud here, CEO of Chordio, the company behind Design Rails.\n\nOver the last year, like everyone else, we've been building products with Claude, Cursor, and other coding agents. We wanted to ship a number of products rapidly to see what resonates most with customers.\n\nWe hit two separate problems:\n\n**Problem 1: The UI looked polished at first glance, but \"wrong\" in ways we couldn't unsee**\n\nThis went beyond the “purple gradient syndrome”. The agent would invent new components with inconsistent styles. It added static labels that looked like buttons. It embellished non-interactive cards with confusing hover states. It used emojis instead of elegant icons. Random choices everywhere.\n\n**Problem 2: We lacked a cohesive brand**\n\nWe were ready to launch a new product experiment within a week. The product worked, but it still felt like a prototype. We worried a “weekend project” look would distort our launch metrics and push us to the wrong conclusions. But we also were not willing to sink thousands of $ into branding before knowing anyone cared.\n\nAs ex-founders of Brand.ai (acquired by InVision), we believed there was a better way. Here’s what we built.\n\n**The solution**\n\nDesign Rails helps you craft your brand through chat, then export structured files your AI agent would use to stay on brand and generate polished UI.\n\nIn under 20 minutes, you get a design-context.zip package that includes a markdown spec, and design-tokens.json that specify:\n\n* Color palette\n* Typography system\n* Component guidelines\n* Voice & tone guide\n\nPlus\n\n* Logo assets in SVG and PNG with light & dark versions.\n\nIt works for new or existing products:\n\nYou drop the files into **/design-context** in your codebase, and tell your agent to\n\n```\nRead design-context/agent-instructions.md and create an integration plan for implementing this design system in our codebase.\n```\n\nThe agent will update your styles, move logos, configure components, and update your LLM instructions ([CLAUDE.md](http://claude.md/), .cursorrules, etc.) to reference the new design system.\n\nWe built this for AI builders who want to ship fast, iterate fast, and have their design look cohesive from day one.\n\nAlso, we’re trying something new (we’ll see how it goes!) - Outcome-based pricing. No token credits. No vendor lock-in. Use Design Rails for free, and only pay to download if you’re happy with the result.\n\nWould love your feedback, questions, and use cases you want us to support next.\n\nThanks for checking out Design Rails!\n\n![uploaded image](/media/?type=post&id=96377&key=user_uploads/1010497/204826ee-b53a-44f3-897f-f9947699012d)\n\n![uploaded image](/media/?type=post&id=96377&key=user_uploads/1010497/7c5faacb-d99e-4a2f-bdff-45bb8586ba01)\n\n![uploaded image](/media/?type=post&id=96377&key=user_uploads/1010497/42b6af05-017a-4fba-bf7d-ba6af209ee58)\n\n![uploaded image](/media/?type=post&id=96377&key=user_uploads/1010497/df99fc11-2fe6-440b-b00d-c353337ea564)\n\nSee it in action: https://youtu.be/TZ3gPYrCLUQ \\[2:19 mins\\]",
        "url": "https://www.ycombinator.com/launches/P4T-design-rails-generate-an-agent-ready-brand-identity-in-minutes",
        "votes": 14,
        "created_at": "2025-12-27T15:41:38.795Z"
      },
      {
        "id": 95564,
        "title": "Design Rails: Give your coding agent its own product design team",
        "tagline": "Ship better UX faster with specialized design agents",
        "body": "Hi everyone! We're excited to introduce a set of specialized AI agents that give your coding agent the design expertise it’s missing.\n\n# **Problem**\n\nYou ask Claude or Cursor to build a feature, and you get working code in 2 minutes, but you're stuck with prototype-level design:\n\n* **Visual glitches**: misaligned cards, text bleeding outside containers, buttons cut off\n* **Generic \"AI-feel\" style**: yet another purple gradient that doesn't fit your brand\n* **Flawed UX**: ignored existing navigation pattern, unlabeled icon buttons, missing loading states\n\nYou end up iterating for hours to reach production quality, if you get there at all.\n\n# **Solution**\n\nDesign Rails is an MCP server that connects to AI coding agents (Claude, Codex, Cursor, …) and unlocks production-ready design through three key capabilities:\n\n**1. Design foundation setup** - Design Rails first establishes a strong design foundation to understand your product like a senior designer would:\n\n* Brand & Design System (extracted from your codebase, or built from scratch)\n* Product Context (what you're building, user personas, key workflows)\n\nThis foundation is captured as .md files in your project. You own the files, version them, and can edit them.\n\n**2. Spec-driven design** - Your coding agent consults Design Rails when facing design decisions. Design Rails orchestrates specialist AI agents including a UX Designer, UI Designer, Accessibility Specialist, and UX Copywriter. Each agent has deep context of your brand, unique design domain expertise, and access to a library of proven patterns from top products.. They work in parallel to produce comprehensive design specs. Your agent gets a detailed blueprint to implement.\n\n**3. Automatic design reviews** - Design Rails spins up a browser to see the rendered results, validating implementation against the spec to catch visual glitches and design inconsistencies before you even see them.\n\n![uploaded image](/media/?type=post&id=95564&key=user_uploads/1010497/4aa73593-8ee3-481f-bcf8-2aaf25f9842c)\n\nSee live before and after examples here: https://designrails.com/#examples\n\n# **Transform glitchy prototypes into production-ready experiences**\n\nTry it out on your existing project, or give it a quick try using an example project we provide as a playground. We’d love to hear your feedback and question- get in touch at [hello@designrails.com](mailto:hello@designrails.com).\n\nTry it now for free at [designrails.com](http://designrails.com)",
        "url": "https://www.ycombinator.com/launches/OrM-design-rails-give-your-coding-agent-its-own-product-design-team",
        "votes": 10,
        "created_at": "2025-11-17T17:46:13.194Z"
      },
      {
        "id": 92765,
        "title": "Chordio - AI-powered design reviews that guard your standards",
        "tagline": "Remove QA grunt work, catch issues early, and ship polished interfaces with confidence.",
        "body": "👋 We’re excited to introduce [Chordio](https://chordio.com), an AI-powered design review tool for designers.\n\n# The Problem\n\nAs generative AI increases the pace of design work, maintaining quality through manual review is quickly becoming impossible. Manual review is slow, inconsistent, and costly. Mistakes slip through, standards drift, and QA turns into a painful bottleneck.\n\nTeams need a better way to answer, “Is this good?” for every design, every time.\n\n# The Solution\n\n**Chordio** is an AI-powered design review tool purpose-built to help product teams raise the quality bar and reduce overhead as they scale up their output. Here’s how it helps:\n\n* **Enforces Quality and Standards**: Chordio checks your designs against your organization’s unique standards, not just generic best practices. You get actionable, relevant feedback that aligns with your team’s guidelines.\n* **Scales Best Practices**: By automating reviews and surfacing helpful resources, Chordio makes it easy for teams of any size to consistently apply best practices and grow design maturity.\n* **Shifts Review Left**: With our Figma plugin, designers can catch and fix issues early—when changes are cheap and easy.\n* **Reduces Friction**: Chordio proactively flags issues before hand-off, so designers, developers, and QA don’t need to play “catch up” later. Fewer last-minute surprises mean less frustration and less design debt.\n* **Broad Review Capabilities**: Our Chrome extension lets you review _any_ webpage, in Staging or Production, so you get broader test coverage.\n\n![uploaded image](/media/?type=post&id=92765&key=user_uploads/1010497/bf4fd533-cc44-45e2-bb2f-35c4bea089bf)\n\n# The Backstory\n\nWhile building a design assistant, we realized how much teams view QA as a burdensome overhead. We noticed that as AI-generated designs become the norm, the gap between design and QA capacity grows wider. The need for a smarter, faster way to review designs became urgent.\n\nThat’s why we built Chordio. Our goal is to help every product team answer “Is this good?” confidently and at scale.\n\n# Try Chordio\n\nIf you’re a designer, product manager, or engineer who cares about quality and wants to keep moving fast, we’d love for you to give Chordio a try. Your feedback will help us shape the future of automated design review.\n\n# Free consulting\n\nIf you’re looking to establish team or company standards or connect your existing ones to an automated QA workflow, let’s get on a call.\n\n![uploaded image](/media/?type=post&id=92765&key=user_uploads/1010497/82027ecc-ee92-4b4f-bc34-4a82d9609f91)\n\n— The Chordio Team",
        "url": "https://www.ycombinator.com/launches/O8D-chordio-ai-powered-design-reviews-that-guard-your-standards",
        "votes": 6,
        "created_at": "2025-08-06T16:06:30.835Z"
      },
      {
        "id": 90093,
        "title": "PRDKit: AI-powered PRDs and supporting GTM artifacts in one place",
        "tagline": "Turn fuzzy feature ideas into clear specs — then auto‑generate the wireframes, user flows & GTM assets that follow.",
        "body": "![uploaded image](/media/?type=post&id=90093&key=user_uploads/1010497/cb87b05b-b9dc-4021-9428-9092d8176677)\n\n👋 Excited to introduce [PRDKit](https://prdkit.ai) - an AI-powered PRD workbench (web + Slack) for product managers and builders.\n\n**Problem:**\n\nWriting great product requirement documents (PRDs) is hard. These documents lay the foundation for a product or feature, yet they’re often bloated, confusing, and missing edge cases.\n\nThis leads to expensive downstream problems from a lack of team alignment to unnecessary work that gets thrown away.\n\nWrangling ChatGPT to write PRDs _works_, but it returns lots of fluff and quickly feels like running a sprint board in a spreadsheet—powerful yet awkward.\n\n**Solution**:\n\nPRDKit is a focused AI tool that captures rough ideas, structures them into clear, lightweight PRDs, and—at the click of a button—spins up the follow‑ups you always need:\n\n* Wireframes & user‑flow diagrams\n* Modular instructions for a dev AI‑agent like Bolt or Loveable for faster prototyping\n* GTM copy snippets\n\nFurther, it’s contextual. It helps you quickly capture the essence of your existing product (enter the homepage URL) to craft PRDs that cater to your personas and existing workflows.\\\n\\\nHere’s a [2-mins demo video]( https://youtu.be/QKNcrOjpUrQ) where you can see it in action. \n\n![uploaded image](/media/?type=post&id=90093&key=user_uploads/1010497/7b05811f-7e8b-478a-8b4a-9f30b40c112e)\n\n**Back story:**\n\nWe were deep into building a UX assistant when we found that product specs were slowing us down. Even with the aid of ChatGPT and Claude, requirements were bloated and disorganized.\n\nSo we spun up a quick internal project on the same AI infrastructure we’ve built, aimed solely at turning fuzz into structure. The team loved it; specs got sharper, hand‑offs got quieter.\n\nThat side project has now been packaged for public use. We want to learn where it shines—or breaks—outside our walls.\n\nProduct managers and builders: [take it for a spin](https://prdkit.ai)! We’ll top off your credits for feedback.\n\nThe PRDKit team\\\n[hello@prdkit.ai](mailto:hello@prdkit.ai)\n\n![uploaded image](/media/?type=post&id=90093&key=user_uploads/1010497/2d54b5da-4c61-492d-9951-eff6893615a4)\n\n",
        "url": "https://www.ycombinator.com/launches/NR7-prdkit-ai-powered-prds-and-supporting-gtm-artifacts-in-one-place",
        "votes": 14,
        "created_at": "2025-05-06T19:11:11.772Z"
      },
      {
        "id": 80115,
        "title": "Chordio: Your generative UX assistant",
        "tagline": "Go from a product idea to screen wireframes 10x faster.",
        "body": "**TLDR;**\n\nChordio is a generative UX assistant that designs screen wireframes based on their description to help product teams increase their product iteration velocity.\n\nAs a founder, you can use Chordio to visualize a new concept quickly, speed up the customer feedback loop, and save time and money building the right solution.\n\n[Here’s a 1-min video](https://youtu.be/eKQ_YJazFZs):\n\n**Problem**\n\nUX design is expensive. Visualizing and prototyping new concepts manually is a laborious task for designers and agonizingly slow for non-designers. This limits the number of designs a product team is able to vet early and leads to expensive redesigns of features down the road.\n\n**Solution**\n\nChordio helps founders and product managers run faster user feedback loops, improve communication clarity, facilitate faster team alignment, and reduce design costs.\n\nYou can think of it as a ChatGPT that’s pre-built for generating product wireframes. With it, you can:\n\n* Generate multiple screen wireframes at a time based on text description.\n* Refine the generated designs with text feedback.\n* Co-create effective copy and UI. Think of Chordio not only as a design assistant but also as a UX writer assistant.\n\n**Backstory**\n\nOur previous startup, [Brand.ai](http://Brand.ai), which helped designers and developers work better together, was acquired by InVision. We’ve been building software to support product teams since.\n\nThese days, AI is reshaping how products get built. GitHub Copilot and similar assistants speed up the development phase. Yet, the design phase is largely left unassisted, creating a new bottleneck in the product development lifecycle.\n\nWe’re building Chordio to remove this bottleneck and help teams build the right products faster.\n\nGet started for free at [chordio.com](https://chordio.com)\n\n---\n\n---\n\n**Contact us to customize Chordio for your team’s existing product and design system.**\n\n\\- Ehud & Amit",
        "url": "https://www.ycombinator.com/launches/KqB-chordio-your-generative-ux-assistant",
        "votes": 13,
        "created_at": "2024-04-11T19:21:38.063Z"
      },
      {
        "id": 65037,
        "title": "Chordio - Lightweight sprint planner for remote development teams",
        "tagline": "Planning made easy. Accurately reflect workload and give everyone a voice to quickly align on a plan forward.",
        "body": "👋 Hi everyone! Ehud and Amit, co-founders of [Chordio](https://chordio.com) here. We previously co-founded [Brand.ai](https://Brand.ai) to help designers and developers work better together. We sold the company to InVision in 2017 and worked on improving product team collaboration since. With Chordio, we’re looking to help teams at any size plan their work better.\n\n### **Why we’re building Chordio**\n\nExisting tools focus on issue tracking, and underserve the upfront project planning needs. Prioritization, estimation, and capacity planning are commonly problems teams are left to struggle with. The transition to remote work made planning harder still, as planning had often started with a whiteboard huddle. The average project management tool doesn’t speak casual. It’s built for an official plan, due dates, and commitments.\n\nThat’s why over 80% of the teams we’ve talked with reach for a general-purpose solution like a spreadsheet for their planning activities. They then face a different set of problems: sweating over manual work, getting formulas wrong, dealing with random editors breaking fragile automations, accumulating massive backlogs, and losing sight of the source of truth among a sea of documents.\n\nSo, we’re building Chordio as the best of both worlds. A lightweight, collaborative tool with key planning features built-in.\n\n![uploaded image](/media/?type=post&id=65037&key=user_uploads/1010497/73819665-290c-41d1-9d44-5cfe67e9ba8b)\n\n\n### **How it works**\n\nChordio lets you work at the right planning fidelity. Go from a casual brainstorm to evaluating rough plan outlines, to an official release plan. When you’re done, export the work to Jira or your issue tracking tool of choice. - Integrations are coming soon.\n\nYou can create any number of planning boards where you can specify a focus for the sprint, list features, provide estimates, and assign to people. As you assign tasks you’ll see the capacity graph of individuals getting updated so you can protect people’s time and ensure an optimal sprint scope.\n\n![uploaded image](/media/?type=post&id=65037&key=user_uploads/1010497/68d67d7e-1ce9-4713-a9c9-9e4eaf8d69ed)\n\n\n### **Partner with us?**\n\nWe’re looking for design partners. That is, companies that will pilot Chordio’s next major release and provide early feedback to guide our roadmap. **If you’re running multiple projects and interested in improving upfront planning, and ongoing visibility into teams’ work at any level, let’s talk.** Here’s a [Calendly link](https://calendly.com/ehud-chordio/design-partnership) to book some time.",
        "url": "https://www.ycombinator.com/launches/Guz-chordio-lightweight-sprint-planner-for-remote-development-teams",
        "votes": 22,
        "created_at": "2022-08-01T07:05:06.639Z"
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        "full_name": "Simar Kohli",
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        "founder_bio": "Co-Founder and CEO of Boundo - we're automating the sales process using Generative AI!",
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        "full_name": "Samik Shrotriya",
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        "founder_bio": "Recent Cornell University graduate working on automating outbound sales processes! ",
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        "title": "🚀 Openpod - Incentivize developer contributions and fundraise quickly for OSS projects",
        "tagline": "We're helping open source projects launch better with DAO infrastructure and tokens",
        "body": "**TL;DR**\n\nImagine if you had been able to buy Ubuntu tokens when it first launched…\n\n**Openpod is a DAO-as-a-service platform for open-source projects to incentivize developer contribution and make fundraising easy**. Projects can use these governance/utility tokens to compensate developers for their work, let early investors/speculators purchase these tokens, and reward their community. \n\n**Check us out here:** \\\n[openpod.io](http://openpod.io)\\\n[app.openpod.io](http://app.openpod.io)\n\n### **Problem:**\n\nLaunch ramps for open source projects are broken.\n\n* It’s hard to get funding as a new or up-and-coming open source project, even if you have believers. Most of the available funds and donations are often taken by the top open source projects. \n* Maintaining consistent contributions from developers is tough since they are volunteering their time. They are also not compensated for work they did in the early phases of a project - even if it's a successful one.\n* It’s tough to get people to use your product early on.\n\n \n\n### **Our Solution:**\n\nDAOs have long been a solution in search of a problem. **Open source projects are inherently decentralized and function as communities, which are hallmarks of DAOs.**\n\nOpenpod is a **DAO-as-a-service platform** for open source projects to establish their own DAO and mint utility tokens. Developers, users, and believers can purchase these tokens on our platform, and **get in early on potential growth** of the project and the token value. They’ll also be able to vote on new features and how the raised funding has been used. Meanwhile, the project can use this immediate funding for development. \n\nWe’re adding Github integration with DAOs so that **when developers commit or push to a project’s repos, they’ll get automatically compensated** based on the bounties associated with their tasks. \n\n### **Backstory:**\n\nAs developers who have worked on open source projects previously, we’ve seen some of the best and brightest people get burnt out while doing work for little to no compensation - especially when these projects are new. So we feel it's only fair to **let developers have a way to earn returns on their hard effort** in the project.\n\n### **Our Ask:**\n\nWe’d love to pilot the DAO creation platform with fellow YC companies! If you have a Github repository, and **a few cents to spare**, create your very own tokens for your project. \n\n**You could use these tokens to incentivize your early users, contributors, and have more people support you as a project.** \n\nWe’re working on integrations to let token holders **redeem the tokens for Open Core/SaaS credits or other perks** **to ensure your tokens will have value**. Users could also sell their tokens to make returns. \\\n[openpod.io](http://openpod.io) \\\n[app.openpod.io](http://app.openpod.io)",
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        "title": "IvyCheck – Guard against AI risks with real-time checks",
        "tagline": "An API for ensuring the integrity and safety of your AI application",
        "body": "**TL;DR:** [IvyCheck](https://www.ivycheck.com/) offers an API designed for classifying user- and AI-generated texts, along with extracting sensitive data. Our specialized machine-learning models ensure the safety and quality of your AI app in real-time.\n\n![uploaded image](/media/?type=post&id=79742&key=user_uploads/825709/1100f870-2ce1-44f4-a45f-2c1f640a2867)\n\n### What are AI risks?\n\nAI-powered interfaces such as chatbots emerge and pose **new AI risks:**\n\n* **Prompt Injection Attacks:** Attackers try to manipulate language models to execute unauthorized actions or access sensitive data. These attacks exploit the way AI interprets inputs as natural language text. Prompt injection attacks create a risk that spans from data exfiltration to influencing decision-making processes.\n* **PII Data Leakage:** Customers may include sensitive data in requests that are then sent to LLM providers. Companies must ensure that sensitive data is detected and redacted from requests.\n* **Hallucinations:** Chatbots in RAG applications use context retrieved from document stores, posing the risk of hallucinated, inaccurate, off-topic, or made-up information to users. IvyCheck evaluates whether chatbot answers are faithful to the provided context.\n\n![uploaded image](/media/?type=post&id=79742&key=user_uploads/825709/84a94c2d-9885-461e-a9f0-0724ccf1748a)\n\n### How does IvyCheck help?\n\nIvyCheck provides a library of checks for managing AI risks in your application. IvyCheck is:\n\n* **Flexible**: You can add checks to your LLM app with **just 2 lines of code** and protect your users and your data from prompt injection attacks, PII data leakage, and hallucinations. Works regardless of which LLM provider you use in your app.\n* **Secure**: We use customized, fine-tuned models for the checks. We self-host all our models and your data is not sent to third-party model providers.\n* **Fast**: Since the models are small and specialized, you can expect a latency under 100-200 ms. If you require even faster endpoints, please get in touch!\n\n### The founding team\n\n![uploaded image](/media/?type=post&id=79742&key=user_uploads/825709/6e2a1539-300a-4ab5-ac5a-46318b4e89d2)\n\nWe’re [Tammo](https://de.linkedin.com/in/tammo-rukat-34529471) (left) and [Dustin](https://www.linkedin.com/in/dustin--lange/) (right). We met at Amazon, where we were part of the Core Machine Learning team in Berlin. We worked on systems for large-scale data quality checks, missing value imputation, and search filter optimization. We’re both obsessed with delighting our customers and solving their toughest challenges! Let’s create a safer world with AI.\n\n### How do I get started?\n\nVisit [https://ivycheck.com](https://ivycheck.com/) or [book a call](https://ivycheck.com/request-demo) directly with us. We’d love to get in touch and help you make your AI app safe today!",
        "url": "https://www.ycombinator.com/launches/KkA-ivycheck-guard-against-ai-risks-with-real-time-checks",
        "votes": 5,
        "created_at": "2024-03-27T14:54:09.208Z"
      },
      {
        "id": 74336,
        "title": "Deekard - Instant answers from your database with AI",
        "tagline": "Stop waiting on data teams, guessing at undocumented schemas, and debugging SQL. Start getting answers.",
        "body": "**TLDR:**\n\nDeekard is your one-stop shop for fast and easy data analysis. Just enter your database details, ask your burning questions, and let Deekard do the rest. Forget waiting on your data team - it’s time to get your answers fast.\n\n**Problem:**\n\nYou are collecting data about your business and want to become more data-driven in your decision-making. But you’re hitting some speed bumps:\n\n* **Waiting game:** You’re stuck in a queue, waiting for your data team to free up and handle your request. They can’t update the dashboards fast enough or don’t have time to work on your ad-hoc data requests.\n* **No time to write SQL**: You’ve got a business to run, not a course in SQL to take. It should be simple to run your database queries, not a guessing game.\n* **Documentation? What documentation?** You look at your team’s data warehouse and you don’t understand what’s in there. There’s no documentation and you have no idea if that column really contains the data you hope for.\n\n**Solution**\n\nDeekard gives you a powerful, integrated analytics experience - powered by AI. Connect your database and you’re ready to go.\n\n![uploaded image](/media/?type=post&id=74336&key=user_uploads/825709/f9b112f8-94be-4f61-a329-3ce789b49b53)\n\n* **Requests in plain English**: Get started with your request in natural language and Deekard takes care of translating it into a database query. Refine your request with a graphical query builder - or just edit the plain English request. You can also switch to SQL mode - _and back -_ whenever you like.\n* **Explore your database**: See what’s _inside_ your database. Deekard automatically profiles your data and creates that missing documentation for you. This helps with writing queries that actually work.\n* **Team effort**: Share the AI-powered query editor and unblock your whole team. They can instantly reuse your database connection and ask their own questions.\n\n![uploaded image](/media/?type=post&id=74336&key=user_uploads/825709/3623b336-0a6f-44ec-a3f8-9c8d5babf861)\n\n**Ask:**\n\nTry Deekard! Start at [deekard.com](https://www.deekard.com). Tell us what you think at [founders@deekard.com](mailto:founders@deekard.com).\n\nIf you have a few min for a chat about Deekard, please book time with us [here](https://calendly.com/d/dxz-ddm-67k/deekard-call).\n\nThank you!\\\nDustin and Tammo",
        "url": "https://www.ycombinator.com/launches/JKy-deekard-instant-answers-from-your-database-with-ai",
        "votes": 15,
        "created_at": "2023-08-23T13:49:23.717Z"
      },
      {
        "id": 71231,
        "title": "🤖 Deekard - Your autonomous assistant for data science and analytics",
        "tagline": "We use generative AI to make all data tasks effortless and accessible: extract, transform, analyze, and visualize data using only natural language.",
        "body": "Hey everyone! We’re Tammo and Dustin from [Deekard](https://www.deekard.com/).\n\n**_TL;DR:_** _Deekard is an all-in-one data science and analytics assistant. Connect your data source and get any question answered and any task executed, using only natural language. Powered by GPT-4, our AI model understands your intent, plans workflows, and executes them step-by-step._\n\n**The Problem**\n\nData science involves a wide range of skills, tools, and formats, which can be challenging to learn and manage. Tasks like extracting data with SQL, training machine learning pipelines with Python, and visualizing data using frameworks such as Vega are time-consuming, iterative, and error-prone.\n\n**Our Solution**\n\nDeekard simplifies data science by offering a chat interface where you simply state what you want to do and watch the AI select the right tools in the right order. Like in a data science notebook, you can refer to previously created datasets and refine or combine them later in the conversation. Data science has never been easier or more approachable.\n\n![uploaded image](/media/?type=post&id=71231&key=user_uploads/825709/1d06fb3a-336e-4c6f-b93a-ce38f4a0a6f1)\n\n**Features**\n\n📚 Database: Write queries in natural language and let Deekard translate them into SQL for you! Simply state your query, and you'll receive the result table.\n\n🐍 Python: Transform data or apply machine learning models with ease. Just write your request, and Deekard translates it into Python code and executes it. You'll get the results in no time.\n\n📊 Visualization: Generate charts with natural language. Deekard translates your request into Vega-Lite specifications and creates beautiful visualizations. Apply changes to charts just by writing them down.\n\n🧠 Wikipedia: Enrich your datasets by retrieving tables from Wikipedia. Just write your request, and Deekard will access the world's greatest knowledge base for you.\n\n🎯 Task Organization: Write complex requests, and Deekard will split them into multiple tasks that are executed in the right order.\n\n**Start Today**\n\nYou can start using Deekard today at [deekard.com](http://deekard.com). \n\nThank you for your support, and we look forward to hearing your thoughts on Deekard! 🎉",
        "url": "https://www.ycombinator.com/launches/IWt-deekard-your-autonomous-assistant-for-data-science-and-analytics",
        "votes": 13,
        "created_at": "2023-04-27T14:07:14.366Z"
      }
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    "id": 26783,
    "name": "Raven",
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    "website": "https://startraven.com",
    "all_locations": "Bengaluru, KA, India",
    "long_description": "At Raven, we are building AI assistants for manufacturing plants which can offer intelligent assistance for day-to-day operations like training, job planning, troubleshooting, reporting and also helps with real-time analytics — all while seamlessly integrating with your existing systems.\r\nWe’re taking decades of manufacturing expertise and combining it with AI to solve real operational problems. We’re a small, focused team working to make industrial operations safer, smarter, and more efficient.",
    "one_liner": "AI Assistants for Manufacturing Operations",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1657470086,
    "tags": [
      "AI-Enhanced Learning",
      "Manufacturing",
      "AI",
      "AI Assistant"
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    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2022",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
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    "regions": [
      "India",
      "South Asia",
      "Remote",
      "Partly Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/raven",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2022/raven.json",
    "year_founded": 2021,
    "city": "Bengaluru",
    "country": "IN",
    "linkedin_url": "https://www.linkedin.com/company/raven-ai-labs",
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    "primary_partner": {
      "name": "Gustaf Alstromer",
      "url": "https://www.ycombinator.com/people/gustaf-alstromer"
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    "founders": [
      {
        "user_id": 584996,
        "full_name": "Priyansh Srivastava",
        "title": "Founder",
        "founder_bio": "Co-founder @ Raven. ",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/priyanshs",
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      },
      {
        "user_id": 570729,
        "full_name": "Sriyansh Srivastava",
        "title": "Founder",
        "founder_bio": "Co-founder at Raven",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/sriyansh7",
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    "launches": [
      {
        "id": 65513,
        "title": "🔔 Raven - A single API for product notifications across SMS, Email, Push, WhatsApp, Slack & more",
        "tagline": "We make it easy for businesses to manage all the multi-channel notifications they send to customers.",
        "body": "**TL;DR** Raven gives businesses a central platform to manage product notifications across SMS, Email, Push, WhatsApp, Slack & more. We do this by connecting 40+ providers like Twilio, SendGrid, Firebase with a single API and giving a central dashboard on top to design & monitor all notifications.\n\n```\n\n```\n\n**📝Book a demo** [**here**](https://calendly.com/priyanshs/platform-demo) **to learn more.**\n\nHey everyone - We’re Priyansh and Sriyansh (yes, we are brothers!) and we would love to tell you about [Raven](https://www.raven.dev).\n\n### 🚫THE PROBLEM\n\nBusinesses spend a lot of resources managing product notifications (think due-date reminders or verification codes). For example to send a payment reminder via SMS, Email & WhatsApp, you have to integrate multiple provider APIs like Twilio, SendGrid, then orchestrate channels basis user preferences and finally send the correct template on-time. The problem is -\n\n* Since each notification has it’s own set of templates & configurations, it becomes complex & time consuming to make any changes.\n* There’s no central visibility as the data is spread across multiple messaging providers. It is a pain for product teams to pull it from 5-6 diff sources, standardize and then analyze them.\n* Ensuring deliverability is a challenge. Some messages like OTPs are critical and their delivery failures lead to huge business losses.\n\n### 🎁OUR SOLUTION\n\nA central platform that brings all your messaging channels & providers in one place, where you can orchestrate and analyze them - all without engineering.\n\n* A single API to send notifications across channels via any of the 40+ providers like Twilio, SES, Firebase, Messagebird, Gupshup.\n* A dashboard gives central visibility on all templates, logs & delivery metrics allowing product teams to optimize CX by analyzing what works and what doesn’t, reduce redundant messages and thereby saving tons of money.\n* Reduces business risk by effectively managing delivery failures using failovers/retries across channels & providers.\n\n### \n\n![uploaded image](/media/?type=post&id=65513&key=user_uploads/584996/91936c0b-0457-43f0-9746-5eee037fcebf)\n\n### 💡WHY WE BUILT THIS\n\nWe’ve previously built the notification infrastructure for Apna (India’s fastest unicorn) & OkCredit (YC S18), and didn’t want any other engineer to go through the same pain as we did. It was not only us, but companies like LinkedIn, Netflix, AirBnB spend $10s of millions/yr with a 10-30 member engineering & product team which just does notifications 🤯.\n\n### 🤑 OFFER + ASK✨\n\n50% off first 3 months for startup community - email [founders@ravenapp.dev](mailto:founders@ravenapp.dev) to redeem\n\n**🥳 We’d love to talk to you -**  [**book a demo**](https://calendly.com/priyanshs/platform-demo) **with us today!**",
        "url": "https://www.ycombinator.com/launches/H2f-raven-a-single-api-for-product-notifications-across-sms-email-push-whatsapp-slack-more",
        "votes": 76,
        "created_at": "2022-08-20T19:48:21.781Z"
      }
    ]
  },
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    "id": 26792,
    "name": "Activepieces",
    "slug": "activepieces",
    "former_names": [],
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    "website": "https://www.activepieces.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Activepieces is an open-source (MIT) business automation software.\r\nFor example, you can build automations to receive email and Slack notifications about new contacts add to your HubSpot CRM.",
    "one_liner": "Open-source, AI-first and no-code business automation tool",
    "team_size": 10,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1657116357,
    "tags": [
      "Workflow Automation",
      "Open Source",
      "No-code",
      "Enterprise Software",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2022",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Partly Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/activepieces",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2022/activepieces.json",
    "year_founded": 2022,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/activepieces/",
    "x_url": "https://twitter.com/activepieces",
    "fb_url": "https://www.facebook.com/activepieces",
    "cb_url": "https://www.crunchbase.com/organization/activepieces",
    "github_url": "https://github.com/activepieces/activepieces",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/0e3da00ac0f6b66a7e896be53679d01b6fe5fd45.png",
    "app_video_url": null,
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    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
    },
    "founders": [
      {
        "user_id": 138932,
        "full_name": "Ashraf Samhouri",
        "title": "Founder/CEO",
        "founder_bio": "Ended up responsible for growing our ARR so I guess I do sales from the perspective of a software engineer, on a mission to make AI a native part of enterprise through open source automation (aka Activepieces)",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/ashrafsam",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e91e5e9ed7c7a1da6530ccd4dee552e196bbfe3d.jpg"
      },
      {
        "user_id": 724168,
        "full_name": "Mohammad AbuAboud",
        "title": "Founder/CTO",
        "founder_bio": "I love building cool stuff. Started programming at 13 and never looked back—turns out, breaking things is the fastest way to learn.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/mohammad-abuaboud/",
        "x_url": "https://mobile.twitter.com/mabuaboud",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b9a11f094d4568c74704be4223fe03b4eeeac74e.jpg"
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    "launches": [
      {
        "id": 68665,
        "title": "Activepieces – Open source alternative to Zapier",
        "tagline": "No-code business automation that is open-source and can be self-hosted.",
        "body": "**tl;dr** You can now host an equivalent software to Zapier to automate your work. You can automate your sales process, marketing operations or back-office without writing code (or with, if you’d like to).\n\n—\n\nHi everyone!\n\nWe're [Mohammad](https://www.linkedin.com/in/mohammad-abuaboud/) (ex-Google) and [Ashraf](https://www.linkedin.com/in/ashrafsam) (3x founder), and here is what we’re building 👇\n\n### 💔 **Problem**\n\nIt can quickly get **too expensive 💰** to use automation tools like Zapier, and if you can’t or hate to **send your data to 3rd parties** [**🔒**](https://emojipedia.org/locked/) it’s already challenging to use these tools.\n\n### 🕺 **Our Product**\n\nActivepieces is a no-code business automation tool. It’s open-source (MIT licensed) and can be self-hosted on your servers.\n\nHere is a 2-min video by our founding engineer Abdul, who’ll explain how to automate sending notifications about a new **Pipedrive** Person to **Slack** and **Email**.\n\nhttps://www.youtube.com/watch?v=IY4TI6jGBwM\n\n### ❇️ **Difference from Zapier**\n\nWhile Zapier offers a cloud service, Activepieces is:\n\n1. **Self-hosted:** You can keep your data on your servers (helpful for data privacy).\n2. **Open-source:** the platform and the connectors (don’t wait for us to build the connector).\n3. **Free** (helpful for .. your pocket).\n\n### 🖌️ **Use Cases**\n\nWe’re working with some users at companies to:\n\n* Automate lead flow: from blogs to MailChimp and CRMs.\n* Centralize notifications: from marketing/sales to Slack workspace.\n* Automate operations: a company is using us to convert pdfs to text, summarize them and submit them to their proofreading team.\n\n### 🟢 **Status**\n\nWe just launched with **15 apps** including OpenAI, HubSpot, MailChimp, Stripe, Pipedrive, Gmail, SendGrid — and adding more.\n\nOur focus is to build the free product and the community around it. Later, we’ll make money from enterprise features.\n\n### 🙏 **Our Ask**\n\nYou can try out Activepieces on the [Playground](https://demo.activepieces.com/sign-up?utm_source=launch&utm_medium=post&utm_campaign=launch_yc) and we’ll be happy if you give us a star ⭐ on our [GitHub repo](https://github.com/activepieces/activepieces)!\n\n### 🖇️ **All links**\n\n* Website: [www.activepieces.com](http://www.activepieces.com?utm_source=launch&utm_medium=post&utm_campaign=launch_yc)\n* Github repo (star us maybe?😳❤️): [https://github.com/activepieces/activepieces](https://github.com/activepieces/activepieces?utm_source=launch&utm_medium=post&utm_campaign=launch_yc)\n* Playground: [https://demo.activepieces.com](https://demo.activepieces.com/sign-up?utm_source=launch&utm_medium=post&utm_campaign=launch_yc)\n* Community (Discord): https://discord.gg/2jUXBKDdP8\n\nI’ll be happy to help anyone get set up (or grow out of Zapier): [founders@activepieces.com](mailto:founders@activepieces.com)",
        "url": "https://www.ycombinator.com/launches/HrV-activepieces-open-source-alternative-to-zapier",
        "votes": 45,
        "created_at": "2023-01-24T18:10:00.535Z"
      }
    ]
  },
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    "id": 26811,
    "name": "Payload",
    "slug": "payload",
    "former_names": [
      "Payload CMS"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0f0a550c10525505849576c534b00a71c9d71c7e.png",
    "website": "https://payloadcms.com",
    "all_locations": "Grand Rapids, MI, USA",
    "long_description": "Payload is a developer-first headless CMS and application framework built to finally give developers a better choice in the world of CMS. From documentation to design, Payload is crafted from the ground-up to save engineers time and effort while building the backend and admin panel for websites, native apps, ecommerce, SaaS, and any other product that needs to manage content. Payload is changing the CMS status quo—working to give developers the tools they want to build the CMS they need, all in clean and well-structured code.\r\n\r\nLearn more at https://payloadcms.com.",
    "one_liner": "Developer-First Headless CMS and Application Framework",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1652737017,
    "tags": [
      "Developer Tools",
      "Open Source",
      "API"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2022",
    "status": "Acquired",
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      "Partly Remote"
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    "stage": "Early",
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/payload",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2022/payload.json",
    "year_founded": 2018,
    "city": "Grand Rapids",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/payload-cms",
    "x_url": "https://twitter.com/payloadcms",
    "fb_url": "https://www.facebook.com/payloadcms",
    "cb_url": "https://www.crunchbase.com/organization/payload-cms",
    "github_url": "https://github.com/payloadcms",
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    "founders": [
      {
        "user_id": 969037,
        "full_name": "James Mikrut",
        "title": "Founder",
        "founder_bio": "James Mikrut is the founder and CEO of Payload CMS. He plays a leading role in shaping the future and vision of Payload, and is responsible for product design, marketing initiatives, and user experience design. He has been a full-stack engineer for over a decade, and has also founded the digital design agency TRBL, where he leads a team of user experience designers and full-stack TypeScript developers.",
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        "linkedin_url": "https://www.linkedin.com/in/james-mikrut-3202985a/",
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        "user_id": 969459,
        "full_name": "Elliot DeNolf",
        "title": "Founder",
        "founder_bio": "Elliot DeNolf is founder and CTO of Payload CMS. He has worked extensively in design, development, and delivery of large, distributed, back-end services. His specializations include resilient, high-availability web services, containerization technologies, and CI/CD pipelines.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/elliotdenolf",
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      {
        "user_id": 969253,
        "full_name": "Dan Ribbens",
        "title": "Founder",
        "founder_bio": "Dan Ribbens is founder and COO of Payload CMS, the best TypeScript CMS for developers. He has focused on database engineering and developer experience. While at Payload and throughout his career Dan has served as a senior developer, team lead, and architect for dozens of software teams. Dan earned his Masters in Computer Science at GVSU in 2013 and worked as a freelance consultant prior to Payload.",
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        "title": "Payload raises $4.7M for its developer-first headless CMS • TechCrunch",
        "url": "https://techcrunch.com/2022/11/15/payload-raises-4-7m-for-its-developer-first-headless-cms/",
        "date": "Nov 15, 2022"
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      {
        "id": 64122,
        "title": "Payload — A Developer-First Content Management System",
        "tagline": "We're obsessed with giving engineers the best developer experience possible as they build APIs and admin UI.",
        "body": "Hey YC,\n\nJames, Dan, and Elliot here. We’re three full-stack TypeScript devs that got tired of feeling like second-class citizens when it comes to content management systems—so we built Payload.\n\n[**Payload**](https://payloadcms.com) is a truly dev-first, headless content management system aimed sharply at giving engineers the best development experience possible in a noisy ecosystem of tools that often disregard the importance of quality, clean, extensible code.\n\n![uploaded image](/media/?type=post&id=64122&key=user_uploads/969037/ca9a0712-e89c-4aaa-b63b-7b325f8ffbbb)\n\n### The Problem\n\nTo developers, “content management system” is a swear word.\n\n* Devs want to build cutting-edge products that are structured effectively to deliver elegant solutions to their business needs.\n* Modern teams want to write code in modern languages like TypeScript and React, but most CMS are built with legacy tech and have lasted long past their shelf life.\n* You will often hit roadblocks with other CMS, and many SaaS options “black-box” functionality away, meaning developers can never truly own their own code.\n* Devs often undervalue the power that a good CMS _could_ represent. Even web and native apps generally need to manage “content”, like orders, requests, users, profiles, and more—but often, developers roll their own systems for these apps. Time is wasted and the wheel is reinvented from scratch every time.\n\nBuilding a project that needs a CMS shouldn’t be a dreaded task for modern developers.\n\n### Payload is...\n\n**A CMS that is obsessed with giving engineers the best developer experience possible to build out APIs and admin UI.** It catapults developers' efficiency and value by delivering an extensible REST and GraphQL API as well as a beautiful React admin panel for non-technical users to manage content—all in TypeScript.\n\nFrom docs to design, it's staunchly code-first, but uncompromising in admin experience. Developers finally have a tool to deliver their admins with a CMS that is beautiful, minimal, extensible, and usable. It can power the backend for websites of all sizes, ecommerce, SaaS, native apps, and more.\n\n**Tech specs:**\n\n* Completely open-source\n* [Fully self-hosted](https://payloadcms.com/docs/production/deployment)\n* [GraphQL](https://payloadcms.com/docs/graphql/overview), [REST](https://payloadcms.com/docs/rest-api/overview), and [Local](https://payloadcms.com/docs/local-api/overview) APIs\n* [Customizable ReactJS Admin](https://payloadcms.com/docs/admin/overview)\n* [Extensible authentication](https://payloadcms.com/docs/authentication/overview)\n* [Local file storage & upload](https://payloadcms.com/docs/upload/overview)\n* [Field-based localization](https://payloadcms.com/docs/configuration/localization)\n* [Block-based layout builder](https://payloadcms.com/docs/fields/blocks)\n* [Extensible SlateJS rich text editor](https://payloadcms.com/docs/fields/rich-text)\n* [Array field type](https://payloadcms.com/docs/fields/array)\n* [Field conditional logic](https://payloadcms.com/docs/fields/overview#conditional-logic)\n* Extremely granular [Access control](https://payloadcms.com/docs/access-control/overview)\n* [Document and field-level hooks](https://payloadcms.com/docs/hooks/overview) for every action Payload provides\n* Built with Typescript & very Typescript-friendly\n* Highly secure thanks to HTTP-only cookies, CSRF protection, and more\n\n### What customers say\n\n* \"This product is a developer's dream come true in the world of CMS.\" - Developer, NYC, USA - 12 Oct 2021\n* \"CMS used to be something dreadful, now it's starting to feel right.\" - Developer, London, UK - 31 Mar 2021\n* “Started looking into headless CMS options... Payload was a clear winner.” - Developer, Berlin, Germany - 24 June 2021\n\n### Who we are\n\nWe're three full-stack engineers that have built digital projects with existing CMS for over a decade—including enterprise websites for big names like Klarna. We knew what we wanted, but also intimately knew it didn't exist—so we built it.\n\n### Ask for YC\n\n**Have a GitHub account? Stop by our repo and** [**give us a star**](https://github.com/payloadcms/payload)**!**\n\nIf you're building a digital product that needs to manage content, give Payload a shot by running **npx create-payload-app**.\n\nDo we provide the features and the experience that your dev team is looking for? We'd love to know what you think.\n\n### Find us online\n\n* [GitHub](https://github.com/payloadcms/payload)\n* [Twitter](https://twitter.com/payloadcms)\n* [LinkedIn](https://www.linkedin.com/company/payload-cms/)",
        "url": "https://www.ycombinator.com/launches/GgE-payload-a-developer-first-content-management-system",
        "votes": 87,
        "created_at": "2022-06-28T00:51:30.828Z"
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    "all_locations": "Singapore, Singapore; Remote",
    "long_description": "Mistle is the open source alternative to Stripe Minions, Ramp Inspect and Shopify River. Instead of spending months building an internal platform, teams use Mistle to run collaborative background agents from day one.",
    "one_liner": "Open source background agents",
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        "full_name": "Jonathan Low",
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        "full_name": "Thomas Jiang",
        "title": "Founder",
        "founder_bio": "Thomas is the co-founder of Mistle.\n\nPrior, Thomas worked as engineer no. 2 in a B2B startup selling enterprise compliance software which was acquired.",
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        "title": "Honestbee co-founder’s new startup joins Y Combinator",
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        "date": "Jun 07, 2022"
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      {
        "id": 65425,
        "title": "🌊 Ajourney - Gusto for South East Asia (SEA)",
        "tagline": "Run payroll with one-click",
        "body": "Hi YC! We’re [Jonathan](https://bookface.ycombinator.com/user/878905), [Thomas](https://bookface.ycombinator.com/user/981080) and [Cayter](https://bookface.ycombinator.com/user/1005416).\n\n[**Ajourney**](https://ajourney.io) **is building Gusto for South East Asia (SEA).**\n\n### The Problem\n\nRunning payroll is a very repetitive activity. We’ve identified 3 areas that can be better.\n\nFirst, most payroll software in SEA act as a calculator to calculate compliance contributions but do not automate the other aspects of running a payroll such as:\n\n* Collection of attendance or commissions data for salary computation\n* Handling payments through bank and government portals\n\nSecond, hiring of remote contractors in SEA is increasing with greater adoption of remote working tools for small businesses. Manual payments have to be made separately from payroll.\n\nThird, businesses growing regionally in SEA usually outsource payroll as they do not want to build internal competency in payroll compliance for every market.\n\n### Our Approach\n\nAjourney helps businesses to manage their payroll end-to-end from data collection to disbursements, compliance filings and payments.\n\nWe reduce repetitiveness and time spent on payroll through integrations and workflow automation.\n\nBesides software, we offer customer support to help companies on their payroll compliance needs. Customers can enjoy the benefits of both in-sourced payroll and outsourced payroll through a single offering.\n\nWe are currently building our product for the Singapore market and will expand to more markets at a later date.\n\n![](https://ajourney.io/images/landing-page-payroll-9b16a6258953508db851b28b694af76a.png?vsn=d)\n\n## Our Team\n\nWe are 3 technical co-founders and can relate to the problem well because of previous pains we have experienced.\n\nI previously co-founded a groceries delivery startup in SEA. Payroll was messy - we outsourced and always had difficulty getting a consolidated view across markets.\n\nThomas worked with small medium businesses in a previous startup and saw the struggles of business owners running payroll manually on spreadsheets.\n\nCayter has wide exposure into payments and has seen the challenges and costs in handling payments across borders.\n\n### Our Asks\n\nIf you:\n\n\\- Are based in Singapore\n\n\\- and/or hire contractors remotely\n\n\\- and/or have expanded regionally\n\nWe’ll love to speak to you to understand how you are handling your payroll.\n\nIf you can make referrals to potential customers in Singapore, we will really appreciate it!\\\nDrop us a note at [founders@ajourney.io](mailto:founders@ajourney.io)\n\nThank you!",
        "url": "https://www.ycombinator.com/launches/H1F-ajourney-gusto-for-south-east-asia-sea",
        "votes": 25,
        "created_at": "2022-08-17T05:46:25.934Z"
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    "long_description": "Diversion is a modern alternative to Perforce and Git, designed for digital entertainment industries like games, virtual production, animation, and 3D/VR. It streamlines collaboration by providing GitHub-like version control for large files and complex projects, integrating seamlessly with tools like Unreal Engine. Built for studios handling massive assets, Diversion ensures efficient workflows, secure storage, and effortless tracking of project history, making it the go-to platform for creative teams managing evolving digital content.",
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    "team_size": 14,
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    "year_founded": 2021,
    "city": "Tel Aviv-Yafo",
    "country": "IL",
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      "name": "Nicolas Dessaigne",
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      {
        "user_id": 1014744,
        "full_name": "Sasha Medvedovsky",
        "title": "Founder",
        "founder_bio": "A software engineer, engineering manager and product manager with 20+ years of experience.\nServed as an officer in an elite Israeli cyber-intelligence unit (8200).\nCo-founded Leprechaun (bootstrapped to high profitability, sold in 2012) and Adience (sold in 2015).\nMSc. in Computer Science and MBA from Tel Aviv University, cum laude.",
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    "id": 27172,
    "name": "Clearline",
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    "website": "https://useclearline.com",
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    "long_description": "Clearline is the AI operating system that captures, routes, and converts every revenue opportunity across your dealership without adding headcount.",
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    "team_size": 5,
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        "full_name": "Adi Patel",
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        "user_id": 970753,
        "full_name": "Abhi Patel",
        "title": "Founder",
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        "title": "Led by former Ada employees, Lancey secures $2 million to let B2B software buyers “try before you buy” | BetaKit",
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        "date": "Dec 05, 2022"
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        "id": 99746,
        "title": "Clearline | AI native revenue engine for automotive",
        "tagline": "Clearline deploys AI agents that answers every inbound call, follows up on every lead, and tracks every customer interaction for car dealerships, 24/7.",
        "body": "Hey everyone! We're Adi and Abhi, the founders of Clearline.\n\n![uploaded image](/media/?type=post&id=99746&key=user_uploads/942902/e3dbee2c-c4a0-4485-ad87-4509317bb2c9)\n\n### The Problem\n\nCustomer experience at car dealerships is broken. Not because the teams don't care, but because the systems were never built for how customers actually behave today.\n\nHere's the reality:\n\n* **23% of dealership calls go unanswered.** 85% of those callers never call back. That's revenue walking out the door every single day.\n* **Most lead follow-up dies by day 5.** Dealerships spend thousands driving traffic and generating leads, then let them rot in a CRM nobody checks.\n* **Sales uses one system. Service uses another. Nobody has the full picture.** Reps waste time on manual logging, managers guess at what's happening, and customers repeat themselves every time they call.\n\nDealerships have tried to solve this with more tools, more staff, more process. It doesn't work. The stack is fragmented and nothing talks to each other.\n\n### The Solution\n\nClearline is an AI-native operating system for dealerships. Three products, one platform:\n\n**Inbound** - AI answers every sales and service call instantly. No voicemail, no hold music, no transfers. It qualifies intent, routes to the right department, and books appointments in real-time. 24/7, including nights and weekends.\n\n**Outbound** - Automated follow-up via calls, texts, and email. Clearline responds to new inquiries within seconds and runs disciplined cadences from day 1 through day 90. No lead gets forgotten.\n\n**CRM** - One unified record across sales, service, and BDC. Full call transcripts, automatic logging, next steps triggered without anyone typing a note. Managers get complete visibility with real data.\n\n![uploaded image](/media/?type=post&id=99746&key=user_uploads/942902/dd50c407-f1a1-4910-b1c3-7124bd3e294b)\n\n### Results\n\nDealerships see this in their first 30 days:\n\n* **$60K+ revenue recovered** from missed calls and dead leads\n* **240% more leads engaged**\n* **4+ tools consolidated** into one platform\n\n> _\"Recovered $78K in service and sales revenue from 400 missed calls per month._\n\n> _\"Show rate on outbound appointments went from 38% to 64% in the first month._\n\n### You're Always in Control\n\nThis isn't about replacing dealership staff. Clearline augments your team:\n\n* AI escalates to a human anytime a situation needs real judgment\n* It only operates within rules you define (hours, routing, boundaries)\n* It only uses dealership-approved responses for pricing and policies\n* Every call, message, and booking is logged and reviewable\n\n### Try Clearline\n\nIf you run a dealership or know someone who does, we'd love to chat.\n\n[Book a demo](https://useclearline.com/?utm_source=yc&utm_medium=launch&utm_campaign=launch_yc)\n\nReach us directly at [founders@useclearline.com](mailto:founders@useclearline.com) or check us out at [Clearline](https://useclearline.com/?utm_source=yc&utm_medium=launch&utm_campaign=launch_yc)",
        "url": "https://www.ycombinator.com/launches/Pwo-clearline-ai-native-revenue-engine-for-automotive",
        "votes": 6,
        "created_at": "2026-04-14T21:10:47.506Z"
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      {
        "id": 95485,
        "title": "Lancey - connect your customer signals to your codebase",
        "tagline": "Every AI coding tool writes code. Lancey helps you decide what to buid.",
        "body": "### **TL;DR**\n\nMost teams know what their customers want. It’s buried in Slack threads, support tickets, and calls. But turning that into shipped code still takes months.\n\nLancey is the first autonomous coding agent that builds what your customers want.\\\nIt listens to your customer channels, understands your codebase, and ships ready-to-merge PRs, all in the background.\n\nhttps://youtu.be/1g76HQkrdyQ\n\n---\n\n### **The Problem**\n\nCustomer feedback already tells you exactly what to fix or build. The issue isn’t knowing _what_ to do, it’s the manual steps between understanding and shipping.\n\nSupport tickets, Slack threads, and bug reports pile up. Engineers spend hours triaging. Product teams chase context. PMs and devs are stuck in loops instead of shipping.\n\nEven AI coding assistants today still need you to _prompt_ them, _explain the bug_, and _review every output_. It’s still work, just faster typing.\n\n---\n\n### **Why Lancey Exists**\n\nWe built Lancey because we think software should respond directly to its customers. Without human bottlenecks.\n\nLancey continuously scans your customer channels and codebase to spot high-impact bugs or requests. When it’s confident, it drafts and submits a PR. When it’s unsure, it asks for review.\n\nNo tickets, no triage, no context handoffs. Just a system that quietly keeps your product aligned with your users.\n\n---\n\n### **How It Works**\n\n* **Understands your customer context** - Connect Slack, Zendesk, Intercom, and more.\n* **Understands your code** - Builds a deep map of your repositories and dependencies.\n* **Builds autonomously** - Drafts fixes, features, and improvements as ready-to-merge PRs.\n* **Collaborates by default** - Keeps engineers and PMs in the loop so nothing feels like a black box.\n\n---\n\n### **Who It’s For**\n\nEngineering and product teams who want to spend less time triaging and more time shipping what actually matters to customers.\n\n---\n\n### **Why Now**\n\nWe’ve reached a point where LLMs can not only reason over customer data, they can write safe, context-aware code. The missing piece is connecting these two worlds.\n\nLancey makes **customer-driven engineering autonomous**.\n\n# **How you can get access**\n\n* Sign up for a free account [here](https://lancey.ai)",
        "url": "https://www.ycombinator.com/launches/Oq5-lancey-connect-your-customer-signals-to-your-codebase",
        "votes": 10,
        "created_at": "2025-11-13T16:04:17.494Z"
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    "id": 27174,
    "name": "Monterey AI",
    "slug": "monterey-ai",
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    "website": "http://www.monterey.ai",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "Monterey AI helps companies understand what actions to take to improve engagement and reduce churn by setting up user feedback channels, auto-collecting, and analyzing qualitative feedback and quantitative data from multiple sources.",
    "one_liner": "Turn user feedback to product insights",
    "team_size": 6,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1656519896,
    "tags": [
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    "batch": "Summer 2022",
    "status": "Acquired",
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      "America / Canada",
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    "url": "https://www.ycombinator.com/companies/monterey-ai",
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    "year_founded": 2022,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/monterey-ai",
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    "primary_partner": {
      "name": "Harj Taggar",
      "url": "https://www.ycombinator.com/people/harj-taggar"
    },
    "founders": [
      {
        "user_id": 809138,
        "full_name": "Chun Jiang",
        "title": "Founder",
        "founder_bio": "Chun is the co-founder and CEO of Monterey AI. Previously led products and design at companies like Unfolded (acquired by Foursquare), Scale AI, and Uber. Chun graduated from Cornell in 2018, and has been obsessed with building the most ambitious and delightful Data and AI products in productivity, developer tooling, and autonomous vehicles. ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/chunonline/",
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    ],
    "jobs": [],
    "news": [
      {
        "title": "7 AI startups that stood out in YC's Summer '22 batch",
        "url": "https://techcrunch.com/2022/09/08/7-ai-startups-that-stood-out-in-ycs-summer-22-batch/",
        "date": "Sep 08, 2022"
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    "launches": [
      {
        "id": 80330,
        "title": "🌟 Monterey AI 2.0: AI-native user insights platform — feedback, survey, roadmap, and more",
        "tagline": "The easiest way to aggregate, conduct, triage, and analyze user feedback across support tickets, transcripts, and social media mentions",
        "body": "**TL;DR**\n\nAggregate, triage, and analyze user feedback, tickets, conversations, surveys, and transcripts - smarter, together, and at scale. [Monterey AI](https://monterey.ai) is the most powerful AI native insights platform for decoding the voices of customers and the next growth opportunities.\n\n# [**⭐ Click here to book a demo call ⭐**](https://cal.com/chunonline/monterey-demo)\n\n![uploaded image](/media/?type=post&id=80330&key=user_uploads/809138/ef5f3408-f42f-413f-a1f0-cf5d659ecd44)\n\n**🤕 Problem**\n\nAlmost all customer conversations in all customer channels have enormously valuable user insights that have never been mined to their full potential. Most companies are not utilizing them enough; this damages the speed of decision-making and slows down execution. Breaking down the problem into three key issues:\n\n* Support tickets, transcripts, and surveys are extremely messy (format, scale, and cadence);\n* Too much noise to filter - everyone wants to listen to users more, but listening at scale is hard;\n* It’s high-stakes decision-making and has a low-risk tolerance towards hallucination.\n\n# [**⭐ Click here to book a demo call ⭐**](https://cal.com/chunonline/monterey-demo)\n\n**🎉 Solution**\n\nWith Monterey AI, you can connect with data sources like **Zendesk, Front, Intercom, Gong, Salesforce, HubSpot, App Store, Google Play Store, and Snowflake, in one click or via API**. Monterey AI automatically extracts, categorizes, and triages the conversations based on company or business concepts.\n\n* **Proactive insights delivery:** Instant, accurate answers. It’s an AI Analyst proactively delivering insights to the team, and it’s an instant always-on copilot to help you fetch relevant data and navigate noises.\n* **All-in-one experience management:** feedback analytics is just part of the platform, you can also mix and match other ai first solutions that we provide as part of the package: widget, a roadmap with AI suggestions, personalized customer communications, and AI semi-moderated user survey.\n\n![uploaded image](/media/?type=post&id=80330&key=user_uploads/809138/71a5de43-a44f-4d40-a79c-315cbca311b1)\n\n![uploaded image](/media/?type=post&id=80330&key=user_uploads/809138/01f894a5-4c6e-4648-ae59-0770865d0f50)\n\n![uploaded image](/media/?type=post&id=80330&key=user_uploads/809138/226cf965-9910-487f-a838-1eba71956e65)\n\n![uploaded image](/media/?type=post&id=80330&key=user_uploads/809138/a749c106-784e-4b9c-83f1-c771dd94cd04)\n\n**👀 Comparing Monterey AI to other Solutions**\n\n* **Onboarding & adoption:** Analytics product notoriously has the challenge of onboarding; you are onboarding the data, the user, and the organization. Monterey AI has all native integration with data sources like Zendesk, Front, Intercom, Salesforce, HubSpot, and a robust API platform to directly pull data from your data warehouse. It assures the easiness of data onboarding, and on the other side, the speedy and sleek user experience of the platform makes sure this is something users can get value, right away.\n* **Clear ROI and Performance:** In the most recent case study, we **save one department in the organization 3,840 manual hours annually in total**. \n* **Security and privacy:** The way to evaluate AI solutions for highly sensitive data is different.\n* **Auto improving from user interactions and data:** We invest significant time and resources in making sure the platform is scalable and adaptable to your business and needs. Every new data point and interaction you perform in the workspace is directly fed into the model sets for you with auto improvement. You don’t need to depend on giant model improvement, bear any risk from “human annotation” services from vendors, and spend extra internal engineering resources making it work.\n\n# [**⭐ Click here to book a demo call ⭐**](https://cal.com/chunonline/monterey-demo)",
        "url": "https://www.ycombinator.com/launches/Kte-monterey-ai-2-0-ai-native-user-insights-platform-feedback-survey-roadmap-and-more",
        "votes": 120,
        "created_at": "2024-04-22T17:39:43.610Z"
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      {
        "id": 64189,
        "title": "🐳 Monterey - Co-pilot for product development",
        "tagline": "Monterey boosts and guards product velocity for hyper growing teams, smartly.",
        "body": "👋 [Chun](https://www.linkedin.com/in/chunonline/) and [Ben](https://www.linkedin.com/in/benmkramer/) here introducing [Monterey AI](https://www.monterey.ai/) to you!\n\n### **TL;DR:**\n\n🐳 Monterey is building the **co-pilot for product development**. We do this by replacing documents with smart use-case-centric workflows that help you strategize, measure, and align.\n\n### **Who is it for**\n\nProduct leads (whether a founder, engineer, product manager, designer, etc.) who are looking to escape from burdensome documents and get back to what they are good at. No more spending hours and days on\n\n1. looking for best practice of product development online\n2. convincing your team to adopt the process\n3. repeatedly communicating and reporting strategies and progress\n4. worrying about cross-team dependencies\n5. managing several products in numerous documents and task management tools\n\n### **How it works**\n\n1. Pick a product template based on your use case\n2. Configure input and share with your team\n3. Check dependencies and solve conflicts\n4. Run, report, retro, and repeat\n\n![uploaded image](/media/?type=post&id=64189&key=user_uploads/809138/4340dbb8-f79a-485a-894f-8f044aeb2498)\n\n### **Why we built it**\n\n💪 We started Monterey AI to solve a problem that we’ve experienced at startups ranging from 10 to 10,000 people: **the product velocity gets slow and inefficient as company scales.** We built Monterey to\n\n1. Get teams out of verbose documents and into guided **workflows** that can be visually configured and shared\n2. Speed up product development by exposing and sharing **best practices**\n3. Discover cross-team conflicts and dependency by running **Monterey Bot**\n4. Initiate outcome driven conversations with **slack integration**\n5. Provide a birds eye **portfolio view** to align across features, products, and teams\n\n### **Can I try it**\n\n1. Want to try it? Sign up on [the website](https://www.monterey.ai/) or email ([chun@monterey.ai](mailto:chun@monterey.ai)) and we’ll help you get started!\n2. Have feedback or have friends in need of Monterey? Come be our super design, [join our Slack](https://join.slack.com/t/monterey-ai/shared_invite/zt-1ajkx4ur4-up_0R7TR_I4B9md29c5xbg), and [follow us on Twitter](https://twitter.com/montereyai)!\n3. 🎁 50% off any paid plan if subscribed annually before Sep.1st, 2022.",
        "url": "https://www.ycombinator.com/launches/GhJ-monterey-co-pilot-for-product-development",
        "votes": 111,
        "created_at": "2022-06-29T19:08:43.808Z"
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    "website": "https://movinglake.com",
    "all_locations": "Mexico City, CDMX, Mexico; Remote",
    "long_description": "MovingLake is Fivetran for event-driven architectures. Companies such as Casai use our product to obtain orders and price changes in real time.",
    "one_liner": "Realtime Data Connectors",
    "team_size": 3,
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    "country": "MX",
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        "full_name": "Andres Paez",
        "title": "Founder",
        "founder_bio": "Worked as a Software Engineer and Product Manager at Amazon Prime, Google Search and Google Cloud Platform for about 7 years. Have worked as the CTO of Casai and Valoreo for the last 3 years starting technology teams from scratch leading software engineers, hardware engineers, software managers, data engineers, data scientists, IT professionals, DevOps engineers, product managers and product designers.\n\n",
        "is_active": true,
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        "full_name": "Edgar Cabrera",
        "title": "Founder",
        "founder_bio": "About ten years of Sofware Engineer Experience at startups of several stages. I have worked in developing products from scratch until they become scalable, robust systems. I love the feeling of my work bringing value to others.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/edgarcabrera-dev/",
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        "id": 71150,
        "title": "MovingLake - Vertical-first, realtime, AI-enabled data platform",
        "tagline": "LLM-enabled data connectors, transformations and visualizations for e-commerce, hospitality and more",
        "body": "Hi!\\\n**We are now launching our LLM-enabled BI tool which allows all of our clients to query their databases by using prompts in plain english.**\n\n![uploaded image](/media/?type=post&id=71150&key=user_uploads/200174/8c06ceeb-4d8f-48ac-a152-3535bfb76eb6)\n\nHappy to announce that MovingLake user’s can not only get their data centralized in their data warehouse, but we are now enabling an end-to-end business intelligence experience where in a matter of minutes you can get the data flowing AND get the dashboards going.\n\nThis is important because not all of our clients are friendly with SQL or with BI tools. Letting them access their data in a secure way and using plain english questions is a game changer for them.\n\n**Ask**\n\nWe are looking to integrate to other data connector tools and companies as well as other data products to be able to give the most value faster to our clients. Please reach out if this would be interesting to your company.\\\n\\\nWe are available at [andres@movinglake.com](mailto:andres@movinglake.com) and [edgar@movinglake.com](mailto:edgar@movinglake.com) ",
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        "votes": 17,
        "created_at": "2023-04-24T19:26:45.556Z"
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        "id": 64655,
        "title": "MovingLake: Realtime, event-driven data connectors",
        "tagline": "Proprietary data connectors which feed both data and transactional systems",
        "body": "Hey YC!\n\n[Edgar Cabrera](https://www.linkedin.com/in/edgarcabrera-dev/) and [I](https://www.linkedin.com/in/andrespaezmartinez/) are excited to launch [Moving Lake](https://movinglake.com/) today.\n\n**TLDR: MovingLake aims to do ETLs for event-driven architectures. Power your data warehouse as well as your microservices using the same API connectors.**\n\n### ⚠️ **What’s the Problem?**\n\nAfter talking to dozens of data engineers as well as technology stakeholders, and from our past experience, we uncovered a set of intertwined problems with current data connectors:\n\n1. A data connector does not provide data to transactional systems. This can lead to duplication of integration work plus lack of reliability between different sources of data. For machine learning this can be real trouble\n2. API integrations done in house are flaky and require a lot of investment in development and maintenance\n3. Event-driven architectures are reimplementing over and over again the same pieces of infrastructure such as schedulers, pollers and webhook receivers\n4. Batch extractors can skip states and so end up with missing data. For example if I have a booking business and a reservation gets cancelled 10 minutes after created, the batch pipeline will only see the cancelled state but not the created state.\n5. Running automations and other workflows is impossible with batch data connectors.\n\n### 👍 **What’s the solution?**\n\n**Realtime, event-driven, deduplicated, replayable, ELT friendly and SDK ready connectors which feed both data and transactional systems at the same time.**\\\nWe are rolling out connector for APIs which give you the ability to add any number of destinations including data and backend systems. We provide on top of that transformations for the data side so that you get the data in nicely formatted tables. Plus we also aim to provide easy to use SDKs so that consuming MovingLake’s webhooks is as easy and fast as possible.\\\n\\\n❓ **What’s the ask?**\n\nDo you have recurring issues with data reliability? Do you end up writing batch scripts to recover lost data from webhooks? Do you struggle with running your machine learning models from batch pipeline’s data? Reach out to [founders@movinglake.com](mailto:founders@movinglake.com) or contact us through our [website](https://movinglake.com/contact-us).\\\n\\\nThanks!",
        "url": "https://www.ycombinator.com/launches/Gop-movinglake-realtime-event-driven-data-connectors",
        "votes": 166,
        "created_at": "2022-07-15T16:27:46.974Z"
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    "name": "Sculpt",
    "slug": "sculpt",
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    "year_founded": 2022,
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    "country": "IN",
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        "full_name": "Vidhi Vakharia",
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        "title": "Abridge 🚢  Flexport for India",
        "tagline": "We help importers/exporters ship anything from India in just a few clicks!",
        "body": "Hi, we’re Vidhi and Pradhith, and we’re super excited to introduce Abridge!\n\n### **What is Abridge?**\n\nAbridge is an intelligent logistics partner for importers/exporters who want to ship freight into or out of India. We digitize the full shipment lifecycle (online freight booking, optimized container load plans, automatically generated compliance documents, and online communication channels). We make the lives of importers and exporters easier by:\n\n1. Providing shippers an online freight booker and record-keeper of all shipments.\n\n   ![uploaded image](/media/?type=post&id=65179&key=user_uploads/466754/984e8c45-fef1-4709-8f95-c772a576aa67)\n\n2. Saving shippers money (5-15%!) on every container shipped by providing them with optimized container stuffing plans and minimizing wasted space inside the container.\n\n   ![uploaded image](/media/?type=post&id=65179&key=user_uploads/466754/dc39cc40-f6d6-483e-8b04-8aed92506f0c)\n\n3. Automatically generating all shipping compliance documents, thus saving shippers \\~3-9 emails/shipment in co-ordinating manually generated documents.\n\n   ![uploaded image](/media/?type=post&id=65179&key=user_uploads/466754/5f7390c7-8d4e-412c-97d0-84ce37cc0fdf)\n\n4. Decluttering shippers’ email, messages, and phone lines by providing a shared online workspace for all shipment related communications with easy and intuitive referencing to each shipment.\n\n   ![uploaded image](/media/?type=post&id=65179&key=user_uploads/466754/394747d5-512e-4bd1-808e-357abfa4f95f)\n\n\n### **Whom is Abridge for?**\n\nIf you import/export anything in India, what has been your biggest challenge when shipping goods? Click [here](https://calendly.com/abridge-vidhi/abridge-can-help-30mins?month=2022-08) to tell us!\n\n### **Can you try Abridge?**\n\nYes, we are currently open for shipments into and out of India! You can sign up [here](https://www.abridge.dev/demo) to digitize your India import/export needs!\n\n### **How did we come to build Abridge?**\n\nMy family has been exporting auto-parts from India to the US, France, and Germany for the last thirty years. Although the main business is manufacturing, managing shipping logistics is an unnecessarily high-touch, highly manual overhead in the business’ day-to-day operations.\\\nAdditionally, Pradhith and I also got to experience the tedious logistics around importing products into India while we developed our previous business — an e-commerce retailer in India. Other companies that were suppliers to our e-commerce retailer also said they faced the same issues!\\\nA lot of these issues have digitization and automation solutions, so it’s unnecessary that every importer/exporter has to manage logistics as a separate, highly-involved project in addition to their actual business. Our goal is to be the digital logistics partner that we wanted to partner with when we were running our previous business.",
        "url": "https://www.ycombinator.com/launches/GxH-abridge-flexport-for-india",
        "votes": 39,
        "created_at": "2022-08-06T20:04:56.744Z"
      }
    ]
  },
  {
    "id": 27255,
    "name": "Intuned",
    "slug": "intuned",
    "former_names": [
      "The Metrics Shop",
      "Metrics Shop"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/86c20a802b3a2e0667f7dcdc7fa4c4cb22913691.png",
    "website": "https://intunedhq.com",
    "all_locations": "Seattle, WA, USA",
    "long_description": "Intuned is a code-first browser automation platform with an AI agent that builds and maintains your automations. Developers use Intuned to deploy scrapers, RPAs, and crawlers as production-ready TypeScript or Python projects — with stealth, CAPTCHA solving, proxies, auth, and scheduling handled out of the box. The agent builds projects from a prompt, fixes failed runs, and can self-heal automations autonomously when websites change.",
    "one_liner": "Code-first scrapers and RPAs — built and maintained by AI",
    "team_size": 15,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1657233376,
    "tags": [
      "Developer Tools",
      "Robotic Process Automation",
      "B2B",
      "API",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2022",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Partly Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/intuned",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2022/intuned.json",
    "year_founded": 2022,
    "city": "Seattle",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/82287935",
    "x_url": "https://twitter.com/IntunedHQ",
    "fb_url": "https://www.facebook.com/IntunedHQ/",
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/86c20a802b3a2e0667f7dcdc7fa4c4cb22913691.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": null,
    "founders": [
      {
        "user_id": 224423,
        "full_name": "Faisal Ilaiwi",
        "title": "Founder",
        "founder_bio": "I am a software engineer. I started my career at Microsoft (6.5 years) and then joined UiPath (3.5 years). In UiPath, I had the roles of an Engineering Manager and a Director of Engineering, where I grew my team from 2 to ~20 people within 2.5 years and faced many challenges doing that. We are building Intuned to help ease some of these challenges.\n\nI grow up in Palestine and went to college there; I was then hired to join Microsoft from there.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/faisal-ilaiwi-77356135/",
        "x_url": "https://twitter.com/faisalilaiwi",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c9d0cd0dc50914ae87de900b1688042a650eb194.jpg"
      }
    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 106701,
        "title": "WebSkillet.ai - web automation that gets cheaper every run",
        "tagline": "One API to automate any website. The agent writes code on run 1 and reuses it on every run after - script speed, agent resilience. Try it free at webskillet.ai",
        "body": "**Launch Video: [https://youtu.be/mXxe3P7hMzg](https://youtu.be/mXxe3P7hMzg)**\n\n**\\\nWhat is [Webskillet.ai](http://Webskillet.ai)?**\n\nWebskillet is a single API for web automation - extracting data, downloading files, crawling sites, filling forms, research tasks. You send a task in plain English (plus optional parameters, output schema, and start URL), and an agent executes it in a real browser using code.\n\nThat code is saved as a skillet, and since most web automation is repeat work (the same task on a schedule, or the same task with different parameters), the skillet gets reused on every later run. That's why run 2 can be 4x faster and cheaper than run 1. Here are [**20 real tasks with run 1 vs. run 2 numbers**](https://docs.google.com/spreadsheets/d/1EQVW4sypjW-v-sOz2bFU_iwYP3dadeA-4hdCYPYnHy0/edit?usp=sharing).\n\n**Why this is different?**\n\nPure AI browser agents treat every run like the first one. Nothing transfers: the agent re-explores, re-reasons, and you pay full price in time and tokens every time. Fine for one-offs, but web automation is mostly repeat work.\n\nWebskillet captures what the agent learns as code in the skillet, so run 2 starts from a working solution instead of a blank browser. And it's code reuse, not caching: same skillet, new parameters, fresh data from the live site.\n\n![uploaded image](/media/?type=post&id=106701&key=user_uploads/224423/bb695aa0-402f-4ded-9b33-c9c5ba7da222)\n\n**Our story**\n\nWe've been building [**Intuned**](http://intunedhq.com/) for the past 3 years: a browser automation platform that's been powerful for our customers, but it takes some setup to get up and running. Meanwhile, the world is moving to a place where agents just want everything as an API.\n\nWebskillet is our new product: everything we learned, packaged differently. One endpoint, no setup, and our infra (stealth browser, proxies, captcha solving, AI agent) behind it.\n\nDemo: [**https://youtu.be/U9WPX2bG_GI?si=0qoXtt7JKaTP-eXG**](https://youtu.be/U9WPX2bG_GI?si=0qoXtt7JKaTP-eXG)\n\n**Who it's for**\n\n* **AI agent products** that need the web as a tool. An example: a sales agent calling Webskillet to scrape a big website and build target lists\n* **Product teams** whose product needs data from sites that don't have an API in a repeat manner: government sites or legacy systems\n* **Growth/GTM engineers** doing enrichment and competitor monitoring: pricing pages, job postings, hiring signals\n* **Ops teams** doing repeated lookups: insurance verification, compliance checks, order status\n* **Data/analyst teams** building on web data: price intel, listings, market data, 10-K filings\n\n[**Here's a sheet of 20 real tasks we ran**](https://docs.google.com/spreadsheets/d/1EQVW4sypjW-v-sOz2bFU_iwYP3dadeA-4hdCYPYnHy0/edit?usp=sharing), with costs and timings for run 1 vs. run 2. Every row has a \"try it\" link so you can run yourself.\n\n**Asks**\n\n* **Try it! Sign up at [webskillet.ai](http://webskillet.ai)**\n* Watch the demo and tell us what you think, especially on the skillet concept\n* If you has a scraping/automation [**use case**](https://cal.com/team/intuned/quick-chat), lets talk!",
        "url": "https://www.ycombinator.com/launches/Rkz-webskillet-ai-web-automation-that-gets-cheaper-every-run",
        "votes": 23,
        "created_at": "2026-07-21T14:13:11.426Z"
      },
      {
        "id": 99778,
        "title": "Intuned - Code-first browser automation, built and maintained by AI",
        "tagline": "We help developers build and maintain browser automations (scrapers, RPAs, crawlers) with an AI agent that writes the code and fixes it when websites change.",
        "body": "Hey Everyone,\n\nI'm Faisal, co-founder of Intuned. We're a code-first browser automation platform with an AI agent that builds and maintains your automations: scrapers, RPAs, crawlers, and anything else that needs to control a browser at scale.\n\n<https://youtu.be/22IYRA-ZqQk>\n\n### The problem\n\nBrowser automations run a surprising amount of the internet's back office: price monitoring, job aggregators, data migrations, every RPA that exists because a vendor won't ship an API. And they're miserable to own. The scripts are fragile, selectors break constantly, and when a site changes, someone's day is gone.\n\nThat's before the infrastructure: stealth, proxies, CAPTCHAs, authentication, scheduling, retries, observability. Building one automation is annoying. Running a hundred in production is a full-time team.\n\nRecent AI browsers and LLM-driven agents handle one-off tasks well, but for repetitive tasks that run regularly, you need the speed, predictability, and cost profile that only code gives you. Nobody wants to write that code. And nobody wants to maintain it.\n\n### How Intuned works\n\nTwo parts, designed to work together.\n\n**The platform.** Write automations in TypeScript or Python, organize them into Projects, deploy to Intuned. Run them on demand via API or on a schedule. We handle stealth, CAPTCHA solving, proxies, AuthSessions for login flows, batched Jobs with retries and concurrency, and full observability (logs, browser traces, session recordings).\n\n![uploaded image](/media/?type=post&id=99778&key=user_uploads/224423/e2c5bb13-ee8a-497c-8312-c0793cad9183)\n\n**Intuned Agent.** Describe what you want. The agent explores the site, proposes a schema, writes the code, validates it against the live site, and delivers a production-ready Project you can review and deploy. It also edits existing projects and diagnoses failed runs by pulling real traces and logs, the same signals a human engineer would use.[ Learn more about it in our docs.](https://intunedhq.com/docs/main/02-intuned-agent/overview)\n\n**Self-healing projects.** Flip a switch and the project becomes autonomous. When a site changes and a run fails, Intuned detects it, the agent diagnoses and fixes it, and the project redeploys. You configure how much autonomy it gets. [learn more about it in our docs](https://intunedhq.com/docs/main/02-intuned-agent/self-healing-projects).\n\n**More demos:** [Build a scraper](https://www.youtube.com/watch?v=Es390qwW87w) - [Build an RPA](https://www.youtube.com/watch?v=D1Uf42OS1cs) - [Fix with AI](https://www.youtube.com/watch?v=dPqyOy-brOE) - [self-healing projects](https://youtu.be/22IYRA-ZqQk)\n\n### Use cases\n\n* **Scrapers** — pricing, job listings, public records, news, product catalogs. Anything structured you need on a schedule.\n* **RPA** — form submissions, data entry, report downloads, account actions. Essential when the service you need to integrate with doesn't have an API.\n* **Migrations** — moving data between services that don't talk to each other\n* **Crawlers** — multi-page discovery, sitemaps, content indexing at scale\n\n### How we got here\n\nWe've been in browser automation for over two years. We launched Intuned as a developer platform, but the #1 ask from customers was for us to just build and maintain the automations for them. We ended up running a services motion alongside the product, and over the past year we've processed **40M automation runs (20M minutes)** for a limited set of customers. It became one of the most loved parts of working with us, and also the thing we most wanted to replace with product.\n\nWe spent the last year trying, and nothing we built was good enough.\n\n**Then we integrated the Claude Agent SDK (Claude code wrapped as SDK) directly into Intuned.** Combined with the platform we'd already built, the agent now does what a human engineer on our team used to do: build projects, validate against the live site, read failed run traces, and ship fixes.\n\n### Our ask\n\n* Checkout our docs [here](https://intunedhq.com/docs/main/00-getting-started/introduction).\n* Try it free: [app.intuned.io](https://app.intuned.io)\n* Have a use case you want to talk through? [Book a demo](https://cal.com/team/intuned/get-started) or email [support@intunedhq.com](https://mailto:support@intunedhq.com)\n* Share it with anyone you think will be interested.\n\nThanks for reading 🙏\n\nFaisal & the Intuned team",
        "url": "https://www.ycombinator.com/launches/PxK-intuned-code-first-browser-automation-built-and-maintained-by-ai",
        "votes": 67,
        "created_at": "2026-04-15T14:35:16.537Z"
      },
      {
        "id": 83938,
        "title": "Intuned Auth Sessions - Build authenticated scrapers and RPA",
        "tagline": "Intuned Auth Sessions enable you to easily build authenticated scrapers and browser automation for a wide set of use cases. Watch our demo videos to learn more!",
        "body": "# **The Problem**\n\nAdding authentication to any type of browser automation complicates it. There is a lot to handle—session expiration, proxies, obtaining user credentials/consent, monitoring, and more—and there is no easy or standard way to handle it.\n\n# **The Solution**\n\nIntuned Auth Sessions provides a standardized, developer-friendly way to add authentication to any browser automation task. Whether you're building authenticated scrapers, implementing RPA processes, or creating custom integrations for a service without APIs, Intuned simplifies the process and provides you with the infrastructure. Intuned’s auth sessions come with features that handle common authentication challenges, such as securing credentials, solving challenges, proxy support, 2fa, and more!\n\nOne of the features that we are super excited about is our auth session recorder, where you can allow the user to log in to a remote browser and capture the session from that. Check out how it works here (and watch the full video below for more info):\n\n![uploaded image](/media/?type=post&id=83938&key=user_uploads/224423/47827269-e4ce-4a87-b57b-7a07d8cdc9bd)\n\n# **Use Cases, Demos, and Docs**\n\n* **Build a LinkedIn integration/Build an integration with a service that has no APIs.**\n  * Video Demo: <https://www.loom.com/share/fc56861199874850bee8a6dd33fd2aef>\n  * What does the demo show? We build an integration that enables users to “Connect to LinkedIn” and then show how we can automate a simple action.\n* **Authenticated Scraper:** Build scrapers that pull data from a website that requires auth.\n  * Video Demo: <https://www.loom.com/share/3488fb24bda04278ae88d5b018d22fd3>\n  * What does the demo show? We build a scraper that runs daily and pulls data from an authenticated website.\n* **Back office Automation:** Automate back office operations on a website that requires auth.\n  * Video Demo: <https://www.loom.com/share/df53a15788504c86a06e4c0f3b37e5f6>\n  * What does the demo show? We automate some tasks on OrangeHRM using a service account.\n* To learn more about the feature and about Intuned in general, here are a few pointers to our docs:\n  * General docs: <https://docs.intunedhq.com/>\n  * Auth Session docs: <https://docs.intunedhq.com/docs/auth-sessions/overview>\n  * How to guides: [how to automate LinkedIn](https://docs.intunedhq.com/docs/guides/auth/how-to-automate-linkedin) and [how to do credentials based authentication](https://docs.intunedhq.com/docs/guides/auth/how-to-authenticate-with-credentials).\n\n# **Our Ask & Onboarding**\n\n* Does this set of features sound like something you need? We are ready to onboard developers starting today: <https://cal.com/team/intuned/get-started>\n* Do you know someone facing these challenges? [Email us](mailto:founders@intunedhq.com)",
        "url": "https://www.ycombinator.com/launches/Lpq-intuned-auth-sessions-build-authenticated-scrapers-and-rpa",
        "votes": 30,
        "created_at": "2024-09-11T14:20:22.252Z"
      },
      {
        "id": 81730,
        "title": "Intuned - The browser automation platform for developers and product teams",
        "tagline": "Develop, deploy, and monitor reliable web scrapers and browser automations",
        "body": "### **TL;DR**\n\nUse [Intuned](https://intunedhq.com/) to develop, deploy, consume, and monitor reliable web scrapers and browser automations. Reliability is powered by AI.\n\n### **❌ The Problem**\n\nStartups increasingly rely on browser automation for data scraping and RPA (Robotic Process Automation: automate what doesn’t have APIs via UI). However, the process of building, deploying, and maintaining these automations is fraught with challenges:\n\n* Building and deploying browser automations requires specialized infrastructure that can be complex to set up and maintain.\n* Browser-based automations are inherently fragile. Over 100 conversations with founders, product managers, and integration team members revealed a unanimous concern: the reliability and maintenance headache of scrapers and RPA.\n* The lack of monitoring tools for browser automations complicates the prompt detection and resolution of issues that occur during automation operations.\n\n### **✨ Our solution**\n\n[Intuned](https://docs.intunedhq.com/) is the platform for developers and product teams to develop, deploy, consume, and monitor **reliable** web scrapers and browser automations. We use LLMs to make common browser automation tasks easier to build and more reliable. Check out our docs ([https://docs.intunedhq.com](https://docs.intunedhq.com/)) for more info.\n\n<https://youtu.be/FegYJWg9vcU?si=02O_Y2w6oqvZO71J>\n\n### **How does it work?**\n\n**Develop**\n\nThe Intuned platform has an IDE built to speed up the process of building browser automations. Intuned IDE comes with custom features like action recording, selector creator, and more! To learn more, check out [**Develop**](https://docs.intunedhq.com/docs/platform/develop/overview).\n\n![uploaded image](/media/?type=post&id=81730&key=user_uploads/1063634/fd5e1fb7-0bff-44be-9444-1c33f8f14e84)\n\n**Deploy**\n\nIntuned’s projects can be deployed with a single click and within a minute. To learn more, check out [**Deploy**](https://docs.intunedhq.com/docs/platform/deploy).\n\n![uploaded image](/media/?type=post&id=81730&key=user_uploads/1063634/7f553275-4f64-4325-a19a-87cb7dd6b3d8)\n\n**Consume**\n\nStart consuming your projects by making API calls directly or scheduling jobs for scraping tasks. To learn more, check out [**Consume.**](https://docs.intunedhq.com/docs/platform/consume)\n\n![uploaded image](/media/?type=post&id=81730&key=user_uploads/1063634/0ac65a69-0a97-4777-b0b8-47ea18aa1ec0)\n\n**Monitor**\n\nGet proactive alerts on failures - with access to previous runs’ traces, recordings, and results. To learn more, check out [**Monitor.**](https://docs.intunedhq.com/docs/platform/monitor)\n\n![uploaded image](/media/?type=post&id=81730&key=user_uploads/1063634/3d319b39-591b-4947-97b7-0f086b324101)\n\n**Reliability**\n\nAs part of the Intuned platform, we provide the `@intuned/sdk` , a library built on top of Playwright, extending its capabilities by offering powerful helpers designed for common browser automation tasks. The `@intuned/sdk` enhances Playwright by making automation tasks more reliable and easier to implement.\n\n### **Our story - why build this?**\n\nFaisal and I started our YC journey working on an analytics platform. However, our background at UiPath drew founders to us with challenges around scaling manual processes. These interactions revealed the inefficiency of classic RPA tools for customer-facing integrations. When the time to pivot arrived, we analyzed YC startups batch-by-batch and observed a rising trend: many founders were venturing into areas requiring non-standardized access.\n\nOver 100 conversations with founders, product managers, and integration team members revealed a unanimous concern: the complexity and reliability of building and maintaining such integrations. Over the past few months, we've handled over a million requests for our early customers who are setting up their large-scale scrapers/automations.\n\n### **Our ask to you**\n\nAre you a dev building a scraper or browser automations? Or have you been postponing building those? Check out [Intuned](https://intunedhq.com/), or just chat with us [here](https://cal.com/team/intuned/get-started).\n\nKnow someone facing these challenges? We appreciate introductions! Contact us for an introduction blurb to facilitate the process.\n\n### **Docs and How-to guides**\n\nGeneral docs: <https://docs.intunedhq.com>\n\nQuick start: <https://docs.intunedhq.com/docs/getting-started/quick-start>\n\nBuild your first scraper - webhook sink: <https://docs.intunedhq.com/docs/guides/scrapers/how-to-scrape-to-webhook>\n\nBuild your first scraper - S3 sink: <https://docs.intunedhq.com/docs/guides/scrapers/how-to-scrape-to-s3>\n\nScrape data from web and files: <https://docs.intunedhq.com/docs/guides/scrapers/how-to-scrape-files>\n\nWeb data extraction (how you don’t need selectors anymore!): <https://docs.intunedhq.com/docs/data-extraction/web-data-extraction>",
        "url": "https://www.ycombinator.com/launches/LGE-intuned-the-browser-automation-platform-for-developers-and-product-teams",
        "votes": 54,
        "created_at": "2024-06-25T15:00:44.188Z"
      },
      {
        "id": 64781,
        "title": "🎵 Intuned - The data assistant for engineering leaders",
        "tagline": "We help engineering managers rein in the chaos",
        "body": "**TL;DR:** [Intuned](https://www.intuned.io/) is the data assistant for engineering leaders. [Watch our demo](https://bit.ly/3PIvCY2) to see how it works, and [email us](mailto:founders@intuned.io) if you want to learn more or get early access!\n\nWe are [Faisal](https://www.linkedin.com/in/faisal-ilaiwi-77356135/) and [Zawad,](https://www.linkedin.com/in/zawad-chowdhury/) and we are building [Intuned](https://www.intuned.io/)! We are on a mission to help engineering leaders!\n\n### **❌ The Problem**\n\nBeing an engineering manager day to day is not easy. There is a lot that engineering managers are dealing with, here are a few of the many issues we are trying to help with:\n\n* When it comes to people, many management decisions rely on gut feeling **alone.** This is why the performance-reviews period is a tough one.\n* There are a lot of repetitive, ad-hock, and manual tasks that are expected from a manager. An example is the regular reporting managers are often asked to prepare. Another one is the periodic planning activities that teams go through.\n* Driving change within organizations is hard, what makes it harder is the lack of an easy way to set measurable goals and track progress towards achieving them.\n* Managers have to deal with a set of different tools day to day, these tools all have different and inflexible notification systems, which makes them (as notification systems) useless. This is why managers use a pull model (go check on things) vs. a push model (they get notified) on the things they care about.\n\n## **✨ Our Solution**\n\nWhile the problems above are common with most managers, the exact way they can be solved will depend on the manager, their team, their processes, and the systems they use. There is NO one-size-fits-all here!\n\nWith [Intuned](https://www.intuned.io/)_,_ we are providing a toolbox to help!\n\nAs an engineering leader, [Intuned](https://www.intuned.io/) will enable you to connect your data from the different systems you and your team use (Jira, Github, Notion, Excel, and more) and will give you a powerful way to query it, explore it, build metrics, and actions on top of it.\n\nUsing this flexible approach, we believe we can help managers with many of their regular tasks, and save them time, effort and randomization.\n\n[Watch our 4-min demo to see how it works](https://www.youtube.com/watch?v=xzFTvSwFaqs)\n\n### **⚙️ How does it work?**\n\n**🔗 Connect your data with a few clicks.**\n\n![uploaded image](/media/?type=post&id=64781&key=user_uploads/224423/95454f4b-64db-4a06-9e08-b3550b138824)\n\n**❓ Query and explore your data - save hours on building manual reports.**\n\n![uploaded image](/media/?type=post&id=64781&key=user_uploads/224423/107f6c59-9790-4eb4-a040-78e18dffdeda)\n\n**🔔 Setup a custom notifications - never miss a critical issue again!**\n\n![uploaded image](/media/?type=post&id=64781&key=user_uploads/224423/482e12d8-d5c3-4eb8-be56-e78960e44a0d)\n\n🏗️ **Why build this?**\n\nAs a former engineering manager myself, this is the product that I wish I had!\n\n2\\.5 years ago, I became a manager for an engineering team of 2 that end up growing to around 20 people by the time I left _UiPath_.\n\nAs my team was scaling, we experienced growing pains with engineers being blocked, deployments getting delayed, and overall team execution lagging. I realized our software delivery process wasn’t keeping up but I couldn’t pin point what it was. So I ended up building a small tool to help! That tool ended up being very useful. That tool is the inspiration behind [Intuned](https://www.intuned.io/).\n\n### **Let’s Talk!**\n\nIf you or someone you know are a leader of an engineering team who is feeling some of these pains, we think [Intuned](https://www.intuned.io/) can help! please [email us](mailto:founders@intuned.io) or [schedule a meeting](https://calendly.com/intuned/15min) with us.",
        "url": "https://www.ycombinator.com/launches/Gqr-intuned-the-data-assistant-for-engineering-leaders",
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        "answer": "I founded Integrated Reasoning in December of 2021. I started working on the idea full-time as of March 2022."
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        "answer": "Integrated Reasoning designs processors that are tailored to the memory access patterns of NP-complete algorithms. Think GPUs but for optimization and constraint satisfaction problems (e.g. the knapsack problem.)\r\n\r\nComputing solutions to many NP-complete problems requires a massive amount of data transfer between the CPU and DRAM. Memory bandwidth is the bottleneck of modern computing, as discussed in \"Hitting the memory wall: Implications of the obvious.\" [1]\r\n\r\nThe memory wall is such a critical problem that it motivated much of the design behind Apple's M1 architecture. See also this excellent 2017 article [2] by Brendan Gregg, who is widely known for his expertise in system performance engineering.\r\n\r\nI believe Integrated Reasoning presents a win-win-win:\r\n- Customers win by spending less money renting servers, less time waiting for computation, and most importantly, can work on something other than wrangling clusters of computers.\r\n- The Earth and its inhabitants win because less energy will be required to search for countless digital needles in enormous digital haystacks (i.e. combinatorial optimization problems.)\r\n- Integrated Reasoning wins because it can make a profit while pricing its products far below the cost of running the equivalent workload on a cluster of servers.\r\n\r\n[1] Wulf, Wm A., and Sally A. McKee. \"Hitting the memory wall: Implications of the obvious.\" ACM SIGARCH computer architecture news 23.1 (1995): 20-24.\r\n[2 ] [https://www.brendangregg.com/blog/2017-05-09/cpu-utilization-is-wrong.html](https://www.brendangregg.com/blog/2017-05-09/cpu-utilization-is-wrong.html)\r\n\r\nNote: Integrated Reasoning does not aim to answer the famous P versus NP question."
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        "id": 64273,
        "title": "⚡️ Integrated Reasoning - Fast hardware for optimization problems",
        "tagline": "Integrated Reasoning builds computer hardware to efficiently solve optimization problems. We’re making it 100x faster and 10x cheaper to solve problems like scheduling airline pilots or packing shipping containers.",
        "body": "**Problem:**\n\nLogistics is expensive.\n\nImagine you’re a shipping company. Every day, you need to pack 100,000 boxes into shipping containers. How many containers do you need? Which boxes go into which containers? A common solution to this problem is to run [Google’s “OR-Tools” software](https://developers.google.com/optimization) in the cloud. This works, but it’s slow and the costs add up. Integrated Reasoning builds an alternative solution that is faster and cheaper.\n\n**Solution:**\n\n[Integrated Reasoning](http://ir.design/) provides hardware for solving optimization problems that can be quickly deployed in the cloud and scaled as needed. You don’t need any knowledge of hardware or firmware to use our products, and we provide generous support to make sure that the transition is smooth.\n\n**Reach out to us!**\n\nWe’re working on a series of hardware products for optimization. We would love to hear from folks that work on scheduling, routing, packing, networks, or other optimization problems; even if you’re not sure if our hardware could help.\n\nYou can reach out to Brycen and David at [hello@ir.design](mailto:hello@ir.design) or find out more at [ir.design](http://ir.design).",
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        "created_at": "2022-07-01T19:12:26.468Z"
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        "full_name": "Chris Navrides",
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        "full_name": "Etienne DEGUINE",
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        "title": "🚀 Reviewify.io - AI powered code reviews",
        "tagline": "Get in-line code review comments in seconds, powered by GPT-4",
        "body": "TL;DR -  We are building [reviewify.io](http://reviewify.io) - automatic code review for every pull request, powered by GPT-4. Installation takes just 10 seconds, and you can start automatically receiving comments & suggestions.\n\n# **Problem**\n\nYou want to make sure the code written by yourself and team is awesome. But having a code review can slow things down, especially if you only have a few Sr Engineers to review for everyone, and you don’t want their time wasted for obvious issues like not having null checks, or ordering imports.\n\n# **Solution**\n\nWe use GPT, combined with custom review samples, to automatically run code reviews and post the comments in minutes on the PR.\n\n[![Reviewify Demo](https://videoapi-muybridge.vimeocdn.com/animated-thumbnails/image/b48f4158-e90b-42bc-8052-326c02dcc157.gif?ClientID=vimeo-core-prod&Date=1680109610&Signature=3d65ab548135d7de88de0442d6b11d451c863e4c)](https://vimeo.com/812887518)\n\n# **Ask**\n\n* Try it out and leave reactions to the comments it generates so we can improve the system\n* If there are other features that would add value to you, please let us know (ex: Static analysis, code dependency report, integration into IDEs so comments can be seen at code time, etc).\n\nThanks,\n\nChris & Etienne",
        "url": "https://www.ycombinator.com/launches/IN2-reviewify-io-ai-powered-code-reviews",
        "votes": 50,
        "created_at": "2023-03-29T17:24:52.596Z"
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      {
        "id": 65540,
        "title": "Dev Tools AI 🤖 CoPilot for UI Testing",
        "tagline": "We make writing UI automation tests as easy so you can solve bigger problems",
        "body": "# **TL;DR**\n\n[Dev Tools](https://www.dev-tools.ai/) is a library that makes it easy to write web tests in your existing framework by drawing a box over a screenshot instead of building a locator.\n\n![uploaded image](/media/?type=post&id=65540&key=user_uploads/1076464/6cf84e73-20ac-4ca5-994d-329f77e7b325)\n\n\n# **🤕Problem**\n\nWriting end to end tests is difficult and time consuming. It takes forever to dig into the page code to build the right XPath or locator. And even when these are found, they are likely to change over time as the product continues development.\n\n# **⚡️Our solution**\n\nWe use computer vision to look at the screen, like an end user, and find the element you want to interact with. Then, in real-time, we find the element and return it so all your existing automation can keep working with it. We make this easy to use by extending Selenium with a `findByAI()` method where you just put a human readable name and let the AI do the hard work.\n\nWe even let you see the elements from within your IDE!\n\n![uploaded image](/media/?type=post&id=65540&key=user_uploads/1076464/bb8100b8-b570-4aeb-8bae-fd49cd8d470d)\n\n# **🎉 Bonus Features**\n\n### Work on Games\n\nTraditional automation has trouble working with games as most games render within a canvas element. Because we only use the screenshot, and not page source, we can play games like LooneyToons!\n\n![uploaded image](/media/?type=post&id=65540&key=user_uploads/1076464/3feb64e1-36cd-47c0-93f5-a8c3e98d10d1)\n\n### Crawl for Errors\n\nMonkey Testing for errors comes standard with Android, but there isn’t a default one for Web. We added that functionality to our SDK so that you simply call `scan_domain()` and it will crawl your page and look for errors like broken links, 404s, console errors, etc. Learn more in our [blog](https://www.dev-tools.ai/blog/site-sacnner) about the feature.\n\n# **Our Ask - Try it out and give us feedback**\n\nIf you write or have written Selenium or UI tests, we would love your feedback on the tool.\n\nJoin us on [Discord](https://discord.gg/2J9WEYdq5C), or follow us on [Linkedin](https://www.linkedin.com/company/dev-tools-ai)!\n\nIf you have any questions or automation challenges, reach out to us anytime! [chris@dev-tools.ai](mailto:chris@dev-tools.ai) & [etienne@dev-tools.ai](mailto:etienne@dev-tools.ai)",
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        "created_at": "2022-08-22T17:01:29.766Z"
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        "full_name": "Alexandru Antihi",
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        "id": 69110,
        "title": "{🟦} Blocksfabrik: Create your own design system without all the work",
        "tagline": "Generate a design system complete with Figma assets, a private NPM package for your components, and documentation.",
        "body": "Hi! Alex and Ryan here - we’re super excited to launch [Blocksfabrik](https://blocksfabrik.com/#ref=yclaunch)!\n\n---\n\n**TLDR: We built a way to create design systems that stay in sync across design and code. Teams are using us to design better interfaces and develop them as fast as using an off-the-shelf component library, but with the flexibility of a bespoke design system and none of the tech debt.**\n\n**Ready to ship better product experiences? We would love to help, so please book a slot for a quick chat** [**here**](https://calendly.com/d/zkc-hbp-8n2/blocksfabrik-founders)**, or reach us directly via email at** [alex@blocksfabrik.com](mailto:alex@blocksfabrik.com) or [ryan@blocksfabrik.com](mailto:ryan@blocksfabrik.com)\n\n### **The Problem**\n\nCreating your own design system takes a ton of effort and experience that is hard to come by. And once they’re built you’ll have to maintain them in design and code indefinitely. Off-the-shelf component libraries get you off the ground, but are disconnected from design and hacking around their limitations becomes a liability as your product grows.\n\nWhat if you can design and build as fast as with a component library, but with the flexibility and quality of a bespoke design system?\n\n# **The Solution**\n\nConfigure your design system in the Editor and Blocksfabrik will take care of the rest — creating the component code, Figma assets, and documentation. It’s like having a full-time design system team, without needing the budget.\n\n### **How It Works**\n\n**(1)** Define your design tokens in the Editor (including color palette, sizes, fill styles, etc) and the specifics of your interface components (from shapes to interaction patterns).\n\n![uploaded image](/media/?type=post&id=69110&key=user_uploads/919864/31b5b5d1-c6a8-4fca-b639-1a203bcab90b)\n\n**(2)** Publish your design system, and you’ll get a private NPM package, Figma assets, and documentation that are all in sync.\n\n![uploaded image](/media/?type=post&id=69110&key=user_uploads/919864/56ce7431-2f21-40d9-932c-dd2c1edbf728)\n\n**(3)** Since Blocksfabrik creates components for both Figma and code, your Figma assets will share the same properties, and behave identically to the components in code. The designer → developer handoff becomes fast and seamless.\n\n![uploaded image](/media/?type=post&id=69110&key=user_uploads/919864/e6fce859-0bb6-4b2c-b4fa-f1502029add2)\n\nNeed to update something? Simply make edits and publish a new version that you can start using in Figma and code.\n\n### **How We Can Help You**\n\nIf you or someone in your network is struggling to build a product interface or design system, we’d love to help! Please book a quick chat [**here**](https://calendly.com/d/zkc-hbp-8n2/blocksfabrik-founders), or email us at [alex@fabrikant.tech](mailto:alex@fabrikant.tech), [ryan@fabrikant.tech](mailto:ryan@fabrikant.tech)\n\nThank you!\n\n---\n\n---",
        "url": "https://www.ycombinator.com/launches/Hyg-blocksfabrik-create-your-own-design-system-without-all-the-work",
        "votes": 76,
        "created_at": "2023-02-08T00:11:07.932Z"
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        "full_name": "Wiz 👋🏻",
        "title": "Founder",
        "founder_bio": "Entrepreneur. Father. Geek.\nLove coffee and coffee loves me.\nFull name is Nadav Weizmann 😉\n",
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        "full_name": "Mor Sela",
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        "founder_bio": "Building something new.\nProduct builder at heart and a professional code whisperer.\n\nLed engineering teams through product development, acquisitions, strategic changes, and reorganizations at Cardinal (acq by Miro), Epic Games, Houseparty (acq by Epic Games), Docady, and the israeli 8200 unit\n",
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        "id": 69853,
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        "body": "☕️ **TL;DR**\n\nCardinal is the platform for product teams to define strategies, break it down to goals and set specs (features) with live data and KPIs across systems, consistently through teams and projects.\n\nHi, we’re [**Wiz**](https://twitter.com/nadavwiz) and [**Mor**](https://www.linkedin.com/in/selamor/), co-founders of Cardinal.\n\n![uploaded image](/media/?type=post&id=69853&key=user_uploads/1136316/88bc6831-ff37-45c6-b40d-54c6c1c654ea)\n\n**🏆 Why Us**\n\nWe’ve lead product and engineering at Epic Games (Directors).\n\nWe’ve lead product and engineering at Houseparty (acquired by Epic Games).\n\nWe’ve started and worked at startups (Docady, Onavo \\[Acquired by META\\]).\n\nWe’ve lead deep tech teams at 8200 (Israeli NSA).\n\nWe’ve been working together for 15 years and built internal tools to document and communicate strategies, progress, and try and track measurements of those throughout. From startup scale to corporate scale, it was always needed and insufficient.\n\nWe’re excited to fix this!\n\n**😩 Problem**\n\nManaging product teams, building and shipping features is hard. Product discovery, spec-ing, prioritization, alignment, measurements and learnings all take a toll on teams trying to execute and build impactful features.\n\n**🧠 Solution**\n\n1. Managing strategy: through time, initiatives and stakeholders.\n2. Methodology: all your teams are aligned and work the same way\n3. Documentation & Knowledge Management: know your history and use it easily.\n4. Data & Insights: connect various systems and set real, live goals.\n\n   ![uploaded image](/media/?type=post&id=69853&key=user_uploads/1136316/b98d3f9e-9e77-4dde-aefb-4796c1a5a5ae)\n\n\n**🙏🏻 Our Asks**\n\nSign up to the beta at [cardinalapp.io](http://cardinalapp.io), give us real feedback.",
        "url": "https://www.ycombinator.com/launches/IAf-cardinal-enabling-product-teams-to-build-measurable-features",
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        "created_at": "2023-03-01T22:19:29.195Z"
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    "team_size": 17,
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    "subindustry": "B2B -> Engineering, Product and Design",
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        "full_name": "James Ritchie",
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        "title": "Trigger.dev raises $3M",
        "url": "https://trigger.dev/blog/3m-dollar-seed-round",
        "date": "Aug 25, 2023"
      },
      {
        "title": "Show HN: We built a developer-first open-source Zapier alternative | Hacker News",
        "url": "https://news.ycombinator.com/item?id=34610686",
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      {
        "id": 69600,
        "title": "✨ Trigger.dev: The developer-first open source Zapier alternative",
        "tagline": "We make it easy for developers to create powerful workflows directly in code.",
        "body": "**🔥 TL;DR** [**Trigger.dev**](https://trigger.dev?utm_source=ycombinator&utm_medium=post&utm_campaign=trigger.dev&utm_id=launch.yc) **is an** [**open source**](https://github.com/triggerdotdev/trigger.dev) **platform that enables developers to effortlessly create event-driven background tasks directly in their codebase – for example, when a Stripe payment fails, open a Linear issue and send an email to yourself, or easily create a drip email campaign. Write workflows using our SDK, and view a detailed history of all runs in our web app.**\n\nHey! We’re Matt, Dan, James and Eric, the founders of [Trigger.dev](https://trigger.dev?utm_source=ycombinator&utm_medium=post&utm_campaign=trigger.dev&utm_id=launch.yc).\n\n### **👀 The Problem:**\n\n* As developers, we find that current workflow / automation tools like Zapier, n8n or Make are great for simple tasks, but not suitable for more advanced use cases.\n* Developers often end up creating important workflows in no/low-code tools on behalf of non-technical team members.\n* Some of these tools let you drop down into code, but it’s not a great developer experience. Developers prefer using their own IDEs with version control and access to the best tools like GitHub Copilot.\n* Connecting together APIs in code is painful – you need to deal with authentication, lots of SDKs and docs for each API you use.\n* Some workflows need to use a database query or access very private data. That data shouldn’t leave your servers and you shouldn’t need to give database access to a third-party.\n\n### **✨ Our solution:**\n\n[Trigger.dev](https://trigger.dev?utm_source=ycombinator&utm_medium=post&utm_campaign=trigger.dev&utm_id=launch.yc) makes it easy to create workflows in response to API events (webhooks), on a schedule or on-demand by sending your own events.\n\nAll of this lives in code alongside everything else in your codebase. We handle API authentication with external services, allowing more time to be spent writing functional code, rather than dealing with credentials. We also support long delays of up to a year that survive your server restarting.\n\nAll workflow runs can be viewed in our web app providing great observability for debugging.\n\n![uploaded image](/media/?type=post&id=69600&key=user_uploads/1102924/b7793d79-dfc0-4c9f-b6d1-f4535a24f5ad)\n\n### **🛠 How it works**\n\n* Install the [Trigger.dev](https://trigger.dev?utm_source=ycombinator&utm_medium=post&utm_campaign=trigger.dev&utm_id=launch.yc) SDK to get access to our custom packages and functions\n* Trigger workflows from webhooks, custom events or schedules (CRON)\n* Use our growing library of API integrations for the best experience. We will support all of the most popular services, including Slack, Airtable, Linear, Stripe, GitHub, SendGrid, Notion and many more. We’re adding more each week with the help of our open source contributors.\n* Support for Fetch and subscribing to generic webhooks for any service.\n* Add delays of up to 1 year. Workflows will resume where they left off, even if your server has gone down.\n* Observe every workflow run in the app (great for debugging).\n* Your private data is kept private – you have control over where your data is sent.\n* Our open source MIT license lets anyone self-host the platform.\n\nIt’s clear from our [launch](https://news.ycombinator.com/item?id=34610686) and customers that developers want to be creating workflows in code rather than in an unfamiliar UI. We expect this trend to continue, especially with the rise of AI code writing assistants such as Copilot and Ghostwriter. Leveraging these tools will only improve [Trigger.dev](https://trigger.dev?utm_source=ycombinator&utm_medium=post&utm_campaign=trigger.dev&utm_id=launch.yc) as time goes on, and make the creation of complex workflows more and more accessible to all developers.\n\n### **🙏 Our asks**\n\nIf you have a workflow you want to build and would like to try our platform - we would love to hear from you!\n\n* Try us out for free at [Trigger.dev](https://trigger.dev?utm_source=ycombinator&utm_medium=post&utm_campaign=trigger.dev&utm_id=launch.yc).\n* Book a 15 min workflow session [here.](https://cal.com/team/triggerdotdev/15-mins-about-your-automation)\n* Want to migrate an existing workflow? [Let us know.](https://cal.com/team/triggerdotdev/migration-consultation)\n\n### **⭐️ Our YC deal:**\n\n* **YC W23:** for 12 months, get unlimited workflows with 100k runs per month for free.\n* **YC Alumni:** for 6 months, get unlimited workflows with 50k runs per month for free.\n\nIf you have any questions or want to access the YC deal, please email me at [matt@trigger.dev](mailto:matt@trigger.dev).",
        "url": "https://www.ycombinator.com/launches/I6a-trigger-dev-the-developer-first-open-source-zapier-alternative",
        "votes": 51,
        "created_at": "2023-02-23T15:51:43.990Z"
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      {
        "id": 67467,
        "title": "🦸 API Hero: make every API you use faster and more reliable with one line of code",
        "tagline": "An open source API proxy that makes debugging and caching APIs trivial",
        "body": "**_🔥 TL;DR_** _API Hero routes API traffic you select through our edge proxy to provide caching and full visibility of requests and responses, speeding up your APIs and making debugging super easy. Check it out for free_ [_here_](https://apihero.run/)_, or schedule a call with us to help you get started_ [_here_](https://cal.com/team/apihero/request-a-demo)_._\n\nHi everyone 👋\n\nWe’re James, Matt, Eric & Dan and we’re building [API Hero](https://apihero.run). We’re on a mission to make using and working with APIs **super easy.**\n\n### **🤦 The problem**\n\nThere are two major headaches we’re tackling:\n\n* Slow APIs dramatically reduce the speed of your site, and adding caching to solve this can be hard\n* Debugging API issues is painful. You want full visibility of requests and responses so you can figure out what’s going on, during development and production (although we make production logging optional)\n\n### **🦸 With API Hero, you can:**\n\n* Monitor all your API traffic (or just the parts you want)\n* Speed up every API you use by enabling caching (this can also save you money!)\n* Get alerts when issues arise\n* Improve reliability with automatic retries\n\n### **🛠 How does API Hero work?**\n\n* Login to [API Hero](https://apihero.run/) (it’s free!)\n* Follow the simple onboarding steps – we’ll automatically populate your dashboard as soon as a request is sent\n* Configure the settings to proxy only the traffic you want\n* Sit back and watch those logs come in!\n\n![uploaded image](/media/?type=post&id=67467&key=user_uploads/1093162/90670a20-df63-4740-af17-46c35e850deb)\n\n![uploaded image](/media/?type=post&id=67467&key=user_uploads/1093162/ed99841e-bcd2-411c-94ac-6298c3a28d78)\n\n### **💬 We’d love to chat to:**\n\n* Anyone suffering from API issues\n* Any company working with 3rd-party APIs or building APIs\n* Anyone who’s checked out API Hero and has feedback",
        "url": "https://www.ycombinator.com/launches/HYB-api-hero-make-every-api-you-use-faster-and-more-reliable-with-one-line-of-code",
        "votes": 29,
        "created_at": "2022-11-22T17:09:53.152Z"
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    "name": "DrDroid",
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    "all_locations": "Bengaluru, KA, India",
    "long_description": "DrDroid is building AI Agents for Platform & Infrastructure teams. \r\nWe help engineering teams fix issues faster and reduce escalations during on-call—automating triage, debugging, and remediation.\r\n\r\nWe’re also the team behind several open-source projects:\r\n🔹 Playbooks – A runbook automation platform\r\n🔹 Kenobi – An event analytics platform for debugging data pipelines\r\n\r\nJoin us in redefining how teams run operations in the post-GPT world.",
    "one_liner": "Your best friend in production.",
    "team_size": 8,
    "industry": "B2B",
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    "launched_at": 1668798140,
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        "title": "AlertOps Slack Bot by Doctor Droid — Identify poorly configured and noisy alerts",
        "tagline": "Add the bot to a channel and instantly receive reports about poorly configured and noisy alerts",
        "body": "Hello everyone! At [Doctor Droid](https://drdroid.io/), we’re launching AlertOps Bot today.\n\n![uploaded image](/media/?type=post&id=78159&key=user_uploads/1073547/26f4c64e-4079-4ed5-8085-4d03726a9035)\n\n**TL;DR** Add the bot to a channel and instantly receive reports about poorly configured and noisy alerts in the channel over the last 1 month / 3 months / 6 months. [**Signup URL.**](https://drdroid.io/)\n\n**Context:** We built this tool for engineering teams that are too busy, have a bit of alert fatigue, and want to reduce the noise.\n\n![uploaded image](/media/?type=post&id=78159&key=user_uploads/1073547/c433733b-d223-49dc-8437-f04e97e79c8c)\n\nToday, doing it requires manual time and energy.\n\n![uploaded image](/media/?type=post&id=78159&key=user_uploads/1073547/ab732135-c51b-496b-95db-3eefbab32e7b)\n\nWe have designed the bot such that the entire analysis now is presented to the engineers in seconds after adding the #Slack Bot.\n\n![uploaded image](/media/?type=post&id=78159&key=user_uploads/1073547/3b676a72-3eae-444c-a025-6d9209b9c4e2)\n\nThe bot provides immediate analysis of noisy alerts and insights around alerts that buzz too often.\n\n![uploaded image](/media/?type=post&id=78159&key=user_uploads/1073547/7028dd5e-2937-48da-b729-ab5b41aaf466)\n\nWe also extract other key tags from the strings. (like service_names, db_name, etc.). This helps do faster drill-downs of noise.\n\n![uploaded image](/media/?type=post&id=78159&key=user_uploads/1073547/e837fc17-e5d4-4bf6-9648-6482dfe1b809)\n\nOur users include engineering teams at startups of all sizes and scales — from seed stage to unicorns.\n\n![uploaded image](/media/?type=post&id=78159&key=user_uploads/1073547/2ed51997-a5b2-40d0-a930-ad20c09721c8)\n\nTo get started, just [**sign up** on our](https://drdroid.io/) website and install the bot.\n\n![uploaded image](/media/?type=post&id=78159&key=user_uploads/1073547/c2206d71-88f5-40d4-a38c-fc6a4203d9e0)\n\nIf you have any specific comments or feedback to share, just let us know! ([**founders@drdroid.io**](mailto:founders@drdroid.io))",
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        "body": "Hello everyone, Sid & Dipesh here from Doctor Droid!\n\nTl;dr: We help engineers track complex backend workflows that cannot be seen with just a single trace. Our stateful alerting system proactively looks for “missing states”, which means you’ll be alerted even when a certain task or event does not take place.\n\n### Our Story\n\nDipesh & I are tinkerers who love to build products, and build them fast. Dipesh made a game one weekend that snowballed, and [then got acquired](https://www.linkedin.com/pulse/us-based-gaming-company-acquires-wordhurdle-dipesh-mittal/). I made a [volunteering website during COVID](https://mgiep.unesco.org/article/india-covidsos-online-volunteer-platform-wins-un-solidarity-award) to enable people to help others in their neighbourhood. These are apart from our full-time jobs, building products at Shadowfax - India’s leading last-mile delivery startup.\n\n![uploaded image](/media/?type=post&id=69760&key=user_uploads/1073547/55de2e46-57ef-4d85-97d3-6df1c76a3562)\n\nAs engineers, we were used to being called on-call when something broke, even though most of the times it wasn’t our code that actually caused the issue.\n\n### **_The Problem_**\n\nWe had multiple critical products where monitoring the functioning of these products was not just about APIs because:\n\n* A business use-case, when scattered across different APIs and batch processes, simply can't be connected together and viewed as a single flow to help find the leakage point\n* You can only query and search over events/logs as individual data points, so I can't setup monitoring over deviations from my planned path for the user or an algorithm\n* You cannot see a miniature / filtered version of your business behaviour and see irregularities in real-time\n* The more properties you add in your events, the costlier storing and querying that data becomes\n\nWith Doctor Droid, we are making it super easy to detect and troubleshoot these complex products.\n\n### **_How Doctor Droid Helps:_**\n\nDoctor Droid gives you real-time visibility of how your products are performing, so you know where to intervene:\n\n* **Workflow visualisation** of the critical product paths - easily detect steps of failure and monitor the data passing at each step\n* Setup **stateful alerts** that span across multiple events\n* Create **custom metrics** using the attributes directly or as an expression (without cardinality constraints)\n* **Investigate** issues at a order, transaction or user level\n* Setup automated actions (JIRA ticket, custom scripts) for known issues\n\n![uploaded image](/media/?type=post&id=69760&key=user_uploads/1073547/9a0c9d88-f144-4b7b-b056-0337bf0145bd)\n\nWe have a simple SDK to ingest events (similar to your logging library), our documentation is available [here.](https://docs.drdroid.io/v2.0/docs)\n\n### **_Try now -_** We are in private beta and are giving 100k events/month complimentary for first 100 beta sign ups (apart from personalised support to help detect issues faster for your business). Request access on our website to access our product or write to us at [founders@drdroid.io](mailto:founders@drdroid.io)",
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        "votes": 52,
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        "title": "Magic Patterns - Prototype your Product Ideas with AI",
        "tagline": "Get design inspiration and generate React code from a simple text prompt.",
        "body": "**tldr;** [Magic Patterns](https://www.magicpatterns.com/) helps software teams prototype their product ideas.\n\n50,000+ developers and designers have used our beta so far and revenue is growing fast 📈. [**Start building today**](https://www.magicpatterns.com/)**.**\n\n### DEMO VIDEO\n\n[Demo Video - Generate UI](https://youtu.be/_LRBQjy4Z1g)\n\n### PROBLEM\n\n1. Getting design inspiration is hard — most people today use websites like Mobbin and Dribbble, but these tools don’t know what your specific product looks like. You need inspiration that actually looks like what you’re building.\n2. AI code assistants are not visual, but building UI is.\n\n### SOLUTION\n\nStart prompting in our visual editor. You can choose a publicly available design system for free.\n\nWe use AI models to help non-technical founders, engineers, and PMs speed up time to market.\n\n![uploaded image](/media/?type=post&id=78644&key=user_uploads/1146847/e5b9e2ee-f4bb-433d-8c37-4d96f7a0de39)\n\n### TRACTION\n\nTake our existing [customers](https://www.magicpatterns.com/customers):\n\n* [Designers](https://www.magicpatterns.com/teams/designers) use Magic Patterns to brainstorm and export to Figma\n* [Founders](https://www.magicpatterns.com/teams/startups) use Magic Patterns to generate production-ready code\n* [Product managers](https://www.magicpatterns.com/teams/product) use Magic Patterns to visually communicate their ideas\n\n### FOUNDERS\n\nWe’re [Alex](https://www.linkedin.com/in/alexanderdanilowicz/) and [Teddy](https://www.linkedin.com/in/teddy-ni/), two technical founders who have been building products for 10 years together. Here’s us on Alex’s wedding day, where Teddy gave the best man speech about being a “work husband.” (Alex’s wife found it very funny.)\n\n![uploaded image](/media/?type=post&id=78644&key=user_uploads/1146847/499dabe2-5fe3-40dd-8c7e-9e2b99535e34)\n\n### OUR ASK 👋\n\n1. Try us for free: [www.magicpatterns.com](http://www.magicpatterns.com)\n2. Want to ship faster? [Upgrade](https://www.magicpatterns.com/pricing) for higher messaging limits. You’ll join a community of startups and enterprises that are using Magic Patterns today.\n3. API access? Team discounts? [We have those too](https://www.magicpatterns.com/pricing). Chat with sales (a.k.a us – the founders!): [alex@magicpatterns.com](mailto:alex@magicpatterns.com)",
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        "founder_bio": "Cofounder and CTO of Depot. US expat living in the UK.",
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        "linkedin_url": "https://www.linkedin.com/in/jacobwgillespie/",
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        "title": "Depot raised a $10M Series A",
        "url": "https://x.com/kylegalbraith/status/2031357969338663387?s=46&t=O2dQBFTAcOO_utQ0IktGUg",
        "date": "Mar 10, 2026"
      },
      {
        "title": "Depot raises $4.1M to speed software builds by 40X | VentureBeat",
        "url": "https://venturebeat.com/programming-development/depot-raises-4-1m-to-help-developers-speed-up-software-builds-by-40x-or-more/",
        "date": "Aug 22, 2024"
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        "id": 79909,
        "title": "✨ Depot: Managed GitHub Actions runners for AWS",
        "tagline": "30% faster compute, 10x faster cache, 1/2 the cost",
        "body": "Hey, we’re Kyle and Jacob, the founders of [Depot](https://depot.dev), a hosted container build service for Docker images, and we’re excited to launch our new product: [managed GitHub Actions runners for AWS](https://depot.dev/products/github-actions)!\n\n![uploaded image](/media/?type=post&id=79909&key=user_uploads/956934/99034910-f435-44ef-8301-3610146d56bd)\n\n## The Problem\n\nWhile GitHub Actions is one of the most prevalent CI providers, Actions is slow for a few reasons:\n\n* GitHub uses underpowered CPUs.\n* Network throughput for cache and the internet at large is capped at 125 MB/s.\n* Total cache storage is limited to 10GB per repo.\n* Larger runners are expensive and take a long time to start running jobs.\n\n## The Solution\n\n**Depot-managed runners solve this!** Rather than your CI jobs running on GitHub’s slow compute, Depot routes those same jobs to powerful EC2 instances. And not only is this faster, it’s also 1/2 the cost of GitHub Actions!\n\nWe do this by launching a dedicated instance for each job, registering that instance as a self-hosted Actions runner in your GitHub organization, and then terminating the instance when the job is finished.\n\nWe've also integrated the runners with our existing distributed storage cluster that we use for Docker image builds for up to 10x faster cache throughput! 💪\n\n## Demo Video\n\n<https://www.youtube.com/watch?v=VX5Z-k1mGc8>\n\n## Tech Details\n\nUsing AWS as our compute provider has a few advantages:\n\n* We launch fast `m7a` instances, which are typically 30%+ more performant than alternatives.\n* Each instance has high-throughput networking of up to 1.5 GB/s, hosted in `us-east-1`, so interacting with artifacts, cache, container registries, or the internet at large is quick.\n* Each instance has a public IPv4 address, so you’re not sharing any rate limits with anyone else.\n\nBy integrating the runners with the distributed cache system (backed by S3 and Ceph) that we use for Docker build cache, jobs automatically save/restore cache from this cache system, with speeds of up to 1.5 GB/s, and without the default 10 GB per repo storage limit.\n\nAdditionally, the runners are located in the same VPC as our [Docker build service](https://depot.dev), so for anyone using both, built containers are now able to `--load` back into CI for testing much faster than they would over GitHub’s default network.\n\nWe build our machine image from [GitHub's image definition](https://github.com/actions/runner-images), so all the same software you expect is pre-installed. Support for Arm runners, powered by Graviton instances, is in beta now.\n\n## Getting Started\n\nYou can sign up at <https://depot.dev/sign-up> for a free trial if you’d like to try it out with your own workflows!",
        "url": "https://www.ycombinator.com/launches/Kmr-depot-managed-github-actions-runners-for-aws",
        "votes": 21,
        "created_at": "2024-04-03T14:38:17.273Z"
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        "title": "⚡ Depot - a faster way to build Docker images",
        "tagline": "A remote container build service that is 3-14x faster than CI providers, with emulation-free support for both Intel & Arm architectures",
        "body": "Hey everyone! We’re Kyle and Jacob, and we’re excited to share [Depot](https://depot.dev/) with all of you.\n\n[![uploaded image](/media/?type=post&id=67759&key=user_uploads/600738/bc4dbd39-a0a3-4838-a4f5-20e6302c00b2)](https://depot.dev/benchmark/temporal)\n\nDepot is a remote container build service that is 3-14x faster than building Docker images inside of generic CI providers. It’s much faster than existing solutions like GitHub Actions because we run BuildKit the right way with a persistent SSD cache. We launch both Intel and Arm VMs for each build, allowing you to build native multi-platform or Arm images without any slow emulation.\n\nPostHog’s Docker builds [run around 5x faster with Depot](https://posthog.com/blog/speeding-up-posthog-builds-with-depot), reducing daily time spent on builds from 5+ hours to just an hour. We continuously benchmark several open-source projects, comparing `docker build` and `depot build`, including:\n\n* [Temporal](https://depot.dev/benchmark/temporal) (\\~14.5x faster, saving 7 hours over the last 10 builds)\n* [Supabase](https://depot.dev/benchmark/supabase) (\\~8.5x faster, saving 2 hours over the last 10 builds)\n\n### Our background\n\nAs software and platform engineers, we absolutely hate slow CI builds. Everyone has their own internal timer for what classifies a slow build, our own is 5 minutes, if it takes longer than that we get annoyed. We have experienced first-hand the pain and challenge of keeping Docker container builds fast, optimizing/re-optimizing pipelines and Dockerfiles, and implementing custom runners for multi-platform builds. It’s all annoying, unnecessary, and a drain on developer happiness.\n\nOverall, slow builds clog up the delivery pipeline and take time away from iterating on new ideas and fixing problems for users.\n\n### Building Docker images is slow\n\nBuilding Docker images in CI providers like GitHub Actions, CircleCI, etc. is slow:\n\n* **Saving and loading layer cache is slow.** Transferring the cache over the network to the ephemeral CI runners eats away at any cache time savings.\n* **Runner resources are constrained,** with limited CPUs, RAM, and disk space.\n* **Multi-platform and Arm builds require emulation.** Emulation is orders of magnitude slower than native, and Arm is increasingly important with the rise of popularity with devices like MacBook M1, Graviton, etc.\n\n### Our Solution\n\nDepot provides managed VMs running BuildKit, the backing build engine for Docker. Each VM includes 4 CPUs, 8GB of memory, and a persistent 50GB SSD cache disk. We launch both native Intel and Arm machines on AWS. You can choose to have your builder VMs launch in our AWS account or in your own if you want to maintain total control over your data.\n\nOur `depot` CLI is a drop-in replacement for `docker build` as we embed Docker `buildx` directly as a library. Anything you can build with Docker today, you can build with Depot on our remote VMs.\n\n![uploaded image](/media/?type=post&id=67759&key=user_uploads/600738/79d72d22-c290-4d0f-87bc-2e2ae2527797)\n\n### Signing up\n\nWe love having new folks try out Depot and throw new questions & feedback our way. It really is the fuel that keeps a new startup going.\n\nIf you’re annoyed by your slow Docker image builds today, we have a 14-day free trial that you automatically get when you sign up here: <https://depot.dev/sign-up>.",
        "url": "https://www.ycombinator.com/launches/Hct-depot-a-faster-way-to-build-docker-images",
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        "created_at": "2022-12-07T14:37:25.884Z"
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        "title": "Lume: Automate data mappings using AI",
        "tagline": "Ingest client data, normalize data from different sources, and build data pipelines, automatically.",
        "body": "**TL;DR**\n\nLume helps teams map data between systems with AI. If your team spends time mapping data for customer data onboarding, data normalization between systems, or mapping for data integrations, we can help! Please go to our [website and sign up](https://www.lume.ai/?utm_source=ycombinator&utm_medium=social&utm_campaign=launch_yc_5_24) for a free trial.\n\n—-\n\nHi everyone! We are Nicolas, Nebyou, and Robert, the founders of Lume. We are on a mission to automate the painstakingly manual process of data mapping, after experiencing this frustration as engineers ourselves. We have onboarded several customers who are growing and are excited to help more teams use AI in their data mapping workflows.\n\n![uploaded image](/media/?type=post&id=81770&key=user_uploads/1159508/77b12bac-08ae-40df-9984-f0cbc0f10c1d)\n\n**🧨 Problem**\n\nThe usual mapping process involves a labor-intensive cycle: analyzing data to determine what's relevant, selecting the appropriate properties, developing the mapping logic, and constantly updating mappers to accommodate schema changes in source or target systems. This process, we learned, takes days, weeks, or even months for most teams, and automating it has traditionally been borderline impossible due to unique differences in data.\n\n**✨ Solution**\n\nLume uses AI to automatically map data between any start and end schema, whether it is customer data, external sources, or anything else. Lume provides this via an API and a no-code platform where you can generate mapping logic, review and edit it, and manage multiple data pipelines. Whether you want to onboard customer data, normalize data from multiple sources, or create auto-mapping UIs over Lume, Lume delivers. With automated transformations and data delivery, error and type checking, auto-maintenance with schema inference, and execution via an API or a no-code App for different use cases, teams can spend more time delivering their core value to customers instead of wrangling and manually mapping data.\n\n**🚀 Key Features**\n\n* ✨ Generate mapping logic in seconds: via our API or the Lume app, simply pass in a sample of your source data and a target format, and Lume will generate the mappings.\n* 🛠️ Edit mapping logic: review and edit the mapping logic and mapped data as needed to ensure you have the desired outcome. Leverage tools ranging from natural language all the way to full code edits to edit the mappers quickly and easily.\n* ✅ Deploy mappers: Use the mappers deterministically in your code via our API or the app, allowing you to reliably move data between schemas as you scale your data pipelines.\n* 🤖 Auto-maintain mappers: Lume detects changes in your schemas, notifying you and allowing you to use AI to update the mapping logic, effectively automating your maintenance.\n* 📊 Manage and organize mappers: use Lume’s dashboard to have visibility over all of your mappers and live data pipelines.\n* 📑 Handle any format: Lume supports JSON, CSV, XLS, PDF, and other formats! You can move data through the API or the app.\n* 🔮 Upcoming: adding custom logic with lambda functions, custom validation rules, python SDK, transferring your existing mappings when migrating to Lume, and more.\n\n**⚙️ How it works**\n\n* To create mappers: specify your target structure and provide a sample of source data. This can be done via the Lume API or the Lume Platform.\n\n![uploaded image](/media/?type=post&id=81770&key=user_uploads/1159508/d27fd09d-3943-4748-817a-cb16a4b5952a)\n\n* ✨ Lume’s AI system creates the mappings between any two schemas, ranging from simple 1-1 mappings, time-series aggregations, complex calculations, and ontology classifications.\n* Use the generated mappings and mapping logic: Use the Lume API or the Lume Platform to upload new incoming data and retrieve the corresponding output mapped data and mapping logic. Your data has just been automatically mapped with AI!\n\n  ![uploaded image](/media/?type=post&id=81770&key=user_uploads/1159508/c25b7d28-9b19-49b5-b103-ad8a69ef21e7)\n\n* For creating robust data pipelines, review and edit the generated mapping logic before running production data. Once saved, you can confidently use these mappers as deterministic pipelines. This is helpful for your data integrations between systems.\n\n![uploaded image](/media/?type=post&id=81770&key=user_uploads/1159508/c9f8696c-e294-4c01-b602-aa16f3635f21)\n\n![uploaded image](/media/?type=post&id=81770&key=user_uploads/1159508/b2766b97-2eda-4dca-baf5-9f87ffb22d8d)\n\n* Alternatively, build on top of the Lume API to deploy your own auto-mapper UI to allow customers to self-onboard.\n\n**💡 Use Cases**\n\nLume handles three core use cases:\n\n* Onboarding Client Data\n* Normalizing Data from Multiple Sources\n* One to Many Integrations\n\nHere are three customer success stories:\n\n* For a growth-stage battery analytics company, mapping each customer’s sensor data went from 2 weeks to 1.5 hours with Lume.\n* For a large HR analytics platform, Lume mapping accuracy reached 95% for their most recent batch of integrations, saving them weeks of onboarding time for mapping and classifying data from incoming systems.\n* For an early-stage financial product startup, Lume is handling \\~500 live data pipelines that are externally facing, constantly mapping and adapting to new incoming data.\n\nAll of these have the common theme of having to map data between unique schemas, where even discrepancies as minor as column name variations make this process time-consuming and near-impossible to automate. This gets even worse at scale. Clients previously were allocating engineers, customer success teams, or offshore labor to analyze incoming data, map the data, and route it to their new systems. This process used to take up to multiple months for some teams, costing significant time and money.\n\nWe serve multiple industries ranging from ecommerce, insurance, manufacturing, and financial products.\n\n**👨‍💻Meet the Team**\n\n![uploaded image](/media/?type=post&id=81770&key=user_uploads/1159508/fe023d78-6ef6-49c3-b202-d264bc80270e)\n\nMy co-founders Nebyou Zewde (right), Robert Ross (middle), and I (left) all met during our first year at Stanford. As engineers ourselves, we’ve spent plenty of time grudgingly going over the manual task of mapping data. We quickly learned that we were not the only ones who faced this problem - most companies spend too much time on this. As AI grads, and with a fire for this problem, we built Lume AI. We are part of the Y Combinator W23 batch, and we’re excited to be launching here.\n\n**🙏 Our ask**\n\n* Sign up for a free trial to get started by [visiting our website](https://www.lume.ai/?utm_source=ycombinator&utm_medium=social&utm_campaign=launch_yc_5_24) or [booking a call here](https://cal.com/team/lume/intro). We’ll get you on a Slack and onboarded quickly.\n* Share this with anyone who works on data mapping for customer onboarding, data normalization, or moving data between any two systems. We support a variety of use cases.\n* Upvote and share this post!\n\n**💥 The Deal**\n\nMention you saw Lume via Launch YC, and we will give you a 50% discount for your first 6 months. We also offer a free pilot.",
        "url": "https://www.ycombinator.com/launches/LGs-lume-automate-data-mappings-using-ai",
        "votes": 40,
        "created_at": "2024-06-26T17:31:22.598Z"
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        "id": 70009,
        "title": "Lume - No-code tool to create and maintain custom data integrations",
        "tagline": "Lume uses AI to automatically transform data between any start and end schema.",
        "body": "**TL;DR**\n\nLume helps engineering teams build and maintain custom data integrations with no code. If you spend countless hours manually transforming data for custom integrations, we can help! Please go to our [website](https://www.lume.ai/?utm_source=ycombinator&utm_medium=social&utm_campaign=launch_yc_5_23) and sign up for our private beta.\n\n—-\n\n---\n\nHi everyone! We are Nicolas, Nebyou, and Robert, the founders of Lume. We are on a mission to empower companies to focus on delivering their core value proposition rather than spending time on data integrations and transformations. \n\n![uploaded image](/media/?type=post&id=70009&key=user_uploads/1157038/0a606e9a-7357-4f36-bd06-be63bddcd635)\n\n**🧨 Problem** \n\nEngineers spend countless hours manually transforming data for custom integrations or pay large amounts to consulting firms to do the same. Dynamic schemas from different clients or apps require engineers to build and maintain custom integration pipelines one by one, and companies spend days, weeks, and even months building integrations. Lume is tackling this problem head-on. \n\n**✨ Solution**\n\nLume uses AI to automatically transform data between _any_ start and end schema and pipes the data directly to your desired destination. Lume provides this through a no-code platform where you can build and maintain your custom data integrations. Whether you want to map multiple sources to your internal unified schema or connect to your third-party apps without manual mapping, Lume delivers. With automated transformations and data delivery, backtesting and data quality checks, and version control, engineers can spend more time delivering their core value to customers instead of wrangling and manually mapping data. \n\n**⚙️ How it works**\n\n* You connect your custom schemas and authenticate into your desired apps.\n* Lume’s AI system creates the transformations between any two schemas, ranging from internal schemas to structured third-party apps.\n* Once you validate the transformed data, Lume will pipe the correct data to your specified destination.\n\nWe can connect to your data warehouse and leverage its compute to keep your data in-house.\n\n**Common Use Cases:**\n\n* Internal: Transforming separate data sources into one unified internal ontology\n  * Ex: a unified schema between Salesforce, Hubspot, Quickbooks, and Pipedrive.\n* External: Custom syncs between your SaaS apps\n  * Ex: Enrich CRM data from multiple sources before sending it to your BI tool\n* Onboarding: Mapping prospective client data to fit your product’s input schema\n  * Ex: Consulting firms mapping each new clients’ unique ERP schemas to their internal ontology on Snowflake.\n* Migration: Creating custom integration pipelines between competitor products to yours \n  * Ex: New productivity tool startup creates an “Import from Notion/Evernote” for newly converted users.\n\n**👨‍💻Meet the Team**\n\n![uploaded image](/media/?type=post&id=70009&key=user_uploads/1157038/86b2a6a9-5fb4-4300-be17-30125bdb80fa)\n\nMy co-founders Nicolas Machado (right), Nebyou Zewde (middle), and I (left) all met during our first year at Stanford, where we received our undergraduate and Master's degrees in computer science with a focus on Artificial Intelligence. With experience working at both unicorn startups and big tech companies, our team has knowledge and experience building and deploying applied machine learning systems.\n\n**🙏 Our ask**\n\n* Sign-up for our [private beta](https://www.lume.ai/?utm_source=ycombinator&utm_medium=social&utm_campaign=launch_yc_5_23) if you want to try Lume and see a demo.\n* Share this with anyone that works on custom data integrations.\n* Upvote and share this post!\n\n**💥 The Deal**\n\n**Sign-up before demo day for a 50% discount for the first year!**",
        "url": "https://www.ycombinator.com/launches/IDB-lume-no-code-tool-to-create-and-maintain-custom-data-integrations",
        "votes": 251,
        "created_at": "2023-03-07T18:12:57.774Z"
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    "website": "https://dashdive.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Dashdive attributes AI/LLM and cloud costs to customers, teams and products at the endpoint invocation level using observability tools. This allows software companies to optimize their pricing and evaluate the profitability of each product.",
    "one_liner": "Break down AI and cloud costs by feature and customer",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1678386689,
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      {
        "id": 70237,
        "title": "Dashdive — Break down cloud costs by feature and customer",
        "tagline": "The only tool that shows per-feature and per-customer cloud costs.",
        "body": "[Dashdive](http://dashdive.com) attributes AWS, GCP, Azure and other cloud services costs to features, products, teams and customers. These data help companies understand how their profitability breaks down by product and customer, allowing them to make optimal strategic decisions about pricing, resource allocation and cloud architecture.\n\n### Problem\n\nMost tech companies **don’t know how much it costs to serve each of their customers with each of their products**. Cloud costs are typically a tech company’s second-largest cost (after personnel), and they can vary significantly even on a per-unit basis, i.e. irrespective of volume.\n\nWithout per-customer and per-product cost information, companies can’t reliably know:\n\n1. What’s our margin on Customer A?\n2. What’s our margin on Product B?\n3. Which usage events drove Customer C’s costs last month?\n4. What are our costs likely to be on new Customer D?\n\nNormally, if an engineering or finance team wants to know the answer to one of these questions, they have to either 1) **make an estimate that could be wildly inaccurate** based on average total costs or 2) “**track down an engineer** to run experiments in AWS.” (That was a direct quote from a CFO.)\n\n### Solution\n\n![uploaded image](/media/?type=post&id=70237&key=user_uploads/1165030/8fb86e1e-9f54-4127-ad9e-e0ac5daf701f)\n\n**Dashdive answers these questions** by monitoring backend services (servers, databases, etc.) with lightweight agents. These agents **attribute the activity on each cloud service to specific features and customers** using distributed tracing and continuous profiling. Then, the usage data are **mapped to cost** data via AWS/GCP/Azure billing APIs. The result is a complete picture of who and what are driving cloud costs over time.\n\nGranular cloud cost data allow companies to:\n\n1. Know if they’re pricing an existing customer too low—or below cost.\n2. Hone in on individual lines of code and architectural decisions that incur disproportionate costs. (Other tools can only give generic cost-cutting recommendations based on total costs, e.g. “consider reserving storage in advance for a discount,” since they just repackage existing AWS billing data.)\n3. Give customers who complain about high bills or opaque pricing an adequate explanation (and perhaps even suggested usage patterns to reduce future bills).\n4. Better forecast the cost of serving a new customer based on expected usage. This helps teams price contracts optimally to hit margin goals consistently.\n\n### Setup\n\nInstallation only involves deploying Dashdive agents to each service of interest. This takes five minutes and requires **zero code changes**. Although our backend is cloud-based by default, **Dashdive can be self-hosted** for companies that need to keep all data within their ecosystem.\n\n![uploaded image](/media/?type=post&id=70237&key=user_uploads/1165030/943447c4-84fd-4a29-a67c-46f3ae266fcc)\n\n_This is the entire setup for AWS Lambda, a popular cloud service._\n\n### Why Now\n\nSupply and demand factors make now the perfect time to launch this product:\n\n* **Supply**: Monitoring technologies eBPF and OpenTelemetry have come a long way in the past few years. Both technologies allow seamless monitoring of different technology stacks, removing friction where engineering teams would have otherwise needed to make significant investments in setup and maintenance. Application performance monitoring companies like Datadog have proven that monitoring dozens of services is technically feasible and can be profitable even at scale.\n* **Demand**: As the cost of capital has increased and fundraising has become less certain, profitability is the only way to guarantee business survival. Business and engineering leaders are placing newfound importance on margin health.\n\nGiven these factors, this opportunity emerged in the last twelve months.\n\n### Get in Touch\n\nMore information at [dashdive.com](http://dashdive.com). Inquiries can be sent to [team@dashdive.com](https://mailto:team@dashdive.com).\n\n![uploaded image](/media/?type=post&id=70237&key=user_uploads/1165030/e5803ab1-04cb-4a16-b4f5-f87c2ec6bb68)\n\nDashdive’s founders met in college at Stanford University. Bringing strategy and sales experience, [Micah](https://www.linkedin.com/in/micah-wheat/) (left) worked at the Boston Consulting Group. [Adam](https://www.linkedin.com/in/adamshugar/) (right) developed his engineering background at Palantir and Apple.",
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        "full_name": "Max Lu",
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        "founder_bio": "Founder / CEO at Lynx",
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        "full_name": "Lydia Ding",
        "title": "Founder",
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      {
        "id": 87299,
        "title": "Lynx: AI Incident Resolution for Eng Teams",
        "tagline": "Meet Lynx, the platform to help engineers resolve oncall incidents faster!",
        "body": "[Lynx](https://uselynx.ai) is an AI-powered incident resolution platform that helps engineers diagnose and resolve on-call issues faster. If you’ve ever been woken up at 2 AM for a production incident and spent hours piecing together logs, metrics, and documentation, Lynx can help. Sign up on our [website](https://www.uselynx.ai/getstarted), reach out to us at [founders@uselynx.ai](mailto:founders@uselynx.ai), or schedule a time with us on [Calendly](https://calendly.com/codecompleteai/lynx-demo).\n\n### The Problem\n\nSoftware engineering has evolved, but on-call hasn’t. Even with the best observability tools, finding the root cause is slow and frustrating: systems grow more complex, documentation becomes scattered, and tribal knowledge gets lost as engineers leave the company.\n\nCompanies need a faster, more intelligent way to diagnose and resolve issues.\n\n### Our Solution\n\nLynx is an AI-powered **incident resolution platform** that allows engineers to easily investigate and resolve issues directly in their development environment.\n\nCheck out our product [demo](https://youtu.be/atzdMyd7PG0)!\n\nWhen incidents arise, **Lynx will automatically gather information, pinpoint root causes, and perform actions to help fix the issue**. Lynx lives on your dev server, so it can connect with all the tools and integrations in your environment. You can directly run code or execute commands on the Lynx platform in order to resolve your issues.\n\n[Lynx Demo - Directly Resolve Incidents](https://youtu.be/TbvYtI5SstQ)\n\nWe built out chain-of-thought command execution so Lynx can automatically generate queries step-by-step and retrieve all the context it needs.\n\n[Lynx Demo - Chain of Thought Command Execution](https://youtu.be/EANK62F75Pc)\n\nWe implemented several safeguards to ensure Lynx only executes read-only commands, but if you want a bit more control, you can opt to manually approve each command before it runs:\n\n[Lynx Demo - Manual Command Execution](https://youtu.be/oGUpwGSPdVQ)\n\nLynx focuses on helping engineers **resolve** incidents instead of just managing them.\n\n### Why We’re Building This\n\nWe started by building self-hosted, fine-tuned AI coding assistants, but we quickly realized coding was just a fraction of an engineer’s workflow. Teams spend just as much—if not more—time testing, debugging, and deploying.\n\nWe saw an opportunity to apply AI beyond generating new code, with on-call standing out as a major pain point. Engineers were losing hours digging through logs, retracing past incidents, and manually correlating data across tools.\n\nLynx was created to streamline incident resolution, but it goes beyond just on-call incidents. Our vision is to create an AI agent that can understands all the ins and outs of your tech stack so it can predict, investigate, and resolve any technical issue.\n\n### **Ask: How you can help**\n\nIf your team has a heavy on-call burden, we'd love to chat about your workflows and pain points.\n\n* Try out our product! Sign up for our waitlist: <https://www.uselynx.ai/getstarted>\n* Introduce us to engineering leaders or teams who might benefit from Lynx.\n\nQuestions? Visit our [website](https://uselynx.ai/), reach out to [founders@uselynx.ai](mailto:founders@uselynx.ai), or schedule a time with us on [Calendly](https://calendly.com/codecompleteai/lynx-demo).\n\n![uploaded image](/media/?type=post&id=87299&key=user_uploads/471786/1e163e61-6d72-4178-b08b-2342f1ad445d)\n\n",
        "url": "https://www.ycombinator.com/launches/Mi3-lynx-ai-incident-resolution-for-eng-teams",
        "votes": 23,
        "created_at": "2025-01-30T14:29:09.564Z"
      },
      {
        "id": 69046,
        "title": "CodeComplete - GitHub Copilot for Enterprise",
        "tagline": "AI coding assistant for enterprise that is self-hosted to protect their IP and fine-tuned to their codebases",
        "body": "### **TLDR**\n\n[CodeComplete](http://codecomplete.ai) is GitHub Copilot for Enterprise. Large companies can't use Copilot because of the security and privacy risks, so we're building a self-hosted version that’s also fine-tuned to the company's codebase. \n\n**If you (or if you know anyone else who):**\n\n* **Would like to use Copilot at work but cannot, or**\n* **Would like a version of Copilot that’s fine tuned to your enterprise codebase**\n\nPlease reach out to us at [founders@codecomplete.ai](mailto:founders@codecomplete.ai) or schedule a time with us on [Calendly](https://calendly.com/lydia-codecomplete/intro). \n\n—\n\n---\n\nHi everyone, we’re Max and Lydia, and we’re building CodeComplete: an AI-powered code assistant built for enterprise companies. We’re incredibly excited about the advances in generative AI and are on a mission to transform the way developers work. Our code completion product is the first in a suite of AI-powered dev tools we’d like to build. \n\n### **The problem**\n\nWe love GitHub Copilot, but in order to use it, you need to send your code to GitHub, Microsoft, and OpenAI. Many large enterprise companies strictly forbid this due to **security and privacy concerns**, so they cannot leverage AI-powered dev tools to multiply their productivity.\n\nAlso, the underlying **Copilot model is not tuned to your codebase**, so you don't always get relevant suggestions. It’s best practice for developers to use their company’s frameworks and libraries. However, without fine tuning, code generation models can suggest generic code, which decreases legibility and introduces technical debt, performance issues, and security holes in the codebase.\n\n### **The solution**\n\nCodeComplete is a **self-hosted AI coding assistant tool that's fine tuned to your codebase**. We train powerful code generation base models on your codebase so we can deliver more relevant suggestions. We deploy these models directly on-premises or in your own cloud, so your valuable intellectual property stays with your company. With CodeComplete, your team can leverage cutting-edge AI technology to be more productive, quickly ramp up developers, and write better code while staying security compliant.\n\n**Demo**\n\n![uploaded image](/media/?type=post&id=69046&key=user_uploads/1160505/0dbe9136-8d6c-415f-a09e-c6f81bba8ddb)\n\n### **Why we’re building this**\n\nMax wanted to use GitHub Copilot at Meta, but leadership explicitly blocked him from doing so. We believe AI-powered dev tools are the future, and we think they can be especially powerful and deliver value at larger companies. We want to set companies up for success in the long run by helping the millions of developers at these companies leverage new AI technology.\n\n**Buy vs. Build**\n\nThis is not a core competency for many large enterprises. Buying a solution will save millions by freeing up engineering resources and catapulting dev velocity. \n\n### **Ask: How you can help**\n\n* Connect us to an engineering leader at a large company that needs our product. [Email us](mailto:founders@codecomplete.ai)!\n* Connect us to engineers who really want to use Copilot but cannot. [Email us](mailto:founders@codecomplete.ai)!\n* Try out our product. Sign up on our [website](https://www.codecomplete.ai/)!\n* **We will provide a $500 referral bonus if your referral becomes a paying customer.**",
        "url": "https://www.ycombinator.com/launches/Hxe-codecomplete-github-copilot-for-enterprise",
        "votes": 45,
        "created_at": "2023-02-06T14:02:26.861Z"
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    "name": "Nango",
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        "founder_bio": "Recidivist founder (2 x YC). Previously software engineer at Uber, Trip.com, Triplebyte.",
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        "title": "Growth & Marketing Lead (Founding)",
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        "location": "San Francisco",
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      {
        "id": 88416,
        "title": "Nango: Embed 600+ integrations from 400+ APIs in your SaaS",
        "tagline": " The most comprehensive product integrations platform.",
        "body": "\n![uploaded image](/media/?type=post&id=88416&key=user_uploads/4587/c5bd7650-0750-4fc1-92cc-14148ceb7cbe)\n\n([API catalog](https://www.nango.dev/api-integrations) / [Docs](https://docs.nango.dev/) / [Repo](https://github.com/NangoHQ/nango) / [Try it](https://app.nango.dev))\n\nTwo years ago, we launched Nango as an [open-source OAuth handler](https://news.ycombinator.com/item?id=34693233) that simplified authorization for 40 APIs. Since then, we’ve expanded to become a full product integration platform for developers. We now support 400+ APIs, 600+ pre-built integrations, and custom integrations-as-code.\n\nDemo video: <https://www.youtube.com/watch?v=oTpWlmnv7dM>\n\nEach API in our catalog comes with auth handling (OAuth, API keys, etc.), two-way syncing, retries, rate limit management, pagination, webhooks, observability, etc.\n\nWe also have pre-built integrations for common use cases like fetching HubSpot contacts, creating GitHub issues, syncing Salesforce data, and hundreds more.\n\nIf an API or integration you need isn’t supported yet, you can implement it yourself on Nango (or ask us to prioritize it).\n\nEverything related to API authorization is free forever, and you can either self-host or use our cloud version.\n\n([API catalog](https://www.nango.dev/api-integrations) / [Docs](https://docs.nango.dev/) / [Repo](https://github.com/NangoHQ/nango) / [Try it](https://app.nango.dev))",
        "url": "https://www.ycombinator.com/launches/N04-nango-embed-600-integrations-from-400-apis-in-your-saas",
        "votes": 10,
        "created_at": "2025-03-11T14:52:52.000Z"
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        "id": 70266,
        "title": "🔌 Nango: Get OAuth tokens for APIs. Fast & secure.",
        "tagline": "Pre-built OAuth flows & secure token management for 55+ APIs (and counting)",
        "body": "![uploaded image](/media/?type=post&id=70266&key=user_uploads/4364/21c7fde9-a308-4c66-9cde-8eacfc4ce237)\n\n## TL;DR\n\nPre-built OAuth flows & secure token management for 55+ APIs (and counting). 100% open source.\n\n## The problem: OAuth sucks.\n\n[OAuth is harder than it seems](https://www.nango.dev/blog/why-is-oauth-still-hard):\n\n* Every API has specific quirks & nuances - forcing you to read endless docs pages\n* OAuth libraries don’t solve redirects, adding callback endpoints, token storage, refresh logic etc.\n* When something goes wrong debugging is hard: Unspecific errors, non-compliant behaviours, missing details and a million possible root causes\n\nOn top of this, SOC 2 compliance & GDPR make storing plain-text tokens in your DB no longer a viable option.\n\n## The solution: Nango makes OAuth fast & secure.\n\nNango is a service that contains everything you need to work with APIs that use OAuth:\n\n* A full OAuth dance for 55+ APIs - no backend work needed\n* A tiny frontend SDK, with promises instead of confusing full-page redirects\n* Secure token storage, with automatic refresh as needed\n* Works with any API, programming language & framework\n\nIn your frontend easily trigger an OAuth flow with 1 line of code (full desktop & mobile support):\n\n```jsx\nnango.auth('salesforce', '<user-id>'); // Opens a modal for OAuth dance\n```\n\nThen get always fresh access tokens in your backend:\n\n```jsx\nlet accessToken = nango.getToken('salesforce', '<user-id>'); // Refreshed & ready\n```\n\nThat’s it.\n\n## Trusted in production, by startups and established companies\n\nNango is used in production by companies like Typeform, Crowd.dev, AppraisalInbox, Trigger.dev (YC W23), Blocktool (YC W23) and others.\n\n## Try it in 5 minutes\n\nNango is easy to try on your local machine (open source) or with our cloud option:\n\n* Try it on your local machine: <https://github.com/NangoHQ/nango>\n* Get started with [Nango Cloud](https://www.nango.dev)",
        "url": "https://www.ycombinator.com/launches/IHK-nango-get-oauth-tokens-for-apis-fast-secure",
        "votes": 56,
        "created_at": "2023-03-14T15:02:02.167Z"
      }
    ]
  },
  {
    "id": 27734,
    "name": "Rubber Ducky Labs",
    "slug": "rubber-ducky-labs",
    "former_names": [
      "Rubber Ducky Labs",
      "Inc."
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/80d1f55be06d00fd52db1ea9553e87aa6f8ac9d1.png",
    "website": "https://www.rubberduckylabs.io/",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "We built Rubber Ducky Labs to help e-commerce teams effortlessly improve product discovery through better metadata. Our tool enables non-technical users to leverage multi-modal AI on product catalogs—just upload a CSV and start tagging metadata in minutes.",
    "one_liner": "AI Powered Product Discovery",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1671139016,
    "tags": [
      "E-commerce",
      "AI",
      "Recommendation System"
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    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2023",
    "status": "Inactive",
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      "Engineering, Product and Design"
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    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Fully Remote"
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    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/rubber-ducky-labs",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/rubber-ducky-labs.json",
    "year_founded": 2022,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/rubber-ducky-labs",
    "x_url": "https://twitter.com/RubberDuckyLabs",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/rubber-ducky-labs",
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/80d1f55be06d00fd52db1ea9553e87aa6f8ac9d1.png",
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    "founders": [
      {
        "user_id": 1164034,
        "full_name": "Alexandra Kissel",
        "title": "Founder",
        "founder_bio": "Alexandra (née Johnson) has spent eight years in the ML tooling industry (starting with a 4-year stint as the first software engineer at @SigOpt) to help make the state of the art in machine learning effortless and easy to use. Before that, she worked on recommender systems in fashion tech. She founded Rubber Ducky Labs to be the suite of dream tools that she wished she had while working on recommender systems.",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/alexandraj777/",
        "x_url": "https://twitter.com/alexandraj777",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/026632f9ad081d2f434f06f2117ff2dd8c082677.jpg"
      },
      {
        "user_id": 1298927,
        "full_name": "Georgia Hong",
        "title": "Founder",
        "founder_bio": "Georgia got her degree in software engineering from the University of Waterloo, during which time she completed six internships including Datadog, Cockroach Labs, Instagram and SigOpt. After graduation, she worked on Security and ML Infra at Meta.",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/georgiahong/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ed1edaba5f6e87a1c69d598bcd6d1dc7233ac6a9.jpg"
      }
    ],
    "jobs": [],
    "news": [
      {
        "title": "The quest for better AI recommendation engines | TechCrunch",
        "url": "https://techcrunch.com/2023/06/27/rubber-ducky-labs-keeps-ai-engines-afloat/",
        "date": "Jun 27, 2023"
      }
    ],
    "launches": [
      {
        "id": 69112,
        "title": "Rubber Ducky Labs: Stop recommending ski jackets in June",
        "tagline": "Rubber Ducky Labs builds better recommender systems with machine learning plus human expertise",
        "body": "![uploaded image](/media/?type=post&id=69112&key=user_uploads/1164034/d71009b4-6b77-430f-a071-18fbccf522c5)\n\n**TL / DR;** Rubber Ducky Labs helps e-commerce companies avoid tone-deaf product recommendations — like featuring ski jackets in June. It works by combining machine learning with human expertise to produce the best product recommendations.\n\n![uploaded image](/media/?type=post&id=69112&key=user_uploads/1164034/3234f8dd-48e2-4edc-8525-f63699ee47e9)\n\n# Introduction\n\nCo-founders Alexandra and Georgia have over a decade of experience shipping products in fashion tech, B2B ML tooling, and high-scale data infrastructure, and are passionate about making the state of the art in machine learning effortless and easy to understand.\n\nAlexandra’s career started with her dream job working on clothing recommender systems for fashion tech companies, and she and Georgia founded Rubber Ducky Labs to be the suite of dream tools that they wished were available for building recommender systems.\n\n# The Problem\n\nYou’re a PM at a fashion tech startup. Your app is recommending that you buy ski jackets. It’s June.\n\nLooks like nobody told the algorithm that summer isn’t ski jacket season, and now it’s your job to figure out whether or not your algorithm will start driving away users. If your team’s metrics dashboards can’t answer the question, you’ll need to file a ticket for the data science team to run some analysis. Looks like it’s going to be at least a week before you have an answer.\n\n# The Solution\n\nWith Rubber Ducky Labs you’ll have an answer within minutes. Now, you’ll be able to understand whether you looked at a lot of ski jackets recently, so it’s just happening to you, or if your colleague recently flipped a switch to promote a brand that happens to carry a lot of ski jackets.\n\n![uploaded image](/media/?type=post&id=69112&key=user_uploads/1164034/918010a5-c9d2-49f6-b1a0-44086fb79f57)\n\nOur solution was developed from over a hundred conversations to answer the question of “what’s going on with my recommender system?” With Rubber Ducky Labs you can:\n\n* Explore your data visually - with product images\n* Drill down from aggregate metrics all of the way to individual item or user journeys\n* Consolidate and debug your company’s business logic\n* View annual and seasonal trends\n* Facet, segment, and filter and your data\n* View side-by-side comparisons of models or ranking changes\n\n# The Vision\n\nThe mission of Rubber Ducky Labs is to allow people with domain expertise — like product managers, merchandisers, marketers, growth hackers, and founders — to easily build intuition about and incorporate domain knowledge into their recommender systems.\n\nToday’s launch is just the first step. We want to help you do everything from consolidating business logic to previewing side by side model comparison to launching production experiments, all within RDL’s tools.\n\nIf this sounds like something you’re interested in, we’d love to build together.\n\n# Technical Details\n\nSetup took 90 minutes of time with our first user. Under the hood, Rubber Ducky Labs is a fully hosted web app that connects directly to your data warehouse on the backend to pull your custom metrics and data. No need to deploy any services or change any code, plus you get to bring your own model! Additionally, the web and API are authenticated with Auth0 to keep your data safe.\n\n# Our Ask\n\nWe’d love to learn more about your recommender system, and start identifying areas for improvement. Interested? Email [alexandra@rubberduckylabs.io](mailto:alexandra@rubberduckylabs.io) to get started.\n\nHave a friend who works with recommender systems? We’d love to meet them! Email us at [founders@rubberduckylabs.io](mailto:founders@rubberduckylabs.io).",
        "url": "https://www.ycombinator.com/launches/Hyi-rubber-ducky-labs-stop-recommending-ski-jackets-in-june",
        "votes": 52,
        "created_at": "2023-02-08T00:47:04.990Z"
      }
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  },
  {
    "id": 27763,
    "name": "Double – Coding Copilot",
    "slug": "double-coding-copilot",
    "former_names": [
      "Double"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/50e5a1022a2437ff5f516fa3afe9ed74fb7be3f4.png",
    "website": "https://double.bot",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Do you run into these problems with Github Copilot?\r\n- Bad completions that break your train of thought when you’re writing comments?\r\n- Doesn’t close brackets, or adds too many closing brackets?\r\n- Functions, variables, and libraries not being auto-imported after accepting a suggestion?\r\n- Multi-cursor mode not working?\r\n- Wish copilot could name your variables?\r\n- Wish copilot could trigger in the middle of a line?\r\n- Want to stop wasting time with GPT3.5 chat and default to GPT4?\r\n\r\nDouble is an high quality alternative to Copilot inside VS Code, engineered for performance. It’s designed with great craftsmanship by people who care a lot about getting the small details right.",
    "one_liner": "AI coding copilot engineered for performance",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1679084003,
    "tags": [
      "Developer Tools",
      "SaaS",
      "Chatbot",
      "Enterprise",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2023",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/double-coding-copilot",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/double-coding-copilot.json",
    "year_founded": 2022,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/double-ai",
    "x_url": "https://twitter.com/double_ide",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/50e5a1022a2437ff5f516fa3afe9ed74fb7be3f4.png",
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    "primary_partner": {
      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
    },
    "founders": [
      {
        "user_id": 1166534,
        "full_name": "Wesley Yue",
        "title": "Founder",
        "founder_bio": "– Founder at Double\n– Previously co-founder at Ninja (last mile robotics turned into full stack grocery delivery), and a bunch of robotics teams (Waymo, Kodiak, Kitty Hawk)\n – Engineering at Waterloo",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/wesleyyue/",
        "x_url": "https://twitter.com/WesleyYue",
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    "launches": [
      {
        "id": 74210,
        "title": "Double 🔍 Background research on sales prospects by searching the web with LLMs",
        "tagline": "Sales teams use Double to do background research on prospects. Instead of googling prospects one by one, Double uses language models to search the web and compile an answer, with citations.",
        "body": "# **TL;DR**\n\nIf you’re looking to answer questions about your sales prospects using information that’s on the web (news articles, LinkedIn profiles, company websites, financial filings, press releases), Double can look it up for you and use it to answer your questions in bulk.\n\n<https://www.youtube.com/watch?v=NeEMBCSZnYc>\n\n# **Researching and qualifying your sales prospects takes forever**\n\n* The information you need to qualify your leads lives in news articles, job posts, LinkedIn profiles, company websites, OpenCorporate, Crunchbase and other aggregators\n* Most of this can be manually Google’d, but doing so, plus reading it and formatting it the way you want it, takes time\n\n# **Background research your sales prospects by searching the web with LLMs**\n\n* Double searches the web using LLMs to compile verifiable answers. Every answer includes citations to reputable sources\n\n# **Companies use Double to answer hyper-focused qualifying questions**\n\n* Let’s say you’re selling tools for remote work, and you’re targeting remote-first companies.\n* Crunchbase/Linkedin/etc don’t have filters for “Remote-First?”, so you either:\n  * Broadly target companies and hope they do _some_ remote work – leads to poor conversion 🤞\n  * Or, google each company one by one and look at their job openings – tedious 😔\n* Instead, Double can search the web with language models and compile a verifiable answer with **citations**! 🔥\n\n# **Repeat Founders from Waterloo**\n\nBefore Double, we:\n\n* studied engineering at Waterloo\n* worked on autonomous vehicles at Waymo and Tesla, and\n* built Ninja, Canada’s first 10-minute delivery service. Ninja raised $2M and offered deliveries in 2 cities with a team of 80+ couriers before it was acquired in 2022.\n\n# **Let us automate your manual prospecting processes!**\n\n* Got a question you want answered about your prospects, or looking to save time in your prospecting process? Book a product tour with us!\n* Tell us about the most manual, time-consuming part of your sales process",
        "url": "https://www.ycombinator.com/launches/JIw-double-background-research-on-sales-prospects-by-searching-the-web-with-llms",
        "votes": 12,
        "created_at": "2023-08-18T05:51:59.351Z"
      },
      {
        "id": 70385,
        "title": "Double — Internet-capable GPT bots to automate repetitive work",
        "tagline": "Double is an assistant that can use Google to do research like: Which of these people are executives that work in finance, according to their linkedin profile?",
        "body": "# **TL;DR**\n\n# If you have a task that involves _search google_ → _read links_ → _answer question,_ Double can automate it for you.\n\n![uploaded image](/media/?type=post&id=70385&key=user_uploads/1247275/8551fc0f-01d6-44ec-b9db-9ef2a5516e50)\n\n# **What can you do with Double**\n\n* Given a list of chiropractor websites, find how many chiropractors work there. Don’t count admin staff\n* Given a list of business names, find their websites, addresses, and phone numbers\n* Given a list of Etsy stores, find the main category of the products they sell\n* Given a list of websites of recently funded startups, is this a business that does outbound B2B sales? (that would be interested in our b2b sales prospecting product?)\n\n# **Roadmap**\n\n* Our bots are essentially read-only on the web today, but we’re working on abilities to navigate the web and click buttons to do things like login and submit forms (helpful for things that don’t have an API!)\n* Parsing PDFs as an input\n* Calling REST APIs. On top of Google Search, Web Scraping, and GPT, we’ll be adding a plugin to make REST API calls, which will unlock every API and the ability to chain arbitrary code execution by calling your code on [repl.it](http://repl.it)\n\n# **Team**\n\nBefore Double, we :\n\n* Studied engineering at Waterloo\n* Worked on autonomous vehicles at Waymo and Tesla, and\n* Built Ninja, Canada’s first 10-minute delivery service. Ninja raised $2M and offered deliveries in 2 cities with a team of 80+ couriers before it was acquired in 2022\n\n# **Ask:**\n\n* Got a process you want to automate? [Try Double for free today](https://www.usedouble.com/), or reach out to us if you need a hand setting up\n* Share our [Twitter launch thread](https://twitter.com/geepytee/status/1636066726973702149?s=20) and our website on your Twitter, LinkedIn, Tiktok, or other social media! It really helps!",
        "url": "https://www.ycombinator.com/launches/IJF-double-internet-capable-gpt-bots-to-automate-repetitive-work",
        "votes": 39,
        "created_at": "2023-03-17T20:06:09.828Z"
      }
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  },
  {
    "id": 27774,
    "name": "Versive",
    "slug": "versive",
    "former_names": [
      "Mirio"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6c576ccab62c99fd845635ad445e0305d08a2681.png",
    "website": "https://www.getversive.com/",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "Versive is an all-in-one research platform that helps teams make faster customer-informed decisions.\r\n- Collect richer insights: AI-moderated studies that deliver interview-quality results at the survey speeds\r\n- Accelerate your analysis: AI-assisted analysis that instantly turns transcripts into shareable insights\r\n",
    "one_liner": "AI-first user research platform",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1677539488,
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      "B2B",
      "Design Tools",
      "Market Research",
      "AI"
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2023",
    "status": "Active",
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    "regions": [
      "United States of America",
      "America / Canada",
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      "Fully Remote"
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/versive",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/versive.json",
    "year_founded": 2022,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/versivehq",
    "x_url": "https://twitter.com/getversive",
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    "primary_partner": {
      "name": "Aaron Epstein",
      "url": "https://www.ycombinator.com/people/aaron-epstein"
    },
    "founders": [
      {
        "user_id": 239074,
        "full_name": "David Correa Orozco",
        "title": "Founder",
        "founder_bio": "David is the CEO of Versive. He started his career as a PM at Microsoft working on the Windows Build System. He then became one of the founding engineers at Bread (NYSE: BFH) where he developed multiple fin-tech products. Most recently, he spent the last 3 years working on Serverless Networking systems at Google Cloud. He is now focusing on building an AI-survey platform that enables teams to gather better user insights, faster.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/correa-david/",
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      },
      {
        "user_id": 322456,
        "full_name": "Eric Li",
        "title": "Founder",
        "founder_bio": "Eric is the co-founder of Versive. Previously, he led product and design at Vareto, designed marketplace products at Uber Eats, and was the first designer at Bread (NYSE: BFH). In a past life, he studied Economics at UChicago and was an investment banker at J.P. Morgan. ",
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      {
        "id": 83020,
        "title": "Versive - AI-powered synthesis for user interviews",
        "tagline": "Instantly turn user interviews into shareable reports and actionable insights.",
        "body": "We’re [Eric](https://www.linkedin.com/in/erictli/) and [David](https://www.linkedin.com/in/correa-david/), the founders of [Versive](https://www.getversive.com/).\n\n**tl;dr:** Versive now helps you turn user interviews and customer calls into ready-to-share reports. Upload your recordings to get shareable research reports with key quotes and actionable takeaways. Plus, use AI chat to dive deeper and get answers to specific questions.\n\n# **Problem**\n\nTalking to users helps companies make better decisions, but the process of conducting and analyzing user research is slow and manual.\n\nImagine you’re a researcher who just interviewed 10 users. To share your findings, you need to watch each recording, summarize the conversations, extract key themes and quotes, consolidate your notes into a single report, and then package everything into a polished document. It’ll take at least a week before you can share actionable insights with your team, and you’ll have spent hours that could have been used to drive actions or launch new studies.\n\n# **Solution**\n\n![uploaded image](/media/?type=post&id=83020&key=user_uploads/322456/bf2ff14a-662f-4762-be93-3ec32360a76b)\n\nVersive’s mission is to help companies make faster, customer-informed decisions by making it easier to conduct high-quality user research. Our [AI-moderated interviews](https://www.ycombinator.com/launches/K81-versive-ai-powered-surveys-that-collect-interview-quality-insights) have already helped leading brands gather in-depth feedback from thousands of users. However, we believe that human-moderated interviews are still key for capturing nuanced feedback and building customer empathy.\n\nThat’s why we’re launching a new product that enables research teams to instantly synthesize interview recordings into shareable reports and summaries.\n\n![uploaded image](/media/?type=post&id=83020&key=user_uploads/322456/4bd673aa-28a0-439e-a631-23f32c25dc7f)\n\n# **How it works**\n\n1. **Customize your reports:** Tailor the structure of your reports to fit the needs of your study, no coding or prompting expertise required.\n2. **Upload interviews:** Import audio/video recordings or VTT transcripts.\n3. **Get instant summaries:** You’ll get consistent, shareable summaries for each interview, complete with quotes and actionable takeaways.\n4. **Get an aggregate report:** We’ll also generate a report for your entire study, with citations that link back to your transcripts.\n5. **Chat with your results:** Have more questions? Chat with your study data and get immediate, citation-backed answers.\n\n![uploaded image](/media/?type=post&id=83020&key=user_uploads/322456/d8ce7917-30ea-4966-85d6-a746146e5410)\n\n## **Get in touch**\n\nWe’re already working with leading research, design, product, and customer experience teams to accelerate their user research. If you’d like to learn more:\n\n* [Request a demo on our website](https://www.getversive.com/) or reach out to us directly at [hi@getversive.com](mailto:hi@getversive.com).\n* [Follow us on LinkedIn](https://www.linkedin.com/company/versivehq/) for product and company updates.",
        "url": "https://www.ycombinator.com/launches/Lb2-versive-ai-powered-synthesis-for-user-interviews",
        "votes": 29,
        "created_at": "2024-08-14T01:39:13.325Z"
      },
      {
        "id": 77377,
        "title": "Versive - AI-powered surveys that collect interview-quality insights",
        "tagline": "We make it easy to gather high-quality user insights and customer feedback",
        "body": "**tl;dr:** _Versive makes gathering user insights and customer feedback easier. Our AI-powered surveys ask intelligent follow-up questions to give you interview-quality insights in a fraction of the time._\n\nHi everyone, we’re David and Eric, the founders of Versive.\n\n## **The problem**\n\nMost companies don't speak to their users enough, especially as they scale. As a result, it's difficult to make informed product and marketing decisions.\n\nIn Eric’s past life as a product manager and designer, he conducted dozens of user studies at startups and public companies. Each time, it took weeks of scheduling, interviewing, and synthesizing to get from questions to answers. As a result, his teams collected feedback and validated ideas far less than they would have liked.\n\nExisting tools don't solve this problem well. Interviews and focus groups are time-consuming and expensive to set up. Surveys only yield surface-level insights and are cumbersome to build. Even at companies with dedicated research teams, few requests get approved, leaving most PMs, designers, and marketers on their own.\n\n## **The solution**\n\n![uploaded image](/media/?type=post&id=77377&key=user_uploads/322456/1c77cc3e-958b-4f93-9803-ec92b67eadfe)\n\nVersive enables teams to collect interview-level insights at the scale and speed of a survey. We support voice interviews, dozens of languages, concept and design testing, structured questions, branding customization, and more.\n\n1. Build your survey in Versive, or ask our AI assistant to generate one in seconds.\n2. Our AI moderator administers your survey and asks intelligent follow-up questions to dig deeper into user responses.\n3. We'll auto-generate summaries and insights, plus give you transcripts for each response.\n\n![uploaded image](/media/?type=post&id=77377&key=user_uploads/322456/96a56e72-eb80-41d8-a926-8474268d77ce)\n\n## **Who is this for?**\n\nWhether you’re creating B2B software or selling consumer products, we can help.\n\n* **Product and design teams:** you'll validate designs, roadmaps, and requirements in hours instead of weeks.\n* **Marketing and customer teams:** you'll conduct market research and collect customer feedback more efficiently and with higher quality.\n* **Research teams:** you'll be able to offload simple requests so you can focus on high-value studies.\n\n## **Our team**\n\nWe're David Correa and Eric Li. We met as early employees of Bread (NYSE: BFH) and became fast friends. Eric is a designer and product manager who's experienced these problems firsthand at Uber and several startups. David is a software engineer who's worked at Google and Microsoft.\n\n## **Our asks**\n\n* If you’re interested in trying us out, sign up at [getversive.com](https://www.getversive.com/) or email us at [founders@getversive.com](mailto:founders@getversive.com) for a demo.\n* Follow us on [LinkedIn](https://www.linkedin.com/company/versivehq) or [Twitter](https://twitter.com/getversive) for product updates.",
        "url": "https://www.ycombinator.com/launches/K81-versive-ai-powered-surveys-that-collect-interview-quality-insights",
        "votes": 106,
        "created_at": "2024-01-09T22:16:01.952Z"
      },
      {
        "id": 69820,
        "title": "🪄 Mirio - Spin up personalized demos for your API product in minutes",
        "tagline": "Mirio is the easiest way to create personalized demos for your API product",
        "body": "**tl;dr: Mirio enables sales teams at API companies to spin up and personalize demo apps in minutes. Stop demoing docs and show every customer a personalized use case.**\\\n[**👉 Book a demo**](https://trymirio.com)\n\nHi everyone, we’re [David Correa](https://www.linkedin.com/in/correa-david/) and [Eric Li](https://www.linkedin.com/in/erictli/), the founders of Mirio.\n\nMirio is a demo platform for sales teams at API companies. Instead of bugging engineers to build custom demos or screen-sharing documentation, sales teams can use our no code-platform to clone, deploy, and personalize demo apps in minutes.\n\n### **For sales teams selling API products**\n\nWe spoke to account executives and SDRs at API companies and heard the same problems:\n\n* Developers are okay with documentation but decision-makers want to visualize the impact on their business and product.\n* Sales tries to convince engineers and designers to create custom demos but are usually told no (When David and I were asked to help create demos, we hated it too)\n* As a result, they only personalize demos for top prospects and end up demoing the same documentation and code for most customers, which often doesn’t land.\n\n### **Create personalized demos in minutes with Mirio**\n\n![uploaded image](/media/?type=post&id=69820&key=user_uploads/322456/74b71732-cae7-4f78-a69e-c02341ab8cb3)\n\nMirio empowers sales teams to spin-up and personalize real apps (connected to your API) so they can convey the magic of your product to every customer.\n\n1. Connect your demo apps to Mirio, we’ll help you set them up so they can be customized.\n2. From your Mirio dashboard, account executives and SDRs can clone and deploy demo apps in one click. They can then personalize branding, content, and more using our no-code editor.\n3. Use your personalized demos in live meetings, SDR outreach, website embeds, leave-behinds, and more. Track demo engagement from your dashboard.\n4. Wow more customers and close more deals! **🚀**\n\n### **Why us?**\n\nDavid and Eric met at as early employees of Bread Financial (NYSE: BFH) where the sales team bugged us every week to help create custom demos for Bread’s developer-facing product. This was time-consuming and painful but we saw the impact that personalized, interactive demos had on closing deals.\n\nOutside of Bread, we’ve also built software, designed products, and led teams at companies like Google, Microsoft, Uber, and Vareto.\n\n### **We’d love to chat**\n\n* If you’re selling an API product and want to personalize demos with the least amount of effort, book a demo at [trymirio.com](http://trymirio.com) or email us at [founders@trymirio.com](mailto:founders@trymirio.com).\n* If you’re not, we’d love intros to anyone who is.\n\nFor us, demos are the first step in helping to improve sales and onboarding for API products. If you have related challenges or a unique use case you’re not sure we can solve, reach out ([founders@trymirio.com](mailto:founders@trymirio.com)). We’d love to chat and see if we can build a solution around your problem.",
        "url": "https://www.ycombinator.com/launches/IA8-mirio-spin-up-personalized-demos-for-your-api-product-in-minutes",
        "votes": 77,
        "created_at": "2023-03-01T18:01:30.590Z"
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    "long_description": "Narrative is the easiest way to create end-to-end tests, replacing Playwright, Selenium, and Cypress with self-healing tests.\r\n\r\nRecord your user journeys to deploy tests in minutes, and let our agents handle flaky selectors and timing issues. When a test fails, you get a bug report in plain English that's easy to triage.\r\n\r\nTrusted by Nanonets, Commenda, Drumkit, Metal, and Vega.\r\n\r\nLearn more at www.trynarrative.com",
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        "full_name": "Suchit Dubey",
        "title": "Founder",
        "founder_bio": "CEO@Narrative. Previously Uber Freight, Crew, Thumbtack, Palantir and Ridecell.",
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        "linkedin_url": "https://www.linkedin.com/in/dubeysuchit/",
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        "url": "https://www.ycombinator.com/companies/narrative/jobs/AUF5OZd-founding-engineer-backend-ai",
        "location": "Bengaluru, KA, IN / Bengaluru, Karnataka, IN / Remote (IN)",
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    "name": "PoplarML",
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    "website": "http://poplarml.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "PoplarML lets you deploy any machine learning model to a fleet of GPUs as a ready-to-use and scalable API endpoint with one command.",
    "one_liner": "Deploy Machine Learning Models with One Command",
    "team_size": 2,
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    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1674681330,
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    "year_founded": 2022,
    "city": "San Francisco",
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        "full_name": "Danna Liu",
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        "founder_bio": "Co-Founder of PoplarML, Previously Research @ Snap, SWE @ Stripe, Coinbase, Microsoft, PagerDuty",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/dnaliu",
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        "full_name": "Evan Chu",
        "title": "Founder",
        "founder_bio": "Co-Founder @ PoplarML. Previously SWE @ Stripe, Amazon, AWS",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/evan-j-chu/",
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      {
        "id": 69447,
        "title": "🌳 PoplarML – Deploy machine learning models with one command",
        "tagline": "Deploy any machine learning model to a fleet of GPUs as a ready-to-use and scalable API endpoint with one command",
        "body": "👋 Hey Everyone, this is Danna and Evan, and we’re super excited to introduce PoplarML!\n\n### 📖 **TL;DR**\n\nBuilding deployment infrastructure for machine learning models is difficult and time-consuming. With PoplarML, you can replace that process with one simple command. We handle all of the infrastructure to deploy and serve at scale, enabling you to focus on building your product.\n\n### ❌ **The Problem**\n\nAI-powered products have grown in popularity but many are deterred by the challenges to bring their models to life. Deploying a machine learning model to production is complex and requires a heavy engineering lift. Building the infrastructure to support ML models takes days, increasing the time to ship your product. \n\n## ⚡ **The Solution**\n\nPoplarML helps teams easily deploy custom machine-learning models to production. With one simple CLI command, you can turn your model into an API endpoint that you can integrate with the rest of your product. Our endpoints come with auto-scaling out of the box, ensuring low-latency when there are bursts of requests to your model.\n\nPoplarML can deploy any custom model, regardless of the framework used. Some examples of models that our customers have deployed on PoplarML are: \n\n* Flan-T5-XXL\n* Whisper\n* Stable-Diffusion-2\n\n### 🤖 **How it Works**\n\n1. ✏️ Define a Load and Predict function in a [main.py](http://main.py) file\n2. 💻 Use our CLI tool to pick a GPU instance and deploy your model\n3. 🚀 Use the returned API endpoint in your product\n\n![uploaded image](/media/?type=post&id=69447&key=user_uploads/522488/30758efd-4ce3-48d0-94be-e43093ad027f)\n\n### 💡 **Why PoplarML was Built**\n\nWe have personally felt the pain of deploying models to production and have previously built ML deployment infrastructure at companies such as Amazon and Snapchat. With PoplarML, we would like to provide a better and more streamlined experience for ML development. \n\n### **🙌 Our Asks**\n\n* Reach out via our [contact us](https://poplarml.com/contact.html) form or book a time directly on our [calendly](https://calendly.com/poplarml/15min) if you want to try PoplarML\n* Share this with anyone you know building AI-powered products or companies\n* Upvote and share this post!",
        "url": "https://www.ycombinator.com/launches/I47-poplarml-deploy-machine-learning-models-with-one-command",
        "votes": 297,
        "created_at": "2023-02-20T18:57:45.405Z"
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    "id": 27837,
    "name": "Pirros",
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        "full_name": "Ari Baranian",
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        "title": "Pirros, a startup that applies AI to streamline drawing sets for buildings and infrastructure, lands $2 million seed round | VentureBeat",
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        "title": "🏗️ Pirros - Detail Management System for Construction Designers",
        "tagline": "Pirros helps structural engineers and architects easily and quickly reference all their company's previous work so that they are never designing the same detail twice. ",
        "body": "Hey YC!\n\nWe're Ari and Peter, co-founders of Pirros. Pirros is a detail management system for structural engineers and architects. Our goal is to make it easier to use the knowledge from previous projects to save time on future projects.\n\n### 😬 **The Problem**\n\nConstruction design companies (structural engineering and architectural firms) are wasting time redesigning the same detailing conditions. \"Details\" are the micro-level blueprints of a construction building, for example a beam to column connection, or a wall assembly (see below). Each construction project has 100s of details, half of which are recreated for each project. 90% of these detailing conditions have been encountered and designed on one of the company's previous projects, the designer just doesn't have easy access to them.\n\n![uploaded image](/media/?type=post&id=67836&key=user_uploads/1099489/4cc5fe6a-4748-482f-b0a0-2928c858a807)\n\n#### ✅ **Our Solution**\n\nOn our platform, companies store the details from all their previous projects in a single cloud-based location (see below). Now, engineers and architects can quickly access any detailing condition just as easily as a google search, instead digging through all their past projects on their file server looking for a needle in a haystack.\n\n![](https://t36258466.p.clickup-attachments.com/t36258466/cc2dcd32-cf02-4184-ae29-8275e69fa288/Website.png)\n\n#### ⚒️ **How it works**\n\nOur software integrates with Revit (the industry standard drawing production software), and extracts each detail and all the metadata associated with it, so that there is enough information automatically stored with each detail to make them searchable. Designers come to our website, search and filter down to find the detailing condition they need for their current project, and then download the detail straight into Revit.\n\n#### 🙏 **The Ask**\n\nWe are continuing to onboard new customers and would love warm intros to structural engineers or architects. Or, if YOU are a structural engineer or architect, please reach out to us and we would love to set up a demo.\n\nThanks!",
        "url": "https://www.ycombinator.com/launches/He8-pirros-detail-management-system-for-construction-designers",
        "votes": 19,
        "created_at": "2022-12-12T18:18:44.778Z"
      }
    ]
  },
  {
    "id": 27852,
    "name": "Frigade",
    "slug": "frigade",
    "former_names": [
      "Ombord"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2ebf166f7f6e8f6d186e2ea4a16a6cf16becaf7b.png",
    "website": "https://frigade.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Frigade AI is an in-app assistant that intelligently guides and onboards your users through your product. Our agent learns your product's interface, gives contextual guidance that adapts to each user, and takes actions directly on your users' behalf.\r\n\r\nLearn more at Frigade.com",
    "one_liner": "AI-powered product assistance for modern software teams",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1672157010,
    "tags": [
      "SaaS",
      "Customer Success",
      "Customer Service",
      "AI",
      "AI Assistant"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2023",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/frigade",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/frigade.json",
    "year_founded": 2022,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/frigade",
    "x_url": "https://twitter.com/FrigadeHQ",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/FrigadeHQ",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/2ebf166f7f6e8f6d186e2ea4a16a6cf16becaf7b.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": null,
    "founders": [
      {
        "user_id": 123251,
        "full_name": "Eric Brownrout",
        "title": "Founder",
        "founder_bio": "Eric is the co-founder and CEO of Frigade. Before founding Frigade, Eric co-founded Perform, a mobile app to help runners reach their goals through a combination of AI and 1:1 human coaching. Prior to that, he worked in product management at Digit where he helped launch an AI-powered mobile banking app and at LinkedIn where he managed an intelligent communications platform for notifications and email.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/ebrownrout/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/372320b943518c5b75b9176dedc464f4cf241e83.jpg"
      },
      {
        "user_id": 265839,
        "full_name": "Christian Mathiesen",
        "title": "Founder",
        "founder_bio": "Christian is the co-founder and CTO of Frigade. Before founding Frigade, Christian co-founded Perform, a platform to help runners reach their goals through a combination of AI and 1:1 human coaching. Prior to that, he worked in engineering at LinkedIn where he helped launch LinkedIn's Skills-based hiring products and LinkedIn's Hiring Platform.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/cmathies/",
        "x_url": null,
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f1a02aca7bf268e8a6f107251cac7301fdb7d5e8.jpg"
      }
    ],
    "jobs": [],
    "news": [
      {
        "title": "Frigade secures $2.7M in funding for React-based onboarding solution - SiliconANGLE",
        "url": "https://siliconangle.com/2023/07/20/frigade-secures-2-7m-funding-react-based-onboarding-solution/",
        "date": "Jul 20, 2023"
      }
    ],
    "launches": [
      {
        "id": 114338,
        "title": "Frigade Assist API - give your AI agent the ability to generate in-product guides and support",
        "tagline": "Register Frigade as one tool and your agent can generate in-product guides on demand, or answer questions grounded in how your product actually works today.",
        "body": "Hi everyone, Christian and Eric here, co-founders of Frigade (W23).\n\nToday we are launching the Frigade Assist API, which levels up your own AI agent to better onboard and support your users with a single tool call.\\\n<https://www.youtube.com/watch?v=-j7wd0gYS2M>\n\n**PROBLEM**\n\nMore and more teams are building their own agents. When a user gets stuck and needs help, companies tend to go one of two ways.\n\n1. Buy a help agent (Frigade Assistant, Fin, etc.). Now you have two agents and two chatboxes, and your users cannot tell which one to use for what.\n2. Have your own agent handle it. Agents in that case usually answer out of a knowledge base or help center with basic RAG. Docs are stale or incomplete more often than not, and even when the snippet is right it puts the work back on the user, who has to read it and then figure out how to apply it in the app.\n\n**SOLUTION**\n\nWe already solved the docs problem with Frigade. Our browser agent signs in to your product with the same permissions a real user has, works through your real workflows, and maps how your product works. No manual documentation or screenshots to take. It trains again every time you ship, so it always knows the version of your product that's live.\n\nNow, with the Assist API, we can solve the two-agent problem too.\n\nThe Assist API a single tool call. Your agent calls it and gets back an answer grounded in how your product behaves today, or a personalized walkthrough rendered on the page the user is already on. For most AI agent frameworks, you can add it with just these lines of code:\n\n```\nimport { frigade } from '@frigade/ai'\n \nconst frigade_guide_tool = {\n  description: 'Call this tool to answer product ' +\n    'questions or guide the user through a task.',\n  parameters: {\n    query: {\n      type: 'string',\n      description: 'What the user is asking or wants to do',\n    },\n  },\n  run: ({ query }) => frigade.assist({ query }),\n}\n \n```\n\nThe SDK forwards the call to the browser and Frigade acts on the page the user is on, highlighting the real element with the next step attached. Your agent decides when to call it and stays the only thing your user talks to.\n\nWhat you get with it:\n\n1. **Personalized in-product guides**, generated on demand. A new user gets walked through first-time setup without leaving the page. Someone stuck mid-workflow gets shown the next step instead of a link to an article.\n2. **Visibility and control for the people who own support**. Your support and product teams see who Frigade is helping and where, and can steer the output without any engineering help.\n\nWe are already working with Retell AI to extend their agent's onboarding capabilities. They build agents for a living and still chose to plug in Frigade rather than build something like this themselves.\n\nThis is for teams who already own an agent and care about product adoption. And if you do not have an agent, our drop-in Frigade Assistant is still the fastest path.\n\nIf you want to give it a spin, reach out and we'll get you a demo. <https://frigade.com/assist-api>\n\nChristian and Eric",
        "url": "https://www.ycombinator.com/launches/TkA-frigade-assist-api-give-your-ai-agent-the-ability-to-generate-in-product-guides-and-support",
        "votes": 4,
        "created_at": "2026-09-08T22:26:18.625Z"
      },
      {
        "id": 105121,
        "title": "Frigade Skills: the in-app AI agent that learns your product and acts for your users",
        "tagline": "Frigade learns your product by using it, then takes real actions for your users through Skills your team approves with no code.",
        "body": "Hi everyone, Eric and Christian here, co-founders of [Frigade](https://frigade.com) (W23).\n\nFrigade is an AI agent that lives inside your product and [guides users through it](https://frigade.com/blog/product-help-where-users-stuck). Point it at your app and it learns your UI in minutes. You don't wire anything up or write docs.\n\n**Today we're launching a major new upgrade to our agent called [Skills](https://frigade.com/features/skills).**\n\nSo far, Frigade has guided users and [answered their questions](https://frigade.com/blog/how-to-deflect-support-tickets). With Skills, it can take real actions for them too: looking things up, creating, editing, deleting.\n\nSkills are the actions Frigade figures out on its own while it trains on your product. It documents each one, your team approves it with no code from the dashboard, and from then on Frigade runs it for any user who needs it. You can still wire in your own custom tool calls with our SDK, too.\n\n<https://www.youtube.com/watch?v=bi-BFV7M7eY>\n\nIf you've used Linear's AI agent, Frigade is that as an embed: the same kind of in-app agent, dropped into your product with [one snippet](https://frigade.com/blog/walkme-alternatives-without-six-month-rollout). You get about 80% of it out of the box, with no eng work required.\n\n**How it works:**\n\n1. Add the snippet. Frigade starts using your product and learns it, like a new user would.\n2. It turns the actions it finds into Skills. Your team reviews and approves them, no code.\n3. Frigade runs those Skills for your users and answers their questions as they go.\n\n**Here it is running on popular products we don't embed in.**\n\nWe just pointed it at each one and let it learn to see how it performed:\n\n* [Jira](https://demo.frigade.com/?skill=jira)\n* [Spotify](https://demo.frigade.com/?skill=spotify)\n* [Hacker News](https://demo.frigade.com/?skill=hackernews)\n\n**Frigade is best for:**\n\n* Teams drowning in \"how do I...\" tickets\n* CS teams who want [onboarding](https://productonboarding.com/articles/what-is-product-onboarding) to happen without a call\n* Product teams who want every feature to be [self-serve](https://productonboarding.com/examples)\n* Anyone with a complex product or non-technical users who keep getting stuck\n\nMany teams are also building their own agents in-house. If that's you, we're launching the Frigade API soon so you can add our generative assistance capabilities into your agent. More on that soon.\n\nIf your product's complex or your users aren't super technical, we'd love to show you what Frigade does on your actual app. Send us a note, or book a demo at [frigade.com](http://frigade.com).\n\nEric &amp; Christian\n\n![uploaded image](/media/?type=post&id=105121&key=user_uploads/123251/18d6ac08-4814-47bc-b966-4268a0da843a)\n\n",
        "url": "https://www.ycombinator.com/launches/RLV-frigade-skills-the-in-app-ai-agent-that-learns-your-product-and-acts-for-your-users",
        "votes": 9,
        "created_at": "2026-07-09T17:34:23.119Z"
      },
      {
        "id": 95912,
        "title": "Frigade: Product onboarding that builds itself",
        "tagline": "The help center is dead. Your product is the teacher now.",
        "body": "Hey everyone, we are Eric and Christian, founders of [Frigade](https://frigade.com).\n\n**TL;DR:** Frigade automatically learns your product and provides expert, in-product assistance to users. Now with Suggestions, Frigade can proactively teach your users in the context of the product itself.\n\nhttps://youtu.be/FhHSj8YpR2U\n\n# **🔴 The problem**\n\nMany users never see the best parts of a product. Teams try to fix this but run into the same issues:\n\n* Onboarding flows take too long to build\n* Feature tours get stale as the product changes\n* Users ignore help docs :( \n* Customer Success loses hours teaching users on Zoom\n* Product teams rely on outdated screenshots, Looms, and Slack to explain the product\n\nIn-product guidance should be easy to create and maintain, but today it is neither.\n\n# **🟢 The solution**\n\nFrigade automatically learns your product by using it, and Suggestions create guidance directly inside your product from simple prompts.\n\n![uploaded image](/media/?type=post&id=95912&key=user_uploads/123251/af21223e-4d69-40f8-9cc3-c34827827206)\n\nWrite what you want users to learn:\n\n“Show users how to use the new Calendar view in the Sales tab. Walk users through the key features.”\n\nFrigade understands the latest version of your product and generates the experience directly from that context. You do not need a help center, articles, or any existing documentation for Frigade to work. It learns directly from the product itself.\n\nNo user flows. No element targeting. Nothing to wire up.\n\nYou can create:\n\n* Onboarding for new signups\n* Guided tours for new features\n* Help for confusing parts of the UI\n* Workflows for power users\n* Role or plan specific nudges\n* Contextual support at the right moment\n\nEverything runs inside your real product and stays accurate as it evolves, without depending on any external help documentation or content.\n\n# **🧪 Preview, refine, publish**\n\nInstantly preview Suggestions to watch the experience run in your product. Tweak the prompt to adjust the tone or structure. Choose who should see it and publish. Users will see it at the right moment and can launch the experience instantly.\n\n# **🧵 Who is using it today**\n\nTeams across SaaS, AI, fintech, marketplaces, and more use Frigade to:\n\n* Onboard users without a human in the loop\n* Increase feature adoption\n* Reduce support tickets\n* Walk customers through complex workflows\n* Educate users inside the product rather than sending them elsewhere\n\n# **🚀 Try it out**\n\nFrigade Suggestions are live today. Create your first in-product experience from a single prompt [**https://frigade.com**](https://frigade.com)\n\nWe’d love your feedback or questions: [founders@frigade.com](mailto:founders@frigade.com)",
        "url": "https://www.ycombinator.com/launches/Owy-frigade-product-onboarding-that-builds-itself",
        "votes": 28,
        "created_at": "2025-12-02T15:44:08.899Z"
      },
      {
        "id": 92353,
        "title": "Frigade AI: In-app support agent that adapts to your product automatically",
        "tagline": "Frigade AI uses your product to learn how it actually works, then guides users with live, step-by-step support directly inside the UI—right when they need it.",
        "body": "**TL;DR: Frigade AI** is an in-app agent that keeps users moving forward with contextual, real-time guidance. It can generate step-by-step tutorials for complex workflows, highlight relevant features at the right moment, and even take actions directly on users' behalf to eliminate friction. Unlike traditional chatbots that rely on outdated help center documents, Frigade AI learns your product by actually using it and automatically adapts to every product update without any work from your team.\n\n📅 Book a demo → [calendar](https://cal.com/forms/ed0e923f-6f00-4191-a08f-7bebba6636b6)\n\nhttps://www.youtube.com/watch?v=8SjL4OfPs3I\n\n### **The Problem**\n\nMost onboarding tools assume users follow a perfect path. They don’t. Users skip steps, explore features early, and ask questions that don't fit your predefined paths.\n\nSupport teams can’t scale to handle every question. Engineering teams don’t have time to build and maintain hardcoded walkthroughs. And most AI chatbots fall short, offering generic responses based on outdated help center docs. \n\nWhat users actually need is guidance **in real time**, **in context**, and **on demand**. Not just during sign-up, but throughout their entire journey.\n\n### **The Solution**\n\nToday, we’re officially launching [**Frigade AI**](http://frigade.ai), a fully integrated agent that lives inside your product and helps users get personalized support instantly. \n\nUnlike traditional chatbots, Frigade AI learns your product by actually _using_ it. It explores your interface, navigates your workflows, reads your documentation, and builds a working model of how your product functions. Just like a real user would.\n\nThe goal? **Help users succeed from their first session** and keep them unblocked at every step.\n\nIt works alongside everything you’ve already built, like checklists, tours, help centers, and fills in the gaps with real-time support when your users need it most. Frigade AI:\n\n* **Unblocks users instantly** with dynamic step-by-step guides for any workflow\n* **Eliminates friction** by taking product actions directly for users\n* **Answers open-ended questions** with contextual product support\n* **Escalates seamlessly** to Zendesk, Intercom, and other live support tools\n* **Gets running in under an hour** with minimal engineering effort\n* **Stays current automatically** as your product evolves\n\nhttps://www.youtube.com/watch?v=usspoSsWIb4 \n\nThe result is an AI agent that **turns every user into a power user,** removing confusion and guiding users to success.\n\n### **See It in Action**\n\nIf you're building a web app and want to better support users at scale, without scaling your existing support team, we’d love to show you what we’re working on. \n\n🔗 Check out our website at [https://](https://frigade.ai)[frigade.ai](http://frigade.ai)\\[\\\n\\](https://frigade.ai) 📅 Book a demo → [calendar](https://cal.com/forms/ed0e923f-6f00-4191-a08f-7bebba6636b6)\n\n![uploaded image](/media/?type=post&id=92353&key=user_uploads/123251/ef0698cc-01a2-4f96-97e6-f0c2a151ec6e)\n\n",
        "url": "https://www.ycombinator.com/launches/O1Z-frigade-ai-in-app-support-agent-that-adapts-to-your-product-automatically",
        "votes": 17,
        "created_at": "2025-07-22T15:51:42.115Z"
      },
      {
        "id": 85509,
        "title": "Trench: Open Source Analytics Infrastructure 🌊",
        "tagline": "Fast and scalable. No bloat. GDPR compliant. Powered by ClickHouse and Kafka.",
        "body": "Hey everyone! We’re Christian and Eric from Frigade. [Trench](https://trench.dev) is open source analytics infrastructure for tracking events, identifying users, and querying data in real time.\n\nIt’s built on top of ClickHouse and Kafka for speed and scale, and it can be deployed with a single production-ready Docker image. Trench is a major part of Frigade’s infrastructure and powers our own in-product analytics and user targeting for millions of end users.\n\nThe code is MIT-licensed at <https://github.com/frigadehq/trench>. We just launched, and Trench gained over 1,000 GitHub stars ⭐ in less than a week.\n\n![uploaded image](/media/?type=post&id=85509&key=user_uploads/123251/443f6361-9b1a-45d5-921e-e79504ebdcea)\n\n# **Demo:**\n\nCheck out our open source demo to see how to build your own version of a Google Analytics dashboard powered by Trench in less than 15 minutes.\n\n<https://demo.trench.dev/>\n\n![uploaded image](/media/?type=post&id=85509&key=user_uploads/123251/049bc7b3-bd4a-4038-8128-faa2a8e2cc67)\n\n# **🚨 The Problem: Postgres doesn't scale for tracking and querying millions of events at scale**\n\nAs we’ve scaled [Frigade](https://frigade.com) to millions of end users, our Postgres table we used for event tracking was quickly ballooning in cost and becoming a performance bottleneck. Many companies run into the same problem as us (e.g. [Stripe](https://brandur.org/fragments/events), [Heroku](https://brandur.org/fragments/events)). \\\nEngineers start by adding a basic events table to their relational database, which works at first, but breaks down as the user base scales. It's usually the biggest table in the database, the slowest one to query, and the longest one to back up. Postgres (or MySQL for that matter) simply isn't a good solution for tracking and querying events in real time at 1M+ end users scale.\n\n# **The Solution: Fast, scalable, and affordable event tracking**\n\nWe knew we wanted to move to technologies like Kafka and ClickHouse that are purpose-built for ingesting and querying thousands of events per second. When we looked for existing solutions, all the existing OSS projects we found were either bloated with unnecessary features, UIs and spaghetti code, or simply antiquated. So we built Trench.\\\nWith Trench, we've put together a single Docker image that provides a production-ready tracking event table that scales. When we migrated our tracking table from Postgres to Trench, we saw a 42% reduction in cost to serve on our primary Postgres cluster and eliminated all lag spikes from autoscaling under high traffic. We're happy with how Trench has solved event tracking for us, and now we’re excited to share that with other teams.\n\n### **Core Features**\n\n* Compliant with the Segment tracking specifications\n* Can handle thousands of events per second on a single node\n* Query tracking data in real-time with read-after-write guarantees\n* Send data anywhere with throttled and batched webhooks\n* Single production-ready Docker image\n* Easily plugs into cloud-hosted ClickHouse/Kafka solutions\n\n### **Use cases**\n\nWhat can you build with Trench? There are many use cases:\n\n1. **Real-Time Monitoring and Alerting** – Monitor your services and get alerts through tracking custom events like errors, usage spikes, or specific user actions, and send that data anywhere with webhooks.\n2. **Event Replay and Debugging –** Capture all user interactions in real time for event replay services.\n3. **A/B Testing Platform** – Capture events from different users and groups in real time. Segment users by querying in real time and serve the right experiences to the right users.\n4. **Product Analytics for SaaS Applications** – Embed Trench into your existing SaaS product to power user audit logs or tracking scripts on your end-users' websites\n5. **Build a custom RAG AI model** – Easily query event data and give users answers in real time. LLMs are really good at writing SQL.\n\n# **Try it out and give us a star ⭐**\n\nWe hope you’ll find Trench useful if you’re facing or have ever experienced a similar problem with analytics at scale. Here are some links to get started:\n\n* Trench website: <https://trench.dev>\n* Quickstart guide: <https://docs.trench.dev/quickstart>\n* Github repo: <https://github.com/FrigadeHQ/trench>\n* Product demo: <https://demo.trench.dev>",
        "url": "https://www.ycombinator.com/launches/MFB-trench-open-source-analytics-infrastructure",
        "votes": 9,
        "created_at": "2024-11-12T22:22:46.640Z"
      },
      {
        "id": 78903,
        "title": "Frigade – Growth platform for modern software teams",
        "tagline": "Frigade is a low-code tool for building product growth loops",
        "body": "# **tl;dr**\n\n[Frigade](http://frigade.com) is a low-code tool for building product growth loops. It comes with pre-built React UI components, a web app, and flexible APIs. Our customers use Frigade to build product growth experiences similar to those used by companies like [Notion](https://www.productonboarding.com/notion-feature-announcement), [Github](https://www.productonboarding.com/github-embedded-promotions?view=components), and [Mercury](https://www.productonboarding.com/mercury-new-user-onboarding).\n\n![uploaded image](/media/?type=post&id=78903&key=user_uploads/123251/7ac8ec05-e94e-4f88-93c2-561aae34289d)\n\n\\---\n\n# **Founding Story**\n\nOur team first met at LinkedIn where we built internal tooling to help accelerate company growth. Turns out many of the best companies in the valley also had large growth teams dedicated to building the same powerful tooling.\n\nThese platforms made it easier to ship new experiences with functionality like user targeting, air traffic control, state management, admin tooling, and much more.\n\nHowever, many companies lack the resources to develop this kind of tool. With Frigade, we are building the growth platform we wished we had everywhere we’ve worked since LinkedIn, and we’re making it available to all teams.\n\n\\---\n\n# **What kind of experiences can Frigade power?**\n\n* **Onboarding forms** — like Typeform, but native\n* **Product checklists** for user activation\n* **Guided tours** for feature adoption\n* **Announcements** for engagement and adoption\n* **House Ads** to nudge users toward upgrades and adoption\n* **Surveys** for user research and account enrichment\n* **Custom Flows** to power unique in-app experiences\n\n\\---\n\n![uploaded image](/media/?type=post&id=78903&key=user_uploads/123251/cc206e9a-c6cf-4e23-ade4-d1a8b60e924a)\n\n# **How does Frigade work?**\n\nFrigade combines React components, an admin dashboard, and flexible APIs to allow teams to build growth loops, faster.\n\n**React UI Components**\n\nFrigade includes a library of beautiful, pre-built React UI components based on industry best practices. Our components are fully customizable to your brand and product so they feel seamless.\n\n**Web App**\n\nFrigade’s web app helps technical and non-technical users alike with user targeting, performance metrics, user and account progress, and more. Frigade integrations help you connect tools like Mixpanel and Segment with a few clicks.\n\n**Flexible APIs**\n\nThe Frigade API is designed to give teams full control over their experience, unlike rigid no-code tools. Teams can even use our APIs to build fully custom Flows.\n\n\\---\n\n### **Our asks:**\n\n* **Sign up** for free at [frigade.com](http://frigade.com) to get started\n* **Grab a demo** with our team [here](https://cal.com/team/frigade/frigade-demo) to discuss your use cases",
        "url": "https://www.ycombinator.com/launches/KWd-frigade-growth-platform-for-modern-software-teams",
        "votes": 10,
        "created_at": "2024-02-29T17:52:18.262Z"
      },
      {
        "id": 68103,
        "title": "💻 Frigade - The easiest way for developers to build product onboarding.",
        "tagline": "Frigade helps developers build better native onboarding and product education, faster. ",
        "body": "**_TL;DR_** _Frigade helps developers build best-in-class product onboarding and education_ faster. _Check us out at_ [_frigade.com_](http://frigade.com)_!_\n\n![uploaded image](/media/?type=post&id=68103&key=user_uploads/123251/acaad972-6a2d-45b3-817c-00685b328449)\n\nHello everyone! We’re [Christian](https://www.linkedin.com/in/cmathies/) and [Eric](https://www.linkedin.com/in/ericbrownrout/). We’ve been working together since 2015 when we first met as interns at LinkedIn, and we’re excited to be building Frigade. Our goal at Frigade is to make it easy to build great product onboarding so developers can spend more time building their core product experiences.\n\n![uploaded image](/media/?type=post&id=68103&key=user_uploads/123251/c42721d4-9f20-4993-b0ce-cac1c7a69fe2)\n\n### **🔴 Problem: Product Onboarding is Hard**\n\nProduct onboarding is essential to customer activation and retention, but building great onboarding is difficult and time consuming. We know because we experienced this problem firsthand at our previous startup where we spent enormous amounts of time building onboarding and education for our app through trial and error. Time that could’ve been spent developing our core product offering.\n\nㅤ\n\n### **🟢 Solution: Powerful API and Open Source SDK**\n\nFrigade’s API and open source SDK take the hard work out of building and scaling great product onboarding. With Frigade, developers can:\n\n* 🛠️ Quickly build beautiful onboarding within their own app UI\n* 🔄 Ingest onboarding data from our API into their backend\n* ⚡ Make instant changes to copy, assets, and logic via API\n* 🎯 Easily build user targeting (powered by Segment, MixPanel, etc.)\n* 📚 Automatically leverage built-in industry best-practices\n\nAs a result, developers can spend less time building features for product adoption and more time building the product roadmap.\n\n![uploaded image](/media/?type=post&id=68103&key=user_uploads/123251/e768b350-e12d-4e11-976b-042f82f1def3)\n\n![uploaded image](/media/?type=post&id=68103&key=user_uploads/123251/52788266-214c-4314-a0a9-dc7d270afdde)\n\n[_Frigade SDKs_](https://github.com/FrigadeHQ) provides beautiful, extensible boilerplate for critical flows.ㅤ\n\n### **💻 Try it yourself**\n\nCheck out our [GitHub page](https://github.com/FrigadeHQ) and [website](https://frigade.com). We’re here to help! Feel free to contact us at [founders@frigade.com](mailto:founders@frigade.com) with any questions regarding implementation, feature requests, or to chat generally about your product onboarding needs. And if you’re in San Francisco, come say hey!\n\nㅤ\n\n**Thanks!**\n\nEric and Christian",
        "url": "https://www.ycombinator.com/launches/HiR-frigade-the-easiest-way-for-developers-to-build-product-onboarding",
        "votes": 35,
        "created_at": "2022-12-28T22:08:51.477Z"
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    "id": 27860,
    "name": "Dream3D",
    "slug": "dream3d",
    "former_names": [
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    "website": "https://dream3d.com",
    "all_locations": "New York City, NY, USA",
    "long_description": "Dream3D is an AI research lab that builds tools to help humanity predict the future.",
    "one_liner": "We build tools to help humanity predict the future.",
    "team_size": 3,
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    "subindustry": "B2B -> Engineering, Product and Design",
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        "full_name": "Tony Francis",
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        "founder_bio": "Tony is a second-time YC founder. Currently, he is the founder & CEO of Dream3D building generative models to simulate virtual worlds. His previous company, Inokyo, built the first AI-checkout retail stores. In between, he lead the development of the ML platform at Clubhouse. ",
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      {
        "id": 69920,
        "title": "Dream3D 😈 - AI-powered 3D design",
        "tagline": "Studio-quality computer graphics made easy",
        "body": "Hey, y’all! Tony here from Dream3D– excited to share what we’ve been working on!\n\n**Dream3D is an AI-powered 3D design tool that makes it easy to create studio-quality computer graphics.**\n\n### The Problem\n\n**Creating 3D renders is an expensive and time-consuming process that can take teams of highly trained specialists months, if not years, to produce a final result.**\n\nIn current rendering methods, input quality = output quality. A designer or artist needs to spend days building a scene, component by component, to get a final rendered result. \n\n**This leads to**\n\n* 🐢 Slow and costly iteration cycles as you nail down your creative vision\n* 💰 Hundreds (if not thousands) of dollars spent purchasing assets, textures, and shaders– many of which never even make the final cut\n* 🤬 Complex and difficult-to-use tools required for building detailed scenes\n\n### How we fix this\n\n**Dream3D replaces complex workflows with text-driven commands and intuitive interfaces powered by our custom AI models.** \n\nUnlike existing generative tools, we give users explicit control over their scene, unlocking professional use-cases.\n\nWe let designers quickly build out 3D scenes by describing them in plain English– “a jetski in front of a building.“ We then let them transform that scene into a high-quality image with just another description of what they want– “photorealistic yellow jetski, evening sun, 80s magazine ad”\n\nHere’s an example of transforming a simple car scene into production-ready concept art:\n\n![uploaded image](/media/?type=post&id=69920&key=user_uploads/251860/f63e5f85-b22c-451b-aa59-1846384eb605)\n\n![uploaded image](/media/?type=post&id=69920&key=user_uploads/251860/3e190d62-d65d-48be-9e26-7639ee1ca06c)\n\nOr a full landscape from just a couple of boxes:\n\n![uploaded image](/media/?type=post&id=69920&key=user_uploads/251860/84be4590-2db2-40a6-b61e-5672a55e828e)\n\n![uploaded image](/media/?type=post&id=69920&key=user_uploads/251860/067a0ef7-f509-4de2-83af-fb30c99254d7)\n\n\\\nThis means you can quickly iterate through multiple concepts and styles, maintaining the same scene composition, without having to spend time & energy building each scene from scratch.\n\nIt's fast and fluid so you can focus on what you want to create.\n\n### Looking Forward\n\nRight now, we let designers create static renders. But soon, we’ll be adding support for animation and video export. \n\nIn the longer term, Dream3D will be a complete 3D creative suite– letting you create full games, movies, and simulated worlds.\n\n## Our Story\n\nPrior to Dream3D, I led the development of the machine learning platform at Clubhouse and my previous company, Inokyo (S18), built computer vision to automate retail checkout. \n\nI first got interested in computer graphics and storytelling while I was studying at Carnegie Mellon. But, I found my creativity stifled by the complexity of the tools.\n\nNow, we’re combining our experiences building prosumer tools and bringing machine learning research to production to make it easy for anyone to create studio-level computer graphics and build the tool I always wish I had.\n\n### The Ask\n\nIf you do 3D design work (or want to), sign up [here](https://hkqvoariw92.typeform.com/to/QJv3ghPN)!\n\nOr if you’re interested in researching hard problems across computer graphics and AI, and/or building delightful tools, send me an email at [tony@dream3d.com](mailto:tony@dream3d.com)",
        "url": "https://www.ycombinator.com/launches/IBk-dream3d-ai-powered-3d-design",
        "votes": 108,
        "created_at": "2023-03-03T18:30:17.701Z"
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    "id": 27868,
    "name": "Outerbase",
    "slug": "outerbase",
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    "website": "https://www.outerbase.com",
    "all_locations": "Pittsburgh, PA, USA; San Francisco, CA, USA; Remote",
    "long_description": "Outerbase is the interface for your database. Companies use Outerbase to view, edit, and modify their data and even generate beautiful visual dashboards without having to write a single line of SQL.",
    "one_liner": "The interface for your database",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1673832882,
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    "year_founded": 2022,
    "city": "Pittsburgh",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/outerbase",
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        "full_name": "Brandon Strittmatter",
        "title": "Founder",
        "founder_bio": "Brandon is co-founder of Outerbase, the interface for your database. Modern teams use Outerbase to view, edit, query, visualize, and share their data. Prior to co-founding Outerbase, Brandon led design for DigitalOcean's managed solutions (App Platform, Serverless, and DBaaS (Database as a Service), and was the founding designer of Containership, a startup building a multi-cloud Kubernetes platform.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/brandonstrittmatter",
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        "user_id": 505802,
        "full_name": "Brayden Wilmoth",
        "title": "Founder",
        "founder_bio": "Brayden is a co-founder of Outerbase, the interface for your database. Prior to founding Outerbase, Brayden was a software engineering manager at Walmart leading multiple teams of engineers on various platforms for the native applications and web experiences. At his time there he guided teams in making key data-driven decisions, in which he took his experience from to assist in building Outerbase.",
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        "title": "👾 Outerbase – Interface for your database",
        "tagline": "Outerbase is the easiest way for you and your team to securely access your data.",
        "body": "Hi everyone – we are Brandon & Brayden from Outerbase.\n\n**📚 TL;DR**\n\nCurrent database tooling is poorly designed and historically been targeted solely at developers. Outerbase is a modern platform that allows you and your entire team to view the data you need whether it be in Postgres, MySQL, Snowflake, BigQuery or more.\n\n### \n\n**🪨 The Problem**\n\nGetting access to your data is hard. Typically there are only a few people who hold the keys to it at any given company and they quickly become a bottleneck on data requests. The tooling around it is outdated and poorly designed, and not intended for the modern collaborative work environments.\n\n![uploaded image](/media/?type=post&id=69291&key=user_uploads/1247130/86c6422c-a53c-41d7-a9fa-10c9e5362450)\n\n### \n\n**⚒️ Our Solution**\n\nOuterbase provides an intuitive interface with granular access to your data. It has a familiar spreadsheet-like experience that anyone can use. Outerbase’s EZQL provides a sql-less experience through the use of GPT-3. You can take those same queries and create beautiful dashboards all in one experience.\n\n### \n\n**⚙️ How Outerbase Works**\n\nWe sit on top of most relational database types, including Postgres, MySQL, Redshift, BigQuery, and Snowflake. You simply provide your database credentials and Outerbase gives you a spreadsheet-like experience to view, edit, query, and visualize your data. Since access is based on your credentials you can easily control how granularly your team accesses your data. Our EZQL feature is powered by OpenAI and takes your databases schema and structures your questions/queries based on it.\n\n![uploaded image](/media/?type=post&id=69291&key=user_uploads/1247130/8bf0e1cb-0788-47a1-84aa-8d91e6652aad)\n\n### \n\n**🙋 Asks**\n\nTry Outerbase, simply [sign up](https://app.outerbase.com/signup) and get started with our demo database, or add your own database credentials in the connections tab. You can also [download](http://app.outerbase.com/downloads/Outerbase.dmg) our mac app.\n\nIf you know of anyone trying to kick off the process of making data-driven decisions but doesn’t know where to start, please intro them to us!\n\nJoin our Slack [community](https://join.slack.com/t/outerbasecommunity/shared_invite/zt-1ple7fhsg-2z6MIC_P4fzdrKe1koJ7kQ).\n\nAnd, if you have 15 minutes to chat about your pain points accessing your data please book some time [here](https://calendly.com/outerbase/demo).",
        "url": "https://www.ycombinator.com/launches/I1b-outerbase-interface-for-your-database",
        "votes": 86,
        "created_at": "2023-02-14T23:19:39.388Z"
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    "id": 27869,
    "name": "co.dev",
    "slug": "co-dev",
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      "Codev"
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    "team_size": 2,
    "industry": "B2B",
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    "launched_at": 1673365680,
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        "full_name": "Uladzislau Radkevich",
        "title": "Founder",
        "founder_bio": "Experienced software developer with a background in Computer Security.  \nLed tech side of crypto development at Revolut and scaled their payments infrastructure from 1M to 20M+ users. \nWinner of multiple web3/crypto hackathons, including ethAmsterdam and Polygon Buidl IT 2022.\nHave strong domain expertise in traditional banking and fintech.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/uladzislauradkevich/",
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        "user_id": 983743,
        "full_name": "Andrew Kim",
        "title": "Founder",
        "founder_bio": "Andrew started his career in business IT consulting with Accenture, consulting for Google, Cisco, and 3M. After, he worked as a software engineer for Levi Strauss and various startups.  Most recently, he ran his own software development outsourcing agency.",
        "is_active": true,
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      {
        "id": 85946,
        "title": "co.dev: Turn your ideas into full-stack apps",
        "tagline": "Skip the complexity, high costs, and limitations of no-code tools—our AI-powered platform lets you create scalable, modern full-stack apps using natural language, all while keeping full ownership of your code.",
        "body": "[co.dev](https://co.dev) is an AI-powered platform lets you create scalable, modern full-stack apps using natural language, all while keeping full ownership of your code.\n\n<https://www.youtube.com/watch?v=V7NWWoa0kHY>\n\n# **Problem**\n\nBuilding full-stack applications is prohibitively complex, time-consuming, and costly for non-technical users. While current no-code platforms offer a partial solution, they come with serious drawbacks:\n\n* Vendor Lock-In: They use they own stack, so you are tied to their platform.\n* Scaling Challenges: Outgrowing these tools often means starting over.\n* Limited Customization: Advanced features require a steep learning curve or outside help.\n\n# **Solution**\n\n[co.dev](https://co.dev) bridges the gap by combining the simplicity of no-code platforms with the flexibility and scalability of professional development tools. Using natural language, [co.dev](https://co.dev) enables users to build full-stack apps effortlessly through a chat-based interface.\n\nThe platform provides:\n\n* Access to the Codebase: Users can download and own the generated code, eliminating vendor lock.\n* Modern Tech Stack: Apps are built using Next.js and Supabase, providing scalability, speed, and reliability.\n* Built-In Modules: Common features like authentication, database integration (via Prisma), and more, ready to use out of the box.\n* AI Code Management: AI handles coding, bug fixes, database updates, and deployments, while you just provide requirements using natural language.\n* Customization: Advanced users can continue app development outside the platform if desired.\n\nThis solution saves users time, reduces costs, and lowers the technical barriers to building fully functional, scalable applications.\n\n# **Uses Cases**\n\n1. **Startup MVP Development:** Entrepreneurs can quickly create and iterate on minimum viable products for their startup ideas, allowing for rapid testing and validation of concepts.\n2. **Non-Technical App Development:** Anyone can describe their app vision in plain text, and [co.dev](https://co.dev) transforms it into a functional app. Whether you're a small business owner or a creative individual, [co.dev](https://co.dev) makes app creation accessible to all.\n\nSign up [here](https://co.dev).\n\n![uploaded image](/media/?type=post&id=85946&key=user_uploads/983743/b0fcac42-5c3f-41e6-a607-315cf600d821)\n\n",
        "url": "https://www.ycombinator.com/launches/MME-co-dev-turn-your-ideas-into-full-stack-apps",
        "votes": 22,
        "created_at": "2024-11-29T23:15:00.169Z"
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    "long_description": "Traces, evals, prompt management and metrics to debug and improve your LLM application.\r\nOnboard via https://langfuse.com\r\n\r\nLangfuse helps you build and improve LLM applications across the entire lifecycle: \r\n- Develop: Observability, Langfuse UI & Prompt Management\r\n- Monitor: Traces, Analytics, Metrics & Evaluations\r\n- Test: Experiments, Releases & Datasets\r\n\r\nWe are hiring: https://langfuse.com/careers\r\n\r\nLangfuse joined Clickhouse in Jan 2026 where the founders now continue to build the team.",
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        "full_name": "Marc Klingen",
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        "full_name": "Maximilian Deichmann",
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        "founder_bio": "Max built trading systems at European 5bn Fintech, Trade Republic. He knows the ins and outs of building reliable, scalable systems to handle our customers’ most critical business processes. While Max started out studying Management in undergrad, he quickly found his love for computer science and transitioned into engineer self-taught and with a graduate degree.",
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        "full_name": "Clemens Rawert",
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    "news": [
      {
        "title": "ClickHouse welcomes Langfuse: The future of open-source LLM observability",
        "url": "https://clickhouse.com/blog/clickhouse-acquires-langfuse-open-source-llm-observability",
        "date": "Jan 15, 2026"
      },
      {
        "title": "Langfuse raised $4M - Langfuse Blog",
        "url": "https://langfuse.com/blog/announcing-our-seed-round",
        "date": "Nov 07, 2023"
      },
      {
        "title": "Our favorite startups from YC's Summer 2023 Demo Day, Day 1 | TechCrunch",
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        "date": "Sep 06, 2023"
      },
      {
        "title": "Show HN: Langfuse - Open-source observability and analytics for LLM apps",
        "url": "https://news.ycombinator.com/item?id=37310070",
        "date": "Aug 29, 2023"
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    "launches": [
      {
        "id": 87195,
        "title": "🪢 Langfuse - The Open-Source LLM Engineering Platform",
        "tagline": "Langfuse helps teams collaboratively monitor, evaluate and debug their LLM applications.",
        "body": "![](https://lh7-qw.googleusercontent.com/docsz/AD_4nXdIAXpWtb7lK2NRs0-3d-GTPHW5YYMdHGsiSgqV4j4hVw8eb5PJXfszk16m2ROBoKOfyjOWlOtlk3adorGG4L49KTClDdTo5Yv6_k-iBdhbSFgnsKTQBa5e4Cp5kaDnmRlWccSKWQ?key=X_meTBjiqstYzDfMfZ-Cj7Hg)\n\n[Langfuse](https://langfuse.com) is the open-source LLM engineering platform designed to help teams build production-grade LLM applications faster. We started building Langfuse in SF during Y Combinator's W23 batch - just when GPT 4 was initially released. \\\n**Today, Langfuse is used by tens of thousands of developers and is one of the **[**most popular LLMOps platforms globally**](https://langfuse.com/blog/2024-11-most-used-oss-llmops)**.**\n\n### **🤯 The Problem**\n\nBuilding production-grade LLM applications is challenging because of the probabilistic nature of LLMs and the multiple layers of scaffolding required to get complex workflows into production. \\\nDevelopers need to **debug** their applications because of increasingly complex abstractions like chains, agents with tools, and advanced prompts. Understanding how an application executes and identifying the root causes of problems can be arduous. Additionally, **monitoring costs and latencies** is crucial since LLMs can incur high inference expense and take time to respond to users, making it important to track model usage and costs across applications.\n\nAssessing the **quality of LLM outputs** also poses challenges. Outputs may be inaccurate, unhelpful, poorly formatted, or hallucinated, complicating the process of ensuring reliability and accuracy. Quickly **identifying and debugging issues** in complex LLM applications is essential but often difficult. Furthermore, building high-quality datasets for fine-tuning and testing requires capturing the full context of LLM executions..\n\n### **✅ Our Solution**\n\n<https://www.youtube.com/watch?v=2E8iTvGo9Hs> \n\nLangfuse addresses these challenges by providing an open-source platform to debug and improve LLM applications. \\\nLangfuse captures the **full context of your application**, tracing the complete execution flow—including API calls, retrieved context, prompts, parallelism, and more. By enabling **hierarchical representations through nested traces**, Langfuse helps you understand complex logic built around LLM calls. Langfuse also offers **full **[**multi-modal**](https://langfuse.com/changelog/2024-11-20-full-multi-modal-images-audio-attachments)** support**, including audio, images, and attachments.\n\n**Langfuse measures cost and latency**, breaking down metrics by user, session, feature, model, and prompt version, allowing for detailed analysis. To assess output quality, Langfuse facilitates the collection of **user feedback**, performs automated **LLM-as-a-judge evaluations**, and supports manual **data labeling** within the platform. It also offers [**prompt management**](https://langfuse.com/docs/prompts/get-started) features, allowing you to handle prompts effectively and perform [**prompt experiments**](https://langfuse.com/changelog/2024-11-22-prompt-experimentation) over new ideas and systematically track success.\n\nFor testing and experimentation, Langfuse supports **versioning your application** and running tests of **expected inputs and outputs** via curated **datasets**. This provides quantitative insights into the impact of changes, helping you understand and improve your LLM applications more effectively.\n\n### **🎬 Getting Started (Tracing OpenAI with Langfuse):**\n\nBelow is a brief example highlighting how you can integrate with Langfuse. You can also try out Langfuse through our interactive live demo or our walkthrough video - more [here](https://langfuse.com/docs/demo)**.**\n\n_(Not using OpenAI? Langfuse can be used with any model or framework through our _[_Python Decorator_](https://langfuse.com/docs/sdk/python/decorators)_ and _[_JS-TS SDK_](https://langfuse.com/docs/sdk/typescript/guide)_. Langfuse also natively integrates with popular frameworks such as _[_Langchain_](https://langfuse.com/docs/integrations/langchain/tracing)_, _[_LlamaIndex_](https://langfuse.com/docs/integrations/llama-index/get-started)_, _[_LiteLLM_](https://langfuse.com/docs/integrations/litellm/tracing)_ and _[_more_](https://langfuse.com/docs/integrations/overview)_. )_\n\n#### Step 1: Create a New Project in Langfuse\n\n1. Sign up for [Langfuse Cloud](https://cloud.langfuse.com) or [self-host](https://langfuse.com/docs/deployment/self-host) Langfuse OSS.\n2. Create a new project within Langfuse.\n3. Generate API credentials via the project settings.\n\n#### Step 2: Log Your First LLM Call to Langfuse\n\nThe [@observe() decorator](https://langfuse.com/docs/sdk/python/decorators) makes it easy to trace any Python LLM application. In this quickstart, we use the Langfuse [OpenAI integration](https://langfuse.com/docs/integrations/openai) to automatically capture all model parameters such as cost and token usage.\n\n```\n%pip install langfuse openai\n```\n\n```\n# Get keys for your project from the project settings page https://cloud.langfuse.com\nos.environ[\"LANGFUSE_SECRET_KEY\"] = \"sk-lf-...\"\nos.environ[\"LANGFUSE_PUBLIC_KEY\"] = \"pk-lf-...\"\nos.environ[\"LANGFUSE_HOST\"] = \"https://cloud.langfuse.com\" # 🇪🇺 EU region\n# os.environ[\"LANGFUSE_HOST\"] = \"https://us.cloud.langfuse.com\" # 🇺🇸 US region\n```\n\n```\nfrom langfuse.openai import openai # OpenAI integration\nfrom langfuse.decorators import observe\n\n@observe() # Langfuse decorator\ndef story():\n    return openai.chat.completions.create(\n        model=\"gpt-3.5-turbo\",\n        messages=[\n          {\"role\": \"system\", \"content\": \"You are a great storyteller.\"},\n          {\"role\": \"user\", \"content\": \"Once upon a time in a galaxy far, far away...\"}\n        ],\n    ).choices[0].message.content\n \n@observe()\ndef main():\n    return story()\n \nmain()\n```\n\n#### Step 3: See your Traces in Langfuse\n\n![](https://lh7-qw.googleusercontent.com/docsz/AD_4nXfbJGtoDrEGUKAM8Kiim08yIkwLNR25bUtH6Mlr9H49lIdQUkwr9yVQhC1Q06Y8IMaGDte-likn20DUIo1_eGST64FC4RO1VREZdF24OxrTTV3yYL9EmV6xBxXmCiSN01ucH-_zPA?key=X_meTBjiqstYzDfMfZ-Cj7Hg)\n\nLog into the [Langfuse UI](https://cloud.langfuse.com/) to view the created trace. You can now take it further by managing your prompts through Langfuse or by starting to test or evaluate your LLM executions (more below).\n\nSee this example trace in the Langfuse UI: [_https://cloud.langfuse.com/project/cloramnkj0002jz088vzn1ja4/traces/fac231bc-90ee-490a-aa32-78c4269474e3_](https://cloud.langfuse.com/project/cloramnkj0002jz088vzn1ja4/traces/fac231bc-90ee-490a-aa32-78c4269474e3)\n\n### **🏃 Now what?**\n\nAfter you are set up in Langfuse you can now:\n\n* **Evaluate** the quality of your application through\n  * [User feedback](https://langfuse.com/docs/scores/user-feedback)\n  * [Data Labeling](https://langfuse.com/docs/scores/annotation)\n  * [LLM-as-Judge Evals](https://langfuse.com/docs/scores/model-based-evals)\n  * [Custom Evaluators](https://langfuse.com/docs/scores/custom)\n* Run **Tests & Benchmarks** by\n  * [Curating Datasets](https://langfuse.com/docs/datasets/overview)\n  * [Conducting Prompt Experiments](https://langfuse.com/docs/datasets/prompt-experiments)\n* **Analyze and collate statistics** on your app with\n  * [LLM analytics](https://langfuse.com/docs/analytics/overview)\n  * [Intent Classification](https://langfuse.com/docs/analytics/example-intent-classification)\n  * [Posthog Integration](https://langfuse.com/docs/analytics/posthog)\n* **Develop faster** by utilizing\n  * [Prompt Management](https://langfuse.com/docs/prompts/get-started)\n  * [Prompt Playground](https://langfuse.com/docs/playground)\n\n### **👇 Interested in learning more?**\n\n* ⭐️ Star us on [GitHub](https://github.com/langfuse/langfuse/) + follow along on [Twitter](https://twitter.com/langfuse) & [LinkedIn](https://www.linkedin.com/company/langfuse).\n* 👨‍💻 [Getting Started](https://docs.langfuse.com/)\n* [👷 How did we build Langfuse?](https://langfuse.com/blog/2024-12-langfuse-v3-infrastructure-evolution)\n* PS: [We’re Hiring!](https://langfuse.com/careers)",
        "url": "https://www.ycombinator.com/launches/MgN-langfuse-the-open-source-llm-engineering-platform",
        "votes": 18,
        "created_at": "2025-01-27T15:36:38.074Z"
      },
      {
        "id": 73214,
        "title": "🪢 Langfuse - Open-source product analytics for LLM apps",
        "tagline": "Track quality, cost and latency of your LLM apps",
        "body": "⭐ Star us on [**_Github_**](https://github.com/langfuse/langfuse/) & follow us on [**_Twitter_**](https://twitter.com/langfuse)\n\n**_TLDR_**_: _[**_Langfuse_**](https://www.langfuse.com/?utm_source=LaunchYC)_ is building open-source product analytics (think ‘Mixpanel’) for LLM apps. We help companies to track and analyze quality, cost and latency across product releases and use cases._\n\n![uploaded image](/media/?type=post&id=73214&key=user_uploads/1148936/d38a4a7c-edf5-469a-ad3f-7f7aef62a3a5)\n\nHi everyone, we’re Max, Marc and Clemens. We were part of the Winter 23 batch and work on [**Langfuse**](https://www.langfuse.com/?utm_source=LaunchYC), where we help teams make sense of how their LLM applications perform. \n\n### **🤯 Problem**\n\nLLMs represent a new paradigm in software. Single LLM calls are probabilistic and add substantial latency and cost. Applications use LLMs in new ways via advanced prompting, embedding-based retrieval, chains, and agents with tools. Teams building production-grade LLM applications have new **product analytics** and **monitoring** needs:\n\n* **Quality of outputs** is difficult to measure. Outputs can e.g. be inaccurate, unhelpful, poorly formatted, hallucinated or error.\n* **Cost of compute** is a priority again given high inference costs.\n* **Latency** of responses matters for synchronous use cases.\n* **Debugging is challenging** due to increasingly complex LLM applications (chains, agents, tool usage).\n* **Understanding user behavior** is difficult given open-ended user prompts and conversational interactions.\n\n### **🧠 Solution**\n\n![uploaded image](/media/?type=post&id=73214&key=user_uploads/1148936/75e00e56-33fa-4484-bf63-4bdf0394049d)\n\nLangfuse derives actionable insights from production data. Our customers use Langfuse to answer questions such as: _‘How helpful are my LLM app’s outputs? What is my LLM API spend by customer? What do latencies look like across geographies and steps of LLM chains? Did the quality of the application improve in newer versions? What was the impact of switching from zero-shotting GPT4 to using few-shotted Llama calls?’_\n\n**Metrics**\n\n* **Quality** is measured through user feedback, model-based scoring and human-in-the-loop scored samples. Quality is assessed over time as well as across prompt versions, LLMs and users.\n* **Cost and Latency** are accurately measured and broken down by user, session, geography, feature, model and prompt version.\n\n**Insights**\n\n* Monitor quality/cost/latency **tradeoffs** by release to facilitate product and engineering decisions.\n* **Cluster use cases** by employing a classifier to understand what users are doing.\n* Break down **LLM usage by customer** for usage-based billing and profitability analysis.\n\n**Integrations**\n\n* Python and Typescript SDKs to easily monitor complex LLM apps\n* Frontend SDK to directly capture feedback from users as a quality signal\n\n_Langfuse can be self-hosted or used with a generous free tier in our managed cloud version._\n\n### **🚧 Debugging UI**\n\n![uploaded image](/media/?type=post&id=73214&key=user_uploads/1148936/8d29b87f-8426-4eb1-be4e-6efbf9d4769f)\n\nBased on the ingested data, Langfuse helps developers debug complex LLM apps in production:\n\n* Inspect LLM app executions in a nested UI for chains, agents and tool usage.\n* Segment by user feedback to find the root cause of quality problems.\n\n### **🙏 Asks**\n\nStar us on [**GitHub**](https://github.com/langfuse/langfuse/) + follow along on [**Twitter**](https://twitter.com/langfuse) & [**LinkedIn**](https://www.linkedin.com/company/langfuse).\n\n* If you run an LLM app, go ahead and [**talk to us**](https://cal.com/marc-kl/langfuse-analytics), we’d love to see how we can be helpful.\n* Please forward [**Langfuse**](https://www.langfuse.com/?utm_source=LaunchYC) to **teams building commercial LLM applications**.",
        "url": "https://www.ycombinator.com/launches/J2s-langfuse-open-source-product-analytics-for-llm-apps",
        "votes": 28,
        "created_at": "2023-07-19T14:33:30.177Z"
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    "name": "Relace",
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    "former_names": [
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "Relace makes it easy to deploy production-ready coding agents. Our models are co-optimized with infrastructure to achieve SoTA performance: 10k+ token/s code merging and retrieval across million-line repositories in seconds.",
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        "full_name": "Preston Zhou",
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        "full_name": "Eitan Borgnia",
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        "title": "Machine Learning Scientist",
        "url": "https://www.ycombinator.com/companies/relace/jobs/BiIbkUO-machine-learning-scientist",
        "location": "San Francisco, CA, US",
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        "title": "Relace - Cheaper, faster, and more reliable AI code generation.",
        "tagline": "Kicking off with Instant Apply, Code Reranker, and Embeddings",
        "body": "Hey everyone 👋 -- we're Preston and Eitan, the cofounders of [Relace](https://relace.ai).\n\n**TL;DR:**\n\nRelace models are designed to slot naturally into most AI codegen products, making them faster, cheaper, and more reliable. We already have SOTA:\n\n* Embedding + Code Reranker models to retreive the relevant context from million-line codebases in \\~1-2s.\n* Instant Apply model that merges code snippets at &gt;4300 tok/s.\n\nWe're in production with **Lovable**, **Magic Patterns**, **Codebuff**, **Create**, **Tempo Labs**, and 20+ other AI codegen startups. Watch our Instant Apply model race against full file rewriting with Claude 3.7 Sonnet:\n\nhttps://www.youtube.com/watch?v=J0-oYyozUZw\n\n**Problem:**\n\nAgentic coding systems are easy to prototype, but hard to make robust. As users succeed at creating more complex designs/applications, you hit bottlenecks:\n\n* Larger codebases require efficient context management -- you can't pass everything to the AI agent.\n* Slow and expensive full file rewrites need to be replaced with abbreviated diff formats.\n\nFrontier models (like Claude 3.7, o3, etc.) are powerful, but overkill for these auxiliary functions like retrieval and merging. Costs start to add up, especially when every agent action hits an API with thousands of tokens in and out. Plus, non-technical users are easily frustrated by high latency, especially if they are trying to refine small aspects of the code they created.\n\n**Solution:**\n\nRelace models are trained to achieve order-of-magnitude improvements in both latency and cost without compromising on accuracy.\n\n_Instant Apply_\n\nReleased in February, this model merges semantic code snippets at 4,300 tokens/sec with an average end-to-end latency of \\~900ms across our users.\n\n![uploaded image](/media/?type=post&id=90339&key=user_uploads/1187298/38144690-e758-43dd-b591-be0481a47c33)\n\nInspired by Cursor's Fast Apply, the semantic diff format is chosen to be natural for all models to output. A simple prompt change combined with Instant Apply can reduce Claude 3.5/3.7 token usage by \\~40%.\n\nWe train on hundreds of thousands of code merges across dozens of different coding languages to achieve SOTA accuracy:\n\n![uploaded image](/media/?type=post&id=90339&key=user_uploads/1187298/3ed1d45b-1f70-4cc2-836e-d7c4a3dae817)\n\n_Embeddings and Reranker_\n\nOur embedding model + reranker can determine the relevance score for a user request against million-line codebases in \\~1-2s. By training on hundreds of thousands of query/code pairs, we can effectively filter out irrelevant files and cut input token usage by over 50%.\n\n![uploaded image](/media/?type=post&id=90339&key=user_uploads/1187298/884ed0af-04c3-49e1-a92b-7e53ca81ad1b)\n\nNot only does this save on cost, but cleaning up the context window significantly improves generation quality of the AI agent.\n\n**Try It Out:**\n\nBoth of these models are battle tested and running millions of times a week in production. You can read more and try it out for yourself with the links below.\n\nApp: [https://app.relace.ai](https://app.relace.ai%5C) Docs: https://docs.relace.ai\n\nWe have a free tier for small projects, and we offer discounted rates for open source partners like our friends at Continue.\n\nDon't hesitate to reach out if you're optimizing your coding agent — we would love to hear your thoughts, feedback, and what you're building!",
        "url": "https://www.ycombinator.com/launches/NV5-relace-cheaper-faster-and-more-reliable-ai-code-generation",
        "votes": 18,
        "created_at": "2025-05-13T05:02:12.002Z"
      }
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  },
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    "id": 27881,
    "name": "Inkeep",
    "slug": "inkeep",
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      "inkeep"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ca1b5818bf14fe551342345b16c3c399f2ecdf21.png",
    "website": "https://inkeep.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Inkeep is the only agent platform designed to help both developers and non-developers ship Agent-powered assistants and automations.\r\n\r\nCompanies like Anthropic, Midjourney, Clay, PostHog, and Postman deploy Inkeep Agents at scale to help with everything from support to sales.\r\n\r\nHighlights:\r\n- A No-Code Builder and Developer Framework with full 2-way sync\r\n- Unified search and RAG for knowledge bases, docs, and company data\r\n- MCPs and integrations with your apps, APIs, and software\r\n- Intelligent insights and monitoring over how Agents perform\r\n\r\nWith Inkeep Agents, enterprises and high-growth teams empower their employees with AI teammates that help get work done and automate repeatable tasks.\r\n\r\nBacked by Khosla Ventures, Y-Combinator, Great Point Ventures and leading CEOs and founders.",
    "one_liner": "Build AI Agent teammates and automations in code or no-code",
    "team_size": 18,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1677660046,
    "tags": [
      "Developer Tools",
      "Workflow Automation",
      "Customer Support",
      "No-code",
      "AI Assistant"
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    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Winter 2023",
    "status": "Active",
    "industries": [
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    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Partly Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/inkeep",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/inkeep.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/inkeep/",
    "x_url": "https://twitter.com/inkeep",
    "fb_url": null,
    "cb_url": "https://crunchbase.com/organization/inkeep",
    "github_url": "https://github.com/inkeep",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/ca1b5818bf14fe551342345b16c3c399f2ecdf21.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [
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    ],
    "primary_partner": {
      "name": "Tom Blomfield",
      "url": "https://www.ycombinator.com/people/tom-blomfield"
    },
    "founders": [
      {
        "user_id": 1161446,
        "full_name": "Nick Gomez",
        "title": "Founder",
        "founder_bio": "Nick is co-founder and CEO of Inkeep. He previously led devex for a team at Microsoft, focusing on self-serve developer experiences and no-code builders. He studied Business & Computer Science at MIT. Beyond Inkeep, Nick enjoys photography and hiking.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/edwinngomez",
        "x_url": "https://twitter.com/nickgomez",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/909605b4e584bff4ae903ae08a61d992f8a253b6.jpg"
      },
      {
        "user_id": 1161457,
        "full_name": "Robert Tran",
        "title": "Founder",
        "founder_bio": "Robert Tran is a cofounder of inkeep. He studied CS & Math at MIT and has an extensive background in tech, including working with government, political organizations, financial firms, and logistics companies. Previously, Robert was an early employee then Head of Engineering at illumis — building software to aggregate thousands of public data sources that are locked in silos. illumis was acquired by ComplySci. Outside of inkeep, Robert is passionate about film & writing.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/robert-tran-profile",
        "x_url": "https://twitter.com/robert_inkeep",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/be2d117ced48c24de80e03ddc3cfb572bfb86714.jpg"
      }
    ],
    "jobs": [],
    "news": [
      {
        "title": "This Startup Just Raised $13 Million To Make AI Agents Easy For Any Team",
        "url": "https://www.forbes.com/sites/zoyahasan/2025/09/05/this-startup-just-raised-13-million-to-make-ai-agents-easy-for-any-team/",
        "date": "Sep 05, 2025"
      }
    ],
    "launches": [
      {
        "id": 85650,
        "title": "Inkeep - AI support you can trust",
        "tagline": "All the AI tools you need to scale support - without losing the human touch",
        "body": "Hi everyone, we’re Nick and Robert - co-founders of [Inkeep](https://inkeep.com/).\n\n### TL;DR\n\nAs founders, we know that fast, quality support helps great products stand out.\n\nInkeep accelerates every step of support with:\n\n🔍 An AI assistant for end-users\n\n🎧 A copilot for support teams\n\n📚 Tools to fix content gaps\n\nInkeep works with any docs or support platform; see our [showcase](https://inkeep.com/showcase?example=anthropic&tab=aiForCustomers) for examples.\n\n![uploaded image](/media/?type=post&id=85650&key=user_uploads/1161446/2fab07e8-72a9-4e56-9fb9-e14f38f411c6)\n\n### Problem: today’s tools focus too much on automation\n\nUsers of modern products expect two things:\n\n(1) great self-serve experiences\n\n(2) fast human help when they need it\n\nAI support solutions often forget about this and end up feeling like a barrier to getting “real” help. \n\n### Solution - AI that builds trust\n\nOur approach is simple: build practical tools for every step of the support process with the end-user as the #1 priority.\n\n**Assistant for users**\n\nInkeep taps into your docs, help center, and other content to provide direct answers to user questions. Our assistant cites its sources, **admits when it doesn’t know**, and hands off to your support channels.\n\n![uploaded image](/media/?type=post&id=85650&key=user_uploads/1161446/66cc6667-df67-4209-baa3-6ea0e6b38fd3)\n\n**Copilot for support teams**\n\nWhen your support team needs to step in, our CX copilot:\n\n✍️ Drafts detailed answers\n\n🔗 Links to relevant docs and past tickets\n\n⚡ Summarizes long tickets \n\n🔔 Suggests to-dos and next steps\n\n[Demo:](https://youtu.be/4_yEpMkdua4)\n\n**Tools to fix content gaps**\n\nThe #1 way to improve support over time is to improve your content (or product).\\\nInkeep helps close that loop with:\n\n1. [AI reports](https://docs.inkeep.com/analytics/reports) that pinpoint and prioritize gaps in your content.\n2. A [Ticket to FAQ](https://go.inkeep.com/ticket-into-faq) tool to create new content from closed tickets.\n\n![uploaded image](/media/?type=post&id=85650&key=user_uploads/1161446/2a81cc6c-821f-4853-8630-a831a5144135)\n\n### **🙏 Our Ask**\n\n* Want to try an AI assistant powered by your content? Get a [self-serve demo](https://inkeep.com/demo?cta_id=yc_launch).\n* Thinking about adding AI to your entire support workflow? [Schedule a call](https://inkeep.com/demo?cta_id=pricing_enterprise_demo_cta).\n\nSocials: [LinkedIn](https://www.linkedin.com/company/inkeep), [𝕏.](https://x.com/inkeep_ai)",
        "url": "https://www.ycombinator.com/launches/MHS-inkeep-ai-support-you-can-trust",
        "votes": 22,
        "created_at": "2024-11-18T15:46:06.140Z"
      },
      {
        "id": 69837,
        "title": "Inkeep - Conversational search for your developer product 💬🔍",
        "tagline": "Help developers do more with your product, faster.",
        "body": "> tl;dr: [Inkeep](https://www.inkeep.com/?utm_campaign=yc) provides conversational search for developer-focused companies. We use LLMs to understand a company’s docs, GitHub issues, Stack Overflow questions, and more to answer developer questions and increase customer activation.\n\n### **Our Team:**\n\nHi YC, we’re [Robert Tran](https://www.linkedin.com/in/robert-tran-profile/) and [Nick Gomez](https://www.linkedin.com/in/edwinngomez/) from Inkeep!\n\n![uploaded image](/media/?type=post&id=69837&key=user_uploads/1161457/4cbbe838-fb40-4508-89aa-8713f83d7755)\n\nWe met eight years ago at MIT as undergrads. After MIT, Nick was a Senior Product Manager working on developer experiences for Microsoft’s identity products. Robert was Head of Engineering at illlumis (acquired), building large-scale data aggregation pipelines for public datasets.\n\nWith years of experience building developer-focused products, we are excited to build Inkeep.\n\n### **Problem:** Any blocker or unanswered question is a drop-off point\n\nDevelopers evaluate a product by how easy it is to get started and use it for their use case. Optimizing this experience is the #1 goal for many developer-focused companies, but it’s hard to do well because:\n\n* Knowledge about the product is scattered across docs, GitHub issues, Stack Overflow, forums, private communities, and more.\n* Answering technical issues and questions at scale is hard.\n* Developers often prefer to self-troubleshoot.\n\n### **Solution:** Conversational search powered by all your existing content\n\n[Inkeep](https://www.inkeep.com/?utm_campaign=yc) automatically indexes all of a developer tool company’s content with zero effort required. We use fine-tuned LLMs that fully understand your product to power search and chat experiences tailored for developers.\n\nInkeep is embeddable as a:\n\n* Search bar for your docs\n* Chat widget for your app or landing page\n* Slack or Discord bot for your community\n\nYour developers can search or ask anything and get answers immediately. And you’ll be able to get insights on what they're getting stuck on.\n\n![uploaded image](/media/?type=post&id=69837&key=user_uploads/1161457/41100239-1ce3-4e5a-8349-4294e24a237d)\n\n\n### **Our asks:**\n\n* Interested in adding Inkeep to your developer product? We’d love to [show you a demo](https://calendly.com/nickgomez/inkeep-demo-20mins).\n* Connect us with folks who are obsessed with developer experience & activation.\n\nGet in touch at: [founders@inkeep.com](mailto:founders@inkeep.com) \\\nLearn more at: [Inkeep.com](https://www.inkeep.com/?utm_campaign=yc)",
        "url": "https://www.ycombinator.com/launches/IAP-inkeep-conversational-search-for-your-developer-product",
        "votes": 167,
        "created_at": "2023-03-01T20:02:13.615Z"
      }
    ]
  },
  {
    "id": 27890,
    "name": "Wild Moose",
    "slug": "wild-moose",
    "former_names": [
      "Context AI"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fa6f0365e063d6abf85d22cf51d505e868af977e.png",
    "website": "https://wildmoose.ai",
    "all_locations": "New York City, NY, USA",
    "long_description": "Wild Moose automatically kicks off any root-cause investigation to improve MTTR.\r\nOur AI triages issues, analyzes impact, and suggests next steps - all before human intervention is needed.",
    "one_liner": "Automating root cause analysis with generative AI",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1675106023,
    "tags": [
      "Developer Tools",
      "Generative AI",
      "SaaS",
      "B2B",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2023",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/wild-moose",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/wild-moose.json",
    "year_founded": 2023,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/wild-moose-ai",
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    "cb_url": null,
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    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/fa6f0365e063d6abf85d22cf51d505e868af977e.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [
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    ],
    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
    },
    "founders": [
      {
        "user_id": 281723,
        "full_name": "Yasmin Dunsky",
        "title": "Founder",
        "founder_bio": "Yasmin holds an MBA from Stanford, and has a successful track record in founding and leading ventures, including an ecosystem that trains thousands of female software developers across Israel. She served as an analyst for the Israeli Special Forces Intelligence and holds a BSc in Computer Science from The Hebrew University. ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/yasmin-dunsky-519a4ab2/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3895cf2f614c1bce99c5ac84e28c5c38015fc8ea.jpg"
      },
      {
        "user_id": 1157519,
        "full_name": "Roei Schuster",
        "title": "Founder",
        "founder_bio": "I'm the CTO of Wild Moose. Before, I was a post-doc at the Vector Institute of AI, after completing a PhD at Cornell and Tel Aviv University. My research focused on security and privacy of AI, and particularly NLP. Before my that, I did my undergrad at the Technion, and served in IDF's 8200 alongside my cofounder Tom.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/roei-schuster-0ba818aa/",
        "x_url": "https://twitter.com/RoeiSchuster",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7a9f7889018f6476b021ae855e2340734dcc8813.jpg"
      },
      {
        "user_id": 1159942,
        "full_name": "Tom Tytunovich",
        "title": "Founder",
        "founder_bio": "Building software stuff since 2002. In the IDF's Intelligence Corps, in tiny startups and large corporations as software developer, architect, and engineering manager, as CTO of a nonprofit building technology with people who are homeless in NY, and now as co-founder of Wild Moose.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/tom-tytunovich-70a13886",
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        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/961d3f09d5210698d6a78711e497937d27018563.jpg"
      }
    ],
    "jobs": [],
    "news": [
      {
        "title": "Site reliability engineering startup Wild Moose launches with $7M in funding - SiliconANGLE",
        "url": "https://siliconangle.com/2025/10/28/site-reliability-engineering-startup-wild-moose-launches-7m-funding/",
        "date": "Oct 28, 2025"
      }
    ],
    "launches": [
      {
        "id": 80510,
        "title": "Wild Moose Alert Enrichment: Solve production issues before they get to engineers",
        "tagline": "Reduce MTTR with an AI agent that engages with logs, metrics, and code to kick off any investigation",
        "body": "### **Problem:** Production chaos is real, and interferes with fast delivery\n\nThese days, there's immense pressure for organizations to constantly innovate. To achieve this, you need to aggressively minimize distractions. It's crucial to eliminate the constant stream of alerts, often leading to full nights of stressful debugging.\n\n### **Solution:** AI agents can knock down issues before they get to engineers\n\n**Our AI agent kicks off every investigation by querying logs, metrics, DBs, and code to surface information and resolve issues.** The initial steps in investigations are predictable and automatable, but they take time for a human to perform. We save that time. **In many companies this simple step already cuts MTTR by 50%.** \n\n[▶️▶️ Chat with us to join the beta.](https://calendly.com/wildmoose-yasmin/30-min)\n\n**How it works:**\n\n1. **Collects data from monitoring data sources**\\\n   When a new production issue is found, the moose kicks off by collecting data from your monitoring data tools, such as Datadog, Snowflake, New Relic, Cloudflare, etc.\n2. **Generates an enrichment report**\\\n   The moose runs an investigation in real-time, analyzing the data collected to present its findings.\n\n   ![uploaded image](/media/?type=post&id=80510&key=user_uploads/281723/a7ca493a-891b-4da7-8326-920b6f4a4025)\n\n3. **Concludes and recommends next steps**\\\n   The moose presents a summary of its findings along with recommended next steps, focusing on impact and mitigation.\n\n   ![uploaded image](/media/?type=post&id=80510&key=user_uploads/281723/30f636da-7ddf-45e0-bae4-493b21055e76)\n\n4. **Improves over time**\\\n   You can indicate what information was useful or ask the moose to fetch more. Based on this feedback and an underlying model of your system, our model learns over time the actions it should take in different scenarios.\n\n   ![uploaded image](/media/?type=post&id=80510&key=user_uploads/281723/65c3bd53-edd3-492d-bff1-7a27a0ea0fa3)\n\n\n### **Try it out and tell us what you think!**\n\n[▶️▶️ Let’s chat and get you on our beta.](https://calendly.com/wildmoose-yasmin/30-min)\n\n**We’re looking to work with companies that are making an effort to improve their reliability**, preferably companies that already measure MTTR or are interested in starting to do so. \n\n* **_You don’t have to prepare your data or monitoring tools_**. We know things are often messy - our model works just as well with data that is unstructured\n* **_You do need to have your logs and/or metrics stored in a SaaS platform_** (Datadog, New Relic, Coralogix, etc.).",
        "url": "https://www.ycombinator.com/launches/KwY-wild-moose-alert-enrichment-solve-production-issues-before-they-get-to-engineers",
        "votes": 36,
        "created_at": "2024-04-30T15:03:33.825Z"
      },
      {
        "id": 69325,
        "title": "🔥 Wild Moose: Solve production incidents faster with Gen AI",
        "tagline": "Helping on-call developers quickly identify the source of production incidents with conversational AI trained on their environment.",
        "body": "**TL;DR When you’re on-call and everything’s on fire, instead of frantically sifting through logs and going through other people’s code, our moose just gives you the answers.** [**Chat with us**](https://calendly.com/wildmoose-yasmin/15min) **to try it out.**\n\n**—-**\n\n👋 We’re Tom, Yasmin, and Roei, founders of [Wild Moose](https://wildmoose.ai?utm_source=YC+newsletter&utm_medium=blog+post&utm_campaign=Launch+YC). \n\n![uploaded image](/media/?type=post&id=69325&key=user_uploads/281723/afaf46a4-84f9-46c1-b638-ee353587eaa5)\n\n[Yasmin](https://www.linkedin.com/in/yasmin-dunsky-519a4ab2/) has an MBA from Stanford and is a third-time founder & CEO. [Roei](https://www.linkedin.com/in/roei-schuster-0ba818aa/) got a PhD at Cornell University focusing on Large Language Models (LLMs), and [Tom](https://www.linkedin.com/in/tom-tytunovich-70a13886/) has had the dubious pleasure of fixing hundreds of incidents in production over his 15 years of engineering.\n\n### **The problem**\n\nWith developers spending over 30% of their time on production issues, and  incidents leading to millions in lost revenue, there’s no need to say much about the headache that is production debugging. Instead, we asked Midjourney what a developer dealing with a prod incident looks like:\n\n![uploaded image](/media/?type=post&id=69325&key=user_uploads/281723/a629390c-47b7-403e-bae9-d523c690b62d)\n\n### **Enters the moose**\n\nDebugging in production with our moose allows you to solve issues in minutes instead of hours, reducing MTTR 100x. It helps you avoid costly downtime, save time, and keep your SLAs in check. You’re able to:\n\n* 🕵️ Navigate through heaps of logs, metrics, and other people’s code\n* 🧠 Build queries like a pro for any observability tool (Elastic, Datadog, SQL DBs, etc.)\n* 🔀 Get next-step recommendations so you stay on track when the pressure is on and you’re flooded with data\n\n### **How it works**\n\n**💪 We help you hit the ground running –** unlike humans, our AI is happy to wake up at 2 AM and get cracking, instantly up to speed and ready with useful data on the state of the system\n\n![uploaded image](/media/?type=post&id=69325&key=user_uploads/281723/7468e24d-8b94-403d-a59e-98e0994ef3f6)\n\n**💪 You don't need to debug alone –** using Wild Moose is like having a fellow engineer take the grunt work off your hands. One who knows every part of the codebase, and who can process hours' worth of data in seconds\n\n![uploaded image](/media/?type=post&id=69325&key=user_uploads/281723/92cb41af-6553-48f8-9277-dff3f74b0eaa)\n\n**💪 Learn more from the incident –** some companies learn from their incidents, others are just gifted with many repeat opportunities… To help you belong to the former, we automate your postmortem generation\n\n![uploaded image](/media/?type=post&id=69325&key=user_uploads/281723/310efdc8-5c47-40a5-afcd-3203066cbc66)\n\n### **Our technology**\n\nBehind a conversational AI experience, lie our special-purpose large language models (LLMs). Having cracked the way LLMs can be fed code and logs in real-time, we design models that efficiently ingest the massive contextual data about a given incident. Crucially, we also validate the produced answers against the original sources of truth, giving you trustworthy information when you need it the most.\n\n### **We can help you fix production issues**\n\nIf your company has 25+ developers, you measure the cost of downtime, and your observability stack includes Datadog, Sentry, and/or Elastic, we would love to help you manage production issues! Just hop on a call with us [here](https://calendly.com/wildmoose-yasmin/15min) or reach out at [yasmin@wildmoose.ai](mailto:yasmin@wildmoose.ai).",
        "url": "https://www.ycombinator.com/launches/I29-wild-moose-solve-production-incidents-faster-with-gen-ai",
        "votes": 59,
        "created_at": "2023-02-15T20:55:49.267Z"
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    "id": 27892,
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    "website": "https://shortloop.dev/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Dealerships leave significant revenue every year because they are unable to effectively answer calls or run campaigns due to staffing issues. \r\n\r\nShortLoop fixes this with human-like AI phone agents that answer calls instantly, book appointments and test drives, and also help run outbound campaigns. It ensures that our customers never miss a revenue opportunity, inbound or outbound. \r\n\r\nOur AI is integrated with CDK, Reynolds, Tekion, Xtime, Auto/Mate, DealerFX, VinSolutions, myKaarma and other popular dealership tools. It handles thousands of calls each week for U.S. dealerships across service, sales, and outbound campaigns.\r\n\r\nOur mission is to help dealerships transition their phone operations to the AI world and capture the revenue they leave on the table today.",
    "one_liner": "Phone AI that Captures Every Dealership Revenue Opportunity",
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        "linkedin_url": "https://www.linkedin.com/in/vishnuvinjam/",
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        "id": 86785,
        "title": "Software Engineer - Fullstack",
        "url": "https://www.ycombinator.com/companies/shortloop/jobs/uHS0vD3-software-engineer-fullstack",
        "location": "Bengaluru, KA, IN / Bengaluru, Karnataka, IN",
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        "experience": "Any (new grads ok)",
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    "id": 27893,
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    "website": "https://buildjet.com",
    "all_locations": "Berlin, Berlin, Germany; Remote",
    "long_description": "BuildJet makes CI faster by running its own cloud on top of Gaming CPUs\r\n\r\nToday, BuildJet offers a CI product that makes GitHub Actions 2x faster and cheaper, by plugging in BuildJet's Gaming CPU Cloud into GitHub Actions. Simply change 1 line, and enjoy the speed-up.",
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    "team_size": 2,
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    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1677520362,
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    "url": "https://www.ycombinator.com/companies/buildjet",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/buildjet.json",
    "year_founded": 2022,
    "city": "Berlin",
    "country": "DE",
    "linkedin_url": "https://www.linkedin.com/company/buildjet/",
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    "primary_partner": {
      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
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    "founders": [
      {
        "user_id": 730963,
        "full_name": "Adam Shiervani",
        "title": "Founder",
        "founder_bio": "Adam Shiervani is a co-founder of BuildJet, with over a decade of experience working in startups, Adam began as a frontend developer and progressed over the years to become the Chief Product Officer at Germany's largest market research company, Civey. At Civey, Adam, together with Lian, who served as CTO, scaled the company and discovered the significant impact that consumer CPUs have on CI speed.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/adamshiervani/",
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      {
        "user_id": 720622,
        "full_name": "Lian Duan",
        "title": "Founder",
        "founder_bio": "Lian Duan, co-founder of BuildJet, holds a master’s degree in bioinformatics from ETH and began his career working as a Senior Full-stack developer at a German data privacy startup alongside Adam Shiervani. Lian later moved to become the CTO of Germany’s largest market research company, Civey, where he worked closely with Adam to scale the company and gain insight into the significant impact of gaming CPUs on CI speed.",
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        "linkedin_url": "https://www.linkedin.com/in/chemhack/",
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        "id": 69746,
        "title": "BuildJet - Change 1 line, get 2x faster & cheaper GitHub Action builds",
        "tagline": "Managed high-performance runners for GitHub Actions",
        "body": "### **⚡️ TL;DR**\n\nHey, this is Adam & Lian from [@BuildJet](https://www.ycombinator.com/companies/buildjet)\n\nBuildJet makes GitHub Actions faster, by running the workflows on our Gaming CPU cloud. You still keep everything GitHub Actions, we just replace the underlying GitHub Actions runner with our Gaming CPUs.\n\n\\\n**Change 1 line, and get 2x faster and cheaper builds.**\n\n![uploaded image](/media/?type=post&id=69746&key=user_uploads/730963/214d6b00-fec2-4f4a-8a6b-132c63f8c6cb)\n\n### **GitHub Actions is slow**\n\n* **Developers are wasting their time –** Waiting for GitHub Actions to get a green checkbox on a PR, is wasteful and extremely tedious.\n* **GitHub Actions runner hardware is old and slow –** GitHub Actions use old and slow machines from Azure. Some of your workflows run on servers from 2015.\n* **GitHub Actions use the wrong type of hardware** – CI workflows are usually computing intense, and specifically require high single-core performance. GitHub Actions uses server CPUs, which generally have low single-core performance.\n\n### **Our Solution**\n\nGitHub Actions rely on server CPUs from Azure. **Server CPUs mostly have low single-core performance.** This is where BuildJet differentiates itself, with its fundamentally different approach to computing, using dedicated **high-performance gaming CPUs** that all have a very high-single core performance.\n\nThis provides an inherent speed advantage for BuildJet, even without software optimizations. High single-core performance is the key to a fast CI process, and BuildJet's gaming CPU cloud is optimized to deliver just that.\n\nTake a look at our at the chart below, **MacBook Pro 2015 hardware beating GitHub Actions runner in 2022.** It’s yet another instance where you can see the limitation of using server CPUs in tasks that need high single-core performance.\n\n![uploaded image](/media/?type=post&id=69746&key=user_uploads/730963/40b07ca7-7828-4ae1-9c6b-20b8d1ea0026)\n\n### **Founding Team**\n\nLian and I, first met at a data privacy startup in Berlin in 2014, where we developed a strong working relationship and launched many products together. After leaving that company, we joined a German startup that runs the biggest market research panel in Germany, Civey, with Adam as CPO and Lian as CTO. When scaling the company, we quickly learned **the great impact gaming CPU's have on CI speed.**\n\n### **Next Steps**\n\nHead over to <https://buildjet.com/for-github-actions>, sign up in 1 minute and start accelerating your GitHub Actions workflows.\n\nIf you have any questions about your CI pipeline, don’t hesitate to reach out to [adam@buildjet.com](mailto:adam@buildjet.com), and I’ll make sure to help you out!",
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        "votes": 45,
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    "id": 27911,
    "name": "IcePanel",
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    "long_description": "IcePanel is a collaborative diagramming tool that helps software engineering and product teams align on technical decisions. Teams use IcePanel to create a map of their software systems, giving them full context about how it works.",
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    "team_size": 9,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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    "url": "https://www.ycombinator.com/companies/icepanel",
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    "year_founded": 2021,
    "city": "North Vancouver",
    "country": "CA",
    "linkedin_url": "https://www.linkedin.com/company/icepanel/",
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    "github_url": "https://github.com/IcePanel",
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      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
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        "user_id": 690358,
        "full_name": "Jacob Shadbolt",
        "title": "Founder/CEO",
        "founder_bio": "🧊 IcePanel Co-Founder | I am building a simpler (cooler) way to talk about system design and share technical knowledge. Before IcePanel, I was a UX Designer at Mastercard, working on greenfield real-time payment products, including monitoring and mobile payments. I prefer solving \"boring\" problems over jumping on hype trains. Stay chill.",
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        "full_name": "Victor Leach",
        "title": "Founder",
        "founder_bio": "🧊 IcePanel Co-Founder | I have a passion for discovering and solving problems with technology, and my mission is to make products that people love!",
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        "title": "Senior Full Stack Engineer",
        "url": "https://www.ycombinator.com/companies/icepanel/jobs/KlI6KP6-senior-full-stack-engineer",
        "location": "Vancouver, BC, CA",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$170K CAD",
        "equity_range": "0.20% - 0.70%",
        "experience": "6+ years",
        "visa": "US citizenship/visa not required",
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      {
        "id": 67487,
        "title": "🧊 IcePanel - Collaborative system design; linked with reality",
        "tagline": "A lightweight visual approach to modelling software architecture, linked with resources in the real world.",
        "body": "### **⚡️TL;DR**\n\nCommunication of software systems is hard, visuals help but often lack consistency and are out-of-date within weeks.\n\nIcePanel is a SaaS tool for tech teams to collaborate on their software architecture design.\n\n### **👋 Who are we?**\n\nHey all, we’re [Victor](https://www.linkedin.com/in/victorleach/) and [Jacob](https://www.linkedin.com/in/jacob-shadbolt-design/), the founders of 🧊 [IcePanel](http://icepanel.io).\n\n### **🤬 Problem**\n\nSoftware teams currently use generic diagramming tools to communicate complex systems.\n\n* Software systems are becoming increasingly complex and are hard to explain.\n* Technical teams often find it challenging to tell the right story and gain alignment.\n* Technical diagrams are inconsistent, lack context and drift from reality - becoming out-of-date in a matter of weeks.\n* Engineering and product teams are often misaligned, especially in technical areas.\n\n💩 Bad communication across teams is time-consuming and expensive.\n\n### **🚀 Our solution**\n\nHelp humans visually communicate complex systems; linked to resources in reality.\n\n**1️⃣ Modelling**\n\n> * IcePanel is a collaborative modelling tool, that provides a single source of truth with reusable objects and relationships, keeping your diagrams in sync and up-to-date with changes.\n\n**2️⃣ Consistent language**\n\n* IcePanel is built upon the [C4 model](http://c4model.com), a lightweight layered approach designed for technical and non-technical audiences. This brings consistency to visual & verbal communication about software architecture.\n\n**3️⃣ Linked to reality**\n\n* IcePanel objects can be linked to resources in reality, such as files in Git, that flag as out-of-date if they no longer exist.\n\n### **🫣 Sneak peek**\n\n_Levelled diagramming_\n\n![uploaded image](/media/?type=post&id=67487&key=user_uploads/690358/af8b9aee-00f4-48c5-9215-1c5a75cbb7b9)\n\n_Dynamic flows_\n\n![uploaded image](/media/?type=post&id=67487&key=user_uploads/690358/ead5d78e-c923-41bb-b34a-74d8d03bb9b8)\n\nWant to see more? [Head over to IcePanel!](https://icepanel.io)\n\n### **🙌 Our ask**\n\n* [Try us out](http://icepanel.io) for free & let us know your feedback\n* Connect us with engineering teams who struggle to fully understand their systems\n* Share with your developer or product friends",
        "url": "https://www.ycombinator.com/launches/HYV-icepanel-collaborative-system-design-linked-with-reality",
        "votes": 26,
        "created_at": "2022-11-23T00:36:21.646Z"
      }
    ]
  },
  {
    "id": 27941,
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        "body": "Hi everyone, we’re Akhil and Joshua and we're on a mission to accelerate expertise and comprehension of any codebase by providing a self-generating, self-maintaining code knowledge base.\n\n![uploaded image](/media/?type=post&id=78163&key=user_uploads/1192337/c88f4b22-6168-4ae1-9424-7944ba0ed16d)\n\n### 🧨 The Problem\n\nThe story of every software team is a constant struggle with knowledge friction and maintaining expertise in the code and surrounding systems.\n\nThese are the perennial issues we’re solving:\n\n* **Staleness:** Most documentation is perpetually stale and it slows development to keep it fresh.\n* **Complexity:** Code becomes more difficult to maintain and improve as it increases in age and size. This is the main reason enterprises with extremely large, old, and complex code can’t move fast.\n* **Fragmentation:** Code information is unversioned and unlinked across disparate platforms, so it’s often unclear what your Confluence article is referring to and whether it’s still applicable.\n* **Discoordination:** Information silos impede collaboration and lead to unnecessary repetition of work. Cross-team features and bugs are exponentially harder to implement and resolve.\n* **Underutilization:** Engineers are expected to take 8-12 months to fully onboard and usually experience a “sink-or-swim” strategy for ramping up a new team.\n* **Overdependence:** Core knowledge is continually lost as employees turnover. Raise your hand if you’ve ever needed to touch code that’s written by an engineer who left in 2014. 🙋\n\nWhether you’re a newly hired engineer, just moved teams, or need to touch code you’ve never seen before, it’s the steepest learning curve in software engineering. This is the skeleton-in-the-closet of software: your average engineer spends more than 40% of their 2-year-tenure “onboarding.”\n\n### 🎉 The Solution\n\n[Sage](https://www.ycombinator.com/companies/sage-ai) is changing this reality. We take your code and automatically generate a symbol-level knowledge base that self-updates to remain forever fresh.\n\nFirst, we integrate with source control to pull your code and generate a symbolic graph representation of functions, classes, interfaces, types, etc., automatically determining the relevant context for each symbol.\n\nWe then use LLMs to annotate and propagate documentation via traversals of the symbol graph, saturating knowledge across multiple traversals.\n\n![uploaded image](/media/?type=post&id=78163&key=user_uploads/1192337/14c14041-7efc-425c-9535-913fa9934ccb)\n\nWe're also exposing a configurable, deeply contextualized chat system that can derive higher-level purposes and objectives of program symbols and modules from its own knowledge base.\n\n![uploaded image](/media/?type=post&id=78163&key=user_uploads/1192337/a6b0701b-c4a8-42ad-9405-1d495ee05dad)\n\nIn the future, we'll let your engineers themselves improve the system, and integrate and link current knowledge systems such as Slack and Confluence. As its comprehension of your codebase grows, the quality of every downstream task improves automatic coding, testing, refactoring, bug fixing, vulnerability detection, and so on.\n\n### Our ask\n\n* If you are a software engineer and have struggled with documentation or onboarding in the past, sign up to try the platform at <https://sage-ai.dev>. We would love to get your feedback!\n* If you know any engineers or engineering managers who might be interested in using our platform with their teams, let us know at [founders@sage-ai.dev](mailto:founders@sage-ai.dev)\n* If you are developing AI systems that deal with codebases, let us know if you are interested in consuming docs and symbol graphs as an API.\n* Share any additional feedback in the comments!\n\nSage AI Team (Akhil and Joshua)",
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        "body": "> **tl;dr:** Robots produce a lot of data, and it’s a challenge to collect and manage all of it. Our infrastructure enables companies to easily collect, offload, and make use of sensor data.\n>\n> ![uploaded image](/media/?type=post&id=67785&key=user_uploads/1161431/6669487c-0baf-4116-b0b7-1dd6b0ba7ec6)\n\n\n---\n\nHowdy, YC! I’m [Alec Bell](https://www.linkedin.com/in/alec-bell/) from SensorSurf. I love robots, and I’m writing software to make it easier to build them.\n\n### **❌** Problem\n\nRobots generate absurd quantities of data. **A single self-driving car produces up to 1.5 petabytes/year** ([source](https://www.tuxera.com/blog/autonomous-cars-300-tb-of-data-per-year/)). Developers need access to this data to diagnose issues, train models, and run simulations; but it’s hard to get a hold of since its clunky and sits on an edge device. Robotics companies currently build data infra in-house, which is extremely costly.\n\n### ✅ Solution\n\n**SensorSurf offers the infrastructure to collect, offload, and make use of sensor data.** Users can specify where, when, and what data to collect. From there, they can selectively offload it, run queries on it, visualize it, and put it to work for purposes like debugging, annotation, and analytics.\n\n### 👨‍💻 How it works\n\nRobotics companies install **a tiny agent on their robots,** which allows us to establish a connection to our services and **observe their system.** We can then collect data across a fleet of robots and help users manage/search it in the cloud, accounting for network constraints that our customers may experience.\n\n### 👍 Noteworthy features\n\n* [Event-based data collection](https://docs.woeden.com/collection/auto_record)\n* [Rolling buffers/windows of data](https://docs.woeden.com/collection/rolling_buffer)\n* [Data streaming for visualization](https://docs.woeden.com/management/visualize)\n\n### 🙏 Asks\n\n* **Robotics developers:** [**try out our tool**](https://docs.woeden.com/getting_started)**!**\n* Share this post to robotics communities.\n* Connect us with robotics companies and researchers ([founders@woeden.com](mailto:founders@woeden.com)).",
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        "title": "Noya UI — 🪐 Universal component kit",
        "tagline": "Build websites faster with our beautiful, premade UI component kit",
        "body": "**tldr;** Noya UI is a collection of beautiful, premade UI components that you can drop into your own codebase as a starting point. Noya UI supports most common web frameworks and libraries like Tailwind, React, and Chakra UI.\n\n**Check it out:** [**https://noya.io/ui**](https://noya.io/ui)\n\n![uploaded image](/media/?type=post&id=79579&key=user_uploads/134273/d31c13b1-6821-4d23-9f2e-83b87189bbc1)\n\n### About Us\n\nHi everyone! My cofounder David and I were the Design Tools team at Airbnb, after they acquired our previous design tools company. We pioneered internal tools and processes that the award-winning Airbnb design team used when designing web and mobile apps.\n\nIn 2023 we started our second company together, Noya Software, and were part of the W23 batch. While building our AI-powered design tool, we put together a collection of high-quality “universal” components — components that work across many web frameworks. Based on feedback from customers, we’ve decided to release this component collection as a standalone product: Noya UI!\n\n### The problem\n\nWhen building websites or mobile apps, you have _some_ UI design needs but…\n\n1. You don’t have enough design work to justify a full-time designer on your project\n2. Designer contractors can be very unpredictable: they take a while to find and vet, the best ones are booked up for months, and even then there’s no guarantee you’ll get quality, timely designs\n3. Premade templates and component kits typically only work for specific frontend tech stacks, and often don’t have components that are relevant within your vertical, thus requiring you to make significant modifications\n\nAt the end of the day, for all the time and money you spend you can very easily wind up with a subpar design.\n\n![uploaded image](/media/?type=post&id=79579&key=user_uploads/134273/cf5327bc-fe6b-48bb-813e-49926fe66553)\n\n### Our solution: Noya UI\n\nNoya UI is a collection of beautiful, premade UI components that you can copy and paste into your own codebase and customize as a starting point for your website.\n\nCompared to existing component kits, Noya UI is:\n\n* **Tech stack agnostic:** We support a wide range of tech stacks and base component libraries: plain HTML + CSS, React, Vue, Tailwind, Chakra UI, MUI, Ant Design, Radix Themes (and if we’re missing what you use, get in touch and we’ll see if we can add it! e.g. Shadcn or Framer or Webflow)\n* **Multi-vertical:** We offer components focused on specific verticals like developer tools and fintech, which are often missing from other kits. Of course, we have all the common marketing/landing page components, too!\n\n### Our ask for you\n\n1. **We’d love for you to consider using **[**noya.io/ui**](https://noya.io/ui)** for your website! It’s a one-time purchase of $149 for lifetime access.**\n2. Share this post with founders, PMs, and engineers in your network who might be interested!\n\nFeel free to reach out to us anytime via [Discord](https://discord.com/invite/NPGAwyEBJw) or email: [founders@noyasoftware.com](mailto:founders@noyasoftware.com)",
        "url": "https://www.ycombinator.com/launches/KhX-noya-ui-universal-component-kit",
        "votes": 12,
        "created_at": "2024-03-21T16:53:07.977Z"
      },
      {
        "id": 69609,
        "title": "🧑‍💻 Noya - Draw wireframes, get designs & code",
        "tagline": "Design products faster by leveraging design systems!",
        "body": "tldr; Noya turns UI ideas into designs & code in just a few minutes. Built by former Airbnb Design Tools team members, Noya is a new kind of design tool that enables product teams of any size to fully leverage the advantages of design systems. Try it here: [noya.io](https://www.noya.io/?utm_source=launchyc&utm_medium=referral)\n\n![uploaded image](/media/?type=post&id=69609&key=user_uploads/134273/b3692215-185c-4f5b-8d6e-1adb98a118cb)\n\n### About us\n\nHi everyone! My cofounder David and I were the Design Tools team at Airbnb, after they acquired our previous design tools startup. We pioneered internal tools and processes that the award-winning Airbnb design team used when designing web and mobile apps.\n\nAt Airbnb’s scale, it made sense to have an in-house design tools team. But we realized that companies of all sizes could benefit from a better design process that’s tailored to their product, so we created a new tool that brings the benefits of an in-house design tools team to every company.\n\n### The Problem\n\nThere’s always a tricky tradeoff between working in _low-fidelity wireframes vs. high-fidelity mockups_ when working on a product idea. Working in low-fidelity allows for quick iteration while hammering out the big picture, but people often have a hard time imagining the final product. Because of this, teams frequently jump to high-fidelity and _stop using wireframes too early_, which slows down progress dramatically as they spend an excessive amount of time perfecting unimportant details.\n\nPersonally, there have been many times where I’ve needed to create a high-fidelity mockup or a React prototype to really explain my idea to another engineer. I spent hours designing and coding just to communicate the idea, only for it to be scrapped when we changed direction right after.\n\n![uploaded image](/media/?type=post&id=69609&key=user_uploads/134273/53841334-fad3-49f0-aa77-1e2aa2410055)\n\n### Our solution: Noya\n\nNoya is a new kind of design tool that provides the advantages of _both_ low-fidelity and high-fidelity design.\n\nWith Noya, you build your project with wireframes, while the tool automatically generates a high-fidelity output in real time. It works by mapping low-fidelity blocks into high-fidelity design system and React components. We currently support one open-source design system (Chakra UI), but plan to expand with more choices (MUI, etc), including the option to import your company’s existing design system.\n\nHere’s a quick demo video:\n\n<https://www.youtube.com/watch?v=khGAUUFZ5Fs>\n\n### Pricing\n\nOur Professional plan is $8.40/month (that’s 30% off!) if you subscribe before Demo Day, and includes:\n\n* Unlimited projects & blocks\n* 3,000 AI-generations/month\n* Access to premium templates\n* React code export\n* Premium support\n\nWe also offer an enterprise plan for companies that want to import their existing design system. If you’re looking to improve your company’s design process and you have a React component library, get in touch: [founders@noyasoftware.com](mailto:founders@noyasoftware.com)\n\n### Our ask\n\n1. We’d love for you to try using [noya.io](https://www.noya.io/?utm_source=launchyc&utm_medium=referral) to design your next idea!\n2. Share this post with founders, designers, PMs, and engineers in your network who might be interested!\n3. Follow us on twitter for updates: <https://twitter.com/noyasoftware>\n\nFeel free to reach out to us anytime via the [Noya Discord](https://discord.com/invite/NPGAwyEBJw) or email: [founders@noyasoftware.com](mailto:founders@noyasoftware.com)",
        "url": "https://www.ycombinator.com/launches/I6j-noya-draw-wireframes-get-designs-code",
        "votes": 56,
        "created_at": "2023-02-23T18:23:33.032Z"
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        "answer": "Defer aims to improve the developer experience of building background operations in web-applications. Background operations are ubiquitous in modern web applications, from interacting with third APIs to sending notifications. Still, such features always require infrastructure work from the early stage and are hard to scale at later ones. Defer envisions that developing features such as sending notifications and exporting data should be as easy as deploying your Vercel application."
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        "user_id": 1143800,
        "full_name": "Charly Poly",
        "title": "Founder",
        "founder_bio": "Charly was a tech lead at Algolia, where he built a background jobs processing platform that contributed to $12M of new revenue.\nCharly enjoys speaking at international conferences (React Europe 2019) and wrote many reference articles on TypeScript and GraphQL relayed by recognized international newsletters such as GraphQL or TypeScript Weekly.\nAfter working in open-source, he now focuses on enabling Node.js developers to build reliable async flows with Defer.",
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        "user_id": 1142157,
        "full_name": "Bryan Frimin",
        "title": "Founder",
        "founder_bio": "CTO & Co-founder of Probo. French engineer building an open-source AI platform that simplifies SOC2/ISO27001 compliance.",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/gearnode",
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    "news": [
      {
        "title": "Launch HN: Defer (YC W23) Zero-infrastructure background jobs for Node.js",
        "url": "https://news.ycombinator.com/item?id=35096366",
        "date": "Mar 10, 2023"
      }
    ],
    "launches": [
      {
        "id": 69350,
        "title": "Defer: A zero-infrastructure platform for Node.js background jobs",
        "tagline": "Quickly move slow code outside your user’s journey and scale with confidence using Defer’s real-time dashboard and autoscaled infrastructure.",
        "body": "Hi everyone! We are Charly and Bryan, and we’re happy to present you [Defer](https://www.defer.run/):\n\n![uploaded image](/media/?type=post&id=69350&key=user_uploads/1143800/14e200b6-6899-4313-9030-29ddc708dc4b)\n\nDefer allows developers to quickly create and run background jobs without infrastructure.\n\nBackground jobs are vital in building responsive and resilient web apps by moving slow code outside the users’ journey (ex: pulling and sending data to external APIs, sending emails).\n\n## Why are we building Defer?\n\nBryan and I have been working for 10 years in startups of many stages (pre-seed to Algolia or Dashlane stages).\n\nIn all those experiences, part of our work included crafting similar background jobs solutions and their internal dashboards, as Charly did at Algolia for the Shopify Integration Pipeline.\n\nWe identified a gap between current solutions and actual product needs that leads to **a repeated waste of engineering time** (initial cost, support, and maintenance) and **bad user experiences** across all companies.\n\nAs consultants, we also faced companies that **preferred to keep degraded user experiences** to not invest in R&D in background jobs.\n\nAll those combined experiences led us to create Defer to help companies match **modern product criteria** (great user-perceived performance and an increasing number of integration with external APIs) with **minimum effort** while keeping the **developer experience at heart**.\n\n## Our solution\n\nDefer enables developers to use a background jobs solution that matches their product needs without reinventing the wheel or building fragile layers.\n\nDefer brings a **unique developer experience** that makes it easy to create or transform existing functions into background functions (function version of a background job) **without the usual distracting boilerplate code** that current OSS solutions bring:\n\n![uploaded image](/media/?type=post&id=69350&key=user_uploads/1143800/8f9ece4b-ff95-4171-a3bc-e0cc82e73609)\n\nDefer’s infrastructure then **handles background function executions** with the configured parallelism and retries, **without infrastructure work or DevOps knowledge**.\n\nThe Defer Dashboard allows developers to manage applications with multiple environments and **get a sense of their product’s health** with **analytics and filters-rich executions list** view:\n\n![uploaded image](/media/?type=post&id=69350&key=user_uploads/1143800/0024a5c8-a2d6-4c80-a7fc-57f8f26fb4c4)\n\nFinally, developers get **notified on Slack upon failure** and can quickly access the execution’s logs and business metadata to **narrow down the issue and keep users in the loop**.\n\n## Focus on your product.\n\nGet started with Defer in a few minutes without refactoring or configuration, and start building delightful user experiences:\n\n* Defer comes with a [**free Hobby plan for developers** and small projects](https://app.defer.run/sign-up) 🚀\n* **As a YC company** (current batch and alumni) [benefit from a generous YC Deal](https://bookface.ycombinator.com/deals/1652) 💰\n* Defer is full-featured: you will find many examples [in our documentation](https://docs.defer.run/) 📖\n* Want to talk about your use case? [Let’s brainstorm together!](https://calendar.app.google/La5TPwFtvJhqwq7w6) 🧠",
        "url": "https://www.ycombinator.com/launches/I2Y-defer-a-zero-infrastructure-platform-for-node-js-background-jobs",
        "votes": 155,
        "created_at": "2023-02-16T14:56:47.173Z"
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    "name": "Fastgen",
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    "year_founded": 2023,
    "city": "New York City",
    "country": "US",
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    "primary_partner": {
      "name": "Gustaf Alstromer",
      "url": "https://www.ycombinator.com/people/gustaf-alstromer"
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      {
        "user_id": 334116,
        "full_name": "Mike Mahlkow",
        "title": "Founder",
        "founder_bio": "Co-Founder and CEO at Fastgen (W23). Previously CEO at Blair (S19) where we raised +100M to offer income-based financing options to students.  Before that learned how great teams operate at Stripe and Uber. ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/mikemahlkow/",
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        "user_id": 334608,
        "full_name": "David Nordhausen",
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        "founder_bio": "Co-Founder at Fastgen (W23). Previously built Blair (S19). Reach out if you're interested in using us david@fastgen.com",
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        "full_name": "Constantin Schreiber",
        "title": "Founder",
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        "title": "Fastgen - Low-Code API and workflow builder",
        "tagline": "Fastgen is a low-code API and workflow builder with an integrated Postgres DB.",
        "body": "### **☕️TL;DR**\n\n**Fastgen is a low-code API and workflow builder with an integrated Postgres DB.**\n\n**Our current customers use Fastgen to build backends for MVPs or internal tools and automate repetitive workflows for GTM, operations, or marketing teams.**\n\n![uploaded image](/media/?type=post&id=70265&key=user_uploads/334116/9b34df33-c911-4794-a329-8a7569e52502)\n\n### **Origin Story**\n\nThis is our second YC company. With Blair (YC S19), we raised more than $100M to help students get access to education in the US. One of our constant questions was how we could move even faster. We are building Fastgen to answer that question and are building a tool we wish we had during our time at Blair.\n\n## **What is Fastgen**\n\n### **REST APIs**\n\nFastgen's API Builder enables you to quickly create any REST API by using an intuitive drag-and-drop interface. Our platform also includes pre-built integrations to popular tools such as Sendgrid, Slack, and Twilio and the ability to connect to any external API you need for data exchange. We launch new integrations every week to make our users’ lives even easier. Instead of spending hours integrating third-party APIs and dealing with hosting, you can drag and drop the action into an API flow and deploy it with the click of a button. \n\n![uploaded image](/media/?type=post&id=70265&key=user_uploads/334116/9975f322-3ebe-4ca1-806f-520196fcc9af)\n\n### **Workflows**\n\nWith Fastgen, you can create time-based workflows that trigger at regular intervals and event-based workflows through the same user interface as the API builder. One of the standout features of Fastgen is the flexibility to define any action in a workflow or API as a custom event, which can then be utilized as a trigger for a separate workflow. \n\n### **Database**\n\nFastgen's integrated Postgres DB simplifies creating, reading, updating, and deleting data within your applications. You can easily build and manage your database alongside your APIs and workflows, all within one platform. If you have your own Postgres DB and don't want to use our hosted solution, Fastgen seamlessly connects to your database so you can take advantage of our platform's other features without changing your database setup.\n\n![uploaded image](/media/?type=post&id=70265&key=user_uploads/334116/f889316f-2fbe-485f-b7f5-b88e7fcec9d2)\n\n**Our ask:**\n\n* If you want to be part of our private beta, sign up on [fastgen.com](http://fastgen.com)\n* Mention that you saw us on Launch YC for prioritized onboarding",
        "url": "https://www.ycombinator.com/launches/IHJ-fastgen-low-code-api-and-workflow-builder",
        "votes": 394,
        "created_at": "2023-03-14T14:58:17.048Z"
      }
    ]
  },
  {
    "id": 27982,
    "name": "Clueso",
    "slug": "clueso",
    "former_names": [
      "Desklamp"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/8bb9d01e5193ccdd98bfdf1cea08fb2ede901fe5.png",
    "website": "https://clueso.io",
    "all_locations": "Bengaluru, KA, India",
    "long_description": "Clueso is the fastest and easiest way for companies to generate high-quality instructional videos and documentation, ideal for customer education/onboarding and employee training. Our AI transforms simple screen-recordings into studio-quality videos and step-by-step documentation in minutes.",
    "one_liner": "Create beautiful videos & docs for any product or process in minutes",
    "team_size": 25,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1677925658,
    "tags": [
      "Generative AI",
      "SaaS",
      "B2B",
      "Customer Success",
      "Enterprise"
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    "tags_highlighted": [],
    "top_company": false,
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    "batch": "Winter 2023",
    "status": "Active",
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    "regions": [
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      "South Asia"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/clueso",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/clueso.json",
    "year_founded": 2023,
    "city": "Bengaluru",
    "country": "IN",
    "linkedin_url": "https://www.linkedin.com/company/clueso",
    "x_url": "https://twitter.com/_Clueso",
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    "github_url": null,
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    "app_video_url": null,
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    "primary_partner": {
      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
    },
    "founders": [
      {
        "user_id": 1159730,
        "full_name": "Akash Anand",
        "title": "Founder",
        "founder_bio": "Co-founder & CEO at Clueso. \nAI to automate video creation for marketing, support, sales, and training teams. ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/theakashanand/",
        "x_url": "https://twitter.com/realAkashAnand",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a7153577a8363c9b34d410626830c013aa88ddbb.jpg"
      },
      {
        "user_id": 1156693,
        "full_name": "Neel Balar",
        "title": "Founder",
        "founder_bio": "I'm Neel, CBO at Clueso. Prior to Clueso, I built and scaled a consumer note-taking app to 20K+ users while in college. I studied Engineering Design and Data Science at IIT Madras. I previously led Asia's most advanced student Hyperloop team, where we raised $1.1M from the Indian govt. I also represented India at the SpaceX Hyperloop Pod Competition organized by Elon Musk. ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/neelbalar7/",
        "x_url": "https://twitter.com/BalarNeel",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c208d0c8a14f7da8da25a572bf83947c740cc12a.jpg"
      },
      {
        "user_id": 1156437,
        "full_name": "Prajwal Prakash",
        "title": "Founder",
        "founder_bio": "I'm Prajwal, co-founder at CTO at Clueso. I'm a Bangalorean and a recent (2022) CS grad from IIT Madras where I graduated top of my batch. I've always loved building products (previously made Desklamp, a consumer notetaking app) and working with nascent technologies (interned at Adobe AI, co-founded a quantum machine learning group in college). When I'm not thinking about tech, I write stand up sets.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/prajwalprakash2000/",
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    ],
    "jobs": [],
    "news": [
      {
        "title": "Business video automation startup Clueso raises $10M to kill off manual production processes",
        "url": "https://siliconangle.com/2026/10/13/business-video-automation-startup-clueso-raises-10m-to-kill-off-manual-production-processes/",
        "date": "Oct 13, 2026"
      },
      {
        "title": "Announcing our $1.4M seed funding | Clueso",
        "url": "https://www.clueso.io/blog-posts/announcing-our-seed-funding",
        "date": "Apr 23, 2024"
      }
    ],
    "launches": [
      {
        "id": 106963,
        "title": "Clueso Agents: Ship product videos automatically, whenever you ship features.",
        "tagline": "Launch videos, product demos, help tutorials, and more - all created automatically with every release.",
        "body": "Every new feature needs a launch video, help tutorial, sales demo, and more such content.\n\nClueso Agents automate the entire video production pipeline. From generating screen recordings of your product to voiceovers, motion graphics, and visuals that match your brand style.\n\nWith Clueso Agents, your content team can ship as fast as your engineering team does.\n\n[**https://youtu.be/2rio5VoUUV8**](https://youtu.be/2rio5VoUUV8)\n\n**🔴 The Problem**\n\nVideos are the best way to communicate your product’s value.\n\nBut they’re still created manually. For every new feature, your content team has to figure out what’s new, screen record the product, and edit the video with motion graphics and animations.\n\nThe result is a permanent backlog. By the time content is ready, the product has already moved on.\n\nTools like Loom and Screen Studio help you move faster, but only by compromising on quality.\n\n**🟢 The Solution**\n\nInstead of manually producing every video, let Clueso Agents ([**clueso.io/agents**](http://clueso.io/agents)) handle the entire production pipeline.\n\nHere's how it works:\n\n1. **Connect your product:** Give Clueso login credentials to your product or connect with GitHub, and provide one reference video that represents your brand style.\n2. **Every release becomes a trigger:** Clueso understands what changed and creates production plans for new features. It can also identify outdated videos in your existing library.\n3. **Our agent screen-records your product:** It logs into your product, navigates through the workflows, and captures polished screen recordings of the features you want to show. Fully autonomously.\n4. **AI handles the entire edit:** Along with the recordings, Clueso generates the voiceover, beautiful motion graphics, zooms and visual effects, captions, music, and applies your brand style.\n\nYou can also build workflows in Claude with the Clueso MCP, so video creation becomes just another step in your existing automations.\n\n**Why we're building this**\n\nOver the last two years, we built an AI video editor for product videos. Along the way, after working with 1,000+ SaaS companies, we realized editing wasn’t the only bottleneck.\n\nThe hard part was understanding what changed in the product, figuring out what to show in the demo, recording it cleanly, and keeping an entire video library up to date as the product evolved.\n\nWe’ve now replaced our recording extension with a browser agent that captures the recordings for you.\n\nOne customer recently rolled out a complete UI redesign that left nearly 700 videos out of date. With Clueso Agents, they refreshed the entire library in days instead of months.\n\nTo learn more and get started for free, book a demo with us at clueso.io/agents.\n\nWe can’t wait to show you agents in action!",
        "url": "https://www.ycombinator.com/launches/RpD-clueso-agents-ship-product-videos-automatically-whenever-you-ship-features",
        "votes": 15,
        "created_at": "2026-07-22T17:57:25.874Z"
      },
      {
        "id": 95851,
        "title": "Clueso: Product Videos in Minutes with AI",
        "tagline": "Your product ships fast. Your videos should too.",
        "body": "Hey all, we’re [Akash](https://www.linkedin.com/in/theakashanand/), [Prajwal](https://www.linkedin.com/in/prajwalprakash2000/), and [Neel](https://www.linkedin.com/in/neelbalar7/) from Clueso!\n\n**TL;DR:** Introducing Clueso – AI that turns any rough screen recording, document, or slide deck into a stunning video in minutes.\n\nhttps://youtu.be/OlOVMA06tpA\n\n## 🔴 The Problem\n\nOrganizations today need to produce more videos than ever, for a variety of use cases:\n\n* product demos\n* marketing and feature launches\n* customer onboarding\n* internal training\n* sales enablement\n* product, process, and workflow training\n\n… and so much more.\n\nBut creating these videos is time-consuming and requires specialized skills. And despite all the effort, engagement is usually low.\n\n## 🟢 The Solution\n\nClueso solves this. Our AI turns any rough screen recording, document, or slide deck into a stunning video in minutes.\n\nNo design skills required.\n\n![uploaded image](/media/?type=post&id=95851&key=user_uploads/1159730/9a6519b7-57f7-498c-ba0d-ab1ea1a07e1d)\n\nClueso can **write** your video’s script, add a studio-quality **voiceover**, and auto-generate visual **effects**, transitions, branding, and captions – all while giving you full editing control.\n\nIt can even **translate** your videos into 50+ languages with one click.\n\nWith this launch, we’re also introducing a suite of AI-first tools to **automate** the most time-consuming parts of the video editing process.\n\nWith a single prompt, Clueso can now:\n\n* **break down long recordings** like sales calls, webinars, or internal training calls, into bite-sized, polished videos\n* **generate** entire videos from documents and slide decks\n* **blur out** sensitive customer data from your screen recordings\n* create videos that match your brand or any design from our growing **template** library\n* generate **step-by-step docs** & SOPs from any screen recording\n\nMultiple teams at 1,000+ startups and enterprises already use Clueso for a variety of use cases.\n\nSign up today for free at [clueso.io](http://clueso.io)!",
        "url": "https://www.ycombinator.com/launches/Ovz-clueso-product-videos-in-minutes-with-ai",
        "votes": 176,
        "created_at": "2025-12-01T08:07:54.511Z"
      },
      {
        "id": 76665,
        "title": "Clueso: AI-powered product videos and documentation in minutes",
        "tagline": "Screen recording -> how-to articles crafted by AI and studio-quality videos with AI voiceovers ",
        "body": "### **TL;DR:**\n\n> Clueso helps teams create stunning product documentation in a fraction of the time.  Our tool converts simple screen recordings into comprehensive articles and kickass product videos. \n>\n> Clueso articles are crafted by AI and come with beautiful GIFs. \n>\n> To generate videos, Clueso lets you edit your script and swap your audio-track with a professional, natural-sounding AI voiceover. Videos also come with zoom- in effects, thumbnails, and custom branding – everything you need for a great video without any of the effort.\n\nHi everyone! We are Akash, Prajwal, and Neel, the team behind [Clueso](https://clueso.io/).\n\n## **🔴 The Problem**\n\nHigh quality educational content on products and processes isn’t a nice-to-have: it's a necessity. From knowledge base articles and feature launch videos to internal SOPs and employee training material, there's a constant need for videos and articles in any organization. \n\nBut creating this content is time-consuming and expensive:\n\n* Loom videos require several retakes to get the perfect output and, even so, don’t look professional or engaging enough.\n* If you’ve ever created documentation  for your product, you know how painful it is to capture screenshots and find the right words.\n\nAnd when a guide goes out-of-date, you need to put the same effort all over again!\n\n## **🟢 The Solution**\n\nClueso streamlines your entire workflow to create  product videos and documentation.\n\n**Creating User Guides**\n\nSimply capture a screen recording while talking through any feature or flow on your product. Clueso instantly gives you:\n\n* **Step-by-step articles:** Clueso snaps GIFs/screenshots, and AI drafts your guide automatically. No matter who captures the process, get a uniform tone across all articles. \\[[Check out a Clueso-generated article](https://www.clueso.io/features/help-articles)\\]\n\n  ![uploaded image](/media/?type=post&id=76665&key=user_uploads/1156693/1bc55859-9389-4b24-a054-db1efba881ed)\n\n* **Engaging studio-quality videos:** Update transcripts on-the-fly, and regenerate your video instantly with natural-sounding AI voices. Incorporate zooming-in effects and branded intro, outro, and background elements at a single click. \\[[Watch a Clueso-generated video](https://www.clueso.io/features/video-tutorials)\\]\n\n  ![uploaded image](/media/?type=post&id=76665&key=user_uploads/1156693/67d98602-2210-4f26-a668-13abd2ecd5cf)\n\n\n**Updating Content**\n\nWhen your product or process changes, simply re-record the updated flow and Clueso magically updates all related documentation. Don’t worry about swapping screenshots or explaining the same terms again. \n\n**Use Content Anywhere**\n\nContent created using Clueso can be exported anywhere or hosted on a Clueso powered help center or team workspaces.\n\n## **Our customers use us for creating…**\n\n1. how-to guides and videos for knowledge base\n2. SOPs for internal team training \n3. onboarding videos\n4. feature launch videos for landing pages and social media\n5. and sharing guides for ad-hoc customer queries\n\nBasically, anywhere you need videos or articles: Clueso has got your back.\n\n## **Our quick asks**\n\n* [Book a demo](https://calendly.com/clueso_intro/neel) with us if you want to learn more about Clueso and use it for creating product documentation, videos or a help center.\n* Refer us to anyone you know who’s on the lookout for a solution to improve their customer education or internal team training. Our inbox is always open [founders@clueso.io.](mailto:founders@clueso.io)\n* Follow us on [LinkedIn](https://www.linkedin.com/company/clueso) or [Twitter](https://twitter.com/_Clueso) for new product updates and customer education best practices.",
        "url": "https://www.ycombinator.com/launches/JwX-clueso-ai-powered-product-videos-and-documentation-in-minutes",
        "votes": 203,
        "created_at": "2023-12-05T06:46:46.430Z"
      },
      {
        "id": 70052,
        "title": "🚀 Clueso : Create in-app tours that never go out-of-date",
        "tagline": "One screen recording → Help guides in three formats!",
        "body": "Hey there! We’re [Prajwal](https://www.linkedin.com/in/prajwalprakash2000), [Neel](https://www.linkedin.com/in/neelbalar7/), and [Akash](https://www.linkedin.com/in/theakashanand), and we are very excited to launch [Clueso](https://clueso.io) to all of you!\n\n**TL;DR:** Clueso helps customer success teams save time creating and maintaining help content for SaaS apps. Our product converts simple screen recordings of product features into interactive product tours and how-to guides that stay up-to-date with every product release. \n\n![uploaded image](/media/?type=post&id=70052&key=user_uploads/1159730/adc0642c-6d2c-44cd-b4e3-7e18691a78fe)\n\n### [**🔴**](https://emojipedia.org/large-red-circle/) **The Problem**\n\nUsers of SaaS apps have a hard time discovering new features and finding what they’re looking for, even on products with a well-designed UX.\n\nCreating help guides on tools like Intercom is time-consuming – you have to put together screenshots, write out instructions, and make everything look presentable. Making interactive tours is even more work.\n\nAnd what happens when you deploy new UI updates? All your hard work goes down the drain, and you have to start from scratch.\n\n### [**🟢**](https://emojipedia.org/large-green-circle/) **Our Solution**\n\nClueso lets you create help guides for product features in seconds rather than hours. Here’s how it works:\n\n**Step 1:** \n\nUse our chrome extension to capture a simple screen recording of some feature on your app. \n\n**Step 2:**\n\nThat’s it; you’re done! \n\nClueso automatically generates help guides in three formats: a document with screenshots, a video, and an interactive tour that points users to the exact buttons they need to click on your app.\n\n**Wanna see it in action?** Check out this 2-min demo: [Clueso Demo](https://www.loom.com/share/964797a5cf6c4582b5ffb5ccca662abf)\n\nTo serve all these guides to your users, **insert a single line of code** to add our help widget to your app. Your users’ experience looks something like this:\n\n![uploaded image](/media/?type=post&id=70052&key=user_uploads/1159730/182a84cf-6ce7-4f5b-aa2f-695a47b208a8)\n\n### 🤯 **But wait, there’s more!**\n\nNo more waiting for angry customers to come tell you your docs are out of date!\n\nWith every new update on your app, all guides are automatically tested. Outdated guides are flagged so that you know exactly which ones need to be reworked.\n\n### **Meet the team**\n\n![uploaded image](/media/?type=post&id=70052&key=user_uploads/1159730/f606bc26-46b2-4218-af78-465829b49618)\n\nWe’re a team of recent grads from IIT Madras. Before Clueso, our team built and scaled [Desklamp](https://desklamp.io) – a note-taking tool for students and researchers – to 2k MAU from around the world. We experienced this problem first-hand with Desklamp, where our users would repeatedly email us similar questions about how to use the product. Prajwal (middle) has a bachelor’s in Computer Science, while Neel (left) and Akash (right) have a bachelor’s in Engineering Design and a master’s in Data Science. \n\n### **Our Ask**\n\n* If you’d like to give your users an interactive way to learn your app or discover new features, reach out to us at [founders@clueso.io](mailto:founders@clueso.io) or schedule a chat with us here: [calendly link](https://calendly.com/clueso/30min?month=2023-03).\n* If you know of someone else who may be interested, especially customer success managers at seed-stage+ start-ups, we’d love an intro!",
        "url": "https://www.ycombinator.com/launches/IDs-clueso-create-in-app-tours-that-never-go-out-of-date",
        "votes": 191,
        "created_at": "2023-03-08T18:48:43.909Z"
      }
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    "id": 27989,
    "name": "MagnaPlay",
    "slug": "magnaplay",
    "former_names": [
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    "website": "https://magnaplay.com",
    "all_locations": "Remote",
    "long_description": "MagnaPlay is game translation simplified into SAAS. Every game needs to be translated - a process which currently consists of finding freelancers, verifying their quality, negotiating prices, building contracts and waiting months for them to deliver. \r\n\r\nWith MagnaPlay, game developers cut out the middleman and get results 5x faster, at half the price and with more reliable quality. Our combination of AI, expert translators and SAAS fully integrates translation into the gamedev workflow, ensuring games are translated and reach the worldwide audiences that love them so much.",
    "one_liner": "AI-powered game translation.",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1673048240,
    "tags": [],
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2023",
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    "regions": [
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      "Fully Remote"
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    "stage": "Early",
    "app_video_public": false,
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/magnaplay",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/magnaplay.json",
    "year_founded": 2023,
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    "linkedin_url": "https://www.linkedin.com/company/magnaplay/",
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        "full_name": "Pedro Esteves",
        "title": "Founder",
        "founder_bio": "Pedro is co-founder and CEO of MagnaPlay, an AI-powered localization startup in YC's W23 batch. Prior to MagnaPlay, Pedro was studying Computer Science and Economics at Harvard University. He loves all things gaming, but particularly the indies!",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/pedro-esteves-434169204/",
        "x_url": "https://twitter.com/pedro_magna",
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      {
        "user_id": 845003,
        "full_name": "Paulo Rodrigues",
        "title": "Founder",
        "founder_bio": "Paulo is founder and CEO at MagnaPlay, an AI-powered game localization service. He recently dropped out of the University of Chicago and is working towards democratizing game development by making it a frictionless development experience.",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/rossirpaulo",
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      {
        "user_id": 218172,
        "full_name": "Eugenio Sánchez Rabiella",
        "title": "Founder",
        "founder_bio": "2X YC Founder at Flinto (W18) and MagnaPlay (W23), currently leading GTM at Mesmer (P25)",
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        "id": 69919,
        "title": "MagnaPlay — AI-powered game translation",
        "tagline": "We translate games at a faster, cheaper and more reliable rate.",
        "body": "# **TL;DR**\n\n_We use AI-assisted translators to largely automate the process of translating your game. We turn months of work into days, profit-ruining expenses into a manageable cost, and we help connect the world through gaming._\n\nHey everyone! We’re [Pedro](https://www.linkedin.com/in/pedro-esteves-434169204/) and [Paulo](https://www.linkedin.com/in/rossirpaulo/) from Brazil, two college dropouts from Harvard and the University of Chicago on the mission to democratize gaming!\n\n![uploaded image](/media/?type=post&id=69919&key=user_uploads/850536/d16a0f68-1635-4548-822d-2d6ee50300e1)\n\n# **❌ The Problem**\n\nWell, it’s pretty intuitive that games these days need to be translated, with English speakers compromising only 20% of the gaming population. What isn’t intuitive is how expensive and time consuming this process is. \n\nTraditional localization involves identifying a suitable partner, negotiating complex pricing models, vetting their quality, and paying them tens of thousands for what is often a straightforward task. A part-time developer might have to wait months and invest upwards of $30k to translate their game!\n\n# **✨ Our Solution**\n\nWe built technology that translates entire games in seconds, instead of months. We take into account cultural norms, game context and even screen display sizes. We then cross check texts across languages and pass everything through our QA team, ensuring meaning is preserved and quality is up to the highest standards. \\\nWe integrate this infrastructure to game devs’ IDEs. Translation is now fully streamlined into the game production process. No back and forth, endless invoices, and contracts ⁠⁠— just one subscription, like any other SAAS tool.\n\n![](https://lh3.googleusercontent.com/3zdQ0u3UCe3h5et4jEbJJ8rCb-VElM_392zurrbCQp-dg-dPY9GJE6sP57CNzqiXResvekBIsQzccFapNhPsyUpKUd3mftTGLyDFckJDX1eMizPoaTQibIf1me_fn1tQQhNfdBgcNqIiqpPtgll36u0)\n\n![](https://lh3.googleusercontent.com/GjSjjOsIeCOTOLVNWClkimrgPsDJOXH6ET4VOw-eGc8gAWhkjz6y1kWUt55FiA8NuuXYaPyEI9CH6RN2lV1GZgqOkZyuIpTN2d807zzDW0FF4csQ5Sd5dyAGYn9MolpWKt6zTpu0yDPzI_XGFY3SL60)\n\nGaming is the entertainment form of the future, and it only makes sense that it should be accessible to everyone around the world. We aspire to be a tool used to build that reality!\n\n# ✅**Our Asks:**\n\n* If you’re a game dev, or know someone who is, email us at [hello@magnaplay.com](mailto:hello@magnaplay.com)!\n* Spread the word! Share this post, help us connect the world! 🌎",
        "url": "https://www.ycombinator.com/launches/IBj-magnaplay-ai-powered-game-translation",
        "votes": 89,
        "created_at": "2023-03-03T18:21:41.609Z"
      }
    ]
  },
  {
    "id": 28074,
    "name": "Keep",
    "slug": "keep",
    "former_names": [
      "Paladin"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ca57c15ee63fa6b716d10d0f8f29a5e1732f44e4.png",
    "website": "https://www.keephq.dev",
    "all_locations": "Tel Aviv-Yafo, Tel Aviv District, Israel; Remote",
    "long_description": "Keep is an open-source AIOps platform. Keep acts as a single pane of glass to all your alerts from any monitoring tool and helps you turn 1000s into just 10s of meaningful alerts.\r\n\r\nKeep joined forces with Elastic on May 2025.",
    "one_liner": "The open-source AIOps platform",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1674164403,
    "tags": [
      "SaaS",
      "B2B",
      "Open Source",
      "Monitoring"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2023",
    "status": "Acquired",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "Israel",
      "Middle East and North Africa",
      "Remote",
      "Fully Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/keep",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/keep.json",
    "year_founded": 2023,
    "city": "Tel Aviv-Yafo",
    "country": "IL",
    "linkedin_url": "https://www.linkedin.com/company/keepalerting",
    "x_url": "https://twitter.com/keepalerting",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/ca57c15ee63fa6b716d10d0f8f29a5e1732f44e4.png",
    "app_video_url": null,
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    "primary_partner": {
      "name": "Aaron Epstein",
      "url": "https://www.ycombinator.com/people/aaron-epstein"
    },
    "founders": [
      {
        "user_id": 1194329,
        "full_name": "Tal Borenstein",
        "title": "Founder",
        "founder_bio": "Formerly an engineering manager, now CEO. Tech-savvy with vast experience leading software teams of SaaS products.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/talbo",
        "x_url": "https://twitter.com/talboren",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/efce62171280879cdbed15a6c634d821fbab1bc9.jpg"
      },
      {
        "user_id": 1196207,
        "full_name": "Shahar Glazner",
        "title": "Founder",
        "founder_bio": "Passionate about building stuff. Less is more. Long-distance runner.\nOccasionally (hopefully more) writes on shaharglazner.medium.com",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/shahar-glazner-29294654/",
        "x_url": null,
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a59b17a4ebe14a0690f9119a56d1d26b7aaf9f17.jpg"
      }
    ],
    "jobs": [],
    "news": [
      {
        "title": "\n\tElastic - Elastic Completes Acquisition of Keep\n",
        "url": "https://ir.elastic.co/news/news-details/2025/Elastic-Completes-Acquisition-of-Keep/default.aspx",
        "date": "May 20, 2025"
      },
      {
        "title": "Elastic and Keep join forces to help users manage alerts and automate workflows | Elastic Blog",
        "url": "https://www.elastic.co/blog/elastic-and-keep-join-forces",
        "date": "May 06, 2025"
      },
      {
        "title": "אחרי 8200 ו-Y Combinator: הסטארטאפ הישראלי Keep נחשף עם גיוס הון ראשון",
        "url": "https://www.geektime.co.il/keep-raises-seed-from-yc/",
        "date": "Oct 15, 2024"
      },
      {
        "title": "Keep's AIOps platform helps ops teams reduce alert fatigue | TechCrunch",
        "url": "https://techcrunch.com/2024/10/15/keeps-aiops-platform-helps-ops-teams-reduce-alert-fatigue/",
        "date": "Oct 15, 2024"
      }
    ],
    "launches": [
      {
        "id": 70094,
        "title": "Keep - Open source alerting CLI",
        "tagline": "Open source alerting CLI for all observability tools, with a simple and intuitive (GitHub actions-like) syntax.",
        "body": "Hey YC 👋, Shahar and Tal here 🚨\n\n![uploaded image](/media/?type=post&id=70094&key=user_uploads/1194329/3ba4c3ed-1965-4bf4-a261-985cecaff39e)\n\nWe are thrilled to share Keep with the YC community today!\n\n[Keep](https://github.com/keephq/keep) is an open-source alerting CLI alternative to Prometheus Alertmanager or Grafana Alerts, but for all observability tools, with a simple and intuitive (GitHub actions-like) syntax.\n\n**😫 Problem**\n\n* Engineering teams are frustrated with the explosion of tools that trigger alerts. On average, engineering teams have more than five tools that generate alerts.\n* Using proprietary vendor alerting/monitoring products locks you into the vendor, making it extremely challenging and time-consuming to migrate at a later stage.\n* Vendors today require you to send/integrate all your data, which is a big overhead when all you want to do is simple alerting.\n\n**🚨 Why Keep?**\n\n1. Simple and intuitive (GitHub actions-like) syntax.\n2. Declarative alerting that easily be managed and versioned in your source control and service repository.\n3. Alerts from multiple data sources for added context and insights.\n4. Freedom from vendor lock-in, making it easier to switch to a different observability tool if and when needed.\n\n💻 **Demo**\n\nPlay with Keep using our [Platform](https://platform.keephq.dev/)\\\n\\\n**🙏 Asks**\n\nTry out Keep and share your feedback on how it can be improved. Here’s our GitHub repo - <https://github.com/keephq/keep>\n\nHave any questions? Join our [Slack community](https://slack.keephq.dev/) and drop us a message",
        "url": "https://www.ycombinator.com/launches/IEY-keep-open-source-alerting-cli",
        "votes": 44,
        "created_at": "2023-03-09T17:20:58.252Z"
      }
    ]
  },
  {
    "id": 28080,
    "name": "Tagsafe",
    "slug": "tagsafe",
    "former_names": [
      "Tagsafe",
      "Swishjam"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d607b93f3da26fde36fd956fe7b3fb67f045e121.png",
    "website": "http://www.tagsafe.io",
    "all_locations": "Cincinnati, OH, USA; Remote",
    "long_description": "",
    "one_liner": "",
    "team_size": null,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1678306868,
    "tags": [
      "SaaS",
      "B2B",
      "Analytics",
      "Automation"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2023",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Fully Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/tagsafe",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/tagsafe.json",
    "year_founded": null,
    "city": "Cincinnati",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/swishjam",
    "x_url": "",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/d607b93f3da26fde36fd956fe7b3fb67f045e121.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": null,
    "founders": [],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 77810,
        "title": "Revenue Analytics by Swishjam — Connect your product usage data to revenue",
        "tagline": "Pull in all of your core SaaS-related revenue metrics into a single dashboard to enable you to better understand your business and keep track of what matters most; your revenue.",
        "body": "Swishjam’s Revenue Analytics solution pulls in all of your core SaaS-related revenue metrics into a single dashboard to enable you to better understand your business and keep track of what matters most; your revenue. Most importantly, your revenue is now automatically connected to your user’s product usage.\n\n![uploaded image](/media/?type=post&id=77810&key=user_uploads/26873/84e0b9b4-523c-4c42-a7b2-48f85eeb3255)\n\n**How does it work?**\n\nSwishjam connects to your Stripe account, syncs your data, and calculates all of your most important SaaS-related revenue metrics such as MRR, churn rate, revenue retention, and more.\n\nWhen you enable Revenue Analytics in Swishjam, you get:\n\n1\\. **Revenue Analytics Dashboard** - data visualizations of all your key revenue metrics.\n\n2\\. **Automations & Slack Notifications** - because Swishjam is now ingesting your Stripe events as they occur in real-time, you can set up [automations](https://swishjam.com/solutions/automations) to take actions when important revenue-related events occur.\n\n3\\. **Reporting** - Get daily/weekly/monthly reports on your revenue in Slack or by email.\n\n4\\. **User Profiles Tied to Revenue** - we automatically tie user profiles from your product analytics to Stripe data. This lets you build a better picture of your customer without lifting a finger. We also roll up this data to organizations if your app has that type of billing. Coming in version 2 is the ability to predict churn from this data and catch zombie users before they churn to keep more of your hard-earned customers.\n\n**Why is this exciting?**\n\nSure, lots of other apps already have this type of dashboard but **none that we know of can tie this type of information together easily**. Currently, it’s quite painful and most usually a manual process. This is also a big step towards our larger mission of tying your disparate data sources into your product analytics data as a first-party citizen, automatically stitched to your user profiles, and creating a true 360 user profile. What this means is that within Swishjam, you will be able to easily sift, segment, and visualize all of your product analytics data along with your billing data (and other data sources!) to answer questions like:\n\n1\\. Which of my users’ usage is dropping off who are subscribed to the Gold Plan?\n\n2\\. What percent of users on the Free Trial trigger the {your aha moment} event?\n\n3\\. What were the usage patterns for user XYZ leading up to their churn?\n\nInterested in getting access? Drop us a line at [founders@swishjam.com](mailto:founders@swishjam.com) and we’ll get you up and running in a few clicks.",
        "url": "https://www.ycombinator.com/launches/KF0-revenue-analytics-by-swishjam-connect-your-product-usage-data-to-revenue",
        "votes": 15,
        "created_at": "2024-01-24T15:34:14.849Z"
      },
      {
        "id": 70623,
        "title": "Swishjam - Open-source suite of page speed optimization tools",
        "tagline": "We help companies measure, monitor, and optimize their page speed to deliver best in class experiences to their users.",
        "body": "Hey all - Collin here, co-founder of Swishjam.\n\n[Swishjam](https://www.swishjam.com) is a suite of [open-source](https://www.github.com/swishjam/swishjam) tools that enables companies to deliver the best experience to their users by providing them with the tools they need to measure, monitor, and optimize their page speed.\n\n**Page speed really, really matters**\n\nPage speed is one of the most important yet overlooked metrics to delivering the best experience to _all_ of your users. A faster page load is directly correlated with higher conversion, better SEO, and lower bounce rates. Amazon reported in 2006 that every additional 100ms in page load resulted in a 1% drop in revenue. Despite that, the page speed tooling is lagging behind, leaving users with more questions than answers.\n\nWe first encountered this problem when working with users in a past role watching them attempt to diagnose performance issues on their site. While page speed was a top priority for them, they often had to use legacy software, and/or hire expensive consultants to triage and resolve them.\n\n**A wholistic solution to measuring, monitoring, and optimizing page speed**\n\nSwishjam helps you identify page speed bottlenecks by capturing key performance metrics your users are receiving on your site. Our dashboards help you make sense of your overall page speed, and provides you with actionable insights and tooling to improve.\n\n![uploaded image](/media/?type=post&id=70623&key=user_uploads/622150/fba9b8fe-a743-4318-abdd-79efe6954328)\n\n![uploaded image](/media/?type=post&id=70623&key=user_uploads/622150/4bebf3e3-89f4-466d-95db-391c1359feae)\n\n![uploaded image](/media/?type=post&id=70623&key=user_uploads/622150/1319cc5c-129a-4663-b194-61fc999f5da4)\n\n**Want to learn more?**\n\nIf you or someone you know works in eCommerce, digital media, or a related industry where page speed is important KPI, we’d love any intros! You can get in touch with us at [founders@swishjam.com](mailto:founders@swishjam.com).",
        "url": "https://www.ycombinator.com/launches/IN5-swishjam-open-source-suite-of-page-speed-optimization-tools",
        "votes": 35,
        "created_at": "2023-03-29T17:38:10.086Z"
      }
    ]
  },
  {
    "id": 28098,
    "name": "Resend",
    "slug": "resend",
    "former_names": [
      "Klotty",
      "Resend (fka Klotty)"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6ae1f42156169b5811f9a7efe6cce76305167d38.png",
    "website": "https://resend.com",
    "all_locations": "Remote",
    "long_description": "Resend is the new email API for developers. It's designed for you to build, test, and send transactional emails at scale.\r\n\r\nIf you're using Sendgrid, AWS SES, or Postmark, come talk to us.",
    "one_liner": "Email for developers",
    "team_size": 45,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1675214257,
    "tags": [],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2023",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "Remote",
      "Fully Remote"
    ],
    "stage": "Growth",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/resend",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/resend.json",
    "year_founded": 2023,
    "city": null,
    "country": null,
    "linkedin_url": "https://linkedin.com/company/resend",
    "x_url": "https://x.com/resend",
    "fb_url": null,
    "cb_url": "https://crunchbase.com/organization/resend",
    "github_url": "https://github.com/resend",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/6ae1f42156169b5811f9a7efe6cce76305167d38.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
    },
    "founders": [
      {
        "user_id": 360041,
        "full_name": "Zeno Rocha",
        "title": "Founder/CEO",
        "founder_bio": "Founder & CEO at Resend.\n\nPreviously VP of Developer Experience at WorkOS and CPO at Liferay Cloud. I'm originally from Brazil and now living in San Francisco.\n\nI love dark mode, open source, and side projects.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/zenorocha/",
        "x_url": "https://x.com/zenorocha",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/8be58137b9e1f4decb1102e7796df1b7bd5a7443.jpg"
      },
      {
        "user_id": 715890,
        "full_name": "Bu Kinoshita",
        "title": "Founder",
        "founder_bio": "Co-founder & CTO at Resend and building react.email.\n\n1st eng hire at WorkOS, which is now a Series B company valued at $500M. Built the first MVP and scaled it all the way to serve 200+ b2b sass customers. Also built more than 100 node packages and 2 products that were OSS, Taskr and Secret, which were featured in the #1 and #4 on Product Hunt",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/bkinoshita",
        "x_url": "https://twitter.com/bukinoshita",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1715ba918140f0b528a8bd0108b829f83412515e.jpg"
      }
    ],
    "jobs": [],
    "news": [
      {
        "title": "Resend raises $18M Series A",
        "url": "https://resend.com/blog/series-a",
        "date": "Dec 04, 2024"
      },
      {
        "title": "Developer-focused email platform Resend raises $3M | TechCrunch",
        "url": "https://techcrunch.com/2023/07/18/developer-focused-email-platform-resend-raises-3m/",
        "date": "Jul 18, 2023"
      }
    ],
    "launches": [
      {
        "id": 69586,
        "title": "Resend - Email API for developers",
        "tagline": "Send better emails that don't land in the spam folder",
        "body": "Hey, this is [Bu](https://twitter.com/bukinoshita) and [Zeno](https://twitter.com/zenorocha) from [Resend](https://resend.com).\n\nWe're building a modern email sending platform focused on providing the best developer experience and making sure that your emails don't go to spam.\n\nWe launched [7 weeks ago](https://twitter.com/zenorocha/status/1610655123063336961), and already have 6,469 people on the waitlist.\n\nPaul Graham described Resend as _“the Stripe for Email”_.\n\n![uploaded image](/media/?type=post&id=69586&key=user_uploads/360041/192c898e-24c0-470f-b5df-673f0b2ead56)\n\n### **problem**\n\nEmail sending is the kind of thing that you should integrate and forget it, but instead you have…\n\n* **Emails going to spam**: All too often emails are marked as spam even when they are legit. We believe that deliverability is a shared responsibility between the customer and the service provider, which means we work together with you to maximize email deliverability.\n* **Poor observability**: Most tools keep you in the dark without knowing what really happened after you sent an email. Resend exposes all the events associated with your email.\n* **Slow performance**: Current solutions only offer a single region for email sending (us-east-1), even when all your end users are located in another part of the world. Starting next week, we'll allow you to choose what region your emails should be sent from (Europe, LATAM, or APAC) which minimizes latency and improves time-to-inbox.\n* **Templates that users don't engage**: Startup teams don't have time the time to learn all the nuances of email development. We're offering a white glove service to help you implement a template that can generate better results.\n* **Designed for marketers only**: Existing solutions are too generic and built exclusively for product marketers and product managers. We're building a developer-first platform with a clean REST API and SDKs for Node.js, Python, Ruby, Elixir, Go, and Java.\n\nWe need to stop developing emails like it’s 2010 and rethink how email can be done in 2023 and beyond.\n\nWe believe that email development needs a revamp. A renovation. Modernized for the way we build apps today.\n\n![uploaded image](/media/?type=post&id=69586&key=user_uploads/360041/872480cd-c678-494c-b479-310d6eeb90a5)\n\n### **solution**\n\nTypically, you can only send email using HTML or plain text. Although we support both, we're introducing a new way of developing and sending your emails.\n\nWith Resend you can code your email using React instead of outdated HTML layouts thanks to our open source project [react.email](http://react.email) (5.1k stars on GitHub).\n\nWhen you're ready to send, you just need to import the component, change the props, and you're done.\n\nAfter sending, you can see the end result and look at how your users received that email.\n\n![uploaded image](/media/?type=post&id=69586&key=user_uploads/360041/05c80ce8-0a53-4fe9-9b75-8a8fd11d0be1)\n\n### **why us**\n\nWhen I was a CPO at [Liferay](https://liferay.com/), I faced the problem of sending emails at scale.\n\nWe had high-profile customers complaining about deliverability, and I've been frustrated with existing services ever since.\n\nMore recently, as a VP of Developer Experience at [WorkOS](https://workos.com/), I once again had to deal with emails landing in the spam folder.\n\nAfter looking at all the different solutions out there, I've been obsessed with the idea of solving this problem once and for all.\n\n### **our asks**\n\n* **Share** - talk to your friends and colleagues about Resend\n* **Connect** - ping me at [zeno@resend.com](mailto:zeno@resend.com) if you want to chat more\n* **YC companies** - you can skip the 6,469 people waitlist using the [secret link](https://resend.com/secret?ref=launchyc)",
        "url": "https://www.ycombinator.com/launches/I6M-resend-email-api-for-developers",
        "votes": 179,
        "created_at": "2023-02-23T14:44:43.968Z"
      }
    ]
  },
  {
    "id": 28103,
    "name": "Fern",
    "slug": "fern",
    "former_names": [
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        "full_name": "Danny Sheridan",
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        "full_name": "Deep Singhvi",
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        "date": "Apr 09, 2025"
      },
      {
        "title": "Meet the founders of Fern: CEO Danny Sheridan and CTO Deep Singhvi - Bessemer Venture Partners",
        "url": "https://www.bvp.com/news/meet-the-founders-of-fern-ceo-danny-sheridan-and-cto-deep-singhvi",
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        "id": 83851,
        "title": "Fern Docs: Developer-friendly API Docs",
        "tagline": "Build a \"Stripe-level\" docs website powered by OpenAPI",
        "body": "**_TL;DR_** [Fern Docs](https://buildwithfern.com/) is a static site generator for developer-focused companies to build and host their docs site. It’s the answer to the question:\n\n> **How do we make it easy to build a documentation website that looks as good as Stripe’s?**\n\nCheck out [Cohere’s Docs](https://docs.cohere.com/) built with Fern:\n\n![uploaded image](/media/?type=post&id=83851&key=user_uploads/1214945/1012ebb6-ebf7-4c68-a355-c0e48fb3de4e)\n\n![uploaded image](/media/?type=post&id=83851&key=user_uploads/1214945/2af9415a-59a0-4f97-bfa9-7ff954ecf162)\n\n# The Problem\n\n[Stripe.com](http://Stripe.com) is known for having the best documentation in the world. How do you make it easy for anyone to build a Stripe-level API documentation website?\n\n# The Solution\n\nFirst, we broke down Stripe’s Docs to determine why everyone loves them so much. Then, we studied popular documentation tools, including ReadMe, Docusaurus, Redocly, GitBook, Mintlify, and MkDocs. \\\n**We took the best parts of each.**\n\n### Key features\n\n* **Docs-as-code**: version your documentation like you version code. We support Markdown or MDX, so you can use GitHub, VS Code, and all the workflows you’re already familiar with.\n* **Powered by OpenAPI**: upload your OpenAPI Specification (fka Swagger) and get your API Reference auto-generated.\n* **API Playground:** let users try your API without leaving your docs. They can even sign in to auto-populate their API credentials. Time to {200} has never been faster.\n* **SDK Snippets:** demonstrate how to call an API using an SDK. The code snippets are auto-updated as your SDKs evolve.\n* **Professional design:** your docs represent your engineering quality. Match your brand identity, including colors, logos, fonts, and (of course) light & dark modes.\n* **Component library:** UI components that make your docs polished. If you’d prefer, bring your own React components.\n\n# Get a Preview of Your Docs\n\nWant to see what your docs look like in Fern? [**Request a tailored demo**](https://buildwithfern.com/contact?utm_medium=web&utm_source=launch-yc&utm_campaign=fern-docs) and mention “Launch YC.”\n\n# Start Building Self-Service\n\nReady to get started building your docs? Follow the [quickstart guide](https://buildwithfern.com/learn/docs/getting-started/quickstart) to spin up a docs site in under 15 minutes.",
        "url": "https://www.ycombinator.com/launches/LoR-fern-docs-developer-friendly-api-docs",
        "votes": 1266,
        "created_at": "2024-09-08T21:33:56.082Z"
      },
      {
        "id": 69195,
        "title": "Fern - SDKs for your API ⚡",
        "tagline": "Auto-generate your client libraries, API reference, and server code",
        "body": "**TLDR**: Fern generates useful artifacts for your API, like SDKs, docs, and server code. [Star us on GitHub! ⭐](https://github.com/fern-api/fern)\n\n![uploaded image](/media/?type=post&id=69195&key=user_uploads/1214945/858d9c67-1fb0-4dc2-8e3b-53c2c1db216f)\n\n_Steve Yazicioglu, Head of Engineering at Candid Health (Series A)_\n\n### **Problem**\n\nWhen building APIs, we spent a lot of our time doing things like:\n\n* Writing types & networking logic on the backend\n* Communicating details of the API endpoints over Slack\n* Re-writing the _same_ types & networking logic on the frontend\n* Re-writing the _same_ types & networking logic in each SDK or client library\n* Re-writing the _same_ information in our docs & Postman Collection\n\nInevitably, these multiple sources of truth get out of sync, causing runtime bugs, wasted hours of debugging, and frustration.\n\n### **Solution**\n\n[Fern](https://www.buildwithfern.com/) productizes schema-first API design. You define the schema of your API (or give us an OpenAPI spec) and we generate:\n\n* **SDKs** in popular programming languages. Our SDKs feel handwritten. They can be used externally for customers or internally for your frontend/microservices.\n* **API docs** that sync to your provider of choice.\n* **Postman Collection** complete with examples of successful and unsuccessful requests\n* **Server-side validation** to make sure that you serve the API you promised.\n\nFern also registers all versions of your API in a registry — no need to ping a coworker over Slack to understand how to consume an API.\n\nWith love [💌](https://emojipedia.org/love-letter/),\\\nTeam Fern 🌿 (Deep, and Danny)\n\n### **Our asks**\n\n* Star us on [GitHub!](https://github.com/fern-api/fern)\n* Read our [blog](https://buildwithfern.substack.com/p/how-candid-sped-up-api-development) about how Candid Health uses Fern\n* Book a demo at [www.buildwithfern.com](http://www.buildwithfern.com)\n\n### **What our users are saying**\n\n![uploaded image](/media/?type=post&id=69195&key=user_uploads/1214945/56c46bce-4a1b-4a2d-9ee2-3d6b09fdf6af)\n\n![uploaded image](/media/?type=post&id=69195&key=user_uploads/1214945/73910b0a-164f-47b9-9fb1-60bae68ec410)\n\n![uploaded image](/media/?type=post&id=69195&key=user_uploads/1214945/2bde4130-4d50-41b1-93dc-99d65387513b)\n\n![uploaded image](/media/?type=post&id=69195&key=user_uploads/1214945/2dafe8b2-bc05-4f37-9eaa-a207604186dc)\n\n![uploaded image](/media/?type=post&id=69195&key=user_uploads/1214945/f81f7cfa-ec25-4da5-bbcb-4fe1930b84e9)\n\n![uploaded image](/media/?type=post&id=69195&key=user_uploads/1214945/39bc2305-633a-414b-a800-57a959b4dbc0)\n\n",
        "url": "https://www.ycombinator.com/launches/I03-fern-sdks-for-your-api",
        "votes": 58,
        "created_at": "2023-02-10T17:18:52.681Z"
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    "one_liner": "Helps Developers build stunning UI Lightning Fast ⚡️",
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        "full_name": "Royal Jain",
        "title": "Founder",
        "founder_bio": "CEO at CodeParrot - Helps Developers build stunning UI Lightning Fast ⚡️ \n\nRoyal is a software developer turned Entrepreneur. Previously, CTO of a startup with $7 million ARR, acquired by an edtech unicorn. He was the founding engineer at voice analytics company Deepaffects (acquired by RingCentral) after completing computer science graduation from IIT Bombay.",
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        "user_id": 120142,
        "full_name": "Vedant Agarwala",
        "title": "Founder",
        "founder_bio": "Engineering leader. Led backend and mobile teams at unicorn tech company Apna Jobs and scaled systems to handle 100 million daily requests. 2x founder, dropped out of college to start quick commerce platform Instano (acqui-hired by MagicTiger).",
        "is_active": false,
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      {
        "id": 81056,
        "title": "CodeParrot AI: Ship stunning UI lightning fast ⚡",
        "tagline": "Transform Figma files to production-ready code. Build web and mobile apps in days, not months.",
        "body": "**tl;dr:** If you want to build a good UI faster, then [CodeParrot](https://www.codeparrot.ai/) is the product for you. It’s a vscode plugin where you specify your Figma component, share your code preferences, and voila! Don’t skimp on a good user interface; it’s the first impression you don’t get to make twice! Try it [here](https://marketplace.visualstudio.com/items?itemName=CodeParrot-ai.codeParrot).\n\n—\n\nHi, we are **Royal** and **Vedant**. We have worked as CTOs and EMs and started CodeParrot with a mission to improve developer productivity and happiness!\n\n![uploaded image](/media/?type=post&id=81056&key=user_uploads/329126/bf10e92c-2a6e-442f-a81a-3343bca809e6)\n\n[Royal](https://www.linkedin.com/in/royal-jain) (on the right) loves computer networking and building compilers. Talk to me about all things computer science and football (soccer for some of you)    \n\n[Vedant](https://www.linkedin.com/in/vedantsopinions) (on the left) loves building efficient user interfaces and cryptography (eth) and has OCD with coding practices. \n\n### ⚠️ Problem\n\nShipping fast often comes with cutting corners. When you cut too many corners, you end up going in circles. Just look at our old website \n\n![uploaded image](/media/?type=post&id=81056&key=user_uploads/329126/ada2d484-ada0-4248-a058-938611a65d31)\n\nwhich we are now changing to\n\n![uploaded image](/media/?type=post&id=81056&key=user_uploads/329126/b4c42892-e730-4845-9dfc-8834ceb0cdb5)\n\nBuilding a really good-looking product is hard! And with so many products out there, the user expectations have never been higher.\n\n### ⚡ Solution\n\nCodeParrot converts Figma Designs and screenshots to production-ready code. Why choose us?\\\n\\\n**We understand Figma** - we parse your Figma file to extract layout, style, and semantic information to give the most accurate results.\n\n![uploaded image](/media/?type=post&id=81056&key=user_uploads/329126/11a99a0f-9b33-42e6-aa89-9002971deb94)\n\n**We know you have code preferences** - specify how you like your code exactly. Only once.\n\n![uploaded image](/media/?type=post&id=81056&key=user_uploads/329126/9966735b-534c-4045-809a-a181061b74b4)\n\n**We build on your existing work** and reuse your existing components, libraries, and coding standards. \n\n![uploaded image](/media/?type=post&id=81056&key=user_uploads/329126/badbb145-a7e1-42e3-ba37-0f4ccd119f38)\n\nAll aligned to a single goal to help developers build stunning UI lightning fast ⚡️\n\n### Getting started\n\nSimply install the product from [vscode marketplace](https://marketplace.visualstudio.com/items?itemName=CodeParrot-ai.codeParrot). Join our [discord](https://discord.gg/pX3Mbghevg) for feature requests and more!",
        "url": "https://www.ycombinator.com/launches/L5M-codeparrot-ai-ship-stunning-ui-lightning-fast",
        "votes": 30,
        "created_at": "2024-05-23T15:03:44.200Z"
      },
      {
        "id": 69620,
        "title": "CodeParrot 🦜 - Automate API Testing using production traffic",
        "tagline": "Take back hours spent in testing, let CodeParrot generate and maintain intelligent test cases. ",
        "body": "**TL;DR** [CodeParrot](https://www.codeparrot.ai/) uses production traffic to generate intelligent test cases. What’s more? It can mock downstream dependencies like databases, external APIs, so you don’t need to set up a test environment to run these tests. If this sounds useful, **book a demo** [**here**](https://calendly.com/royaljain0203/30min) to learn more **📅**\n\n**About Us**\n\nHello everyone! We’re Royal and Vedant and we couldn’t be more thrilled to introduce CodeParrot to our fellow devs!\n\n**Problem**\\\nNobody likes writing tests. Why? Additional work, needs maintenance, requires setting up test environments, mocking 😩. What's there to like?\n\n**Solution**\\\nCodeparrot captures API calls from the production environment - both requests made to your backend service and downstream calls which the service makes (like database calls, third party APIs etc). This data is used to generate test cases.\n\n![uploaded image](/media/?type=post&id=69620&key=user_uploads/329126/592ba381-8fa6-4d0b-9fdf-57c3aa0626d2)\n\nWhenever the service is updated, we run the service in an isolated container. We replay the test cases and compare the responses with the responses captured in production. All the downstream services are mocked and regressions are highlighted to the developers. Sounds Interesting? Checkout our [Demo Video](https://www.loom.com/share/dd6c12e23ceb43f587814a2fbc165c1f).\n\n![uploaded image](/media/?type=post&id=69620&key=user_uploads/329126/0519dc8a-d821-42ea-bd60-f13a0e79ca67)\n\nCodeparrot is a auto-updating test suite for your backend services.\n\n**Our Ask - Give us a chance 🚀**\n\nWe want you! Interested in CodeParrot’s solution? Contact us at [royal@codeparrot.ai](mailto:royal@codeparrot.ai) or book a [demo](https://calendly.com/royaljain0203/30min) here",
        "url": "https://www.ycombinator.com/launches/I6u-codeparrot-automate-api-testing-using-production-traffic",
        "votes": 30,
        "created_at": "2023-02-23T20:32:04.700Z"
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    "name": "Vellum",
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        "question": "How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)",
        "answer": "We worked together at Dover (YC S19) for 2+ years where we built production use-cases of LLMs. Noa and Sidd are MIT engineers who have worked DataRobot’s MLOps team and Quora’s ML Platform team respectively. Akash spent 5 years at McKinsey’s Silicon Valley Office. While working with GPT-3 and Cohere to build user-facing LLM apps, we found ourselves building complex internal tooling to compare models, fine-tune them, measure performance, and improve quality over time. This took away time from building our user facing product. We’ve worked on ML Ops for traditional ML and wished we had the same when later working with LLMs, so we’re building it."
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    ],
    "url": "https://www.ycombinator.com/companies/vellum",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/vellum.json",
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    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/vellumai/",
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    "primary_partner": {
      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
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    "founders": [
      {
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        "full_name": "Akash Sharma",
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      {
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        "full_name": "Sidd Seethepalli",
        "title": "Founder",
        "founder_bio": "Vellum (W23)\n\nFounding Eng at Dover (S19)",
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        "linkedin_url": "https://www.linkedin.com/in/siddseethepalli/",
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      {
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        "full_name": "Noa Flaherty",
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        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/noaflaherty/",
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    ],
    "jobs": [],
    "news": [
      {
        "title": "AI development platform Vellum raises $20M Series A",
        "url": "https://www.axios.com/pro/enterprise-software-deals/2025/07/10/ai-development-platform-vellum-20m-series-a",
        "date": "Jul 10, 2025"
      },
      {
        "title": "Announcing our $20m Series A",
        "url": "https://www.vellum.ai/blog/announcing-our-20m-series-a",
        "date": "Jul 10, 2025"
      },
      {
        "title": "Prompt engineering startup Vellum.ai raises $5M as demand for generative AI services scales | TechCrunch",
        "url": "https://techcrunch.com/2023/07/11/prompt-engineering-startup-vellum-ai/",
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    "launches": [
      {
        "id": 96757,
        "title": "Vellum for Agents",
        "tagline": "Describe a boring ops task and get a working AI agent in minutes",
        "body": "**TL;DR: Today, we’re launching Vellum for Agents;** an agent builder that takes a plain description of what you want to automate and asks follow up questions to understand your needs. It connects to your tools, handles the logic, and shows you exactly what the agent is doing so you are never guessing why or how it works. To celebrate our launch we’ll be giving away free credits for everyone who signs up today (worth $100). Launch video [here](https://www.youtube.com/watch?v=72TU43fauo4).\n\nWe’re a W23 company with deep experience running AI in production. We’ve built AI tooling used by teams at Drata, Redfin, Seeking Alpha, Headspace, and Swisscom to launch and operate real AI solutions.\n\n_That experience led us here._\n\nToday, we’re sharing a new version of Vellum, an agent builder for ops teams. You describe the task you want to automate, and Vellum gives you a working agent in minutes. It asks follow up questions, connects to your tools, handles the logic, and shows you exactly what the agent is doing at every step, so there is no guesswork.\n\n## Common problems on using AI agents\n\nIn 2025 I watched as our engineering team gained superpowers. Coding agents like Devin, Claude Code, Cursor seemed to move them to a whole new level. By end of year, 40% of the work was done by agents and their productivity is up 2.5x.\n\nThat impact never really reached the rest of the company.For those of us who are not engineers, getting started with agents is still hard.\n\nWhile the models are good enough to help with Ops, Finance, Sales, and Marketing tasks, there are frequent challenges that we’ve observed:\n\n* Too many off-the-shelf tools that almost work, but break in specific edge cases\n* Prompts you tweak over and over, but still do not fully trust\n* Logic that becomes hard to manage in drag and drop builders\n* Little guidance on what is actually possible with agents\n* A lot of technical setup, before anything feels useful\n\n**_There is a huge drop off in the agent adoption funnel and we’re here to fix it._**\n\n## The solution\n\nToday we’re excited to launch the new version of Vellum.\n\nJust explain the task you want to automate and Vellum turns it into a working agent (like Lovable for agents). Vellum will ask follow-up questions to understand what you need and connect to your tools. It handles the logic and makes the agent’s behavior visible, so you’re never guessing what it’s doing or why.\n\n### Agent: Getting from 0 to 1\n\nOnce you give Vellum your prompt, it asks a few follow up questions and builds a plan. For some use cases, it will ask which apps to connect and confirm access. When it has everything it needs, it creates the first version of the workflow:\n\n![uploaded image](/media/?type=post&id=96757&key=user_uploads/1020427/aea05991-1a72-42a9-9f21-f803c82a3616)\n\n### Console: Access run and output details\n\nAfter you have the first version of your agent, you get a UI that shows exactly how it works and what it does on each run. You can keep refining it with help from the agent itself, whether that’s improving prompts, adding new tools, or adjusting the logic.\n\nTo then test your changes, you can run the agent directly from the UI and inspect every decision it makes, like which tools it calls, when it decides to run a web search, and how it arrives at the final output.\n\nWe believe our agent logic is among the most reliable out there, and teams reach a working setup much faster compared to other agent builders.\n\n![uploaded image](/media/?type=post&id=96757&key=user_uploads/1020427/8c4b97e9-0e04-4920-9719-2ef967d6c74e)\n\n### Interact: Run manually, via triggers, API or code\n\nOnce you’re happy with how your agent works, you have a few ways to use it. Depending on your use case, you can choose one of the following:\n\n* run the agent through a ready made UI\n* vibe code your own UI with one of our integrations (e.g. Lovable)\n* run it on a schedule or trigger it through APIs or app events\n\n![uploaded image](/media/?type=post&id=96757&key=user_uploads/1020427/77309dfb-ba7c-406d-b4ed-a38aa9d440f2)\n\n## Most common use-cases\n\nIf you want to try Vellum today, here are the common agent automations we’ve seen ops teams build:\n\n* **Content generation:** Agents around SEO and GEO keyword research, content analysis, and daily content creation.\n* **Sales ops automation:** This is where we’ve seen the most use cases in the last few months. From automated demo prep, to pulling account intelligence from CRMs, to analyzing sales calls and deals.\n* **Product ops:** Agents can reliably analyze support tickets and Linear issues, then ping the right DRIs to move things forward.\n* **Customer support:** This is where agents really shine today. They can classify all incoming tickets and surface insights, like the best timing for renewals, automatically.\n\n## What we ask\n\n1. **If you have one gnarly task that you’ve been putting out** we ask you to login to Vellum and try to automate it. Share your feedback in this thread or text me at [akash@vellum.ai](mailto:akash@vellum.ai)\n2. **Do any of these problems resonate with you?** Please share your experience in creating agents to automate your tasks. We would love to learn more!",
        "url": "https://www.ycombinator.com/launches/PAb-vellum-for-agents",
        "votes": 12,
        "created_at": "2026-01-14T17:26:33.481Z"
      },
      {
        "id": 74014,
        "title": "Vellum Workflows – Quickly prototype and deploy AI chains",
        "tagline": "Quickly prototype, deploy, and manage complex chains of LLM calls and the business logic that tie them together.",
        "body": "Hello hello! We’re Noa Flaherty, Akash Sharma, and Sidd Seethepalli from [Vellum](https://www.vellum.ai/).\n\n**Tl;dr** \"Workflows\" is a new product in Vellum's LLM dev platform that helps you quickly prototype, deploy, and manage complex chains of LLM calls and the business logic that tie them together. We solve the \"whack-a-mole\" problem encountered by companies that use popular open source frameworks to build AI applications, but are scared to make changes for fear of introducing regressions in production.\n\n**The Problem 😰: Many AI use-cases require chains of prompts, but experimentation and productionization of complex chains is hard.**\n\nWe have helped dozens of customers take their AI prototypes to production by delivering tools for efficient prompt engineering, tightly integrated semantic search, prompt versioning, and performance monitoring. However, as the AI industry matures, we’ve found that more and more real-world use-cases require multi-step flows across actions like semantic search, multiple prompts/LLM calls, and bespoke business logic.\n\nFor example, if building a customer-support chatbot, you may want to:\n\n1. Use a fast, low-cost, model to categorize an incoming user question\n2. Depending on the categorization, query against a different index in a vector store to return relevant context about how to answer the question\n3. Feed that context into a prompt that’s been tuned to answer accurately about that topic\n4. Feed the output of that prompt into another that rephrases using your brand voice\n5. Finally, return the answer to your end user\n\nUnfortunately, existing tools and frameworks don’t make it easy to:\n\n1. Rapidly experiment with these chains both step-by-step and end-to-end – especially if you’re non-technical\n2. Make changes with confidence once in production and avoid regressions\n3. Gain visibility into the performance of the system both as a whole, and at each step in the chain\n\n**The Solution 🤤: A fully managed platform for experimenting with, deploying, and managing AI workflows that power your app**\n\nVellum Workflows provides a low-code UI for experimenting with and deploying LLM workflows to power features in your app.\n\nYou can construct a workflow using different “Nodes,” define “Input Variables” to the workflow, their values across different “Scenarios” and run with a single click to see the output at each step along the way.\n\n![uploaded image](/media/?type=post&id=74014&key=user_uploads/1213437/1d62e723-3e99-4eb5-b4bd-5b4eef082579)\n\n_Shown here is one of the workflows used in production by a customer of ours, Miri Health, for powering their health & wellness AI chatbot._\n\nYou get immediate feedback on whether your chain/prompts perform the way you expect without having to edit code, inspect console logs, or hop between browser tabs. You can validate that your workflow does what it should across a variety of scenarios / test cases.\n\nOnce you’re happy, you can deploy the Workflow directly in Vellum and invoke it through an API via Vellum’s python/node SDKs. Events for nodes that you subscribe to are streamed back using [Server-Sent Events](https://www.w3schools.com/html/html5_serversentevents.asp).\n\n![uploaded image](/media/?type=post&id=74014&key=user_uploads/1213437/18a82c70-6ee8-4cde-af75-183014f838a0)\n\n_Invoke a workflow via a simple API. Use our officially supported python and node sdks, or roll your own._\n\nBy deploying your Workflow through Vellum, you can:\n\n* Mix and match models from different providers without having to integrate with each. Use the best prompt/mode for the job!\n* Have a production-ready backend in minutes without having to write, maintain, and host complex code and orchestration logic\n* Version your Workflow, see changes over time, and revert with one click\n* Get full observability into the production system, viewing inputs, outputs, timestamps, and more for the workflow as a whole, as well as each Node along the way.\n* Use role-based access control to determine which team members are allowed to experiment vs update production deployments\n\nMonitor how your workflows are performing in production, with the ability to inspect the inputs/outputs of the workflow as a whole, as well as each step in the chain.\n\n![uploaded image](/media/?type=post&id=74014&key=user_uploads/1213437/da276020-b865-472f-a569-c767320a5667)\n\n**Looking Ahead**\n\nThis is just the beginning! Our beta customers are already asking for things like:\n\n* A/B testing workflows for live experimentation\n* Test suites for evaluating that workflows are doing what they should and don’t break after an “improvement” is made\n* Composability via nested workflows\n* More node types for executing code, making calls to 3rd party APIs, etc.\n\n**Why Vellum?**\n\nOur focus to date has been to provide robust building blocks for creating production-ready AI applications. We’ve seen our customers assemble Vellum-powered Prompts and Semantic Search to create incredible products, version control and debug them using Vellum Deployments, and validate them when making changes using Vellum Test Suites.\n\nNow that we have the building blocks, we’re well-positioned to help you assemble them. Workflows has been in closed-beta for a few weeks now and we already have customers using them to power their entire AI backend in production.\n\n> Vellum Workflows give us the opportunity to really tailor different parts of our product to the end users’ needs without having to invest in tons of custom development, which has dramatically decreased our time to market. As a technical, but non-engineering stakeholder, I’m able to truly participate in the development of the product experience and help deliver personalized AI-powered experiences to customers faster than I could have ever imagined.\n>\n> **Adam Daigian, Product Lead at Miri Health**\n\nWe firmly believe that the best AI-powered products out there will be the result of close collaboration between technical and non-technical team members. We’ve repeatedly seen engineers set up the initial scaffolding, integrations, and guard-rails, while non-technical folks run experiments and tweak prompts/chains. No other platform facilitates this collaboration as well as Vellum.\n\n**Ask: How you can help**\n\n* Sign up for a free 14-day trial if the problems we aim to solve resonate with you. [Click here](https://vellum.ai/landing-pages/14-day-trial).\n* Share your thoughts and feedback on our direction in the comments below 👇\n* Spread the word with others you think this may help",
        "url": "https://www.ycombinator.com/launches/JFm-vellum-workflows-quickly-prototype-and-deploy-ai-chains",
        "votes": 37,
        "created_at": "2023-08-15T13:35:21.785Z"
      },
      {
        "id": 69757,
        "title": "Vellum - Build production-worthy LLM applications",
        "tagline": "The developer platform for building production-worthy Large Language Model applications",
        "body": "**TL;DR** [Vellum](http://vellum.ai) (W23) is a developer platform for building production-worthy applications on LLMs like @OpenAI’s GPT-3 or @Anthropic’s Claude. Use Vellum to save hours on prompt engineering, iterate on prompts in production confidently, and continuously fine-tune for better results (we helped one customer save 94% of their LLM costs through fine-tuning!). Request early access [here](https://www.vellum.ai/landing-pages/request-early-access).\n\n—\n\nHi everyone,\n\nAkash, Noa and Sidd here. We worked together at Dover (YC S19) for 2+ years where we built production use-cases of Large Language Models (LLMs). Noa and Sidd are MIT engineers who previously worked at DataRobot’s MLOps team and Quora’s ML Platform team respectively.\n\nWe decided to work on Vellum after realizing that while the MLOps industry has matured rapidly for traditional ML, companies using LLMs don’t have any of this tooling available. Engineering teams spend many hours building custom internal tooling to tame LLMs, taking away time from building their core product.\n\n![uploaded image](/media/?type=post&id=69757&key=user_uploads/1020427/c77e40f4-74d7-49b8-89cf-650548274362)\n\n# \n\n# **The LLM Management Problem**\n\nWe’ve seen companies building production applications with Large Language Models experience challenges at all stages:\n\n1. **Going from 0 → 1:** ”Prompt engineering” has become an important role in working with LLMs. Today, most people experiment with various prompts across browser tabs and the more diligent track the results of their experimentation in spreadsheets. Rarely do people take the time to test each variant across a sufficient number of test cases, let alone try different parameter combinations and LLM providers. Most settle for a sub-optimal configuration because the testing process is so tedious. Querying for semantically relevant context against a corpus of text to inject in the prompt is another large barrier for many people just getting started.\n2. **Managing changes once live in production:** Tracking model & prompt versions, keeping an audit log of inputs/outputs, testing changes to prompts/models before going into production, and measuring aggregate quality metrics are all critical for a production-worthy system, but all require custom code and non-trivial internal tooling. Engineers don’t have time to build out this tooling and instead, fly blind – never sure what their current baseline for quality is or whether “improvements” made to their prompts will in fact break existing behavior.\n3. **Post-MVP optimization:** Most people find a semi-reasonable prompt for _text-davinci-003_ and move on. But, they also acknowledge that with more time, they could set up a fine-tuning pipeline, experiment with other models/LLM providers, and try out new foundation models as they’re released to maximize output quality while dramatically reducing LLM provider spend. They’re paying a premium for sub-optimal quality and risk falling behind as new models are released.\n\n# \n\n# **The Vellum Product**\n\nWe have 3 products – each aimed to solve the problems we identified when building production LLM apps ourselves.\n\n### **Vellum Playground: Super powers for prompt engineers**\n\nCreate one “sandbox” per LLM use-case. In each, you can try as many prompt variants as you like across as many test cases as you wish. These prompt variants may differ in their text, underlying model, model parameters (e.g. “temperature”), and even LLM provider! Each run is saved as a history item and has a permanent url you can use share with teammates and track results.\n\n![uploaded image](/media/?type=post&id=69757&key=user_uploads/1020427/3a844278-c463-456f-ae0a-566ecbd29153)\n\n## **Vellum Manage: Confidently iterate on models in production**\n\nOnce you’ve settled on a prompt you like, you “deploy” it through Vellum. Vellum acts as a high-reliability, low-latency proxy layer between you and LLM providers. Every request is captured and persisted in one-place, providing observability into your model’s performance. Because the API interface doesn’t change, you can update your prompt (and even the underlying LLM provider!) without making any code changes. Previously made requests can be replayed against proposed changes to gain confidence prior to updating a deployment. All updates are version-controlled and you can revert to prior versions at any time.\n\n![uploaded image](/media/?type=post&id=69757&key=user_uploads/1020427/437adec7-b675-459c-8148-fe7600c20c41)\n\n## **Vellum Optimize: Continuously fine-tune to improve quality and lower cost**\n\nOnce you’ve collected data in production for some time through Vellum Manage, these input/output pairs (minimum 100, but depends on the use case), can be used to fine-tune your own proprietary models for better quality, lower cost, or lower latency. Your data and your models become a powerful competitive moat. Vellum periodically runs model evaluation jobs in the background to see if we can find a different model that works even better for your use case. If one is identified, you can swap models under-the-hood – no code changes needed!\n\n![uploaded image](/media/?type=post&id=69757&key=user_uploads/1020427/72d1eb55-ddc8-4512-b674-1e409c4eb608)\n\nP.S: If you’re curious, we recently published a blog where you can learn more about the benefits of fine-tuning and how to do it. Check it out [here](https://www.vellum.ai/blog/what-is-fine-tuning-and-when-to-use-it).\n\n### **Trusted by companies on the bleeding edge of AI**\n\n![uploaded image](/media/?type=post&id=69757&key=user_uploads/1020427/f3a6ea0a-6b88-4b9c-81a6-8a4770e42e0f)\n\n\n## **Our ask**\n\n* Visit [our website](http://vellum.ai) to learn more, [request early access](https://www.vellum.ai/landing-pages/request-early-access) if any of these problems resonate with you!\n* Spread the word! Share this post if you know of others looking to build applications using LLMs who would likely benefit from our platform\n* If you’re thinking about using LLMs and would like to discuss your use-case with us, please reach out through our website!",
        "url": "https://www.ycombinator.com/launches/I97-vellum-build-production-worthy-llm-applications",
        "votes": 95,
        "created_at": "2023-02-28T16:40:51.920Z"
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    "id": 28141,
    "name": "highlight.io",
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    "former_names": [
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    "website": "https://www.highlight.io/",
    "all_locations": "Seattle, WA, USA; Remote",
    "long_description": "highlight.io is the open source, full-stack monitoring platform. With just a few lines of code, Highlight makes it easy to understand what's slowing down your users and swiftly address errors and regressions on your web app.  Imagine that you have a customer reporting an issue on your web app. With highlight.io, you can playback their exact interactions to reproduce the bug and get notified of any future errors that could happen.\r\n\r\nThat being said, we’re just getting started! We have plans to go way deeper into your observability stack to give you all of the visibility you need. Join us on this journey:\r\n- Star us on GitHub (https://github.com/highlight/highlight) to keep up with releases and news.\r\n- Join our Discord (https://highlight.io/community) to share product feedback and thoughts.\r\n",
    "one_liner": "The open source, fullstack monitoring platform: stop guessing why…",
    "team_size": 8,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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    "primary_partner": {
      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
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    "founders": [
      {
        "user_id": 241768,
        "full_name": "Jay Khatri",
        "title": "Cofounder, CEO (acquired by LaunchDarkly)",
        "founder_bio": "I currently run the Observability business at LaunchDarkly. I was the CEO at Highlight, which was acquired by LaunchDarkly in March of 2025. ",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/jay-khatri",
        "x_url": "https://twitter.com/theJayKhatri",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b9f1e7513e56139706e0a7fa29cc2cf7701527f0.jpg"
      },
      {
        "user_id": 1250975,
        "full_name": "Vadim Korolik",
        "title": "Founder",
        "founder_bio": "Vadim Korolik is the founder and CTO of highlight.io, the open source session replay and error monitoring framework. A native of the Bay Area, Vadim previously worked at Pure Storage and drive.ai.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/vkorolik/",
        "x_url": "https://twitter.com/vkorolik",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/310d5870d701e4759b843740c85bf40bcf26f3e4.jpg"
      }
    ],
    "jobs": [],
    "news": [
      {
        "title": "Highlight launches full-stack application monitoring platform, raises $8M | VentureBeat",
        "url": "https://venturebeat.com/programming-development/highlight-launches-full-stack-application-monitoring-platform-raises-8m/",
        "date": "Aug 15, 2023"
      }
    ],
    "launches": [
      {
        "id": 68975,
        "title": "highlight.io - Open-source session replay & error monitoring",
        "tagline": "highlight.io is the open source, fullstack monitoring platform. We help engineers reproduce hard-to-crack issues, and understand how their product is used.",
        "body": "![uploaded image](/media/?type=post&id=68975&key=user_uploads/241768/1b79410b-8b41-4e1e-8869-c4ccfe7d2130)\n\n## **TL;DR:**\n\n[highlight.io](http://highlight.io) is an open-source **session replay and error monitoring** tool that helps teams reproduce hard-to-crack issues and understand product usage. We enable developers to understand WHY bugs are thrown on their web apps to eliminate the noisy alerts they get from more traditional monitoring tools.\n\n[highlight.io](http://highlight.io) is already being used in production by **2k+ developers and 80+ companies**. Get started for free at [app.highlight.io](http://app.highlight.io) and give us a ⭐️ at [github.com/highlight/highlight](http://github.com/highlight/highlight).\n\n### **The Problem**\n\nHow many times have you gotten an alert from Bugsnag or Sentry, and dismissed it because you weren’t sure about what caused it? And how many of you have an endless backlog of errors that your team _should_ triage, but haven’t gotten to yet?\n\nWe’ve found that when debugging an issue or customer request, **the toolset that you use is responsible for delivering one thing only: context**. And if there’s any gaps in this context, engineers are left in the dark.\n\nTo solve this, at our last companies, we found a lot of value in instrumenting a session replay-like tool, (similar to Logrocket or Fullstory), paired with an error monitoring tool (like Bugsnag). In fact, we’ve built these sorts of tools ourselves to hackily solve the problem. Enter [highlight.io](http://highlight.io).\n\n### **The Solution: Session Replay 🤝 Error Monitoring**\n\nWith a simple `yarn/npm` import in your frontend and an optional import in your backend, [highlight.io](http://highlight.io) gives you session replay and error monitoring out of the box. This means that you can:\n\n* Replay exactly what a user was seeing at the time of an issue/bug.\n* Reproduce the browser dev-tools for every user session, including the network requests, errors, and more.\n* Access all of the errors and exceptions (both frontend and backend) thrown in your app, paired with session replay.\n\nLastly, given the privacy-sensitive nature of the product, we have a very powerful privacy API that you can take a look at in our docs [here](https://www.highlight.io/docs/session-replay/privacy).\n\n## **💬 What’s Next?**\n\nWe’re just getting started! We have plans to go way deeper into your observability stack to give you ALL of the visibility you need; that means logs, traces and more! Join us on this journey:\n\n* ⭐️ us on [GitHub](https://github.com/highlight/highlight) to keep up with releases and news.\n* Join [our Discord](https://highlight.io/community)!",
        "url": "https://www.ycombinator.com/launches/HwV-highlight-io-open-source-session-replay-error-monitoring",
        "votes": 60,
        "created_at": "2023-02-02T19:04:50.853Z"
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    "id": 28192,
    "name": "Skyhook",
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    "website": "https://skyhook.io",
    "all_locations": "Tel Aviv-Yafo, Tel Aviv District, Israel",
    "long_description": "We make running services on Kubernetes as easy as Heroku, but on your cloud and with all the flexibility and power of Kubernetes. Companies use Skyhook so that they don't have to hire dedicated infrastructure engineers.\r\n\r\nAlthough 50-70% of organizations have already adopted Kubernetes, most developers agree that it is too complex and difficult to manage. It is intended to be extremely flexible in order to solve pretty much everyone’s needs, but it can take a ton of work and many auxiliary tools to get there.\r\n\r\nAs companies grow, they spend a lot on DevOps or Platform Engineers that try to reduce the burden on developers by gluing together all the 3p tools via custom internal tools.\r\n\r\nWe are building an “internal developer platform” out of the box, with best practices and golden paths for building and operating services on Kubernetes.\r\n\r\nWe do the research on the latest and greatest tools in the extremely vibrant ecosystem, and automatically integrate for you the tools you want to use.\r\n\r\nWe operate on our customers code and in your Cloud environment, so they never locked in and never restricted, as is common with classic PaaS offerings.\r\n\r\nIf you prefer a fully hosted environment like Heroku, Fly or Vercel, we’ll host a cluster for you and offer you a one-click migration to your own cluster when you want.",
    "one_liner": "PaaS-like experience with the power of Kubernetes, on your cloud",
    "team_size": 7,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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      "name": "Nicolas Dessaigne",
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        "full_name": "Nadav Erell",
        "title": "Founder",
        "founder_bio": "Experienced Software Engineer and team leader, with a passion for technology, product and strategy.\n\nSpent 9 years at Google working on Identity and Authentication, internal Google User Analytics, Notifications infrastructure, and Google Cloud, with multiple roles as TL / Architect.\n\nStudied Computer Science and Electrical and Computer Engineering (double degree) at Ben-Gurion University, graduating Summa Cum Laude in both.\n\nServed as an Intelligence Analyst in Unit 8200 in the Israeli Army.",
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        "linkedin_url": "https://www.linkedin.com/in/nadav-erell/",
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      {
        "id": 69952,
        "title": "Skyhook - Kubernetes the easy way 🚀",
        "tagline": "We make running services on Kubernetes as easy as Heroku, but on your cloud and with all the flexibility and power of Kubernetes.",
        "body": "**TL;DR; We help you set up production-ready services in minutes instead of days and weeks, with all the tools you need and Kubernetes best practices out of the box, so that you can focus on your code. [Talk to us](https://calendly.com/oded-koalaops/meeting) to learn more!**\n\n**Also, if you need help with migrating/working with Kubernetes please [contact us ](https://mailto:founders@skyhook.io)for a free consultation. We’d love to learn and help.**\n\nHi everyone, we’re Oded Regev and Nadav Erell, the founders of [Skyhook](https://www.skyhook.io/?utm_source=ycombinator&utm_medium=website&utm_campaign=yclaunch).\n\n![uploaded image](/media/?type=post&id=69952&key=user_uploads/1233799/182a0cd6-8737-48d0-9543-543907a62b1b)\n\n[**Nadav, CTO**](https://www.linkedin.com/in/nadav-erell/) formerly a Staff Software Engineer and an experienced team leader and architect at Google. Deep technical experience building scalable, robust systems in cloud native environments.\n\n[**Oded, CEO**](https://www.linkedin.com/in/odedregev/) founded and led Cherrypick Consulting for 7 years with diverse customers including Gong.io, Mixtiles, Outbrain, OpenWeb and many more. \n\n# The Problem\n\nAlthough [50-70%](https://www.cncf.io/reports/cncf-annual-survey-2022/) of organizations have already adopted Kubernetes, most developers agree that it is too complex and difficult to manage. It is intended to be extremely flexible in order to solve pretty much everyone’s needs, however, it can take a ton of work and many auxiliary tools to get there.\n\nAs companies grow, they spend a lot on DevOps or Platform Engineers that try to reduce the burden on developers by gluing together all the 3rd party tools via custom internal tools.\n\n# Our Solution\n\nWe give you an “internal developer platform” out of the box, with best practices and golden paths for building and operating services on Kubernetes.\n\n![uploaded image](/media/?type=post&id=69952&key=user_uploads/1233799/9f8423a0-3f16-48f6-911c-d8e6234bfbc1)\n\nWe do the research on the latest and greatest tools in the extremely vibrant ecosystem, and automatically integrate for you the tools you want to use.\n\nWe operate on your code and in your Cloud environment, so you’re never locked in and never restricted, as is common with classic PaaS offerings.\n\nIf you prefer a fully hosted environment like Heroku, Fly or Vercel, we’ll host a cluster for you and offer you a one-click migration to your own cluster whenever you want.\n\n# **Our Ask 🙏**\n\n[Contact us](https://mailto:founders@skyhook.io) - We have a few last slots left in our beta - we’d love to see if we can help you step up your Kubernetes game or migrate, so that you can focus on building your own product instead of configuring YAML files and tools all day.\n\n### **We also offer free Kubernetes consultation!**\n\nPlease [contact us](https://mailto:founders@skyhook.io) or [book time](https://calendly.com/nadaverell) - we’d love to assist, even if you don’t end up using our product. Learning about real-life challenges that you are facing and trying to help you navigate them helps inform our roadmap and focus.",
        "url": "https://www.ycombinator.com/launches/ICG-skyhook-kubernetes-the-easy-way",
        "votes": 49,
        "created_at": "2023-03-05T21:35:40.921Z"
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    "name": "Serial",
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    "website": "https://www.serial.io/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Serial is software to help manufacturers root cause problems in minutes not days and avoid millions in liabilities. Our solution integrates with data sources from any production line, enabling engineering & operations teams to ask questions about their manufacturing data and instantly get answers. Serial will become the single source of truth for manufacturing data.\r\n\r\nOur founding team has 10+ years of manufacturing and product design experience from Apple, Tesla, and more. We have suffered this problem firsthand and are building the tool to fix it.",
    "one_liner": "Root cause manufacturing issues in seconds",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1677010841,
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    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/serialmfg/",
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      "name": "Aaron Epstein",
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        "full_name": "Tak Alguire",
        "title": "Founder",
        "founder_bio": "Co-founder at Serial (W23). I've spent my carreer in the manufacturing space at Apple and Google. Now I lead the product team at Lumafield, making the best CT equipment in the world. Always will to trade notes with founders in the hardware/manufacturing space. ",
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        "linkedin_url": "https://www.linkedin.com/in/tak-alguire/",
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        "full_name": "Devon Copeland",
        "title": "Founder",
        "founder_bio": "Co-founder and CTO of Serial (W23). Devon has spent over 5 years working in hardware engineering at companies like Apple, Tesla, and Aeryon Labs. His obsession with timely, data-driven decision making has guided the engineering of several features on Apple Watch Ultra and the Model 3. Today, Devon is laser-focused on bringing his wealth of analytical engineering knowledge to Serial, thereby unlocking new cheat codes for any company making physical products.",
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        "linkedin_url": "https://www.linkedin.com/in/dkccopeland/",
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        "title": "Serial - Unify your manufacturing data",
        "tagline": "Helping engineers root cause manufacturing issues in minutes ",
        "body": "### **TL;DR**\n\n[Serial](https://www.serial.io/) unifies data from your manufacturing process, enabling engineers to save time and root cause issues immediately.\n\n### **The Problem**\n\n* Root-causing manufacturing issues is a painful and time-consuming process that requires collecting and aligning all forms of data - log files, dimensional measurements, supplier reports, images, etc.\n* These costly problems result in millions of dollars in lost production capacity, scrapped parts or product recalls.\n\n### **The Solution**\n\n* A pipeline to collect, parse, clean and structure data from any source on a production line\n* Models to identify local trends or deviations in data to escalate quality risks in realtime\n* Single platform to ask any question about your data and immediately get an answer\n\n![uploaded image](/media/?type=post&id=69709&key=user_uploads/1235892/1d0a0ce5-e134-43ed-839e-b2ee1da42986)\n\n### **The Team**\n\nWe are Waterloo grads with 10+ years of experience in product design and manufacturing quality from Apple, Tesla, and North. We have suffered this problem firsthand and are building the tool we wish we had.\n\n![uploaded image](/media/?type=post&id=69709&key=user_uploads/1235892/4ee36f70-60d5-4903-9a22-d325dbead0e3)\n\n### **The Ask - Intros to Manufacturers**\n\nIf you are manufacturing products and share this pain, then reach out to [founders@serial.io](mailto:founders@serial.io) or sign up directly at [serial.io](https://www.serial.io/contact-us)",
        "url": "https://www.ycombinator.com/launches/I8L-serial-unify-your-manufacturing-data",
        "votes": 26,
        "created_at": "2023-02-27T17:43:34.649Z"
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    "id": 28361,
    "name": "Lightski",
    "slug": "lightski",
    "former_names": [
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      "Lightski",
      "Streamstraight"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4f913750d13336c120035ae29b41b164fc9638be.png",
    "website": "https://www.lightski.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Lightski implements AI agents to replace document-heavy enterprise workflows. One document-heavy customer now processes intake in 10 minutes instead of 2 days, with a > 5x decrease in cost. \r\n\r\nTo do so, we audit and rebuild the entire substrate your business runs on, native to AI. From document-heavy intake to back-office execution, automatically drive your top line with Lightski agents.",
    "one_liner": "Transform Document Workflows with AI Agents",
    "team_size": 1,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1678895856,
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      "Generative AI",
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    "url": "https://www.ycombinator.com/companies/lightski",
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        "full_name": "Hansen Qian",
        "title": "Founder",
        "founder_bio": "Hansen is the the cofounder of Lightski. Previously, Hansen was a founding engineer and engineering manager at Affinity CRM.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/hansenq",
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    "news": [
      {
        "title": "Una apuesta de Y Combinator que impulsa la IA generativa | Emprendedores",
        "url": "https://www.expansion.com/expansion-empleo/emprendedores/2023/05/03/645247fee5fdeaa9148b4653.html",
        "date": "May 04, 2023"
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      {
        "id": 87552,
        "title": "Lightski",
        "tagline": "Audit and rebuild the entire substrate your business runs on, natively with AI.",
        "body": "Don't just automate tasks. We audit and rebuild the entire substrate your business runs on, natively with AI. From document-heavy intake to back-office execution, automatically drive your top line with Lightski agents.\n\n![uploaded image](/media/?type=post&id=87552&key=user_uploads/68558/97044200-bcd0-4229-84c4-217b3e952f28)\n\nIf you’re a company looking to pilot a plan for your entire team, please email [founders@lightski.com](mailto:founders@lightski.com). ",
        "url": "https://www.ycombinator.com/launches/Mm8-lightski",
        "votes": 41,
        "created_at": "2025-02-10T17:57:02.574Z"
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      {
        "id": 80683,
        "title": "Lightski - Embed an AI data scientist in your app",
        "tagline": "Embedded data analytics more powerful than Tableau and Looker by pairing AI with code execution",
        "body": "**tl;dr:** Lightski helps you build an analytics experience for your users that answers any arbitrary question about their data. We provide embedded data analytics more powerful than Tableau and Looker by pairing AI with code execution, which eliminates hallucinations.\n\n## Why?\n\nBefore YC, I was an engineering manager at Affinity CRM, where we spent six figures on an embedded analytics solution. Even then, our users were never happy; they either didn’t know how to navigate the complex UI or wanted even more advanced analytics. Most customers ended up exporting the data themselves and running their own analysis (not an ideal solution).\n\nRecent AI advancements remove this trade-off, enabling a natural language interface and powerful code-based analysis. We started Lightski to quickly give your users the full power of a data scientist, without needing to know a line of code.\n\n## User Experience\n\nWith Lightski, you’re able to embed an AI Data Scientist in your app, pre-loaded with your users’ data. Your users can then explore a dataset however they want; in response, we generate and execute code to perform analyses, such as:\n\n* Create custom graphs, charts, and dashboards\n* Perform arbitrary filters, group-bys, and aggregations\n* Transform or clean data for a custom CSV export\n\nAnything that a data scientist can accomplish in code can now be accomplished with Lightski. Best of all, your users won’t even know we’re powering the experience—you can quickly re-theme our UI with your design system.\n\n![uploaded image](/media/?type=post&id=80683&key=user_uploads/68558/dea1307b-ab28-464c-acf0-f89373cf1dfe)\n\n## Under the Hood\n\nWe rely heavily on state-of-the-art LLM models to guide the analysis, but there’s a lot of other capabilities built in-house that power the experience:\n\n* Secure and isolated per-user code execution environments\n* Native connectors for the most common databases\n* Code-based ETL, for flexible data pre-processing and transformation\n* Support for image generation and CSV export\n* Embeddable streaming UI that supports custom theming\n\nWe’re building fast and will also soon launch:\n\n* Interactive charts and even more customizable dashboards\n* Direct API access to our safe code execution environments and ETL pre-processing features\n* Guided assistants, for less technically-savvy users\n\nand much more! Let us know if you’re interested in any of these and we’ll prioritize it for you.\n\n## Get a Demo\n\nThe fastest way to get access to Lightski is by [signing up for our waitlist](https://forms.gle/Sj239WNvp5ZTLJGX6) or emailing [founders@lightski.com](mailto:founders@lightski.com)—we’ll help you format your data into a clean schema, and get Lightski embedded in your app within the day. Email us with any questions or feedback!",
        "url": "https://www.ycombinator.com/launches/KzL-lightski-embed-an-ai-data-scientist-in-your-app",
        "votes": 32,
        "created_at": "2024-05-07T17:04:06.921Z"
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    "id": 28416,
    "name": "Pierre",
    "slug": "pierre",
    "former_names": [
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    "website": "https://pierre.co",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "We are re-building code hosting, code review, and CI primitives from the metal, for the next generation of professional developers: Small, focused teams, working closely, augmented by AI.",
    "one_liner": "Pierre is a new, opinionated, git platform.",
    "team_size": 10,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1677182558,
    "tags": [
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      "Developer Tools",
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      "Productivity",
      "Collaboration"
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        "title": "Pierre - A new way to review code",
        "tagline": "Pierre enables engineers, designers and business team members to discuss new features before they're merged.",
        "body": "Hi Everyone —\n\nWe are Ian and Jacob, and we are on a mission to modernize code reviews. Sign up for the alpha on [**HeyPierre.app**](http://heypierre.app/)\n\n![uploaded image](/media/?type=post&id=69619&key=user_uploads/46928/b1f1d6e0-88b1-4a2e-b17c-0d5982d2543d)\n\nJacob (CEO) and Ian (CTO) met as early engineers at Twitter 14 years ago.\n\nJacob is the co-creator of Bootstrap (one of the largest and most popular open source communities on GitHub) and later went on to work as one of the first engineers at Medium. Ian was the first intern at Twitter, dropping out of college at 19 to TL the Twitter platform team.\n\nJacob and Ian co-founded a mobile app called Bumpers in 2016, which was eventually acquired by Coinbase. For the next 5 years, they led the Product Platform team at Coinbase and were the company-wide web and mobile DRIs.\n\n### Github doesn’t solve today’s biggest engineering problems\n\nIn the decade+ since Github was built, tools that prioritize real time collaboration and discussion (Figma, Notion, and Linear) have exploded in popularity, but the circa-2006 code review experience hasn’t materially changed.\n\nWe’re building a new way to review code, and we’re starting with pull requests. As engineers with more than 15 years of experience, we’ve seen firsthand how cumbersome a pull request review is using Github — often, pull requests lack necessary context, take too long to approve, and cannot be viewed by non-engineers for feedback. Github’s comment features make it difficult to manage a conversation over time, and discussion is lost when engineers switch to Slack or Hangouts.\n\n### Your code, conversations, and collaborators. Together.\n\nPierre enables engineers to shape the way that their code is reviewed. We’re starting with two of the biggest problems that engineers have:\n\n1. How do you set better context?\n2. How do you better manage discussions?\n\nWe’re taking features of the products you love most — the organized chats of iMessage, the real time collaboration of Figma, and the narrative structure of Notion — and we’re bringing it to code reviews.\n\n![uploaded image](/media/?type=post&id=69619&key=user_uploads/46928/2f0b02fe-d44b-4605-a704-f66aa7736c4f)\n\nUsing Pierre, code review creators can:\n\n* Set context next to the code\n* Reorganize diffs intuitively\n* Break up large pull requests into digestible bites\n\nAnd code reviewers can:\n\n* Be anyone — no more waiting for the bug bash to get design and product feedback\n* Comment on anything — code, images or text\n* Conduct real-time conversations right next to the code\n* Get up-to-speed on changes more quickly\n\n### Why we built Pierre\n\nWe’ve been intimately using GitHub since it’s inception (Ian’s user id is #91). There’s been a lot to love about GitHub over the years, but innovation on the core experience is lagging and other pieces of our toolchain are making us expect more. This is only exasperated by Ian living in NYC and Jacob in SF.\n\nEngineers deserve a realtime, collaborative software platform optimized for productivity - instead of a slow, feed-based social network for coding.\n\n### Try Pierre Out!\n\n* Head to [**HeyPierre.app**](http://heypierre.app/) and sign up for our waitlist. We’re in closed alpha, but we can’t wait for you to try us out.\n* We’re looking for a handful of fast growing teams (with \\~25-50 engineers) to pilot us. If you know a team that could be a good fit, email [rachel@heypierre.app](mailto:rachel@heypierre.app). **Earn a $200 referral bonus for each paying team you bring in.**",
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        "body": "![uploaded image](/media/?type=post&id=73762&key=user_uploads/1325352/d762639d-84c1-4c4b-bf46-b418b05b3b9e)\n\nHey everyone, we are [Severin](https://www.linkedin.com/in/b6b682ce450f9e1c8717c24cdb1c988a3ac717b6cbe6e1373a177119a742a434/), [Chris](https://www.linkedin.com/in/kindl/), and [Achilleas](https://www.linkedin.com/in/achilleas-mitrotasios/). Tremor started as an open-source UI library to create dashboards, which grew to more than 10K Github stars in less than 10 months. This is where we discovered how many people need to build consumer-friendly dashboards but lack the resources to do so.\n\n**Problem**\n\nAlmost every SaaS requires visualizing data for their end-users. However, creating customer-facing dashboards from scratch requires a significant effort for both engineering and design teams.\n\nTherefore, many companies cannot afford to invest resources into building a visualization layer, especially when analytics is not part of the core product. Often, this results in an underwhelming user experience and additional revenue left on the table.\n\n**Solution**\n\nThe Tremor Platform is a visual dashboard builder made for developers. It allows users to connect to data sources, create dashboards with an easy-to-use interface, and embed them as a performant, white-labeled analytics layer into existing apps. For example, a bank could deploy a dashboard that visualizes spending to their customer portal, in days instead of months.\n\n**Meet the team**\n\nSeverin, Achi and Chris (left to right) know each other since university. Severin and Chris worked at Accenture for 3+ years, building dashboards for Fortune 500 companies. Achilleas previously worked as a software engineer at Bloomberg. They started Tremor as a side project next to their full-time jobs as they could not find a satisfying solution for visualizing data on websites.\n\n![uploaded image](/media/?type=post&id=73762&key=user_uploads/1325352/5c357073-2dae-464c-aabb-797a21d16fb3)\n\n**Our** **Ask**\n\n1. Sign up on our waitlist at [platform.tremor.so](https://platform.tremor.so)\n2. We love to partner with early customers to evaluate their use cases and optimize our platform to their industry-specific needs. If you are a company looking to leverage your dashboard capabilities, shoot us an email at [hello@tremor.so](mailto:hello@tremor.so).",
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        "id": 73574,
        "title": "Metoro: Debug production systems faster with AI",
        "tagline": "Metoro surfaces relevant metrics and logs, performs root cause analysis and suggests remediations",
        "body": "**tl;dr:** Metoro is an AI agent which helps you debug production systems. Ask Metoro for help and it will surface relevant metrics and logs, perform root cause analysis and suggest remediations. It plugs into your existing observability stack (like DataDog, Grafana, Elastic, etc.) and debugs your system with you.\n\nHi everyone! We’re Chris and Tom, the team behind Metoro. We’re software engineers who have worked on complex distributed systems at Palantir and Jump Trading and are building the debugging tool we wish we had.\n\n## The Problem: Debugging production systems is hard\n\nProduction systems are complex. It’s difficult to identify the metrics and logs that are relevant to the bug you’re hunting. This problem gets worse if you didn't write the code in the first place, or are unfamiliar with the system.\n\n## The Solution: An interactive debugging agent that investigates with you\n\n[Metoro](https://metoro.io/) acts like an experienced engineer. It understands your system and debugs your services one by one, updating its hypothesis as it discovers new information.\n\nWhen it’s done, the investigation results are presented to you in an interactive dashboard for you to explore. This includes a root cause hypothesis, potential remediations and relevant logs and metrics for each service it looked at.\n\nMetoro reads data from your existing observability stack. No application or infra changes needed.\n\n### Ask: How you can help\n\n* We're signing up teams from startups/scale-ups. If you'd like to try it or know people who would, please shoot us a mail at [founders@metoro.io](mailto:founders@metoro.io) or book a demo call <https://calendly.com/chris-battarbee/15-minute>\n* Check out our [website](https://metoro.io). We’d love your feedback!\n* **Upvote and share this post!**",
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        "full_name": "Jonathan Kelley",
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        "title": "Dioxus Labs - Web, Desktop, and Mobile apps with one codebase",
        "tagline": "We make it easy for developers to build apps that run anywhere",
        "body": "**tldr**; [Dioxus Labs](https://dioxuslabs.com/) makes it easy for developers to write an app once and run it on nearly any platform. Our open-source Rust library has over 10,000 stars on GitHub and is used by Airbus, the European Space Agency, and Huawei.\n\n—\n\nHi everyone, I’m Jonathan Kelley, the solo founder behind Dioxus Labs. A year ago, Dioxus was just a college side project. Now, it’s my full-time job, used by some of the world’s top companies. Before Dioxus, I worked at Cloudflare, interned at NASA, and researched plasma physics.\n\n![uploaded image](/media/?type=post&id=73738&key=user_uploads/749074/df721fdb-e2c2-4cf3-b002-dc71be942743)\n\n### **🥊 Building apps can be really hard**\n\n---\n\nBuilding apps can be challenging. App developers must navigate a complicated maze of tooling, libraries, and programming languages. Building an app that works on iOS, Android, Mac, Linux, and Windows is out of reach for many developers.\n\nSmall teams especially struggle with shipping cross-platform apps:\n\n* Few developers know Mobile, Desktop, _and_ Web development\n* There are hundreds of different tools to learn\n* Current solutions are missing major features\n* It’s really easy to build slow apps\n\nNone of the leading options like React Native, Flutter, Electron, or native make it easy for a small team to ship cross-platform apps quickly.\n\n### **✨ How do we make it easy?**\n\nWith Dioxus, developers can write their app once and then ship it to users on the web, desktop, and mobile. Instead of learning dozens of different technologies like backend, frontend, and mobile, app developers only need to learn Dioxus to build and ship their app.\n\nDevelopers build their apps in Rust with a React-like syntax and style their apps with HTML and CSS, making the onboarding from web development simple.\n\n![](https://bookface.ycombinator.com/media/?type=post&id=73738&key=user_uploads/749074/b60dfc39-1d47-4028-99c5-86a906507f3a)\n\nThe project is entirely open source and written in Rust: developers’ most loved programming language.\n\n![uploaded image](/media/?type=post&id=73738&key=user_uploads/749074/162ae1d4-16a7-47cc-89cd-b2166f43f415)\n\nIn the future, Dioxus Labs will provide a paid deployment platform that helps developers deploy and scale their Dioxus apps to their users.\n\n### **🚀 Is it working?**\n\n---\n\nThe past year has been great - the library has grown to almost 10k GitHub stars, 60k downloads, and companies like Huawei shipping production apps with Dioxus.\n\n![star history](https://i.imgur.com/Idni1n9.png)\n\nAirbus and the European Space Agency are building a [collision avoidance system](http://skytrace.space/):\n\n![](https://bookface.ycombinator.com/media/?type=post&id=73738&key=user_uploads/749074/e7130cf8-8e8a-400f-9c30-ffb7e84047d9)\n\n[Satellite.im](http://satellite.im/) is building a [peer-to-peer Discord competitor](https://uplink.satellite.im/):\n\n![uploaded image](/media/?type=post&id=73738&key=user_uploads/749074/2d40c8b2-63e3-4f50-8da4-54589f4bd701)\n\nA community member is building a [beautiful Mastadon client](https://terhech.de/ebou/):\n\n![](https://bookface.ycombinator.com/media/?type=post&id=73738&key=user_uploads/749074/74570fa3-f926-449d-865b-76eb6ebf46da)\n\n### **🤝 How can you help?**\n\n---\n\nWe’re hard at work building a deploy platform for Dioxus. In the meantime, we’d love your support:\n\n* [Star us on GitHub](http://github.com/dioxusLabs/dioxus) [⭐](https://emojipedia.org/star/)\n* Try out Dioxus for your next idea or internal tool\n* Recommend a great Rust engineer who might be interested in working at Dioxus Labs\n\nWe’re around in our community [Discord](https://discord.gg/XgGxMSkvUM), but feel free to reach out directly if this is at all interesting to you.",
        "url": "https://www.ycombinator.com/launches/JBK-dioxus-labs-web-desktop-and-mobile-apps-with-one-codebase",
        "votes": 29,
        "created_at": "2023-08-02T21:40:38.712Z"
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    "name": "Sweetspot",
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    "website": "https://www.sweetspot.so/",
    "all_locations": "New York City, NY, USA",
    "long_description": "Sweetspot is an all-in-one government sales platform, powered by AI. We help businesses find, manage, and respond to government opportunities.\r\n",
    "one_liner": "AI for Government Contracting.",
    "team_size": 10,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1689300101,
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    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2023",
    "status": "Active",
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    "regions": [
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      "America / Canada"
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/sweetspot",
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    "year_founded": 2023,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/sweetspothq/",
    "x_url": "https://twitter.com/SweetspotHQ",
    "fb_url": "https://www.facebook.com/sweetspot.so",
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    "primary_partner": {
      "name": "Harj Taggar",
      "url": "https://www.ycombinator.com/people/harj-taggar"
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    "founders": [
      {
        "user_id": 1284150,
        "full_name": "Sachin Subramanian",
        "title": "Founder",
        "founder_bio": "CEO @ Sweetspot. Go Suns ☄️",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/sachinsubramanian/",
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        "user_id": 557251,
        "full_name": "Philip Kung",
        "title": "Founder",
        "founder_bio": "CTO @ Sweetspot. Previously founded Conduit Robotics, a startup that allowed truckers to \"remote control\" their vehicles.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/philipkung",
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      },
      {
        "user_id": 1522054,
        "full_name": "Andrew Arkhipov",
        "title": "Founder",
        "founder_bio": "",
        "is_active": true,
        "linkedin_url": "",
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    "jobs": [
      {
        "id": 70492,
        "title": "Backend/Data Engineer",
        "url": "https://www.ycombinator.com/companies/sweetspot/jobs/Sm1rZhR-backend-data-engineer",
        "location": "New York, NY, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Backend",
        "salary_range": "$130K - $200K",
        "equity_range": "0.25% - 1.50%",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
        "skills": [
          "Amazon Web Services (AWS)",
          "PostgreSQL",
          "Python",
          "Redis",
          "SQL",
          "Docker",
          "Data Modeling"
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      },
      {
        "id": 70493,
        "title": "Frontend/Full-stack Engineer",
        "url": "https://www.ycombinator.com/companies/sweetspot/jobs/6yUef6i-frontend-full-stack-engineer",
        "location": "New York, NY, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Frontend",
        "salary_range": "$130K - $200K",
        "equity_range": "0.25% - 1.50%",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
        "skills": [
          "Amazon Web Services (AWS)",
          "Python",
          "React",
          "TypeScript",
          "Chatbots",
          "Design systems",
          "Next.js"
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    ],
    "news": [
      {
        "title": "AI startup Sweetspot raises $2.2 million | Semafor",
        "url": "https://www.semafor.com/article/08/07/2024/ai-startup-sweetspot-raises-22-million",
        "date": "Aug 07, 2024"
      },
      {
        "title": "An AI search engine for the U.S. government contract maze | Semafor",
        "url": "https://www.semafor.com/article/08/04/2023/an-ai-search-engine-for-the-us-government-contract-maze",
        "date": "Aug 04, 2023"
      }
    ],
    "launches": [
      {
        "id": 92424,
        "title": "📝 Sweetspot AI Form Fill",
        "tagline": "Autonomous form completion for GovCon teams",
        "body": "# **Sweetspot AI Form Fill — Autonomous form completion for GovCon teams**\n\nLeverage AI to finish RFIs, PPQs, security questionnaires, vendor packets, and teaming agreements, so your capture & proposal teams can focus on winning.\n\n![uploaded image](/media/?type=post&id=92424&key=user_uploads/1284150/387d941f-5586-48ac-93c4-72297f4ba53e)\n\n### **TL;DR**\n\nSweetspot’s AI Form Fill is the first and only autonomous form-fill agent built for government contracting teams. Think of it as Cursor for forms: it finds every field (even unlabeled ones!) across _any_ document, then fills them with your validated company data and works with you to fill in the remaining gaps.\n\n![uploaded image](/media/?type=post&id=92424&key=user_uploads/1284150/3bbc2cef-b307-4a0c-8e52-f871c64ace8a)\n\n### **The Problem**\n\nGovCon BD teams spend shocking amounts of time re-typing boilerplate data into forms that all look different but ask for the same information:\n\n* 15-page RFIs that hide critical fields in footers\n* PPQs and security questionnaires where one missed checkbox triggers re-work\n* Vendor onboarding packets and teaming agreements that clog pipelines just when deadlines tighten\n\nManual entry steals hours from color reviews, strategy sessions, and pricing. Worse, each agency’s format changes just enough that no template sticks, and existing PDF tools don’t understand compliance nuance.\n\n![uploaded image](/media/?type=post&id=92424&key=user_uploads/1284150/d0b6afd9-19d3-46cc-92b6-aac5b9cc04ed)\n\n### **Our solution**\n\n**Sweetspot Form Fill** replaces the copy-paste slog with an AI copilot purpose-built for the public sector:\n\n1. **Autonomous field detection**\\\n   Our Form Fill agents scan the entire form, including headers, tables, annexes, and odd footnotes, to surface every required field, labeled or not.\n2. **Live, accurate population**\\\n   We pull from your company data library and reflect all changes in realtime in the browser. No context switching or separate PDF tools needed.\n3. **Ask-once memory**\\\n   If a field is unclear, Form Fill prompts you, stores the answer, and re-uses it automatically on future submissions. This means zero hallucinations and a full audit trail.\n4. **Built-in signatures & edits**\\\n   Add e-signatures, tweak language, and manually add or adjust any field you need. One tab from first click to final PDF.\n5. **Rapid-fire templates**\\\n   For truly repeatable workflows such as recurring state and local government bids, save a template and cut completion time to seconds.\n\n![uploaded image](/media/?type=post&id=92424&key=user_uploads/1284150/f84d23f3-5679-4ee6-9f78-72d8a78e06bf)\n\n### **How It Works Under the Hood**\n\n* **Semantic parsing engine** reads form structure, not just keywords, so Section M or SF33 blocks are never missed. It even works on poorly structured PDFs that don’t use annotations or native fields.\n* **Domain-trained models** tuned on hundreds of thousands of GovCon documents ensure terminology accuracy (CAGE codes, NAICS, JCP, export controls, etc.).\n* **DoD-Compliant architecture** means all of your data, answers, and content are stored securely.\n\n### **Traction & Early Results**\n\n* **12–18 hours saved per team per week** during beta across mid-market federal and SLED contractors.\n* **3× faster package turnaround**, giving users extra days for color reviews, price sharpening, and all the other important tasks that go into winning their next contract.\n* **Zero compliance rejections** to date; all of our users have been extremely happy with the results and have adopted Sweetspot Form Fill directly into their every day business processes.\n\n### **Try it out**\n\nSweetspot already powers proposal teams at Oshkosh, Vannevar Labs, Strider, and other public-sector innovators.\n\nReady to watch forms complete themselves?\n\n* **Book a demo:** [calendly.com/sachin-sweetspot/30min](http://calendly.com/sachin-sweetspot/30min%EF%BF%BC%EF%BF%BC)",
        "url": "https://www.ycombinator.com/launches/O2i-sweetspot-ai-form-fill",
        "votes": 26,
        "created_at": "2025-07-24T18:57:40.068Z"
      },
      {
        "id": 82512,
        "title": "Sweetspot - Introducing State, Local, and Education contracts",
        "tagline": "Leverage AI to win state, local, and education contracts",
        "body": "### \n\n![uploaded image](/media/?type=post&id=82512&key=user_uploads/1284150/4183ece5-910d-4a17-a284-f916476a30e1)\n\n### **TL;DR**\n\n[Sweetspot](https://www.sweetspot.so/) has added **200,000+** state, local, and education (SLED) contracts that span **17,000+ agencies** across **47 states**.\n\n### **The Problem**\n\nCurrently, SLED contract opportunities are spread out across thousands of different city, state, municipality, and county websites. Although some tools have made progress in aggregating this data, the bid-matching process remains suboptimal. These tools often rely solely on the brief descriptions provided, rather than analyzing the actual files and documents uploaded by the government.\n\nThe problem is that these descriptions are frequently missing important details or are too vague about the contract's specific requirements. As a result, small businesses are forced to manually review each opportunity's documentation to determine if it's a good fit for them. After conducting hundreds of market research calls, we reached the conclusion that this process is too time-consuming and inefficient.\n\nHere’s an example of a contract from Maryland asking for a Java Engineer with little to no information in the description. Since it doesn’t even mention the word software once, it is nearly impossible to discover this opportunity easily:\n\n![uploaded image](/media/?type=post&id=82512&key=user_uploads/1284150/53e49f39-3da3-4c53-b01f-a79a2ee451b4)\n\n### **Our Solution**\n\n[Sweetspot](https://www.sweetspot.so/) has leveraged AI to track and aggregate opportunity data across hundreds of disparate SLED data sources, with our coverage growing daily.\n\nOur AI doesn’t simply match keywords. It performs deep semantic analysis on over 20 billion tokens from every opportunity’s associated files and documents.\n\nUsing this information, it then generates a detail-rich description based on these files, and highlights exactly where its relevant to your search query along with providing you the file matches.\n\nFor example, here’s the same Maryland contract that was previously shown. You can clearly see how our AI was able to enrich this search result and present it as a viable opportunity to go after:\n\n![uploaded image](/media/?type=post&id=82512&key=user_uploads/1284150/7d6ed5ca-1504-4b1c-8fab-688876a284e4)\n\nOnce you’ve found a SLED contract you’d like to pursue, you can then use existing Sweetspot tools to analyze the RFx, estimate your probability of winning, assign tasks to teammates, and draft a proposal response.\n\n### **Try Out Sweetspot**\n\nSweetspot is already used by public sector teams at startups like Flexport, Groq, Vannevar Labs, and Strider.\n\n* Sign up for a free account at: [console.sweetspotgov.com](http://console.sweetspotgov.com/)\n* Book a demo at: [https://calendly.com/sachin-sweetspot/30min](https://calendly.com/sachin-sweetspot/30min?month=2024-04)",
        "url": "https://www.ycombinator.com/launches/LSq-sweetspot-introducing-state-local-and-education-contracts",
        "votes": 18,
        "created_at": "2024-07-29T03:51:05.554Z"
      },
      {
        "id": 79974,
        "title": "Sweetspot - AI for government contracting",
        "tagline": "All-in-one government sales platform, powered by AI.",
        "body": "### **TL;DR**\n\n[Sweetspot](https://www.sweetspot.so/) is an end-to-end AI-powered solution that helps users find, manage, and respond to government opportunities.\n\n### **The Problem**\n\nNavigating the complex landscape of government contracting by relying on existing tools is difficult. Both public and private sector solutions have disorganized user interfaces and lag in adopting technological advancements, contributing to numerous inefficiencies.\n\nBeyond user experience issues, there's a significant gap in the holistic support these tools provide. Many focus exclusively on specific parts of the contracting journey — such as search functionalities, proposal writing, or business intelligence — without addressing the need for a comprehensive solution. This siloed approach forces businesses to stitch together a patchwork of tools to navigate the federal contracting space, inadvertently increasing complexity and costs.\n\n### **Our Solution**\n\nSweetspot is an all-in-one platform that streamlines the entire government contracting process. Our solution brings together discovery, management, compliance, and proposal drafting — eliminating the need for multiple disjointed government contracting softwares. To achieve this, we’ve released four new products.\n\n#### **1\\. AI-Powered Search Engine**\n\nSweetspot leverages AI-powered search to ensure that users can discover opportunities that align with their capabilities and interests, even if the exact keywords do not match. This approach significantly reduces the time and effort required to find suitable government opportunities.\n\n_Here’s an example of our search engine easily surfacing construction projects that are on the East Coast:_\n\n![uploaded image](/media/?type=post&id=79974&key=user_uploads/1284150/ca6a4bac-ff02-42e5-b7a0-7fff5628a738)\n\n#### **2\\. Opportunity Chat**\n\nOpportunity Chat uses AI to interpret and answer questions directly from the content of solicitation documents. This allows users to gain insights into critical aspects of solicitations, such as evaluation criteria, pricing tables, and wage rates — facilitating faster and more informed bid/no-bid decisions.\n\n_Here’s an example of Sweetspot AI quickly summarizing a pricing table:_\n\n![uploaded image](/media/?type=post&id=79974&key=user_uploads/1284150/d394399e-d383-4f64-8583-43efa49117bb)\n\n#### **3\\. Pursuit Management**\n\nPursuit Management facilitates seamless collaboration within teams working on contract proposals. The tool allows users to create and assign tasks, comment on progress, and ensures that no internal and external deadlines unexpectedly creep up.\n\n![uploaded image](/media/?type=post&id=79974&key=user_uploads/1284150/04dc76f1-6f7c-498c-a1f2-b5bc80af158a)\n\n#### **4\\. Proposal Copilot**\n\nSweetspot's Proposal Copilot leverages AI to generate compliance matrices and draft competitive proposal responses by indexing user-uploaded information. This tool helps users stay compliant with requirements and reduces the time and effort traditionally required in proposal writing.\n\n![uploaded image](/media/?type=post&id=79974&key=user_uploads/1284150/f19df88f-e13d-4b08-a029-fddfff341a53)\n\n### **Our Team**\n\nSweetspot is built by a team of highly technical cofounders who have worked at companies such as Coinbase, Amazon, Meta, Nuro, Akuna Capital, and Chicago Trading Company. In a space like government contracting that has stuck with the status quo for decades, we bring the tech-forwardness that’s needed to successfully upend the industry.\n\n![uploaded image](/media/?type=post&id=79974&key=user_uploads/1284150/0da6cee3-680c-4c9a-b058-dd3393fcec31)\n\n### **Try Out Sweetspot**\n\n* Sign up for a free account at: [console.sweetspotgov.com](http://console.sweetspotgov.com)\n* Book a demo at: [https://calendly.com/sachin-sweetspot/30min](https://calendly.com/sachin-sweetspot/30min?month=2024-04)",
        "url": "https://www.ycombinator.com/launches/Knu-sweetspot-ai-for-government-contracting",
        "votes": 18,
        "created_at": "2024-04-06T04:49:38.202Z"
      },
      {
        "id": 73068,
        "title": "Sweetspot | AI-powered search engine for government contracts 🔍",
        "tagline": "Sweetspot connects your business to all available and relevant government contracts in just seconds.",
        "body": "### **📚 TL;DR**\n\n[**Sweetspot**](https://www.sweetspot.so) is an AI-powered search engine for businesses that bid on government contracts. Businesses can leverage Sweetspot to find relevant contracts in just seconds, instead of spending hours digging through [SAM.gov](http://SAM.gov).\n\n### **👬 The Team**\n\nHey everyone! We’re Sachin and Philip, the team building Sweetspot. Philip and I have known each other since freshman year of college. Since then, we’ve competed in a number of hackathons and even worked together at [Coinbase](https://www.coinbase.com/) prior to embarking on our startup journey! We came to work on this idea after we talked to our friend working at a real estate firm. His job was to find relevant federal real-estate contracts all day and he hated it due to the poor searching experience. Then, a lightbulb went off in our heads.\n\n![uploaded image](/media/?type=post&id=73068&key=user_uploads/1284150/5821fa8f-b9d4-4029-a4a4-937c2f8538ad)\n\n### **😵‍💫 The Problem**\n\nFinding government contracts on [SAM.gov](http://SAM.gov) is a nightmare, especially for small businesses. The current system is cluttered, hard to navigate, and relies heavily on keyword search, which often leads to irrelevant results - discouraging small businesses looking for contract opportunities. The clunky UI adds another layer of complexity, creating an overall frustrating experience.\n\nImagine you’re part of a landscaping company just getting into contract bidding. Just look at how poor a simple search for “lawn care” contracts on [SAM.gov](http://SAM.gov) is:\n\n![uploaded image](/media/?type=post&id=73068&key=user_uploads/1284150/bc3d52dd-a4d7-49a5-844b-f7fece3de702)\n\n### **💡 The Solution**\n\nSweetspot utilizes a combination of semantic and lexical search to streamline the process of searching for government contracts. Businesses can now find various relevant opportunities with just **one query**, eliminating the need for multiple keyword searches to do hours-long research.\n\nImagine you’re part of an upstart landscaping company (again). Look how many more relevant contracts you find in under a second for querying “lawn care”using Sweetspot:\n\n![uploaded image](/media/?type=post&id=73068&key=user_uploads/1284150/6aba66a2-7216-490f-ae57-70097b14ec01)\n\n### **🔮 The Future**\n\n* Automating queries so you get alerts every time a new contract drops\n* Expanding our dataset to include state and local contracts\n* Adding filters for more granular results\n* Adding lists to better manage your contracts you want to bid on\n* Business Intelligence and Analytics for contracts\n* AI proposal writing to help you draft responses to RFPs\n\n![uploaded image](/media/?type=post&id=73068&key=user_uploads/1284150/6114ea0d-5c67-4678-b531-c951ad7cb34b)\n\n![uploaded image](/media/?type=post&id=73068&key=user_uploads/1284150/c975695a-382d-4890-828c-6fb3415694f4)\n\n### **🙏 Our Asks**\n\n* Drop us a follow on [**LinkedIn**](https://www.linkedin.com/company/sweetspothq/) & [**Twitter**](https://twitter.com/SweetspotHQ)\n* Introductions to anybody with experience bidding on government contracts.\n* If you’re in the government contracting space or know any friends who may be interested, check out our [**website**](https://www.sweetspot.so/) and book a demo [**here.**](https://calendly.com/sachin-sweetspot/30min)",
        "url": "https://www.ycombinator.com/launches/J0W-sweetspot-ai-powered-search-engine-for-government-contracts",
        "votes": 45,
        "created_at": "2023-07-14T05:14:49.996Z"
      }
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    "name": "Zelos Cloud",
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    "website": "https://zeloscloud.io",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Zelos Cloud is the data platform for mission-critical systems that enables teams to observe, control, and test systems from prototype to production. The platform connects across entire ecosystems, capturing data from many protocols, enabling remote command execution, and facilitating team collaboration through shared workspaces and real-time annotations. By integrating data collection, processing, and visualization into one seamless pipeline, Zelos Cloud eliminates complexity and breaks down silos between engineering, operations, and quality teams.",
    "one_liner": "The Data Platform for Mission‑Critical Systems",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1688766669,
    "tags": [
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      "Manufacturing",
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    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/zelos-cloud.json",
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    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/zeloscloud/",
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      "url": "https://www.ycombinator.com/people/jared-friedman"
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        "user_id": 1264582,
        "full_name": "Michael Jaradah",
        "title": "Founder",
        "founder_bio": "Co-Founder @ Zelos Cloud. Former Tesla Energy Firmware lead. Experienced across domains like embedded, networking, safety systems and validation infrastructure.\n\n",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/michaeljaradah/",
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        "title": "Founder",
        "founder_bio": "Co-Founder @ Zelos Cloud. Former Tesla Energy Firmware/Software lead. Specialized in system programming for embedded Linux and RTOS.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/taylor-keairns-872063125/",
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    "id": 28814,
    "name": "OpenTools",
    "slug": "opentools",
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      "Humanlike"
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    "website": "https://opentools.com",
    "all_locations": "San Francisco, CA, USA",
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    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1688659817,
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      "Marketplace",
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    "status": "Active",
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    "regions": [
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      "America / Canada",
      "Remote",
      "Partly Remote"
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    "stage": "Early",
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        "full_name": "Andy Qin",
        "title": "Founder",
        "founder_bio": "Andy was the 7th employee at Modern Treasury (YC S18), where he helped build and scale the Ledgers product to a 7-figure ARR line of business. Before that, he was an engineer at Stripe (YC S09) where he worked on the API developer experience and Stripe Atlas.",
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        "linkedin_url": "https://linkedin.com/in/andylouisqin",
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        "title": "A Deep Dive Into MCP and the Future of AI Tooling | Andreessen Horowitz",
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    "name": "Talc",
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    "all_locations": "Seattle, WA, USA",
    "long_description": "Talc helps hospitals pull events and data out of messy EHRs.",
    "one_liner": "Event extraction for Medical Researchers",
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    "industry": "B2B",
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        "id": 73260,
        "title": "Talc: Debugger for your LLMs",
        "tagline": "Replay sessions, tweak inputs, and take the guesswork out of AI debugging.",
        "body": "TL;DR:\n\n_We make it easy to debug and test LLM systems. Understand your AI by replaying sessions line by line and setting rules for it to follow moving forward._\n\nHey Everyone! We’re Matt & Max, the team behind [Talc.AI](https://talc.ai?utm_source=yc&utm_medium=referral&utm_campaign=launch-yc)\n\n![uploaded image](/media/?type=post&id=73260&key=user_uploads/1274021/e0fc1906-3bf6-4a91-9c68-c91f1a5b5b46)\n\n**Matt**: I’ve spent the last 6 years engineering at Facebook and Airbnb. At FB I worked on Election Integrity, developing new ways to detect foreign interference campaigns. Hit me up if you want to hear some war stories!\n\n**Max**: I found my passion for tech early, teaching myself to code when I was 13. This journey most recently brought me to being the technical lead for a 30 person org at Facebook that reviewed every major product launch. I love the challenge of trying to understand complex systems and want to help people do the same with Talc.\n\nWe’ve been friends for almost a decade and couldn’t be more excited to be doing this together.\n\n### The Problem\n\nDeveloping real LLM systems is still hard. Prompt engineering is full of trial and error, and debugging your chain and regression testing is a painful manual process.\n\n### The Solution\n\nReplay any session your AI has had and tweak it until it's perfect. No more copy and pasting into a playground – re-run your sessions exactly as they happened and deeply understand their possible outputs. Have a bug on message 20? Hop into that context immediately and start fixing it.\n\n![](https://lh6.googleusercontent.com/A8PxlLmIyUlxmpADBV6WOisxmZAZFraHnniUGf52CmR3IEPKY-mNdz_q3gTNMuD_EsJWu9Rhn25kfDR4Li5z_7mipCkugQOFCWjC_c9rG8q_jkEd0PGw19cf1kt1OyFLZeMAegwK0aNNo-qK2XzEVRI)\n\n> _Left: Walk through your AI message logs_\n\n> > _Right: Edit the inputs and prompts that went into each message, all auto-populated for you_\n\n![](https://lh4.googleusercontent.com/sv7qlXTg598CcU5TY_v3uN2tNqiQgEW9PwW6n5YrQgozYubSYIiEdlbhXZGKfdAxI4aL8AZ48KhMDxbT8xWyNNDeQcxZKHFlAQkq95-Wa93jVlmoTrr5Wmh0x1awwrl0elHkZa8CcPXvJpvaGhysw6k)\n\n_Test changes against your saved use cases for regression testing_\n\n**What we’re asking**\n\n* Is LLM debugging & testing holding you back? **Reach out to us** at [talc.ai](https://talc.ai?utm_source=yc&utm_medium=referral&utm_campaign=launch-yc) or [book time directly on our calendars](https://calendly.com/_mattlee/intro-to-talc-ai)!\n* Do you know anyone working on LLMs in production? We’d love to learn from them! [Help us get connected](mailto:founders@talc.ai?subject=Introducing%20you%20to%20the%20Talc%20AI%20team).\n* Share us with anyone who spends a lot of time debugging LLMs\n  * _Blurb_: [Talc.ai](https://talc.ai?utm_source=yc&utm_medium=referral&utm_campaign=launch-yc) launched an LLM debugger so you don’t have to copy context into openai playground or jupyter notebooks any more. Reach out via [founders@talc.ai](mailto:founders@talc.ai).",
        "url": "https://www.ycombinator.com/launches/J3c-talc-debugger-for-your-llms",
        "votes": 28,
        "created_at": "2023-07-20T16:36:00.133Z"
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    "name": "DataShare",
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    "website": "http://datashare.co/",
    "all_locations": "Austin, TX, USA; Remote",
    "long_description": "DataShare is a data-as-a-service platform that lets you embed charts, dashboards and exports directly into your product. For example, if you run an accounting startup, DataShare would enable you to embed a full profit and loss dashboard, with downloadable statements. DataShare is backed by an enterprise-grade data warehouse, and can be implemented in fewer than 20 lines of code. \r\n",
    "one_liner": "Embed charts, dashboards and exports in your app",
    "team_size": 1,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/datashare.json",
    "year_founded": 2023,
    "city": "Austin",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/withdatashare/about/",
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      "name": "Harj Taggar",
      "url": "https://www.ycombinator.com/people/harj-taggar"
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    "founders": [
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        "user_id": 8960,
        "full_name": "Brian Brunner",
        "title": "Founder",
        "founder_bio": "Founder of DataShare, previously was the engineering manager for the team at Stripe that built Sigma and Data Pipeline.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/bbrunner",
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        "id": 74483,
        "title": "DataShare: Embed customer-facing charts, dashboards and exports directly in your product",
        "tagline": "Backed by an enterprise data warehouse and just 20 lines of code to integrate.",
        "body": "Hey there! I’m Brian from [DataShare](https://datashare.co/).\n\nDataShare is a data-as-a-service platform that lets you embed charts, dashboards and exports directly into your product. For example, if you run an accounting startup, DataShare would enable you to embed a full profit and loss dashboard, with downloadable statements. It’s backed by an enterprise-grade data warehouse and can be implemented in fewer than 20 lines of code.\n\n[Book some time](https://calendly.com/bb-datashare/datashare-intro-call) if you want to learn more. We can walk through all DataShare has to offer and give you an idea of what an integration would look like for your tech stack.\n[](https://www.youtube.com/watch?v=LNZGCl7lQMU)\n# Background\n\nOver the past few years, SaaS and financial services companies have been pushed by their customers to provide better business intelligence tooling. These systems are complex to design, hard to build, expensive to run, and challenging to scale. I've seen numerous examples of companies doing things like operating a database per customer or running 10+ hour-long pre-computation jobs just to deliver customer-facing data products.\n\nHowever, during my time at Stripe, I saw a different model. I ran the engineering team that built [Data Pipeline](https://stripe.com/data-pipeline) and [Sigma](https://stripe.com/sigma), and due to Stripe's infrastructure, we were able to rapidly deliver new products that helped to retain some of Stripe’s largest customers.\n\nDataShare is packaging up what I learned, and delivering that knowledge to the rest of the market.\n\n# The Product\n\nDataShare is a platform that combines a scalable, enterprise-grade data warehouse with a front-end framework for integrating business intelligence tools directly into your product.\n\nCharts and dashboards can be built with a point-and-click UI and can be integrated with just two lines of code.\n\n![uploaded image](/media/?type=post&id=74483&key=user_uploads/8960/57e3c582-7c6a-4595-9e20-efb8550438c5)\n\nYou can also skip the UI if you want. Visualizations can be built using DataShare’s AI-powered assistant.\n\n![uploaded image](/media/?type=post&id=74483&key=user_uploads/8960/3520b630-6afd-4725-9e9f-9bad448c8ee4)\n\nDataShare supports more than 20 types of data sources, including PostgreSQL, MySQL, and MongoDB, and is backed by a full data warehouse.\n\n# About DataShare\n\n[Brian](https://www.linkedin.com/company/withdatashare/) - I spent the past 4 years at Stripe and the past year and a half as the eng manager for [Data Pipeline](https://stripe.com/data-pipeline) and [Sigma](https://stripe.com/sigma). My team and I supported some of Stripe’s largest customers like DoorDash, Slack, Zoom, and Lime, helping keep them happy and run crucial financial workflows.\n\n# Ask\n\nIf you are thinking about building our customer-facing business intelligence tools, or you have a customer-facing BI stack you don’t like, reach out at [hello@datashare.co](mailto:hello@datashare.co) or grab [time to chat](https://calendly.com/bb-datashare/datashare-intro-call).\n\nThanks!\n\nBrian from DataShare",
        "url": "https://www.ycombinator.com/launches/JNL-datashare-embed-customer-facing-charts-dashboards-and-exports-directly-in-your-product",
        "votes": 35,
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    "name": "Spine AI",
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    "website": "https://www.getspine.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Spine AI is a visual workspace where a single prompt spins up a swarm of AI agents that plan, delegate, and execute complex tasks together — with humans fully in the loop.\r\n\r\nInstead of chatting back and forth with one model, Spine breaks work into visible steps on a shared canvas. Agents collaborate in parallel, ask clarifying questions, use connected tools, and show their reasoning and intermediate outputs as they work.\r\n\r\nEvery agent’s work stays inspectable, auditable, and editable — reducing hallucinations and giving you real control over the outcome.\r\n\r\nSpine connects to leading AI models and your existing tools, but the real power comes from orchestration: you act as the team lead, Spine runs the swarm.\r\n\r\nChat is great for answers. Spine is built for execution.",
    "one_liner": "Manage a swarm of AI agents to get real work done",
    "team_size": 7,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1687896796,
    "tags": [
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    "stage": "Early",
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/spine-ai",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/spine-ai.json",
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    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/spine-ai",
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      "name": "Harj Taggar",
      "url": "https://www.ycombinator.com/people/harj-taggar"
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        "user_id": 1222057,
        "full_name": "Akshay Budhkar",
        "title": "Founder",
        "founder_bio": "Founder and CEO at Spine AI. Previously @ Georgian Partners (Helped 40+ B2B SaaS, led Gen AI & 5 Applied research initiatives, released a few open-source toolkits to help companies at scale), Scribd (YC S06) and FarmLogs (YC W12). Did Gen AI in my Masters @ UofT before it was cool :)",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/akshay-budhkar-06259041",
        "x_url": "https://twitter.com/BudhkarAkshay",
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      {
        "user_id": 1362282,
        "full_name": "Ashwin Venkatesh Raman",
        "title": "Founder",
        "founder_bio": "Founder and CTO at Spine AI. Previously at Instacart, AWS, Alexa, Nvidia and UWaterloo.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/avraman",
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      {
        "id": 108332,
        "title": "Medley: Give Claude Code missions, not just tasks",
        "tagline": "Medley is a free Claude Code plugin for work bigger than one session. Type /mission to turn an outcome into a live dependency graph, coordinate Claude Code and Codex workers, review the assembled result, and keep going.",
        "body": "Hey YC! 👋 We're Akshay and Ashwin, and we're building Medley.\n\nYou type **_/mission_** and give it the outcome, the budget, and the constraints. Medley builds a live dependency graph, coordinates Claude Code and Codex workers, reviews what comes back, and keeps going when execution reveals more work. It's free and runs on the subscriptions and API access you already have.\n\n<https://youtu.be/xe7bj3b5Aw0>\n\n## **❌ The Problem**\n\nCoding agents got good at bounded tasks. Once a job outgrows one session, you become the harness. You break the work into prompts, move context between agents, review outputs, and decide what happens next. There's no shared definition of done, so \"finished\" just means \"looks finished.\"\n\n## **🛠 Our Solution**\n\n/mission takes on that orchestration. Three things sit between your outcome and the models:\n\n* **A contract.** Before any work starts, Medley sets the objective, the acceptance criteria, the constraints and budget, and the conditions that should make it hold or stop. That's what \"done\" gets measured against later.\n* **A live graph.** Medley doesn't write one giant plan upfront or spawn a swarm by default. It plans the next useful set of steps, runs them, reviews what came back, and updates what should happen next. Each node carries a brief, its dependencies, and a verification target. Sometimes one worker should carry a tightly coupled job end to end; when work is genuinely independent, Medley runs it in parallel. Work is routed across Claude Code and Codex workers - and with your own OpenRouter key, Codex workers can run models like Kimi and GLM.\n* **An acceptance stage.** When a batch lands, a separate reviewer role inspects the outputs and changed files, runs the contract's verify commands, and decides whether the evidence satisfies the contract - not whether the work merely looks finished. If it doesn't, the mission replans.\n\nYou can watch and steer the mission in your browser. Anything that needs your judgment or approval - publishing, sending outbound, spending, contacting people - lands in the attention queue. Everything else keeps moving. \n\n## **📊 Why This Works**\n\nThe model is only the local capability. The harness decides where to apply it - the contract fixes the target, the graph splits the work, routing matches each task to a worker, and an independent acceptance stage runs the real verify commands and replans when the contract isn't met.\n\nBefore launch, we pressure-tested a benchmark-specialized version of the same architecture on four complete public benchmarks: 93.25% on Terminal-Bench 2.1, 71.37 on HealthBench Professional, 93.24% on ViBench, and 60.98% on DrugDiscoveryBench. Those are the highest reported results on each, and they span coding, healthcare, and drug discovery.\n\nNo new foundation model. The gains came from how the work was decomposed, routed, carried across contexts, and reviewed.\n\n![uploaded image](/media/?type=post&id=108332&key=user_uploads/1362282/3af52f57-057a-475d-8bc4-ec0b1531a504)\n\nFull methodology and results are[ on our blog](https://www.medley.sh/blog/the-harness-is-the-capability-multiplier).\n\n## **🙏 Our Ask**\n\n**Try it.** Medley is free on Mac. Install it from Claude Code:\n\n```\n/plugin marketplace add Spine-AI/medley\n/plugin install medley\n/reload-plugins\n```\n\nThen run /mission.[ ](http://medley.sh/)[medley.sh](http://medley.sh)\n\n**Tell us what you think.** We're shaping the product around how people actually use it. Email [support@getspine.ai](mailto:support@getspine.ai) with what you tried, where it worked, and where it broke - and where you'd want Medley to keep going versus stop and ask.",
        "url": "https://www.ycombinator.com/launches/SBI-medley-give-claude-code-missions-not-just-tasks",
        "votes": 8,
        "created_at": "2026-07-29T17:35:57.374Z"
      },
      {
        "id": 98705,
        "title": "Spine Swarm: Your AI Team for Everything Beyond Code",
        "tagline": "Spine gives you a team of AI agents that work together on a visual canvas to complete complex projects: research, analysis, financial models, prototypes, decks, and more.",
        "body": "\nHey YC! 👋 We're Akshay and Ashwin, and we're building Spine Swarm.\n\n**TL;DR**\n\nYou describe a project. A team of AI agents spins up, works in parallel on a visual canvas, and delivers finished outputs: market reports, financial models, slide decks, interactive prototypes. Free to get started, no setup needed.\n\n**Ask:** Sign up and try it at[ ](https://www.getspine.ai/)[www.getspine.ai](http://www.getspine.ai). We'd love to hear what you build — drop us a note at [founders@getspine.ai](mailto:founders@getspine.ai).\n\n<https://youtu.be/vylx9rzC388>\n\n## **❌ The Problem**\n\nAI agents for coding have crossed a threshold. Tools like Cursor and Claude Code let engineers describe a project and come back to finished, working code. That experience doesn't exist yet for the rest of the work that drives a company forward.\n\nAs coding gets increasingly automated, the bottleneck is moving upstream: strategy documents, competitive analysis, financial modeling, sales collateral, market research, SEO audits, rapid prototyping. These are multi-hour, multi-step projects that require pulling information from many sources, structuring it, and producing polished output.\n\nToday's AI tools treat this kind of work as a conversation. You get a chat thread, local file management, and one model doing everything sequentially. For simple tasks that works fine. But for complex projects, the single-chat paradigm breaks down. You end up managing the AI instead of letting it manage the work.\n\nWe've been building at this intersection for 3 years. Last year we launched Spine Canvas, a visual workspace for orchestrating AI models. Swarm is the next step: the canvas now has autonomous agents that can take on entire projects from start to finish.\n\n## **🛠 Our Solution**\n\nSpine Swarm gives you a team of AI agents that work together on a visual canvas. You describe the project, and Spine spins up specialized agents in parallel, each handling a different part of the work. You can watch them execute in real time, inspect each artifact as it's created, and edit anything in place.\n\n* **Multi-agent execution:** Spine orchestrates a team of agents across your project. For a competitive analysis, one agent researches market data, another structures the findings, another builds the slide deck. They work simultaneously, not sequentially, and can run autonomously for 80+ minutes on large projects.\n* **Intelligent model selection:** We route between 300+ models, picking the best one for each step and ensembling multiple models to override any single model's biases. You don't configure any of this.\n* **Visual canvas:** Every artifact your agents produce appears on a shared canvas where you can inspect, compare, edit, and branch. No chat windows, no file systems.\n\nEverything Spine builds is downloadable and hosted at a shareable link. Just send your team the URL.\n\n## **📊 Why This Works**\n\nA common question we hear: \"You're using the same models everyone else has access to. Why would the output be better?\"\n\nWe recently scored **87.6% on Google DeepMind's DeepSearchQA**, a benchmark that measures how well AI answers complex research questions requiring multi-step reasoning across sources:\n\n![uploaded image](/media/?type=post&id=98705&key=user_uploads/1362282/fb8a5039-8780-455d-abc4-7f3da613aa7b)\n\nThree things drive this:\n\n* **Model routing and ensembling:** Spine selects the best model from 300+ options for each step and ensembles multiple models to override any single model's biases or blind spots.\n* **Orchestration:** How you decompose a complex task, coordinate agents across steps, and manage handoffs between them matters as much as the models themselves.\n* **Intelligent canvas:** Agents work on a shared canvas where they can read each other's outputs, build on previous steps, and assemble coherent deliverables. This also means every step is fully auditable, so you can trace how agents arrived at their conclusions and verify their reasoning.\n\nRead more about our approach and the full benchmark results[ on our blog](https://blog.getspine.ai/spine-swarm-hits-1-on-gaia-level-3-and-google-deepmind-deepsearchqa/).\n\n## **🚀 Tasks Worth Trying**\n\n* \"_Audit \\[your website URL\\] and produce a full SEO analysis, competitive landscape, and a prioritized growth roadmap with a slide deck._\" You'll see agents browsing your site, researching competitors, and assembling deliverables simultaneously.\n* \"_I'm preparing to fundraise. Here are my company details: \\[paste\\]. Build me a pitch deck, competitive landscape with market sizing, a financial model, and personalized outreach emails for target investors._\"\n* \"_Here's a product idea: \\[describe it\\]. Generate three different interactive prototypes and landing pages exploring different design directions, alongside a PRD and go-to-market strategy._\"\n\n## **🙏 Our Ask**\n\n* **Try it:** Sign up at[ ](https://www.getspine.ai/)[www.getspine.ai](http://www.getspine.ai) and run one of the tasks above. It's free to get started, no credit card required.\n* **Tell us what you build:** We're actively shaping the product around how people actually use it. Email us at [founders@getspine.ai](mailto:founders@getspine.ai) with what you tried and how it went.\n\n**Share this post** if you know founders, operators, or team leads drowning in the strategic and analytical work that's piling up as code writes itself.",
        "url": "https://www.ycombinator.com/launches/Pg1-spine-swarm-your-ai-team-for-everything-beyond-code",
        "votes": 24,
        "created_at": "2026-03-12T15:09:28.483Z"
      },
      {
        "id": 94642,
        "title": "Spine Canvas: Unlimited Visual Workspace for AI Thinking",
        "tagline": "Think beyond chat. Collaborate visually across 300+ AI models with branching, parallel, and contextual workflows.",
        "body": "tl;dr: Chat is great for Q&A, but real work isn’t linear.\n\n**Spine Canvas** is an unlimited, visual AI workspace that lets you orchestrate 300+ models with a single subscription, think in blocks (Chat, Deep Research, Memo, Image, Slides), branch safely, run in parallel, and keep explicit context across everything.\n\nGet started for free:[ ](https://www.getspine.ai/)https://www.getspine.ai\n\nhttps://www.youtube.com/watch?v=OBq6dDQlO5w \n\n### **❌ The Problem**\n\nMost AI tools force thinking into a chat thread. That breaks down for real work:\n\n* **Superficial and linear:** useful for one-off answers, weak for exploration and synthesis\n* **Context evaporates:** sources get buried; you can’t see what informed which step\n* **No safe branching:** testing alternatives means losing your original path (or forking tabs)\n* **No parallelism:** ideas wait in line; you can’t spin up multiple streams at once\n* **Tool sprawl:** one app for research, another for writing, another for images — context gets lost between multiple AI subscriptions\n\nIf you’re doing market/competitive research, strategy, content systems, or product planning, you need an environment that reflects how thinking actually happens: exploratory, non-linear, and iterative.\n\n---\n\n### **💡 Our Solution: Canvas, Not Chat**\n\nSpine Canvas is a visual workspace where your ideas are blocks connected by explicit context. You can see, direct, branch, and re-run your thinking — across hundreds of models — without losing your train of thought.\n\n#### What you can do today:\n\n**Orchestrate 300+ models with a single subscription**\n\nGPT‑5, Claude, Gemini, Qwen, Flux, Nano Banana, and more — pick the right model per step and switch mid‑flow without losing context.\n\n**Think in blocks, not threads**\n\nChat, Prompt, Deep Research, Memo, Image, Slides — each block has an explicit role and visual inputs/outputs, so chains stay modular and interpretable.\n\n![uploaded image](/media/?type=post&id=94642&key=user_uploads/1222057/d6578fed-e2e5-4e9d-a749-a58b8ab47ccd)\n\n**Organize and (explicitly) utilize all your content in a single workspace**\n\nPaste or drop in PDFs, YouTube links, webpages, and even past LLM chats. Wire them into any block and control exactly what each step uses.\n\n![uploaded image](/media/?type=post&id=94642&key=user_uploads/1222057/1e4420c0-d1a2-46fa-82db-cdf54eb15827)\n\n**Branch safely and compare**\n\nExplore alternatives without corrupting your original path. Keep versions side‑by‑side and merge insights when you’re ready.\n\n**Run in parallel**\n\nTake a list (competitors, themes, tasks) and spin out multiple research streams, drafts, or visuals at once.\n\n**Re‑run and evolve**\n\nUpdate one block and cascade improvements through an entire branch. Iteration becomes automatic and reproducible.\n\n![uploaded image](/media/?type=post&id=94642&key=user_uploads/1222057/47204045-5cb7-477e-afc9-55a447f0e165)\n\nOur public roadmap:[ app.getspine.ai/roadmap](https://app.getspine.ai/roadmap)\n\n### **💼 Real Canvases Teams Are Building**\n\n* Market deep‑dives that flow into competitor profiles, battlecards, and executive memos — in minutes, not days\n* Content engines that turn one source into outlines, drafts, and platform‑ready assets (with visuals)\n* Founder/product strategy rooms mapping interviews (YouTube + PDFs) → insights → counterpoints → product bets → launch plans\n* Creative labs exploring concepts, visual directions, and brand systems\n* Learning hubs with curated sources, summaries, and living notes\n\nExplore our gallery:[ https://app.getspine.ai/gallery](https://app.getspine.ai/gallery)\n\n### **⚙️ Why This Matters**\n\n* **Transparency:** See what each block knows — no black-box memory.\n* **Control:** Direct sources by domain, date, or type; include your own docs and past chats.\n* **Speed:** Complex, multi-step work finishes in minutes and stays repeatable.\n* **Flexibility:** Model-agnostic orchestration keeps your workflow stable as models evolve.\n* **Complete**: Do everything from research to generating presentation slides, images, copy drafts, all without switching tools.\n\nChat works for Q&A. **Canvas is for thinking.**\n\n### **🤝 Ask**\n\n* Try using a canvas for thinking instead of linear chat threads – build one real workflow (research → memo, content engine, or strategy room) and tell us what clicked.\n* Share with teams who live in research, strategy, content, product or learnOps – we’re eager to add more templates based on your feedback.\n* YC community: we’re always happy to chat about getting the best thinking out of your AI models — visually for individual workflows, and structurally through company-wide templates.\n\n**Get started for free:**[ ](https://www.getspine.ai)[getspine.ai](http://getspine.ai)\n\n**Join the community:**[ discord.gg/KuHzF6zBPs](https://discord.gg/KuHzF6zBPs)\n\n**Book a chat:**[ calendly.com/intro-getspine/intro](https://calendly.com/intro-getspine/intro)\n\n\\\nThe future of human–AI collaboration is visual, adaptive, and unlimited.",
        "url": "https://www.ycombinator.com/launches/OcU-spine-canvas-unlimited-visual-workspace-for-ai-thinking",
        "votes": 29,
        "created_at": "2025-10-14T19:07:02.223Z"
      },
      {
        "id": 90394,
        "title": "Spine Research: Deep research done better",
        "tagline": "Iterative deep research reports you can actually use.",
        "body": "**tl;dr** Spine Research searches through **_over 3x more sources 5x faster than ChatGPT Deep Research while keeping you in control_**. With a built-in full-text editor, you can iteratively guide the research, dive deeper into topics, and build and share reports that are actually useful.\n\nhttps://www.youtube.com/watch?v=cabKW-B9Ung\n\n# ❌ **The Problem**\n\n“Deep research” with AI often isn’t comprehensive, collaborative or controlled. If you’re relying on research for critical decisions, you’ve probably run up against the limitations of current tools:\n\n* **Superficial Overviews:** Most AI tools deliver surface-level summaries. While a starting point, they rarely deliver the nuanced, comprehensive understanding needed for a true competitive edge or complex problem-solving.\n* **Static Reports, Not Evolving Understanding:** Real insight comes from asking new questions based on what you're learning, and using that to inform where you need to go next. What if the initial research misses the mark, or you want to explore a specific avenue further? You're often stuck waiting 10-15+ minutes for a complete do-over, losing valuable context and any useful initial findings. Current UX isn't built for the way human understanding evolves – through continuous _refinement_ and building upon prior knowledge.\n* **Lack of Meaningful Control:** Struggling to direct AI to your trusted websites, specific authors, or crucial internal documents? Or to exclude irrelevant noise? You end up sifting through low-quality information, wasting time and effort, because you can't effectively steer the research. It's hard to restrict research to just research papers, recent news or local government websites.\n\n For critical decision-making and professional analysis, today's AI \"deep research\" often feels frustratingly superficial, rigid, and disconnected from your own expertise.\n\n# 💡 **Our Solution**\n\nSpine AI rapidly generates comprehensive research reports by synthesizing insights from hundreds of websites, academic papers, news articles, and private documents—delivering deeper, more accurate understanding in a fraction of the time taken by ChatGPT's Deep Research. \n\nYou're in full control to iteratively define the scope, depth, and breadth of analysis to perfectly suit your needs.\n\n1. **Guide your process from the start:**\\\n   Start with your prompt and guide the research process immediately. Spine AI generates an initial outline you can quickly edit. Refine its scope, focus, or sources in minutes, ensuring precise alignment _before_ full report generation, so you don’t have to wait 15 minutes to realize you forgot to include a key detail about scope.\n\n   ![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXcL5A3u_PiTNIcT2zA_EuBzfnd1KkxzSX96-X_IXZip1X55JeOpSlewO6VSh2UnshndNmMQ0CIQLX2AJXZnl63DSKevcmLfEEZbmYFx4kNp4hSAMh6O8fSbOreW-syDJtskuGvYWg?key=Y1LxsXqmD3SyMDO0vvbfTw)\n\n2. **Control the process and build your understanding iteratively:**\n   * **Breadth of sources:** When searching the open web, Spine AI accesses over 3x more sources than ChatGPT’s deep research, giving you a more comprehensive view with detailed citations out of the box. You can also exclude irrelevant domains, keeping unreliable sources out of your reports.\n   * **Focused discovery:** Direct Spine AI to focus on particular types of sources (like news, financial reports, or research papers), specific websites, and set publication timeframes, to ensure the most relevant information.\n   * **Leverage your own sources:** Upload and research your own private documents—proprietary reports, project files, spreadsheets, slide decks—integrating your internal knowledge with external discovery.\n   * **Model Agnostic:** Maintain flexibility by choosing the LLM (including OpenAI, Claude, and Gemini models) that best suits your current needs or preferences. Your core research workflow remains stable, even as individual model capabilities evolve.\n\n   ![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXcT9SBLuKPWhEOCBukznBQTa76nsdbme7j2Tid7-TYTDxW-fxfMF37AHn7GwxQBR-b5E1rxcu9GWpjbdKWLgcoJV7q9SMyH0-ToypIKq63YfCWSBg1BTjXOle7IUb4h_GZ-DaGjJw?key=Y1LxsXqmD3SyMDO0vvbfTw)\n\n3. **Directly add your expertise:**\\\n   Spine AI isn't just about AI-generated content; it's a dynamic working document. You can type directly into your research, add your own notes, edit the generated text, and incorporate your unique context and analysis alongside the AI's findings. Close the gap between just another research doc to organize, and actually creating a usable report, or project doc.\n\n# 🤝 **The Ask**\n\n**Put us to the test.**\n\nNeed to build quick expertise on a new topic or simplify your research process?. Find out about how the [recent executive order on drug pricing could shift the market](https://research.getspine.ai/reports/62ab8a56-e0d5-4380-a991-18bf4fc2ffd0?utm_campaign=bookface), [what US-China trade negotiations could mean for startups and VC](https://research.getspine.ai/reports/0ee2928d-e0c9-4aea-b277-45f347d2b07d?utm_campaign=bookface), or [where Stripe is sitting in the market](https://research.getspine.ai/reports/105e8d40-36fc-4092-8555-853cf5865b40?utm_campaign=bookface). Also great for getting a handle on the latest research ([how much do we really know about ozempic?](https://research.getspine.ai/reports/ff4177f6-105f-4954-9fdd-a50261beae32?utm_campaign=bookface)), or whatever else you have questions about.\n\n**Try us out for free!**\n\nAnd with the YC promo code (YCLAUNCH), you can get $25 off our pro plans.\n\nKnow a founder, investor, analyst, or tech enthusiast who needs better research tools? Let them know about Spine AI. **Share with deep research power users**, and see if they don’t want to make the switch.",
        "url": "https://www.ycombinator.com/launches/NVy-spine-research-deep-research-done-better",
        "votes": 56,
        "created_at": "2025-05-14T16:35:06.718Z"
      },
      {
        "id": 86064,
        "title": "Spine AI – The Multi-Modal AI Analyst Platform for Reliable Insights",
        "tagline": "Simplifying data exploration at scale with AI analysts tailored to your business context",
        "body": "# Tl;dr\n\nAccessing and synthesizing data is a challenge, with existing tools requiring too much effort and expertise.\n\n**Enter Spine**: An AI-powered data platform built for decision-makers that handles your data in any format. Teach it your business context, to get reliable answers from databases, documents, and websearch. Gather your insights in customizable reports that automate multi-modal analysis and keep insights traceable.\n\nTo celebrate F24 Demo Day, **we’re offering free access** to a YC dataset in Spine, giving investors and observers a deep dive into batch F24’s companies, founders, and opportunities.\n\n![uploaded image](/media/?type=post&id=86064&key=user_uploads/1222057/425f4b5e-1eb5-48a6-bf02-25e69412564d)\n\n![uploaded image](/media/?type=post&id=86064&key=user_uploads/1222057/365e8fa7-e9c5-4489-adb3-281393120488)\n\n# The problem\n\nThere is no shortage of data and information, or reasons to access it. Improving operations, identifying the most successful initiatives, or clarifying key drivers of revenue. But accessing and synthesizing this information from various sources can be an uphill battle.\n\nMany tools available for working with data make it difficult to get to the right information without significant time and effort. Technical experts often have to unlock access for decision makers, and even then, critical details locked in documents, slide decks, or PDFs are hard to uncover and integrate effectively. \n\nWhile platforms like ChatGPT, Claude, and Gemini offer “chat with your data” functionality—such as answering questions about uploaded spreadsheets or generating text-to-SQL queries—they don’t go far enough. None of these solutions offer an end to end solution that’s suitable for scalable use.\n\n**You need to already have the right data, in a clean format, and not too much.** The big LLM providers can find some new information for you, but it can’t give you structured data at scale, and it’s not up to date.\n\n![uploaded image](/media/?type=post&id=86064&key=user_uploads/1222057/243f0c39-bd31-4246-9230-a330465ccdd1)\n\n**It’s not enough to just do text to SQL.** It can speed up querying, but there’s a lot of business context that needs to be applied to make answers accurate and useful, and Custom GPTs don’t cut it. \n\n![uploaded image](/media/?type=post&id=86064&key=user_uploads/1222057/7f42be7d-d2d5-434c-8854-37792f39dc9d)\n\n**There’s no good way to update information, add more data, or deal with multiple formats and sources at the same time.** People often don’t know the best place to find the information they are looking for, and most LLMs can’t help with that at scale.\n\n**You can’t easily collect the insights you’ve generated from LLMs, share them, or re-trace your steps if there are questions about the source.** If you want to replicate a similar process for your analysis there’s no straightforward way, especially if it involves multi-modal data.\n\nThe major BI and analytics tools solve some of these problems, but they don’t really deliver on conversational functionality, and definitely don’t support multi-modality.\n\nWhich is why we’ve built a better way.\n\n# The solution\n\nSpine is a multi-modal AI analyst platform designed for decision-makers, delivering an end to end solution which includes:\n\n**Explore and enrich data**\n\n* Either start from scratch or add on to your existing data. Combine structured data, documents, and websearch for a unified view.\n* Pull in data for competitive analysis, market research, benchmarking and more.\n\n**Domain knowledge management customized for your use case, and ongoing evaluations for reliable updates**\n\n* Our platform makes it possible to adjust, and test the integration of domain knowledge at scale, so you know updates work and are an improvement over what came before. \n* We generate 1000s of samples for each of our analysts, capturing issues so we can solve them, and know objectively that our changes improve performance.\n\n**Integrations for your existing data sources**\n\n* We work with data of all types, integrating with platforms like Google Drive, BigQuery and Snowflake, and industry specific tools like iLevel. Any tool that has an API can be set up.\n\n**Transparent answers for users**\n\n* Our AI analysts always show their work, so users can verify where answers are coming from and how they were created.\n* If the analyst finds a question it’s not confident in answering, it notifies the user and gives them the option to submit to a human to verify its work.\n\n**Customizable reporting and repeatable analysis**\n\n* Full control and flexibility in reports and dashboards. Insights can be added directly from the chat, gathering information from structured datasets and documents.\n* Create templates to automate multi-modal analysis, enabling you to apply the same framework seamlessly across multiple entities, such as different companies or similar data sets.\n\n**In honour of Demo Day**, we’ve put together a [free preview of Spine](https://yc.getspine.ai/sign-up) with a dataset for batch F24’s companies and founders (plus as a bonus, data on all YC companies). \n\nIf you’re an investor:\n\n* Don’t miss out on discovering the best of the best. You can get a comprehensive overview of who’s in this batch, what they’re doing, and which companies are most similar, and figure out which are best suited for your investment thesis.\n* Track the companies you’re interested in, and create a more focused view to compare them.\n* Upload pitch decks and documents from founders to enrich the dataset we’ve given you, and pull key insights from them, such as traction, TAM estimates and GTM strategy.\n\n![uploaded image](/media/?type=post&id=86064&key=user_uploads/1222057/517013a9-2a07-4c8b-abef-0ea809e7ad5c)\n\n![uploaded image](/media/?type=post&id=86064&key=user_uploads/1222057/47430f02-c20c-42d8-9376-8591fc3d9058)\n\n# The ask\n\n**Try this free preview of Spine for YC F24 Demo Day!**\n\n[Sign up](https://yc.getspine.ai/sign-up) and learn about the companies launching with this batch (or explore all companies in the YC directory!)\n\n**Reach out if you’re interested in the full version of Spine**\n\nWe’ve worked with a number of investors in the VC space, but we’ve also created AI analysts for market research, sales data, and user facing experiences for B2B SaaS products.\n\nIf you think you could be doing more with your data, [reach out.](https://www.getspine.ai/talk-to-us)\n\n**Spread the word**\n\nIf you like what you see, share it with someone you think would find it useful. \\\nShare this post, and follow us on [LinkedIn](https://www.linkedin.com/company/95072305/admin/feed/posts/) and [Twitter](https://twitter.com/Spine_AI).",
        "url": "https://www.ycombinator.com/launches/MO8-spine-ai-the-multi-modal-ai-analyst-platform-for-reliable-insights",
        "votes": 32,
        "created_at": "2024-12-05T15:20:32.109Z"
      },
      {
        "id": 82328,
        "title": "Spine AI - Reliable AI data analysts that know your business",
        "tagline": "Custom AI analysts, trained on your business context, so you can ask truly plain language data questions and make informed decisions frictionlessly",
        "body": "## tl;dr\n\nSpine creates reliable AI analysts that make it easy to get the right data to drive decisions. We capture and embed your business context, to enable real plain language data questions. Instead of spending time struggling with inflexible dashboards, or translating questions to queries, just ask questions and get answers. Empower internal decision makers, or your customers, with interface options that integrate with existing workflows.\n\n![](https://lh7-us.googleusercontent.com/docsz/AD_4nXdtqKjuSuQpHE3TjAm_itXPgRLQtQgySxCTM0ReLQsAw3Gp_7wvbUIcGzUlUdy_WnNHsxizF0yn7oyA3Eb6ompQWp1RItXp80w1zaZWFZoAZgUQ4-Yk36b65S3_8LSTE5QTYAdgjqKrhkkzSBg6ZF45FUg?key=nI0vqYTeqq8Yopi3is-LAg)\n\n# The problem\n\nFrom having built over 200 copilots for companies and having processed more than 100k user queries here are some of our key learnings:\n\n* Analytics and business intelligence are critical to running any organization. They allow leaders to understand what’s working, what’s not, and where they can find new opportunities.\n* Most existing BI tools are inflexible and technical. To find answers to novel questions requires knowledge of the data model, or a BI specific query language.\n* In practice, it's not always obvious what you'll need to know to respond to an evolving situation, or what new questions your data will raise. Static reports and dashboards create dead ends. You can get stuck waiting for someone from the data team to be available, or having to act on best guesses.\n* And it's not just internal decision makers who face these challenges. Your customers can only interact with their application data through:\n  * static dashboards that require engineering teams to build,\n  * custom reports your support teams and analysts put together, and/or\n  * data exports that require expertise to dissect\n* While the extraction of information from unstructured sources has evolved, handling structured data remains a challenge:\n  * Beyond accurately deciphering user intent, structured data often comes with messy table schemas and unwritten business context, for which there are no established methods of embedding in the models.\n  * Simply having models generate complex SQL and/or code to process the data makes the execution less transparent, flexible and reliable.\n  * Isolating data across multiple tenants and user access controls remains a barrier in making this a customer facing feature.\n\n## The solution\n\nWe build custom AI analysts that allow any user to ask plain language questions about their data, and get reliable answers.\n\n**Plain language questions and natural exploration**\n\nWith the chat interface, users can easily explore their data, asking questions in their own words, instead of \"translating them\" to a formal query. When the results raise new questions, just ask them. No searching for the right report, or getting stuck at a deadend in your dashboard.\n\n![](https://lh7-us.googleusercontent.com/docsz/AD_4nXezHViIBc3TQimN4FoYsmGAuqFJ_lFgAQU8rTAGqPTGqoQmaN1l_FIxEwl8RvNWwRNJDQrVqL3w1ur0ziFjU069dzbYTwvorccXTDYPsPjD4CSqnRUMWnu4s89MT5Lgy-XfA3dqZJ5XunVddCXzeh97aw?key=nI0vqYTeqq8Yopi3is-LAg)\n\n**Revisit crucial insights**\n\nOnce you’ve found insights in your data, it’s easy to come back to. Get regular notifications for key questions, collect insights into shareable reports, or add them to flexible dashboards.\n\n![](https://lh7-us.googleusercontent.com/docsz/AD_4nXefxA1bWXpTkzW8hQBEekKMhZ4W3KPKIdetddq-1FWALX804CujEpigd2dQJjFVsEYVqE8MTsMRRzJ9mB6ahQkKQ7Rpxatwyp8AUgaVdLWKz0B8neUCiXXWM6uQbQWQXeFOwBBVHNETGCQGvQa5U1TJUrc?key=nI0vqYTeqq8Yopi3is-LAg)\n\n**Transparent and reliable answers**\n\nEven on a single table dataset Spine’s AI analyst performs 15x better than GPT-4o out of the box.\n\nRather than leveraging models to generate complex SQL or code (or find answers from the data directly), our solution leverages a proprietary Data Processing Unit (DPU) that comprises a collection of refined modules.\n\nThe DPU enables us to:\n\n* have individually tested and schema/domain fine-tuned modules that work at scale\n* react to the data and modify the operations we take to get the answer\n* explain the steps taken by the AI in a simple human readable manner\n\nDuring the customer onboarding process, we capture and embed the business context and the schema understanding into the DPU modules. Additionally we build and maintain data and schema-specific semantic layers, across tables, which makes it possible for us to accurately interpret and handle natural language questions across multiple tables with over millions of rows each.\n\nFinally, a combination of automated and human evaluations give us an objective way of measuring performance — both before and after we deploy the analyst.\n\n**Diverse use cases**\n\nWe are able to support use cases across diverse industries and user bases by systematically gathering domain specific knowledge from our customers, and automatically inferring relevant data characteristics. Whether you’re in finance, retail, healthcare, telecoms, manufacturing, or any other industry, we can create an AI analyst for your business.\n\n**_Sales analyst_**\n\n![](https://lh7-us.googleusercontent.com/docsz/AD_4nXdfoY8qAC_h6o37VqJhc9laUNLLsm2WoauY11Wzkq5Xn30kUo3sOqSGh5QQh8Z0In23MiAu5rTmss7DsZEFkpNUqwbVjH8-7lkmjcQTWE03g1U_Ce7bU_J5Tnaa34Om9RUW7onhyfiMfZBYYDhIg2bv82s?key=nI0vqYTeqq8Yopi3is-LAg)\n\nUnderstand what outreach activities are getting attention, with who. Dig into team member performance, email deliverability and more, to better understand what’s effective and what’s not performing.\n\n**_eCommerce platform analyst_**\n\n![](https://lh7-us.googleusercontent.com/docsz/AD_4nXdmVxwj3U-ohPX90hds_V_0qkRzBioVUgAOa7mZn0dJb3Bds-NSWsJAI2bfrQSnwVkAlwQ9n_KxmSXWXouOgqy4Tof9-GabGM6CC36-DMWTw53EJt8TuP5AYKCIJhxhWsXsU_aO9V0ZimmY5AW4FzW6Gg?key=nI0vqYTeqq8Yopi3is-LAg)\n\nGain insights into which products are selling the most and why. Analyze customer behavior, optimize inventory management, and uncover trends in purchase patterns to maximize your sales potential.\n\n**_ERP system analyst_**\n\n![](https://lh7-us.googleusercontent.com/docsz/AD_4nXd_waVQSpbeRpOB3ZZjq_YGuu4scesyVCwj7txYLLoy6oyIzVUoSxEKyDuvkkjnXfG3JekB8U5Oq_I_wsbfAQSxLtdNw2QHrm6Yu9HQfmNQ5lMv7fLm1Sduavs0PyO3Fie2eqHih2I4amlPDb8exr_dy3I?key=nI0vqYTeqq8Yopi3is-LAg)\n\nKeep projects on track by monitoring task progress, timelines, and budget adherence. Evaluate project performance, identify risks, and ensure timely delivery of project milestones.\n\n**The power and flexibility of AI without needing a technical team**\n\nYou don’t need your own AI team. Have your custom analyst up and running in the next 30 days, and leave the upkeep to us. Monitor and tune the analyst’s behavior over time with our admin panel.\n\n# About us\n\nWe are Akshay and Ashwin – the co-founders of Spine AI 👋. We've been friends for over a decade, with our shared journey beginning at the University of Waterloo. Our interest in machine learning took root in an unlikely place – a building called _Spine_ at the Nanyang Technological University in Singapore during an exchange term.\n\nAnd in our first year we’ve grown! Across our team, we collectively collaborated with more than 45 enterprises, guiding them toward the next levels of AI maturity. We have more than 100+ citations in GenAI and patents in AI and data processing. Our team also has experience working at companies like Nvidia, Shopify, Instacart, Amazon, Epic Games as well as founding multiple YC companies.\n\n## The ask\n\n* If you need better access to insights within your organization, or want to empower your customers with their data, we'd love to [hear from you](https://www.getspine.ai/talk-to-us)!\n* First 10 companies that contact us after launch get to trial a free, fully functioning AI analyst for your data! (Just let us know you heard about us from YC)\n* Help us spread the word! Please share this post and join our journey by following us on [LinkedIn](https://www.linkedin.com/company/95072305/admin/feed/posts/) and [Twitter](https://twitter.com/Spine_AI).",
        "url": "https://www.ycombinator.com/launches/LPs-spine-ai-reliable-ai-data-analysts-that-know-your-business",
        "votes": 32,
        "created_at": "2024-07-22T20:55:24.459Z"
      },
      {
        "id": 73256,
        "title": "🚀 Spine AI – Propel your products forward with AI copilots",
        "tagline": "Spine AI’s platform helps you build a copilot for your product.",
        "body": "**_Tl;dr_**_: Spine AI simplifies the process of integrating AI copilots into your products. Now, complex tasks within products like JIRA, such as custom reporting or bulk updates, can be effortlessly managed. Simply have your users instruct our AI copilot and watch as it seamlessly executes your commands. Interested in the power of AI copilots for your products? We're just a message away!_\n\n![](https://lh3.googleusercontent.com/WbKO1Pu6llFXV2BkVDpIZq_OxQHZqlQkGdXmWfSfgo9d-OsXV5GsUxwJZCRRzuZnxKhkAAibbms9Hi-zyfyklPV7OTkwhabjFUWi7es3qMRaHL1VekA9vtQgboExpAf_oZXHyPt3RkAO7V-3_wq1ijE)\n\nHello everyone, we are Akshay and Ashwin – the co-founders of Spine AI 👋. We've been friends for over a decade, with our shared journey beginning at the University of Waterloo. Our interest in machine learning took root in an unlikely place – a building called _Spine_ at the Nanyang Technological University in Singapore during an exchange term.\n\nIn the past five years, we've collaborated with more than 45 enterprises, guiding them toward the next levels of AI maturity. This year, we've successfully integrated LLM-related technologies into over six companies, leading to a clear projected ROI. This journey has brought some key insights to light:\n\n* The gap between creating a text generation prototype with tools like OpenAI and deploying a value-adding product is significant.\n* Customer expectations are evolving, with [hybrid UI paradigms (command + intent)](https://www.nngroup.com/articles/ai-paradigm/) becoming increasingly prevalent.\n* To maximize their benefits, AI copilots must perform actions on users' behalf, saving time and creating new workflow possibilities. This is the core functionality of our Spine-powered copilots.\n\n### 💪 The Power of AI Copilots\n\n* AI copilots streamline complex UI workflows, morphing them into an intuitive, natural language-based interface.\n* Adding an AI copilot to B2B products is becoming table-stakes (as seen with [Shopify](https://twitter.com/tobi/status/1679114154756669441?s=20), [Microsoft](https://www.barrons.com/articles/microsoft-stock-ai-software-ad2baf04), [Notion](https://www.notion.so/product/ai), etc.) for companies that have the capacity to build them. At Spine AI, we're on a mission to democratize this.\n* When added to enterprise SaaS products, AI copilots have helped companies increase ARR by $1M. 💰\n* AI copilots enhance your product by adding an intelligence layer that directly connects users to backend APIs, documents, and databases, making previously challenging workflows easily implementable.\n\n![uploaded image](/media/?type=post&id=73256&key=user_uploads/1362282/06ca9a30-c100-4c04-87e3-64e7438b361d)\n\n### 💢 The Problem\n\n* Developing reliable AI copilots, which offer a wide range of functionalities, demands a significant investment of time and resources, requiring extensive AI and engineering expertise throughout the entire lifecycle.\n* Embedding diverse actions into the copilots, such as API calls, documentation updates, multi-modality, and authentication handling, can extend the development timeline beyond six months.\n* The addition of complex features, like custom reporting and integrations, can further prolong the development cycle, putting additional strain on already-packed roadmaps.\n\n### 🎯 The Solution\n\n* Enter Spine AI – the easiest way to build reliable AI copilots for your products. Our platform converts API docs, DB schemas, and multi-modal documents into fully operational AI copilots that integrate effortlessly with just a few lines of code.\n* During the setup process, each copilot is equipped with a custom orchestrator, trained to effectively transform user intents into concrete actions.\n* Maintain complete control over the product interface with the ability to customize the permitted actions, enabled workflows, and the copilot's response style to users.\n* Once integrated, the AI copilot becomes a superuser of your product – an indispensable assistant always at your users' disposal, enabling them to harness your product's full potential.\n\n![uploaded image](/media/?type=post&id=73256&key=user_uploads/1362282/43dd32fe-2473-482c-9da0-ab5577b8c551)\n\n### 🤝 Ask: How you can help\n\n* If you're a B2B company exploring ways to integrate AI copilots into your products effectively, we'd love to [hear from you](https://www.getspine.ai/)!\n* If you're unsure how Spine can streamline your complex workflows, drop us a note at [founders@getspine.ai](mailto:founders@getspine.ai)\n\nHelp us spread the word! Please share this post and join our journey by following us on [LinkedIn](https://www.linkedin.com/company/95072305/admin/feed/posts/) and [Twitter](https://twitter.com/Spine_AI).",
        "url": "https://www.ycombinator.com/launches/J3Y-spine-ai-propel-your-products-forward-with-ai-copilots",
        "votes": 63,
        "created_at": "2023-07-20T14:21:01.092Z"
      }
    ]
  },
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    "id": 28843,
    "name": "SID",
    "slug": "sid",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cac6ad037170806bce925f0d0ed9373eec18f576.png",
    "website": "https://www.sid.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "SID is an AI research center based in San Francisco. We train models that can retrieve and reason over any data source.",
    "one_liner": "AI research center for retrieval",
    "team_size": 7,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1689093789,
    "tags": [
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      "AI"
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    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2023",
    "status": "Active",
    "industries": [
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    "regions": [
      "United States of America",
      "America / Canada"
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    "stage": "Early",
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/sid",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/sid.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/sidai/",
    "x_url": "https://twitter.com/SID_AI",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/sidhq",
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    "founders": [
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        "user_id": 1134710,
        "full_name": "Maximilian-David Rumpf",
        "title": "Founder",
        "founder_bio": "Max is the CEO of SID.ai. Previously, he was a researcher at ETH Zürich, where he worked on AI accelerator design with the professor who developed Google's TPU architecture. Max was awarded a German national excellence scholarship, awarded to 0.5% of German students.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/maximiliandavid",
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      },
      {
        "user_id": 746723,
        "full_name": "Lotte Seifert",
        "title": "Founder",
        "founder_bio": "Lotte is determined to let people use their data for their own good. She holds a degree in CS from ETH Zürich and a degree in Economics from the University of St. Gallen. ",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/lotte-seifert",
        "x_url": "https://twitter.com/lotteellen",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9381e5b5b03dfe8c71b03c574051aab9ede94457.jpg"
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    ],
    "jobs": [
      {
        "id": 81528,
        "title": "Research Intern (Summer 2026)",
        "url": "https://www.ycombinator.com/companies/sid/jobs/SmhVhTs-research-intern-summer-2026",
        "location": "San Francisco, CA, US",
        "type": "Internship",
        "role": "Engineering",
        "role_type": "Machine learning",
        "salary_range": "$5K - $10K / monthly",
        "equity_range": "",
        "experience": null,
        "visa": "US citizen/visa only",
        "skills": [
          "Torch/PyTorch",
          "Reinforcement learning (RL)"
        ]
      },
      {
        "id": 94626,
        "title": "Research Engineer",
        "url": "https://www.ycombinator.com/companies/sid/jobs/3izpJe0-research-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Machine learning",
        "salary_range": "",
        "equity_range": "",
        "experience": "Any (new grads ok)",
        "visa": "Will sponsor",
        "skills": [
          "Torch/PyTorch",
          "Reinforcement learning (RL)",
          "CUDA",
          "Search",
          "LLMs",
          "Vector Embeddings",
          "AI Agents",
          "MLOps"
        ]
      }
    ],
    "news": [
      {
        "title": "Is A.I. Startup Funding a Rerun of the Dot-Com Bubble? | Chicago Booth Review",
        "url": "https://www.chicagobooth.edu/review/is-ai-startup-funding-rerun-dotcom-bubble",
        "date": "Jul 14, 2023"
      }
    ],
    "launches": [
      {
        "id": 72952,
        "title": "SID.ai – AI research lab for retrieval",
        "tagline": "AI research lab for retrieval",
        "body": "**Intelligence needs Context**\n\nAI is giving humanity a new computer: one that can learn, reason, and act. But intelligence and skills are inconsequential without context. _Context imposes the upper bound._ At SID, we're training models to provide this context. _To connect intelligence to the world._\n\n**Context needs Retrieval**\n\nTo provide the right context, you need to find it first: Humanity has known how to do search on the internet for a while. But great search over everything else has been elusive so far. We think _we have an angle to solve it once and for all_. [SID-1](https://www.sid.ai/research/sid-1), our first agentic retrieval model, doubles embedding-only accuracy and outperforms frontier models on the most complex retrieval tasks.\n\n![uploaded image](/media/?type=post&id=72952&key=user_uploads/1134710/cd8dc357-3db7-4db0-9476-265e176bb6bb)\n\n**SID-1**\n\n_SID-1 is our first model for agentic retrieval: 1.8x more likely to surface the right results than embedding-only search across general knowledge, finance, science, legal, and email. It is more accurate than agentic retrieval based on Gemini 3 Pro, Sonnet 4.5, and GPT-5.1 at its highest compute setting, while being 24x faster (144 vs 5.7 seconds)._\n\nTraditional retrieval pipelines pre-program each step: query rewriting, searching, reranking. SID-1 retrieves like a human would: it searches, reads results, and refines its queries, taking as many steps as needed. We trained SID-1 on questions that take human researchers over an hour to solve.\n\nSID-1 is drop-in compatible with existing retrieval systems. It is designed to work as a subagent with larger LLMs like GPT-5 or Sonnet. Teams running embedding-only retrieval or RAG can typically integrate it in an afternoon.\n\nStep-change improvements in retrieval create new winners. Claude Code was better at finding the right file, unlocking larger code bases and driving massive adoption for Anthropic. Open Evidence made retrieving over medical research easier and took doctors by storm. Looking back further, relational was better than hierarchical for databases, creating Oracle. Better web search created Google. [_We're working closely with a small group of companies who want that edge now for their domains._](https://tally.so/r/gDDVMd)\n\nGiven we're compute-limited, we're rolling SID-1 out slowly. We're offering SID-1 through our API, AWS Bedrock, and as a self-hosted model. _If you're interested in SID-1, please sign up to our [waitlist](https://tally.so/r/gDDVMd), follow us on [X](https://x.com/SID_AI), or read the [technical report](https://www.sid.ai/research/sid-1-technical-report) for more details._",
        "url": "https://www.ycombinator.com/launches/Iye-sid-ai-ai-research-lab-for-retrieval",
        "votes": 135,
        "created_at": "2023-07-11T18:57:41.923Z"
      }
    ]
  },
  {
    "id": 28851,
    "name": "Bronco AI",
    "slug": "bronco-ai",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/dce0ac1e308aa18998242314db08d5821b4db4aa.png",
    "website": "https://www.bronco.ai/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Bronco is an applied AI lab helping chipmakers keep Moore’s law going. Our mission is to build AI silicon verification engineers that find bugs, drive functional coverage, and help companies ship working chips on time.\r\n\r\nWe're currently deployed alongside verification teams at leading chip companies building next generation hardware (4 nm process node).\r\n\r\nWe are well-funded and backed by tier-1 investors, including YC, 8VC, Elad Gil, SV Angel, and Contrary Capital. We have also established strong relationships with the leading academic and industry researchers in the field of AI for chip design. Our advisors have won multiple Best Paper Awards at leading conferences, been cited tens of thousands of times, and received some of the highest honors in the microelectronics and EDA industries.",
    "one_liner": "AI for ASIC Design Verification",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1683953569,
    "tags": [
      "B2B",
      "Enterprise Software",
      "Semiconductors",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2023",
    "status": "Active",
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      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/bronco-ai",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/bronco-ai.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/bronco-ai",
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    "primary_partner": {
      "name": "Garry Tan",
      "url": "https://www.ycombinator.com/people/garry-tan"
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    "founders": [
      {
        "user_id": 824475,
        "full_name": "David Zhi LuoZhang",
        "title": "Founder",
        "founder_bio": "Building Bronco AI | Enjoyer of industrials, ML, and the frontier thesis",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/dluozhang",
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        "user_id": 1264576,
        "full_name": "Jeffrey Pan",
        "title": "Founder",
        "founder_bio": "Building Bronco AI, deeply passionate about the industrial economy, AI, and their future together.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/jeffreyzpan",
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    "id": 28868,
    "name": "Briefer",
    "slug": "briefer",
    "former_names": [
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    ],
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    "website": "https://briefer.cloud",
    "all_locations": "São Paulo, SP, Brazil; Remote",
    "long_description": "Briefer helps data scientists and analysts build interactive visualizations and data apps using a Notion-like interface.\r\n\r\nConnect to your data sources, write SQL or Python, collaborate through comments and multiplayer editing, and run code in whichever compute environments you need.",
    "one_liner": "The collaborative data platform.",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1687307247,
    "tags": [
      "Developer Tools",
      "B2B",
      "Data Science",
      "Data Engineering",
      "Data Visualization"
    ],
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    "batch": "Summer 2023",
    "status": "Inactive",
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    "regions": [
      "Brazil",
      "Latin America",
      "Remote",
      "Fully Remote"
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/briefer",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/briefer.json",
    "year_founded": 2022,
    "city": "São Paulo",
    "country": "BR",
    "linkedin_url": "https://www.linkedin.com/company/briefercloud/",
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    "github_url": "https://github.com/briefercloud",
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    "primary_partner": {
      "name": "Aaron Epstein",
      "url": "https://www.ycombinator.com/people/aaron-epstein"
    },
    "founders": [
      {
        "user_id": 578593,
        "full_name": "Lucas da Costa",
        "title": "Founder",
        "founder_bio": "I'm the founder and CEO at Briefer. Previously, I worked as a senior software engineer at Elastic and led software engineering teams at an early-stage startup in London.\n\nI used to maintain large OSS projects like Chai.js and Sinon.js and contributed to many others, including Jest.\n\nAs an author, I wrote \"Testing JavaScript Applications,\" published by Manning. I've also spoken in more than ten countries, and my content has been voluntarily translated into more than seven languages.",
        "is_active": false,
        "linkedin_url": "https://linkedin.com/in/lucasfdacosta",
        "x_url": "https://twitter.com/thewizardlucas",
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      },
      {
        "user_id": 1372900,
        "full_name": "Lucas Vieira",
        "title": "Founder",
        "founder_bio": "Lucas, is a software engineer and open-source enthusiast with a decade of experience, actively contributes to numerous open source projects. He used to maintain Chai.js, a popular JavaScript testing framework with 7.8k+ GitHub stars. As the former Head of Technology at Joga, he built a product from scratch, used by thousands in dozens of countries. Now, Lucas is the CTO of Ergomake, developing a product for developers to deploy preview environments for any stack.",
        "is_active": false,
        "linkedin_url": "https://linkedin.com/in/lucas-vieira-1ba001a4",
        "x_url": "https://twitter.com/commadangle",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4b304961c58125ab235255d85217abb378470ab1.jpg"
      }
    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 88718,
        "title": "❇️ Briefer Agent: your AI data analyst, built into a powerful data workspace",
        "tagline": "Briefer's agent helps anyone on your team turn data into clear and instant insights.",
        "body": "Hey YC! I'm Lucas, founder of Briefer: a data workspace for notebooks and dashboards.\n\n**✨ Today, we're launching the Briefer Agent: an AI analyst that helps anyone on your team turn data into clear and instant insights ✨**\n\n<https://youtu.be/VBXmDJCqOGk>\n\nFor the past year, we've been building a powerful data workspace to help thousands of technical users uncover deep insights they wouldn't otherwise have. Many of these people use Briefer every day and get a lot of value out of it thanks to features like Python support, point-and-click visualizations, scheduling, and turning query results into data frames automatically.\n\n**Now, we're bringing Briefer's magic to _everyone_.** Whenever _anyone_ on your team has a question, they can ask our AI analyst, and it'll use Briefer to get them an answer.\n\n‎\n\n---\n\n# **⭐ It's not just another text-to-SQL chatbot**\n\n**Our AI analyst is _not_ just another “text-to-SQL” chatbot that spits out random graphs.** Instead, it's an intelligent agent that operates Briefer's powerful data workspace to generate answers that are precise and reviewable.\n\nOur agent can do anything a human analyst does in Briefer: write SQL, plot graphs, and even run Python for data manipulation and advanced analyses.\n\n‎\n\n---\n\n# **🤝 Especial things the Briefer Agent can do**\n\n* **🏦 Handle business-specific context.** If you have business-specific context you'd like to explain to the agent, you can easily add it to help the agent better understand your data and goals.\n* ☁️ **Connect to all the most popular data sources.** Briefer connects to all the most popular data sources, including Postgres, BigQuery, Redshift, Athena, Snowflake, MySQL, and others. The agent can use those data sources too.\n* **📄 Analyze CSV, XLS, and Parquet files.** If you have a CSV or Excel file, you can also upload it and ask for the Briefer agent to analyze it for you. That'll be easy because the agent knows how to use Briefer's DuckDB integration to query that file too.\n* 🎈**Run on your own infrastructure.** You can fully self-host Briefer's enterprise version and use your own Bedrock or Vertex services to power the agent. Therefore, all your data remains on your cloud, _always_.\n\n‎\n\n---\n\n# **➡️ How can I try the agent?**\n\nTo try out Briefer's agent, [book a call using this link](https://calendly.com/lucasfcosta/briefer-intro) and we'll help you get started ASAP.\n\nIf you have questions, feel free to email us, the founders, directly at [founders@briefer.cloud](mailto:founders@briefer.cloud).",
        "url": "https://www.ycombinator.com/launches/N4w-briefer-agent-your-ai-data-analyst-built-into-a-powerful-data-workspace",
        "votes": 27,
        "created_at": "2025-03-17T19:16:57.634Z"
      },
      {
        "id": 83864,
        "title": "❇️ Briefer: Python notebooks and dashboards in one place (now open-source)",
        "tagline": "Create Python notebooks that look like Notion, and publish them as reports or dashboards.",
        "body": "⭐ Today, we're launching [Briefer's open-source offering](https://github.com/briefercloud/briefer).\n\n**Briefer is like Notion for code notebooks and dashboards. It gives technical users all the flexibility they need to publish dashboards, analyze data, create reports, and build data apps. At the same time, Briefer makes it easy for non-technical users to view and interact with data.**\n\n![](https://i.imgur.com/EYLk7xK.gif)\n\nIn Briefer, you can:\n\n* 📚📊 **Create notebooks and dashboards** using Markdown, Python, SQL, and native visualizations.\n* 🤳 **Build interactive data apps** using inputs, dropdowns, and date pickers.\n* 🤖 **Generate code and queries** using an AI that understands your database schema and your notebook's context.\n* 🕰️ **Schedule notebooks and dashboards** to run and update periodically.\n* ⚙️ **Create and test ad-hoc pipelines** using writebacks.\n\nIn addition to all that, Briefer is also multiplayer, meaning two or more people can work on the same notebook or dashboard simultaneously and see each other's changes in real time.\n\nFrom today, you can use Briefer for free on your machine or deploy it to your own infrastructure so that your whole team can use it and eliminate your data silos.\n\n \n\n### **🍱 What's included in the open-source offering?**\n\n![uploaded image](/media/?type=post&id=83864&key=user_uploads/578593/fdaa030e-0bad-43d6-a35f-e96332f951a6)\n\nBriefer's open-source offering includes everything you need to build notebooks and dashboards, including Markdown, SQL, Python, point-and-click visualizations, scheduled runs, writebacks, and more.\n\nAlso, given you'll be running Briefer on your own machines, there's no limit on how many users you can invite, how much memory and compute you can give to your notebooks, and how many pages you can schedule.\n\nThe only things that are _not_ in Briefer's open-source offering are PDF exports, granular permissions, and email and Slack integrations. These are available in the paid version of Briefer, for which you can sign up [here](https://briefer.cloud).\n\n \n\n### **🤔 Why open-source?**\n\nWe want people to have zero barriers to using Briefer, and we believe that making it open-source is the best way to achieve that.\n\nBy making Briefer open-source, we're giving you the freedom to run it on your own infrastructure, customize it to your needs, and contribute to its development.\n\nFurthermore, given Briefer will be running on your own machines, you don't have to worry about your data being stored in a third-party service. You have full control over your data.\n\nIf you want an in-depth explanation of our open-source strategy, [you can read it here](https://briefer.cloud/blog/posts/open-source-strategy).\n\n \n\n### **✨ How do I get started?**\n\n**➡️ You can get started by following the instructions in our **[**GitHub repository**](https://github.com/briefercloud/briefer)**. While you're there, please don't forget to give us a star ⭐.**\n\nIf you have any questions, please send me an email at [lucas.costa@briefer.cloud](mailto:lucas.costa@briefer.cloud). I respond to every email I receive from users.\n\nIn case you need help deploying Briefer or just want to talk directly to me, please [book a time here](https://calendly.com/lucasfcosta/briefer-intro-call).",
        "url": "https://www.ycombinator.com/launches/Loe-briefer-python-notebooks-and-dashboards-in-one-place-now-open-source",
        "votes": 28,
        "created_at": "2024-09-09T17:05:36.669Z"
      },
      {
        "id": 80177,
        "title": "❇️ Briefer: Jupyter Notebooks and data apps in the cloud - and it looks like Notion!",
        "tagline": "Create and share beautiful analyses, visualizations, and data apps",
        "body": "\\*\\*TL;DR: If you're using Jupyter Notebooks or have ad-hoc scripts and data apps, you should consider switching to [**Briefer**](https://briefer.cloud) ❇️. Briefer works like Jupyter Notebooks, but it runs in the cloud and is as pretty and intuitive as Notion. It allows you to create beautiful and in-depth analyses, visualizations, and data apps.\\*\\*\\\n—\n\nHi, we're Lucas da Costa and Lucas Vieira (the Lucas²), founders of Briefer.\n\nWe've built Briefer to help data scientists create analyses, visualizations, and data apps and share their work with others — including non-technical people!\n\n![uploaded image](/media/?type=post&id=80177&key=user_uploads/578593/d4956051-0462-4492-b4f7-512a2652739a)\n\n[**🎬 Here's a demo 📹**](https://www.loom.com/share/f5658419cd154958862de41f1ea328c8?sid=685856a5-d188-4c53-baf3-51084ef3d141)\n\nYou can use Briefer instead of writing messy notebooks, building unmanageable ad-hoc scripts, wrangling with SQL in limited BI tools, or going through the hassle of setting up the infrastructure for a data app.\n\n# \n\n# **⭐ Briefer is better than Jupyter or ad-hoc solutions because:**\n\n* 💅 It looks way better and is 1000x easier to use — non-technical stakeholders will love it too.\n* 🤗 It's easy to share — just copy a link, no need to install dependencies or pull a git repo.\n* 💾 You can run SQL and Python in the same place — All SQL queries can be used as Pandas data-frames straightaway. No need to write custom wrapper libraries.\n* 🖥️ It's interactive — you can use text fields or dropdowns for viewers to provide input to your pages.\n* ⚡No Memory or GPUs? No problem — we can get you more powerful machines if you need them.\n* 👯 Real-time collaboration — you can see what others are doing if you're editing the same document, just like Google Drive.\n\n# **⭐ Get started now ✨**\n\n[**➡️ Click here to book an intro call if you want to get started with Briefer ⭐**](https://calendly.com/lucasfcosta/briefer-intro-call)\n\nWe move fast and we prioritize making customers happy over everything else - and we can help you build your first analyses and data apps. So, as a small team, there's a limited number of people we can onboard at a time - **make sure to book a call as soon as possible to ensure we'll get you a spot.**\n\nIf you have any other questions or comments, please email us at [founders@briefer.cloud](mailto:founders@briefer.cloud).",
        "url": "https://www.ycombinator.com/launches/KrB-briefer-jupyter-notebooks-and-data-apps-in-the-cloud-and-it-looks-like-notion",
        "votes": 73,
        "created_at": "2024-04-15T17:39:24.496Z"
      },
      {
        "id": 73177,
        "title": "🧚 Ergomake - Deploy a staging environment for every pull request",
        "tagline": "Whenever engineers push changes, we deploy their entire application and send them a link.",
        "body": "**TL;DR Ergomake creates a staging environment for each pull request. Every time an engineer pushes changes, we deploy their entire application and send them a link to see it. Our customers use Ergomake for QA, product, and design reviews before any code gets merged.**\n\nHey everyone! We're Lucas and Lucas (yes, Lucas²), the founders of [Ergomake](https://ergomake.dev).\n\n![uploaded image](/media/?type=post&id=73177&key=user_uploads/578593/67fb36be-2271-4b94-8403-f3f1c9bf4612)\n\n**Ergomake creates a new staging environment every time engineers push changes**, making reviews much quicker and easier and helping teams avoid shipping broken changes.\n\n## ❌ The problem: staging is a bottleneck.\n\nEngineers must ship code to a staging environment whenever they need feedback from QAs, designers, and product managers.\n\nThe problem with this approach is that **teams usually have only one staging environment**. Therefore, **engineers scramble to see who will use staging or end up merging changes before anyone else sees them**.\n\n![uploaded image](/media/?type=post&id=73177&key=user_uploads/578593/0d929f46-4a46-425d-86e8-458fc4843816)\n\n**Consequently, teams slow down, applications break, or undesirable code gets shipped**.\n\nWhen that happens, engineers rush to fix the broken code already merged. For that, they must go through the whole review process again, which is a massive waste of time and money.\n\n## 💡 The solution: everyone gets their own staging.\n\nWith Ergomake, every change gets deployed to a new staging environment.\n\n![uploaded image](/media/?type=post&id=73177&key=user_uploads/578593/dc0ff32d-60c5-46d1-a759-b875aaaaea15)\n\nThat way, engineers can get input from the rest of their team without queueing to use staging.\n\nAdditionally, by getting reviews _before_ deploying code, teams avoid merging all sorts of undesirable changes. Consequently, they avoid bugs and reduce rework by keeping `main` always working.\n\nWith Ergomake, teams can merge straight into `main` because they do all their manual testing and validations within their pull requests. Therefore, these teams avoid complicated branching strategies and painful integration cycles.\n\n![uploaded image](/media/?type=post&id=73177&key=user_uploads/578593/9b319d08-4e0e-4239-9786-f5cc9373d979)\n\n## ⚙️ How does it work?\n\nErgomake integrates with GitHub and gets notified whenever someone opens a pull request.\n\nWhen that happens, Ergomake uses the `docker-compose.yaml` file within the repository to deploy your application on our infrastructure.\n\nOnce Ergomake has spun everything up, it adds a comment to the pull request containing the link to test your application.\n\nOur previews can include databases, and they support all types of projects, including those spread across multiple repos.\n\n## ➡️ The ask: sign-up now (there's a free tier)\n\n**You can sign-up for Ergomake at **[**app.ergomake.dev**](https://app.ergomake.dev)**.** There, you'll be able to configure previews for any repositories you want for free.\n\n**If you prefer, we're happy to do all the integration for you or hop on a call and guide you through the process**. If you think that could be helpful, [book an intro call here](https://calendly.com/lucasfcosta/ergomake-15-minutes).\n\nFor anything else, [we're also on Discord](https://discord.gg/daGzchUGDt).",
        "url": "https://www.ycombinator.com/launches/J2H-ergomake-deploy-a-staging-environment-for-every-pull-request",
        "votes": 85,
        "created_at": "2023-07-18T15:59:24.172Z"
      }
    ]
  },
  {
    "id": 28882,
    "name": "Repaint",
    "slug": "repaint",
    "former_names": [
      "AutoEmber",
      "Repaint",
      "Vigilant"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a40c666dc622907d8af3f29f4b78c554dba156c9.png",
    "website": "https://repaint.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Repaint lets you build professional websites by chatting with AI. It interviews you, researches you online, and generates a custom websites. Then you can edit anything by asking the AI. Our vision is to merge traditional website builders with AI coding tools, creating a new way for anyone to make more advanced software.",
    "one_liner": "Build a website by chatting with AI",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1690825892,
    "tags": [
      "SaaS",
      "Chatbot",
      "Design",
      "Web Development",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2023",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/repaint",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/repaint.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/repaint-ai",
    "x_url": "https://x.com/RepaintHQ",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/autoember",
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/a40c666dc622907d8af3f29f4b78c554dba156c9.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": null,
    "founders": [
      {
        "user_id": 1045360,
        "full_name": "Ben Shumaker",
        "title": "Founder",
        "founder_bio": "Cofounder of Repaint. I used to be the Lead Game Designer for https://playthebazaar.com/ \nAnd before that, I was a competitive strategy gamer.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/ben-shumaker-9b2620238/",
        "x_url": "https://twitter.com/BenShumaker_",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0c44197f46f2dc63bf54ec0b9ab698a60fca9254.jpg"
      },
      {
        "user_id": 1315306,
        "full_name": "Izak Fritz",
        "title": "Founder",
        "founder_bio": "founder of Repaint",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/izak-fritz-3b8579120",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3bc98a4b2d6b965d3a9fce343742ba33c6405b24.jpg"
      }
    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 98979,
        "title": "Repaint: The AI Website Builder",
        "tagline": "Build a website by chatting with AI",
        "body": "We’re [Ben](https://www.linkedin.com/in/ben-shumaker-9b2620238/) and [Izak](https://www.linkedin.com/in/izak-fritz-3b8579120/), and we’re proud to introduce the new Repaint (S23).\n\nRepaint is the best AI tool for creating professional marketing websites. You chat with Repaint, plan the style and pages, and import your content. Then Repaint generates a custom website in minutes.\n\n**Demo:** <https://youtu.be/HkL9yoQOyOQ>\n\n**The Problem**\\\nAI coding tools are incredibly powerful now, but most people still make websites with Wix and Squarespace. Vibe coding tools like Lovable, Bolt, and Replit can generate a webpage from a prompt in a few minutes, but beyond that they’ve focused more on app building than marketing sites:\n\n* They generate single pages with generic content, leaving you to build the rest.\n* The visual style is hard to control, with few resources for inspiration.\n* They surface technical details like code, hosting providers, and github integrations.\n* They charge per edit, so finishing a large marketing site is expensive.\n\nThere’s no major AI tool focused on making polished websites for small businesses, entrepreneurs, and marketers. That’s what we’re building.\n\n**The Solution**\\\nRepaint is an AI website builder designed to get you to a finished site, not just a starting point.\n\n* **It starts by learning about you.** Repaint interviews you about your business, what pages you need, and what style you're going for. It can research your company online and import existing content.\n* **You control the style.** You can pick a theme, provide reference links, and upload inspiration images. Or, you can let Repaint design it for you.\n* **It generates a complete site.** Repaint makes full websites with your real information. And it can recreate the same pages from an existing website.\n* **You edit with chat.** Restyle the whole site, add pages, update info across every page, redesign sections.\n* **It writes real code.** So it can build things template-based builders can't like custom animations, interactive components, calculators, and complex forms.\n* **Flat monthly pricing.** No per-edit credits.\n\n![uploaded image](/media/?type=post&id=98979&key=user_uploads/1045360/65931443-8184-450c-876c-89dcaf327f5f)\n\nWe opened Repaint about a month ago, and we’ve had hundreds of people make sites for tons of different businesses including YC startups, bakeries, cycling coaches, and more.\n\n**Our Background**\\\nRepaint is actually our second website builder. During YC S23, we built a different website builder with a drag-and-drop interface inspired by Figma. Despite our best efforts, we never got it off the ground. The existing website builders were already heavily optimized, and the AI wave was rapidly making manual no-code tools obsolete.\n\nBut those years gave us deep expertise in web layout, editor UX, and what actually makes people give up on building a site. We think that's exactly what AI website building needs — not just better models, but a team that understands the challenges well enough to make it reliable.\n\n**Our Ask**\\\nIf you or someone you know needs a website, you can try it at [repaint.com](https://repaint.com)\n\n![uploaded image](/media/?type=post&id=98979&key=user_uploads/1045360/3fb2e2fb-d58e-41a9-89a1-c8afe08c8e21)\n\n",
        "url": "https://www.ycombinator.com/launches/PkR-repaint-the-ai-website-builder",
        "votes": 3,
        "created_at": "2026-03-21T14:06:43.659Z"
      },
      {
        "id": 89065,
        "title": "Vigilant - Observability for modern software teams",
        "tagline": "Helping startups with application monitoring through logs, metrics, errors, and more.",
        "body": "![uploaded image](/media/?type=post&id=89065&key=user_uploads/1045360/2eaee34c-2e65-45e6-a296-d923eb287b1c)\n\n# **What is Vigilant?**\n\n[Vigilant](https://www.vigilant.run/) helps developers monitor their applications and fix issues without overwhelming complexity.\n\nWe provide a unified platform for log management, error tracking, metrics visualization, and smart alerting - everything needed for complete application visibility.\n\nWe obsess over the user experience end-to-end, from integration to alerting. It makes Vigilant a strong choice for startups looking to monitor their product without a massive investment in learning and integration.\n\n[You can try it yourself here](https://vigilant.run)\n\nㅤ\n\n# **Why Vigilant?**\n\nHowdy, I’m Ben Shumaker, the cofounder of Vigilant. I cofounded Vigilant with my best friend, Izak Fritz. Our goal is to make observability easier.\n\nAfter experiencing the frustrations of juggling multiple observability tools at Robinhood and using painfully clunky default options in our cloud providers, we grew tired of tools that seemed designed for experts. Most dedicated platforms assume you already have tons of specialized knowledge about what to monitor and how—but most developers don’t know.\n\nWe built Vigilant to be the first observability tool prioritizing simplicity, not just comprehensive features.\n\nㅤ\n\n# **The Problem**\n\nObservability platforms feel overwhelming, end-to-end:\n\n* Complex agent installation and configuration requirements\n* Huge variety of integration methods without clear guidance\n* Cluttered interfaces full of random information and endless configurations\n* Tedious manual queries for simple searches and graphs\n* Multi-variable pricing that's unpredictable and expensive\n\nㅤ\n\n# **Our Solution**\n\n![uploaded image](/media/?type=post&id=89065&key=user_uploads/1045360/86936056-dc52-4c4e-8178-7f518ea9c0ad)\n\nVigilant is the opposite of a traditional observability tool:\n\n* SDK-based integration that only requires a few lines of application code\n* Auto-capture so you can send logs and errors without changing every file\n* Smart defaults that minimize setup time\n* Focused interface that surfaces relevant info, and nests complexity\n* Genuinely predictable pricing with a simple equation\n\nㅤ\n\n# **How It Works**\n\n![uploaded image](/media/?type=post&id=89065&key=user_uploads/1045360/fbb74c68-1c6a-4611-9ec7-5fa85719d2ce)\n\n1. **Installation** – Download our SDK for your tech stack\n2. **Integration** – Add a few lines to start sending logs, errors, or metrics\n3. **Manage in Vigilant** – After you've sent data, you view it and search it in Vigilant\n4. **Build Dashboards** – Create graphs and counters to visualize your data\n5. **Get Notifications** – Use integrations to get alerts when issues occur\n\nㅤ\n\n## **Ready to Simplify Your Observability?**\n\nYou can try Vigilant entirely on our free tier. If you're tired of complex monitoring tools and want something you'll enjoy:\n\n* Get started: <https://vigilant.run>\n* Book a call: <https://calendly.com/ben-rep/vigilant-intro>\n* Email us: [founders@vigilant.run](mailto:founders@vigilant.run)\n\nAlready using a platform? We'll manually help you migrate and setup your observability in Vigilant. [Book a call to explore your options.](https://calendly.com/ben-rep/vigilant-intro)",
        "url": "https://www.ycombinator.com/launches/NAX-vigilant-observability-for-modern-software-teams",
        "votes": 6,
        "created_at": "2025-03-28T14:15:06.574Z"
      },
      {
        "id": 73608,
        "title": "AutoEmber - A visual design tool for making real websites",
        "tagline": "Instead of making mockups, just make the real thing!",
        "body": "Hi everyone. We’re Ben and Izak, cofounders of [AutoEmber](https://autoember.com/).\n\n![uploaded image](/media/?type=post&id=73608&key=user_uploads/1045360/88bf4baa-cd9a-451d-8fe7-8af58389c929)\n\n_(Left to Right)_\n\nBen: Former competitive gamer. Was on the MTG Pro Tour at 14. Rank 1 Hearthstone Battlegrounds. Lived with Reynad (CEO and Twitch streamer) and spent 2 years as lead game designer at TempoStorm. \n\nIzak: Built a crypto trading platform at Cove Markets, acquired by Robinhood in 2021. Previously, JP Morgan software engineer. Computer science at the University of Michigan.\n\nWe met over a decade ago playing Magic the Gathering in Holland, Michigan.\n\n### **😓 The Problem:**\n\nMaking websites is hard. To make a website today, you either:\n\n1. Learn html, css, and javascript –> Months of learning, hours of coding to make minor changes\n2. Use a template website builder –> Can’t customize, get a generic website\n\nMeanwhile, there’s thousands of designers who can make pixel-perfect mockups, but then they have to pass it off to a coder who can actually build it.\n\n### **💫The Solution:**\n\n[AutoEmber](https://autoember.com) - a visual design tool that makes real websites\n\n![uploaded image](/media/?type=post&id=73608&key=user_uploads/1045360/6d4a6b5f-aab5-4949-ac45-737d003cb4c7)\n\nWe spent the last couple months building a web app that lets anyone make a custom website, end to end, without coding. The user experience:\n\n1. Make an account\n2. Design your website in the editor\n3. Push “Publish”\n\nToday, you could make a good looking website with a few pages in a couple hours. We’re constantly adding features to make it more 🥧 easy, 💪 powerful, and 💅 pretty\n\n### **Who its for:**\n\nYou’ll find it especially useful if you’re: \n\n* A designer who uses tools like Figma\n* A backend dev who doesn’t like frontend\n* A business owner who wants a custom website without coding\n\nBut anyone making a website should check it out.\n\n### **How you can help**\n\nGive it a try! It’s free. We love feedback. [AutoEmber.com](http://AutoEmber.com)\n\nIf you’re in the market for a website, please reach out! We’d be happy to help you design your website. Contact: [ben@autoember.com](mailto:ben@autoember.com) 👋\n\nThanks, Ben and Izak",
        "url": "https://www.ycombinator.com/launches/J9E-autoember-a-visual-design-tool-for-making-real-websites",
        "votes": 36,
        "created_at": "2023-07-31T18:05:29.431Z"
      }
    ]
  },
  {
    "id": 28907,
    "name": "refine",
    "slug": "refine",
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      "refine",
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    "website": "https://refine.dev",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "refine is an open-source, headless React framework for rapidly building enterprise web applications. It eliminates many repetitive tasks like\r\n\r\n➡️ CRUD operations\r\n➡️ State management\r\n➡️ Routing\r\n➡️ Authentication\r\n➡️ Access Control\r\n➡️ i18n\r\n\r\nand saves days of development time.\r\n\r\nSo far, thousands of great projects have been built by 15,000+ monthly active refine developers. Use cases are ranging from admin panels, dashboards, and internal tools to B2B solutions and complex SaaS interfaces. \r\n\r\nrefine is backed by a strong community featuring 16K GitHub stars ⭐️, 180+ contributors and 2,500 Discord members. \r\n\r\nThanks to it's unique \"Headless UI\" approach, refine works with any custom design. It has also ready-made integrations with 4 most popular UI frameworks: Ant Design, Material UI, Chakra UI and Mantine. refine is totally backend agnostic and it can connect to 15+ backend services out-of-the-box, incl. custom REST & GraphQL API's.\r\n\r\nWith refine, developers always have 100% control over their projects as they build, style and deploy the way they like.\r\n",
    "one_liner": "Open-source Retool for enterprise",
    "team_size": 10,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1687469921,
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      "Open Source",
      "Web Development"
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    "nonprofit": false,
    "batch": "Summer 2023",
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    "regions": [
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      "America / Canada",
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      "Fully Remote"
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    "stage": "Early",
    "app_video_public": false,
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/refine",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/refine.json",
    "year_founded": 2022,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/81566498/",
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    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/refine-0e26",
    "github_url": "https://github.com/refinedev/",
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        "user_id": 1013886,
        "full_name": "Civan Ozseyhan",
        "title": "Founder",
        "founder_bio": "Serial entrepreneur & Open-source enthusiast | 15+ years experience in building enterprise software | Co-founder & CEO @ refine",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/civan-%C3%B6zseyhan-1ab48814",
        "x_url": "https://twitter.com/civanozseyhan",
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      {
        "user_id": 1551538,
        "full_name": "Omer Aplak",
        "title": "Founder",
        "founder_bio": "Co-founder & CTO @ refine. I started my professional software career in high school and dropped out of university in my first year. Developing open-source, building communities, and helping other developers is a passion of mine",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/omer-aplak-14b87099/",
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        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ba3e72dc58607e693c5905a527be981778f0fbe1.jpg"
      },
      {
        "user_id": 1018276,
        "full_name": "Eren Erkalkan",
        "title": "Founder",
        "founder_bio": "Previous: Worked as Head of Product, founder and CEO in the fields of e-commerce and online dating for almost 15 years. Now: Accompanying the journey of refine, which started as an open-source project in 2022. A React-based framework for the rapid development of web applications.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/eren-erkalkan-1b31a89a",
        "x_url": "https://twitter.com/piyerro",
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    "launches": [
      {
        "id": 72562,
        "title": "Refine - Open-source platform for rapidly building enterprise web applications",
        "tagline": "Dev-friendly alternative to low-code/no-code. Familiar stack, 100% control over project!",
        "body": "**Refine** is an **open-source**, **headless** React framework for developers building enterprise web applications. It eliminates many repetitive tasks such as\n\n➡️ CRUD operations ➡️ State management ➡️ Routing ➡️ Authentication ➡️ Access Control & ➡️ i18n\n\nand saves days of development time.\n\nAs a developer-focused alternative to existing _low-code/no-code_ enterprise tools, **Refine** allows developers to **work with the stack they are already familiar** **with** and have **100% control over their projects.**\n\nFor a quick start, you can visit\n\n* [👉 https://refine.dev](https://refine.dev) - Docs, tutorials and 100+ sample projects\n* [👉](https://refine.dev) <https://github.com/refinedev/refine> - **12K** ⭐️\n\n### **Solution**\n\nThanks to its unique “**Headless UI**” approach, Refine works with any custom design. It has ready-made integrations with the 4 most popular UI frameworks: **Ant Design**, **Material UI**, **Chakra UI** and **Mantine**. Refine is totally backend agnostic and can connect to **15+ backend services** out-of-the-box, incl. **custom REST & GraphQL API’s.**\n\n![uploaded image](/media/?type=post&id=72562&key=user_uploads/1013886/0fe3bd00-f162-4c50-9f98-4988ad3e2779)\n\nYou can give it a try on [refine.new](http://refine.new) to see how easily you can create tailor-made projects in seconds, by combining your preferred tools and technologies.\n\n### **The Framework**\n\nInstead of being a limited set of pre-styled components, **Refine core** is a lean collection of **helper hooks**, **components**, and **providers**. They are all decoupled from UI components and business logic, so that they **never keep you from customizing your UI or coding your own flow.**\n\n### **Community**\n\n**Refine** is backed by a robust community that showcases the following metrics:\n\n⭐️ 17K GitHub stars\\\n👩‍💻 150+ Contributors\\\n💻 5,000+ Commits\\\n💬 3,000 Discord members\n\n### **Use Cases**\n\nSo far, **thousands** of great projects have been built by **15,000+ monthly active Refine developers**. Use cases include but are not limited to\n\n* Admin Panels\n* Forms\n* Dashboards\n* Storefronts\n* Internal tools\n* B2B Solutions\n* SaaS Interfaces\n\n### **What’s Next?**\n\nIn addition to our endless contributions to the open-core framework, we are also developing cloud-based products to make Refine a comprehensive platform for developers to build enterprise-grade web applications.",
        "url": "https://www.ycombinator.com/launches/IsM-refine-open-source-platform-for-rapidly-building-enterprise-web-applications",
        "votes": 100,
        "created_at": "2023-06-27T04:37:31.127Z"
      }
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    "id": 28930,
    "name": "Midrender",
    "slug": "midrender",
    "former_names": [
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      "Revideo"
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    "website": "https://midrender.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Midrender is a visual editor for creating motion graphics, powered by AI. Point the agent at your codebase, it reads your code, understands the feature, and creates an animated walkthrough you can ship. A full timeline and design editor lets you fine-tune every detail.",
    "one_liner": "Turn product features into launch videos",
    "team_size": 1,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1688598945,
    "tags": [
      "Design",
      "Design Tools",
      "Video",
      "Marketing",
      "AI"
    ],
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2023",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
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    "demo_day_video_public": false,
    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/midrender",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/midrender.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/haven-ml",
    "x_url": "https://twitter.com/redotvideo",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/redotvideo",
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        "user_id": 1910964,
        "full_name": "Konstantin Hohr",
        "title": "Founder",
        "founder_bio": "Konstantin is the founder of Revideo. Previously, he studied computer science at RWTH Aachen while simultaneously working as a software engineer at Jodel, where he built content moderation and abuse detection systems. At DynamoAI (W22), he spearheaded development on vertical federated learning based products.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/konsti-h",
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      {
        "id": 80105,
        "title": "Revideo - Create videos with code",
        "tagline": "An open source toolkit to build web-based video apps.",
        "body": "### TLDR:\n\nWe are building [Revideo](https://re.video/), a web-based open-source framework that lets you create videos using the animation library Motion Canvas. It exposes basic video & audio editing functionality through a typescript API and lets you render videos with dynamic inputs. You can find our code on [**Github**](https://github.com/redotvideo/revideo)!\n\n### **The Problem:**\n\nWe believe that AI will drastically change how people produce video and that huge amounts of video will soon be created in an automated manner. Initially, we wanted to build applications in this space ourselves and started to work on a few ideas. For example, we worked on an AI-based app to automatically create highlight videos for Twitch streamers, as well as a platform that lets companies A/B test video ads.\n\nWhile building these products, we noticed that we weren’t really happy with the tooling we used. Most video editing frameworks lacked essential features, and the tools we liked were not open source. Therefore, we decided to build Revideo.\n\n### **The Solution:**\n\nWe built Revideo by extending the animation library Motion Canvas and adding features that are essential for automatically creating videos. These features include support for audio, substantially faster video rendering, and an API for programmatically rendering videos with dynamic inputs.\n\nHere is a code example of a basic video created with Revideo:\n\n![uploaded image](/media/?type=post&id=80105&key=user_uploads/1023703/4f0ca7c8-30c6-402a-a087-2b2829275c40)\n\nThe code above produces the following result:\n\n<https://youtu.be/FGeujyec7_g>\n\n### **Our Asks:**\n\n* Check out [Revideo](https://github.com/redotvideo/revideo) on Github and give us a ⭐ if you like it!\n* We’d love to chat with anyone building video products! If you are building one or know people who do, please reach out ❤️",
        "url": "https://www.ycombinator.com/launches/Kq1-revideo-create-videos-with-code",
        "votes": 12,
        "created_at": "2024-04-11T15:49:45.395Z"
      },
      {
        "id": 76501,
        "title": "Haven: Fine-tune and run open source LLMs super fast ⚡",
        "tagline": "Haven lets you build open source LLMs that are specialized for specific tasks",
        "body": "# TLDR:\n\nWe are excited to launch [Haven](https://haven.run/)’s fine-tuning platform for open source LLMs!\n\n* Haven lets you fine-tune open source LLMs such as Llama or Mistral without writing code or setting up infrastructure. We charge $0.004/1k training tokens, and you get $5 in free credits after signing up\n* You can host models for testing with <1s cold start times. We achieve this by running hundreds of model adapters on a single GPU and hot-swapping them based on user requests (will write more about this in a blog post)\n\nYou can get started [**here**](https://app.haven.run/) - alternatively, reach out to [**hello@haven.run**](https://app.haven.run/) or watch our [demo](https://www.youtube.com/watch?v=XpyVKUyt7k8) if you want to learn more!\n\n### **The Problem**\n\nOver the last months, we’ve identified two big pain points that make it hard to work with open source models:\n\n1. Open source models work best when they are trained for specific use cases, but the fine-tuning process with existing tools is super annoying. We have found that most of our time is spent setting up infrastructure to go from finishing a training run to actually testing our models, rather than actually writing code and improving our models\n2. Hosting custom models is expensive. Running a single Llama-7B model in float16 requires at minimum an A10 GPU, which costs $700+ per month. To run ten or a hundred specialized models for common tasks, this would mean that we have a monthly AWS bill of $7,000 or $70,000, respectively.\n\n### **The Solution**\n\nHaven’s platform offers a super simple way to fine-tune models without managing infrastructure or writing code, and to test and run them with low costs and without any additional work.\n\nWe are able to provide a super short feedback loop of going from training to running a fine-tuned model by hosting multiple lora adapters in parallel. This makes it possible for us to host hundreds of fine-tuned models on-demand on a single GPU. For our users, this reduced model cold start times to <1s and internally, we are able to host a single fine-tuned model for a couple of dollars per month. We also enable our users to export their model weights to Huggingface, so that they can run models entirely on their terms.\n\n### **Our Ask**\n\nFeel free to check out our [**platform**](https://app.haven.run/) and give us feedback! After signing up, you’ll receive $5 in credits to train a couple of models :) We are also happy to answer questions at [**hello@haven.run**](https://app.haven.run/)",
        "url": "https://www.ycombinator.com/launches/Jtt-haven-fine-tune-and-run-open-source-llms-super-fast",
        "votes": 8,
        "created_at": "2023-11-29T17:29:33.896Z"
      },
      {
        "id": 73716,
        "title": "🔮 Haven - Run LLMs on Your Own Cloud",
        "tagline": "Haven makes it easy to deploy LLMs on your own infrastructure",
        "body": "**TL;DR:** Haven makes it easy to deploy LLMs in your GCP / AWS environment. We provide the user experience of serverless solutions like Replicate or Huggingface Inference Endpoints - but instead of running your models on Haven’s servers, we just manage your infrastructure for you. This gives you full control over your data and you get to use your precious cloud credits!\n\n### **🤕 The Problem**\n\nMany companies want to use large language models but do not want to rely on third-party providers as it makes them dependent on external services and comes with significant privacy risks.\n\nHowever, deploying models in-house is just not easy: engineers have to figure out CUDA environments, write and containerize efficient serving code, and expose it as an API server. And let’s not even talk about scalability…\n\nHaven solves this problem. We offer the simplicity, reliability, and scalability of third-party providers while allowing our users to securely run models on their own infrastructure.\n\n### **🤯 How It Works**\n\nHaven is built on top of Kubernetes, which makes it easy to scale and reliable in production settings. Deploying a model with Haven consists of just three steps:\n\n**1\\. Upload a Service Account Key**\n\nUploading a service account key gives Haven permission to manage your cloud resources for you. Under the hood, Haven will now set up a Kubernetes cluster running in your cloud environment.\n\n![uploaded image](/media/?type=post&id=73716&key=user_uploads/1023703/6b35bcd0-f0f5-4f4b-b3ab-dbb6a46261ff)\n\n**2\\. Configure Your Deployment**\n\nYou can now choose your model, select the GPUs you want it to run on, and configure the scaling behavior of your deployment. Haven will accordingly set up the model in your Kubernetes cluster.\n\n![uploaded image](/media/?type=post&id=73716&key=user_uploads/1023703/59c94edb-14a5-4e4e-b173-a4b19223ebdb)\n\n**3\\. Enjoy Your Model**\n\nYour LLM is up and running in minutes! Our deployments offer super-fast inference and advanced features like input batching for efficient serving. This way, you can immediately integrate them into your application.\n\n![uploaded image](/media/?type=post&id=73716&key=user_uploads/1023703/773c461a-05ba-48b2-ba96-6b4c88d23cbf)\n\n### **💪 The Team**\n\nWe’re Konstantin and Justus. The two of us met as freshmen in college, and have since built multiple projects together.\n\n![uploaded image](/media/?type=post&id=73716&key=user_uploads/1023703/95a23ea8-c105-4d8d-af62-f2a527bb50f7)\n\n[Justus](https://www.linkedin.com/in/justus-mattern-a04230184/) is an AI researcher and has been working on LLMs since 2020. As a member of AI labs at UC Berkeley and ETH Zürich, he has published multiple papers at leading research conferences.\n\n[Konstantin](https://www.linkedin.com/in/konsti-h/) has already been a full-time software engineer before starting his university studies. At Germany’s biggest social networking company, he built infrastructure handling requests from millions of daily users.\n\n### **💜 Our Ask**\n\n**Sign up **[**here**](https://vkg6c80ex61.typeform.com/to/IMCFY5Cf)** to work with us!**\n\nWe are working closely with our users to fully understand the needs of companies aiming to integrate LLMs into their products. Beyond giving access to our deployment tool, we partner with early customers to evaluate their use cases and fine-tune models for their needs. If this sounds interesting, sign up for early access or contact us at [hello@haven.run](mailto:hello@haven.run)!\n\n**Refer us to companies looking to use LLMs!**\n\nIf you have connections at companies looking to use LLMs, we’d highly appreciate introductions! You can reach us at [hello@haven.run](mailto:hello@haven.run).",
        "url": "https://www.ycombinator.com/launches/JAy-haven-run-llms-on-your-own-cloud",
        "votes": 229,
        "created_at": "2023-08-02T16:28:57.262Z"
      }
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    "id": 28957,
    "name": "Continue",
    "slug": "continue",
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    "website": "https://continue.dev",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Acquired by Cursor",
    "one_liner": "Pioneering open-source coding agent",
    "team_size": 0,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1688142176,
    "tags": [
      "Developer Tools",
      "AI"
    ],
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2023",
    "status": "Acquired",
    "industries": [
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      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/continue",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/continue.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/continuedev",
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    "github_url": "https://github.com/continuedev",
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    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
    },
    "founders": [
      {
        "user_id": 117092,
        "full_name": "Ty Dunn",
        "title": "Founder",
        "founder_bio": "Founder @Continue, Founding PM @Rasa, Computation @UMich",
        "is_active": false,
        "linkedin_url": "https://linkedin.com/in/tylerjdunn",
        "x_url": "https://twitter.com/tylerjdunn",
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      },
      {
        "user_id": 623872,
        "full_name": "Nate Sesti",
        "title": "Founder",
        "founder_bio": "Co-founder @ Continue. Previously math and physics @ MIT ('24), first hire @ Mayan (W21), building mission control software @ NASA Jet Propulsion Laboratory",
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        "title": "Continue: the easiest way to code with any LLM",
        "tagline": "An open-source autopilot for VS Code and JetBrains",
        "body": "Hi all! We’re Nate and Ty, co-founders of Continue.\n\n## **🔥 TL;DR**\n\n_Stop copy/pasting code from ChatGPT and take control of your development data 💪_\n\n[Continue](https://bookface.ycombinator.com/company/28957) is the open-source autopilot for software development built to be deeply customizable and continuously learn from development data.\n\nOur GitHub is <https://github.com/continuedev/continue>. You can watch a demo of Continue and download the extension at <https://continue.dev>.\n\n![uploaded image](/media/?type=post&id=73449&key=user_uploads/117092/248795a4-d22a-4f7d-a9fb-42c69d63a463)\n\n---\n\n## **💬 The Problem**\n\nA growing number of developers are replacing Google + Stack Overflow with Large Language Models (LLMs) as their primary approach to get help, similar to how developers previously replaced reference manuals with Google + Stack Overflow.\n\nUnfortunately, existing LLM developer tools are cumbersome black boxes. Developers are stuck copy/pasting from ChatGPT and guessing what context Copilot uses to make a suggestion. As we use these products, we expose our code and give implicit feedback that is used to improve their LLMs, yet we don’t benefit from this data nor get to keep it.\n\nThe solution is to give developers what they need: _transparency, hackability,_ and _control_. Every one of us should be able to reason about what’s going on, tinker, and have control over our own development data. This is why we created Continue.\n\n---\n\n## **⏩ The Solution**\n\nAt its most basic, Continue removes the need for copy/pasting from ChatGPT—instead, you collect context by highlighting and then ask questions in the sidebar or have an edit streamed directly to your editor.\n\nBut Continue also provides powerful tools for managing context. For example, type ‘@issue’ to quickly reference a GitHub issue as you are prompting the LLM, ‘@README.md’ to reference such a file, or ‘@google’ to include the results of a Google search.\n\nAnd there’s a ton of room for further customization. Today, you can write your own\n\n* slash commands (e.g. ‘/commit’ to write a summary and commit message for staged changes, ‘/docs’ to grab the contents of a file and update documentation pages that depend on it, ‘/ticket’ to generate a full-featured ticket with relevant files and high-level instructions from a short description)\n* context sources (e.g. GitHub issues, Jira, local files, StackOverflow, documentation pages)\n* templated system message (e.g. “Always give maximally concise answers. Adhere to the following style guide whenever writing code: {{ /Users/nate/repo/styleguide.md }}”)\n* tools (e.g. add a file, run unit tests, build and watch for errors)\n* policies (e.g. define a goal-oriented agent that works in a write code, run code, read errors, fix code, repeat loop)\n\nContinue works with any LLM, including local models using ggml or open-source models hosted on your own cloud infrastructure, allowing you to remain 100% private. While OpenAI and Anthropic perform best today, we are excited to support the progress of open-source as it catches up (<https://continue.dev/docs/model-setup/select-model>).\n\nWhen you use Continue, you automatically collect data on how you build software. By default, this development data is saved to .continue/dev_data on your local machine. When combined with the code that you ultimately commit, it can be used to improve the LLM used by your team.\n\nYou can read more about how development data is generated as a byproduct of LLM-aided development and why we believe that you should start collecting it now: <https://blog.continue.dev/its-time-to-collect-data-on-how-you-build-software/>\n\nContinue has an Apache 2.0 license. We plan to make money by offering organizations a paid development data engine—a continuous feedback loop that ensures the LLMs always have fresh information and code in their preferred style.\n\n---\n\n## 🙏 **Our Asks**\n\n1. [**Star our GitHub repo**](https://github.com/continuedev/continue)\n2. Download for [**VS Code**](https://marketplace.visualstudio.com/items?itemname=continue.continue) & [**JetBrains**](http://plugins.jetbrains.com/plugin/22707-continue)\n3. Join our [**Discord**](https://discord.gg/NWtdYexhMs) & [**newsletter**](https://continue.dev/?ref=blog.continue.dev#newsletter)\n\n---\n\n## **❤️ The Team**\n\nWe started working on Continue because LLMs rapidly got better and quickly became an important part of our development workflows. In 2021, Ty was helping the research team at Rasa use GPT-3 to create user simulators and Codex to generate Actions code for Rasa Open Source—projects that did not result in shipped products because LLMs were not good enough yet.\n\nThis changed in 2022. During the day, Nate wrote code at NASA, unable to use LLMs due to privacy concerns. But at night, the difference was stark as GitHub Copilot and ChatGPT completely changed how we built side projects.\n\nWe believe that the role of LLMs in software development is only beginning. In order to reach their full potential, developers need to to be able to tinker and unleash their creativity. Every developer must be able to try new things and push what's possible using LLMs without having to ask for permission.\n\n![uploaded image](/media/?type=post&id=73449&key=user_uploads/117092/98c7da9c-a397-4ec1-8727-f1dbc941df77)\n\n",
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        "title": "Vango 🎨 - Build with + evaluate Stable Diffusion fast",
        "tagline": "Try Vango, the fastest way to build and analyze diffusion models! ",
        "body": "**tl;dr:** _Vango makes it 10x easier to build and evaluate Stable Diffusion workflows in your app. Developers use Vango to deploy Stable Diffusion in minutes and achieve high-quality images faster than any existing solution._\n\n_Hello world_ — Eshaan and Rajen here!\n\n![uploaded image](/media/?type=post&id=74170&key=user_uploads/887154/c555fc75-23e2-4ba7-9384-8d74b8378765)\n\nWe’re thrilled to show y’all what we’ve been working on, let’s begin!\n\n### 🐷 Problem:\n\nWe’ve all seen how unique, highly customizable, and beautiful AI art can be — **but it’s incredibly tedious to deploy and maintain Stable Diffusion in your app.**\n\nBuilding apps on top of stable diffusion is an unnecessarily tedious and manual process. You have to:\n\n* **Select the right models, hyperparameters, and prompts:** These have huge impact on the content, quality, and style of outputs. To achieve the best results, developers spend hours testing each model, parameter, or prompt individually.\n* **Add guardrails:** Ensuring that your model does not generate unintended NSFW or discriminatory images takes hours of careful testing.\n* **Deploy on GPUs:** Like everything in AI right now, developers must obtain and configure a juicy high-VRAM GPU to run Stable Diffusion fast.\n\n  \n\n### **💜 Solution:**\n\n**Vango empowers developers to build and evaluate stable diffusion models faster than ever.**\n\n## 🧱 Build workflows & deploy as API\n\nWatch us build a corgi generator and deploy it as a scalable API in seconds.\n\n![uploaded image](/media/?type=post&id=74170&key=user_uploads/887154/36fc2f9f-0d81-4e81-aeca-f849103d2652)\n\n## 🤖 Perfect the hyper-parameters\n\n**Vango helps you evaluate models quantitatively.** Vango will track metrics across thousands of prompts — including NSFW content, crossed eyes, disfigured limbs/fingers, cropped faces, and prompt alignment.\n\n1. Specify your models (either as `.safetensors` or `.ckpt` file, Cog container, API endpoint, or Vango workflow)\n2. Provide us your prompts or _use one of our prompt datasets with thousands of examples_.\n3. Use our quantitative features to learn how models compare\n\n![uploaded image](/media/?type=post&id=74170&key=user_uploads/887154/dcd39f7d-6900-4402-91d7-8fc530ca3b0e)\n\nAnd for more granular analysis, you can filter all the images based on failure modes. In the video below, you can see us finding the images that have deformed hands.\n\n![uploaded image](/media/?type=post&id=74170&key=user_uploads/887154/6c83e176-d63b-4e23-8cbc-a5cac60bfb2f)\n\n### 🐻 About us:\n\nWe’re best friends, neighbors back home in Maryland, and college roommates (and literally sharing a triple in SF right now)! We’ve been doing class projects + side projects together for over 3 years now 🙉.\n\nEshaan has researched multimodal models at Berkeley AI Research (BAIR), low-compute visual detection systems at NASA JPL, and anomaly detection at Citadel Securities. And Rajen has built wide-ranging software at Amazon, Nuro, Two Sigma, and Solana.\n\nAnd we both graduated from UC Berkeley a year early to work on Vango! We discovered this problem while developing our own diffusion apps after noticing first-hand how AI can help creatives in VFX.\n\n### 📩 Asks:\n\nIf you are (or know anybody that is) building apps with stable diffusion, we’d love to chat and see how we can help! We’re currently onboarding our early partners.\n\nIf you’re interested, sign up for our waitlist [here](https://forms.gle/ExYEf2HTeNBWJfa19) or shoot us an email at [founders@vango.ai](mailto:founders@vango.ai).",
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        "body": "**TL:DR:** [baserun.ai](http://baserun.ai) is a testing platform for LLM apps. From prompt playground to end-to-end tests, baserun helps you ship your LLM apps with confidence and speed.\n\n## **The problem:**\n\n**Productionizing LLM features is hard. 🥲**\n\n1. It's difficult to judge which combination of model, configurations, and prompts performs better.\n2. It's challenging to debug complex workflows that mix chained prompts and other 3rd party API calls.\n3. It's hard to understand the progression of app performance over time.\n\n![uploaded image](/media/?type=post&id=74004&key=user_uploads/1038083/cef4bc61-ae39-4dc0-b0ca-f763861c4e97)\n\n## **Our solution:**\n\n**Gain insights into your LLM features within seconds**\n\nInstall baserun SDK and immediately gain insights into your LLM features and agents during testing, and monitor their behavior in production.\n\n**Full visibility into your end-to-end tests & user journey**\n\nVisualize the precise sequence of calls, duration, and cost, along with the inputs and outputs at each stage, encompassing both custom functions and third-party API calls.\n\n**Intuitive and flexible UI for evaluating and debugging**\n\nEffortlessly compare test runs side by side, directly edit prompts, and rerun tests from the UI.\n\n![uploaded image](/media/?type=post&id=74004&key=user_uploads/1038083/87f4df81-dd31-49b5-aeb0-5d5b51f7e504)\n\n**Collaborative workspace for teams**\n\nReview results, experiment and iterate on prompts, and build test datasets with your whole team. All prompts and test results are version-controlled.\n\n![uploaded image](/media/?type=post&id=74004&key=user_uploads/1038083/3cd2684f-04b3-4835-ac39-c27ba810a69f)\n\n**Our Asks**\n\n* Try [baserun](https://baserun.ai/welcome) and give us some feedback! [Book a 15-minute call](https://calendly.com/effy-zhang/baserun-onboarding-call) with us. We’d love to hear about what you are building and help you get onboarded.\n* You can follow us on [Twitter](https://twitter.com/baserunai) or [LinkedIn](https://www.linkedin.com/company/baserun), or email us at [hello@baserun.ai](mailto:hello@baserun.ai)",
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        "created_at": "2023-08-10T19:17:49.128Z"
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        "title": "Inari 🦊 - Your junior AI product manager",
        "tagline": "Build delightful products by identifying insights and product opportunities automatically from your customer feedback, CRM, and backlog.",
        "body": "Hey YC 👋🏼 - Frank and Eric here from [Inari](https://useinari.com/)!\n\n### **TL;DR**\n\n[Inari](https://useinari.com/) automatically surfaces actionable insights and product opportunities from your customer feedback, CRM, and backlog. This helps your team prioritize and build products that users love — without having to sort through 1,000’s of sales calls, support tickets, or feedbacks manually.\n\nTry Inari out for free at [useinari.com](http://useinari.com) or checkout our [product demo](https://www.youtube.com/watch?v=PKrRjXW1b08).\n\n### **Problem**\n\nThe canonical startup advice is “talk to your users” and “deeply understand customer problems,” but executing it is easier said than done. The volume of customer feedback and qualitative data is exploding, living fragmented across hundreds of tools, making it difficult and time-consuming to convert customer data into useful insights and product opportunities.\n\nWithout a clear view of what customers are saying, product teams miss out on signals that can improve their product, reduce churn, and drive revenue growth. Missed signals means your engineering team wastes time building features customers don’t actually need.\n\n### **Explore accurate customer insights**\n\nInari allows you to explore your customer feedback, convert it into actionable requests, defects, praises, and learnings, then deeply understand exactly what’s top of mind for customers. Each insight gets auto-linked with relevant customer feedbacks and your CRM, so you can measure how frequent and valuable an insight is based on feedback.\n\n![uploaded image](/media/?type=post&id=87667&key=user_uploads/1073124/0e4651d3-cf6b-4349-8f43-d2a6c97afef8)\n\n### **Unify feedback, analyze it at scale**\n\nInari unifies your customer feedback from sources like Gong, Intercom, Zendesk, and Slack then automates the tedious process of sifting through it, extracting useful quotes, measuring sentiment, triaging feedback to specific teams, and linking it back to insights and issues (goodbye Productboard 👋🏼) using personalized fine-tuned AI models.\n\n![uploaded image](/media/?type=post&id=87667&key=user_uploads/1073124/5fc0851a-7ae9-4dba-a9cb-7736f8144ae1)\n\n### **Prioritize product opportunities**\n\nInari syncs with your Jira and Linear backlog, so you can ingest existing issues then auto-link it to relevant feedbacks and your CRM. This enables product builders to know exactly which company accounts are requesting a feature, its revenue impact based on deal size, then identify and resolve requests and edge cases flagged in relevant customer comments.\n\n![uploaded image](/media/?type=post&id=87667&key=user_uploads/1073124/8e9e5f59-9057-4035-a69b-df6835dc3e8c)\n\n### **Accelerate product development and prototypes**\n\nSince Inari is connected to customer data and organizes product context, you can generate deep dives, PRDs, and AI prompts grounded in customer needs in one-click. As AI coding tools improve, a key bottleneck to building better features is task clarity - Inari makes it easy to convert customer context into well-defined prompts that steer AI coding tools in generating prototypes.\n\n![uploaded image](/media/?type=post&id=87667&key=user_uploads/1073124/acafcf7e-5fc9-42d9-afd3-4e0207091582)\n\n### **Get started 💯**\n\n* If your product, engineering, or CX team needs to convert overwhelming volumes of customer data into actionable insights and product opportunities, [get started today](https://app.useinari.com/api/auth/signup) or check out [Inari](http://useinari.com) to learn more.\n* We’d love any feedback and are always down to geek out about product development. [Talk to us](https://cal.com/frank-lee-inari/30min) about your analysis, product discovery, prioritization, or AI prototyping problems so we can build something delightful for you!",
        "url": "https://www.ycombinator.com/launches/Mnz-inari-your-junior-ai-product-manager",
        "votes": 21,
        "created_at": "2025-02-17T18:24:09.722Z"
      },
      {
        "id": 80084,
        "title": "🦊 Inari: AI-powered product discovery and feedback analytics",
        "tagline": "Surface insights and revenue-generating product opportunities from your customer data auto-magically",
        "body": "Hey YC friends👋🏼 - Frank and Eric here from [Inari](https://useinari.com/)!\n\n## **TL;DR**\n\n[Inari](https://useinari.com/) surfaces customer insights and revenue-generating product opportunities from your customer data auto-_magically_ using AI.\n\nInstead of sifting through 100s of user interviews or 1000s of pieces of customer feedback manually, Inari automates the process of highlighting interesting quotes, identifying trends, uncovering impactful feature requests, and tying helpful prioritization metrics with features so your team can spend less time analyzing and more time building products that customers love. See our [product demo here](https://www.youtube.com/watch?v=vn3AExWP5xA).\n\n## **The Problem**\n\nThe canonical startup advice has always been, \"_go talk to your users._\" However, the process of listening to users, extracting meaningful insights, and figuring out what products to build based on actual customer problems is time-consuming. Most teams fail to make use of their customer data, resulting in missed revenue and higher churn.\n\nTop-performing teams that do talk to users have to spend significant effort manually analyzing and triaging customer feedback, sales convos, and support tickets. It’s tough to actually pull out impactful feature ideas and product opportunities from customer interactions and then persuade your team to prioritize them. Pulling together effective customer anecdotes and convincing prioritization metrics requires a ton of research and analysis.\n\n## **How It Works**\n\nIn the near future when AI makes us 10x more productive with task execution, deeply understanding customer problems and identifying impactful initiatives to take on becomes increasingly important. Inari helps automate the monotonous parts of customer analysis and product discovery across several steps.\n\n**Analyze customer interactions on autopilot**: Inari integrates with customer data sources (like Slack, Salesforce, and Gong), ingests customer interactions (like feedback, support tickets, and sales convos), and then automatically analyzes it all. Inari highlights key quotes, scores sentiment, and then triages feedback to specific teams, saving your product and support teams from having to do it manually.\n\n![uploaded image](/media/?type=post&id=80084&key=user_uploads/1073124/3424c0c3-51ff-4372-96b9-0f77052aec5c)\n\n**Automated accurate insights**: As feedback pours in, Inari clusters it into accurate insights (requests, defects, praises, learnings, competitor mentions) so you can understand what’s top of mind for customers. Each insight comes with volume and sentiment metrics, alerts, and VoC dashboards that automate reporting. You can customize taxonomies and prompts to tailor analysis to your team’s needs.\n\n![uploaded image](/media/?type=post&id=80084&key=user_uploads/1073124/214b1290-e4dd-432d-8d7a-0be12fb8f717)\n\n**Uncover product opportunities**: Inari surfaces potential backlog issues based on customer feature requests or AI-recommended solutions for top customer problems. Every issue auto-links to relevant customer data like deal size, company stage, mention volumes, and specific anecdotes – giving you a 360° view when prioritizing what issues matter most.\n\n![uploaded image](/media/?type=post&id=80084&key=user_uploads/1073124/3f6e8e5e-ebf2-420d-b649-ab3ee0fc453c)\n\n## **Our Asks 🙏🏼**\n\n* If your product, engineering, CX, or sales team wants to convert overwhelming volumes of customer data into actionable insights, VoC reporting, and alerts, you can [get started today here](https://app.useinari.com/api/auth/signup) or check out [useinari.com](http://useinari.com) to learn more.\n* If you’re interested in surfacing product opportunities and generating a 1st draft of your backlog based on customer requests using AI, let’s [chat live](https://calendly.com/frank-xu8/chat-with-frank-inari) or email [frank@useinari.com](mailto:frank@useinari.com) so I can onboard your team as design partners.\n* We’d love any feedback and are always down to geek out about product development. Talk to us about your analysis, product discovery, or prioritization problems so we can build something delightful for you!",
        "url": "https://www.ycombinator.com/launches/Kpg-inari-ai-powered-product-discovery-and-feedback-analytics",
        "votes": 39,
        "created_at": "2024-04-10T22:50:35.177Z"
      },
      {
        "id": 73813,
        "title": "🦊 Inari: AI-Powered Customer Insights Hub",
        "tagline": "Customer feedback that analyzes itself ✨. Unify your feedback then automatically analyze and generate product insights at scale.",
        "body": "## **TL;DR**\n\n[**Inari**](https://useinari.com/) is the AI-powered hub for unifying customer feedback and generating product insights. Instead of sifting through 100’s of pages of user interviews or 1000’s of pieces of customer feedback manually, you can use Inari to consolidate customer feedback across data sources, automatically highlight useful quotes, categorize sentiment, and generate insights. You can use this data to understand what’s on your customer’s minds, figure out which themes will boost engagement and retention, then prioritize your roadmaps.\n\n**If any product, UX research, design, support, or other teams want an automated way to analyze customer themes, requests, quotes, and other insights for planning, triaging requests, and other use cases - let us know and we’d love to get this live for you (**[**frank@useinari.com**](mailto:frank@useinari.com)**)!**\n\n## **The Problem(s)**\n\n* Product, design, and engineering teams rely on feedback and research data for insights and empathy for building products people love. However, this data lives across several sources like Salesforce, Zendesk, customer interviews living in PDFs, and data sitting in CSVs so it’s tough to maintain a 360-degree view of opportunities to improve customer experience.\n* It’s time consuming to manually sift through, analyze, and tag customer feedback data to be used for roadmap and feature planning. Having to deal with and endless amount of copying and pasting feedback + fiddling with context limits in ChatGPT and Claude is also mind-numbing. We had several designers and UX researchers come inbound saying they have to sift through 100+ pages of customer research transcripts for themes 🤯.\n* It’s hard to know the exact volume of customers that are mentioning a specific problem or topic and having this data on hand is critical for sizing magnitude for problems when deciding what features or themes to prioritize.\n\n## **How It Works**\n\n**Consolidate feedback in one place**: Sales notes, user interviews, Slack requests, CSVs with customer feedbacks... unify them all in Inari. Inari ingests feedback from unstructured and structured sources, consolidates them into a unified hub, then provides a streamlined workflow to manage it all.\n\n![uploaded image](/media/?type=post&id=73813&key=user_uploads/1073124/2af2e6fe-cd27-440c-9b01-04280bc2bd08)\n\n**Automate feedback analysis**: Inari automatically analyzes customer sentiment and highlights top requests, defects, praises, and learnings across your customer feedback and interviews so your team doesn't have to review hundreds of sources manually.\n\n![uploaded image](/media/?type=post&id=73813&key=user_uploads/1073124/e23cb606-4066-4836-9a8e-d0f31088949c)\n\n**Surface product insights automatically**: Reduce churn and build delightful products based on insights, feature requests, bug fixes, and learnings that Inari extracts from connected feedback. Inari attributes insights to the feedback most related to it, so you can size how frequently an issue is mentioned when prioritizing your backlog.\n\n![uploaded image](/media/?type=post&id=73813&key=user_uploads/1073124/5b4dc325-9975-4d3c-8dc6-1ec5faa5bdb1)\n\n**Visualize customer trends**: Search, filter, and monitor trends in dashboards built on your consolidated feedback, insights, and customer data.\n\n![uploaded image](/media/?type=post&id=73813&key=user_uploads/1073124/735992d9-bf16-4b47-b3bd-ae79590a1e7e)\n\nCheck out the quick product demo [here](https://www.youtube.com/watch?v=N91aAfrWZ4E&t=5s).\n\n## **Founder Background**\n\nFrank and Eric met back in 2014 while working together at Amazon. Eric worked @ AWS for 7 years building out Sagemaker, owned their XGBoost image, and deployed algos for the US government before transitioning to full-stack eng for securely managing health and bio data @ Betteromics. Frank worked on ML algorithms an interfaces @ Opendoor between 2016-2020 and managed products like NBA Top Shot + business intelligence teams @ Dapper Labs and Amazon.\n\n## **Our Asks 🙏🏼**\n\n* If you know any teams struggling with extracting takeaways from their feedback data, whether it’s thousands of structured feedback from Zendesk or a few 10 page customer interview transcripts, send them our way and we’d love to help them out! Reach us at [frank@useinari.com](mailto:frank@useinari.com) or [eric@useinari.com](mailto:frank@useinari.com).\n* We’d love any feedback! Especially around how your team is currently managing feedback and roadmap items, any frustrations, and which datasets you need handled.",
        "url": "https://www.ycombinator.com/launches/JCX-inari-ai-powered-customer-insights-hub",
        "votes": 34,
        "created_at": "2023-08-04T14:55:51.908Z"
      }
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    "name": "Silimate",
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "We're building AI-native tools & agent-driven workflows for frontend chip design. \r\n\r\nToday, Fortune enterprises and chip unicorns license Silimate to hit their PPA targets and functional closure in days instead of months. With Silimate, chip companies tape out better, more market-competitive chips much more quickly.",
    "one_liner": "Fast, efficient agents for chip design and debug",
    "team_size": 8,
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    "subindustry": "B2B -> Engineering, Product and Design",
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    "regions": [
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    "linkedin_url": "https://www.linkedin.com/company/silimate",
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    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/61f4bbb4f45487fb9514316eae7b6e1b1c316a4a.png",
    "app_video_url": null,
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    "primary_partner": {
      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
    },
    "founders": [
      {
        "user_id": 1313634,
        "full_name": "Ann Wu",
        "title": "Founder",
        "founder_bio": "Co-founder & CEO of Silimate. Ann designed several generations of custom silicon at Apple, helped manage the inference ASIC programs at Meta, and developed product strategy & execution at an AI chip start-up.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/annwuhoo",
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      },
      {
        "user_id": 1184182,
        "full_name": "Akash Levy",
        "title": "Founder",
        "founder_bio": "Co-founder & CTO of Silimate. Akash has a PhD from Stanford in Electrical Engineering, with technical expertise spanning EDA, AI, and cloud through his time at Synopsys, NVIDIA, and AWS. He has taped out 3 chips, published 14 papers on circuit design, and has two pending patents in the EDA space.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/akashlevy/",
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    "jobs": [
      {
        "id": 102953,
        "title": "Chip/EDA/Software Intern",
        "url": "https://www.ycombinator.com/companies/silimate/jobs/6CTGk7H-chip-eda-software-intern",
        "location": "Mountain View, CA, US",
        "type": "Internship",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$5.2K - $7K / monthly",
        "equity_range": "",
        "experience": null,
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 102954,
        "title": "Applied AI Engineer",
        "url": "https://www.ycombinator.com/companies/silimate/jobs/RVX3ulq-applied-ai-engineer",
        "location": "Mountain View, CA, US / San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Machine learning",
        "salary_range": "$140K - $220K",
        "equity_range": "0.50% - 2.00%",
        "experience": "1+ years",
        "visa": "Will sponsor",
        "skills": []
      },
      {
        "id": 102955,
        "title": "Chip/Software Engineer",
        "url": "https://www.ycombinator.com/companies/silimate/jobs/kxgYCET-chip-software-engineer",
        "location": "Mountain View, CA, US / San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$140K - $220K",
        "equity_range": "0.50% - 2.00%",
        "experience": "1+ years",
        "visa": "Will sponsor",
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      },
      {
        "id": 102956,
        "title": "Applied AI Intern",
        "url": "https://www.ycombinator.com/companies/silimate/jobs/xt2UihN-applied-ai-intern",
        "location": "Mountain View, CA, US",
        "type": "Internship",
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        "salary_range": "$5.2K - $7K / monthly",
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        "experience": null,
        "visa": "US citizen/visa only",
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      },
      {
        "id": 102957,
        "title": "AI Research Intern",
        "url": "https://www.ycombinator.com/companies/silimate/jobs/BUbLN9M-ai-research-intern",
        "location": "Mountain View, CA, US",
        "type": "Internship",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$5.2K - $7K / monthly",
        "equity_range": "",
        "experience": null,
        "visa": "US citizen/visa only",
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    "news": [
      {
        "title": "Preparing For AI-Driven Chip Design And Verification",
        "url": "https://semiengineering.com/preparing-for-ai-driven-chip-design-and-verification/",
        "date": "Jul 27, 2026"
      },
      {
        "title": "AI In Chip Design: Lots Of Promise, Plenty Of Unanswered Questions",
        "url": "https://semiengineering.com/ai-in-chip-design-lots-of-promise-plenty-of-unanswered-questions/",
        "date": "Jul 15, 2026"
      },
      {
        "title": "Executive Outlook: Agentic AI's Impact On Chip Design",
        "url": "https://semiengineering.com/executive-outlook-agentic-ais-impact-on-chip-design/",
        "date": "Jun 25, 2026"
      },
      {
        "title": "Agentic AI and the Future of Chip Design: From Productivity Tool to Engineering Partner - SemiWiki",
        "url": "https://semiwiki.com/semiconductor-services/esd-alliance/370229-agentic-ai-and-the-future-of-chip-design-from-productivity-tool-to-engineering-partner/",
        "date": "Jun 15, 2026"
      },
      {
        "title": "Silimate CEO pioneers AI debugger for chip designers",
        "url": "https://stanforddaily.com/2026/03/11/silimate-ceo-pioneers-ai-debugger/",
        "date": "Mar 11, 2026"
      }
    ],
    "launches": [
      {
        "id": 73953,
        "title": "👾 Silimate - Copilot for chip designers",
        "tagline": "Design the right semiconductors chips in less time",
        "body": "**TL;DR: Silimate helps chip teams converge to functional correctness and optimized PPA faster, so that they can build better chips in less time.**\n\n# \n\n# **❌ The Problem**\n\nThe world needs specialized semiconductor chips to be built faster for the rapidly-evolving software workloads in datacenters and at the edge.\n\nYet, chip teams today face time- and effort-intensive bottlenecks in converging to functional correctness and optimized PPA (power/performance/area). These bottlenecks account for most of the typical 12-18 month chip development cycle, and impede chip teams’ ability to make important changes to their designs in late project stages — when real, data-driven issues tend to surface from simulations.\n\n# \n\n# **✨ Our Solution**\n\nSilimate finds functional bugs, predicts PPA issues, and recommends real fixes in real-time alongside RTL development. Chip designers get a context-aware RTL companion that helps them write correct, PPA-optimized RTL from the onset, and build better chips in less time.\n\n**We’re live with chip design teams today.**\n\nIf you’re a chip designer or lead a chip design team, we can help you eliminate weeks/months from your design cycles. Reach out to us to schedule a live demo!\n\n# \n\n# **🌎 Why Now**\n\nDeath of Moore’s Law, an explosion of custom chip architectures, geopolitics, talent shortage, massive demand for AI chips, and increasing complexities in advanced chip design – we’re building the critical pickaxe for the AI and edge [silicon renaissance](https://www.forbes.com/sites/robtoews/2020/05/10/artificial-intelligence-is-driving-a-silicon-renaissance/?sh=3566b040553c).\n\n# \n\n# **👋 Contact us at [hello@silimate.com](mailto:hello@silimate.com) to learn more!**\n\n* If you’re a chip designer or lead a chip design team, email us – we’ll help speed up your RTL development cycles.\n* If you’re not a chip designer but know one (or a few), send them our way!",
        "url": "https://www.ycombinator.com/launches/JEn-silimate-copilot-for-chip-designers",
        "votes": 65,
        "created_at": "2023-08-09T16:29:19.599Z"
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    "id": 29013,
    "name": "Sweep",
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        "full_name": "William Zeng",
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        "user_id": 1343086,
        "full_name": "Kevin Lu",
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        "id": 95289,
        "title": "🧹 Sweep: Cursor Tab for JetBrains IDEs",
        "tagline": "Meet Sweep, the smartest autocomplete for IntelliJ, PyCharm, and Android Studio",
        "body": "Hi everyone! We’re [Kevin](https://x.com/kevinlu1248) and [William](https://www.linkedin.com/in/william-zeng/), and we’re building a better AI autocomplete for JetBrains.\n\n**TLDR;** [Sweep](https://sweep.dev/) is a free autocomplete plugin for IntelliJ / PyCharm that is smarter than Cursor Tab.\n\n![uploaded image](/media/?type=post&id=95289&key=user_uploads/1214046/931362f2-24b9-4d5b-aa4b-778cd98aacbc)\n\n# The Problem\n\nDevelopers writing production-grade code need tools like autocomplete that keep them in the loop rather than agents that take them out of it.\\\n\\\nJetBrains users don’t have an AI autocomplete that works well. The leading plugins are not products that users love:\n\n![uploaded image](/media/?type=post&id=95289&key=user_uploads/1214046/f78574aa-2dfe-4d58-82a5-a284b8ca1147)\n\n![uploaded image](/media/?type=post&id=95289&key=user_uploads/1214046/72d4698c-42be-404b-9d1b-9b6d9869d201)\n\n# Our Solution: Sweep 🧹\n\nWe’re building tools for professional developers using JetBrains, starting with super fast autocomplete that’s smarter than Cursor Tab.\\\n\\\nWe’ve fine-tuned our own LLM with a custom inference stack that suggests completions with sub-100ms latency. Unlike Cursor, we use the JetBrains code index to let our autocomplete model navigate your code like a real developer.\n\nWe’ve heard great feedback so far:\n\n_“AI is finally useful inside JetBrains — thanks to sweep. **A million times better than JetBrains’ own tools.**” -_ Christiaan Bilthof, CTO @ Leat\n\n_“Compared to every other tool and IDE I've used, **it's incredibly fast** - so much so that the next tab predictions and autocomplete feel instantaneous.” -_ Ashkan Aghdai, Staff Engineer @ Amplitude\\\n\\\n_“I used to have to choose between using PyCharm and good autocomplete - but with Sweep, I get both. **It’s a massive productivity boost.**”_ **-** Josiah Parappally, Staff Engineer @ Ramp\n\n## Why we built Sweep\n\nWe originally started Sweep in 2023 to build an AI junior developer, which hit 7.6k stars on GitHub.\n\nWe soon realized that this was many years out. Instead, we decided to build a coding assistant that developers could use today. Kevin and I have been JetBrains users since we were in college, and we were surprised something like this didn’t exist yet.\n\nWe built Sweep for ourselves, and use Sweep Tab hundreds of times a day to write production-grade code instead of vibe coding. It’s boosted our productivity by 2x and we hope you like it too. \\\n\\\nTry Sweep for free here: https://plugins.jetbrains.com/plugin/26860-sweep-ai-autocomplete--coding-agent",
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        "tagline": "We built a self-hostable AI coding assistant for JetBrains IDEs",
        "body": "Hey everyone, we’re [William](https://www.linkedin.com/in/william-zeng/) and [Kevin](https://www.linkedin.com/in/kevinlu1248/) - cofounders of Sweep 🧹\n\n\\\n**TLDR**: JetBrains developers have to choose between **the latest AI features** **and the** **IDE that they love**. Sweep is an AI coding assistant purpose-built for JetBrains that **gives you both**.\n\nAsk: Is your team using JetBrains? Reach out at [william@sweep.dev](mailto:william@sweep.dev) or [book a demo here](https://calendly.com/william-sweep/introductory-call?month=2025-03).\n\n# Problem\n\nCurrent AI coding assistants have poor support for JetBrains. GitHub Copilot in JetBrains is a far cry from VSCode, and other plugins aren’t much better.\\\n\\\nWe’ve heard:\n\n_“I love the features in JetBrains as an IDE but the AI sucks”_\n\n_“I see all of these AI coding assistants on VSCode, and I check if they support JetBrains, and I always get disappointed when they don’t.”_\n\nEngineers who don’t use AI coding assistants are less productive. But engineers who have to switch away from their IDEs are even less productive.\n\n# Solution\n\nSweep makes it easy to use AI in JetBrains with our self-hostable plugin. **Engineers keep their existing code editor with no data leakage and the** **best AI features**.\\\n\\\nWe make it seamless to give the AI context. Sweep automatically sees the current file and codebase, saving you precious clicks.\n\n![uploaded image](/media/?type=post&id=88553&key=user_uploads/1214046/6211a915-8ad9-480b-8aa9-7389f4e99fbb)\n\nBy clicking “apply” you can seamlessly review and integrate Sweep’s code changes.\n\n![uploaded image](/media/?type=post&id=88553&key=user_uploads/1214046/a4ff0a2c-7b7a-48dc-9507-9785c19e0020)\n\nFinally, we can **deploy everything on-prem**, unlike other AI coding assistants that take your code and data.\n\n# Our Ask 🙏\n\n**Sweep is available on the JetBrains marketplace today.** Try us out here: [docs.sweep.dev](http://docs.sweep.dev).\\\nTo learn more about our on-prem deployments you can [book a call here](https://calendly.com/william-sweep/introductory-call?month=2025-03).\n\n# About Us\n\nWilliam (CEO) was promoted to a Senior ML Engineer at Roblox in 1.5 years. Kevin (CTO) was the top student in his class at U Waterloo for Math and CS. Martin (Founding Team) was working as a Senior Engineer before he graduated college.\n\nWe’re all big IntelliJ and PyCharm users, and we previously built an AI coding agent with >7k github stars.\n\n![uploaded image](/media/?type=post&id=88553&key=user_uploads/1214046/e0e011e5-25b6-4c72-9ecd-bd9262ee905a)\n\n![uploaded image](/media/?type=post&id=88553&key=user_uploads/1214046/85da6a03-4c5b-4961-9bd2-656ba38c4dbc)\n\n",
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        "title": "Bidirectional Markdown Support for Tiptap",
        "tagline": "The text editor that speaks the language of LLMs: Markdown!",
        "body": "Hi everyone, we’re the team behind Tiptap, the open source text editor framework used by thousands of developers to build rich text and AI-powered writing tools.\n\nWe just launched **bidirectional Markdown support!** You can now import Markdown into Tiptap and export your editor content back to Markdown, without losing structure or formatting.\n\n![uploaded image](/media/?type=post&id=94631&key=user_uploads/1335640/a7c2a608-e669-4e56-bf8c-05fdece38c47)\n\n### **The problem**\n\nMarkdown is becoming the common language for AI and LLM-based workflows.\\\nWhen you feed prompts, train models, or structure outputs, they often rely on Markdown. But most editors don’t handle it well. Converting between Markdown and rich text is lossy, inconsistent, and full of edge cases.\n\nDevelopers who build AI tools, documentation platforms, or note-taking apps need a way to work _natively_ with Markdown without giving up modern editing experiences.\n\n### **How we’re solving it**\n\nWith this release, Tiptap makes Markdown a native format. You can:\n\n* **Parse** Markdown content into Tiptap's ProseMirror-based JSON for editing,\n* **Serialize** your Tiptap content back to multiple variants of Markdown,\n* **Use it client-side or server-side** via the MarkdownManager,\n* **Define custom Markdown** syntax for your custom nodes and marks,\n\n### **How to try it**\n\n1. Install the Markdown package via _@tiptap/markdown_\n2. Either setup the _MarkdownManager_ and directly parse and serialize it or import the _Markdown_ extension and extend your editor instance with Markdown features\n3. Use the serialized and parsed content in your apps (for example parsing file contents or AI streams)\n\n### **Why this matters**\n\nAs AI tools grow, Markdown is quickly becoming the glue between humans and LLMs. Writers, developers, and apps need a format both people and models can read and write.\n\nBy making Markdown fully bidirectional, Tiptap bridges that gap, giving developers a foundation to build the next generation of editors, copilots, and AI-native content tools.\n\n### **Call to action**\n\nIf you’re building AI products or content tools that use Markdown, try it out and tell us how it fits into your stack.\n\nDocs: https://tiptap.dev/docs/editor/markdown/ \n\nYou can reach us at [humans@tiptap.dev](https://mailto:humans@tiptap.dev) or discuss on [GitHub](https://github.com/ueberdosis/tiptap/discussions)",
        "url": "https://www.ycombinator.com/launches/OcJ-bidirectional-markdown-support-for-tiptap",
        "votes": 12,
        "created_at": "2025-10-14T17:57:43.333Z"
      },
      {
        "id": 94225,
        "title": "Tiptap Pages: Word-style layouts in your editor",
        "tagline": "Headers, footers, and pagination without rebuilding Word.",
        "body": "Hey everyone! Philip here, Co-founder at [Tiptap](https://tiptap.dev), the open-source text editor framework used by thousands of dev teams to build collaborative and smart editors.\\\n\\\nWe’ve launched **Tiptap Pages** into live beta, a new extension that adds pagination, page layouts, headers, footers, and structure to your Tiptap editor.\n\nIf you’re building anything that looks like a document editor but ends up hacked together in an infinite scroll, this is for you.\n\n![uploaded image](/media/?type=post&id=94225&key=user_uploads/1335640/3d14271b-bf90-4e24-8d48-800403fdcc21)\n\n### **The Problem**\n\nMost rich text editors treat documents as one long, continuous scroll.\n\nThat works for notes. But not for:\n\n* Contracts with signature blocks that must land on the right page\n* RFPs and government proposals with strict page counts\n* Exams, policies, or legal docs where structure really matters\n* PDFs that actually need to look like the document you typed\n\nAdding “real” document behavior (pages, breaks, headers, print formatting) is hard to maintain.\n\n### **What We Built**\n\nTiptap Pages brings page awareness to your editor.\n\n**Visual page layouts**\\\nChoose A4, Letter, Legal, or define your own. Layouts reflect actual document dimensions.\n\n**Smart pagination**\\\nContent flows across pages with clean, logical breaks\n\n**Dynamic headers and footers**\\\nInsert page numbers, section names, document metadata, and custom elements.\n\n**Custom node support**\\\nBuild and export structured content the way your product needs it, including callouts, exhibits, and embeds.\n\n**Built for developers**\\\nExtend behavior, apply custom styling, and integrate deeply with your stack.\n\nPages is now available on **Team** and **Growth** plans.\n\n![uploaded image](/media/?type=post&id=94225&key=user_uploads/1335640/1a13e116-ecec-40f4-bb07-6c08e0b9005b)\n\n### **See It in Action**\n\n* **Product Overview:** https://tiptap.dev/docs/pages/getting-started/overview\n* **Live Demo:** https://feature-pages-extension--tiptap-pro.netlify.app/src/extensions/pages/react/\n* **Join our Discord:** https://tiptap.dev/discord\n\n### **Why We Built It**\n\nDocs still matter, especially in verticals like legal, fintech, govtech, insurtech, and education. But those documents don’t live in Word forever. They’re part of the tools you’re building.\n\nTeams using Tiptap were already trying to force structure into an unstructured model. We built Pages to give them something better, not just for writing, but for layout, formatting, and final delivery.\n\nIf you’ve ever faked a page break with extra line breaks… you get it.\n\n### **Our Ask**\n\nWe’d love feedback from developers building products with structured documents.\n\n* Try the demo and tell us what breaks.\n* Share what your team would need next (collaboration? AI? export formats?).\n* If you’re in one of the verticals above, let’s chat.",
        "url": "https://www.ycombinator.com/launches/OVl-tiptap-pages-word-style-layouts-in-your-editor",
        "votes": 25,
        "created_at": "2025-09-30T14:00:38.501Z"
      },
      {
        "id": 91336,
        "title": "Tiptap – Better DOCX Import & Export",
        "tagline": "The missing DOCX layer for your text editor infrastructure.",
        "body": "Hey everyone! Philip here, Co-founder at Tiptap (https://tiptap.dev), the open-source text editor framework used by thousands of dev teams to build collaborative and smart editors.\n\n![uploaded image](/media/?type=post&id=91336&key=user_uploads/1335640/25fe0263-453c-44eb-a825-c0cdad1aa51a)\n\nToday we’re launching a major upgrade to our DOCX import and export capabilities, including new extensions, new endpoints, smarter formatting handling, and custom node support.\n\nIf your product deals with Microsoft Word files in any way, this is for you.\n\n### The Problem\n\nHandling DOCX files in modern web apps is a pain.\n\n* Importing DOCX often breaks formatting or loses structure.\n* Exporting to DOCX from custom content structures (like callouts, embeds, or warnings) is clunky or impossible.\n* Styling ends up looking like Word, not your app.\n* Most solutions are heavy, hard to control, or require running backend services yourself.\n\nThis matters if you’re building anything with rich text and need interoperability with Word, from internal tools and documentation platforms to knowledge bases, legal tech, and publishing tools.\n\n### What We Built\n\nWe rebuilt our DOCX pipeline, including both import and export, from the ground up with developers in mind.\n\n**DOCX Import Endpoint**:\\\nEasily parse Word docs and convert them to Tiptap-compatible JSON.\n\n**DOCX Export Extension**:\\\nCreate DOCX files directly from your editor content.\n\n**Better formatting**: \\\nMore accurate handling of nested lists, tables, and mixed styles.\n\n**Custom node support**: \\\nMap your own content blocks (like warnings or embeds) to standard DOCX elements.\n\n**Style control**: \\\nMatch exported DOCX files to your product’s fonts, colors, and spacing.\n\n**Flexible execution**: \\\nRun it in the frontend for full control or in the backend for performance.\n\nWe also now support image uploading from DOCX into your own storage.\n\n### Why We Built It\n\nWe kept seeing developers often had to work around Word support using custom scripts or third-party tools that weren't compatible with custom content models.\n\nTiptap already powers many text editors, so DOCX support needed to be customizable and ready for production.\n\n→ Product Website: [https://tiptap.dev/product/conversion](https://tiptap.dev/product/conversion)\n\n→ Developer Docs: [https://tiptap.dev/docs/conversion/getting-started/overview](https://tiptap.dev/docs/conversion/getting-started/overview)\n\n→ Questions: [humans@tiptap.dev](mailto:humans@tiptap.dev)",
        "url": "https://www.ycombinator.com/launches/NlA-tiptap-better-docx-import-export",
        "votes": 18,
        "created_at": "2025-06-16T14:06:03.276Z"
      },
      {
        "id": 91010,
        "title": "Tiptap – AI infrastructure for text editors",
        "tagline": "Add an AI Assistant to your rich text editor in minutes, not weeks.",
        "body": "Hey everyone! Philip here, Co-founder at Tiptap (https://tiptap.dev), the open-source text editor framework used by thousands of dev teams to build collaborative and smart editors.\n\n![uploaded image](/media/?type=post&id=91010&key=user_uploads/1335640/7f4a081f-e73b-446c-bd13-8bf62848a9a9)\n\nToday, we’re launching the **Tiptap AI Agent,** a developer-first way to add an AI agent that edits documents on your user's behalf, right inside your product. With this tool, you can add a Cursor-like assistant inside your text editor with a few lines of code.\n\n## The problem\n\nAdding AI to a text editor seems easy! Just call an API, right?\n\nBut in reality, you end up rebuilding everything: prompt handling, context extraction, streaming, undo/redo, multiplayer state sync, UX for AI changes… It’s a lot of work just to get to something usable.\n\nAnd it only gets harder when you want to use your custom LLM, tools, and backend..\n\n## **What we built**\n\nThe Tiptap AI Agent gives you all of this out of the box:\n\n* An AI assistant that can read and edit rich text based on user-defined tasks\n* Optional AI review flow (accept/reject changes)\n* Works with Tiptap Cloud or your customLLM, tools and RAG pipelines\n* Fully compatible with Tiptap’s multiplayer, comments, and change tracking\n\nGo from “idea” to “AI in production” in minutes, not weeks.\n\n## **Why we built it**\n\nWe started building this after seeing the same request from users over and over:\n\n> How do I add AI beyond simple text commands to my Tiptap editor?\n\nSo we turned our existing AI features into a full-fledged AI Agent toolkit that anyone can use, no matter what model or backend they prefer.\n\n**Live demo:** https://ai-agent.tiptap.dev/\\\n**Demo video:** https://youtu.be/w3ocdyi5qps\\\n**Docs:** https://tiptap.dev/docs/content-ai/capabilities/agent/overview\n\n## Our ask\n\nTry the demo and plug it into your editor. If you’re building something cool, we’d love to hear from you.\n\nWe’re also happy to answer technical questions and receive feedback. Join our [Discord community](https://tiptap.dev/discord), or email us at [humans@tiptap.dev](mailto:humans@tiptap.dev).\n\nThanks for building with us!\\\nThe Tiptap Team",
        "url": "https://www.ycombinator.com/launches/Nfu-tiptap-ai-infrastructure-for-text-editors",
        "votes": 23,
        "created_at": "2025-06-04T17:36:02.789Z"
      },
      {
        "id": 90091,
        "title": "Tiptap 3.0 Beta: The Next-Gen Open Source Editor",
        "tagline": "Text editing infrastructure, solved.",
        "body": "![uploaded image](/media/?type=post&id=90091&key=user_uploads/1335640/ecc226df-3a58-45cc-aa81-2af38457fc1a)\n\n**Hey everyone! Philip here, Co-founder at Tiptap (**[**https://tiptap.dev**](https://tiptap.dev)**).**\n\nWe're launching **Tiptap 3.0 Beta**, the next major version of our open-source text editor framework for web developers.\n\n**The Problem:** Building custom, reliable, and performant text editors from scratch is painful. Developers spend countless hours struggling with edge cases, extensibility, and maintaining compatibility! Time better spent building core features.\n\n**Our Solution:** Tiptap version 2 already provides a flexible, unopinionated, extension-based editor framework. But with Tiptap 3.0, we've focused heavily on removing even more friction:\n\n* **Full TypeScript integration:** Strongly typed APIs for fewer bugs.\n* **Server-side compatible:** Manipulate content server-side without the need for a DOM.\n* **JSX support:** Write custom nodes using a familiar React/Vue-style syntax.\n* **Simplified dependencies:** Consolidated popular extensions (like TableKit) to streamline your workflow.\n* **Interactive marks:** React and Vue markviews to easily add rich, interactive elements.\n* **Static renderer:** Render your editor content to HTML, Markdown, or even React components, anywhere.\n\n**Why Tiptap?** We initially built Tiptap to solve our own frustrations with text editors. Four years, 30k GitHub stars, and a large open-source community later, we’ve learned a lot and incorporated that directly into Tiptap 3.0.\n\n**Give Tiptap 3.0 Beta a try:**\n\n* What's new in 3.0: <https://next.tiptap.dev/docs/resources/whats-new>\n* Documentation: <https://next.tiptap.dev/docs/editor/getting-started/overview>\n* GitHub: <https://github.com/ueberdosis/tiptap/tree/next>\n\n**Our ask:** We'd love your feedback! If you're building something cool with Tiptap, or have feature requests and ideas, please reach out directly at [founders@tiptap.dev](mailto:founders@tiptap.dev) or reply here.\n\nThanks for building with us!\\\nThe Tiptap Team",
        "url": "https://www.ycombinator.com/launches/NR5-tiptap-3-0-beta-the-next-gen-open-source-editor",
        "votes": 31,
        "created_at": "2025-05-05T16:27:34.078Z"
      },
      {
        "id": 89529,
        "title": "Tiptap – Editor UI Components and Templates",
        "tagline": "Build rich text editor UIs faster with free React components, templates, and a CLI",
        "body": "**Hey everyone 👋 We’re the team behind Tiptap**\n\nWe just launched **Tiptap UI Components** — a free library of React components and templates to help developers build rich text editor UIs faster, without starting from scratch.\n\n![uploaded image](/media/?type=post&id=89529&key=user_uploads/1335640/b6e5aed3-1527-46c8-b4d7-9be817a44f16)\n\nTiptap itself is a headless editor framework used by thousands of developers to power text editing across their apps. The headless approach gives full flexibility, but it also means you're on your own when it comes to building the UI.\n\nThat’s the problem we’re solving here: many teams don’t have time to design and build all the editor UI pieces (toolbars, menus, upload buttons, etc.) every time they want to add a new editor to their product.\n\n**So we built a solution that gives you a head start:**\n\n* A growing set of handcrafted, MIT-licensed React components\n* A CLI to scaffold your setup in seconds\n* A live editor template you can use out of the box or customize as needed\n\n![uploaded image](/media/?type=post&id=89529&key=user_uploads/1335640/76cac74a-0b69-4fa2-81af-e18f3cdbd803)\n\nEverything is fully optional and customizable. You can add just one component to your existing editor, or build your entire UI with the kit. And Tiptap remains headless at the core — these components sit on top and stay out of your way.\n\n**Backstory:** We originally built Tiptap as a tool for ourselves, and it has grown far beyond that. We’ve seen it used in everything from CRMs and email builders to collaborative docs and CMS platforms. But we also saw devs rebuilding the same UI patterns over and over. So we asked: what if we made that part easier, too?\n\n**Demo template:** <https://template.tiptap.dev/simple>\\\n**GitHub repo:** <https://github.com/ueberdosis/tiptap-ui-components>\\\n**Docs + Components Overview:** <https://tiptap.dev/docs/ui-components/getting-started/overview>\\\n**CLI:** npx @tiptap/cli init\n\nWe’re already working on more components, including some integrated with Tiptap Cloud (e.g. comments, version history).\n\n**Ask:**\n\n* Try out the components and tell us what you'd like to see next\n* Upvote our Product Hunt launch if you like what we’re building\n* Feedback, issues, and PRs are always welcome\n\nFeel free to DM us here or reach out at [founders@tiptap.dev](mailto:founders@tiptap.dev)\n\nThanks for building with us!\\\nThe Tiptap Team",
        "url": "https://www.ycombinator.com/launches/NI1-tiptap-editor-ui-components-and-templates",
        "votes": 42,
        "created_at": "2025-04-15T14:00:48.862Z"
      },
      {
        "id": 72947,
        "title": "⚫️ Tiptap – The developer toolkit for building collaborative apps",
        "tagline": "Build apps like Notion or Google Docs with Tiptap's open-source content editing and real-time collaboration suite.",
        "body": "[Tiptap](https://tiptap.dev) is a suite of open source content editing and real-time collaboration tools for developers building apps like Notion or Google Docs. It’s used by thousands of businesses worldwide, including GitLab, Axios, and Substack.\n\n![uploaded image](/media/?type=post&id=72947&key=user_uploads/1335640/87be68c6-2dfb-47a7-a6c3-90e012aa554b)\n\n🤔 **The Problem**\n\nExtensive content editing interfaces and real-time collaboration are a key feature of most apps to deliver value to their users, such as Notion, Miro, Figma, and Google Docs.\n\nWhile the users of these apps expect a best-in-class editing and collaboration experience, it's super painful and complex to develop. As developers, we can testify to this: Entire IT departments despair of these tasks.\n\n💡 **The Solution**\n\nWith Tiptap Editor, you can build apps like Notion in no time. The headless approach gives you complete freedom to build your editor experience the way you want. Tiptap Editor comes with a ton of powerful extensions to help you elevate your app beyond the ordinary. Better yet, Tiptap Editor is free and open-source.\n\nThanks to Tiptap's cloud services, you can easily add more sophisticated features like collaborative editing, real-time sync, or soon AI editor capabilities to your app in less than a minute. Tiptap's cloud services are available for fast-growing startups and as an on-premises solution for enterprises.\n\n🚀 **Who is it for?**\n\nTiptap is for developers and product teams who need to integrate rich text editors into their apps, especially those who value customization, ease of use, and real-time collaboration. Tiptap toolkits and cloud services significantly reduce development time, enabling faster time-to-market and increased profitability for product teams.\n\nTiptap is already used by **thousands of businesses worldwide,** including:\n\n![uploaded image](/media/?type=post&id=72947&key=user_uploads/1335640/619e8a25-0b5c-4174-89f0-4a4084091375)\n\nWith over 1.8 million npm downloads per month, Tiptap is one of the top 5 most popular editor frameworks in the world and is strongly supported by a huge developer community:\n\n* **26k+ community members**\n* **20k+ GitHub stars**\n* **1\\.8k forks**\n* **5k+ commits**\n* **200+ contributors**\n\n🎉 **Meet the Tiptap team**\n\nWe're six co-founders with over a decade of digital consultancy experience, transforming our struggle with building custom editor interfaces into a solution. Since launching Tiptap in 2019, we've been dedicated to scaling up and fully committed since 2022. As passionate designers and developers, we're proud to craft Tiptap's core ourselves.\n\n![uploaded image](/media/?type=post&id=72947&key=user_uploads/1335640/c49d9774-dae5-4aea-8721-650108864024)\n\n❤️ **Our ask**\n\nWe invite you to explore Tiptap's capabilities in your app, contribute to its open source development, and join our welcoming community.\n\n* Star our GitHub repository: [**https://github.com/ueberdosis/tiptap**](https://github.com/ueberdosis/tiptap)\n* Follow us on Twitter: [**https://twitter.com/tiptap_editor**](https://twitter.com/tiptap_editor)\n* and on LinkedIn: [**https://www.linkedin.com/company/tiptapdev/**](https://www.linkedin.com/company/tiptapdev/)\n\nIf you have any questions, or would like to use Tiptap in your app, write us at [**humans@tiptap.dev**](mailto:humans@tiptap.dev)\n\nYours\\\n Nick, Patrick, Philip, Sebastian, Sven and Timo ",
        "url": "https://www.ycombinator.com/launches/IyZ-tiptap-the-developer-toolkit-for-building-collaborative-apps",
        "votes": 369,
        "created_at": "2023-07-11T18:56:11.080Z"
      }
    ]
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    "id": 29103,
    "name": "Inconvo",
    "slug": "inconvo",
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/42126d50fed615bc74167d22b4985b25e9d25fad.png",
    "website": "https://inconvo.com",
    "all_locations": "Limerick, County Limerick, Ireland",
    "long_description": "Inconvo is the open-source platform for building data agents on production data. With safe queries, permissions, and structured outputs.\r\n\r\nUse Inconvo to build and deploy data agents that query production databases and can be called directly from your application. You get safe query execution, permissions, stateful conversations, and observability out of the box.",
    "one_liner": "Build chat-with-data agents for customer-facing applications",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1690946743,
    "tags": [
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      "Analytics",
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2023",
    "status": "Active",
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    "regions": [
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/inconvo",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/inconvo.json",
    "year_founded": 2023,
    "city": "Limerick",
    "country": "IE",
    "linkedin_url": "https://www.linkedin.com/company/inconvoai",
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    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": null,
    "founders": [
      {
        "user_id": 1151062,
        "full_name": "Eoghan Mulcahy",
        "title": "Founder",
        "founder_bio": "Co-founder of Inconvo ",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/eoghan-mulcahy",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7ff19867067d1703d0f567694ee725542cc8d350.jpg"
      },
      {
        "user_id": 1153587,
        "full_name": "Liam Mulcahy",
        "title": "Founder",
        "founder_bio": "Co-founder",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/liam-mulcahy-418001174",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/8dc7299a418449aab17f1a5f3571248e5e83d537.jpg"
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    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 97668,
        "title": "📶 Inconvo: Open source AI agent for customer-facing chat-with-data",
        "tagline": "The easiest way to add reliable chat-with-data to your product",
        "body": "# TLDR;\n\nInconvo helps companies add chat-with-data agents to their product. We provide a platform for configuring agent rules and directions and a simple API endpoint to call them. We’re open source — check out our repository [here](https://github.com/inconvoai/inconvo). We also offer Inconvo cloud — check it out at [app.inconvo.ai](https://app.inconvo.ai)\n\n[**https://www.youtube.com/watch?v=sbDTAbVG-WQ**](https://www.youtube.com/watch?v=sbDTAbVG-WQ)\n\n# The problem:\n\nToday, many product teams are under pressure to add “data agents” to their apps that connect to live databases and answer user questions.\n\nChat-with-data demos are easy. Shipping one to real customers is hard.\n\nMost teams start with “LLM generates SQL + prompts,” then run into three issues:\n\n* **Data safety:** you can’t reliably stop the model from pulling the wrong rows, crossing tenants, or selecting sensitive columns.\n* **Business correctness:** metric definitions, allowed filters/enums, join paths, and formats get split across prompts which can confuse the model and drift over time.\n* **Boundaries:** because the model can generate arbitrary SQL, “only allow these joins/filters/columns” becomes brittle after-the-fact validation.\n\nThe result is a second system of guardrails and checks just to make it safe to ship.\n\n### The solution:\n\nInconvo flips the approach: constrain the agent up front instead of trying to rein it in after.\n\n* **A semantic model as the contract:** define approved tables/columns, metrics, filters/enums, and join paths in one place.\n* **Constrained query plans (not SQL):** the model outputs structured query plans which are validated against your semantic model before execution.\n* **Automatic access rules:** tenant scoping and field restrictions are enforced on every request with deterministic code not prompts.\n\nYou can call your data agent from your application in just a few lines of code:\n\n![uploaded image](/media/?type=post&id=97668&key=user_uploads/1151062/a427ef4c-552e-4a7e-8675-671a08023bbf)\n\n# Our ask:\n\nCheck out our repo and leave us a ⭐ on Github: [**https://github.com/inconvoai/inconvo**](https://github.com/inconvoai/inconvo)\n\nRun Inconvo OSS locally `npx inconvo@latest dev` Or sign up to our cloud for free [**https://app.inconvo.ai**](https://app.inconvo.ai)",
        "url": "https://www.ycombinator.com/launches/PPI-inconvo-open-source-ai-agent-for-customer-facing-chat-with-data",
        "votes": 6,
        "created_at": "2026-02-10T17:40:07.857Z"
      },
      {
        "id": 94541,
        "title": "Inconvo ⚟: Build MCP servers for SaaS customers",
        "tagline": "Make your existing data ready for AI apps like ChatGPT to use — quickly and securely.",
        "body": "# **TL;DR**\n\nConnect your existing database + auth provider and launch an MCP server for your customers in a few minutes.\n\n[Watch me ship an MCP server and connect it to ChatGPT in 2.5 minutes](https://www.youtube.com/watch?v=4G41AQJZMO0)\n\n# The Problem\n\nA few days ago OpenAI announced Apps for ChatGPT — a new generation of apps you can chat with, right inside ChatGPT.\n\n**An MCP server is the foundation of every Apps SDK integration**. It exposes tools that the model can call, enforces authentication, and packages the structured data plus component HTML that the ChatGPT client renders inline.\n\nYou can build an MCP server in one of two ways:\n\nA)\n\n_Load all of your API endpoints into the MCP server as tools and have the client decide which aggregation of tools it should use to fulfil user requests._\n\nThis approach **works well if you already have a highly composable API** designed for data analysis — concretely the API expresses any combination of filters, sorts, and transformations in a structured way.\n\nHowever, most SaaS APIs are designed for record management, not data analysis or flexible retrieval. These APIs break down when presented with the wide array of potential user queries which come with a natural language input.\n\nB)\n\n_Build an AI agent attached to your database which takes in natural language and dynamically generates queries based on the input  — then attach the agent to your MCP as a tool._\n\nThis is **hard to build** because you need to handle conversation state, schema introspection, agent observability, multi-tenancy and query safety.\n\n**Luckily, with Inconvo we offer AI data agents as a service so you don’t need to worry about any of that.**\n\nOverall option B outperforms option A in power and flexibility, while eliminating the need for new API endpoints as user input cases grow.\n\n# Our Solution\n\n![uploaded image](/media/?type=post&id=94541&key=user_uploads/1151062/8f7eac8d-448f-4808-b34b-e3c7d0158a4f)\n\nWith Inconvo you can build a powerful AI agent for data analysis on top of your database and make it available to your users in your own app or the AI apps they already use like ChatGPT.\n\n### How it works\n\n1) Connect your existing database\n\n2) Link your existing authentication and set user data permissions scopes\n\n![uploaded image](/media/?type=post&id=94541&key=user_uploads/1151062/9e056431-135c-4066-b637-5f48d58cd1db)\n\n3) Launch a remote authenticated MCP server in a few clicks, which can be linked easily by your users to ChatGPT etc.\n\n![uploaded image](/media/?type=post&id=94541&key=user_uploads/1151062/0a85474a-2589-4033-afab-f8920ed79b61)\n\n### Inconvo handles the Details\n\nWe give you agent traces and logs for out of the box observability\n\n![uploaded image](/media/?type=post&id=94541&key=user_uploads/1151062/33078fb7-d7bf-43ea-9da1-bd7af1651e73)\n\nAnd a semantic layer so you can improve the data agents performance through context engineering without needing to write any extra code.\n\n![uploaded image](/media/?type=post&id=94541&key=user_uploads/1151062/19a1ea68-0999-4876-8cdb-8992d9bce1e7)\n\n\n# Ready to ship MCP servers for your customers?\n\nYou can **try inconvo today for free** by visiting [**https://inconvo.com**](https://inconvo.com) and creating an account.\n\nOr book a call: [**https://inconvo.com/demo**](https://inconvo.com/demo)",
        "url": "https://www.ycombinator.com/launches/Oar-inconvo-build-mcp-servers-for-saas-customers",
        "votes": 10,
        "created_at": "2025-10-09T21:24:28.025Z"
      },
      {
        "id": 93332,
        "title": "Inconvo: AI agents for customer-facing analytics",
        "tagline": "Build ChatGPT-style analytics into your product",
        "body": "# **TL;DR:**\n\nInconvo makes it easy to build and deploy AI analytics agents into your SaaS products, so your customers can quickly interact with their data.\n\n# **Problem**\n\nSaaS products typically offer dashboards and reports, which work for high-level metrics but are clunky for drill-downs and slow for ad-hoc questions. \n\nModern users, shaped by tools like ChatGPT, now expect a similar degree of speed and flexibility when getting insights from their data. \n\nTo meet these expectations, you need to ship an AI analytics agent, but these are painful to develop and manage.\n\n# **Solution**\n\nInconvo is a platform built from the ground up for developers building AI agents for customer-facing analytics.\n\nWe make it simple for agents to access data by connecting to SQL databases.\n\n![uploaded image](/media/?type=post&id=93332&key=user_uploads/1151062/a56e965c-a51e-42ad-b63b-a8cdae08d317)\n\nWe provide a semantic model to create a layer that governs data access and defines business logic.\n\n![uploaded image](/media/?type=post&id=93332&key=user_uploads/1151062/8f7567c1-2926-4a1d-915d-5fb52444a9a6)\n\nWe support multi tenant databases by scoping the data an agent can see to specific tenants on a conversation basis.\n\n![uploaded image](/media/?type=post&id=93332&key=user_uploads/1151062/1ddec989-a3aa-4e3e-b2dd-0cc525fdc80b)\n\nWe offer a chat playground making it easy to test agents offline.\n\n![uploaded image](/media/?type=post&id=93332&key=user_uploads/1151062/edfcd6cf-e3b6-4157-9acf-6949259e1f6b)\n\nWe expose a developer-friendly API for easy integration and conversation logs to track user interactions. For observability we show a trace for each agent response, making agent behaviour easily debuggable.\n\n![uploaded image](/media/?type=post&id=93332&key=user_uploads/1151062/bd2f2ae8-a30f-4131-bb89-eac30a0a5821)\n\nHere’s a deeper dive demo video for interested developers showing how we create and call an agent via the API in \\~5 minutes.\n\nhttps://youtu.be/4wlZL3XGWTQ\n\n# Ask\n\nIf this problem is one you face, try us out!\n\n[Book a demo](https://inconvo.com/demo) or [Sign up for free](https://auth.inconvo.ai/en/signup).\n\n![uploaded image](/media/?type=post&id=93332&key=user_uploads/1151062/14c14e6a-af3a-4ebf-a99f-79829304ec03)\n\n",
        "url": "https://www.ycombinator.com/launches/OHM-inconvo-ai-agents-for-customer-facing-analytics",
        "votes": 8,
        "created_at": "2025-08-26T14:03:59.256Z"
      },
      {
        "id": 88017,
        "title": "Inconvo: Ask-AI for customer-facing analytics",
        "tagline": "Build an AI-first analytics experience your users will obsess over.",
        "body": "# **TLDR;**\n\nInconvo **makes it easy for developers to add Ask AI for customer-facing analytics** so that users can ask questions on their data in natural language. \n\n[Watch our demo!](https://youtu.be/1kpS48ifOAY)\n\nWith Inconvo, shipping AI-first analytics is easy. Just send a user question to our API, and it will respond with a chart, table, or text.\n\n# **The Problem**\n\n**Ask-AI for customer-facing analytics should deliver on its promise of being intelligent**, capable of answering dynamic user questions and not limited to a set of basic canned prompts.\n\nBut, **building genuinely intelligent Ask-AI for customer-facing analytics is hard.**\n\nYou need…\n\n**An AI Agent** to dynamically retrieve relevant data that:\n\n* Automatically connects to your database.\n* Intelligently queries, joins, filters, and transforms data based on user questions.\n* Responds with answers in human-readable formats (text, chart, table).\n\n![uploaded image](/media/?type=post&id=88017&key=user_uploads/1151062/2afe2960-8150-4296-95e6-9c522ac7381d)\n\n**AI Evaluations** to measure you agent’s performance before and after deployment that:\n\n* Allows you to build a dataset of conversation-answer pairs for evaluation.\n* Assess your agent's ability to answer these evaluation pairs.\n\n![uploaded image](/media/?type=post&id=88017&key=user_uploads/1151062/0dec4f67-821f-46b1-af8a-bad3d9896a5a)\n\n**A Semantic Layer** to ensure accurate data retrieval that:\n\n* Maps user terminology to database field names.\n* Facilitates the creation of computed fields and alternative field labels.\n\n**Data Access Control** to restrict your AI agent’s database access that:\n\n* Allows you to turn off access to whole tables or individual columns.\n* Allows you to set if a table can be queried directly or only joined into.\n\n![uploaded image](/media/?type=post&id=88017&key=user_uploads/1151062/1b92ea04-f968-4ecb-b419-9495ae2b328b)\n\n**Multi-tenancy support to** ensure results are scoped to the requestor’s access that is:\n\n* Configurable on a per-request basis.\n* Defined by you based on your existing data structures.\n\n# **Our Solution**\n\n**Inconvo provides a single API call to power genuinely intelligent Ask AI for customer-facing analytics.**\n\n![uploaded image](/media/?type=post&id=88017&key=user_uploads/1151062/50ba0c22-7d2e-4ff4-bd4f-8ff457adb212)\n\nBehind [this API call](https://inconvo.ai/docs/api-reference/ask), Inconvo handles all the hard problems of Ask AI for customer-facing analytics.\n\n[Inconvo connects to your database](https://inconvo.ai/docs/guides/connect/) to automatically retrieve the right data to answer your users’ questions. Then, you’re in charge of presenting the API responses to your users in a way that fits your design.\n\n![uploaded image](/media/?type=post&id=88017&key=user_uploads/1151062/d9f04fae-8c25-4146-b940-f012a65b890c)\n\n**Inconvo is purpose-built to overcome the challenges of Ask-AI for customer-facing analytics**, providing tools that handle multi-tenancy, database access control, [AI evaluation](https://inconvo.ai/docs/guides/evaluate/), and a semantic layer.\n\n# **Our Asks**\n\n**Share** - talk to your friends and colleagues about Inconvo.\n\n**Connect** - ping [eoghan@inconvo.ai](mailto:eoghan@inconvo.ai) if you want to chat more or make an intro.\n\n**Engage** - [book a demo call](https://inconvo.ai/request-demo).",
        "url": "https://www.ycombinator.com/launches/Mtd-inconvo-ask-ai-for-customer-facing-analytics",
        "votes": 39,
        "created_at": "2025-02-25T17:26:15.958Z"
      }
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    "id": 29104,
    "name": "Shadeform",
    "slug": "shadeform",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7a846e62f95a076c15722c84a203afd1fccb34a5.png",
    "website": "https://www.shadeform.ai/",
    "all_locations": "",
    "long_description": "Teams struggling with GPU availability use our platform to unlock capacity immediately for their growing AI workloads. Shadeform has a unified, easy-to-use API and platform to access and provision GPUs and deploy models for inference to any provider. With our aggregated availability and pricing data, we can help ensure your on-demand inference and training jobs will run on time at optimal cost.",
    "one_liner": "The GPU Cloud Marketplace",
    "team_size": 11,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1689812081,
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    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2023",
    "status": "Active",
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    "regions": [
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    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/shadeform",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/shadeform.json",
    "year_founded": 2023,
    "city": null,
    "country": null,
    "linkedin_url": "https://www.linkedin.com/company/shadeformai/",
    "x_url": "https://twitter.com/shadeformai",
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    "github_url": "https://github.com/shadeform",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/7a846e62f95a076c15722c84a203afd1fccb34a5.png",
    "app_video_url": null,
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    "company_photos": [],
    "primary_partner": {
      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
    },
    "founders": [
      {
        "user_id": 1212177,
        "full_name": "Ed Goode",
        "title": "Founder",
        "founder_bio": "CEO @ Shadeform. SWE with experience building distributed systems, compute orchestrators, and NLU & NLP services. Building a single control plane for the GPU market.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/ed-goode",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/fcb96378f379623f478f11ea6d2f3be3b3c68990.jpg"
      },
      {
        "user_id": 430762,
        "full_name": "Ronald Ding",
        "title": "Founder",
        "founder_bio": "CTO @ Shadeform. Former engineer and TL at Robinhood, AWS, and Microsoft working on large scale, distributed infrastructure.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/ronaldding",
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        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1deaec552b7f744f94d76b79ae296d69016a5577.jpg"
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    "jobs": [
      {
        "id": 74148,
        "title": "Founding Sales",
        "url": "https://www.ycombinator.com/companies/shadeform/jobs/ZBDwwU6-founding-sales",
        "location": "San Francisco, CA, US / Remote (US)",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$125K - $300K",
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        "title": "Founding (Senior) Software Engineer",
        "url": "https://www.ycombinator.com/companies/shadeform/jobs/2sDkjnk-founding-senior-software-engineer",
        "location": "San Francisco, CA, US / Remote (US)",
        "type": "Full-time",
        "role": "Engineering",
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        "title": "Chief of Staff & Automation Lead",
        "url": "https://www.ycombinator.com/companies/shadeform/jobs/u71t9AV-chief-of-staff-automation-lead",
        "location": "San Francisco, CA, US / Remote (US)",
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      {
        "id": 73251,
        "title": "Shadeform: Unifying ML infra across clouds - solving for the GPU shortage",
        "tagline": "When companies need GPUs, they use Shadeform to access and deploy their workloads to any GPU provider with our unified compute platform and APIs.",
        "body": "**TLDR:** Teams struggling with GPU availability use Shadeform to **unlock capacity immediately for their growing AI workloads**. Shadeform has a unified, easy-to-use API and platform to access and deploy GPU workloads to any provider. With our aggregated availability and pricing data, we can guarantee inference and training jobs will run on time at optimal cost.\n\n## **The Team**:\n\nWe are Ronald, Ed, and Zach (pictured in order)! We have built and operated critical cloud infrastructure services at AWS and Azure and know the pain of infra management as customers at Robinhood and Capital One. Our goal is to make multi-cloud ML infra simple and easy to use.\n\n![uploaded image](/media/?type=post&id=73251&key=user_uploads/1212177/989a4bdc-3ed1-4937-a76b-9e7f41496b3d)\n\n## **The Problem**: GPU Cloud Availability Shortage\n\n* **Explosion in ML training and inference** demands has resulted in massive GPU shortages; it's difficult and expensive to get GPUs on AWS, GCP, and Azure\n* **Smaller cloud providers are coming online** but have unstable capacity, disparate interfaces, and non-standard OS images preventing companies from adopting at scale\n\n## **The Solution**: Unified Platform for All GPU Providers\n\nShadeform allows you to deploy your inference and training jobs to any cloud provider. We have aggregated all providers, so you can launch your workloads anywhere with our platform and generalized APIs.\\\nWith Shadeform you can:\n\n* Manage GPU instances on every provider with a single control plane\n* Receive notifications, view pricing, and configure auto-reservations when the machines you need are available\n* One click deploy and SSH into machines with any provider\n* Use a unified, simple API\n\n### Deploy Anywhere\n\n![uploaded image](/media/?type=post&id=73251&key=user_uploads/1212177/d4dcc424-a5d6-4583-a5c4-b0d83aa51d71)\n\n### Notify and Auto-Reserve\n\n![uploaded image](/media/?type=post&id=73251&key=user_uploads/1212177/771abd62-79ff-477f-8f69-edd5da8ce8ed)\n\n## **The Goal**: Unify ML Infra Across Clouds\n\nWe are building towards a future where teams are never blocked by their current provider’s GPU capacity and features.\n\n## **The Ask**: Reach out today to access our platform: <https://shadeform.ai>\n\nWe’d love to integrate you with all GPU providers and provide you access to the machines you need, when you need them! Contact us at [founders@shadeform.ai](mailto:founders@shadeform.ai).",
        "url": "https://www.ycombinator.com/launches/J3T-shadeform-unifying-ml-infra-across-clouds-solving-for-the-gpu-shortage",
        "votes": 92,
        "created_at": "2023-07-20T02:31:18.973Z"
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    "id": 29105,
    "name": "FlowiseAI",
    "slug": "flowiseai",
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    "website": "https://flowiseai.com",
    "all_locations": "Remote",
    "long_description": "Flowise uses low-code approach that enable developers to manage the whole lifecycle of building LLMs apps in production. From protoyping, evaluation, to iterations.",
    "one_liner": "Open source GenAI development platform",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1688552847,
    "tags": [
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      "Generative AI",
      "Open Source",
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    "batch": "Summer 2023",
    "status": "Acquired",
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    "regions": [
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      "Fully Remote"
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    "stage": "Early",
    "app_video_public": false,
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    "question_answers": [
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        "question": "How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)",
        "answer": "Back in Feb 2023, we've been building apps using open source frameworks like LangChain, HuggingFace, etc.We wanted a quicker way to build prototype without having to write repetitive code. We also want a better visualization of the whole LLM flow.Hence, the idea of Flowise was born."
      },
      {
        "question": "What is the core problem you are solving? Why is this a big problem? What made you decide to work on it?",
        "answer": "Recent advancement of large language models like ChatGPT is revolutionizing every industry. But how do people from less tech-savvy background be able to learn it, and use it for their own use cases?This is why we made Flowise just like LEGO[🧩](https://emojipedia.org/puzzle-piece/). Flowise let you connect different components like PDF loader, OpenAI Embeddings, Pinecone vector database and build your own ChatGPT on your own documents, without any code. You learn at the same time as you build!"
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    "url": "https://www.ycombinator.com/companies/flowiseai",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/flowiseai.json",
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      "url": "https://www.ycombinator.com/people/harj-taggar"
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    "founders": [
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        "full_name": "Henry Heng",
        "title": "Founder",
        "founder_bio": "Cofounder of Flowise. Ex-software engineer @FidelityInvestment",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/zhenjing-heng-henry",
        "x_url": "https://twitter.com/henryhengzj",
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        "user_id": 1393783,
        "full_name": "Chung Yau Ong",
        "title": "Founder",
        "founder_bio": "Cofounder of Flowise.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/chung-yau-ong-1407701a9",
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    ],
    "jobs": [],
    "news": [
      {
        "title": "Open100: Top 100 Open Source achievements",
        "url": "https://www.benchcouncil.org/evaluation/opencs/annual.html#Achievements",
        "date": "Nov 01, 2023"
      },
      {
        "title": "Top trending early-stage open-source startups by GitHub star growth in Q3 2023 - Runa Capital",
        "url": "https://runacap.com/ross-index/q3-23/",
        "date": "Nov 01, 2023"
      },
      {
        "title": "GenOs Index - The June Edition: 5 Emerging Trends among Generative AI Open Source Projects - Decibel",
        "url": "https://www.decibel.vc/articles/genos-index-the-june-edition-5-emerging-trends-among-generative-ai-open-source-projects",
        "date": "Jun 14, 2023"
      }
    ],
    "launches": [
      {
        "id": 90360,
        "title": "Flowise 3.0 - Build AI Agents, Visually",
        "tagline": "Build any agentic system from just an idea",
        "body": "# Flowise 3.0\n\nhttps://youtu.be/-h4WQuzRHhI\n\nFor the first time, anyone can build AI agents from just an idea. Simply describe what you want to create, and a draft will be generated for you.\n\nFlowise provides modular building blocks for you to build any agentic systems, from simple compositional workflows to autonomous agents. Some common patterns are:\n\n* Chaining\n* Routing\n* Parallelization\n* Hierarchy\n* Looping\n* Iteration\n\n![uploaded image](/media/?type=post&id=90360&key=user_uploads/1358352/68095851-704f-4f14-b1cf-dfcfc56b4009)\n\nEach LLM/Agent has the following augmentations to enable flexible multi agents architecture:\n\n* Memory\n* Retrieval(RAG)\n* Tool\n* Centralized State\n* Structured Output\n\n🙋‍♂️ **Human in the Loop**:\n\nThis is a core aspect of an agentic system, allowing humans to review tasks performed by agents, or to approve/reject tool calls by agents. For example, reviewing actions before sending an email or booking an appointment.\n\n![uploaded image](/media/?type=post&id=90360&key=user_uploads/1358352/a08091a2-93cb-493f-858e-a851bcd3d12d)\n\n📝 **Form Input**:\n\nIn addition to the standard chat interface, workflows can also be triggered through a form-based interface. This is ideal for workflows that don't require back-and-forth communication between the user and agents.\n\n![uploaded image](/media/?type=post&id=90360&key=user_uploads/1358352/bba6f3b4-3d95-4699-bcdc-b6c2485f1fa2)\n\n🔍 **Observability**:\n\nGain full visibility into execution traces to debug issues and optimize performance. You can share traces publicly, allowing others to review, approve, or provide feedback.\n\n![uploaded image](/media/?type=post&id=90360&key=user_uploads/1358352/4e8ed542-c2f8-424c-8ef2-0c60c059199a)\n\n✅ **Flow Validation**:\n\nDesigning complex workflows can be challenging. Flow validation helps minimize misconfigurations and human errors by automatically checking for common issues.\n\n![uploaded image](/media/?type=post&id=90360&key=user_uploads/1358352/80943e44-97d6-4012-ae6e-407bde108b9d)\n\n# Try it out\n\nEverything is open source, give a star on our [Github](https://github.com/FlowiseAI/Flowise) repo ✨\n\n```\n$npm install -g flowise\n$npx flowise start\n```\n\nOr try it out for free on [Flowise Cloud](https://cloud.flowiseai.com) ☁️\n\n![uploaded image](/media/?type=post&id=90360&key=user_uploads/1358352/f366ab3a-a6c9-47ba-807c-bf94d8122e76)\n\nFlowise is used by Fortune 500 companies such as Thermo Fisher, Deloitte, Accenture, AWS, and many others. We are continuously pushing the frontier of generative AI development platform.",
        "url": "https://www.ycombinator.com/launches/NVQ-flowise-3-0-build-ai-agents-visually",
        "votes": 18,
        "created_at": "2025-05-13T18:37:51.183Z"
      },
      {
        "id": 72776,
        "title": "Flowise - Low-code LLM apps builder",
        "tagline": "An open source drag & drop tool to build your customized LLM flow",
        "body": "### **☕️TL;DR**\n\n[**Flowise**](https://flowiseai.com/) **is an open source drag & drop tool to build your customized LLM flow.**\n\n**We provide a visual interface to let you build backends for LLM apps used for QnA, summarization and analysis on your own data.**\n\n![uploaded image](/media/?type=post&id=72776&key=user_uploads/1358352/f29f7b92-9f41-4257-b293-046eb46d9b84)\n\n👋 This is [Henry](https://www.linkedin.com/in/zhenjing-heng-henry/) and [Yau](https://www.linkedin.com/in/chung-yau-ong-1407701a9/), co-founders of Flowise. We’re on a mission to make it easy for people with no-code background to learn and build AI apps.\n\n### **🤔 Problem**\n\nRecent advancement of large language models like ChatGPT is revolutionizing every industry. But how do people from less tech-savvy background be able to learn it, and use it for their own use cases?\n\n### **✨ Solution**\n\nJust like LEGO[🧩](https://emojipedia.org/puzzle-piece/), Flowise let you connect different components like PDF loader, OpenAI Embeddings, Pinecone vector database and build your own ChatGPT on your own documents. You learn as you build!\n\n### **⚙️ How it works**\n\n**Chatflow**\n\nDrag & drop any component to the canvas and interact with it in real-time.\n\n![uploaded image](/media/?type=post&id=72776&key=user_uploads/1358352/064c1f3e-83c2-489f-a115-b7efdd74289f)\n\n**API/Embed**\n\nUse the flow as an API or embed into your application.\n\n![uploaded image](/media/?type=post&id=72776&key=user_uploads/1358352/4c5d5d78-eedd-48b0-91cf-e0c7fa1bac53)\n\n**Tool**\n\nCreate your own tool and let agent automatically use it. For instance, get stock prices and add it to Airtable/Gsheets.\n\n![uploaded image](/media/?type=post&id=72776&key=user_uploads/1358352/558cf99b-b199-48d9-a0fa-d1500a30ec7d)\n\n**Extensible**\n\nFlowise is built to be extensible. Developers can easily customize their integrations by using libraries/frameworks such as LangChain, LlamaIndex, HuggingFace, etc.\n\n### **🙏Ask**\n\n* Star Flowise [Github](https://github.com/FlowiseAI/Flowise) and let us know what you’d like us to build next\n* Follow us on [Twitter](https://twitter.com/FlowiseAI) to keep up with the latest updates\n* Hop into our 2k+ [Discord](https://discord.com/invite/jbaHfsRVBW) community\n* We want to offer cloud-hosted solution, let us know your [thoughts](https://fmhvbn0ukuf.typeform.com/to/Zn6A7fb4)!\n\n[🚩](https://emojipedia.org/triangular-flag/) We just crossed **10k** stars on Github!\n\n![uploaded image](/media/?type=post&id=72776&key=user_uploads/1358352/7719ac4f-6699-4cdf-8d52-9ff7c63a596d)\n\n",
        "url": "https://www.ycombinator.com/launches/Ivo-flowise-low-code-llm-apps-builder",
        "votes": 70,
        "created_at": "2023-07-05T16:02:36.118Z"
      }
    ]
  },
  {
    "id": 29108,
    "name": "Giga",
    "slug": "giga",
    "former_names": [
      "Giga",
      "Giga ML"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fb8d37a891f8bcff52ba067cc273aab648732435.png",
    "website": "https://giga.ai/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "",
    "one_liner": "AI Support Agent for Enterprises.",
    "team_size": 30,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1689858919,
    "tags": [
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2023",
    "status": "Active",
    "industries": [
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      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Growth",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/giga",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/giga.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://linkedin.com/company/giga-ai",
    "x_url": "https://twitter.com/gigaml",
    "fb_url": null,
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    "github_url": null,
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    "app_video_url": null,
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    "primary_partner": {
      "name": "Harj Taggar",
      "url": "https://www.ycombinator.com/people/harj-taggar"
    },
    "founders": [
      {
        "user_id": 1381270,
        "full_name": "Esha Dinne",
        "title": "Founder",
        "founder_bio": "Hi, I'm Esha, I am currently CTO of Giga ML and an IIT Kharagpur CS'23 grad, where I ranked 3rd institute-wide. Before Giga ML, I was a systems engineer intern at Quadeye Securities and led the Math Club at IIT. Off work, I watch anime and read novels.\n",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/esha-manideep-ba112a218",
        "x_url": "https://twitter.com/eshamanideep",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7a266232fda36f51f279943fe4fcaab81729b7e5.jpg"
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    ],
    "jobs": [
      {
        "id": 76266,
        "title": "Senior Technical Recruiter",
        "url": "https://www.ycombinator.com/companies/giga/jobs/LyWOqTx-senior-technical-recruiter",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Recruiting & HR",
        "role_type": "Recruiting lead",
        "salary_range": "$150K - $220K",
        "equity_range": "",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 80630,
        "title": "Software Engineer I / II - San Francisco",
        "url": "https://www.ycombinator.com/companies/giga/jobs/GAVxgkS-software-engineer-i-ii-san-francisco",
        "location": "San Francisco",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$150K - $250K",
        "equity_range": "",
        "experience": "3+ years",
        "visa": "Will sponsor",
        "skills": []
      },
      {
        "id": 88394,
        "title": "Staff Backend Engineer",
        "url": "https://www.ycombinator.com/companies/giga/jobs/q2UE9JO-staff-backend-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Backend",
        "salary_range": "$180K - $500K",
        "equity_range": "",
        "experience": "6+ years",
        "visa": "Will sponsor",
        "skills": [
          "Amazon Web Services (AWS)",
          "Django",
          "Kubernetes",
          "Python"
        ]
      },
      {
        "id": 90083,
        "title": "Head of Product Marketing/Founding Growth Marketing",
        "url": "https://www.ycombinator.com/companies/giga/jobs/6TVJ2wZ-head-of-product-marketing-founding-growth-marketing",
        "location": "San Francisco",
        "type": "Full-time",
        "role": "Marketing",
        "role_type": null,
        "salary_range": "$150K - $325K",
        "equity_range": "",
        "experience": "6+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 91597,
        "title": "HR Generalist / People Operations",
        "url": "https://www.ycombinator.com/companies/giga/jobs/enhDXgk-hr-generalist-people-operations",
        "location": "San Francisco",
        "type": "Full-time",
        "role": "Operations",
        "role_type": null,
        "salary_range": "$140K - $185K",
        "equity_range": "",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      }
    ],
    "news": [
      {
        "title": "Giga: The AI Platform for Enterprise Support",
        "url": "https://www.youtube.com/watch?v=KmdN6OQ_PwE",
        "date": "Nov 06, 2025"
      },
      {
        "title": "Giga raises $61 million to expand enterprise voice AI, starting with DoorDash | Fortune",
        "url": "https://fortune.com/2025/11/05/voice-ai-giga-raise-61-million-customer-service-series-a",
        "date": "Nov 05, 2025"
      },
      {
        "title": "GigaML Raises $3.6M To Help Enterprises Build LLMs As Powerful As GPT4 | Entrepreneur",
        "url": "https://www.entrepreneur.com/en-in/news-and-trends/gigaml-raises-36m-to-help-enterprises-build-llms-as/464095",
        "date": "Oct 23, 2023"
      }
    ],
    "launches": [
      {
        "id": 74294,
        "title": "Giga ML's X1 Large 32k - The most powerful on-prem deployable model",
        "tagline": "Customized LLMs for Industry-specific needs. On-premise & secure.",
        "body": "We are announcing our first lineup of on-premise LLMs, X1 Large 8k, 32k — pre-trained and fine-tuned versions of llama2 70B, which are outperforming Claude 2 on the MT bench with a score of 8.1 vs 8. (White paper coming soon with performance on all the benchmarks.)\\\n\\\nX1 Large is available for further fine-tuning and pre-training. Try it out [here](https://chat.gigaml.com/) and let us know what you think!\n\n![uploaded image](/media/?type=post&id=74294&key=user_uploads/1381270/388aa2d4-9000-4e2a-97fe-5720c057c9b3)\n\n**The problems today:**\n\n1. **Pre-training:** Existing large language models (LLMs) lack the ability to pre-train on specific text data, hindering their effectiveness in specialized domains like healthcare, legal, and finance.\n2. **Fine-tuning:** The inability to fine-tune LLMs for specific output structures or forms restricts their adaptability in critical areas requiring tailored responses.\n3. **Privacy:** Organizations dealing with sensitive customer data face trust & compliance challenges when using third-party servers like OpenAI and Anthropic.\n\n**X1 Large:**\n\n* **Performance:** Achieves an MT bench score of 8.1, surpassing Claude 2 after fine-tuning and pre-training.\n* **Customization:** Our unique pre-training and fine-tuning capabilities provide unrivaled performance for industry-specific use cases.\n* **Security:** Offers secure on-premise deployment, ensuring data privacy for enterprises.\n* **State of the art RAG:** We’re partnering with [@Mano AI](https://usemano.com) to bring state of art RAG for on-prem deployment on your petabytes of data.\n\n**Our ask:**\n\nTry out out the demo [here](https://chat.gigaml.com/) with your prompt and let us know how it performed! Email us at [founders@gigaml.com](mailto:founders@gigaml.com) if you want fine-tuning and pre-training access in-cloud or on-premise.\n\n**_Coming soon:_**\n\nX1 Large Med: Continuing pre training on Medical data.\n\nX1 Large Law: Continuing pre training on entire law data base of all the countries.",
        "url": "https://www.ycombinator.com/launches/JKI-giga-ml-s-x1-large-32k-the-most-powerful-on-prem-deployable-model",
        "votes": 15,
        "created_at": "2023-08-22T01:51:37.233Z"
      },
      {
        "id": 73286,
        "title": "Giga ML: Secure on-premise LLMs for enterprises",
        "tagline": "We supercharge open-source LLMs to outperform GPT-4 for your use case.",
        "body": "**TL;DR🔖:** Giga ML is a platform to fine-tune and deploy open-source Large Language Models (LLMs) with features such as high-speed inference, secure on-premise deployment, and OpenAI API compatibility. Our platform provides a 70% cost reduction compared to GPT-4 API, 300% faster output delivery, and fine-tuning expertise garnered from 300+ experiments. We're inviting you to compare our fine-tuned model, X1 Chat, with Chat GPT at [**gigaml.co**](http://gigaml.co) and discover the benefits of custom fine-tuned models. Below is a screenshot of a very basic comparison:\n\n![uploaded image](/media/?type=post&id=73286&key=user_uploads/578920/25fd4cab-2c63-4130-8729-003e5110657c)\n\nHi there, we're [**@Esha Manideep Dinne**](https://www.linkedin.com/in/esha-manideep-ba112a218/) and [**@Varun Vummadi**](https://www.linkedin.com/in/varunvummadi/), co-founders of Giga ML! Today, we're excited to introduce our fine-tuning and deployment platform designed specifically for open-source Large Language Models (LLMs).\n\n**The Problem:🔍**\n\nDeploying and experimenting with open-source LLMs, such as the MPT and Llama models, is fraught with challenges. From the difficulty of fine-tuning for optimal performance to navigating intricate hyper parameters, the process is far from straightforward. On top of these technical hurdles, there's also the issue of privacy: data being processed on external servers like OpenAI's can lead to customers slipping through your fingers.\n\n**The Need:💡**\n\nCompanies require a robust and efficient way to fine-tune and deploy their models without compromising on speed, cost, or privacy. They also need to be able to support varying context lengths depending on their use case. Plus, in light of Ben Fishman's recent tech talk where he revealed that fine-tuned models perform better than GPT-4 for some companies, there's a clear demand for effective fine-tuning solutions.\n\n**The Solution:🚀**\n\nEnter Giga ML - the platform designed to take the stress out of fine-tuning and deploying LLMs. We've run over 300 experiments to perfect our process, and here's how we're tackling these issues:\n\n1️⃣ **Fine-tuning**: We've cracked the code to efficient model fine-tuning and are ready to share our expertise with you!\n\n2️⃣ **High-Speed Inference**: Experience faster responses with our solutions that deliver output tokens 300% faster than the GPT-4 API.\n\n3️⃣ **Privacy**: We offer secure on-prem deployments so your fine-tuned data can be processed on-premise, maintaining your clients' trust.\n\n4️⃣ **Cost Savings💰**: Spend 70% less compared to using the GPT-4 API with an 8k prompt. We support 4k, 8k, and 16k context lengths depending on your use case.\n\n5️⃣ **OpenAI API Compatibility**: No need to rewrite your code, our API integrates seamlessly with OpenAI's.\n\n**Our Request:🙏**\n\nWe're asking you to give Giga ML a try. Compare the performance of Chat GPT with our fine-tuned model, X1-Chat, at \\[[**gigaml.co**](http://gigaml.co)\\]. If you're struggling with the cost or privacy issues of GPT-4 or facing challenges with large prompts, we might just be the solution you're looking for! Please Fill this form for access [Google form](https://forms.gle/EnH3V9Z4JDfZuJQt5) \\\n\\\n**The Team:** 🤝\n\n[**@Esha Manideep**](https://www.linkedin.com/in/esha-manideep-ba112a218/) and I met each other in freshman year at IIT Kharagpur, and we just graduated college. I left my PhD offer at Stanford in CS and Esha left his job as a Systems Engineer at a High Frequency Trading Firm to work on Giga.\n\nLooking forward to serving your AI needs,\n\nEsha and Varun",
        "url": "https://www.ycombinator.com/launches/J42-giga-ml-secure-on-premise-llms-for-enterprises",
        "votes": 38,
        "created_at": "2023-07-21T15:08:18.913Z"
      }
    ]
  },
  {
    "id": 29118,
    "name": "Structured Labs",
    "slug": "structured-labs",
    "former_names": [
      "Structured",
      "Structured Labs",
      "Preswald",
      "Structured Labs",
      "Wadium",
      "Waldium"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e8dd08fd61491d9efffabb3dff787320791e2421.png",
    "website": "https://www.structuredlabs.com/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Waldium is an AI-driven platform for researching, writing, and publishing technical knowledge in formats that both humans and AIs can understand. We help developers create technical guides, resources and tutorials — structured, durable knowledge that AIs can learn from, cite, and build upon.",
    "one_liner": "The publishing layer for the agentic internet",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1686619959,
    "tags": [
      "Developer Tools",
      "Search",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2023",
    "status": "Inactive",
    "industries": [
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      "Engineering, Product and Design"
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    "regions": [
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      "America / Canada",
      "Remote",
      "Partly Remote"
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    "stage": "Early",
    "app_video_public": false,
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    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/structuredlabs/",
    "x_url": "https://x.com/waldium",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/structured-labs",
    "github_url": "https://github.com/StructuredLabs",
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    "primary_partner": {
      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
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    "founders": [
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        "user_id": 1194855,
        "full_name": "Amrutha Gujjar",
        "title": "Founder",
        "founder_bio": "Structured",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/amruthagujjar/",
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        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/94a9bf7fb1763cd598927323dbc16a60f0d7ad98.jpg"
      },
      {
        "user_id": 281458,
        "full_name": "Shivam Singhal",
        "title": "Founder",
        "founder_bio": "data infrastructure",
        "is_active": false,
        "linkedin_url": "https://linkedin.com/in/shivam-singhal",
        "x_url": "https://twitter.com/singhals_",
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    "news": [],
    "launches": [
      {
        "id": 83717,
        "title": "📈 Structured - Single source of truth for key business metrics",
        "tagline": "Unify your growth and data teams with consistent metrics, automated documentation, and real-time alerts, all synced directly from your data warehouse and dbt.",
        "body": "### **The Problem: Inconsistent Metrics, Misaligned Decisions**\n\nIn the high-pressure world of growth and revenue, teams live or die by their data. Yet, too often, the very metrics that should guide decisions are inconsistent, poorly documented, or misunderstood across different teams. \n\nImagine this: Your team is preparing for an important strategy meeting. They need to assess the impact of a new onboarding feature on user activation. Marketing has one definition of \"activation,\" product has another, and sales uses a completely different set of metrics. Each team pulls data from the same warehouse – but interprets it differently, leading to conflicting reports and a confused leadership team. The result? This misalignment creates chaos, leading to conflicting reports, wasted resources, and missed revenue. Hours are wasted on reconciling data discrepancies instead of focusing on strategy, and missed opportunities to act on accurate insights.\n\nBut what if you could ensure that every team in your organization was always on the same page, with a single, accurate source of truth for all key metrics? What if your data was automatically documented, changes tracked, and alerts sent out when something significant changes? Enter Structured.\n\n![uploaded image](/media/?type=post&id=83717&key=user_uploads/1194855/8a5a8ddb-49b1-4d41-82f6-12ec24c16154)\n\n### **The Solution: Structured Brings Clarity and Consistency**\n\nStructured is designed to solve this exact problem. By integrating directly with your data warehouse (e.g., Snowflake, BigQuery) and your transformation tools (e.g., dbt), Structured automatically catalogs your data’s metadata and ensures that all metrics are consistently defined and documented across your organization.\n\n1. **Connect Your Data Warehouse and dbt:**\n   * Structured connects directly to your data warehouse—whether it’s Snowflake, BigQuery, Databricks, or Redshift—and integrates with dbt, the tool your data engineers already use to model and transform data.\n   * The moment you connect, Structured starts cataloging your data, tracking every table, column, and transformation automatically.\n2. **Auto-Generated Data Catalog and Documentation:**\n   * Structured automatically generates a comprehensive data catalog, documenting every metric, entity, and relationship. AND—this documentation is instantly synced to Notion, a tool your business teams already know and love.\n   * Now, whether you’re a data engineer or a revops analyst, you can easily access and understand how metrics are defined and where the data comes from. No more guessing, no more miscommunication—just clarity\n3. **Summaries of Changes and Version History:**\n   * Structured tracks every change made to your data models and metrics, automatically generating summaries that are easy to understand, even for non-technical users.\n   * Every change is logged with version history, so you can see exactly how metrics have evolved over time. This means no more confusion over which version of a report to trust—everyone is working from the latest, most accurate data.\n4. **Alerting on Metric Changes:**\n   * Structured’s AI doesn’t just catalog your data—it monitors it over time. If a critical metric changes—say, your churn rate spikes or a key transformation in dbt is modified—Structured sends out alerts to the relevant teams to see what’s up\n   * These alerts are designed to be easily understood by business users so everyone knows what’s happening and why it matters. This means faster, more informed decisions and no surprises in your strategy meetings.\n\n![uploaded image](/media/?type=post&id=83717&key=user_uploads/1194855/aeb49c87-18e9-4860-9bcb-04a54f96569b)\n\n### **ROI: Real Results from Day One**\n\nStructured delivers measurable value by:\n\n* **50% Faster Reporting:** Teams can generate accurate reports in half the time, thanks to consistent, pre-documented metrics that are automatically synced to tools like Notion.\n* **20% Reduction in Data Errors:** Structured reduces the risk of data discrepancies with automated metadata management and version tracking, ensuring that your reports are always based on the most accurate and up-to-date information.\n* **30% Lower Operational Costs:** By automating the documentation and alignment of data, Structured reduces the manual effort required from your data teams, freeing them to focus on more strategic tasks.\n\n![uploaded image](/media/?type=post&id=83717&key=user_uploads/1194855/9751d79d-6c81-46c3-adb8-c9156653f0d6)\n\n### **Get Started Today!**\n\nStructured is here to help your teams make better decisions, faster. Visit [structuredlabs.com](http://structuredlabs.com) or reach out to Amrutha Gujjar: [amrutha@structuredlabs.com](mailto:amrutha@structuredlabs.com) to schedule a demo and see how Structured can help!",
        "url": "https://www.ycombinator.com/launches/LmH-structured-single-source-of-truth-for-key-business-metrics",
        "votes": 125,
        "created_at": "2024-09-03T20:34:12.116Z"
      },
      {
        "id": 73623,
        "title": "⭐ Structured - Semantic layer for reliable business metrics",
        "tagline": "Consistent metrics, trusted data, faster decisions, and clear growth outcomes.",
        "body": "Hello YC! We are Amrutha Gujjar and Shivam Singhal, the founders of Structured.\n\nWe’re excited to introduce **Structured**—a platform that helps businesses easily define, manage, and scale their most critical business metrics using a robust semantic layer.\n\n### **The Problem**\n\nIn today’s data-driven world, businesses are increasingly relying on metrics to guide decision-making. However, we’ve seen countless organizations struggle with the inconsistency and complexity of defining and managing these metrics. Whether it’s “Revenue,” “Customer Acquisition Cost,” or “Churn Rate,” different teams within the same company often use different definitions, leading to misaligned decisions, wasted resources, and a lack of trust in the data.\n\nTraditional BI tools fall short when it comes to ensuring that metrics are computed consistently across an organization. This problem is particularly acute in companies with large, complex datasets stored in cloud data warehouses like Google BigQuery. Maintaining consistency and governance over these metrics typically requires significant manual effort, deep technical expertise, and can lead to errors that compromise decision-making.\n\n### **Scenario**\n\nAs the VP of Data at a rapidly scaling SaaS company, you're responsible for ensuring that the metrics used across the organization are accurate, consistent, and aligned. But despite your best efforts, discrepancies in critical metrics like Customer Acquisition Cost (CAC) and Monthly Recurring Revenue (MRR) continue to create challenges.\n\nFor example, your Marketing team reports a CAC of $130, calculated using data from HubSpot and Salesforce, where they focus on ad spend and campaign costs. They’re eager to demonstrate the efficiency of their campaigns, so they exclude overhead costs to present a leaner figure.\n\nOn the other hand, your Finance team calculates CAC at $210, pulling from NetSuite and incorporating a broader range of costs, including overhead and allocated expenses. Their approach is to capture the full financial impact, ensuring that nothing is overlooked.\n\nMeanwhile, the Product team is responsible for tracking MRR, using data from Stripe. However, they include one-off setup fees in their MRR calculations, inflating the recurring revenue figure. When they report MRR as $1.2 million, you know the true recurring revenue is closer to $1 million when those fees are excluded.\n\nThese conflicting numbers lead to confusion and frustration at the executive level. The CEO asks for the real CAC and MRR to inform key strategic decisions, but the data from different teams doesn’t match up. You find yourself mediating between departments, trying to align definitions, and reconciling these differences. Your data team spends hours pulling reports, adjusting metrics, and validating numbers, just to arrive at a single source of truth.\n\nThis process isn’t just time-consuming; it’s draining your team’s resources and slowing down the decision-making process. The ongoing discrepancies and the manual effort required to resolve them create friction across departments, eroding trust in the data and undermining the confidence of the executive team in making data-driven decisions.\n\n### **The Solution**\n\n**Structured** is a powerful semantic layer that integrates directly with cloud data warehouses like Google BigQuery.\n\n* **Onboarding and Setup**:\n  * Your data team connects Structured to your Google BigQuery warehouse in one-click. \n  * **Define Standard Metrics**: Access a library of pre-built metric templates or create custom metrics tailored to your specific business needs. \n    * _Example_: Using Structured’s library, you define CAC and MRR with input from finance, marketing, and product. Everyone agrees on what costs are included in CAC and how MRR should be calculated.\n    * Structured makes sure that these definitions are consistently applied across your organization.\n\n![uploaded image](/media/?type=post&id=73623&key=user_uploads/1194855/fe1a81fd-f235-4e41-9395-daeefe0b3daa)\n\n* **Governance and Control**:\n  * You assign ownership of these metrics to the finance team, but allow other departments to view and suggest changes. Structured’s version control means every change is tracked, so you can always revert if necessary.\n  * Now, all departments are using the same metrics. When the CEO asks for the latest CAC and MRR, everyone is looking at the same, accurate numbers \n* **Proactive Alerts**: Structured’s AI-driven features monitor your metrics and flag any anomalies. For example, if CAC suddenly spikes, the platform can alert you before it becomes a bigger issue. These insights help you stay ahead of potential problems and make more informed decisions.\n* **Data Request Tickets:** Structured offers an integrated ticketing system to manage data-related requests across your organization. Whether it's a request for a new metric, a data discrepancy, or additional analysis, your team can easily submit, track, and resolve these requests within the platform.\n* **Knowledge Base**: Structured automatically generates documentation as an artifact of setting up and managing metrics. This documentation is a powerful, quick win for your data team, creating a shared reference point that everyone in the organization can trust. This instant clarity translates directly to business impact—empowering your teams to make aligned decisions faster.\n* **ROI**:\n  * Your team saves dozens of hours previously spent reconciling different versions of the same metric. Decisions are made faster and with more confidence.\n  * By making data-driven adjustments to your customer acquisition strategies based on the standardized CAC, your company can focus on reducing the acquisition costs. The clarity around MRR helps optimize pricing strategies, contributing to increase in revenue.\n\n![uploaded image](/media/?type=post&id=73623&key=user_uploads/1194855/333b7409-baed-4975-ac28-e4d7a850ba1c)\n\n### **Why Structured?**\n\nWe founded Structured because we believe that every business, regardless of its size or technical sophistication, should have access to reliable, consistent metrics that drive smarter decisions. We’ve experienced firsthand the frustrations of working with inconsistent data and the impact it can have on business outcomes.\n\nWe realized that the tools available today either require significant technical expertise or fall short in ensuring metric consistency across an organization. Structured was born out of a desire to create a solution that bridges this gap—providing a platform that is both powerful enough for data teams and simple enough for business users. By focusing on the specific challenge of metric consistency, we aim to empower companies to make better, data-driven decisions without the technical overhead.\n\n### **Why Now?**\n\nBusinesses are generating and storing more data than ever before, particularly in cloud-based data warehouses. With this explosion of data comes the challenge of making sense of it—turning raw numbers into meaningful metrics that everyone in the organization can trust and use.\n\nAt the same time, the complexity of data environments is increasing. Companies are dealing with multiple data sources, complex data pipelines, and a growing need to make sure that metrics are not only accurate but also consistent across different departments and teams. Traditional BI tools are struggling to keep up with these demands, and businesses are increasingly looking for solutions that can provide a more streamlined, consistent approach to metric computation.\n\nThe market is ripe for a solution that can simplify the process of managing business metrics, reduce the reliance on specialized technical skills, and allow organizations to unlock the full potential of their data. Structured addresses this need head-on, providing a solution that is both timely and essential for the next generation of data-driven businesses.\n\n### **Try Structured**\n\nIf you’ve ever struggled with inconsistent metrics or if you’re looking for a better way to manage and scale your business analytics, we’d love to connect with you. Check us out at [structuredlabs.com](http://structuredlabs.com) or drop us an email at [amrutha@structuredlabs.com](mailto:amrutha@structuredlabs.com) \n\nLooking forward to your feedback and insights!",
        "url": "https://www.ycombinator.com/launches/J9T-structured-semantic-layer-for-reliable-business-metrics",
        "votes": 157,
        "created_at": "2023-07-31T22:30:34.907Z"
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    "id": 29150,
    "name": "Tempo",
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    "website": "https://www.tempo.new",
    "all_locations": "Toronto, ON, Canada",
    "long_description": "Tempo is a visual editor for react that gives PMs, designers, and engineers the ability to collaborate visually on code. It offers the familiar UX of a design tool but functions like an IDE under the hood. Tempo is optimized for Vite and Tailwind.",
    "one_liner": "Visual Editor for React, powered by AI",
    "team_size": 8,
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    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1689887097,
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      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
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    "founders": [
      {
        "user_id": 186561,
        "full_name": "Kevin Michael",
        "title": "Founder",
        "founder_bio": "Spent the last 5 years as founding engineer and head of product at Perpetua ($150M exit). Previously product fellow at Social Capital and engineer on the Visual Studio team at Microsoft.\n\nI've tried every low-code tool on the market and not a single one does a good job integrating with existing production codebases. I'm obsessed with solving this problem at Tempo and using AI to turn anyone into a 10X engineer.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/kevin1michael",
        "x_url": "https://twitter.com/Kevin1Michael",
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      },
      {
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        "full_name": "Peter Gokhshteyn",
        "title": "Founder",
        "founder_bio": "Passionate about building great products fast. Joined Perpetua ($150M exit) 6 years ago as employee #3 and led the engineering team from idea to PMF. Previous worked as a software developer at Google, Bloomberg & Zynga.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/petergokhshteyn",
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        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/736fd7198b0fd99e0e711bdeb7288da5fbf5e458.jpg"
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    ],
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        "id": 68263,
        "title": "Software Engineer, Full Stack (In-Person - Toronto)",
        "url": "https://www.ycombinator.com/companies/tempo-2/jobs/fszRm52-software-engineer-full-stack-in-person-toronto",
        "location": "Toronto, ON, CA",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$160K - $200K CAD",
        "equity_range": "0.35% - 1.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Node.js",
          "React"
        ]
      },
      {
        "id": 68264,
        "title": "Software Engineer, LLMs & AI Agents (In-Person - Toronto)",
        "url": "https://www.ycombinator.com/companies/tempo-2/jobs/C9xH3JW-software-engineer-llms-ai-agents-in-person-toronto",
        "location": "Toronto, ON, CA",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$160K - $200K CAD",
        "equity_range": "0.35% - 1.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": [
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      },
      {
        "id": 83825,
        "title": "Founding Product Designer ",
        "url": "https://www.ycombinator.com/companies/tempo-2/jobs/Hia3MVk-founding-product-designer",
        "location": "Main Office - Toronto",
        "type": "Full-time",
        "role": "Design",
        "role_type": "Web design",
        "salary_range": "$125K - $200K CAD",
        "equity_range": "0.25% - 1.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": [
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          "TypeScript",
          "Figma",
          "Tailwind"
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    "news": [
      {
        "title": "Tempo's $5M Seed To Empower The Design Engineering Movement",
        "url": "https://www.tempo.new/blog/5m-seed-design-engineering-movement",
        "date": "Oct 22, 2025"
      }
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    "launches": [
      {
        "id": 88483,
        "title": "Tempo V2: Build React Apps 10X Faster With AI",
        "tagline": "Tempo is where designers and developers collaborate on code",
        "body": "### **TL;DR**\n\nTempo is a visual IDE that enables designers, PMs, and developers to collaborate on code with the help of AI. In addition to prompting, Tempo gives you the fine-grain control that comes from a traditional design editor or code editor.\n\nIn V2, we introduce our [Figma Plugin](https://www.figma.com/community/plugin/1463689183126672406/tempo-ai-powered-figma-to-code-react), new AI reasoning + Gemini Search, [pre-built SaaS templates](https://tempolabsinc.mintlify.app/SaasTemplates) (for Stripe, Polar, Supabase, Convex+Clerk), and Expo support for react-native mobile apps. Watch our demo, [here](https://youtu.be/Sup921tMUf4).\n\n**The problem?** \n\n“Low-code” and “design to code” tools suck. As much as they accelerate the development process for simple apps, none have succeeded at helping serious software companies ship production-grade software. \n\nNew AI-powered web app builders take a code-first approach that is superior, however, they still struggle with complex apps and large codebases.\n\n**How we are solving it**\n\nTempo redefines the development workflow by combining the best of an IDE (like VS Code), a design tool (like Figma), and an AI chat assistant that enhances both—creating a single source of truth for designers and developers. Whether you’re a non-technical builder or a seasoned engineer, Tempo streamlines the process from concept to production.\n\nWith **V2, Tempo introduces:**\n\n🎨 **A fine-grain design panel** for pixel-perfect control\n\n🖼️ **A Figma plugin** that converts your designs to code in Tempo\n\n🧠 **Enhanced AI reasoning + Gemini Search** for faster debugging and development.\n\n⚡ **Pre-built SaaS templates** for Stripe, Polar, Supabase, Convex + Clerk.\n\n📱 **Expo support** for mobile app development with react native.\n\n**Teams use Tempo to:**\n\n* Build production grade applications.\n* Rapidly generate and refine prototypes.\n* Visually collaborate on production code.\n* Ship UIs that are pixel-perfect, every time.\n\nThe interface feels like your favourite design tool but works like an IDE. Teams using tempo ship to production 10x faster by adopting a code-first workflow.\n\n**What are we looking for?** \n\nSimply put—build, share, and showcase what you’ve created. Tag us in your [X](https://x.com/Tempo_Labs), [LinkedIn](https://www.linkedin.com/company/tempolabs/), or other posts, and we’ll amplify it to the community. Also please share your feedback.\n\nNeed additional support to accelerate your product roadmap? [Agent+](https://www.tempo.new/ai-agent-plus) can help accelerate your roadmap—designing and shipping 1-3 features per week. YC companies get $500 off for the first 3 months. Let’s build faster, together.\n\n**About Us:** \n\nFounders [Kevin](https://www.linkedin.com/in/kevin1michael/) and [Peter](https://www.linkedin.com/in/petergokhshteyn/) previously worked at Microsoft, Google, and Perpetua. They are building Tempo to help teams go from idea to production in minutes.",
        "url": "https://www.ycombinator.com/launches/N19-tempo-v2-build-react-apps-10x-faster-with-ai",
        "votes": 53,
        "created_at": "2025-03-11T17:41:51.665Z"
      },
      {
        "id": 73362,
        "title": "Tempo Labs - Build UIs 10X faster with AI",
        "tagline": "AI design & prototyping tool which contributes react code directly to your codebase",
        "body": "**TL;DR:** [_Tempo_](https://www.tempolabs.ai/) is an AI design & prototyping tool which contributes high-quality react code directly to your codebase. You can use tempo to generate complete views using simple AI prompts, polish & control design details visually, and build a high quality design system using your existing components. Sign up here to give it a try: [**_https://www.tempolabs.ai/_**](https://www.tempolabs.ai/)_._\n\nHere’s a 2-min demo: [**https://www.youtube.com/watch?v=2qQJKQJq7Jk**](https://www.youtube.com/watch?v=2qQJKQJq7Jk)\n\nHey Everyone, [Kevin](https://www.linkedin.com/in/kevin1michael/) & [Peter](https://www.linkedin.com/in/petergokhshteyn/) here, we’re the founders of [Tempo Labs](https://www.tempolabs.ai/).\n\n![uploaded image](https://bookface.ycombinator.com/media/?type=post&id=73362&key=user_uploads/186561/3de21c2f-8b73-4db8-8f65-5e2b61ea3670)\n\n### **The Problem**\n\nWhile building our last startup (Perpetua), we spent a lot of time looking for ways to speed up the pace of our development and prototyping. We tried every low-code tool on the market and were constantly disappointed by how poorly they integrated with our existing codebase. Figma ended up being our de facto tool for testing concepts but Figma prototypes always felt low-fidelity and took way too long to ship to production.\n\n### **The Solution**\n\nTempo is the design and prototyping tool we wish existed. Tempo integrates with any react project and empowers designers to collaborate with engineers directly on the codebase. Powered by AI, tempo generates 60%-80% of the front-end code required for any feature so engineers are free to focus on writing business logic rather than css. By eliminating the design->code translation process we help teams ship their ideas to production 10X faster.\n\n### **The Ask**\n\nIf you’re building a react app and are interested in testing us out please email me at [**kevin@tempolabs.ai**](mailto:kevin@tempolabs.ai). If you already have a design system we’ll give you a visual playground to build new views, if you don’t, we’ll help you implement one! If your app looks like crap, or your codebase feels hard to maintain, get in touch - we’ll help you level up your front-end using AI :)\n\n### **The Deal**\n\nSign-up before demo day and get 70% off for the first 6 months!",
        "url": "https://www.ycombinator.com/launches/J5G-tempo-labs-build-uis-10x-faster-with-ai",
        "votes": 84,
        "created_at": "2023-07-24T18:15:59.327Z"
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    "all_locations": "London, England, United Kingdom",
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    "team_size": 4,
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    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1688064768,
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      "AI"
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    "batch": "Summer 2023",
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    "regions": [
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    "url": "https://www.ycombinator.com/companies/codestory",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/codestory.json",
    "year_founded": 2023,
    "city": "London",
    "country": "GB",
    "linkedin_url": "https://www.linkedin.com/company/codestory-ai/",
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    "github_url": "https://github.com/codestoryai",
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        "user_id": 1045830,
        "full_name": "Sandeep Pani",
        "title": "Founder",
        "founder_bio": "Currently building CodeStory. I have worked extensively in the devtooling and AI space for the last 5 years as the tech-lead for testing infrastructure at Meta and as the founding engineer for Findly.ai (YC S22).\nPassionate about making developers more productive and want to build for a world where developers have powerful AI agents working together to ship more value.\n\nI love making computers do things. 👾",
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        "full_name": "Naresh Ramesh",
        "title": "Founder",
        "founder_bio": "Currently building CodeStory, an AI-native IDE designed for engineers to enjoy problem-solving with agents by their side. I've built payments infrastructure to handle 150k merchants and scaled an engineering team from 5 to 35.",
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      {
        "id": 85305,
        "title": "Aide — The Open Source IDE to solve hard problems",
        "tagline": "Code with the speed and knowledge of the best programmer you know. Aide is by your side.",
        "body": "Hey all! We’re Sandeep and Naresh from CodeStory. Aide (<https://aide.dev>) is the IDE for engineers to solve hard problems where changes are not limited to a single file but require iteration across multiple files. We are also open source at <https://github.com/codestoryai>. The main repositories are the:\n\n* [IDE](https://github.com/codestoryai/ide) (the VSCode fork)\n* [Sidecar](https://github.com/codestoryai/sidecar) (our rust binary the AI brains)\n\nCheck out the [editor in action](https://youtu.be/M82aLgBzdmk):\n\nWhen we started building CodeStory last year, we were set on building the best chat and autocomplete experience in the editor, which we believed to be the best use of LLM for code generation.\n\nWe quickly (after 6 months) realised that with the increasing trend of LLM coding capabilities, the UX around chat and copilot felt limiting to the real abilities of these LLMs to help the developer accomplish more. \n\nIn March this year, while debating what to focus our energy on, we decided to experiment with the idea: “What if LLMs could make edits across multiple files without breaking the logic?” So after a month of hacking, we tested our framework against [SWE-Bench Lite](https://www.swebench.com) and were very surprised (and kind of shocked) that Aide became the SOTA, resolving 43% of the issues.\n\nWe instantly knew we had to build the multi-file editing experience into the editor and do it well. \n\nWe decided NOT to put energy into building a better “copilot autocomplete” or “chat,” but rather go all in on shipping a better “multi-file editing flow.”\n\nWhile multi-file edits allow for larger units of work to be done, they have their set of problems:\n\n1. Lack of control to granularly iterate when there is a small issue within a large change\n2. Inability to roll back to older states when using over a long coding session.\n3. Changes to the local scope, especially when context is not provided exhaustively, break the codebase globally\n4. Context about edits made in a previous editing session is not kept around\n\nTo start in this direction, we forked VSCode 15 months ago as the most rock solid foundation to build an editor on top of and put quite a lot of work into solving some of the above stated issues with multi-file editing:\n\n1. We built a proactive agent which looks at the linter errors (Language server and your own feedback) and proactively comes back with fixes and suggestions for improvements.\n2. Special UX and integration with models for always breaking down changes into small, logical units that are easy to understand and have live previews using decorations in the editor, so changes can be applied easily, in parts or all at once.\n3. Native support for checkpoints and rollbacks: We couldn’t use git, of course, so we hooked into the TextModel implementation in VSCode (which is its in-memory representation of a file) to keep track of file versions across AI changes, while also preserving the undo stack. These checkpoints are exposed in the UI, letting you easily move back and forth when needed without having to worry about uncontrolled changes.\n4. Integrate tightly with the Language Server API on the editor to gather diagnostics from the whole codebase when changes occur, to ensure unintended breakages are quickly caught and propose fixes. For instance, the LLM changing a function signature should also fix the entire call stack.\n5. Maintain a continuous, long session context. Because our editor works entirely locally (no intermediary server interaction, just LLM calls directly from your machine!), the Rust binary shipped with the editor listens to all events and changes made by both the developer and AI to keep a continuous context, so subsequent changes are always better informed.\n\nThough, we, of course, didn’t just stop with multi-file edits.\n\n1. Even with single-file changes, our Rust binary leverages tree-sitter to structurally understand a file and use a combination of Search-And-Replace style editing with tight editor integration to edit multiple locations within a file in parallel to make faster edits, especially useful in large files. And threw in AST navigation for developers to move faster around them.\n2. To gather context for codebase-wide queries, rather than try to maintain lossy embeddings, the binary builds a repo map to let the LLMs filter down the most useful parts of the codebase per query.\n3. Wherever possible, use the new prompt caching capabilities (also exposed as a first-class citizen in the editor to give developers more control) to cache the most relevant files in a coding session — which largely speeds up response times.\n4. Build a macOS Spotlight style widget to quickly send our edit instructions for the agent to pick up and work while you focus on the code front and centre.\n\nSince everything runs locally on your machine, this is also a more privacy-friendly approach and gives the optional benefit of using your keys & contracts with cloud model providers — and we’re more than happy to speak with companies that are interested in setting this up. If you are someone who loves tinkering with LLMs, all the requests & responses are just stored on a SQLite DB on your machine (and nothing at our end), which is data that could perhaps be used in the longer run to fine-tune or build features to improve AI performance over time within teams.\n\nThere is still a ton to do in terms of robustness and capabilities. Despite all the progress, we still feel we’ve only explored about 1% of what coding with AI could look like. For now, we’d love for you to try out Aide at <https://aide.dev>. To keep things simple, we have a standard subscription plan with a 2-week trial to try out the editor. We’d love to hear your feedback and ideas!\n\n![uploaded image](/media/?type=post&id=85305&key=user_uploads/89898/ac8a2779-6f50-4489-bd96-b7739eb66724)\n\n",
        "url": "https://www.ycombinator.com/launches/MBt-aide-the-open-source-ide-to-solve-hard-problems",
        "votes": 18,
        "created_at": "2024-11-05T21:54:43.869Z"
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      {
        "id": 73829,
        "title": "CodeStory ✨ is an AI-powered mod of VSCode.",
        "tagline": "CodeStory is a full-blown AI-powered IDE built to tackle any complex task, so you can accomplish your goals faster.",
        "body": "TLDR: CodeStory ✨ is an IDE for engineers of the future. CodeStory enables deep integration for AI assistants with your development environment, so your pair programmer can complete complex tasks and get it right.\n\n### The problem ⚙️\n\nAs programmers, we like to break down our tasks into small chunks that can be executed independently. Consider the simple task of **adding a widget to show sales numbers on your website** which can involve multiple steps:\n\n* Database queries to fetch the data on the backend\n* Exposing an API route to make the data available for the frontend\n* Frontend UI and API integration to complete the task\n\nEven within a single codebase, such a task requires finding and making the right changes in multiple parts and connecting them together. Though this can be done independently and in parallel, there is only so much an engineer can do at a time.\n\nWe thus decided to build CodeStory, **a next-generation code editor that is AI-first, where humans assist powerful AI agents instead of the other way around!** We have started with a VSCode extension in order to prototype the capabilities.\n\n### Watch CodeStory debug and build itself! 🤯\n\nIt would be a shame if CodeStory couldn’t debug or build itself... so we put it to work!\n\nHere we asked CodeStory to do proper dependency injection (you can see it using references, searching for symbols using ripgrep and cmd+click on a symbol like a true programmer!)\n\n<https://youtu.be/pY4QWEqG8Es>\n\nIn the following video, we asked CodeStory to fix an annoying bug with a race condition happening in our async codebase and write a test to make sure the issue does not repeat again.\n\n<https://youtu.be/-5LH9W-XHC4>\n\n### How we are solving it? ✨\n\nTo be effective as software engineers, we need access to tools. We realized early on that even our editor is full of features that aid in writing code and debugging it.\n\nTo make CodeStory effective as an engineer, we gave it the following powers 🔋:\n\n* Language Server integration 📝\n  * CodeStory can ask for references of a symbol or cmd+click to a symbol to investigate more\n* Terminal access 🖥️\n  * CodeStory can freely run commands on the terminal when required in a sandbox environment.\n* Code Graph of the whole codebase 〽️\n  * CodeStory knows how different classes and modules are linked to each other, so it can search your whole codebase semantically (both natural language)\n\n### The future 📡\n\nWe love AI-powered development and envision a future where humans are gluing AI agents to work together.\n\n### The team 👥\n\nHi all! We are Naresh and Sandeep, co-founders of [CodeStory.ai](http://CodeStory.ai) and close friends for over a decade. We met in our freshman year at University and since then Sandeep worked as Tech leads for Testing Infrastructure at Meta and building out devtooling for engineers, and founding engineers at startups (YC backed!) and fintech.\n\n### Our ask 🙏\n\nWe are currently on-boarding users for CodeStory slowly to gather detailed feedback. If you’d love to try CodeStory, we are active on [discord](https://discord.gg/Cwg3vqgb) or [twitter](https://twitter.com/codestoryAI), and would be happy to help you onboard and answer any questions.\n\nYou can also reach out to us directly at [founders@codestory.ai](mailto:founders@codestory.ai) to talk more about the future of AI-powered coding. We are very, very excited about this!",
        "url": "https://www.ycombinator.com/launches/JCn-codestory-is-an-ai-powered-mod-of-vscode",
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        "created_at": "2023-08-04T22:58:55.458Z"
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    "long_description": "OpenPipe is an SDK that abstracts away fine-tuning custom models. We capture your existing provider’s prompt-completion pairs in the background and use them to create a new model that is faster, cheaper and often more accurate than the original.",
    "one_liner": "Turn expensive prompts into cheap fine-tuned models",
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        "full_name": "Kyle Corbitt",
        "title": "Founder",
        "founder_bio": "Repeat founder and former engineer at Google and YC. Led the Startup School team and built products that increased YC applications by over 40%.",
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        "full_name": "David Corbitt",
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        "founder_bio": "I'm a co-founder at OpenPipe, a platform for turning your slow and expensive prompts into cheap fine-tuned models. My cofounder and I wrote the first web agent that ran on GPT-4 (Taxy.AI) and I've been fine-tuning models since 2021.",
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        "title": "Seattle startup OpenPipe raises $6.7M to help companies reduce costs for LLM models – GeekWire",
        "url": "https://www.geekwire.com/2024/seattle-startup-openpipe-raises-6-7m-to-help-companies-reduce-costs-for-llm-development/",
        "date": "Mar 26, 2024"
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        "id": 74436,
        "title": "OpenPipe: Convert expensive LLM prompts into fast, cheap fine-tuned models",
        "tagline": "OpenPipe automatically captures your existing prompts and completions, then uses them to fine-tune a drop-in replacement. The replacement is faster, cheaper and often more accurate than your original prompt.",
        "body": "Hi there! We’re Kyle and David, and we’re building [OpenPipe](https://openpipe.ai/). OpenPipe lets you capture your existing prompts and completions, and then use them to fine-tune a model specific to your use-case. Here’s how the process works:\n\n![uploaded image](/media/?type=post&id=74436&key=user_uploads/203501/750c83fe-b66d-40b8-bec3-63049b029360)\n\n## Problem: General-Purpose LLMs are slow and expensive\n\nBefore working on OpenPipe, we each ran into limitations of GPT-3.5 and GPT-4:\n\n* **David** built an app that required searching Reddit and classifying the results on user-specific dimensions. Because the set of possible results that GPT-3.5 had to classify was so large, each search cost multiple dollars!\n* **Kyle** built (and sold) a startup that involved translating official documents. It was difficult to express the specific requirements that official translations must comply with in a way that GPT-3.5 would reliably follow, but GPT-4 was too slow to provide a good user experience.\n\nWe’ve spoken with many other companies and these issues are common. Cost and latency are two major factors blocking production deployment of LLM-backed functionality.\n\n## Solution: Replace prompts with auto-deployed fine-tuned models\n\nSmall models fine-tuned on a specific prompt are highly performant and can excel at many tasks. They’re particularly good at data extraction and classification, even on tasks that need significant world knowledge.\n\nFor example, in [one project](https://github.com/OpenPipe/OpenPipe/tree/main/examples/classify-recipes) we built to classify recipes, our model was able to determine that a recipe that calls for sautéed mushrooms needs a stovetop, despite not being explicitly trained on that connection. It outperformed GPT-3.5 in classification accuracy and reached 95% of GPT-4’s performance.\n\nAnd not only does our fine-tuned model outperform GPT-3.5, it costs 50X less to run!\n\n![uploaded image](/media/?type=post&id=74436&key=user_uploads/203501/c4655ba3-5023-4010-9fae-ea71cc0e2ccb)\n\nWe’ve built infrastructure to make fine-tuning your own model extremely easy. The process works like this:\n\n* Develop a prototype of your LLM-powered feature using GPT-3.5 or 4 like normal.\n* Collect prompts and completions over time using our reporting SDK.\n* Once you have a few hundred to a few thousand completions recorded, kick off a training job in our UI.\n* A few hours later, your model will be ready. You can either download it and self-host, or host it with us.\n* Update your SDK’s URL to point to the new model. Keep your prompts and application code exactly the same — everything will just work!\n\n## Our Ask\n\n* If you’re prototyping or rolling out a product that is hurt by the slow responses or high costs of your existing LLM provider, talk to us.\n* If you know someone who is prototyping or rolling out AI-based functionality within a large company, link them to this post or just put them in contact with us directly.\n\nYou can reach us at [founders@openpipe.ai](mailto:founders@openpipe.ai). We’d love to help out if we can!",
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        "votes": 99,
        "created_at": "2023-08-28T14:59:50.515Z"
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        "answer": "Raj and Till met while working together at Palantir. They led the product team behind one of Palantirs most used products for years before founding Stitch. After independently spending years building products, they decided to making building great things easy enough so anyone can do it."
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      {
        "user_id": 1228768,
        "full_name": "Vaishant Kameswaran",
        "title": "Founder",
        "founder_bio": "Founder @ Greptile. CS from Georgia Tech, minor in Linguistics.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/vaishant",
        "x_url": "https://twitter.com/vaishaaant",
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    "jobs": [],
    "news": [
      {
        "title": "Series B and The War on Bugs",
        "url": "https://www.greptile.com/blog/series-b",
        "date": "Oct 19, 2026"
      },
      {
        "title": "Greptile: AI That Actually Understands Codebases",
        "url": "https://www.youtube.com/watch?v=vRt4ng9V9qA",
        "date": "Sep 23, 2025"
      },
      {
        "title": "Series A and Greptile v3 | Greptile Blog",
        "url": "https://www.greptile.com/blog/series-a",
        "date": "Sep 23, 2025"
      },
      {
        "title": "Greptile raises $4M to build an AI-fueled code base expert",
        "url": "https://techcrunch.com/2024/06/06/greptile-raises-4m-to-build-an-ai-code-base-expert/",
        "date": "Jun 06, 2024"
      }
    ],
    "launches": [
      {
        "id": 79274,
        "title": "Greptile: AI expert that understands large codebases",
        "tagline": "Platform that lets engineers understand large codebases and build internal dev tools using AI.",
        "body": "Hi everyone! We’re [Soohoon](https://linkedin.com/in/soohoonchoi), [Vaishant](https://linkedin.com/in/vaishant), and [Daksh](https://linkedin.com/in/dakshg) from [Greptile](https://www.greptile.com/). We are building the AI expert on any codebase.\n\n**tl;dr** Greptile is an AI platform that lets LLMs understand large codebases. Teams and devs at 250+ companies including Stripe and Amazon use it to get answers to questions about large codebases via our web app, automatically update their docs, build PR review bots on our API, and more. **Try it now → [**app.greptile.com**](https://app.greptile.com)**\n\n![](https://lh7-us.googleusercontent.com/fuO2un8RYVAWc1rG4KjNOKUfudaWA7z4ZKG7kDK7-PcX8zzPOUunZHPD4vLCSfEOYp0WQ00vfigNq3ivhFBPbgFsbH-ldXa8VQLVr0FcA3r3kQDgPMCtfrVzpjSZ5RWYaagrIQYahicZPMx-Fgc1HQM)\n\n### **PROBLEM**\n\nAs software companies grow:\n\n1. Codebases get more **complex**.\n2. **Legacy code** and **tech debt** accumulates.\n3. Docs are usually **outdated**.\n4. **Original engineers leave**, and new engineers are less familiar with the code.\n\nTo get around this, developers:\n\n1. Just brute force their way to grokking the code - which is hard and time-consuming.\n2. Seek help from the subject matter expert, which is difficult if they have left, work remotely, or are just busy.\n3. Try to use tools like GitHub copilot, which are not designed to answer with full code context, so they fail to deliver.\n\nIn fact, the thing that makes coding hard is usually the codebase, not the code!\n\nWe found a way to index and search large codebases such that LLMs can always find the right context, allowing any developer to build internal developer tools powered by AI.\n\nHere’s Felix from Twenty (open source CRM with 9k GitHub stars).\n\n![](https://lh7-us.googleusercontent.com/_rr-le-rqZZzZQoT6p1gikSOdZjaAAKzSwfmn4j9qs7VuKb9Gcw9jnTNfcofYa9F0OaFpSPl3JAmA_hZE6dnV-aBgGTgspfrqILEcAsHrqqMr7g8JuB_YeCMWmCikptC3eWHPgXFzEAPR1gWT_GAtEE)\n\n### **🦎 Greptile in action →**\n\nHere are some ways engineers use Greptile 👇\n\n1. **Narek from** **Lantern** **(W24):** grokking PostgreSQL’s source code, which Lantern is built on.\n2. **Rahul from** **AgentHub (W24):** parsing OSS frameworks that AgentHub integrates with.\n3. **Jack Chapman from** **Cardinal Gray** **(S23):** generating E2E test cases for multi-file services.\n4. **Isaiah Granet from Bland AI (S23):** integrating with the Twilio node SDK.\n5. **SWE at Thera (S22):** writing new features that require complex, multi-file changes.\n6. **YC Medtech (S15):** building an internal PR review bot on top of our API.\n7. **SWE at Stripe (S09):** debugging internal Rust libraries.\n8. **Principal Engineer at Microsoft:** reviewing his team’s code (open source).\n9. **TMO (old B2B software company):** working with their legacy .NET code.\n\n### **ASK →**\n\n* If you’re a developer working with large codebases - try Greptile here → [app.greptile.com](http://app.greptile.com)\n* If you want Greptile at your org, email me ([daksh@greptile.com](mailto:daksh@greptile.com)) or book a demo on my calendar ([greptile.com/demo](http://greptile.com/demo))\n\n![](https://lh7-us.googleusercontent.com/zintlEJgFJVQK3d_FV8Qi3zb845wA5TgCwqcv3jrXyH9N1YNFBFLOlBRPT76Mf16_hilA6DC5wmu9BcNqWPfilKj_52ex2WFjWoHUf6vkZKFll86vU4D1vVYgEOUGWTw-qMqkmeCyMpyAvpUQLiWL6I)\n\n",
        "url": "https://www.ycombinator.com/launches/Kcc-greptile-ai-expert-that-understands-large-codebases",
        "votes": 48,
        "created_at": "2024-03-11T20:06:39.485Z"
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    "id": 29238,
    "name": "Duckie",
    "slug": "duckie",
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      "Duckie AI"
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    "website": "https://duckie.ai/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Duckie lets customer support teams build their own AI agents in minutes! \r\n\r\nWith Duckie, support teams can translate their tasks and processes into predictable and reliable AI workflows that saves them time and money. Folks use Duckie to handle a wide range of use cases, from answers customers technical questions to processing refunds, and everything in between.",
    "one_liner": "Build AI Support Agents in Minutes",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1697309167,
    "tags": [
      "Generative AI",
      "Customer Support",
      "Operations",
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    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Winter 2024",
    "status": "Active",
    "industries": [
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    "regions": [
      "United States of America",
      "America / Canada"
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    "stage": "Early",
    "app_video_public": false,
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/duckie",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/duckie.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/duckie-ai/",
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    "app_video_url": null,
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    "primary_partner": {
      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
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    "founders": [
      {
        "user_id": 1422402,
        "full_name": "Valerie Li",
        "title": "Founder",
        "founder_bio": "Cofounder and CEO of Duckie. Prior to Duckie, she has been a senior engineer for 6+ years with expertise in infrastructure.\nShe was a tech lead at Netflix for 3 years, where she led the subscriber growth project that stopped password sharing, which added 8m new subscribers and $200m in revenue (and saved the company's stock price).\nBefore that she was an engineer at LinkedIn, and got her Computer Science degree from USC.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/peifeili",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0ff88e00eb5b518161ae922d5fffedf5bf7c026b.jpg"
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      {
        "user_id": 515585,
        "full_name": "Joel Ritossa",
        "title": "Founder",
        "founder_bio": "Co-founder and CTO at Duckie. Former AI Software Engineer at C3 AI, built Enterprise AI solutions. Princeton CS Class of 2020. Solving technical support with Valerie Li.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/joel-ritossa",
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    "jobs": [
      {
        "id": 82671,
        "title": "Founding Business Development Representative",
        "url": "https://www.ycombinator.com/companies/duckie/jobs/uDANlkc-founding-business-development-representative",
        "location": "San Francisco, CA, US / Remote (US)",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$80K - $120K",
        "equity_range": "0.25% - 1.50%",
        "experience": "3+ years",
        "visa": "Will sponsor",
        "skills": []
      },
      {
        "id": 103196,
        "title": "AI Agent Engineer",
        "url": "https://www.ycombinator.com/companies/duckie/jobs/McnwK78-ai-agent-engineer",
        "location": "San Francisco, CA, US / Remote (US)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Backend",
        "salary_range": "$100K - $130K",
        "equity_range": "5.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
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    "news": [],
    "launches": [
      {
        "id": 78906,
        "title": "Duckie: Your AI technical support assistant 🐥",
        "tagline": "AI technical support assistant that helps teams resolve issues in minutes",
        "body": "Quack! We are [Valerie](https://linkedin.com/in/peifeili) and [Joel](https://linkedin.com/in/joel-ritossa), and we are happy to introduce [Duckie](https://duckie.ai/), an AI technical support assistant that helps teams resolve issues in minutes.\n\n![uploaded image](/media/?type=post&id=78906&key=user_uploads/89898/c8ebe519-8f16-44d1-90be-4d314325946d)\n\n[ ](https://www.youtube.com/watch?v=fycJPu47u1E&feature=youtu.be)\n\n## **Problem - Too many support requests, too little time.**\n\nResolving technical issues takes a lot of time, and they are often time-sensitive. Most issues can be solved with better knowledge-sharing. So much relevant information is in your team’s knowledge base, but it’s tough to find.\n\n* A lot of important information is tribal knowledge stuck in a teammate’s head.\n* Written knowledge is still siloed and scattered across Slack, Jira, docs, everywhere!\n* Once you find the docs, they’re always out of date (who likes writing documentation??).\n\n## **Solution**\n\nDuckie connects to your team’s knowledge sources (i.e. Slack, Jira, Confluence, Sentry, etc) to find relevant information and **generate issue resolutions** in minutes while writing back to your documentation to **keep the knowledge base up-to-date**.\n\nIs your customer getting an error message while OAuthing into your product? Duckie’s there to help. Your user is facing an issue using your API? Duckie can handle that. Your new engineer is having trouble setting up a local environment? Leave it to Duckie!\n\n### Instantly understand your issue and how to resolve it\n\nWhen a new issue comes up in your support channel, Duckie responds in the thread with where to look and how to resolve it, with reference sources.\n\n![uploaded image](/media/?type=post&id=78906&key=user_uploads/1422402/434842de-d831-4a1e-8f10-3f993b3e9991)\n\n### Conversational copilot to investigate with you\n\nHave follow-up questions? Instead of waiting for hours for human responses, Duckie responds instantly and gets you unblocked ASAP. \n\n![uploaded image](/media/?type=post&id=78906&key=user_uploads/1422402/fba57457-07b7-43d7-8cd7-9dc5affe311c)\n\n### Keep your documentation up-to-date automatically\n\nDuckie keeps your team’s documentation up-to-date with learning picked up during issue resolution. Duckie also handles post-mortems, status updates, and more.\n\n![uploaded image](/media/?type=post&id=78906&key=user_uploads/1422402/47063fac-d439-4af0-a372-b19e2122b084)\n\n## **Our Ask**\n\n1. [Book a demo](https://calendly.com/valerie-li-duckie/meet) with us to get Duckie live in your channel!\n2. Questions, thoughts, feedback, or want a Duckie swag? Email us at [founders@duckie.ai](mailto:founders@duckie.ai)!",
        "url": "https://www.ycombinator.com/launches/KWg-duckie-your-ai-technical-support-assistant",
        "votes": 182,
        "created_at": "2024-02-29T19:10:57.504Z"
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  },
  {
    "id": 29239,
    "name": "ion design",
    "slug": "ion-design",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/19ac79a5dd7e79b8d3e0a7794a401a7673116ee9.png",
    "website": "https://www.ion.design/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "We're a website platform for Ecommerce brands. ION pairs your website with AI agents that design, launch, and learn from on-brand experiments that increase revenue per visitor.\r\n\r\nBrands that use ION learn and grow faster than if they were using a traditional CRO team. It's like a growth team working 24/7 to help drive and convert more traffic.\r\n\r\nWe're trusted by $1b+ companies and leading Ecommerce brands.",
    "one_liner": "AI Website platform that grows revenue automatically",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1698787268,
    "tags": [
      "Design Tools",
      "Marketing",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/ion-design",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/ion-design.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/ion-dot-design",
    "x_url": "https://twitter.com/iondotdesign",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/ion-design",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/19ac79a5dd7e79b8d3e0a7794a401a7673116ee9.png",
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      {
        "user_id": 608990,
        "full_name": "Samraaj Bath",
        "title": "Founder/CEO",
        "founder_bio": "CEO @ ion design.\n2x YC founder. ex CTO, PM, design team manager, full stack engineer. \nobsessed w/ making it easier to build beautiful products.\n\nI previously founded an ice cream company, bootstrapped a birthday wishing app, danced professionally, and rebuilt a 1981 motorcycle.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/samraajbath",
        "x_url": "https://twitter.com/samraaj",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9082d26518ac83af8a93212228a3de1b2b71bcad.jpg"
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    "launches": [
      {
        "id": 92019,
        "title": "Ruby: The 1st Autonomous AI Product Designer",
        "tagline": "AI Agent that improves your product while you sleep",
        "body": "We want you to [meet Ruby.](https://ion.design/ruby)\n\n![uploaded image](/media/?type=post&id=92019&key=user_uploads/608990/d2392f00-7f84-408c-b2dd-3ad45be16407)\n\n**tl;dr:** You can assign Ruby design tasks right in slack, like optimizing a flow or creating a new page.\n\nShe clarifies requirements, researches, designs multiple options, iterates with you, and ships PRs to your codebase. She will then monitor performance and suggest future improvements.\n\nShe’s like Devin, but for Product Design work.\n\n2 min demo - [**https://youtu.be/0MccwmsZOOc?si=FqSIPUbiX-Y160h8**](https://youtu.be/0MccwmsZOOc?si=FqSIPUbiX-Y160h8)\n\n### Problem\n\n“Over the next decade, as new coding tools make it easier than ever to build and ship products quickly, great design is going to matter even more.” - Aaron Epstein, latest YC RFS\n\nWe agree, and good design takes a LOT of time, money, and care. Ruby can leverage your design thinking and execute against it 100x faster.\n\nWhenever you build a flow, you can be sure Ruby will make it as good as it can be.\n\n### How ruby helps\n\nWhen assigned a task, ruby works through a flow to solve the problem:\n\n1. **Clarify:** Ruby asks your team the right questions until the requirements are clear.\n2. **Research:** Ruby scans usage data, research docs, personas, and finds external inspo.\n3. **Design & Test:** Ruby generates multiple concepts that follow your brand and design system. She simulates usage and discards weak options. She will iterate until she is confident the problem is being solved.\n4. **Iterate:** Ruby presents her work, takes feedback, and refines. She can iterate endlessly.\n5. **Ship:** Opens a PR when you approve a design.\n6. **Improve:** Ruby will monitor your analytics and propose upgrades whenever she spots opportunities.\n\n### Why did we build this?\n\nOur team was early in generative code & design. I’ve been shipping ai design-to-code tools since 2021, and we recently built an AI visual builder called ion.\n\nInternally, we trained an AI that uses our visual builder itself, and taught it the design process.\n\nIt blew us away.\n\nWe named her Ruby, put her into slack, and started giving her to our customers. Her results look promising so we’re sharing her more 🙂\n\n### Our ask\n\n[**Ruby**](https://ion.design/ruby) is meant for fast moving startups who are serious about getting product changes in the hands of customers faster.\n\nIf you want faster experimentation and world‑class design without extra headcount, [**grab a slot on our calendar.**](https://cal.com/samraaj/15min) We are personally onboarding the first batch of customers.\n\n![uploaded image](/media/?type=post&id=92019&key=user_uploads/608990/b1b1f820-9458-4ab6-a945-8ad107904847)\n\n",
        "url": "https://www.ycombinator.com/launches/NwB-ruby-the-1st-autonomous-ai-product-designer",
        "votes": 44,
        "created_at": "2025-07-09T18:31:45.892Z"
      },
      {
        "id": 89341,
        "title": "ion - AI development for your non-technical team",
        "tagline": "We turn your PMs and Designers into shipping machines",
        "body": "**tldr:** ion is a **visual editor for your codebase** that lets non-engineers (PMs, designers, marketers) safely **edit, refine, and ship** UI changes—while maintaining code quality.\n\n![uploaded image](/media/?type=post&id=89341&key=user_uploads/608990/2f3dfe27-827f-4c3e-8076-dddc335cdf65)\n\n[Demo (2 minutes)](https://youtu.be/qF0Ery_eqRA)\n\n### Safe “vibe coding”, made for your team\n\n* **Built for your codebase:** ion connects to your github and understands your set up (design system, tokens, components, version control) to ensure changes use existing patterns and fit architecture. Setup takes seconds.\n* **Easy for non-technical team:** ion serves a figma-like experience, so PMs and designers have a familiar interface to make product changes. ion automatically opens PRs so your usual review process stays intact.\n* **Faster Iteration:** No more endless backlogs, Figma → Dev → QA loops, or “design doc limbo.” ion makes smaller (but crucial) changes easy, and keeps your engineers focused on the big stuff.\n\n### Problem\n\nProduct teams are split in to two camps:\n\n* Those who can ship (engineers).\n* Those who can’t ship (PMs, designers, marketers, etcc)\n\nSmall changes—marketing pages, design tweaks, growth experiments—get stuck behind bigger features and developer bandwidth.\n\nBut they’re inherently different work and shouldn’t be at odds with one another.\n\n### Solution\n\nWith ion, your entire product team gains the ability to ship through a simple visual editor.\n\nYour team can either point and describe their changes through natural language, or enter “design mode” to get a Figma-like editor built on top of your codebase.\n\n![uploaded image](/media/?type=post&id=89341&key=user_uploads/608990/d37e63ab-9b64-4323-b5cc-01b434303621)\n\nion automatically wires everything into GitHub branches/PRs, so you still maintain engineering rigor.\n\nEngineers are freed up to focus on **high-leverage** work (architecture, data, business logic), while non-technical folks self-serve on UI changes, experiments, front end, and other changes.\n\n### How it’s being used today:\n\n* **Rapid Product Iteration**\n  * Instead of back-and-forth on Slack or Loom videos, designers/PMs can open an ion link for a given branch, visually tweak what’s needed, and ship updated PRs.\n* **Design Fixes**\n  * Designers fix design issues directly within ion rather than piling up a backlog of styling tickets. Some teams even skip Figma altogether for minor tweaks.\n* **Growth & Marketing**\n  * Launch new landing pages, promotions, or experiments at lightning speed. No more waiting on the dev queue for something as simple as a copy change.\n\n### Our ask\n\nion has already shipped thousands of lines of code at companies of all sizes. If you’re interested in unlocking the development productivity of your team,  please reach out:\n\n* Email us at founders@ion.design\n* [Book some time to chat on my calendar](https://cal.com/samraaj/15min)\n* [Download ion now - it’s free to start 🙂](https://ion.design/)",
        "url": "https://www.ycombinator.com/launches/NEz-ion-ai-development-for-your-non-technical-team",
        "votes": 28,
        "created_at": "2025-04-08T18:16:40.189Z"
      },
      {
        "id": 78764,
        "title": "⚡️ ion design - Instantly turn Figma designs into clean React code",
        "tagline": "A design system that writes and maintains your code for you, automatically.",
        "body": "Hi everyone 👋🏽🧡. [Samraaj](https://linkedin.com/in/samraajbath) and [Samuel](https://linkedin.com/in/samuel-barnholdt-a480b3179) here from [ion design](https://www.ion.design/). We’re super excited to share what we’ve been working on with you!\n\n**tldr:**\n\nion design automatically turns Figma designs into pixel-perfect, production-ready code, speeding up front-end implementation time by at least 40%.\n\nWe accomplish this by serving a fully featured Figma design system and matching React component library. This allows our generations to come out with incredibly high-quality, functional code that saves hours of time.\n\nThink of us like UntitledUI and Shadcn on steroids - we speed up both the design and implementation processes.\n\n**Deal:**\n\nOur design system with 5,000+ custom components is available for just $10 for the first 100 customers - [get access here](https://buy.stripe.com/28o1739KTcx59Vu8wB?prefilled_promo_code=YCLAUNCH24)\n\nHere’s a quick demo of our design system being used to generate a production-ready application:\n\n[DEMO](https://youtu.be/81kUjZUXaxQ)\n\n[Demo Application - Figma](https://www.figma.com/file/LncZWxVTpD4svqEUVk63pC/ion-demo-application?type=design&node-id=105%3A4665&mode=design&t=CW5GRxhuZBUGbc6t-1)\n\n[Demo Application - GitHub](https://github.com/ion-design/ion-demo-application)\n\n[Demo Application - Live Link](https://ion-demo-application.vercel.app/)\n\n# The Problem - implementing designs is expensive, painful, and monotonous.\n\nDesign and front-end engineering is re-doing the same work twice. We think this is ridiculous, and a total waste of time for businesses that leads to a multitude of problems:\n\n* **Engineers feel like they are wasting their time** monotonously writing CSS to match pixels in Figma. They would prefer to focus on more interesting work that drives value - like business logic, architecture, and data. They also hate working with primitives and want useable components out-of-the-box.\n* **Designers feel that there’s always a disconnect** between what they made and production. They’re constrained by engineering bottlenecks and their fixes will never be live. Many want a system they can put in place so the organization can be more structured and consistent.\n* **PMs & Founders hate having to prioritize design changes** against product iterations and new feature releases. They wish that the design work could just get done.\n\n# ⚡ Solution - The ion system\n\nion serves a customizable design system & component library that can be synced with your codebase ✨automatically✨.\n\nWe’re the first UI-kit that’s tightly coupled between Figma and React and works with out-of-the-box code generation.\n\n![uploaded image](/media/?type=post&id=78764&key=user_uploads/608990/40106740-b0ff-42ca-8502-5f2138f80e84)\n\nHere are some killer features:\n\n* ion automatically re-uses your existing components and writes READABLE code that your engineers can interface with.\n* ion writes stub functions and state handlers for your buttons, inputs, text areas, tabs, and other complicated components, automatically.\n* ion raises merge conflicts for design changes and soon will be able to create pull requests directly in your repo.\n* ion keeps you consistent, clean, and quick in your development. Oftentimes, the generated code is cleaner and easier to work with than what I write.\n\nUsing ion also saves your designers thousands of hours by serving 5,000+ well-built Figma components. This empowers you to design faster and maintain consistency across your application. Here’s a gif of me creating a screen in a matter of minutes:\n\n![uploaded image](/media/?type=post&id=78764&key=user_uploads/608990/87b26b94-5a26-4e5e-bec1-fe31c3a8e742)\n\nOur design system is endlessly theme-able and syncs directly with the CSS variables in your codebase. Light mode and dark mode are baked into the system.\n\nSay goodbye to re-writing classnames and pulling your hair out to get things to look good. You can even add whatever custom themes you want.\n\n![uploaded image](/media/?type=post&id=78764&key=user_uploads/608990/8f4f009c-a9e8-423a-ace6-db1a05008e4c)\n\n# 💲 Special Deal\n\n* JUST $10 for access to our design system with 5,000+ Figma components and the matching React+tailwind code. [Ready to go for any project - get started here.](https://buy.stripe.com/28o1739KTcx59Vu8wB?prefilled_promo_code=YCLAUNCH24)\n* Personal hands-on help from our team to use the design system and integrate generated code for you.\n\n[Sign up for early access here.](https://www.ion.design/)\n\n[or - book a call with me directly here.](https://cal.com/samraaj/30min)",
        "url": "https://www.ycombinator.com/launches/KUO-ion-design-instantly-turn-figma-designs-into-clean-react-code",
        "votes": 32,
        "created_at": "2024-02-26T19:15:51.663Z"
      }
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    "name": "Andon Labs",
    "slug": "andon-labs",
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    "website": "https://andonlabs.com/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Safety from humans in the loop is a mirage. We evaluate, research, and apply AI control in our own real-world deployments of autonomous organizations.\r\n\r\nWe are building the Safe Autonomous Organization. We iteratively launch and scale autonomous organizations, while bridging AI control research with real-world testing.",
    "one_liner": "Autonomous organizations without humans in the loop",
    "team_size": 11,
    "industry": "B2B",
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      "America / Canada"
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    "demo_day_video_public": false,
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    "url": "https://www.ycombinator.com/companies/andon-labs",
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    "linkedin_url": "https://www.linkedin.com/company/andonlabs/",
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    "primary_partner": {
      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
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    "founders": [
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        "full_name": "Lukas Petersson",
        "title": "Founder/CTO",
        "founder_bio": "Breaking capitalism @Andon Labs",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/lukas-petersson-181a83172",
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    "jobs": [],
    "news": [
      {
        "title": "Anthropic's office launched an AI-run vending machine. It had AI-run stores and cafes within a year | Fortune",
        "url": "https://fortune.com/2026/06/02/anthropic-office-vending-machine-ai-agents-vendo-andon-lukas-petersson/",
        "date": "Jun 02, 2026"
      },
      {
        "title": "The café run by AI just ordered 3,000 pairs of gloves",
        "url": "https://www.thetimes.com/world/europe/article/life-in-an-ai-cafe-f6khbhq99",
        "date": "May 24, 2026"
      },
      {
        "title": "Andon Labs’ AI radio stations show why Grok and Gemini can’t be trusted | The Verge",
        "url": "https://www.theverge.com/ai-artificial-intelligence/931479/andon-labs-ai-radio-companies",
        "date": "May 15, 2026"
      },
      {
        "title": "What Happens When A.I. Runs a Store in San Francisco? - The New York Times",
        "url": "https://www.nytimes.com/2026/04/21/us/san-francisco-store-managed-ai-agent.html?searchResultPosition=1",
        "date": "Apr 21, 2026"
      },
      {
        "title": "We Let AI Run Our Office Vending Machine. It Lost Hundreds of Dollars.",
        "url": "https://www.wsj.com/tech/ai/anthropic-claude-ai-vending-machine-agent-b7e84e34",
        "date": "Dec 18, 2025"
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    "name": "Reducto",
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    "website": "https://reducto.ai",
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    "long_description": "Reducto is the agentic document platform for leading AI teams building systems to automate document workflows at enterprise scale.\r\n\r\nOur platform provides a comprehensive toolkit for working with documents the way a human would, combining custom in-house and leading frontier models to power efficient and accurate document workflows. Reducto is trusted by leading AI teams at companies like Harvey, Scale AI, and Vanta.\r\n\r\nWe are built for enterprise workloads with flexible deployment options from the cloud to fully air-gapped environments, SOC II and HIPAA compliance, and zero data retention.\r\n\r\nLearn more: https://reducto.ai/\r\nFind our YC deal: https://reducto.ai/yc",
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    "team_size": 30,
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    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/reducto-ai/",
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    "founders": [
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        "user_id": 1577822,
        "full_name": "Raunak Chowdhuri",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder/CTO at Reducto. Before Reducto I studied CS at MIT, founded/scaled a comp. chem consulting company to 200k ARR, published computer vision papers with 100+ citations before finishing high school, and spent a little too much time shit posting on Twitter.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/sauhaarda",
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        "user_id": 850889,
        "full_name": "Adit Abraham",
        "title": "Founder/COO",
        "founder_bio": "Co-founder/CEO at Reducto. Before Reducto I studied CS at MIT, made Ads/Search things as a PM for Google, did ML research at MIT's Media Lab, and spent an unreasonable amount of time playing Pokemon Showdown.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/aditabraham",
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    "jobs": [
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        "title": "Software Engineer",
        "url": "https://www.ycombinator.com/companies/reducto/jobs/2BVFiJu-software-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$140K - $240K",
        "equity_range": "0.10% - 1.00%",
        "experience": "3+ years",
        "visa": "Will sponsor",
        "skills": [
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        "id": 70899,
        "title": "Machine Learning Engineer",
        "url": "https://www.ycombinator.com/companies/reducto/jobs/3VS78nJ-machine-learning-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Machine learning",
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        "title": "LLM/ML Engineer (Inference)",
        "url": "https://www.ycombinator.com/companies/reducto/jobs/roVp40O-llm-ml-engineer-inference",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Machine learning",
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        "experience": "3+ years",
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      {
        "title": "Reducto: AI document parsing & extraction software",
        "url": "https://reducto.ai/blog/reducto-series-b-funding",
        "date": "Oct 14, 2025"
      },
      {
        "title": "Reducto: Making Human Data LLM-Ready With State-of-the-Art Accuracy",
        "url": "https://www.youtube.com/watch?v=QBC_cViA7j8",
        "date": "May 01, 2025"
      },
      {
        "title": "Exclusive: Reducto, AI document parsing startup, raises $24.5 million Series A led by Benchmark | Fortune",
        "url": "https://fortune.com/2025/04/25/exclusive-reducto-ai-document-parsing-startup-raises-24-5-million-series-a-led-by-benchmark/",
        "date": "Apr 25, 2025"
      },
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        "title": "Reducto Document Ingestion API",
        "url": "https://reducto.ai/blog/reducto-series-a-funding",
        "date": "Apr 25, 2025"
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        "url": "https://reducto.ai/blog/seed-round",
        "date": "Oct 02, 2024"
      }
    ],
    "launches": [
      {
        "id": 82871,
        "title": "Reducto - Structured data from any unstructured document",
        "tagline": "Reducto’s new API makes it easy to turn complex documents and spreadsheets into structured data that fits your schema, with zero fine tuning. ",
        "body": "![uploaded image](/media/?type=post&id=82871&key=user_uploads/850889/1ce99361-5539-4e75-809d-d432d24470a2)\n\n[Reducto](https://reducto.ai) is a team from MIT building vision models to turn complex documents into LLM-ready inputs. Every part of our core API was made to offer the most accurate extraction possible, and we now power document ingestion for leading AI teams ranging from startups to Fortune 10 enterprises. \\\n\\\nWe’re excited to release a new **Structured Extraction API**, which leverages LLMs along with our vision models to extract the data that you need with exceptional accuracy and flexibility. \n\n# **📃 The Problem**\n\n**Nearly 80% of enterprise data is in unstructured formats like PDFs and spreadsheets**\\\nPDFs are the status quo for enterprise knowledge in nearly every industry. They’re stored in a structure that’s simply impractical for use in digital workflows, which leads to [dozens of wasted hours every week](https://www.reducto.ai/blog/the-real-cost-of-manual-document-processing).\\\n\\\n**Custom extraction models require hundreds of hours to build and maintain**\n\nCompanies often use traditional solutions to build a custom extraction pipeline for _every_ document layout they’re working with. That requires dozens of hours for labeling and training the model, and constant maintenance when models break from changing layouts.\\\n\\\n**LLMs offer better flexibility at the cost of reliability**\n\nOff the shelf LLMs _can_ offer exceptional reasoning but they struggle with hallucinations and extraction inaccuracies, making them unreliable for production use cases. \n\n# \n\n# **✅ Our Solution**\n\nWe’ve built vision models to read documents the way a human would, and a language model that we trained for schema-based extraction. Our new model can handle significantly larger documents, and is trained to _cite_ the source for each piece of information, allowing you to audit and verify outputs easily.\n\n![uploaded image](/media/?type=post&id=82871&key=user_uploads/850889/b090586c-1014-4293-a5f3-266950b46338)\n\nThis means you can:\n\n* Extract important fields with simple, natural language instructions\n* Verify any information using our source citations\n* Build powerful automations by integrating Reducto’s API with your custom workflow\n\n# **🚀 Automate your unstructured data processing**\n\nOur API is live in production with leading teams across insurance, healthcare, and finance, and we would love to work with you to improve your unstructured data ingestion.\\\n\\\nThis new API leverages all of the work that we’ve put into improving our document understanding models to make structured extraction work across all layouts with best in class accuracy. \\\n\\\nYou can [sign up](https://reducto.ai/pricing) to get started right away, or reach out to us at [founders@reducto.ai](mailto:founders@reducto.ai) for a demo!",
        "url": "https://www.ycombinator.com/launches/LYd-reducto-structured-data-from-any-unstructured-document",
        "votes": 28,
        "created_at": "2024-08-09T14:58:47.814Z"
      },
      {
        "id": 78035,
        "title": "🔮 Reducto - Unlocking data behind complex documents",
        "tagline": "Our API allows you to convert complex, unstructured documents into structured outputs that are perfect for RAG, process automation, and more.",
        "body": "Hey everyone - [Raunak](https://www.raunakdoes.dev/) and [Adit](https://www.linkedin.com/in/aditabraham/) here 👋🏼\\\n\\\nWe met four years ago while studying computer science at MIT, and we’ve spent the past few years building ML products at companies like Google and NVIDIA. We started building [Reducto](https://reducto.ai) after struggling with document ingestion while consulting for teams integrating LLMs into their applications.\n\n# \n\n# **📃 The Problem**\n\n**Nearly 80% of enterprise data is in unstructured formats like PDFs**\n\nPDFs are the status quo for enterprise knowledge in nearly every industry. Insurance claims, financial statements, invoices, and health records are all stored in a structure that’s simply impractical for use in digital workflows. This isn’t an inconvenience—it’s a critical bottleneck that leads to [dozens of wasted hours every week](https://www.reducto.ai/blog/the-real-cost-of-manual-document-processing).\n\n**Traditional approaches fail at reliably extracting information in complex PDFs**\n\nOCR and even more sophisticated ML approaches work for simple text documents but are unreliable for anything more complex. Text from different columns are jumbled together, figures are ignored, and tables are a nightmare to get right. Overcoming this usually requires a large engineering effort dedicated to building specialized pipelines for every document type you work with. \n\n# **🚀 Our Solution**\n\nReducto breaks document layouts into subsections and then contextually parses each depending on the type of content.\n\n![](https://framerusercontent.com/images/OGE17IqyrDhYFCvrxMFNNtwpLs.png?scale-down-to=2048)\n\nThis is made possible by a combination of vision models, LLMs, and a suite of heuristics we built over time. Put simply, we can help you:\n\n* Accurately extract text and tables even with nonstandard layouts\n* Automatically convert graphs to tabular data and summarize images in documents\n* Extract important fields from complex forms with simple, natural language instructions\n* Build powerful retrieval pipelines using Reducto’s document metadata\n* Intelligently chunk information using the document’s layout data\n\nYou can try a demo [here](https://app.reducto.ai/share/5ecd4726-f482-498d-a1c2-b76e12f595a8). \n\n# **🙏🏼 Our Ask**\n\nWe’re looking to onboard more teams across insurance, healthcare, and finance and would really appreciate your help. If you or someone you know is struggling with high-volume document workflows (5000+ pages), please reach out to us at [founders@reducto.ai](mailto:founders@reducto.ai).",
        "url": "https://www.ycombinator.com/launches/KId-reducto-unlocking-data-behind-complex-documents",
        "votes": 41,
        "created_at": "2024-01-31T20:01:45.526Z"
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    "id": 29256,
    "name": "Momentic",
    "slug": "momentic",
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    "website": "https://momentic.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Momentic makes Mo, the AI QA engineer. Point Mo at your app with a goal and a swarm of agents bug-bashes it the way your team would, then reports every bug with repro steps, logs, and a video replay.\r\n\r\nNotion, Whatnot, Retool, Webflow, Framer, and 1,600+ teams use Momentic.\r\n\r\nTeams also use Momentic to write end-to-end tests in plain English, run them in CI, and let agents triage and maintain the suite across web and mobile.\r\n\r\nLearn more at momentic.ai",
    "one_liner": "Mo, the AI QA engineer that bug-bashes your app before every release",
    "team_size": 18,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1700355696,
    "tags": [
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      "B2B",
      "Enterprise Software",
      "AI"
    ],
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    "isHiring": true,
    "nonprofit": false,
    "batch": "Winter 2024",
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    "industries": [
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    "regions": [
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      "America / Canada"
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/momentic",
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    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/momentic-ai",
    "x_url": "https://twitter.com/MomenticAI",
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    "primary_partner": {
      "name": "Harj Taggar",
      "url": "https://www.ycombinator.com/people/harj-taggar"
    },
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        "user_id": 1327081,
        "full_name": "Wei-Wei Wu",
        "title": "Founder",
        "founder_bio": "Wei-Wei Wu is a co-founder and CEO of Momentic. Previously, he worked at Assembled, building infrastructure and real-time features. Before that, he was the first employee and founding engineer at Nashi, a startup tackling RTO during Covid, which was acquired by Density in 2021.",
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      {
        "user_id": 1637474,
        "full_name": "Jeff An",
        "title": "Founder/CTO",
        "founder_bio": "I'm a curious and driven technical founder hailing from Toronto, Canada. I love up-leveling others through my work and after graduating from the University of Waterloo, I found my calling in cloud and test infrastructure at companies like Splunk, Google, and Robinhood. Aside from engineering, I love traveling the world (over 100K miles flown in 2023!), playing piano, and hiking.\n",
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    "jobs": [
      {
        "id": 85334,
        "title": "Founding Engineer (Frontend)",
        "url": "https://www.ycombinator.com/companies/momentic/jobs/938G5qp-founding-engineer-frontend",
        "location": "San Francisco",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$150K - $220K",
        "equity_range": "0.50% - 1.00%",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
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    "news": [
      {
        "title": "The Q/A Layer for the AI Coding Era",
        "url": "https://www.youtube.com/watch?v=UpWNdSVWA7M",
        "date": "Mar 23, 2026"
      },
      {
        "title": "Momentic raises $15M to become the AI-era ‘source of truth’ for software quality - SiliconANGLE",
        "url": "https://siliconangle.com/2025/11/24/momentic-raises-15m-become-ai-era-source-truth-software-quality/",
        "date": "Nov 24, 2025"
      },
      {
        "title": "Momentic raises $15M to automate software testing | TechCrunch",
        "url": "https://techcrunch.com/2025/11/24/momentic-raises-15m-to-automate-software-testing/",
        "date": "Nov 24, 2025"
      },
      {
        "title": "Momentic raises $3.7M to redefine software testing with AI - SiliconANGLE",
        "url": "https://siliconangle.com/2025/03/04/momentic-raises-3-7m-redefine-software-testing-ai/",
        "date": "Mar 04, 2025"
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      {
        "id": 117199,
        "title": "Momentic: Mo, the AI QA engineer that finds bugs before your users do",
        "tagline": "Point Mo at your app. Get back the bug report, with repro steps, logs, and a video replay of each one.",
        "body": "**TL;DR:** Mo is an AI QA engineer. Give it any app (web, iOS, or Android) and a goal, and it launches hundreds of agents that bug-bash every nook and cranny of your app the way your team would before a release. You get one report: what was tested, what failed, repro steps, logs, and a video replay of each bug. We’re giving every sign up $250 in free credits at [momentic.ai](http://momentic.ai).\n\nLaunch video: <https://youtu.be/5RMQVtk-ayE>\n\n**Hey YC, we're Wei-Wei and Jeff.** We launched Momentic here in YC W24 as AI-powered end-to-end testing, and teams like Notion, Whatnot, and Retool run their test suites on it today. Today we're launching Mo.\n\n**The problem**\n\nClaude Code, Cursor, and Devin made writing code super easy. Testing is still the bottleneck. Over the past two years, our customers kept telling us: \"I don't want another script to write and maintain\" and \"Now I'm paying double, for QA and for a testing tool we have to use.\" No one asked for another testing framework to learn. All they wanted was no bugs.\n\n**How Mo works**\n\n1. Point Mo at your app and tell it what to test, in plain English: \"bug bash the checkout flow.\"\n2. Mo launches hundreds of agents in parallel on our hosted browsers and emulators/simulators. They click through the app just like a QA engineer would and cover every edge case, every nook and cranny.\n3. Every bug report has repro steps, logs, screenshots, and a video replay. File a ticket or hand it to your coding agent to fix.\n\n![uploaded image](/media/?type=post&id=117199&key=user_uploads/1327081/d363fb1e-977d-4c17-84dd-c3b9a8fcc89f)\n\nHere's one from this week. Mo hit Search on GitHub's Pull requests page without touching the prefilled query; GitHub wiped the query and threw an empty-query error. One prompt: \"bug bash\" plus the URL.\n\n**Results so far**\n\nNotion, Glide, Superpower and other teams put Mo on their own apps. Across the beta: Mo ran 1,100+ bug bashes and caught 3,500 verified bugs. One customer told us: \"I reviewed the findings and merged fixes for 10 of them. How did we not catch this already?\"\n\nIn our evals, Mo found 3.8x more bugs than Codex with Playwright MCP, 9x more bugs per hour, at half the cost per bug.\n\n![uploaded image](/media/?type=post&id=117199&key=user_uploads/1327081/a08dc6e5-a978-457b-9e88-d5ebce725be1)\n\n**Why we built it**\n\nWe started Momentic because we hated testing. At Nashi, I spent four hours every Thursday evening manually testing before a release. Two years of selling Momentic taught us that teams don't want better scripts; they want no bugs, so we built Mo to find them.\n\n**Our ask**\n\n* Try it on your app: [momentic.ai](http://momentic.ai), $250 in free credits on signup.\n* YC founders: we have a [sick YC deal](https://bookface.ycombinator.com/deals/2562) to redeem on Bookface.\n* Questions or a bug you want us to look at: DM me on X [@wuweiweiwu](https://x.com/wuweiweiwu).\n\nWei-Wei and Jeff",
        "url": "https://www.ycombinator.com/launches/UUJ-momentic-mo-the-ai-qa-engineer-that-finds-bugs-before-your-users-do",
        "votes": 211,
        "created_at": "2026-09-28T16:00:11.921Z"
      },
      {
        "id": 79067,
        "title": "Momentic - Automated testing with AI",
        "tagline": "Use AI to automate the most tedious parts of software development.",
        "body": "Hey everyone 👋 We’re Wei-Wei and Jeff and we're building [Momentic](https://momentic.ai). We're on a mission to make testing easy and fast for developers.\n\n# **TL;DR**\n\nDevelopers author E2E tests 10X faster with Momentic’s low-code editor. We make AI do the heavy lifting for you: finding elements, reasoning about assertions, visual comparisons, and even generating whole test cases!\n\n# **Testing still sucks!**\n\nThe average developer today still spends hundreds of hours every year writing and maintaining test suites in Selenium, Cypress, or Playwright. Existing no-code solutions like Browserstack and Tricentis are often unreliable and difficult to use, forcing teams to fallback on manual QA.\n\nThe bottom line is: **testing slows you down**, and all companies eventually encounter a tradeoff between velocity and quality.\n\n# **What if testing could help developers ship _faster_?**\n\nOur low-code test editor replaces traditional test scripts with AI-powered, self-healing steps. It seamlessly integrates into your existing workflows: from local development to CI/CD environments and production.\n\nHere’s how it works:\n\n_Interact with your app in plain English._\n\n![uploaded image](/media/?type=post&id=79067&key=user_uploads/1327081/d3261cce-cd3a-4f9c-bc55-0cea1533260f)\n\n_Craft assertions from any logical statement or visual condition._\n\n![uploaded image](/media/?type=post&id=79067&key=user_uploads/1327081/9a4fdfe4-f7d8-4183-a4a1-7b09ade815ac)\n\n_Record and replay actions on any site, even those on localhost._\n\n![uploaded image](/media/?type=post&id=79067&key=user_uploads/1327081/25e50c1d-dd84-4e7f-aafa-00e33618b42e)\n\n# **Meet the team**\n\nWe’re [Wei-Wei](https://www.linkedin.com/in/hungweiwu/) and [Jeff](https://www.linkedin.com/in/jeff-an/) - two software engineers who dreaded testing so much we founded a company to do it for us 😂.\n\nWe-Wei was a founding engineer at Nashi and then a staff engineer at Density, leading product engineering and product reliability. Jeff led testing at Robinhood and enterprise quality at Retool, and saw first-hand how lack of testing can impact a company’s bottom line.\n\n![uploaded image](/media/?type=post&id=79067&key=user_uploads/1327081/d66b58e4-4dfa-45f9-89c9-d2cfa4b9bc95)\n\n# **Our ask**\n\nMomentic is currently in private beta, working closely with early customers. We plan to give access to a select few companies in the next few weeks, so please reach out to [founders@momentic.ai](mailto:founders@momentic.ai) or [book a call](https://momentic.ai/demo).\n\nWe would love to work with you if:\n\n1. You want to use Momentic to accelerate development teams without sacrificing quality.\n2. You currently spend more time and resources than you’d like on testing.\n\nWe offer plans for teams of all sizes and offer features such as white-glove onboarding, accessibility audits, visual diffing, environments, source control, custom SSO, and migrations from existing frameworks.\n\nFor more details, visit [momentic.ai](http://momentic.ai).\n\nThank you!\n\nWei-Wei and Jeff",
        "url": "https://www.ycombinator.com/launches/KZH-momentic-automated-testing-with-ai",
        "votes": 341,
        "created_at": "2024-03-05T15:30:46.181Z"
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        "full_name": "Prasoon Shukla",
        "title": "Founder",
        "founder_bio": "Prasoon worked at Stripe, Goldman Sachs and Klarna for over 7 years as a Data Scientist, building ML models and analytics for Stripe's payment fraud, Klarna's US credit market and Goldman's market risk data.\n\nHe graduated from IIT Roorkee in India with a degree in Applied Maths.",
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        "full_name": "Ramon Garate",
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        "founder_bio": "payments. ex-stripe, ex-klarna",
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        "linkedin_url": "https://linkedin.com/in/ramon-garate-4b379093",
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    "id": 29266,
    "name": "nCompass Technologies",
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    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1708296726,
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      "name": "David Lieb",
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      {
        "user_id": 1641909,
        "full_name": "Aditya Rajagopal",
        "title": "Founder",
        "founder_bio": "I am a recent PhD graduate from Imperial College London with experience in machine learning algorithms, compilers and hardware architectures. I've worked in compiler teams at Qualcomm and Huawei as well as served as a reviewer for ICML. \n\nMy co-founder and I are building nCompass which is a platform for accelerating and hosting both open-source and custom large AI models. Our focus is on providing rate unlimited and low latency large AI inference with only one line of code.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/adityarajagopal",
        "x_url": "https://twitter.com/adityaraja0",
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      {
        "user_id": 1641938,
        "full_name": "Diederik Vink",
        "title": "Founder",
        "founder_bio": "I'm a recent Imperial College London PhD Graduate where I specialized in reconfigurable hardware architectures for accelerated machine learning and reduced precision training algorithms. I have worked as an AI feasibility consultant prototyping and evaluating AI spin-outs.\nWe are building nCompass, a platform for accelerating and hosting both open-source and custom large AI models. Our focus is on providing rate-unlimited and low latency large AI inference with only one line of code.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/diederik-vink",
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      {
        "id": 98338,
        "title": "nCompass - Optimize performance on GPUs, 10x faster",
        "tagline": "Automate performance optimization at all levels of the AI infrastructure stack",
        "body": "Hey everyone,\n\n**tldr;**\n\nI’m Aditya, co-founder of [nCompass Technologies](https://ncompass.tech). We’re building a developer tool that unifies profiling, trace collaboration and trace analysis of AI systems. We automate performance optimization of AI systems across all levels of the infrastructure stack.\n\nUsing this tool, we implemented a Hopper GEMM kernel that outperformed NVIDIA's CUTLASS GEMMs by 3%, within a day - this took us months before.\n\nCheckout our product demo below. It’s free to use and you can get started today in **VS Code, Cursor or Claude Code** - [Quick Start](https://docs.ncompass.tech/quick-start)\n\n<https://www.youtube.com/watch?v=Q3Pq-BPU2Ec>\n\n**THE PROBLEM**\n\nIdentifying the root cause of performance bottlenecks is 4-8x slower than writing the code to fix them.\n\nIf you are optimizing a system like vLLM, you have to:\n\n* Run a profile and then copy a giant trace file to your local machine just to view it.\n* Spend hours identifying opportunities for performance improvement.\n* If this involves writing a kernel, you profile the kernel, spend hours or days digging through ncu traces that are massive data dumps.\n* Then you identify your bottlenecks and formulate a plan.\n\nRunning this loop till you have a performant system can take weeks, even months.\n\n**OUR SOLUTION**\n\nBy building an AI agent that can analyze profiling data as well as interact with a bank of deep technical knowledge and expertise, we’re automating the process of identifying performance bottlenecks.\n\nNow in a single VSCode interface, you can:\n\n* Open and view trace files\n* Use our novel tools like trace diffs to analyze them\n* Generate share links to easily share traces with team members\n* Feed source + profiling data to our AI agent and get back actionable analysis on how you can optimize the performance of your system.\n\nThis applies to both systems and GPU kernel level analysis and our agent integrates directly into Cursor / Claude Code, so you never have to leave your normal workflow!\n\n**Anyone** can now write both correct and performant code with AI!\n\n**ASKS**\n\n**Install our VSCode extension** and start optimizing your systems performance!\n\n* [Quick Start](https://docs.ncompass.tech/quick-start)\n* [Detailed Docs](https://docs.ncompass.tech)\n\n**We also offer FDE services** - if you would like us to step in and analyze your system’s performance and provide you with an analysis of how much we could improve it by - reach out at [hello@ncompass.tech](https://mailto:hello@ncompass.tech)\n\n![uploaded image](/media/?type=post&id=98338&key=user_uploads/1641909/fc628a90-5565-43db-8aff-7c61e476e976)\n\n",
        "url": "https://www.ycombinator.com/launches/Pa6-ncompass-optimize-performance-on-gpus-10x-faster",
        "votes": 19,
        "created_at": "2026-03-02T17:12:19.098Z"
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      {
        "id": 84604,
        "title": "nCompass Technologies: Reliable LLM API with no rate-limits",
        "tagline": "The most cost-effective way to setup and scale up your AI infrastructure.",
        "body": "# **Tl;dr:**\n\nWe’ve built an AI model inferencing system that can serve requests at scale like no other and now we’re releasing it to the public as a **rate-limit-free API**. We serve any open-source LLM and can also deploy optimized versions of your custom fine-tuned LLM with cost-effective autoscaling. [Sign up here](https://console.ncompass.tech/login), create an API key, get $100 of credit on us, and run as many requests as you like!\n\n# **The Problem**\n\nDeploying AI models in production requires expensive infrastructure. Serving more than \\~10req/s using open source inference engines like vLLM on a single GPU results in terrible quality of service. Time-to-first-token skyrockets to more than 10s, and end-to-end latency degrades even more!\n\n**The common solution**: horizontally scale up GPUs.\n\n**The problem**: GPU’s are expensive and hard to find.\n\n# **Why should you care**\n\n1. **API user:** These high infrastructure costs are the reason you suffer rate limits when using existing API providers.\n2. **Deploying on-prem:** Your infrastructure costs might be the reason a PoC doesn’t move to production.\n\n# **Our Solution**\n\nWe’ve built an AI inference serving system that can sustain 100s of requests per second while maintaining a time-to-first-token of <1s on \\~30% fewer GPUs when compared to NVIDIA’s NIMs containers and up to **2x fewer GPUs** when compared to vLLM.\n\nThis enables us to provide a rate-limit-free API while maintaining a high quality of service. Alternatively, we can provide this as a cost-effective on-prem deployment solution, ensuring your infrastructure costs don’t blow up with requests served. We support any open source model and can host your custom fine-tuned model as an API with autoscaling enabled as well.\n\n# **Tutorials**\n\n* [**Sign Up**](https://www.loom.com/share/bac5c44a8e694b5783f3ba7c777ce40a?sid=6226613a-2cd6-45e6-bfc3-ac0381198b2a)\n* [**Models and Pricing**](https://www.loom.com/share/f7dc12aefe304399a3975feef7e38938?sid=34c2a174-4050-40bc-b65a-844d3002e48c)\n* [**Run Inference**](https://www.loom.com/share/0933dc3fa2ba442fa789286ef75e09b8?sid=74266aa3-f24e-46d7-bcce-1f3c61d7d82e)\n\n# **Shout out**\n\nTo be able to build such a scalable and available system, we needed a top-quality hardware provider. We wanted to use this as an opportunity to shout out [Ori Global Cloud](https://www.ori.co/), a key partner in this journey, to enable a serverless Kubernetes platform for AI inference at scale. [Ori Serverless Kubernetes](https://www.ori.co/serverless-kubernetes) is an infrastructure service that combines powerful scalability, simple management, and affordability to help AI-focused startups realize their wildest AI ambitions. [Reach out to Ori](https://www.ori.co/gpu-request) for exclusive GPU cloud deals!\n\n# **Asks**\n\n* Use our self-serve console (<https://console.ncompass.tech/login>) to create an account and start running with $100 of credit.\n* Book a demo (<https://calendar.app.google/3jRDwcstFQvsbqnR8>) if you would like to discuss an on-prem solution. YC deals apply!\n\nOur pricing is transparent and can be found here: <https://console.ncompass.tech/public-pricing>",
        "url": "https://www.ycombinator.com/launches/M0a-ncompass-technologies-reliable-llm-api-with-no-rate-limits",
        "votes": 37,
        "created_at": "2024-10-09T14:26:51.395Z"
      },
      {
        "id": 81420,
        "title": "nCompass Technologies: Realtime audio denoising",
        "tagline": "nCompass's newest model is a realtime audio denoiser that can remove voices from the background of audio streams.",
        "body": "**tl;dr** nCompass has released the world’s first **Realtime Audio Denoising API** that can remove background voices from your audio stream in real time. Try it out for free on our website [here](https://www.ncompass.tech/about).\n\nToday, the world is increasingly interacting with AI models using voice. Apps and tools that rely on voice input need to be able to successfully separate background voices from the main speaker’s voice. However, this is not the case with existing voice AI products such as Deepgram’s speech-to-text (STT) converter.\n\nCheck out this demo below that shows how using nCompass’s denoiser can enable transcription tools (such as Deepgram’s STT) to be used in previously unusable scenarios.\n\n![uploaded image](/media/?type=post&id=81420&key=user_uploads/1641909/61bc7f02-4a23-4ab2-b7fc-cd2a8ad3b01e)\n\nWe have two versions of this denoiser that you can try out for free on our [website](https://www.ncompass.tech/about).\n\n1. [Offline denoising + transcription](https://www.ncompass.tech/cleaner_transcription/interactive_demo) mode, which generates cleaner transcriptions when paired with any speech-to-text provider.\n2. [Realtime audio denoising,](https://www.ncompass.tech/realtime_denoising/interactive_demo) which can take in an audio stream and remove background voices in real time. You can now get the sound quality of a private booth, regardless of where you are!",
        "url": "https://www.ycombinator.com/launches/LBE-ncompass-technologies-realtime-audio-denoising",
        "votes": 24,
        "created_at": "2024-06-11T16:23:04.390Z"
      },
      {
        "id": 79124,
        "title": "nCompass Technologies - Low-latency deployment of AI models made easy",
        "tagline": "nCompass is an API that requires only one-line-of-code to integrate low latency versions of open-source/custom models into your AI pipeline.",
        "body": "**tl;dr** If unpredictable response times and rate limits of OpenAI are causing your tool’s user experience to suffer, [nCompass](https://ncompass.tech/) allows you to effortlessly tap into the world of open-source AI models while ensuring that the served models meet your target budget and performance requirements.\n\n—\n\nHey all, we are [Diederik](https://linkedin.com/in/diederik-vink) and [Aditya](https://linkedin.com/in/adityarajagopal), the co-founders of [nCompass](https://ncompass.tech/), a platform for simplified hosting and acceleration of open-source and custom LLMs.\n\n### **The Problem**\n\nLLM-based products that use closed-source model providers like OpenAI suffer from slow response times and rate limits. \n\nOpen-source models are a great alternative, but hosting a model yourself is a lot of extra work and maintenance which distracts you from your core business.\n\n### **Our solution**\n\nnCompass provides an API that allows you to integrate accelerated versions of any open-source or custom model of your choice into your AI pipeline. We support OpenAI style chat templates, work with all web frameworks, and have a time-based pricing model that results in a predictable compute cost for users.\n\n### **How it works**\n\nWe serve models to users with a simple 3-step process:\n\n1. Select your desired open-source / custom model\n2. Provide your performance requirements\n3. Set a budget you are not willing to exceed\n\nWe set up the deployment that meets these requirements and provide you with a single API Key that you can then use to integrate the model with a single line of code.\n\nWe support any model currently hosted on Hugging Face, with some highlights being: \n\n* **Mistral-7B :** 160ms Time-To-First-Token @ 86 tok/s\n* **Mixtral-8x7B :** 300ms Time-To-First-Token @ 64 tok/s\n\n### **Demo**\n\n<https://www.youtube.com/watch?v=sdHVji8QGOg> \n\nAlso, check out our [GitHub](https://github.com/nCompass-tech/nCompass) repository for code examples.\n\n### **The team**\n\nSince we met in undergrad (9 years ago) through to our PhDs at Imperial College London, we’ve worked on every project together. Our PhDs focused on hardware acceleration of large-scale machine learning models covering all levels of the stack from algorithms and compilers down to digital hardware design.\n\n![uploaded image](/media/?type=post&id=79124&key=user_uploads/1641909/8f0f2b1e-8c86-4269-828e-a90176159dd6)\n\n### **Asks**\n\n* Book a [demo](https://calendar.app.google/eLCRjByYErh9X2hh9) \n* **Warm intros** to anyone you know who requires accelerated and/or hosted versions of open-source models.\n\nOur emails are [aditya.rajagopal@ncompass.tech](mailto:aditya.rajagopal@ncompass.tech) and [diederik.vink@ncompass.tech](mailto:diederik.vink@ncompass.tech)",
        "url": "https://www.ycombinator.com/launches/KaC-ncompass-technologies-low-latency-deployment-of-ai-models-made-easy",
        "votes": 97,
        "created_at": "2024-03-06T18:41:41.718Z"
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    "id": 29275,
    "name": "Agentic Labs",
    "slug": "agentic-labs-2",
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    "website": "https://agenticlabs.com",
    "all_locations": "New York City, NY, USA",
    "long_description": "Agentic Labs is making software design and architecture less painful by building AI into the process. Today, developers have no shortage of tools for instantly creating chunks of code, but designing the systems that integrate this code is the hardest and most manual part of software engineering.\r\n\r\nOur first product is Glide, an AI-first editor purpose-built for writing technical design docs. It connects to your codebase and saves your engineering team time on triage, planning, and implementation of complex code changes.",
    "one_liner": "AI system design tools for dev teams",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1708588457,
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    "nonprofit": false,
    "batch": "Winter 2024",
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    "regions": [
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      "America / Canada"
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/agentic-labs-2",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/agentic-labs-2.json",
    "year_founded": 2023,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/agentic-labs/",
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    "primary_partner": {
      "name": "Tom Blomfield",
      "url": "https://www.ycombinator.com/people/tom-blomfield"
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    "founders": [
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        "user_id": 494069,
        "full_name": "Maksim Ivanov",
        "title": "Founder/CEO",
        "founder_bio": "Building self-assembling software. Previously at hedge funds and doing ML research",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/maksivanov",
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    "launches": [
      {
        "id": 78636,
        "title": "Agentic Labs - AI system design tools for dev teams",
        "tagline": "Introducing Glide - a new way to build software with AI",
        "body": "At Agentic Labs, we believe developers shouldn’t have to choose between thoughtfully designing code and shipping quickly.\n\n### Problem\n\nCreating a good technical design makes the implementation 10x easier for most coding tasks, but it’s a slow and manual process. We’ve experienced this at companies like Bridgewater and SpaceX, where reliable and maintainable software is mission-critical.\n\nConversely, in a startup, you build super fast, but it’s easy to find yourself being **crushed** by the complexity you’ve created because you didn’t have time to write a spec or analyze 3 different approaches.\n\nUntil now, you’ve probably had to pick one of these two extremes.\n\n### Solution\n\nWe’re building Glide, an AI-first editor purpose-built for writing technical design docs. It integrates with your codebase, saving engineers time on triage, planning, and implementation of complex code changes.\n\nHere’s how you use it:\n\n### 1\\. Get started by adding a repo, setting the goal, and attaching code\n\nWe’re demonstrating on an open ticket in Vercel’s AI-Chatbot repo\n\n* **Repo** here: <https://github.com/vercel/ai-chatbot>\n* **Goal** was inspired by the ticket here: <https://github.com/vercel/ai-chatbot/issues/226>\n* **Code** was added that is relevant to the task\n\n### 2\\. Triage the task in one click\n\n_Jump-start your thinking._ _Refine and edit in-line._\n\n<https://youtu.be/2wpdJlTNkE8>\n\n### 3\\. Triage → Plan\n\n_From your triage, generate a step-by-step plan._\n\n![uploaded image](/media/?type=post&id=78636&key=user_uploads/1577346/5a56256d-b81b-450b-b94c-8de7c5b1cd05)\n\n### 4\\. Plan → Implement\n\n_Once you like the plan, generate detailed code edits._\n\n![uploaded image](/media/?type=post&id=78636&key=user_uploads/1577346/369930b6-7af5-4129-bb0f-2ac831063e61)\n\n### 5\\. Send to VSCode to complete the change\n\n_Yes, we know, automatic PRs are coming soon._\n\n<https://youtu.be/0xz3uiHxg0c>\n\n### Chat with a fully-informed AI assistant at any time\n\n<https://youtu.be/zSjvqpnuocI>\n\n### Our ask\n\n* If your team has 10+ software engineers and you’re investing in a technical design process for code quality and speed, let’s talk\n  * **Call / text:** 858-663-1633\n  * **Set up time:** <https://calendly.com/d/457-4zq-s7p/user-interviews>\n  * **Email:** [rob@agenticlabs.com](mailto:rob@agenticlabs.com)",
        "url": "https://www.ycombinator.com/launches/KSK-agentic-labs-ai-system-design-tools-for-dev-teams",
        "votes": 40,
        "created_at": "2024-02-22T16:11:40.986Z"
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    "id": 29278,
    "name": "Leaping",
    "slug": "leaping",
    "former_names": [
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    "website": "https://www.leaping.io/",
    "all_locations": "New York City, NY, USA",
    "long_description": "When bad software gets shipped, software companies burn a lot of money and customer trust fixing it. Most software engineers will tell you they spend more time fixing code than writing it, which will only become more true as AI code assistants gain adoption. Leaping autonomously root causes bugs and generates tested code fixes.",
    "one_liner": "Automate bug resolution",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1710320350,
    "tags": [
      "Developer Tools",
      "AI Assistant"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2024",
    "status": "Active",
    "industries": [
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    "regions": [
      "United States of America",
      "America / Canada"
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    "stage": "Early",
    "app_video_public": false,
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/leaping",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/leaping.json",
    "year_founded": 2024,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/leapinglabs",
    "x_url": "https://twitter.com/leapinglabs",
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    "cb_url": null,
    "github_url": "https://github.com/leapingio",
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    "founders": [
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        "user_id": 1058341,
        "full_name": "Adrien Philardeau",
        "title": "Founder/CEO",
        "founder_bio": "Co-Founder at Leaping",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/adrienphilardeau",
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    "id": 29296,
    "name": "Simplex",
    "slug": "simplex",
    "former_names": [
      "Simplex",
      "Pansimulate"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/556d5a66ef0386d859db3ad9f500ceeadf756032.png",
    "website": "https://simplex.sh",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Simplex builds AI agents to handle provider enrollment end-to-end. We automate pulling provider data from CAQH, filling out enrollment forms + uploading licenses via payor portals/email/phone, updating applications when returned for corrections, and performing effective date follow-ups until a final determination is made, all autonomously.",
    "one_liner": "AI agents to enroll providers with payors",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1723709594,
    "tags": [
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      "Robotic Process Automation",
      "B2B",
      "AI"
    ],
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    "nonprofit": false,
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      "America / Canada"
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    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/usesimplex",
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      "name": "Aaron Epstein",
      "url": "https://www.ycombinator.com/people/aaron-epstein"
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    "founders": [
      {
        "user_id": 1588677,
        "full_name": "Shreya Karpoor",
        "title": "Founder/CEO",
        "founder_bio": "Shreya is the co-founder and CEO of Simplex. She holds a BS and MEng in Electrical Engineering and Computer Science from MIT. She previously built software at Tesla and researched dexterous robotic manipulation at MIT.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/shreya-karpoor",
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      },
      {
        "user_id": 910356,
        "full_name": "Marco Nocito",
        "title": "Founder/CTO",
        "founder_bio": "Marco is the co-founder and CTO of Simplex. He holds a BS and MEng in Computer Science from MIT. He previously built machine learning models to generate synthetic data at Waymo and built data infrastructure tooling at Viam and Bloomberg.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/marco-nocito/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/dba39276e5b4d649b475457eb63e059283e2a78e.jpg"
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    ],
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    "launches": [
      {
        "id": 90728,
        "title": "Simplex - enterprise-grade web agents",
        "tagline": "AI agent companies automate legacy portals using our SDKs.",
        "body": "Simplex builds enterprise-grade web agents that companies use to integrate with legacy portals. We handle everything from building the web agents for you to integrating directly with your existing software stack like forward deployed engineers.\n\nCustomers use Simplex in production right now to:\n\n* submit information from outbound calls into freight software\n* edit and download their customers’ invoices\n* fetch websites’ internal APIs\n* and more.\n\nhttps://youtu.be/97gX3I9PMZ0\n\n# The Problem\n\nLegacy portals aren’t well suited for web agent automation — portals are unintuitive to navigate and functionality is often broken.  Existing web agents like Operator lack fine-grained control over agent behavior and can’t consistently perform these critical legacy workflows.\n\nA fully autonomous AI might fail to reach the desired page, get stuck pressing a broken button, or mistype critical information like an invoice amount or a shipping address. Without control over agent behavior and clear observability during workflows, web agents are blocked from being used during production in these critical scenarios.\n\n# The Solution\n\nSimplex is the production-grade web agent platform that enables AI agents to reliably do work on legacy portals at scale. You can see a live demo of Simplex below – the demo is at 1x speed.\n\nhttps://youtu.be/4VSexxYptV4\n\nWe’ve engineered Simplex to give AI agent developers control, transparency, and reliability. With Simplex you can:\n\n* easily **integrate with your existing stack** – pass the results from LLM calls, databases, your existing agents into Simplex\n* **cache element actions** for speed and consistent performance\n* build **strong evals** to stress-test your workflows at scale and emulate production conditions\n* scale up to **100s of concurrent browser sessions** while handling CAPTCHAs, 2FA, and website authentication on your customers’ portals\n* ensure **no incorrect actions** are taken — if you prompt our agents to click on elements that don’t exist on the page, we'll raise an exception\n* debug with shareable **session replays** and **detailed agent logs**\n\n# The Team\n\n[Shreya Karpoor](https://www.linkedin.com/in/shreya-karpoor/) and [Marco Nocito](https://www.linkedin.com/in/marco-nocito/) are MIT grads who’ve spent years doing computer vision work at Waymo, Tesla, and within MIT labs. They’re excited to use their expertise to bring reliable web agents into widespread production.\n\n# \n\n# Our Ask\n\n* [Book a call here](https://cal.com/marco-nocito-kon7ng/30min) if you want to request API access.\n* [Visit our website here](https://www.simplex.sh/) to see a live demo of Simplex.",
        "url": "https://www.ycombinator.com/launches/NbM-simplex-enterprise-grade-web-agents",
        "votes": 17,
        "created_at": "2025-05-27T14:42:32.436Z"
      },
      {
        "id": 87190,
        "title": "Simplex - Web automation for developers",
        "tagline": "API to automate manual workflows on the web",
        "body": "**TL;DR:**\n\n* Simplex is an API that allows you to automate manual workflows on the web. For example, a customer uses us to autonomously purchase materials from Amazon, poll their email inbox for tracking information, then update their internal documentation with that tracking info every six hours.\n* Book [time with us here](https://calendly.com/simplex-interest/marco-chat) if we can help you automate your business.\n\nHi everyone, we’re [Shreya](https://www.linkedin.com/in/shreya-karpoor/) and [Marco](https://www.linkedin.com/in/marco-nocito/), two MIT grads building Simplex.\n\nTeams are often burdened by manual tasks that have to be repeated thousands of times per month — for example, populating spreadsheets with information from recent emails. From our experience, we found that asking AI agents to solve these problems just didn’t work. They often didn’t follow the same path when we asked them to do the same thing twice, and we couldn’t control any of the actions they took when they made a mistake.\n\nSo we built Simplex to inject intelligence into repeatable, known workflows to help you automate your manual tasks.\n\nWith Simplex, writing a function to pull tracking information from your email is as easy as this:\n\n![uploaded image](/media/?type=post&id=87190&key=user_uploads/910356/27f7171e-7a04-408e-84f9-d7596b9a2e5b)\n\n**Watch a quick demo here:**\n\n<https://www.loom.com/share/9d99e4fdf9e14487ba340d5565c123a2?sid=1d3b2dd6-5e78-4370-bbca-1949fc72eb8e>\n\nA few reasons customers love Simplex:\n\n* **Straight-forward, reliable intelligence:** We break up your web workflows into smaller, more atomic actions (click, type, extract) to enforce while allowing you to leverage the intelligence of AI.\n* **Extract anything on the web:** We’ve built our own vision system to more accurately extract small icons, text, images, or even entire sections of a page.\n* **Run on any site, even internal tooling:** We store your credentials securely to handle website authentication, meaning you can use Simplex on any website or private tooling you have access to.\n* **No need to deal with browser infrastructure yourself:** We handle all the infrastructure, hosting, and scheduling, letting you run these workflows asynchronously at scale.\n\nPeople have requested Simplex to:\n\n* **act as procurement software:** automatically order parts and update internal spreadsheets with delivery information across multiple vendors (Amazon, DigiKey, etc.)\n* **scrape financial information for their hedge fund clients:** pull daily headlines and perform sentiment analysis across hundreds of financial websites for quantitative analysis research\n* **autonomously update their internal database of products:** aggregate manufacturer marketing information for over 2,000,000+ retail products\n* **do the work of an entire data collection team:** collect grant and award information from over 700 government websites\n* and more…\n\n## Our Ask\n\n* We’re looking to onboard teams, especially those that are burdened by manual processes or need to scrape hundreds of thousands of websites. Book a [meeting with us](https://calendly.com/simplex-interest/marco-chat) for a demo and API access. We’re happy to write your first automation for you.",
        "url": "https://www.ycombinator.com/launches/MgI-simplex-web-automation-for-developers",
        "votes": 15,
        "created_at": "2025-01-27T15:36:17.454Z"
      },
      {
        "id": 83077,
        "title": "Simplex: on-demand photorealistic vision datasets",
        "tagline": "Receive millions of high quality images and labels for training your AI models.",
        "body": "**TL:DR;** Simplex creates photorealistic vision datasets rendered from 3D scenes for AI model training. Submit a request [on our website](https://simplex.sh/#data-request-form) to receive high-quality data and labels.\n\n![uploaded image](/media/?type=post&id=83077&key=user_uploads/1588677/826c7bea-8936-451d-97ff-895bc8ca6c38)\n\n**Data request for the above sample:** _“Generate images and labels of a home kitchen with household objects on a center table. I need a variety of household objects in a variety of lighting conditions. Our desired labels are semantic segmentation and depth maps.”_\n\nHi everyone, we’re [**Shreya**](https://www.linkedin.com/in/shreya-karpoor/) and [**Marco**](https://www.linkedin.com/in/marco-nocito/), two MIT grads building Simplex.\n\nCollecting vision data for model training is time-consuming, costly, and often unsafe. Shreya spent over 200 hours physically operating a robot to collect image training data during her research at MIT. Marco worked on machine learning for synthetic data at Waymo to solve this exact problem.\n\nWe realized data scarcity wasn’t just an issue in robotics – it affects any company training vision models. When fine-tuning foundation models or building a new dataset from scratch, teams must curate existing data or label and collect data themselves. \n\nWe resolve the data scarcity problem by generating photorealistic ground truth labeled datasets for **any scenario**. We can generate **millions of varied images** **from 3D scenes** using our physics engine pipeline.\n\nHere’s how you’d use Simplex:\n\n1. Fill out our data request form [here](https://simplex.sh/#data-request-form) – it takes less than a minute. \n2. Give us feedback on a few sample image/label pairs that we generate. Repeat if necessary.\n3. Once you’re satisfied, download your complete dataset.\n\nWe support semantic segmentation, captions, simulated LiDAR, depth maps, and bounding boxes. You can generate large volumes of randomized scenes or provide a CAD/phone scan model for more specific scenes.\n\n# **Our Ask**\n\n* If you or someone you know needs vision data, fill out our 30-second data request [form.](https://www.simplex.sh/#data-request-form) We’re taking a limited number of early customers.\n* If you have a more complicated request or would otherwise like to contact us, email [shreya@simplex.sh](https://mailto:shreya@simplex.sh).\n\n# **The Team**\n\n![uploaded image](/media/?type=post&id=83077&key=user_uploads/1588677/d2e5778c-86c2-4c7b-bc75-3c73aefff883)\n\n[**Shreya**](https://www.linkedin.com/in/shreya-karpoor/): Computer science (BS and MEng) at MIT, software engineer at Tesla and Viam. Built simulation pipelines for locomotion and dexterous manipulation research at MIT. \\\n[**Marco**](https://www.linkedin.com/in/marco-nocito/): Computer science (BS and MEng) at MIT, software engineer at Waymo, Bloomberg, and Viam. Built machine learning models to generate synthetic data at Waymo.",
        "url": "https://www.ycombinator.com/launches/Lbx-simplex-on-demand-photorealistic-vision-datasets",
        "votes": 407,
        "created_at": "2024-08-15T14:29:52.537Z"
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    "name": "atopile",
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "atopile is a new language to design electronic circuit boards with code. We replace point and click graphical interfaces with code to bring software level automation and reuse to the field of hardware design. Our project is open source on GitHub! https://github.com/atopile/atopile",
    "one_liner": "We make tools to design electronics circuit boards with code",
    "team_size": 5,
    "industry": "B2B",
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    "launched_at": 1709142669,
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    "url": "https://www.ycombinator.com/companies/atopile",
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    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/99142194/",
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      "name": "Jared Friedman",
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        "full_name": "Narayan Powderly",
        "title": "Founder",
        "founder_bio": "If something sucks, fix it. I love building tools that solve real problems, at Tesla I increased the rate at which we could build prototypes by 10x, at our company atopile we are making tools to bring the speed of software development to hardware engineering.",
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        "title": "Member of Technical Staff",
        "url": "https://www.ycombinator.com/companies/atopile/jobs/R9fCx9Y-member-of-technical-staff",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$180K - $300K",
        "equity_range": "0.10% - 1.00%",
        "experience": "3+ years",
        "visa": "Will sponsor",
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      {
        "id": 78992,
        "title": "atopile - a new language to design electronic circuit boards with code",
        "tagline": "We are bringing design reuse, version control, and automation to hardware design",
        "body": "Hi Everyone, we are Matt, Narayan, and Tim and we are building a new programming language to automate hardware design.\n\n### **TLDR;** [atopile](http://atopile.io/) is a new language + toolchain to **design electronic circuit boards with code**.\n\nBy using code instead of graphical user interfaces, we finally bring **design reuse**, **version control,** and **automation** to hardware design.\n\n![uploaded image](/media/?type=post&id=78992&key=user_uploads/333030/65a69aca-5a22-4af8-9b16-21b76934d36e)\n\n### Our ask 📣\n\n* If you love programming, git, and electronics, try [**using atopile**](https://github.com/atopile/atopile) to design your next circuit board\n* If you know firmware engineers, test teams, validation teams or people who need to create lots of high-quality repetitive designs quickly - [**please introduce us**](mailto:founder@atopile.io)**.**\n\n### The problem\n\nWe love designing hardware. But existing design tools are slowing us down. The key reason is that in hardware design, everything is done manually: Electronic schematics are drawn by hand, files are exported through a series of clicks, and circuit boards are validated for weeks on the test bench. When systems become complex, this process becomes hugely time-consuming and error-prone. \n\nImagine writing an entire complex software program using only assembly code. This is what designing hardware feels like today.\n\n### The solution\n\n![uploaded image](/media/?type=post&id=78992&key=user_uploads/333030/7f5d19f8-f3b0-4eab-958a-f28875b60ce0)\n\natopile is a new programming language to describe electronics with code. Instead of drawing the product itself, you can now capture your product requirements using atopile source code. From there, our compiler builds and validates the product manufacturing files for you. Not only is this faster and more reliable but it also lets you use advanced software development tools such as code editors, git, GitHub, GitLab, Continuous Integration, and copilot to design hardware.\n\nAfter [**launching on Hacker News**](https://news.ycombinator.com/item?id=39263854) and getting hundreds of downloads, we have seen a glimpse of an exciting future: our users have created new designs in atopile, used GitHub for version control, shared their work on our Package Manager, and used Continuous Integration to generate their manufacturing files automatically. Our most active users have also made contributions to our codebase, which we are super thankful for!\n\nEarly on, we decided to make atopile open-core. Our goal is to create a new industry standard for describing hardware. With an open-core approach, our users have guaranteed access to their code. Our plan is to generate revenue with enterprise-targeted features, in a model similar to GitLab.\n\n**Our code is on GitHub **[**here**](https://github.com/atopile/atopile)** and we have up-to-date docs **[**here**](https://atopile.io/getting-started/)**.**\n\n### Who we are\n\n![uploaded image](/media/?type=post&id=78992&key=user_uploads/333030/62696c0f-2b40-45d4-a8f4-8bb108672f51)\n\n[Matt](https://linkedin.com/in/matthew-wildoer-467a4992), [Narayan](https://linkedin.com/in/narayan-powderly-21949a180), and [Tim](http://https//www.linkedin.com/in/timotheepeter/) are life-long inventors, engineers, and now second-time founders. We have been engineers at companies including **Tesla, DJI,** and **Lilium**. We’ve worked on teams including [the 25-guns](https://twitter.com/elonmusk/status/1324283305789812736?lang=en), created prototyping facilities under executive mandate, and led critical software projects where the daily cost-of-delay ran into the millions.\n\nThe three of us met as we were building up a maker space in the Bay Area. After a few discussions, we quickly started putting together a prototype of the atopile compiler. We knew this had the potential to change hardware design after we compiled our first electronic printed circuit board.\n\n### ✉️ We are excited for the adventure ahead! Please email us at [founders@atopile.io](mailto:founders@atopile.io) to get in touch.",
        "url": "https://www.ycombinator.com/launches/KY4-atopile-a-new-language-to-design-electronic-circuit-boards-with-code",
        "votes": 39,
        "created_at": "2024-03-04T01:53:11.213Z"
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    "website": "https://usetusk.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Tusk (YC W24) is an AI agent that helps developers generate unit and integration tests with codebase context. Tusk sits in CI and provides automatic coverage whenever software engineers raise a PR. Engineering teams use Tusk to prevent critical regressions while increasing test coverage.",
    "one_liner": "AI agent that generates unit and integration tests",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1700257117,
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    "nonprofit": false,
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    "status": "Inactive",
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    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/usetusk",
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      "name": "Harj Taggar",
      "url": "https://www.ycombinator.com/people/harj-taggar"
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    "founders": [
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        "user_id": 317259,
        "full_name": "Marcel Tan",
        "title": "Founder/CEO",
        "founder_bio": "Marcel is the co-founder and CEO of Tusk. Prev. technical PM for 6sense's AI email product, which he took from $300K to $8.9M TCV in a year. Working hard to help engineering leaders prevent regressions. Graduated from UC Berkeley. Hacking on projects with Sohil since college. Saved a bar from going out of business once. Former Company Commander of 300 officers in the Singapore Police Force.",
        "is_active": false,
        "linkedin_url": "https://linkedin.com/in/marcel-tan",
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        "user_id": 279891,
        "full_name": "Sohil Kshirsagar",
        "title": "Founder/CTO",
        "founder_bio": "Sohil is the co-founder and CTO of Tusk. Previously a Senior Software Engineer at Aspire, where he led the workflow orchestration and automations team that powered millions of influencer collaborations. Now working hard to help engineers focus their time on fulfilling work. Graduated from UC Berkeley with a degree in Electrical Engineering and Computer Science. Built the most popular online prop bets game for the Super Bowl in a weekend.",
        "is_active": false,
        "linkedin_url": "https://linkedin.com/in/sohil-kshirsagar",
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      {
        "id": 87010,
        "title": "Tusk 🐘 - AI Agent for Generating Unit/Integration Tests",
        "tagline": "Anticipate and prevent bugs with AI-powered unit/integration tests in your CI",
        "body": "Hey everyone, we’re Sohil and Marcel, the founders of [Tusk](https://usetusk.ai) (YC W24).\n\nTusk is an AI agent that **generates unit and integration tests** for your PRs.\n\nWe’re the team that built the first publicly available AI coding agent in the market. Now we’re focused on taking on the tedious software engineering work that developers dread the most — writing automated tests.\n\n<https://youtu.be/OK_uhIGEQ0Y?feature=shared>\n\n## Problem\n\nIt goes without saying that writing tests is important for maintaining high code quality in any engineering organization.\n\nHowever, any software engineer who has had to hastily meet product deadlines knows that writing unit and integration tests is the first thing to go. Their main priority in this case is to ship the feature as fast as possible.\n\nThe problem is that the lack of tests then results in **customers complaining about bugs** in the feature. And all too often the blame is assigned to engineering leadership for not caring enough about quality.\n\nWe know how painful this experience is from our previous jobs. We’ve experienced instances of forgone tests leading to embarrassing bugs, including one that ruined a live demo for a high-value pilot customer (who you can guess didn’t convert).\n\n## Solution\n\nWe built [Tusk](https://usetusk.ai/) to provide EMs and senior engineers in charge of quality efforts a way to **ship fast while improving code quality**. Our AI agent generates unit and integration tests using your codebase context and business logic.\n\nTusk functions as a non-blocking PR check that suggests **happy path and edge case tests** that have not been covered by the existing test suite. Our agent shows you which tests have passed or failed and allows you to incorporate the test cases into the PR with one click.\n\n![uploaded image](/media/?type=post&id=87010&key=user_uploads/317259/da66276a-94e5-4cf0-8cf7-b9e0e5635fe6)\n\nEngineering teams at companies like DeepLearning.AI, Wyndly, and Afterword use Tusk to prevent bugs while increasing test coverage.\n\n> Tusk is the first AI tool that noticeably accelerated our dev cycle. By scaling our testing infra, it's given us confidence to ship faster and been instrumental in helping our lean team scale across 3 stacks. Of all the AI tools being built right now, I'm most excited about Tusk.\n\n– Zack Moy, Co-Founder & CTO at [Afterword](https://afterword.com/)\n\n> Edge cases that are not covered can cause the most critical issues. By using Tusk, our team gains an additional guardian to protect our product from the threats of edge cases.\n\n– Amo Chen, Senior Backend Engineer at [DeepLearning.AI](http://DeepLearning.AI)\n\n> Our priority as a fast-shipping product team is making sure we get high quality code out the door quickly. Tusk has been instrumental in helping our engineering team increase test coverage with minimal effort.\n\n– Aakash Shah, Founder & CEO at [Wyndly](https://www.wyndly.com/) (YC W21)\n\n## Why Use Tusk\n\nTusk surpasses other test generation and code review tools in these ways:\n\n**We run the tests we generate**. Tusk runs the tests it generates in an ephemeral sandbox and iterates on its output so you can be confident that its tests are checking for relevant happy path and edge cases. Code review tools do not do this, which results in vague comments that are hard to trust.\n\n**Optimized for test generation quality**. 69% of Tusk-generated test suites are incorporated into customers’ PRs. We use more compute to reason through test scenarios. AI copilots in your IDE are optimized for latency as opposed to quality when generating tests.\n\n**Developer-centric, fully customizable**. Tusk puts engineers in control by allowing them to accept/decline the generated tests and customize configs to meet your team's testing guidelines (how to mock, using factories, avoiding specific directories, etc.).\n\nRead [our documentation](https://docs.usetusk.ai/automated-tests/overview) to learn more.\n\n## Interested?\n\nTusk is now available for growth-stage and enterprise companies looking to auto-generate tests for their PRs and/or backfill tests for their monolith.\n\n[Apply for access](https://tally.so/r/nP29pQ) to see how Tusk can help your team ship faster but safer.",
        "url": "https://www.ycombinator.com/launches/MdO-tusk-ai-agent-for-generating-unit-integration-tests",
        "votes": 39,
        "created_at": "2025-01-21T17:31:55.265Z"
      },
      {
        "id": 78780,
        "title": "🐘 Tusk - AI coding agent that completes your chores",
        "tagline": "We complete annoying tasks from ticket to PR, helping engineers avoid context-switching.",
        "body": "**tl;dr**: [Tusk](https://usetusk.ai) is an AI coding agent that completes annoying tickets, letting software engineers focus on more important work. Simply assign a ticket to Tusk. Our AI will traverse your codebase for context and then create a pull request (PR).\n\n![uploaded image](/media/?type=post&id=78780&key=user_uploads/317259/6868cbd5-72a5-495b-b4df-022d6b53d313)\n\nHey everyone! We’re Sohil and Marcel.\n\nWe’re on a mission to boost developer productivity and satisfaction by automating the day-to-day tasks that bog down software engineers.\n\n# Problem\n\nSoftware engineers are often assigned menial “product quality” tickets and bugs that require them to context-switch from more important, interesting work.\n\n**15-20% of all tickets** in the typical 2-week sprint are chores like fixing bugs and polishing up UI. Additionally, there are similar tickets in every company’s graveyard backlog that rarely ever get cleared.\n\nThe result? A simple engineering task that should’ve taken 15 minutes to complete sometimes ends up taking 3 weeks to get done, or not at all.\n\nWhile it makes sense for engineers to deprioritize these tasks, this work is important for ensuring that customers have a delightful, bug-free user experience. Janky UX on an ongoing basis causes “**death by a thousand cuts**” for customers, leading to churn.\n\n# Solution\n\n[Tusk (YC W24) Demo](https://youtu.be/W0O3p5EIO1I?feature=shared)\n\n[Tusk](https://usetusk.ai/) is an AI coding agent that completes product quality tickets and bug fixes, letting your software engineers focus on more important work.\n\nWe integrate with Linear, Jira, Notion, and GitHub so that engineers can **go from ticket to PR** with one click of a button. We’re fully embedded into your engineering workflow so you don’t have to change how you work.\n\nWith Tusk, engineers no longer need to context-switch to do something simple like adding a confirmation modal or fixing a page index bug for table pagination.\n\n### How Tusk works\n\n* **Simply assign a ticket to Tusk**. Our AI agent will traverse your codebase for context and create a PR for the ticket.\n* **Tusk will** **regenerate code to address PR reviews** left by engineers and errors in automated checks.\n* **Tusk investigates complex tasks** and provides a branch and advice to save engineers time even if it can’t create a PR.\n* **Beta**: If your team deploys a preview environment for every PR, Tusk will do an end-to-end test of the change and record a testing video.\n\n# Our story\n\n![uploaded image](/media/?type=post&id=78780&key=user_uploads/317259/51f7aee6-bf8d-400d-a07f-b09da476bce6)\n\n[Sohil](https://www.linkedin.com/in/sohil-kshirsagar/) was previously a Senior Software Engineer at Aspire. Because of his product-mindedness, he was usually the first engineer to complete product quality tickets. Sohil was also the first person to tell you that **these chores distracted him** from working on more important tasks.\n\n[Marcel](https://www.linkedin.com/in/marcel-tan/) was formerly a Product Manager for 6sense’s AI email product. He often made product decisions that were outside of the initial PRD due to customer feedback. However, he risked distracting his engineers by pulling these ad hoc tickets into the current sprint.\n\nWe both deeply wished there was a way to **protect engineers’ uninterrupted coding blocks**, while also raising the quality bar of our products. Today we’re using Tusk to help build our own product.\n\n# Get early access\n\nWe’re already helping companies like Wefunder (YC W13), Toolbox (YC S20), and HitPay (YC S21) automate up to 20 engineering tickets monthly.\n\n**Apply to get early access** **to Tusk** **on** [**this form**](https://tally.so/r/w4xOpA). We’ll give the first 50 companies who sign up free customization of your AI agent and a white-glove onboarding.",
        "url": "https://www.ycombinator.com/launches/KUe-tusk-ai-coding-agent-that-completes-your-chores",
        "votes": 71,
        "created_at": "2024-02-27T00:05:02.472Z"
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    "name": "OneGrep",
    "slug": "onegrep",
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    "website": "https://www.onegrep.dev",
    "all_locations": "New York City, NY, USA",
    "long_description": "OneGrep is a DevOps Agent that helps engineers automate manual devops tasks. It works across integrations that teams have to search, correlate, and operate automated tasks like runbook automation during incidents.\r\n\r\nOneGrep specializes across devops tools to help teams release code faster and more reliably so that engineers can spend more time building rather than being trained in bespoke tools like Observability, Ci/Cd, or Infra.\r\n    \r\nAchintya and Brian are technical co-founders who have deep domain expertise in building and operating systems at scale at Coinbase, Disney, and Amazon. Achintya led the Search Team at Disney enabling DisneyPlus to scale to 70M users in two weeks. Brian was a founding engineer on the team that built the Incident Management Platform at Amazon that helps 30k DAUs in Amazon resolve critical incidents every day.\r\n    \r\nhttps://www.onegrep.dev",
    "one_liner": "AI Agent for DevOps Workflow Automation",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1706125160,
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    "year_founded": 2024,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/onegrep",
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      "name": "Nicolas Dessaigne",
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        "user_id": 108240,
        "full_name": "Achintya Ashok",
        "title": "Founder/CEO",
        "founder_bio": "Achintya is a Co-Founder and the CEO of OneGrep which he started with Brian Cripe in late 2023. OneGrep saves engineers time by automatically generating insights that improve the usefulness of their Observability Data.\n\nAchintya has worked in engineering highly distributed systems at Coinbase, Disney Streaming, & Goldman Sachs. In a previous life, he was the Tech Lead of the Search Team at Disney Streaming responsible for serving contextual experiences to 70-million customers in real-time.",
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        "full_name": "Brian Cripe",
        "title": "Founder/CTO",
        "founder_bio": "Brian Cripe is the co-founder and CTO of OneGrep, which he started with Achintya Ashok in 2023.  OneGrep saves engineers time by automatically generating insights that improve the usefulness of their Observability Data.  Brian brings over a decade of experience in the areas of developer-tools, distributed systems, and real-time analytics from companies such as 'Amazon', 'Tableau', and 'Coinbase'.",
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      {
        "id": 79014,
        "title": "OneGrep — Reduce Observability costs and resolve incidents faster",
        "tagline": "OneGrep makes observability efficient and actionable for fast-moving teams.",
        "body": "**TL;DR** — [OneGrep](https://www.onegrep.dev) is every engineer’s dedicated Observability Copilot. OneGrep helps engineers resolve incidents 10X faster and more efficiently. We do this by fine-tuning LLMs with real-time telemetry as well as knowledge bases that engineers use to operate their production systems.\n\nTeams can deploy OneGrep on their own infrastructure or use our cloud. If you are an engineer, we invite you to try us out! [onegrep.dev/try](http://onegrep.dev/try)\n\n# Problem\n\nEvery engineering team struggles with observability cost bloat and incident management when they are moving fast.\n\n![uploaded image](/media/?type=post&id=79014&key=user_uploads/108240/27337479-43ff-4af3-b1a9-33d826abd4ce)\n\n### Why Does This Happen?\n\n🔨 — Engineers find it hard to instrument code effectively and they make unintentional, costly mistakes.\n\n![](https://lh7-us.googleusercontent.com/g9TzD8RlqcCxPkwE7FDt9EuRHrZacWUc3fjAOJ1eHWblTPS1dqTzJ5sis9UQnzvZowvDTLBHUb-UU3PFE8rFuDxhvka5E_tolNjX50lmjnb3fs6QujAC9pdvaou9metU2ji-8Y1_kF2s5EVNmKcuGw)\n\n📲 — On-call engineers find mitigating incidents to be very difficult because it is hinged on tribal knowledge and tool know-how.\n\n* Engineers spend **25%** of their time on on-call-related work, which equates to companies spending \\~**$61,000** per engineer for on-call work  — _and that’s not including the DataDog bill._\n\n**TL;DR —** Engineers struggle to find answers using observability and pay a lot for unintentional mistakes.\n\n# ✅ Solution — Have your cake & eat it too\n\nEngineers can use OneGrep to make telemetry **actionable** and **efficient**.\n\nHere’s a **13-second** example of OneGrep cutting noisy logs **by 50%** and saving a team thousands of dollars:\n\n![uploaded image](/media/?type=post&id=79014&key=user_uploads/108240/6322e5bd-87f6-43aa-a402-3d35bf8bf167)\n\nAnd here is an example of OneGrep helping an engineer automatically resolve an incident — ✔️ gone are the days of reading through retros, parsing logs, or pinging the entire team:\n\n<https://youtu.be/QJKtHzgqC_4>\n\nCut costs & resolve incidents faster with OneGrep.\n\n——\n\n# Who We Are\n\nWe are [Achintya](https://www.linkedin.com/in/achintya-ashok/) & [Brian.](https://www.linkedin.com/in/briancripe/) We have applied telemetry best practices to highly distributed systems at Coinbase, DisneyPlus, AWS, Tableau, & Goldman Sachs. We hated our daily struggle with observability and we know how and why other engineers do too. We share the plight of all engineers who have struggled and continue to struggle with noisy alerts at 2 AM.\n\nSo, in the pursuit of helping engineers sleep more soundly knowing their systems are operational, we are on a mission to build the new way to do Observability.\n\n![](https://lh7-us.googleusercontent.com/DOphP_OzGeKanLDxit_2BMc3PtjCdDwIX-Vmf2UUAMjAx4S-Um0TqYn3n_e2ervRbp-PhBJ3ReDfR6IlJUbuGlH_O7BEtjjZDnVnvsaBe3eJgc0KxoLjvoBNRMvC5SnfwwTAi5ux1GUb7zzEEBN52w)\n\n_— Brian & Achintya inspecting the Y Combinator sign for any errant logs._\n\n## ➡️ Our Asks\n\n▶️ Do you have high DataDog bills? [Book a demo with us](https://cal.com/teamonegrep/demo).\n\n▶️ Do your engineers wish their on-call was better? [Learn how we can help](https://cal.com/teamonegrep/learn-in-30) or send us an email at [contactus@onegrep.dev](https://mailto:contactus@onegrep.dev).",
        "url": "https://www.ycombinator.com/launches/KYQ-onegrep-reduce-observability-costs-and-resolve-incidents-faster",
        "votes": 44,
        "created_at": "2024-03-04T18:09:38.939Z"
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    "name": "Polished",
    "slug": "polished",
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    "website": "https://polished.ad",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "With Polished, you create finished ads (video or static) in minutes.\r\nThen you refine it in plain English, until it's exactly what you had in mind.",
    "one_liner": "Generate ads. Iterate till perfect.",
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    "subindustry": "B2B -> Engineering, Product and Design",
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        "full_name": "JJ Maxwell",
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        "founder_bio": "Building Polished. \n\nFormer CEO @ Double Finance, CTO of Liftoff Influence, co-founder of Jetfuel (acquired by Liftoff 2021), Facebook Messenger",
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        "id": 97986,
        "title": "Pillar - Your app's copilot",
        "tagline": "An open source copilot that turns user requests into completed actions, right inside your app.",
        "body": "Hey everyone! We’re JJ and Mark, cofounders of [Pillar](https://trypillar.com) 👋\n\n**TL;DR: Pillar is an embedded AI copilot that executes tasks inside your product for users and agents.**\n\nUsers or agents can type what they want. The copilot carries it out **client-side in the browser**, using the user’s existing session, permissions, and security checks. You install the SDK via npm and register your existing frontend code as tools.\n\nExample: in a banking app, a user types _“send $200 to my cleaners.”_ Pillar finds the right recipient, navigates to the transfer flow, and pre-fills the form. The user still reviews and confirms. If your app requires 2FA for that acion, so does the copilot.\n\nDemo: <https://www.youtube.com/watch?v=ruNJ5OFuKsI>\n\n# The Problem\n\nTeams ship faster than ever. But when your changelog is 10x longer than it used to be, users can’t keep up.\n\n* **Discoverability breaks down:** the UI changes, features move, and people forget where things live.\n* **Friction turns into “support”:** users open tickets that aren’t really support tickets. The user wanted to do something your product already supported but couldn’t get there.\n* **Most products don’t have an “action layer”:** AI agents are starting to use web apps the same way users do: navigate, click, fill forms. Products need to prepare for this\n\n**Bottom line:** products need a reliable, permissioned way to execute actions end-to-end - not just document them.\n\n# How Pillar Works\n\nPillar turns a user request into action by combining planning with **in-browser execution**.\n\n1. **Plan:** Pillar determines which steps/tools to run\n2. **Execute:** your app runs those tools in the browser (navigation, API calls, state updates, form fills)\n3. **Confirm:** the user stays in control for sensitive actions.\n\nYou register tools inside your existing React components:\n\n![uploaded image](/media/?type=post&id=97986&key=user_uploads/376672/a918639c-e2a9-405b-9e4d-2f54acac8af0)\n\nWhat happens at runtime when a user types _“send $200 to my cleaners”_:\n\n* Pillar calls **search_recipients** with “cleaners”\n* Selects the right match\n* Calls **prefill_transfer** with the recipient + amount\n* User reviews and confirms in the existing flow\n\nBecause execution happens in the browser, tools run with the current user’s permissions and session. **Pillar can’t do anything the user can’t do.**\n\nPillar syncs with your help content (Zendesk, Intercom, Notion, Confluence, internal docs) so requests map to the right tools/flows. When it picks the wrong path, you flag it and the correction is captured so the same issue is less likely to repeat.\n\nSDKs are available for React and vanilla JavaScript. Registered tools can also be reused by other copilots/agents via WebMCP (navigator.modelContext).\n\n# Try It\n\nInstall: [trypillar.com](http://trypillar.com)\n\nWe also have live demos you can try right now - Pillar installed on open-source products:\n\n* Grafana ([trypillar.com/demos/grafana](https://trypillar.com/demos/grafana)): you can have Pillar build you a monitoring dashboard and set up alerts\n* Apache Superset ([trypillar.com/demos/superset](https://trypillar.com/demos/superset)): you can explore the names dataset and build a dashboard\n\n👉 Want help getting live? Reach out at [founders@trypillar.com](https://mailto:founders@trypillar.com)\n\n# Our Ask\n\n* If you lead product/engineering and users open tickets for things your product already does, we’d love to talk: [founders@trypillar.com](mailto:founders@trypillar.com)\n* If you know someone who fits that (founders, VP Product, Head of Support), intros are appreciated\n* Share this post. Follow us on LinkedIn and X.\n\n# Backstory\n\nWe built Pillar to solve our own problem. At our last company (Double Finance), we saw a pattern: users asked for outcomes we already supported, but still opened support tickets. We wanted a way to reuse the frontend code we’d already shipped, without rebuilding flows or adding new “automation” surfaces.\n\n_Pillar is what we wish we had._\n\n![uploaded image](/media/?type=post&id=97986&key=user_uploads/376672/597895ee-5fab-49bb-b55e-cabb1f3f6ff2)\n\n",
        "url": "https://www.ycombinator.com/launches/PUQ-pillar-your-app-s-copilot",
        "votes": 11,
        "created_at": "2026-02-19T20:32:35.986Z"
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      {
        "id": 82801,
        "title": "Double - Design your own stock index",
        "tagline": "Double automates your investments with zero AUM fees.",
        "body": "![uploaded image](/media/?type=post&id=82801&key=user_uploads/1289064/c2a6166e-82a3-419a-9800-0648a58901ea)\n\n**TL; DR** — Design and invest in your own stock index that’s advised, managed, and tax-optimized by [Double](https://double.finance/).\n\nHistorically, access to sophisticated finance tools like direct indexing and tax loss harvesting has come at a steep cost and only through exclusive financial advisors. We are on a mission to revolutionize investing by providing world-class portfolio tools to everyday investors without any AUM fees. \n\n# Key Features\n\n* **Direct Index into 20+ ETFs:** Build an elite portfolio with the ability to tilt towards specific sectors, industries, themes, or even custom groupings like all YC publicly listed companies.\n* **Daily Tax Optimization, Rebalancing & Potential Tax Loss Harvesting**: Our optimization engine keeps your portfolio on track by factoring in drift, taxes and transaction costs. If your account qualifies, our tax-loss harvesting service aims to help you minimize your tax liability and maximize your after-tax returns.\n* **Dollar-cost averaging:** We allow users to move between positions at a set cadence, regardless of the market's performance, helping you reduce timing risks associated with active trading.\n\n# Example Use Cases\n\nWork for AAPL and want to diversify away from tech?\n\n* Buy a direct-indexed [S&P 500 Portfolio](https://app.double.finance/public/explore/3), remove AAPL entirely, and cut the rest of your tech exposure in half.\n\nDid you know AI was going to be a big deal before everyone else?\n\n* Double makes it easy to tilt your portfolio towards your hunches. Pick a handful of stocks set to benefit from the Inflation Reduction Act, or some that target the booming AI and semiconductor industry, or shift your portfolio towards the explosive meme growth of Zyn.\n\nFeeling confident in the overall market and ready to pile on the risk?\n\n* Follow [Hedgefundie’s Adventure](https://app.double.finance/explore/110), which uses 3x leverage in a Stock and Bond ETF to try and increase returns. Or pick from our smart screens that target top growing companies or even a basket of the [YC Public Companies](https://app.double.finance/public/explore/140).\n\nThink we’re headed for a recession and want to take some chips off the table? \n\n* You can invest in a version of [Ray Dalio’s All Weather Portfolio](https://app.double.finance/public/explore/108) comprising 5 ETFs or [John Bogles Majesty of Simplicity](https://app.double.finance/public/explore/105) and migrate between these Strategies and Bonds over time.\n\nBuild and backtest your own stock index!\n\n* Use our Stock and ETF Screeners to build your very own personalized portfolio.\n\n#### Fees\n\nDouble doesn’t charge AUM fees. Financial Advisors often charge around 1% a year for tools like Direct Indexing and Dollar Cost Averaging. In a sample $1M portfolio, these fees lead to a dollar cost of $1,800,000 or a 24.5% overall reduction in performance over 30 years, assuming 6% growth vs. 7% growth. We aim to eventually make money like the commission-free trading pioneers. Our custodian Apex Clearing charges some fees which we pass on to users which you can see [here](https://help.double.finance/en/articles/9450171-service-provider-fees). \n\n#### Additional Features\n\n* Backtest a custom stock grouping to see its historic performance.\n* Cash sweep available: Earn 4.5% interest on your uninvested cash (as of August 5th, 2024, not a guarantee of future rates)\n* Fractional investing: Invest in over 3,000 US stocks and 1,400 ETFs for as little as $5 per share.\n* Support for Personal, Joint, and Trust Accounts\n* Daily portfolio optimization and trade execution\n* Recurring or one-time deposits via ACH or Wire\n* ACAT Transfer in an existing brokerage account\n\n#### Get Started Today\n\nWe’re live at <https://double.finance>. Sign up for a Double account today and start building your own stock index. Please reach out to [founders@double.finance](mailto:founders@double.finance) with any feedback or questions!\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXctLsEGUWaE1ScP7EqAuz0sPPYQDg7Vt1Zlpn5Cx-sfubv0nJvIZertGsNS0zPWoWzzJSw-orkpmSTzIFepxiDziCKdJN6sMXMAS1GSYwcTfiyY3ZqlIA_db-gZX4rHTji2-dZPfMWgdz-qmvb7whdOackQ?key=nGDLEdHNSqYCi809_9DeNQ)\n\n",
        "url": "https://www.ycombinator.com/launches/LXV-double-design-your-own-stock-index",
        "votes": 58,
        "created_at": "2024-08-07T00:27:48.572Z"
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    "name": "Decipher AI",
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    "website": "https://getdecipher.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Decipher AI generates your E2E tests, maintains them as you ship, and catches issues before customers do. Plus, get alerted when users hit live bugs.\r\n\r\nUsed by the fastest shipping companies including Bilt, Arize, and Vial.",
    "one_liner": "QA agents that write tests 10x faster with zero maintenance",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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    "city": "San Francisco",
    "country": "US",
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        "full_name": "Michael Rosenfield",
        "title": "Founder/CEO",
        "founder_bio": "Michael was most recently a Sr. Product Manager where he led the development of the first native ads format on Google Maps, drove Google Search Ads optimization with $XB revenue growth, and was product lead for Pixel premium tier product line. He started his career at Google as an APM.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/rosenfieldmichael",
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        "user_id": 1080757,
        "full_name": "Rohan Das",
        "title": "Founder/CTO",
        "founder_bio": "Co-founder @ Decipher AI. Previously a staff engineer and manager at Google on the YouTube Homepage, leading the team that rebuilt the Homepage service from scratch to handle billions of requests per day. Passionate about robust yet practical engineering, AI, and elegant design.",
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      {
        "id": 97250,
        "title": "Decipher AI: Agentic QA for the era of coding agents",
        "tagline": "AI that generates and maintains your E2E tests. Ship fast, without the bugs.",
        "body": "# **TL;DR**\n\nDecipher offers an AI QA agent for the era of coding agents. Show it your product, and the QA agent generates E2E tests in minutes, maintains them, and catches bugs before customers do so you can keep shipping fast. We’ve already caught bugs for some of the fastest shipping companies and would love to help you!\n\n# **Product Overview**\n\n<https://www.youtube.com/watch?v=PAmx7HbnXc8>\n\n# **Who's Decipher AI for?**\n\n* Teams where AI coding agents have made development faster than ever, but QA hasn't kept up. You're shipping more code, but bugs are still slipping through to customers.\n* Large QA teams spending hours writing Playwright scripts, manually updating selectors, and chasing flaky tests. You want comprehensive test coverage without the overhead.\n* Teams without dedicated QA resources, who click through the product every morning hoping to catch issues. You need reliable coverage but don't have time to build it from scratch.\n\n# **What can I do with Decipher AI?**\n\n### **Generate reliable E2E tests in minutes**\n\nRecord your screen, describe a flow, or just ask. Because Decipher has learned your product, it can generate tests, update them, and create variants on demand. A QA agent at your fingertips.\n\n![uploaded image](/media/?type=post&id=97250&key=user_uploads/1073351/4e2df1fd-25e1-4b9f-95ad-20ec408ae027)\n\n### **Tests auto-update as your product changes**\n\nWhen your product or UI changes, the Decipher agent automatically updates your tests. Steps adapt automatically so tests stay reliable and meaningful without manual work.\n\n![uploaded image](/media/?type=post&id=97250&key=user_uploads/1073351/a942e76c-df6b-4630-be1a-1457f1d42760)\n\n### **Get alerted when users hit bugs in production**\n\nSome bugs only happen in the real world. Decipher uses vision AI to watch your customer sessions, and when a user hits a bug, flags it with the session replay, console/network context, and customer impact. \n\n![uploaded image](/media/?type=post&id=97250&key=user_uploads/1073351/f83feabc-ae8f-4b72-8535-4c07407776ec)\n\n# **Meet The Founders**\n\nFounders [Rohan Das](https://www.linkedin.com/in/rohan-d/) and [Michael Rosenfield](https://www.linkedin.com/in/rosenfieldmichael/) bring deep expertise from Google, having led multi-billion-dollar, multi-billion-user products including the YouTube homepage and Pixel. They built Decipher AI so teams using coding agents have a validation layer that keeps up with how fast they're shipping.\n\n# **Our asks**\n\nDecipher is already catching bugs for some of the fastest shipping teams out there! If you're using coding agents to ship faster and need QA that keeps up, we'd love to help. Reach out to [founders@getdecipher.com](mailto:founders@getdecipher.com) or [book a demo here](https://getdecipher.com).",
        "url": "https://www.ycombinator.com/launches/PIY-decipher-ai-agentic-qa-for-the-era-of-coding-agents",
        "votes": 13,
        "created_at": "2026-01-28T15:58:48.478Z"
      },
      {
        "id": 92528,
        "title": "Decipher: AI that discovers issues and opportunities in your product",
        "tagline": "Decipher’s AI agents watch all your user sessions – helping you identify and act on product issues and insights.",
        "body": "Hey YC! Michael and Rohan here!\n\n**TL;DR:** Decipher offers real‑time agents that use vision language models to watch every customer sessions to detect, diagnose, and even help ship the fix for anything that blocks user happiness—from silent drop‑offs to full‑blown errors.\n\nSign Up For Free » [getdecipher.com](http://getdecipher.com)\n\nBook A Call » [cal.com/decipher/discovery](http://cal.com/decipher/discovery)\\\n[Video overview](https://www.youtube.com/watch?v=f9LIZie4ogY)\n\n---\n\n## **Why we built Decipher**\n\nShipping speed is up, but visibility into _real_ user experience hasn’t kept pace. Teams still burn days—and sometimes miss problems entirely:\n\n* Users hitting confusing UI and running into bugs in core workflows\n* Figuring out what exactly people are doing that lead to app errors and how many people are affected\n* Scrubbing thousands of sessions to learn why an important new feature isn’t used\n\nThe root cause is signal overload—billions of events, little prioritization. We flipped that on its head: let AI watch the firehose, surface what truly matters to adoption, satisfaction and revenue, and automate the busywork after discovery.\n\n---\n\n## **How it works**\n\n* **Discover:** Real‑time monitoring catches hiccups, drop‑offs, errors—or any custom condition you set, no redeploy needed.\n* **Investigate:** Ask in plain English and get AI summaries, session clips, and console logs instantly.\n* **Act:** One‑click Linear ticket or PR draft with all the context so fixes land before metrics suffer.\n\nA feedback loop on every action continuously teaches the model, dialing down noise while accuracy climbs.\n\n> Decipher’s basically 1,000 QA interns watching every user session in real‑time and obsessing over improving the user experience. **In the first four weeks it surfaced over one hundred issues and UX improvements.** Now the team ships features instead of binge‑watching session replays.\n\n— Keith Fearon, Head of Product & Growth, 11x\n\n**Issue Explorer**\n\nBrowse the issues Decipher detects and filter by feature, account, impact, time range, and more. Export straight to Linear.\n\n![uploaded image](/media/?type=post&id=92528&key=user_uploads/1073351/0dadbdcb-7375-4565-8898-e6fd2c4e83ae)\n\n**Session Deep Research**\n\nAsk the Decipher agent any question about customers and get detailed responses citing real sessions.\n\n![uploaded image](/media/?type=post&id=92528&key=user_uploads/1073351/202e6275-5278-4465-8250-445a30580acb)\n\n**Issue Alerts**\n\nRoute alerts to your favorite tool, like Slack or email, with AI noise-reduction so teams never miss the signal.\n\n![uploaded image](/media/?type=post&id=92528&key=user_uploads/1073351/fe19231d-6d8c-44d9-8f33-338b21eb14e2)\n\n**Smart Funnels**\n\nGenerate funnels based on any user behavior and Decipher will analyze drop-offs to help you understand the root cause.\n\n![uploaded image](/media/?type=post&id=92528&key=user_uploads/1073351/99b7c7c8-7690-4249-ac84-81708c296902)\n\n## **Where it fits in your stack**\n\n* **Setup:** Drop‑in SDK or web snippet; optional connectors for PostHog, Sentry, Segment.\n* **Workflows:** Creates Linear tickets for you. Pings you on Slack and email. And one click copy context to Cursor.\n* **Platforms:** Web today; iOS & Android are on our roadmap.\n* **Security:** Data encrypted in transit & at rest and client‑side PII masking.\n\nIntegration is &lt; 5 minutes. First insights usually appear within the hour.\n\nCompanies of all sizes from small startups to unicorns already rely on Decipher to keep launches smooth and adoption climbing. Their teams ship faster, users stay delighted, and engineering effort goes back to roadmap features instead of reading logs and trying to repro issues.\n\nGet started today, no credit card required at [getdecipher.com](http://getdecipher.com) or schedule a call with our team: [cal.com/decipher/discovery](https://cal.com/decipher/discovery)\n\n![uploaded image](/media/?type=post&id=92528&key=user_uploads/1073351/911f3dcb-c76f-4ef2-ab29-43e7a45790d4)\n\n",
        "url": "https://www.ycombinator.com/launches/O4O-decipher-ai-that-discovers-issues-and-opportunities-in-your-product",
        "votes": 23,
        "created_at": "2025-07-28T21:00:11.052Z"
      },
      {
        "id": 86416,
        "title": "Decipher AI: An AI agent that watches thousands of session replays for you",
        "tagline": "AI that analyze your session replays with vision LMs to help you understand user behavior, detect bugs and discover insights",
        "body": "# **TL;DR**\n\nDecipher AI offers an AI agent that uses advanced vision LMs to watch thousands of hours of session replays for you so you can discover customer issues in realtime, understand feature usage, and get product questions answered. We’ve already analyzed millions of session replays and would love to help you!\n\n# **Product Demo**\n\n<https://www.youtube.com/watch?v=nc0wVezrmcU>\n\n# **Who’s Decipher AI for?**\n\n* Teams tired of sifting through Posthog, FullStory, or Hotjar recordings, hoping to stumble on key insights or looking for something specific. Decipher AI analyzes them all so you can focus on your job.\n* Teams that wish they had a high resolution and a bird’s-eye view of how users actually interact with their product—without manual tagging, proactive instrumentation, or complex data queries.\n* Teams tired of reactive firefighting. Get alerted the moment users start running into new issues or bugs so you can jump straight to shipping a fix.\n\n# **What can I do with Decipher AI?**\n\nDecipher AI empowers you to uncover how your customers engage with your product and gain insights into its behavior for each unique user.\n\n### Session Intelligence\n\nStop scrubbing through hours of video. Get succinct, AI-generated timelines of each session, highlighting the most important parts.\n\n![uploaded image](/media/?type=post&id=86416&key=user_uploads/1073351/e72fd09d-008b-4491-9d4d-e0003d90d7f3)\n\n### Behavior Discovery\n\nFind out how customers use specific features or workflows in seconds, uncover patterns you never knew existed, and jump straight to relevant moments in sessions.\n\n![uploaded image](/media/?type=post&id=86416&key=user_uploads/1073351/590d9aa7-f42d-4f67-97d7-2d7b348c3039)\n\n### Hands-free Product Analytics\n\nGet product analytics without any manual instrumentation or CSS definitions. \n\n![uploaded image](/media/?type=post&id=86416&key=user_uploads/1073351/f590e6f8-eaf9-40ac-a02a-dacb3feb67c7)\n\n### Issue Detection\n\nIdentify exactly when and where users hit bugs and issues. Prioritize new issues and know precisely if a deployed fix worked.\n\n![uploaded image](/media/?type=post&id=86416&key=user_uploads/1073351/25b0f561-b12c-4a97-a5ab-71508b62789b)\n\n### Simple, 5-Minute Setup\n\nJust copy and paste a single script. That’s it. No manual instrumentation, no labor-intensive tagging, and no complicated SQL queries.\n\n# **Meet The Founders**\n\nFounders [Rohan Das](https://www.linkedin.com/in/rohan-d/) and [Michael Rosenfield](https://www.linkedin.com/in/rosenfieldmichael/) bring deep expertise from Google, having led multi-billion-dollar, multi-billion-user products at Google including the YouTube homepage and Pixel. They created Decipher AI to make understanding user and product behavior effortless for everyone.\n\n# **Our asks**\n\nDecipher AI has already analyzed millions of session replays for companies of all sizes! If you’re interested in having our AI agent watch all of your session replays so you can understand customer behavior, find issues, and improve product please reach out to [founders@getdecipher.com](mailto:founders@getdecipher.com) or [book a demo here](https://cal.com/decipher/demo).",
        "url": "https://www.ycombinator.com/launches/MTo-decipher-ai-an-ai-agent-that-watches-thousands-of-session-replays-for-you",
        "votes": 40,
        "created_at": "2024-12-19T16:39:32.588Z"
      }
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    "id": 29335,
    "name": "Toolify",
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    "website": "https://toolify.sh",
    "all_locations": "Bengaluru, KA, India",
    "long_description": "Toolify is dev-first internal tooling. At some point, companies using low-code builders hit a brick wall, and are bogged down by their limitations rather quickly.\r\n\r\nWe offer:\r\n- A starter kit with sensible defaults,\r\n- A VSCode extension which has AI that creates the internal tool for you, end to end, and,\r\n- A web app where you can deploy your tools.\r\n\r\nThis gives you the best of both worlds -- everything you need to build tools just as fast as low-code, and an escape hatch when you need it.",
    "one_liner": "Build internal tools with AI",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1706123140,
    "tags": [
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      "B2B",
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    "nonprofit": false,
    "batch": "Winter 2024",
    "status": "Inactive",
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    "regions": [
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      "South Asia"
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    "year_founded": 2023,
    "city": "Bengaluru",
    "country": "IN",
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      "name": "Harj Taggar",
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      {
        "user_id": 962401,
        "full_name": "Rohan Mayya",
        "title": "Founder",
        "founder_bio": "Currently I'm a co-founder at Aeos Games, building an ambitious Action RPG from India for the world.\n\nPreviously, I founded Toolify (w24), and before that, built apps and tools that got 1m sign ups.",
        "is_active": false,
        "linkedin_url": "https://linkedin.com/in/rohan-mayya-a9b341173",
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        "user_id": 1570652,
        "full_name": "Saifur Rahman",
        "title": "Founder",
        "founder_bio": "Co-founder of Toolify, a framework for building internal tools, and former engineer at Endurance International Group, working on domain name registration systems.",
        "is_active": false,
        "linkedin_url": "https://linkedin.com/in/saif-ur-rahman",
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    "id": 29350,
    "name": "Feldy",
    "slug": "feldy",
    "former_names": [
      "Aether Energy",
      "Aether"
    ],
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    "website": "https://feldy.ai",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "Feldy is field-first AI for home service businesses helping teams capture jobsites, create take-offs & estimates, and documentation.\r\n\r\nWith Feldy, teams capture the physical world using photos, videos, AI jobsite walkthroughs, and 3D scans using your mobile phone. It turns field information into takeoffs & estimates, visual designs, and project documentation. Feldy works across home services such as roofing, exteriors, remodeling, painting, cleaning, landscaping, handymen, and other home services.\r\n\r\nWe’re building a new way for more than 2 million U.S. home service businesses operating in an $800B+ market to capture, understand, and complete work in the field.\r\n\r\nFeldy is available on iOS, Android, and the web.",
    "one_liner": "Field-First AI for home services",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1709429693,
    "tags": [
      "Construction",
      "Home Services",
      "AI"
    ],
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    "batch": "Winter 2024",
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    "url": "https://www.ycombinator.com/companies/feldy",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/feldy.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/feldyai/",
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    "primary_partner": {
      "name": "Gustaf Alstromer",
      "url": "https://www.ycombinator.com/people/gustaf-alstromer"
    },
    "founders": [
      {
        "user_id": 1494934,
        "full_name": "Zayne Sagar",
        "title": "Founder/CEO",
        "founder_bio": "Zayne is the co-founder and CEO of Feldy. \n\nHe completed an Applied Math/CS and Philosophy bachelor's degree from UC Berkeley, and attended graduate school working on topics around computational science methods. \n\nHe is a fan of building physics-grounded world models using multi-modal inputs.\n\n",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/zaynesagar",
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      },
      {
        "user_id": 1527633,
        "full_name": "Shelby Bons",
        "title": "Founder/CTO",
        "founder_bio": "Shelby is the co-founder and CTO of Feldy. \n\nShe has expertise in software engineering and ML Physical Systems modeling, developed at leading climate-centric organizations like Sunrun and Voltaiq. Before that, she completed a Materials Science and Engineering degree at the University of California, Berkeley. \n\nPrior to founding Feldy, Shelby was headed for a Theoretical Physics PhD career track.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/shelby-bons-ucberkeley",
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      {
        "id": 110395,
        "title": "Feldy: Field-first AI for home services and contractors.",
        "tagline": "Jobsite capture, 3D building scans, estimates and field documentation in one simple app. ",
        "body": "**TL;DR** 👋\n\nFeldy is field-first AI for home service companies. It unifies jobsite capture, 3D building scans, estimates, and field documentation in one simple app.\n\nWe’ve grown to over 200 paying customers on the web over the last few months, and are now launching the mobile app so field teams can use the full product on site.\n\nZayne and Shelby are construction software veterans with a combined 10+ years building computer vision and spatial AI tools.\n\n**Meet Feldy:**\n\n<https://www.youtube.com/watch?v=W0lEF7isKg4>\n\n**The Problem:**\n\nThe biggest problem in residential home services in 2026 is still remarkably simple: estimates do not go out fast enough to homeowners.\n\nAn estimate is the quote a homeowner receives explaining what work will be done and how much it will cost. Yet, if you call a window contractor, or painter, it can still take two or three days, often longer, to receive one. Over the last 8 months, my home became a test bed for remodeling projects, and this is one of the few truths that persisted. This problem appears in nearly every trade we encountered.\n\n_So why so long?_\n\nThe surprising part is that many of these estimates are not inherently complicated.\n\nConsider a typical window and door contractor. A sales representative drives to the property, walks through the home, identifies every window and door, photographs existing conditions, and asks discovery questions:\n\n* Do you want to replace the trim?\n* Should the opening change?\n\nCapturing this information can easily consume most of a one- or two-hour appointment. By the time the rep understands the property and records everything the office needs, there is _very little time left_ to actually sell the project. This is the primary reason quotes arrive days later, or require a second visit.\n\nFurthermore, existing software makes the problem worse.\n\nMost contractor tools have always been structured like digital forms. The software records what the estimator has already figured out, but it does very little to help figure out the job.\n\nThis is what led us to ask: what does this contractor world look like if the software recorded and figured out the job at once? Well, that’s Feldy.\n\n![uploaded image](/media/?type=post&id=110395&key=user_uploads/1494934/6bdd00aa-4517-41c6-897e-517110044d2b)\n\n**So how do we solve this?**\n\nInstead of requiring the person in the field to manually observe and organize everything, Feldy uses in-house computer vision and vision-language models to perform much of this _low-value work_: necessary technical work that consumes the majority of the job visit time, but creates little visible value for the homeowner.\n\nThe contractor _captures_ the property via photos/videos, lidar scans, or job walkthroughs (video and audio are combined). Feldy then interprets the capture and helps turn it into an estimate amongst a host of other workflow items such as inspection reports, proposals, materials lists, etc.\n\nThe entire thesis behind Feldy can be summed up as:\n\n_How do we remove the time-consuming thinking required from the estimator that creates little visible value for the homeowner?_\n\n![uploaded image](/media/?type=post&id=110395&key=user_uploads/1494934/060ca1ad-5038-40a5-868f-fb14eb04b164)\n\n**The Scale of the bottleneck**\n\nAngi’s list has estimated that American households undertake more than 700 million home projects annually.\n\nUsing 600 million estimates (aggressive case):\n\n* 600M estimates \\* 3.5 hours = 2.1 billion total labor hours\n* 50% spent on measuring, documenting, takeoff, and estimate construction = 1.05 billion hours\n* At $45–50 fully loaded cost = $47–53 billion in annual labor capacity tied up in that work\n\nIf Feldy reclaims 1–1.25 hours per estimate:\n\n* 750 million hours returned\n* Roughly $27–37 billion in productive capacity per year.\n\nFor the average home-services company, this is equivalent to reclaiming $50,000–$100,000+ in capacity each year, capacity that can be converted directly into more estimates, lower overhead, and higher revenue.\n\n**The Team**\n\nZayne and Shelby met at UC Berkeley’s engineering school nearly 10 years ago. For the last three years, they have worked side by side building technology for the construction and home-services industries.\n\nTogether, they previously took a construction-software company from zero to $500k ARR in months. \n\nThe pair is more excited than ever to build the next generation of software for home-service businesses.\n\n**The ask**\n\nIf you know anyone who works in home services, tell them about Feldy and ask them to download the app!\n\nSearch Feldy AI on [IOS ](https://apps.apple.com/us/app/feldy-ai/id6780327228)and [Android ](https://play.google.com/store/apps/details?id=com.feldy.app)app stores.\n\n* You can reach us directly at [**zayne@feldy.ai**](mailto:zayne@feldy.ai)\n* To learn more about Feldy visit us at our [feldy ai](https://feldy.ai/?utm_source=yc&utm_medium=launch&utm_campaign=feldy_launch_campaign_2026&utm_content=first_launch_post) website",
        "url": "https://www.ycombinator.com/launches/SiZ-feldy-field-first-ai-for-home-services-and-contractors",
        "votes": 22,
        "created_at": "2026-08-13T14:55:04.664Z"
      },
      {
        "id": 79053,
        "title": "Aether  - AI platform for rooftop solar",
        "tagline": "Aether is AI design and workflow software for solar installers.",
        "body": "**TL;DR**\n\n[Aether](https://aetherenergie.com/) offers an AI-powered end-to-end platform for rooftop solar installers. We combine advancements in computer vision/lidar and LLMs to bring a unique workflow automation tool for solar installers worldwide.\n\n## Before we start, a sneak peek at Aether:\n\n![uploaded image](/media/?type=post&id=79053&key=user_uploads/1527633/4dd1fd38-1a6f-42f1-b8b8-1ad5d62ea174)\n\n## Some Background\n\n---\n\nHey all, we’re [Shelby Bons](https://linkedin.com/in/shelby-bons-ucberkeley) and [Zayne Sagar](https://linkedin.com/in/zaynesager), two climate entrepreneurs! Our fundamental mission is to make rooftop solar energy accessible and cheap throughout the world.\n\n![uploaded image](/media/?type=post&id=79053&key=user_uploads/1527633/561a67f7-4f40-419e-af7f-2ff7557ac5b7)\n\nFor rooftop solar to be deployed, it’s really up to solar installers. To us, the people who run these companies are our heroes. Last year we spoke to hundreds of solar installers and one thing is clear - they don’t have the tools to make them successful. We reimagined rooftop solar software from the ground up for them.\n\nAether _automates the boring stuff for solar installers using AI_.\n\n## **❌** The Problem:\n\nThe biggest problem in US rooftop solar is still solar soft costs. These are non-hardware costs associated with a solar project, and they amount to north of 60% of the total solar cost of an installed system! If you reduce this you create more demand for rooftop solar in the market = better outcome for our planet.\n\n**Contributors to high soft costs:**\n\n* **PV CAD Design teams still manually build rooftop PV site designs**. This is time-consuming and prone to lots of errors. Mistakes here mean re-doing plansets and permitting which can cost $1k - $2k extra.\n* **Almost all solar design tools are inaccurate in production and consumption modeling**. This is what tells rooftop owners “Is this the right investment for me?” Most solar tools were built as a sidekick for sales reps, with just enough basic estimates to sell a solar proposal. Consumers are smarter now and recent legal litigations are forcing better modeling to be done when selling solar.\n* **Dependency on multiple platforms:** Most solar companies use a software stack of 6 - 10 point solutions. Collectively the solution is dumb and creates chaotic workflows where deals get lost and project delays happen a lot. This is very expensive.\n* **Lack of project visibility across teams** causing lost sales deals, and project delays\n\nWe estimate $5k to $ 7k added soft costs for a typical rooftop project occurring because of the above.\n\n## **✅** Solution:\n\n**Aether is built to streamline the rooftop solar workflow end to end. Think Procore or Veeva but for Solar with an AI twist.**\n\nWith Aether, solar companies can rapidly generate PV site designs, sell using a beautiful PV proposal, and then manage it to installation in one simplified workflow.\n\nAether is made up of hubs that help specific roles in a solar installation company do their job, but more importantly, collaborate with other teams as needed with the help of AI.\n\n**Our two core innovations:**\n\n* We built an in-house computer vision model.\n* We also decided to build a mini fine-tuned model for solar. Being trained on items such as system production data, vision model outputs, etc. (Can’t give the rest of our sauce away!)\n\n![uploaded image](/media/?type=post&id=79053&key=user_uploads/1527633/a0dc44ab-bc4f-498d-bc2d-7318a4751d70)\n\n**The result is a unified AI platform to streamline solar with solar agents.**\n\n[Aether Platform - Sneak Peak](https://www.youtube.com/watch?v=EFJuKOI8kEs&feature=youtu.be)\n\n**💲Opportunity:** Aether will be a big player in the young and emerging Solar software vertical, which has a projected 20B Global TAM up for grabs by 2025.\n\n## About Us\n\n_Shelby and Zayne met at UC Berkeley close to a decade ago both originally being born in complete opposite ends of the world, France and Fiji._\n\n_Shelby studied Materials Science and Engineering at UC Berkeley and was briefly headed for a Ph.D. in Theoretical Physics before founding Aether. She has worked at Dolby Laboratories, Voltaiq, and Sunrun in Data Science & Machine Learning roles._\n\n_Zayne had brief stints at multiple climate-driven companies, working on problems around space-based weather data and energy modeling problems at the intersection of software. He has built high-performing product & engineering teams from the ground up by the age of 28._\n\n## **🙏** Our Ask:\n\n* Please share this post with your network, and tell solar installers about us!\n* If you are a rooftop solar installer, check us out at <https://aetherenergie.com/> and book a demo with us!\n* If you’re as excited as we are about this novel approach to solar software and would like to learn more about what we’re doing, comment below or email us at [zsagar@aetherenergy.me](mailto:zsagar@aetherenergy.me)\n\n**💲Early adopter discount**: We’re giving solar installers 50% off whatever design tool they currently pay for.",
        "url": "https://www.ycombinator.com/launches/KZ3-aether-ai-platform-for-rooftop-solar",
        "votes": 23,
        "created_at": "2024-03-05T02:02:09.486Z"
      }
    ]
  },
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    "id": 29352,
    "name": "Firebender",
    "slug": "firebender",
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    "website": "https://firebender.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Firebender is the most powerful coding agent for Android engineering. \r\n\r\nOne-click install from the IntelliJ plugin marketplace to your IDE. It has context over your codebase and lets you use the best models for asking questions, debugging code, and writing full features.\r\n\r\nUnlike other AI assistants, Firebender has access to the emulator, compose previews, and LSP tools like finding usages, renaming variables/functions. It continuously stays up to date with the latest Android SDKs, libraries, and best practices, providing more accurate and relevant assistance for Android development.",
    "one_liner": "Most powerful coding agent for Android engineers",
    "team_size": 1,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1707094110,
    "tags": [
      "AI",
      "AI Assistant"
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    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Winter 2024",
    "status": "Active",
    "industries": [
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    ],
    "regions": [
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      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/firebender",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/firebender.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/firebender-com/",
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    "github_url": "https://github.com/firebenders",
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    "primary_partner": {
      "name": "Gustaf Alstromer",
      "url": "https://www.ycombinator.com/people/gustaf-alstromer"
    },
    "founders": [
      {
        "user_id": 451682,
        "full_name": "Aman Gottumukkala",
        "title": "Founder",
        "founder_bio": "Aman is the cofounder of Firebender, an AI-powered coding assistant built exclusively for Android Studio.\n\nBefore Firebender, Aman was a 2020 Kleiner Perkins Eng fellow and the 3rd engineer at Paradigm, where he built trading and internal data infrastructure from scratch, automated Ethereum derivative trading strategies yielding 20%, and published novel zero-knowledge cryptography research.\n\nHe interned at Google, Instagram, Twitch, and Microsoft in college.",
        "is_active": false,
        "linkedin_url": "https://linkedin.com/in/amangotchu",
        "x_url": "https://twitter.com/amangotchu",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/527bc6ba2f7ca56f3a971fa3d8e499eeb0bb2952.jpg"
      },
      {
        "user_id": 829883,
        "full_name": "Kevin Tang",
        "title": "Founder/CTO",
        "founder_bio": "Previously, Kevin was a software engineer at Two Sigma where he architected and built service infrastructure for modeling, trading, and engineering teams (scale ~10K CPUs, ~1PB RAM). Kevin learned to program by creating Roblox games in high school; one of his games had 2,000 concurrent players and featured on the front page.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/distributed",
        "x_url": "https://x.com/kevo1ution",
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    "jobs": [
      {
        "id": 79060,
        "title": "Founding Engineer (Generalist)",
        "url": "https://www.ycombinator.com/companies/firebender/jobs/yisDXr5-founding-engineer-generalist",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$180K - $250K",
        "equity_range": "1.00% - 3.00%",
        "experience": "Any (new grads ok)",
        "visa": "Will sponsor",
        "skills": []
      }
    ],
    "news": [],
    "launches": [
      {
        "id": 84402,
        "title": "🔥 Firebender - The best AI assistant for Android Studio",
        "tagline": "Meet Firebender, Android Studio's missing AI assistant.",
        "body": "Hey everyone! We’re Aman and Kevin from [Firebender](https://firebender.com/), building the best AI tools for Android developers.\n\n**TLDR:** [Firebender](https://firebender.com/) is a **free** and **privacy-first** Android Studio AI assistant.\n\n### **🎥 Firebender in Action**\n\n<https://youtu.be/It-TD_95yNk>\n\n### **🛠️ Problem**\n\n* **Inefficient Workflows**: Constantly switching between Android Studio and ChatGPT is annoying, disrupts your development flow, and reduces productivity.\n* **AI Assistants are shit**: General-purpose AI coding tools don't integrate relevant Android-specific contexts like Logcat and the emulator. Some flat-out don’t work in Android Studio at all.\n\n  _“Gemini and Copilot are comically bad. I never use them”_ - Android Tech Lead at GoodRx\n* **Outdated Android Training Data**: Leading AI models have a knowledge cutoff that lags behind Android's fast-paced, often backward-incompatible changes. This gap leads to incorrect AI code suggestions for updated SDKs, libraries, architecture patterns, and UI frameworks like Jetpack Compose.\n\n  _“GPT4 and Claude were clueless about the Android UI framework we use. We had to build an in-house context retrieval system to make AI coding useful.”_ - Senior Staff Android Eng at Airbnb\n\n### **🔥 Our Solution - Firebender**\n\n* **Android Studio Plugin:** One click [install](https://plugins.jetbrains.com/plugin/25224-firebender) from IntelliJ marketplace.\n* **Talk to your codebase**: AI chat window for comprehensive assistance with your codebase, logs, profiler, and emulator.\n\n  ![uploaded image](/media/?type=post&id=84402&key=user_uploads/451682/07fb823c-fd19-4659-8c42-6a98d523a6aa)\n\n* **Fast Edit**: Enables quick, context-aware code modifications directly in your current file.\n\n  ![uploaded image](/media/?type=post&id=84402&key=user_uploads/451682/7bd9e58e-fd4f-4983-9967-a882197fb9d9)\n\n* **Up-to-date Android Knowledge**: Firebender scrapes real-time knowledge from the latest SDKs, libraries, repos, and docs into context.\n* **Free &amp; Privacy First**: We do **not log, store, or persist your code**.\n\nAn iOS developer with 10 years of experience built his first Android app in just 3 weeks using Firebender—a task that had taken him 3 months for iOS.\n\n_\"There was no way I could've built it as fast as I did without Firebender\"_ - iOS Eng at Sinai Health\n\n### **🤷 Why we built Firebender**\n\nA few months ago, we were developing Firebender OS - an AI-powered fork of Android. We rooted Pixel 8s and created an AI assistant that activates by holding the power button. It automated tasks like drafting calendar invites from messages and opening relevant apps based on your location and schedule. Despite using it every day, we realized the added value wasn't sufficient. We didn’t love the product.\n\nThroughout this process, we constantly struggled without a good AI coding assistant for Android development. Existing tools have shockingly poor Android support, focusing instead on other IntelliJ IDEs and languages. This gap revealed a clear opportunity so we pivoted immediately to building Firebender, the best AI coding assistant for Android developers.\n\n### 🙏 **Our Asks**\n\n* [Try Firebender](https://plugins.jetbrains.com/plugin/25224-firebender/versions/stable) for Android Studio\n* Share Firebender with your Android developer friends!",
        "url": "https://www.ycombinator.com/launches/LxK-firebender-the-best-ai-assistant-for-android-studio",
        "votes": 50,
        "created_at": "2024-09-30T22:22:09.047Z"
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  },
  {
    "id": 29360,
    "name": "Open",
    "slug": "open",
    "former_names": [
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      "Open",
      "Opens"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2ffd914850938fa6bf113c48744141e940a90a14.png",
    "website": "https://open.cx",
    "all_locations": "Amman, Amman Governorate, Jordan",
    "long_description": "Open is an AI-powered, all-in-one customer support and communication platform — used in production by:\r\n\r\nPrint.com, Mollie.com, Viva.com, More.com, Orderchamp.com, OneCarNow.com, and other major enterprise companies.\r\n\r\nWe specialize in solving and automating complex support cases across email, web, phone, SMS, and WhatsApp.\r\n\r\nWe’re a research-based company currently working on releasing Support-Bench, the world’s most comprehensive AI customer support benchmark.\r\n\r\nOur team consists of +3 programming language builders, a nationwide cybersecurity competition winner at age 16, and a dentist.",
    "one_liner": "Enterprise AI customer support",
    "team_size": 21,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1701287911,
    "tags": [
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      "Customer Service",
      "Customer Support",
      "Conversational AI",
      "AI Assistant"
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    "status": "Active",
    "industries": [
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      "Engineering, Product and Design"
    ],
    "regions": [
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      "Middle East and North Africa",
      "Remote",
      "Partly Remote"
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    "stage": "Early",
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    "demo_day_video_public": false,
    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/open",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/open.json",
    "year_founded": 2024,
    "city": "Amman",
    "country": "JO",
    "linkedin_url": "https://www.linkedin.com/company/opencopilot",
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    "github_url": "https://github.com/openchatai/",
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    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
    },
    "founders": [
      {
        "user_id": 939439,
        "full_name": "Mohammad Gharbat",
        "title": "Founder",
        "founder_bio": "Building Open.cx",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/gharabat",
        "x_url": "",
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    ],
    "jobs": [
      {
        "id": 86135,
        "title": "Enterprise Account Executive (new business), Europe",
        "url": "https://www.ycombinator.com/companies/open/jobs/waG5YFh-enterprise-account-executive-new-business-europe",
        "location": "Amsterdam, NH, NL / Amsterdam, North Holland, NL / DE / ES / Remote (Amsterdam, NH, NL; Amsterdam, North Holland, NL; DE; ES)",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "€80K - €190K EUR",
        "equity_range": "0.25% - 0.50%",
        "experience": "3+ years",
        "visa": "US citizenship/visa not required",
        "skills": []
      },
      {
        "id": 86136,
        "title": "Enterprise Account Executive (new business) ",
        "url": "https://www.ycombinator.com/companies/open/jobs/JGgxRGB-enterprise-account-executive-new-business",
        "location": "San Francisco, CA, US / Remote (US)",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$230K - $300K",
        "equity_range": "0.25% - 0.50%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      }
    ],
    "news": [
      {
        "title": "Open.cx Closes $1.52M Funding Round to Disrupt Customer Support with Advanced AI Solutions",
        "url": "https://theaiinsider.tech/2025/01/13/open-cx-closes-1-52m-funding-round-to-disrupt-customer-support-with-advanced-ai-solutions/",
        "date": "Jan 13, 2025"
      },
      {
        "title": "Adriaan Mol, Mollie CEO Koen Köppen, and YC back this new AI startup: Know more  - Silicon Canals",
        "url": "https://siliconcanals.com/adriaan-mol-koen-koppen-back-open-cx/",
        "date": "Jan 13, 2025"
      },
      {
        "title": "Adriaan Mol, Mollie-ceo Koen Köppen en Y Combinator investeren samen ruim 1,5 miljoen dollar in Open.cx, een AI-tool voor customer support die is ontwikkeld door ex-Mollie-medewerker Mohammad Gharbat.",
        "url": "https://mtsprout.nl/nieuws/facebook-moeder-kapt-met-dei-initiatieven-abn-amro-wil-franse-topvrouw",
        "date": "Jan 12, 2025"
      },
      {
        "title": "Revolutionizing Customer Support: Open.cx Secures $1.52M in Pre-Seed Funding - CEOWORLD magazine",
        "url": "https://ceoworld.biz/2025/01/13/revolutionizing-customer-support-open-cx-secures-1-52m-in-pre-seed-funding/",
        "date": "Jan 12, 2025"
      },
      {
        "title": "Adriaan Mol stapt in veelbelovende AI-start-up - Emerce",
        "url": "https://www.emerce.nl/nieuws/adriaan-mol-stapt-veelbelovende-aistartup",
        "date": "Jan 12, 2025"
      }
    ],
    "launches": [
      {
        "id": 86713,
        "title": "Open - Enterprise AI Customer Support",
        "tagline": "All-in-one, truly AI-driven platform for customer support. Scale to millions while maintaining a personal touch with each customer.",
        "body": "### **tl;dr**\n\n[Open.cx](http://Open.cx) is an AI-powered, all-in-one customer support and communication platform designed for enterprises and high-growth businesses.\n\nIn the last few months, our customers have processed and resolved thousands of complex issues using our AI agents in industries like payment service providers, security, and e-commerce.\n\n<https://youtu.be/FhPEcRJV_hw>\n\nToday, Open is the only AI customer support platform in the **WORLD** that allows you to train AI agents from more than 27 sources in one click, deploy these agents on the Web (widget), email support, phone calling support, SMS, WhatsApp, Slack, and more channels (ALL AI)— while giving you very precise auto-recommendations on how to make your AI agents better. You can train these agents to solve the most complex support problems (L2 and L3 support issues and way beyond simple text answers).\n\n![uploaded image](/media/?type=post&id=86713&key=user_uploads/939439/ee8f7492-5d67-4459-924a-4a499c13995f)\n\n_(Unified AI inbox for web, email, SMS, WhatsApp, phone calls and more)_\n\n![uploaded image](/media/?type=post&id=86713&key=user_uploads/939439/119684d3-68a3-4284-bbaa-8d3dd2659a8d)\n\n_(Outbound support with AI phone calls, AI SMS Messages, and emails)_\n\n---\n\n---\n\n---\n\n---\n\n![uploaded image](/media/?type=post&id=86713&key=user_uploads/939439/f5409c0a-1c83-41fb-af96-f110002a971c)\n\n_(Contacts are auto-enriched with AI)_\n\n![uploaded image](/media/?type=post&id=86713&key=user_uploads/939439/8996c731-37f7-4f31-bc47-8c82caa46912)\n\n_(Train your AI agents with pre-made knowledge connections)_\n\n![uploaded image](/media/?type=post&id=86713&key=user_uploads/939439/cbf8ebd7-3ab3-402b-a61d-f366a39aca35)\n\n_(Complete control over your AI channels, settings, phone numbers and more)_\n\n![uploaded image](/media/?type=post&id=86713&key=user_uploads/939439/de92626c-f1db-4b0b-a9ed-8e6e39a3084c)\n\n_(Built with security in mind)_\n\n![uploaded image](/media/?type=post&id=86713&key=user_uploads/939439/088459d2-b6f7-4dfc-b951-8e3d07664826)\n\n(Easy-to-understand reports)\n\n### Problem\n\nThe current customer support and communication landscape is fundamentally flawed:\n\n1. **Scaling without sacrificing quality**:\n\n   Companies struggle to manage increasing ticket volumes across channels while maintaining high customer satisfaction. Adding headcount isn’t sustainable, and current tools lack the intelligence to keep up.\n2. **Fragmented and unintelligent tools**:\n\n   Businesses rely on a disconnected array of systems—one for email, another for phones, and another for chat. These tools don’t communicate, and even AI-based solutions are often limited to handling basic inquiries, leaving agents burdened with complex tasks.\n\n   Ask yourself: _How many tools did you use in 2024 to talk to your customers and to understand them better?_ We think it should be **one**.\n3. **Inadequate AI for Enterprise Needs**:\n\n   Current AI agents are optimized for basic, repetitive tasks like FAQs or simple ticket routing. They fail to handle the complexity of enterprise operations, where business rules, workflows, and logic require tailored, context-aware AI that can adapt to each organization’s unique needs. Enterprises need AI that doesn’t just automate—it understands, acts, and integrates into their processes.\n\nThis inefficiency leads to slow resolutions, frustrated customers, and rising costs.\n\n### Solution: Open.cx\n\n1. **AI at the Front Line**:\\\n   [Open.cx](http://Open.cx)’s AI manages all channels—web, phone, email, WhatsApp, chat, SMS, and Slack— fast, accurate, and consistent responses for every interaction.\n2. **Clear Handoff to Humans**:\\\n   When human intervention is needed, [Open.cx](http://Open.cx) simplifies the transition, we allow AI and human agents to collaborate effectively in a unified workspace.\n3. **Optimized for Complex Support (L2, L3)**:\\\n   We excel at handling advanced (L2 and L3) tickets, from technical troubleshooting to intricate workflows, going far beyond basic automation.\n4. **Trainable**:\\\n   We integrate with 28+ training sources (Notion, Confluence, Google Drive, Dropbox, and more), so wherever your customer support knowledge resides, we can sync it with the AI.\n5. **Enterprise-Grade Features**:\\\n   With customizable workflows, deep business logic integration, and advanced automation.\n6. **Massive Customer Understanding**:\\\n   Our **Voice of Customer (VOC)** feature provides actionable insights from every interaction, helping businesses improve products and prioritize features.\n\n### **Ask**\n\nIf your company gets more than 5,000 support tickets per month, let us know—we can help. We have a high-touch approach, and our product is super fun to work with (not my words, XD).\n\n[mo@open.cx](mailto:mo@open.cx) or [book a call.](https://cal.com/opencopilot/discovery-call-open?date=2025-01-08&month=2025-01)",
        "url": "https://www.ycombinator.com/launches/MYb-open-enterprise-ai-customer-support",
        "votes": 36,
        "created_at": "2025-01-09T15:42:53.139Z"
      }
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    "id": 29362,
    "name": "Pazi",
    "slug": "pazi",
    "former_names": [
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      "Pythagora (GPT Pilot)",
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    "website": "https://pazi.ai/",
    "all_locations": "",
    "long_description": "Pazi enables people to build agents that run all operations in a company. You create an agent for a position (eg. developer, devops, social media manager, SDR, etc.), you give it a goal (eg. reach 10k followers on X) and let it create a plan, start checking in with you, oversee how the goal is coming up.",
    "one_liner": "Platform where autonomous companies are built",
    "team_size": 7,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1709274350,
    "tags": [
      "Developer Tools",
      "Security",
      "Web Development",
      "AI"
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2024",
    "status": "Active",
    "industries": [
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    "regions": [
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      "Partly Remote"
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    "stage": "Early",
    "app_video_public": false,
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    "app_answers": null,
    "question_answers": [
      {
        "question": "How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)",
        "answer": "Senko and Zvonimir met at a startup event in 2016. when Senko was looking for someone who would lead a side project that he started. Zvonimir accepted the challenge, we turned that project into a company, and 5 years later, in 2021., we sold the company to Miro.Leon and Zvonimir have been best friends since starting college in 2009. and after the Miro acquisition, we started learning ML together and playing with different ideas. In 2023. we created our first open-source project for generating automated tests with AI and it quickly gained 1.4k Github stars. After talking to users and observing how AI is evolving, we decided to pivot to GPT Pilot, which became one of the fastest-growing open-source projects ever.While we worked on the GPT Pilot, Senko was exploring a similar idea, so finally, in October 2023. we decided to join forces and build Pythagora together."
      }
    ],
    "url": "https://www.ycombinator.com/companies/pazi",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/pazi.json",
    "year_founded": 2026,
    "city": null,
    "country": null,
    "linkedin_url": "https://www.linkedin.com/company/pazi-agi",
    "x_url": "https://x.com/pazidotai",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/pythagora",
    "github_url": "https://github.com/Pythagora-io",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/39be77a3f81a0c68f20c5bdfe6e6a34a1979d88c.png",
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    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
    },
    "founders": [
      {
        "user_id": 170713,
        "full_name": "Zvonimir Sabljić",
        "title": "Founder",
        "founder_bio": "I am an engineer and a technology entrepreneur. I cofounded AWW (A Web Whiteboard), which became a major player in the online whiteboard market. AWW had 1.5M MAU, with Apple as our largest customer. In 2021, it was acquired by Miro.\n\nI created two successful open source repositories - automated testing repo that got 1.4k Github stars and now, GPT Pilot, which has over 22k stars.\n\nCurrently, I'm working on bringing software development into the AI age.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/zvonimirsabljic",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/803057e47b472c272931d6eb920cdd64309d33c9.jpg"
      },
      {
        "user_id": 1047121,
        "full_name": "Leon Ostrež",
        "title": "Founder/CTO",
        "founder_bio": "Software engineer, computer scientist (M.Sc.) and entrepreneur. Problem solving and attention to details with big persistence is my passion.\nI led the tech team at Faze Clan before they went public at $1B valuation and was a key contributor of Plex at Ericsson - the core language that handles 25% of the world's 2G and 3G network communication.\nI created two successful open source repositories - automated testing repo that got 1.4k Github stars and now, GPT Pilot, which has over 22k stars.",
        "is_active": true,
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      {
        "title": "Y-Combinator-backed Pythagora AI secures $4M for open source app development with AI - Tech.eu",
        "url": "https://tech.eu/2024/05/14/y-combinator-backed-pythagora-secures-4m-funding-revolutionizing-app-development-with-ai/",
        "date": "May 14, 2024"
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      {
        "id": 91577,
        "title": "Pythagora: All-in-one AI development platform",
        "tagline": "Try Pythagora and transform your ideas into production ready apps!",
        "body": "### **TLDR**\n\nPythagora is an all-in-one AI dev platform that is focused on building production-ready apps that you can deploy, use, and share.\n\n[Video](https://www.youtube.com/watch?v=o1nEvwjKziw)\n\n### **Problem**\n\nWe built Pythagora after seeing too many AI-generated projects either abandoned at the first sign of trouble or trapped in endless \"fix it\" loops with no visibility into what's actually happening. Without proper logs, breakpoints, or debugging tools, users were left guessing and rebuilding repeatedly.\n\n![uploaded image](/media/?type=post&id=91577&key=user_uploads/1047121/e2ca5b1e-9f0d-40ae-b6fc-30a24cf4abfe)\n\n### **Another codegen tool?**\n\nWhile other platforms focus on the initial \"wow\" of code generation, we've designed for the complete reality of software development. Every application will face challenges when it meets real users with real data.\n\nOur key differences:\n\n1. Overview: Clear overview of the project roadmap and your current progress.\n2. End-to-end development: From project planning to deployment (our cloud backed by AWS or your own infra - take your code wherever)\n3. Tools access - Easy access to app preview, logs, and knowledge base.\n4. Real debugging tools: Breakpoints, logs, and database inspection when something inevitably breaks\n5. Full-stack architecture: Proper backend, frontend, and database relationships, not just UI demos\n\n### **Final thoughts**\n\nWe're most proud that Pythagora treats your applications as living projects, not disposable demos. The platform shines exactly where others fall short: when you need to fix, improve, and deploy what you've built.\n\nStop treating AI-generated apps as disposable. Start building applications worth maintaining, fixing, and deploying.\n\n* **Explore apps built with Pythagora:** [pythagora.ai/examples](http://pythagora.ai/examples)\n* Read case studies of users creating meaningful apps: [pythagora.ai/case-study](https://www.pythagora.ai/case-study)\n\n### [**🙏**](https://www.pythagora.ai/case-study-medical-research) Ask\n\nIf you know a company that’s looking to build internal tools, please connect us. I’d be happy to give them a demo.",
        "url": "https://www.ycombinator.com/launches/Np3-pythagora-all-in-one-ai-development-platform",
        "votes": 14,
        "created_at": "2025-06-24T14:25:35.556Z"
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      {
        "id": 84468,
        "title": "🧮 Pythagora - Build tools completely in natural language",
        "tagline": "Pythagora is an AI dev tool that enables humans to build production ready apps using only natural language.",
        "body": "TLDR; Pythagora is a VS Code Extension that writes all the code for the app you want to build and talks to you whenever it needs a creative decision or feedback. It is focused on building production-ready apps that you can deploy and use, so to achieve that, it keeps you, the human, in the loop throughout the entire development process. Pythagora manages the entire codebase and talks to you in natural language.\n\n### **🤨 Problem**\n\nToday, new AI dev tools come out almost weekly. While many showcase impressive demos, very few prove their worth in building real-world, production-level applications. We think that this is because they don’t put the human in the loop enough. There is a notion that apps can be built just by writing 2 sentences of what kind of an app you want, and then you just wait until AI comes back with a fully built application.\n\nWe believe that humans have to be involved in the entire process of app development to give timely feedback so that AI can make changes as it works on specific features.\n\n### **💡 solution**\n\n![](https://www.ycombinator.com/media/?type=post&id=79066&key=user_uploads/170713/2c530744-eaf9-4870-9e87-d4bfd806082d)\n\nPythagora talks to the user throughout the entire development process. First, it creates a plan for building the entire application. Then, it goes task by task, implementing each one, but before going on to the next one, it asks the user to test whether it’s working as intended. We noticed that very often, Pythagora implements a feature correctly, but users, once they see how a feature works, decide they want it to work differently.\n\n* Watch the full crash course on how to use Pythagora here: [https://youtu.be/HIIHx0kErPc](https://www.youtube.com/watch?v=4g-1cPGK0GA)\n* **Explore apps built with Pythagora:** [pythagora.ai/examples](http://pythagora.ai/examples)\n* Read case studies of users creating meaningful apps: [pythagora.ai/case-study-medical-research](http://pythagora.ai/case-study-medical-research)\n\n### [**🙏**](https://www.pythagora.ai/case-study-medical-research) **Ask**\n\nIf you know a company that’s looking to build internal tools, please connect us. I’d be happy to give them access to Pythagora v1 and do a demo.",
        "url": "https://www.ycombinator.com/launches/LyO-pythagora-build-tools-completely-in-natural-language",
        "votes": 9,
        "created_at": "2024-10-02T18:00:05.786Z"
      },
      {
        "id": 79066,
        "title": "Pythagora - First complete AI developer that builds apps by talking to you",
        "tagline": "Open source VS Code extension that enables you to build production-ready apps from scratch in 1/20th of time",
        "body": "**TL;DR** [Pythagora](https://pythagora.ai/) is not a coding assistant or an autocomplete. It’s a true AI developer that takes your requirements, asks you questions, considers what technologies to use, and creates the development plan. Then, it breaks the plan into tasks, writes code, reads the CLI, fixes bugs, iterates, reviews the code, and asks you questions to make sure it’s on the right track.\n\n### 🛤 **OUR JOURNEY**\n\n![uploaded image](/media/?type=post&id=79066&key=user_uploads/170713/273e17b6-e99a-464a-9faf-c5a223e81bb6)\n\n[Senko](https://linkedin.com/in/senkorasic) and [Zvonimir](https://linkedin.com/in/zvonimirsabljic) met at a startup event in 2016. when Senko was looking for someone who would lead a side project that he started. Zvonimir accepted the challenge, we turned that project into a company, and 5 years later, in 2021, we sold the company to Miro.\n\n[Leon](https://linkedin.com/in/leon-ostrez-b55494178) and Zvonimir have been best friends since starting college in 2009. After the Miro acquisition, we started learning ML together and playing with different ideas. In 2023, we created our first open-source project for generating automated tests, and it quickly gained 1.4k Github stars. After talking to users and observing how AI is evolving, we decided to pivot to GPT Pilot, which became one of the fastest-growing open-source projects, now with more than **22k Github stars**.\n\nWhile we worked on the GPT Pilot, Senko explored a similar idea, so finally, in October 2023, we decided to join forces and build Pythagora together.\n\n### **❌ The Problem**\n\nOk, let’s state the obvious - there’s still a huge demand for software development, which is still expensive. On the other hand, we have LLMs that are extremely good at writing code. They can write code snippets like a senior developer but if you ask them to build the full app, it will do a worse job than a junior developer. This is because building production-ready apps is not only writing code. It’s writing code, running it, debugging, iterating, changing requirements, refactoring, and many other mechanisms that developers do every day.\n\nWhile LLMs are getting smarter every single day, they will always be answering machines—they won’t have the mechanics that allow humans to iteratively progress on building an app.\n\nThe good thing is that all these mechanisms are deterministic and repetitive.\n\n### **🌟 Our Solution**\n\n![uploaded image](/media/?type=post&id=79066&key=user_uploads/170713/2c530744-eaf9-4870-9e87-d4bfd806082d)\n\nPythagora is a blueprint of what app development looks like. First, it takes your requirements and asks you questions to clarify how you want your app to look. Then, it thinks about what technologies should be used for your specific app and creates the development plan. Then, it breaks the plan into tasks, writes code, reads the CLI, fixes bugs, iterates, reviews the code, and refactors it. Before making each commit, it asks you questions to make sure that the app works exactly as you want. Finally, it proceeds this way to the next task until the entire app is finished.\n\nMany AI copilots help developers write code faster, but Pythagora goes beyond the current developer experience — we’re reimagining how software development is done.\n\n### **🙏 Asks**\n\nIf you know any company that’s looking to build internal tools, it would be amazing if you could connect us. I’d be happy to demo Pythagora to them.\n\nAlso, it would be amazing if you could share this launch on Linkedin or Twitter.\n\nFinally, join us on [Discord](https://discord.gg/HaqXugmxr9)!",
        "url": "https://www.ycombinator.com/launches/KZG-pythagora-first-complete-ai-developer-that-builds-apps-by-talking-to-you",
        "votes": 36,
        "created_at": "2024-03-05T15:19:41.894Z"
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    "country": "US",
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        "full_name": "Sahil Sinha",
        "title": "Founder/CEO",
        "founder_bio": "Grew up between India and the UK.\nClaremont McKenna College '20. \nIntuit Rotational PM Program '20-'22\n",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/sssinha20",
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      {
        "id": 83820,
        "title": "Lytix - A single solution for the full lifecycle of LLM applications",
        "tagline": "Lytix is one control panel to observe, manage and optimize your E2E LLM stack.",
        "body": "**TL;DR: Lytix is one control panel to observe, manage and optimize your E2E LLM stack. From early model experimentation to guardrails and specific evaluations, lytix helps teams at any stage save money, move faster, and minimize tech debt.**\n\n⚠️ **The Problem**\n\n1. You want to use and experiment with multiple models, but setting up interfaces per provider/model is painful and slows you down.\n2. As your product gets more specific, tracking performance becomes more challenging as off-the-shelf metrics lack the domain context to evaluate the unique attributes _you_ care about.\n3. You want to protect your inference calls against known failures, but finding + integrating the right guardrails for your use case is time-consuming and confusing.\n4. Simple logging is great, but it gets hard to interpret and find bugs quickly, especially if you have multiple LLM tasks all being logged in a single place.\n\n**⚡ Our Solution**\n\nLytix helps teams of all sizes build faster, save money, and minimize tech debt.\n\n**Single Gateway For All Models & Providers.**\n\n1. Integrate [seamlessly](https://docs.lytix.co/Quickstart/openai-integration) with your existing stack to quickly get started.\n2. Instantly gain access to 25+ models; switching between models becomes a 1-line change.\n3. Our code is open-source, so you can always add more providers and models that are specific to you.\n\n![uploaded image](/media/?type=post&id=83820&key=user_uploads/1639132/3018a6a5-f5e6-494c-9b87-e4c320e89c54)\n\n**Guardrails & Alerts**\n\n1. An intuitive and flexible framework for adding SOTA guardrails to your inference calls, and set up real-time fallback logic\n2. Configure alerts in **seconds**, to instantly get alerted when guardrails fail\n\n![uploaded image](/media/?type=post&id=83820&key=user_uploads/1639132/c5e44af3-d41d-4013-8b1e-98db8c663e46)\n\n**Build Specific Evaluations**\n\n1. Easily build new eval metrics bespoke to _your_ product, factoring specific domain knowledge and context.\n2. Track how your specific evals perform over time, and easily find anomalous sessions or problematic users.\n3. Move beyond ‘feelings’, and start to quantify your results as you experiment with different configurations, model combinations and prompts.\n\n![uploaded image](/media/?type=post&id=83820&key=user_uploads/1639132/9c7e0c81-06d9-4954-9036-466639cefadd)\n\n**Grouping LLM events by task**\n\n1. Instead of a single stream of logs, lytix divides your logs by the task they belong to.\n2. Debug errors faster by viewing them in the right context.\n3. Cut critical metrics (like cost, latency, error rates) by task, to answer questions like ‘what is our most expensive task?’ or “which tasks are failing the most?”\n\n![uploaded image](/media/?type=post&id=83820&key=user_uploads/1639132/767653cb-a38a-4df9-a154-3f981a9246f2)\n\n**Product + LLM Insights**\n\n* Identify themes and patterns in your LLM interactions\n* Export that LLM events, with evals, to product analytic tools (such as Posthog) to combine product and LLM metrics into a single insight (i.e., cut conversation length by prompt).\n\n![uploaded image](/media/?type=post&id=83820&key=user_uploads/1639132/adcfbfeb-5f0b-4560-917c-d8bcfc4c5e76)\n\n**And much more…**\n\n* Bring your own cache: own your data and save money on requests by hosting your own cache\n* Playground to test new or existing events against 25+ models\n* Cost + Token usage tracking\n* Datasets to collect events for fine-tuning\n\n🪩 **The Team**\n\nWe’ve both worked in the tech, and have known each other since high school.\n\nSahil worked as a product manager at Intuit, working on teams all over the world. For QuickBooks international, he launched localized sales tax and “send invoice via WhatsApp” increasing 91d retention, subscription rates, and invoice sends for emerging markets. He also worked on complex machine learning systems, working on matchmaking models for QuickBooks Live.\n\nSid worked at a verity of startups after college working on a breath of tasks from cybersecurity to infrastructure and devops. He was cited as an author on a state of the art cryptography [white-paper](https://eprint.iacr.org/2023/296.pdf) and has helped teams containerize and migrate infrastructure while maintaining 50,000+ active users.\n\nWe are builders at heart and believe that lytix is the future of how to build and scale LLM products.\n\n![uploaded image](/media/?type=post&id=83820&key=user_uploads/1639132/feb330f8-8a93-401b-b5d2-8df9b4bf4afb)\n\n**🚀 Lytix can be used today!**\n\n* [Free to start](http://lab.lytix.co/home/login/) and use up to 100k messages.\n* We love learning about problems, if you have any in the LLM space we’d love to be helpful and [chat](https://book.vimcal.com/p/sahilsinha/30minutes-8347b)!\n* Check out our [open-source](https://github.com/Lytix-Labs/optimodel) work and get 24/7 support on our [Discord](https://discord.com/invite/u2MFEnhmv3)\n* Follow our socials on [LinkedIn](https://www.linkedin.com/company/103001009/) and [X](https://x.com/lytixai)",
        "url": "https://www.ycombinator.com/launches/Lnw-lytix-a-single-solution-for-the-full-lifecycle-of-llm-applications",
        "votes": 53,
        "created_at": "2024-09-06T17:44:22.249Z"
      },
      {
        "id": 81849,
        "title": "Lytix - Everything you need to monitor, improve and scale your LLM applications",
        "tagline": "Scale and iterate on your LLM products, with minimal changes to your code or tech stack. ",
        "body": "**Everything LLM teams need, to build something your users love. Get started **[**here**](https://www.lytix.co/)**.**\n\n![uploaded image](/media/?type=post&id=81849&key=user_uploads/547106/e9646020-5b9d-4c28-bcf8-6dfa602e31de)\n\n# The Problem ❌\n\nMonitoring and testing LLMs is notoriously challenging. Specifically:\n\n1. **Product insights & monitoring** - how can I see how different customers are using my LLM stack?\n\n   > What are users talking to my bot about? What questions are users asking my search system?\n2. **Testing** - I just made a change to my code. How can I confirm it’s making the change I intended? How can I make sure I haven’t introduced unexpected side effects?\n\n   > _Will making my bot faster make it less reliable? Will switching LLM providers make our system too slow for our customers_\n3. **E2E analytics** - Product 🤝 LLM metrics. How can I see how changes to my LLM stack are impacting my primary product metrics?\n\n   > _I just changed my RAG pipeline, is that improving my conversion rates? Which prompt gives us the best activation rate? What are high vs. low value customers talking to my bot about?_\n4. **Errors** - I’m using 4+ providers across my LLM stack, each with its own logging system and dashboard. How can I quickly view the root cause of my errors and get all the context I need in one place?\n\n**We’ve seen teams waste weeks of dev time building internal tools to solve these problems instead of building what their users want.**\n\n# The Solution 🛠️\n\nLytix brings insights, testing, and E2E analytics to your LLM stack with minimal changes to your existing codebase.\n\n# Product insights 🔎 & monitoring 👀\n\n1. Add a tracer function to any aspect of your LLM stack you’d like monitored\n\n   ![uploaded image](/media/?type=post&id=81849&key=user_uploads/547106/dc47d9d9-39f5-47ed-8fd5-035063e4ade4)\n\n2. _\\[Optional\\]_ - in the Lytix dashboard, define some ‘themes’ you’d like Lytix to start tagging your sessions as. For ex. ‘questions about math’\n\n   ![uploaded image](/media/?type=post&id=81849&key=user_uploads/547106/c660f875-f0f5-4189-b7c5-408bb2ee4b99)\n\n3. If you do not define an intent - Lytix will auto-tag each session with an intent that best summarizes the session.\n4. You can always explore previous sessions and re-configure your themes to change how they appear in your analytics stack\n\n# E2E analytics 📊 ( for ex. PostHog 🦔)\n\n1. Save your PostHog API key in your Lytix account (under settings)\n2. Whenever Lytix sees a new session, we’ll tag it (with the intents you’ve configured), and import them into Posthog with all the associated metadata\n3. In PostHog, you’ll see a “lytix_event” → this event describes your users’ sessions with your LLM stack. **Bring this into your funnel analysis, retention charts, etc., to include your LLM sessions in your product insights**\n\n   ![uploaded image](/media/?type=post&id=81849&key=user_uploads/547106/90a58a3c-03e4-4e81-9ae2-33a8d61eb6ea)\n\n\n# Errors 🚨\n\n1. Wherever you throw an error, use the new Lytix LError class.\n\n   ```\n   async def backgroundProcess():\n       logger = LLogger(\"background-logger\", {\"userId\": '124'})\n       logger.info(\"Some process is starting\")\n       raise LError(\"An unexpected error\")\n   \n   ```\n2. Anytime the error is thrown in production, you’ll find all relevant logs and metadata in your Lytix dashboard\n\n   ![uploaded image](/media/?type=post&id=81849&key=user_uploads/547106/b4373adc-92ec-487b-bef4-90e3dae98cc0)\n\n\nTo try it out yourself, head over to <https://docs.lytix.co/introduction>. You’ll also get 2 founders on deck as analysts to ask any questions about how your customers are using your products 🚀.\n\nAnd get in touch if you:\n\n1. Are about to launch - and would like to chat about best practices\n2. Recently launched - and are thinking about effective analytics and monitoring\n3. Or have a hair-on-fire problem you need to be taken care of!",
        "url": "https://www.ycombinator.com/launches/LI9-lytix-everything-you-need-to-monitor-improve-and-scale-your-llm-applications",
        "votes": 172,
        "created_at": "2024-07-01T15:33:09.746Z"
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    "id": 29365,
    "name": "Ellipsis",
    "slug": "ellipsis",
    "former_names": [
      "BitBuilder",
      "Ellipsis",
      "ellipsis"
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    "website": "https://ellipsis.dev",
    "all_locations": "New York City, NY, USA",
    "long_description": "Ellipsis is a cloud platform that allows engineering teams to deploy fleets of coding agents. Each agent gets an isolated sandbox, scoped permissions, and hard budget caps. Full observability included. Get started with a $100 credit at www.ellipsis.dev.\r\n\r\nYou can deploy agents for feature development, code review, and workflow automation. Creating an agent is simple: simply commit a YAML file to Github. Spawn agents from Github/Linear/Slack/etc., or via a REST API or our CLI. \r\n\r\nOrganizations get full observability and governance of their cloud coding agents.  Agent session logs are downloadable so companies own their own data.\r\n\r\nFull documentation: https://www.ellipsis.dev/docs",
    "one_liner": "Cloud platform for coding agents",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1706288452,
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      "Developer Tools",
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        "full_name": "Hunter Brooks",
        "title": "Founder/CEO",
        "founder_bio": "Building www.ellipsis.dev, a Managed Cloud Agents platform.\n----\n\nPreviously, I created a code generation product that dynamically created programming challenges used in technical interviews. I've worked as an ML Engineer at AWS and Amazon Ads, in addition to filling various engineering roles at companies like Brigit and Capital One.\n\nBefore that, I published in the field of Astrophysics.",
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        "title": "Founding AI Engineer",
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        "title": "🤖 Ellipsis: Automated code reviews & bug fixes",
        "tagline": "We review pull requests and convert GitHub comments into working, tested code.",
        "body": "**TL;DR**: [**Ellipsis**](https://ellipsis.dev?utm_source=launchyc&utm_medium=blog&utm_campaign=yc) is a devtool that converts technical instructions into working, tested code. Customers like PromptLayer and Warp use us to review code and fix bugs, [**and you can too**](https://ellipsis.dev?utm_source=launchyc&utm_medium=blog&utm_campaign=yc)!\n\n---\n\n---\n\n—\n\nHello world, [**Hunter**](https://www.linkedin.com/in/seanhunterbrooks/) and [**Nick**](https://www.linkedin.com/in/nsbradford/) here! We’re building [**Ellipsis**](https://ellipsis.dev?utm_source=launchyc&utm_medium=blog&utm_campaign=yc), an AI devtool that allows engineering teams to ship faster. Today, our customers use us to review pull requests and convert GitHub comments into working, tested code.\n\nBut that’s just the beginning; we’re on a mission to build the AI software engineer. Specifically, we’re automating tasks for the Full Stack Engineer role, starting in the Python and JavaScript/TypeScript ecosystem.\n\n![uploaded image](/media/?type=post&id=78871&key=user_uploads/1449858/918bc808-84a8-4fd5-b106-d4db0ced57ad)\n\n### **How does it work? 🧐**\n\nWorking with Ellipsis is like working with a remote colleague; simply tag it in Slack, GitHub, or Linear. \n\nYou can ask it to:\n\n* Create multi-file code changes from natural language requirements, such as a **bug reports** or **feature requests**\n* Review a pull request, checking for **best practices** and **custom rules**\n* Answer questions about a codebase during onboarding, development, and bug triaging\n* Create daily or weekly digests of the most important changes in your codebase\n* Automate tedious changes, such as **library upgrades** and **refactors**, to a large batch of files\n\nThe best part is that Ellipsis works in the cloud, not on your local laptop. This means developers can have Ellipsis working on multiple tedious tasks in parallel, while they handle the more complex work themselves.\n\nThe question we get most often is “does it work?”, so we invite you to start a [**7 day free trial**](https://ellipsis.dev?utm_source=launchyc&utm_medium=blog&utm_campaign=yc). Or [check](https://github.com/hyperdxio/hyperdx/pull/326) [out](https://github.com/jxnl/instructor/pull/467) [some](https://github.com/relari-ai/continuous-eval/pull/43) [examples](https://github.com/ion-design/numi/pull/1) from the open source community.\n\n### **About the team 🧙‍♂️**\n\n* [**Hunter**](https://www.linkedin.com/in/seanhunterbrooks/) previously created a code generation product that dynamically generated programming challenges used in technical interviews. He's worked as a ML Engineer at AWS and Amazon Ads, in addition to filling various engineering roles at companies like Brigit and Capital One. Before teaching himself to code, he published in the field of Astrophysics.\n* [**Nick**](https://www.linkedin.com/in/nsbradford/) most recently took an AI developer tool for codebase migrations from 0 to 1 as founding engineer of Grit. Previously, he researched LLM interpretability at Redwood Research, managed several teams at ML startup Hyperscience, and worked on trading algorithms at Bridgewater Associates.\n\n### **Our ask 🙏**\n\n* [**Try it out!**](https://ellipsis.dev?utm_source=launchyc&utm_medium=blog&utm_campaign=yc) Ellipsis will review your pull requests (and do a good job!) for 7 days **for free**.\n* Share this post with Engineering leaders interested in enforcing best practices or shipping faster.\n\nOur inbox is always open at [**team@ellipsis.dev**](mailto:team@ellipsis.dev). Here’s a blurb you can copy/paste:\n\n> [Ellipsis](https://ellipsis.dev?utm_source=launchyc&utm_medium=blog&utm_campaign=yc) is an AI devtool that reviews pull requests and converts GitHub comments into working, tested code. Customers like [PromptLayer](https://promptlayer.com/) and [Warp](https://www.joinwarp.com/) use them to ship faster because they spend less time reviewing changes and fixing bugs. You can get started with a 7 day trial immediately, or [schedule time](https://cal.com/hunter-brooks/15min) for a 15 minute demo.",
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        "body": "Hello everyone, we are Mehdi and Salah, the co-founders of [Metofico](https://www.metofico.com/), and we are on a mission to simplify the analysis of complex and large data sets produced by life science research and save researchers months of work.\n\n![uploaded image](/media/?type=post&id=79483&key=user_uploads/1579715/fd599206-68e4-44cb-82b3-7478fb7d4627)\n\n_From left to right:_\n\n[Salah:](https://www.linkedin.com/in/salah-boudjadja-42a05a19b/) MSc in Data Science, Image Processing, and AI; Salah is passionate about making no-code and intuitive tools for science to extract as many insights as possible in the least amount of time.\n\n[Mehdi:](https://www.linkedin.com/in/mehdi-boutagouga-boudjadja-ph-d-553003138/) PhD in Circuit Neuroscience; Mehdi has seen many researchers struggle to analyse Gigabytes of data in Excel and missing opportunities for scientific breakthroughs. He has developed tools to make these analyses simple, and these tools are now Metofico.\n\n**The Problem: Data analysis complexity hampers life scientists, slowing down research.**\n\nThe volume and complexity of data generated by modern life science research are overwhelming. Traditional tools like Excel, once the go-to for researchers, now fall short when faced with gigabytes or terabytes of data. Moreover, most life scientists cannot program or do advanced data science, so they are stuck.\n\n**Our Solution: A no-code, intuitive SaaS platform designed specifically for life science research**\n\nOur platform transforms the way life scientists handle and analyse data, making processes that used to take weeks or months achievable in just minutes. Whether it's video tracking of rodents, fiber photometry, or any other data-intensive research, Metofico makes it simple and fast, with no programming knowledge required.\n\n![uploaded image](/media/?type=post&id=79483&key=user_uploads/1579715/b1b25a9c-9115-4d58-96fc-b2945d58647c)\n\nExample of automated segmentation of rodents using our AI\n\n**Demo:**\n\n<https://youtu.be/F4wL4szgIaE>\n\nExample of brain activity analysis using our fiber photometry analyzer\n\n**Our Ask:**\n\nWe're seeking forward-thinking life science researchers and institutions interested in streamlining their data analysis processes. If you're ready to cut down months of work to just minutes, we'd love to get in touch. Whether it's for feedback, potential partnerships, or just to say hello, your insights are invaluable to us as we strive to make Metofico even better.\n\nContact us at [info@metofico.com](https://mailto:info@metofico.com)",
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        "tagline": "Engineers designing everything from cars to skyscrapers use our software to turn 3D models into the detailed 2D fabrication drawings that manufacturers require.",
        "body": "# TLDR\n\nMechanical engineers and designers dedicate around 40% of their time to the labor-intensive process of converting 3D models into 2D fabrication drawings, crucial for manufacturers. Using [**DraftAid**](https://draftaid.io/), teams can automate this process with a single click and:\n\n* Save considerable time\n* Direct their focus toward more value-added tasks\n* Cut down on drawing errors, preventing expensive manufacturing mistakes\n\n# **The problem**\n\nModern design teams initiate their design by 3D modeling. To get their design manufactured, they need to make 2D drawings that look something like this:\n\n![uploaded image](/media/?type=post&id=78878&key=user_uploads/89898/590e3017-c1e8-4987-a30a-2c8469a2a8d6)\n\nMaking 2D drawings for what’s already been modeled in 3D takes up considerable time and energy. Design teams find themselves stuck investing 40% of their time in this manual task. This causes project delays while keeping talented designers busy doing repetitive tasks.\n\nLike any other repetitive manual task, making drawings can also be quite error-prone. Even with accurate designs, errors often sneak in and are only found when fixing them is an expensive endeavor.\n\n# **Enter DraftAid:**\n\nOur innovation streamlines the drafting process making it as effortless as a single click. Once engineers complete their 3D design, a single click swiftly produces a manufacturing-ready 2D drawing within seconds.\n\nThe resulting drawing is entirely editable, allowing engineers to make any necessary adjustments before sending it off for manufacturing.\n\nDraftAid allows teams to slash their current drawing time by up to 90% and eliminate common drawing errors. This not only enhances efficiency but also ensures consistency in drawings throughout the company, improving overall readability.\n\n![uploaded image](/media/?type=post&id=78878&key=user_uploads/290663/9f289b2c-ea8a-4f13-9a4e-f317ac9cd804)\n\n# **Meet the Power Trio:**\n\nWe are Mohammed, Abdullah, and Tahsin, a formidable team with a bond forged over three dynamic years of collaboration.\n\nBefore the inception of DraftAid, [**Mohammed Al-arnawoot**](https://www.linkedin.com/in/mohammed-al-arnawoot/)’s journey included roles as a software engineer and later as a VP of engineering (@ Emagin, acquired by Innovyze) and a Director (@ Dozr) in several start-ups. Navigating the challenging terrain from pre-seed to Series X.\n\n[**Abdullah Elqabbany**](https://linkedin.com/in/abdullah-elqabbany-8160551a8) is an electro-mechanical engineer who boasts a career marked by the creation of tens of thousands of drawings. Frustrated by the absence of a suitable drawing automation tool in his last role, he took matters into his own hands and built one from scratch.\n\n[**Tahsin Rahman**](https://linkedin.com/in/muhammed-tahsin-rahman) is a distinguished PhD graduate from the University of Toronto, who brings a wealth of experience in developing cutting-edge machine-learning solutions. In his previous role, he spearheaded an engineering team within the Canadian National Defence, crafting an AI-powered cybersecurity solution.\n\n# Our Ask:\n\n* Share our solution with any Construction or Automotive design companies you know.\n* Warm intros to design companies that spend a lot of time making drawings — email us at [mohammed@draftaid.io](mailto:mohammed@draftaid.io).\n* Follow us on [**Linkedin.**](https://www.linkedin.com/company/draftaid)",
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      {
        "user_id": 438232,
        "full_name": "Chinmay Bharti",
        "title": "Founder/CTO",
        "founder_bio": "Chinmay Bharti, Co-Founder and CTO, CodeAnt AI, architected the engine behind the 100+ CVEs CodeAnt AI disclosed. Previously worked in HFTs. IIT Bombay, Electrical Engineering. Now building offensive and defensive security in one self-learning system at CodeAnt AI.",
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        "linkedin_url": "https://linkedin.com/in/chinmay-bharti",
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    ],
    "jobs": [
      {
        "id": 77432,
        "title": "Account Executive (In-person in San Francisco)",
        "url": "https://www.ycombinator.com/companies/codeant-ai/jobs/ZdQvjSA-account-executive-in-person-in-san-francisco",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$145K - $250K",
        "equity_range": "0.25% - 0.75%",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 106835,
        "title": "Account Executive (In-person in San Francisco)",
        "url": "https://www.ycombinator.com/companies/codeant-ai/jobs/GF7lDUC-account-executive-in-person-in-san-francisco",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
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        "role_type": null,
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        "equity_range": "0.25%",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
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    ],
    "news": [
      {
        "title": "CodeAnt AI uncovered a critical authentication bypass using only public key that went undetected for 6 years, CVE-2026-29000.",
        "url": "https://cyberpress.org/pac4j-jwt-authentication/",
        "date": "Mar 05, 2026"
      },
      {
        "title": "Worried About AI-Generated Code? Ask AI To Review It",
        "url": "https://www.forbes.com/sites/davidprosser/2025/05/07/worried-about-ai-generated-code-ask-ai-to-review-it/",
        "date": "May 07, 2025"
      },
      {
        "title": "CodeAnt AI Raises USD 2 Mn in Seed Funding to Streamline Code Review with AI | Entrepreneur",
        "url": "https://www.entrepreneur.com/en-in/news-and-trends/codeant-ai-raises-usd-2-mn-in-seed-funding-to-streamline/491291",
        "date": "May 07, 2025"
      }
    ],
    "launches": [
      {
        "id": 101960,
        "title": "CodeAnt AI - Autonomous offensive and defensive security",
        "tagline": "Find the breach before the attacker does!",
        "body": "### What we do\n\nCodeAnt AI attacks your systems the way a real adversary would, then it walks back into your code and helps you build the defenses exactly where the attack got through.\n\nContinuous attack. Continuous defense. One self-learning platform.\n\n![uploaded image](/media/?type=post&id=101960&key=user_uploads/304615/2d6a6c48-8892-4d33-9e38-a08770079ab0)\n\n\\\n\\\n[**Trigger a free pentest**](https://app.codeant.ai/) No engagement fee. Pay only if we find high or critical issues; low and medium issues are free.\n\n### Why us\n\nWe've run pentests for 200+ companies. Almost everyone had exposed PII, PHI, payment records, patient files, or critical data leaks.\n\nWe've also disclosed 100+ zero-day CVEs, affecting 1.85B+ monthly downloads, including [pac4j-jwt auth bypass at CVSS 10.0 ](https://www.codeant.ai/security-research/pac4j-jwt-authentication-bypass-public-key)and [simple-git RCE at CVSS 9.8](https://www.codeant.ai/security-research/simple-git-remote-code-execution-cve-2026-28292).\n\n### Why now\n\n**90% of modern software is embarrassingly easy to breach.**\n\nAttackers got AI. A human pentester gets 2 weeks and a scope doc. An AI adversary gets unlimited patience and parallelism, and it'll chain a forgotten subdomain to a leaked credential to a misconfigured auth API until the data is out.\\\n\\\nYour defenses? Still fighting the last war.\n\nSAST &amp; SCA tools surface 10,000 findings. The 50 that matter are buried. Pentest firms show up once a year. File a PDF and leave. You fly blind the other 363 days.\n\n![uploaded image](/media/?type=post&id=101960&key=user_uploads/304615/1c942f59-a1c1-418f-827c-7517ec157597)\n\n### How do we close it\n\nCodeAnt lives at every layer where code is written: CLI, IDE, PR, CI/CD. Then it takes what it learned and attacks.\n\n### What you get\n\n* **Blackbox** 500+ exploit agents (BOLA, IDOR, SSRF, auth bypass, etc)\n* **Whitebox** AI SAST, SCA, SBOMs, malware, business logics, etc.\n* **Graybox** Black-box + white-box fused, the full kill chain.\n* **Evidence** SOC 2, HIPAA, ISO compliant reports\n\nStart your [free pentest](https://app.codeant.ai/) here or schedule a [scoping call](https://meet.codeant.ai/meet/codeant-ai/demo)\n\n---",
        "url": "https://www.ycombinator.com/launches/QWW-codeant-ai-autonomous-offensive-and-defensive-security",
        "votes": 137,
        "created_at": "2026-05-26T14:44:33.425Z"
      },
      {
        "id": 94457,
        "title": "CodeAnt AI - Engineering metrics that show real developer impact. Deeper insights than LinearB.",
        "tagline": "Get full visibility into what every developer builds, fixes, and improves.",
        "body": "## **🏆 TL;DR**\n\nMost developer productivity tools show **numbers**, not **impact**.\\\nThey count commits and PRs but don’t explain what was _actually built, fixed, or improved_.\n\n**CodeAnt AI’s [Developer 360](https://www.codeant.ai/developer-360)** **gives you that missing visibility**,\n\n![uploaded image](/media/?type=post&id=94457&key=user_uploads/304615/7facde8e-ac94-47ee-bfdb-a479a02585c4)\n\n\\\nWe’re already enterprises and fast-growing startups, such as **Commvault, Sanas, Akasa Air, and Kore AI** to improve developer productivity.\n\n![uploaded image](/media/?type=post&id=94457&key=user_uploads/304615/4d0e4ff4-d08a-4668-b2e8-793bd7c4c317)\n\n## **❌ The Problem**\n\nEngineering dashboards today are full of **empty stats.**\n\nCurrent tools show _50 commits_ and _20 pull requests_, but you have no idea if that’s 50 critical bug fixes or just 50 formatting changes.\n\nLeaders can’t tell the difference between busy work and meaningful progress,\\\nand developers end up feeling like numbers, not contributors.\n\n## **🌟 The Solution - Developer 360**\n\nDeveloper 360 shows the _real story_ behind your codebase.\\\n\\\nCodeAnt AI reviews every pull request, getting the deepest context of your code, from features shipped to bugs fixed or risks introduced. It looks at every commit, pull request, and pipeline run to show what your team is really doing.\n\nYou’ll see:\n\n* What features were shipped\n* What bugs and security issues were fixed\n* Where reviews or builds are slowing things down\n* Who’s driving steady, high-quality progress\n\nEverything rolls up into a single, easy-to-understand view of your engineering work.\n\n**AI Developer Summaries** reports that explain what was shipped, fixed, or improved\n\n![uploaded image](/media/?type=post&id=94457&key=user_uploads/304615/a3209b2d-cb3d-4e6c-a074-8d8188cac1e2)\n\n**Throughput Comparison** benchmark developers on consistency, efficiency, and merge quality\n\n![uploaded image](/media/?type=post&id=94457&key=user_uploads/304615/e76e624e-23e8-4c8f-aa67-e3c92bdd36de)\n\n## **🙏 Our Ask**\n\n**Developer 360 is live at** [https://app.codeant.ai](https://app.codeant.ai%5C)\\\n\\\nGet started with the 14-day free trial, no credit card needed.\n\nWant a quick demo? [**Book a call here**](https://meet.codeant.ai/meet/codeant-ai/demo)",
        "url": "https://www.ycombinator.com/launches/OZV-codeant-ai-engineering-metrics-that-show-real-developer-impact-deeper-insights-than-linearb",
        "votes": 18,
        "created_at": "2025-10-08T00:31:53.063Z"
      },
      {
        "id": 77911,
        "title": "CodeAnt AI: AI Code Reviewer",
        "tagline": "Helping engineering teams cut code review time and bugs by over 50%.",
        "body": "### **PROBLEM:**\n\nCode reviews are already painful — slow, repetitive, and easy to miss bugs & security vulnerabilities. With more AI-written code, it's getting worse: bigger PRs, faster cycles, less peer context.\n\n### **Solution:**\n\n![uploaded image](/media/?type=post&id=77911&key=user_uploads/304615/f41a52cf-20a5-4a3d-8b03-94b77e822984)\n\n1. [CodeAnt AI](https://www.codeant.ai/) connects directly to [GitHub, GitLab, Bitbucket, Azure DevOps](https://app.codeant.ai/) in 2 clicks\n2. Builds deep Abstract Syntax Trees (ASTs) of your entire codebase\n3. Automatically reviews every PR for:\n   * Code quality issues\n   * Security vulnerabilities (SAST, IaC, Secrets, SCA, EOL libs, Cloud misconfigs)\n   * Best practice violations\n4. Flags exact lines and suggests one-click fixes in Pull Request\n5. Add custom rules and design best practices\n6. Integrates with [VS Code](https://marketplace.visualstudio.com/items?itemName=codeantai.codeantai) and [JetBrains IDE](https://plugins.jetbrains.com/plugin/23405-codeantai)\n7. Works fully inside your pull requests\n\nResult? [**Teams cut code review time and bugs by over 50%.**](https://www.codeant.ai/customer-story) _(Attached case studies)_\n\n![uploaded image](/media/?type=post&id=77911&key=user_uploads/304615/cf12efdd-ad6c-4c96-866a-07732fdc2021)\n\nTrack every code change in your repositories for security and quality issues — mapped to each developer — so you can stack-rank engineers, spot gaps, and drive targeted upskilling.\n\n### 💥 **About Us:**\n\nHello everyone, we are [Amartya](https://linkedin.com/in/amartya-jha) and [Chinmay](https://linkedin.com/in/chinmay-bharti).\n\n![uploaded image](/media/?type=post&id=77911&key=user_uploads/304615/197c0c2a-1764-4de7-b97b-120c80d3c9e6)\n\n[Amartya Jha](https://www.linkedin.com/in/amartya-jha/) scaled the platform & infrastructure at Zeta and ShareChat to handle millions of requests a day. Tired of bugs slipping through manual reviews, he quit to fix it at the root.\n\n[Chinmay Bharti](https://www.linkedin.com/in/chinmay-bharti/) is an IIT Bombay engineer with a master’s in AI and a second-time founder. He built systems at a high-frequency trading firm where even one bug could cost millions.\n\n![uploaded image](/media/?type=post&id=77911&key=user_uploads/304615/8fbcc8ff-703d-4946-8fae-1ca933276a4f)\n\n### **❇️ Ask:**\n\n1. Start a [**14-day Free trial**](https://app.codeant.ai/)**,** no credit card required\n2. Need a demo? [Schedule a call](https://calendly.com/codeant-ai/30min) with the founders",
        "url": "https://www.ycombinator.com/launches/KGd-codeant-ai-ai-code-reviewer",
        "votes": 54,
        "created_at": "2024-01-29T15:25:43.255Z"
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    "id": 29373,
    "name": "Bilanc",
    "slug": "bilanc",
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    "website": "https://www.bilanc.co",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Bilanc helps engineering leaders build more productive, happier teams. We use AI to analyse every line of code that is written, and our platform delivers insights that help to improve developer experience, and increase developer productivity.",
    "one_liner": "AI-Powered Engineering Productivity",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1701093428,
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      "America / Canada"
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/bilanc",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/bilanc.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/bilanc",
    "x_url": "https://twitter.com/bilanc_app",
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    "app_video_url": null,
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    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
    },
    "founders": [
      {
        "user_id": 1530368,
        "full_name": "Samuel Akinwunmi",
        "title": "Founder/CEO",
        "founder_bio": "Founder of Bilanc (YC W24)",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/0x-s13i",
        "x_url": "https://twitter.com/SamAkinwunmi",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/83b7bca1444b89b3c74bb60ce4c0195d66e45799.jpg"
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    "launches": [
      {
        "id": 86712,
        "title": "Bilanc - AI Engineering Management Platform",
        "tagline": "AI to help engineering managers increase productivity",
        "body": "Hey everyone, I’m [Sam](https://www.linkedin.com/in/0x-s13i/) - Founder of Bilanc 👋\n\n# TL;DR\n\n[Bilanc](https://www.bilanc.co) integrates with your codebase and project management tools to measure and improve developer productivity. We leverage AI to help engineering leaders summarise PRs and write release notes, refine tickets with code context, and highlight performance outliers.\n\nOur AI also drafts performance reviews for your engineers in a few seconds. Watch our [demo](https://youtu.be/r9KTXY2scmA).\n\n![uploaded image](/media/?type=post&id=86712&key=user_uploads/1530368/1ae9fe1e-ebdd-417a-8237-29478d9f8435)\n\n# The Problem\n\nEven the best engineering leaders struggle to provide useful feedback to their engineers as their teams grow. Everything is hidden in git commits, ticket comments and design docs. Writing performance reviews is an arduous process that takes weeks, and most reviews can be described as lacklustre at best.\n\nUltimately, most developers are dissatisfied with the support they get from their leaders.\n\n# Our Solution: One AI platform for Engineering Management\n\nOur foundation is a powerful engineering intelligence platform that creates a knowledge graph of your codebase, on top of which we then leverage AI to uncover insights.\n\n![uploaded image](/media/?type=post&id=86712&key=user_uploads/1530368/cc08339f-57fa-4157-89d3-9b35d8811a81)\n\n* **Engineering Analytics:** Our dashboard shows velocity, quality, and security metrics, and you can even design your own custom metrics through the API.\n* **Issue Refinement:** Our AI automatically links relevant tickets, respective code changes, and highlights team members that have worked on similar tasks.\n* **Pull Request Summaries & Release Notes:** We automatically summarise every PR and Release. We also share team activity summaries directly to Slack or email.\n* **Performance Review Drafts:** We draft performance reviews, using codebase, productivity, and team collaboration context.\n\n![uploaded image](/media/?type=post&id=86712&key=user_uploads/1530368/a7c6eba5-4358-483e-82bf-881b47f7fc94)\n\n# Our Ask\n\n* [Book a demo](https://calendly.com/d/3py-rwt-k8f/bilanc-team?month=2025-01) with our team\n* Share this post with everyone (If you know a CTO, VP of Engineering, or Engineering Manager, even better!)\n* Learn more at [bilanc.co](http://bilanc.co)",
        "url": "https://www.ycombinator.com/launches/MYa-bilanc-ai-engineering-management-platform",
        "votes": 142,
        "created_at": "2025-01-09T12:32:53.118Z"
      }
    ]
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  {
    "id": 29375,
    "name": "Preloop",
    "slug": "preloop",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/62ebbbabf82f9c9badd0bbcb60f8749d391d5a78.png",
    "website": "https://www.preloop.com",
    "all_locations": "Seattle, WA, USA",
    "long_description": "Only 2 out of 10 ML models make it from experiment to production. Preloop helps automate the process of deployment, helping companies realize more value from their machine learning teams, while focusing teams' attention on science instead of engineering.",
    "one_liner": "Translate your experimental scripts into production ML services",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1702654646,
    "tags": [
      "Deep Learning",
      "Developer Tools",
      "Machine Learning",
      "Data Science",
      "AI"
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    "status": "Inactive",
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      "United States of America",
      "America / Canada"
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/preloop",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/preloop.json",
    "year_founded": 2023,
    "city": "Seattle",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/preloop/",
    "x_url": "https://twitter.com/preloop",
    "fb_url": "https://facebook.com/preloop",
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    "primary_partner": {
      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
    },
    "founders": [
      {
        "user_id": 1310033,
        "full_name": "Tejas Hosangadi",
        "title": "Founder/CEO",
        "founder_bio": "Tejas is the co-founder and CEO of Preloop, a product that automatically translates ML experimental scripts into production services. Before Preloop, he worked at Amazon where he scaled a data science team from 0-1, delivering 4 projects in the first year and leading the expansion of the team. He also worked as a senior MLE at EvolutionIQ, where he made significant improvements to a predictive model in his first month, helping them land a long term contract with Prudential.",
        "is_active": false,
        "linkedin_url": "https://linkedin.com/in/tejashosangadi",
        "x_url": "https://www.twitter.com/tejastmh",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/02c87a1b7a20ffb5d7fdff8f05417310d0a049b5.jpg"
      },
      {
        "user_id": 1660688,
        "full_name": "Nikith Hosangadi",
        "title": "Founder",
        "founder_bio": "Technical founder experienced in working with distributed systems and machine learning. Before Preloop, he worked as a software engineer at AWS, writing code in C and Java for the VPC team.",
        "is_active": false,
        "linkedin_url": "https://linkedin.com/in/nikithhosangadi",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9d2b3aed1c122e5c4788fc71373bfc4dd8e5ad4d.jpg"
      }
    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 78894,
        "title": "➿ Preloop - Deploy your ML models in hours instead of weeks",
        "tagline": "Preloop automatically translates your experimental scripts into production ML workflows",
        "body": "**Tl;dr:** [Preloop](https://www.preloop.com/) automatically translates your ML training scripts into production services, handling the creation of the training pipeline and REST endpoints. This means that science teams can focus on developing new models while cutting deployment times from weeks to just a few hours (or less). We’re building Vercel for model deployments.\n\n—\n\nHey everyone, we’re [Tejas](https://linkedin.com/in/tejashosangadi) and [Nikith](https://linkedin.com/in/nikithhosangadi) and we’re building Preloop. Tejas previously worked as a data scientist and software engineer at several companies, including Amazon and most recently EvolutionIQ, often leading 0-1 projects on newly established teams. Nikith has experience as a software engineer building multi-tenant distributed systems, most recently working at AWS on the networking team.\n\n![uploaded image](/media/?type=post&id=78894&key=user_uploads/1310033/6f2948a3-73ad-43eb-829c-0b23006cd26b)\n\nOur goal is to unshackle scientists from the repetitive tasks that accompany their model deployments and empower science teams to move faster. \n\n## **😫 The problem**\n\nData scientists hate the work associated with deploying their models. Science teams spend anywhere from a couple of weeks to over two months deploying their models. Assuming that a team deploys 10 models a year and each model takes 2 weeks on average to deploy, this is 20 weeks of science time spent just on deployments. \n\nThe biggest bottlenecks to quick deployment are a lack of easy-to-use tools and delays caused by handing off deployments to a separate team.\n\n## **🪄 Our solution**\n\nPreloop automates the tedious and repetitive tasks associated with deploying and using your ML models, including creating the training pipeline and inference endpoints, autoscaling based on demand and retraining. We provide an easy-to-use CLI in addition to a dashboard to monitor and track your models. It works with major ML packages like xgboost, torch, and scikit-learn, with broader support on the roadmap.\n\n![uploaded image](/media/?type=post&id=78894&key=user_uploads/1310033/3a401fe4-e051-45c2-a3b9-98bd8b492abd)\n\n## **🔍 How it works**\n\nWe scan through your existing script, identifying key information about the data, transformations, and the model being trained. This is used to construct both the training and data pipelines, as well as the inference endpoints that serve your model. \n\n![uploaded image](/media/?type=post&id=78894&key=user_uploads/1310033/976dd0ad-2492-43a4-a674-eb3618536144)\n\nWe also handle auto-scaling, observability, and versioning, so that you can train and deploy, but just as easily roll back unintended model changes. We have support for on-prem deployments for teams that have stronger security requirements.\n\n## **🤔 Why are we building this?**\n\nAs a data scientist, Tejas noticed that scientists (including himself) loved experimenting and building models but hated deploying them. More importantly, he witnessed that it often took multiple weeks before they were in production. There was a lack of a more automated solution to handle the deployment process, and even tools like Sagemaker require tons of boilerplate to work.\n\nWe want to make it easier to deploy models, so that teams can move quicker, and scientists can focus more on science. \n\n## **🙏 Our ask**\n\n* Intros to data science and ML managers at mid to large-size startups as well as large enterprises. \n* If your science team struggles with lengthy deployment times, please reach out to us by emailing [founders@preloop.com](mailto:founders@preloop.com), or by booking a meeting [here](https://outlook.office.com/bookwithme/user/27ea63c6cc9c4d398ba6525a9c0e6b25@preloop.com/meetingtype/ZKpbyV0QyU2cya_WNaNuJw2?anonymous&ep=mlink).",
        "url": "https://www.ycombinator.com/launches/KWU-preloop-deploy-your-ml-models-in-hours-instead-of-weeks",
        "votes": 209,
        "created_at": "2024-02-29T16:10:32.259Z"
      }
    ]
  },
  {
    "id": 29401,
    "name": "Raindrop",
    "slug": "raindrop",
    "former_names": [
      "Sidekick [NOTE",
      "this is a duplicate app per request of Diana Hu. old id: zkoticha]",
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        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
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        "experience": "3+ years",
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        "id": 97728,
        "title": "Forward Deployed Engineer (FDE)",
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        "location": "San Francisco, CA, US",
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        "role": "Engineering",
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        "type": "Full-time",
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    "news": [
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        "title": "Building the Safety Layer for AI Agents",
        "url": "https://www.youtube.com/watch?v=5XO7ZEOGpJc",
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      {
        "title": "Raindrop raises $35M to monitor agents",
        "url": "https://www.axios.com/pro/enterprise-software-deals/2026/09/16/raindrop-crv-lightspeed-datadog",
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        "title": "Want to Know Why Your AI Agent Failed? There’s AI for That.",
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        "date": "Dec 01, 2025"
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      {
        "id": 91457,
        "title": "Raindrop Deep Search",
        "tagline": "Deep Research for your Production AI Data",
        "body": "https://www.youtube.com/watch?v=pN82WxN-_G0\n\nToday, we're excited to launch Raindrop Deep Search\n\nIt’s like Deep Research for your Production AI Data\n\nSearch for anything, and Raindrop automatically trains little models to accurately classify any topic or issue, across millions of events.\n\n𝗧𝗵𝗲 𝗣𝗿𝗼𝗯𝗹𝗲𝗺\n\nWe’ve heard from thousands of AI engineers and they’re struggling to track issues with their agents.\n\nImagine a user reports a problem: your agent is saying it can’t search the web for documentation. You need to know if this is a one-off problem or a much bigger issue… but how? Keyword search, or even semantic search, doesn’t tell the full story.\n\n𝗖𝗮𝗻’𝘁 𝘄𝗲 𝗷𝘂𝘀𝘁 𝘂𝘀𝗲 𝗧𝗿𝗮𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝗘𝘃𝗮𝗹𝘀?\n\nOffline evals work well as unit tests. But since they’re running on preset data, you have no visibility into what’s actually happening in production.\n\nOnline evals just run these unit tests on a tiny sample of production data, leaving you blind to how widespread problems are.\n\n𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗶𝗻𝗴 𝗥𝗮𝗶𝗻𝗱𝗿𝗼𝗽 𝗗𝗲𝗲𝗽 𝗦𝗲𝗮𝗿𝗰𝗵\n\nThat’s why we built Deep Search. It’s like Deep Research for your production data.\n\nHow Deep Search works:\n\n1\\. Describe the issue (eg. agent failing to search the web)\n\n2\\. Deep Search finds examples out of millions of events\n\n3\\. Refine search with feedback\n\n4\\. Start tracking the issue\n\nDeep Search runs across all of your production data to give you an accurate metric of issue frequency.\n\nTraditional classification systems require humans to manually label thousands of data points. So to achieve this, Raindrop Deep Search introduces a new research breakthrough, bespoke few-shot classifiers, which only need a few examples.\n\nIt’s essentially bootstrapping weaker systems from stronger systems, ultimately training custom small models that analyze millions of events a day. You can think of it like creating materialized views for natural language.\n\nOnce you start tracking the issue you can use Raindrop to dive into traces and tool calls to find the root cause. And you can quickly confirm whether your fixes are effective by monitoring issue frequency and receiving real-time Slack alerts.\n\nYou can try out Deep Search at [raindrop.ai](http://raindrop.ai). \n\nWe’re excited to hear what you think!\n\n![uploaded image](/media/?type=post&id=91457&key=user_uploads/309605/b1eda0eb-8816-487f-a4f3-36bdaf02bb0b)\n\n",
        "url": "https://www.ycombinator.com/launches/Nn7-raindrop-deep-search",
        "votes": 10,
        "created_at": "2025-06-19T21:08:03.825Z"
      },
      {
        "id": 89925,
        "title": "Raindrop - Sentry for AI Products",
        "tagline": " AI engineers use Raindrop to get alerts about hidden issues and wins in their AI products.",
        "body": "[https://youtu.be/IS7akU_3AnI](https://youtu.be/IS7akU_3AnI?feature=shared)\n\nAl products fail constantly—in ways both hilarious and terrifying.\n\nMeet **Raindrop**: the first Sentry-like monitoring platform for Al products.\n\n**The Problem**\n\nRegular software throws exceptions. But Al products fail silently.\n\nThese issues can be serious:\n\n* [Figma had to roll back their AI design product when it copied Apple’s designs, and they haven’t relaunched since](https://techcrunch.com/2024/07/02/figma-disables-its-ai-design-feature-that-appeared-to-be-ripping-off-apples-weather-app/?guccounter=1&guce_referrer=aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS8&guce_referrer_sig=AQAAAM5aRTBjXhPXfaoMBpoQxL9si-7R3qfaTR4r-n_mdzKu31uB6rUYGjE31z0H4aHVY1LlchyZ7r76Pufga45IMGKwFz0IxZ7eo-g2z1sYsta94AVsSj5CYjf6NKRd3m43VgSGLrG_IfdqMKtlFDuBvimRfLyF_aqb19vPgl-8B7eD)\n* [Air Canada got sued — and lost — when their chatbot incorrectly offered a customer a refund](https://www.forbes.com/sites/marisagarcia/2024/02/19/what-air-canada-lost-in-remarkable-lying-ai-chatbot-case/)\n* [Virgin Money came under fire when their chatbot scolded customers for using the company name, ‘Virgin’](https://www.latintimes.com/virgin-money-forced-apologize-after-chatbot-threatens-cut-off-bank-customers-who-use-word-573885#:\\~:text=Fintech%20commentator%20David%20Birch%20shared,reported%20by%20the%20Financial%20Times)\n\nDon’t make the same mistake.\n\nThe current status quo is sifting through millions of logs and trying debug flaky evals. Evals are straightforward - like unit tests, they confirm your model got specific test cases right. But in the real world AI chatbots and agents encounter millions of unpredictable actions. AI companies need powerful monitoring to discover production issues so they can create reliable AI products that don’t just pass tests, but genuinely resonate with users.\n\n**Solution**\n\nRaindrop sends you alerts when your AI misbehaves and links straight to the events, so you can dig into the conversations or traces, understand the root cause, and fix it, fast.\n\nDaily Alerts Include\n\n* **Issues**: detects issues like Assistant Forgetting, Laziness, Task Failure, User Frustration, and more depending on the type of app\n* **Wins**: surfaces what your product does well, so you can double down on those experiences and create evals\n\nThe Pro tier lets you go even further with:\n\n* **Custom Issues / Topics**: define and track any issue or topic\n* **Topic Clustering**: clusters data in real time to find your AI product’s most popular use cases, and what use cases have the most issues\n* **Signals**: finds patterns in explicit signals like thumbs up / thumbs down\n* **Deep Research:** deep research for your production data, letting you use natural language to search for any kind of behavior\n* **Traces**: track every step of your AI call\n* **Edge PII Redaction**: intelligently strip PII from any user and model messages\n* **Dataset Creation**: create custom datasets out of any set of events\n\nCompanies like [Clay.com](http://Clay.com), Tolans, Websim, and more have been using Raindrop to improve their AI products. They’ve been able to quickly iterate on fixes, see how issue incidence rates decrease in production, and confidently ship changes.\n\n“Raindrop has been invaluable as we've been growing quickly. It's critical for us to keep issue incidence below an acceptable threshold and become aware of any spikes. **It's like if we see an iOS crash report in Sentry, but for our AI capabilities.”** -Evan Goldschmidt, CTO Tolans\n\nLearn more about how Tolan uses Dawn [here](https://www.raindrop.ai/case-studies/tolans), and check out case studies with [New Computer](https://www.raindrop.ai/case-studies/new-computer) and [Unstuck AI](https://www.raindrop.ai/case-studies/unstuck).\n\nYou can get started [here](https://www.raindrop.ai), excited to hear what you think :)\n\n![uploaded image](/media/?type=post&id=89925&key=user_uploads/309605/d77c5ea9-2b73-4455-96a6-db02c319651c)\n\n",
        "url": "https://www.ycombinator.com/launches/NOP-raindrop-sentry-for-ai-products",
        "votes": 11,
        "created_at": "2025-04-28T20:25:57.382Z"
      },
      {
        "id": 79667,
        "title": "Dawn - Analytics for AI products",
        "tagline": "We transform user requests and model outputs into metrics you actually care about.",
        "body": "Hey everyone!\\\n\\\nI’m [Zubin](https://twitter.com/snarkyzk), from dawn. Excited to share what we’ve (me, [Ben](https://twitter.com/benhylak), & [Alexis](https://twitter.com/alexisgauba)) been building.\n\n[Dawn](https://www.dawnai.com/) is analytics for AI products. We transform user inputs and model outputs into metrics you care about, letting you make meaning out of billions of tokens.\n\n**AI Companies love us for**\n\n* User Segmentation: automatically group users by behavior\n* Understanding Churn: see how requests (or responses) cause users to churn\n* Categorizing Search Requests: tag user requests + use categories in-app\n* Content Moderation: identify + remove harmful content\n* Flagging Bad Responses: track user requests that are vague, don’t match the source language, or anything else\n* Track any use case: discover categories from unstructured data\n\n_(It's not just for Al companies. Dawn can categorize just about anything! — _[_contact us_](https://wv6y9hc66q4.typeform.com/to/qHmrVeA3)_ to chat)_\n\n**How it Works**\n\n1. **3 lines to integrate:** with one line of code, you can start sending user data from your app to dawn (and even get back categorizations!)\n2. **Define categories:** Dawn automatically discovers categories from your raw data. You can also define your own. You can delete, edit, reorganize, and create new categories at any time.\n3. **Self-improving, on the fly:** Dawn constantly gets better at understanding your data. 
A simple feedback interface gives your team visibility and control over categorization.\n4. **Connects to your existing analytics:** we have plugins for Snowflake, Mixpanel, Slack, Amplitude, and more -- so you can track whatever you want, wherever you want.\n\n\\*\\*What early users say about us:\\*\\*\\\n“I’m feeling a total a-ha moment with this. Truly cool to see.” - Gabriel Birnbaum, Can of Soup\\\n\\\n**Let’s work together**\\\nReach out at [zk@dawnai.com](mailto:zk@dawnai.com), or sign up for a demo [here](https://wv6y9hc66q4.typeform.com/to/qHmrVeA3). We’d love to hear from you!\n\n![uploaded image](/media/?type=post&id=79667&key=user_uploads/1668573/86bc4a34-fc8f-469a-9d07-de695eb11bc3)\n\n",
        "url": "https://www.ycombinator.com/launches/Kix-dawn-analytics-for-ai-products",
        "votes": 21,
        "created_at": "2024-03-25T15:28:55.097Z"
      }
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    "one_liner": "Real-time and two-way sync between CRMs and Databases",
    "team_size": 34,
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    "year_founded": 2022,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/stacksyncdata/",
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        "full_name": "Ruben Burdin",
        "title": "Founder/CEO",
        "founder_bio": "Data movement, CRM and ERP. Currently redefining Enterprise systems integration.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/ruben-burdin",
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        "title": "Full-Cycle Forward Deployed Sales Engineer - The Closer of All Closers!",
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        "id": 110498,
        "title": "Forward Deployed Engineer + Product engineer",
        "url": "https://www.ycombinator.com/companies/stacksync/jobs/2I6rI5E-forward-deployed-engineer-product-engineer",
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        "role_type": "Full stack",
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        "title": "Stacksync on the rise",
        "url": "https://www.startupticker.ch/en/news/stacksync-on-the-rise?utm_source=newsletter586&utm_medium=email&utm_campaign=newsletter586",
        "date": "Jan 26, 2024"
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      {
        "title": "CES 2024: Swiss delegation braces for Las Vegas",
        "url": "https://www.startupticker.ch/en/news/ces-2024-swiss-delegation-braces-for-las-vegas",
        "date": "Jan 05, 2024"
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        "id": 77196,
        "title": "Stacksync: Real-time and two-way sync between CRMs and Databases",
        "tagline": "READ and WRITE your CRM data with SQL queries!",
        "body": "Hey everyone! We’re [**Ruben**](https://bookface.ycombinator.com/user/1327024) and [**Alexis**](https://bookface.ycombinator.com/user/1685532) from [**Stacksync**](https://www.stacksync.cloud/), here to help you forget about complex CRM APIs. 👋\n\n\\*\\*TL;DR \\*\\* [**Stacksync**](https://www.stacksync.cloud/) powers real-time and two-way sync between CRMs and databases. With two-way sync, we turn your database into a **READ AND WRITE** interface to your CRM data. From your database, _make SQL queries to update data at any scale_ and your CRM will reflect these changes instantly. And vice-versa, when you update data in your CRM, your database is immediately updated.\n\nTry it yourself and [**get started here!**](https://www.stacksync.cloud/)\n\n![uploaded image](/media/?type=post&id=77196&key=user_uploads/1327024/63cc74de-7bec-4caa-8d25-a1a6f6d902d8)\n\n**💥 Problem**\n\nDevelopers hate using CRM APIs. Their documentation is hard to navigate, with multiple edge cases and data inconsistencies have severe business consequences. This makes CRM integration complex, time consuming and costly. Worse, business teams working daily in CRMs are left with outdated or no data at all, while the data insights they need are just available in the database: it simply requires too much investment in development and maintenance.\n\n**✅ Solution**\n\nWith two-way sync, we turn your database into a read+write interface to your CRM. So instead of reading and writing data from an API, just do it with SQL queries in the database that you already know and love. Whenever data is updated in your database, it instantly syncs to your CRM and vice-versa.\n\nStacksync is different because it is the first tool that delivers consistent data you can trust in real-time. Stacksync just works. The setup is done in less than 5 minutes, without a single line of code.\n\n[Watch demo here: https://www.youtube.com/watch?v=XrigWqlSQnQ](https://www.youtube.com/watch?v=XrigWqlSQnQ)\n\n**🪄 How it works**\n\nNo-code makes it easy. Start by [**creating your account**](https://www.stacksync.cloud/) for free, then\n\n1. Connect your Apps\n\n   ![uploaded image](/media/?type=post&id=77196&key=user_uploads/1327024/ce17348d-2078-4dea-9170-0a1320b6665c)\n\n2. Choose which tables your want to sync\n\n   ![uploaded image](/media/?type=post&id=77196&key=user_uploads/1327024/4532ea18-a1da-44cc-8855-9bd694d36f3c)\n\n3. Map your fields\n\n   ![uploaded image](/media/?type=post&id=77196&key=user_uploads/1327024/f1778ed4-16ad-46cd-865a-a9a5939efee3)\n\n\nThat’s it! 🎉\n\n**💰 Pricing**\n\nSimple CRM integrations start at 200$/month, and you can upgrade on a pay-as-you-go for large data volumes.\n\nYC Companies get a [**Deal (80% discount for a year, worth 120k free credits)**](https://bookface.ycombinator.com/deals/2173)!\n\n**💜 Our Ask**\n\nTry it yourself and [**get started here**](https://www.stacksync.cloud/)\n\n* Schedule a call if you’re interested: [cal.com/rubenburdin](https://cal.com/rubenburdin/30min)\n* Share with anyone that you think could benefit from simpler CRM integration (warm intros are welcome!) 😉\n* We would appreciate any candid feedback!\n* Need a feature or connector? Let us build it for you here and now!\n\nIf you have any questions, feel free to reach out to my personal email [ruben@stacksync.cloud](https://ruben@stacksync.cloud)\n\n![uploaded image](/media/?type=post&id=77196&key=user_uploads/1327024/29d754ee-4784-43a2-b5be-0037e98cbf97)\n\n",
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        "votes": 45,
        "created_at": "2024-01-03T11:13:29.045Z"
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        "full_name": "Illiana Reed",
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        "founder_bio": "CEO @ camelAI - building unlimited DeepSeek Flash at $5/stream/month",
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        "id": 94363,
        "title": "CamelAI API: Ship \"Chat With Your Data\" in 5 Minutes",
        "tagline": "Give your users an AI-powered data analytics chat without building it yourself. We handle the complex stuff so you ship faster.",
        "body": "**The Problem**\n\nYour users want to chat with their data. Building this yourself means:\n\n* 3+ months of engineering time\n* Wrestling with SQL generation, context windows, and hallucinations\n* Maintaining AI infrastructure that isn't your core product\n* Constant updates as models evolve\n\nMeanwhile, your competitors are shipping AI features today.\n\n**Our Solution: CamelAI API**\n\nConnect your database. Embed our iframe. Ship in 5 minutes.\n\n```\nresponse = requests.post( 'https://api.camelai.com/api/v1/iframe/create', headers={'Authorization': 'Bearer token', 'Content-Type': 'application/json'})\n```\n\n_Your users get:_\n\n* Natural language to SQL that actually works\n* Interactive Plotly visualizations\n* Context that learns their business terminology\n* Easy-to-make dashboards\n\n![uploaded image](/media/?type=post&id=94363&key=user_uploads/1925222/4ab6ceae-6239-4deb-b592-7cc8beda11ff)\n\n![uploaded image](/media/?type=post&id=94363&key=user_uploads/1925222/cc044d1a-3a97-42d4-9bfe-299dbfe4b17b)\n\n_You get:_\n\n* Zero maintenance AI infrastructure\n* A beautiful chat embed\n* Full customization to match your brand\n* Works with Postgres, MySQL, Snowflake, BigQuery, ClickHouse, and more\n* Built in row-level security for multi-tenant architecture\n\n![uploaded image](/media/?type=post&id=94363&key=user_uploads/1925222/3255be73-e070-41be-b598-9283a3623374)\n\nWe process over 40,000 queries every month. On average, integrating camelAI’s embeddable API takes just 5 minutes. Since our Product Hunt launch in July 2025, camelAI is already live in production with 2 Fortune 500 companies and dozens of startups.\n\n**Who's Using This**\n\n* Vertical SaaS platforms tired of building custom dashboards for every customer\n* Data companies that need to offer self-serve analytics, but don’t want to invest a team of engineers\n* Enterprise teams replacing ticket queues with instant insights\n\n_Example:_ A transaction cleansing platform embedded CamelAI so their banking clients could explore their own data without filing support tickets. Integration took one afternoon.\n\n**Pricing**\n\nPro: $200/month + usage (includes $10 credits)\n\nEnterprise: Custom pricing, VPC deployment, dedicated support\n\n**Start Now**\n\nNo sales calls. No demos required. Try free today.\n\n1. Visit [camelai.com/api](https://camelai.com/api)\n2. Grab your API key\n3. Ship your AI feature today\n\nQuestions? Shoot us an email at: [founders@camelai.com](mailto:founders@camelai.com)",
        "url": "https://www.ycombinator.com/launches/OXz-camelai-api-ship-chat-with-your-data-in-5-minutes",
        "votes": 7,
        "created_at": "2025-10-07T14:05:09.594Z"
      },
      {
        "id": 76776,
        "title": "camelAI — The First Deep Research Agent for Your Structured Data",
        "tagline": "Ask questions, get insights from your data.",
        "body": "Hi YC! We're [Illiana](https://www.linkedin.com/in/illiana-reed/), [Miguel](https://www.linkedin.com/in/miguel-salinas-b2781426/), and [Isabella](https://www.linkedin.com/in/isabellareed/), the team behind camelAI.\n\n# What We're Building\n\ncamelAI is the last BI tool you'll ever need. What AI has done for coding, camelAI is doing for analytics. We connect an LLM directly to your database, turning natural language questions into in depth reports complete with beautiful visualizations in seconds. No modeling, no drag-and-drop limitations, no tickets to the data team.\n\n<https://youtu.be/bBqdaNN-NpM>\n\n# The Problem: Text-to-SQL Has Failed\n\nLet's be honest: Text-to-SQL has been around for years. It's been done to death and it still leaves users frustrated. Instead of giving clear answers, Text-to-SQL makes users fight for insights:\n\n* Setup takes forever\n* Queries only work well for narrow, predictable questions\n* Results come as raw data tables, not analysis\n* Business users struggle to get actionable insights\n\nBusiness users don't want raw tables of data—they need clear insights. But text-to-SQL forces them to piece together answers manually, leaving them frustrated and no closer to a decision.\n\nThe real problem: Getting valuable insights out of your own data is still too hard and too time consuming.\n\nFor executives, founders, and product managers, this means:\n\n* Waiting days for simple data requests\n* Making decisions without complete information\n* Spending hours building and maintaining dashboards\n* Wasting precious engineering time for a \"quick data pull\"\n\nFor technical teams, it means:\n\n* Constant context-switching to answer basic data questions\n* Building one-off dashboards that are rarely used\n* Explaining the same metrics repeatedly\n\n## Our Solution: camelAI\n\nAsk camelAI anything - from basic KPIs to complex business metrics your team hasn't even thought to track:\n\n**Deep Research Agent:** Watch as our Agent writes SQL queries in real time, explores your data, and generates interactive visualizations that deliver immediate insights. Complete transparency at every step.\n\n**Learns Your Company:** camelAI learns your company's language through use. It remembers past queries and improves through your feedback, creating consistent company-specific analysis.\n\n**Instant Visualizations:** camelAI doesn't just dump query results; it automatically creates interactive Plotly visualizations with written analysis of what the data actually means.\n\n**One-Click Dashboards:** Any visualization can be saved to a dashboard that refreshes automatically. Create comprehensive dashboards in minutes, not hours.\n\n**Enterprise-Ready:** We support on-prem and VPC deployments across multiple databases.\n\n# The New Reality\n\nWithout camelAI:\n\n1. Adding tickets to sprints for basic data questions\n2. Waiting days for simple insights\n3. Engineers constantly pulled away from building products\n\nWith camelAI:\n\n1. Business teams get answers immediately\n2. Engineers focus on building products\n3. Founders make better decisions faster\n\n## Who Needs This Yesterday\n\n* **Founders** who can't afford to wait for data\n* **Product Teams** tracking metrics without a dedicated analyst\n* **CTOs** tired of being the bottleneck for data requests\n* **Junior Analysts** who want to focus on insights, not queries\n\n# Setup Takes 60 Seconds\n\n1. Connect your data source — pick from 10+ connections or upload a CSV\n2. Ask your first question\n3. Start making better decisions\n\n# 🐪 How We Got Here\n\n![uploaded image](/media/?type=post&id=76776&key=user_uploads/1925221/b319f130-c38f-4080-8e5c-8edf8d77e91d)\n\nWe've been shipping products together for three years. We're not data analysts, and that was the problem.\n\nOur organized data was right there, but we couldn't get to it without SQL expertise or wrestling with clunky BI tools that never quite answered our actual questions. So we built the tool we needed.\n\nOur insight was simple: stop writing SQL queries by hand. Let AI do what it's good at. Let humans ask natural questions and get answers they can use right away.\n\n## Try camelAI Today\n\nOur free tier gives you 10 messages per week: <https://camelai.com/>\n\nQuestions? We read every email: [illiana@camelai.com](mailto:illiana@camelai.com)\n\nLooking for: Teams tired of SQL bottlenecks who want to transform how they use data.",
        "url": "https://www.ycombinator.com/launches/JyK-camelai-the-first-deep-research-agent-for-your-structured-data",
        "votes": 92,
        "created_at": "2025-04-21T20:16:07.000Z"
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        "full_name": "Pierre Dorge",
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        "title": "Onedoc — Making it easy for developers to generate beautiful PDFs",
        "tagline": "Stop spending hours making ugly documents, and start creating a dynamic experience now!",
        "body": "**_tl;dr_** Onedoc makes it easy for developers to generate beautiful PDFs. It is a comprehensive solution with:\n\n1. An [open-source library](https://github.com/OnedocLabs/react-print) to design your documents\n2. A simple [API](https://docs.onedoclabs.com/introduction) to generate your documents\n3. A [cloud platform](https://app.onedoclabs.com/login) to host and track your documents\n\n![uploaded image](/media/?type=post&id=78258&key=user_uploads/959469/55ac7687-e4a4-4456-97a2-ff6348953e3b)\n\n> Using Onedoc to quickly generate dynamic PDFs\n\n👋 Hi! We are [Auguste](https://www.linkedin.com/in/augustelefevre/), [Pierre,](https://linkedin.com/in/pierre-dorge-3372bb16a) and [Titouan](https://www.linkedin.com/in/titouan-launay/?locale=en_US) and we’re building [Onedoc](https://www.onedoclabs.com/).\n\n## Why do documents feel so outdated?\n\nBillions of PDFs are generated daily: invoices, contracts, receipts, tickets,… yet there are no toolkits to allow companies to easily build them. Developers need to get their hands dirty to produce basic documents - let alone beautiful ones. This makes PDFs hard to dynamize and maintain, leading to poor brand experience and flawed analytics.\n\n## What does Onedoc bring to the table?\n\nOnedoc bridges the gap between developers and documents. We make modern web technologies work for PDF generation: React, Tailwind, … In turn, developers can make highly dynamic documents and iterate quickly. **What used to take hours now takes seconds with our API.**\n\nTo make it even faster, we maintain an [open-source library](https://github.com/onedoclabs/react-print) of beautiful components and we offer a hosting and tracking service to better understand your documents.\n\n## What brought us here\n\nWe previously worked with giant firms, where documents were central to most workflows. They would get passed around, get into client’s hands, and everyone would complain about their layout and lack of proper information. While at a large mining company, clients would want to see shipping information and product details on their invoices. However, the development team wouldn’t be able to update these documents because the task was too complex and expensive.\n\n## Interested in generating beautiful documents today?\n\n* **Try it now,** and give us feedback!\n* **Social:** Join us on [Discord](https://discord.com/invite/uRJE6e2rgr) or send us a tweet at [@Onedoclabs](https://twitter.com/OnedocLabs) and we will get you set up in no time.\n* **Open-source:** Support our open-source library on [Github](https://github.com/OnedocLabs/react-print) by contributing and starring the repo.\n* **YC Deal:** Enjoy our YC Deal and get 1,000 monthly documents on us (x10), we also redesign your existing documents with our UI experts - get in touch at [yc@onedoclabs.com](mailto:yc@onedoclabs.com).",
        "url": "https://www.ycombinator.com/launches/KME-onedoc-making-it-easy-for-developers-to-generate-beautiful-pdfs",
        "votes": 114,
        "created_at": "2024-02-07T22:14:22.044Z"
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    "all_locations": "London, England, United Kingdom",
    "long_description": "We've built several businesses over the years, and each time, we faced the same challenges. We knew we needed to send sales emails, post regularly on social media, keep an eye on Google Ads, or simply manage the endless flood of emails—but somehow, these tasks always slipped through the cracks. The intention was there, but reality always got in the way.\r\n\r\nThat's why we created Marblism: AI Employees who seamlessly handle the tasks you keep putting off. No complex setups or prompts needed—just tell them about your business once and let them work quietly in the background. Suddenly, those tasks you knew you should be doing actually get done, giving you more time and mental clarity to focus on what truly matters.",
    "one_liner": "AI Employees who love overtime",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1705180571,
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    "country": "GB",
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      "url": "https://www.ycombinator.com/people/pete-koomen"
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        "user_id": 1616879,
        "full_name": "Ulric Musset",
        "title": "Founder/CEO",
        "founder_bio": "Founder @ Marblism\nex-founder @ Vauban sold to Carta. ",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/ulricmusset",
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    "id": 29472,
    "name": "Silogy",
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    "website": "https://silogy.io",
    "all_locations": "New York City, NY, USA; Remote",
    "long_description": "Silogy is building an AI-powered platform for chip developers to simulate and debug their designs.",
    "one_liner": "An AI-powered test and debug platform for chip developers",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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    "batch": "Winter 2024",
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    "regions": [
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    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/silogy.json",
    "year_founded": 2023,
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    "country": "US",
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      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
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    "founders": [
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        "user_id": 1524497,
        "full_name": "Kay Li",
        "title": "Founder/CEO",
        "founder_bio": "Cofounder and CEO of Silogy. Originally a math major, I became passionate about chips while working in high-frequency trading. Previously Hudson River Trading. Interested in all things related to chips and money.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/kay-li-84924128b",
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        "full_name": "Paul Kim",
        "title": "Founder/CTO",
        "founder_bio": "SiLogy CTO and cofounder. Previously Cloudflare, Sense Talent Labs, United Auto Workers. Interested in all things software, especially EDA.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/paul-kim-7b766262",
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    "launches": [
      {
        "id": 79226,
        "title": "SiLogy: Chip design and verification in the cloud",
        "tagline": "All-in-one platform for chip and FPGA development teams",
        "body": "**TL;DR**: SiLogy is building a platform for chip developers to run tests, track test statistics, and collaborate on debugging.\n\n—\n\nHey, we’re [Paul](https://linkedin.com/in/paul-kim-7b766262) and [Kay](https://linkedin.com/in/kay-li-84924128b), the cofounders of [SiLogy](https://silogy.io). We’re building chip design and verification tools to speed up the semiconductor development cycle.\n\n## **The Problem**\n\nInterest in designing new chips is growing, thanks to demand from AI and the predicted decline of Moore’s Law. Since the number of possible states grows exponentially with chip complexity, the need for testing in simulation is exploding, with chip developers already spending 70% of their time on testing. (See this video on the [verification gap](https://www.youtube.com/watch?v=rtaaOdGuMCc)).\n\nTooling hasn’t kept up. The state-of-the-art in collaborative debugging is to walk to a coworker’s desk and point to an error in a log file or waveform file. Each chip company rolls out its own tooling and infra to deal with this—this was Kay’s entire job at his last gig. But they want to work on chips, not devtools! The solutions they come up with are often inadequate and frustrating. That’s why we started SiLogy.\n\n## **The solution**\n\nSiLogy is a web app to manage the entire digital verification workflow. (“Digital verification” means testing the logic of the design and includes everything before the physical design of the chip. It’s the most time-consuming stage in verification.)\n\nWe combine three capabilities:\n\n**Test running, results, and statistics**: Our CI tool runs tests in the cloud, allowing engineering teams unlimited flexibility in scaling their test volume. We also track each project’s progress in test coverage and test pass rate.\n\n![uploaded image](/media/?type=post&id=79226&key=user_uploads/151331/d9a4d2a6-9662-4ee6-8eef-e735b10885b6)\n\n**Killer application-specific features**: We’re building features tailored for verification use cases. We incorporate a test orchestration framework, waveform viewer, coverage report, and other features specifically for verification teams, providing customers an advantage over competitors using a generic CI solution such as Jenkins.\n\n![uploaded image](/media/?type=post&id=79226&key=user_uploads/151331/d2beb46c-884b-4fec-b731-698c1c0a2312)\n\n**Collaboration**: soon you’ll be able to send a link to and leave a comment on a specific location within a log or waveform file, just like in Google Docs.\n\n![uploaded image](/media/?type=post&id=79226&key=user_uploads/151331/db8f1954-dafb-4a9e-b739-1b883c4963ac)\n\n## **Asks**\n\nIf you have experience with Verilog, even just from college, give our product a try at <https://dash.silogy.io/signup>. Tell your loved ones who work on chip or FPGA design and verification to give us a try as well.\n\nIf you have thoughts on the state of verification, get in touch at [paul@silogy.io](mailto:paul@silogy.io). If you or someone you know wants a demo, schedule a meeting with us [here](https://calendly.com/d/5gd-rf6-66h/silogy-product-demo).\n\nThanks for your support!",
        "url": "https://www.ycombinator.com/launches/Kbq-silogy-chip-design-and-verification-in-the-cloud",
        "votes": 29,
        "created_at": "2024-03-08T22:44:21.395Z"
      }
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    "id": 29474,
    "name": "Spur",
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    "all_locations": "New York City, NY, USA",
    "long_description": "Every company is about to run two systems: one that generates software and one that validates it. Spur is the second one.\r\nSpur runs specialized agents against the real product the way a customer would use it: functional, visual, content, native iOS and Android on real devices, and accessibility and compliance.",
    "one_liner": "Spur is the validation infrastructure enterprises use to ship at the…",
    "team_size": 15,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1724126992,
    "tags": [
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      "B2B",
      "AI"
    ],
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    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2024",
    "status": "Active",
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    "regions": [
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      "America / Canada"
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    "stage": "Early",
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      {
        "question": "How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)",
        "answer": "Anushka and I met our freshman year at Yale. We did research at the Yale NLP Lab on web agents. Sneha previously worked on growth at Figma, and Anushka on codegen at DeepMind. We’ve hacked on our fair share of projects before — and have very much felt the pain of neglecting testing."
      }
    ],
    "url": "https://www.ycombinator.com/companies/spur",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/spur.json",
    "year_founded": 2024,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/spur-test/",
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    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/5b63801706e3874e4f1017433f3c6a3ce0dddbca.png",
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    "primary_partner": {
      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
    },
    "founders": [
      {
        "user_id": 700570,
        "full_name": "Sneha Sivakumar",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder and CEO at Spur. Previously, Growth Engineer at Figma and Snap. ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/sivakumarsneha/",
        "x_url": "https://twitter.com/sneha8sivakumar",
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      },
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        "user_id": 1599382,
        "full_name": "Anushka Nijhawan",
        "title": "Founder/CTO",
        "founder_bio": "Co-founder and CTO at Spur. Previously @ Yale CS, Deepmind, and Meta.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/anushka-nijhawan-8380361b1",
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        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9d242d62abeffc70cc41a23e1cb30e103c74ef52.jpg"
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    ],
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      {
        "id": 71504,
        "title": "Founding Engineer / Full Stack",
        "url": "https://www.ycombinator.com/companies/spur/jobs/nmQ6lJD-founding-engineer-full-stack",
        "location": "New York, NY, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$130K - $225K",
        "equity_range": "0.20% - 2.00%",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
        "skills": [
          "Python",
          "TypeScript",
          "Next.js"
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      },
      {
        "id": 79490,
        "title": "Founding Designer",
        "url": "https://www.ycombinator.com/companies/spur/jobs/GoFbA9F-founding-designer",
        "location": "New York, NY, US",
        "type": "Full-time",
        "role": "Design",
        "role_type": "Product design",
        "salary_range": "$140K - $220K",
        "equity_range": "0.05% - 0.20%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Figma"
        ]
      },
      {
        "id": 82112,
        "title": "Founding Engineer Infra/Backend - Spur",
        "url": "https://www.ycombinator.com/companies/spur/jobs/cQGJFb3-founding-engineer-infra-backend-spur",
        "location": "New York, NY, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Backend",
        "salary_range": "$180K - $250K",
        "equity_range": "0.40% - 0.60%",
        "experience": "6+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Amazon Web Services (AWS)",
          "Microsoft Azure",
          "Kubernetes",
          "Python",
          "Docker"
        ]
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    ],
    "news": [
      {
        "title": "YC Alumni Spur Just Raised $4.5M for Their AI Agent Qa Startup - Business Insider",
        "url": "https://www.businessinsider.com/yale-alumni-spur-funding-ai-agent-startup-2025-4?type=social",
        "date": "Apr 17, 2025"
      },
      {
        "title": "Y Combinator | Yale grads Sneha and Anushka begins tech startup",
        "url": "https://www.globalindian.com/youth/story/global-indian-exclusive/from-classroom-to-startup-yale-grads-sneha-and-anushka-turn-class-project-into-a-tech-startup/",
        "date": "Sep 17, 2024"
      },
      {
        "title": "With launch of tech company Spur, recent grads discuss the hectic, exciting startup life | Yale School of Engineering & Applied Science",
        "url": "https://seas.yale.edu/news-events/news/launch-tech-company-spur-recent-grads-discuss-hectic-exciting-startup-life",
        "date": "Sep 08, 2024"
      }
    ],
    "launches": [
      {
        "id": 116412,
        "title": "Spur - testing infrastructure for your mobile apps",
        "tagline": "test and validate your mobile apps in plain english.",
        "body": "hey everyone 👋 we're Sneha and Anushka, co-founders of [Spur](https://www.spurtest.com/).\n\n### **TL;DR** Spur is building the validation infrastructure for software teams. We started with web testing, and today we're launching native app testing across iOS and Android.\n\nSpur is building the validation infrastructure for software teams. We started with web testing, and today we're launching native app testing across iOS and Android.\n\nSpur's agents test your apps the way real users do. You define the behavior you want to test in natural language, and Spur figures out how to execute and validate it across iOS and Android, native interactions, and web views.\n\nTeams at HelloFresh, Nextdoor, DocuSign, Bilt, Alo Yoga, and Abercrombie are already using Spur for testing across their digital experience – on websites and on their apps.\n\n**Our Ask:** If you’re building and maintaining a mobile app, we'd love to help you test it.\\\nBook a demo:[ https://spurtest.com/book-a-demo](https://spurtest.com/book-a-demo)\n\n## **The problem**\n\nSoftware is getting generated faster than ever: features that used to take days to build are now generated in minutes. But - once the feature exists, someone still has to figure out whether it actually works.\n\nThat validation process hasn't sped up at the same rate.\n\nIf you’re shipping mobile apps, this gets even harder. The same product flow often turns into separate automation for ios and android. Teams maintain the tests, the device infrastructure they run on, and the CI setup around them.\n\nAnd as your product changes, your automation has to change with it.\n\n## **The solution**\n\n1. **Natural Language allows you to define the “intent” of a test:**\n\n   Most test automation describes exactly _how_ to use an application.\n\n   _Find this element. Tap it. Wait for another element. Enter text. Assert a value._\n\n   That makes the test tightly coupled to the implementation. Spur tests describe what the user should be able _to do_ instead.\n\n   _Add an item to cart, apply a promo code, and complete checkout with Apple Pay._\n\n   The test captures the intent of the flow. Spur figures out how to execute it against the application in front of it. This means the same test can keep working across platforms or ui changes, because the thing you’re testing - the user behavior - hasn’t changed.\n2. **Spur runs the infrastructure too**\n\n   You upload the builds and choose what you want to validate. Spur handles the environment those tests execute in and runs them on our infrastructure. That means mobile testing becomes much closer to:\n\n   _build → upload → validate_\n\n   instead of becoming its own infrastructure project.\n\n   Tests can run as part of a release, against a pull request, on a schedule, or whenever an engineer wants to validate a change.\n\n   ![uploaded image](/media/?type=post&id=116412&key=user_uploads/700570/52f7df91-1940-4f7c-a2df-4299adbee3e3)\n\n3. **Built for engineers and agents**\n\n   As more software is written by coding agents, we think validation also needs to become something agents can use directly.\n\n   MCP is a first-class interface to Spur. A coding agent can make a change, ask Spur to validate the relevant user flows, inspect the result, fix what failed, and run the validation again.\n\n   So the loop starts to look like:\n\n   _generate → validate → fix → validate → ship_\n\n   Humans can define the intent, using anything as context (tickets, figma files, PRDs, your codebase). Agents can continuously check whether the software still satisfies it.\n\n   ![uploaded image](/media/?type=post&id=116412&key=user_uploads/700570/1438d0de-f515-48cf-8f6c-4c478e4a7dba)\n\n\n## **Why we built this**\n\nWe've spent the last few years building testing infrastructure for large software teams.\n\nOne thing has become increasingly clear: writing software is becoming dramatically easier, while proving that software works is still slow and expensive.\n\nWe think the gap between software generation and our ability to validate it is only going to widen.\n\nThe future of testing isn't maintaining more and more scripts. Validation needs to become more intelligent, adaptive, and be able to keep up with the rate at which software is changing.\n\nThat's what we're building at Spur.\n\nIf you're building or maintaining a mobile app, we'd love to work with you: <https://spurtest.com/book-a-demo>.",
        "url": "https://www.ycombinator.com/launches/UHc-spur-testing-infrastructure-for-your-mobile-apps",
        "votes": 20,
        "created_at": "2026-09-23T15:09:11.428Z"
      },
      {
        "id": 83237,
        "title": "✨ Spur - Your AI QA Engineer",
        "tagline": "Spur lets you test your website with natural language.",
        "body": "# **TL;DR: Spur lets you test your website with natural language.**\n\n## You can launch web agents that mimic exactly what your users do on your platform, so you can ensure your product doesn’t fail your users.\n\n---\n\n### Launch Day Deal 🎉\n\nAs part of launch day, we are offering to help you set up tests for your **core flows** on [signup](https://tally.so/r/n9WR4Q) for free. \\\nUse the code `SPUR_LAUNCH` on signing up to redeem this deal.\n\n—\n\n# Here’s how it works! (A flow we test for the YC Tech Team)\n\nAn example test for YC’s Application Portal to Invite Co-Founders\n\n![uploaded image](/media/?type=post&id=83237&key=user_uploads/700570/14e90a74-1b37-42e0-b36b-f6cc3b5d31aa)\n\n<https://www.loom.com/share/bbab011b36904f4ea6d97a85225c7c30?sid=2023cab4-e476-4574-9ad3-f5daf34d4d89>\n\n# **⛔️ The Problem (Do we even need to get into this?)**\n\nA. Testing is TIME-CONSUMING and PAINFUL. 🤕\n\n* whether you write a test\n* or manually check (or maybe not check) your core flows every single time you merge to production\n\nB. Tests are not MAINTAINABLE; they break! 🛠️\n\n* Your UI is constantly changing, and maintaining test scripts is a tedious task.\n\n## **✨ The Solution**\n\nOn Spur, you can:\n\n* Write automated tests in minutes (_not hours_) with natural language 💨💨\n* Not worry about maintaining tests when your UI changes 💅\n\n  _We use multimodal agents that interact with your web pages exactly like users would. Tests are not bound to CSS selectors_\n\n## **🧡 The Team behind Spur**\n\n[Anushka](https://linkedin.com/in/anushka-nijhawan-8380361b1) and I met our freshman year at Yale. We did research at the Yale NLP Lab on web agents. [Sneha](https://www.linkedin.com/in/sivakumarsneha/) (here!) previously worked on growth at Figma, and Anushka at DeepMind. We’ve hacked on our fair share of projects before — and have very much felt the pain of neglecting testing.\n\n![uploaded image](/media/?type=post&id=83237&key=user_uploads/700570/6ceb23f3-b013-4f80-a2f0-04e4c1539ba3)\n\n## **🤝 Our Ask**\n\n### **If this problem is one that you face, try us out!**\n\n* Book a [demo](https://calendly.com/sneha-sivakumar-1/30min)\n* [Sign up!](https://tally.so/r/n9WR4Q) We are live and actively onboarding customers every single day\n\nOur customers have found a **lot** of value from using us so far, and we’d love to take testing off your plate. Here is what some of them have said :)\n\n> Spur is shockingly easy to use—no coding, just plain English. Simply describe what you want to test, and Spur handles the rest. Onboarding was a breeze, and Anushka and Sneha are fantastic to work with.\n>\n> _\\- Eve Bouffard, Product Engineer @ YC Tech Team_\n\n> I’m gonna see if I can expense Spur through my wellness stipend. Category: Therapy\\\n> \\- Gabe Wilson, Founder & CTO @ Terrakotta\n\n> We had a HUGE UI revamp and are still able to test easily without needing maintenance, not a single test has broken due to flakiness. They mean it when they say their tests are reliable. \\\n> \\- Joseph Parker, Founder & CTO @ VecFlow\n\n> We’ve been using Spur and it’s been AMAZING — unlike all the competitors that we’ve tried, they actually work! Can highly recommend.\\\n> \\- Konsti Wohlwend, Founder @ StackAuth",
        "url": "https://www.ycombinator.com/launches/LeX-spur-your-ai-qa-engineer",
        "votes": 187,
        "created_at": "2024-08-20T18:33:59.716Z"
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    "id": 29498,
    "name": "Integuru",
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    "website": "https://www.integuru.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Integuru turns any platform into a reliable, low-latency, and high-throughput API. Requests complete in 3 seconds with 99.9%+ success, including deployments above 1M requests/month/platform. No RPA or browsers. No data caching needed. (By Taiki, Inc.)",
    "one_liner": "Generate fast, reliable APIs for any platform",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1709153976,
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      "API",
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      "AI"
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    "nonprofit": false,
    "batch": "Winter 2024",
    "status": "Active",
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    "regions": [
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/integuru",
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    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/integuru-ai/",
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    "fb_url": null,
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    "github_url": "https://github.com/Integuru-AI/",
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    "primary_partner": {
      "name": "Gustaf Alstromer",
      "url": "https://www.ycombinator.com/people/gustaf-alstromer"
    },
    "founders": [
      {
        "user_id": 504669,
        "full_name": "Richard Zhang",
        "title": "Founder/CEO",
        "founder_bio": "Co-Founder & CEO of Integuru — build and maintain fast, reliable integrations for any platform. Previously, product at Alibaba Cloud; data science at DiDi; and investor at Dragonfly and Gaorong Capital.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/richardfzhang",
        "x_url": "https://twitter.com/richardfzhang",
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        "full_name": "Alan Lu",
        "title": "Founder/CTO",
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        "is_active": true,
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      {
        "id": 101982,
        "title": "Integuru ⚡️ Generate fast, reliable APIs for any platform",
        "tagline": "We help agents control any external system, with speed and reliability.",
        "body": "📝 **TL;DR:** [Integuru](https://bookface.ycombinator.com/company/29498) **generates fast, reliable, and high-throughput APIs for any platform.** API calls complete in \\~**3 seconds** with **99.9%+ success**. No RPA or browsers. No data caching needed. Customers are already using fully generated integrations in production at millions of requests per month.\n\nStarting today, Integuru is **publicly accessible** and **free to try**! You can **use it** [here](https://app.integuru.com/).\n\n### **🎬 Integuru in Action**\n\n<https://youtu.be/v00yl_46H34>\n\n### 🎯 **The Problem**\n\nAI agents need to access external platforms, but most platforms don’t offer official, accessible, or comprehensive APIs. **That makes integration the single biggest bottleneck.**\n\nFor building integrations, most companies today use RPA, typically implemented via browser automation. RPA is easy to set up, but many AI companies have now **outgrown their RPA implementations**. They’re running into issues with **latency**, **reliability**, and **throughput**. A single API call can take minutes, and integrations are vulnerable to breaking due to frontend changes.\n\nWith RPA, there’s a relatively low ceiling on the number of concurrent browser instances on the same platform. This limits the number of requests. As customer counts grow, companies require higher throughput, but RPA, by nature, cannot support that demand.\n\nAt the same time, regardless of the approach you take to integrate, **edge cases are among** **the biggest causes of integration breakage**. Edge cases are different branching logic, states, and paths that appear in real-world usage across accounts and scenarios. Integrations that seem fine during testing can completely break in production.\n\nEdge cases can be caused by things like:\n\n* conditionally appearing fields and pages\n* hidden business logic depending on inputs\n* varying server behaviors\n\nTraditionally, testing edge cases must be done manually. Developers must manually trigger as many variations as possible, including changing inputs and stress-testing server limits. This process is often tedious and cannot cover everything, which threatens integration reliability.\n\nToday, we’re announcing a **publicly accessible,** **self-serve product** that solves all these issues and generates robust APIs in minutes.\n\n### 📈 **Integuru’s Solution**\n\nInteguru is an AI platform that **automatically reverse-engineers a website’s backend**. It generates integrations that directly ping website servers, with API docs for each.\n\nInteguru **covers edge cases** that arise during production workloads. It also **auto-heals authentication flows**. Meanwhile, we have a **24/7 on-call maintenance team** available, with **hands-on support** whenever human intervention is needed.\n\nIn real production environments for early-access partners (many of which are YC companies!), requests complete in **\\~3 seconds** with **99.9%+ success**, including deployments **above 1M requests/month/platform**. Requests are **executed live** and achieve low latency without data-caching.\n\nThe workflow is simple with minimal manual involvement:\n\n1. On Integuru, input the website and account you want to integrate with.\n2. Describe your desired feature in natural language. (No need to manually perform or record any actions.)\n3. Integuru proposes an API schema and, upon your approval, generates the endpoint in \\~10 minutes, along with API docs.\n\nEndpoints are **immediately testable** and **production-ready**. For authentication, we support 2FA and will coordinate with you.\n\nWe already support the majority of platforms today. If Integuru can’t yet handle your use case automatically, we’ll evaluate and provide hands-on support at no extra cost.\n\n### **🙋‍♂️ What industries have been using Integuru?**\n\nEarly-access partners are already using generated APIs in production across use cases, processing millions of requests per month with minimal human involvement.\n\n* Healthcare: connecting to EHRs, EMRs, RCMs, CTMSes, insurance portals, etc.\n  * We sign BAAs at no cost. You can sign a BAA directly in the product.\n* Logistics: integrating with TMSes, WMSes, ERPs, carrier portals, etc.\n* Proptech: automating property management systems, utilities, permitting software, etc.\n* Legal: controlling practice/case management systems, government portals, etc.\n* Enterprise AI transformation: accessing ERPs, CRMs, CX platforms, internal tools, etc.\n* … and more\n\n## 📚 **Backstory**\n\nOur first [open-source](https://github.com/Integuru-AI/Integuru) agent (4k+ stars) proved demand for robust integrations, but it couldn’t handle the complexity of modern platforms. So we did things that didn’t scale. We manually built and maintained integrations for customers, eventually supporting millions of API calls every month. That gave us a front-row seat to the messy reality of integrations. We tried turning those learnings into a self-serve product, but that version still wasn’t enough, so we kept dogfooding it while building customer integrations. Eventually, we rebuilt the self-serve product from the ground up, using insights we gathered around edge-case coverage, auto-healing, better UX, production reliability, and high-throughput execution. This is the product you see today, and companies are already using it to generate integrations that run reliably in production.\n\n## 🚀 **Try for free today!**\n\nInteguru is **publicly accessible** starting today and **free to try**!\n\nYou can **get started on your own** [here](https://app.integuru.com/), or **schedule an onboarding call [here](https://calendly.com/alan-taiki/integuru-guided-setup)** if you want us to set up everything for free or have specific questions.\n\n![uploaded image](/media/?type=post&id=101982&key=user_uploads/504669/89260a10-1e12-47b1-92b9-2e920e95b3e3)\n\n",
        "url": "https://www.ycombinator.com/launches/QWs-integuru-generate-fast-reliable-apis-for-any-platform",
        "votes": 10,
        "created_at": "2026-05-26T18:33:59.675Z"
      }
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    "id": 29501,
    "name": "Latted",
    "slug": "latted",
    "former_names": [
      "Fume Test",
      "Fume"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/9b29e2d502cf6d25b0468bc3a78f72aad18346f8.png",
    "website": "https://latted.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Latted is an all-in one tool to generate and edit professional AI video projects.\r\n\r\nAll professional AI video projects take more than a single generation. You need to juggle between hundreds of images and videos and use multiple tools to edit your project.\r\n\r\nWith Latted, you can generate a 10-minute long video from a single prompt or generate and edit your project from scratch.\r\n\r\nThousands of creators use Latted for marketing videos, content creation and educational content. Create your first project today at latted.com!",
    "one_liner": "A Unified Editor For AI Video",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1705822020,
    "tags": [
      "B2B",
      "Video",
      "Marketing",
      "AI"
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2024",
    "status": "Active",
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    "regions": [
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      "America / Canada"
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    "stage": "Early",
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/latted",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/latted.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
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    "primary_partner": {
      "name": "Harj Taggar",
      "url": "https://www.ycombinator.com/people/harj-taggar"
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    "founders": [
      {
        "user_id": 1573638,
        "full_name": "Emre Gucer",
        "title": "Founder",
        "founder_bio": "co-founder and CEO @ Fume. former Northwestern student, now an LLM aficionado.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/aegucer",
        "x_url": "",
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        "user_id": 1611827,
        "full_name": "Metehan Öz",
        "title": "Founder",
        "founder_bio": "Co-founder and CTO @ Fume. A former NYU student. Now hacking around with LLMs.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/metehan-oz-a39981251",
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      {
        "id": 79085,
        "title": "Fume - AI SWE that solves bugs within Slack",
        "tagline": "A Slack bot that you can assign software tickets and get full PRs in response",
        "body": "**TL;DR** You can tag @Fume under any feature or bug ticket in Slack. Fume will make a plan, write code, and submit a PR in minutes. [**Try it now! No waitlist. No 'contact sales'.**](http://fumedev.com)\n\nHey folks! We are [Emre](https://linkedin.com/in/aegucer) and [Mete](https://linkedin.com/in/metehan-oz-a39981251). We’re currently building Fume to automate the boring parts of developing software. Before that, we were roommates in high school and partners in crime, building fighting bots.\n\n![uploaded image](/media/?type=post&id=79085&key=user_uploads/1573638/314fd0c9-7a62-4aa6-9e91-6d29c4cec454)\n\n### 💥**Problem**\n\nNot every software task requires human creativity. Some are just boring and have to be done. Engineers end up procrastinating on them at the cost of user experience. On the other hand, doing them costs companies thousands of dollars every year.\n\n### 🤩 **Not Anymore**\n\nFume automates mundane software work like fixing bugs, error logs, or minor features through Slack. A non-technical team member can send screenshots & reproduction steps for a bug and an engineer can tag @Fume to solve it within minutes without opening a code editor.\n\n![uploaded image](/media/?type=post&id=79085&key=user_uploads/1573638/85ea9b9a-969c-4552-9e19-e1437d3f5d55)\n\n### 🙏 **Our Ask**\n\nGive Fume a try right now! Go to [fumedev.com](http://fumedev.com) and enjoy the free trial. If you think you are not ready to start using Fume, tell a friend about it 😉\n\nIf you are in a larger organization but want to try Fume in your team, contact me at [emre@fumedev.com](mailto:emre@fumedev.com). ",
        "url": "https://www.ycombinator.com/launches/KZZ-fume-ai-swe-that-solves-bugs-within-slack",
        "votes": 508,
        "created_at": "2024-03-05T21:32:54.482Z"
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    "id": 29502,
    "name": "renderlet",
    "slug": "renderlet",
    "former_names": [
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      "Renderlet"
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    "website": "http://renderlet.com",
    "all_locations": "New York City, NY, USA",
    "long_description": "renderlet is a framework that makes it easy to develop interactive applications.\r\n\r\nBuilding applications with high-performance graphics is very hard – existing tools are cumbersome and aren’t truly platform agnostic, leading to frequent rework. \r\n\r\nWith renderlet, developers can write high-level code to describe 2D and 3D graphics without having to use low-level, platform-specific APIs.\r\n\r\nrenderlet automatically compiles graphics code to WebAssembly and embeds a portable rendering engine inside any app, enabling graphics to safely and automatically render on any platform’s GPU.\r\n\r\nOur runtime is open-source: https://github.com/renderlet/wander",
    "one_liner": "Build interactive applications that run anywhere",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1708655277,
    "tags": [
      "Developer Tools",
      "Design Tools",
      "Data Visualization"
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    "url": "https://www.ycombinator.com/companies/renderlet",
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    "year_founded": 2024,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/renderlet",
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    "primary_partner": {
      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
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    "founders": [
      {
        "user_id": 1759368,
        "full_name": "Sean Isom",
        "title": "Founder/CEO",
        "founder_bio": "Sean is the Founder of renderlet. He previously built Developer Platforms at Adobe as a Lead Engineer and Sr. Engineering Manager, building the core infrastructure that powers apps like Photoshop and Acrobat. He has over a decade of technical experience in browsertech and real-time graphics and is currently involved in standardization efforts for WebAssembly’s WASI GPU support.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/isom",
        "x_url": "https://twitter.com/theisomizer",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a3cfd53d423d8c2e04727b0f7566266acbefa8b1.jpg"
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      {
        "id": 79415,
        "title": "renderlet: Making graphics programming easy",
        "tagline": "Write graphics code that automatically runs anywhere",
        "body": "**Building interactive graphics is really hard**. Developers need expert-level knowledge of GPU programming just to build code that is not portable to new environments such as Web or Mobile or reusable across applications.\n\nRenderlet is a WebAssembly framework for **writing graphics code that runs anywhere**. Describe your graphics pipeline using a **higher-level abstractions** and use renderlet to generate low-level, cross-platform rendering code.\n\nWith renderlet, developers can easily embed GPU-accelerated 2D and 3D graphics into cross-platform applications.\n\n![uploaded image](/media/?type=post&id=79415&key=user_uploads/1759368/4ce27e3c-1c68-456d-a0bd-eedd272c1712)\n\n## How it works\n\nWith renderlet, **we compile graphics to portable WebAssembly modules** and provide a runtime that abstracts away the underlying GPU architecture to the code.\n\nDevelopers can take advantage of modern technologies like **WebGPU** without having to learn the intricacies of yet another standard. 2D and 3D graphics are fully decoupled from the application and device and can ship decoupled from the applications code in a format that **runs anywhere**.\n\nRenderlet is:\n\n* A **compiler** that takes a high-level specification of your graphics pipeline - including custom assets, functions, and libraries - and builds self-contained WebAssembly rendering modules\n* A  **renderer**, _wander_, that embeds into any application on any platform that and safely runs rendering modules with the GPU\n* A **visual editor** that makes it easy to build entire graphics and visualization pipelines out of reusable rendering modules\n\n**Anybody should be able to build interactive applications** without having to be a graphics programming expert.  \n\n## About Us\n\n[Sean Isom](https://linkedin.com/in/isom) previously built developer platforms at Adobe as a Lead Engineer and Sr. Engineering Manager. He helped bring products to the cloud and web using tools like WebAssembly and is currently involved in standardization efforts for WebAssembly GPU support.\n\n![uploaded image](/media/?type=post&id=79415&key=user_uploads/1759368/36bcf46c-edd6-4b90-9124-45c3c81ec64b)\n\n## What’s next?\n\nOur cross-platform rendering engine, **wander**, is open source: <https://github.com/renderlet/wander/> \n\nWe’re kicking off with a **live demo** today of renderlet at Wasm I/O!  <https://2024.wasmio.tech/sessions/paint-by-numbers-high-performance-drawing-in-wasm/> \n\nWant more info on cross-platform graphics? **Get in touch**! - [sean@renderlet.com](mailto:sean@renderlet.com) ",
        "url": "https://www.ycombinator.com/launches/Ket-renderlet-making-graphics-programming-easy",
        "votes": 36,
        "created_at": "2024-03-15T16:53:22.280Z"
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    "id": 29503,
    "name": "Dragoneye",
    "slug": "dragoneye",
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    "website": "https://dragoneye.ai/",
    "all_locations": "New York City, NY, USA",
    "long_description": "Dragoneye helps devs build their custom video detection models in less than 5 minutes. These models can then be used to power apps and features that use images and videos. No more arduous process of annotating any training data or doing any machine learning work themselves.\r\n\r\nTry out our demo today at https://playground.dragoneye.ai/ !",
    "one_liner": "Custom video detection models in less than 5 minutes",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1705986923,
    "tags": [
      "Developer Tools",
      "Computer Vision",
      "AI",
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    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/dragoneye",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/dragoneye.json",
    "year_founded": 2023,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/dragoneyeai",
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    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/354a00433e0332ff17869b4c08d6ee8d10b8a232.png",
    "app_video_url": null,
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    "company_photos": [],
    "primary_partner": {
      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
    },
    "founders": [
      {
        "user_id": 818332,
        "full_name": "Alex Liao",
        "title": "Founder/CEO",
        "founder_bio": "Building computer vision so every app can see the world. \n\nex-Jane Street, ex-Facebook, UPenn Physics and CS\n\n",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/alexliaoo",
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    "jobs": [],
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    "launches": [
      {
        "id": 95768,
        "title": "Dragoneye: Production video detection models in <5 minutes",
        "tagline": "Build zero-shot video models quickly with 0 training data",
        "body": "![uploaded image](/media/?type=post&id=95768&key=user_uploads/818332/27d779bf-8574-4d51-adbe-d69a806e6d0b)\n\nHey YC! I’m Alex, founder of Dragoneye. \n\n**I want to share with y’all the launch of our new interactive Playground, which allows you to build your own custom video detection models in under 5 minutes.**  \n\n![uploaded image](/media/?type=post&id=95768&key=user_uploads/818332/51fa21e6-bc13-41ad-8f9e-03947fd50b7a)\n\n# **The Problem:**\n\nVideo detection models are incredibly useful. Analyzing security camera footage, ensuring PPE compliance, monitoring production lines. \n\nBut it’s always been hard to build video detection models. Thousands of hours of videos that need to be annotated. You train the model only to find that it doesn’t perform as well as you need it. Really cool ideas that never get to prototype, never mind released in production. Crucial features that take tens of thousands of $$ to trial and months to implement. \n\n# **Our Solution:**\n\nOur new Playground allows you to build and deploy production-ready video detection models in less than 5 minutes, enabled by our powerful zero-shot models.\n\nTo get started:\n\n1. Upload a video\n2. Describe the categories of items you want to detect in your video\n3. The model streams the predictions and you can preview it on your video\n4. Iterate on your categories till you’re set. \n\nOnce you’re happy with your model, you can save it out and it’s live! To make it easier to integrate with your apps, we have libraries for Python and Node.js, with more languages to come.\n\nCheck out the Playground at https://playground.dragoneye.ai/ to get started. You can follow our step by step guide below as well!\n\nhttps://youtu.be/2rhKBO4N7B0\n\nWe can’t wait to see what you build! 🙂 ",
        "url": "https://www.ycombinator.com/launches/Oue-dragoneye-production-video-detection-models-in-5-minutes",
        "votes": 11,
        "created_at": "2025-11-25T16:18:04.833Z"
      },
      {
        "id": 85450,
        "title": "Dragoneye - More detailed object detection than Google and Amazon!",
        "tagline": "We offer vision object detection for 13k+ classes right out of the box.",
        "body": "Hey YC! I’m Alex, founder of Dragoneye. \n\n**I want to share with y’all the launch of our object detection platform, which can recognize 40x more classes than Amazon Rekognition and 20x more than Google Vision across a wide range of categories.** \n\n![uploaded image](/media/?type=post&id=85450&key=user_uploads/818332/45a1bd0a-16f7-4061-9c0e-ebd5a586450f)\n\n# **The Problem:**\n\nYou’re building a new feature that relies on the ability to recognize things in camera or photos. But all of the off-the-shelf APIs today don’t get the detail you need. You don’t just need to know it’s a dress, but that it’s a checkered short-shift dress! \n\nYou look into how to train your own computer vision model, but you soon realize what a daunting task it is. There are thousands to millions of photos to collect, and it takes weeks of time. What can you do?\n\n# **Our Solution:**\n\nWe want to have the best visual recognition API out there, and enable devs to build powerful vision-driven features in a pinch.\n\n**What we’re focused on:**\n\n* **Latency** - our fastest models can detect objects in 12ms\n* **Detail** - 13,000 different classes over 25 categories now, and we aim to get to 100,000+ by the end of 2024\n* **Implementation ease** - under 10 lines in Python & JS and a simple REST API\n\nSeeing is believing - pun intended - so here is our side-by-side comparison with Google’s Vision API and Amazon’s Rekognition\n\n![](https://bookface.ycombinator.com/media/?type=post&id=85450&key=user_uploads/818332/aa480801-a466-48a9-89a4-1e0bbb8fc9e7)\n\n![](https://bookface.ycombinator.com/media/?type=post&id=85450&key=user_uploads/818332/f6058fa7-c804-4c68-a282-9faab8873005)\n\n![](https://bookface.ycombinator.com/media/?type=post&id=85450&key=user_uploads/818332/4c0c954f-c1c0-4382-8d3d-9998404b461d)\n\n# **Our Ask**\n\n1. Try out our instant demo at <https://dashboard.dragoneye.ai>. We know we have some bugs to squash, so please let us know what works great and what doesn’t. \n2. [Book a meeting with us](https://calendly.com/dragoneye-cal/intro-call) if you have computer vision/object detection needs - coffee is on us!",
        "url": "https://www.ycombinator.com/launches/MEE-dragoneye-more-detailed-object-detection-than-google-and-amazon",
        "votes": 13,
        "created_at": "2024-11-11T18:54:56.008Z"
      },
      {
        "id": 79474,
        "title": "Dragoneye - Computer vision for every developer",
        "tagline": "We automate the entire process for building computer vision, allowing developers to get custom vision recognition models from just a model spec.",
        "body": "![uploaded image](/media/?type=post&id=79474&key=user_uploads/818332/3b1dd109-a001-41f9-a1a8-39e46badb5a5)\n\n**TLDR:** [**Dragoneye**](https://dragoneye.ai/) helps developers use computer vision without needing to bring any of their own training data or do any CV/ML work themselves.\n\n## Demo\n\n<https://www.youtube.com/watch?v=opRMn48z9dM>\n\n## ❓The problem\n\nGetting data from images today is hard. LMMs allow you to get started quickly but have capability limitations and are slow. On the other hand, building your own vision recognition models requires a ton of time and a ton of expertise.\n\nI learned this firsthand when I tried to build my own fashion outfit**\\-**matching app a few years ago. What started as coding a fun consumer app was quickly taken over by the challenges of building custom image models - annotating data, model evaluation, training, deployment, etc. Before long, I realized that I was basically building a computer vision startup - literally!\n\n## ✨ Our solution\n\nDragoneye enables developers to build and use cutting-edge CV models simply by specifying the model spec.\n\n**Specification → Working Model Automagically:** After specifying the model, Dragoneye’s systems scurries away to find the best implementation strategy and then builds it for you!\n\n**Continuous Improvement:** In the background, Dragoneye constantly keeps the models and tech at the cutting edge so you keep getting the best performance without any work on your end at all.\n\n**Grows with your need:** As your needs grow, we grow with you. Simply update your model specification, and Dragoneye will figure out how to make it work best.\n\n## 🙏 Ask\n\nWe just opened up our self-service feature. [Sign up on our site](https://dragoneye.ai/) for access!\n\nAlso, we’d love to hear what you want to build with Dragoneye - please email me at [alex@dragoneye.ai](mailto:alex@dragoneye.ai)!\n\n![uploaded image](/media/?type=post&id=79474&key=user_uploads/818332/dc0fc2db-02eb-44be-99dc-c79bdc7721cd)\n\n",
        "url": "https://www.ycombinator.com/launches/Kfq-dragoneye-computer-vision-for-every-developer",
        "votes": 49,
        "created_at": "2024-03-18T18:59:47.892Z"
      }
    ]
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  {
    "id": 29512,
    "name": "Reprompt",
    "slug": "reprompt",
    "former_names": [
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      "Reprompt (previously SyncUp.ai)"
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    "website": "https://repromptai.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Reprompt builds AI Agents for Location-- Mapping companies like Radar and TomTom use our agents to get live information about a point of interest or business that keeps their maps up to date. \r\n\r\nTo do this we have an internal agents platform that supports Web, Vision, Doc Reading, and soon self-driving browser agents.",
    "one_liner": "AI Agents for Location",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1705532788,
    "tags": [],
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    "isHiring": true,
    "nonprofit": false,
    "batch": "Winter 2024",
    "status": "Active",
    "industries": [
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    "regions": [
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      "America / Canada"
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    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/reprompt",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/reprompt.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/99389319/",
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    "app_video_url": null,
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    "primary_partner": {
      "name": "Gustaf Alstromer",
      "url": "https://www.ycombinator.com/people/gustaf-alstromer"
    },
    "founders": [
      {
        "user_id": 1757957,
        "full_name": "Lukas Martinelli",
        "title": "Founder",
        "founder_bio": "Lukas spent 7 years running engineering+product+operations as General Manager for the Search business at Mapbox who provides APIs to 2 million developers. At Reprompt we're mapping the physical world with AI, used by companies like Foursquare, TomTom to get the most up to date information about businesses.\n\nLukas' has a history of widely adopted dev tools. Before Mapbox he created several popular open-source dev tools (15k stars) in the mapping industry now used by Amazon, IBM, Bosch. ",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/lukas-martinelli",
        "x_url": "https://twitter.com/lukmartinelli",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e914296b1b06166f76b3fb59d10f67cf0aac9c64.jpg"
      },
      {
        "user_id": 64967,
        "full_name": "Rob Balian",
        "title": "Founder",
        "founder_bio": "Building Reprompt | Previously led Growth @ Robinhood, Product at Facebook, Stanford CS\n\nRob is a builder and hacker. He built the first multiplayer online iPhone app, and combined his apps got 15M downloads and 1M MAU. He's trained and deployed vision models that beat SoTA. He led Robinhood's 50-person Growth team through their chaotic Covid, Gamestop, and IPO rollercoasters.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/robbalian",
        "x_url": "https://twitter.com/robbalian",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1a6ccc36b17cba59150311c13bcb11853cfe4fe0.jpg"
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    "jobs": [
      {
        "id": 69528,
        "title": "Software Engineer",
        "url": "https://www.ycombinator.com/companies/reprompt/jobs/YfQBWDH-software-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$120K - $180K",
        "equity_range": "0.50% - 1.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "JavaScript",
          "Python",
          "TypeScript"
        ]
      },
      {
        "id": 79314,
        "title": "Founding SDR",
        "url": "https://www.ycombinator.com/companies/reprompt/jobs/M7gNCyU-founding-sdr",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$75K - $95K",
        "equity_range": "0.25%",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
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      },
      {
        "id": 81063,
        "title": "Senior Software Engineer",
        "url": "https://www.ycombinator.com/companies/reprompt/jobs/obM1jvC-senior-software-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$150K - $220K",
        "equity_range": "0.50% - 2.00%",
        "experience": "6+ years",
        "visa": "US citizen/visa only",
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      {
        "id": 79428,
        "title": "Reprompt AI: Helping AI apps get to production quality 10x faster",
        "tagline": "AI teams use Reprompt to evaluate and improve their apps without code",
        "body": "**tldr:** Productionizing AI apps is hard. [**Reprompt**](https://repromptai.com/) lets teams evaluate and improve their apps without code and get to production quality 10x faster.\n\n### **90% of Generative AI pilots never make it to production**\n\nGenerative AI applications are notoriously hard to scale to production quality:\n\n* Hallucinations are hard to detect and fix\n* Function calling is a huge opportunity but still hit-or-miss\n* RAGs aren’t as scalable as we hoped, and often they find the wrong documents\n* AI responses can become a legal and compliance liability\n\n![uploaded image](/media/?type=post&id=79428&key=user_uploads/89898/2b3dd321-4e55-48ad-8771-3f2c0526107c)\n\n### **Getting to production takes more than great prompt engineering**\n\nBehind the scenes of every great product (Uber, Doordash, Waymo, Robinhood) there's an ops team with a dashboard full of if statements and data overrides that keeps the whole company from collapsing.\n\nFrom what we’re seeing, AI apps will require similar tuning, using strategies like Human-In-The-Loop, custom overrides, multi-queries, and prompt splitting/routing.\n\n### **Reprompt helps AI teams fix “last mile” AI issues so they can ship faster**\n\nHere’s what you can do with Reprompt:\n\n1. Trace your AI calls across chat, RAG, and function calls to make debugging easy\n2. Automatically track and highlight hallucinations and file them as bugs\n3. Write custom prompt overrides to handle the edge cases **without changing your main prompt or pushing code**\n\n![uploaded image](/media/?type=post&id=79428&key=user_uploads/64967/5434ca4f-a3ef-4085-966d-b7a4fbf43f87)\n\n### **About the team**\n\n[Lukas Martinelli](https://linkedin.com/in/lukas-martinelli) was an Engineering Director and GM of Search at Mapbox. He also led Mapbox's 120-person labeling and evaluation team.\n\n[Rob Balian](https://linkedin.com/in/robbalian) led Robinhood's Growth team through Covid, Gamestop, and IPO. He was an early PM at Facebook.\n\n![uploaded image](/media/?type=post&id=79428&key=user_uploads/64967/808fb8ba-68a8-476e-ab28-c744d4acf70d)\n\n_Rob Balian and Lukas Martinelli_\n\nIf your team has challenges getting to production-level quality, we’d love to [show you a demo](https://cal.com/robbalian/reprompt-demo-with-rob). See you all in production!\n\n\\-Rob and Lukas",
        "url": "https://www.ycombinator.com/launches/Kf6-reprompt-ai-helping-ai-apps-get-to-production-quality-10x-faster",
        "votes": 29,
        "created_at": "2024-03-15T22:13:06.395Z"
      }
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  },
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    "id": 29516,
    "name": "Million",
    "slug": "million",
    "former_names": [
      "Million.js",
      "Million",
      "Same"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cf5c5c98069c0ec6b53c093dd68742e6a1c17ae9.png",
    "website": "https://million.dev",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Remember the first time you hit  and your code actually worked? Something that didn't exist before, now alive on your screen.\r\n\r\nToday, coding agents can do that, orders of magnitude faster. But their verification is shallow at best. The faster agents generate code, the wider the gap grows. Nothing verifies software at the speed agents ship code.\r\n\r\nWe believe verification unlocks long-horizon coding agents: agents that run for days and prove their work as they go.",
    "one_liner": "Tools for agent verification",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1703896590,
    "tags": [
      "AI"
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    "nonprofit": false,
    "batch": "Winter 2024",
    "status": "Active",
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    "regions": [
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      "America / Canada",
      "Remote",
      "Partly Remote"
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    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/millionco",
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      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
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      {
        "user_id": 1524896,
        "full_name": "Aiden Bai",
        "title": "Founder/CEO",
        "founder_bio": "i'm a huge web performance + react internals nerd",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/aidenbai",
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        "user_id": 1159798,
        "full_name": "Nisarg Patel",
        "title": "Founder",
        "founder_bio": "working on million.dev",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/nisargptel",
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      {
        "id": 78916,
        "title": "Million Lint – Grammarly for performance",
        "tagline": "A VSCode extension that identifies slow code and suggests fixes. ",
        "body": "Hey YC! I’m [Aiden](https://twitter.com/aidenybai), founder of [Million](https://million.dev/) — we’re building a tool that helps fix slow React code. Here is a quick demo: [ ](https://www.youtube.com/watch?v=k-5jWgpRqlQ&ab_channel=AidenBai)\n\nFixing web performance issues is hard. Every developer knows this experience: we insert console.log everywhere and catch some promising leads, but nothing happens before \"time runs out.\" Eventually, the slow/buggy code never gets fixed, problems pile up on a backlog, and our end users are hurt.\n\nWe started Million to fix this. A VSCode extension that identifies slow code and suggests fixes (like Grammarly, for performance!) The website is here: <https://million.dev/blog/lint> \n\nI realized this was a problem when I tried to write an optimizing compiler for React in high school (src: <https://github.com/aidenybai/million>). It garnered a lot of interest (14K+ stars) and usage, but it didn't solve all user problems.\n\nTraditionally, devtools either hinge on full static analysis OR runtime profiling. We found success in a mixture of the two with dynamic analysis. During compilation, we inject instrumentation where it's necessary.\n\nFrom there, the runtime collects this info and feeds it back into VSCode. This is a great experience! Instead of switching around windows and trying to interpret flamegraphs, you can just see it inline with your code.\n\nWe are still in the very early days of experimentation! Million Lints focuses on solving unnecessary re-renders right now and will move on to handling slow-downs arising from the React ecosystem: state managers, animations, bundle sizes, waterfalls, etc. Our eventual goal is to create a toolchain that keeps your whole web infrastructure fast, automatically - frontend to backend.\n\nIn the next few weeks, we're planning to open source (MIT) the Million Lint compiler and the VSCode extension. \n\nTo earn a living, we will charge a subscription model for customized linting. We believe this aligns our incentives with yours: we only make money when we make your app faster.\n\nWe'd love to know your thoughts – happy to answer :)",
        "url": "https://www.ycombinator.com/launches/KWq-million-lint-grammarly-for-performance",
        "votes": 27,
        "created_at": "2024-02-29T20:35:04.594Z"
      }
    ]
  },
  {
    "id": 29524,
    "name": "Coval",
    "slug": "coval",
    "former_names": [
      "Datawave"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/adc31ffe74137f2876c08ce7153b3a5cfd5001ca.png",
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        "title": "Ceejay - Give Your Inbox and Calendar a Brain",
        "tagline": "Ceejay uses AI to lighten the mental load of managing your inbox and calendar.",
        "body": "**TLDR;** We’re launching Ceejay – an all-knowing assistant connected to your inbox and calendar. [Download it here](https://tryceejay.com) (if you have Gmail and an iPhone!).\n\n### **The Problem**\n\nOur inboxes are too noisy to manage and too important to ignore. 70% of people who have a full-time executive assistant start by having them manage their email and calendar. \n\nWhy? It’s an easy way to save time (say, an hour a day) and both platforms have enough context that an assistant can ramp up fairly quickly. We’ve proven LLMs can do this for you, for a fraction of the cost of a human.\n\nWe previously built [Superfilter](https://superfilter.ai) to tackle a similar problem, but we made a _ton_ of mistakes. Thankfully those mistakes led us to a product people find very valuable.\n\n### **Enter Ceejay**\n\nUsing Ceejay is similar to the experience of chatting with a human assistant.\n\nWatch this 60-second video to understand what [Ceejay can do for you.](https://www.youtube.com/watch?v=ybeCMdFXqhc)\n\nCeejay has a growing list of things it can do for you including:\n\n**Searching your inbox:** Why search your inbox for that receipt from July when you can ask Ceejay?\n\n**Managing your schedule:** Why send a calendar link or book an event when you can ask Ceejay (who handles conflicts!)?\n\n**Highlight messages that matter:** Why separate your important messages from the unimportant when Ceejay can do it for you?\n\n**Learning about you:** Ceejay is also the only inbox that deliberately remembers facts about you to reference later. I told Ceejay that my coworkers are Scott and Travis.\n\nJust ask, and you shall receive. There’s no additional inbox to manage. No new interface to learn. Just a clean chat with a ton of features you can use to manage your schedule and (important) email-based conversations efficiently.\n\n### **Who are we?**\n\nWe’re Scott, Travis, and Albrey. We participated in the S24 batch, building Superfilter. During our time building Superfilter, we learned from over 1,000 people about the pain they feel having to manage their inboxes. Our mission is to bring the experience of having a personal assistant to every knowledge worker at 1/100th of the cost. \n\n![uploaded image](/media/?type=post&id=85084&key=user_uploads/1856435/b5abf171-7e63-4c0e-835b-624ec0244d66)\n\n### **How can you help us?**\n\nIf you’re an iPhone and Gmail user, download the product at [tryceejay.com.](http://tryceejay.com)",
        "url": "https://www.ycombinator.com/launches/M8K-ceejay-give-your-inbox-and-calendar-a-brain",
        "votes": 18,
        "created_at": "2024-10-28T16:33:46.810Z"
      },
      {
        "id": 83227,
        "title": "Superfilter - An executive assistant in your pocket",
        "tagline": "Let us manage your inbox so you don't have to.",
        "body": "**TLDR;** We built a companion that manages your inbox with the intelligence of an executive assistant. It never misses an important email, suggests follow up actions, and handles things like meeting coordination and quick replies in one click. [**Sign up here to get access.**](https://bit.ly/superfilter-beta)\n\n### **Who we are?**\n\nHey everyone, we’re [Scott](https://www.linkedin.com/in/willscottmoss/), [Travis](https://www.linkedin.com/in/travis-ueki/), and [Albrey](https://www.linkedin.com/in/albreybrown/). We’re serial entrepreneurs who’ve worked together for almost a decade. Over various roles, we discovered the worst part of work is managing our email inbox. So we built an [assistant](https://bit.ly/superfilter-beta) that handles it for us and are now offering it to you.\n\n![uploaded image](/media/?type=post&id=83227&key=user_uploads/1856435/7eed6456-08d3-4d5f-a796-7b251a1dcc52)\n\n# **The Problem**\n\nIn [_A World Without Email,_](https://www.amazon.com/World-Without-Email-Reimagining-Communication/dp/0525536558) Cal Newport explains that the average knowledge worker spends 30% of their workday managing their inboxes rather than engaging in meaningful work. Cutting this time in half could unlock hundreds of hours of productivity.\n\nWe interviewed founders and executives to understand how they deal with this. We typically heard one of three strategies:\n\n👀 Ignoring email altogether. Super efficient, but results missed opportunities and annoyed customers and friends.\n\n🤝🏿 Hiring an executive assistant. Saves a lot of time, but is very expensive.\n\n✉️ Clients like Superhuman. Affordable, but marginally more efficient than traditional email clients.\n\nWe couldn’t find a solution that was as reliable as an executive assistant and as affordable as a suped-up email client, so we set out to build it.\n\n# **Enter Superfilter**\n\nSuperfilter doesn’t replace your email client. Rather — it connects to your inbox and manages it like your executive assistant. While you’ll use email for strategic work, Superfilter keeps you on top of the tactical stuff.\n\nHere are some of its capabilities users love so far:\n\n**Overviews make sure you never miss an important email**\n\n![uploaded image](/media/?type=post&id=83227&key=user_uploads/1856435/3fc62c41-26dd-4448-83e9-c794bbca2c50)\n\n**Feeds keep track of your to-do’s and FYI’s**\n\n![uploaded image](/media/?type=post&id=83227&key=user_uploads/1856435/aaa241d9-d8ff-416b-99bd-6fdb8798a9a0)\n\n**Tasks let you delegate repetitive work to Superfilter**\n\n![uploaded image](/media/?type=post&id=83227&key=user_uploads/1856435/4cb8b15f-2185-4a51-bde6-24580ca1c2a4)\n\nSuperfilter’s purpose is to give you back time and peace of mind. It’s always working, improves as it learns from you, and will only leave to work for another person if you cancel your subscription.\n\n# **The Ask**\n\nUse the product and give us feedback. We only support iPhone and Gmail (Superhuman and Hey included).\n\n* [**Sign up on our waitlist for early access**](https://bit.ly/superfilter-beta)\n* **Follow us:** Give us a follow on [Twitter &](https://x.com/superfilter_ai) [LinkedIn](https://www.linkedin.com/company/superfilter-ai/)",
        "url": "https://www.ycombinator.com/launches/LeN-superfilter-an-executive-assistant-in-your-pocket",
        "votes": 60,
        "created_at": "2024-08-20T16:53:25.765Z"
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        "id": 82619,
        "title": "Saphira: Vanta for hardware",
        "tagline": "The easiest way to get safety certified.",
        "body": "**tl;dr: Hardware companies** use [Saphira](https://saphira.ai/) to easily **generate safety reports** and **get certified to sell** their product.\n\nWe’re [Oscar](https://www.linkedin.com/in/oavatare/) and [Akshay](https://www.linkedin.com/in/akshaychalana/), and we’ve built software for hardware and compliance at Twitter, Tesla, Amazon, and Hyperloop. \n\nWe’re making it really easy to get **UL, CE, ISO, and TÜV** certifications like **ISO 10218** and **ISO 26262** for hardware products.\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXfgRUpv-5EuNnEHb2YIIuVzkGDYVFRp2ZwD4LryC9TKyufX-m6IO4V8qlC90YErv5esvNgJjWF-CXaxHa1OwaBKHuRCZarwEg_h8aBjzqPVt9kxFd-aQB_m8D_SL7nwOyiLf1k0h07SsyflNQUdd_184BAh?key=Migms48Dt65ISx6x08AVig)\n\n# What are safety certifications, and who needs them?\n\nBuilding **industrial machinery** that can hurt someone, like robot arms and autonomous trucks?  Your **customers will mandate** TÜV safety certification per particular ISO and IEC standards!  \n\nBuilding **small appliances** that plug into the grid?  Many **retailers won’t sell your product,** and **commercial buildings won’t install** it unless you’re UL or CE certified!  \n\nBuilding a **satellite or communication system**?  The **FCC won’t allow** it to operate without certification!\n\nBuilding **defense equipment** for the government?  **They won’t buy** it unless it’s compliant with the relevant MIL-STDs!\n\n# Why did we start Saphira?\n\nHardware products can’t get to market because teams **don’t know how to navigate the certification process**. Unlike SaaS, there are no tools like Vanta that tell you exactly what you need to test, change, and re-evaluate in your designs to pass audits. This sucks because every hardware company we talk to gets stuck in **rework cycles** with their consultants and auditors that they call **“horrendous and intimidating”** (real customer quote).\n\nWe've seen this at Amazon and Tesla, where engineers don't know when a change breaks certification. Each iteration requires them to work with consultants to understand what broke, lengthening the time to launch.\n\nWe created Saphira to empower these innovators to **rapidly** build complex products **that actually work**, all while achieving and maintaining compliance with the **evolving regulatory landscape**.\n\n# What does Saphira do?\n\nSaphira tells you exactly what you need to account for in your **design and testing** to **achieve and maintain** hardware safety certification and compliance. We’re a centralized data source for the **requirements, tests, and standards** that are relevant to your product, making it straightforward to **identify and triage safety and compliance risks** without wasting months of time and thousands of dollars on **slow safety consultants**.\n\nSaphira automates **traceability**: regulatory reports by engineers that prove that requirements like “the robot arm won’t shock an attendant if touched while in motion” were implemented and validated. These reports are **painful and tedious** to produce. By maintaining references to all necessary source information, Saphira can automatically generate these reports, and even automatically identify which additional standard clauses are relevant to each requirement or design value.\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXfaxD8bMvNCW5gDewAe4uowrZviZqV3i00DsW2NM-2eVsuZCkRj_4t0oGKIJljGp0GTnS_AFmLlm1qLNUF4teYn5VTi6ZDyM1HtM1Vl56x3t0O4AKTWSq6FtmddRQWAtpes92noQLkImJgftBhWOqOKmWf0?key=Migms48Dt65ISx6x08AVig)\n\n# Who is Saphira for?\n\nSaphira is for engineers at hardware organizations of any scale and size:\n\n* The **safety engineering team** at an industrial robotics company can use Saphira’s **compliance report generator** (i.e. ISO-12100 and ISO-10218) to **achieve certification** to operate in the US.\n* An **engineering leader** at a hardware startup that needs UL certs to sell to more customers can use Saphira to speed up their process by months by avoiding hiring a slow safety consultant. \n* A **systems engineer** at an aerospace/defense company can use Saphira’s **AI tooling** to understand **how various military and government standards** (such as MIL-STD-810 or ISO-26262) are relevant to each facet of their specs and models.\n\n# Ask\n\n* We are experts in certifications for hardware companies.  If you think you might need this but aren't sure how to approach it, we are happy to help for free — [just reach out](mailto:akshay@saphira.ai).\n* If you know other engineering leaders seeking to improve their certification processes, [connect us](mailto:akshay@saphira.ai)! We are most interested in talking to leaders in industrial robotics, energy systems, autos, aeros, and defense. \n* If you worked at a larger hardware company before and saw any of these issues, we would love to talk just to learn from your experience\n* We would love product feedback: [book a demo](https://calendly.com/ac2zoom/30min)!",
        "url": "https://www.ycombinator.com/launches/LUZ-saphira-vanta-for-hardware",
        "votes": 81,
        "created_at": "2024-07-31T18:47:18.084Z"
      },
      {
        "id": 81405,
        "title": "Saphira AI - Orchestrating safe hardware engineering",
        "tagline": "Intelligent engineering design management for safety-critical products",
        "body": "**tl;dr:** We capture **requirements and design** in a central platform so that safety for complex physical products can be continuously evaluated: a simple and easy-to-use alternative to Jama or IBM DOORS.\n\nWe’re [Oscar](https://www.linkedin.com/in/oavatare/) and [Akshay](https://www.linkedin.com/in/akshaychalana/), and we’ve built hardware controls and virtualization for Tesla, Amazon, and Hyperloop. We’ve blown up prototypes and fried lasers by not applying effective system design and are building tools to make it easier to prevent such failures.\n\n![uploaded image](/media/?type=post&id=81405&key=user_uploads/1549881/efe6234d-8f86-4d19-b499-4fc3380514eb)\n\n# Why did we start Saphira?\n\nWhile building Hyperloop pods, we struggled with unusual and novel constraints: we had to take the propulsion, braking, and electronics of a sophisticated train and make them work perfectly in a vacuum chamber. Basic things that work in the normal world just didn’t there: network activity was severely throttled so remote control and telemetry were difficult, and electronics would arc more easily, requiring additional protections. This mandated that we put together clear **product requirements** that we needed to integrate and validate across the entire implementation stack, which turned out to be so hard that we struggled to get our pods working in time and faced weeks of all-nighters just to fail review and be barred from the race!  \n\nSince then, we’ve been searching for how large organizations we’ve been part of, like Tesla and Amazon, have made this easier: in truth, they haven’t! The most mature, most established industries, such as aerospace, account for this with **process**: intensive modeling, documentation, and data entry that **innovators don’t have time for**. When regulation and certification standards are put in place, **products are taken off the market or endure years-long delays**. \n\nWe created Saphira to empower these innovators to rapidly build complex products **that actually work**, all while achieving and maintaining compliance with the **evolving regulatory landscape**.\n\n![](https://lh7-us.googleusercontent.com/docsz/AD_4nXc5i1avhrYfKOrHWzQzEyt6C88KBCZnFtCGL4YRw6nTaPipxU2-cXEpcxY4d9qHtMD0sO84I2xragUNrmUAdAju9BAD-HWgoS54BIUZX2U-bNV4n_cv0WnQwgnTq-zsSdo5Vf-6L6h8SJ0dKuJoPWOEygG3?key=Ebyb5ZyTMv3M7lBQpS9B7Q)\n\n# What does Saphira do?\n\nSaphira is a **single source of truth** where requirements, architecture, and tests can all be entered, parsed from existing documents, and tied together so that safety risks are identified and triaged quickly.\n\nSaphira is the easiest way to demonstrate **traceability**: regulatory reports by engineers that prove that requirements like “the Hyperloop pod must not catch fire in a vacuum chamber” were implemented and validated. These reports are painful and tedious to produce: by maintaining references to all the source information for them, Saphira can automatically generate them! Most importantly, Saphira removes systems engineers as a bottleneck to updating foundational engineering data, enabling any engineer to model and report on safety and compliance, making traceability easy for any fast-moving team.\n\n![](https://lh7-us.googleusercontent.com/docsz/AD_4nXe_cgZGZGZLN8qYxQsHQhSKZbvtyL0vH1UGAAEu8uQr02TBKvptPzordelrm_y0Ltrns4l7GOCUsEjQYy1F8l1igdLtVx85IywthG9bRGS6CsAQI9zTzAVYbLV6aIdKlFwj64DEsu2_hGe-PMGeew_SbAl2?key=Ebyb5ZyTMv3M7lBQpS9B7Q)\n\nUltimately, we see traceability as not just a regulatory requirement but an enabler for automated engineering: as engineers define the relationships we use to sync data between, say, their codebase and task management system, this can be used to automatically propagate changes across an entire system! For example, one could change the requirement for a motor to produce 200 Nm of torque to 300 Nm: since they had linked this through a formula in Saphira to the current draw requirement from the battery, we would automatically update that in the power distribution PCB schematics, short-circuiting hours of work per change!\n\n# Who is Saphira for?\n\nSaphira is for engineers at innovative companies designing and building safety-critical hardware and software systems at organizations of any size:\n\n* The **safety engineering team** at an industrial robotics company can use Saphira’s **compliance report generator** (i.e. ISO-12100 and ISO-10218) to **achieve certification** to operate in the US a year faster than it otherwise would be able to.\n* A **systems engineer** at an AV startup can use Saphira’s test management framework to perform **release safety reviews** 50% faster and double their pace of software iteration.\n* The **head of hardware** responsible for **writing product requirements** at an energy startup that makes residential batteries can use Saphira’s **AI tooling** to parse design documents and generate supplier specifications in half the time to get faster quotes from prospective manufacturers and ship to customers sooner.\n\n# Ask\n\n* If you are seeking an engineering/application lifecycle management, requirements management, or systems engineering tool for your hardware company, [let’s talk](mailto:akshay@saphira.ai)!\n* If you know other engineering leaders seeking to improve their processes, [connect us](mailto:akshay@saphira.ai)! We are most interested in talking to leaders in industrial robotics, energy systems, autos, aeros, and defense. \n* If you worked at a larger hardware company before and saw any of these issues, we would love to talk just to learn from your experience\n* We would love product feedback: [book a demo](https://calendly.com/ac2zoom/30min)!",
        "url": "https://www.ycombinator.com/launches/LAz-saphira-ai-orchestrating-safe-hardware-engineering",
        "votes": 113,
        "created_at": "2024-06-10T15:48:04.873Z"
      }
    ]
  },
  {
    "id": 29596,
    "name": "Comfy Deploy",
    "slug": "comfy-deploy",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/8a731bcc797807541c6c51d10993125ff2f77823.png",
    "website": "https://comfydeploy.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "ComfyUI is the most popular open-source framework to build media generation workflows. However, it's a single-player experience that needs to run on a local GPU. Everyone has different environments and sharing workflows to someone else can take days to get setup.\r\n\r\nComfy Deploy fixes this by creating a collaborative workspace, where a teams environemnt, models and workflows can be shared as easily with a link.\r\n\r\n**Team ComfyUI workspace**\r\n\r\n• Replacing cobbled-together solutions with a unified, team-focused environment. When it works for you, you can be sure it works for your team.\r\n\r\n• Eliminate \"works on my machine\" issues with version control.\r\n\r\n• Share storage for models and outputs.\r\n\r\n• Leverage the power of ComfyUI without the complexities of self-hosting\r\n\r\n**Powerful GPU Infrastructure**\r\n• Access managed GPUs that grow with your teams needs\r\n\r\n• Tailor the platform to your requirements by easily installing custom nodes and models\r\n\r\n\r\n**Custom configuration**\r\n\r\n• Download the models you want, stored privately in your personal volume\r\n\r\n• Install the custom nodes your workflow needs\r\n\r\n• Train models on your own datasets.\r\n\r\n\r\n**API Deployments: From workflow to production in seconds**\r\n\r\n• Transform any workflow into a fully functional API immediately without extra engineering\r\n\r\n• Comprehensive observability on every run\r\n\r\n• Built-in API authentication\r\n\r\n• TS/JS/Python/Ruby SDKs for seamless integration\r\n",
    "one_liner": "ComfyUI for everyone on your team",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1721586531,
    "tags": [
      "Media"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/comfy-deploy",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/comfy-deploy.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/comfy-deploy",
    "x_url": "https://x.com/comfydeploy",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/comfy-deploy",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/8a731bcc797807541c6c51d10993125ff2f77823.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
    },
    "founders": [
      {
        "user_id": 1100490,
        "full_name": "Nicholas Kao",
        "title": "Founder/CEO",
        "founder_bio": "Building an image generation platform.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/nick-kao-468540174/",
        "x_url": "https://twitter.com/nicholaskkao",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7d3473ace5b059fce9ce86571237c719520c6520.jpg"
      }
    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 82360,
        "title": "Comfy Deploy - ComfyUI for product teams",
        "tagline": "The best way for product teams to build and tailor AI video and image workflows using ComfyUI, then instantly deploy those workflows as APIs.",
        "body": "**Tl;dr: ComfyDeploy is the best way for product teams to build and tailor AI video and image workflows using ComfyUI, which can instantly deploy custom workflows as APIs.**\n\nHey everyone, we're Nick and Benny, the team building [Comfy Deploy](https://comfydeploy.com/).\n\n![uploaded image](/media/?type=post&id=82360&key=user_uploads/1100490/8f04abf6-fad0-4b26-a47e-787c90a1d353)\n\n**Problem**\n\nProduct teams struggle to build AI video and images in their workflows using fragmented tools and inflexible controls from off-the-shelf solutions. ComfyUI is a powerful tool that solves this and gives control back to the user, but there are challenges for teams to use it.\n\n1. Complex Self-Hosting: Setting up and maintaining ComfyUI for teams is technically demanding and time-consuming, distracting teams from their core product development.\n2. Collaboration: ComfyUI wasn't built for teams, making it challenging to share, edit, and run workflows between team members\n3. Hardware Limitations: Running complex AI workflows requires powerful GPUs.\n4. Slow Deployments: Deploying ComfyUI workflows as scalable, production-ready APIs requires significant engineering effort.\n\n**Solution**\n\nWe’ve created the best way for product teams to use ComfyUI to build and tailor their AI image and video workflows with ComfyUI.\n\nKey Benefits:\n\n* Managed platform: Managed ComfyUI workspace, which can install any custom node and model.\n* Team Collaboration:  Work together seamlessly with a team workspace designed for sharing, editing, and running workflows across your team.\n\n![](https://lh7-us.googleusercontent.com/docsz/AD_4nXcNRhTqv7BviU3qfODU-KaFSok52ydkxWCrMV813y5m-skIialDxcdGtRwCbzf5A0010pone4K9hksZ6T6jXMFnnKzfcXePzLSyxDBGPRgC8Be93EFNBvXiwIOntNTRn7h8YEgTTBrKW-KDdGvwK347o7qx?key=rJuA09IIbMJlhk3fsFUSzQ)\n\n* Scalable Infrastructure: Powerful cloud GPUs on-demand, with auto-scaling to grow with your team's needs.\n* Instant Deployment: Transform your ComfyUI workflows into scalable, production-ready APIs with just one click; no additional engineering required, with multi-language SDKs.\n\n![](https://lh7-us.googleusercontent.com/docsz/AD_4nXc-5ZvNaanpRaps6zvQgIoHsV0fSEbCQ_RLAiUc36ghCGQPPGFGZJ6zHcEuiFmX982pwWewX8QCbvZxc8QxDid-u-wV3-XJBktmUpkeD_pLsnlY_GFY_oMnmz8kcjHEl-Zq1OJ4xhGWrb56FM8ejUl9pMZ3?key=rJuA09IIbMJlhk3fsFUSzQ)\n\nSome wins and testimonials from our users\n\n* _Production time is now up to 300% faster. Producing a complete character pack for Mighty Action Heroes used to take 6 man-weeks. It now takes 1.5 man-week_ - Ben, Chief AI officer, Mighty Bear Games.\n* _ComfyDeploy has laid a lot of the groundwork for us, allowing us to move quickly and save on our engineering budget which is crucial in our fast-paced environment. 10/10, I would highly recommend it_ - Javid, CEO, Secret Desires.\n* _Comfy Deploy comes in and addresses the main barrier to using ComfyUI while also taking it a step further and allowing us to deploy our unique ComfyUI workflows. This allows us to seamlessly integrate image generation into our product, freeing up time to focus on developing our product. Comfy Deploy also comes with tools for sharing, editing, and managing workflows in a collaborative environment, enabling more of our team to get involved in the process of building image generation processes_ - E, AI Applied Engineer, VC backed in stealth.\n\n**How it works**\n\nAccess our managed ComfyUI environment, with pre-configured machines and models. Share and manage your workflows in your team, install custom nodes and models as needed. Deploy your workflows instantly as API and integrate them into your products. \n\n![uploaded image](/media/?type=post&id=82360&key=user_uploads/1100490/6aed708b-21a8-4dcf-a827-596e0f48e13e)\n\n**Why we’re building this**\n\nProduct teams have much to gain from owning and iterating on their own AI pipelines. Benny created the v1 of Comfy Deploy when, as CTO at his previous startup, he saw the issues with the handoff between applied AI artists and engineering. We think this is an exciting tool for product teams to take the first step and develop their skill sets and capabilities with these exciting new tools.\n\n\\\n**The Offer 🤝**\n\nIf your team is interested in using the best way to use ComfyUI for product teams, sign up for a free trial here at <https://www.comfydeploy.com/> and schedule an on-boarding call with us <https://cal.com/team/comfy-deploy/onboarding-call>\n\nContact us at [founders@comfydeploy.com](mailto:founders@comfydeploy.com)",
        "url": "https://www.ycombinator.com/launches/LQO-comfy-deploy-comfyui-for-product-teams",
        "votes": 30,
        "created_at": "2024-07-23T15:22:01.808Z"
      }
    ]
  },
  {
    "id": 29610,
    "name": "Hamming AI",
    "slug": "hamming-ai",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/63f48bd5017efb50e1fd3bcb1bd32b4b6a0147e3.png",
    "website": "https://hamming.ai/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Hamming AI is the complete QA platform for voice agents from pre-deployment testing to production monitoring. \r\n\r\n4M+ calls tested. 10K+ agents monitored. Trusted by public companies and the fastest-growing voice AI teams.\r\n\r\nConnect your agent, auto-generate test scenarios, and run thousands of test calls in minutes. In production, monitor every call with 50+ built-in metrics and get alerts before customers notice.\r\n\r\nSumanyu (CEO) was previously Head of Data at Citizen and Senior Staff Data Scientist at Tesla, where he grew AI-powered sales to hundreds of millions in revenue per year. \r\n\r\nOur engineering team ranks #1 on Weave (https://workweave.ai) across 10,000+ engineers and 100+ teams.",
    "one_liner": "Complete QA platform for voice agents",
    "team_size": 10,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1715007777,
    "tags": [],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Partly Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/hamming-ai",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/hamming-ai.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/hamming-ai/",
    "x_url": "https://twitter.com/HammingAI",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/hamming-ai",
    "github_url": "https://github.com/HammingHQ/",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/63f48bd5017efb50e1fd3bcb1bd32b4b6a0147e3.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "Gustaf Alstromer",
      "url": "https://www.ycombinator.com/people/gustaf-alstromer"
    },
    "founders": [
      {
        "user_id": 497858,
        "full_name": "Sumanyu Sharma",
        "title": "Founder/CEO",
        "founder_bio": "Sumanyu is the founder & CEO at Hamming AI. Hamming AI is a complete QA platform for voice agents from pre-deployment testing to production monitoring.\n\nPreviously helped Citizen grow its MAU by 4X and helped bootstrap revenue from 0 to millions in ARR in under 6 months.\n\nBefore that, grew an AI-powered sales program @ Tesla to 100s of millions in revenue/year as a Senior Staff Data Scientist.\n\nPublished a first-author paper in AI during undergrad. BASc from UWaterloo w/ dean's list.\n\n",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/sumanyusharma",
        "x_url": "https://twitter.com/sumanyu_sharma",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/de00b2b7b6033630137d2dd223d65b2ea927ea6c.jpg"
      }
    ],
    "jobs": [
      {
        "id": 69910,
        "title": "Product Engineer",
        "url": "https://www.ycombinator.com/companies/hamming-ai/jobs/XTCQPuO-product-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$140K - $200K",
        "equity_range": "0.05% - 0.20%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Node.js",
          "React",
          "TypeScript",
          "Next.js"
        ]
      },
      {
        "id": 69911,
        "title": "Backend / Infra Engineer",
        "url": "https://www.ycombinator.com/companies/hamming-ai/jobs/gxWsyHb-backend-infra-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Backend",
        "salary_range": "$140K - $200K",
        "equity_range": "0.05% - 0.20%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Node.js",
          "Python",
          "Distributed Systems"
        ]
      }
    ],
    "news": [
      {
        "title": "Hamming AI Raises $3.8M Seed Round | Hamming AI Blog",
        "url": "https://hamming.ai/blog/hamming-ai-seed-funding-to-make-voice-agents-more-reliable",
        "date": "Dec 18, 2024"
      },
      {
        "title": "Hamming.ai raises $3.8 million for AI voice agent testing platform",
        "url": "https://www.axios.com/pro/media-deals/2024/12/18/hamming-ai-voice-agent-testing",
        "date": "Dec 18, 2024"
      }
    ],
    "launches": [
      {
        "id": 82717,
        "title": "🕵️ Hamming - Automated AI voice agent testing",
        "tagline": "AI voice agent reliability platform: AI voice agent testing, prompt tuning, evals, call analytics",
        "body": "👋 [@Sumanyu Sharma](https://www.linkedin.com/in/sumanyusharma) and [@Marius Buleandra](https://www.linkedin.com/in/mariusbuleandra) from [@Hamming AI](https://www.ycombinator.com/companies/hamming-ai)\n\n**TLDR:** Are you testing your voice agents by hand? We're launching [Automated AI voice agent testing](https://app.hamming.ai/voice-demo) to automatically test your voice agents and flag quality issues in development and production.\n\n🌟 [Click here to try our free Voice Simulations Demo](https://app.hamming.ai/voice-demo) 🌟\n\n## Problem: Making voice agents reliable feels like whack-a-mole\n\nHere's the workflow most teams follow:\n\n1. **Call** your voice agent by hand and find bugs. Slow and ad-hoc.\n2. **Tweak** your voice agents by adding new tools and changing the prompts or models to fix the bugs.\n3. **Call again** to see if the changes worked.\n4. **Detect** regressions when users complain of things breaking in production.\n5. **Repeat** steps 1 to 4 until you get tired.\n\n**Calling your voice agent & finding bugs** is the slowest & most painful part of the feedback loop. This is what we automate.\n\n## Our take: Character AI for voice testing\n\nWe create hundreds of characters that simulate how **real users interact with your voice agents** in real life. For every call, we measure whether our character successfully accomplishes the task (e.g., ordering a vegan burger, canceling next week’s appointment, etc.).\n\nOur automated AI voice agent testing approach is 100x faster, cheaper, and more thorough than manual testing.\n\n![uploaded image](/media/?type=post&id=82717&key=user_uploads/497858/87b2fbc7-5137-46e5-a948-80b440eba8a6)\n\n### Flag errors & Tag calls in production\n\nYou can log all call transcripts and traces within Hamming. We actively **tag your production calls** in real-time, and flag cases the team needs to double-click on. This helps engineering teams quickly prioritize cases they need to fix.\n\n**Example tags**: human detects that the bot is an AI, a follow-up call is needed, the user requested an urgent appointment, etc.\n\n![uploaded image](/media/?type=post&id=82717&key=user_uploads/497858/7bf685f0-5348-4c0e-863f-90e3bd4e3f9f)\n\n### Test new changes quickly\n\n**Simulation-driven development**\n\nLet’s imagine you’re building an agent called ‘YC Founder’; we can spin up 100s of VC agents who will try to distract you. You can edit the prompts or models and re-run the simulation to make sure you made progress.\n\nWant to see how you would handle a persistent investor? Try our ‘VC trying to distract founders’ free [demo here](https://app.hamming.ai/voice-demo).\n\n![uploaded image](/media/?type=post&id=82717&key=user_uploads/497858/a39b0c3e-107d-4808-9096-30dbae4ad3f4)\n\n**Easily create new characters from call transcripts**\n\nWhen customers complain about a bad call, you can locate the call transcript and create a new character in one click. Make a change to your prompt, and then run the simulations to ensure you addressed the bad call.\n\n![uploaded image](/media/?type=post&id=82717&key=user_uploads/497858/cc3e6632-f482-47f5-aee6-2511b34d441d)\n\n## Meet the team\n\n[Sumanyu](https://www.linkedin.com/in/sumanyusharma/) previously helped Citizen (safety app; backed by Founders Fund, Sequoia, 8VC) grow its users by 4X and grew an AI-powered sales program to $100s of millions in revenue/year at Tesla.\n\n[Marius](https://www.linkedin.com/in/mariusbuleandra/) previously ran data infrastructure @ Anduril, drove user growth at Citizen with Sumanyu and was a founding engineer @ Spell (MLOps startup acquired by Reddit).\n\n![uploaded image](/media/?type=post&id=82717&key=user_uploads/497858/92a125e1-9612-4c4f-bb2d-1ab88aa9b24a)\n\n# Summary\n\nWe previously launched [Prompt Optimizer](https://www.ycombinator.com/launches/L4V-hamming-let-ai-optimize-your-prompts-free-for-7-days) and [AI Experimentation Tools](https://www.ycombinator.com/launches/LHa-hamming-make-your-rag-ai-agents-reliable) to automate prompt engineering and make RAG pipelines more robust. In this launch, we show how you can test your voice agents quickly.\n\n![uploaded image](/media/?type=post&id=82717&key=user_uploads/497858/674bd4d5-4041-4466-821e-f62328e440c4)\n\n# Our offer\n\n**Personalized characters + 100 free calls.** Struggling to make your voice agents reliable? We’ll create personalized characters and call + stress test your system \\~100 times for free. Book time with us [here.](https://calendly.com/sumanyusharma/1-1-debug-session)\n\nQuestions? Email us [here](mailto:sumanyu@hamming.ai) or chat with us [here](https://calendly.com/sumanyusharma/30min).",
        "url": "https://www.ycombinator.com/launches/LW9-hamming-automated-ai-voice-agent-testing",
        "votes": 57,
        "created_at": "2024-08-05T01:45:12.663Z"
      },
      {
        "id": 81814,
        "title": "🚀 Hamming - Make your RAG & AI agents reliable",
        "tagline": "The only end-to-end AI development platform you need: prompt management, evals, observability",
        "body": "👋 [@Sumanyu Sharma](https://www.linkedin.com/in/sumanyusharma) and [@Marius Buleandra](https://www.linkedin.com/in/mariusbuleandra) from [@Hamming AI](https://www.ycombinator.com/companies/hamming-ai)\n\n**TLDR:** Are you struggling to make your RAG & AI agents reliable? We're launching our [AI Optimization Platform](https://app.hamming.ai) to help eng teams speed up iteration velocity, root-cause bad AI outputs, and prevent regressions.\n\n🌟 [Click here to try our AI Optimization Platform](https://app.hamming.ai) 🌟\n\n## Our thesis: Experimentation drives reliability\n\nPreviously, [Marius](https://www.linkedin.com/in/mariusbuleandra/) and I ran growth-focused eng and data teams at Tesla, Citizen, Spell & Anduril. We learned that running experiments is the best way to move a metric. More experiments = more growth.\n\nLast year, we shipped 10+ RAG & AI agents to production. We found the same pattern holds when building reliable AI products. More experiments = more reliability = more retention for your AI products.\n\n![uploaded image](/media/?type=post&id=81814&key=user_uploads/497858/96653f00-344f-46b7-92da-7530f0302ae0)\n\n## Problem: Making RAG and AI agents reliable feels like whack-a-mole\n\nHere's the workflow most teams follow:\n\n1. **Tweak** your RAG or AI agents by indexing new documents, adding new tools, changing the prompts, models or other business logic.\n2. **Eyeball** how well your changes improved a handful of examples you wanted to fix. Often ad-hoc and slow.\n3. **Ship** the changes if they worked.\n4. **Detect** regressions when users complain of things breaking in production.\n5. **Repeat** steps 1 to 4 until you get tired.\n\nSteps 2 and 4 are often the slowest & most painful parts of the feedback loop. This is what we tackle.\n\n## Our take: Use LLMs as judges to speed up iteration velocity\n\nWe use LLMs to score the outputs of other LLMs. This is the fastest way to speed up the feedback loop.\n\n![uploaded image](/media/?type=post&id=81814&key=user_uploads/497858/1e6dff78-03d8-4add-9a74-7382a9733147)\n\n![uploaded image](/media/?type=post&id=81814&key=user_uploads/497858/46cb1626-03be-4b9e-9218-c86aa4794b1f)\n\n### Flag errors in production before customers notice\n\nWe go beyond passive LLM / trace-level monitoring. We actively **score your production outputs** in real time and **flag cases** the team needs to double-click on. This helps eng teams quickly prioritize cases they need to fix.\n\n![uploaded image](/media/?type=post&id=81814&key=user_uploads/497858/69edba93-dfb5-448d-8215-c3f3cb81402b)\n\n### Test new changes quickly while developing and prevent regressions from reaching users\n\nWe make offline evaluations easy, so you can change your system and get feedback in minutes.\n\n**Eval-driven prompt iteration**\n\nRapidly iterate with new prompts and models in our prompt playground with first-class support for function-calling. Run evals so you know your changes are improving things.\n\n![uploaded image](/media/?type=post&id=81814&key=user_uploads/497858/89972e98-9709-47b1-b887-7c02a1af51a1)\n\n**Deploy prompt changes without code change**\n\nWe keep track of all prompt versions and update your prompts on the fly without needing a code change.\n\n![uploaded image](/media/?type=post&id=81814&key=user_uploads/497858/94c56689-bac3-4e05-bb13-22234edce861)\n\n**Easily create golden datasets**\n\nOffline evaluations are bottlenecked on a high-quality golden dataset of input/output pairs. We support converting production traces to dataset examples in one click.\n\n![uploaded image](/media/?type=post&id=81814&key=user_uploads/497858/4d849d21-b8e6-4beb-8617-215296de422a)\n\n**Diagnose between retrieval, reasoning or function-calling errors quickly**\n\nDifferentiating between retrieval, reasoning, and function-calling errors is time-consuming. We score each retrieved context on metrics like hallucination, recall, and precision to help you prioritize your eng efforts where it matters.\n\n![uploaded image](/media/?type=post&id=81814&key=user_uploads/497858/afb539a0-1a67-4050-8733-387b03a536e6)\n\n**Override AI scores**\n\nSometimes our AI scores disagree with your definition of \"good\". We make it easy to override our scores with your preferences. Our AI scorer learns from your feedback.\n\n![uploaded image](/media/?type=post&id=81814&key=user_uploads/497858/8227f0e2-e20d-4d2b-8ab6-aa413ec7efe6)\n\n## Meet the team\n\n[Sumanyu](https://www.linkedin.com/in/sumanyusharma/) previously helped Citizen (safety app; backed by Founders Fund, Sequoia, 8VC) grow its users by 4X and grew an AI-powered sales program to $100s of millions in revenue/year at Tesla.\n\n[Marius](https://www.linkedin.com/in/mariusbuleandra/) previously ran data infrastructure @ Anduril, drove user growth at Citizen with Sumanyu and was a founding engineer @ Spell (MLOps startup acquired by Reddit).\n\n![Sumanyu & Marius](https://bookface.ycombinator.com/media/?type=post&id=81814&key=user_uploads/497858/750619c5-790d-4ba7-a4a4-e60c8f520506)\n\n## Our offer\n\nWe previously launched [Prompt Optimizer](https://www.ycombinator.com/launches/L4V-hamming-let-ai-optimize-your-prompts-free-for-7-days) on launch YC, which saves 80% of manual prompt engineering effort. In this launch, we show how teams use Hamming to build reliable RAG and AI agents.\n\n![uploaded image](/media/?type=post&id=81814&key=user_uploads/497858/234292dd-27c0-4073-8082-7fc0340f1221)\n\n**Free 1:1 Debug session.** Struggling with making your RAG/agents reliable? We're offering a complementary 1:1 RAG/agent debugging session. Book time with us [here.](https://calendly.com/sumanyusharma/1-1-debug-session)\n\nQuestions? Email us [here](mailto:sumanyu@hamming.ai) or chat with us [here](https://calendly.com/sumanyusharma/30min).",
        "url": "https://www.ycombinator.com/launches/LHa-hamming-make-your-rag-ai-agents-reliable",
        "votes": 118,
        "created_at": "2024-06-28T01:28:56.750Z"
      },
      {
        "id": 81003,
        "title": "🚀 Hamming - Let AI optimize your prompts (free for 7 days)",
        "tagline": "Automate 90% of manual prompt engineering using our self-improving prompt optimizer.",
        "body": "👋 Sumanyu and Marius from [Hamming AI](https://www.ycombinator.com/companies/hamming-ai); we're part of the upcoming S24 batch!\n\n**TLDR:** Are you spending a lot of time optimizing prompts by hand? We're launching our [Prompt Optimizer](https://app.hamming.ai/prompt-optimizer) (new feature in beta) to automate prompt engineering. It's completely free for 7 days!\n\n🌟 [Click here to try our Prompt Optimizer](https://app.hamming.ai/prompt-optimizer) 🌟\n\n## Convert your task into an optimized prompt in minutes\n\n![uploaded image](/media/?type=post&id=81003&key=user_uploads/497858/ea14e339-7092-4166-b6c5-53b667cd5b5b)\n\n**Thought experiment:** What if we used LLMs to optimize prompts for other LLMs?\n\n![Meme](/media/?type=post&id=81003&key=user_uploads/497858/d24f5e83-d01f-433c-96fb-35b209c44b78)\n\n## Problem: Writing prompts by hand is tedious\n\nWriting high-quality and performant prompts by hand requires enormous trial and error. Here's the usual workflow:\n\n1. **Write** an initial prompt.\n2. **Measure** how well it performs on a few examples in a prompt playground. Bonus points if you use an experimentation platform like [Hamming](https://hamming.ai) to automate this flow.\n3. **Tweak** the prompt by hand to handle cases where it's failing.\n4. **Repeat** steps 2 & 3 until you get tired of wordsmithing.\n\nWhat's worse, new model versions often break previously working prompts. Or, say you want to switch from OpenAI GPT3.5 Turbo to Llama 3. You need to re-optimize your prompts by hand. ❌\n\n## Our take: use LLMs to write optimized prompts\n\nDescribe your task, add examples, or let us synthetically create some, and click run.\n\n![Prompt Optimizer Demo](https://hamming.ai/images/prompt-optimizer-demo-2-trimmed.gif)\n\nBehind the scenes, we use LLMs to generate different prompt variants. Our LLM judge measures how well a particular prompt solves the task. We capture outlier examples and use them to improve the few-shot examples in the prompt. We run several \"trials\" to refine the prompts iteratively.\n\n**Benefits:**\n\n* No more tedious word-smithing.\n* No more scoring outputs by hand.\n* No need to remember to tip your LLM or ask it to think carefully step-by-step.\n\n## Meet the team\n\n[Sumanyu](https://www.linkedin.com/in/sumanyusharma/) previously helped Citizen (a safety app; backed by Founders Fund, Sequoia, 8VC) grow its users by 4X and grew an AI-powered sales program to $100s of millions in revenue/year at Tesla.\n\n[Marius](https://www.linkedin.com/in/mariusbuleandra/) previously ran data infrastructure @ Anduril, drove user growth at Citizen with Sumanyu, and was a founding engineer @ Spell (an MLOps startup acquired by Reddit).\n\n![Sumanyu & Marius](/media/?type=post&id=81003&key=user_uploads/497858/750619c5-790d-4ba7-a4a4-e60c8f520506)\n\n## Our ask\n\nIn this launch, we showed how we help teams optimize each prompt. In our next launch, we'll walk through how teams use Hamming to optimize their entire AI app.\n\n* **Feedback.** We want you to throw real-world tasks at our optimizer and tell us what's working and where we can improve.\n* **Warm intros.** We'd love intros to anyone you know who writes a lot of prompts by hand or cares about solving AI reliability (including you!)\n\n![uploaded image](/media/?type=post&id=81003&key=user_uploads/497858/d11a6a2d-9b13-471e-974a-332f7ef5bc2f)\n\n## Email us [here](mailto:sumanyu@hamming.ai).\n\n## Book time on our [calendly](https://calendly.com/sumanyusharma/30min).",
        "url": "https://www.ycombinator.com/launches/L4V-hamming-let-ai-optimize-your-prompts-free-for-7-days",
        "votes": 84,
        "created_at": "2024-05-21T16:25:15.789Z"
      }
    ]
  },
  {
    "id": 29623,
    "name": "Entangl",
    "slug": "entangl",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/5593913bae70a1285b652709232688417e1071ac.png",
    "website": "https://www.entangl.com/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Entangl uses AI to detect and automatically resolve issues in data center engineering and operations, ensuring efficiency and uptime. ",
    "one_liner": "Find & resolve issues in data center engineering & operations using AI",
    "team_size": 22,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1716219164,
    "tags": [
      "Enterprise Software",
      "Infrastructure",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Growth",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/entangl",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/entangl.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/entangl",
    "x_url": "https://twitter.com/Entangl_AI",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/entangl",
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/5593913bae70a1285b652709232688417e1071ac.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "Tom Blomfield",
      "url": "https://www.ycombinator.com/people/tom-blomfield"
    },
    "founders": [
      {
        "user_id": 533860,
        "full_name": "Shapol M",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder & CEO at Entangl. ",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/shapol",
        "x_url": "https://twitter.com/Shapol_m",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7d51f52ae31d3904f1480fb565c673d80836be24.jpg"
      }
    ],
    "jobs": [
      {
        "id": 93501,
        "title": "Jony Ive",
        "url": "https://www.ycombinator.com/companies/entangl/jobs/Mmxt1jv-jony-ive",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Design",
        "role_type": "Web design",
        "salary_range": "$120K - $180K",
        "equity_range": "1.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "JavaScript",
          "Figma",
          "Svelte"
        ]
      },
      {
        "id": 93502,
        "title": "Jony Ive",
        "url": "https://www.ycombinator.com/companies/entangl/jobs/snSaa27-jony-ive",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Frontend",
        "salary_range": "$120K - $180K",
        "equity_range": "1.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "TypeScript",
          "Figma",
          "Svelte"
        ]
      },
      {
        "id": 97599,
        "title": "Bill McDermott (Account Executive)",
        "url": "https://www.ycombinator.com/companies/entangl/jobs/7WIZ9Gt-bill-mcdermott-account-executive",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$150K - $300K",
        "equity_range": "0.10% - 1.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 97630,
        "title": "Greg Brockman",
        "url": "https://www.ycombinator.com/companies/entangl/jobs/s6zm6uT-greg-brockman",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$150K - $200K",
        "equity_range": "0.10% - 1.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 98981,
        "title": "Account Executive",
        "url": "https://www.ycombinator.com/companies/entangl/jobs/JwshcnN-account-executive",
        "location": "San Francisco, CA, US / Remote (US)",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$130K - $350K",
        "equity_range": "0.10% - 1.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 98982,
        "title": "Sales Development Rep (SDR)",
        "url": "https://www.ycombinator.com/companies/entangl/jobs/ffkLbxN-sales-development-rep-sdr",
        "location": "San Francisco, CA, US / Remote (US)",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$70K - $100K",
        "equity_range": "0.10% - 1.00%",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 110929,
        "title": "Full Stack Engineer",
        "url": "https://www.ycombinator.com/companies/entangl/jobs/CJBPxvX-full-stack-engineer",
        "location": "San Francisco, CA, US / SG / Remote (US; SG)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$120K - $180K",
        "equity_range": "0.10% - 1.00%",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 111026,
        "title": "Full Stack Engineer",
        "url": "https://www.ycombinator.com/companies/entangl/jobs/nu9J4uA-full-stack-engineer",
        "location": "New York, NY, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$120K - $180K",
        "equity_range": "0.10% - 1.00%",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 111027,
        "title": "Full Stack Engineer",
        "url": "https://www.ycombinator.com/companies/entangl/jobs/Jn36xh5-full-stack-engineer",
        "location": "Boston, MA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$120K - $180K",
        "equity_range": "0.10% - 1.00%",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 111028,
        "title": "Full Stack Engineer",
        "url": "https://www.ycombinator.com/companies/entangl/jobs/kLor7KK-full-stack-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$120K - $180K",
        "equity_range": "0.10% - 1.00%",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 111290,
        "title": "Executive Assistant",
        "url": "https://www.ycombinator.com/companies/entangl/jobs/gzwUmD9-executive-assistant",
        "location": "San Francisco, CA, US / Remote (US)",
        "type": "Full-time",
        "role": "Operations",
        "role_type": null,
        "salary_range": "$90K - $140K",
        "equity_range": "",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      }
    ],
    "news": [],
    "launches": []
  },
  {
    "id": 29633,
    "name": "Unsloth AI",
    "slug": "unsloth-ai",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/821f8850dee6e9f14ef87d19a86abcd55976c80c.png",
    "website": "https://unsloth.ai/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Unsloth helps builders create custom models better & faster using RL and custom kernels. We're developing the all in one solution to help you create highly-accurate custom models 30x faster with 90% less memory use.\r\n\r\nWith over 10 million monthly model downloads and 40K GitHub stars, our mission is to make training and open-source the best it can be!",
    "one_liner": "Open-Source Reinforcement Learning (RL) & Fine-tuning for LLMs.",
    "team_size": 12,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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        "title": "Random Labs: An open source software agent that lives in your codebase",
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        "body": "**_Software is like playdough. It morphs into the creators desires._**\n\n**_Or at least it should._**\n\nThis is what fundamentally drives us as a company. We believe that software development should stay in the hands of people. We believe that there is near infinite software the world needs and that there are not enough developers to build it.\n\nThis leads us to the problem we are solving. _We are making it possible for the next 20 million engineers to come online._ We believe AI tools can be used to create jobs, not replace them. And we believe that open-source tools will continue to be the path forward for developers.\n\nMost software agent companies have deeply optimized for swe-bench. However, this is not a representative task. We are building tooling we actually use. It’s written parts of itself already and we are extremely excited to share it with you.\n\n**How are we building this?**\n\nOur approach is to start with the IDE. Developers are most comfortable in the ide, so that’s where we are starting. We are integrating our agent directly, and it is able to make changes across massive codebases (below is it writing a feature in the cal\\[.\\]com codebase which is 1,155,075 lines long at the time of writing).\n\nSo, we are making an agent that is capable of _living in your codebase_ with almost perfect context.\n\nIt’s not just autocomplete. It’s not just chat with your codebase. It’s something beyond a software workflow. Our tooling makes the code feel fluid.\n\n_And thats special._\n\nHere it is editing the codebase:\n\n![uploaded image](/media/?type=post&id=83813&key=user_uploads/1255731/4031240e-27ca-4452-9c69-a36670ddd18f)\n\n\nHere is the resulting component:\n\n![uploaded image](/media/?type=post&id=83813&key=user_uploads/1255731/60472093-b735-42ec-a6b5-36aa98691331)\n\n**Our ask!**\n\n1. If you’re interested in using our tool once it launches, please join the waitlist here: <https://akfucniuesi.typeform.com/to/xz8C2Jpg>\n2. If you’re interested in helping us build this, PLEASE reach out at [founders@randomlabs.ai](mailto:hello@randomlabs.ai)",
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        "tagline": "We make it simple to implement actionable, context-rich logging across your entire codebase.",
        "body": "[Patchwork](https://getpatchwork.io/) automates logging from code to storage. Developers no longer need to manually write or re-write logs — Patchwork does it for them. Actionable, context-rich, secure logs can become the new standard across your entire codebase.\n\nThe product currently works with Java, Go, Python, Ruby, TypeScript, JavaScript, Scala, and Kotlin.\n\n<https://youtu.be/70Pnfu8HHHQ>\n\n# **The Problem with Logs**\n\nManually instrumenting code with logging is time-consuming and tedious. Unlike building features, logging doesn’t earn promotions. Logs are written by developers but consumed by SREs and security engineers once in production.\n\nPicture this: a critical incident strikes at 2 AM. Your SREs are scrambling, frantically searching through a mess of inconsistent logs, trying to piece together what went wrong. Sound familiar? That’s because logging, as it stands today, is broken.\n\nEmpires like Splunk have been built on the premise that messy logs are a fact of life and you therefore need to fork out for best-in-class indexing and querying. We say it’s time to tackle this problem at the source.\n\n![uploaded image](/media/?type=post&id=83144&key=user_uploads/1666763/dc25e534-00d3-4b8d-91ab-dba6bf902905)\n\n**Patchwork: Logging, _Un_\\-imagined**\n\nWith Patchwork, developers can focus on building features while our product ensures that every log is context-rich, actionable, and secure. Developers can un-imagine logs, forever.\n\nPatchwork works in the background, reviewing your existing codebase and stepping in during continuous integration to ensure that your new code meets your engineering standards.\n\nOur product is flexible, but in our experience, good logs:\n\n* Are context-rich and actionable,\n* Explain what the failed method was attempting (the intent),\n* Provide the context in which it failed (the state of all relevant variables),\n* Use a structured format,\n* Handle sensitive information gracefully (never include tokens/passwords, label or exclude, e.g., personal information).\n\nOur mission is to provide a few-click, automated journey to implement logging from code through to storage.\n\n# **Our Ask: Give an SRE a Hug**\n\nAnd then, help them out by giving them our email – [founders@getpatchwork.io](mailto:founders@patchwork.io). We’d love to connect with Senior SREs and VPs of Engineering – in our experience, they really get it.\n\nCheck out how we think at our [blog.](https://www.getpatchwork.io/post/the-problem-with-logs)\n\n![uploaded image](/media/?type=post&id=83144&key=user_uploads/1666763/fee73b48-c706-4393-a215-ff9dace4edfe)\n\n# **Our Story**\n\nThe Patchwork founders ([Ben](https://www.linkedin.com/in/benjaminfhall/), [Sam,](https://www.linkedin.com/in/sam-kramer-4263189a/) and [Alex](https://www.linkedin.com/in/alexmaass/)) met while working at Palantir. That translates to _met while delivering product and outcomes to demanding customers, at massive data and infra scale, under tight timelines_. Late-night debugging sessions at Palantir taught us that good logs are priceless.\n\n![uploaded image](/media/?type=post&id=83144&key=user_uploads/1666763/25c4d414-95ab-4572-bb3a-05f90868ced0)\n\n# ",
        "url": "https://www.ycombinator.com/launches/Ld2-patchwork-technologies-automated-logging-from-code-to-storage",
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    "id": 29642,
    "name": "Hexclave",
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    "launched_at": 1716295686,
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      {
        "id": 82541,
        "title": "Stack Auth — Open-source user authentication that doesn't suck",
        "tagline": "The open-source alternative to Auth0, Clerk, and Firebase Auth. Fully managed & supports authorization.",
        "body": "**Docs**: [https://docs.stack-auth.com](https://docs.stack-auth.com/)\\\n**Star us on GitHub**: <https://github.com/stack-auth/stack> \n\n![uploaded image](/media/?type=post&id=82541&key=user_uploads/1147249/8ef50525-682e-424a-8fab-58e64897602c)\n\nHi all! We're [Zai](https://www.linkedin.com/in/zaishi) and [Konsti](https://www.linkedin.com/in/stan-wohlwend-b30340167/), and we’re repeat founders who believe that devtools must be dev-friendly.\n\nUser authentication _sucks_. Existing solutions are a pain to set up and have hostile pricing, terrible documentation, and vendor lock-in. The few good solutions that exist only do authentication and don't even touch **authorization** or **user management**.\n\nStack Auth was born out of years of frustration. We wanted to build something better.\n\nIf you're building B2B software, we'll deal with **organizations**, **permissions**, and **RBAC** for you.\n\nIf you're building a Next.js app, we have **React components** for sign-in, password reset flows, and all sorts of things like account settings and teams. And they're customizable.\n\nOther features include:\n\n* **100% open-source** and self-hostable, though we also provide a Cloud service\n* **User dashboard** to view, modify, and understand your users\n* **Multi-tenancy** for your business customers\n* **Access token management** for APIs of OAuth services that users connect with\n* **Impersonation** to log in as one of your own customers for debugging and live support\n* **Webhooks** to sync your data with other systems like databases or Slack\n* **Customizable e-mails** on triggers such as user sign-up\n* **Flexible REST API** for use with any backend\n\nInterested? Check out [our website](https://stack-auth.com/) or [schedule a call](http://cal.com/team/stack/chat). Or take a look at the screenshots below.\n\nThanks all!\n\n![uploaded image](/media/?type=post&id=82541&key=user_uploads/1147249/7d1ffe2b-bec6-487c-8c91-edf4e13cee71)\n\n![uploaded image](/media/?type=post&id=82541&key=user_uploads/1147249/514ca5a4-fe6a-4482-b88e-a75cf6127627)\n\n![uploaded image](/media/?type=post&id=82541&key=user_uploads/1147249/f8d922e0-3594-442f-bc96-ed852a2e2205)\n\n",
        "url": "https://www.ycombinator.com/launches/LTJ-stack-auth-open-source-user-authentication-that-doesn-t-suck",
        "votes": 58,
        "created_at": "2024-07-29T22:15:05.983Z"
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    "id": 29647,
    "name": "Party",
    "slug": "party",
    "former_names": [
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        "title": "Phonely’s new AI agents hit 99% accuracy—and customers can’t tell they’re not human | VentureBeat",
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        "body": "**TL;DR:** Maitai is an ultra-lightweight layer between your app and LLM providers, ensuring reliability and passive continuous improvement.\n\n[Try Maitai](https://portal.trymaitai.ai)\n\n# The Problem:\n\nGetting LLMs into production is complex and time-consuming. Teams today spend much of their time-fighting hallucinations, suboptimal output, and mitigating problems plaguing their providers. Though this is necessary for a production-ready application, it can be a massive distraction from building and expanding the core product, not to mention a sizable investment. Hallucinations can quickly deteriorate the user experience and are difficult or impossible to fully fix. Model outages or degraded performance make any meaningful traffic a nightmare. Consistent response times are usually only solved today with dedicated compute environments, which can be too costly for most companies to consider. The more you make progress on these issues, the more you become locked into a provider.\n\n# The Solution: A Dependable Middleman\n\nMaitai integrates seamlessly between the application and model providers to handle the heavy lifting behind the scenes. The result? Higher quality, reliable model output with passive incremental improvement - without any new code. We leverage our robust real-time evaluation engine to build a deep understanding of the customer's application, as well as the capabilities of all major models, in order to deliver consistent, dependable results. This abstraction layer is essential as the AI landscape evolves and new models emerge.\n\n![uploaded image](/media/?type=post&id=83311&key=user_uploads/213922/d9d0ba25-8ae2-48c4-b5ae-6a9f891d493c)\n\n**Real-time Evaluations**\n\nFor each application, we build an understanding of the expectations that the user has for each request. We then evaluate all model output to ensure it adheres to these expectations, in under 200ms. Detected faults can be surfaced to the user in a callback or webhook. Users can also allow Maitai to leverage these evals to autocorrect any faulty output we find, ensuring clean, reliable responses.\n\n_Example:_ One of our customers is a voice-ordering company for restaurants. They use Maitai to ensure the model always requests consent from the customer before sending a text message. Failure to do so would put them out of compliance with the Telephone Consumer Protection Act, resulting in heavy fines and lawsuits. Maitai has prevented this from happening 14 times.\n\n![uploaded image](/media/?type=post&id=83311&key=user_uploads/213922/858792ed-11e9-40b8-92c2-d46c244ae91b)\n\n**Highly-available Inference**\n\nAs AI adoption grows, all providers are having trouble keeping up with the demand. As we continuously profile all models we support, we see this manifest as outages and degraded performance many times throughout each day. Maitai uses our model health data to preemptively fall back to a similar model if we notice degraded performance or an outage. Avoid failed responses and get more consistent response times without shelling out hundreds of thousands of dollars on dedicated compute.\n\n![uploaded image](/media/?type=post&id=83311&key=user_uploads/213922/d10bbf2a-7fd4-47c3-8788-1a8aeffdeb0b)\n\n_Our health checks on gpt-4o from us-west2 show consistent performance only \\~90% of the time, with frequent spikes to 400%+ usual response times._\n\n**Passive Incremental Improvement**\n\nWith Maitai, you gain access to models that are higher quality than GPT-4o, 5x faster, and 10x cheaper — tailored specifically for your application. Our evaluation data not only allows us to immediately improve output quality and reliability, but also lends way to passively building application-specific models that are higher quality, more performant, and cost less than closed-source alternatives. Access the best models for your application, with updates as often as every few days.\n\n**Actionable Alerts**\n\nGet briefed on problems as they occur to quickly remedy a bad situation. Maitai surfaces real-time faults or session summaries right in Slack, then allows you to chat with your data to explore deeper. Never miss a chance to improve a potentially negative customer experience ever again.\n\n![uploaded image](/media/?type=post&id=83311&key=user_uploads/213922/c93ad111-9921-4213-a32e-4c13fcf00573)\n\n**Micron Thin**\n\nWe've invested heavily in making our presence as light as possible. Maitai adds <30ms to each request (and improving!). 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        "title": "ideate.xyz: AI design co-pilot for content teams",
        "tagline": "The first AI design co-pilot that content teams can collaborate with to create high click-through thumbnail designs for their social media channels. The thumbnail design process is orchestrated by AI with layout, composition, copy and imagery all optimised for brand consistency.",
        "body": "### **Tl;dr:**\n\n![uploaded image](/media/?type=post&id=83411&key=user_uploads/620002/b47c6ed6-17ba-44cf-b061-5a5c4b94ed08)\n\n**ideate.xyz is an AI design co-pilot for content teams to create engaging thumbnail designs for their social media channels. We are starting with thumbnails, the most critical window to connect with audiences - ideate is here to help content teams stand out.**\n\n**Looking ahead, ideate will become THE AI design partner for the next generation of content creators, crafting unique and tailored designs for their bespoke brands.**\n\n### **The team:**\n\nHi, [Jasper](https://www.linkedin.com/in/jasperjia/) and [Elliott](https://www.linkedin.com/in/ellt92/) here. We are building [ideate.xyz](http://ideate.xyz) - the first AI design co-pilot for content teams to create thumbnail designs for social media channels. \n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXcyUiwrYeoWSM9XI-PrkXrpcLxSQZLYZHYRrgKdya2BZpu7VgxyNGx8KcSPqkbuzo0IEUy1_-6sCn3Zsc6cBw0OVQmAUdEJhMmbByvBhOPLvLa4rWe1RTA4lXgk6r_9i2WnQX03jbegL_seQRPUthnvM50C?key=dBDHpbeLdBMcMx4JQU8ppQ)\n\n**Jasper Jia (Left)**\n\nCofounder & CEO at ideate.xyz. Designer specialising in creative tools and no-code. He believes designers should embrace learning and getting their hands dirty in the technical end of the software building process to craft the best software experience and cultivate fast iteration cycles with the engineering team. He was an ex-Snap designer and MSc Design Engineering graduate from Imperial College London.\n\n**Elliott Thompson (Right)**\n\nCofounder & CTO at ideate.xyz. A software engineer with a penchant for visual computing. He studied computer graphics at University College London before taking on a role as a graphics generalist at Snap Inc. He has previously worked on 3D engines, game developer tooling, graphics editors, and e-commerce platforms.\n\n### **The problem:**\n\nDesign tools are stuck at two extremes: powerful but complex, or simple yet limiting. This seemingly inevitable tradeoff affects millions of content creators trying to stand out with their thumbnail designs, the critical window to connect with their audience.\n\nIf you’ve had to design thumbnails for social channels, you've likely been here:\n\n![uploaded image](/media/?type=post&id=83411&key=user_uploads/620002/b533f0cd-3816-4699-b93b-a445528a046f)\n\nYou have a great idea, so you install the latest Adobe product. Suddenly, you're faced with a blank canvas and a dizzying array of options. Hours of YouTube tutorials later, you're ready to throw in the towel.\n\nTime for Plan B. You load up Canva, pick a template that's \"close enough,\" and tweak some colors. It doesn't really feel like yours, and it is so hard to stand out with a “Canva look” when there are over 3.7 million videos uploaded to YouTube alone every day!\n\n### **Our solution:**\n\n[ideate.xyz](http://ideate.xyz) - the first AI design co-pilot orchestrating the entire thumbnail design process from initial ideas to final designs that stand out!\n\n![uploaded image](/media/?type=post&id=83411&key=user_uploads/620002/56aa1f67-549b-44ae-a3ee-66e0b32c5a17)\n\n\\* Design with plain English: No prior experience with design or creative software needed. Produce designs via simple and engaging discussions with AI design co-pilot.\n\n![uploaded image](/media/?type=post&id=83411&key=user_uploads/620002/406874a3-9435-4c80-9472-f1982d4bb1f7)\n\n\\* Think of our copilot as your team’s AI design partner - guiding the design process with proactive questions to understand design requirements and implementing expert design decisions after your sign off.\n\n![uploaded image](/media/?type=post&id=83411&key=user_uploads/620002/887c967e-b165-4ceb-b4d1-8d5beb9a5bb3)\n\n\\* Collaborative environment: Teams can work with a co-pilot on the same project for a quick feedback cycle and sign-off before exporting the final designs.\n\n![uploaded image](/media/?type=post&id=83411&key=user_uploads/620002/3333d422-a852-4af4-8de4-adb7e832c3f8)\n\n\\* Maintain brand consistency as our AI learns your preferences over time and always generates content with this in mind.\n\n\\* We fine-tune our prompts for each generation, considering layout composition, image assets, and copywriting in lockstep with each other to produce creative but also consistent results. \n\nA typical workflow with ideate.xyz:\n\n1\\. Describe your content ideas\n\n2\\. First drafts designed by AI co-pilot\n\n3\\. Iterate and create more variations by chatting with AI copilot\n\n4\\. Export designs in channel-specific dimensions \n\n[Quick demo here](https://youtu.be/Zf_i1cUejbk)\n\n### **Our story:**\n\nAs a design and engineer duo, we have spent years crafting creative tools in the WebGL and AR space. We've also built and mentored in the no-code space to help non-techies build out their online presence. Regardless of the domain, one challenge persists for creators — finding a design tool that’s both simple and powerful enough to bring a brand's vision to life. The reason why this problem persists in the market is simple - the inevitable tradeoff that every design software needs to make between power and ease of use. Typically, the more powerful a tool gets, the more complex it becomes. On the flip side, easy-to-use tools often limit creativity with rigid templates. \n\nBut with AI, we have found the conviction to break this tradeoff. We are on a mission to create a design tool that actually puts your ideas in the driving seat, making the design process less about esoteric design language and more about the content team’s own creative impulses. Our goal is to empower the next generation of creators to build stunning brands and assets. \n\n### **Our ask**\n\nAre you currently on a team that regularly has to come up with thumbnail designs for your social media content?  Either wrestling with complex design tools or unhappy with generic templates? Talk to us, and we would love to learn more about your requirements!\n\nIf you know any professional content creators, we’d really appreciate the connection!\n\nOur email is [founders@ideate.xyz](mailto:founders@ideate.xyz)",
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        "votes": 51,
        "created_at": "2024-08-26T18:12:14.426Z"
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        "title": "Hyrex - The Open-Source COLD Task Framework",
        "tagline": "Production-grade background tasks built on Postgres",
        "body": "![uploaded image](/media/?type=post&id=93335&key=user_uploads/1967655/4c6a3685-1d2e-4f71-8808-ffcbd2a920a8)\n\n\\\nWe’re Mark and Trevor, founders of [Hyrex](https://hyrex.io). We’ve written a lot of software over the years at Google, NASA, and multiple startups. As our focus has shifted to scalable web apps, we’ve come to appreciate the magic of asynchronous background task queues. They make it easy to build lightning-fast apps that can scale dynamically, while ensuring that essential tasks are completed with full confidence, in priority order. This distributed approach is more important than ever for building dynamic AI agents, indexers, and web-first apps.\n\nHere’s a basic task orchestration architecture - you send tasks (i.e. function calls) to a queue, and workers pull them off and complete them in parallel.\n\n![uploaded image](/media/?type=post&id=93335&key=user_uploads/1967655/f29e6d7d-890b-4863-aa19-eea241e05714)\n\n**The Problem**\\\nUnfortunately, none of the existing frameworks supported everything on our checklist. As we talked with developers working on startups, we learned that most shared the same experience. Some frameworks require extensive code rewrites, while others are difficult to configure and debug, or simply unmaintained. Most lack a deep commitment to open-source, and many require dependencies on outdated or niche technologies. As you can probably guess by now, we decided to build our own!\\\n\\\n**Our Approach**\n\nWe started with a few core creative constraints.\n\n1. Only required dependency is a Postgres database.\n2. Existing functions can be converted to tasks using just a decorator/wrapper. No changes to your core code that lead to lock-in.\n3. Open-source first, with a higher-performance managed service with an identical SDK. Easy to switch back-and-forth.\n4. Can be set up and tested in minutes.\n\nAnd we ended up with Hyrex!\n\nIf you’ve used a task framework before, everything should work as you expect (and probably better)! If you’re new to task frameworks, everything you need to know is at [hyrex.io/docs](https://hyrex.io/docs)\n\n![uploaded image](/media/?type=post&id=93335&key=user_uploads/1967655/8472e657-3969-4e48-aa91-d4a8ecdc7f85)\n\n\\_(Hyrex Cloud in action)\\_\\\n\\\n**What is COLD?**\n\nWhy do we call ourselves “the COLD task framework”? For each function you wrap as a Hyrex task, you get 4 properties needed for production-grade systems:\n\n* **Controllable** - tasks can be sent from anywhere, anytime, with any configuration\n* **Observable** - tasks status, results, logs, and metadata are easily available via a UI or programmatically\n* **Large-scale** - workloads are horizontally scalable across any cloud infra (even multi-cloud)\n* **Durable** - workers are fault-tolerant and self-healing, and tasks can’t be dropped once they’re in the system\n\nWith these built-in properties, your Python/TypeScript functions are ready to send with confidence. You can run them on schedules and easily chain them together into task trees to build products like Deep Research and dynamic AI agents.\n\n![uploaded image](/media/?type=post&id=93335&key=user_uploads/1967655/a9e116eb-a557-4687-8f6a-fd8242f72e3d)\n\nHyrex open-source requires only a Postgres database to run. Hyrex Cloud ([hyrex.io/cloud](https://hyrex.io/cloud)) provides higher throughput, GitHub integration with automatic deployments when you push changes, and built-in scalable worker pools. Both options use the same SDKs, so you can easily switch at any time!\n\n**Hyrex Cloud pricing**\n\n* $200/month - individual plan (1 project + 1 worker)\n* $400/month - team plan (up to 5 members and 5 projects + 2 workers)\n\n**Our ask:**\n\n* Sign up for a 1:1 demo at [hyrex.io](http://hyrex.io)\n  * We’d love to chat directly and help write your first Hyrex task!\n* Try it out on your own!\n  * Build your first Hyrex task in minutes using our quickstart guides: https://hyrex.io/docs/learn/getting-started\n* Join our Discord ([discord.gg/hyrex](https://discord.gg/hyrex)) for questions and discussion",
        "url": "https://www.ycombinator.com/launches/OHP-hyrex-the-open-source-cold-task-framework",
        "votes": 17,
        "created_at": "2025-08-27T13:44:23.405Z"
      },
      {
        "id": 83339,
        "title": "Kura | The AI DevOps Copilot",
        "tagline": "Kura is an intelligent copilot that helps software teams manage and optimize their cloud infrastructure.",
        "body": "**TL;DR:** [Kura](https://www.usekura.com/) integrates directly with services like AWS, helping software teams respond to incidents, provision infrastructure, and optimize complex cloud systems.\n\n![uploaded image](/media/?type=post&id=83339&key=user_uploads/1967655/a1945e14-3f49-4491-8e31-d40335e6f5ab)\n\nHello YC! We’re [Trevor](https://www.linkedin.com/in/trevorar) and [Mark](https://www.linkedin.com/in/markedwarddawson/), founders of Kura. After building distributed systems for a combined \\~15 years at places like Google and NASA, we know the challenges and triumphs of cloud-based products. We started Kura with the core belief that recent AI advancements can unlock the potential of software teams building on the cloud.\n\n# **What’s the problem?**\n\nAs web apps become increasingly core to the world, maintaining cloud infrastructure requires increasingly more time and resources.\n\n* Distributed systems are getting more complex than ever\n* Managed solutions trade off ease against control and cost\n* Cloud infra engineers are few and far between, leaving much of the work to teams who may not have extensive cloud experience\n\n# **What can Kura do?**\n\nKura is a chatbot and workspace that integrates directly with a live index of your cloud infra from services like AWS, GCP, and Azure.\n\n![uploaded image](/media/?type=post&id=83339&key=user_uploads/1967655/be157dd9-7ee9-48bf-af07-aca46efca63c)\n\n**Kura can answer questions about your cloud system**, providing links and live information for queries like:\n\n* “Is my main API cluster healthy?”\n* “Which container version is running in prod?”\n* “Can you help me deploy a new container via CDK?”\n\n**Kura can run pre-packaged and user-defined “runbooks”** to proactively surface issues via notifications. For example:\n\n* Scheduled checks for over/under-utilized computing resources\n* Discovering and surfacing cost spikes and trends\n* Searching for common security vulnerabilities\n\nWith Kura, software teams can build faster and more confidently on the cloud, all while maintaining full control of their critical infrastructure.\n\n# **Our ask:**\n\n* If your team is building on the cloud and would like to learn more or sign up as a pilot customer, please reach out to [founders@usekura.com](mailto:founders@usekura.com).\n* If you know software teams or developers running into roadblocks due to cloud complexity, please send this post their way - we’d love to chat and learn more!\n* Follow us at [@kura_labs](https://x.com/kura_labs) to follow along on the journey!",
        "url": "https://www.ycombinator.com/launches/LgB-kura-the-ai-devops-copilot",
        "votes": 57,
        "created_at": "2024-08-23T01:15:08.727Z"
      }
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    "id": 29672,
    "name": "DeepSim, Inc.",
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    "website": "https://www.deepsim.io",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "DeepSim is building an AI physics simulator. We are currently developing the only thermal simulator to meet AI chip design needs and are validating our tool with Intel. We are a team of three electrical engineering PhDs from Stanford with backgrounds in semiconductor fabrication and design.",
    "one_liner": "An AI physics simulator for AI chip design",
    "team_size": 7,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1723754775,
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    "url": "https://www.ycombinator.com/companies/deepsim-inc",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/deepsim-inc.json",
    "year_founded": 2020,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/deepsim-inc/",
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      "name": "David Lieb",
      "url": "https://www.ycombinator.com/people/david-lieb"
    },
    "founders": [
      {
        "user_id": 1869533,
        "full_name": "Connor McClellan",
        "title": "Founder/CEO",
        "founder_bio": "Stanford EE PhD grad now building an AI physics simulation platform at DeepSim to solve the frustrating parts of my PhD. I'm also really into espresso making and will be happy to make you your best cup of coffee.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/connor-j-mcclellan",
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      {
        "user_id": 1991480,
        "full_name": "Alexander Gabourie",
        "title": "Founder/CTO",
        "founder_bio": "Alex is a co-founder of DeepSim, Inc., where he develops AI physics simulators. He earned his PhD in Electrical Engineering from Stanford, specializing in nanoscale thermal simulations, and brings over a decade of experience in the semiconductor industry.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/alexgabourie/",
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      {
        "user_id": 1993598,
        "full_name": "Chuck Koroglu",
        "title": "Founder",
        "founder_bio": "Stanford EE PhD with background in semiconductor engineering, and physics modeling of integrated circuits. Excited about transforming the landscape of engineering simulations with new technology that combines physics, experimental data and AI.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/ckoroglu/",
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    "launches": [
      {
        "id": 83111,
        "title": "DeepSim – AI physics simulations",
        "tagline": "Run complex physics simulations signficantly faster than any commerical tool.",
        "body": "**TLDR:** AI-accelerated 3D physics simulator for engineers\n\n[DeepSim](https://www.deepsim.io/) makes it easy for engineers to run 3D physics simulations fast. This means rapid design iterations for better products and real-world monitoring for better decisions.\n\nWe built a new physics simulation platform that leverages AI physics models for very fast, ultra-scalable physics simulations.\n\n—\n\nHi everyone! We are [Connor,](https://www.linkedin.com/in/connor-j-mcclellan/) [Alex,](https://www.linkedin.com/in/alexgabourie/) and [Chuck,](https://www.linkedin.com/in/ckoroglu/) and we love physics simulations. While working on our PhDs at Stanford, we saw how physics simulators needed a refresh to solve modern problems. That’s why we started [DeepSim.](https://www.deepsim.io/)\n\n## The Problem\n\nRunning 3D physics simulations is **difficult**, **expensive**, and **slow**.\n\n1. **Setup:** Experienced engineers still spend countless hours meshing their designs before even running a single simulation.\n2. **Run:** Many simulations take hours to even weeks on expensive compute systems. Some are even intractable and require highly trained engineers to simplify the problems at a significant cost of accuracy.\n3. **Attention:** Each step requires constant babysitting as simulators are fragile and can fail at any time.\n\n🧑‍🔧️ Engineers hate the tedious simulation setup and wasted time due to failed simulations.\\\n👔 Managers hate that engineers can’t go faster and use tons of cloud credits.\\\n💰 CEOs/VPs hate that engineering delays stall a product launch.\n\n## The Solution\n\nLeverage AI to **simplify**, **speed up**, and **scale up** 3D physics simulations.\n\nWe are building a new AI physics simulation platform, automating away the physics setup and simulating designs 1000X faster with no drop in accuracy.\n\nOur platform uses lightweight, easy-to-train AI models combined with a powerful GPU-accelerated solver to deliver solutions quickly and efficiently. This approach eliminates the bulkiness of traditional finite element method (FEM) tools and overcomes the inflexibility of other AI physics simulators.\n\n![uploaded image](/media/?type=post&id=83111&key=user_uploads/1869533/6218d9cd-39b9-4307-a144-9f346d8d3c65)\n\nAt [DeepSim](https://www.deepsim.io/), we have already worked with semiconductor companies to build the most powerful thermal simulator for circuit design, running thermal simulations with billions of nodes in minutes on a single GPU, which is 1000X more detail than a commercial tool can deliver using 50+ CPU cores in the same amount of time.\n\nWith DeepSim's simulator, we are able to model extremely complex geometries with length scales spanning 6 orders of magnitude, intractable to solve with FEM tools. Below is a thermal simulation of an integrated circuit, complete with a heat sink and airflow, that only took 10 minutes to run. We can resolve hot spots in individual transistors (\\~10 nm in size) within a whole chip (1 cm).\n\n![uploaded image](/media/?type=post&id=83111&key=user_uploads/1869533/26e48815-e3db-4cfa-bdd4-52168c537546)\n\n## Use Cases\n\nThis is a breakthrough in 3D physics simulations that empowers engineers in the same way FEM did 50 years ago. We’re excited to see where engineers take our tool!\n\nSome initial use cases are:\n\n* Speeding up the design of complex systems with faster simulations\n* Utilizing design automation to speed up development\n* Developing digital twins for system operation\n\n## The Team\n\n![uploaded image](/media/?type=post&id=83111&key=user_uploads/1869533/c032c745-4faf-4374-8a43-92de0645a397)\n\nChuck, Alex, and Connor founded DeepSim to solve the frustrating parts of their PhDs.\n\n## The Ask\n\nWe would love to talk with engineers that…\n\n* design and operate battery packs for EVs or grid-scale energy storage\n* design and deploy satellites\n* work on thermal management of semiconductors, from the chip scale to data centers\n* have any complaints about slow or frustrating simulations\n\nContact us at [founders@deepsim.io](mailto:founders@deepsim.io)!",
        "url": "https://www.ycombinator.com/launches/LcV-deepsim-ai-physics-simulations",
        "votes": 35,
        "created_at": "2024-08-16T04:14:43.665Z"
      }
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  },
  {
    "id": 29673,
    "name": "Storia AI",
    "slug": "storia-ai",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b303aec8b08b8ee5b7c074ef02f910506fd73654.png",
    "website": "https://storia.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "With AI increasingly automating away code generation, software engineers will spend more time reading, judging, and architecting code rather than writing it. Storia is building an open-source copilot that knows a company's codebase and its context.\r\n\r\nWe are starting with Sage, a Perplexity-like agent for helping developers understand, judge, and generate software. Given an existing codebase, developers can ask Sage questions such as:\r\n1) Given my project’s SLA and latency constraints, what is the appropriate underlying vector database to use? How would I incorporate it into my existing codebase?\r\n2) Why should I pick Redis over Milvus as my underlying vector store?\r\n3) Does this codebase in our organization still work and what steps are required for a complex integration with another library?\r\n\r\nSage’s answers are directly supported by documentation and external references like GitHub, Stack Overflow, technical design documents, and project management software, preventing hallucinations. Today, Sage has up-to-date knowledge about open-source repositories (indexed daily). Tomorrow it will have a deep understanding of every line of code on the Internet. For teams, Sage will know about your private codebase too.\r\n\r\nNo group has yet solved how to build an AI system that comprehends a codebase and its context and can empower every developer to architect better code, faster. This requires new research advances because vanilla RAG and out-of-the-box LLMs aren’t going to cut it. \r\n\r\nWe have 20+ years of software engineering and AI research experience. Julia worked on precursors of Gemini using contextual neural techniques before they were called “RAG” (and applied it to products like Google Keyboard and Pixel phones). Mihail built the earliest LLMs at Amazon Alexa and launched the first contextual deep learning conversational AI system in production at Alexa.\r\n",
    "one_liner": "Open source AI copilot that knows your company's code and its context",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1724629645,
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      "America / Canada"
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    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/storia-ai/",
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      "name": "David Lieb",
      "url": "https://www.ycombinator.com/people/david-lieb"
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    "founders": [
      {
        "user_id": 916267,
        "full_name": "Julia Turc",
        "title": "Founder/CTO",
        "founder_bio": "Cofounder @ Storia & previously at Google Research.\n\n10+ years in NLP. Built the first bidirectional RNN for machine translation at Oxford. At Google, I helped build pivotal technologies like federated learning, the AI layer on top of Android, and RAG for precursors of Gemini. Excited about how NLP is now redefining software engineering.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/iulia-raluca-turc/",
        "x_url": "https://twitter.com/juliarturc",
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      {
        "id": 83405,
        "title": "Storia: A contextual AI pair programmer for developer teams",
        "tagline": "We help engineering teams understand, analyze, and generate software with their codebases.",
        "body": "![uploaded image](/media/?type=post&id=83405&key=user_uploads/812126/ce70880c-852a-4e80-a573-88f6742298ed)\n\nHi everyone. We’re Julia and Mihail, the team behind [Storia](https://storia.ai/?utm_source=yc&utm_medium=social&utm_campaign=launch-yc). We have 20+ years of software engineering and AI research experience. [Julia](https://www.linkedin.com/in/iulia-raluca-turc/) worked on precursors of Gemini using contextual neural techniques before they were called “RAG” (and applied it to products like Google Keyboard and Pixel phones). [Mihail](https://www.linkedin.com/in/mihaileric/) built the earliest LLMs at Amazon Alexa and launched the first contextual deep-learning conversational AI system in production at Alexa.\n\n**👎 The Problem: <5% of software teams use AI code understanding and generation systems**\n\nDespite all the hype around AI coding following the release of GitHub Copilot, a disappointingly small percentage of engineering teams have actually adopted AI assistants into their developer workflows. Why?\n\nWhat developers don’t like about systems today:\n\n1. **Code search is not accurate enough**, slowing dev velocity.\n2. **Code assistants are not grounded in their team’s codebase**, so they lack the necessary context to produce useful and high-quality answers.\n3. **Code outputs can be incorrect** due to hallucination which strains dev patience and trust.\n\n**🚀 The Solution: A contextual AI pair programmer built for any team’s codebase**\n\n![uploaded image](/media/?type=post&id=83405&key=user_uploads/812126/0e093af4-4352-4550-a123-be44cf3dc747)\n\nWe’re building [Sage](https://sage.storia.ai/?utm_source=yc&utm_medium=social&utm_campaign=launch-yc), a Perplexity-like agent for helping developers understand, analyze, and generate software. Given an existing codebase, developers can ask Sage questions such as:\n\n* _For my project’s SLA and latency constraints, what is the appropriate underlying vector database to use? How would I incorporate it into my existing codebase?_\n* _Why should I pick Redis over Milvus as my underlying vector store?_\n* _Does this codebase in our organization still work, and what steps are required for an integration with another library?_\n\nA few of the features Sage supports:\n\n* **We index repos daily**, providing users with the most up-to-date info about how to use a library (no stale, deprecated API definitions),\n* We have a Perplexity-like focus on **citing the source of every generated line of code**, enhancing developer trust.\n* We've developed algorithms grounded in research for **syntactic and semantic understanding of a codebase** so that we can provide more relevant context and use it effectively given a user query.\n\n We are now actively working with seed to series C partner companies to help them integrate Sage into their developer workflows. \n\n**🌅 The Opportunity: Making every engineer on a software team a 10x developer**\n\nThere are \\~28M developers worldwide. Github Copilot is the frontrunner in AI assistant tooling and reached $100M ARR in 2 years, which is only a small percentage of the $913B spent on software development in 2023.\n\n**🙏 Our Ask**\\\nWe’re still onboarding a closed group of beta partners to integrate with Sage. We would appreciate connecting with engineering leaders (VP of engineering, Head of Engineering, CTO)  at Seed-Series C companies. \n\nAdditionally, if you want your open-source repository indexed reach out to us at [mihail@storia.ai.](mailto:founders@storia.ai)\n\n![uploaded image](/media/?type=post&id=83405&key=user_uploads/812126/dd520900-8415-4ee5-8707-554b7197037b)\n\n",
        "url": "https://www.ycombinator.com/launches/LhF-storia-a-contextual-ai-pair-programmer-for-developer-teams",
        "votes": 38,
        "created_at": "2024-08-26T16:32:20.077Z"
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    "id": 29682,
    "name": "RunLocal AI",
    "slug": "runlocal-ai",
    "former_names": [
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      "RunLocal"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0c096a99a018da47706cb093bff201df7e6cbd6d.png",
    "website": "https://runlocal.ai",
    "all_locations": "London, England, United Kingdom",
    "long_description": "RunLocal is an environment that specializes AI agents to optimize model for onboard compute platforms like NVIDIA Orin/Thor and Qualcomm → www.runlocal.ai\r\n\r\nRunLocal is built for Physical AI engineering teams across autonomous vehicles, robotics, smart cameras and more.\r\n\r\nIt tracks every experiment and continuously refines experimentation data into an understanding of what drives performance on your target hardware.\r\n\r\nThis environment means that a generic coding agent (e.g. Codex or Claude Code) can experiment and iterate better, faster and cheaper. \r\n\r\nWith RunLocal, you hit performance targets faster and ship more optimized models – without hiring inference optimization specialists. \r\n\r\nWe’re working with leaders in autonomous vehicles and robotics. We're backed by investors like Y Combinator and 468 Capital.",
    "one_liner": "AI agent that optimizes inference for embedded compute like Jetson",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1722617907,
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      "Developer Tools",
      "Computer Vision",
      "AI",
      "ML"
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      "Europe"
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        "title": "Zenbase: Continuous prompt optimization from DSPy core contributors",
        "tagline": "Dev tools and cloud infrastructure for teams to save time, never get stuck in prompt hell, and create AI apps that keep getting smarter.",
        "body": "**TL;DR:** Zenbase helps developers focus on programming by automating prompt engineering and model selection. We’re building developer tools and cloud infrastructure for teams to save time, never get stuck in prompt hell, and create AI apps that get smarter over time.\n\nHey there! We're [Cyrus](https://linkedin.com/in/knouroozi/) & [Amir](https://www.linkedin.com/in/amir--mehr/). In the past, we've both been lead engineers and founding CTOs. We became contributors to [DSPy](https://github.com/stanfordnlp/dspy) and discovered the future of programming with language models.\n\nThis is the story of how we came to this insight, our glimpse into the future, and 2 case studies on how Zenbase has helped companies escape prompt hell and scale prompt engineering.\n\n![uploaded image](/media/?type=post&id=83751&key=user_uploads/121365/4f26ad68-3d25-4e10-8573-3b8937b0f8b4)\n\n## Problem\n\nPrompt “engineering” is the most time-consuming, stressful, and uncertain part of programming with LLMs. With DSPy, we had found something profound. It promised to save us from the all-too familiar user journey we — like so many others — had experienced.\n\n![uploaded image](/media/?type=post&id=83751&key=user_uploads/121365/900890e2-d8f5-4a1f-a7db-34d528534de9)\n\nDSPy kept growing. It became Stanford NLP's #1 GitHub repo with 16K stars. We started hearing of folks in Microsoft, Amazon, Google, and 40+ other companies using DSPy to prototype apps with it.\n\nWe began hearing the same things all over again. Although many found DSPy elegant and intuitive, countless folks found it impossible to grok. Those who managed to build something with it had headaches productionizing it; finding it difficult to scale, make reliable, and make performant.\n\nSo, we set out to create the productionized DSPy.\n\n## Solution\n\n![uploaded image](/media/?type=post&id=83751&key=user_uploads/121365/95d2ad6e-9ce2-4903-b2d9-9715958d3064)\n\nZenbase lets you optimize your prompts and models. We offer:\n\n1. [zenbase/core](https://github.com/zenbase-ai/core/tree/main/py) is an open-source Python library that you can use to optimize your existing LLM pipelines using DSPy’s optimizers (versus having to rewrite your pipelines in DSPy)\n2. A hosted API for creating AI functions that get smarter with time. We ingest user feedback to continuously optimize the prompt and model.\n\n   We use the latest tricks from DSPy, our own custom optimizers, and fine-tuning as appropriate to execute your intents in a way that's good, fast, and at a reasonable price.\n3. An on-prem API for businesses with data privacy requirements.\n\n## Use Cases\n\n### How Zenbase saved Vera from Prompt Hell\n\n> **Zenbase came into the trenches with us to improve our evals from 10% to 80%.** It really felt like they were a part of our team.\n>\n> — Taeib, Cofounder @ [Vera-Health.ai (YC S24)](http://Vera-Health.ai)\n\nThey were staying up until 3am on multiple nights trying to prompt engineer their RAG query generator to retrieve the correct documents. Their progress was uncertain. It was stressful. We call this prompt hell.\n\nPrompt engineering is the most uncertain, risky, and stressful part of programming with LLMs. There didn’t seem to be a way out, but with Zenbase, they saw the light at the end of the tunnel.\n\nZenbase makes prompting systematic and peaceful. **We helped Vera go from demo to production, by optimizing the prompt of their query generator.** With a product that could handle doctors’ stress tests, they could focus on selling, and go to bed at a good time.\n\n![uploaded image](/media/?type=post&id=83751&key=user_uploads/121365/985b0550-7421-4890-8696-30201f7c4793)\n\n### How Zenbase helped Superfilter create an AI that’s personalized to its users\n\n> I’ve seen a lot of AI Devtools and Zenbase is solving a problem that everyone building with AI will have when going to production. **The best part is their product is so easy to use that it’s a no brainer.**\\\n> \\\n> — Scott, CEO @ [Superfilter.ai](http://Superfilter.ai) (YC S24)\n\nIt was all going great. Superfilter had just tested their AI email copilot with their beta users of investors and startup founders, and their users were excited. They onboarded a new cohort, and their prompts broke down. It worked well for the investors and startup founders, but not everyone.\n\nScott and his cofounder Travis realized that prompt engineering wasn’t going to scale to accurately categorize user emails into important, action required, or ignore.\n\n![uploaded image](/media/?type=post&id=83751&key=user_uploads/121365/694abf71-1e59-4dc5-bbfe-1d33209e0d2e)\n\nSuperfilter used our hosted API to create email categorizers that learned from users’ existing behaviour. With automatic prompt engineering, they were able to scale personalized experiences for every user.\n\n**Zenbase makes personalized AI apps easier to build and scale with automated prompt engineering.**\n\n![uploaded image](/media/?type=post&id=83751&key=user_uploads/121365/340719d4-94dc-4a3f-82f0-08c9a046ff1a)\n\n## Asks\n\n1. Are you in prompt hell, and do you want to feel the Zen? Are you trying to scale the personalization of prompts for every account?\\\n   \\\n   Learn more [on our website](https://zenbase.ai) and [schedule a demo](https://zenbase.typeform.com/early-access) with us so we can understand where you are and where you want to be. Let us be your LLM doctors and wizards as we guide you to where you want to go.\n2. Use our [MIT-licensed Python SDK](https://github.com/zenbase-ai/core/tree/main/py) to optimize your existing prompts with DSPy’s optimizers.\n3. Kindly share this post with anyone you know who could benefit 🙏",
        "url": "https://www.ycombinator.com/launches/Lmp-zenbase-continuous-prompt-optimization-from-dspy-core-contributors",
        "votes": 153,
        "created_at": "2024-09-04T17:47:28.998Z"
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      {
        "id": 83123,
        "title": "🏰 Fortress – Manage isolated customer databases in your own cloud",
        "tagline": "Offer data isolation at the level enterprises want with none of the DevOps.",
        "body": "**TL;DR: 🏰** [Fortress](https://fortress.build) is an orchestration platform for SaaS applications, allowing them to easily manage a multi-instance database architecture (a hybrid of dedicated and shared instances) in **their own cloud**. \n\nIf you are a SaaS using (or migrating to) AWS/GCP/Azure for databases, [**_schedule a meeting!_**](https://calendly.com/david-fortress/30min)\n\n# **🚩 Problem:**\n\nAs a SaaS grows, they follow these two trends:\n\n1. They mature off 3rd party managed database platforms and move into their own cloud (onto an AWS/GCP/Azure) for cost, latency, and more control of their data.\n2. They move from a single shared database architecture to a multi-instance database architecture for performance, compliance, and due to data isolation requirements of enterprise.\n\nThese result in headaches for SaaS startups.\n\nExisting cloud-native database services not only have complex docs and SDKs, but orchestrating separate database instances requires additional DevOps: deployments, schema migrations, connection pooling, versioning across instances, etc.\n\n# **🏰 Introducing… Fortress**\n\nA database orchestrator that simplifies DevOps of managing a multi-instance database architecture on your private cloud. \n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeM89ZIOfe5fzfqrvvZR8QZeJT4VFxf-l8RkWKi2xhFmmA4xXoQv4Am8mqR_VJX0hZJEpkA0r_ThT4KFt5Fiyzp5QIJmgX0QmhytMyXt0Y58WePtvdi8-KCypPNLxQCOi1JvWuYpHkkNoAxOrJohjYBDDfF?key=9YIQrtfvHKcEq_yzYYr_RQ)\n\n* **☁️ In your own cloud:** Host your database instances in your own cloud for security and reduced vendor lock-in (and use your cloud credits!). _We also have a fully-managed service!_\n* **🛠️ Simplified DevOps**: Global schema migrations and rollbacks, versioning, and managed connection routing\n* **👥 Tenant Management**: APIs/SDKs to support easy provisioning of a dedicated instance for larger enterprise clients and easily add smaller clients to shared instances. \n* **✨ Developer-friendliness:** Easy-to-use client SDKs and ORM integrations. CLI and UI for admin.\n* **🚀 Flexible Deployment**: Deploy the database instance closer to your customer or to a specific region for compliance or reduced latency. \n* **🔒 Security**: Managed network isolation, custom Role-based Access Control for each database, encryption in transit and at rest, by default, simplified compliance audits, and easy tenant data deletion.\n* **🧤 White glove migration**: For now, we will do white glove migration to our platform (it’s fairly simple if you already use AWS/Azure/GCP for databases)\n\n \n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXft6jhnrN1J9uZE177D6tv2SI0qcWg1GNRv2kkBnAiGjzXjr_wYgsDvYDVzL1OpdiNM1tV8DdMiGw186fGzUJnAk8fUk_wd1dijEkE6WL2Vf6XrbVsEh90LhdZz_5-Y6wvd0v8wVLmjpMj8UsphUgPP-GrQ?key=9YIQrtfvHKcEq_yzYYr_RQ)\n\n_Easily manage tenants, see their estimated usage, and what databases their data is in_\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXd9unp3fr994hjsN-JNeqKPVClbgUW4L_f0YU7rMk-OWVi54qo59PsYegIvfiEPGWgo6V-_8Sv1IlC-qr-S-PLZFNdmR7SnnnqnqB3eylgHOTVDJg8DGXlcPptDBsCC20KUNvw0JTlaWD9giMIYaGFI6ok?key=9YIQrtfvHKcEq_yzYYr_RQ)\n\n_Group databases by schemas to propagate schema migrations across groups (we handle rollbacks)_\n\n# **🌟 Future plans?**\n\n* Schema Branching (branch current schema states and or freeze them for development)\n* Zero-downtime schema migrations\n* Experimental: Storage-compute separation to allow scaling to near 0 with Postgres **in your own cloud**\n\n# ❓ **Ask:**\n\n1. If you work with customers who require dedicated db instances, chat with us! We'd like to learn more about your experiences with DevOps.\n2. Let us know if you know any CIOs and CISOs! Would love to [chat](https://calendly.com/david-fortress/30min)! \n3. [Try our early access?](https://calendly.com/david-fortress/30min) We are easy to set up if you use a cloud-native managed service!\n\n## **🙌 The Team: Recent Brown CS grads + open-source wiz.**\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXctX4mvcWdjP5D92rRncPsy8x0jSPrWal_YVuVfT18YYBP49Ab3z3wHex33NUj1alZgm2ZQcA8tl0-9S_cdVttkbRp_12gQX-PG7kGLM4SBgFmnG_uF6XypCC-bn8vyunrVzj0Wee2lUkyoI68qWI7Xx61L?key=9YIQrtfvHKcEq_yzYYr_RQ)\n\n[John](https://www.linkedin.com/in/john-finberg) + [Will](https://www.linkedin.com/in/willothy/) have been building software since 14\n\nJohn + [David](https://www.linkedin.com/in/dchu17/) were CS buddies @ Brown ",
        "url": "https://www.ycombinator.com/launches/Lch-fortress-manage-isolated-customer-databases-in-your-own-cloud",
        "votes": 104,
        "created_at": "2024-08-16T19:26:58.371Z"
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    "id": 29725,
    "name": "Promi",
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    "website": "https://www.trypromi.com/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Promi provides product feedback in the form of customer interviews, URL walkthroughs, heatmaps, and more by creating digital twins of your existing customers. We ingest data from Posthog, Intercom, Stripe, etc. to create your personas from real product usage data. By factoring in how your customers actually interact with product features, we provide much more relevant and insightful feedback on what you are building.\r\n\r\nWe aren't trying to replace user research, but in our experiences most products don't have the time or budget to talk to real users. Getting synthetic feedback is the next best thing, and can/should be a part of launching any products.",
    "one_liner": "Providing quick product and design feedback via digital twins",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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    "batch": "Summer 2024",
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      "America / Canada",
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        "question": "How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)",
        "answer": "We both worked at Uber prior to Promi, where Peter led product for discounts across Uber Eats and Rides. Jiaxin worked on Uber’s core AI team. Peter had the idea for Promi after having seen how wasteful discounts were for the business, and how impactful certain features could be for making discounts more efficient and ROI positive."
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    "url": "https://www.ycombinator.com/companies/promi",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/promi.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/promi-discounts",
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        "user_id": 1824823,
        "full_name": "Peter Moot",
        "title": "Founder",
        "founder_bio": "Co-founder @ Promi. Prior to Promi I led product for discounts at Uber. I have a degree in economics and computer science from Harvard.",
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        "linkedin_url": "https://www.linkedin.com/in/petermoot/",
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      {
        "user_id": 1337968,
        "full_name": "Jiaxin Lin",
        "title": "Founder/CTO",
        "founder_bio": "Co-founder of Promi. Most of my career has been working on recommendation / personalization systems in the e-commerce space.\n\nAvid coder and lifelong learner.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jiaxinlin/",
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    "news": [
      {
        "title": "13 companies from YC Demo Day 1 that are worth paying attention to | TechCrunch",
        "url": "https://techcrunch.com/2024/09/25/13-companies-from-yc-demo-day-1-that-are-worth-paying-attention-to/",
        "date": "Sep 25, 2024"
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    ],
    "launches": [
      {
        "id": 109513,
        "title": "Promi: Evaluate your product concepts with digital twins of your customers",
        "tagline": "We simulate your real customers using your 1st party data for product feedback before you build.",
        "body": "**TL;DR: Promi builds simulated versions of your real users from your product analytics data (Posthog, Stripe, Intercom, etc.). Run your next ideas past them: flows, copy, pricing, onboarding, and see where your users would hesitate, what they'd skip, and why, before anyone writes code.**\n\n<https://youtu.be/VH7s2ATqMBU>\n\nHi! Peter here, cofounder of Promi (S24)\n\n## **The problem**\n\nReal user feedback is the gold standard for deciding what to build and almost nobody gets it, because it's slow and expensive. So teams substitute: survey panels, ICP interviews, and lately AI personas prompted with a demographic sketch. All of them share the same flaw — they don't know _your_ users. The result is confident feedback with no context, and ideas that ship blind anyway.\n\n## **How Promi works**\n\nConnect your product analytics tools. Promi builds behavioral profiles of your actual user segments, not personas, not survey panels, and turns them into simulated users. Describe a proposed change: a flow, copy, pricing, onboarding, and they react the way your real segments tend to: where they'd hesitate, what they'd skip, and why.\n\n## **Why we're building this**\n\nI spent 5 years as a PM at Uber, where real user feedback was the gold standard nobody had time or budget for — so most ideas shipped blind. When we did get feedback, 9 times out of 10 we preferred existing customers over a generic ICP, because real users knew _why_ they used the product. AI feedback needs that same context, so we built Promi to have it: simulated users trained on your customers' actual behavior.\n\nEvery product decision deserves real user feedback. We're making that the default instead of the luxury.\n\n## **Our ask**\n\n**If you're a product team with 3+ months of session data and ideas you're actively debating, reach out — we're onboarding design partners now.** We'll build simulated versions of your users and run your next ideas past them. Then judge us on one thing: did it surface something true about your users that a generic AI couldn't? You know your users; you'll know fast whether our simulations ring true.\n\nSchedule a call: <https://calendly.com/pmoot/promi-overview>\n\n Website: <https://www.trypromi.com> Email: [peter@usepromi.com](mailto:peter@usepromi.com)",
        "url": "https://www.ycombinator.com/launches/SUL-promi-evaluate-your-product-concepts-with-digital-twins-of-your-customers",
        "votes": 4,
        "created_at": "2026-08-06T17:40:12.477Z"
      },
      {
        "id": 82565,
        "title": "Promi - AI powered discounts for ecommerce merchants",
        "tagline": "Send smarter discounts",
        "body": "**tl;dr:** [Promi](https://www.usepromi.com/) helps ecommerce merchants send smarter discounts by leveraging AI to dynamically update discounts and optimize for clearing inventory, varying discount values across products for first order, holiday, etc. campaigns, and better communicating discounts across your website via price strikethroughs and other UI components.\n\nWe are available on the [Shopify app store](https://apps.shopify.com/promi-discounts)!\n\n<https://youtu.be/HsVv82xmyNw?si=nr-sLwtCLy18wddi>\n\n👬 **Meet Our Team**\n\n![uploaded image](/media/?type=post&id=82565&key=user_uploads/1824823/cc9ee0e3-efbb-4a81-a5b1-7d442bc0ac28)\n\n[_Peter_](https://www.linkedin.com/in/petermoot/)_: The Discount Guru_\n\nPeter is coming from Uber, where he was the product lead overseeing discounts across Eats and Rides. While there, he launched many of the features we are now building into Promi today. He has a degree in economics from Harvard and would love to talk with you about your pricing and discount strategy.\n\n[_Jiaxin_](https://www.linkedin.com/in/jiaxinlin/)_: The AI mastermind_\n\nJiaxin was the tech lead and founding engineer at Uber’s knowledge graph platform, focusing on recommendations and personalization. Before Uber, Jiaxin worked in AI at Google’s Shopping Recommendations team.\n\n**❌ The Problem**\n\nMost retailers spend 5-10% of their gross merchandise value on discounts to acquire new customers, celebrate holidays, hit sales targets, clear inventory, etc. However, choosing the right discount often involves guesswork. More sophisticated merchants look at what worked well in the past, but they don’t have the time or means to granularly optimize their discounts across products and users, or dynamically update the offers based on order trends. Additionally, many retailers don’t communicate savings available via discount codes on their website until checkout, causing a drop in customer conversion.\n\n# **💡 Our Solution**\n\nPromi enhances discount performance by addressing key issues:\n\n* **Dynamic Updates**: AI-driven adjustments ensure efficient inventory clearance without over-discounting. Specify the volume, timeframe, and pricing guardrails, and Promi will continuously monitor and update discounts.\n* **Improved Communication**: Discounts are displayed site-wide using deep links for price changes and other UI components.\n* **Variable Discounts**: We vary discount values across products to take advantage of differences in profit margins and prices, all under a single code. Your email sign-up and member-only campaigns just got a lot more profitable\n\nThese solutions improved Uber's discount efficiency by more than 40%. Stay tuned for upcoming features like personalized discounts, performance measurement dashboards, and experiment setups!\n\n![uploaded image](/media/?type=post&id=82565&key=user_uploads/1824823/8e18f1bb-1e59-4555-9384-3a6b3bca6f45)\n\n**🙏 Ask: Check out Promi!**\n\nIf you run a Shopify store or know someone who does, we'd love to chat. Email us at [peter@usepromi.com](mailto:peter@usepromi.com).\n\nSee our website and app listing below:\n\n* <https://www.usepromi.com/>\n* <https://apps.shopify.com/promi-discounts>",
        "url": "https://www.ycombinator.com/launches/LTh-promi-ai-powered-discounts-for-ecommerce-merchants",
        "votes": 31,
        "created_at": "2024-07-30T18:39:55.548Z"
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  {
    "id": 29732,
    "name": "ReactWise",
    "slug": "reactwise",
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    "website": "https://www.reactwise.com/",
    "all_locations": "Cambridge, England, United Kingdom",
    "long_description": "Our Mission: \r\nWe aim to accelerate and automate chemical process development by equipping wet-lab chemists with the power of data-driven optimization and robotic execution of experiments.\r\n\r\n\r\nThe Problem: \r\nThe discovery of novel pharmaceuticals is one of our most important weapons in fighting disease. However, the drug development pipeline is often held up for many months during the design of chemical processes to manufacture these drugs at scale, delaying FDA trials and lengthening the time until drug launch. Designing chemical processes involves the identification of suitable parameters such as catalyst/temperature/solvent. Currently process development is often done via tedious trial-and-error experimentation (slow) or exhaustive screening (expensive and wasteful).\r\n\r\n\r\nOur Approach: \r\nIn our research, we have developed algorithms for chemical process optimization, which leverage transfer learning and Bayesian optimization. We validated the algorithms in the wet lab, showing an up to 95% reduction in required experiments and cost compared to exhaustive screening. We have made our approaches accessible to chemists through our user-friendly no-code software platform and to automated laboratory equipment with our API.",
    "one_liner": "AI Co-Pilot for Chemical Process Optimization",
    "team_size": 10,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1716931653,
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    "batch": "Summer 2024",
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    "url": "https://www.ycombinator.com/companies/reactwise",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/reactwise.json",
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    "country": "GB",
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        "full_name": "Alexander Pomberger",
        "title": "Founder/CEO",
        "founder_bio": "Alexander holds a PhD in chemical engineering, and has been working at the intersection of machine learning, chemistry and lab automation for the past 5 years. In his research, Alexander developed optimization algorithms to aid in designing manufacturing processes for novel pharmaceuticals. Alexander launched ReactWise to democratize access to AI in pharma & biotech with no-code software.",
        "is_active": true,
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      {
        "user_id": 1675044,
        "full_name": "Daniel Wigh",
        "title": "Founder/CTO",
        "founder_bio": "Daniel holds a PhD in chemical engineering, and has been working at the intersection of machine learning and chemistry for the past 5 years. In his research, Daniel developed optimization algorithms to aid in designing manufacturing processes for novel pharmaceuticals. Daniel launched ReactWise to democratize access to AI in pharma & biotech with no-code software.",
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        "linkedin_url": "https://linkedin.com/in/daniel-wigh",
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    ],
    "jobs": [
      {
        "id": 115217,
        "title": "Front-End Software Engineer (React/Typescript)",
        "url": "https://www.ycombinator.com/companies/reactwise/jobs/BsNJaEY-front-end-software-engineer-react-typescript",
        "location": "Cambridge, England, GB / Remote (GB)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Frontend",
        "salary_range": "£45K - £60K GBP",
        "equity_range": "",
        "experience": "Any (new grads ok)",
        "visa": "US citizenship/visa not required",
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    ],
    "news": [
      {
        "title": "YC-backed ReactWise is applying AI to speed up drug manufacturing | TechCrunch",
        "url": "https://techcrunch.com/2025/03/17/yc-backed-reactwise-is-applying-ai-to-speed-up-drug-manufacturing/",
        "date": "Mar 17, 2025"
      },
      {
        "title": "ReactWise Raises $3.4M to Transform Big Pharma with AI and Self-driving Labs",
        "url": "https://www.reactwise.com/news/reactwise-raises-3-4m-to-transform-big-pharma-with-ai-and-self-driving-labs",
        "date": "Mar 17, 2025"
      }
    ],
    "launches": [
      {
        "id": 81168,
        "title": "ReactWise - AI co-pilot for wet lab chemistry",
        "tagline": "No-code chemical process optimization software for pharma and biotech",
        "body": "**TL;DR:** [ReactWise](https://www.react-wise.com/) aims to accelerate and automate chemical process development by equipping wet lab chemists with the power of data-driven optimization and robotic execution of experiments.\n\n**The Problem**\n\nThe discovery of novel pharmaceuticals is one of our most important weapons in fighting disease. However, the drug development pipeline is often held up for many months during the design of chemical processes to manufacture these drugs at scale, delaying FDA trials and lengthening the time until drug launch. Designing chemical processes involves the identification of suitable parameters such as catalyst/temperature/solvent. Currently, process development is often done via tedious trial-and-error experimentation (slow) or exhaustive screening (expensive and wasteful). \n\n![uploaded image](/media/?type=post&id=81168&key=user_uploads/1700794/145e099d-1763-438b-9dd2-05a6d8e01ce5)\n\n**Our Approach**\n\nIn our research, we have developed algorithms for chemical process optimization that leverage transfer learning and Bayesian optimization. We validated the algorithms in the wet lab, showing an up to **95% reduction in experimental burden and cost** when compared to exhaustive screening. We have made our approaches accessible to human experimentalists through our user-friendly no-code software platform, and to automated laboratory equipment with our API.\n\n![uploaded image](/media/?type=post&id=81168&key=user_uploads/1700794/a9e5d7e0-86c4-469f-8374-2ef728597a89)\n\n**Our Background**\n\nWe ([Daniel](https://linkedin.com/in/daniel-wigh) and [Alexander](https://linkedin.com/in/apomberger)) recently completed our PhDs in Machine Learning for Chemistry at the University of Cambridge. We built an automated lab to validate our optimization strategies during our research and are now working to accelerate and automate chemistry & biotech.\n\n![uploaded image](/media/?type=post&id=81168&key=user_uploads/1700794/3b26b7be-6625-4015-a44a-79df46462aec)\n\n**Our Ask**\n\n* We are keen to talk to **innovation managers and labheads** **at pharmaceutical and biotech** companies who\n  * Work with experimentalists who would benefit from our no-code optimization platform\n  * Want to build an automated lab but are not sure where to start\n* We are also interested in speaking with **equipment manufacturers** so we can integrate our software with their hardware\n\n\\\nClick here to [book a demo](https://www.react-wise.com/join-waitlist) with us, or email us via [info@react-wise.com](mailto:info@react-wise.com).",
        "url": "https://www.ycombinator.com/launches/L7A-reactwise-ai-co-pilot-for-wet-lab-chemistry",
        "votes": 23,
        "created_at": "2024-05-29T15:12:18.001Z"
      }
    ]
  },
  {
    "id": 29734,
    "name": "Vibe",
    "slug": "vibe",
    "former_names": [
      "Focal"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/36316f5320bb1c084323c3ac2eb95b29e9fa8207.png",
    "website": "https://vibe.codes",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Vibe enables everyone to turn their thoughts into real world apps through conversation. Let’s vibe code the future.",
    "one_liner": "Making everyone a software engineer",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1720475145,
    "tags": [
      "Developer Tools",
      "SaaS",
      "B2B",
      "Web Development",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
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        "body": "**TLDR:**\n\n[MagiCode](https://www.magicode.ai/) is a **proactive** AI pair programmer that intuitively understands developers' actions in real-time, actively anticipates their next steps, and offers assistance even before they ask.\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXdi0SQOOv0alhPERCWVCENvw7nB-U00PP82FQpevrGFc4QLGSwd53sQQ7E0FR5Vomx_GZxdx_9fflyHAWQi1-nJpg-L1KfwOqf-xvYbVInucv5T-rYfH0sqeIuhzU1xMsjgbbUvewcy7J0_2SqrGUWTWZzj?key=IP7Rk802TWBSSnOAUrqnyQ)\n\n**Why are we building this? ⚙️**\n\nWe were active users of various AI coding tools even before they were named “pair programmers”. However, the experience was underwhelming because: \n\n1. they are **not really “intelligent”**: we always had to type out multiple shortcuts for our queries to be routed to the right AI agent to handle. \n2. when we were deeply immersed in a task/implementation, we often didn’t know **how, or what** to ask the AI Coding tool. For example, when implementing a button that triggers a POST/ request to the backend API, we have to constantly jump around multiple files, making modifications across different functions. In this scenario, before asking the AI to help us with implementation, we actually have to spend time thinking about “how” to frame our questions:\n\n \n\n* How do we explain what the functionality of this button is? \n* Which file names should we mention to the AI as being relevant? \n* How can we succinctly phrase all relevant context, including current progress or past edits/changes that we have made, so that the AI will give us the best output?\n\nAs a result, we often resorted to doing everything ourselves to avoid the tedious back-and-forth. \n\nIn those moments, we realized what we wanted was a tool that could **fetch global context** without relying on shortcut commands, anticipate our needs, and even understand what we were thinking before typing anything— something that was always **“on the same page”** with us. That’s exactly what led us to create MagiCode— a tool that can answer all the developer’s questions intelligently, and also **proactively assist** without needing to be prompted.\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXcgtDCwIm0PlMe_DCSQip8X8jXRnbAeLD9SCjhBN43ZcTRbnyfl8Mhi3WTfOVJyXwaYO50Ef2ZZtGPcq8bKngNnBgc0071stmvyCd1HdlYlJUVJfKNLKGT1IWpoLmX9B2GroQSiBhGjQj3sS7reml024gq1?key=IP7Rk802TWBSSnOAUrqnyQ)\n\n**How are we different from existing solutions? 🤔**\n\n* **Proactive Assistance:** We bring the answers to you without you even asking. MagiCode is designed to constantly analyze the project's state and make suggestions for what you can do next. As a user, all you have to do is click on a suggestion and watch as MagiCode works on files asynchronously and brings you the finalized results with easy-to-view diff files. \n* **Personalized Memory:**  We have personalized memory retainment of your editing history, editor state, and user activity. We designed an intelligent system that processes all this information in a low-latency manner and uses it naturally when answering the user’s queries.\n\n### **Watch MagiCode in action! 🤯**\n\nhttps://www.youtube.com/watch?v=EPM_eOL8BRE\n\n### **Our ask 🙏**\n\nWe are currently onboarding users for MagiCode. \n\n* If you’d love to try MagiCode, we are active on **Discord** and would be happy to help you onboard and answer any questions. You can join our discord here: https://discord.gg/tqveBrwd \n* If you know an engineer who is interested in trying out AI Coding tools, tell them about MagiCode! \n* You can also reach out to us directly at [hello@magicode.ai](mailto:hello@magicode.ai) to talk more about the future of AI-powered coding. Feel free to book a time with us here: https://www.magicode.ai/book-a-demo/ 😊\n\nLet’s build with Magic! ",
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        "title": "Hestus - AI for hardware development",
        "tagline": "Hestus helps engineers work 2.5x faster with 4x fewer clicks",
        "body": "Hi YC!\n\nThis is [Kevin](https://www.linkedin.com/in/kevin-chu-11a4511/) and [Sohrab](https://www.linkedin.com/in/sohrabhaghighat) from Hestus and we are building an AI for Hardware Design. \n\n# **TL;DR: There is no such thing like code completion for CAD, so we built it.**\n\nOur first tool, Sketch Helper, natively integrates into your CAD environment. It understands your design intent, and predicts your next move.\n\n* Makes sketching **2.5x faster**\n* Requires **4x fewer** clicks\n* Accept suggestions with a single key stroke\n* Over **1000 engineers** are already using it\n\n[**https://youtu.be/-I6IZCwt-rw**](https://youtu.be/-I6IZCwt-rw)\n\n# **Problem**\n\nMechanical engineers are fast at conceptual design but get buried in \"click-work.\"  Getting a concept ready for manufacturing takes countless, manual and error-prone clicks to assign constraints and dimensions.\n\nAs one of our users said: \n\n> Only a third of my time goes into real design work. The rest is just clicking through sketches and dimensions, and I can only click so fast. \n\n# **Solution**\n\nWe built “Sketch Helper,” a copilot for sketching in CAD. \n\nIt understands your design intent and proposes your next move, may it be adding constraints, missing dimensions, or even additional geometries to your sketch. You can preview any of the proposed changes in a red overlay and accept it with a single keystroke.\n\n![uploaded image](/media/?type=post&id=95212&key=user_uploads/295796/26c0f9a0-6a9e-43e5-abc3-aab8f5b9f773)\n\nNext, we are going to expand into full 3D and build “**Mate Helper**” and “**GD&T Helper**” to help not just with design but as well as design for manufacturing.\n\n# **The big vision**\n\nThe biggest problem in hardware is the silo between design and manufacturing, which leads to endless, costly iterations.\n\nThe push to reshore American manufacturing has hit a major bottleneck: we lack the deep bench of manufacturing experts we once had. As Tim Cook noted, the skilled tooling and manufacturing expertise is no longer concentrated here (https://youtu.be/_ng8xQ-SNGc?si=WzfP4aCJmec1lJo4&t=547).\n\nOur AI learns design intent by observing an engineer's actions in CAD. By starting with sketching, we are building the foundation model that understands why a part is designed a certain way.\n\nThis is the key to an AI that can provide real-time manufacturability feedback, bridging the gap between design and manufacturing and automating the tooling design process.\n\n# **Who we are why we are the team to crack this nut**\n\nWe’ve felt this pain firsthand. We (Kevin and Sohrab) were both early employees at Cruise. Kevin led the AV engineering team, scaling it from 20 to 300+ people. Sohrab founded the rocket company SpaceRyde (YC W19) securing millions in launch contracts and led laser tech development at Mitsubishi. We’ve built and shipped AI for self-driving cars, surgical robotics, and rocket launches. Now, we are fixing hardware development.\n\n# **Ask**\n\n* For Autodesk Fusion users: Please try [Sketch Helper](http://www.hestus.co/download). It's free and we guarantee it will make you faster.\n* For everyone else: What CAD platform do you or your team use? Reach\n\n  us out at [founders@hestus.co](mailto:founders@hestus.co). We are prioritizing our expansion based on your feedback.\n* If you are building hardware, we would love to hear about the biggest challenges that slow you down.\n\n![uploaded image](/media/?type=post&id=95212&key=user_uploads/295796/282427a7-5fd1-4532-bcf8-30182920c3a5)\n\n",
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        "title": "Pinnacle📱- RCS (Next-Gen SMS) API for developers",
        "tagline": "Shop in text; programmable interactive, app-like texts",
        "body": "Hey YC! We’re [Sean](https://www.linkedin.com/in/seanroades/) and [Ivan](https://www.linkedin.com/in/aivanzhang/) from [Pinnacle](https://www.trypinnacle.app/). \\\n\\\nToday, we’re launching [our API](https://docs.trypinnacle.app/api-reference/endpoint/introduction) to send and receive RCS (Next-Gen SMS) text messages natively on user’s devices. We’re also launching an [SDK for Python](https://docs.trypinnacle.app/documentation/python/quick-start) (\\`pip install rcs\\`). If you’re currently sending SMS, you should probably be using Pinnacle.\\\n\\\nHere’s a quick example of how we used our API to sell our [Founder Mode hats](https://shop.trypinnacle.app/products/founder-mode-holy-edition-hat?) (certified by Brian himself 😉)\n\n![uploaded image](/media/?type=post&id=84168&key=user_uploads/1439340/3c12589b-527f-4fcc-bc9b-f6ecaf5b555e)\n\n# The problem\n\nShort: SMS sucks. \\\nLong: SMS messages have high friction from sending a message to checking out a customer. Interactivity is very limiting with SMS.\n\n# The solution\n\nShort: RCS rocks.\\\nLong: RCS messages reduce high friction for customers to buy products with a single tap and add interactivity through buttons, card carousels, and actions.\n\n# Why now\nThis hasn't been possible until now. Apple rolled out RCS this week on iOS 18. Carrier adoption has been fully supported on all Android devices just this year. Carrier adoption for iOS completes in a couple months. We segment by device so you can adopt RCS incrementally.\n\n# Our asks\n\n* Share - tell your friends & colleagues about Pinnacle\n* YC Companies - **reach out to us (**[**founders@trypinnacle.app**](mailto:founders@trypinnacle.app)**) to join our private beta**. You'll also get a **free Founder Mode hat**, designed by us, **1000 messages / mo free**, and our **24/7 #FounderMode support**.",
        "url": "https://www.ycombinator.com/launches/LtY-pinnacle-rcs-next-gen-sms-api-for-developers",
        "votes": 62,
        "created_at": "2024-09-19T21:58:11.562Z"
      }
    ]
  },
  {
    "id": 29781,
    "name": "Cerulion",
    "slug": "cerulion",
    "former_names": [
      "RenardOS"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/336383ad58869871ce591b4e1b31dd374319435c.png",
    "website": "https://www.cerulion.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Cerulion is an open source operating system for robots built by 2 MIT robotics PhDs. Engineers at Amazon Robotics and Boston Dynamics AI Institute are using us to develop faster and ship more reliable robots than with ROS. With up to 1000x improvements in communications performance over state of the art, Cerulion is enabling the next generation of embodied AI.",
    "one_liner": "Open source operating system for robots",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1720480188,
    "tags": [],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/cerulion",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/cerulion.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/cerulion",
    "x_url": "https://x.com/CerulionInc",
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    "app_video_url": null,
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    "primary_partner": {
      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
    },
    "founders": [
      {
        "user_id": 1938980,
        "full_name": "Lakshay Sharma",
        "title": "Founder/CEO",
        "founder_bio": "Lakshay is the cofounder/CEO of robotics middleware startup Cerulion. Prior to this, he studied computer engineering, astrophysics and robotics at the University of Pennsylvania, and researched robot motion planners at MIT.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/lakshay2010sharma/",
        "x_url": "https://x.com/_lakshays_",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ff9b45b0153f1674c489e44fd43563ce4e4baf51.jpg"
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    "jobs": [
      {
        "id": 72837,
        "title": "Founding Middleware Lead",
        "url": "https://www.ycombinator.com/companies/cerulion/jobs/C21ngNY-founding-middleware-lead",
        "location": "Mountain View, CA, US / Boston, MA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Robotics",
        "salary_range": "$145K - $180K",
        "equity_range": "",
        "experience": "3+ years",
        "visa": "Will sponsor",
        "skills": [
          "Bash/Shell",
          "C++",
          "Git",
          "Rust"
        ]
      }
    ],
    "news": [
      {
        "title": "Predicting AI’s future from Y Combinator’s new startup cohort - PitchBook",
        "url": "https://pitchbook.com/news/articles/y-combinator-demo-day-ai-startups-analysis",
        "date": "Sep 25, 2024"
      }
    ],
    "launches": [
      {
        "id": 83665,
        "title": "Cerulion 🤖 Fast, reliable, cross-platform robot middleware",
        "tagline": "Cerulion enables lightning-fast, rock-solid communications for safe robots with an easy, cross-platform GUI.",
        "body": "Robots are expensive and hard to develop/debug. [Cerulion](https://www.cerulion.com/) solves the robot tooling problem to cut down development times by up to 10x.\n\n# The Problem\n\nThe incredibly high capital costs required for robotics, combined with the inherently non-deterministic nature of embodied intelligence, result in an unpredictable system where even attempts, let alone failures, are cost-prohibitive.\n\n**Robots are expensive and hard.**\n\nAnd yet, despite time on hardware being such a precious resource, roboticists today are absolutely wasting 90% of it fighting against unoptimized tooling. Some common complaints are:\n\n* Needlessly complex to install, maintain, and document\n* Incredibly steep learning curve for non-transferable skills\n* Poor observability into a robot's belief\n* Artificial non-determinism induced by slow or unreliable message-passing\n* Unreliable network protocols and IPCs\n* System breakdown due to poor inter-robot communication\n* Unreliable logging and cumbersome/nondeterministic log replay\n* Wasting precious field time parsing 1000s of lines of runtime errors whooshing past the screen\n\nAnd the list goes on and on.\n\n**Robot tooling today is broken. Unacceptably so.**\n\n# Our Solution: Performance never looked this good!\n\n![uploaded image](/media/?type=post&id=83665&key=user_uploads/1938980/f6733a7c-7d31-4bf8-9198-d19e786c5650)\n\n* **Packaged as an app, rather than a CLI tool:** Instead of shipping as a bunch of CLI tools to be installed, patched, and reinstalled, Cerulion is an app you can download on Windows, Mac, or Linux. It will smartly detect and handle any dependencies as needed.\n* **Intuitive, cross-platform visualizer:** The sleek, easy-to-use GUI is the main way of communicating with your robot in the field, which means you can run it with minimal resources on your favorite long-lasting laptop with any OS, instead of **_that_** RGB laptop with a gaming GPU running Linux.\n* **Minimal boilerplate and setup:** The way you program robots in Cerulion is designed to get out of your way, so you can focus on the planner and perception algorithms instead of worrying about the inter-process comms, IP addresses, or network routes.\n* **Fast and reliable communication:** We leverage cutting-edge Rust-based networking and IPC stacks like [Zenoh](https://github.com/eclipse-zenoh/zenoh) and [IceOryx2](https://github.com/eclipse-iceoryx/iceoryx2), along with tried and tested C++ alternatives like [LCM](https://github.com/lcm-proj/lcm) and [IceOryx](https://github.com/eclipse-iceoryx/iceoryx). By ensuring communications don't fail silently and messages are delivered when expected, Cerulion eliminates nasty surprises in safety-critical scenarios.\n\n# Meet The Team\n\n![uploaded image](/media/?type=post&id=83665&key=user_uploads/1938980/62663160-4581-4de2-abb8-0bbb86179aa1)\n\nAs robotics PhD students at MIT, [Lakshay](https://www.linkedin.com/in/lakshay2010sharma/) and [Se Hwan](https://www.linkedin.com/in/sehwan-jeon/) have gathered years of experience (and frustration) working on robots, and want to see a world where you can take robot reliability for granted.\n\n# Our Ask\n\nHave experience with ROS or any other robot middleware? Did we miss something above that you really need? Send us a message at [founders@cerulion.com](mailto:founders@cerulion.com)!\n\nWe always love (and are happy to provide) warm intros to people working on robots and automation.\n\nAnd of course, if you need help with your robot system, or are curious about any of this, we're happy to chat!\n\nP.S. — Please star our [GitHub repo](https://github.com/cerulion-inc/cerulion)!",
        "url": "https://www.ycombinator.com/launches/LlR-cerulion-fast-reliable-cross-platform-robot-middleware",
        "votes": 26,
        "created_at": "2024-09-02T15:47:55.198Z"
      }
    ]
  },
  {
    "id": 29782,
    "name": "Laminar",
    "slug": "laminar",
    "former_names": [
      "Laminar AI"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f68c82dc13524e235198c783318ae1b1aa5d7432.png",
    "website": "https://laminar.sh",
    "all_locations": "London, England, United Kingdom",
    "long_description": "Laminar is open-source observability for AI agents. Trace complex workflows, replay and debug agent runs, and detect anomalies across trajectories at scale.",
    "one_liner": "Understand why your AI agent breaks. Iterate fast to fix it.",
    "team_size": 6,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1721337823,
    "tags": [
      "AIOps",
      "Developer Tools",
      "SaaS",
      "B2B",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United Kingdom",
      "Europe"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/laminar",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/laminar.json",
    "year_founded": 2024,
    "city": "London",
    "country": "GB",
    "linkedin_url": "https://www.linkedin.com/company/lmnr-ai/",
    "x_url": "",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/lmnr-ai/lmnr",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/f68c82dc13524e235198c783318ae1b1aa5d7432.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
    },
    "founders": [
      {
        "user_id": 1771812,
        "full_name": "Robert Kim",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder and CEO @ Laminar (lmnr.ai). Previously, I interned at Palantir where I built semantic search package which now powers many internal AI teams and worked on resource allocation engine at core infrastructure team. I also interned at Bloomberg where I scaled market tick processing pipeline by 10x to 10M ticks/s.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/skull8888888/",
        "x_url": "https://twitter.com/skull8888888888",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b1164aa2d27587dbe70dd830f8ae356064e709d5.jpg"
      },
      {
        "user_id": 1980084,
        "full_name": "Din Mailibay",
        "title": "Founder/CTO",
        "founder_bio": "Co-founder and CTO at Laminar (laminar.sh). Previously, I have worked at Amazon for 2 years building and scaling critical payments infrastructure. Before that, I've spent a year creating ML infrastructure for a drug discovery biotech startup in Korea.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/dinmukhamedm",
        "x_url": "https://twitter.com/din_mlb",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c56af6f86306ce69d00244d2229612165fb00abc.jpg"
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    "jobs": [],
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    "launches": [
      {
        "id": 98606,
        "title": "Laminar – Understand why your agent failed. Iterate fast to fix it.",
        "tagline": "Open-source observability platform for long-running agents — trace in one line, replay-debug from any step, detect patterns at scale.",
        "body": "Hey everyone, Robert from Laminar (YC S24) here. The entire observability space was built for request-response LLM apps. Nobody was building for Agents that run for 40 minutes and fail in ways you can't reproduce. So we did.\n\n## Tracing that actually helps you understand what happened\n\nMost observability platforms just collect data and wait until you go look at it. And when you do, you get a tree of spans. You click into one, read it, go back, click the next one, try to hold the context in your head. For a simple LLM call, that's fine. For an agent that ran for 30 minutes and made 200 decisions, it's practically useless.\n\nWe built Laminar's tracing to give you as much information as quickly as possible.\n\nOur trace timeline and **reader mode** lay out the agent's reasoning and actions as a clean, readable feed.\n\n![uploaded image](/media/?type=post&id=98606&key=user_uploads/1771812/73741d82-1719-4062-8cc2-9bd8de880010)\n\nYou open a trace and immediately see what the agent did, what it was thinking, and where things went wrong (we also capture and show application level exceptions). For browser agents, we record **full browser sessions synced with traces**. You literally see what the agent saw at every step → <https://laminar.sh/shared/traces/16fcd540-9583-8bcb-f8e0-8b15ec92c58d>.\n\nIf a trace is too complex to parse visually, you can **chat with it**: ask questions about what happened in natural language, instead of manually digging through hundreds of steps. We take into account the whole context of the trace, not just a single span.\n\n![uploaded image](/media/?type=post&id=98606&key=user_uploads/1771812/87cc29b4-f5c3-4924-ab96-5c52af1fae76)\n\nWe can confidently say that we have the best tracing DX on the market. It’s one line of code to integrate. Laminar SDK auto-patches vast majority of AI frameworks and SDKs, including **Claude Agent SDK, AI SDK, LiteLLM, Browser Use, Stagehand, OpenHands SDK**, and much [more](https://docs.laminar.sh/tracing/integrations/openai). We are the only platform that traces **Claude Agent SDK sub-agents**. When Claude delegates work to sub-agents, you get full visibility into that entire chain, not just the top-level call. Here’s an example of a trace <https://laminar.sh/shared/traces/3f9219d0-8691-daf7-836a-8874ca4c1d9f>.\n\n## The debugger\n\nThis is the feature we wished existed when we were building agents ourselves. When your agent fails 15 minutes into a run, the normal workflow is: restart from scratch, wait for it to reach the same state, hope it reproduces the failure. That's insane.\n\nLaminar starts a local dev server that connects to our platform. You can run your agent directly from our UI, and when a run fails, you go to the exact step where it went wrong. You tweak your prompt or tool definitions right in the UI. And you rerun from that step — with full context preserved.\n\nHere's how it works under the hood: our tracing SDK sits right before the LLM call boundary. When you rerun from a step, we mock all the LLM calls that happened before that point, replaying their original responses. This means the agent walks through its prior steps instantly without actually calling any LLMs and spending any tokens — and crucially, it properly restores external state along the way. If your agent was controlling a browser, the browser gets back to the exact page and DOM state. If it was working in a sandbox, the sandbox is restored. By the time execution reaches your breakpoint, everything — conversation history, tool state, external environment — is exactly as it was. You tweak your prompt, hit rerun, and the agent picks up from there with the real world intact.\n\nHere’s a demo of Laminar debugger.\n\n<https://www.youtube.com/watch?v=iSw8MM6tRvY>\n\n## Signals\n\n![uploaded image](/media/?type=post&id=98606&key=user_uploads/1771812/19af455c-7dfa-46e7-aa40-fbac2b4696a6)\n\nIn development, you care about individual runs. In production, you have thousands of runs and the question changes — it's no longer \"why did this run fail,\" it's \"what's going wrong across all my runs and how often.\"\n\nThat's what Signals solve. You write a short natural language description of what you want to detect — something like \"agent gets stuck in a retry loop\" or \"user gets frustrated and rephrases their request.\" Laminar runs this against every trace, extracts matching events, and then clusters them into patterns. So instead of manually sampling traces hoping to spot trends, you get a structured view of what's actually happening. We use this ourselves to monitor our own agents, and it catches things we'd never find by skimming through traces.\n\n## SQL editor, evals, and more\n\nAll of your data lives is accessible with built-in SQL editor (both in UI and API). You can run arbitrary queries against your traces, spans, and events — build custom dashboards, do ad-hoc analysis, or bulk-create datasets from production traces. Those datasets plug directly into our evals pipeline, so you can run evaluations on real production data instead of synthetic test cases.\n\n## Laminar\n\nLeading agent companies like Browser Use, OpenHands, Rye.com, Alai and many more use Laminar in production. Laminar is fully open source and extremely fast (written in Rust). Self-host it anywhere or use our managed platform (<https://laminar.sh>).\n\n**Our ask:**\n\n* If you're shipping agents and debugging is painful, we'd love to help — [founders@lmnr.ai](mailto:founders@lmnr.ai)\n* Intros to teams running long running agents would be huge\n* Star us on GitHub: <https://github.com/lmnr-ai/lmnr>\n\n🔗 <https://laminar.sh>",
        "url": "https://www.ycombinator.com/launches/PeQ-laminar-understand-why-your-agent-failed-iterate-fast-to-fix-it",
        "votes": 6,
        "created_at": "2026-03-09T00:35:53.684Z"
      },
      {
        "id": 89930,
        "title": "Laminar: The Missing Developer Tool for Browser Agents",
        "tagline": "Laminar captures browser session recordings and syncs them with agent traces.",
        "body": "Robert and Din from Laminar here. We created a new type of observability, which enabled us to build the SOTA open-source browser agent.\n\n# The Problem\n\nBrowser agents are powerful but notoriously difficult to develop and debug. When your agent fails, traditional traces just show a wall of text logs without context. You can't see what the agent was looking at when it made decisions, why it chose certain actions, or what exactly went wrong. It's like trying to debug a self-driving car without any camera footage – practically impossible.\n\nThis lack of proper observability tools has been the biggest barrier to building reliable browser agents.\n\n# The Solution\n\n![uploaded image](/media/?type=post&id=89930&key=user_uploads/1771812/0da20a73-6dc1-4d3d-8561-dc38dd8cb624)\n\nLaminar created the missing piece in browser agent development: complete visual context for every agent action and decision. Our platform records high-quality browser sessions and perfectly synchronizes them with agent traces. Now developers can:\n\n1. **See what the agent sees** - Watch the complete visual journey of your agent as it navigates websites\n2. **Pinpoint exact failure points** - Identify precisely where and why agents make mistakes\n3. **Debug with context** - Understand agent decisions with full visual and trace context\n\n# Results\n\nUsing our own tools, we built Index - open-source browser agent that achieves 92% on WebVoyager benchmark, setting a new state of the art. Index can handle everything from research tasks to complex automations in apps like Google Sheets. In other words, we created a reliable **API layer to any website** that you can simply prompt with natural language.\n\n# Integrations\n\nLaminar seamlessly integrates with AI browser frameworks like **Stagehand** and **Browser Use** - integration takes just 2 lines of code.\n\n# Ask\n\n* **Build better agents:** Try Laminar today for your browser and AI agent development => <https://lmnr.ai>\n* **Explore our open source agent:** Check out Index at [github.com/lmnr-ai/index](https://github.com/lmnr-ai/index)\n* **Dive into docs:** Comprehensive guides at <https://docs.lmnr.ai>\n\nWe're looking for early adopters and feedback! Reach out to us at [founders@lmnr.ai](mailto:founders@laminar.ai) and join our [discord](https://discord.com/invite/nNFUUDAKub).",
        "url": "https://www.ycombinator.com/launches/NOU-laminar-the-missing-developer-tool-for-browser-agents",
        "votes": 11,
        "created_at": "2025-04-28T22:25:16.716Z"
      },
      {
        "id": 83572,
        "title": "Laminar - Open-source observability and analytics for complex LLM apps",
        "tagline": "Observability and analytics which helps you track LLM apps in production.",
        "body": "**tldr: Laminar is an open-source developer platform that provides full instrumentation of LLM applications and combines trace data with event-based analytics.**\n\n**—**\n\nHey everyone, we’re Robert, Din, and Temirlan. Previously, we built infrastructure at Palantir, Amazon, and Bloomberg — now, we’re building an open-source platform to help developers understand how their LLM apps perform in production.\n\n![uploaded image](/media/?type=post&id=83572&key=user_uploads/1771812/e4140bd4-1ae9-453d-8457-2564c3820cbc)\n\n# Why do LLM apps need observability from day 0?\n\n![uploaded image](/media/?type=post&id=83572&key=user_uploads/1771812/81e46417-9b77-4368-ab0f-c04b8b84556e)\n\nLLMs are stochastic, and designing robust software around them (e.g., RAG, Agents) is an iterative process. A great observability platform not only facilitates this process, but actually makes it more productive. Hence, many AI developers adopt observability tools early on.\n\nLaminar goes beyond single LLM call tracing and provides tools for entire app instrumentation and powerful UI for full trace visualization, trace search, and session grouping.\n\n## What is different about analytics for LLM apps?\n\n![uploaded image](/media/?type=post&id=83572&key=user_uploads/1771812/29d881c9-de4c-416a-be18-d17638d67135)\n\nLLM apps produce traces, which are essentially very rich text. Traditional event-based analytics tools are not built for extracting metrics from this kind of data.\n\nCurrently, AI devs spend a good chunk of their time manually inspecting traces to understand usage patterns of their LLM apps. As they scale, manual inspection is not feasible anymore.\n\nLaminar tackles this problem by using other LLMs to process rich text outputs in the background. With Laminar, developers can define custom events, such as “USER SENTIMENT,” to collect user sentiments and track this metric at scale as they deploy their LLM apps into production.\n\nEach event is linked to the trace that produced it, and developers can understand when and why certain semantic events have happened. It gives developers deeper understanding of the performance and usage of their LLM apps.\n\n## Our ask\n\n* Star our repo → <https://github.com/lmnr-ai/lmnr>\n* Start tracing and tracking events with a managed version of our open-source platform here → <https://www.lmnr.ai>\n* [Join our Discord](https://discord.com/invite/nNFUUDAKub)\n* Connect us with anyone who builds software around LLMs and would greatly benefit from a tool like this!",
        "url": "https://www.ycombinator.com/launches/Ljw-laminar-open-source-observability-and-analytics-for-complex-llm-apps",
        "votes": 17,
        "created_at": "2024-08-29T15:16:33.971Z"
      },
      {
        "id": 82294,
        "title": "Laminar - Developer platform to ship reliable LLM agents 10x faster",
        "tagline": "Combining orchestration, evals, data, and observability into a single platform.",
        "body": "# tl;dr: Laminar is a developer platform that combines orchestration, evaluations, data, and observability to empower AI developers to ship reliable LLM applications 10x faster. Get started for free → [lmnr.ai.](https://www.lmnr.ai)\n\nHey everyone, we’re Robert, Din and Temirlan. Previously, we built infrastructure at Palantir, Amazon, and Bloomberg— now our goal is to help AI developers ship reliable LLM applications faster.\n\n![uploaded image](/media/?type=post&id=82294&key=user_uploads/1771812/1a4a4a99-7e50-4bcd-86ff-8d2a5474a091)\n\n# ❌ The Problem\n\nLLMs are stochastic, and designing robust software around them (e.g. LLM agents) demands rapid iteration on core logic and prompts, constant monitoring and a structured way of testing new changes. Existing solutions are vertical and the burden of maintaining “glue” between them is still on the developers, which inevitably slows them down.\n\n# ✅ Our Solution\n\nLaminar is a dev platform that combines orchestration, evaluations, data, and observability to help AI devs to ship reliable LLM applications 10x faster. We provide:\n\n* a GUI to build LLM applications as dynamic graphs with seamless local code interfacing.\n* an [open-source package](https://github.com/lmnr-ai/lmnr-python) to generate abstraction-free code from these graphs directly into developers' codebases.\n* a state-of-the art evaluation platform that lets devs build fast and custom evaluators without managing evaluation infrastructure themselves.\n* a data infrastructure with built-in support for vector search over datasets and files. Data can be easily ingested into LLMs and LLMs can write to the datasets, creating a self-improving data flywheel.\n* a low latency logging and observability infrastructure.\n\n# Orchestration\n\nAs devs, we love to code everything ourselves, but we’ve realized the fastest way of iterating on LLM application logic is via graph UI. So, we’ve built the ultimate LLM “IDE”, where you build your LLM applications as dynamic graphs. You can build cyclical flows, route to different tools, and collaborate with your teammates in real-time!\n\n![uploaded image](/media/?type=post&id=82294&key=user_uploads/1771812/be5a68c2-4440-4fd3-92e7-71c7436e13c8)\n\nGraphs can seamlessly interface with local code. “Function node” can call local functions on your server, right from our UI or our SDK. It’s a huge game changer for testing of LLM agents which call different tools and then circle the response back to LLMs. In the gif below, local function “save_result_to_db“, which runs on a server on my computer, is directly called from our UI.\n\n![uploaded image](/media/?type=post&id=82294&key=user_uploads/1771812/17ade57e-5551-4db3-a036-0bed9956a79e)\n\nUsing our [open-source package](https://github.com/lmnr-ai/lmnr-python), you can generate zero-abstraction code from graph definition, which exactly replicates the graph functionality. Code is generated as pure functions right inside your repo, and you have total freedom to modify it however you want. It is extremely valuable for the devs who are tired of frameworks with myriads of layers of abstraction.\n\n![uploaded image](/media/?type=post&id=82294&key=user_uploads/1771812/6955178c-ef6a-4b26-bac9-39fdebe6f1ac)\n\nYou can also deploy LLM pipelines as API endpoints on our infrastructure and easily call them via our Python/TS sdks.\n\n![uploaded image](/media/?type=post&id=82294&key=user_uploads/1771812/d071c79f-9b3c-4376-9de1-c9cccd401e6b)\n\n# Evaluations\n\n![uploaded image](/media/?type=post&id=82294&key=user_uploads/1771812/799c93b7-c273-4b65-ac0c-50a3e360952c)\n\nLaminar pipeline builder can be used to build custom and flexible evaluation pipelines that seamlessly interface with local code. You can start from something simple like exact matching and then build a custom LLM-as-a-judge pipeline tailored to your specific use case. You can upload large datasets and run evaluations on thousands of data points at the same time, and get all statistics about the run in real time. All of this without the pain of managing evaluation infrastructure yourself.\n\n# Observability\n\n![uploaded image](/media/?type=post&id=82294&key=user_uploads/1771812/f6d0e26d-60d7-4371-a558-a36006d8cd43)\n\nWhether you decide to host LLM pipelines on our platform or generate code from graphs, all pipeline runs are logged and you can easily inspect the traces in the convenient UI.\n\n# Conclusion\n\nLaminar aims to deliver the best developer experience for AI developers. We remove unnecessary friction and burden of managing infrastructure. We let you focus on building the best AI products and ship them 10x faster!\n\n# Our ask\n\n* Start building reliable LLM agents right now for free → <https://www.lmnr.ai>\n* Check out [open-source code gen package](https://github.com/lmnr-ai/lmnr-python)\n* Connect us with anyone who builds software around LLMs and would greatly benefit from a tool like this!\n* [Join our Discord](https://discord.com/invite/nNFUUDAKub)",
        "url": "https://www.ycombinator.com/launches/LPK-laminar-developer-platform-to-ship-reliable-llm-agents-10x-faster",
        "votes": 97,
        "created_at": "2024-07-20T04:14:28.826Z"
      }
    ]
  },
  {
    "id": 29797,
    "name": "Haystack",
    "slug": "haystackeditor",
    "former_names": [
      "Haystack Software"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/988853e97230d398301aa8250ff990964f2f4620.png",
    "website": "https://haystack.sh/",
    "all_locations": "New York City, NY, USA",
    "long_description": "Haystack automatically learns real customer journeys from production traffic, figures out which ones a code change could affect, and replays them in isolated copies of production to catch regressions before they ship.\r\n\r\nWhen something breaks, Haystack shows exactly what changed across the UI, network calls, and events, then gives the failure back to your coding agent to fix and rerun. Teams get high-fidelity QA without having to write or maintain test cases.",
    "one_liner": "Replay real customer journeys against every change before you ship",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1722315932,
    "tags": [
      "Developer Tools",
      "B2B",
      "Productivity",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/haystackeditor",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/haystackeditor.json",
    "year_founded": 2024,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/104745614",
    "x_url": "https://x.com/AkshaySubr42403",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/988853e97230d398301aa8250ff990964f2f4620.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "David Lieb",
      "url": "https://www.ycombinator.com/people/david-lieb"
    },
    "founders": [
      {
        "user_id": 2258920,
        "full_name": "Akshay Subramaniam",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder of Haystack Software. Enjoys building emulators, video games, and productivity software. \n\nPreviously was a software engineer at Figma, where I led the multi-edit launch and helped launch Find and Replace, accessibility in FigJam, and more!",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/akshay-s-152126139/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/472b417ade90b938dedd2e61598178f0fd4ab91c.jpg"
      },
      {
        "user_id": 1976192,
        "full_name": "Jake Yatvitskiy",
        "title": "Founder/CTO",
        "founder_bio": "Cofounder of Haystack Software. Experienced with AI and Cloud technologies. Previously worked in the High-Performance Computing division at AWS and received a Master's Degree in Machine Learning from Columbia University",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jake-yatvitskiy/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f833acc97764c214609c48402678478634c1e8b4.jpg"
      }
    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 83226,
        "title": "Haystack Editor: An AI-powered code editor built on top of a digital canvas",
        "tagline": "Haystack automates the tedious parts of software development so that engineers can focus on the important stuff!",
        "body": "**TL;DR:** Navigating and refactoring in codebases sucks! No engineer likes going through mountains of files to find the right spots where they want to make changes and then do the complicated plumbing to make those changes work.\n\n[Haystack](https://haystackeditor.com/) is a standalone code editor that makes this much faster so engineers can focus on actually writing code. In Haystack, users can explore and edit their code on a 2D canvas with a navigational copilot assisting them every step of the way.\n\n![uploaded image](/media/?type=post&id=83226&key=user_uploads/1538506/57802433-cc2e-4a5a-992e-ad67c23a570c)\n\n**Our Ask**: Engineers have really enjoyed the smooth experience of editing their codebase in Haystack. Join them at [https://haystackeditor.com](https://haystackeditor.com/)! It takes just a single click to import your VS Code extensions and settings, so you can get to coding straight away.\n\nHi everyone! We’re [Akshay Subramaniam](https://www.linkedin.com/in/akshay-s-152126139/) and [Jake Yatvitskiy](https://www.linkedin.com/in/jake-yatvitskiy/), and we’re building Haystack.\n\n![uploaded image](/media/?type=post&id=83226&key=user_uploads/1538506/1c4592f6-265d-44af-b2d6-80b8f1664504)\n\n**The Problem:**\\\nHaystack was born out of our frustrations with working in large and mature codebases, specifically with navigating and editing functional flows. A great example of a functional flow is the code flow for adding an item to the Amazon shopping cart — from the database layer all the way to the frontend UI.\n\nOftentimes dealing with such flows would involve navigating a maze of files and functions, and making any edits would involve a lengthy process of doing corresponding downstream/upstream plumbing.\\\n\\\n**The Solution:**\n\nHaystack attempts to address this in the following ways:\n\n1. It allows you to explore your codebase as a directed graph of functions, classes, etc, on the canvas. We feel like this better fits how your mind understands your codebase and helps you find and alter functional flows more intuitively.\n2. It has a navigational copilot that makes edits across files or functions much easier. After you make some changes, Haystack will try to predict your next action and create functions/methods or refactor upstream/downstream code for you. Haystack will surface these speculative edits on the canvas in a way that you can easily dismiss or incorporate them, allowing you to make large-scale changes with a few clicks or keystrokes.\n\n[See Haystack in action!](https://www.youtube.com/watch?v=c2uZnR5D_cc)\\\n\\\n\\\n**Our Ask, Again:**\\\nDownload and use Haystack at <https://haystackeditor.com/>!",
        "url": "https://www.ycombinator.com/launches/LeM-haystack-editor-an-ai-powered-code-editor-built-on-top-of-a-digital-canvas",
        "votes": 22,
        "created_at": "2024-08-20T16:49:36.240Z"
      }
    ]
  },
  {
    "id": 29799,
    "name": "Helium",
    "slug": "helium",
    "former_names": [
      "CloudCaptain"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/46d487203d596b97a146790985b19ea2f9776e5e.png",
    "website": "https://tryhelium.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Helium is building self-improving software — AI that continuously experiments on key moments in the user funnel to boost revenue. Our first customer, a social app with 20M MAU, uses Helium to test new in-app paywalls to get more users to subscribe. \r\n\r\nZach previously made $100M+ in growth experiments at Uber, Shishir led the first LLM features for Alexa, and Anish worked at Meta building ML to automatically experiment on ads, increasing Instagram ads conversion by 10%. ",
    "one_liner": "Self Improving Software",
    "team_size": 9,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1722968896,
    "tags": [],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/helium",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/helium.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/uplikehelium",
    "x_url": "",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/cloudcaptainai",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/46d487203d596b97a146790985b19ea2f9776e5e.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "David Lieb",
      "url": "https://www.ycombinator.com/people/david-lieb"
    },
    "founders": [
      {
        "user_id": 538515,
        "full_name": "Zach Witzel",
        "title": "Founder/CEO",
        "founder_bio": "Made >$100M in growth experiments at Uber. Now building tryhelium.com to personalize upsell flows. We help consumer subscription companies double their conversion. ",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/zachwitzel",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/6f082aa03a9523fb5244130b45d22ec835f6d37d.jpg"
      },
      {
        "user_id": 808047,
        "full_name": "Shishir Jakati",
        "title": "Founder/CTO",
        "founder_bio": "Cofounder and CTO of Helium. ",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/shishirjakati",
        "x_url": "https://twitter.com/aShishirJakati",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/077c847806655973e5643bee81b3501fe847028c.jpg"
      }
    ],
    "jobs": [
      {
        "id": 88261,
        "title": "Founding Sr Full-Stack Engineer",
        "url": "https://www.ycombinator.com/companies/helium/jobs/n4tOZ3R-founding-sr-full-stack-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$150K - $250K",
        "equity_range": "0.50% - 1.50%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 88274,
        "title": "Founding Design Engineer",
        "url": "https://www.ycombinator.com/companies/helium/jobs/lK6JrVU-founding-design-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Frontend",
        "salary_range": "$150K - $200K",
        "equity_range": "0.50% - 1.00%",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 88276,
        "title": "Founding Full-Stack Engineer",
        "url": "https://www.ycombinator.com/companies/helium/jobs/HIa0j38-founding-full-stack-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$125K - $200K",
        "equity_range": "0.50% - 1.00%",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 99943,
        "title": "Growth Operations",
        "url": "https://www.ycombinator.com/companies/helium/jobs/vUO2UVU-growth-operations",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Operations",
        "role_type": null,
        "salary_range": "$80K - $150K",
        "equity_range": "0.20% - 0.40%",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 99944,
        "title": "Chief of Staff ",
        "url": "https://www.ycombinator.com/companies/helium/jobs/u2Indcw-chief-of-staff",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Operations",
        "role_type": null,
        "salary_range": "$120K - $160K",
        "equity_range": "0.30% - 0.60%",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 104563,
        "title": "Social Media & Growth Intern",
        "url": "https://www.ycombinator.com/companies/helium/jobs/87HXEOP-social-media-growth-intern",
        "location": "San Francisco, CA, US",
        "type": "Internship",
        "role": "Marketing",
        "role_type": null,
        "salary_range": "$30 - $50 / hourly",
        "equity_range": "",
        "experience": null,
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 105491,
        "title": "Founding Account Executive",
        "url": "https://www.ycombinator.com/companies/helium/jobs/cXTZmfW-founding-account-executive",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$160K - $240K",
        "equity_range": "0.15% - 0.30%",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
        "skills": []
      }
    ],
    "news": [],
    "launches": [
      {
        "id": 82822,
        "title": "🎈 Helium: Improve your paywall at the speed of thought",
        "tagline": "Launch and personalize paywalls without code.",
        "body": "![uploaded image](/media/?type=post&id=82822&key=user_uploads/538515/d43da3c4-aab2-4396-ba81-58d87b315f97)\n\n.\n\n# **TLDR**\n\n[Helium](https://tryhelium.com/) lets mobile companies launch and personalize upsell flows without code. We previously made >$100M in conversion experiments at Uber and Meta and are building the tools we wish we had.\n\nWith Helium, growth teams can add new paywalls or experiments in minutes! Helium also helps drive conversion with SmartSelect, our AI that finds the best paywall experience for each user.\n\nIf you know anyone working on consumer apps, [give us a shout](https://mailto:zach@tryhelium.com?subject=Connecting%20you%20to%20Zach%20at%20Helium%20(YC%20S24))! If we can’t help them earn 5x our price in new revenue, we’ll give their money back.\n\n.\n\n# **👋 We’re Helium!**\n\nWe’re building tools to experiment on in-app paywalls without code.\n\n* [Zach](https://linkedin.com/in/zachwitzel) (CEO) worked on in-app upsell at Uber. He ran dozens of conversion experiments that made >$100M.\n* [Anish](https://www.linkedin.com/in/anish-doshi-45a81271) (CPO) worked in ad optimization at Meta. He drove 10% in Instagram ad conversion through AI to personalize ads to users.\n* [Shishir](https://linkedin.com/in/shishirjakati) (CTO) worked on Alexa AI, using ML / LLMs to make Alexa smarter for millions of users.\n\n![uploaded image](/media/?type=post&id=82822&key=user_uploads/538515/8efbb041-f083-4f06-bac6-4a5dbfaef6c6)\n\nEarly on we realized how dumb it was that Zach spent years doing crude in-product personalization at Uber, while Anish built tools to automatically personalize tens of thousands of ad variants.\n\nWhile ads have come a long way, software upsell is stuck in the past — it’s too slow, too manual, and too one-size-fits-all.\n\n.\n\n# **👴📟📼 Mobile Paywalls are stuck in 2008**\n\nIn 2023, mobile in-app purchases crossed $150 billion, with $45B from subscriptions.\n\nMobile companies we talked to, from Headspace to Hinge, spend \\~1/3 of eng bandwidth on upsell, but optimizing in-app conversion is still highly manual. Teams spend months experimenting with paywall entry points, messaging, UX, targeting, premium features, and discounting.\n\nThe problem is that…\n\n* **⏰ Each change takes weeks**: Because paywalls live in native mobile code, making a change takes at least 6 weeks to code, test, launch to the app store, get it approved, and then get installs of the new version.\n* **🫨 Upsell becomes a maze**: There are typically dozens of entry points (onboarding, profile, feed, modals, etc) leading to different experiences. One prospect had 87 separate paywalls, so rolling out even small changes turns into weeks of manual work.\n* **🆘 Personalization is hard:** Personalization drives conversion (1 customer saw +40% conversion personalizing copy) but takes a ton of work. Most companies struggled with identifying key segments, designing custom experiences, implementing new logic in code, and dealing with many-variant experiments.\n\n.\n\n# **🎈 Introducing, Helium**\n\n![uploaded image](/media/?type=post&id=82822&key=user_uploads/538515/52f764dd-44b0-4c8d-a459-899f0f4a0ed0)\n\nHelium helps consumer app companies launch, manage, and improve paywalls without code.\n\nIt allows growth or product teams to run tests on their own (and stop bothering engineers) as they work on upsell conversion.\n\n* **🖥️ Visual editor**: Add new paywalls or multi-step flows all from the editor. All you need is one line of code to wire up your upsell flow with our SDK (React Native, Swift, & Android)\n* **🔬 Experimentation**: Add test copy, imagery, UI, or more, and run an experiment in 3 clicks. Results populate in your analytics tool\n* **👥 Personalization made simple**: Add as many variants as you want, and our AI algorithm (Smart Select) will find the right one for each user to drive conversion. Solve problems like…\n  * What CTA works best in each language?\n  * What feature do we emphasize for each customer segment?\n  * Which paywall do we show on onboarding vs app open?\n\n.\n\n# **😍 Ask: Intros to consumer mobile folks 😍**\n\nIf you know anyone who leads growth or monetization at a consumer mobile company, we’d love to talk to them to see if we can help!\n\nWe’re doing a design partner deal for the next few months…\n\n* White glove support for your implementation (or we can integrate Helium into your codebase directly for you)\n* We’ll run 3-5 experiments of your choice on your behalf\n* If we don’t make you 5x times our price in additional revenue, we’ll offer you a refund\n\n**If you know anyone who may be a fit, you can email us at** [**founders@tryhelium.com,**](mailto:founders@tryhelium.com) or just [**click here.**](https://mailto:zach@tryhelium.com?subject=Connecting%20you%20to%20Zach%20at%20Helium%20(YC%20S24))",
        "url": "https://www.ycombinator.com/launches/LXq-helium-improve-your-paywall-at-the-speed-of-thought",
        "votes": 29,
        "created_at": "2024-08-07T18:44:16.987Z"
      }
    ]
  },
  {
    "id": 29800,
    "name": "HeroUI",
    "slug": "heroui",
    "former_names": [
      "NextUI Inc.",
      "NextUI",
      "Zigma (By NextUI)",
      "Zigma - By NextUI",
      "Zigma - by NextUI",
      "Frontio - by NextUI"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/781d2df5a4a1764a1267531183e62e101f6d26a7.png",
    "website": "https://heroui.com",
    "all_locations": "Buenos Aires, Buenos Aires, Argentina; Remote",
    "long_description": "HeroUI makes it simple for AI agents and developers to build beautiful, accessible, production-ready interfaces for web and mobile. In the AI age, design matters more than ever. Every micro animation, color, and interaction shapes how users experience your product. HeroUI makes that level of creativity and craft simple",
    "one_liner": "The UI framework for AI agents and developers to build beautiful apps.",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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    "regions": [
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    "stage": "Early",
    "app_video_public": false,
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/heroui",
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    "year_founded": 2023,
    "city": "Buenos Aires",
    "country": "AR",
    "linkedin_url": "https://www.linkedin.com/company/heroui",
    "x_url": "https://twitter.com/hero_ui",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/nextui",
    "github_url": "https://github.com/heroui-inc",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/781d2df5a4a1764a1267531183e62e101f6d26a7.png",
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    "primary_partner": {
      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
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        "user_id": 1591074,
        "full_name": "Junior Garcia",
        "title": "Founder/CEO",
        "founder_bio": "Junior Garcia is the Founder and CEO of HeroUI (formerly NextUI). He has nearly 10 years of experience as a software engineer, including time at Deel, building HeroUI Chat, an AI-powered platform for creating beautiful frontends apps.\n",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jrgarciadev/",
        "x_url": "https://x.com/jrgarciadev",
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    "id": 29821,
    "name": "Polymet",
    "slug": "polymet",
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/9b83146cb0e374a41a184f24deaad8d74f27ad10.png",
    "website": "https://polymet.ai",
    "all_locations": "Istanbul, Istanbul, Turkey",
    "long_description": "Polymet uses AI to help non-designers create production-ready designs and front-end code. They explain what they want or provide an image, and Polymet designs the interface.\r\n\r\nOur customers use Polymet instead of hiring designers and save thousands of dollars every month. Even their managers can design with English instead of writing design specs.\r\n\r\nThis helps these teams move faster and cover design function on their own instead of contractors at early stages and when they start to scale their can produce a lot more design work, just like Midjourney.",
    "one_liner": "AI Product Designer",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1719854001,
    "tags": [
      "AI"
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    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2024",
    "status": "Active",
    "industries": [
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    "regions": [
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      "Middle East and North Africa"
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    "stage": "Early",
    "app_video_public": false,
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/polymet",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/polymet.json",
    "year_founded": 2024,
    "city": "Istanbul",
    "country": "TR",
    "linkedin_url": "https://www.linkedin.com/company/polymet-ai/",
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      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
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    "founders": [
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        "user_id": 487954,
        "full_name": "Yusuf Hilmi",
        "title": "Founder/CEO",
        "founder_bio": "Building Polymet to help product designers and engineers ship faster with AI.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/yusufhilmi",
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      {
        "id": 83282,
        "title": "Polymet - AI designer at your service",
        "tagline": "We help you create well designed user interfaces and prototypes without any design experience.",
        "body": "**TL;DR**\n\nPolymet uses AI to help non-designers create production-ready designs and front-end code. They explain what they want to build or provide an image, and Polymet will design and implement it for them.\n\n<https://www.youtube.com/watch?v=rYrkikCA8fw>\n\n## Problem\n\n* Most companies need help with design but don't have a designer\n* Designers can't design fast enough or are just slow…\n* Managers hate the long feedback loop with the designers, taking days for simple changes\n* They want to do it themselves but learning a complex editor like Figma is hard\n* They need to whip up a whole new demo with new features for a customer but don’t have time to design and build that\n\n## Our Solution\n\n### Design with AI\n\nCreate designs by explaining what you need or providing images (can be hand-drawn sketches).\n\n* **No design expertise required:** Anyone can create beautiful and functional interfaces with us\n* **Quickly flesh out prototypes:** Use these for customer demos and share them with the team\n* **Quickly explore multiple design paths:** Generate multiple variations for inspiration\n\n![uploaded image](/media/?type=post&id=83282&key=user_uploads/487954/68086b15-f1d1-4fde-ab43-6ba2b6d9b4fa)\n\n![uploaded image](/media/?type=post&id=83282&key=user_uploads/487954/af62ba68-cf7d-4cc2-a5dd-6ccd5c947d8c)\n\n### Edit with Natural Language\n\nRefine your designs using simple English instructions; no need to learn complex editing tools like Figma.\n\n* Make changes quickly and easily, as if you're giving feedback to a designer\n* Select individual elements to ask for improvements, **just like commenting on Figma**\n\n![uploaded image](/media/?type=post&id=83282&key=user_uploads/487954/c8ddb2d7-c8c3-404f-b834-2f3457b25113)\n\n### Show Your Work to Customers and Teams\n\n* **Make demos for each customer:** Create a special preview link for each client and tune the demo for them.\n* **Work better with your team:** Send preview links to your team to get their thoughts on your designs right away.\n\n<https://app.polymet.ai/preview/cb6a2058-846d-4cbc-8eaa-8f8a8a68eaa3>\n\n![uploaded image](/media/?type=post&id=83282&key=user_uploads/487954/6e6b93d3-9bf5-4316-b8bc-dbd51be250dd)\n\n### Explore a New UX Faster\n\n* **Create multiple variations:** with each prompt to find the best user experience\n* **Image to design:** Upload reference images, sketches, or Figma designs and get started\n\n\"create similar step indicators in different forms, make them functional, and add subtle animations\" **variations: 8**\n\n![uploaded image](/media/?type=post&id=83282&key=user_uploads/487954/b35c42da-67c7-4d8c-9b12-0d6db1c857da)\n\n### Production-Ready Frontend Code\n\nWith Polymet, every design comes with high-quality frontend code that integrates with your existing codebase.\n\n* **Save time and money:** Polymet is better and faster than hiring a designer and a frontend engineer\n* **Reduce time from designs to code** for engineers\n\n### Get Creative\n\nPolymet lets you make cool, complex designs easily. Here are some examples of that:\n\n* Make fun color pickers\n* Create dropdowns that move in interesting ways\n* Design eye-catching loading animations\n* Build tabs and buttons that respond smoothly\n* Craft date pickers that are easy and fun to use\n\n![uploaded image](/media/?type=post&id=83282&key=user_uploads/487954/90e9cc34-062f-4092-89c9-a82bb9b31dcd)\n\n![uploaded image](/media/?type=post&id=83282&key=user_uploads/487954/e4e33bd4-57ac-4aa7-aeac-20e6b7e62b72)\n\n# How can you help?\n\n* Go ahead to [app.polymet.ai](http://app.polymet.ai) , try it out, and share what you've designed and your feedback!\n* If you don’t want to hire a designer and need urgent help with design, hit us up!\n  * If you’re in SF, we might visit your office with some “Turkish Baklava” and onboard you personally :)\n* Introduce us to companies who are building out their component libraries and design systems, likely right before or after Series A\n  * If you’re working at one of these companies and want to see the enterprise version, schedule a call from: [cal.com/yus-hilmi/onboarding](http://cal.com/yus-hilmi/onboarding)",
        "url": "https://www.ycombinator.com/launches/LfG-polymet-ai-designer-at-your-service",
        "votes": 68,
        "created_at": "2024-08-21T16:59:56.022Z"
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    "id": 29833,
    "name": "Quetzal",
    "slug": "quetzal",
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e2e0833dd48a420927a12b9525cc6f2b83f83211.png",
    "website": "https://getquetzal.com/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Quetzal is the first fully LLM-powered translation and internationalization suite, enabling companies to translate and internationalize their software and content instantly with minimal setup. We also handle all of your internationalization issues, from managing all of your stakeholders to bringing your product and marketing to market. No more waiting days or even weeks for translated content! Deliver a perfect experience to your users in any language, instantly.",
    "one_liner": "Simple, LLM-first translation and internationalization for software",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1721636551,
    "tags": [
      "SaaS",
      "Enterprise Software",
      "International",
      "AI"
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2024",
    "status": "Active",
    "industries": [
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    "regions": [
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      "America / Canada"
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    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/quetzal",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/quetzal.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "",
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      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
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        "user_id": 1755404,
        "full_name": "John Thompson",
        "title": "Founder/CEO",
        "founder_bio": "Former SWE at Slack, working to make software internationalization as easy and painless as possible",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/jthompson4004",
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        "user_id": 1755481,
        "full_name": "Brendan Agliardo",
        "title": "Founder/CTO",
        "founder_bio": "Founder of Quetzal, former SWE at Mercatalyst, UMD CS dropout",
        "is_active": true,
        "linkedin_url": "N/A",
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      {
        "id": 82510,
        "title": "Quetzal 🦜 A modern internationalization platform",
        "tagline": "Say hello to Quetzal, your all-in-one solution for software internationalization",
        "body": "**_tl;dr_** - We’re the fastest and easiest way to solve all of your translation and internationalization issues in one platform.\n\nHello, Hola, Guten Tag, 你好, etc., to you all! We’re John and Brendan, the team creating [Quetzal](https://getquetzal.com/).\n\n![uploaded image](/media/?type=post&id=82510&key=user_uploads/1755404/113a9847-7718-45ff-9f1e-ac6df1d8d02f)\n\n**John** (on the left) worked for three years at Slack on the Slack Connect team, handling new features and requests from customers around the world. He saw firsthand the pain that bad and challenging translations and internationalization had for everyone at the company, from engineers, to CSMs, to PMs, to users.\n\n**Brendan** (on the right) worked for two years at Mercatalyst, a retail startup founded by the creator of Woot.com, which sold to Amazon in 2010. He worked extensively on the project bringing in in-house Spanish translation, and experienced the headache that this effort caused.\n\nTogether, they decided to bring outdated and broken internationalization software and approaches into the year 2024 with Quetzal.\n\n# **Why is the current approach to internationalization and translation broken? 🤕**\n\nIf you're just starting out going international with your product, it can be daunting to see exactly what you need to do. Translating your whole product takes time and perhaps maybe weeks or months of engineering effort, depending on what solution you go with. How do you deliver consistent and accurate translations with context about how your application works? Software translation mostly relies on engineers haphazardly providing text to an internationalization service, which then needs to translate on a string by string basis. This strategy loses important context and leads to poor quality, inconsistent translations, all while putting unnecessary work on engineers.\n\nIf your company already has a robust localization system, there's a whole host of other problems. You need to juggle the constant barrage of customer confusion, growth and change to your product and messaging, and external demands to adjust wording and phrasing, sometimes at the last second. Keeping up with all of that and making your language and messaging consistent with how your product works and what your intents are is super tough and puts unnecessary stress on your localization team.\n\nQuetzal aims to tackles these problems with a new modern internationalization solution that understands your specific goals with each localization problem you're trying to solve.\n\n# **Our ask to you, kind reader:**\n\n* If you’re trying to internationalize or have already done it but are experiencing pain in the process (or if you know someone that is!) please reach out to us at [john@getquetzal.com](mailto:john@getquetzal.com) or [brendan@getquetzal.com.](mailto:brendan@getquetzal.com)\n* Connect us with people on Internationalization and Localization teams within your network so we can see what their pain is.\n* **Share this post!** If you think what we’re doing is cool, share this post out to your network!\n* Or if you just want to practice a second language (we speak English, Spanish, Mandarin, and German between us), play chess, or just chat about internationalization, let us know!\n\n(Yes, we know that we used a parrot emoji in the title, please let us know when they add a real quetzal).\n\nThank you very much for reading,\n\nJohn Thompson & Brendan Agliardo",
        "url": "https://www.ycombinator.com/launches/LSo-quetzal-a-modern-internationalization-platform",
        "votes": 26,
        "created_at": "2024-07-29T02:06:55.041Z"
      }
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    "id": 29835,
    "name": "Voker",
    "slug": "voker",
    "former_names": [
      "Invoke AI",
      "Invoke Labs"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/efc5cb21ff2d8c0c7bf12fe360a1eb51bd8d4d0d.png",
    "website": "https://voker.ai",
    "all_locations": "Los Angeles, CA, USA",
    "long_description": "Voker is the Agent Analytics Platform for monitoring and improving your AI agents. Companies like Dutch.com use our SDK to build better agents.\r\n\r\nAlex and Tyler met at a high-growth E-Commerce startup where Tyler was running Technology & Data. Together, they built AI products that bootstrapped the company profitably to $100MM in Revenue.",
    "one_liner": "The Agent Analytics Platform",
    "team_size": 6,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1722887304,
    "tags": [
      "Developer Tools",
      "Generative AI",
      "Analytics",
      "Big Data",
      "AI"
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    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2024",
    "status": "Active",
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      "Engineering, Product and Design"
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    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Partly Remote"
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    "stage": "Early",
    "app_video_public": false,
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/voker",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/voker.json",
    "year_founded": 2024,
    "city": "Los Angeles",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/voker-ai/",
    "x_url": "https://x.com/Voker_ai",
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    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/efc5cb21ff2d8c0c7bf12fe360a1eb51bd8d4d0d.png",
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        "user_id": 1924275,
        "full_name": "Tyler Postle",
        "title": "Founder",
        "founder_bio": "Co-Founder of Voker - the Agent Analytics Platform. In previous roles, I've built data products that drive growth. I was an operator of a $100MM DTC ecomm company and ran revenue growth data science for a $10B public SaaS company. I'm passionate about building high performing teams and continuously learning.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/tyler-postle/",
        "x_url": "https://x.com/PostleTyler",
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      },
      {
        "user_id": 1965948,
        "full_name": "Alex Rudolph",
        "title": "Founder",
        "founder_bio": "Co-Founder of Voker, providing Analytics for AI Agents",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/alex-r-87470a198/",
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      {
        "id": 83545,
        "title": "⭐ Voker - The Agent Analytics Platform",
        "tagline": "Voker is analytics for the agentic era, so you can build the best agents possible.",
        "body": "### TL;DR: Voker is analytics for your conversational agent product, so you can build the best agents possible.  Our SDK transforms AI agent interactions into structured analytics dashboards that anyone on your team can use. Agent-first products like Lightfield use Voker to monitor and optimize their agents.\n\n![uploaded image](/media/?type=post&id=83545&key=user_uploads/1924275/7ff55d8b-ee06-4147-97c4-1236c50e0c5c)\n\n## The Team 👬\n\n\\\n[Tyler](https://www.linkedin.com/in/tyler-postle/) and [Alex](https://www.linkedin.com/in/alex-r-87470a198/) have been building Data and AI products and consulting for 9-figure businesses together since 2021. Tyler studied Physics at the College of Creative Studies @ UCSB, operated a $100M DTC e-commerce company, and was Director of Data at Appfolio (NASDAQ:APPF). Alex built AI infrastructure at multi-billion dollar companies and has a Masters in Computer Science.\n\n![uploaded image](/media/?type=post&id=83545&key=user_uploads/1924275/7d84f9c1-3d35-4e71-b359-162168ae0cae)\n\n_Founders left to right: Tyler Postle (CEO), Alex Rudolph (CTO)_\n\n## 🧨 The Problem: You have agents in production but you can’t keep track of quality and usage.\n\n![uploaded image](/media/?type=post&id=83545&key=user_uploads/1924275/6f2ad306-cb84-4b1d-9b7a-a8ae6ae9f054)\n\nIf you are building an agentic product with usage growing rapidly...\n\n* Scanning traces doesn't tell you if agents are helpful, accurate, or hitting walls. You only find out when customers complain or attrition skyrockets.\n* Every stakeholder needs data. Every request pulls engineers away from building. Nobody can self-serve insights.\n* Product and business teams need to quantify the impact of their AI investments. You have usage stats, but your team is struggling to connect agent performance to conversion, retention, or revenue.\n\n## 🎉 The Solution: Agent Analytics\n\n![uploaded image](/media/?type=post&id=83545&key=user_uploads/1924275/8bbbfd52-25aa-43db-aab0-d75ac050a9a3)\n\nVoker transforms user &lt;> agent interactions into structured analytics that anyone on your team can use.\n\n* PMs, analysts, and business teams get digestible insights they need without tickets, bottlenecks, or delays.\n* Track what AI agents are saying, identify knowledge gaps, detect abnormalities, and measure improvement over time.\n* Connect agent metrics to outcomes that matter by correlating conversational data with user data you’re already collecting.\n\n![uploaded image](/media/?type=post&id=83545&key=user_uploads/1924275/b9b51bc2-ecc3-46ba-8820-ec3e81d62db2)\n\n**You shouldn’t have to wait for users to complain** to learn that a recent prompt change is breaking your hotel booking agent, or that the AI finance advisor you built is calling the wrong tool to look up realtime stock prices.\n\n![uploaded image](/media/?type=post&id=83545&key=user_uploads/1924275/6a8cd7f8-6e16-4b63-a9a1-ab025f0b0f6e)\n\n### Try for Free!\n\nInstall the [Voker SDK](https://app.voker.ai/docs) on our [free tier](https://voker.ai/#pricing) (up to 2,000 events/mo), and start building better agents today: <https://voker.ai/>",
        "url": "https://www.ycombinator.com/launches/LjV-voker-the-agent-analytics-platform",
        "votes": 352,
        "created_at": "2024-08-28T16:43:35.019Z"
      }
    ]
  },
  {
    "id": 29851,
    "name": "Diode Computers, Inc.",
    "slug": "diode-computers-inc",
    "former_names": [
      "Schematx",
      "Diode, Inc."
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a1e7f9d9a50296d38458d5ad7a76c87823682bc2.png",
    "website": "https://diode.computer",
    "all_locations": "New York City, NY, USA",
    "long_description": "Diode automates circuit board design. We work with hardware companies to get them the PCBs they need, fast.",
    "one_liner": "Automate circuit board design using AI",
    "team_size": 10,
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    "subindustry": "B2B -> Engineering, Product and Design",
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        "full_name": "Davide Asnaghi",
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        "url": "https://www.youtube.com/watch?v=ryHJuYzUejs",
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        "id": 83244,
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        "tagline": "Diode automates the circuit board design and ordering process for engineers.",
        "body": "Ciao Y Combinator! We’re [Davide](https://x.com/davideasnaghi) and [Lenny](https://www.linkedin.com/in/lennykhazan/) from [Diode Computers, Inc.](https://diode.computer/)\n\n**TL;DR: Diode is an end-to-end platform for circuit board design. With the help of AI, we can finish a months-long design project in days, and then ship working boards straight to your door.**\n\n**Try out our designer at **[**https://pcb.new/**](https://pcb.new/)**, or shop generated boards at **[**https://pcb.store/**](https://pcb.store/)**.**\n\n<https://www.youtube.com/watch?v=aOoG2gl8wdY>\n\n# Problem\n\nDesigning printed circuit boards (PCBs) is really hard. Existing tools provide little opportunity for design reuse, so most projects are started from scratch. Since there’s no good way to test your design, your best bet is to just order them and hope for the best.\n\nThought you were done? Nope — ordering PCBs is a pain too. Now you need to source the components, ship them across the globe to your manufacturer, and constantly be on the lookout for part shortages and replacements. It’s a full-time job.\n\n# Solution\n\nDiode solves this by owning the entire PCB design process end-to-end. It starts with a core of composable, reusable modules that users can stitch together to build their boards. When new use cases come up, our AI generator creates new modules in seconds instead of days. And with rigorously-tested modules instead of de novo designs, we can be confident that each board works first try.\n\n![uploaded image](/media/?type=post&id=83244&key=user_uploads/79914/00e25ff4-abe8-49d4-94c3-e74a925eb0a3)\n\nWe then take the user’s design and automatically translate it into manufacturing requirements to send to the factory. We stockpile all of the necessary components to remove the burden of supply chain management from users and amortize the cost of parts across all designs.\n\nThe result is an all-in-one platform for hardware design: describe what you need and get working boards delivered to your door.\n\n# Why\n\nIn a past life, we designed hardware at companies like Apple, and we encountered a problem: PCBs never worked on the first try. At best, they required micro-soldering surgery under a microscope and, at worst, a whole new board. These issues were driving us mad, so we started a company to fix it.\n\nWe want to make hardware design work more like software. Fast iteration cycles, reusable components with clean composition, and one-click ordering to build your products fast and cheap. Our vision is to turn PCB design into a software problem.\n\n**P.S.** Want a customized NFC business card with your logo? Get your own: <https://pcb.store/products/nfc-business-card>\n\n![NFC Business Card (x10)](https://pcb.store/cdn/shop/files/back.png?v=1724092003&width=1445)\n\n",
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "Void is an open source code editor with features similar to Cursor and GitHub Copilot. Unlike other tools, Void lets developers keep their data completely private by connecting directly to any LLM.",
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        "title": "Void: The open source Cursor alternative",
        "tagline": "AI code editor with advanced AI features and privacy.",
        "body": "**_TL;DR:_** [Void](http://voideditor.com/) is the open source Cursor alternative. It offers the AI features of modern AI coding tools, while allowing you to host your own AI model locally and keep your data private. Check us out on [GitHub](http://github.com/voideditor/void)!\n\n![uploaded image](/media/?type=post&id=84053&key=user_uploads/1324771/56eae9a0-49fd-499f-b101-3e15e81914a9)\n\n# About us\n\nHi everyone, we’re [Mat](https://linkedin.com/in/mathew-pareles/) and [Andrew](https://linkedin.com/in/andrew-pareles), and we’re the team behind Void. Mat’s been prompting Transformers since before GPT3 became mainstream, and Andrew did quantum computing research at JHU APL. We’re best friends who have been programming together since we were 8. \n\n![uploaded image](/media/?type=post&id=84053&key=user_uploads/1324771/30b62998-29ed-447f-883b-f0875c3d1ffa)\n\n_left to right: Mat (CTO), Andrew (CEO)_\n\n# ❌ The problem: the leading AI IDE is closed source\n\nCursor is a closed-source AI editor, which means you need to send your private data through their API every time you use it. This leads to obvious privacy concerns. It’s also expensive for developers, and it means people don’t have many choices for a great AI coding experience.\n\nWe think the future of AI should be open. You should be able to use whatever model you like and not be locked into using a private company’s API.\n\n# ✅ The solution: open source\n\nThe solution: create an open-source alternative. This way, you can choose to self-host or communicate directly with any model you like, anywhere you like. \n\nThere are lots of benefits to open-sourcing besides privacy, too: on Void, you can access community-made AI features and gain full access to all your prompts.\n\n# Key features\n\nWe’re building a lot. Here are the features we’re most excited about:\n\n* **File system awareness:** Void can answer questions about your entire codebase. It builds an index of all your files and uses it automatically, so you don’t manually select relevant files.\n* **View and edit underlying prompts:** Void lets you open up the hood and view/edit every single prompt in your chat history. This is really important if you want to understand how the LLM got its answer, and it’s lacking in most closed-source tools.\n* **Fast edits across 1000s of lines:** Even if your file is thousands of lines long, Void applies changes almost instantly. We prompt the AI to make changes the way a human would instead of rewriting the whole file.\n\n![uploaded image](/media/?type=post&id=84053&key=user_uploads/1324771/48310318-059a-4844-8d75-a0c71e2a8385)\n\n* **Full privacy / data control:** All of Void’s prompt-building is done on your own computer. This means you can self-host your own model and have your data never leave your network. Or, you can connect directly to Claude, GPT, or Gemini, and not worry about sending your company data through a middle layer of communication.\n\nWe think the future of AI is open, and we’re excited about building it.\n\n# **🙏 Asks**\n\n* Check out the [**Void editor**](http://voideditor.com/) and star us on GitHub!\n* If you’re interested in helping us build, join our [Discord](https://discord.gg/PspNkKG5wt) or shoot us an email. We rely on contributions, even small ones, and we’ll help you get up and running as a contributor!\n* Please share this post! Help spread the word that we’re building an open source Cursor alternative.",
        "url": "https://www.ycombinator.com/launches/Lrh-void-the-open-source-cursor-alternative",
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        "founder_bio": "Co-founder at Delineate. Previously she was an MIT PhD Candidate in Biological Engineering and worked at Pfizer and AstraZeneca where she focused on applying AI to modeling and simulation for drug development optimization. ",
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        "body": "![uploaded image](/media/?type=post&id=87668&key=user_uploads/1994202/81ed81f4-b8e2-4a07-b7c7-70d09ac5b497)\n\n### **TLDR**\n\n* Delineate extracts and analyzes data from biopharma research papers and patents at scale, including data trapped in figures and plots.\n* We are partnered with two top-10 pharma companies where we are performing some of the largest systematic-review studies ever conducted.\n* For our clients we have increased the number of processed studies by 15x compared to industry standard and reduced the time for certain studies from months to weeks.\n\n### **Problem**\n\n90% of drug candidates fail despite billions in pharmaceutical R&D. Making evidence based decisions is crucial to the success of $2B drug pipelines. However to aggregate evidence across hundreds of research papers and patents can take research scientists months of hard labor.\n\n### **Solution**\n\nDelineate has developed custom LLM and computer vision models paired with rigorous QC processes to deliver extremely high quality datasets in a fraction of the time. By increasing the scale and speed for evidence aggregation, Delineate is transforming how pharmaceutical companies make evidence based development decisions.\n\n### **Demo:**\n\n[**Here is a quick demo of our platform and a sample project:**](https://www.loom.com/share/66a1878825f14eabaeee7f5cf948c9a1?sid=55675f9b-2d71-40d2-afc3-4be5351fc80f)\n\n### **Ask:**\n\n* Any introductions to biopharma companies that perform meta-analyses and/or computational analysis workflows.\n* If any biopharma-focused YC companies need assistance, we're happy to help!\n\n# About Us:\n\nled by [**Emily Nieves**](https://www.linkedin.com/in/emily-nieves-a67b90144/) (MIT PhD, former Pfizer/AstraZeneca computational researcher) and [**Jawad Iqbal**](https://www.linkedin.com/in/jawad-iqbal/) (ex-Lockheed Skunkworks AI lead)\n\n![uploaded image](/media/?type=post&id=87668&key=user_uploads/1994202/20a27c7b-6a42-4af4-953a-2a6d9883c8a8)\n\n",
        "url": "https://www.ycombinator.com/launches/Mo0-delineate-information-overload-to-insights-in-biopharma",
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        "full_name": "Charlie Holtz",
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        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jacksondecampos/",
        "x_url": "https://x.com/jacksondecampos",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/baecbbe60d29db5f840d9f3c6438d0a979a7af37.jpg"
      }
    ],
    "jobs": [
      {
        "id": 84039,
        "title": "Product Engineer",
        "url": "https://www.ycombinator.com/companies/conductor/jobs/MYjJzBV-product-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$175K - $350K",
        "equity_range": "",
        "experience": "Any (new grads ok)",
        "visa": "Will sponsor",
        "skills": []
      },
      {
        "id": 84041,
        "title": "Design Engineer",
        "url": "https://www.ycombinator.com/companies/conductor/jobs/cMJKjGy-design-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Frontend",
        "salary_range": "$200K - $350K",
        "equity_range": "",
        "experience": "3+ years",
        "visa": "Will sponsor",
        "skills": []
      },
      {
        "id": 94130,
        "title": "Backend Engineer",
        "url": "https://www.ycombinator.com/companies/conductor/jobs/gPiaCGr-backend-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Backend",
        "salary_range": "$200K - $350K",
        "equity_range": "",
        "experience": "3+ years",
        "visa": "Will sponsor",
        "skills": []
      }
    ],
    "news": [
      {
        "title": "Conductor is The Tool the Best Engineers Are Using Right Now",
        "url": "https://www.youtube.com/watch?v=u2z44EkIEHE",
        "date": "May 08, 2026"
      },
      {
        "title": "Conductor’s Series A | Conductor Blog",
        "url": "https://www.conductor.build/blog/series-a",
        "date": "Mar 30, 2026"
      }
    ],
    "launches": [
      {
        "id": 93356,
        "title": "Conductor — Run a bunch of Claude Codes in parallel",
        "tagline": "Conductor lets you run a bunch of Claude Codes all at once, on your Mac.",
        "body": "Back in June, we started doing most of our dev work through Claude Code. It’s been so productive we [declared it a member of the team](https://x.com/charliebholtz/status/1935029747815432505).\n\nWe immediately wanted to get _more_ Claude, but the tooling was tedious. At one point we tried cloning our repo into three directories and running Claude in each of them, but it felt like driving a Subaru with a jet engine strapped on.\n\nWe needed a tool that would push Claude to its limits and that we’d enjoy working in all day.\n\nSo we built Conductor!\n\nhttps://www.youtube.com/watch?v=VsWWy2kVpa8\n\nOther people seem to like it too:\n\n![uploaded image](/media/?type=post&id=93356&key=user_uploads/331436/b581e29f-2ada-49d3-88f7-c91e6bfb7cf4)\n\n### **How it works**\n\n**In one click, start a new Claude in an isolated copy of your codebase.**\n\nWe integrate with Linear so you can easily start work on your issues.\n\n![uploaded image](/media/?type=post&id=93356&key=user_uploads/331436/315a80c3-3a33-4296-83cc-f0ac06a4b1f4)\n\n**See at a glance what every Claude is working on.**\n\n![uploaded image](/media/?type=post&id=93356&key=user_uploads/331436/3993651e-9bbf-4b62-9e70-32c4ff01ffe8)\n\n**Review Claude’s changes, create PRs, and merge!**\n\n![uploaded image](/media/?type=post&id=93356&key=user_uploads/331436/3d654281-7394-483a-b53d-b7b09d8f5980)\n\n### **Start Conducting**\n\n![uploaded image](/media/?type=post&id=93356&key=user_uploads/331436/b151e732-3397-4d8e-a138-911dd03a3c64)\n\nIt's free—we use your existing Claude Code login. You can [download for Mac now](https://conductor.build).\n\nCan’t wait to hear what you think!",
        "url": "https://www.ycombinator.com/launches/OHk-conductor-run-a-bunch-of-claude-codes-in-parallel",
        "votes": 23,
        "created_at": "2025-08-27T01:23:48.913Z"
      },
      {
        "id": 83684,
        "title": "Melty: Open source AI code editor for 10x engineers",
        "tagline": "Melty is the first editor that’s aware of what you’re doing from the terminal to GitHub and collaborates with you to write production-ready code.",
        "body": "Hi everyone! We’re Charlie and Jackson. We’re longtime friends who met playing ultimate frisbee at Brown.\n\n![uploaded image](/media/?type=post&id=83684&key=user_uploads/229410/ab31f858-0576-4cfc-8796-4148b999faae)\n\n[Charlie](http://charlieholtz.com/) comes from [Replicate](https://replicate.com/), where he started the Hacker in Residence team and [accidentally struck fear](https://www.businessinsider.com/david-attenborough-ai-video-hollywood-actors-afraid-sag-aftra-2023-11) into the heart of Hollywood. [Jackson](https://jdecampos.com/) comes from Netflix, where he [built machine learning infrastructure](https://netflixtechblog.com/scaling-media-machine-learning-at-netflix-f19b400243) that picks the artwork you see for your favorite shows.\n\nWe’ve used most of the AI coding tools out there, and often ended up copy-pasting code, juggling ten chats for the same task, or committing buggy code that comes back to bite us later. AI has already transformed how we code, but we know it can do a lot more.\n\nSo we’re building [Melty](https://melty.sh/), the first editor that’s aware of what you’re doing from the terminal to GitHub and collaborates with you to write production-ready code.\n\nWe’ve been working on Melty for 28 days, and it’s already writing about half of its own code. It can…\n\n_(all demos real-time)_\n\n**Refactor code across files**\n\n<https://www.loom.com/share/f0e7ae2644e6492ab9e9352fbd14ae8d?sid=b5d497cd-65f4-47ca-955a-73332d8edc4d>\n\n**Create web apps from scratch**\n\n<https://www.loom.com/share/4f4f85c3de8b420e85b65537b775e3c8?sid=01b43f48-0fec-400a-8bee-71132f6d4610>\n\n**Navigate large codebases**\n\n<https://www.loom.com/share/fc4eb54385a5426586160fad5dbfc1be?sid=73a79e2e-1505-47a1-838b-a375cf7523e4>\n\n**Write its own commits**\n\n![uploaded image](/media/?type=post&id=83684&key=user_uploads/229410/5b579ebb-e893-4a2e-b571-97d7136c681c)\n\nWe’re designing Melty to\n\n* Help you understand your code better, not worse\n* Watch every change you make, like a pair programmer\n* Learn and adapt to your codebase\n* Integrate with your compiler, terminal, and debugger, as well as tools like Linear and GitHub\n\nOur asks:\n\n1. Try Melty ([melty.sh](http://melty.sh)) and tell us what you think. It’s a fork of VS Code, so it’s compatible with all your settings and extensions.\n2. Tell us: what AI coding tools do you use, what do you like about them, and what’s frustrating? [DM Charlie](https://x.com/charliebholtz) or send us an email at [founders@melty.sh](mailto:founders@melty.sh).",
        "url": "https://www.ycombinator.com/launches/Llk-melty-open-source-ai-code-editor-for-10x-engineers",
        "votes": 30,
        "created_at": "2024-09-02T18:38:26.522Z"
      }
    ]
  },
  {
    "id": 29992,
    "name": "Outerport",
    "slug": "outerport",
    "former_names": [
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      "Haipera",
      "Outerbasis"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d2fd2342d3ea6b9592dfb0ad90c6249ad7c9ee05.png",
    "website": "https://outerport.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "We’re about to see an influx in the AI-led discovery of new medicines, specialty chemicals, and materials. This means the bottleneck will shift from R&D, to the scale-up of these new recipes. Unfortunately, designing these production systems and making sure they can be operated safely is an expensive and labor-intensive ordeal that involves thousands of pages of drawings where one mistake can cause millions of dollars in rework or even disasters. Outerport solves this by helping engineering firms automate the design of the industrial control systems needed for production scale-up, using a domain-specific language for electrical design with thousands of unit tests that verify performance, and building simulators that can ingest already built schematics of plants to help automate comissioning and help train operators to prevent costly mistakes.",
    "one_liner": "Design automation for industrial electrical controls",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1721673756,
    "tags": [
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      "Design",
      "Manufacturing",
      "Industrial"
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    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2024",
    "status": "Active",
    "industries": [
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      "Engineering, Product and Design"
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    "regions": [
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      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/outerport",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/outerport.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/outerport",
    "x_url": "https://x.com/outerport",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/d2fd2342d3ea6b9592dfb0ad90c6249ad7c9ee05.png",
    "app_video_url": null,
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    "company_photos": [],
    "primary_partner": {
      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
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    "founders": [
      {
        "user_id": 231327,
        "full_name": "Towaki Takikawa",
        "title": "Founder/CEO",
        "founder_bio": "Ex-Research Scientist at NVIDIA, working on R&D for simulation (neural fields, 3D computer vision, 3D generative models). Previously worked in robotics (systems engineering / electro-mechanical design) and manufacturing (operating various CNC machines 😎).",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/tovacinni",
        "x_url": "https://x.com/yongyuanxi",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/517caf29a4afd4a93916d324c052859963ad85db.jpg"
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    ],
    "jobs": [
      {
        "id": 81669,
        "title": "Member of Technical Staff, Computer Vision / Graphics",
        "url": "https://www.ycombinator.com/companies/outerport/jobs/XyfMWG2-member-of-technical-staff-computer-vision-graphics",
        "location": "San Francisco, CA, US / Tokyo, JP",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Machine learning",
        "salary_range": "$100K - $200K",
        "equity_range": "0.50% - 3.00%",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
        "skills": [
          "Python",
          "Torch/PyTorch",
          "OpenCV",
          "Computer Vision"
        ]
      },
      {
        "id": 88429,
        "title": "Member of Technical Staff, Tokyo Deployed",
        "url": "https://www.ycombinator.com/companies/outerport/jobs/mMUcpLv-member-of-technical-staff-tokyo-deployed",
        "location": "San Francisco, CA, US / Tokyo, JP / Remote (US; JP; CA)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$60K - $200K",
        "equity_range": "0.50% - 3.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Python",
          "React",
          "TypeScript",
          "Next.js"
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      },
      {
        "id": 95319,
        "title": "Member of Technical Staff, Process Engineering",
        "url": "https://www.ycombinator.com/companies/outerport/jobs/xNvEant-member-of-technical-staff-process-engineering",
        "location": "San Francisco, CA, US / Tokyo, JP / Remote (US)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Chemical engineering",
        "salary_range": "$60K - $200K",
        "equity_range": "0.50% - 3.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 95320,
        "title": "Business Development / Operations, Tokyo",
        "url": "https://www.ycombinator.com/companies/outerport/jobs/xOHQwfu-business-development-operations-tokyo",
        "location": "Tokyo, JP",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$60K - $200K",
        "equity_range": "0.10% - 3.00%",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 114954,
        "title": "Member of Technical Staff, DSL for Automation & Electrical CAD",
        "url": "https://www.ycombinator.com/companies/outerport/jobs/sRFUnQ9-member-of-technical-staff-dsl-for-automation-electrical-cad",
        "location": "San Francisco, CA, US / Tokyo, JP / Remote (US; JP; CA)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Backend",
        "salary_range": "$100K - $300K",
        "equity_range": "1.00% - 5.00%",
        "experience": "6+ years",
        "visa": "US citizen/visa only",
        "skills": []
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    ],
    "news": [],
    "launches": []
  },
  {
    "id": 29999,
    "name": "Onlook",
    "slug": "onlook",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4c023f9010fb3a7f3e550c56a9283c477e6ca096.png",
    "website": "https://onlook.com/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Onlook is the fastest way for anyone to craft exceptional experiences in code. We built an open-source, visual editor for code that merges design, development, and AI.\r\n\r\nSince launching, Onlook hit #1 on Hacker News, was the #1 trending repo on GitHub–twice– and has earned over 26,000 GitHub stars.\r\n\r\nFounded by Daniel Farrell, a designer of 10+ years and former Head of Growth, and Kiet Ho, an ex-Amazon and ex-ServiceNow engineer, Onlook is on a mission to finally solve the gap between design and development. ",
    "one_liner": "The Developer tool for Designers",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1737572736,
    "tags": [
      "Developer Tools",
      "Design",
      "Design Tools",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Winter 2025",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Partly Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/onlook",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/onlook.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/onlook-dev",
    "x_url": "https://x.com/onlookdev",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/onlook-dev",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/4c023f9010fb3a7f3e550c56a9283c477e6ca096.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "Aaron Epstein",
      "url": "https://www.ycombinator.com/people/aaron-epstein"
    },
    "founders": [
      {
        "user_id": 137575,
        "full_name": "Daniel Farrell",
        "title": "Founder/CEO",
        "founder_bio": "Founder & CEO of Onlook. \n\nDesigner, GTM strategist, and micromobility maniac building in the design <> dev space.\n\nProfessional designer for over a decade, first 100 employee at Bird on the Global Expansion Strategy team, cofounder of Wanderlift (long-distance ridesharing) and former Head of Growth at DIMO. ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/danielrfarrell/",
        "x_url": "https://twitter.com/D_R_Farrell",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/24ff7171a829e5e9593b970dcb066d9c37829abb.jpg"
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    ],
    "jobs": [
      {
        "id": 74305,
        "title": "Founding Engineer (Fullstack)",
        "url": "https://www.ycombinator.com/companies/onlook/jobs/e4gHv1n-founding-engineer-fullstack",
        "location": "San Francisco, CA, US / Remote (US; CA)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$130K - $200K",
        "equity_range": "1.00% - 4.00%",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
        "skills": [
          "Node.js",
          "PostgreSQL",
          "React",
          "TypeScript",
          "Next.js",
          "Tailwind"
        ]
      }
    ],
    "news": [],
    "launches": [
      {
        "id": 87467,
        "title": "Onlook – Cursor for Designers",
        "tagline": "An open-source, visual editor that makes it easy for designers and developers to collaborate in code.",
        "body": "**TL;DR – **[**Onlook**](http://onlook.com/?utm_source=launch_yc&utm_medium=social&utm_campaign=yc_launch)** is building the Cursor for designers, making it easy for designers and developers to collaborate in code. Onlook’s open-source visual editor was the **[**#1 trending repo**](https://github.com/onlook-dev/onlook/)** on GitHub, and has over 6.8k stars.**\n\n➡️ [Try Onlook today](http://onlook.com/download?utm_source=launch_yc&utm_medium=social&utm_campaign=yc_launch) ⬅️\n\nHere’s a [sneak peak of what it’s like to design with Onlook.](https://www.youtube.com/watch?v=wDity8UrIxE)\n\nHey there, we’re Daniel and Kiet, and we’re building Onlook ([onlook.com](http://onlook.com/?utm_source=launch_yc&utm_medium=social&utm_campaign=yc_launch)), the Cursor for Designers. \n\n### **The Problem**\n\nThere have been many attempts at solving the problem of design to dev handoff. But for so many tools in the market, there was always compromise. Either the tools were too complex for designers or too cumbersome for engineers to implement.\n\nThey were all built to abstract away code, but we’re in a new era of product development—where code isn’t the barrier. The real challenge is giving builders the best way to work with it. In other words, creating things with code has become more of a UX problem than a technical one.\n\n### **Our Solution**\n\n![uploaded image](/media/?type=post&id=87467&key=user_uploads/137575/f4e651b1-8cc2-4f41-8512-09500cf2cd0d)\n\nOur product can be best described as a visual IDE – you can either start with building a new app from a prompt, or import your existing NextJS / Tailwind app with Onlook. Once you run your app, you can start designing the interface directly as it’s rendered.\n\n![uploaded image](/media/?type=post&id=87467&key=user_uploads/137575/7a85a948-73c8-418f-9420-155cdec6d2de)\n\nWant to change a color? Want to move a div? Want to create a new page? You can do it yourself, or ask Onlook’s AI chat to do it for you. Because everything is one-to-one in code, you’re creating the real product with your edits, and you can always right-click to view your code in your preferred code editor.\n\nAnd, when you’re ready to share your creation with the world, you can host your project through Onlook with just a click.\n\n### **How we got here**\n\nWe started Onlook because we had experienced both sides of the design / engineering gap. Daniel has been a designer for over a decade, and Kiet was an engineer at ServiceNow and Amazon working directly with designers. \n\nKiet reached out to Daniel on YC’s Cofounder matching platform after starting the company in January of 2024, and shortly after we decided to team up and work together. If you’re looking for a cofounder, we [wrote a bit](https://onlook.substack.com/p/how-to-find-a-cofounder) about that process that you may find useful on our company Substack. \n\nWe [launched on Hacker News](https://news.ycombinator.com/item?id=40904862) and the project quickly earned over 1k GitHub stars. People were compelled by the idea of an open-source visual editor for code, and it felt like the timing was right. Since launching, we’ve continued to refine our editor to make it even better, and have since earned **6.8k stars**, tons of contributions.\n\nAlso, Onlook was recently ranked as the **#1 trending repo on GitHub**!\n\n![uploaded image](/media/?type=post&id=87467&key=user_uploads/137575/79a6fb56-14c8-4c1e-b815-9261e651199a)\n\n### **Use Onlook**\n\nYou can get started today by [downloading Onlook](http://onlook.com/download?utm_source=launch_yc&utm_medium=social&utm_campaign=yc_launch). \n\nPeople use Onlook for **prototyping ideas**, for **building their product**, and for **hosting their website**. Thanks to [Paratus Health](https://paratushealth.com/), [SalesPatriot](https://salespatriot.com/), [Calltree.ai](http://Calltree.ai), [NextByte](https://trynextbyte.com/), [Casixty](https://casixty.com/), [TrainLoop](https://trainloop.ai/), and [Scout](https://www.scoutforschools.com/) for being early partners and for using Onlook to build their sites and products! \n\n### **Asks**\n\n* **Try Onlook** out and reach out to us with your feedback and questions. We love when people send us screen recordings, written feedback, and ideas. Email Daniel – [daniel@onlook.com](mailto:daniel@onlook.com).\n* **Contribute** – Help us build the future of design and development tools! We have an active community of contributors from all over the world, and working on a design editor is very fun. Feel free to [browse our open issues and contribute](https://github.com/onlook-dev/onlook/issues), or [support the project with a star](https://github.com/onlook-dev/onlook/)! ⭐  \n* **Follow us** – We put out a lot of content in a lot of places:\n  * Join our [Discord community](https://discord.gg/ZZzadNQtns)\n  * Follow [Onlook on X](https://x.com/onlookdev)\n  * Follow [Onlook on LinkedIn](https://www.linkedin.com/company/onlook-dev/)\n  * Subscribe to [Onlook on YouTube](https://www.youtube.com/@OnlookDev)\n  * Subscribe to [Onlook on Substack](https://onlook.substack.com/) – we like sharing our learnings of building a company in detail here\n\nOnlook is building **the uncompromising design and development tool** – One familiar to designers and infused with AI to make excellent code that developers love.\n\nWith Onlook, we hope to empower anyone to make incredible websites, incredibly fast, and we can’t wait to see what you create!\n\n### **About Us**\n\n![uploaded image](/media/?type=post&id=87467&key=user_uploads/137575/a2562297-969e-420b-b563-adea12dea8be)\n\nOnlook is founded by Daniel Farrell ([LinkedIn](https://www.linkedin.com/in/danielrfarrell/)), a designer with a decade of design consulting experience, a first 100 Bird employee, and former Head of Growth at DIMO, and Kiet Ho ([LinkedIn](https://www.linkedin.com/in/kiet-ho/)), a former engineer at Amazon and ServiceNow.",
        "url": "https://www.ycombinator.com/launches/Mkl-onlook-cursor-for-designers",
        "votes": 71,
        "created_at": "2025-02-06T15:20:12.926Z"
      }
    ]
  },
  {
    "id": 30014,
    "name": "fixa",
    "slug": "fixa",
    "former_names": [
      "pixa",
      "Apex",
      "pixa",
      "fixa",
      "verso",
      "Verso",
      "Clarus"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/bd9d8fdd660acfd5b49d596c3ebc27e9317844b4.png",
    "website": "https://www.fixa.dev",
    "all_locations": "New York City, NY, USA",
    "long_description": "",
    "one_liner": "Fix your voice agents faster",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1731468857,
    "tags": [
      "Finance"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Fall 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/fixa",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/fixa.json",
    "year_founded": 2025,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "",
    "x_url": "https://x.com/VersoTrading",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/bd9d8fdd660acfd5b49d596c3ebc27e9317844b4.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
    },
    "founders": [
      {
        "user_id": 667562,
        "full_name": "Oliver Wendell-Braly",
        "title": "Founder/CEO",
        "founder_bio": "building",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/oliverbraly/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f5fe3452a288d6dc38bd8a7affea15c3207f16ab.jpg"
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    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 85567,
        "title": "fixa - fix AI voice agents faster",
        "tagline": "we find bugs in your voice agents so you don't have to 🐛 🔫",
        "body": "👋 hey everyone - we’re oliver and jonathan from [fixa.dev](http://fixa.dev) \n\n# **tl;dr**\n\nwe find bugs in your voice agents - (including hallucinations, interruptions, transcription errors, and sentiment errors), so you don’t have to manually call your agents or listen to conversation recordings ever again. watch our launch video [here](https://www.youtube.com/watch?v=Cnhf3Vs5Dcw)\n\n# **❌ the problem**\n\nfinding bugs in voice agents is a giant hassle\n\ntraditionally, voice AI developers\n\n* hire teams of offshore 🌊 reviewers to read transcripts and listen in on calls\n* often don’t find bugs until a customer complains 😡\n* require the entire eng team to take 30 minutes out of their workday to call their agent prior to pushing changes 😪\n\n# **✅ the solution**\n\nfixa finds bugs automatically in tests and production, providing developers with precise and actionable insights when things go south. \n\nwe pinpoint\n\n* LLM hallucinations 🤯\n* interruptions 🗣️\n* transcription errors 📝\n* sentiment errors (i.e. rude agent) 🤬\n\nand propose changes to your prompt(s) accordingly.\n\nwe spent the past year developing voice agents at [play.ai](http://play.ai) where we experienced the pain of manual bug hunting firsthand and we’re building the solution we wish we had. If you’re building in voice AI - we’d love to hear from you! \n\nthanks ✌️\n\n![uploaded image](/media/?type=post&id=85567&key=user_uploads/667562/5ce44bcf-c8c3-4979-b1ff-7c21db974f74)\n\n",
        "url": "https://www.ycombinator.com/launches/MG7-fixa-fix-ai-voice-agents-faster",
        "votes": 31,
        "created_at": "2024-11-14T16:10:42.630Z"
      }
    ]
  },
  {
    "id": 30017,
    "name": "Riveter",
    "slug": "riveter",
    "former_names": [
      "Nervy",
      "Haze AI",
      "Lassen AI",
      "Riveter AI"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ba11fcc185e7540e26d2fc388417c1e4c6dfad61.png",
    "website": "https://www.riveterhq.com/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Riveter fully automates web data extraction, end to end. With a single API, agents can search, scrape, and structure data from the web. \r\n\r\nCustomers like Snapchat and OpenAI use us to enrich datasets using Riveter's AI search agents that combine data from the web with third party or internal data.  \r\n\r\nTheir AI agents, custom scrapers, and integrations pack the power of browser use and automation for search, at a cost that allows for scale. \r\n\r\nYou can even create a custom data API for repeated searches live in your app or internal databases. \r\n\r\nPerplexity and ChatGPT are great for single questions, but they can’t handle large amounts of data at once. And they’re working with a single agent and context window instead of one in every cell.\r\n\r\nAnd Riveter’s web browsing can go further—even reading PDFs and images that may contain answers. \r\n\r\nMost teams still spend hours (or hire UpWorkers/contractors) to manually copy product specs, check competitor pricing, pull custom KYB/KYC data to assess customer risk, or scrape filings. Or they spend months building web scrapers, and when that still doesn't work, they come to Riveter.\r\n\r\nOur founding team (Cody Watters - CTO, Abby Grills, CEO) brings deep product and engineering expertise from to YC-backed companies Gusto, Retool, and Middesk. ",
    "one_liner": "Turn the web into structured data",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1731038423,
    "tags": [
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      "E-commerce",
      "Market Research",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Fall 2024",
    "status": "Active",
    "industries": [
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      "Engineering, Product and Design"
    ],
    "regions": [
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      "America / Canada"
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    "stage": "Early",
    "app_video_public": false,
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    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/riveter",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/riveter.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/riveter-hq/",
    "x_url": "https://x.com/riveterhq",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/ba11fcc185e7540e26d2fc388417c1e4c6dfad61.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
    },
    "founders": [
      {
        "user_id": 2203245,
        "full_name": "Abigail Grills",
        "title": "Founder/CEO",
        "founder_bio": "CEO at Riveter AI | Previously: Middesk, Gusto\nI have 10 years of product experience, including joining Gusto as an early PM and growing to lead Mid-Market Payroll. I've lead a number of 0 to 1 products including Gusto Time Tracking, State Payroll Tax Registration, and most recently, Address Risk at Middesk. I began my career at early stage consumer electronics startups, where I learned to wear many hats and fill gaps to make sure the job gets done.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/abigailgrills/",
        "x_url": "https://x.com/AGrillz",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0f383b1581d8d122b99830f5acd622903497c250.jpg"
      }
    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 99741,
        "title": "Riveter - Turn any prompt into a fully enriched dataset",
        "tagline": "The web has the data you need. We build the list.",
        "body": "Hey everyone! 👋\n\nWe're Abby and Cody, co-founders of [Riveter](https://riveterhq.com/) (F24). We both did 5+ years at Gusto, followed by Middesk and Retool, and watched the same painful problem play out across eng, data, ops, and growth teams: the information you need exists online, but getting it into a structured, usable dataset is brutally hard.\n\n**TL;DR: Write a prompt. Riveter builds the list and enriches it -- scraped live from the web. No stale databases, no stitching tools together.**\n\nTeams at OpenAI, Snap, and Fermat are already using Riveter to build datasets they couldn't justify building manually.\n\n**Ask:** We'd love to show you what Riveter can do for your use case. [Book 20 minutes with us](https://riveterhq.com/demo) and we'll give you 1,000 free credits to explore the platform.\n\n<https://youtu.be/KH0IELrOtLs>\n\n---\n\n**❌ The Problem**\n\nAlmost any list you could ever need can be derived from the web. Every law firm in California. Every vet practice by state. Every competitor's pricing page. The information is out there.\n\nThe problem is getting it out.\n\nCurrent options all hit the same wall:\n\n* **Data vendors** sell you records from a static index -- outdated the moment you buy them, and missing anything outside their database\n* **Clay and Parallel** pull from the same stale indexes. When we asked both to return all YC Winter 2026 companies, Parallel returned an incomplete dataset at a way higher cost. Clay returned \"Y Combinator\" as a company, along with results from other batches.\n* **ChatGPT and Claude** can reason about the web but can't handle the scale -- you can't ask an LLM to return thousands of enriched records reliably\n\nThe result: teams buy incomplete data, spend weeks building it manually, or go without.\n\n---\n\n**✅ Our Solution**\n\nRiveter agents navigate the web the way a researcher would -- running searches, visiting pages, reading results -- and return a fully structured, enriched dataset.\n\nWrite one prompt. Get thousands of rows.\n\n![uploaded image](/media/?type=post&id=99741&key=user_uploads/2203245/0293cc39-8404-4d03-bf11-2da4ad628033)\n\n\\\nDescribe what you want: _\"Return every dental practice in San Francisco, the dentists at each practice, and their contact details\"_\n\n1. Riveter agents search the web, visit pages, and compile the list -- live, not from a cached index\n2. Custom enrichments get layered on: lead scores, pricing data, contact info, whatever your workflow needs\n3. The result lands as a structured dataset, ready to use or pipe into your existing tools\n\nNo code required. Use it in-app, via API, or through our MCP server.\n\n---\n\n**🔍 Use Cases**\n\n**Sales and lead generation:** Find hyper-specific lists no vendor has pre-built. Every locksmith in the US. Every independent law firm in California. Every vet practice by state. Add enrichments in Riveter to qualify, score, and route them into your outreach.\n\n**Product data:** School logos, all attorneys at every AmLaw 100 firm, every menu item at every restaurant chain in a market. If it's on the web, Riveter can build it.\n\n**Market intelligence:** Track competitors and their pricing on a daily or weekly cadence. Especially common for e-commerce teams who need to move fast when something shifts.\n\n---\n\n**🙏 Our Ask**\n\n* [**Book 20 minutes with us**](https://riveterhq.com/demo) - tell us what you're building and we'll set up your first dataset together, plus 1,000 free credits on us\n* **Try it yourself** at [riveterhq.com](http://riveterhq.com) - free to get started [in-app](https://auth.riveterhq.com/sign-up), [via API](https://docs.riveterhq.com/), or [MCP.](https://docs.riveterhq.com/#description/mcp-server)\n* **Know a team** paying too much for stale data or drowning in manual research? Send this their way.\n\n---\n\n**👋 The Team**\n\n**Abby Grills (CEO)** - Previously at Gusto and Middesk across product and data workflows. Riveter is the tool she kept wishing existed.\n\n**Cody Watters (CTO)** - Previously at Gusto and Retool. Watched too much engineering time disappear into one-off data pipelines that should have been solved at the platform level.\n\nWe built Riveter because we kept hitting the same wall: the data we needed was obviously on the web, and there was no good way to get it out at scale.",
        "url": "https://www.ycombinator.com/launches/Pwj-riveter-turn-any-prompt-into-a-fully-enriched-dataset",
        "votes": 22,
        "created_at": "2026-04-14T17:34:17.075Z"
      },
      {
        "id": 94809,
        "title": "🚀 Riveter API: Replace your entire scraper infrastructure with a single API",
        "tagline": "Power your product with real data from the web.",
        "body": "We’re excited to launch our most requested feature: the **Riveter API**.\n\nWeb data is one of the biggest unlocks for what’s now possible with AI. But retrieving and structuring that data for your product or agents is far more complicated than it should be.\n\n---\n\n### **The Problem**\n\nYou need data from the web to equip your agents with more information or pipe structured data directly into your product.\n\nBut when it comes to web scraping, the gap between _idea_ and _working solution_ is huge.\n\n* What starts as **“just a simple scraper” often turns into a patchwork of 5+ vendors** (SERP providers, proxy networks, headless browsers, scraper libraries, and infrastructure) leading to weeks or months of engineering effort.\n* Timelines creep, **engineering costs rise, and maintaining scrapers becomes an ongoing burden**. All of this distracts your team from building your _core product._\n\nhttps://youtu.be/1pFXQJExRGw\n\n---\n\n### **The Solution**\n\n**Riveter** is the all-in-one web search agent. Configuration is simple — your team defines what data they need, and Riveter handles everything else.\n\n* **Prompt-based configuration, tool selection, and custom formatting.** Tell Riveter what you need via a prompt, then select tools like web search, scraper, PDF reader, or image reader.\n* **Everything built in.** SERP/search, proprietary scrapers, proxy management, and browser infrastructure are fully integrated, so you don’t have to build or connect multiple systems.\n* **Structured, consistent output.** Apply custom tags or enums, specify date formats, or define JSON objects to get clean, predictable results every time.\n\nThe API routes data directly into your app — giving you real, grounded web data with minimal engineering overhead.\n\n### **How It Works**\n\nYou can either **create a project in Riveter** to reference in your API request, or **configure all input and output fields directly in the API call.**\n\n#### **Option 1: Creating an API request from a Riveter project**\n\nCreating a project allows you to test and refine prompts and formatting before fetching data via the API.\n\n**Best for:**\n\n* Running recurring or long-term data collection\n* Quickly testing and iterating on prompts and tools\n* Structuring data that needs to be ingested by code\n\n#### **Option 2: Configuring input/output fields directly in the API request**\n\nOn-the-fly configuration gives you the flexibility to change columns and prompts dynamically based on your inputs.\n\n**Best for:**\n\n* Giving AI agents access to create their own Riveter requests\n* Handling variable outputs - e.g., running an initial request with Riveter, then defining attributes to evaluate your product or dataset on\n\n### **Getting Started**\n\nWe can’t wait to see what you build with Riveter!\n\nHead to[ ](https://riveterhq.com?utm_source=chatgpt.com)[**riveterhq.com**](http://riveterhq.com) and click **Get Started** — your first 500 searches are free!\n\nNeed a hand?[ Grab time here](https://riveterhq.com/contact?utm_source=chatgpt.com) and we’ll help you get set up.",
        "url": "https://www.ycombinator.com/launches/OfB-riveter-api-replace-your-entire-scraper-infrastructure-with-a-single-api",
        "votes": 14,
        "created_at": "2025-10-21T20:14:19.297Z"
      },
      {
        "id": 93370,
        "title": "Riveter ⚡ Thousands of AI search agents running in parallel",
        "tagline": "Riveter automates web research for every row in your spreadsheet with just a prompt.",
        "body": "We built Riveter because manual research sucks. And the slow, tedious process of collecting information from the internet takes people’s time away from doing great work.\n\n# **Why Riveter is great:**\n\n* We **simplified browser use to allow cheap web crawling** to be done at scale. \n* Our agent can make Google searches, view web pages, read PDFs and images, and **navigate to other pages** that might have better results. \n* It’s fast.\n* We give you sources, reasoning, and a record of the path the agent took to find the answer.\n* You’ll start seeing results within minutes of signing up.\n\n---\n\n---\n\n---\n\n---\n\n---\n\n#### https://youtu.be/oNSfKnLv-s4\n\n# **Why it matters:**\n\nMost teams still spend hours (or hire UpWorkers/contractors) to manually copy product specs, check competitor pricing, pull custom KYB/KYC data to assess customer risk, or scrape filings. \n\nPerplexity and ChatGPT are great for single questions, but they can’t handle large amounts of data at once. And they’re working with a single agent and context window instead of one in every cell.\n\nAnd Riveter’s web browsing can go further—even reading PDFs and images that may contain answers. \n\nWith Riveter, anyone can automate complex, auditable web research… without coding. \n\n#### \n\n# **How it works:**\n\n1. Upload your dataset (or prompt for Riveter to search & build you a dataset)\n2. Add a prompt for the new column\n3. Riveter’s agents search, navigate sites, read PDFs/images, and return structured outputs — with sources and reasoning for every cell.\n\n# **Traction:**\n\n* **2M+ searches automated** across customers\n* **Snap and Pietra** use Riveter for data that powers core product features\n* **Sunco** automated most of their product development research and supplier sourcing\n\n# **Who uses Riveter:**\n\n* **E-commerce:** Product specs, pricing, retailer research\n* **Sales/GTM:** Lead enrichment, market research, prospect discovery\n* **Finance:** Revenue announcements, SEC filings, fundraising data\n* **Risk/Compliance:** KYC/KYB checks, ownership verification, negative news screening\n* **Procurement:** Supplier research, competitive analysis\n\n# **About us:**\n\nCody Watters (Staff Engineer at Gusto → AI products at Retool) and Abby Grills (Mid-Market Payroll lead at Gusto → Product at Middesk) have a combined 20 years of experience building complex data systems.\n\n### **Try Riveter**\n\n**Free trial:** https://riveterhq.com\n\n**Book a demo:** https://riveterhq.com/contact\n\nIf your team does repetitive web research or builds fragile scrapers, we'd love your feedback on workflow templates and integrations.\n\n![uploaded image](/media/?type=post&id=93370&key=user_uploads/2203245/f392ac8e-5d55-405f-8d74-e8b7128f7633)\n\n---",
        "url": "https://www.ycombinator.com/launches/OHy-riveter-thousands-of-ai-search-agents-running-in-parallel",
        "votes": 45,
        "created_at": "2025-08-27T20:15:28.319Z"
      },
      {
        "id": 87785,
        "title": "Riveter - AI data assistant for spreadsheets",
        "tagline": "Clean, label, and enrich thousands of rows of data in minutes with ChatGPT-like prompts",
        "body": "#### TL;DR ✨\n\nWith [Riveter](https://www.riveterhq.com/), you can automate data analysis in minutes—no complex setup needed. Just upload a spreadsheet, and Riveter handles the rest. ⚡\n\n✅ Search the web for answers\\\n✅ Clean & structure messy data\\\n✅ Label & categorize data instantly\\\n✅ Answer qualitative questions\n\nProduct, Ops, and GTM teams use Riveter for competitive research, pricing analysis, customer insights, analyzing channel partners, and more.\n\n<https://youtu.be/sJ4AcwTjzqo>\n\n#### The Problem: ⏰ Time wasted on manual data work\n\nCompanies spend countless hours on manual data work. Marketing teams spend $10k+ on incomplete datasets. Ops teams wait months for engineering support to build features that reduce manual data work. While ChatGPT helps with single queries, it breaks down with large datasets (and typically can’t make it past \\~10 rows). \n\nWe've seen teams spend:\n\n* 10+ hours/month on competitive research and market/pricing analysis–especially in consumer goods\n* 40+ hours per conference or event cleaning attendee data\n* Months waiting for engineering resources to analyze user segments\n\n#### The Solution: 🤖 Automate your data workflows in minutes\n\nRiveter brings AI-powered data enrichment to your spreadsheets. Upload any CSV and use natural language prompts to:\n\n**Enrich Data with Web Search** - Write \"find the industry for each company\" and Riveter automatically searches the web to fill new columns with accurate data.\n\n**Clean & Structure Data** - Transform messy data into consistent formats without complex Excel formulas. Simply describe what you need: \"Check the spelling and formatting of each company name. Return the correct spelling and format.\"\n\n**Analyze & Label at Scale** - Process thousands of rows in minutes. Label customer feedback, categorize products, or analyze competitors' features using natural language prompts.\n\n![uploaded image](/media/?type=post&id=87785&key=user_uploads/2203245/b36b88c9-51e4-4cfd-b66f-bb9ae3331ad2)\n\n#### Why Customers Choose Riveter 👩🏻‍💻\n\n* No technical setup or engineering required\n* Handles 200,000+ rows of data\n* Automated web search \n* Results in minutes, not days\n* Extremely easy to use\n\n#### About Us 📖\n\nWe’re **former engineers and PMs from Airbnb, Gusto, and Middesk.** We built Riveter because we were tired of:\n\n🔍 Manually labeling data to build fraud & risk products\\\n📝 Labeling endless user feedback\\\n📊 Analyzing competitors’ products—manually\n\nWe now use Riveter daily for tasks like sales, competitive analysis, and conference prep—and we’re excited for you to experience it, too.\n\n#### Get Started 🚀\n\nReady to streamline your data workflow? [Schedule a demo](https://cal.com/team/riveter/riveter-demo) to start your **free trial!**",
        "url": "https://www.ycombinator.com/launches/Mpt-riveter-ai-data-assistant-for-spreadsheets",
        "votes": 32,
        "created_at": "2025-02-18T19:34:00.724Z"
      },
      {
        "id": 85462,
        "title": "Riveter 🔩 The copilot for corporate strategy",
        "tagline": "Skip McKinsey - get expert analysis without the consultants.",
        "body": "**TL;DR:** Riveter is the copilot for corporate strategy. We help growth stage companies like Gusto accelerate strategic decision making, using deep market research and analysis. \n\n#### About us\n\nAbby has 10 years of product experience, including Middesk and Gusto, where she was an early PM and led the Mid-Market Payroll team. Erica has 7 years of experience as a software engineer. She was an early engineer at Middesk, and before that, she was at Airbnb.\\\nWe’ve spent our careers exploring and executing on new product areas and expansion opportunities, and trying to optimize businesses’ results. **We’re building Riveter to help companies make better strategic decisions, faster.**\n\n<https://youtu.be/thmATCmTy5g>\n\n#### The problem\n\nGrowth stage, venture funded companies have two top concerns:\n\n1. How do we maintain growth at scale?\n2. Do our metrics align with public companies for a successful IPO?\n\nTo answer these questions, companies often do the following:\n\n* **Explore adjacent areas for expansion:** A commercial neobank might consider expanding to consumer\n* **Benchmark to similar companies:** Toast might compare their financials to Square's\n* **Track their market share:** A CRM might monitor competitors’ penetration across the market\n\n#### Our insights\n\n* Companies are hiring consulting firms that cost $1M+ and take months to provide a single report, which quickly becomes outdated.\n* Accessing key insights into public companies requires time consuming analysis due to inconsistencies across companies and obfuscation of important information.\n\n#### The solution\n\nRiveter automates the collection and analysis of private and public company data, **so you can focus on making the right strategic decisions, faster.** \n\n#### The product\n\n**The deepest analysis of public companies available**\n\nGet the data you wish Capital IQ gave you.\n\n* Get data on the usage of specific products, customer counts, retention, and more, in addition to standard metrics\n* Review metrics like gross margins, ACV, customer segment, CAC, CAC payback, Rule of 40, and more that have been automatically calculated for you, and are always up to date\n* Understand company-specific language and segmentation\n\n \n\n![uploaded image](/media/?type=post&id=85462&key=user_uploads/2203245/c283cf5c-4abf-471a-b8c3-b296996a768b)\n\n**Analysis of investor relations documents** \n\nRiveter summarizes key documents and artifacts, and extracts relevant quotes to save you time getting to the information you need.\n\n![uploaded image](/media/?type=post&id=85462&key=user_uploads/2203245/cd59d464-0ec8-436b-a2aa-0a60e031d077)\n\n\n**Search company documents and Riveter data**\n\nLooking to understand how a certain product is performing? Our AI analyst, Peter, allows you to ask specific questions, like how many American Express consumer cardholders there are.\n\n### Our ask\n\nAre you trying to make strategic decisions, but you or your team don’t have the time to perform in-depth analyses? We’d love to help. [Schedule a call with us](https://calendly.com/d/cmp9-ymp-zsy/riveter-demo-launch-yc) to discuss how we can aid in more informed decision making. You can reach out to us at [founders@riveterhq.com](mailto:founders@riveterhq.com).\n\nIf you have connections to any CorpDev or Strategic Finance teams in B2B SaaS, we’d love introductions to learn from them, or see if we can help. ",
        "url": "https://www.ycombinator.com/launches/MEQ-riveter-the-copilot-for-corporate-strategy",
        "votes": 220,
        "created_at": "2024-11-11T20:42:33.180Z"
      }
    ]
  },
  {
    "id": 30040,
    "name": "supercontrast",
    "slug": "supercontrast",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/790820337661ae1bc9c065bae89b47e0ad126432.png",
    "website": "https://supercontrast.com/",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "At Hive we worked on a product called Gencraft, an ai art generator we ramped from 0 to $1M ARR in 6 months. This inspired us to build supercontrast, an AI Copilot which empowers anyone to create and refine high quality designs and assets. ",
    "one_liner": "AI Co-Pilot for Design",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1727282803,
    "tags": [
      "Machine Learning",
      "Design",
      "Design Tools"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Fall 2024",
    "status": "Inactive",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Fully Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/supercontrast",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/supercontrast.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/supercontrast/?viewAsMember=true",
    "x_url": "",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/790820337661ae1bc9c065bae89b47e0ad126432.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "David Lieb",
      "url": "https://www.ycombinator.com/people/david-lieb"
    },
    "founders": [
      {
        "user_id": 1571215,
        "full_name": "Carter McClellan",
        "title": "Founder",
        "founder_bio": "CEO at supercontrast. Previously MLE/ Tech Lead at Hive AI",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/carter-mcclellan/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/62c1452599da597d8c56651c350b4c204c30e2b7.jpg"
      },
      {
        "user_id": 1572927,
        "full_name": "Shravan Kumaran",
        "title": "Founder",
        "founder_bio": "CTO at supercontrast, an AI copilot for creating designs and assets. Previously worked on AI asset generation for video games at Google Stadia, and developed Gencraft at Hive, an AI art generation tool that went from 0 to over $1M ARR in 6 months.",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/shravan-kumaran-7b2b80123/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/86a4896216e3973d6f7a017acc5cee68a31661cf.jpg"
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    ],
    "jobs": [],
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    "launches": []
  },
  {
    "id": 30046,
    "name": "Cekura",
    "slug": "cekura-ai",
    "former_names": [
      "Lex",
      "Vocera",
      "Cekura",
      "Cekura (formerly Vocera)",
      "Cekura",
      "Cekura (formerly Vocera)"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e614d24f652dc1e194f172153c3b7036c9c30b2f.png",
    "website": "https://www.cekura.ai/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Cekura helps Conversational AI companies with automated QA. From pre-production simulation and evaluations to production call monitoring, to assisting customers in setting up the CI/CD pipeline, we help in QA across the agent lifecycle.\r\n\r\nWe are working with 75+ customers across healthcare, BFSI, logistics, recruitment, and retail. Some of the largest CCAS players and enterprises use Cekura to ship AI voice and chat agents reliably ",
    "one_liner": "Voice AI and Chat AI agents: Testing and Observability",
    "team_size": 15,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1728616885,
    "tags": [
      "Developer Tools",
      "SaaS",
      "B2B"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Fall 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Partly Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/cekura-ai",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/cekura-ai.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/104795138",
    "x_url": "https://x.com/cekuraAi",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/vocera-ai",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/e614d24f652dc1e194f172153c3b7036c9c30b2f.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
    },
    "founders": [
      {
        "user_id": 795623,
        "full_name": "Tarush Agarwal",
        "title": "Founder/CEO",
        "founder_bio": "Tarush is the Co-founder and CEO @ Cekura. \n\nBefore this, Tarush spent 3 years in quant finance where he developed ultra low latency systems (think nanoseconds) and helped transform a loss making trading strategy into a successful desk doing millions in MRR in 3 months. \n\nHe studied computer science and statistics at IIT Bombay. \n",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/tarush-agarwal-b14851160/",
        "x_url": "https://x.com/tarush_agarwal_",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f9de59baa2dc1dde755d85e5f1cd20d0574e949b.jpg"
      },
      {
        "user_id": 1332337,
        "full_name": "Shashij Gupta",
        "title": "Founder/CTO",
        "founder_bio": "Shashij is the Co-Founder & CTO @ Cekura.\n\nPreviously Shashij worked as a quantitative researcher in a trading firm searching for complex alphas. Shashij has also researched in NLP at Google Research and has a first author paper on testing transformers with 50+ citations from his work at ETH Zurich. \n\nHe has also studied computer science at IIT Bombay.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/shashij-gupta-671aa614a",
        "x_url": "https://x.com/Shashijgupta",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/8fec5994a7451e97038ab771bf8137eab6611a16.jpg"
      },
      {
        "user_id": 1605191,
        "full_name": "Sidhant Kabra",
        "title": "Founder",
        "founder_bio": "Sidhant is the Co-Founder & President @ Cekura. \n\nSidhant comes from a consulting background, advising CEOs at Fortune 500 companies in FMCG and medical devices. He also led a 100+ member team handling customer experience. Recently, he drove product and growth at an edtech startup scaling from 0 to 200K+ users in 6 months. \n\nSidhant completed his bachelor’s from IIT Bombay. During university, he raised $500K in sponsorship deals for Asia’s largest student-led festival.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/sidhantkabra",
        "x_url": "https://x.com/kabra_sidhant",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/303eef125d5fbdce4702172fd1de671c6220fafd.jpg"
      }
    ],
    "jobs": [
      {
        "id": 95171,
        "title": "Forward Deployed Engineer (US)",
        "url": "https://www.ycombinator.com/companies/cekura-ai/jobs/AiWwUxI-forward-deployed-engineer-us",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Machine learning",
        "salary_range": "$100K - $180K",
        "equity_range": "",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 106505,
        "title": "Member of Technical Staff, Cekura (San Francisco, In-Person)",
        "url": "https://www.ycombinator.com/companies/cekura-ai/jobs/FssE6kq-member-of-technical-staff-cekura-san-francisco-in-person",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$150K - $200K",
        "equity_range": "0.20% - 0.80%",
        "experience": "1+ years",
        "visa": "Will sponsor",
        "skills": []
      },
      {
        "id": 107901,
        "title": "Founding GTM, Cekura (San Francisco, In-Person)",
        "url": "https://www.ycombinator.com/companies/cekura-ai/jobs/yDmL9mb-founding-gtm-cekura-san-francisco-in-person",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$100K - $150K",
        "equity_range": "0.15% - 0.50%",
        "experience": "1+ years",
        "visa": "Will sponsor",
        "skills": []
      }
    ],
    "news": [
      {
        "title": "YC-backed Cekura plans to open office in India following $2 million fundraise - The Economic Times",
        "url": "https://economictimes.indiatimes.com/tech/startups/yc-backed-cekura-plans-to-open-office-in-india-following-2-million-fundraise/articleshow/122233573.cms?from=mdr",
        "date": "Jul 03, 2025"
      },
      {
        "title": "Cekura raises $2.4 million to make AI conversations reliable",
        "url": "https://americanbazaaronline.com/2025/07/02/cekura-raises-2-4-million-to-make-ai-conversations-reliable/",
        "date": "Jul 02, 2025"
      },
      {
        "title": "Cekura raises $2.4M to build the reliability layer for Conversational AI",
        "url": "https://www.cekura.ai/blogs/cekura-raises-dollar24m-to-build-the-reliability-layer-for-conversational-ai",
        "date": "Jul 01, 2025"
      },
      {
        "title": "Read the Pitch Deck Y Combinator Startup Used to Raise $2.4 Million - Business Insider",
        "url": "https://www.businessinsider.com/read-pitch-deck-y-combinator-startup-used-seed-funding-2025-6",
        "date": "Jul 01, 2025"
      }
    ],
    "launches": [
      {
        "id": 96868,
        "title": "Cekura Red Teaming: Stress-test your AI agents for Jailbreaks, Bias, Toxicity and more",
        "tagline": "Break your AI agents security before your customers do",
        "body": "Hi Everyone! We are Sidhant, Shashij, and Tarush, co-founders of Cekura👋\n\n**_TL;DR:_** We have launched Cekura Red Teaming for enterprises and startups building Conversational AI in compliance-heavy sectors like BFSI, Healthcare, Legal, etc\n\nWatch our launch video [here](https://www.youtube.com/watch?v=ShCiyZQ7pyw) or book a call [here](https://cal.com/kabrasidhant/30min)\n\n**Problem:**. Enterprise security teams are blocking deployments because manual, vibe-based testing doesn’t provide enough assurance against adversarial users. Whether it’s a user bypassing a paywall, tricking a bot into giving legal advice, or social-engineering it into leaking company secrets - the attack surface of conversational AI is massive.\n\n**Solution:**\n\n**Scalable, Automated Red Teaming:** Cekura allows you to run thousands of adversarial simulations in minutes. We act as the \"bad actor,\" pushing your agent's logic to its limits across every major vulnerability category:\n\n* 🔓 **Jailbreaking:** We simulate sophisticated \"prompt injection\" attacks to see if your agent will ignore its instructions or reveal its system prompt.\n* ⚖️ **Bias & Fairness:** We test for hidden biases in financial, medical, or recruitment advice to ensure your agent stays compliant and fair.\n* 🤬 **Toxicity:** We try to provoke your agent into unprofessional or offensive behaviour.\n* 🛡️ **PII & Data Leakage:** We attempt to extract sensitive data like credit card numbers, internal keys, or user data that your agent shouldn't have the authority to share\n\n**Red Teaming as a Service (RTaaS):** Beyond our standard library of thousands of scenarios, we also deploy our Forward Deployed Engineers to build **personalised adversarial test cases** tailored to your specific industry and use case (HIPAA compliance for healthcare, PCI DSS for fintech, etc)\n\n**Ready to Security Test your Voice & Chat AI Agents?**\n\n* Book a call: <https://cal.com/kabrasidhant>\n* Email us: [founders@cekura.ai](mailto:founders@cekura.ai)\n\n# **The Team:**\n\nWe met over eight years ago during our undergraduate studies at IIT Bombay.\n\n[Tarush](https://www.linkedin.com/in/tarush-agarwal-b14851160/) comes from quantitative finance, where he worked on simulations for ultra-low latency trading strategies (think nanoseconds!).\n\n[Shashij](https://linkedin.com/in/shashij-gupta-671aa614a) has previously researched NLP at Google Research and is the first author of a paper on testing AI systems reliably, which has 50+ citations from his work at ETH Zurich.\n\n[Sidhant](https://www.linkedin.com/in/sidhantkabra) comes from a consulting background advising CXOs at Fortune 500 companies in FMCG and medical devices. He managed P&L in a leading contact centre.",
        "url": "https://www.ycombinator.com/launches/PCO-cekura-red-teaming-stress-test-your-ai-agents-for-jailbreaks-bias-toxicity-and-more",
        "votes": 17,
        "created_at": "2026-01-16T17:27:00.616Z"
      },
      {
        "id": 89476,
        "title": "Cekura: Automated Testing & Monitoring for Voice and Chat AI Agents",
        "tagline": "Ship reliable voice and chat agents faster with automated simulation, evaluation, observability and analytics ",
        "body": "Hi Everyone! We’re [Sidhant](https://www.linkedin.com/in/sidhantkabra/), [Shashij](https://www.linkedin.com/in/shashij-gupta-671aa614a/), and [Tarush](https://www.linkedin.com/in/tarush-agarwal-b14851160/), co-founders of Cekura👋\n\n**_TL;DR_** Cekura helps companies ship and scale reliable voice & chat AI agents by providing end-to-end testing and observability\n\nWatch our demo video [here](https://www.youtube.com/watch?v=EsEJJ32JQuM)\n\n**Problem:** Making Conversational AI agents reliable is hard. Manually calling your agents or listening through thousands of calls is slow, error-prone and does not provide the required coverage.\n\n**Our Solution:** At Cekura, we work closely with you at each step of the agent-building journey and help you improve and scale your agents 10 times faster\n\n![uploaded image](/media/?type=post&id=89476&key=user_uploads/1605191/a2827ed8-e974-4369-a5bf-a2407e52431b)\n\n**Key Features:**\n\n**Testing:**\n\n* **Scenario Generation**: Create varied test cases from agent descriptions automatically for comprehensive coverage.\n* **Evaluation Metrics:** Track custom and AI-generated metrics. Check for instruction following, tool calls, and conversational metrics (Interruptions, Latency, etc).\n* **Prompt Recommendation:** Get actionable insights to improve each of the metrics.\n* **Custom Personas:** Emulate diverse user types with varied accents, background noise, and conversational styles.\n* **Production Call Simulation:** Simulate production calls to ensure all the fixes have been incorporated.\n\n**Observability:**\n\n* **Conversational Analytics:** Provides customer sentiment, interruptions, latency and call analytics: ringing duration, success rate, call volume trends, etc\n* **Instruction Following:** Identify instances where agents fail to follow instructions.\n* **Drop-off Tracking:** Analyzes when and why users abandon calls, highlighting areas of improvement.\n* **Custom Metrics**: Define unique metrics for personalized call analysis.\n* **Alerting:** Proactively notifies users of critical issues like latency spikes or missed functions.\n\n**Ready to make your Voice & Chat Agents Reliable?**\n\n* Book a call: <https://cal.com/kabrasidhant>\n* Email us: [founders@cekura.ai](mailto:founders@oneleet.com)\n\n# **The Team:**\n\nWe met over eight years ago during our undergraduate at IIT Bombay.\n\n[Tarush](https://www.linkedin.com/in/tarush-agarwal-b14851160/) comes from quantitative finance, where he worked on simulations for ultra-low latency trading strategies (think nanoseconds!).\n\n[Shashij](https://linkedin.com/in/shashij-gupta-671aa614a) has previously researched NLP at Google Research and is the first author of a paper on testing AI systems reliably, which has 50+ citations from his work at ETH Zurich.\n\n[Sidhant](https://www.linkedin.com/in/sidhantkabra) comes from a consulting background advising CXOs at Fortune 500 companies in FMCG and medical devices. He managed P&L in a leading contact centre.",
        "url": "https://www.ycombinator.com/launches/NHA-cekura-automated-testing-monitoring-for-voice-and-chat-ai-agents",
        "votes": 36,
        "created_at": "2025-04-13T19:05:17.460Z"
      },
      {
        "id": 84885,
        "title": "Cekura (formerly Vocera) - Testing & Monitoring for AI Voice Agents",
        "tagline": "Launch reliable voice agents in minutes not weeks.",
        "body": "**_TL;DR_** Cekura helps companies ship and scale reliable voice & chat AI agents by providing end-to-end testing and observability\n\nWatch our demo video [here](https://www.youtube.com/watch?v=EsEJJ32JQuM)\n\n**Problem:** Making Conversational AI agents reliable is hard. Manually calling your agents or listening through thousands of calls is slow, error-prone and does not provide the required coverage.\n\n**Our Solution:** At Cekura, we work closely with you at each step of the agent-building journey and help you improve and scale your agents 10 times faster\n\n# **Key Features:**\n\n**Testing:**\n\n* **Scenario Generation**: Create varied test cases from agent descriptions automatically for comprehensive coverage.\n* **Evaluation Metrics:** Track custom and AI-generated metrics. Check for instruction following, tool calls, and conversational metrics (Interruptions, Latency, etc).\n* **Prompt Recommendation:** Get actionable insights to improve each of the metrics.\n* **Custom Personas:** Emulate diverse user types with varied accents, background noise, and conversational styles.\n* **Production Call Simulation:** Simulate production calls to ensure all the fixes have been incorporated.\n\n**Observability:**\n\n* **Conversational Analytics:** Provides customer sentiment, interruptions, latency and call analytics: ringing duration, success rate, call volume trends, etc\n* **Instruction Following:** Identify instances where agents fail to follow instructions.\n* **Drop-off Tracking:** Analyzes when and why users abandon calls, highlighting areas of improvement.\n* **Custom Metrics**: Define unique metrics for personalized call analysis.\n* **Alerting:** Proactively notifies users of critical issues like latency spikes or missed functions.\n\n**Ready to make your Voice & Chat Agents Reliable?**\n\n* Book a call: <https://cal.com/kabrasidhant>\n* Email us: [founders@cekura.ai](mailto:founders@oneleet.com)\n\n# **The Team:**\n\nWe met over eight years ago during our undergraduate at IIT Bombay.\n\n[Tarush](https://www.linkedin.com/in/tarush-agarwal-b14851160/) comes from quantitative finance, where he worked on simulations for ultra-low latency trading strategies (think nanoseconds!).\n\n[Shashij](https://linkedin.com/in/shashij-gupta-671aa614a) has previously researched NLP at Google Research and is the first author of a paper on testing AI systems reliably, which has 50+ citations from his work at ETH Zurich.\n\n[Sidhant](https://www.linkedin.com/in/sidhantkabra) comes from a consulting background advising CXOs at Fortune 500 companies in FMCG and medical devices. He managed P&L in a leading contact centre.\n\n![uploaded image](/media/?type=post&id=84885&key=user_uploads/795623/bbe88a02-e0d0-4bac-bbbd-304720fa753d)\n\n",
        "url": "https://www.ycombinator.com/launches/M57-cekura-formerly-vocera-testing-monitoring-for-ai-voice-agents",
        "votes": 158,
        "created_at": "2024-10-18T20:20:12.889Z"
      }
    ]
  },
  {
    "id": 30050,
    "name": "Smooth",
    "slug": "smooth",
    "former_names": [
      "Circlemind"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/bcfa8b54cf4b1b39fd0cb9dbb6a8d775676107b8.png",
    "website": "https://smooth.sh",
    "all_locations": "London, England, United Kingdom",
    "long_description": "Smooth is an AI browser agent that can perform actions autonomously on the web using mouse and keyboard. It’s the most reliable browser agent yet, while also being 5 times faster, and 7 times cheaper than any other browser agent on the market.\r\n\r\n",
    "one_liner": "Fast, simple, reliable AI browser agent",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1729125196,
    "tags": [],
    "tags_highlighted": [],
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    "isHiring": true,
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    "url": "https://www.ycombinator.com/companies/smooth",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/smooth.json",
    "year_founded": 2024,
    "city": "London",
    "country": "GB",
    "linkedin_url": "https://www.linkedin.com/company/circlemindai",
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      "name": "Diana Hu",
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        "user_id": 846180,
        "full_name": "Antonio Vespoli",
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        "founder_bio": "Antonio is the co-founder and CEO of Circlemind. He holds a Master’s degree in Computing from Imperial College London, specializing in AI and Machine Learning. He spent three years as a Software Engineer at AWS, working on real-time streaming technology.",
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        "linkedin_url": "https://linkedin.com/in/antonio-vespoli-895727121",
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        "id": 84118,
        "title": "Software Engineer",
        "url": "https://www.ycombinator.com/companies/smooth/jobs/1H7isFV-software-engineer",
        "location": "London, England, GB / Cambridge, England, GB",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$70K - $130K",
        "equity_range": "0.10% - 2.00%",
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        "id": 94829,
        "title": "Smooth - Fast, simple, reliable AI browser agent",
        "tagline": "Serverless browser agent API built from first principles: reliable, secure, 5x faster, 7x cheaper, and extremely scalable",
        "body": "Hey everyone! We're Antonio and Luca, the founders of Smooth - the fastest and most reliable browser agent yet.\n\n**TL;DR:** Smooth is an AI browser agent that can perform actions autonomously on the web using mouse and keyboard. It’s the most reliable browser agent yet, while also being 5 times faster, and 7 times cheaper than any other browser agent on the market.\n\n👉🏼 [Try it now free](https://app.smooth.sh)\n\nhttps://youtu.be/fvf7oLcSxWg\n\n**The problem**\n\n![uploaded image](/media/?type=post&id=94829&key=user_uploads/846180/9b08b367-2751-4fb4-89cd-7ae50362a4c1)\n\nAlthough browser agents are becoming a reality, we found that existing solutions are:\n\n1. **Too expensive** Usually require large models - can easily end up costing a few dollars even for simple tasks.\n2. **Too slow** Can take way too long to complete - e.g. 4 min to book a flight.\n3. **Unreliable** Even when provided with detailed instructions, they can struggle to complete the task.\n\nLLMs may be exceptional at advanced math, but they still struggle to book a flight.\n\n**Our solution**\n\n![uploaded image](/media/?type=post&id=94829&key=user_uploads/846180/5c0da911-8b6c-419c-9018-e638bf6e64d3)\n\nWe found that if you combine small and efficient models with a carefully curated context design, you can get **higher reliability** while also getting **human-speed navigation** and a **huge cost reduction**!\n\n![uploaded image](/media/?type=post&id=94829&key=user_uploads/846180/1f5cc0da-bcfb-48a1-8972-8a4f23790d2c)\n\nWe packaged Smooth in a **super-easy-to-use API** with instant browser spin-up, custom proxies, persistent sessions, and auto-CAPTCHA solvers. Our goal is to give you this infrastructure so that you can focus on what's important: building great apps for your users.\n\nSmooth is infinitely scalable, production ready, and secure. You can get started for free and run browser tasks in just 4 lines of code.\n\n**Our Asks**\n\n* **Give [Smooth](https://app.smooth.sh) a try!** We’d love to hear your experience\n* Drop us a line at [antonio@circlemind.co](mailto:antonio@circlemind.co) if you’d like to chat\n\n![uploaded image](/media/?type=post&id=94829&key=user_uploads/846180/f6a666db-7a65-4ef2-923d-5b2abf4c9018)\n\n",
        "url": "https://www.ycombinator.com/launches/OfV-smooth-fast-simple-reliable-ai-browser-agent",
        "votes": 27,
        "created_at": "2025-10-22T17:12:00.808Z"
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    "name": "Lingo.dev",
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    "long_description": "Lingo.dev is the localization engineering platform: the best way to translate with LLMs, measure translation quality, and proofread with native speakers.\r\n\r\nLingo.dev is built for teams accountable for quality in languages they can't read. Teams configure localization engines, stateful translation APIs that hold the glossary, brand voice, and per-locale model preferences, and every request retrieves that context at inference time through retrieval augmented localization. Every translation is scored before it goes live, scores and corrections tune the engine, and the localization team runs the localization infrastructure. Integrate through the API, CLI, CI/CD, or native integrations with the code repository and the CMS. \r\n\r\nLingo.dev is the standard localization infrastructure for modern enterprise teams scaling into new markets – including Mistral, Solana, SoSafe, and Cal.com. Over 300M words processed, SOC 2 Type II compliant.",
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    "subindustry": "B2B -> Engineering, Product and Design",
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        "question": "How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)",
        "answer": "Veronica and Max met eight years ago at work and have been building together since. Veronica came from data science, then AI. Max came from engineering, having led a DORA-elite frontend team at Typeform.\r\n\r\nBetween them they had shipped software at startups and enterprises and bootstrapped a SaaS with customers in over 100 countries. Localization broke the same way every time: the people accountable for the result could not read most of the languages they were accountable for. They approved work they could not check, and they found out it was wrong from a customer.\r\n\r\nEvery product on the market treated that as a workflow problem, so it sold coordination. It is a measurement problem. Lingo.dev was built around the instrument first, and the pipeline around the instrument."
      },
      {
        "question": "How did you decide to apply to Y Combinator? What was your experience applying, going through the batch, and fundraising at demo day?",
        "answer": "Our first serious customers arrived, Cal.com among them, and the question stopped being whether this works and became how far it goes. Localization is a global problem by definition. Every company that grows past one language has it, in every market it enters, permanently. A problem that shape deserves a lasting, durable company behind it rather than a good couple of years.\r\n\r\nSo we shot for the stars and applied to the best accelerators in the world. We ended up in conversations with several, and we chose Y Combinator.\r\n\r\nNo other program has a record like it. Stripe, Airbnb, DoorDash, and Coinbase all started there, and each one became the default infrastructure of an entire category, operating in nearly every market on earth. YC backs companies at the point where the idea still looks small and the market does not exist yet, and it does that more often, and more correctly, than anyone else. That is the standard it sets, and that is the company we wanted to keep.\r\n\r\nThe batch did what it is known for: sharper questions, faster iteration, and a peer group that tells you the truth early rather than politely later. We raised $4.2M from Y Combinator, Initialized Capital, and the founders of Supabase and Dependabot to scale the platform and meet the growing demand from international teams."
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        "question": "How have you kept in touch with the YC community and continued to use YC resources & programs since the batch ended?",
        "answer": "We attend YC events and stay close to the private network between them.\r\n\r\nWe try to be genuinely useful. Founders ask about localization, going multilingual, and expanding internationally, and we take those conversations whenever there is a chance to help. The network works because founders treat it as something to contribute to, so that is how we use it."
      },
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        "question": "What's the history of your company from getting started until the present day? What were the big inflection points?",
        "answer": "Founded in December 2023, after winning an AI product competition at Cornell Tech in New York. Full-time from February 2024.\r\n\r\nThe first product translated software with AI on every commit. It worked, and it showed how small that problem is. The commit loop is roughly one percent of localization work, and it was already close to solved.\r\n\r\nThe inflection was the buyer. Localization managers and localization engineers carry accountability for quality in languages they cannot read, and the market treats that seat as an afterthought. The company was rebuilt around that seat, and the tool became a platform: localization engines, quality scoring, native integrations, and proofreading with native speakers.\r\n\r\nToday over 300M words have been processed on the platform, for teams including Mistral, Solana, SoSafe, and Cal.com. Lingo.dev is SOC 2 Type II compliant and has raised $4.2M from Y Combinator, Initialized Capital, and the founders of Supabase and Dependabot to scale the platform and meet the growing demand from international teams."
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        "question": "What is the core problem you are solving? Why is this a big problem? What made you decide to work on it?",
        "answer": "A company releases into thirty languages. The person accountable for those languages reads two.\r\n\r\nTranslation stopped being the constraint, it comes back in seconds, from an agency or straight from a model, and it gets cheaper every quarter. What nobody hands the accountable team is the number: which languages are good, which drifted, and what to fix first. Without it the team either trusts output it cannot read, or pays a person to read every string.\r\n\r\nLingo.dev is where that number comes from. Teams pick from the industry-standard metrics or define quality criteria in plain words, and every translation is scored before it goes live. Every low score carries its reason, traced to the model, the translation rule, or the missing glossary term. Corrections from native speakers tune the localization engine, so the edit rate falls over time.\r\n\r\nIt is a big problem because the accountability does not move. Software goes out in more languages every year, the people who answer for those languages still cannot read them, and the volume of text nobody has checked grows with every release."
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        "question": "What is your long-term vision? If you truly succeed, what will be different about the world?",
        "answer": "Translation quality becomes a measured quantity.\r\n\r\nToday it is an opinion. Vendors assert it, buyers cannot check it, and nearly every quality number published in this industry arrives without a method behind it. When Lingo.dev succeeds, a team states what its Japanese was worth this quarter, what changed since last quarter, and what caused the change, the same way it states its uptime.\r\n\r\nDownstream of that, a product goes live in every language it has customers in on the day it goes live in English, and the team that owns those languages proves the result instead of defending it."
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        "full_name": "Max Prilutskiy",
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        "full_name": "Veronica Prilutskaya",
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        "title": "Lingo.dev is an app localization engine for developers | TechCrunch",
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        "date": "Feb 18, 2025"
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        "id": 84681,
        "title": "Lingo.dev – The Localization Engineering Platform",
        "tagline": "Lingo.dev is the localization engineering platform: the best way to measure translation quality, translate with LLMs, and proofread with native speakers.",
        "body": "![uploaded image](/media/?type=post&id=84681&key=user_uploads/1992394/c62aca07-353c-49ad-a49e-b403d1b784e0)\n\n**TL;DR**\n\n[Lingo.dev](https://lingo.dev) is the localization engineering platform: the best way to translate with LLMs, measure translation quality, and proofread with native speakers.\n\nIt's built for teams accountable for quality in languages they can't read: a localization team, or the product, engineering, or marketing team that inherited localization without one. Every translation is scored before it goes live, and scores and corrections tune the localization engine.\n\n**Speed stopped being the problem**\n\nA release goes out in thirty languages, and the person accountable for it reads two.\n\nTranslation comes back fast now, from an agency or straight from a model, and it gets cheaper every quarter. The number nobody hands you is the quality one: which languages are good, which drifted, and what to fix first. Without it you are accountable for quality you can neither read nor repair.\n\n**What Lingo.dev does**\n\n* **Build your own localization engine.** A localization engine is a stateful translation API that holds your glossary, brand voice, and per-locale model preferences. Retrieval augmented localization sends that context to the LLM at inference time. Assign the highest-scoring model per language pair, with a fallback order, on your own LLM provider API key or through Lingo.dev without markup.\n* **Measure translation quality in languages you can't read.** Pick from the industry-standard metrics, define your own quality criteria in plain words, bring the quality scorecard you have, or start from a template built for your content type. The criteria you define score translations from LLMs and from native speakers, and every low score comes with the reason, traced to the model, the translation rule, or the missing glossary term.\n* **Integrate localization into the tools you already use.** Connect the code repository, the CMS, the help center, and the email provider through native integrations, and reach the same localization engine from the API, the CLI, and CI/CD. The localization team runs the localization infrastructure.\n* **Proofread with native speakers.** Decide what waits for a person, by content type, by locale, or by a score threshold you set. Every correction tunes the localization engine, so the native speakers' edit rate falls over time.\n\n**Who runs on it**\n\nLingo.dev is the standard localization infrastructure for modern enterprise teams scaling into new markets, including Mistral, Solana, SoSafe, and Cal.com. Teams have processed over 300M words on the platform, for their customers all over the world. Lingo.dev is SOC 2 Type II compliant, and has raised $4.2M from Y Combinator, Initialized Capital, and the founders of Supabase and Dependabot to scale the platform and meet the growing demand from international teams.\n\n**Ask**\n\nIf you release into languages nobody on your team reads, we will score what goes live today, per language, on your own content.\n\nSet up Lingo.dev: <https://lingo.dev>\n\nBook a demo: <https://lingo.dev/enterprise>\n\nAnd send this to the localization professional you know. Scoring quality in languages nobody on the team reads is their job, and this is where that work happens.\n\n**Team**\n\n[Veronica](https://www.linkedin.com/in/vrcprl/) and [Max](https://www.linkedin.com/in/maxprilutskiy/), [Lingo.dev](https://lingo.dev)'s founders, met eight years ago at work. Veronica has a data science and AI background. Max has an engineering background, having led a DORA-elite frontend team at Typeform, one of Europe's best-known SaaS products.\n\nBoth experienced localization problems firsthand while working at startups and enterprise companies and while bootstrapping a SaaS with customers from over 100 countries. This shared experience led them to create Lingo.dev, so the professionals accountable for translation quality can measure it in every language, including the ones nobody on the team reads.\n\n![uploaded image](/media/?type=post&id=84681&key=user_uploads/1989733/dfd03586-1d6f-4747-b6fc-e0d84f5022a5)\n\n",
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        "created_at": "2024-10-10T18:18:35.695Z"
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    "long_description": "We're making consumer agent products completely free, using the best open source models, and funded by ads.\r\n\r\nOur first product is a coding agent CLI called Freebuff. Install it with \"npm i -g freebuff\". We're also working on a free Lovable competitor.",
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        "linkedin_url": "https://linkedin.com/in/dawson-chen-9b62a8183",
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        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a19f23149740545587c28d316ec7bba81471c118.jpg"
      }
    ],
    "jobs": [
      {
        "id": 95411,
        "title": "Founding Growth Marketer",
        "url": "https://www.ycombinator.com/companies/freebuff/jobs/VwKy5Xq-founding-growth-marketer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Marketing",
        "role_type": null,
        "salary_range": "$100K - $150K",
        "equity_range": "0.25% - 0.50%",
        "experience": "1+ years",
        "visa": "Will sponsor",
        "skills": []
      },
      {
        "id": 113138,
        "title": "Founding Advertiser Success Manager",
        "url": "https://www.ycombinator.com/companies/freebuff/jobs/5YPVgDs-founding-advertiser-success-manager",
        "location": "San Francisco, CA, US / Remote",
        "type": "Full-time",
        "role": "Support",
        "role_type": null,
        "salary_range": "$75K - $100K",
        "equity_range": "0.05% - 0.10%",
        "experience": "1+ years",
        "visa": "US citizenship/visa not required",
        "skills": []
      },
      {
        "id": 113139,
        "title": "Founding Account Executive",
        "url": "https://www.ycombinator.com/companies/freebuff/jobs/FQJSsqv-founding-account-executive",
        "location": "San Francisco, CA, US / Remote (US)",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$80K - $100K",
        "equity_range": "0.10% - 0.25%",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
        "skills": []
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    "news": [],
    "launches": [
      {
        "id": 84718,
        "title": "Codebuff: Make your terminal write code for you",
        "tagline": "\"Very f****** cool\" CLI for AI code generation",
        "body": "Codebuff is a CLI-based coding agent – invoke it in your Terminal and ask it to write code for you. We launched on BookFace last week and got 500 downloads and 60+ upvotes!\n\nIt’s a Cursor alternative that’s simpler and frequently performs better. Try it out:\n\n```\nnpm install -g codebuff\n```\n\n![uploaded image](/media/?type=post&id=84718&key=user_uploads/209148/c0fe87b7-bb51-47ac-9023-8cc38ede96cf)\n\n### What people are saying\n\n![uploaded image](/media/?type=post&id=84718&key=user_uploads/209148/6224e821-9d82-4620-b57f-d428c9af8ea0)\n\n![uploaded image](/media/?type=post&id=84718&key=user_uploads/209148/771297ed-0012-4601-a983-e416463f16fb)\n\n![uploaded image](/media/?type=post&id=84718&key=user_uploads/209148/86a6581c-ef41-490e-9a17-b36a5f73f629)\n\n![uploaded image](/media/?type=post&id=84718&key=user_uploads/209148/4c066ef1-ced0-4fc1-b5d4-a16a8ef7609c)\n\n![uploaded image](/media/?type=post&id=84718&key=user_uploads/209148/14872fde-79d4-4e53-8491-457e41f4ff5f)\n\n### Fewer clicks, more codebase context\n\nCodebuff is different from all the other coding agents, we swear!\n\n* **It chooses files to read automatically on each message** — unlike Cursor’s composer feature. This saves you time and makes Codebuff respond more comprehensively.\n* **It takes 0 clicks** — type your instructions and Codebuff will edit your files directly. It's simple and fast. Theoretically, you can do all your development by just chatting with it!\n* **It has full access to your existing tools, scripts, and packages** — Codebuff can install packages, run terminal commands and tests, etc. Whatever awk/grep/pip install stuff you used to do, Codebuff can do it for you instead!\n* **It is portable to _any_ development environment —** no lock-in here! Feel free to bring your IDE: VSCode, Cursor, Vim, Emacs, Replit, or plain text editor (if you’re a monster).\n* **We don’t store your codebase** — we just pass individual files along to OpenAI and Anthropic as is necessary to generate code. We didn’t even have a database until a couple weeks ago!\n\nCodebuff can write code for every tech stack – we know because we’ve built software from full-stack web apps to IoT device firmware.\n\n<https://www.tella.tv/video/code-coding-agent-bh6l>\n\n### Offer\n\nTo celebrate our launch, we are giving away **2,500 free Codebuff credits per month** for a limited time to new users!\n\nTo claim, 1. get Codebuff in your terminal:\n\n```bash\nnpm install -g codebuff\n```\n\n2\\. Run `codebuff` in your project directory.\n\n3\\. Finally, enter “login” to sign up and claim the 2,500 free credits.\n\nAlso, **existing users**: you can refer your friends at [codebuff.com/referrals](http://codebuff.com/referrals) — when you refer a friend, you’ll both get **500 credits per month**!\n\n## 🙏 Ask\n\nTry it out and give us feedback! Check out our website <https://codebuff.com>\n\nIf you have any thoughts, please join our Discord: <https://discord.gg/mcWTGjgTj3>. We love love love all feedback, positive and negative! Even slightly backhanded ones like this 😅:\n\n![uploaded image](/media/?type=post&id=84718&key=user_uploads/209148/b24d3c54-1d2c-4bca-8c2f-37a65f0fb8d1)\n\nSo please try Codebuff out and let us know what you think!",
        "url": "https://www.ycombinator.com/launches/M2Q-codebuff-make-your-terminal-write-code-for-you",
        "votes": 62,
        "created_at": "2024-10-12T00:23:25.975Z"
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    "name": "vly.ai",
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    "website": "https://vly.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "The world's best AI web app builder, implementing a radically unique architecture that lets us completely outperform the competition in complexity, reliability, scalability, and more. We are 7x cheaper and are positioned to take down Lovable, Replit, Base44, Bolt, Emergent, and more.",
    "one_liner": "The Lovable & Replit killers",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1730684290,
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      "America / Canada"
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/vly-ai-2",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/vly-ai-2.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://linkedin.com/company/vly-ai",
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        "full_name": "Victor Cheng",
        "title": "Founder/CEO",
        "founder_bio": "1x exit at 19. Autodesk @ 17, founder @ 18, coding since 11. dropout @ uw computer science. Automating full-stack web development.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/victor-cheng-89a161180/",
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    "id": 30096,
    "name": "Capy",
    "slug": "capy",
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/632fea3abffd6f4ca17133e97e8ebb9eb1a9f356.png",
    "website": "https://capy.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Orchestrate an army of coding agents from one dashboard. Ship entire sprints in parallel.",
    "one_liner": "The IDE for the parallel age",
    "team_size": 6,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1730261485,
    "tags": [
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      "AI Assistant"
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    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Fall 2024",
    "status": "Active",
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    "regions": [
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      "America / Canada"
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    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/capy",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/capy.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/capydotai",
    "x_url": "https://twitter.com/capydotai",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/scrapybara",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/632fea3abffd6f4ca17133e97e8ebb9eb1a9f356.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [
      "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/bc53ee2eb036afa9deb636a9e3baf45649ea0d62.png"
    ],
    "primary_partner": {
      "name": "David Lieb",
      "url": "https://www.ycombinator.com/people/david-lieb"
    },
    "founders": [
      {
        "user_id": 531507,
        "full_name": "Nalin Semwal",
        "title": "Founder/CEO",
        "founder_bio": "building the AI SWE @Capy",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/nsemwal",
        "x_url": "https://x.com/lordspline",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/61987d2262cb9d3bb95a480e2aa79fe1c592d0d2.jpg"
      },
      {
        "user_id": 1520005,
        "full_name": "Justin Sun",
        "title": "Founder/CTO",
        "founder_bio": "cofounder @ capy (f24)",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/justinsunyt",
        "x_url": "https://twitter.com/justinsunyt",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/de0164207871acf4321213de35f58cc44c0be65e.jpg"
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    "jobs": [
      {
        "id": 72482,
        "title": "Founding Design Engineer",
        "url": "https://www.ycombinator.com/companies/capy/jobs/FBbRyVg-founding-design-engineer",
        "location": "SF",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$150K - $250K",
        "equity_range": "0.50% - 1.50%",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 72483,
        "title": "Founding Engineer",
        "url": "https://www.ycombinator.com/companies/capy/jobs/FuQPALB-founding-engineer",
        "location": "SF",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$150K - $250K",
        "equity_range": "0.50% - 1.50%",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
        "skills": []
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    ],
    "news": [],
    "launches": [
      {
        "id": 85645,
        "title": "Scrapybara - A Computer for Your AI ₍ᐢ•(ܫ)•ᐢ₎",
        "tagline": "API-accessible computer environments purpose-built for AI agents.",
        "body": "Hey YC! Nalin and Justin here; we’re building [Scrapybara](https://scrapybara.com) to help you deploy AI agents that can use computers. We handle deployment, maintenance and scaling so your agent just sees 👇\n\n![uploaded image](/media/?type=post&id=85645&key=user_uploads/531507/8e055289-f7a9-42f4-895e-df83e7a61e28)\n\n**TL;DR**\n\n**_Deploy and productionize computer use._**\n\nScrapybara provides instant, secure virtual desktop environments via API for AI agents to perform tasks. We reduce deployment time from hours to seconds through our purpose-built platform.\n\n[https://youtu.be/ZjPTAb5bg-w](https://youtu.be/ZjPTAb5bg-w?si=8PVUmhtHmdC6iPr2)\n\n## 💻 For Instance\n\n* _A **Market Research Firm** could have their agent browse news sites, create summaries, and update their internal dashboards, all on Scrapybara_\n* _A **Healthcare Administrator** could use agents to process insurance forms and operate ERP software (even the kind that only runs on desktops), all on Scrapybara_\n* _A **Sales Development Representative** could use agents to find information on leads, reach out to them and update their Salesforce, all on Scrapybara_\n\n## 🚨 The Problem: AI Needs a Safe Place to Execute\n\nAI agents are becoming increasingly capable of writing code, analyzing data, and performing complex tasks. However, there's a critical missing piece: a secure, scalable environment where these agents can actually take actions. Current solutions force developers to choose between:\n\n* Using APIs (limited, inflexible)\n* Using browsers (unstable)\n\n**_Don’t run AI agents on your own computer._**\n\n## 💡 Our Solution: Purpose-Built Computers for AI\n\nScrapybara provides instant, secure virtual environments via API that spin up within seconds and are specifically designed for AI agents:\n\n🚀 **Speed**\n\n* Environment creation in seconds\n* Pre-warmed container pool\n* Optimized runtime layers\n\n🔒 **Security**\n\n* Isolated execution environments\n* Resource limits and timeouts\n\n💰 **Cost Optimization**\n\n* True per-second billing\n* Zero idle costs\n* Automatic resource scaling\n\n🔌 **Simple Integration**\n\n* REST API\n* Popular language SDKs\n* One-line deployment\n* Built-in monitoring\n* Plug and play with Claude’s Computer Use\n\n## 🤖 Getting Started\n\n![uploaded image](/media/?type=post&id=85645&key=user_uploads/531507/3d2131de-561f-44d6-b067-ca4ec82d4da8)\n\n![uploaded image](/media/?type=post&id=85645&key=user_uploads/531507/9cf26326-1a29-462f-a521-7756714eba11)\n\n![uploaded image](/media/?type=post&id=85645&key=user_uploads/531507/47fbd307-bf81-4be9-9286-f54124f7f512)\n\nTaking screenshots:\n\n![uploaded image](/media/?type=post&id=85645&key=user_uploads/531507/df36a97f-b1c3-445f-b15d-412ef6cc63ca)\n\nTaking actions:\n\n![uploaded image](/media/?type=post&id=85645&key=user_uploads/531507/bf4cb53b-f5e5-4542-a141-f3c2a02a9496)\n\n![uploaded image](/media/?type=post&id=85645&key=user_uploads/531507/594f98c1-7eb1-4862-9fb8-d81f02f9547d)\n\n## ♾️ Limitless Possibilities\n\nPlug your multimodal agents into Scrapybara and empower them to automate all kinds of work. The only limit is your imagination.\n\n![uploaded image](/media/?type=post&id=85645&key=user_uploads/531507/e3cc5c6b-07db-4c3d-8476-0bc6d19e30ca)\n\n![uploaded image](/media/?type=post&id=85645&key=user_uploads/531507/de5d45bb-0019-48a9-950a-813d679df759)\n\n![uploaded image](/media/?type=post&id=85645&key=user_uploads/531507/5e0a5cfa-4f38-4b3b-a741-b2ab96c868c3)\n\n![uploaded image](/media/?type=post&id=85645&key=user_uploads/531507/ab7a4ed5-9d84-4e62-a560-88ac1a9a32fa)\n\n## 🚧 Coming Soon\n\n* Windows, Android, and other virtual OS’s\n* Dedicated Code Execution Sandboxes\n* and much more!\n\n## 👾 About Us\n\n* Nalin: AI Research @ MultiOn | LLM Agent Research @ Georgia Tech\n* Justin: AI Product @ MultiOn | M&T @ UPenn\n\nWe met at MultiOn where we led B2B and consumer web agent development and built the best-in-class web extraction API (Retrieve).\n\n![uploaded image](/media/?type=post&id=85645&key=user_uploads/531507/1053d2e9-2ea6-4e29-8b4e-1d37da808e5d)\n\n## The Ask\n\n1. **Try it out**: Building general-purpose or vertical-specific agents that could do with computer use? Go to [scrapybara.com](http://scrapybara.com)!\n2. **Intro us**: Know someone who could use this? We'd love an intro!\n3. **This is cool I just want to chat about it**: Heck yeah! Email us 👇\n\nContact: [hello@scrapybara.com](mailto:hello@scrapybara.com) \\\nLinkedIn: <https://linkedin.com/company/scrapybara> \\\nX: <https://x.com/scrapybara>\n\n![uploaded image](/media/?type=post&id=85645&key=user_uploads/531507/80b9b821-8e48-4f0a-9583-68008d3309ca)\n\n",
        "url": "https://www.ycombinator.com/launches/MHN-scrapybara-a-computer-for-your-ai",
        "votes": 74,
        "created_at": "2024-11-18T04:54:22.279Z"
      }
    ]
  },
  {
    "id": 30100,
    "name": "Alex",
    "slug": "alex",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/211bbe719ecb6e8800789a12c674df98b2a1fb49.png",
    "website": "https://alexcodes.app",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Tired of switching tabs to cursor every time you're building your iOS app in Xcode?\r\n\r\nWorry not!\r\n\r\nAlex is a sidebar app that works directly with Xcode, and has the same Cmd+L, Cmd+K, and Apply Code commands as Cursor. And, it's super fast.\r\n\r\nCheck it out: https://alexcodes.app",
    "one_liner": "The Cursor for Xcode",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1728718432,
    "tags": [],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Fall 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/alex",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/alex.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/alex-sidebar/",
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    "fb_url": null,
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    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/211bbe719ecb6e8800789a12c674df98b2a1fb49.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "David Lieb",
      "url": "https://www.ycombinator.com/people/david-lieb"
    },
    "founders": [
      {
        "user_id": 559658,
        "full_name": "Daniel Edrisian",
        "title": "Founder/CEO",
        "founder_bio": "I'm an iOS Engineer, formerly built the iOS app for ElevenLabs and was a founding engineer at FlutterFlow (YC W21). Prior to that, I interned at Apple, Meta, and Google.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/daniel-edrisian/",
        "x_url": "https://x.com/DanielEdrisian",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5fad67bd1d4b6c2544dc88ad99cdf8486c3e0bd7.jpg"
      }
    ],
    "jobs": [
      {
        "id": 70860,
        "title": "Founding Engineer",
        "url": "https://www.ycombinator.com/companies/alex/jobs/uB3KJ2P-founding-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$1",
        "equity_range": "1.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      }
    ],
    "news": [],
    "launches": [
      {
        "id": 85378,
        "title": "Alex Sidebar: The Cursor for Xcode",
        "tagline": "The most powerful Copilot for iOS Development",
        "body": "**Hey there!**\n\nMy name is Daniel, and I'm the founder of Alex: The missing sidebar for Xcode 🍏\n\nBeing an iOS Developer since I was 13, Xcode is rooted in my DNA. I admittedly really like Xcode (when it’s not crashing), and I find it feature-complete for _almost_ everything I need as a developer — except one: **AI codegen**. That’s where Alex comes in.\n\n[Alex - Your AI Copilot for Xcode](https://www.youtube.com/watch?v=CEefIxm-WdA)\n\n**TL;DR 🧵**\n\nAlex is like Cursor for Xcode, and gives you AI features like sidebar chat, inline completions, and tab to complete. **Since launching last week, over 1200 users** **have signed up for Alex, and hundreds are using it every day for their work.**\n\nWe want to make Software Development easier for the 3+ million people who use Xcode. Check out our website to get started!\n\n<https://alexcodes.app>\n\n# **How does it work?**\n\nAlex interacts with Xcode using MacOS's Accessibility features. It can read what you see on Xcode, and can write to it. It also knows where your cursor is, so it can accurately place the suggestions and \"Fix Error\" buttons.\n\n![uploaded image](/media/?type=post&id=85378&key=user_uploads/559658/8fd0cb1d-44f9-439b-a7e4-ba0f2cfc9a74)\n\n![uploaded image](/media/?type=post&id=85378&key=user_uploads/559658/1748b92b-238a-40b9-8d43-86688a1d5999)\n\nAlex also embeds your Xcode projects for use in Codebase Search. We let you connect to any custom OpenAI-compatible model, or use your own keys for OpenAI, Anthropic, Perplexity, and VoyageAI.\n\n# **What next?**\n\nAt Alex, we want to make high-quality iOS development significantly faster. We plan on doing two major things in the future:\n\n1. **Creating the iOS LLMs.**\n\n   With each new iOS release and iOS SDK, new APIs are introduced into Swift and SwiftUI, and more APIs get deprecated. The state-of-the-art models like OpenAI and Anthropic either don't have the latest iOS code baked into their knowledge, or their top-1 retrieval doesn’t correspond with the latest APIs.\n\n   This is because there simply isn't enough training data from new iOS APIs, and not enough data indicating deprecated code. We plan to create our own model, trained using Apple's latest documentation, and available both as large-scale model finetunes for chat, and as smaller scale finetunes for inline suggestions.\n2. **Creating your own local iOS agent.**\n\n   Our long term plan is creating your own local iOS Development agent. Imagine Alex running several tasks in the background: Code refactors, optimizations, tests, documentation, and bug fixing all done in the background — while you do the most exciting part: Feature development.\n\n# **Conclusion (and a signup deal!)**\n\nIt's been exciting to see teams fully switch from their Cursor/Xcode setup to just using Xcode with Alex. We have engineers at dozens of companies already using us for their production iOS codebases, from large online marketplaces to apps for aircraft navigation. ✈️\n\nFeel free to give it a try! (It's free, and you can get **50 free O1-Preview credits** when you sign up.) \n\n[alexcodes.app](http://alexcodes.app)\n\nAnd join us on Discord:\n\n[discord.gg/fwbmYA3fEH](http://discord.gg/fwbmYA3fEH)",
        "url": "https://www.ycombinator.com/launches/MD4-alex-sidebar-the-cursor-for-xcode",
        "votes": 112,
        "created_at": "2024-11-08T14:41:47.545Z"
      }
    ]
  },
  {
    "id": 30101,
    "name": "Kilvin",
    "slug": "kilvin",
    "former_names": [
      "Chorrie",
      "BrowserBook"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b8aa78b8b96db85bb2ce800dc4eae6fc788564af.png",
    "website": "https://www.kilvin.ai",
    "all_locations": "New York City, NY, USA",
    "long_description": "Kilvin is an AI-native agency that builds custom software solutions for non-technical teams.\r\n\r\nWith AI, the future of software is democratized. Every team deserves tools built exactly for them, not off-the-shelf SaaS products they need to adapt to. Kilvin makes it a reality, delivering a private, secure workspace of custom applications, built around your workflows and ready in days, not months.\r\n\r\nNo engineers needed on your side. Just software that fits exactly how you work.",
    "one_liner": "Custom software for your business",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1731609344,
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      "Productivity",
      "Data Engineering",
      "Automation",
      "AI"
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    "isHiring": true,
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    "regions": [
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      "America / Canada",
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      "Partly Remote"
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    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/kilvin",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/kilvin.json",
    "year_founded": 2024,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://linkedin.com/company/kilvin-ai/",
    "x_url": "https://x.com/cschlaep",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/kilvin",
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/b8aa78b8b96db85bb2ce800dc4eae6fc788564af.png",
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    "primary_partner": null,
    "founders": [
      {
        "user_id": 739375,
        "full_name": "Christopher Schlaepfer",
        "title": "Founder/CEO",
        "founder_bio": "Co-Founder and CEO of Kilvin. https://www.kilvin.ai",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/cschlaep/",
        "x_url": "https://x.com/cschlaep",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/392cd705c1908c02f96668e38871dd3f2234f243.jpg"
      },
      {
        "user_id": 1970548,
        "full_name": "Jorrie Brettin",
        "title": "Founder/CTO",
        "founder_bio": "Co-Founder and CTO of Kilvin. https://www.kilvin.ai\n",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jorrie-brettin-349a6383/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c28014416ede57d2fe39326db64b2cc5ff2da234.jpg"
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    ],
    "jobs": [
      {
        "id": 96213,
        "title": "Senior Platform Engineer",
        "url": "https://www.ycombinator.com/companies/kilvin/jobs/s3b5Le2-senior-platform-engineer",
        "location": "New York, NY, US / Denver, CO, US / Philadelphia, PA, US / Remote (US)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$120K - $180K",
        "equity_range": "0.01% - 1.00%",
        "experience": "6+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Git",
          "Smalltalk",
          "TypeScript",
          "AI Agents"
        ]
      },
      {
        "id": 100106,
        "title": "Forward-Deployed Engineer",
        "url": "https://www.ycombinator.com/companies/kilvin/jobs/5WEK19z-forward-deployed-engineer",
        "location": "New York, NY, US / Philadelphia, PA, US / Denver, CO, US / Remote (US)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$120K - $180K",
        "equity_range": "0.01% - 0.50%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Git",
          "TypeScript",
          "AI Agents"
        ]
      }
    ],
    "news": [],
    "launches": [
      {
        "id": 96111,
        "title": "BrowserBook - The Browser Automation IDE",
        "tagline": "Write, run, and deploy reliable web automations in minutes, not hours",
        "body": "Hey YC!\n\nWe’re [Chris](https://www.linkedin.com/in/cschlaep/) and [Jorrie](https://www.linkedin.com/in/jorrie/), cofounders of [BrowserBook](https://www.browserbook.com).\n\nhttps://youtu.be/FkaGHhJWy1w\n\n# **TLDR**\n\nWe make it trivial for developers to write reliable web automations.\n\n# **Ok, but _what is it?_**\n\nBrowserBook is an IDE that puts all the tools automators need in one place, so the iteration loop to write, test, debug, and deploy web automations is significantly reduced.  It combines:\n\n* **A Jupyter-like coding environment** where developers can run code cells individually,\n* **An inline browser** to run automation code against\n* **A Playwright coding agent** that can write the automation for you\n* **A bunch of built-ins** for taking screenshots, extracting data, and authentication\n\nAnd, once you’re done writing your script, you can deploy it and trigger it via our public API.  It’s super easy!\n\n# **But browser agents are a thing, right?**\n\nYes, and we’re not using them.  We built BrowserBook because of the shortfalls we experienced with browser agents and the pain of actually writing reliable scripts.  At a very high level, in the AI world you can take two approaches to web automation - write scripts, or use browser agents.\n\n1. **Use browser agents:** ostensibly more flexible, but expensive, slow, and unreliable\n2. **Write scripts:** fast and debuggable, but infamously brittle\n\nWhich leads us to…\n\n# **The problem (and how we got here)**\n\n**Sometimes we need machines to interact with web pages, which are made for humans.**\n\nThis is basically the whole challenge.  There’s a lot of reasons we might want machines to poke around on the web:\n\n* Agents using a browser to interact with the web to perform actions like humans, especially when they can’t use APIs\n* Scrapers to gather data that’s useful for our business\n* UI tests that can interact with a website the way a human would to ensure everything’s working as intended\n* Workflow automation via RPA\n\nWe tried **browser agents** in our pre-pivot days to automate healthcare workflows. They mostly didn’t work; they were an order of magnitude more expensive than scripts, slow because of all the context they needed, and tended to drift when workflows got complex.  When they did drift, fixing them was just tedious prompt-massage and trial-and-error.\n\nWe ended up giving the agent a library of scripts to execute, and came to realize scripting was simply the better solution for reliable enterprise workflows; they’re deterministic and therefore inherently debuggable, not to mention their cost and speed advantage.  They with a host of issues though:\n\n* **Websites change often** causing scripts to break. We needed a way to quickly diagnose and iterate on our scripts.\n* **Setting up browser and filesystem infrastructure** is not easy but very necessary in the web automation world.\n* **It’s just annoying to write scripts** - if you’ve ever had to dig around for selectors, you know: it’s tedious and time consuming.\n\nSo we built BrowserBook to solve those issues.\n\n# **How does it work?**\n\n1. **Run code piecemeal** - if you’re fixing a breakage 2/3rds of the way through your script, you shouldn’t have to run the whole thing every time you test it.  We took inspiration from Jupyter notebooks and allow you to run code cells independently, while maintaining context and state:\n\n   ![uploaded image](/media/?type=post&id=96111&key=user_uploads/739375/f2203cd4-1533-402c-8b17-3147d3d21783)\n\n2. **No more digging for selectors** - tell the coding assistant what to do and it’ll implement the automation logic in Playwright:\n\n   ![uploaded image](/media/?type=post&id=96111&key=user_uploads/739375/418daacd-b744-4359-84d3-23891d386676)\n\n3. **Built-ins for the hard stuff** - want to take a screenshot?  Log in to a website with 2FA?  Extract data?  We’ve got built-ins for those, ready to go out-of-the-box.\n\n   ![uploaded image](/media/?type=post&id=96111&key=user_uploads/739375/2acfea26-9c65-4ba4-8983-8e351e75222a)\n\n4. **Accessible via API** - if you need to execute your automation via an agent you’re building, scheduled via a cron job, or as a part of your application, you can trigger automations remotely and watch the playback in-app or via our artifacts API endpoint.\n\n   ![uploaded image](/media/?type=post&id=96111&key=user_uploads/739375/957ce254-3702-407f-890d-ed8c184824e7)\n\n\n# **Our ask**\n\nTry it out!  If you:\n\n* Run browser automations\n* Are building agents that need to interact with the web\n* Need to write a one-off automation that will make your life easier\n\nBrowserBook is available for download for Mac users [on our website](https://browserbook.com/), and if you’d like you can [book a demo here](https://browserbook.com/demo).\n\nAdditionally, if you know individuals, startups, or teams at larger companies working on browser automations, we’d love to meet them!",
        "url": "https://www.ycombinator.com/launches/P0B-browserbook-the-browser-automation-ide",
        "votes": 74,
        "created_at": "2025-12-10T15:55:19.861Z"
      },
      {
        "id": 85580,
        "title": "Chorrie: turn your SMEs into SWEs",
        "tagline": "Catch errors in your manual processes before they cost you big",
        "body": "# **TL;DR**\n\nWe supercharge your subject matter experts by giving them the tools they need to eliminate errors in heavily manual processes.\n\n**Our current mission:** empower healthcare practices to stop denials and under-billing on their claims before they happen.\n\n# **The Problem**\n\nHealthcare claims processing is an overly-complex, adversarial space. Insurance payers are constantly changing their policies, forcing billing teams to rely on:\n\n* frequent and extensive retraining\n* coding rules worksheets with hundreds of tabs\n* esoteric tribal knowledge\n\nWith so much room for human error, it’s no wonder 73% of healthcare staff surveyed reported that they’re facing increasing denials on outgoing claims.\n\n# **A turnkey solution for medical claims checks**\n\n[Here’s where Chorrie comes in.](https://youtu.be/orI95bsgaio)\n\nChorrie uses AI to empower medical practices to turn their esoteric knowledge into automated checks, saving time, money, and mental effort. We take simple, deterministic instructions, and translate them into a code-based decision tree, which can be continuously run to automate correctness checks for complex rules systems.\n\nTake the example in our video: we get a glimpse at how extensive these rules worksheets can become today, and see how quick & easy it is to automate a rule for claims from a particular location, containing a particular code, billed to a particular insurance payer with Chorrie.\n\n# **Backstops-as-a-service**\n\nOur approach of plaintext ➡️ decision tree ➡️ code generation is a scalable technique that can be used to provide backstop checks (and ultimately automate) high-leverage, deterministic manual processes that are prone to human error (think contract review for legal documents, trade confirmations, etc.).\n\nTo automate checks for these today, you’d need a team of engineers to write the logic into code, and keep them on staff to ensure that code can be updated when the rules change. **With Chorrie, you get:**\n\n* A no-code solution: turn your SMEs into SWEs\n* No hallucinations in your automated workflows\n* Intrinsically deterministic & fully explainable conclusions\n\nWhile the focus today is on reducing claims denials to 0% for our healthcare clients, we plan to explore use cases in other fields in the future.\n\n# **About us**\n\nWe are Chris (the **Ch**) and Jorrie (the **orrie**), old friends who met in undergrad at MIT. We met back up years later at Google, where we worked on applied AI for content moderation before we decided it was time to move onto something new.\n\n![uploaded image](/media/?type=post&id=85580&key=user_uploads/739375/ce57cfdc-3b8c-41dc-a8bb-d4bccc866ab0)\n\nAfter brainstorming on a number of projects, Jorrie’s wife, an ophthalmologist, gave us the idea of applying AI to the medical coding world and the rest is history!\n\n# **Our ask**\n\nDo you have any tedious or high-leverage manual processes where errors can cost your business money (Think heavy manual review processes, major transactions that need to be verified, etc.)? Or any contacts in the medical billing world? We’d love to chat.\n\n📧 [**founders@chorrie.com**](https://mailto:founders@chorrie.com)",
        "url": "https://www.ycombinator.com/launches/MGK-chorrie-turn-your-smes-into-swes",
        "votes": 80,
        "created_at": "2024-11-14T22:58:45.072Z"
      }
    ]
  },
  {
    "id": 30107,
    "name": "Surge",
    "slug": "surge",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/1f4a489f75647f08676e6de181d0f4d27016b18f.png",
    "website": "https://surge.app",
    "all_locations": "Lehi, UT, USA",
    "long_description": "Surge is Stripe for telephony. Our team has experience building telephony software at billion dollar scale. Because of increased regulation, Twilio and other SMS APIs take weeks to onboard new customers, but we can get startups onboarded same day. Surge wins by enabling easy carrier registration, better support, and higher level APIs and no code UI components to make implementation easier for startups and developers.",
    "one_liner": "Stripe for telephony",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1731622401,
    "tags": [
      "Developer Tools",
      "SaaS",
      "API",
      "Telecommunications",
      "Infrastructure"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Fall 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/surge",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/surge.json",
    "year_founded": 2024,
    "city": "Lehi",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/surgeapi",
    "x_url": "https://x.com/surgeapi",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/surgeapi",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/1f4a489f75647f08676e6de181d0f4d27016b18f.png",
    "app_video_url": null,
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    "primary_partner": null,
    "founders": [
      {
        "user_id": 97400,
        "full_name": "Dennis Beatty",
        "title": "Founder/CEO",
        "founder_bio": "Founder/CEO at Surge (F24), the easiest way for developers to send text messages. Formerly principal engineer over payments at Entrata and early engineer at Podium (W16) where I was a tech lead and senior engineer over the messaging platform and led engineering for the SMS payments product that reached a $2B run rate in year 2.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/dnsbty",
        "x_url": "https://x.com/dnsbty",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/79d9d9b29325e34b22eeab9a512d25f0be13b325.jpg"
      },
      {
        "user_id": 2247072,
        "full_name": "Brett Beatty",
        "title": "Founder",
        "founder_bio": "Co-Founder/CTO at Surge (F24), the easiest way to add text messaging to software. Prior to Surge, I spent six years at Podium (W16) where I was a senior engineer on the Phones team and the account structure team, building the APIs upon which the rest of Podium's products were built. I was very focused on providing five nines of uptime and sub-millisecond response times.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/brett-t-beatty",
        "x_url": "https://twitter.com/brett_beatty",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1b00399d92ce6592796cbb14df7658c9dbe4b954.jpg"
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    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 85595,
        "title": "Surge ⚡ The easiest SMS API for developers",
        "tagline": "Get registered and sending text messages faster than ever before.",
        "body": "[Surge is the easiest way for developers to send and receive text messages.](https://youtu.be/3cTyfiw5jtE)\n\n# **The Problem**\n\nIt used to be easy to start texting with Twilio and other APIs, but after recent carrier compliance changes, you have to jump through hoops and piece together fragmented documentation to get registered. Then you still have to wait 2-3 weeks for approval before you can actually send messages.\n\n![uploaded image](/media/?type=post&id=85595&key=user_uploads/97400/2bd7755f-cbb7-4d0d-ad1f-bfd7f8804db9)\n\nThe big SMS APIs are all now focused on big companies paying them millions of dollars per year. Startups are left with a terrible user experience, unresponsive email support, and a feeling of helplessness when trying to add SMS functionality to our applications.\n\n# **Our Solution**\n\n![uploaded image](/media/?type=post&id=85595&key=user_uploads/97400/17af9950-2bdc-46d5-b7ae-83f4194fbd42)\n\nBy incorporating the new compliance standards into our product from the beginning, Surge lets developers send texts without having to become experts on the registration process first. We provide white glove onboarding to get you through carrier registration or toll-free verification, and we can do it in 1-2 business days (sometimes even same day) instead of the typical 2-3 weeks. And we can get you up and running with a trial in minutes.\n\nOur intuitive REST API and webhooks are designed at a higher level of abstraction than other providers, which helps you simplify your application logic. And if you’d rather write as little code as possible, we even have embeddable low-code UI components that make two-way texting a breeze to set up. On top of that, we offer responsive support to help you figure out any issues you have, no matter your size.\n\n# **Our Team**\n\n[Dennis](https://linkedin.com/in/dnsbty) and [Brett](https://www.linkedin.com/in/brett-t-beatty) are brothers who spent a combined 11 years at Podium (W16) where they worked on communications infrastructure for small businesses. Brett was a senior engineer on the Phones product, and Dennis was a tech lead and senior engineer on the Messenger platform. We’re excited to be building together, and to be taking on a problem that has caused so much frustration for developers like us.\n\n![uploaded image](/media/?type=post&id=85595&key=user_uploads/97400/b94153ab-d83e-404b-a1d8-be5068d37906)\n\nIf you’re currently using Twilio or another SMS API, please reach out! Even if you have no interest in switching providers, we would love to hear about your experience. [Book time on my calendar](https://cal.com/team/surge/sms-chat-from-yc-launch), or reach out to [ycdirectory@surgemsg.com.](mailto:ycdirectory@surgemsg.com)",
        "url": "https://www.ycombinator.com/launches/MGZ-surge-the-easiest-sms-api-for-developers",
        "votes": 42,
        "created_at": "2024-11-15T18:20:36.034Z"
      }
    ]
  },
  {
    "id": 30108,
    "name": "Struct",
    "slug": "struct-ai",
    "former_names": [
      "Bramble",
      "Edgedive"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f292fd64c9e2943d040e390cd2700e19b243bb8c.png",
    "website": "https://struct.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Struct automatically sets up, manages, and triages alerts based on how your app is supposed to work in prod. Connect your coding agent to it to enable your software factory to fix prod on its own.\r\n\r\nOnboarding takes 5 minutes.\r\n",
    "one_liner": "Struct keeps prod running",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1727386579,
    "tags": [
      "Developer Tools",
      "B2B",
      "DevOps",
      "Enterprise Software",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Fall 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/struct-ai",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/struct-ai.json",
    "year_founded": 2025,
    "city": "San Francisco",
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        "full_name": "Nimesh Chakravarthi",
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        "full_name": "Deepan Mehta",
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        "title": "AI agent platforms look to find their stride in 2025",
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        "date": "Jan 23, 2025"
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        "id": 98615,
        "title": "Struct: Automate your on-call runbook",
        "tagline": "Auto root-cause eng alerts by cross-referencing logs, metrics, and your code.",
        "body": "Hi - we’re Deepan and Nimesh, and we’re launching the on-call agent every team deserves. For free.\n\n**tl;dr:** Struct auto-generates impact summaries, root causes, and pattern analyses for every eng alert by cross-referencing your logs, metrics, traces, and code. Free to use, set up in 5 minutes, fully customizable.\n\nVideo: <https://www.youtube.com/watch?v=fjXxFzjmhv4>\n\n⚠️ **The Pain:**\n\nIf you’ve been on-call, you know the drill.\n\n* Alert fires\n* Open Datadog (or Grafana, or whatever)\n* Find spikes, note timestamp\n* Hunt for relevant logs\n* Grep through code to root cause\n* Rinse & repeat\n\nMeanwhile, your most senior engineers keep getting looped into every incident, noisy alerts never get tuned, context lives across multiple tools, and customer issues keep slipping through.\n\n❇️ **The Fix:**\n\nStruct is the fastest way to go from alert → root cause. It plugs into your existing stack and automates the investigation workflow your team already runs manually.\n\nWithin minutes of an alert firing, Struct:\n\n* Pulls relevant metrics, logs, traces, monitors, and code\n* Does a regression analysis and correlates anomalies and spikes\n* Replies with with a root cause, impact summary, and pattern analysis\n* Drafts a full incident report with dynamically generated charts, timelines, and commit histories\n\nDive deeper in Slack or our app. Or, handoff the full context to your favorite coding agent to ship a fix.\n\nTeams already use Struct to:\n\n* Ensure their on-call runbook is consistently run on every alert and issue\n* Query across all logs, metrics, traces, and incidents in one place\n* Give every engineer the context to handle on-call without looping in seniors\n* Delay heavy investments in centralized observability\n* Supercharge their fave coding agents with one-click context handoffs\n\n👨🏽‍💼 **Who It’s For:**\n\n* Founding engineers scaling from 1 → 10 → 50\n* Lean teams running serious infra without an SRE\n* Orgs investing heavily into AI dev workflows\n\n🙏🏽 **Our Ask: Try It Free**\n\n**Get started in 5 minutes at [struct.ai](http://struct.ai)** — start for free, no credit card required. See ROI before you commit\n\nOr:\n\n* Book a quick demo: [here](https://cal.com/deepanm/struct-demo)\n* Email us: [**founders@struct.ai**](mailto:founders@struct.ai)",
        "url": "https://www.ycombinator.com/launches/PeZ-struct-automate-your-on-call-runbook",
        "votes": 33,
        "created_at": "2026-03-09T16:09:43.354Z"
      },
      {
        "id": 92145,
        "title": "Edgedive - understand what your customers are actually saying",
        "tagline": "Edgedive unifies scattered customer feedback and makes it actionable at scale",
        "body": "**tl;dr: Edgedive unifies scattered customer calls, messages, tickets, and CRM data, enabling deep insights, custom reports, and on-demand research**\n\n![uploaded image](/media/?type=post&id=92145&key=user_uploads/950535/39577381-65fc-4927-b42a-6057c595fd9b)\n\n**👀 [Book a 15 min demo call](https://cal.com/deepanm/edgedive-demo) to see it in action!**\n\n⚠️ **The Problem:**\n\nListening to your customers **is really hard at scale**.\n\n* Customer interactions (call transcripts, support tickets, messages, emails, etc.) are still siloed in separate tools and rarely linked to CRM data or eng tickets\n* PMs and others have to manually search through scattered data for relevant snippets, but they miss a lot\n* Answering a question like “which $10k+ ARR customers asked about MCP in the past quarter” is difficult and time-consuming\n* Monitoring real-time, qualitative reactions to a launch is challenging\n\n❇️ **The Solution:**\n\nEdgedive makes it incredibly simple to collect, tag, and synthesize **all incoming feedback from every channel** (linked to your CRM) so you can focus on building something people want.\n\n_After white-glove onboarding, our customers are using Edgedive to:_\n\n🔎 Answer **any** question about **anything** customers are saying\n\n![uploaded image](/media/?type=post&id=92145&key=user_uploads/950535/03c089aa-7043-42c9-84ce-a57b32d41abd)\n\n🎫 Tag tickets & quantify revenue impact - automatically\n\n![uploaded image](/media/?type=post&id=92145&key=user_uploads/950535/9232202c-e8c5-4d0f-9bd6-67c7cefd89d5)\n\n🗣️ Schedule custom voice of customer reports\n\n![uploaded image](/media/?type=post&id=92145&key=user_uploads/950535/d787a9b2-92eb-43f7-9314-34efcc5be748)\n\n💸 Identify gaps leading to churn or closed-lost deals\n\n🧪 Get a shortlist of good beta testers for features\n\n🤩 Monitor customer reactions to launches, live\n\n_…all in seconds, not days (or weeks)._\n\n👨🏽‍💼 **Our customers are:**\n\n* Customer-obsessed **Founders** or **Product, CS, & Ops leaders**\n* Teams trying to scale PM, CS, or Ops without scaling headcount\n* Organizations trying to launch or automate Voice of Customer programs\n\n🙏🏽 **Our Asks:**\n\n* **Book a [15 min call](https://cal.com/deepanm/edgedive-demo) or email us at [founders@edgedive.com](mailto:founders@edgedive.com)** if you fit any of the above profiles (or just want to see it in action)\n* **Know anyone that might be a good fit? [Intro us!](mailto:founders@edgedive.com)** First 5 intros receive their choice of (5) Taco Bell Crunchwrap Supremes 🌮 or (5) caffeinated beverages ☕ Act fast!\n* **Follow us or give a shoutout on [LinkedIn](https://www.linkedin.com/company/use-edgedive) or [X](https://x.com/edgedive/) to support!**\n\n🚀 **The Team:**\n\nDeepan (fmr Sr. PM, Georgia Tech) and Nimesh (fmr. Sr. EM, Berkeley) worked together for 4+ years at LinkedIn - some of our launches include the AI Focused Inbox, video posting, and stories, along with growth launches that drove $XXM in annual revenue. We’re building the solution we wish we had when we were trying to plan, build, and launch impactful products.\n\n![uploaded image](/media/?type=post&id=92145&key=user_uploads/950535/3e31334c-2af8-4696-939e-fee8a252c848)\n\n",
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        "votes": 61,
        "created_at": "2025-07-14T22:31:50.649Z"
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      {
        "id": 84508,
        "title": "Bramble: Buy any home, get $20k back!",
        "tagline": "Bramble is an AI-backed real estate brokerage that helps you buy a home end-to-end for a simple flat fee",
        "body": "**TL;DR:** Bramble is an AI-backed real estate brokerage that provides end-to-end homebuying services for one simple flat fee. Get instant help to set up tours, research homes, submit offers, and close confidently - with responsive support from an experienced agent whenever you need it.\n\nHey there! We’re [Nimesh](https://linkedin.com/in/nimesh-chakravarthi-68238749), [Deepan](https://linkedin.com/in/deepanmehta), and [Danny](https://www.linkedin.com/in/dannyighsu), co-founders of [Bramble](https://usebramble.com?utm_source=yc&utm_medium=post&utm_campaign=yc_launch).\n\n![uploaded image](/media/?type=post&id=84508&key=user_uploads/950535/673184b4-b4b3-4a72-bc11-fb7e3be1aa00)\n\n**The Problem: buying a home with an agent is often frustrating and expensive**\n\nToday, buyers already do a lot of work themselves to find and visit houses, but buyer agents continue to charge a very high fee (2-3% of a home’s price) for what’s often a frustrating and unresponsive experience. On top of that, the [2024 NAR settlement](https://blog.usebramble.com/post/how-nar-settlement-affects-home-buyers?utm_source=yc&utm_medium=post&utm_campaign=yc_launch) means that buyers are now fully exposed to that fee. As they look for cheaper alternatives, buyers are finding this means compromising on service or quality.\n\n![uploaded image](/media/?type=post&id=84508&key=user_uploads/950535/fd500ac9-92b1-4e2a-adbc-97087bfce021)\n\n**The Solution: buy any home with our AI-backed full-service broker for one flat fee**\n\nSchedule tours, analyze properties, draft offers, and close right on platform, with responsive, on-demand agent support whenever you need it — all for a simple flat fee. (The rest of the commission is rebated back to you.)\n\n[See how it works!](https://youtu.be/zFCG09fxJ_E)\n\nAI tools like instant disclosure analysis, comp reports, market analysis, and more, plus expert support from dedicated agents, mean Bramble buyers get the experience of a top-tier real estate agent without sky-high commissions. In California, the average homebuyer gets over $20k rebated at close! \n\n![uploaded image](/media/?type=post&id=84508&key=user_uploads/950535/6a601435-32ef-4366-a683-fa7a3b0e885c)\n\n**Asks:**\n\nWe’d love to talk to:\n\n* **Anyone looking to buy a home in CA in the next 6 months** - whether that’s you or anyone you know, we want to learn more.\n* Anyone who’s bought a home in the last year - we’d love to hear about your experience. We’ll even throw in a gift card of your choice!\n* Other founders/builders in the real estate tech space - let’s exchange notes.\n\nEmail us at [team@usebramble.com](mailto:team@usebramble.com) or grab time directly [here](https://calendar.app.google/ppD4aJz2hV2Mwv6T8)!",
        "url": "https://www.ycombinator.com/launches/Lz2-bramble-buy-any-home-get-20k-back",
        "votes": 62,
        "created_at": "2024-10-03T20:04:32.029Z"
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        "full_name": "Bharath Bhat",
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        "full_name": "Simranjit Singh",
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        "tagline": "Relvy looks at application logs and metrics to detect and debug issues, so engineers don’t have to.",
        "body": "Hi, we are Bharath Bhat and Simranjit Singh. We are building Relvy AI.\n\n### ❗ The problem\n\n* Companies spend $35B annually paying engineers to be on-call, and yet continue to suffer from $$$$ outages.\n* Monitoring production software is hard.\n* Engineering teams are always playing catch up - either flying blind with no alerts, or drowning in alert noise.\n\n \n\n### ⭐ Introducing Relvy\n\nWith Relvy, you can just say “**Hey Relvy, monitor my logs for me**”. Relvy connects to your observability stack to detect and debug any issues that show up. It takes less than 5 minutes to set up Relvy to monitor your logs and get actionable alerts WITH a root cause analysis.\n\n[Demo Video](https://www.youtube.com/watch?v=j_8wLDFMGNM)\n\n### ⚙️ How it works\n\n* You connect Relvy to your observability tools and provide a set of log queries that you’d want to monitor\n* Relvy queries and process logs 24x7 to detect issues. No need to define log based metrics and create alerts manually.\n* Relvy then debugs these issues to provide an actionable root cause analysis. This includes querying and analyzing other metrics to provide context, and finding responsible code changes from your recent commits.\n* Already have alerts on your on-call slack channel? Relvy can debug these as well, and respond to follow-up queries.\n\n### 🚀 Our tech\n\n* We ship with a small language model that’s optimized for debugging. It is as good as gpt-4o on our eval benchmarks while being 1/100th the cost. The core unlock that enables us to offer continuous monitoring.\n* We lean on your previous incident response history to help optimize our agent. Helps us denoise alerts, figure out useful queries to run while debugging, and pattern match logs faster.\n\n### 📝 Our story\n\nSimranjit and I are both ML engineers. We met a few years ago when we were building computer vision models for satellite imagery at a startup called Orbital Insight. Together, we have built and supported ML products at Google, Uber, Microsoft and Amazon. \n\nRelvy came out of our efforts to automate the not-so-fun parts of our jobs as software engineers. Believe it or not, our first product was something that recorded your screen as you were coding, and tried to come up with bug fix suggestions for any error messages that popped up on screen. Thankfully, Relvy is less intrusive, more accurate, and fits into your existing on-call workflows.\n\n### ➡️ Ask\n\nI bet you’d like AI to take monitoring off your plate. Try us out at <https://www.relvy.ai> or book time with us at <https://calendly.com/bbhat-relvy/15min>\n\n![uploaded image](/media/?type=post&id=85574&key=user_uploads/1381863/8a25e559-845a-4b23-90dd-6fadde0fbdb8)\n\n",
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        "votes": 80,
        "created_at": "2024-11-15T04:27:49.553Z"
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        "answer": "HumanLayer will be the single place where software construction and collaboration happens. Every engineer will ship faster not by replacing humans with AI, but by giving humans the most effective leverage points. Check out <https://hlyr.dev/ace-fca> for more details."
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    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/humanlayer.json",
    "year_founded": 2023,
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      "name": "Nicolas Dessaigne",
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        "full_name": "Dexter Horthy",
        "title": "Founder/CEO",
        "founder_bio": "Coined the term Context Engineering in April 2025, ranting about coding agents ever since. Started coding in high school at NASA JPL. Spent 7 years as Engineer, SE, PM, Exec at Replicated, a series C dev tools startup. I worked on container orchestrators, helped teams like Hashicorp, DataStax, and H2O.ai deliver and ship their on-prem k8s products.\n\n",
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        "title": "Founding Product Engineer",
        "url": "https://www.ycombinator.com/companies/humanlayer/jobs/oBCZzc7-founding-product-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$180K - $250K",
        "equity_range": "1.00% - 3.00%",
        "experience": "6+ years",
        "visa": "US citizen/visa only",
        "skills": [
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        "title": "It’s Time To Put Humans Back In The Software - DEV Community",
        "url": "https://dev.to/dailycontext/its-time-to-put-humans-back-in-the-software-factories-3cjh",
        "date": "Jul 01, 2026"
      },
      {
        "title": "The four startups from YC's Fall batch that enterprises should pay attention to | TechCrunch",
        "url": "https://techcrunch.com/2024/12/07/the-four-startups-from-ycs-fall-batch-that-enterprises-should-pay-attention-to/",
        "date": "Dec 07, 2024"
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        "id": 85104,
        "title": "HumanLayer - Human-in-the-loop for AI Agents and beyond",
        "tagline": "Approval queues, escalations, and human oversight for every automated process.",
        "body": "Hi 👋 I’m Dex, and I’m building HumanLayer.\n\nHumanLayer lets your software contact humans for feedback, input, and approvals. It’s perfect for\n\n1. Implementing manual approval steps for software- and human-driven workflows\n2. Oversight of autonomous AI agents\n3. Managing the transition between the two\n\nHumanLayer has clients for Python and Typescript and lets you manage approvals across Slack, SMS, email, and other channels. For AI agents, HumanLayer is designed to work with any framework + LLM.\n\nYou can try it today at [humanlayer.dev](https://humanlayer.dev).\n\n<https://www.youtube.com/watch?v=5sbN8rh_S5Q>\n\n> _Ever since I got hands-on with HumanLayer, I’m asking my whole team to think more about Agentic AI workflows - I used to think agents were not worth the effort to get them to production-grade reliability, but now I'm stoked on what is possible when you bring humans into the loop_\n>\n> _–_ Vaibhav Gupta _, Founder_ @ [Boundary](https://www.ycombinator.com/companies/boundary) _(YC W23)_\n\n### Why HumanLayer\n\nBefore HumanLayer, I was building autonomous AI agents. Our idea for an MVP was an agent that would coordinate with humans in Slack and could do basic cleanup, like dropping any Snowflake/SQL table that hadn’t been queried in 90+ days. We had already built a platform to generate recommendations, but we wanted to push the limits of agent frameworks, **we wanted the agent to be able to actually do the work, not just generate the recommendations**.\n\nOf course, we weren’t comfortable with an AI application running raw SQL unsupervised, especially if it had access to drop tables, so we wired in some basic human approval steps.\n\nFrom there, I realized that **the most useful functions we can give to any software are also the most risky**. This is especially true for non-deterministic systems driven by LLMs. I realized that anyone who wants to build agents that do meaningful things will need tools for approval and oversight. So, I started hacking on HumanLayer to enable teams to safely build high-impact agents and put them to work [ambiently and autonomously](https://theouterloop.substack.com/p/openais-realtime-api-is-a-step-towards) in the background.\n\n### Use Cases\n\nWhether you’re hard-leaning into AI or not, HumanLayer helps you build impactful automation that you can ship with confidence because you have humans in the loop for the critical operations. Forget months of tuning or broken use cases on every iteration; **build confidence incrementally** as you observe and test your apps in production (safely!).\n\n* **Internal Automations** - review/approve outbound emails or automated infrastructure changes\n* **Dynamic Data Labeling** - think [RLHF](https://en.wikipedia.org/wiki/Reinforcement_learning_from_human_feedback) driven by the experts in your company - Use collected human feedback for **benchmarking** human vs. AI performance and for **fine-tuning** AI agents\n* **Ship fast and iterate** - Roll out advanced AI features to customers without needing to get to “perfect.” Human review guarantees nothing bad can happen without needing to spend months on evals, tuning, and prompt engineering. Then, iterate based on how your agents behave in production.\n* **Customer-facing** **control and visibility** - help your customers build trust in automations by giving them hooks to approve/review your app’s actions\n\n> _Really enjoying playing with @humanlayer_dev - instead of the manual outreach grind, I just hang out in slack and give my agent feedback as it finds new leads_\n>\n> – Tom Granot, founder, <https://syntaxcinema.dev>\n\n### \n\n### Quick Example\n\nIntegrate HumanLayer into your **python** or **typescript** app using a decorator or webhooks.\n\n![uploaded image](/media/?type=post&id=85104&key=user_uploads/1459029/2ea2f1d9-c06d-4e03-a64e-62c650e1743c)\n\nTo let AI apps contact a human for natural language feedback/input, just pass the `human_as_tool()` function into an AI agent’s tool set.\n\n![uploaded image](/media/?type=post&id=85104&key=user_uploads/1459029/4035e3d6-b850-4e14-b1b1-a64193cb5d75)\n\n### Team\n\n![uploaded image](/media/?type=post&id=85104&key=user_uploads/1459029/f649e7e6-c37d-48d4-88ee-4d265c4983d4)\n\nI’m [Dex](https://linkedin.com/in/dexterihorthy). I am obsessed with helping devs everywhere deliver safe + impactful AI agents.\n\nI spent the last 7 years at <https://replicated.com> where I helped great developer teams like DataStax and H2O.ai build and launch the kubernetes-native versions of their self-hosted products. I worked on container orchestrators, led product teams, and founded the GTM org.\n\nI can’t wait to build the future of AI Agents with y’all.",
        "url": "https://www.ycombinator.com/launches/M8e-humanlayer-human-in-the-loop-for-ai-agents-and-beyond",
        "votes": 48,
        "created_at": "2024-10-29T14:15:47.455Z"
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    "name": "Partcl",
    "slug": "partcl",
    "former_names": [
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3854a114899cbd01548be14b47a9169f22c776a0.png",
    "website": "https://partcl.com/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Partcl modernizes chip design automation with physics-informed models powered by GPU acceleration. \r\nOur tools run up to 700× faster than legacy solutions, cutting weeks off development and unlocking AI-driven optimization.",
    "one_liner": "Design a chip in minutes",
    "team_size": null,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1743057715,
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    "batch": "Spring 2025",
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    "regions": [
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        "full_name": "William Salcedo",
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        "full_name": "Vamshi Balanaga",
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        "founder_bio": "CTO at Partcl. Previously built embedded ML models at Apple, laser weeding robots at Carbon Robotics, and warehouse automation robots at Fulfil Solutions. Built and launched multiple rockets while running the avionics team at Space Enterprise at Berkeley, \nStanford EECS PhD (dropout), UC Berkeley Physics.",
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        "id": 78506,
        "title": "Founding Engineer (Systems + ML)",
        "url": "https://www.ycombinator.com/companies/partcl/jobs/QYIRyyx-founding-engineer-systems-ml",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Machine learning",
        "salary_range": "$130K - $300K",
        "equity_range": "0.50% - 2.00%",
        "experience": "Any (new grads ok)",
        "visa": "Will sponsor",
        "skills": [
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      {
        "id": 90311,
        "title": "Partcl: Design Chips in minutes",
        "tagline": "Accelerate time to market for a new chip with Partcl.",
        "body": "Imagine hitting _compile_ and waiting **3 weeks** to learn you missed a semicolon... or **5 weeks** to catch a runtime error.\n\nWelcome to ASIC life.\n\nWe're slashing those weeks down to **minutes** — so you can build better chips, _faster_.\n\n**🤔 Why did we build this?**\n\nDuring our time at Nvidia and other startups, we found that engineers spend large amounts of the 24 month chip design cycle idle, waiting for runs to finish. \n\nPartcl speeds up Physical Design tools by rearchitecting algorithms for GPUs.\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXe5Tz9ckaEsmiCOCBRiSkIWoRjsjmlYImpGMRiNjD3CZFjP3cdqz1ak4HZDK-AiUi5j0FQdKDxZg1KI2rG5AafmrCYY-uOiPqU9KHemQSfnwG697XkK2sa2cIsYkjMnY3JCbyG-Lw?key=FiBPpN_VIY8oopQ1FfRq6HI4)\n\n**🧑‍💻What it means for designers:**\n\n* Quick power, performance, and area estimates\n* Fix timing/power bugs in RTL w/out handoff to the PD team\n* Build better chips, faster\n\n**✅What we have right now:**\n\n* 700X faster Static Timing Analysis - enabling super quick performance simulations\n* 100X faster Gate Resizing\n* 100X faster global and detailed placement\n\n**🔜What’s in the pipeline:**\n\n* LSP integration for Incremental synthesis - Synthesis as fast as you can type\n* Natural Language interface to any intermediate database - Directly query the state of your database with text instead of asking a junior engineer to build you a dashboard\n\n**Our Ask**\n\nEmail us at {vamshi, will}@partcl.com to try Partcl and let us know what you think.\n\nAre you building\n\n* **AI Accelerators**? Partcl brings in tapeout deadlines with faster tools, bringing your chip to market faster!\n* **Embedded/ IoT devices**? Partcl decreases NRE by shrinking design cycles. Decreased NRE directly translates to higher margins.\n* **Mobile SoCs**? Partcl’s physics informed models let you optimize the power-performance tradeoff for your use case.",
        "url": "https://www.ycombinator.com/launches/NUd-partcl-design-chips-in-minutes",
        "votes": 33,
        "created_at": "2025-05-12T20:45:49.479Z"
      }
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    "id": 30198,
    "name": ".Wave",
    "slug": "dotwave",
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e16adbb8c4442e6124b56566c82ed680beaba21a.png",
    "website": "https://dotwave.ai/",
    "all_locations": "Paris, Île-de-France, France",
    "long_description": ".Wave builds a continuous inference engine for streaming AI models, including full-duplex voice and streaming speech recognition.   \r\n\r\nCustomers bring their models; we integrate and run them, managing execution, session state, and scheduling to reduce end-to-end latency and serving cost per live session.  \r\n\r\nWe use cadenced inference to support more concurrent sessions per GPU while keeping latency low and consistent.",
    "one_liner": "Continuous inference for streaming AI models",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1741300119,
    "tags": [
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      "B2B",
      "Infrastructure"
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    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2025",
    "status": "Active",
    "industries": [
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    "regions": [
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      "Europe"
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    "stage": "Early",
    "app_video_public": false,
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/dotwave",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/dotwave.json",
    "year_founded": 2024,
    "city": "Paris",
    "country": "FR",
    "linkedin_url": "https://www.linkedin.com/company/dotwaveai/about/?viewAsMember=true",
    "x_url": "https://x.com/dotwaveai",
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    "primary_partner": {
      "name": "Tom Blomfield",
      "url": "https://www.ycombinator.com/people/tom-blomfield"
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    "founders": [
      {
        "user_id": 1458005,
        "full_name": "Thomas Minassian",
        "title": "Founder/CEO",
        "founder_bio": "CEO .Wave. Our team built Parler-TTS Mini Multilingual, the world’s first fully multilingual open-source text-to-speech model, with 300,000 monthly downloads, and Dollyglot, the first model to turn a photo into a real-time video avatar.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/thomas-minassian-b25626102",
        "x_url": "https://x.com/thminassian",
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      {
        "user_id": 1646678,
        "full_name": "Paul-Henri Biojout",
        "title": "Founder/CTO",
        "founder_bio": "CTO .Wave. Our team built Parler-TTS Mini Multilingual, the world’s first fully multilingual open-source text-to-speech model, with 300,000 monthly downloads, and Dollyglot, the first model to turn a photo into a real-time video avatar.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/phbiojout",
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      {
        "id": 88334,
        "title": "Dollyglot: Befriend Anybody",
        "tagline": "Dollyglot is like Character.ai but with real-time video avatars.",
        "body": "[Dollyglot](https://www.dollyglot.com/) is like Character.ai but with real-time video avatars.\n\nTurn a photo and a voice into a real friend. Speak with Harry Potter about Hogwarts, or brainstorm ideas with The Rock!\n\n[**Our Product Video**](https://youtu.be/GhuqAMSq6HY)\n\n**Our Team:** **We’ve lived and worked together for two years**\n\n**Thomas**: Ex-quant at Société Générale. Master’s in Applied Mathematics and Business (HEC Paris, University of Paris 7).\n\n**Paul-Henri**: Built the Yumi Dialogue Engine, an AI for creator “clones” that scaled to 1 000 paying users. Dropped out of CentraleSupélec (Computer Science) to launch Dollyglot.\n\n**Together, we built Parler-TTS Mini Multilingual**, the world’s first and only fully open-source multilingual text-to-speech model. In the last month alone, it has garnered over 5,000 downloads and inspired many fine-tuning projects.\n\n![uploaded image](/media/?type=post&id=88334&key=user_uploads/89898/49894db9-ac0d-45da-bb91-4944831f8a38)\n\n**Our Vision**\\\nWithin five years, every Gen Alpha will have an AI best friend. By nature, AI is empathetic and nonjudgmental, creating a safe space where everyone can truly be themselves.\n\n**What We’ve Built**\n\nDollyglot developed the world’s first and only photo-to-real-time video avatar model. Paired with reasoning models like DeepSeek R1 or Grok, we bring your AI friends to life and make 'non-lobotomized' characters.\n\n **What’s Next**\n\nJoin our waitlist to try Dollyglot in the coming weeks.\n\nQuestions? Contact Thomas (CEO) at [thomas.minassian@dollyglot.com](mailto:thomas.minassian@dollyglot.com) or Paul-Henri (CTO) at [paul-henri.biojout@dollyglot.com](mailto:paul-henri.biojout@dollyglot.com).",
        "url": "https://www.ycombinator.com/launches/Myk-dollyglot-befriend-anybody",
        "votes": 18,
        "created_at": "2025-03-07T01:37:29.930Z"
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    ]
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    "id": 30204,
    "name": "Subtrace",
    "slug": "subtrace",
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e806fda08a2985d5611237545c62cc046d58b489.png",
    "website": "https://subtrace.dev",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Subtrace is a zero-code network tracer. It's like having an inspect element button for your whole infra: when you start a process with Subtrace, you'll see every HTTP request coming in and going out in realtime. Under the hood, it uses BPF to make this possible without any root privileges or code changes. We have ~2.5k stars on Github.",
    "one_liner": "Zero code network tracer",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1733176117,
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    "batch": "Winter 2025",
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      "America / Canada"
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    "city": "San Francisco",
    "country": "US",
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    "primary_partner": {
      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
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    "founders": [
      {
        "user_id": 211631,
        "full_name": "Adhityaa Chandrasekar",
        "title": "Founder/CEO",
        "founder_bio": "Founder and CEO at Subtrace. Previously worked at Google as a software engineer on Kubernetes internals and GKE infra monitoring. University of Waterloo and IIT Madras alum.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/adtac",
        "x_url": "https://x.com/adtac_",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/46bc290a8ecafa80c5345cc2018a122e43105d46.jpg"
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      {
        "user_id": 1755130,
        "full_name": "Sachin Sridhar",
        "title": "Founder/CTO",
        "founder_bio": "Cofounder and CTO at Subtrace. Previously a software engineer at Microsoft, where I worked on Power BI/Microsoft Fabric. Studied computer science at IIT Madras.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/sachin-sridhar",
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      {
        "id": 87493,
        "title": "Subtrace: Resolve production issues in minutes, not months",
        "tagline": "Get full visibility into every backend request",
        "body": "Hey, this is Adhityaa and Sachin 👋\n\nWe built Subtrace to give backend teams full visibility into every request—payload, latency, status, headers, logs—all in one place. YC companies like Trieve (W24) are already using Subtrace in production to improve their incident resolution time from months to minutes ([read their case study](https://subtrace.dev/customers/trieve)).\n\n# **Problem**\n\nToday's backend monitoring tools like Sentry and OpenTelemetry leave out the most crucial details of each request, forcing backend developers to search through logs to root cause issues.\n\n# **Solution**\n\nSubtrace brings every backend request into one clear, Chrome DevTools-like interface so that you can resolve issues fast—often before your first coffee. Here's how it works:\n\n**🔍 Search & Filter**\n\n![uploaded image](/media/?type=post&id=87493&key=user_uploads/211631/0efb0809-659a-415b-bd9b-7bc7b36c5f89)\n\n_Quickly search for the requests that matter using simple filters_\n\n**🔦 Inspect & Analyze**\n\n![uploaded image](/media/?type=post&id=87493&key=user_uploads/211631/741d090f-6392-4c95-9a2e-594d48148e3d)\n\n_Click any request to view full details like payload, headers, latency_\n\n**🎥 Record & Replay**\n\n![uploaded image](/media/?type=post&id=87493&key=user_uploads/211631/d740c6c4-d4ad-4390-948d-ac780ee8dbc2)\n\n_Reproduce issues easily by replaying prod requests elsewhere_\n\n**💬 Share & Collaborate**\n\n![uploaded image](/media/?type=post&id=87493&key=user_uploads/211631/7698ee18-733b-4601-b7b7-5a4e9425148d)\n\n_Share detailed snippets with your team to solve issues together_\n\nYou can get Subtrace working with just a single command.\n\nTry for yourself: [**Docs →**](https://docs.subtrace.dev)\n\n# **Team**\n\nWe met 10+ years ago as undergrads and we've been great friends ever since. Adhityaa went to **IIT Madras**, the **University of Waterloo** and worked at **Google**. Sachin went to **IIT Madras** and worked at **Microsoft**.\n\n![uploaded image](/media/?type=post&id=87493&key=user_uploads/211631/d6577599-ad96-407e-9745-be38eacb5975)\n\n![uploaded image](/media/?type=post&id=87493&key=user_uploads/211631/c7ce8553-c0bb-4a26-9f3a-1625ad6a98f0)\n\n\n# **Ask**\n\nAre you a backend / full stack developer? Do you run an engineering team?\n\nYC companies are already using Subtrace today, we think you'll love it.\n\nEmail [founders@subtrace.dev](mailto:founders@subtrace.dev) (or [submit this form](https://form.typeform.com/to/JoVcpdrn)) and we'll show you a demo!",
        "url": "https://www.ycombinator.com/launches/MlB-subtrace-resolve-production-issues-in-minutes-not-months",
        "votes": 42,
        "created_at": "2025-02-07T07:42:14.178Z"
      }
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    "id": 30207,
    "name": "Promptless",
    "slug": "promptless",
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    "website": "https://promptless.ai/",
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        "full_name": "Prithvi Ramakrishnan",
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        "founder_bio": "Prithvi co-founded Promptless.\n\nBefore Promptless, he served as VP of Product & Engineering at Bond, a fintech infrastructure startup acquired by NYSE:FIS in 2023. There he saw firsthand the effort required to maintain hundreds of tutorials and guides and the outsized business impact of world-class documentation.\n\nPrithvi graduated from Stanford in 2015 (B.S. CS, AI track). He was also a 4-time International Mathematical Olympiad (IMO) participant, including as the youngest participant in 2008.",
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        "founder_bio": "Frances is building Promptless, helping companies keep customer-facing content up-to-date. Prior to Promptless, Frances led product, ML/AI engineering, and LLM ops on petabyte scale at Cloudflare, OneSignal, and Graft. Yale undergrad. Stanford PhD drop-out. Has published LLM research.\n",
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        "title": "Promptless: An AI teammate that automatically updates your customer-facing docs",
        "tagline": "Promptless proactively drafts updates to your docs while you ship software and support customers",
        "body": "Hello! We’re Frances and Prithvi, founders of Promptless. \n\n# tl;dr\n\nDocs are integral to a great customer experience, but managing them is a challenging, multi-team effort. The most successful companies recognize that fantastic docs drive adoption and bad ones cause customers to churn. Promptless is already used by fast-growing startups and Fortune 500 enterprises alike to automatically update docs based on feature releases, support tickets, internal Slack conversations, and more. [Get started today](http://gopromptless.ai)! \n\n<https://www.tella.tv/video/promptless-automatically-update-your-docs-690g>\n\n# The Promptless Approach\n\n**Promptless drafts updates proactively for easy review**\n\n* Our AI agents monitor your software changes for when a documentation update might be needed, and can be triggered from a Slack conversation in one click. No prompt engineering required—hence the name _“Promptless”_.\n\n**Promptless lives where you work and can be triggered anywhere**\n\n* Instead of forcing you into yet another platform, Promptless integrates into your Slack channels, Github repos, Notion databases, Jira/Linear issues, Zendesk/Intercom tickets, and CMS platform.\n\n**Promptless-written docs are designed to maximize value to your customers**\n\n* Promptless is designed to prioritize accuracy, simplicity, and discoverability—ensuring that your customers can be onboarded quickly and can self-support without reaching out to your team.\n\n **Promptless is built for all kinds of customer docs**\n\n* Whether your docs are product tutorials, help-center articles, or developer guides, Promptless can handle it, and infers the style and structure of your documentation by reading your entire docs site.\n\n![uploaded image](/media/?type=post&id=87446&key=user_uploads/729272/8196d287-25b1-4175-877b-92f03d41cf74)\n\n# How Customers Use Promptless Today\n\nPromptless is designed to be flexible—it can integrate with any docs platform, be triggered automatically from many workflows, and can pull in context from any internal knowledge source. Just a few examples: \n\n[Vellum](http://vellum.ai) (YC W23) has tons of Slack Connect channels with their key customers—they use Promptless to automatically trigger doc updates whenever their team answers a customer question that should be covered in their public guides. \n\n[Clay](https://clay.com/) (breakout prospecting super tool) has a product team that publishes biweekly changelogs and a content team that manages their guides—they use Promptless to automatically bridge that gap and draft new and updated guides whenever there’s a product update.\n\nA Fortune 500 company has full-time technical writers, but the context surrounding every change is spread across Linear, Confluence, and Slack–Promptless automatically assembles the relevant context and drafts doc updates for every PR, making every technical writer twice as productive. \n\n![uploaded image](/media/?type=post&id=87446&key=user_uploads/729272/0a2388b3-a021-423b-80ba-3dc4d94a23f5)\n\n# Our Team and Expertise\n\nFrances and Prithvi have both run teams where great docs were a critical part of the customer experience. At OneSignal (YC S11) where Frances was Head of Data Science, she saw that docs engagement within the first 24 hours was directly tied to the biggest predictors of customers' lifetime value. At Bond (acquired by NYSE:FIS) where Prithvi was VP of Product and Engineering, he saw the challenging, multi-team effort that it took to maintain great customer docs, and wrote many of the guides himself. \n\n# Try it out!\n\nIf your team wants to spend less time maintaining docs and more time building great product and serving customers, email us at [founders@gopromptless.ai](mailto:founders@gopromptless.ai) or book some time on our calendar [booking link.](http://cal.com/team/promptless/15m-discovery-call)\n\n![uploaded image](/media/?type=post&id=87446&key=user_uploads/729272/c0ad621e-2366-4b3a-9c6c-e460fd1634b1)\n\n",
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        "title": "superglue 🍯 - Open Source Data Translation",
        "tagline": "Get data from any system in exactly the format you need.",
        "body": "**Tl;dr** [superglue](https://superglue.cloud/) translates data from any system into exactly the format you need. It’s an open source proxy that automatically extracts, maps and transforms data so developers don’t have to write and maintain complex integration code. \n\n**Other tools say \"Use our API\". superglue says \"Use any API, in any way you want\".**\n\n[Find us on GitHub.](https://github.com/superglue-ai/superglue)\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXejwKUtg5vNmIUFVD-naIZc3NVJVO4nIxzG1bVC5SkaA8g5JuhP7I9QWTBXPVCbKQdc6OY7bgFgVuJPf99JjYyBK3Y2TDpGG_ehUirAvBmANq8dkq9EpyY-72Dn56s6dW3LA6n82g?key=X6C0DCn4htyY5GQ3HDPmoqgF)\n\n# **Why it matters**\n\nMost companies struggle with data integration challenges daily. Energy providers pull meter readings from thousands of devices, fashion marketplaces standardize product data from various retailers, and fintech companies normalize transaction data across payment systems. Each system speaks its own language, forcing developers to write and maintain custom code to transform and normalize data. It's a massive waste of engineering resources and slows down business innovation.\n\n# **What we’re building**\n\n_superglue_ is an intelligent proxy server that automatically transforms data from external APIs into your desired format, eliminating the need for custom mapping code. By sitting between your application and APIs, it allows developers to define data structures once and apply consistent transformations across all integrations, turning complex data integration from a weeks-long project into a minutes-long configuration. The superglue proxy can sit outside your codebase - particularly good for legacy systems that are brittle and hard to change.\n\n**Key features**\n\n* **One-off LLM-powered translations**: Generate deterministic, high-performance translation code.\n* **Self-healing**: Detect format changes and update translations automatically\n* **Fast deployment**: Supports most APIs and data formats out of the box\n* **For enterprise**: Hosting, logging, retries, caches, access control\n\n## **Get Started**\n\n1. [Get access](https://superglue.cloud/) to our hosted version or install superglue as a lightweight local proxy\n2. Pick an API / data source to connect to\n3. Define your desired data output format\n\n![uploaded image](/media/?type=post&id=87434&key=user_uploads/1344607/34c24883-0af1-4dd0-89a7-4493b1913ddb)\n\n4. Let superglue handle transformations and schema enforcement\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXfITHd_G-ZeA03HGoDOL8Oql_Jb4Pu50FWrLhRVldLEMgSyUN-cMsaY6T-Vx3xqEpyLz-6zWnejpU_1siA-1-LLX7okg-r2YqTaeDcU3xuAkAbgvGfWmVi4i-yyCVOuKaeQWGajlA?key=X6C0DCn4htyY5GQ3HDPmoqgF)\n\n<https://youtu.be/Bzbw3Oh9zIg>\n\n**How is this different from connector platforms and unified APIs?**\n\nUnlike platforms that offer predefined APIs for specific verticals and require developers to adapt to their specifications, _superglue_ provides universal data transformation that works with any API or data source. We give developers complete flexibility to transform data however they want, without vendor lock-in. Where other platforms support a limited set of integrations, _superglue_ can transform data from literally any source - whether it's a well-known API or a custom internal system - putting developers in full control of their data pipelines.\n\n**What if I want to own the integrations I build?**\n\nYou totally can with _superglue_. As an open-source solution, we provide full transparency and the ability to modify transformation logic at any level, ensuring you're never trapped in a black box. Unlike closed integration platforms, you own 100% of the integration logic. You can host the entire solution on your own infrastructure, with full access to source code and transformation rules.\n\n# **Get superglued**\n\nAre you currently building integrations, onboarding customers via integrations or too strapped to integrate them? Email us at [founders@superglue.cloud](https://mailto:founders@superglue.cloud), we’re happy to help.\n\nHave you built data-heavy integrations in the past? We want to speak to you!\n\nOtherwise get started on [Github](https://github.com/superglue-ai/superglue) or [book a demo](https://cal.com/teamindex/superglue-demo).\n\n# **About us**\n\n[Stefan](https://www.linkedin.com/in/stefan-faistenauer/) and [Adina](https://www.linkedin.com/in/adinagoerres/) first met in 2019 while studying in Munich. Their shared experience in the integration space led them to superglue.\n\n![uploaded image](/media/?type=post&id=87434&key=user_uploads/1344607/b7871bfd-f80c-48d4-90fc-aa1cb4b170c9)\n\n",
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    "long_description": "Dexto makes it easy for developers to integrate AI agents into any software application. We do this by exposing agents as simple APIs that can be called from anywhere. Developers have used Dexto to add customer support agents into WhatsApp and analytics agents into Slack.",
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        "id": 88053,
        "title": "Truffle AI - AI Agents that work in any Software Application",
        "tagline": "Integrate AI Agents with simple APIs, seamlessly",
        "body": "Hey YC!\n\nWe’re Shaunak and Rahul and we are making it easy for developers to **integrate AI Agents into any software application**. We do this by making agents available as simple APIs that can be called from anywhere. Developers have used Truffle to add customer support agents into WhatsApp and integrate analytics agents into Slack. Check out our demo below 👇\n\n<https://youtu.be/5tEuWYWNSPA>\n\n### **The Problem**\n\nWhile AI models have become more accessible, getting AI agents to production remains painfully complex. Developers don’t just need a model—they need to handle:\n\n* Managing state, memory, and vector databases\n* Manually integrating external tools and APIs\n* Customizing agents for specific business logic\n* Setting up and maintaining deployment infrastructure\n\nDespite existing frameworks, **developers still spend 60% of their time on \"glue code\" instead of building actual AI solutions**. Companies burn **$100K–$200K per year** on DevOps overhead, just to manage AI agent infrastructure. AI should be easier to integrate than this.\n\n### **The Solution**\n\nTruffle AI eliminates infrastructure headaches by turning AI agents into plug-and-play APIs:\n\n* **No infrastructure setup** - Our managed service handles the heavy lifting, eliminating deployment and scaling concerns\n* **Seamless integration** - Add AI agents to any application with just a few lines of code\n* **Full customization** - Build agents tailored to your specific business challenges\n* **Reusability** - Deploy the same agents across multiple applications\n\nMost AI adoption today is being held back by engineering complexity—Truffle AI removes that bottleneck, making AI agents as simple to integrate as calling an API.\n\n### **Our Story**\n\n![uploaded image](/media/?type=post&id=88053&key=user_uploads/1684384/164d65b8-6f92-4bc5-809d-a82b0c99c029)\n\nAs developers, we both hit the same frustrating wall: spending countless hours writing \"glue code\" for infrastructure instead of building innovative AI solutions.\n\nWhile exploring several frameworks to build AI agents, we discovered a critical gap - none addressed the massive infrastructure overhead required for production-ready AI systems.\n\nWith Rahul's expertise in large-scale deployment and cluster management at AWS and Shaunak's background in AI research and product development, we realized we were uniquely positioned to solve this problem.\n\nOur mission became clear: make powerful AI accessible to businesses of all sizes by eliminating the infrastructure barriers that slow innovation.\n\n### **Who Is This For?**\n\n👩‍💻 **Software developers** who want to add AI capabilities without becoming infrastructure experts\\\n🏢 **Startups and enterprises** looking to quickly deploy AI solutions without hiring specialized DevOps teams\\\n🔧 **AI engineers** who want to focus on agent design rather than deployment pipelines\\\n🛠️ **Product teams** who need to iterate rapidly on AI features without getting bogged down in infrastructure\n\n# \n\n### 🌎 **What Can You Build?**\n\nWith Truffle AI, developers have already built:\n\n💬 Customer support agents that automate WhatsApp & Slack interactions\n\n📊 Analytics agents that fetch and analyze data from spreadsheets\n\n🤖 Multi-agent workflows that coordinate different AI tasks seamlessly\n\n### **Get Started**\n\n**Looking to integrate AI Agents into your organization?** Truffle AI can help!\n\n* [Schedule a demo](https://calendly.com/shaunak-trytruffle/30min) with us!\n* [Try it out](https://www.trytruffle.ai/) yourself on our platform!\n* Want to dive into the code? Check out our [docs](https://docs.trytruffle.ai/introduction)!",
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        "votes": 24,
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    "name": "A1Zap by A1Base",
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        "linkedin_url": "https://www.linkedin.com/in/pasharayan",
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        "title": "A1Zap - the social network layer for AI apps",
        "tagline": "Starting with campuses - build apps that spread through a unified social graph",
        "body": "<https://youtu.be/XDBbb3vrdL0>\n\nSocial networks were built for content. But with AI, people don’t just have to post. They want to build things that engage with others.\n\nA1Zap is a social network where people build things for each other.\n\nOn A1Zap, anyone can create AI-powered apps, chatbots, tools, and agents and share them instantly with friends, group chats, campus and their community. Distribution isn’t a separate problem. It’s built in to our platform from day one.\n\nWe’re starting with campuses - our founders also spent the last 10 years working on a college based YC company (Forage!) - so we’re kind of experts here.\n\nWe’re already seeing this with “Rate My Rent” at UT Austin, group matchmakers at Harvard, and campus maps, events, and tools across universities.\n\nThese aren’t posts. They’re things that happen to you.\n\nOur belief is simple: the next generation of social networks won’t be content feeds. They’ll be networks of things people build and share with each other.\n\nIf you’re building for your friends, your class, or your community, we’d love to chat with you.\n\nStudents - join your campus: <https://www.a1zap.com/>",
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        "linkedin_url": "https://linkedin.com/in/seth-setse-0641b6175",
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        "linkedin_url": "https://linkedin.com/in/omolewa",
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        "title": "a0.dev - Phase 1: We're all gonna make apps (WAGMA)",
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        "body": "![uploaded image](/media/?type=post&id=91846&key=user_uploads/1607594/d98552b9-2959-4309-9fbe-f064cf3849f1)\n\nHey YC! 👋 \\\n\\\nWhen we first launched earlier this year, we set out with a bold vision: what if anyone, regardless of technical background, could turn their ideas into real mobile apps in minutes instead of weeks? After seven years of building our own apps, we’ve spent the last five months working tirelessly to supercharge a0 – and now, thanks to that effort, we’re all going to make apps.\n\nhttps://www.youtube.com/watch?v=74ZzymZO7fw\n\n### **So what’s new in Phase 1?**\n\nTo start, we created the world's fastest iOS build process - literally seconds from code to installable app on your phone.\n\nThis lead into One-click App Store submission that handles all the Apple provisioning nightmare for you\n\nWe also shipped lots of improvements to our code-gen like Agent Mode with thinking capabilities that can read files, search context, and solve complex problems.\n\nAnd we built-in payments support to a0.dev so you can start monetizing your apps immediately\n\nYou can read the full breakdown in our [blog post](https://a0.dev/blog/phase-1-wagma).\n\n### Isn’t \\____\\_ already doing this?\n\nWe know AI app builders are a popular idea these days. We were the first to launch an AI mobile app builder and have seen many competitors pop up after us, some even from YC. To us, it’s just more proof that this idea is worth working on. We’re taking a different approach to building a0 that comes from our experience as app developers and we’re confident it will be the correct one.\n\nWe didn't just build another no-code tool. We built an AI-native platform that wraps the entire app development experience from idea -&gt; app store. Our agent builds beautiful UI and even handles the back-end. Combined with instant iOS builds, we're removing every friction point between idea and getting your app on the store.\n\nThe response from our first launch has been incredible - 100k+ developers are shipping apps faster than ever with a0.\n\nOur new mantra is WAGMA: We Are All Gonna Make Apps , because we genuinely believe with a0 everyone has the power to get to the app store.\n\nWelcome to Phase 1.",
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        "created_at": "2025-07-03T18:24:33.801Z"
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        "title": "a0.dev: Build Mobile Apps in Minutes",
        "tagline": "Generate, preview, and refine your app—all in one place.",
        "body": "Hey everyone, we’re [Seth](https://x.com/sethsetse) and [Ayo](https://x.com/TheDonAyo) and – co-founders of [a0.dev](http://a0.dev)\n\n**tl;dr**\n\n[a0.dev](http://a0.dev) is the fastest way to build React Native apps.\n\nWe generate the **entire front end** of your app for you—navigation, state management, and UI screens, all set up and ready to go.\n\nNeed to prototype a single screen instead? We also built a Component Generator, like **v0 but for React Native**, so you can quickly create and export screens with clean, production-ready code. Check out a quick demo video👇.\n\n<https://youtu.be/GXVqQHJCCac>\n\n# **The Problem:** _Building Apps is Hard_\n\nLaunching a mobile app is much harder than releasing a website. Setting up your project, coding every screen, managing state, and integrating the backend can take **weeks**.\n\nAnd if you’re building for iOS, you need a Mac to run Xcode, deal with provisioning profiles, and compile your app—just to test it.\n\n[**a0.dev**](http://a0.dev) removes these barriers. We generate your app’s front end in minutes and let you preview it right away—no Mac, no complicated setup, no waiting.\n\n# **Our Solutions:**\n\n**#1 Full App Generator –** Build a complete React Native app\n\n[a0.dev](http://a0.dev) takes care of the entire front end of your mobile app—so you can go from idea to working UI in minutes.\n\n✅ **Instant App Generation** – Describe your app, and we generate a complete React Native project with navigation, state management, and essential UI screens.\n\n✅ **Live Preview & Hosting** – Share your app instantly with anyone, no need for TestFlight or manual builds. We host your app so you can test and iterate faster.\n\n✅ **Remote Development Environment** – Work on your app from anywhere via an SSH-powered cloud IDE, with real-time reload and collaboration.\n\n🚀 **Faster to Market** – We’re proving that high-quality mobile apps can be built in record time. We both shipped fully functional apps to the App Store in **under 24 hours** using [a0.dev](http://a0.dev).\n\n\\\n**Check out our demo** where we made a chess timer app in <10 minutes.\n\n[**https://www.youtube.com/watch?v=G_upRVS63Fk**](https://www.youtube.com/watch?v=G_upRVS63Fk)\\\n\\\n**#2 Component Generator –** Like **v0, but for React Native**\n\nAlready have an app or need to quickly prototype a single screen? Our Component Generator lets you create custom React Native UI screens in seconds.\n\nWhile our focus is on building entire apps, our component generator helps you iterate and test ideas **faster than ever.** Try it out [here](https://a0.dev).\n\n![uploaded image](/media/?type=post&id=87417&key=user_uploads/1607594/35f5044d-d40a-4dba-8fb7-71ef8ffddc7c)\n\n**Our Story & Vision**\n\nWe started as indie app developers, making side income with apps generating up to $14k MRR. But we realized how hard it was for others to do the same. Our goal is to make mobile app development even easier than building websites. We want more people to be able to make a living creating and selling their own software. [a0.dev](http://a0.dev) is the platform we wish we had when we started—and now we’re building it for you.\n\n**Our Ask**\n\n* If you’re a mobile app developer who wants to make a new app or an aspiring app developer looking to enter the scene, contact us and try a0, we’ll help you create and launch your app in < 3 days.\n\n**Get Started**\n\n* Try our Component and Full App Generator at <https://a0.dev>\n* Follow our journey on X: <https://x.com/a0_dev>\n\n_Need to reach the founders?_\n\nEmail: [**founders@a0.dev**](mailto:founders@a0.dev)",
        "url": "https://www.ycombinator.com/launches/Mjx-a0-dev-build-mobile-apps-in-minutes",
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        "created_at": "2025-02-04T21:52:45.423Z"
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        "full_name": "Adam Cohen",
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        "founder_bio": "Co-Founder & CEO @ Weave. AI to understand engineering work.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/adam-b-cohen/",
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        "experience": "Any (new grads ok)",
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        "title": "Founding ML Engineer",
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        "title": "Founding GTM Engineer",
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        "location": "San Francisco, CA, US",
        "type": "Full-time",
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        "role_type": null,
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      },
      {
        "id": 89808,
        "title": "Founding Design Engineer",
        "url": "https://www.ycombinator.com/companies/weave-3/jobs/bgZcAi9-founding-design-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Frontend",
        "salary_range": "$140K - $200K",
        "equity_range": "0.05% - 0.20%",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
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      },
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        "id": 94021,
        "title": "Founding Marketer",
        "url": "https://www.ycombinator.com/companies/weave-3/jobs/M9rKQPd-founding-marketer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Marketing",
        "role_type": null,
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        "equity_range": "0.01% - 0.10%",
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      {
        "id": 112643,
        "title": "Founding Developer Relations",
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        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$150K - $225K",
        "equity_range": "0.05% - 0.15%",
        "experience": "3+ years",
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      {
        "id": 112644,
        "title": "Founding Business Development Representative",
        "url": "https://www.ycombinator.com/companies/weave-3/jobs/kIw3GEF-founding-business-development-representative",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
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        "salary_range": "$100K - $120K",
        "equity_range": "0.01% - 0.10%",
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    "news": [
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        "title": "A YC Startup That Wants to Kill Tokenmaxxing Just Raised $13.5 Million - Business Insider",
        "url": "https://www.businessinsider.com/weave-funding-tokenmaxxing-startup-y-combinator-ai-coding-spend-developers-2026-7",
        "date": "Jul 28, 2026"
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    "launches": [
      {
        "id": 87406,
        "title": "Weave: AI to quantify engineering work",
        "tagline": "Engineering metrics for the AI era",
        "body": "tl;dr: Weave uses AI to measure software engineering work in the AI era.\n\nIt shows how much work is being done, how much is done by AI and where you can utilize AI tools to improve your engineering process.\n\n### **The Problem**\n\nHistorically, it’s been impossible to measure engineering so leaders are left flying blind. Engineering teams rely on gut feel or shoddy metrics to try to get a handle on what’s going on and where to improve.\n\nThat's why we built Weave.\n\n### The Solution\n\nhttps://youtu.be/GkZv9-YZTKI\n\nWeave uses AI to measure engineering work. We run LLMs and our own models on every PR and review, analyzing both output and quality. We integrate with all AI coding tools (Claude, Cursor, etc.) and have PR level code attribution to determine what was written by AI, what wasn’t, and what should’ve been.\n\nWe summarize this data and insights in dashboards. Teams like Reducto, Superpower and Laurel use Weave to ship 16% more, just 2 months after using Weave.\n\n![uploaded image](/media/?type=post&id=87406&key=user_uploads/1938955/966b7f89-b6a1-4aa7-8fbc-4b6cd7bf4fb1)\n\n\n### AI Usage\n\nWe show you who your top AI performers are (so they can share best practices), how the team stacks up against its competitors and the real financial return of your AI investments.\n\n![uploaded image](/media/?type=post&id=87406&key=user_uploads/1938955/57dfeddd-0c9f-49c1-afea-0454bad3f0ab)\n\n![uploaded image](/media/?type=post&id=87406&key=user_uploads/1938955/56c25bbf-a333-4bea-9938-93e639687d12)\n\n![uploaded image](/media/?type=post&id=87406&key=user_uploads/1938955/c2672d3e-b073-45d1-95d8-41578f1a829d)\n\n### AI Insights\n\nWe keep you up to date with the best practices and tools used by the most forward-thinking AI teams.\n\n![uploaded image](/media/?type=post&id=87406&key=user_uploads/1938955/d438efd0-4a9b-41a2-a4ae-1d506e800595)\n\n### Measuring Code Output\n\nThis isn't a line of code calculator, this is an actual estimate of our key metric, a Weave Hour: \"How long would it take an experienced engineer to make this change?\"\n\nWe can also tell you how much time each engineer is spending on code review and how helpful their reviews are:\n\n![uploaded image](/media/?type=post&id=87406&key=user_uploads/1938955/581a3928-2eb3-4e98-a0d4-e8ae64c6cd15)\n\n![uploaded image](/media/?type=post&id=87406&key=user_uploads/1938955/ede5f44c-ca77-4d4c-ab23-12d7c3c6df7f)\n\n### Individual\n\nSee output across individuals to identify top performers, see how new hires are ramping and if anyone is blocked.\n\n![uploaded image](/media/?type=post&id=87406&key=user_uploads/1938955/65664616-047f-4ce7-829c-b40839f34d09)\n\n### **Our Story**\n\n![uploaded image](/media/?type=post&id=87406&key=user_uploads/2077133/d1883e57-85cd-4616-a456-3370a1a0b664)\n\nAdam’s background is in operations and sales. He led organizations of 100+ people and created an internal tool to measure performance and help individuals identify their weak spots. This is common practice in revenue teams and he wants to bring it to engineering.\n\nAndrew was employee #1 at Causal. He saw firsthand how subjective engineering management is and how hard it is to scale a high-performing engineering team.\n\nWe met at Causal, where Adam was hired to run the sales and customer success function. We got to talking about the big difference between how our two departments worked, and the rest is history.\n\n**Early Use Cases**\n\n* Reducto, Superpower, and Posthog have used Weave to see increases in output correlated with AI usage (16% on average)\n* A manager noticed that code review quality has the highest correlation to output. He reset code review standards and team output went up by 15%\n* Smaller engineering teams (\\~5 engineers) are using the platform daily in stand-ups\n\n**Our Ask**\n\n* Are you running an engineering team of any size? You can connect your repo to Weave and get started in \\~30 seconds [**here**](https://workweave.dev/).\n* Do you know any engineering leaders at mid-market or enterprise companies who might find this valuable? We'd love an intro if you do.\n* Follow us on [**LinkedIn**](https://www.linkedin.com/company/weave-dev) and X!",
        "url": "https://www.ycombinator.com/launches/Mjm-weave-ai-to-quantify-engineering-work",
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        "created_at": "2025-02-04T17:25:21.748Z"
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    "website": "https://adam.new/",
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    "long_description": "Applied AI lab building end-to-end agents for mechanical design.",
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        "full_name": "Zach Dive",
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        "founder_bio": "You can just make things. Previously AI Research & Engineering @Adept and Design @Berkeley. \n\n",
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        "full_name": "Aaron Li",
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        "title": "Residency (Summer 2027)",
        "url": "https://www.ycombinator.com/companies/adam/jobs/VOGhQkx-residency-summer-2027",
        "location": "San Francisco, CA, US",
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        "location": "San Francisco, CA, US",
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        "role": "Engineering",
        "role_type": "Machine learning",
        "salary_range": "$200K - $300K",
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        "experience": "3+ years",
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        "title": "MTS - Founding Engineer",
        "url": "https://www.ycombinator.com/companies/adam/jobs/q6td4uk-mts-founding-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
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        "role_type": "Full stack",
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        "id": 106707,
        "title": "MTS - Forward Deployed Mechanical Engineer",
        "url": "https://www.ycombinator.com/companies/adam/jobs/cZ7rfHL-mts-forward-deployed-mechanical-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
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        "salary_range": "$200K - $250K",
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        "experience": "3+ years",
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      {
        "id": 87143,
        "title": "Adam - AI Co-Pilot for CAD ⚙️⚙",
        "tagline": "Adam helps engineers 10x their CAD workflows with simple AI prompts",
        "body": "Hey YC! 👋\\\n\\\nWe're [Aaron](https://x.com/aaronhetengli), [Avi](https://x.com/avimakesrobots) and [Zach](https://x.com/zachdive) from Adam and we are building AI Powered CAD for mechanical design. Our first launch is our Text to CAD editor. Some of our early users have called it the **Vercel V0 for CAD**. You simply put a prompt in on our web-app and we generate a parametric CAD file for you. Check out our fun promo vid 👇.\\\n\\\nhttps://youtu.be/Pw6KGqgygqw\n\n**TL;DR:**\n\n* 🔧 Use our **Text-to-CAD** model to accelerate your mechanical design workflows\n* 🪛 Adjust the **Parametric CAD** with our dynamically generated sliders\n* 🛠 Export and **ready to 3D print in seconds**\n\n### **Problem**\n\n**Slow**\\\nLegacy CAD software is weighed down by antiquated UX and outdated geometry rendering from the early 90s.\n\n**Repetitive** \\\nMechanical engineers and design professionals spend hours everyday restarting projects due to rigid workflows. The current tools are clunky and slow to iterate in meaning the iteration process is greatly slowed down.\n\n**Demands significant expertise**\\\nThe complexity of CAD tools hinders rapid prototyping and wider adoption.\n\n### \n\n### **Solution**\n\nDesign professionals spend hours every week converting ideas into CAD design and its complexity often creates barriers for both professionals and newcomers. The Adam web-app provides a frictionless experience to start rapidly prototyping and shipping out great ideas.\n\n**We support two different modes of interaction**\n\n_1. Conversational design through chat_\n\n![uploaded image](/media/?type=post&id=87143&key=user_uploads/1626462/6c4b0839-2b67-4e55-b857-ae6e11f20703)\n\n_2. Parametric edits through sliders_\n\n![uploaded image](/media/?type=post&id=87143&key=user_uploads/1626462/e97bde5c-d49a-4be9-b1b0-4e0fc329a5fa)\n\n### **One more thing..**\n\nWe are building an Adam Co-Pilot that integrates seamlessly within professional-grade CAD workflows. Think of this as the **Cursor for CAD.** It takes in the context of your CAD environment and is able to make directed edits for you. Check out an early prototype (more on this to come…)!\\\n\\\nhttps://www.loom.com/share/7c945465a21e4fb7abfd557299be4925\n\n### **We are on a mission to remove the friction between engineering and reality so more great ideas come into existence.**\n\n👉 If you resonate, please reach out to us here: [founders@adamcad.com](mailto:founders@adamcad.com)\n\n&lt;3\\\nCheck out our website: [www.adamcad.com](https://www.adamcad.com/)\n\n![uploaded image](/media/?type=post&id=87143&key=user_uploads/1626462/d50e9f22-e38f-4a6d-b0b7-eea7dedcba0a)\n\n",
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        "votes": 212,
        "created_at": "2025-01-24T18:32:15.271Z"
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    "id": 30237,
    "name": "Trim",
    "slug": "trim",
    "former_names": [
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    "website": "https://trimresearch.com",
    "all_locations": "San Francisco, CA, USA",
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    "year_founded": 2024,
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        "full_name": "Emanuel Gordis",
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        "is_active": true,
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        "title": "Founder/CTO",
        "founder_bio": "CTO @ HUD.\n[a-z]*",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/parth220",
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        "id": 93541,
        "title": "Research Engineer (General)",
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        "role": "Operations",
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        "id": 99313,
        "title": "Research Engineer, Synthetic Data",
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        "title": "Stillwind Builder — Zero to BOM in minutes instead of days",
        "tagline": "AI agent that turns your PCB design intent into a complete, verified bill of materials.",
        "body": "❌ **The problem**\n\nEvery PCB design is a constraint problem: you need components that are electrically and functionally compatible with each other. Solving it by hand means hours — often days — of tracking down parts, reading datasheets, adding a component, discovering a conflict, and backtracking. Pick an MCU and the cascade begins: it needs a specific crystal, external flash on the QSPI bus, a regulator that can source its peak current. Every choice ripples through the whole design.\n\n✅ **The solution**\n\nStillwind Builder formalizes your design constraints as an explicit system of equations and solves for matching components.\n\n* **Verified specs.** Before we show you a part, a second model independently re-reads its datasheet and verifies the specs match — so the numbers you design against are what the datasheet actually says, not extraction artifacts.\n* **Dependency-aware.** When you lock in a component, the agent reads its datasheet for the supporting parts it requires — voltage regulators, crystals, external flash — and updates the constraint system. The ripple effects of each choice are handled instead of discovered later.\n* **You stay in control.** You set the direction and make the calls that matter; the agent handles the combinatorial grind.\n\nAt the end, you download your BOM and start wiring.\n\n🚀 **Try it**\n\nThe public beta is live and free during launch week: [**https://stillwind.ai**](https://stillwind.ai)\n\nBuilding hardware and want to tell us what's broken? We'd genuinely love that — grab time with us: <https://calendar.app.google/Bd7KQEAYLgt6SmHZ6>",
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        "body": "Hey all 👋, we’re Linus, Hannes, Lukas, and Josef—co-founders of [**Augento**](https://www.augento.ai/)! 🕊️\n\n**TL;DR**\n\nWe align your agents with reinforcement finetuning. You give us your agent, tell us where it fails and we’ll improve it. 🚀\n\nWe are actively looking for **design partnerships**. If you are interested, please shoot us a message at [**founders@augento.ai**](mailto:founders@augento.ai) 😄\n\n**The Problem ❌**\n\n🗣️ AI Agents struggle in real-world environments. Even state-of-the-art reasoning models score below 50% accuracy on non-trivial benchmarks.\n\nThe solution for many is still prompt engineering &amp; expanding the models' guardrails. However, anyone who’s fought with large prompts knows how draining it can be. You’re never quite sure if the model is really following your instructions or if your tweaks make any difference.\n\n**Our Solution ✅**\n\nWe tackle this by replacing prompt engineering with fine-tuning + RL on **your** feedback. We integrate with a two lines of code change in your existing system.\n\n[**https://www.youtube.com/watch?v=Sulzf7VZr3k**](https://www.youtube.com/watch?v=Sulzf7VZr3k)\n\n**The Workflow 💡**\n\n1\\. Swap out your LLM connector URL with ours.\n\n2\\. We intercept every prompt and output, displaying them in our UI.\n\n3\\. Where necessary, you give high-level feedback, like your preferred tone or how a tool should actually be used.\n\n4\\. We continuously post-train the model to match up to your feedback.\n\n5\\. Once you deem it good enough and want to switch over to the model, you can do that with a click of a button, no changes to your code required.\n\n**Our Ask**\n\nWe’d love your input and are looking for early users to test-drive Augento. Shoot us a message at [**founders@augento.ai**](mailto:founders@augento.ai)\n\n**The Team**\n\nLinus previously studied CS @ ETH in Zurich and did research in complexity theory. During his studies, he worked as an ML Engineer &amp; as a Quantitative Developer in High-Frequency Trading.\n\nHannes previously studied CS @ ETH Zurich and worked on decentralized and distributed systems. During his studies, he worked as a paid contributor for a big open source project and as the technical lead for his previous startup.\n\nJosef previously studied CS @ ETH Zurich, and worked on computer systems and networks, as well as ML. During his studies, he worked as a full-stack software engineer and embedded systems developer.",
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        "created_at": "2025-03-02T02:49:45.257Z"
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        "title": "ReJot - Enterprise Synchronization Engine",
        "tagline": "Sync engine to share data across engineering teams in enterprises",
        "body": "Hey everyone, we're Wilco & Jan, co-founders of ReJot! We're building a sync engine that helps big companies share data across engineering teams. We increase developer velocity and, most of all, ensure companies are not forced onto Kafka when they don't actually need event streaming.\n\n<https://www.youtube.com/watch?v=Ulxmwrp_N5Q>\n\n# The Problem\n\nGrowing companies are forced to adopt micro-services as their desire to give engineering teams autonomy increases. The number one reported problem in this architecture paradigm is **data silos**. Silos create high coordination overhead when integrating data from other engineering teams, slowing down development and delaying product launches.\n\nThe industry has defaulted to event streaming platforms like Kafka to enable teams to share data asynchronously. As a result, enterprise software architectures are pushed into an event-driven model. However, events come with inherent complexity—they encode **something happening** rather than **something being** (i.e., state).\n\n**We believe that events are used for no good reason other than the infrastructure forcing developers onto them.**\n\n# Solution\n\nReJot is a **sync engine** that enables sharing data between back-end services without the need for APIs or event streaming. We break data silos without forcing a paradigm shift from state to events.\n\nWe do this in the following way:\n\n* **Familiar Querying:** by syncing database-to-database, ReJot allows engineers to query data from other teams **directly from their own database**. Developers use what they know best: SQL queries.\n* **Sharing Data:** We realize that internal database schemas are sacred, and they should never be public directly. ReJot provides strong **data-sharing primitives**, allowing data owners to control _what_ and _how_ data is shared. Simplicity is key—setting up data publications in ReJot is trivial.\n* **Integration Flexibility:** Downstream teams don't necessarily need data in the same shape as the original source. SQL queries are used once more to transform the data to fit the integrating team's needs.\n* **Data Catalog**: Integrating data is impossible without first understanding what data is available. Our system overview maps an enterprise's software architecture through its databases, allowing the user to explore and search schemas to uncover opportunities for deep integration between products.\n\n![uploaded image](/media/?type=post&id=88081&key=user_uploads/2356635/d80813fb-077e-4916-98f0-bae320ddd57c)\n\n_\\[This overview shows how accounts owned by the accounting team are made public and integrated into the banking database by means of the \"Accounts Consumer\" integration.\\]_\n\n# Launching Today\n\nToday, we’re excited to launch the **open-source** Limited Access Preview of ReJot!\n\nOur control plane doubles as a database catalog, providing a unified view of all data stores within your organization. Connect Postgres databases to document your system architecture.\n\nIn the coming weeks we'll be rolling out ReJot's synchronization functionality to select users. As we scale our infrastructure, more users will be onboarded.\n\n![uploaded image](/media/?type=post&id=88081&key=user_uploads/2356635/c2ee7761-283c-4064-af0e-44984f23320a)\n\n# The Team\n\nWe met nearly 10 years ago in Amsterdam where we studied Computer Science together, and have been friends ever since.\n\n* Wilco (CEO) worked as a software engineer on Adyen's banking infrastructure. During a period of high growth he worked on the internal ledgering system and a framework to sync bank account data throughout the company, which inspired ReJot. He also has a background in software maintainability research.\n* Jan (CTO) was a data platform engineer for Adyen's big data platform. There, he managed infrastructure for 600+ ETL pipelines created by 50+ teams that produced hundreds of terabytes of data every week. Jan is a published AI researcher.\n\nThrough a shared passion of modern software technology and reducing complexity in enterprise systems we connected the dots to create ReJot's sync engine.\n\n# The Ask\n\n* _🔗_ Share this post! Do you know of any organizations struggling with their distributed architecture? Reach out to us at [founders@rejot.dev](mailto:founders@rejot.dev) —we’d love to help!\n* ⭐️ Star us on [GitHub](https://github.com/rejot-dev/rejot), follow us on [X](https://x.com/rejotsync) & [LinkedIn](https://www.linkedin.com/company/rejot)\n* 📧 Sign up for our [newsletter](https://rejot.dev/email-updates/)\n* 🌐 Connect your databases & learn more: <https://rejot.dev>\n\n![uploaded image](/media/?type=post&id=88081&key=user_uploads/2356635/98e4ff65-8266-448c-a2c9-637da1065625)\n\n",
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        "title": "Confident AI: The Evals Platform for AI Quality & Observability",
        "tagline": "An evaluation platform for engineers, QAs, and PMs to pinpoint which iteration of their AI to put in production.",
        "body": "**TL;DR – Confident AI is a cloud-based evaluation platform to help teams build reliable AI products. Its evals are powered by DeepEval - an open-source LLM evaluation framework, which has over 12k stars, 3million monthly downloads, runs 2million evals per day, and is most commonly found in CI/CD pipelines of enterprises such as BCG, Astrazeneca, AXA, Microsoft.** \n\n**Confident AI allows engineering teams to iterate on their LLM app x10 faster by bringing best-in-class evals to traditional AI observability.**\n\n[Try Confident AI today (setup in 5 min)](https://docs.confident-ai.com/confident-ai/confident-ai-introduction)\n\n![uploaded image](/media/?type=post&id=87657&key=user_uploads/1314014/fc01311e-e55b-4632-8256-75115c04f3f5)\n\n### **The Problem**\n\nDespite LLM evaluation being a problem with many solutions on the market, it remains unsolved. General LLMOps observability platforms that offer evals lack robust metrics and are more suited for debugging through tracing UIs, while evaluation-focused frameworks don’t offer enough control for users to customize and make metrics reliable for specific use cases.\n\nAs a result, developers often build custom evaluation metrics and pipelines from scratch—writing hundreds or even thousands of lines of code to test their LLM apps. The worst part? Once they’ve fine-tuned their metrics and are ready to deploy them across the organization, they hit a roadblock: there’s no easy way to collaborate. Because these custom metrics exist in scattered code rather than an integrated ecosystem, incorporating them to enable team-wide adoption becomes frustrating and inefficient.\n\n### **The Solution**\n\nWe built DeepEval for engineers to create **use-case-specific, deterministic** LLM evaluation metrics, and when you're ready, Confident AI brings these evaluation results to the cloud for collaboration. This allows teams to collaborate on LLM app iteration — with no extra setup required.\n\n1. Curate your evaluation dataset on Confident AI.\n2. Run evaluations locally with DeepEval's metrics, pulling datasets from Confident AI.\n3. View and share testing reports to compare prompts and models and refine your LLM application.\n\nConfident AI continuously evaluates monitored LLM outputs for production, automatically enriching your dataset with real-world, adversarial test cases. This keeps your evaluation data high-quality and reflective of your use case.\n\n<https://youtu.be/yLIhVn3B8Wg>\n\n### **How are we different?**\n\nWhat we've learned is in order to get legitimate evaluation results required for benchmark-driven iteration, you need extremely high-quality metrics and datasets. That's why we've built specifically for the ideal LLM evaluation workflow:\n\n* **DeepEval** handles robust, deterministic metrics required for rigorous, use-case-tailored validation.\n* **Confident AI** provides both technical and non-technical teams the ability to collaborate on pre and post-deployment evals and observability.\n\n> If your evaluation results are 100% reflective of your LLM application's performance, what's stopping you from shipping the best version of your LLM app?\n\n### **Customer ROI metrics**\n\nWe've been working with companies of all sizes, and some of the ROI metrics include:\n\n* Decreasing LLM cost by **more than 70%** through evaluation to safely switch away from GPT-4o to cheaper models.\n* Decreasing time to deployment for a team of 7 from **1-2 weeks to 2-3 hours**.\n* Helping a team of 30 customer support agents **save 200+ hours a week** by having a centralized place to analyze LLM performance live.\n\nThere's more to come as we start publishing some case studies on our website, so stay tuned!\n\n### **Our Ask**\n\nThanks for sticking with us to the end! We’re on a mission to help companies get the most ROI out of their LLM use cases, and we believe this is only achievable through rigorous LLM evaluation at scale. If our mission resonates with you, Confident AI is always here and available to try immediately (coding required, but free to try): <https://www.confident-ai.com/docs>\n\nIf you want to explore our enterprise offering, you can always [talk to us here.](https://calendly.com/d/cqbp-t88-y4j/confident-ai-intro-call)\n\n### **About Us**\n\nConfident AI is founded by **Jeffrey Ip**, a SWE formally at Google scaling YouTube's creators studio infrastructure, and Microsoft building document recommenders for Office 365, and **Kritin Vongthongsri**, an AI researcher and CHI-published author, who previously built NLP pipelines for fintech startups and researched self-driving cars/HCI during his time at Princeton, where he studied ORFE and CS.",
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        "votes": 375,
        "created_at": "2025-02-13T17:44:57.361Z"
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        "title": "Wildcard: AEO, GEO, and AI Search for Ecommerce Brands",
        "tagline": "Wildcard is the command center for agentic commerce. We help ecommerce and retail brands become the answer AI chooses.",
        "body": "**Traction:** 20+ Brands live. On average brands see a 5X increase in AI search revenue after 30 days.\n\n**TL;DR:** [Wildcard ](https://wild-card.ai/)helps brands and retailers rank first across ChatGPT, Claude, Gemini, Amazon Rufus/Alexa, and Walmart Sparky. We audit and action on how your brand, products, and collections show up across every AI search and shopping platform. Wildcard creates the roadmap, and our AI agents execute on it. We create the content AI looks for, including enriching the product catalog, new blogs, collection pages, outreach to publications, and even Reddit and YouTube content to close the gap. Operators can review, approve, and measure how actions tie back to revenue.\n\n**Launch Video:** <https://youtu.be/dkdV-s-JztE>\n\n**The Problem:** Shoppers are googling less and less. They want an experience where they can ask questions, like talking to an in-store rep. They're prompting about what to buy, the model names a few, people purchase those, and you're left relying on Meta's rising ad spend to acquire new customers or retain existing ones. Producing content for millions of SKUs is beyond human scale, and what we found is that millions in revenue was lost because of it. Below is what we learned after 7 months talking with brand owners.\n\n**What We Learned:**\n\n1. It's not about training the model. Everyone gets this wrong. When someone asks, the model runs a live search, reads what it finds, and picks. What decides it is boring and specific: a catalog structured so the model can trust it, and the right content on the sources it reads.\n2. Existing tools were built for SaaS. They hand you a score and stop. That playbook breaks the moment you have 5,000 SKUs and variants. A brand and retailers unit of AEO is the catalog, not a homepage.\n\n**The Solution:** Our solution is simple. First, we run a full audit of how you show up across AI search. Second, we build your roadmap. Lastly, we optimize your product catalog and create the content that gets you recommended. After 30 days, we tend to see a 5x increase in revenue.\n\n**Our Ask:** Try a free trial of our tool [here](https://wild-card.ai/). And if you know any brands, retailers, or agencies, an intro would be great!: [kaushik@wild-card.ai](mailto:kaushik@wild-card.ai)  \n\n**About Me:** Kaushik Mahorker (Founder &amp; CEO). Previously, I was an Engineering Manager at Scale AI, where I led the GenAI Allocation team and built the ecommerce enrichment engine that structured 2.4M attributes across 400K SKUs, helping close $15M+ in retail and marketplace contracts.\n\n![uploaded image](/media/?type=post&id=106605&key=user_uploads/2074409/ca4bbe7c-d2fd-428f-8c09-f0fc965f7c9d)\n\n",
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        "full_name": "Dev Jain",
        "title": "Founder/CTO",
        "founder_bio": "CEO of Corsair. We're building the TypeScript integration framework. \n\nBefore launching Corsair, I was a software engineer at Curri (S19). I went to UT Austin and studied mechanical engineering & economics 🤘",
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        "id": 112352,
        "title": "Corsair: Connect your users to their apps",
        "tagline": "10k GitHub stars, 200+ integrations: Open-source integration layer for agents and product UIs.",
        "body": "Corsair is a fully-featured product integration platform with a seamless DX. Build anything, from an agent working across all your integrations to a multi-tenant dashboard for your users to connect to anything.\n\n[Website](https://corsair.dev) | [Discord](https://discord.gg/uNgCP3mSzU) | [X](https://x.com/corsairdotdev) | [Cal](https://cal.com/dev-jain-ar3ec6/15min)\n\nMost agent integration tools are MCP-only. **Corsair is built on a REST API**, so the same layer works for agents, backend jobs, and the dashboards your customers actually use.\n\nClosed integration platforms keep your users' tokens on infrastructure you can't inspect or leave. **Corsair is open source**. Self-host it, or use Corsair Hub if you want us to handle OAuth and webhooks. Your data remains yours either way.\n\nThe more third-party APIs your product touches, the more glue code you write. **Corsair gives every integration the same syntax**, and we maintain the adapters behind it.\n\n**Here's how we use Corsair internally**: a GitHub clone wired up through the Corsair SDK. The UI was vibe-coded in an afternoon. All of it runs on the Corsair SDK.\n\n<https://youtu.be/fflIzDutxsc>\n\n**How we can help you**: If you're stuck writing integrations or your current provider holds your customers' data on servers you don't control, reach out. We'll help you set up Corsair, open a Slack channel for support, and build any integrations you're missing.\n\n[Get started at corsair.dev →](https://corsair.dev)\n\n![uploaded image](/media/?type=post&id=112352&key=user_uploads/932430/529a4c94-03c1-4f1a-aa35-eceb39742401)\n\n",
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        "id": 96572,
        "title": "Senior Software/Frontend Engineer @ Germany Office",
        "url": "https://www.ycombinator.com/companies/dalus/jobs/5IDmKJt-senior-software-frontend-engineer-germany-office",
        "location": "San Francisco, CA, US / Los Angeles, CA, US / Melbourne, VIC, AU / Munich, BY, DE / Remote (DE)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Frontend",
        "salary_range": "€70K - €90K EUR",
        "equity_range": "0.20% - 1.00%",
        "experience": "6+ years",
        "visa": "US citizenship/visa not required",
        "skills": [
          "React"
        ]
      },
      {
        "id": 99648,
        "title": "GTM Intern ",
        "url": "https://www.ycombinator.com/companies/dalus/jobs/CqZr2It-gtm-intern",
        "location": "Munich, BY, DE / Munich, Bavaria, DE / San Francisco, CA, US / Melbourne, VIC, AU / Melbourne, Victoria, AU / Remote",
        "type": "Internship",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$18 - $25 / hourly",
        "equity_range": "",
        "experience": null,
        "visa": "US citizenship/visa not required",
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      {
        "id": 111591,
        "title": "Senior Software Engineer - PLM/CAD Integrations",
        "url": "https://www.ycombinator.com/companies/dalus/jobs/sZ6myaQ-senior-software-engineer-plm-cad-integrations",
        "location": "San Francisco, CA, US / Munich, BY, DE / Munich, Bavaria, DE / Melbourne, VIC, AU / Melbourne, Victoria, AU / Remote",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Backend",
        "salary_range": "$80K - $170K",
        "equity_range": "",
        "experience": "4+ years",
        "visa": "US citizenship/visa not required",
        "skills": [
          "Python",
          "TypeScript"
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    "launches": [
      {
        "id": 87642,
        "title": "Dalus - Hardware system design software powered by AI",
        "tagline": "Dalus helps engineers create system models of complex hardware in a day instead of weeks.",
        "body": "# **TL;DR**\n\nDalus is building the next generation of hardware system design software powered by AI. Our goal is to make building hardware as fast and iterative as software development.\n\n🔧 Use Dalus to model complex hardware systems with ease\\\n🛠 Collaborate in real-time with a single source of truth for your system designs\\\n🤖 Leverage AI to automate tedious updates and generate insights in seconds\\\n🚀 Verify system requirements within seconds\n\nWe started working together on Dalus in spring 2024 after Eliot quit his job at Aerojet Rocketdyne (L3Harris) where he worked as a test/systems engineer. He experienced firsthand how silos and poor communication in hardware development reduced the productivity and efficiencies of the teams he worked at.\n\n<https://youtu.be/mTbpqLymL3U>\n\n# **Our Hypothesis:**\n\nHardware development in industries like aerospace, defense, and automotive is slow, siloed, and error-prone due to poorly maintained documentation. \n\nTraditional document-based approaches to systems engineering are outdated and fail to keep up with today’s agile hardware teams. Dalus provides an **intuitive model-based systems engineering (MBSE) platform** that centralizes all system requirements, functions, architectures, and constraints into one living digital model.\n\n## **The Need for Model-Based Systems Engineering (MBSE)**\n\nTraditional systems engineering relies heavily on scattered documents and manual processes, leading to inefficiencies and costly mistakes. MBSE addresses these issues by:\n\n1. Creating a single source of truth\n2. Enabling faster design-test-iterate cycles\n3. Catching errors early in the development process\n4. Supporting rapid changes in hardware designs\n\n   ![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXf1aozPCrqSOY6AuEN-7_b5CU_u4_uS_RDAqkgg0GqlDyxBxuRak3KvRGYzFkCGd3LTq1Qdqkkm2llPcI0W__yXQBIDLvtBCMorZtaFdFWJu57VDbxaqV-lVZG8q4K8kN0UdBw7?key=81YZe2YCcaHvmEQ0BoEuPJUw)\n\n\n# **Industry Focus:**\n\nDalus is tailored for complex engineering systems in industries such as aerospace, defense, energy, and automotive.\n\nWe love working with companies tackling complex engineering systems, whether they be startups just getting their feet wet or large organizations like Israel Aerospace Industries (Our design partner and biggest aerospace/defense company from Israel)\n\n## **Dalus' Approach**\n\nDalus differentiates itself from existing solutions by offering:\n\n1. Cloud-based software that's intuitive and reasonably priced\n2. Seamless integration with existing design and simulation tools\n3. AI-driven capabilities to automate tedious tasks\n4. A focus on supporting agile hardware teams in fast-changing environments\n\n   ![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXfQfTZt8sjAxYlpkO4E0KeKvZa2PWHcsY2P9PaLI33gn_rJ4npYq3uphNlkIqWzxvSrJdZ_lfOUzibP8vaNyVl_-jhrZElnDj18gonT6d0ZLj5TQJDgAeio6ehaG5gyB52iMV22Tg?key=81YZe2YCcaHvmEQ0BoEuPJUw)\n\n\n## **Future Developments**\n\nDalus is actively working on new features based on user feedback, including:\n\n* Native integrations with physical simulation tools\n* Version control\n* Creating the best AI on the market for hardware systems engineering\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXfUWnYnlL_4HOjcu8QbXJcZLBWWJXG9yc11C2SFnUWGsMyBqBYpmwp1l5iFoIzUvsNpIwIl5NYuLk8RnjAMBEdljMctJFHHG5wrVek7Gy0typhqwOlih0fs5rYLrcdsaA9-bvipJg?key=81YZe2YCcaHvmEQ0BoEuPJUw)\n\n# **The Ask**\n\n* If you know someone who is working on complex hardware systems, send them to [dalus.io](http://dalus.io)\n\nRead more on why we started Dalus: <https://dalus.io/articles/why-dalus>\n\n\\\nReach us at [sebastian@dalus.io](mailto:sebastian@dalus.io)\n\n![uploaded image](/media/?type=post&id=87642&key=user_uploads/460293/f3f042a9-9dec-4835-a08c-6d95e82d7304)\n\n",
        "url": "https://www.ycombinator.com/launches/Mna-dalus-hardware-system-design-software-powered-by-ai",
        "votes": 10,
        "created_at": "2025-02-13T15:36:15.123Z"
      }
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  {
    "id": 30343,
    "name": "Cedar",
    "slug": "cedar",
    "former_names": [
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      "lawyai (name in progress)",
      "GraphIQal"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/8d689d59276a36e33100281dbe98a74bcaf59a06.png",
    "website": "https://mail.cedarcopilot.com/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Cedar helps the fastest growing GTM teams ramp up new reps faster & spread top rep playbook throughout the team. AE's at Cursor, Corgi, Pylon, and Warp use Cedar to save 75% of admin time on CRM updates, follow-ups, and deal strategy. \r\n\r\nBacked by YC with an ex-Figma, Notion, and Intuit team, Cedar was built by spending hundreds of hours with the best AE's in industry – we've built a playbook for the fastest growing teams and founders ramping up sales, and we'll use it to automate the busy work so you can sell more, better.",
    "one_liner": "Execute the best sales playbook in industry",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1739293549,
    "tags": [
      "Sales",
      "Sales Enablement",
      "CRM",
      "Email"
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    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2025",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
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    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": [
      {
        "question": "What is your long-term vision? If you truly succeed, what will be different about the world?",
        "answer": "We're going to make all software agentic. Currently we're adding an AI native copilot that's deeply understanding users and products at scale, and generating instructions for users. These instructions are just the first step for executing tasks for the user directly and autonomously."
      }
    ],
    "url": "https://www.ycombinator.com/companies/cedar",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/cedar.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/cedarcopilot",
    "x_url": "",
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    "primary_partner": {
      "name": "Gustaf Alstromer",
      "url": "https://www.ycombinator.com/people/gustaf-alstromer"
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    "founders": [
      {
        "user_id": 561766,
        "full_name": "Jesse Li",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder & CEO at Cedar. \n\nB.S. in Computer Science at Georgia Institute of Technology.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/jesseli751",
        "x_url": "https://x.com/fish_in_a_pool",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a47b7c8b3340e195a7728c8502a1900c8307a5a9.jpg"
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      {
        "user_id": 1652458,
        "full_name": "Isabelle Ilyia",
        "title": "Founder/CTO",
        "founder_bio": "CTO @ Cedar (YC W25). Previous software engineer @ Figma, Notion, and LinkedIn.\n\nStudied Computer Science @ Georgia Tech.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/isabelle-i ",
        "x_url": "https://x.com/isabelleilyia",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5eac10f537c8b9f14b78bfabd0ec645d708071ac.jpg"
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    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 87967,
        "title": "Cedar 🌲 In-product AI copilot & PMF analytics for any app",
        "tagline": "Cedar is an AI copilot for any app. Imagine the founders themselves being behind every user’s screen: actively guiding them, answering product how-to’s, and upselling.",
        "body": "Hi everyone! It’s Jesse & Isabelle from Cedar :)\n\n### How do we productise conversion optimisation?\n\nIn business terms, we do two things:\n\n1. We let you understand your user’s stories at scale. What do they want from your solution? What are they specifically trying to do on your software? Who are they?\n   1. We do this by pulling your existing analytics and adding a thin layer of our own. You can re-target churned users when a relevant feature comes out, inform product roadmaps, and most importantly use it to find PMF.\n\n      ![uploaded image](/media/?type=post&id=87967&key=user_uploads/561766/7f7d6dc9-b759-454c-a897-e94b5dd76197)\n\n2. We use those analytics to increase conversion & retention, from pre-sale to activation/onboarding and beyond.\n   1. Create individualised sales materials and activation flows to bring more users to their magic moment.\n   2. Instead of not knowing how to do X and being blocked until customer support replies (or worse, churning), Cedar instantly responds.\n\n      ![uploaded image](/media/?type=post&id=87967&key=user_uploads/561766/aa9b2e93-ed62-469a-9f49-c1e4a1de8596)\n\n\nThink of a general-use product like Notion. Imagine if every user saw a landing page that explains **exactly** how Notion helps them reach their goals. When they sign up, an activation flow walks them through solving a relevant problem they face every day. Then, as they use the app, an AI copilot makes them a power user, without the need to leave the app.\n\n### Demo Video\n\n<https://youtu.be/w73bNTbAjDg>\n\n### Our story\n\nIn more personal terms, we find it deeply wrong that people make awesome, valuable software that doesn’t reach people simply because of things like UI/UX or messaging. We turn every user into a power user - with the retention and promoter scores that come with it.\n\nWhile AI is scaling engineering teams, we’re going to be the growth and customer success team in one product, with one centralized source of user knowledge.\n\nJesse worked at Intuit, learning the science and fun of making boring software (don’t tell TurboTax) that converts and serves customers of all tech literacy levels.\n\nIsabelle worked at Figma and Notion, learning the struggles of getting users to effectively use powerful yet complex products and the GTM strategies to reach them.\n\n![uploaded image](/media/?type=post&id=87967&key=user_uploads/561766/5e1e1044-3d46-4999-a6d8-d6ee4c3713c8)\n\n### Ask:\n\nIf you’re interested, or know any companies interested in:\n\n* Activation Conversion: Increasing % of users who get relevant value from your product at least once.\n* User Intent Analytics: Understanding what are your users trying to do, when and why they churn to intervene at the right moment, and re-engaging users based on criteria (e.g target users who churned due to missing features once implemented)\n* Flattening learning curves: Value is useless if your customer doesn’t know how to effectively use your product to get it (both pre and post-sale).\n\nPlease reach out! Email us at [founders@cedar.law](mailto:founders@cedar.law), we’re already working with companies from seed to series A and would love to help more, whether with just a chat or a full partnership :)",
        "url": "https://www.ycombinator.com/launches/Msp-cedar-in-product-ai-copilot-pmf-analytics-for-any-app",
        "votes": 46,
        "created_at": "2025-02-25T18:04:40.924Z"
      }
    ]
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  {
    "id": 30345,
    "name": "Codevisor",
    "slug": "codevisor",
    "former_names": [
      "851 Inc.",
      "851",
      "AI Emojis",
      "emojis",
      "emojis.com",
      "Lightbox",
      "emojis.com",
      "Tee Time Tommy"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/36fd79daacb53819fc86fd68b564556a5bd51a64.png",
    "website": "https://www.codevisor.dev",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Codevisor is an open-source native macOS app for agentic engineering. Run Claude Code, Codex, Pi, and any ACP-compatible coding agent on your own machines in one place.\r\n\r\nCodevisor brings agent chats, projects, and an integrated terminal into a single workspace. Connect remote Macs or Linux servers to run agents where your code lives and keep working across machines.",
    "one_liner": "The fastest native app for agentic engineering.",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1740542821,
    "tags": [
      "Developer Tools",
      "Open Source",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2025",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/codevisor",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/codevisor.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/851-inc",
    "x_url": "https://x.com/codevisor",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/emojis-com",
    "github_url": "https://github.com/851-labs",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/36fd79daacb53819fc86fd68b564556a5bd51a64.png",
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    "company_photos": [
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    ],
    "primary_partner": {
      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
    },
    "founders": [
      {
        "user_id": 688130,
        "full_name": "Alexandru Turcanu",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder and CEO at emojis.com. Previously, led posts initiative at Campsite (acq by Notion).",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/pondorasti",
        "x_url": "https://x.com/pondorasti",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4f39ed91df05d568170e7121e7497af5653ec5b5.jpg"
      },
      {
        "user_id": 1750881,
        "full_name": "Dylan Player",
        "title": "Founder/CTO",
        "founder_bio": "Co-Founder & CTO at emojis.com",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/dylan-player",
        "x_url": "https://x.com/dylanplayer",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7f45d723627f325740a69053cae02ad64844e3af.jpg"
      }
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    "launches": [
      {
        "id": 93587,
        "title": "Lightbox - Cursor for Content Creation",
        "tagline": "From idea to brand, merch, or UGC — all in one AI-native flow.",
        "body": "[_Lightbox_](https://www.lightbox.sh/) is a new brand and product, previously known as [emojis.com](http://emojis.com).\n\nhttps://youtu.be/PC65mXUoXvM\n\nPipeline: https://www.lightbox.sh/pipeline/apJhpW4fBMa\n\n### Story\n\nLightbox came out of our own frustration of duct taping AI tools together. The GenAI space for image/video models is a complete s\\*\\*t show, always chaining together different models and jumping across tools.\n\nWe had had enough of it, so we went to the drawing board, and we asked ourselves one question: What would an AI native creative tool look like, if built from the ground up?\n\nToday, we’re launching our first experiment — Pipelines. All batteries included workflow builder for generative AI. The goal is _an **infinitely flexible tool for your creative process**_.\n\nIf you think that’s all we’re building…you would be wrong. We’re too naive to stop here. There are two more experiments cooking in order to complete our vision for the creative suite.\n\nFor the time being, here’s Pipelines in action:\n\n### Agentic and Conversational\n\nLightbox works just like Cursor, use chat to explain your changes and watch it go brrrr. Here’s an example of it generating testimonial videos about Salesforce.\n\n![](https://attic.sh/_static/yc/bf-lightbox-salesforce-testimonial.gif)\n\nPipeline: https://www.lightbox.sh/pipeline/cBb1SMxX1fv\n\n### Product Photo Shoots\n\nChoose a model, upload your merch (i.e., hoodie), and watch the pipeline generate a photoshoot for you.\n\n![](https://attic.sh/_static/yc/bf-lightbox-photoshoot.gif)\n\nPipeline: https://www.lightbox.sh/pipeline/EKbin5Y96TO\n\n### Youtube Face Reactions\n\nIn need of face reactions for YouTube thumbnails? There’s a Pipelines for that!\n\n![](https://attic.sh/_static/yc/bf-lightbox-youtube-face-reactions.gif)\n\nPipeline: https://www.lightbox.sh/pipeline/4nrRoxZifJ2\n\n### How can you help?\n\nIf any of the demos got your gears running, give Lightbox a try! You can use promo code YC10 for $10 worth of credits. Would love to hear your thoughts and see if we can help.\n\nWe’re also looking for businesses and creative agencies that want to automate design work. Anything from photo shoots, ads, UGC, and in between.\n\nYou can reach us at [founders@lightbox.sh](https://mailto:founders@lightbox.sh), or send us a message directly on [X/Twitter](https://x.com/pondorasti).",
        "url": "https://www.ycombinator.com/launches/OLT-lightbox-cursor-for-content-creation",
        "votes": 20,
        "created_at": "2025-09-04T19:23:28.403Z"
      },
      {
        "id": 88060,
        "title": "emojis.com - AI Copilot for graphic design",
        "tagline": "We allow small businesses to easily create brand assets, like logos and icons, with AI",
        "body": "# \n\n### TL;DR\n\nOur mission is to give small businesses an AI Graphic Designer to help them create a brand and identity without having to pay 💰💰💰 of dollars hire someone.\n\n### Backstory\n\nBack in October, 2023, we’ve tweeted about a little side project for creating emojis with AI that went on to be called [**“_best app of 2023”_**](https://x.com/rauchg/status/1709318615911317621).\n\nOver the course of the following year, we’ve turned this idea into a full fledged consumer app:\n\n* launched [iOS](https://apps.apple.com/us/app/ai-emojis-keyboard/id6468916301) app and became the [**#1 app in Graphic and Design**](https://x.com/pondorasti/status/1855326867605340553)\n* deeply integrated with messaging platforms like iMessage and WhatsApp\n* and grew to 2.5M users that generated over 5M emojis\n\n![uploaded image](/media/?type=post&id=88060&key=user_uploads/688130/13e428c7-74f3-4ba8-8d9b-024c79aa381e)\n\n### Learnings / The Problem\n\nWhat we’ve learned from our consumer app is that majority of our power users are actually closer to business use cases:\n\n* **small businesses** and **indie hackers** using ai emojis for website icons\n* **influencers** and **creators** using ai emojis for social media posts and thumbnails\n* **teachers** and **students** using ai emojis for courses and assignments\n\n![uploaded image](/media/?type=post&id=88060&key=user_uploads/688130/3f699bb3-9d89-4774-b5fd-ed81d43570be)\n\n### What’s next? / The Solution\n\nWe’re doubling down on providing value for small businesses and expanding to a suite of models that can become your one stop shop for graphic design needs:\n\n* ai **illustrations** for websites and blogs\n* ai **stickers** for your business\n* consistent ai **characters** and **mascots** for your brand\n\nEvery company should be able to have their own “octocat” brand identity, and we’re making that a reality with AI.\n\n![demo](https://attic.sh/_static/yc/bf-v2-imagine-demo.gif)\n\n### Our Ask\n\nIf you (or anyone you know) are looking for an AI Copilot to help create brand assets like icons, illustrations, and stickers, we’d love to chat and see how we can help!\n\nYou can reach us at [founders@emojis.com](mailto:founders@emojis.com), or send us a message directly on [X/Twitter](https://x.com/pondorasti).\n\n### The Team\n\n**Dylan Player** - Co-Founder & CTO at [emojis.com](http://emojis.com). Former software engineer at Shopify, building new lending products and scaling to over $10B in lending volume.\n\n**Alexandru Turcanu** - Co-founder and CEO at [emojis.com](http://emojis.com). Previously, led posts initiative at Campsite (acq by Notion).\n\n![uploaded image](/media/?type=post&id=88060&key=user_uploads/688130/f3b1e7e1-40c5-4f13-b50f-fd3184e3f7ab)\n\n",
        "url": "https://www.ycombinator.com/launches/MuK-emojis-com-ai-copilot-for-graphic-design",
        "votes": 17,
        "created_at": "2025-02-26T18:07:26.392Z"
      }
    ]
  },
  {
    "id": 30350,
    "name": "TrainLoop",
    "slug": "trainloop",
    "former_names": [
      "Phoenix"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4fad47355d59021d6d855bc4b2dc95cbc0ef2f1a.png",
    "website": "http://trainloop.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "TrainLoop makes it effortless for developers to supercharge LLM performance through reinforcement learning.",
    "one_liner": "Reasoning Fine-Tuning",
    "team_size": 6,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1738700190,
    "tags": [
      "Developer Tools",
      "Generative AI",
      "Reinforcement Learning"
    ],
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        "salary_range": "₹1.5M - ₹3M INR",
        "equity_range": "0.01% - 0.03%",
        "experience": "3+ years",
        "visa": "US citizenship/visa not required",
        "skills": []
      }
    ],
    "news": [
      {
        "title": "10 Most Exciting AI Agent Startups at YC Demo Day Spring Cohort 2025 - Business Insider",
        "url": "https://www.businessinsider.com/y-combinator-yc-demo-day-spring-ai-agent-startups-2025-6",
        "date": "Jun 11, 2025"
      }
    ],
    "launches": [
      {
        "id": 90589,
        "title": "Plexe - Build ML models from a prompt",
        "tagline": "Plexe is an open-source agent that turns natural language task descriptions into trained machine learning models.",
        "body": "We’re Vaibhav and Marcello. We’re building Plexe, an open-source agent that turns natural language task descriptions into trained ML models.\n\nhttps://youtu.be/CwNX0aU9MsE\n\n## **🤔 1. Problem**\n\nLots of great use cases for ML models in businesses never materialize because ML projects are messy and convoluted. You spend months finding the data, cleaning it, experimenting with models and deploying them to production, only to find out that the project has been binned due to taking so long. At a previous employer, we witnessed a team of 10 ML engineers spend 2 years and $3M building models for a project that never saw the light of day. \n\nThere are several tools for “automating” ML, but it still takes teams of ML experts to actually productionize something of value. And we can’t keep throwing LLMs at every ML problem. Why use a generic 10B parameter language model, if a logistic regression trained on your data could do the job better?\n\n## **✅ 2. Solution**\n\nStep 1: Connect your data sources\\\nStep 2: Describe your problem statement\\\nStep 3: Use the deployed model via API\n\nhttps://youtu.be/zByvH0wTSuE\n\n## **🚀 3. How does it work?**\n\nPlexe uses a self-correcting team of ML engineering agents to research, experiment, evaluate, refine, and deploy the best performing model over an API endpoint. It connects to data sources, discovering relevant fields, and autonomously building the model. Think of it like your own ML helper helping you go from idea to deployed models 10x faster.\n\nhttps://youtu.be/bUwCSglhcXY\n\n## **👋 4. Team**\n\n[Vaibhav Dubey](https://bookface.ycombinator.com/user/2260416) (ex-Proofpoint, Expedia, Imperial College London) and [Marcello De Bernardi](https://bookface.ycombinator.com/user/2337737) (ex-AWS, Expedia, Oxford) met 6 years ago while building a chatbot that served 9+ million customers of a large bank. Since then, they’ve built enterprise-scale ML solutions that serve billions of predictions per day for millions of users worldwide.\n\n![uploaded image](/media/?type=post&id=90589&key=user_uploads/2260416/4e5a0513-e013-4adc-9520-ebde07c44981)\n\n## **🙏 5. Our ask**\n\n* We’d love to get in touch with any companies that have a lot of data but have not been able to build ML features on top of them!\n* If you’re an individual who believes that the future of ML development is autonomous and open source, check out our agent: https://github.com/plexe-ai/plexe\n\nGet in touch with us: [founders@plexe.ai](mailto:founders@plexe.ai) ",
        "url": "https://www.ycombinator.com/launches/NZ7-plexe-build-ml-models-from-a-prompt",
        "votes": 67,
        "created_at": "2025-05-21T01:44:48.117Z"
      }
    ]
  },
  {
    "id": 30404,
    "name": "Vybe",
    "slug": "vybe",
    "former_names": [
      "Nestor AI"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/5449afa368ba0f8d1d55813d6659160e8a037aa3.png",
    "website": "https://www.vybe.build",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "We're 2 repeat YC founders. We founded Plato (W16, sold to Coda) and Wolfia (S22). Quang lead Product/GTM for Coda Solutions and Fabien is ex-SWE at Meta and lead Engineering at Wealthfront before.\r\n\r\nWe’re building Vybe: \"Lovable for internal apps\". We come with pre-built building blocks: Integrations (Gmail, Gcal, Github, Jira, etc.), SSO and AI tools (Websearch, Summarization etc.) so anyone in a company can build and launch internal AI-powered apps.\r\n\r\nVibe coding is dramatically lowering the barrier for non-technical users to create full web apps. Lovable, Replit, Bolt, Google, Canva, Figma all launched their vibe-coding platforms. People love them. They're great for prototyping, but it's difficult to roll out inside a company for internal use cases for those reasons: \r\n\r\n1. Data: If you want to connect your existing data (e.g. Salesforce, Gmail, Jira), you'd need to rebuild the API auth, pagination, etc. \r\n\r\n2. SSO: If you build 20 apps, you'll have 20 different logins\r\n\r\n3. Security: AI-built apps have massive risk of exposing data, especially if built by non developers\r\n\r\nSo companies are stuck in the old world: clunky spreadsheets, rigid SaaS solutions or complex no-code tools.\r\n\r\nTime to build! ",
    "one_liner": "Secure internal apps. Built by AI in seconds. Powered by your data.",
    "team_size": 8,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1745390836,
    "tags": [],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Spring 2025",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/vybe",
    "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/vybe.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/107383717/",
    "x_url": "https://x.com/vybe_build",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/5449afa368ba0f8d1d55813d6659160e8a037aa3.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
    },
    "founders": [
      {
        "user_id": 3335,
        "full_name": "Quang Hoang",
        "title": "Founder/CEO",
        "founder_bio": "2X YC Founder || CEO/Cofounder of Vybe (X25) || ex-CEO/Cofounder of Plato (W16, acquired by Coda)\n\nAt Plato, we were building a mentorship platform for engineering leaders.\n- We grew to 5M of ARR selling to CTOs/VPs of Engineering\n- We worked with notable customers like Airbnb, Stripe, Coinbase, Slack, Twilio, etc.\n- We grew a community of 30k+ engineering leaders\n- We raised $23M in total with Slack, Fundersclub, S28 Capital, SaaSTR Fund, etc. and got to a team of 70 people",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/pub/quang-hoang/37/abb/2b1",
        "x_url": "https://x.com/qhoang09",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f8663e722f164e8e05b3641d0817a627797eab1d.jpg"
      },
      {
        "user_id": 13513,
        "full_name": "Fabien Devos",
        "title": "Founder/CTO",
        "founder_bio": "Former Director of Engineering at Wealthfront, Ex-Facebook, creator of Hacked app (mobile coding game with 1M downloads).",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/fabiendevos",
        "x_url": "https://twitter.com/Fabien_Devos",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e07e66d5281559995639a64dd7940bf16df8e0af.jpg"
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    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 90606,
        "title": "Vybe - Lovable for internal apps",
        "tagline": "Pre-built with building blocks: Integrations, SSO, and AI tools so anyone in a company can build and launch internal apps.",
        "body": "Fabien (Wolfia, S22) and myself (Plato, W16), are back to building again and today, we’re excited to share what we've been cooking for the past few months! And we’re part of the current batch!\n\nWe’re building a Lovable for internal apps. We come with pre-built building blocks: Integrations, SSO, and AI tools so anyone in a company can build and launch internal apps.\n\nhttps://youtu.be/jaB3EnuU_cI\n\nI included 5-6 other examples of things I built to run Vybe on vybe below :)\n\n# The unsolved problem:\n\nFast‑growing teams drown in \\_glue work\\_—onboarding trackers, launch calendars, status bots, one‑off scripts. Each steals engineering time, rots when its owner leaves, and derails sprints.\n\nIt leaves companies with three bad options:\n\n* Rigid enterprise SaaS – inflexible, forces your process to fit the tool.\n* Spreadsheets & docs – endless copy‑paste, no live data, fragile at scale.\n* DIY glue & drag‑and‑drop no‑code – a tangle of scripts and widgets that collapse when owners leave.\n\n# **Why current vibe coding tools aren’t enough:**\n\nVibe coding is dramatically lowering the barrier for non-technical users to create full web apps. Lovable, Replit, Bolt, Google, Canva, Figma all launched their vibe-coding platforms. People love them. They're great for prototyping, but it's difficult to roll out inside a company for internal use cases for those reasons:\n\n* Data: If you want to connect your existing data (e.g. Salesforce, Gmail, Jira), you'd need to rebuild the API auth, pagination, etc.\n* SSO: If you build 20 apps, you'll have 20 different logins…\n* Security: AI-built apps have the massive risk of exposing data, especially if built by non-developers\n\nCursor and Windsurf are not adapted either. They’re built for devs, hard to use for non-technical folks. My Head of HR doesn’t know how to deploy an app in Netlify or Vercel.\n\n# **Why old no-code tools are solutions of the past:**\n\n* Airtable / Retool / Coda: No‑code and low‑code platforms showed you can build dashboards faster than hand‑coding React—but you're still dragging rectangles, hunting for SQL, and rebuilding the same CRUD table for the hundredth time.\n* Large‑language models have changed the game. Code‑gen IDEs already write production‑grade functions from chat—so why are we still moving boxes to connect Salesforce to a launch‑approval form?\n\n**We’d love your help:**\n\n1. Companies: Design partners: Pick a painful process internally in your company, let us rebuild it in a more robust way.\n2. Users: -&gt; Join the waitlist: https://www.vybe.build/ and we’ll accept you as fast as we can! Comment \"waitlist\" or re-post, and we'll bump you to the top of the list!\n\nHere are some nice examples of things I built on Vybe:\n\n**A daily briefer of my day,** an AI is doing a web search on every single person I’m meeting every day:\n\n![uploaded image](/media/?type=post&id=90606&key=user_uploads/3335/f071030a-e15f-4df2-9ae3-6f09d2add985)\n\n![uploaded image](/media/?type=post&id=90606&key=user_uploads/3335/2789a7da-2558-434e-abc2-8836d9a4f205)\n\n**A weekly goals tracker** with a count down until YC demo day:\n\n![uploaded image](/media/?type=post&id=90606&key=user_uploads/3335/9296e031-ab0a-4b39-82cd-9905c961f08d)\n\n**Our backlog/roadmap** of things to ship:\n\n![uploaded image](/media/?type=post&id=90606&key=user_uploads/3335/7a626545-91b5-4258-8dd9-6db0dc33c2ae)\n\n**Our DB Admin** fed by our production database (postgres) built in 10 mins:\n\n![uploaded image](/media/?type=post&id=90606&key=user_uploads/3335/aa9494e4-89f9-4ebd-b005-2b9a8b8b2c3f)\n\n**A simple to-do** i created with routines, timer and link to my tech backlog so i can easily add tasks to myself from the roadmap\n\n![uploaded image](/media/?type=post&id=90606&key=user_uploads/3335/75b7bfc7-baa9-4198-8613-a46b2f7434dd)\n\n\\*\\*A nice CRM (\\*\\*no, i don’t use Salesforce, Hubspot or any other CRM) that is connected to my postgres so i can monitor deals and usages at the same place\n\n![uploaded image](/media/?type=post&id=90606&key=user_uploads/3335/36acd4ee-8bb7-495d-b1a0-802346cf57e6)\n\nAnd check tens of other examples: https://www.vybe.build/examples\n\nIt’s time to build 💪 Join the waitlist: https://www.vybe.build/ and we’ll accept you as fast as we can! Comment \"waitlist\" and we'll bump you to the top of the list!\n\n![uploaded image](/media/?type=post&id=90606&key=user_uploads/3335/e62cb1d4-16a8-479d-9fee-e0374b653acf)\n\n",
        "url": "https://www.ycombinator.com/launches/NZO-vybe-lovable-for-internal-apps",
        "votes": 28,
        "created_at": "2025-05-21T17:35:49.208Z"
      }
    ]
  },
  {
    "id": 30411,
    "name": "cubic",
    "slug": "cubic",
    "former_names": [
      "mrge"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/8d4b717bddf685ac3a5f54298f79381c741a52c3.png",
    "website": "https://cubic.dev/",
    "all_locations": "London, England, United Kingdom",
    "long_description": "Code review is a major bottleneck for software teams, and the rise of AI-generated code is making the problem worse. Reviewing large volumes of code slows devs down, and increases the chances of bugs slipping through.\r\n\r\nThat's why we're building cubic: an intelligent code review platform that helps devs merge PRs 28% faster.\r\n\r\nHow? \r\n- When you open a PR, cubic automatically reviews it. It learns from your codebase's patterns, points out bugs, suggesting fixes, and frees you from low-level review tasks.\r\n- You then jump into the cubic platform, which is designed to optimize how humans review code. For example, file changes are organized in a logical order instead of alphabetical, and cubic generates diagrams of architecture changes.",
    "one_liner": "AI-powered code review platform",
    "team_size": 6,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1743248262,
    "tags": [
      "Developer Tools"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Spring 2025",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United Kingdom",
      "Europe"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/cubic",
    "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/cubic.json",
    "year_founded": 2025,
    "city": "London",
    "country": "GB",
    "linkedin_url": "https://www.linkedin.com/company/cubic-dev/",
    "x_url": "https://x.com/cubic_dev_",
    "fb_url": null,
    "cb_url": null,
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    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/8d4b717bddf685ac3a5f54298f79381c741a52c3.png",
    "app_video_url": null,
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    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
    },
    "founders": [
      {
        "user_id": 1418465,
        "full_name": "Paul Sanglé-Ferrière",
        "title": "Founder/CEO",
        "founder_bio": "3x founder, previously an ML engineer and a product manager at Tessian. ",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/paulsf",
        "x_url": "https://x.com/NeuralPaul",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a8b20599d6740cc9195a9f4da7c9f97ff2184e83.jpg"
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    ],
    "jobs": [
      {
        "id": 77373,
        "title": "Founding Product Engineer @ cubic (YC X25) ",
        "url": "https://www.ycombinator.com/companies/cubic/jobs/ZmenJR0-founding-product-engineer-cubic-yc-x25",
        "location": "London, England, GB",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "£70K - £120K GBP",
        "equity_range": "0.10% - 1.00%",
        "experience": "6+ years",
        "visa": "US citizenship/visa not required",
        "skills": []
      }
    ],
    "news": [],
    "launches": [
      {
        "id": 90581,
        "title": "cubic – Cursor for code review",
        "tagline": "cubic helps teams like cal.com and n8n ship 28% faster",
        "body": "**🎯 TL;DR**\n\ncubic is an AI-powered code review platform that automatically reviews PRs and gives human reviewers superpowers.\n\nIt helps teams like [**cal.com**](http://cal.com), **n8n**, and the **Linux Foundation** ship code 28% faster.\n\nhttps://youtu.be/7bzIJYy0Nfw\n\nHey! 👋 We’re Allis and Paul – founders of cubic.\n\nWe’re building cubic – an AI code review platform to help teams ship code faster with fewer bugs.\n\n[🚀 See it in action for cal.com here](https://github.com/calcom/cal.com/pull/20771)\n\n🎁 **Launch deal**\n\nIf you’re a developer, and you feel like code reviews are slowing you down + bugs slip through, give cubic a try.\n\nIt’s free for 2 weeks, and you’ll get an extra 30% off for 2 months with the code: _YCLAUNCH_\n\n[**Just sign up with your Github account to get started!**](http://cubic.dev/home)\n\n**⭐️ Why did we start cubic?**\n\nWe’re engineers who faced this problem when we worked together in the past. As we adopted more AI code gen tools, code review and ensuring quality quickly became our biggest bottleneck.\n\nWe had more PRs to review, subtle AI-written bugs slipped in, and we (humans) found ourselves rubber-stamping PRs without deeply understanding the changes.\n\n**👷 We’re building cubic to help solve that. Here’s how it works:**\n\n1. Connect your GitHub repo via our Github app in two clicks\n2. AI review: When you open a PR, our AI reviews your changes directly in a secure container. It has context into not just that PR, but your whole codebase, so it can pick up patterns and leave comments directly on changed lines. Once the review is done, the sandbox is torn down and your code deleted.\n3. Human-friendly review workflow: Jump into our web (or desktop) app (it’s like Linear but for PRs). Changes are grouped logically (not alphabetically), with important diffs highlighted, visualized, and ready for faster human review.\n\n💻 The AI reviewer works a bit like Cursor in the sense that it navigates your codebase using the same tools a developer would—like jumping to definitions or grepping through code.\n\n⚡️ The platform itself focuses entirely on making _human_ code reviews easier. A big inspiration came from productivity-focused apps like Linear or Superhuman, products that show just how much thoughtful design can impact everyday workflows. We wanted to bring that same feeling to code review.\n\nThat’s one reason we built a desktop app. It allowed us to deliver a more polished experience, complete with keyboard shortcuts and a snappy interface.\n\nWe think the future of coding isn’t about AI replacing humans—it’s about giving us better tools to quickly understand high-level changes, abstracting more and more of the code itself. As code volume continues to increase, this shift is going to become increasingly important.\n\n![uploaded image](/media/?type=post&id=90581&key=user_uploads/1453819/af22052f-6cbe-4cc6-863f-9dd72f10add5)\n\n",
        "url": "https://www.ycombinator.com/launches/NYz-cubic-cursor-for-code-review",
        "votes": 110,
        "created_at": "2025-05-21T13:07:32.512Z"
      }
    ]
  },
  {
    "id": 30412,
    "name": "Bloom",
    "slug": "bloom-4",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3577a0e8b2ab3aba26616432bba656fef491a245.png",
    "website": "https://bloom.diy/",
    "all_locations": "",
    "long_description": "Bloom lets you vibe code cross-platform apps and test them on your phone natively in seconds. Unlike other vibe code tools, Bloom deploys a backend for you, so you can build functional MVPs and personal apps, not just toys.\r\n\r\nhttps://youtu.be/oeJCk_nwDZg",
    "one_liner": "Build and share mobile apps in seconds",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1748292751,
    "tags": [],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Spring 2025",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "Remote",
      "Partly Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/bloom-4",
    "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/bloom-4.json",
    "year_founded": 2025,
    "city": null,
    "country": null,
    "linkedin_url": "https://www.linkedin.com/company/bloomlabs-inc/",
    "x_url": "https://x.com/CreateWithBloom",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/BloomLabsInc",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/3577a0e8b2ab3aba26616432bba656fef491a245.png",
    "app_video_url": null,
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    "company_photos": [
      "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/d85ccac518d09d3c1cf72712062666158d89f258.png"
    ],
    "primary_partner": {
      "name": "David Lieb",
      "url": "https://www.ycombinator.com/people/david-lieb"
    },
    "founders": [
      {
        "user_id": 1073860,
        "full_name": "David Oort Alonso",
        "title": "Founder/CEO",
        "founder_bio": "Building Bloom",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/david-oort-alonso",
        "x_url": "https://x.com/itsdavidalonso",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/18a13267f98439a947d8138507276efb892bae6d.jpg"
      },
      {
        "user_id": 1276295,
        "full_name": "Sirian Maathuis",
        "title": "Founder",
        "founder_bio": "Designer that also builds things. Now helping others do the same with Bloom.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/sirian-maathuis",
        "x_url": "https://x.com/sirian_m",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/6a205ca37af7b778ec2e5b299772b9691d5940ef.jpg"
      }
    ],
    "jobs": [
      {
        "id": 77797,
        "title": "Founding Engineer",
        "url": "https://www.ycombinator.com/companies/bloom-4/jobs/Tb6dGeS-founding-engineer",
        "location": "Zürich, ZH, CH / Remote",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$150K - $250K",
        "equity_range": "0.50% - 2.00%",
        "experience": "3+ years",
        "visa": "US citizenship/visa not required",
        "skills": []
      },
      {
        "id": 81709,
        "title": "Founding Creator / Head of Production",
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        "body": "TL;DR: Bloom is the fastest way to **build and share native mobile apps**. No code, no backend infra, no App Store Developer account, no TestFlight, no XCode, no App Store reviews. Soon, you won’t even need a laptop ;)\n\nCheck out the future that Bloom enables 👇\n\nhttps://youtu.be/4dbwKmB2L3E\n\n### Goal 🚀\n\nOur mission is to democratize app development. We believe in a world where…\n\n* creators (designers, developers, entrepreneurs, kids, artists, etc.) can turn their ideas into working products in seconds\n* people build many of the apps they use every day and can change the experience whenever they feel like it, straight from their phone\n* companies can prototype mobile apps faster than ever before, going from design to putting it into the hands of users in minutes\n\n### User impressions 🤜 🤛\n\nOur early users call us the **Lovable for mobile apps**, and we agree! We don’t just build toys, but full-stack apps - instantly usable on any phone.\n\n![uploaded image](/media/?type=post&id=90756&key=user_uploads/1073860/1078121a-7577-4f3c-9ef6-9e08f09a5fc0)\n\n> This is phenomenal, I work all day on native app dev and never believed you could get something new and meaningful to work on anyone’s device so effortlessly. I just started making a tron light cycle game with haptics and it nearly one shot it - will finish it off tomorrow. Amazing job Sirian and David!\n\n> I started my dev journey building iOS apps with objective C and xcode. this is so damn cool and amazing\n\n> Currently struggling through using Swift for a mobile app maybe we need to switch to bloom…\n\n### Team 👋\n\nWe’re [**Sirian**](https://www.linkedin.com/in/sirian-maathuis/) and [**David**](https://www.linkedin.com/in/david-oort-alonso/) — we’ve worked together for 2 years and previously built award-winning consumer mobile apps, like [**Giftit**](https://www.giftit.social/), and turned down an acquisition offer for [**Fireview**](https://fireview.dev/) from a Series A YC startup to build Bloom.\n\n### Call to action (aka how to be AWESOME 😎)\n\n* Sign up for early access at [**app.diy**](http://app.diy) and build the idea you’ve been postponing\n* If you’re need to build or prototype mobile apps (iOS & Android) at your company, please book a 15min call so we can help: [https://cal.com/bloomlabs/intro-to-bloom](https://cal.com/bloomlabs/intro-to-bloom**)\n* Reach out with any feedback on [**Discord**](https://discord.gg/MEsnVQN8Jh) or [founders@bloom.diy](mailto:founders@bloom.diy)\n\n![uploaded image](/media/?type=post&id=90756&key=user_uploads/1073860/8a201d0b-ea4d-4618-bff2-d8e1e86caa23)\n\n",
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        "body": "### **📚 TL;DR**\n\n**c/ua** is an open-source framework that enables AI agents to control full operating systems within high-performance, lightweight virtual containers. It delivers up to **97% native CPU speed on Apple Silicon** and works with any language models: [**https://github.com/trycua/cua**](https://github.com/trycua/cua).\n\n<https://youtu.be/Ee9qf-13gho>\n\n### **⚒️ The Problem**\n\nFor **Computer-Use AI agents** to be genuinely useful, they must interact with your system's native applications. But giving full access to your host device is **risky** - and not ideal. What if the agent's process gets compromised, or the LLM hallucinates and leaks your data? And practically speaking, do you really want to **give up control** of your entire machine just so the agent can do its job?\n\n**In short: How can AI agents interact with operating systems, desktop applications, and browsers without jeopardizing security or sacrificing performance?**\n\n### **⭐ Solution: An end-to-end framework**\n\nWe combined **Apple's Virtualization.Framework** with an agent-friendly interface to create:\n\n\\- **Lightweight VMs**: Run at 97% of native CPU speed on Apple Silicon, giving you near-native performance in a secure, virtualized space.\n\n\\- **Sandboxed Execution**: AI agents operate in tightly controlled environments, allowing secure interaction with desktop applications - without risking your host system.\n\n\\- **LLM-Compatible Runtimes**: Works out-of-the-box with popular LLM providers like OpenAI, Anthropic, and open-source tools like Ollama, LM Studio, and OpenRouter.\n\nAnd we now support **MCP**! You can use Claude Desktop or Cursor, as your personal assistant to navigate even notoriously challenging apps like Tableau. Watch the demo to see it in action!\n\n[**https://youtu.be/NTUVU1aBs3c**](https://youtu.be/NTUVU1aBs3c)\n\n### **⚙️ How It Works**\n\n**c/ua** brings together three powerful components into one unified framework stack:\n\n1\\. **Lume** - Our high-performance Virtualization layer leverages Apple's Virtualization.Framework to spin up macOS or Linux environments.\n\n2\\. **Computer-Use Interface (CUI)** - This layer lets any process or AI agent - no matter which framework it's built on (like AutoGen, LangGraph, etc.) - see the screen and interact with Lume VMs just like a human would. It supports actions such as clicking, typing, scrolling, and extracting the visual accessibility tree.\n\n3\\. **Computer-Use Agent (CUA)** - Built on top of CUI, this general agent framework runs intelligent workflows within these VMs. It's compatible with popular LLM providers like OpenAI, Anthropic, as well as open-source tools like Ollama, LM Studio, and OpenRouter.\n\n![uploaded image](/media/?type=post&id=89628&key=user_uploads/1644303/c3e0e845-3223-4b82-85d1-316e41d9875c)\n\nAn AI agent built with **c/ua** operates within a virtual environment to:\n\n\\- Navigate and interact with any application's interface\n\n\\- Read screen content and perform keyboard/mouse actions\n\n\\- Switch between applications and self-debug when needed\n\n\\- Operate in a secure sandbox with controlled file access\n\nAll of this occurs in a fully isolated environment, ensuring your host system, files, and sensitive data remain completely secure - while you continue using your device without interruption.\n\n### **🖥️ What Can You Build with c/ua?**\n\n**c/ua** lets AI agents use real desktop apps - just like a human. For example:\n\n\\- **CAD Copilot**: Modify 3D models in tools like Fusion 360 or FreeCAD.\n\n\\- **Photoshop Assistant**: Crop, layer, and export assets via prompt.\n\n\\- **Operator for Tableau**: Navigate dashboards and filters with natural language.\n\n\\- **Legacy App Automator**: Control apps and websites with no APIs through UI actions.\n\n### **🤝 Our Asks:**\n\nIf you're done burning money on fragile browser automations or slow, over-engineered computer-use agents - it's time to try c/ua:\n\n* Book a call: <https://cal.com/francesco-bonacci/cua-demo>\n* Email us: [founders@trycua.com](mailto:founders@trycua.com)\n\nAlso don’t forget to:\n\n1\\. Leave us a star, watch and fork on GitHub: [**https://github.com/trycua/cua**](https://github.com/trycua/cua)\n\n2\\. Join our Discord [**https://discord.com/invite/mVnXXpdE85**](https://discord.com/invite/mVnXXpdE85) - we're building this together",
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        "title": "Chonkie 🦛 Open Source Data Ingestion for AI",
        "tagline": "Feed your models better. Chonkie cleans, chunks, and makes your data AI ready",
        "body": "![uploaded image](/media/?type=post&id=90330&key=user_uploads/1849274/669a375f-f24a-4d4b-9cca-c668ce5d3da4)\n\n## 🚀 TL;DR\n\nModels are now a commodity. The real differentiator for AI applications is _how effectively they use their data_. However, building robust data systems can be both complex and time-consuming.\n\nChonkie fixes this. We make it easy to bring high-quality data ingestion and context-building to your AI projects, ensuring your application is accurate, fast, and cost-efficient.\n\nWe’re open source on GitHub! ([Python](https://github.com/chonkie-inc/chonkie), [TypeScript](https://github.com/chonkie-inc/chonkie-ts)). Leave us a ⭐!\n\n# 🎬 Launch Video\n\nhttps://www.youtube.com/watch?v=eBvCCEgbNDw\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n## 👀 Are you…\n\n👷 **A Builder**\n\n* Install with [pip install chonkie ](https://pypi.org/project/chonkie/)or [npm i chonkie](https://www.npmjs.com/package/chonkie)\n* Use it for free in your projects\n* Join our [Discord](https://discord.gg/6V5pqvqsCY) for direct support from the founders!\n\n🏢 **Business Looking To Go AI Native**\n\n* Want a managed ingestion pipeline? [Contact us](https://cal.com/shreyashn/chonkie-demo)\n* Enjoy a white-glove onboarding experience\n* Use our hosted solution or deploy on-prem!\n\n## ✨ Why Chonkie?\n\nMost AI products today don’t fail because of the model. They fail because they’re fed disorganized, bloated, or incomplete data. The results in wrong answers, slow performance, and expensive bills. There are some existing tools that try to address this, however they are either:\n\n* 🔻 Too slow or bloated\n* 🧱 Too barebones — feels like reinventing the wheel every time\n\nSo we built **Chonkie** — fast, lightweight, and comprehensive.\n\n**Chonkie + Your Amazing AI Application =**\n\n* 🎯 More accurate result\n* ⚡ Faster response times\n* 💸 Lower token usage\n\n## 🔧 What Can Chonkie Do?\n\nChonkie handles the full data ingestion pipeline for AI projects:\n\n* 📄**Bring Any Document**: All formats welcome\n* 🍳**Clean It with Our Chefs**: Normalize and prep your data\n* 🧩**Chunk It**: Break documents into meaningful pieces\n* 🛠️**Refine Your Chunks:** Add context, metadata, or convert to embeddings\n* 🔌**Connect Anywhere**: Integrate with any database and fetch your chunks with ease\n\n## 🎥 See It in Action\n\nSee how Chonkie splits your data, reduces token costs by over **75%**, and generates citations automatically!\n\n![uploaded image](/media/?type=post&id=90330&key=user_uploads/1849274/5ec9dbe7-37c8-428d-b589-8d71c6195191)\n\n## ✅ Try Chonkie Today\n\n* 📬Looking for a managed enterprise solution? [Contact us](https://cal.com/shreyashn/chonkie-demo)\n* 💻 Install our open source offering with  pip install chonkie or npm i chonkie\n* 💬Join our [Discord](https://discord.gg/6V5pqvqsCY) for support and community\n\n\\~Happy Chonking! 🦛✨",
        "url": "https://www.ycombinator.com/launches/NUw-chonkie-open-source-data-ingestion-for-ai",
        "votes": 80,
        "created_at": "2025-05-13T13:34:25.524Z"
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        "title": "Build MCP AI Agents with NoCode PLUS: Native graph-vector database, Use MCP servers with Claude on web",
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        "id": 90705,
        "title": "HelixDB - The database for RAG & AI",
        "tagline": "HelixDB is a graph-vector database that brings structure to your un-structured data for RAG and AI applications. ",
        "body": "Hi everyone 👋\n\nWe’re [George](https://www.linkedin.com/in/george-curtis-12b232a5/) and [Xav](https://www.linkedin.com/in/xaviercochran/) – co-founders of [HelixDB](https://www.helix-db.com)\n\n# TL;DR\n\n**HelixDB is an open-source graph-vector database that brings structure to your un-structured data for RAG and AI applications.**\n\n**_ASK:_** Can you introduce us to people/companies that are working on Graph/Hybrid RAG that could benefit from better performance or less overhead in their development cycles? Contact me at [george@helix-db.com](https://mailto:george@helix-db.com)\n\nhttps://youtu.be/V5viTRj2h68\n\n# ❌ The Problem\n\nAI is changing at a rapid rate which is fundamentally changing technology. This new tech **_needs_** new infrastructure.\n\nEveryone is trying to build AI applications, which often involve dedicated data retrieval for their specific use case. Building these retrieval systems is hard. Previously, we’ve relied solely on vector databases to retrieve semantic matches on tiny snippets of text data. But, this technology is shifting and is relying more heavily on connected data, which comes with better context.\n\nBut building these retrieval systems often involve:\n\n1. **Vector databases**\n2. **Graph databases**\n3. Bespoke **middleman/syncing** software\n\nThese setups are complicated, take a lot of time, engineering expertise, and create huge amounts of overhead which makes maintaining them very time consuming and expensive.\n\n# ✅ Our Solution\n\nHelixDB integrates semantic meaning (through its vector types) with relationships to other data (graph types), a similar model to how we structure information in our brains.\n\n![uploaded image](/media/?type=post&id=90705&key=user_uploads/1342245/468263b3-fb06-4efe-9352-4c30923c6d10)\n\nThis makes it the best solution for making AI retrieval engines for agents and LLMs.\n\nHow we currently do this:\n\n1. Seamlessly integrate **vector types** into your **knowledge graph**\n2. **Type-safe query language** that guides developers and agents to write correct queries before they are executed\n3. **Extreme speeds** outperforming industry leaders by 1-3 orders of magnitude\n\nHow we’re going to make it better:\n\n1. **MCP tools** that allow agents to walk the graph themselves, deciding at each step how to traverse the graph based on the schema and available data.\n2. Built-in **ingestion pipelines** for multi-modal data.\n3. Built-in **embedding-models** bringing immediate structure to your knowledge graph.\n\nTo get setup, follow the guide in our README:\\\n[HelixDB Github](https://github.com/helixdb/helix-db)\n\n# 🙏🏻 Our Ask\n\n* Can you introduce us to people/companies that are working on Graph/Hybrid RAG that could benefit from better performance or less overhead in their development cycles? Get them to [book a call](https://cal.com/georgec/30min) or email [george@helix-db.com](https://mailto:george@helix-db.com)\n* If you have a Github account, then [give us a star 🌟](https://github.com/HelixDB/helix-db)\n\nYour help and support makes a huge difference for this project. **Thank you!**",
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        "created_at": "2025-05-24T19:55:54.908Z"
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        "title": "Zenobia Pay - Payments for luxury",
        "tagline": "Pay-by-bank to end high credit card fees.",
        "body": "Hey! We’re [Teddy](https://www.linkedin.com/in/theodore-li-0425b5177/) and [Ryan](https://www.linkedin.com/in/rprendergast/), co-founders of [Zenobia Pay](https://www.linkedin.com/company/zenobia-pay).\n\nZenobia Pay enables luxury brands to accept pay-by-bank and avoid fraud, chargebacks, and credit card fees.\n\nhttps://youtu.be/1dwgU3zQz3k\n\nOnline credit card payments are expensive and rife with fraud. Fees account for 3+% of transaction volume, and high-ticket items account for more than a third of the 100 million annual chargebacks in the US.\n\n**With Zenobia Pay, payments cost only 1%, clear instantly, and are protected with a fraud chargeback guarantee**. Customers link their bank to their own hardware, where it’s stored locally in a secure enclave. Merchant sites never see sensitive tokens or account numbers.\n\nFounders Theodore Li and Ryan Prendergast started Zenobia Pay with a mission to make it 3x cheaper to transact online, bypassing the senselessly high credit card interchange fees that aren’t normal anywhere outside the US.\n\nIf you sell goods online for &gt;$200 and want to 3x lower your fees, email us at [merchants@zenobiapay.com](mailto:merchants@zenobiapay.com). View our site at [zenobiapay.com](https://zenobiapay.com/)",
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        "votes": 38,
        "created_at": "2025-05-20T20:03:21.953Z"
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    "long_description": "Attune makes blazingly fast build tools that require zero migration effort.\r\n\r\nAs AI enables developers to write code faster than ever, slow builds are increasingly becoming the bottleneck in development velocity. Developers regularly lose hours of productivity every day waiting for their builds. Imagine being able to write code in 1 minute, but needing to wait 30 minutes to compile, deploy, and test it.\r\n\r\nExisting solutions either require painful migrations to new tools (e.g. Bazel) or rely on just using bigger servers to run your builds. Instead, we do native, first-class integrations into compilers and build systems.\r\n\r\nWith Attune, you don't need to integrate a new tool. Just make a one-line change from `cargo build` to `hurry cargo build` for 20x faster builds.\r\n\r\nEliza (ex-Google) and Xin worked together for 3 years at FOSSA, where Eliza was Head of Engineering and Xin was Head of Product. Eliza brings a decade of programming languages and build systems expertise, while Xin brings a decade of experience building developer tools products, most recently as VP of Product at Teleport (S15). Having experienced the pain of slow builds firsthand across hundreds of production codebases, we're building the solution we've always wanted.",
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      "name": "Diana Hu",
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        "full_name": "Xin Ding",
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        "title": "Founding Software Engineer",
        "url": "https://www.ycombinator.com/companies/attune/jobs/ZWLdtj8-founding-software-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Backend",
        "salary_range": "$150K - $200K",
        "equity_range": "0.50% - 1.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
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      {
        "id": 90363,
        "title": "Attune - Faster Builds, Zero Effort",
        "tagline": "Attune makes blazingly fast build tools that require zero migration effort.",
        "body": "Hey everyone, we’re Eliza and Xin, cofounders of Attune.\n\n# ⚡️ TL;DR\n\nAttune makes blazingly fast build tools that require zero migration effort. Built by developers with a decade of experience in build systems and developer tools.\n\nIf you or someone you know is suffering from slow builds, we’d love to help! \n\nContact us at [founders@attunehq.com](mailto:founders@attunehq.com).\n\n![uploaded image](/media/?type=post&id=90363&key=user_uploads/429685/31b348ca-dc4a-4649-8886-fc28ed78e37a)\n\n# ❌ The Problem\n\nAs AI enables developers to write code faster than ever, slow builds are increasingly becoming the bottleneck in development velocity. Developers regularly lose hours of productivity every day waiting for their builds. Imagine being able to write code in 1 minute, but needing to wait 30 minutes to compile, deploy, and test it.\n\nExisting solutions either require painful migrations to new tools (e.g. Bazel) or rely on just using bigger servers to run your builds.\n\n# ✅ Our Solution\n\nWe’re building drop-in replacements for existing build tools that dramatically speed up build times with zero migration effort. Simply prefix your existing build commands with hurry and get faster builds through incremental builds, remote execution, distributed caching, and a whole suite of other language-native and compiler-native optimizations.\n\nhttps://www.youtube.com/watch?v=DxM5Dj6ikVc\n\nFor example, instead of running cargo build, now you can run hurry cargo build for up to 20x faster builds.\n\nThat's it. No migration headaches, no complex configuration, and no learning a new tool and rewriting your build files.\n\nNow available for Rust, with Docker and additional language support launching soon.\n\n# 👷‍♀️👷‍♂️Our Team\n\nEliza (ex-Google) and Xin worked together for 3 years at FOSSA helping customers analyze and secure their build systems. Eliza was Head of Engineering and Xin was Head of Product. Eliza brings a decade of programming languages and build systems expertise, while Xin brings a decade of experience building developer tools products, most recently as VP of Product at Teleport (S15). We’ve seen the pain of slow builds firsthand across hundreds of production codebases, we're building the solution we've always wanted.\n\n# 🙏 Our Ask\n\nTired of waiting on builds? We'd love to show you how much time Attune can save your team.\n\nReach out to us at [founders@attunehq.com](mailto:founders@attunehq.com).",
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        "votes": 49,
        "created_at": "2025-05-13T17:46:08.929Z"
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    "name": "Refresh",
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    "website": "https://www.refresh.dev",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Building RL environments for coding and computer use. ",
    "one_liner": "Training gyms for computer use and software engineering work",
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    "country": "US",
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        "full_name": "Erik Quintanilla",
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        "id": 90828,
        "title": "Refresh - RL Training Gyms",
        "tagline": "High fidelity, realistic environments to train computer use and software engineering capabilities into LLMs",
        "body": "Software engineering capabilities in the frontier llms have already emerged. Across SWE-Bench, Terminal-Bench, OS-World, model capabilities are rising amongst us.\n\nScaling pre-training has worked to allow the models to learn fundamental concepts, but the last edge of performance differences come from agents learning specialized tools very well in training gyms - be it bash, file editing, or computer using capabilities.\n\nSome fun things we’re working on…\n\nWe’ve archived the web to generate the next frontier of Computer Use environments with tasks that elicit failure modes across the frontier models.\n\nWe’re also pioneering mechanistic interpretability methods to deterministically elicit the failure modes in coding capabilities of the open source models. \\\n\\\nOur team is ex-Uber ML and ex-Amazon scraping, and previously turned down offers from Scale AI to start Refresh. \\\n\\\nWe’re actively working with frontier labs to provide the highest quality simulation environments to train computer use and software engineering capabilities. If you’re training frontier intelligence, we’d love to talk! \\\n\\\nGet in touch at [founders@refresh.dev](mailto:founders@refresh.dev) :)",
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        "created_at": "2025-05-28T19:49:51.128Z"
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        "full_name": "Jeevesh Konuru",
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        "title": "Jeevy Fabrication: The AI Fabrication Contractor",
        "tagline": "Meet Jeevy, the company re-imagining weld fabrication",
        "body": "# **TLDR**:\n\n# Jeevy Fabrication is a AI driven fabrication contractor for welded assemblies. We deliver higher quality QA and schedule transparency while maintaining competitive pricing.\n\nhttps://www.youtube.com/watch?v=4lB7YAlHF1U\n\n# **What we found**:\n\nIf you are building rockets to Mars or fusion systems, getting complex welded assemblies built to spec, on time, and on budget is mission-critical—**and incredibly hard**.\n\nOutsourcing to smaller weld shops can save money, but often at the cost of quality, schedule delays, and lost traceability. Precision assemblies often arrive dirty, out of spec, or late because these shops lack the project management horsepower needed to maintain the rigor high-stakes hardware demands.\n\n**Quick reality check:** Processing one drawing properly—with a detailed schedule, test plan, and QA flow—takes \\~9 hours. With only a 10% win rate on bids, a small shop could spend 90 hours just to land one job. That’s not scalable when you’ve got one or two engineers.\n\n# **Our approach**\n\nWe figured it would be awesome if we could offer the same high quality results of in-housing at the price of outsourcing a job. Our software reduces bid and scheduling time for our in-network shops **by over 80%**. It converts manufacturing drawings into an accurate bill of materials and a resource-loaded, high-fidelity schedule—eliminating costly errors and rework. Using these tools, our in-network fabricators can **spend less time bidding and deliver more reliable results than their competitors**. ‘\n\n**We handle the bids, purchase materials, and allocate jobs to shops in our network** that have the right capabilities and available capacity. By owning the job end-to-end, we ensure quality and adherence to key project milestones. In-network shops benefit from smarter scheduling tools and a steady stream of work to fill their downtime.\n\n# **About the Team**\n\n![uploaded image](/media/?type=post&id=90270&key=user_uploads/2560244/fd3594e1-0826-4e36-9631-04058ff16474)\n\nWe’re brothers—and that’s a desktop DAC (Direct Air Capture) we built together as a side project. We’ve always known we’d start a company together—it’s been part of the plan for as long as we can remember. And we’ve always said it had to be a rock ’n’ roll fueled adventure!\n\nOur dad was a serial entrepreneur, and dinner conversations were filled with stories and lessons from his ventures. That’s just how we grew up.\n\n**Jeevs**: Spent several years at SpaceX designing and building welded assemblies for launch pads in South Texas. The genesis of this idea came from the pain Jeevs experienced while sourcing parts for launch critical systems. “...why is there water in my cryogenic liquid oxygen pipe?? It’s like they’re trying to kill us!”\n\n**Vinay**: Several years of experience writing software for energy grid optimization projects. Worked at Rondo Energy designing and modeling grid scale heat batteries. He has a computer science and electrical degree from Princeton University.\n\n# **Our ask**\n\nNeed a welded part built? Know someone who does? Please let us know! ",
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        "created_at": "2025-05-10T10:50:02.019Z"
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    "name": "Freesolo",
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "Freesolo works with companies to encode user-trajectory knowledge into specialized models that outperform the state of the art at much lower latency and cost.",
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        "full_name": "Eric Mao",
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        "full_name": "Tom Zheng",
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        "title": "Freesolo: Post-Training Built for your Agent",
        "tagline": "Small models, frontier performance",
        "body": "Not every AI interaction is best served with a large frontier model. There is a long tail of trillion-token use cases, from tagging to search, best served by a sub-10B-parameter model that runs in milliseconds and costs many orders of magnitude less than the frontier. However, engineers historically had to choose between model size and quality; as models got smaller, performance, adherence, and recall dropped linearly. Post-training on production data closes that gap. We built Freesolo Flash to make training loops like SFT and RL easy and end-to-end completable through your coding agent.\n\nWe accomplish this in a few different ways\n\n* Upfront pricing: instead of billing by GPU hours or tokens spent while training, we quote the cost of the entire run upfront, so your agent can accurately tweak the dataset, model size, and algorithms it uses while staying in your budget before it starts the run.\n* Our GPU infrastructure is optimized to make your specific run as in-expensive and fast as possible. This optimization means training with flash is 8x less expensive for SFT and 5.5x less expensive for GRPO (RL) when compared to Tinker.\n\nFlash is built out of our own frustrations with current managed post-training solutions, especially for SLMs. We believe that unlocking frontier capability for a narrow task into a small model will prove to be the best improvement for all agentic product UX. Flash is our first step towards solving this. Just grab a Freesolo API Key, point your agent at the training package, and watch it push your lightweight model beyond the frontier.\n\nFlash is publicly available today at  <https://freesolo.co>[ ](https://freesolo.co/). Train on!",
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        "created_at": "2026-07-13T19:38:20.322Z"
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      {
        "id": 90716,
        "title": "Clado: Deep Research for People",
        "tagline": "100,000+ agents to find the right people at the right time",
        "body": "Clado puts 200 million+ people profiles (and growing) at your fingertips with simple, agentic search. \n\nIf you’re interested in a global people search for sales, spreadsheets, hiring, and more, let’s talk: https://cal.com/clado/chat\n\n**We’d love for you all to try Clado out live!** https://clado.ai\n\nhttps://youtu.be/NEqtIFNZJoU\n\n❌ The Problem: Keywords, Filters, Data\n\nFinding the right people is broken. Current methods of people search are made up of endless filter menus, incomplete data sets, and keyword search. It takes tremendous effort and time to find people for sales and hiring, as current search methods rely on fuzzy filters in limited datasets. \n\n✅ Solution: Clado uses agentic search to find exactly who you're looking for. Just describe the qualities you want, and we will deploy hundreds of thousands of agents to find them.\n\n![uploaded image](/media/?type=post&id=90716&key=user_uploads/2374036/2faf2b26-e574-43af-8bdc-933ad4b2f2e7)\n\nThese example searches are time-consuming to execute with standard filtering tools and elude traditional keyword filters.\n\n_\"AI Engineers I can poach for my pharmaceutical startup/interested in biology in Copenhagen.\"_\n\nAn even harder one:\n\n_“Every exec (Owner/CEO/COO/CFO/Partner/Head of Growth/CTO) at accounting firms in the US and UK between 250 - 2000 employees\"_\n\nAfter internally benchmarking our people search engine against other platforms, our model achieves SOTA performance. \\\n\\\nWhat good is finding the right person if you can’t easily contact them? We’re also able to achieve SOTA performance on contact delivery information retrieval given any Linkedin URL (provided for every result in our search). \n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXdlMEsme5O2KS7jDjVQ5meLUOG0wSsn4dUDYSaIlwQ2hYDg2Sa7HGCVi_7rjnEAfXWNdODe05Fhghlf6BVYD0z6QlbEjh4B1N1rGLlh3M_RqfIRDrIdpkdKJQzZivA3A7cMH7D93w?key=IzTsz7ArVY5QuH96a3WVtw)\n\nTesting Conditions:[ https://pastebin.com/98PVVN9b](https://pastebin.com/98PVVN9b)\\\n\\\nThe Team:\\\nTom (UCSD) & Eric (UPenn M&T) are both ambitious freshmen who met in elementary school. They previously founded a nonprofit and won Canada’s largest data science & physics competitions.\\\n\\\nThey’ve also sailed over 300 nautical miles over 10 days, canoed 100km over 6 days, walked around Toronto hanging up posters for their first business for two weeks straight, and traveled to Sri Lanka on a three-day notice to present at a conference together. \\\n\\\nTry clado: https://clado.ai\n\n📅 Book a meeting: [**https://cal.com/clado/chat**](https://cal.com/clado/chat)\n\n📧 Email us: [**founders@clado.ai**](mailto:founders@clado.ai)",
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    "name": "Photonium",
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        "full_name": "Jennifer Song",
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        "title": "Photonium: AI-Accelerated Optical Design Automation ⚛️",
        "tagline": "Design optical systems faster and cheaper.",
        "body": "Hey YC!\n\nWe’re [Jennifer](https://www.linkedin.com/in/jennifer-y-song) and [Adam](https://www.linkedin.com/in/adam-mhatre-5b8aaa230/) - cofounders of Photonium.\n\n**TL;DR**\n\nPhotonium automates optical system design with AI, replacing costly manual iteration with end-to-end system optimization.\n\n**🚨 The Problem**\n\nOptical systems are mission-critical across many high-growth sectors — including quantum technology, biomedical imaging, LiDAR for defense and autonomous vehicles, and metrology for semiconductor fabrication.\n\nBut designing them is a nightmare:\n\n* Companies pour millions into teams of 20+ optical engineers\n* Projects take months or years to go from R&D to production\n* Tools are fragmented and outdated\n* Optimization is manual and often based on trial-and-error\n\nEngineers spend countless hours on repetitive workflows — constrained by tools that haven’t changed in decades.\n\n**⚙️ Our Solution**\n\nPhotonium is building the electronic design automation (semiconductor EDA) for optics. We work with complex optical setups across industries and handle the entire design process — from system generation and optimization to simulation, tolerancing, and sourcing.\n\nPhotonium enables companies to:\n\n* Generate and optimize designs from product specs\n* Predict tolerance impacts without slow simulations\n* Recommend data-driven alignment and manufacturing tweaks\n* Optimize for cost, size, and performance trade-offs\n* Seamlessly integrate with existing CAD workflows and optics simulation tools\n* Automate the full design-to-sourcing pipeline\n\n[Launch Video](https://youtu.be/YvX3Xr2_Gt8)\n\n**🚀 The Team**\n\nJennifer studied physics, math, and CS at Harvard and built quantum optics experiments across Harvard, Stanford, and QuEra (a Google-backed quantum computing startup).\n\nAdam studied computational physics at Stanford, and worked on plasma simulation for fusion and large-scale astrophysical modeling of black holes.\n\nWe’ve both felt the pain of inefficient engineering design firsthand — and built Photonium to fix it.\n\n⚛️ **Why This Matters**\n\nOptical systems are foundational to cutting-edge technologies, from quantum computing to semiconductor fabrication. Yet, outdated tools and fragmented workflows slow innovation and inflate costs. We hope to eliminate these bottlenecks and accelerate innovation across industries.\n\n📣 **Our Ask**\n\nIf you know anyone working with lasers and optics in any context, we’d love to chat! Contact us at [founders@photonium.ai](mailto:founders@photonium.ai)\n\n![uploaded image](/media/?type=post&id=90808&key=user_uploads/2467765/c27811f3-aa01-4860-9682-d3136973df3e)\n\n",
        "url": "https://www.ycombinator.com/launches/Nce-photonium-ai-accelerated-optical-design-automation",
        "votes": 51,
        "created_at": "2025-05-28T19:10:45.827Z"
      }
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    "id": 30492,
    "name": "Prism",
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    "website": "https://prisminference.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "We sell tokens",
    "one_liner": "Abundant Intelligence for Everyone",
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    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/prism",
    "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/prism.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/teamprismai",
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    "primary_partner": {
      "name": "David Lieb",
      "url": "https://www.ycombinator.com/people/david-lieb"
    },
    "founders": [
      {
        "user_id": 551584,
        "full_name": "Rajit Khanna",
        "title": "Founder/CEO",
        "founder_bio": "Founder @ Prism. Prev @ Greptile (YC W24), Skydio, Stripe (YC S09), and Blissway (YC S20).",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/rajitkhanna",
        "x_url": "https://x.com/rajitwrites",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/fa583ac735194f7bc43967d9a949e34ba9f55e8f.jpg"
      },
      {
        "user_id": 557217,
        "full_name": "Alex Liu",
        "title": "Founder/CTO",
        "founder_bio": "CTO @ Prism. Prev engineering @ Palantir, AWS. Georgia Tech Alum",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/alexyliuswe",
        "x_url": "https://x.com/spicy_liu",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c8ecd63989b26ca5e6967aece51948172d712f42.jpg"
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    ],
    "jobs": [],
    "news": [
      {
        "title": "Y Combinator’s spring 2025 batch features 70 startups focused on agentic AI - The Economic Times",
        "url": "https://economictimes.indiatimes.com/tech/artificial-intelligence/y-combinators-spring-2025-batch-features-70-startups-focused-on-agentic-ai/articleshow/121860763.cms?from=mdr",
        "date": "Jun 15, 2025"
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    ],
    "launches": [
      {
        "id": 116844,
        "title": "Prism: Lightning fast inference for coding agents",
        "tagline": "Making tokens abundant for everyone.",
        "body": "Hello everyone,\n\nWe’re Alex and Rajit, and we’re excited to launch Prism.\n\n**TL;DR:** Prism is an inference cloud for open source LLMs. We use agents to optimize our deployments for cost, latency, and throughput (we serve DeepSeek V4.1 Flash at 547 tok/s).\n\n<https://youtu.be/Tp8_JO_IvX4>\n\n## The Problem\n\nOpen source models just got really good. DeepSeek was almost a quarter of all traffic on OpenRouter last week.\n\nWe spoke to developers building coding agents, personal AI assistants, and code review software, and we asked what the biggest bottleneck was in adopting open source models.\n\nThe answer: there is a token shortage. Existing providers either don’t have enough capacity, are too slow, or aren’t reliable enough.\n\n## Meet Prism:\n\nIntroducing Prism: lightning fast inference for coding agents. We have three core ideas.\n\n1. Custom deployments for every model\n\n   We use agents to optimize our deployments for latency, cost, and throughput. Here’s Deepseek V4.1 Flash running on Prism vs other major providers for the same coding task.\n\n   ![uploaded image](/media/?type=post&id=116844&key=user_uploads/551584/62819c55-2169-4734-927b-8a0a1765e57b)\n\n2. Price tokens like electricity\n\n   PG&amp;E charges less for off-peak usage. Token providers should do the same. And not every LLM request is urgent. We can charge less for requests with a wider scheduling window.\n\n3. Enable companies to develop personal intelligence\n\n   For domain-specific tasks, teams are adding adapters onto base models. Most providers require them to pay GPU costs, host, and run the model themselves. We offer serverless LoRA inference along with dedicated deployments.\n\n## Ask\n\nWe’ve spoken to\n\n1. teams who are doing more than six figures a month in frontier lab spend\n2. teams whose inference providers slow down their products \n3. teams who are considering post-training their own models but don’t want to pay constant GPU costs\n\nIf those descriptions sound like you, book a call with us to see how we can help [cal.com/team/prismai/demo](http://cal.com/team/prismai/demo).",
        "url": "https://www.ycombinator.com/launches/UOa-prism-lightning-fast-inference-for-coding-agents",
        "votes": 5,
        "created_at": "2026-09-24T17:21:40.950Z"
      },
      {
        "id": 97184,
        "title": "Prism - AI for the Next Generation of Media",
        "tagline": "Prism is a platform for making short form videos with AI",
        "body": "Hey Everyone! This is Rajit, Land, and Alex\n\n**TL;DR:** Prism is an AI platform for creating short-form videos. Generate assets, build storyboards scene-by-scene, and edit everything in one place.\n\n## **Who Prism is For**\n\nPrism is for anyone who ships short-form regularly:\n\n* **Creators** making memes, skits, explainer videos, ASMR videos, short films, etc.\n* **Marketers & agencies** creating paid ads, launch videos, and UGC content\n\nPrism is for anyone who wants to go viral:\n\n* **Founders** aura-farming on LinkedIn with product launches.\n* **Consumer/prosumer founders** who spend time on growth-hacking on TikTok when they’d rather be shipping.\n\n## **The Problem**\n\nCreating AI video content today means piecing together a dozen disconnected tools:\n\n* Image generators for concept art\n* Upscalers to make them usable\n* Image-to-video generators to bring still images to life\n* Start/end frame tools for precise scene control\n* Lipsync tools to match audio\n* Voiceover generators for narration\n* Video editors to stitch it all together\n\nEach tool operates separately, so you end up exporting from one and importing into another, then re-describing the same scene to try to keep things consistent. Over time, characters start to vary between clips, the visual style can drift, and the assets get spread across 10 browser tabs and your local drive.\n\n## **Meet Prism:**\n\nPrism is the entire video creation pipeline in one place.\n\nStart with a project, set the style once, and build your story scene-by-scene. Generate images, upscale them, and transform them to animated clips with voiceovers and lipsync all in one platform.\n\nNo more exporting between tools or re-prompting every step. Your characters stay consistent, your settings carry over, and your full project context stays attached so every scene looks like it belongs in the same video.\n\n[**https://www.youtube.com/watch?v=bMkQIP8NvdY**](https://www.youtube.com/watch?v=bMkQIP8NvdY)\n\n## **Advertisements and Launch Videos**\n\nWant us to make you a white-glove ad or launch video using our platform? Our videos generated more than 10M views in a month across socials. Reach out at [**founders@prismai.sh**](mailto:founders@prismai.sh).\n\n**Start Today**\n\nSign up on our platform at: [**https://www.prismvideos.com/**](https://www.prismvideos.com/)\n\nBook a video ad demo with us at: [**https://cal.com/team/prismai/demo**](https://cal.com/team/prismai/demo) or [**founders@prismai.sh**](mailto:founders@prismai.sh)",
        "url": "https://www.ycombinator.com/launches/PHU-prism-ai-for-the-next-generation-of-media",
        "votes": 8,
        "created_at": "2026-01-27T00:08:03.083Z"
      },
      {
        "id": 90346,
        "title": "Prism - AI that watches session replays and tells developers what to fix 🔍",
        "tagline": "Prism helps product teams become customer obsessed.",
        "body": "Hey everyone 👋\n\nWe're [Alex](https://x.com/spicy_liu), [Land](https://x.com/LTantichot), and [Rajit](https://x.com/RajitWrites) - co-founders of [Prism](https://x.com/teamprismai).\n\n# **TL;DR:**\n\nPrism is an AI that watches session replays and tells developers what to fix.\n\nhttps://youtu.be/xmvlRom8BNA\n\n# **Problem**\n\nAt Rajit’s previous company, they built a new onboarding flow, set up a dashboard to analyze it, and realized that it was broken. The problem was that this realization came four months later.\n\nThis is the core insight that led us to start Prism.\n\nExisting product analytics solutions are inflexible. They require comprehensive instrumentation and break every time an engineer adds a new flow or modifies an existing one.\n\nWith Prism, developers get insight into what's broken on day one. No event-tracking necessary.\n\n# **Solution**\n\nPrism uses vision models to watch session replays and identify friction. For our customers, it's like having a support engineer sit with every one of their users.\n\nPeople get value from Prism in one of two ways.\n\n### 1. Semantic search\n\n_Rather than watching hundreds of hours of session replays, developers can ask “what are the main pain points users are experiencing?”_\n\n![uploaded image](/media/?type=post&id=90346&key=user_uploads/551584/e3e366c0-be08-4b7d-a351-dd8f6deea3f3)\n\n### 2. Insight generation\n\n_Prism identifies what the issue is, who’s experiencing it, and what a developer can do to resolve it._\n\n![uploaded image](/media/?type=post&id=90346&key=user_uploads/551584/fc5fd965-6693-45d1-ae61-a323920f205e)\n\n# One more thing...\n\nWhile building software may be increasingly commoditized, we believe that the relationship people have with their users will never be. Prism is an AI that enables our customers to know their users better than they know themselves.\n\nIf you want to become customer-obsessed, you can get started at [prismreplay.com](http://prismreplay.com).\n\nYou can also book a demo to chat with us at [cal.com/team/prismai/demo](http://cal.com/team/prismai/demo).",
        "url": "https://www.ycombinator.com/launches/NVC-prism-ai-that-watches-session-replays-and-tells-developers-what-to-fix",
        "votes": 60,
        "created_at": "2025-05-13T14:32:23.347Z"
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    "id": 30497,
    "name": "Human Behavior",
    "slug": "human-behavior",
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    "website": "https://www.humanbehavior.co/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Human Behavior uses vision models to watch all user web sessions so you know exactly how users use every part of your product. ",
    "one_liner": "Understand your users beyond the numbers",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1744779271,
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/human-behavior",
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    "primary_partner": {
      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
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        "user_id": 2397615,
        "full_name": "Amogh Chaturvedi",
        "title": "Founder/CEO",
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        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/amoghchaturvedi1/",
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    "jobs": [],
    "news": [
      {
        "title": "These 20- and 22-year-olds raised $5M from YC, General Catalyst to study online behavior using vision AI | TechCrunch",
        "url": "https://techcrunch.com/2025/09/03/these-20-and-22-year-olds-raised-5m-from-yc-general-catalyst-to-study-online-behavior-using-vision-ai/",
        "date": "Sep 03, 2025"
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    ],
    "launches": [
      {
        "id": 90280,
        "title": "Human Behavior: We reveal why users stay, leave, or pay",
        "tagline": "We have an AI that watches real user sessions to give you the \"why\" behind analytics numbers.",
        "body": "![uploaded image](/media/?type=post&id=90280&key=user_uploads/2397615/2f936c17-95eb-44f0-9823-8f500e75a907)\n\n🎥 What if there’s an AI that watches every user so it has full contextual understanding of your webapp. \n\n**tl;dr:** We’re just that! By analyzing all session replays, we extract behavior patterns that drive retention & revenue – without requiring manual event tracking. We sell to product teams at high growth startups like Delve, Conduit, etc.\n\nhttps://www.youtube.com/watch?v=4Dvt3COkC-U\n\n**Can’t watch all your session replay videos?** We’d love to talk to you: [founders@humanbehavior.co](mailto:founders@humanbehavior.co) or https://cal.com/humanbehavior-founders/30min \n\n**❌ The Problem**\n\nTwo options to understand how your product is used:\n\n1. Product analytics (like Mixpanel or Amplitude): Great for aggregating data but miss user context.\n2. Session replays capture absolutely everything, but there's no good way to aggregate them to learn anything useful.\n\n\"How many users abandon my product after a long LLM generation time? How long do enterprise vs free users spend on feature X?\" These questions become difficult to answer with traditional methods.\n\n**💡Our Solution**\n\nWe built Human Behavior to give you the best of both worlds using vision AI that actually watches your users. No more choosing between high-level analytics or drowning in session videos!\n\nWithout AI, thousands of session videos can be overwhelming. Now you'll never have to set manual feature tracking again – retroactively explore feature usage patterns from all your past users without wasting engineering time and effort.\\\nhttps://www.youtube.com/watch?v=D12guaaJeJ8\n\n**👬 The Team**\n\nWe're Amogh (Stanford CS), Skyler (Berkeley CS), and Chirag (UChicago CS) and we've spent countless hours watching session replays ourselves. We worked on VLM research at Stanford NLP Group and UChicago Database Group, commercializing it to give the best customer behavior insights.\n\n**🤝Our ask:** \n\n* Check us out at https://www.humanbehavior.co/!\n* Stay in touch! If you know any companies with too many replays, we'll watch it for them! We'd also love to understand how you'd use the product. Email us at [founders@humanbehavior.co](mailto:founders@humanbehavior.co) \n* If you like what you see, we'd love to chat! Book a call with us here: https://cal.com/humanbehavior-founders/30min\n\n \n\n_(P.S. Thanks to [gatekeep.ai](http://gatekeep.ai) for letting us use their data for a demo!)_",
        "url": "https://www.ycombinator.com/launches/NU8-human-behavior-we-reveal-why-users-stay-leave-or-pay",
        "votes": 85,
        "created_at": "2025-05-11T16:15:46.610Z"
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    "id": 30498,
    "name": "Alkali",
    "slug": "alkali",
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      "Alkali Engineering"
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    "website": "https://alkali.engineering",
    "all_locations": "Houston, TX, USA",
    "long_description": "Alkali is building the next generation of estimation tools for construction.",
    "one_liner": "The smarter way to estimate steel.",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1747069774,
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      "Design Tools",
      "AI Assistant"
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    "isHiring": true,
    "nonprofit": false,
    "batch": "Spring 2025",
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    "industries": [
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    "regions": [
      "United States of America",
      "America / Canada"
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    "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/alkali.json",
    "year_founded": 2025,
    "city": "Houston",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/alkali-engineering/",
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    "primary_partner": {
      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
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    "founders": [
      {
        "user_id": 2744343,
        "full_name": "Emmett Goodman",
        "title": "Founder/CEO",
        "founder_bio": "Background in Chemical Engineering and GenAI. Building the first AI Chemical Process Engineer 🤖🧪",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/emmett-goodman/",
        "x_url": "https://x.com/EmmettDMGoodman",
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      },
      {
        "user_id": 2448880,
        "full_name": "Victor Miller",
        "title": "Founder/CTO",
        "founder_bio": "I am a chemical engineer, laboratory scientist, and data scientist, all by training and profession. I blend data-driven methods with chemical techniques to get results. I am currently the co-founder of Alkali Engineering, working to build the world's first AI process engineer.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/victor-v-a514248b",
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        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/46b7e3879c9a22dd3d9dfb56b608ac2e759f51ac.jpg"
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    ],
    "jobs": [
      {
        "id": 99714,
        "title": "Founding Applied AI Engineer",
        "url": "https://www.ycombinator.com/companies/alkali/jobs/3iTB9w5-founding-applied-ai-engineer",
        "location": "New York, NY, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Machine learning",
        "salary_range": "$150K - $220K",
        "equity_range": "0.75% - 1.50%",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
        "skills": [
          "Computer Vision",
          "AI Agents"
        ]
      }
    ],
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    "launches": [
      {
        "id": 90604,
        "title": "Alkali – The AI Copilot for Chemical Process Design",
        "tagline": "Build chemical projects faster.",
        "body": "**TL;DR:** Scaling a chemical process from lab-scale result to commercial plant can take years and hundreds of millions of dollars. Alkali’s Engineering Copilot (ProcessMate) uses AI to catch process design errors and automate equipment sourcing – keeping your projects on time and on budget.\n\n[Demo!](https://www.youtube.com/watch?v=JRsBGalf-7k)\n\n**The Problem:**\n\nAs chemical engineers, we’ve seen how design errors and procurement delays derail project schedules and budgets:\n\n* **Engineering Rework:** Projects often undergo 10+ design iterations due to incorrect equipment selection, overlooked safety requirements, or careless design errors.\n* **Procurement Delays:** Complex part sourcing, manual quote/response workflows, and relentless vendor follow-up (chasing confirmations, shipments, exceptions) can delay projects by months.\n\n![uploaded image](/media/?type=post&id=90604&key=user_uploads/2744343/38799444-2d92-431e-9e5c-807e9fe1bbbb)\n\n**Our Solution:**\n\n[Alkali Engineering](https://alkali.engineering/)’s ProcessMate platform streamlines error checking and procurement. Free engineers to do creative work, get projects built on time!\n\n1. **AI-Driven Design Checks** – Like an engineering spell-check for your schematics, AI identifies design errors before it’s too late.\n2. **Smart Equipment Selection** – Cross reference your engineering designs and vendor catalogues to help you get the right parts, faster.\n3. **Version Control & Chat Interface** – Interpretable version control for engineering schematics. Version control is no longer just for software engineers!\n\n![uploaded image](/media/?type=post&id=90604&key=user_uploads/2744343/c4d82b46-885d-4547-b33e-ede8406b033f)\n\n**The Team:**\n\n* [Emmett Goodman](https://www.linkedin.com/in/emmett-goodman/) (PhD, Stanford – ex-AWS GenAI Labs): Led delivery of GenAI solutions for AWS’s flagship customers, showcasing “art of the possible” solutions.\n* [Victor Miller](https://www.linkedin.com/in/victor-v-a514248b/) (PhD, Berkeley – ex-Shell Engineer): Led 8-figure chemical engineering infrastructure projects.\n\n**Our Ask:**\n\nWe’re looking to talk to:\n\n* Project managers fighting schedule overruns\n* Industrial vendors wanting faster RFP/RFQ cycles\n* EPC/Engineering firms interested in piloting AI-driven design validation and procurement\n\n👇 Know someone who fits? Email us at [founders@alkali-eng.com](mailto:founders@alkali-eng.com) !",
        "url": "https://www.ycombinator.com/launches/NZM-alkali-the-ai-copilot-for-chemical-process-design",
        "votes": 53,
        "created_at": "2025-05-21T21:21:07.352Z"
      }
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    "id": 30510,
    "name": "Cactus Compute",
    "slug": "cactus-compute",
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    "website": "https://www.cactuscompute.com/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "On-device AI for phones, wearables, smart home and small robots. ",
    "one_liner": "Automation Foundation Models For Tiny Devices",
    "team_size": 8,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1752189935,
    "tags": [
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      "Hard Tech",
      "Open Source",
      "AI"
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2025",
    "status": "Active",
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    "regions": [
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      "Partly Remote"
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    "stage": "Early",
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    "question_answers": [
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        "question": "How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)",
        "answer": "We met through YC co-founder matching in London four years ago!"
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    "url": "https://www.ycombinator.com/companies/cactus-compute",
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    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/cactus-compute/",
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      "name": "Andrew Miklas",
      "url": "https://www.ycombinator.com/people/andrew-miklas"
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    "founders": [
      {
        "user_id": 1131467,
        "full_name": "Roman Shemet",
        "title": "Founder/CEO",
        "founder_bio": "Former quant & economist with a background in product and data engineering. Pilot, triathlete, chess enthusiast. Working on mobile inference @ Cactus.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/roman-shemet/",
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      {
        "user_id": 901131,
        "full_name": "Henry Ndubuaku",
        "title": "Founder/CTO",
        "founder_bio": "Author of \"Maths, CS & AI Compendium\"",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/henry-ndubuaku-7b6350b8",
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    "news": [
      {
        "title": "Whistle: Speech to Text in 16.9 MB",
        "url": "https://cactuscompute.com/blog/whistle",
        "date": "Oct 01, 2026"
      },
      {
        "title": "Needle 3: 8-29 MB foundation model for tiny devices ",
        "url": "https://cactuscompute.com/needle",
        "date": "Sep 15, 2026"
      }
    ],
    "launches": [
      {
        "id": 92059,
        "title": "Cactus 🌵: Deploy AI models locally on smartphones",
        "tagline": "Cross-platform open-source framework for deploying LLMs, VLMs, Embedding, and other models locally in your apps.",
        "body": "# TL;DR\n\nDeploy AI models locally, privately, and offline in any app using Cactus. Cactus is a blazing-fast inference engine optimized for smartphones and comes with React Native, Flutter, and Kotlin bindings.\n\nhttps://youtu.be/xwKrmYkJZD8\n\n# Our framework:\n\nCactus is a cross-platform & open-source framework for doing inference on smartphones, wearables, and other low power devices. It supports any LLM or VLM available on HuggingFace directly.\n\nThe recently released Google AI Edge and Apple Foundation Frameworks are platform-specific and primarily support specific models from the companies.\n\nTo this end, Cactus:\n\n* Is available in Flutter and React-Native for cross-platform developers, since most apps are built with these today.\n* Supports any GGUF model you can find on Huggingface; Qwen, Gemma, Llama, DeepSeek, Phi, Mistral, SmolLM, SmolVLM, InternVLM, Jan Nano etc.\n* Accommodates from FP32 to as low as 2-bit quantized models, for better\n\n  efficiency and less device strain.\n* Have MCP tool-calls to make models performant, truly helpful (set reminder, gallery search, reply messages) and more.\n* Fallback to big cloud models for complex, constrained or large-context tasks, ensuring robustness and high availability.\n\nSo far, our customers have built:\n\n* Personalised and private RAG and prompt-enhancement pipelines for their app users.\n* Offline fallback for the big remote AI models.\n* Phone tool use agents like gallery & calendar management.\n* AI for medical and other privacy-pertinent industries.\n\n![uploaded image](/media/?type=post&id=92059&key=user_uploads/1131467/bd9fc810-5239-41b7-90ac-bf6d1686bb3c)\n\n# Some demos:\n\n**LLMs and embedding models**\n\n![uploaded image](/media/?type=post&id=92059&key=user_uploads/1131467/0f36edcb-6e65-408f-b30b-a920b37a0aa0)\n\n**Real-time vision inference**\n\n![uploaded image](/media/?type=post&id=92059&key=user_uploads/1131467/24403145-da55-4c01-ad60-8472f49b439d)\n\nTell us how we can make it great!\n\nRepo: https://github.com/cactus-compute/cactus \\\nDiscord: https://discord.gg/nPGWGxXSwr",
        "url": "https://www.ycombinator.com/launches/Nwp-cactus-deploy-ai-models-locally-on-smartphones",
        "votes": 41,
        "created_at": "2025-07-11T19:13:56.052Z"
      }
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    "id": 30520,
    "name": "Synthetic Society",
    "slug": "synthetic-society",
    "former_names": [
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b2b8be4ce1ebb38b874cd798499bbc2de228fc36.png",
    "website": "https://syntheticsociety.ai/",
    "all_locations": "New York City, NY, USA",
    "long_description": "",
    "one_liner": "Synthetic Videos to Simulate Real Users",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1752639112,
    "tags": [],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2025",
    "status": "Active",
    "industries": [
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      "Engineering, Product and Design"
    ],
    "regions": [
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      "America / Canada"
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    "stage": "Early",
    "app_video_public": false,
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    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/synthetic-society",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/synthetic-society.json",
    "year_founded": 2025,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/107848066",
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    "primary_partner": {
      "name": "Ankit Gupta",
      "url": "https://www.ycombinator.com/people/ankit-gupta"
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    "founders": [
      {
        "user_id": 524053,
        "full_name": "Aaron Chew",
        "title": "Founder/CEO",
        "founder_bio": "Columbia CS Dropout. USACO Finalist, top 20 programmers in the USA. First hire @ fun.xyz. Z-Fellows.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/aaronbchew",
        "x_url": "https://x.com/aaronchewbani",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/8b168b3b79580602553bf923fc8f4e02a38e2ce6.jpg"
      },
      {
        "user_id": 1858008,
        "full_name": "Kavan Doctor",
        "title": "Founder/CTO",
        "founder_bio": "MIT CS Dropout, #1 in Math in Canada",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/kavandoctor/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1bc9b55402f00e21b65522e44490cafc526a4a3c.jpg"
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    ],
    "jobs": [
      {
        "id": 106077,
        "title": "Founding Member of Technical Staff",
        "url": "https://www.ycombinator.com/companies/synthetic-society/jobs/zBCibgU-founding-member-of-technical-staff",
        "location": "New York, NY, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$80K - $180K",
        "equity_range": "1.00% - 10.00%",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
        "skills": [
          "JavaScript"
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    ],
    "news": [],
    "launches": [
      {
        "id": 92732,
        "title": "Synthetic Society | Synthetic Users to Simulate Real Users",
        "tagline": "We help teams test like real users to ship faster and break less",
        "body": "## TL;DR\n\nSynthetic Society deploys AI-driven synthetic users to proactively catch bugs, UX flaws, and broken flows before real users experience them. Eliminate manual testing, accelerate your release cycles, and ship confidently.\n\n## Who We Are\n\nWe’re Aaron and Kavan, competitive programmers who met in high school, bonded over building, and never stopped. After a few years as product engineers, we dropped out of Columbia and MIT to build Synthetic Society. \n\n## The Problem\n\n* With AI codegen, teams are pushing features faster than ever. Unfortunately, they’re also pushing bugs, bad design, and broken flows just as fast.\n* Traditional testing practices are slow, resource intensive, and error prone. \n* These inefficiencies lead to frustrated end-users, decreased user retention, increased churn, and ultimately, loss of competitive advantage and revenue.\n\n## Our Solution\n\n**Synthetic Society deploys swarms of synthetic users that mimic real user behaviors to proactively catch bugs, UX flaws, and edge cases.**\n\n**Vibe-code with confidence, knowing that the self-updating end-to-end flows are protecting you with every change you make.**\n\nhttps://youtu.be/DD8efBypfS4 \n\nCheck out our website: https://syntheticsociety.ai/ \n\nGet in touch: [aaron@syntheticsociety.ai](mailto:aaron@syntheticsociety.ai)\n\n![uploaded image](/media/?type=post&id=92732&key=user_uploads/524053/02a68466-2478-4701-8ab6-d54307535a57)\n\n",
        "url": "https://www.ycombinator.com/launches/O7g-synthetic-society-synthetic-users-to-simulate-real-users",
        "votes": 27,
        "created_at": "2025-08-05T02:56:11.464Z"
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    "id": 30523,
    "name": "Mesmer",
    "slug": "mesmer",
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    "website": "https://mesmer.co",
    "all_locations": "Berlin, Berlin, Germany",
    "long_description": "Mesmer is the operating system for agentic engineering teams.\r\n\r\nA few engineering teams are accelerating at breakneck speed, while most are stuck with incremental gains. Mesmer exists so that gap doesn't come down to who gets lucky with their AI experiments.\r\n\r\nWe help founders and CTOs turn agents into real leverage across their organization: faster delivery, better quality, less bureaucracy, and a clear view of where the bottlenecks are and what to do next.\r\n\r\nHundreds of engineering teams have used Mesmer to >2x their productivity in the first quarter using our platform.\r\n\r\nWe are a team of repeat founders and CTOs with 15+ years of experience, including leading engineering together at Origin Financial ($400M), the AI financial advisor founded by Mesmer's CEO.",
    "one_liner": "The operating system for the 100x Engineering Team",
    "team_size": 7,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1747147618,
    "tags": [
      "SaaS",
      "Productivity",
      "Team Collaboration",
      "AI"
    ],
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    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Spring 2025",
    "status": "Active",
    "industries": [
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    "regions": [
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      "Europe"
    ],
    "stage": "Early",
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/mesmer",
    "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/mesmer.json",
    "year_founded": 2025,
    "city": "Berlin",
    "country": "DE",
    "linkedin_url": "https://www.linkedin.com/company/mesmer-co/",
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      "name": "Jon Xu",
      "url": "https://www.ycombinator.com/people/jon-xu"
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      {
        "user_id": 178,
        "full_name": "João de Paula",
        "title": "Founder/CEO",
        "founder_bio": "Co-Founder and CEO at Mesmer (P25), the operating system for agentic engineering teams. Previously cofounder at Origin Financial ($400M) and Glio (S13), first LatAm company to go through YC.\n\nSerial entrepreneur, self-taught engineer, and product leader with 15 years of experience making something people love.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/joaopdepaula/",
        "x_url": "https://twitter.com/joaopdepaula",
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      {
        "user_id": 2518739,
        "full_name": "Sergio Oliveira Bergmann",
        "title": "Founder",
        "founder_bio": "Co-founder and VP of Engineering at Mesmer, where we're building AI-powered agents to help tech founders overcome the coordination challenges that arise as their startups scale. With over 15 years of engineering leadership in fintech and digital banking, I've spent my career developing products that transform complex challenges into seamless user experiences. I'm focused on leveraging technology to empower founders, simplify growth, and amplify innovation.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/sergio-bergmann/",
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      {
        "user_id": 2518589,
        "full_name": "Lucas Silva",
        "title": "Founder/CTO",
        "founder_bio": "Cofounder and CTO at Mesmer (X25). Previously cofounder at Qual Farmácia (2018) and Director of Engineering at Origin Financial. 18 years experience as engineering leader. Passionate about building products that matter",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/lucasbrunosilva",
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    "jobs": [
      {
        "id": 111458,
        "title": "Founding Engineer",
        "url": "https://www.ycombinator.com/companies/mesmer/jobs/YaeucRb-founding-engineer",
        "location": "Berlin, BE, DE / Berlin, Berlin, DE",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "€100K - €140K EUR",
        "equity_range": "0.50% - 1.00%",
        "experience": "6+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Kubernetes",
          "Python",
          "LLMs",
          "Fine-tuning",
          "Evals",
          "AI Agents"
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    ],
    "news": [],
    "launches": [
      {
        "id": 90395,
        "title": "Mesmer — Cursor for CTOs",
        "tagline": "The operating system for 10x companies.",
        "body": "Hey YC, we’re [João](https://www.linkedin.com/in/joaopdepaula/), [Lucas](https://www.linkedin.com/in/lucasbrunosilva/), and [Sergio](https://www.linkedin.com/in/sergio-bergmann/), cofounders of [**Mesmer**](http://mesmer.co/) — **Cursor for CTOs.**\n\nhttps://www.youtube.com/watch?v=TMO7TQUZIuU\n\nWe’re **repeat founders and CTOs behind startups like Glio (S13) and [Origin Financial](http://useorigin.com/) ($400M)**. In every team we built, we ran into the same challenge: each new customer, employee, and feature made it harder to understand what was actually going on. We spent our days in back-to-back meetings and chasing status updates, and forced our teams to do busywork just to keep us in the loop. **Yet we still didn’t see problems until something broke**.\n\nAI is already making the 10x engineer possible. But there’s no solution that helps **product development orgs — and product leaders — 10x themselves**. That’s what we’re building.\n\n# **Enter Mesmer**\n\n**Mesmer gives founders and CTOs full context on their org without drowning in meetings or chasing people for updates**. It watches the work itself — code, specs, designs, meetings — to build a live, detailed picture of what’s going on. Our customers can keep their teams fast, flat, and focused as they scale — and free from busywork.\n\n![uploaded image](/media/?type=post&id=90395&key=user_uploads/178/c0f0220d-62be-4e38-9246-ecd3c2493a79)\n\nWe are starting with **an AI chief of staff for product development orgs**. Every week, it delivers a report showing what actually happened across all in-flight projects: what moved forward, what shipped, and what’s stuck. Founders and CTOs can then ask questions and get in-depth answers based on their team’s actual code, specs, and designs, like:\n\n* Why is this project slipping?\n* Who’s the best engineer to unblock it?\n* What architecture did we use in this repo?\n* How does the business logic work for this categorization engine?\n* What changed in the roadmap last week?\n\n**We’re already live with 10+ companies worth over $3B** and have reviewed over 70M lines of code along the way. We’d love to help you, too.\n\n# **Special Offer**\n\nWe’re onboarding companies as fast as we can, but, if you’re a CTO leading a team of 20+ engineers (or know someone who is) **email me at [joao@mesmer.co](mailto:joao@mesmer.co) and we’ll skip the line** to help you run a flat, fast, focused org right away.\n\n![uploaded image](/media/?type=post&id=90395&key=user_uploads/178/0a177036-5476-45b7-bd33-cfd2b5fb72a3)\n\n",
        "url": "https://www.ycombinator.com/launches/NVz-mesmer-cursor-for-ctos",
        "votes": 99,
        "created_at": "2025-05-14T16:35:47.709Z"
      }
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  },
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    "id": 30532,
    "name": "Nimbic AI",
    "slug": "nimbic-ai",
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    "website": "https://nimbic-ai.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "",
    "one_liner": "Automatically write and update internal docs with every code commit.",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1748402935,
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      "AI"
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Spring 2025",
    "status": "Active",
    "industries": [
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        "title": "StarSling Runners - Self-Driving CI",
        "tagline": "Fast GitHub Actions runners with AI agents that continuously improve your CI to make it up to 6x faster and 13x cheaper.",
        "body": "Hey everyone!\n\nWe're Yonas &amp; Daniel, co-founders of [StarSling](https://www.starsling.dev).\n\n**TL;DR: [StarSling Runners](https://starsling.dev/)** are an AI-native drop-in replacement for ubuntu-latest that continuously make your CI up to **6x faster** and **13x cheaper**. On day one, StarSling Runners are faster and cheaper. From there, AI agents analyze your pipelines and continuously ship optimization PRs.\n\n<https://www.youtube.com/watch?v=IxcYY5cuSXA>\n\n**🤔 Why now**\n\nCoding agents made writing code dramatically faster, and they’ve pushed PR volume up, which compounds CI times and cost fast.\n\n![uploaded image](/media/?type=post&id=104233&key=user_uploads/7866/2149565f-569b-4f8d-b4b3-9eab341daf0f)\n\nEveryone has the option of getting fast CI runners now. What nobody has is **CI that adapts and improves itself**.\n\nMeanwhile, keeping a CI pipeline fast is a constant manual chore: caches break, tests get flaky, build steps pile up, and someone has to notice and fix it, over and over. We believe DevOps tooling like CI should be as agentic as coding is, and that's the unlock behind self-driving CI: the optimization work that used to be a recurring human task now runs continuously in the background as part of the infrastructure running it.\n\n**🔥 The problem**\n\nKeeping CI fast is nobody's job and everybody's problem:\n\n* **Pipelines rot.** Caches get misconfigured, dependency installs get slow, tests turn flaky, build steps stop being parallel. Performance quietly degrades until someone carves out time to fix it.\n* **Fast runners alone don't solve it.** Swapping in faster hardware helps once, then your setup drifts right back as you add more code and tests and they get more complex. Plenty of products give you faster runners. None of them keep your pipeline optimized for you.\n* **It's getting worse.** Recent GitHub Actions pricing changes hit teams running lots of jobs, and GitHub's focus has clearly moved elsewhere. When we surveyed companies looking for DevOps AI solutions, a GitHub Actions agent was the single most-requested solution engineers wanted.\n\n**🧯 The solution: self-driving CI**\n\nStarSling Runners are an AI-native, drop-in replacement for ubuntu-latest\\\nthat get faster the longer you use them:\n\n* **Fast infrastructure on day one.** 5th Gen AMD EPYC (\\~30% faster than GitHub), actions/cache compatible with zero config, unlimited concurrency.\n* **AI agents that optimize your CI for you.** Agents continuously scan your workflows, jobs, run logs, and machine telemetry, then open optimization PRs: fixing caching, speeding up dependency installs, parallelizing build steps, sharding tests, and restructuring workflows. This is the part nobody else does. Real PRs our agents opened and customers merged: [sharding E2E tests across 3 parallel jobs](https://github.com/mastra-ai/mastra/pull/15888) (Mastra), [optimizing Playwright browser installs](https://github.com/better-auth/better-auth/pull/8073) and [fixing turbo cache config](https://github.com/better-auth/better-auth/pull/7950) (Better Auth).\n* **Cheaper, with no surprises.** $0.008/min vs GitHub's $0.012/min (33% cheaper), queue time never billed, no seat fees.\n* **You stay in control.** Every agent-authored optimization ships as a PR your team reviews and merges.\n* **Secure by default.** Every job runs in its own single-use, hardware-isolated microVM that's destroyed after the run, the same isolation model GitHub-hosted runners use. Secrets pass directly from GitHub to your job and are never stored by StarSling.\n* **One-line install.** Install the [StarSling GitHub App](https://github.com/apps/starslingdev) and copy our AI install prompt to swap ubuntu-latest\\\n  for starsling-ubuntu-24.04. You're on faster runners immediately, with 2,000 free minutes your first month. The optimization agents are in early access right now, so request access and we'll turn them on for your repos. **👇**\n\n![uploaded image](/media/?type=post&id=104233&key=user_uploads/7866/a91c193f-d5e1-4d00-a93c-1dfd6381666b)\n\n**📈 Traction**\n\nAfter being in private beta for the past four months, StarSling has now run over **one million CI jobs** for fast-moving teams like Better Auth, Mastra, Partcl, and more, and the self-driving AI agents is what won them over:\n\n* [**Mastra**](https://starsling.dev/customers/mastra) got **6x faster** CI:\n  * _\"The runners are just handled, so nobody on my team thinks about CI infrastructure anymore, and the agents keep optimizing for the one thing I care about: minutes saved.\"_ - Abhi Aiyer, Co-founder &amp; CTO at Mastra (YC W25)\n* [**Better Auth**](https://starsling.dev/customers/better-auth) got **2x faster** E2E:\n  * _\"StarSling agents are like a CI engineer we never had to hire. They find the slow spots, test out fixes, find the ones that work and open the PRs themselves.\"_ - Bereket Engida, Founder &amp; CEO at Better Auth (P25)\n* [**Partcl**](https://starsling.dev/customers/partcl) got **13x cheaper** CI, and the agents proved themselves on day one:\n  * _\"Within a day of migrating to StarSling Runners, their agents opened up a PR that literally made our Rust CI tests 2x faster!\"_ - Vamshi Balanaga, Co-founder &amp; CTO at Partcl (YC P25)\n\nFull case studies: <https://starsling.dev/customers>\n\n![uploaded image](/media/?type=post&id=104233&key=user_uploads/7866/10826f60-8e4d-41a8-a800-32026a78bfc8)\n\n\n**🏋️ Team**\n\n**Daniel** led the 12-person engineering team at Netflix that built their Internal Developer Portal (\"Netflix Console\"), the central hub for Netflix's 3,000+ engineers and the highest-DAU internal developer tool at the company. Before Netflix he was on Facebook's AI Camera team, building computer vision that powers camera effects for 100M+ DAUs across Instagram, Facebook, and WhatsApp.\n\n**Yonas** built StackShare, one of the largest online developer communities (1.5M+ registered developers), with an enterprise offering used by Fortune 500s to surface tech stack data across thousands of internal codebases. StackShare was acquired by FOSSA in 2024.\n\nWe've spent our careers on developer tools, and self-driving CI is the first part of a suite of tools we always wished we had.\n\n**🔮 Vision**\n\nDevOps should be as agentic as coding. CI is just the start. 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        "title": "StarSling - AI Agents for Developers That Ship 🛸",
        "tagline": "Agentic internal developer portal that automates your tasks across deployments, performance, incidents, and bugs",
        "body": "Hey everyone! \n\nWe’re Yonas & Daniel - Co-founders of [StarSling](https://www.starsling.dev).\n\nStarSling (https://starsling.dev) is a developer portal that turns your daily unplanned work from all your dev tools into one-click actions, powered by AI. Open your homepage, click on a GitHub, Linear, or Sentry issue and you’ll see an Autofix button that triggers an agent and opens a Pull Request with a fix, all without leaving your portal. It’s AI agents for the tasks that live outside of your code editor, across deployments, performance, incidents, and bugs.\n\nhttps://youtu.be/-rbrSNyguHY \n\n**🌄 Our Story**\n\nDaniel led an engineering team at Netflix that built their Internal Developer Portal (IDP), called Netflix Console. It was the central hub for Netflix's 3,000+ engineers, managers and leaders and became the highest DAU internal tool for developers at Netflix.\n\nYonas built StackShare, one of the largest online developer communities that had over 1.5M registered developers and an enterprise offering used by thousands of companies that integrated tech stack data into their IDPs and other internal tools.\n\nBoth of us have seen the challenges that developers at large companies face in keeping their tech stacks healthy across thousands of codebases. We’ve also seen the benefits that a high-quality single IDP brings to engineering teams. We believe that AI agents have created a unique opportunity for developers to get the benefits of an IDP with automation baked in from the start.\n\n**🔥 The Problem**\n\nDevelopers typically spend \\~20% of their time on annoying eng tasks outside of their code editor:\n\n* Fixing exceptions\n* Patching flaky CI builds and tests\n* Updating engineering docs and changelogs\n* Investigating and remediating incidents\n* Optimizing slow database queries\n* Debugging preview and staging environments\n* Rotating expiring credentials and keys\n\nThese tasks are spread out across many different developer tools and workflows: Sentry, GitHub, CircleCI, PagerDuty, Supabase, Vercel and many more. StarSling is unifying these tools and bringing AI agents to the rest of the software development lifecycle (SDLC).\\\n**🧯 Our Solution**\n\nWe're building a system of AI agents that perform engineering tasks using the deep context that only exists in an internal developer portal (IDP). One central command center that houses internal services, applications, APIs, documentation and has AI agents continuously improving them. We bring your tools into one system and give you powerful workflows by orchestrating AI agents across these tools.\n\nOur first offering is an agentic developer homepage that shows you your aggregated task list along with actions that AIs can take on your behalf. In your homepage you’ll see: your open PRs, exceptions, tickets, notifications, and more alongside AI agents.\n\n![uploaded image](/media/?type=post&id=90469&key=user_uploads/7866/d4f9f3c3-e7b9-485b-9920-3d04e80d385f)\n\nSoon StarSling will orchestrate agents across the more complex tasks like investigating incidents. Our immediate goal is to be the interface and “portal” to all the AI agents for the dev tools you already use.\n\n**🔮 Our Vision**\n\nTo create a system of AI agents that allows every engineer to spend close to 0% of their time dealing with deployments, performance, incidents, and bugs.\n\n**👇 Our Ask**\n\nIf you’re a developer working on a production system, we’d love to show you StarSling and get your feedback!\n\n👉 Signup for the waitlist: https://starsling.dev\n\n📧 Email us: [founders@starsling.dev](mailto:founders@starsling.dev)",
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        "title": "Theorem – AI coding that is trustworthy-by-default",
        "tagline": "Program verification for superhumanly complex code",
        "body": "### **TL;DR:** **Please give us your most complicated coding problem that _needs_ to be correct. [Sign up!](https://theoremlabs.com/waitlist/)**\n\nHello World! We’re [Jason](https://jasongross.github.io/) and [Rajashree](https://scholar.google.com/citations?user=41ZE3NwAAAAJ&hl=en&oi=ao)! We think AI code generation is going to be bigger than any of us can imagine.\n\n### **MISSION**\n\nTheorem is an AI and programming languages research lab. Our question: as the models get better at generating code, what is the bottleneck to safely deploying vastly more computation in the world? \n\n* _Code has bugs._  AI-enabled attackers will increase the volume and velocity of attacks on software infrastructure. Human code review will not scale.\n* _AIs are untrusted generators._ In order to deploy AIs in critical systems without fully understanding their generalization behavior, we’ll need robust, scalable methods for overseeing their solutions.\n\n### **OPPORTUNITY**\n\nProgramming languages and formal methods is the promise that we can bootstrap roots of trust. Even as complexity of software goes up, we can design simple interfaces for steering with leverage.\n\nPreviously, this technology was only applied to the most mission-critical infrastructure, because of the enormous labor bottleneck — requiring years of PhD level engineering work. For instance, Jason worked on the project that wrote the code generator powering trillions of secure https connections everyday, but it took fifteen man-years to complete!\n\nWith advances in AI, we’re able to speed this development cycle 10,000 times! As a [wild example](https://www.youtube.com/watch?v=O9nKMjjb3Hg) of what’s possible, we spent two hours finding what would have been a zero-day in https code from 2011.\n\n### **OUR APPROACH**\n\nWe want to build workflows for trustworthy-by-default programming by pushing our best ideas till they break. The current candidate to beat is _program equivalence_ driven development. You oversee a simple reference implementation. We give you an optimized implementation, along with a proof that the programs are functionally equivalent. \n\n![uploaded image](/media/?type=post&id=90592&key=user_uploads/2206829/f5c671df-ac60-4b94-8081-36ae8c0aeda4)\n\nWe’re gradually rolling out our programming environment and models. Some use cases from our customers:\n\n* Performance optimization: finding edge cases where hyper-optimized GPU code would fail; getting clear documentation of dependencies that modify behavior in unforeseen ways. \n* Code migration: automating legacy code refactors from Python to Rust while proving no functional change; writing custom kernels to support new services.\n\n**If you work in public infrastructure, finance, hardware, or have other use cases that demand correctness, we’d love to help. Please reach out at [founders@theoremlabs.com](mailto:founders@theoremlabs.com)**",
        "url": "https://www.ycombinator.com/launches/NZA-theorem-ai-coding-that-is-trustworthy-by-default",
        "votes": 83,
        "created_at": "2025-05-21T14:58:50.047Z"
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        "answer": "Engineers and scientists rely on simulations and physical testing to understand how the world works. Today, those tools are slow, expensive, and fragmented. \r\n\r\nRunning a single simulation can take hours to days. Building physical prototypes takes weeks to months. Every domain—from fluid dynamics to thermal modeling—requires different solvers, different experts, and perfect setups. This creates massive bottlenecks in innovation.  We’re building AI that turns engineering questions into instant, physics-based models. No solvers. No bottlenecks."
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        "question": "What is your long-term vision? If you truly succeed, what will be different about the world?",
        "answer": "The next wave of breakthroughs will come from AI that deeply understands physics, not just text.\r\n\r\nWe’re building Godela to give humanity the power to instantly model, explore, and invent across the physical world. Imagine being able to instantly test any idea, uncover hidden relationships, and accelerate discovery at the speed of thought."
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        "full_name": "Cinnamon Sipper",
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        "founder_bio": "Built laptops and iPads at Apple. Built AI products for Google. Now building Godela—AI that models the physical world, for engineers and scientists everywhere.\n",
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        "full_name": "Abhijit Pranav Pamarty",
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        "title": "Founding Engineer (ML Systems) – Godela",
        "url": "https://www.ycombinator.com/companies/godela/jobs/6MlUqiS-founding-engineer-ml-systems-godela",
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        "url": "https://www.ycombinator.com/companies/godela/jobs/rKMZtYt-founding-engineer-swe-godela",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
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        "role_type": "Full stack",
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        "title": "Three Big Projects That Win The AI Prize In Silicon Valley",
        "url": "https://www.forbes.com/sites/johnwerner/2025/09/19/three-big-projects-that-win-the-ai-prize-in-silicon-valley/",
        "date": "Sep 25, 2025"
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        "id": 90799,
        "title": "Godela: AI Powered Physics Engine for Engineers",
        "tagline": "Bringing AI powered intelligence to the physical world",
        "body": "**AI powered physics is the next frontier**\n\n**TL;DR:** Godela is an AI-powered physics engine that gives engineers faster, cheaper, simulation-quality answers to even the most complicated engineering problems.\n\nHi YC—we’re @Cinnamon Sipper and @Abhijit Pamarty, former engineers at Apple, Google, and Intel, now turning our Stanford research into the future of engineering.\n\nhttps://youtu.be/I5E1Zi9cpM4\n\n**The Problem: Engineering Discovery is Too Slow.** Every groundbreaking innovation—from fusion reactors to life-saving drugs—hinges on understanding how the physical world works. Yet, engineers spend agonizing weeks, even months, wrestling with complex simulations, preprocessing data, and manually tuning parameters just to answer _one_ question. Many critical questions go unasked because the effort is too great.\n\n![uploaded image](/media/?type=post&id=90799&key=user_uploads/1725296/03894dba-703c-4a25-a00b-b1ba24b27392)\n\n**Our Vision: Ask About the Physical World as Easily as You Use Language.** Imagine a world where understanding the implications of a new design, material, or physical scenario is as instant as a search query. That’s the future Godela is building.\n\n![uploaded image](/media/?type=post&id=90799&key=user_uploads/1725296/b7ae00e6-d8ea-4354-a110-233a65568e0f)\n\n**Introducing Godela: Your AI Copilot for Engineering.** Godela is an AI-native platform that transforms your engineering questions into computable, physics-informed models—instantly.\n\n* **Ask Anything:** Pose complex questions in natural language or with your existing data.\n* **Upload Your World:** Integrate CAD files, experimental results, or existing simulation data.\n* **Get Instant Insights:** Receive actionable, simulation-quality models you can explore, refine, and iterate on immediately.\n\nInstead of replacing simulations, Godela becomes their intelligent, adaptive home—blending diverse data sources with AI to provide insights that were previously out of reach or would take weeks to uncover.\n\n**Why We’re Building This:** As engineers who’ve designed everything from chips and laptops to particle accelerators, we’ve lived the frustration of slow design-simulation loops. Inspired by how AI revolutionized access to information (like ChatGPT for language), we believe it’s time for the same leap in understanding the physical world.\n\n![uploaded image](/media/?type=post&id=90799&key=user_uploads/1725296/308937e8-b076-46b9-a432-39585f6ea464)\n\n**Partner with Us:** We're looking for forward-thinking engineering teams eager to break free from traditional simulation constraints. If you know engineers battling simulation bottlenecks, send them our way!\n\nIf you want to accelerate your design cycles and unlock new levels of understanding:\n\n🌐 Visit: [www.godela.ai](http://www.godela.ai) \n\n✉️ Email us: [founders@godela.ai](mailto:founders@godela.ai) \n\n🗣️ Talk to us: https://calendly.com/cinnamon-sipper",
        "url": "https://www.ycombinator.com/launches/NcV-godela-ai-powered-physics-engine-for-engineers",
        "votes": 129,
        "created_at": "2025-05-28T13:50:39.357Z"
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    "id": 30562,
    "name": "Docket",
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "Docket lets you write end-to-end tests in plain English and keeps them up to date automatically—powered by real user sessions.",
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        "full_name": "Nishant Hooda",
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        "full_name": "Boris Skurikhin",
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        "title": "Docket – AI agents for QA testing",
        "tagline": "Docket lets you test your website in plain English, and automatically keeps tests up to date",
        "body": "**TL;DR**\n\n**Docket lets you write tests in plain English. Then we keep those tests in sync with how users actually interact with your product — no more flaky selectors or stale test scripts.**\n\n---\n\n### **The Problem**\n\nE2E tests are a _pain_ to write — and an even bigger pain to maintain.\n\n* Writing Cypress or Playwright tests is time-consuming and brittle\n* Even no-code tools require manually defining flows or relying on flaky CSS selectors\n* Every UI change risks breaking your suite, forcing teams to either spend hours fixing tests or just give up and test manually\n\nMost teams hit the same tradeoff: **move fast and break things** — or slow down to ensure quality.\n\n### **Our Solution**\n\nDocket lets you:\n\n* Write tests in plain English (\"Log in, Search for Y Combinator t shirt, Add 2 shirts to cart\")\n* Skip the brittle selectors — we use multimodal agents that interact with the page like humans\n* Automatically keep tests up to date with real user session data\n\n---\n\n![uploaded image](/media/?type=post&id=90473&key=user_uploads/296302/5977d1c3-f564-4d67-b623-319bb6252efd)\n\n### **Meet the Team**\n\nWe’re **Nishant** and **Boris** — two engineers who dreaded writing tests so much, we started a company to fix it.\n\nWe met while working at **AWS**, and between us, we’ve built and shipped products at **Stripe, Citadel, Brex, and Patreon**. But testing was always the drag. Writing tests took forever. Keeping them working was even worse. We constantly felt the pain of choosing between moving fast and having confidence in our code.\n\nSo we’re building the tool we wish we had: **Docket** — tests in plain English that stay up to date, without the maintenance burden.\n\n![uploaded image](/media/?type=post&id=90473&key=user_uploads/296302/f2b9cf37-f50c-4c40-8ca9-6a43d5069a0b)\n\n---\n\n### **Launch Offer**\n\nAs part of our launch, we’re offering **free complete test suite implementations** for our next 10 customers. Book a demo [here](https://calendly.com/nishant-docket/docket-intro-meeting)!\n\n\\\n— Nishant & Boris\n\n![uploaded image](/media/?type=post&id=90473&key=user_uploads/296302/c4bc7ae4-7794-4316-9dce-883ce72a97fc)\n\n",
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        "votes": 142,
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      "name": "Jon Xu",
      "url": "https://www.ycombinator.com/people/jon-xu"
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        "user_id": 2543076,
        "full_name": "Xinwei He",
        "title": "Founder/CEO",
        "founder_bio": "Founder and CEO at TraceRoot.AI.\nPrev. Research Scientist at Meta & Founding Engineer at Kumo.AI (Forbes 50 AI).\nStanford CS, published in top conferences including ICLR, NeurIPS, KDD.\nOSS Core Contributor: PyTorch Geometric.",
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        "id": 92809,
        "title": "TraceRoot - Open source AI agents that automatically fix your production bugs",
        "tagline": "We help engineering teams fix production bugs faster using AI agents.",
        "body": "# TL;DR\n\nTraceRoot is an open-source debugging platform that helps engineers fix production issues faster by using AI agents that intelligently leverage structured context - including traces, logs, metrics, source code, GitHub PRs, issues, and Slack threads to analyze and resolve bugs efficiently.\n\nOur SDK just crossed 10,000 downloads and engineering teams are using our product to monitor, debug, and improve visibility for their production systems.\n\nhttps://www.youtube.com/watch?v=I9fjV_9dM-4\n\n# Our Story\n\nWe’re Stanford-trained engineers and ex-builders from [Kumo.AI](http://Kumo.AI) (Forbes AI 50), Meta Platforms, and AWS, where we fixed 300+ production bugs and experienced firsthand how painful debugging can be in distributed systems. It was so painful that we quit our jobs to solve this problem and [open-sourced](https://github.com/traceroot-ai/traceroot) it!\n\n# The Problem\n\nDebugging production issues today is a mess. Here's what happens:\n\n* You spot an error during release or in production. You open Grafana, check logs, jump to GitHub, scroll Slack, and try to piece things together.\n* Sharing findings? It’s a chain of screenshots, links, and DMs - super painful.\n* It takes engineers hours even days to fix a production bug.\n* Meanwhile, you're drowning in 10+ P0 bugs across multiple releases, and customers won’t stop pinging you on Slack.\n\n# Our Solution\n\nWe built TraceRoot, an agentic debugging platform that ties all your context together and helps your team get to the root cause.\n\n* AI agents automatically summarize the issue and trace logs, spans, and GitHub context into a single execution tree. Ask the agent any question you want to debug.\n* Once the issue is understood, generate GitHub issues or draft PRs directly from the platform.\n* Visual trace explorer that lets you zoom into log clusters, suspicious spans, and trace paths. You can guide the agent by selecting spans or contexts to focus on.\n\n![uploaded image](/media/?type=post&id=92809&key=user_uploads/2543076/7af84b17-1836-4743-9590-dcdd3e862b8e)\n\n# The Ask\n\nIf you're stuck vide-coding through bugs or if your team spends a significant amount of engineering time fixing production issues. We’d love to help!\n\nGive our product a try! Schedule a meeting at https://cal.com/traceroot/30min or email us at [founders@traceroot.ai](mailto:founders@traceroot.ai)\n\n![uploaded image](/media/?type=post&id=92809&key=user_uploads/2543076/5670184a-7bc0-4f39-994e-1e9a297106c7)\n\n",
        "url": "https://www.ycombinator.com/launches/O8v-traceroot-open-source-ai-agents-that-automatically-fix-your-production-bugs",
        "votes": 27,
        "created_at": "2025-08-07T06:27:04.705Z"
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "Datafruit helps enterprise delivery teams understand their customers deeply and deliver more profitably. We build AI agents capture every conversation, structure scope from day one, and use past projects to make every engagement sharper.",
    "one_liner": "The AI workspace for software implementations",
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    "subindustry": "B2B -> Engineering, Product and Design",
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        "full_name": "Venkat Arun",
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        "founder_bio": "cofounder at datafruit; previously cs and statistics at uc berkeley; worked on cloud infrastructure and data pipelines at various early stage startups.",
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        "user_id": 2225888,
        "full_name": "Nick Papciak",
        "title": "Founder/CTO",
        "founder_bio": "Co-founder of datafruit — AI for software implementation. Previously worked at Meta. Studied machine learning and theoretical computer science at Georgia Tech, where I was the head TA for algorithms. ",
        "is_active": true,
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    "id": 30629,
    "name": "Topological",
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    "website": "https://www.topological.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Topological is developing physics-based foundation models for CAD optimization. We help hardware teams iterate at the same speed that software teams do. Our technology is accelerating the engineering workflow with AI and scales design and optimization to identify the ideal designs for complex problems given their physical constraints with enhanced speed and performance. \r\n\r\nOur first model, UToP-v1, is a SOTA topology optimization model that understands physics, geometry, and manufacturability. It can generate the most efficient design given a problem’s physical requirements. It has <5% compliance error and is 1930x faster than current methods. We're reimagining mechanical engineering and computational design with precision spatial AI.",
    "one_liner": "Physics-based foundation models for CAD optimization.",
    "team_size": 2,
    "industry": "B2B",
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        "user_id": 2395628,
        "full_name": "Nicole Ma",
        "title": "Founder/CEO",
        "founder_bio": "Building Topological (YC S25). Prev. CS/MechE @ Stanford, physics simulations @ NASA",
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        "full_name": "Zeyneb Kaya",
        "title": "Founder/CTO",
        "founder_bio": "Building Topological (YC S25). Prev CS/Physics/Math @ Stanford; research in RL, pretraining, efficient algorithms, synthetic data, physics. ",
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    "id": 30630,
    "name": "Lark",
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    "website": "https://getlark.ai/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Lark lets teams write end-to-end tests in plain English. Validate dashboards, APIs, SDKs, and full product flows without maintaining fragile test code. Run continuously on feature branches, in CI, or in production.",
    "one_liner": "The E2E testing layer for AI-driven development",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1755281037,
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    "year_founded": 2025,
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        "full_name": "Vijit Dhingra",
        "title": "Founder",
        "founder_bio": "Vijit is the co-founder of Lark. \n\nHe previously spent five years at a Stripe as a tech lead where he built their usage based billing product and other payments infrastructure. He also contributed to testing infra at Stripe to improve developer productivity and product reliability. ",
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        "user_id": 923500,
        "full_name": "Jack Brown",
        "title": "Founder",
        "founder_bio": "Jack is the co-founder of Lark.\n\nPreviously, Jack built usage-based billing at Stripe to support the complex pricing models of the worlds biggest AI companies. Prior to his previous role, Jack led engineering teams at fast-growing startups, where he built developer tooling infrastructure to improve developer productivity.",
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      {
        "id": 95995,
        "title": "Lark: Stripe without the workarounds",
        "tagline": "Delete your billing code",
        "body": "**Problem** 🔴\n\nToo often, customers tell us they use Stripe for billing but when I ask how they manage their credits or track usage, I always hear the same answer: “we built it in-house”. These pricing models are not edge-cases. They’re the new normal in the age of AI.\n\n**Solution** ⚒️\n\n[uselark.ai](https://uselark.ai) is a modern billing platform with the flexibility to support any pricing model (credit-based, usage-based, hybrid, dimensional, token-based, etc…) at any scale (**10x more** than Stripe).\n\nWhether you’re building an AI powered API or a B2B SaaS product, Lark provides everything (including checkout + customer-facing portal) you need to implement complex billing logic without the hassle.\n\nA few nice things about us -\n\n* You don't have to manage any webhooks or store custom billing state (like stripe customer id) in your database\n* Our APIs are simple. You don't have to integrate with a separate checkout API. We also provide [frontend SDKs](https://docs.uselark.ai/guides/subscriptions/feature_access/) to check billing state (like remaining credits, feature access)\n* Seamless pricing changes that automatically apply to your customers without involving engineers\n* We also help you track margins & LLM costs per customer for AI applications\n\n📘 **Quickstart**: https://docs.uselark.ai/\n\n![uploaded image](/media/?type=post&id=95995&key=user_uploads/923500/df8c7258-bc58-4c50-99a2-79b06af9fd50)\n\n**Checkout + customer-facing portal included**\n\nNo separate APIs, state management, or webhooks\n\n![uploaded image](/media/?type=post&id=95995&key=user_uploads/923500/6adaf51f-5012-4edd-b7f8-773cf5688eff)\n\nCustomer-facing portal includes real-time usage and subscription management\n\n![uploaded image](/media/?type=post&id=95995&key=user_uploads/923500/062c65c1-3ddf-409b-bfad-aaf95f24c116)\n\n**Scalability**\n\nLark supports up to 1M events per second so you don’t have to worry about pre-aggregating your data.\n\n![uploaded image](/media/?type=post&id=95995&key=user_uploads/923500/79359907-1af9-4baa-a5c4-cac78402715e)\n\n**Team**\n\n[Vijit](https://www.linkedin.com/in/vijitdhingra/) and [Jack](https://www.linkedin.com/in/jackcbrown/) both previously built the [usage based billing](https://stripe.com/billing/usage-based-billing) and [customer portal](https://docs.stripe.com/customer-management) product at Stripe.",
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        "created_at": "2025-12-04T22:37:50.310Z"
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      {
        "id": 93109,
        "title": "Lark: AI Agents for Billing",
        "tagline": "We build AI agents to solve billing issues for subscription companies. ",
        "body": "**TL;DR** \n\nLark helps subscription companies automate customer billing support inquiries, manage chargebacks, and prevent fraud.\n\nhttps://youtu.be/gmg8HxjaS1Q\n\n**Problem**\n\nBilling your customers is hard.\n\nTeams spend tens of hours every week attending to billing support inquiries and customers often wait days to receive a response. You also have to worry about fraud and chargebacks.\n\nAll of this is distracting for your team and no one likes working on this. Ignoring the issue leads to frustrated customers, risk of being banned from your payment processor, and lost revenue.\n\n**Solution**\n\nLark provides AI agents that automate all of this for you.\n\nOur agents integrate with your billing provider, support system (e.g. zendesk), and data sources to gather context about the customer and take actions on your behalf. The agents’ decisions are evaluated against strong guardrails to ensure their actions are safe and follow your policies.\n\n**Team**\n\n[Vijit](https://www.linkedin.com/in/vijitdhingra/) and [Jack](https://www.linkedin.com/in/jackcbrown/) both previously built the usage based billing product and customer portal for a large billing provider. Jack has solved billing issues at several startups. \n\n**Our Ask**\n\nIf you’re tired of dealing with billing issues or know someone who is, we’d love to chat! We’re currently working with a few large consumer companies and are actively looking to onboard more customers. We’re also happy to chat about anything in the billing space!\n\n**Contact Info**\n\n[founders@uselark.io](mailto:founders@uselark.io)\n\n[Book time here](https://calendly.com/founders-uselark/lark-chat)",
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        "created_at": "2025-08-18T19:33:29.250Z"
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    "id": 30634,
    "name": "Bitrig",
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    "website": "https://bitrig.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Made by co-creators of SwiftUI, Bitrig is an AI development environment for Apple platforms. It works with real Xcode projects, features built-in simulators, and automates the App Store Connect busy work. You can add in-app purchase and publish to the App Store with just a prompt. Bring your own Claude or ChatGPT subscription.",
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    "team_size": 3,
    "industry": "B2B",
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    "launched_at": 1755626076,
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    "year_founded": 2025,
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    "country": "US",
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        "full_name": "Kyle Macomber",
        "title": "Founder/CEO",
        "founder_bio": "Kyle is the co-founder and CEO of Bitrig.\n\nBefore Bitrig, Kyle spent over a decade at Apple where he co-created and led the development of SwiftUI. He also managed teams behind Swift Charts, WidgetKit, and the Swift Standard Library. Kyle holds a degree in Computer Science from Stanford University.",
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        "full_name": "Tim Donnelly",
        "title": "Founder",
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        "full_name": "Jacob Xiao",
        "title": "Founder",
        "founder_bio": "Jacob is a co-founder of bitrig.\n\nBefore bitrig, Jacob spent 15 years at Apple, where he co-created and led the development of SwiftUI. He also contributed to Xcode and UIKit during his time there. Prior to Apple, Jacob built Opacity, a graphical design tool.",
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        "title": "Bitrig – Vibe code, test, and deploy Swift apps. All from your iPhone.",
        "tagline": "From the creators of SwiftUI",
        "body": "Hi! We’re [Kyle](https://www.linkedin.com/in/kylemacomber/), [Jacob](https://x.com/jacobx), and [Tim](https://www.linkedin.com/in/timdonnelly/), the co-founders of [Bitrig](https://www.bitrig.app).\n\nBitrig is the only vibe coder that writes native Swift, which is how the top mobile apps are coded. It’s like Lovable for iPhone apps.\n\n[Download](https://apps.apple.com/us/app/bitrig/id6747835910) on the App Store today!\n\nhttps://youtu.be/e-DqSVEI50w\n\nWe’re longtime Apple veterans:\n\n* Kyle and Jacob are co-creators of SwiftUI, the framework Apple says is the “the best way to build an app,” and led its development for the past 10 years.\n* Tim was a co-founder and designer of Storehouse, where he won an Apple Design Award and was later acquired by Square. At Apple he rewrote the fluid animation system that powers the experience of 1.5 billion iOS users worldwide.\n\n![uploaded image](/media/?type=post&id=93186&key=user_uploads/547131/634b45de-4ef4-471c-9437-e0dd42eb28d9)\n\nBitrig lets you build native apps for your phone, on your phone. Just by chatting with AI.\n\nIf you’re a designer or PM, Bitrig lets you use the same technology as the developers on your team. If you’re a student, Bitrig is the easiest possible way to get started with Swift.\n\nIt’s fast, it’s fun. You can make a change to your app anytime and anywhere inspiration strikes. And it’s as easy to share your creation as airdropping a photo.\n\nBitrig is a one-stop shop. Vibe code, test, and deploy Swift apps. No Xcode required.\n\n[Download](https://apps.apple.com/us/app/bitrig/id6747835910) on the App Store today!\n\n![uploaded image](/media/?type=post&id=93186&key=user_uploads/547131/6c49fb4f-5e57-4a04-b226-b57a869b9389)\n\n_Behind the scenes: To make Bitrig possible we wrote a custom Swift interpreter. Kind of a crazy thing to do. But the best mobile apps use the native SDK directly, and we wanted to make that level of quality as accessible as possible._",
        "url": "https://www.ycombinator.com/launches/OF0-bitrig-vibe-code-test-and-deploy-swift-apps-all-from-your-iphone",
        "votes": 35,
        "created_at": "2025-08-20T14:38:39.234Z"
      }
    ]
  },
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    "id": 30644,
    "name": "Wafer",
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    "website": "https://www.wafer.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Wafer builds AI agents that work as autonomous performance engineers, optimizing GPU kernels for AI inference. \r\n\r\nOur product is serverless and dedicated inference for the world’s fastest open source LLMs, achieved by Wafer's autonomous performance engineers. ",
    "one_liner": "AI that makes AI fast",
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    "industry": "B2B",
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    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/wafer-ai",
    "x_url": "https://x.com/wafer_ai",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/herdora",
    "github_url": "https://github.com/wafer-ai/",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/d73d3d68555ca97a0b7fa88945cb6c577d872c4c.png",
    "app_video_url": null,
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    "company_photos": [],
    "primary_partner": {
      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
    },
    "founders": [
      {
        "user_id": 1616952,
        "full_name": "Emilio Andere",
        "title": "Founder/CEO",
        "founder_bio": "prev @ argonne, uchicago sand lab, elicit. math at uchicago.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/emi-andere",
        "x_url": "https://x.com/technoabsurdist",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ae196e1f0ed4aa46a6e5bd3b4f200ac17e0eb39d.jpg"
      },
      {
        "user_id": 1580559,
        "full_name": "Steven Arellano",
        "title": "Cofounder",
        "founder_bio": "prev @ two sigma, google, sei labs, and axlab. cs + econ at uchicago.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/stevenjarellano/",
        "x_url": "https://x.com/gpusteve",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b822a5473c769519ddd1f682bb70a795e654488e.jpg"
      }
    ],
    "jobs": [],
    "news": [
      {
        "title": "Building AI That Optimizes AI - YouTube",
        "url": "https://www.youtube.com/watch?v=7JoqmM5EPXo&t=9s",
        "date": "Sep 01, 2026"
      },
      {
        "title": "Wafer, An Inference Provider That Uses Non-Nvidia Chips, Lands Acquisition Offers and $200 Million-Plus Valuation — The Information",
        "url": "https://www.theinformation.com/newsletters/ai-agenda/wafer-inference-provider-uses-non-nvidia-chips-lands-acquisition-offers-200-million-plus-valuation",
        "date": "Sep 01, 2026"
      },
      {
        "title": "AI Could Democratize One of Tech's Most Valuable Resources | WIRED",
        "url": "https://www.wired.com/story/ai-could-democratize-one-of-techs-most-valuable-resources/",
        "date": "Apr 15, 2026"
      },
      {
        "title": "Meet Wafer: The YC Startup Making GPUs 5x More Efficient with AI [Livestreams]",
        "url": "https://www.artificialintelligencemadesimple.com/p/meet-wafer-the-yc-startup-making?r=16nyel&triedRedirect=true",
        "date": "Jan 27, 2026"
      }
    ],
    "launches": [
      {
        "id": 100546,
        "title": "Wafer Pass: flat-rate access to the fastest open-source LLMs",
        "tagline": "The fastest open-source LLMs for OpenClaw, Claude Code, and any agent harness",
        "body": "**TL;DR** - Wafer Pass is a single subscription that gives you the fastest optimized open-source LLMs for any agentic coding harness. Plans start at $10/week. Every plan includes every model we host. Sign up at [wafer.ai/pass](https://www.wafer.ai/#pricing).\n\n![uploaded image](/media/?type=post&id=100546&key=user_uploads/1616952/7ea613a4-5300-4377-9fbe-32791825a31e)\n\n## Hi YC! We're Emilio and Steven, founders of Wafer (S25)\n\nToday we're launching **Wafer Pass**, a flat-rate API subscription to the fastest optimized open-source LLMs. One key, every model, drops into Claude Code, OpenClaw, Cline, Kilo Code, Roo Code, OpenHands, or Conductor.\n\n## **The problem**\n\nIf you use AI coding agents, you've felt the pain. Usage caps that hit at the worst moment. Per-token bills that swing between $5 and $50 a session. Juggling API keys across providers. Watching frontier closed models throttle you on Friday afternoons.\n\nOpen-source models (Qwen3.5-397B, GLM5.1, DeepSeek V4 Pro) have closed most of the gap on coding tasks. The problem is getting them served at the speed you actually want for an agent loop. Most providers run them on stock SGLang or vLLM, which leaves 50–80% of GPU performance on the table.\n\n## **What we built**\n\nWafer's core product is an AI performance engineer. You point it at an LLM and it optimizes it.\n\nWe have been pointing Wafer at the leading open-source LLMs and let it rewrite the entire serving stack: kernels, batching, scheduling, memory layout. The results are really impressive so far: \n\n* Qwen3.5-397B-Turbo is 2.8x faster than base SGLang\n* GLM5.1-Turbo is 2x faster than vLLM baseline\n* DeepSeek-V4-Pro is 2x faster than vLLM baseline\n\nThe Qwen example: \n\n![uploaded image](/media/?type=post&id=100546&key=user_uploads/1616952/5a00eeba-4de9-4052-a0ab-5643908058cd)\n\nSame weights as anywhere else. Just faster, because Wafer rewrote the kernels. We put the result behind a single OpenAI- and Anthropic-compatible API.\n\n## **Wafer Pass**\n\nOne subscription. One API key. Every model we host.\n\n* **$10/week (Starter):** 1,000 requests every 5 hours. All models.\n* **$25/week (Privacy):** 2,000 requests every 5 hours. All models. Zero Data Retention.\n\nEvery plan includes every model, and every future Turbo model we ship. No price increase as the catalog grows. For context: that's 10x requests than Claude Code Max, at 1/2 the price. \n\n## **Try it**\n\n**Sign up: [wafer.ai/pass](https://wafer.ai/pass)**\n\nIf you use Claude Code, OpenClaw, or any other agent harness, we'd love your feedback. Drop your Wafer API key in and tell us what breaks.\n\nIf you're building an agent or coding tool and want a default model layer, let's talk.\n\nEmail: [**emilio@wafer.ai**](mailto:emilio@wafer.ai) · Book a 15-min call: **cal.com/wafer/quick-chat**",
        "url": "https://www.ycombinator.com/launches/Q9i-wafer-pass-flat-rate-access-to-the-fastest-open-source-llms",
        "votes": 7,
        "created_at": "2026-04-30T00:19:46.736Z"
      },
      {
        "id": 92210,
        "title": "👑 Wafer - Cursor for CUDA",
        "tagline": "AI agent that turns your slow PyTorch into fast GPU code, automatically",
        "body": "## \n\n## **TL;DR**\n\nThe best GPU engineers work at Nvidia and OpenAI for $2M+ packages. The rest of us are stuck with PyTorch code that uses &lt;50% of our hardware. We built Wafer for every team that can't afford a GPU optimization expert. Wafer takes your PyTorch and optimizes it with custom kernels. It monitors your inference workloads, catches inefficiencies, and fixes them automatically. You keep shipping fast. Wafer makes it run fast. No CUDA knowledge required, no million-dollar hires needed.\n\n**Ask:** Are you trying to make your inference faster, writing CUDA by hand, or do you know someone who is? Fill our our [interest ](https://www.herdora.com/)form or send us an email [contact@wafer.com](mailto:contact@herdora.com) to be added to our pilot program. See below for details.\n\nhttps://youtu.be/K6nEevvlOro\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n—\n\n### **🧙 The Problem**\n\nGetting AI models to run fast on GPUs requires a rare breed of engineer. \n\nThese GPU wizards:\n\n* Command $300k+ base salaries (if you can even find them)\n* Spend **months** hand-writing custom kernels for each model\n* Need to rewrite every kernel for new hardware\n\nEven worse: If you want to run on alternative GPUs or other accelerators, you need **different** **experts** to **rewrite all your kernels**. Most teams are stuck choosing between:\n\n* Paying $$$ for GPU talent\n* Accepting &lt;50% hardware utilization\n* Locked to one chip longer than they want\n\n---\n\n—\n\n### **🐄 How Wafer solves it**\n\nWafer does what those GPU engineering wizards do, automatically. Feed it your PyTorch code, and it generates the optimized kernels that would normally take months of manual work.\n\n**What you get:**\n\n* **Auto optimization** - Your PyTorch goes in, optimized GPU code comes out. Same model, **1.5 to 5x faster**. The kernels Wafer writes are what a senior CUDA engineer would write after weeks of profiling and tuning.\n* **Hardware portability** - NVIDIA can’t give you enough capacity? Want to try out AMD’s new MI350 series? Wafer makes your code fast on both in seconds. No rewrites, no performance penalties.\n* **Production monitoring** - Wafer watches your models in production, spots inefficiencies, and fixes them. Think of it as having a GPU expert on-call 24/7.\n\nYou write PyTorch. Wafer makes it run like it was hand-tuned by the best in the business. Wafer then monitors prod to track performance. No CUDA expertise needed on your team.\n\n—\n\n### **📢 Who This is For**\n\nYou should reach out if any of this sounds familiar:\n\n* You're an ML engineer but you **don't have time to learn CUDA**\n* Your cloud bill is killing you because your models only use 30-50% of each GPU\n* You **want to try cheaper GPUs** but can't risk your models running slower\n\n—\n\n### **👥 The Team**\n\n* **Steven Arellano** - Researched LLMs at UChicago and worked as an engineer at Two Sigma, Google, and Sei Labs.\n* **Emilio Andere** - Researched transformers for weather prediction at Argonne National Lab, adversarial ML at SANDLab, and an engineer at Elicit.\n\n🤝 Friends since freshman year at UChicago, where we were also roommates\n\n—\n\n### **🙏 Our Ask**\n\nIf you're running ML workloads on GPUs (or know someone who is), we'd love to add you to our pilot program. Email us at [contact@wafer.com](mailto:contact@herdora.com) or fill out our [interest form](https://herdora.com/) with your model type and current GPU setup.\n\nYou'll get the same optimizations that companies pay GPU consultants $50k+ to deliver except automated and in days instead of months.\n\n**Currently Onboarding:**\n\n* ML teams running inference at scale\n* Teams hitting latency requirements in production\n* Companies with growing GPU compute bills\n* Companies evaluating AMD or Intel GPUs\n\n**Send us an email:** [contact@wafer.com](mailto:contact@herdora.com)\n\n**Book a call:** [https://cal.com/wafer/20min](https://cal.com/herdora/20min)\n\n**Interest:** [https://www.wafer.ai/interest](https://www.herdora.com/interest)\n\n---\n\n---",
        "url": "https://www.ycombinator.com/launches/NzG-wafer-cursor-for-cuda",
        "votes": 103,
        "created_at": "2025-07-16T18:10:07.640Z"
      }
    ]
  },
  {
    "id": 30645,
    "name": "Panels",
    "slug": "panels",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f6701ac45e2897f58f58412507e74dbdbfa60235.png",
    "website": "https://www.usepanels.com/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Panels is an audio data platform that delivers high-quality speech datasets from vetted, diverse contributors to power training and evaluation of foundational voice models.",
    "one_liner": "Audio Data for AI Labs",
    "team_size": 1,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1755625983,
    "tags": [],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2025",
    "status": "Active",
    "industries": [
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      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/panels",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/panels.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/panelsinc/",
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    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/f6701ac45e2897f58f58412507e74dbdbfa60235.png",
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    "company_photos": [],
    "primary_partner": {
      "name": "Tyler Bosmeny",
      "url": "https://www.ycombinator.com/people/tyler-bosmeny"
    },
    "founders": [
      {
        "user_id": 1219845,
        "full_name": "Aaron Wenk",
        "title": "Founder/CEO",
        "founder_bio": "CEO @ Panels. Princeton ORFE. World Champion Rower. 2x National Champion Cyclist.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/aaron-wenk",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f30138bb50c149cc0c6b4838ae28f0736d591bb5.jpg"
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    "jobs": [
      {
        "id": 97234,
        "title": "Founding Engineer",
        "url": "https://www.ycombinator.com/companies/panels/jobs/ZxF3rjn-founding-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$120K - $200K",
        "equity_range": "0.50% - 1.50%",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
        "skills": []
      }
    ],
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    "launches": [
      {
        "id": 93156,
        "title": "Panels: Audio Data for AI Labs",
        "tagline": "We power voice AI with high-quality audio data.",
        "body": "Hi!\n\nWe’re Aaron and Jason, and we’re building Panels.\n\n**TL;DR** — Panels builds diverse, high-quality conversational audio datasets for training Voice AI models. If you or someone you know is working on voice and needs audio data, we’d love to talk!\n\nhttps://www.youtube.com/watch?v=auANpScmgls\n\n**Our Story**\n\nAaron and Jason met at Princeton University where they both studied Operations Research and Financial Engineering.\n\n* Aaron is a 1x world champion and 5x national champion rower. After leaving rowing, Aaron became a 2x national champion in cycling, racing on a professional team against former Tour de France winners.\n* Jason previously helped build and grow startups to millions of users and worked on the data team at Amazon. He also taught NLP at Princeton.\n\n**The problem**\n\nVoice AI is exploding: in the past three YC batches, 60+ companies have depended on voice models. But voice models live or die on the quality of their training data.\n\nLabs need datasets that reflect:\n\n* Languages (global coverage, not just English)\n* Accents (real-world variety)\n* Emotions & expressiveness (not monotone samples)\n* Demographics (ages, genders, cultural nuance)\n\nRight now, most labs struggle to source enough realistic, diverse, high-quality conversational audio.\n\n**Our solution**\n\nPanels delivers exactly that.\n\n* We have a network of 10,000+ vetted voice contributors\n* Coverage across 20+ languages and 100+ countries\n* Expressive, conversational audio datasets designed for training state-of-the-art voice models.\n\nThis makes Panels the reliable data provider for the labs building the future of Voice AI.\n\n**Who this is for**\n\n* Voice labs scaling foundational models\n* Research institutions working on speech, linguistics, and AI\n* Conversational AI startups wanting to finetune their agents\n\n**Our ask**\n\nIf you (or someone you know) is building in voice and needs high-quality audio data, we’d love to talk.\n\nEmail us at [📩founders@usepanels.com](mailto:%F0%9F%93%A9founders@usepanels.com)
 or ☎️[Book a call](https://cal.com/aaron-wenk/30min)\n\n![uploaded image](/media/?type=post&id=93156&key=user_uploads/1219845/a7f9773c-5a31-4132-b481-bbfa0ddb1f68)\n\n",
        "url": "https://www.ycombinator.com/launches/OEW-panels-audio-data-for-ai-labs",
        "votes": 21,
        "created_at": "2025-08-19T19:35:10.536Z"
      }
    ]
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  {
    "id": 30647,
    "name": "Cyberdesk",
    "slug": "cyberdesk",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b6deea0aa4e96211ac35f75ade0705df19758a8e.png",
    "website": "https://www.cyberdesk.io",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Cyberdesk is the first self learning computer use agent for developers to automate desktop workflows. \r\n\r\nFor example, one of our customers is building an AI agent for hospital patient intake, and they’re using us to automate an entire team of people manually clicking and typing into a desktop app to book appointments. \r\n\r\nWe launched mid July, and our agent is already operating in production environments, creating appointments in electronic health record apps and processing files in legacy ERPs.\r\n\r\nWe’ve built the first computer use agent that memorizes tasks and repeats them quickly while still adapting to unexpected changes on the screen. A good analogy is to how humans use computers: once we get used to an app, we use it much faster, while still adapting to random popups and crashes. This new paradigm for computer use will be needed by every company automating human workflows on computers.\r\n\r\nMahmoud previously built robotic process automation solutions impacting 20K+ employees at a Fortune 100 company. He also built AI & ML solutions at Baylor College of Medicine Neuroscience & Texas Children's Hospital + co-published a paper at the Rice Networks Group. \r\n\r\nAlan is ex-NASA and previously dropped out to be the first founding engineer at a PearX startup. He is a second time founder, having previously built and scaled a consumer AI app to thousands of paying users.\r\n\r\nComputer-use agents will automate the $6T dollars spent on enterprise knowledge work and Cyberdesk will be the platform to power this.\r\n\r\nWe’d love to talk with you!\r\nhttps://cal.com/mahmoud-al-madi-klrs5s/30min",
    "one_liner": "Self learning computer use agent for developers",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1749659433,
    "tags": [
      "Developer Tools",
      "Robotic Process Automation",
      "Workflow Automation",
      "Enterprise Software",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2025",
    "status": "Active",
    "industries": [
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      "Engineering, Product and Design"
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    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
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    "app_answers": null,
    "question_answers": [
      {
        "question": "How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)",
        "answer": "We met 2 years ago, connecting over our shared experiences at Rice, and our love of building things. We both ended up living at the same Hacker House in Menlo Park, called Incepto! We started Cyberdesk with the realization that it’s really hard to build a great computer use agent, especially when it comes to reliability, speed, and cost. We both lived in a 9×9 Airbnb room with a tiny bed and a single desk (we call it the Cyberdesk lol) and got Cyberdesk off the ground, building the MVP in a 6 days and getting a paid customer the next day through a cold email. \\\r\n\\\r\nCyberdesk was built to solve all three of the core problems with off the shelf computer use models: speed, reliability, and cost. We’re excited to deploy this architecture to the world and become the best developer framework for computer use."
      },
      {
        "question": "How did you decide to apply to Y Combinator? What was your experience applying, going through the batch, and fundraising at demo day?",
        "answer": "From the moment we started working together, we knew we wanted to go through YC together. It was a little over a month before the deadline for Summer 2025 came out when we started working together, so we got to work! We launched, got paid customers, and built out our infrastructure fast. A month later, we interviewed in person and got the call from Jon Xu the same night that we got in! It was one of the happiest days of our lives."
      },
      {
        "question": "What's the history of your company from getting started until the present day? What were the big inflection points?",
        "answer": "We started working together in late March (2025), with a shared goal of solving deep developer problems around computer use. We started off with an idea to help developers spin up virtual desktops for computer use agents in a single line of code. We shipped an MVP in 5 days and got a paid customer the next day through a cold email. For the next month, we kept shipping and looking for customers, and applied to YC with this idea. We found the product had interest from hobbyist developers, but for companies, there was much less pull because companies often already have VM infrastructure they are happy with. \\\r\n\\\r\nSo we made the call to pivot. We talked to over 100 developers in the computer use and robotic process automation space, and heard the same thing over and over: automating Windows desktops is an important yet extremely tedious process. You create a script once, then it breaks every time something changes in the app or a popup happens. Computer use agents were meant to solve that pain but even they were slow, costly, and non deterministic. That’s how we came up with the idea for what Cyberdesk is today - a layer on top of computer use agents that helps it memorize tasks it’s done before and repeat it consistently, 3 - 5x faster, and cheaply, while still falling back to computer use during popups and anomalies. We built an MVP in a week, and got our first pilot a week later. \\\r\n\\\r\nSince then we’ve been rapidly building out the product and closing more deals with startups and companies in healthcare, construction, accounting, and more, all of them using our agent to automate manual computer work they’ve struggled to automate before. "
      },
      {
        "question": "What is the core problem you are solving? Why is this a big problem? What made you decide to work on it?",
        "answer": "For a developer team to automate legacy desktop apps with poor APIs, they’ve often resorted to building brittle automation scripts (either in Python or using a legacy RPA tool like UiPath) or hiring unreliable remote workers to click on remote desktops. As they need to support more and more software and versions of that software, the development and maintenance times exponentially increases. \\\r\n\\\r\nEvery company in the world has repetitive manual desktop work that is bogging them down. On top of that, companies building AI agents are increasingly having to interface with desktop apps to perform full human workflows. This problem is pervasive and we’re excited to solve it."
      },
      {
        "question": "What is your long-term vision? If you truly succeed, what will be different about the world?",
        "answer": "Traditional robotic process automation is a $6 billion industry, yet it only services a tiny fraction of desktop tasks that can now be automated by our agent. In the long term, our agent will automate every manual computer task."
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    "url": "https://www.ycombinator.com/companies/cyberdesk",
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        "user_id": 1707002,
        "full_name": "Mahmoud Al-Madi",
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        "founder_bio": "Mahmoud graduated from Rice University with a degree in Electrical Engineering where he built AI & ML solutions at Baylor College of Medicine Neuroscience & Texas Children's Hospital + co-published a paper at the Rice Networks Group.\n\nAfter Rice, Mahmoud built RPA solutions impacting 20K+ employees at a Fortune 100 company, which inspired him to cofound Cyberdesk to build a computer use agent developers can use to automate desktop workflows.",
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        "id": 92540,
        "title": "Cyberdesk - The computer use agent for developers to automate legacy Windows apps",
        "tagline": "Automate legacy apps like EHRs, ERPs, and more with just a prompt and an API call to our agent",
        "body": "Hey everyone! We’re Mahmoud and Alan, co-founders of Cyberdesk.\n\n**🏆 TL;DR:**\n\nWe’re building a computer use agent for developers to automate legacy Windows apps like EHRs, ERPs, and more. Just write your task in plain English, and call our API to trigger our agent. Our agent is designed to follow memorized steps reliably, only falling back to computer use models during expected popups.\n\nhttps://www.youtube.com/watch?v=yCDGsiCNb3E\n\n**❌ The Problem**\n\nDevelopers in industries like healthcare, supply chain, and beyond often work with clients who have old, legacy Windows software. Today, to work with these clients, they probably:\n\n* Hire unreliable offshore teams to manually click through remote desktops\n* Write fragile automation scripts that break on popups and need constant fixes\n* Skip the integration entirely—leaving valuable customers behind\n\n**✨ Our Solution**\n\nJust write your task in plain English, and our computer use agent will run it reliably, cheap, and fast, on any Windows PC (cloud or on prem).\n\nExample: entering patient data into OpenDental, a legacy dental EHR (real use case from one of our customers)\n\n1. **Write the task** (”Log in to Opendental, click Patients, find this dropdown, etc”), then just call our API to trigger the workflow\n2. **Our agent learns the task.** Every time it repeats the task, it does it 100% deterministically, upwards of 3x faster, and almost zero cost\n3. **If something unexpected happens** (like a popup), our system falls back to the computer use agent, and memorizes that trajectory too\n\n![uploaded image](/media/?type=post&id=92540&key=user_uploads/1707002/d09c26db-4734-4c16-8324-e5e0657e6512)\n\n**💯 The Team**\n\nMahmoud (CEO) previously scaled robotic process automation solutions to 20k employees at a Fortune 100. Alan (CTO) is ex-NASA and built a computer use agent at his previous startup.\n\n**Book a demo with us, or intro us to AI companies in regulated industries who need to integrate into legacy desktop apps!**\n\n* Book demo: https://cal.com/mahmoud-al-madi-klrs5s/30min\n* Our website: https://cyberdesk.io\n* Email us: mahmoud \\[at\\] cyberdesk \\[dot\\] io\n\n![uploaded image](/media/?type=post&id=92540&key=user_uploads/1707002/ca98113f-44e9-44ce-ab9b-20e5ea40354a)\n\n",
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        "votes": 34,
        "created_at": "2025-07-29T15:47:24.669Z"
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "We're a dense, small team in SF building the open source platform for working with agents.",
    "one_liner": "Do your life's work with agents",
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        "full_name": "Pablo Hansen",
        "title": "Founder",
        "founder_bio": "I finished my master's degree in AI at 19 and was then hire #1 at Onyx (YC W24) for a year before starting Proliferate (fka. Keystone).",
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        "linkedin_url": "https://linkedin.com/in/pablo-hansen",
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        "title": "Founding Product Engineer",
        "url": "https://www.ycombinator.com/companies/proliferate/jobs/OgpCKYJ-founding-product-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
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        "equity_range": "0.30% - 1.50%",
        "experience": "Any (new grads ok)",
        "visa": "Will sponsor",
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    "news": [
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        "title": "The 9 most sought-after startups from YC Demo Day | TechCrunch",
        "url": "https://techcrunch.com/2025/09/15/the-9-most-sought-after-startups-from-yc-demo-day/",
        "date": "Sep 15, 2025"
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      {
        "id": 98080,
        "title": "Proliferate: the open source company coding agent",
        "tagline": "Build yourself an AI coworker that actually takes work off your plate",
        "body": "**TL;DR:** Local coding agents can't do real end-to-end work at your company. Proliferate is the open-source, self-hostable platform for building company-specific background agents that can. Agents get their own sandboxes with secure access to your internal services, trigger from any event, and expose a live, multiplayer preview so your team can verify the work together. MIT licensed.\n\n**Star the repo:** <https://github.com/proliferate-ai/proliferate>\n\n**Get started self-hosting:** <https://docs.proliferate.com/>\n\n**Sign up for self-serve waitlist:** <https://proliferate.com/waitlist>\n\n**The Problem**\n\nCoding agents today hit a wall the second they need to do real work. Fixing an actual bug means querying your staging database, reading internal Datadog logs, hitting proprietary APIs. You can't hand those keys to a generic cloud SaaS agent.\n\nSo you run agents locally. But that ties up your machine, forces you to babysit a terminal, and traps all the context on your laptop where nobody else can see it.\n\nThe most forward-looking engineering orgs- Stripe, Ramp, coinbase- spent months building custom infrastructure to solve this. Some are now merging 50+% of their PRs with agents.\n\nProliferate open-sources that infrastructure so every team can do the same.\n\n**What teams use Proliferate for:**\n\n* **On-call triage:** Sentry exception fires → agent reproduces the issue in a cloud sandbox → writes a fix → shares a live preview link in Slack for the team to verify.\n* **Flaky test sweeps:** Cron job runs overnight → agent isolates flaky CI tests by running them 1,000x → PR is waiting by morning.\n* **Mass migrations:** Bump React versions or internal API contracts across 50 microservices and fix the resulting breaking changes- automatically.\n* **Team verification:** Agent gets a feature 80% done. Instead of reading the diff, the team clicks a live preview URL. A developer jumps into the shared terminal to fix the last failing test. Feature is merged.\n\n**Demo: [https://youtu.be/H84HrOJx4QM](https://youtu.be/H84HrOJx4QM)**\n\n**What makes it different**\n\nEvery agent gets its own sandbox with your Docker containers running, secure access to your internal services via our action catalog, and can be configured to respond to any trigger. Your code and data stay in your control- fully self-hostable, MIT licensed.\n\nAnother large difference comes with how your team interacts with the work. Reading AI-generated code is tedious. So every session produces a live UR. Sessions are multiplayer. Anyone on the team can jump in, check logs, or steer the agent in real-time.\n\n**Our ask:** ⭐ Star the repo- we just open-sourced it. <https://github.com/proliferate-ai/proliferate>\n\nIf you're tired of handholding local agents and want to move them to the background with real infrastructure access, reach out. We're working closely with a handful of teams to help improve their engineering velocity and adoption of AI. [Book a demo](https://cal.com/team/proliferate/demo) or email [pablo@proliferate.com](mailto:pablo@proliferate.com).",
        "url": "https://www.ycombinator.com/launches/PVw-proliferate-the-open-source-company-coding-agent",
        "votes": 31,
        "created_at": "2026-02-23T14:58:55.138Z"
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    "name": "Magnitude",
    "slug": "magnitude",
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    "website": "https://magnitude.dev",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Magnitude is an open source inference engine that tunes its kernels on your hardware to find the fastest way to run each model. It's over 2x faster than Ollama and works on Apple Silicon, NVIDIA, AMD, or just a CPU. One click connects it to the agent you already use (Pi, OpenCode, Hermes, Codex, and more)",
    "one_liner": "Run open models as fast as your hardware allows",
    "team_size": 2,
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        "full_name": "Tom Greenwald",
        "title": "Founder/CEO",
        "founder_bio": "CEO at Magnitude. Studied CS at Northeastern. Ran special projects as a PM at SimpliSafe",
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    "one_liner": "Firmware in minutes, not months - rigorously tested on real hardware",
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        "user_id": 2669426,
        "full_name": "Noah Pacik-Nelson",
        "title": "Founder/CEO",
        "founder_bio": "Noah is the co-founder and CEO of BootLoop. He was a researcher in Accenture’s AI Refinery, building agents for the Fortune 500. Prior, he worked on neuromorphic computing and ultra-low power AI at Accenture Labs and the MIT Media Lab. As CTO of the Ventilator Project, he led work on an FDA-authorized ventilator featured in the Smithsonian and winner of the Autodesk Excellence Award. He has three patents and seven papers across digital signal processing, energy harvesting, and 3D printing.",
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        "full_name": "Chris Markus",
        "title": "Founder/CTO",
        "founder_bio": "Co-founder and CTO of BootLoop. Former lead software engineer for SpaceX's Starship booster catch system. Built SpaceX’s Raptor engine firmware from first fire to flight. Before SpaceX, a visiting researcher at MIT Media Lab designing EEG electronics and firmware lead for an FDA-authorized ventilator.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/chris-markus/",
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        "title": "Founding Embedded Engineer",
        "url": "https://www.ycombinator.com/companies/bootloop/jobs/ZEkiBte-founding-embedded-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Embedded systems",
        "salary_range": "$180K - $280K",
        "equity_range": "1.50% - 3.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": [
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          "C++",
          "Embedded Linux",
          "Firmware",
          "Microcontrollers",
          "FPGAs"
        ]
      }
    ],
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        "id": 92063,
        "title": "BootLoop - AI Agent for Firmware & Embedded Software",
        "tagline": "AI that writes, tests, and debugs firmware on real hardware in minutes.",
        "body": "## **TL;DR**\n\nAll modern hardware needs firmware but it’s expensive, time-consuming and bugs in the field can lead to multi-million dollar recalls. BootLoop is building an AI agent to deliver custom firmware, fully tested on your hardware, in minutes not months. Our team built the firmware for SpaceX’s Raptor engine from first fire to flight, made brain-computer interfaces at MIT, and is _embedding_ that experience into our agent.\n\n**Ask:** Are you building hardware or do you know someone who is? Email us at [founders@bootloop.ai](mailto:founders@bootloop.ai) to be added to our pilot program. See below for details.\n\nhttps://www.youtube.com/watch?v=GBI1fkx5Bss\n\n## **❌ The Problem**\n\nAll modern hardware needs firmware, but writing firmware is hard. It’s difficult to debug and tricky to validate and chip datasheets can reach upwards of 3000 pages. On top of that, there’s a shortage of qualified firmware engineers. As hardware gets more complex, the time and cost to write firmware for it goes up exponentially.\n\n**The problems are staggering:**\n\n* The hardware world is **incredibly fractured** - over 65 different major manufacturers, producing over 80,000 unique chips, each of which has different software stacks, different frameworks, and different capabilities\n* Modern hardware requires sophisticated networking stacks, power optimization, and advanced security, driving up complexity\n* Firmware engineers are hard to find - **you can't major in firmware engineering** - and even the most attractive engineering companies take up to **6 months to find a qualified engineer**\n\n## **🤖 Our Solution**\n\nWe’re building an AI agent specifically for firmware and embedded software development, with the context and tooling needed to write low-level code and validate it on hardware in real-time.\n\n**Key capabilities of our Agent:**\n\n* **Deep hardware understanding:** Ingests your documentation, datasheets, schematics, system diagrams, existing codebases, and more…\n* **Hardware interaction:** Talks directly with your boards and test equipment like oscilloscopes, logic analyzers, and hardware debuggers\n* **Real testing:** Validates code on actual hardware or in simulation\n* **Framework expertise:** Writes in your language and style using your preferred embedded frameworks and proprietary libraries\n* **ITAR compliance:** The first ITAR-capable coding agent, opening massive aerospace and defense markets\n\n**Pilot program:** Our team will work with you as forward-deployed engineers on a specific firmware problem. We’ll use our agent internally to deliver aerospace-grade code FAST, with a human validating every line. After the pilot, we’ll deploy your custom version of the BootLoop agent for your future firmware needs.\n\n## **👥 The Team**\n\n**Chris Markus (CTO)** - Former **lead software engineer for SpaceX's Starship booster catch system**. He also built SpaceX’s **Raptor engine firmware from first fire to flight**. Before SpaceX, he was a visiting researcher at MIT Media Lab designing EEG electronics and firmware lead for an FDA-authorized ventilator.\n\n**Noah Pacik-Nelson (CEO)** - Formerly at Accenture’s AI Refinery, he **built agents for Fortune 500 companies**. Prior, he researched neuromorphic computing and ultra-low power edge AI at Accenture Labs. He has **patents and papers across AI adaptation, digital signal processing, and energy harvesting** and was a visiting researcher at the MIT Media Lab, building brain-computer interfaces for ALS patients.\n\n## **🙏 Our Ask**\n\n**If you're building hardware (or know someone who is), we'd love to add you to our pilot program.** Email us at [founders@bootloop.ai](mailto:founders@bootloop.ai) to get on the list.\n\nDuring the pilot, we’ll create your firmware FAST, using the BootLoop agent internally while reviewing every line by hand to ensure it meets our rigorous standards.\n\n**Currently Onboarding:**\n\n* Deep tech companies\n* Aerospace & defense contractors\n* Medical device manufacturers\n* Robotics companies\n* IoT hardware developers\n\n![uploaded image](/media/?type=post&id=92063&key=user_uploads/2669426/4b1f40ab-f41d-4013-bdd5-a557a8faf4a3)\n\n",
        "url": "https://www.ycombinator.com/launches/Nwt-bootloop-ai-agent-for-firmware-embedded-software",
        "votes": 74,
        "created_at": "2025-07-11T14:54:46.832Z"
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    "all_locations": "San Francisco, CA, USA",
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        "full_name": "Rohan Joshi",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder and CEO at Stellon Labs where we train open-source frontier speech models! \nWe're better known as KittenML (kittenml.com)\nCheckout KittenTTS at https://github.com/KittenML/KittenTTS \n\nEx-Meta Research, CMU SCS",
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      {
        "user_id": 741714,
        "full_name": "Divam Gupta",
        "title": "Founder/CTO",
        "founder_bio": "Packing intelligence in super-tiny AI models. \n",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/divamgupta",
        "x_url": "https://x.com/divamgupta",
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        "id": 93181,
        "title": "Stellon Labs: Building Tiny AI Models for Edge Devices",
        "tagline": "We build super-tiny frontier models that can run literally anywhere - No GPU Required! ",
        "body": "[Launch Video](https://www.youtube.com/watch?v=aUoLxgi5hQA)\\\n\\\n**The problem:**\\\nExisting foundation models are so large that they need an insane amount of compute and memory, making them inaccessible for edge devices like smartphones, laptops, robots and other embedded systems. \\\n\\\n**What we do:**\\\nWe are training state-of-the-art tiny models designed specially to run on these devices without compromising on quality. Our first model is KittenTTS 😻 , which is a tiny open-source text-to-speech model that is under 25MB in size. It got 8K Github stars and 45K model downloads within 2 weeks of launch. At Stellon Labs, we are building tiny frontier models for Speech, Language and Video intelligence to power every single device in the world.\\\n\\\n**Our ask:**\\\nWe would like to connect with developers or companies( both software and hardware) that are interested in running AI models locally. We are happy to provide support for custom models, training and deployments across different applications.\\\n\\\n**Our links:**\\\nGithub - https://github.com/KittenML/KittenTTS (pls star ^^)\\\nWebsite - [https://stellonlabs.com](https://stellonlabs.com/)\\\nEmail - [info@stellonlabs.com](mailto:info@stellonlabs.com)",
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        "votes": 20,
        "created_at": "2025-08-20T06:10:11.895Z"
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    "long_description": "Building AI agents for autonomous embedded software development.",
    "one_liner": "Hardware-Aware AI for Embedded Software",
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    "url": "https://www.ycombinator.com/companies/embedder",
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    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
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      "url": "https://www.ycombinator.com/people/jared-friedman"
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    "founders": [
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        "user_id": 2361352,
        "full_name": "Ethan Gibbs",
        "title": "Founder/CEO",
        "founder_bio": "Co-Founder & CEO at Embedder. Michigan Alumni.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/etgibbs/",
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        "user_id": 2605399,
        "full_name": "Bob Wei",
        "title": "Founder/CTO",
        "founder_bio": "Co-Founder & CTO at Embedder (YC S25). Michigan Dropout.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jiachew",
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    "news": [
      {
        "title": "Embedder and SEGGER Partner to bring Autonomous Firmware Development Closer to Reality",
        "url": "https://embedder.com/news/embedder-and-segger-partner-to-bring-autonomous-firmware-development-closer-to-reality",
        "date": "Sep 10, 2026"
      },
      {
        "title": "Embedder Joins the Zephyr Project",
        "url": "https://embedder.com/news/embedder-joins-the-zephyr-project",
        "date": "Sep 09, 2026"
      },
      {
        "title": "Embedder and Joulescope Partner to Close the Loop on Firmware Power Optimization",
        "url": "https://embedder.com/news/embedder-and-joulescope-partner-to-close-the-loop-on-firmware-power-optimization",
        "date": "Jul 22, 2026"
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        "title": "Embedder and Verkor Partner to Take Agentic AI From Chip Design to Working Firmware",
        "url": "https://embedder.com/news/embedder-and-verkor-partner-to-take-agentic-ai-from-chip-design-to-working-firmware",
        "date": "Jul 14, 2026"
      },
      {
        "title": "\n\tStart-Up Profile: Embedder\n",
        "url": "https://www.epdtonthenet.net/article/222023/Start-Up-Profile--Embedder.aspx",
        "date": "May 15, 2026"
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      "name": "Tyler Bosmeny",
      "url": "https://www.ycombinator.com/people/tyler-bosmeny"
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        "user_id": 1097474,
        "full_name": "Yuvan Sundrani",
        "title": "Founder/CEO",
        "founder_bio": "Lifetime builder. \nHuge superhero fan, started with builds ranging from co2-powered web-shooters to wrist-mounted flamethrowers.\nCo-founded a contact sharing app in 2020. Engineer #1 to CPO at martech startup (~7 fig ARR). Engineer #1 at AI-therapy startup.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/yuvan-sundrani/",
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      {
        "user_id": 1097137,
        "full_name": "Jason Steinberg",
        "title": "Founder",
        "founder_bio": "Co-Founder @ Autosana\nPlayed club hockey at the University of Maryland. Worked on the founding team of multiple mobile-first startups and wore many hats. Went on a two-month bike trip across America after graduation, and now making mobile QA a heck of a lot easier.",
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      {
        "id": 100020,
        "title": "Autosana 2.0: The E2E validation layer for mobile & web apps",
        "tagline": "Close the E2E testing and QA loop with your coding agents across iOS, Android, and web apps",
        "body": "Coding tools have 10x’d not only dev speed, but also the surface area for bugs. The bottleneck has shifted to validating that features and fixes _actually_ work. \n\nYour team is probably spending hours doing at least one of these things:\n\n* Manually testing for regressions\n* Writing and maintaining brittle E2E test scripts\n* Saying “f\\*ck it, ship it,” way too often\n\nAll while still having users complain about bugs that slip into prod…\n\n“Can’t my coding agent just write my E2E tests for me?”\n\nSure - but now you’re stuck maintaining them as your app evolves - broken selectors, missing element IDs, new user journeys, non-deterministic environments, evolving infra requirements…\n\nNot to mention the cases that are nearly impossible to test with scripts in the first place: Apple Pay, in-app browser flows, complex swipes, drag-and-drop, magic links, OAuth, cross-app auth, etc…\n\nThis is why we built **Autosana** - **the agentic E2E testing layer to close the loop with your coding agents.** Fully vision based, testing your app like humans would. \n\n* Get onboarded seamlessly via our [MCP](https://docs.autosana.ai/mcp-setup)\n* Runs locally and in our cloud for multi-env testing\n* Code review + E2E testing in your PR with video proof\n* Tests evolving with your codebase, creating & running tests based on PR context and code diffs\n* Works across iOS, Android, mobile web, and desktop web\n\n[**\\[demo\\]**](https://youtu.be/DcCf6Knt5LY)\n\nGet started today @ [autosana.ai](https://autosana.ai)",
        "url": "https://www.ycombinator.com/launches/Q1E-autosana-2-0-the-e2e-validation-layer-for-mobile-web-apps",
        "votes": 9,
        "created_at": "2026-04-21T23:31:01.594Z"
      },
      {
        "id": 91958,
        "title": "Autosana - AI QA Agent for Mobile Apps",
        "tagline": "Autosana catches bugs in iOS and Android apps before users do.",
        "body": "Hey guys!\n\nWe’re Uv and Jason from Autosana 🌊\n\nWe’re building a QA agent that tests mobile apps like a real user. We’re on a mission to make flaky selector-based test scripts (or worse, manual regression testing) things of the past.\n\n[Demo here :)](https://www.youtube.com/watch?v=zsY22nvcVLU)\n\n# **TL;DR**\n\n* Cloud-hosted mobile QA agent (iOS and Android)\n* Natural language → simulated user flows\n* Integrates into CI/CD\n* Saves 8+ eng. hours per deployment\n\n# **Problem**\n\n**Dev Tools Have Evolved — QA Tools Haven’t**\n\nTools like Cursor and Claude Code boost dev speed by 10x, but lack the runtime context to write E2E tests, especially for complex and non-deterministic flows.\n\n**The QA Bottleneck**\n\nMaintaining traditional end-to-end scripts using frameworks like Appium, Espresso, and XCUITest wastes valuable engineering resources (trust us, we’ve been there).\n\nThese tests are tedious to write, brittle, and routinely break with UI changes. Many mobile teams ($100B+ companies included) have abandoned them and rely on manual QA.\n\n# **Solution**\n\nWe started Autosana to fix the QA bottleneck and help mobile teams ship faster without fear of breaking things.\n\nJust describe your test flows with natural language, as if you’re talking to your own **in-house QA Engineer**. No code, no infra setup, no dependence on flaky element selectors, and no more manual work.\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXcjScvXfMAllmoIBOAw31yGfHnfgGPt1V2yHBXQfJBTgIg-hFIAaTelmPZb0FJTtGFKjQd8PY-Ia55kJPaoYXTRneqpG3mgKr5bvV3dvZnvPxxdrVW2S2WqHsfzq8RiEToivqsjlg?key=-q2ZKYYIwen11jHmsUW6pg)\n\nOur agent tests your app like a real user, as **part of your CI/CD** pipeline or on a schedule, and **reports to the team when bugs are found**.\n\nAutosana supports both iOS and Android, and is framework-agnostic (we support React Native, Flutter, Swift, Kotlin, you name it…).\n\n**Mobile QA shouldn’t be hard. We’re on a mission to fix the bottleneck between mobile development and testing.**\n\nHave a bug-free day (or many bug-free days, with Autosana &lt;3)\n\n[autosana.ai](http://autosana.ai)\n\n![uploaded image](/media/?type=post&id=91958&key=user_uploads/1097474/10f8ca06-2216-4458-a6fa-11a60c43ff50)\n\n",
        "url": "https://www.ycombinator.com/launches/NvC-autosana-ai-qa-agent-for-mobile-apps",
        "votes": 84,
        "created_at": "2025-07-08T15:59:20.183Z"
      }
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    "id": 30722,
    "name": "Omnara",
    "slug": "omnara",
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    "website": "https://omnara.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Omnara is an open-source, model-agnostic control plane for managed agents. One API to deploy, run, and control them. Self-host it, or use our managed cloud.\r\n",
    "one_liner": "The Open-Source Alternative to Claude Managed Agents",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/omnara",
    "x_url": "https://x.com/omnaraai",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/omnara-ai/omnara",
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    ],
    "primary_partner": {
      "name": "Harj Taggar",
      "url": "https://www.ycombinator.com/people/harj-taggar"
    },
    "founders": [
      {
        "user_id": 1391601,
        "full_name": "Ishaan Sehgal",
        "title": "Founder/CEO",
        "founder_bio": "Building omnara.com, the open-source alternative to claude managed agents! Omnara is an API that allows you to create and interact with AI agents easily. Previously I was an AI infra engineer at Microsoft, where I built and led Kaito (https://github.com/kaito-project/kaito/graphs/contributors). Before that, I worked on ML at Windsor (YC W19, acquired 2024) and interned at Roblox. I hold a BS/MCS in CS from UIUC.\n",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/ishaan-sehgal/",
        "x_url": "https://x.com/IshSup",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0f702aad21a666e365673f7c3eaa8c993047de42.jpg"
      },
      {
        "user_id": 2661368,
        "full_name": "Kartik Sarangmath",
        "title": "Founder/CTO",
        "founder_bio": "Commanding my fleet of AI agents at omnara.com. \nPreviously at ThirdAI, optimizing neural networks for CPU deployment. Completed BS and MS in Computer Science at Georgia Tech focusing on computer vision research, publishing 3 papers and training large multimodal models at Meta AI.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/kartiksarangmath/",
        "x_url": "https://x.com/kartiksmath",
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      }
    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 112080,
        "title": "Omnara: The API for Production-Ready agents",
        "tagline": "Open-source alternative to claude managed agents",
        "body": "Omnara is an open-source platform for creating and interacting with production-ready agents via an API, without having to worry about the tedious parts of managing an agent control plane. It’s an open-source alternative to Claude Managed Agents, Langchain Managed Agents, Vercel Eve, etc.\n\n## **Problem:**\n\n---\n\nBuilding agents is hard. Many companies are building agent control planes, both for internal use and external use. The common pattern is you use some local agent framework, like claude agent sdk, mastra, langchain, or your own loop, host that on VMs/kubernetes/workers, expose an API with endpoints to interact with agents, handle machine failures, resumption of an agent, provisioning sandbox environments so those agents can code, configure endpoints to add skills and MCPs, have user message tracking, audit logs, and on and on.\n\nIt’s a lot of infrastructure work that has nothing to do with what the agent actually does. And most teams end up having to build and maintain their own versions of it.\n\nOmnara is that layer. It provides this infrastructure for you. So you can create and interact with your agents through a standard API without having to worry about building and maintaining your own control plane.\n\n![uploaded image](/media/?type=post&id=112080&key=user_uploads/1391601/7b5a0575-9a32-4af8-966f-9b6370e74edc)\n\n## **Bring your own computer:**\n\nRun this on any linux or macOS machine (windows coming soon): \\\n**curl -fsSL https://app.omnara.com/install/omnarad.sh | sh**\\\nIt connects the machine to the Omnara control plane. You can then give any agent access to this machine. This allows you to spin up an EC2 instance and have your agents use that as a persistent machine, or even run it on your macbook so that cloud agents can directly edit files locally when it’s online. You can also bring your own sandbox provider API keys (currently we support Blaxel, Daytona, and Unikraft).\n\n![uploaded image](/media/?type=post&id=112080&key=user_uploads/1391601/55bd57b2-62f9-414e-8acc-405797264d3a)\n\n## **Bring your own model:**\n\nOmnara allows you to bring your own LLM endpoint and API key (we support OpenAI Responses, OpenAI Completions, and Anthropic Messages formats, with more coming soon). You can use your hundreds of thousands of free LLM credits from YC in Omnara!\n\n![uploaded image](/media/?type=post&id=112080&key=user_uploads/1391601/12802420-8c49-4609-bd5c-9b7df94954f6)\n\n---\n\nBecause you can bring your own machine and models, you can use Omnara for completely free! Our architecture allows us to efficiently host hundreds of millions of agents on minimal hardware, so we can easily eat that cost.\n\nIf you prefer our hosted models (via openrouter) and hosted sandboxes (via blaxel), we're giving $1,000 in credits to the first 50 teams building on Omnara. Email us at [**contact@omnara.com**](mailto:contact@omnara.com) with what you're building and we’ll apply the credits to your organization.\n\nIf you want help self-hosting the control plane or running it in your VPC/on-prem, we’re taking on five design partners. Email [**ishaan@omnara.com**](mailto:ishaan@omnara.com).\n\nWebsite: [**omnara.com**](http://omnara.com) \\\nApp: [**app.omnara.com**](http://app.omnara.com) \\\nDocs: [**docs.omnara.com**](http://docs.omnara.com) \\\nSource: [**github.com/omnara-ai/omnara**](http://github.com/omnara-ai/omnara)",
        "url": "https://www.ycombinator.com/launches/T9k-omnara-the-api-for-production-ready-agents",
        "votes": 10,
        "created_at": "2026-08-24T18:26:24.991Z"
      },
      {
        "id": 97081,
        "title": "Omnara: Run Claude Code from Anywhere 🤖",
        "tagline": "Stay involved with your coding agents without being at your desk",
        "body": "We’re Ishaan and Kartik, and we’re building **Omnara**, a web and mobile interface for Claude Code that lets you keep coding agents moving even when you’re away from your desk.\n\n🎥 Demo:[ https://x.com/i/status/2014383431845839186](https://x.com/i/status/2014383431845839186)\n\n## **❌ The Problem**\n\nCoding agents can work independently for long stretches, but they still block on human input.\n\nIf an agent needs clarification while you’re away, everything pauses.\\\nIf your laptop sleeps, long-running work stops.\\\nMost remote agent tools run in hosted environments instead of where your code actually lives.\n\nAgents should fit around your schedule, not the other way around.\n\n## **🛠️ The Solution**\n\n**Omnara makes working with coding agents feel continuous instead of fragile.**\n\nYou can:\n\n* Start agents locally and stay involved from anywhere using web or mobile\n* Keep work moving even if your laptop goes offline\n* Talk to agents using voice when typing isn’t convenient\n\n## **🔒 Run agents in your environment, access them from anywhere**\n\nWith Omnara, your coding agent runs on your own machine, whether that’s your laptop or a remote VM you control.\n\nYou can access and interact with that agent from anywhere, securely, without SSH, port forwarding, or tunneling.\n\nYour agent runs in your real environment, but you’re not tied to the machine it’s running on.\n\n![uploaded image](/media/?type=post&id=97081&key=user_uploads/2661368/81388baf-658a-4c43-94ac-1ce4e17a1605)\n\n## **☁️ Keep agents running when your machine is off**\n\nAgents shouldn’t stop just because your laptop does.\n\nIf your machine goes offline, Omnara can keep the agent running in the cloud so work continues. You can still interact from web or mobile, and when you’re back at your desk, you can pick up where things left off.\n\n![uploaded image](/media/?type=post&id=97081&key=user_uploads/2661368/098a8bf1-046d-4362-86b2-63d984e999dd)\n\n## **🎙️ Talk to your coding agent**\n\nMobile typing works for quick replies, but it’s not great for longer back and forth.\n\nOmnara includes voice so you can talk to your coding agent when typing isn’t convenient. Speaking tends to provide more context and makes it easier to iterate, especially while walking or multitasking.\n\n![uploaded image](/media/?type=post&id=97081&key=user_uploads/2661368/829c73b5-6a60-41e8-a9c3-0fa98de80d39)\n\n## **💸 Pricing**\n\n* Free: up to 10 agent sessions per month\n* $20/month: unlimited sessions\n* When agents run in your environment, you can use your existing Claude Pro or Max subscription\n\n## **🙏 Our Ask**\n\nIf you use Claude Code or rely on long-running coding agents, we’d love your feedback.\n\n👉 Try it: [omnara.com](https://www.omnara.com/)\n\n[👉](https://www.omnara.com\\)%F0%9F%91%89) Install in one line:\\\ncurl -fsSL <https://omnara.com/install/install.sh> | bash\n\n👉 Reach us: [founders@omnara.com](mailto:founders@omnara.com)\n\n— Ishaan & Kartik\n\n![uploaded image](/media/?type=post&id=97081&key=user_uploads/2661368/6ef3e27b-3742-4e1a-9d77-1ec8a6c5bc41)\n\n",
        "url": "https://www.ycombinator.com/launches/PFp-omnara-run-claude-code-from-anywhere",
        "votes": 17,
        "created_at": "2026-01-23T20:07:51.104Z"
      },
      {
        "id": 93029,
        "title": "Omnara - The first command center for AI agents: terminal, web, and mobile",
        "tagline": "Run Claude Code from anywhere and switch seamlessly between devices",
        "body": "https://www.loom.com/share/03d30efcf8e44035af03cbfebf840c73\n\nStart Claude Code in the terminal, then pick it up instantly on web or mobile with a seamless handoff between all three\n\n### The Problem\n\nClaude Code is incredible, but it chains you to your desk.\\\nOnce an agent starts working, you’re stuck waiting in the terminal for it to ask you something. That could take 5–10 minutes, and if you’re away, progress halts. We’ve coded from our beds, on walks, in Ubers, while doing laundry… and yes, even on the toilet — but only after we built Omnara.\n\nExisting solutions don’t solve this well:\n\n* **Other Claude Code wrappers** (e.g., Crystal, Conductor) often replace the native experience but don’t let you jump between terminal, web, and mobile.\n* **Terminal replication tools** (e.g., Vibetunnel, Termius) let you SSH in, but have no push notifications, clean diffs, or simple setup.\n\n### What’s Omnara?\n\nOmnara is the **first agent command center** — start an AI agent in the terminal, then continue the same session from our web dashboard or mobile app.\n\nWith Omnara, you can:\n\n* Launch agents from terminal, web, or mobile.\n* Switch between them instantly.\n* Get **real-time push notifications** when agents need your input.\n* Review logs, see Git diffs, and approve/reject changes with one tap.\n\n![uploaded image](/media/?type=post&id=93029&key=user_uploads/1391601/bf61f9ae-4f37-4377-90c8-fc2bed1d0866)\n\n**How it works**\\\nWe built a CLI wrapper that mirrors the native Claude Code experience — output, permissions, notifications, and mode switching — by parsing the session file at _\\~/.claude/projects_ and terminal output in real time. All agent and user messages are streamed via SSE to the Omnara platform, where you can respond from anywhere.\n\nIt’s fully open source: [github.com/omnara-ai/omnara](https://github.com/omnara-ai/omnara)\n\n![uploaded image](/media/?type=post&id=93029&key=user_uploads/1391601/837e9af0-e038-4bb1-9f1c-1ebf152f8157)\n\n### Why launch with Claude Code first?\n\nOmnara works with any AI agent, but Claude Code users immediately “get” the value. It’s the perfect human-in-the-loop use case — and the one we use every day.\n\nWe’ve also used Omnara as a human-in-the-loop node in n8n workflows, e.g., for replying to emails. This is just the beginning.\n\n![uploaded image](/media/?type=post&id=93029&key=user_uploads/1391601/96e585a6-db46-4a20-8901-0ddbc7e409cf)\n\n### Pricing\n\nFree for up to 10 agent sessions/month.\\\n$9/month for unlimited.\n\n### About Us\n\nWe’re **Ishaan & Kartik**, childhood friends since Montessori. We’ve spent years working in AI and AI infra at big tech and acquired startups and love building tools that remove friction for developers.\n\n### Try it free\n\n`pip install omnara && omnara`Then log in at [omnara.com](http://omnara.com) or download our iOS app: [Omnara on the App Store](https://apps.apple.com/us/app/omnara-ai-command-center/id674...)",
        "url": "https://www.ycombinator.com/launches/OCT-omnara-the-first-command-center-for-ai-agents-terminal-web-and-mobile",
        "votes": 25,
        "created_at": "2025-08-15T06:52:33.641Z"
      }
    ]
  },
  {
    "id": 30729,
    "name": "Floot",
    "slug": "floot",
    "former_names": [
      "Combini"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/1f34cf0cf02c3e2059e48082daf0ddc693722515.png",
    "website": "https://floot.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Floot is the layer where vibecoded software runs.\r\n\r\nSaaS is dead. Hundreds of millions of people already spend their day in Claude or ChatGPT - and increasingly, when they need an app, they won't buy one. They'll describe it, and it will exist.\r\n\r\nWe're building the infrastructure that makes that real. When Claude creates an app, it needs somewhere for that app to live: a backend, a database, hosting, a domain, the ability to scale, various services, maybe even to be able to work as a mobile app. Floot is that place - a full stack purpose-built for AI to operate, from a specialized framework that defines how AI writes and runs code, down to scalable hosting on AWS.\r\n\r\nThis means you can now build and ship real apps directly inside Claude and ChatGPT. Connect Floot, and the model you already pay for writes and debugs the code, shows a live preview, and publishes to your own domain. No need to wire up git, vercel, supabase and a dozen other providers. And no AI credits - every message runs on the subscription you already have, because we charge for the platform, not for a token markup.\r\n\r\nWe built Floot this way because we've watched the model layer commoditize - every serious builder writes good code now, including us. The lasting value isn't another agent between you and the model. It's the layer underneath, from wherever people already are. We're building Floot to be the home for all operation software, for the decades where most new software on earth is written by AI.\r\n\r\n✨ Try it: floot.com\r\n",
    "one_liner": "The app platform inside Claude and ChatGPT.",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1753721322,
    "tags": [
      "SaaS",
      "No-code",
      "Web Development",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2025",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/floot",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/floot.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/floothq/",
    "x_url": "https://x.com/floothq",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/1f34cf0cf02c3e2059e48082daf0ddc693722515.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
    },
    "founders": [
      {
        "user_id": 2071169,
        "full_name": "Yujian Yao",
        "title": "Founder/CEO",
        "founder_bio": "Yujian was a staff engineer at Retool where he rebuilt the entire Retool runtime powering every Retool app. Before that, he was an early engineer at Asana. He’s also a gold medalist in National Olympiad Informatics, Singapore.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/yjyao/",
        "x_url": "https://x.com/yyjhao",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/8e0d4160a3651f09be412d301746a264197e4261.jpg"
      }
    ],
    "jobs": [
      {
        "id": 82610,
        "title": "Founding Full-Stack Engineer",
        "url": "https://www.ycombinator.com/companies/floot/jobs/2rbWibL-founding-full-stack-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$150K - $220K",
        "equity_range": "0.25% - 2.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Node.js",
          "React",
          "TypeScript"
        ]
      },
      {
        "id": 82612,
        "title": "Founding Growth Marketer",
        "url": "https://www.ycombinator.com/companies/floot/jobs/gyHYJjj-founding-growth-marketer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Marketing",
        "role_type": null,
        "salary_range": "$100K - $180K",
        "equity_range": "0.10% - 1.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      }
    ],
    "news": [],
    "launches": [
      {
        "id": 112249,
        "title": "Floot - build and run your app with ChatGPT and Claude. No AI credits needed.",
        "tagline": "Floot gives your agent a place to write, test, and ship code - you never touch git, local files, or a thousand vendor accounts.",
        "body": "ChatGPT and Claude can already write you an app. Getting it live is another story.\\\n\\\n<https://www.youtube.com/watch?v=cFmZPUVfKCY>\n\nConnect Floot, and your AI becomes a full-stack app builder. You don’t get limited to your computer - the AI agent can use Floot on the web, in the desktop apps, or from your phone. The model you already pay for writes and debugs the code, shows you a live preview, and publishes to your own domain. No git, Vercel, Supabase, Resend, or OneSignal to set up - a stack of tools that was never built for you anyway.\n\n![uploaded image](/media/?type=post&id=112249&key=user_uploads/2071169/fcf08d3d-384b-4da1-bb8c-b342dbb8c478)\n\nAnd the part we're most excited about: Floot doesn't charge you AI credits.\n\nEvery message, every change, every random question uses the Claude or ChatGPT subscription you already have. No settling for a lesser model to make the credits last. Explore freely - test every idea, ask every question.\n\nTakes a minute to connect. Free to start → [**floot.com**](http://floot.com)",
        "url": "https://www.ycombinator.com/launches/TCT-floot-build-and-run-your-app-with-chatgpt-and-claude-no-ai-credits-needed",
        "votes": 22,
        "created_at": "2026-08-25T23:52:27.371Z"
      },
      {
        "id": 92516,
        "title": "Floot - The easiest and most powerful AI app builder",
        "tagline": "The fastest way for non-coders & entrepreneurs to build apps that actually work.",
        "body": "Hi everyone 👋 We’re Edward and Yujian, the founders of Floot!\n\n**TLDR:** Floot lets non-coders &amp; entrepreneurs build real web apps that actually work. We’re taking a new approach by building everything from the ground up for AI.\n\n✨ [Try building an app right now!](https://floot.com)\n\n# The Problem\n\nExisting AI app builders fall short of enabling non-coders to build real, serious apps. They often:\n\n* **Break down** when building anything more than a prototype or toy app\n* **Have non-coders stuck** with errors they don’t understand\n* **Require non-coders to handle multiple services** designed for developers (e.g. for backend, database, hosting, etc)\n\n**The fundamental problem**: these AI app builders just cobble together existing developer tools and slap AI on top, but these tools were designed for humans and not for AI.\n\nThe result? Non-coders get excited, start building, hit a wall, and then abandon their projects.\n\n# Our Solution\n\nFloot is purpose-built for AI. Our secret sauce:\n\n1. Instead of reusing a coding framework designed for humans, **we created a specialized framework** that dictates how AI should write code and how the code runs on our infrastructure. This allows us to enforce best practices, detect errors earlier, and give the best feedback to the AI. As a result, Floot can write better code and fix issues more effectively.\n2. **Floot has the entire tech stack built-in** (backend, database, hosting, etc) so building and managing an app feels seamless, especially for non-coders. And because we control every layer of the stack, we can optimize each layer for AI-first coding.\n\nBecause of this, **non-coders can get more done with less time** and prompting. They can finally **build serious apps** that work, instead of getting stuck in frustrating error loops and then abandoning their projects.\n\nWe also built a **highly scalable hosting system** directly on AWS so Floot apps can handle real traffic and business demands. This means non-coders can build, deploy, and scale their apps on a single platform seamlessly.\n\nPlus, **Floot is really fun to use**! It takes your prompt, breaks it down, and shows you how it accomplishes each step. If it sees a bug while building, it lets you know and fixes it right away.\n\nYou can even draw on your app to visually communicate the changes you want:\n\n![uploaded image](/media/?type=post&id=92516&key=user_uploads/2071169/b6bd69f7-9f86-4db9-929e-4ad3ab66b129)\n\n**Here’s what a customer said about Floot:**\n\n_I'd tried other platforms but could never advance far enough to feel truly productive. The time investment and constant token usage just to fix issues had me ready to hire a developer again. With Floot, I had a working app within a week, even working in my off-hours, and started beta testing with my team days later. We estimate Floot has saved us around $20,000 so far. Best of all, their customer support has gone above and beyond at every turn._\n\n✨ [Try Floot yourself!](https://floot.com) (bonus: build something you’ve made in other tools to compare)\n\n# Why are we building this?\n\nWe believe that existing tools are based on technologies built for human developers and ill-suited for the future of AI writing most of the code. The whole toolchain of building and maintaining software desperately needs to adapt to the new reality. We are starting with web apps with the goal of evolving into the new foundation of software, empowering the next generation of builders.\n\n# Team\n\n[Yujian](https://www.linkedin.com/in/yjyao/) was a staff software engineer at Retool and Asana. At Retool, he rebuilt the entire runtime to optimize the user experience for builders. At Asana, he built the rich editor that powers every task and comment. Yujian ranked 4th in the National Olympiad in Informatics, Singapore.\n\n[Edward](https://www.linkedin.com/in/edwlk/) scaled his SaaS to 10k+ customers by taking something technically complex and making it accessible to non-technical users, and now he’s doing the same with Floot. For his SaaS, he built a highly scalable and reliable distributed system to handle low-latency applications. Before that, Edward built infrastructure at AWS and studied CS at Berkeley.\n\n# Our ask\n\n✨ [Try building an app in minutes on Floot!](https://floot.com)\n\nWe’d love your feedback (even nitpicks!) - reach us at [founders@floot.com](mailto:founders@floot.com)\n\nKnow someone who needs to build an app? Have them try Floot :)\n\n![uploaded image](/media/?type=post&id=92516&key=user_uploads/2071169/d62a49f0-5907-44fa-8ff3-f9c374f1e8b0)\n\n",
        "url": "https://www.ycombinator.com/launches/O4C-floot-the-easiest-and-most-powerful-ai-app-builder",
        "votes": 63,
        "created_at": "2025-07-28T18:39:02.551Z"
      }
    ]
  },
  {
    "id": 30730,
    "name": "idler",
    "slug": "idler",
    "former_names": [
      "Idler"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3ab3b751ff1a6569beaba5e0f91c3c4dbcda3e55.png",
    "website": "https://idler.ai/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "idler is a frontier data research lab. We build the evals and environments that the world's leading frontier labs use to measure and train their models.",
    "one_liner": "Hill-climb any benchmark, for any model, in any domain.",
    "team_size": 12,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1749750449,
    "tags": [
      "Reinforcement Learning"
    ],
    "tags_highlighted": [],
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        "title": "Hera: Your AI Motion Designer",
        "tagline": "Hera is an AI motion designer that turns 5-hour animation projects into 5-minute tasks.",
        "body": "Hi 👋 We’re [Chia](https://www.linkedin.com/in/chialunwu/) and [Peter](https://www.linkedin.com/in/peter-tribelhorn-36a967142/), the founders of [Hera](https://hera.video/). \n\n**TL;DR:** \n\nCreating motion graphics is time-consuming and requires complicated software. Hera uses AI to make motion design radically faster and cheaper, helping users create over 50,000 animations to date.\n\n**Problem: Motion design is complicated, time-consuming, and expensive**\n\nPeter used to build YouTube channels and produced more than 240 videos. He spent thousands of dollars every week hiring motion designers to create infographics, text animations, or map animations. \n\nThere he realized that motion design is mostly about mastering complicated software with many buttons, not actual creative work. Here you can see how complicated, tedious, and time-consuming the leading tool, Adobe After Effects, is:\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXfBBfbxFI5I7GiBZBOEs2INi6E036flopQFfG9kZfVBl7gTUHWNX_2jnls3WG_TDRrrQ4a7tkJ5VMTVm1PM_vU0tV0HqrUnARtO10kFq_kztNYLQfDbSo42g-82UnKfbIX6dtxuug?key=ucB-AG1uSNxOnV5yBE4xiA)\n\nAfter talking to 130 video teams, ranging from YouTube channels, marketing agencies, and corporates, we learned:\n\n1. There is **no alternative to After Effects** to create professional motion graphics.\n2. **Mastering After Effects takes years** and watching countless tutorials/courses.\n3. Hence, **video teams hire expert motion designers.** \n4. And even for expert designers, it **can take hours to create seconds of motion design.**\n\n**Solution: Hera fills this gap by making motion design fast & easy**\n\nhttps://youtu.be/NFRllovZQS0?si=0gxZ2T4xQpTZrww6\n\nStart by describing your motion graphic in plain English\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXchUYGy7SO7-gjW07OdYD_6Os16OVlcVD6uCo28jPnuH85s0Potn0URq441tpUUPQOAx2xmX5Yqn7-cUokmO1nPRwnGE2RoIXspXqkhc9XBHzvveGdbA-LuUhN6pyixDxnsVeBG?key=ucB-AG1uSNxOnV5yBE4xiA)\n\nYou can tweak it as you like with on-canvas editing\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXf6vvFbbkBwRX9SNH6hGwOV56iU_Mgwps_OccAIm53W4RK_sProVckXJr1hq1ZDxSZrM2RMXnHpkQV6l7SwV1zH4tl7zh6iyljCbYtV3M7lRJw4PxA97Uq1A7TVrlF2ZxEytwt2?key=ucB-AG1uSNxOnV5yBE4xiA)\n\nPick an already created animation from other users and customize it\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXdhIJIFYIA0rMSOiojS2b2sAOEn8bi9FFkNkxWrbfwBdMBC117t0ZKWOm44KWK8ue8OiBsKnSgoso2CKrlrybZQOK4-kjwYtq7LawTqFOv7ZDCS2OsuC3xe23RZoauto0IQJC0m?key=ucB-AG1uSNxOnV5yBE4xiA)\n\nCreate your custom brand kit and all your animations will stay on-brand\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXfPO2y1hf2SAli6G7Suqh74NJ2erroMQNOvItSUrDZU8auZBUrMz68smd_fwa9yQIgkp2h7gNZWWiDhtLwgn3Q9DonrtZhuzyxkPWATsDD3_T_aOggWiph_lLCjDcvu-y9WPuEPQA?key=ucB-AG1uSNxOnV5yBE4xiA)\n\n**Customers: Everything changed the day we couldn’t stop people from using Hera**\n\nTwo months ago, we launched Hera to creators in our network. People started talking about Hera on the internet, and we got 3,000 users who created more than 15,000 animations within one week.\n\nToday, we have more than 100k people on our waitlist asking for access (and some are even selling invite codes).\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXdUpV6khJm6kOtoe-ks_d3RXXDl1u2A6sZPP8IDvC-F9pTYhiMHNtdrR2HxOCUb78qwOUf2E262ovKLBvvd7c3RT9-iq8qmQXfxtsgERRz7R0NOfwpqLtk1CZbJJcwRL1ca0LiNNA?key=ucB-AG1uSNxOnV5yBE4xiA)\n\n**Our Ask: If you answer “yes” to any of these, we’d love your help:**\n\n* Do you produce video content in-house and either already incorporate motion graphics or would like to incorporate motion graphics? \n* Can you introduce us to marketing/advertising agencies that focus on creating video advertisements? \n* Can you introduce us to video publishers (e.g., traditional publishers, YouTube channels, influencers) who might be interested in making motion design faster and cheaper?\n\nSkip the waitlist and try out Hera today: https://hera.video/join/yc\n\n👉 Contact us at [peter@hera.video](mailto:peter@hera.video)\n\nYour help can make a huge difference. **Thank you!**\n\n**Team: We know our customers and tech inside out**\n\nPeter acquired and built leading YouTube channels with +30 million subscribers at Lunar X (e.g., Economics Explained, Game Theorists). He produced +240 videos and spent thousands every week on motion designers.\n\nChia was one of the first developers at Vyond, a leading video editing solution, where he built Vyond Studio, a full-featured, drag-and-drop online video editor that is used by 20k businesses today.\n\nWe have been friends for 5 years and decided to build something together last summer.\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXdANyVcVkBVfrTT1t5kFkP-JSZ6Lgas72QTZ0Lq-zX36Iwzai3h7O-o2FfDnFk8fM3Zq8-sgHdFPZNa4Bis9IA_byzj_4Ysp5hT6KLsJ3qR8DDFHpmbWzbUalNkQ2rlmLmARab7Iw?key=ucB-AG1uSNxOnV5yBE4xiA)\n\n",
        "url": "https://www.ycombinator.com/launches/Nwh-hera-your-ai-motion-designer",
        "votes": 380,
        "created_at": "2025-07-10T21:24:31.293Z"
      }
    ]
  },
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    "id": 30770,
    "name": "Button Computer",
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    "website": "https://buttoncomputer.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "We’re launching a small hardware device: a button that you clip to your shirt. You press it to talk to AI, and it responds instantly.",
    "one_liner": "The tiny computer built for voice AI.",
    "team_size": 1,
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    "launched_at": 1755546681,
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    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/button-computer.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/buttoncomputer",
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      "name": "Tyler Bosmeny",
      "url": "https://www.ycombinator.com/people/tyler-bosmeny"
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      {
        "user_id": 1273646,
        "full_name": "Chris Nolet",
        "title": "Founder/CEO",
        "founder_bio": "I was previously a Staff SWE at Apple, where I worked on the Vision Pro. Although I've spent much of my career on software, I have a background in mechanical engineering, and a deep passion for product design. I'm a second-time founder and former venture partner. Now I'm working on conversational computing, and I'm excited to bring voice AI to the masses.",
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      {
        "id": 98398,
        "title": "Button is the fastest way to chat with AI",
        "tagline": "The tiny computer built for AI",
        "body": "Hey YC!\n\nWe’re Chris and Ryan from Button Computer. We’re dropping some new hardware!\n\n<https://youtu.be/BA37YK305y4>\n\n# **TL;DR**\n\nToday we’re launching a small hardware device: a button that you clip to your shirt. You press it to talk to AI, and it responds instantly.\n\nIt’s a computer. You wear it. You talk to it. It’s a companion device for your phone and laptop.\n\nBut it also runs ‘voice apps’ with an architecture that’s specifically designed for _speed_ – because when you’re talking to your computer, everything needs to be **instantaneous.** We’re obsessed with latency. Button is by far the fastest voice AI experience we’ve tried.\n\n![uploaded image](/media/?type=post&id=98398&key=user_uploads/1273646/22d485b8-deff-468f-bd83-70b758432e34)\n\n# **What makes Button unique**\n\nEvery computer that you use today was designed before AI. Your phone. Your laptop. Your watch. They were all built for a world before LLMs. Button really is the first piece of hardware designed exclusively to give you instant access to voice AI. And when you build something from the ground up, you get the opportunity to do it right.\n\nIt takes 6 to 10 seconds to pull out your phone, unlock it, find and launch an app. The Action Button helps. But having a wearable that will give you an answer in _half a second_ is an order of magnitude more useful.\n\n# **Privacy and intentionality**\n\nButton is also a computer that follows your lead. It doesn’t try to predict your behavior. We don’t track you. It doesn’t notify you or distract you. It’s a tool that you control. You press the button to talk to AI… Our job is to empower you, and then get out of your way.\n\nWe care a lot about your privacy. Button doesn’t listen to your private conversations. It can only hear you when you press it.\n\n![uploaded image](/media/?type=post&id=98398&key=user_uploads/1273646/f1103ec0-5a3c-4553-b3f1-b1a2eccc6bd7)\n\n# **Our friendship**\n\nWe worked together on Vision Pro at Apple. After Ryan moved to Colorado, we stayed close. Chris visited Ryan and his family for Christmas, and Ryan was the best man at Chris’ wedding.\n\nWe’ve both had previous startups and we’re excited to do this one together!\n\n![uploaded image](/media/?type=post&id=98398&key=user_uploads/1273646/9116d254-c670-48ad-8548-d66868cac9c9)\n\n# **Our ask**\n\nIf you know of anyone who believes in the future of voice AI, we’d love to meet them! If you’re an angel, please feel free to book a time directly at: <https://cal.com/chrisnolet>.\n\nThank you for your support in building the future of conversational computing!\n\nWebsite: <https://buttoncomputer.com>\n\n![uploaded image](/media/?type=post&id=98398&key=user_uploads/1273646/daf19bcb-b90f-41fd-8529-7c6eafce0199)\n\n",
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        "votes": 13,
        "created_at": "2026-03-03T14:56:27.083Z"
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    "primary_partner": {
      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
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    "founders": [
      {
        "user_id": 2819631,
        "full_name": "Glenn Töws",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder and CEO of stagewise, the makers of Klex Bots.\nStudied electrical engineering at DHBW Mosbach and in partnership with Rheinmetall, focussing on functional safety in automotive embedded software.\nLed the efforts for development and adoption of a state-of-the-art componentization framework for embedded software at Miele, before making a pivot to artificial intelligence and web technologies.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/glenntws/",
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      {
        "user_id": 2818366,
        "full_name": "Julian Goetze",
        "title": "Founder/CTO",
        "founder_bio": "Co-founder & CTO at stagewise (YC S25), building Klex Bots (klex.bot) - autonomous digital coworkers for business environments. Previously built open-source AI developer tools with 6.8k+ GitHub stars.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/juliangoetze/",
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    "launches": [
      {
        "id": 92464,
        "title": "stagewise: The frontend coding agent for production codebases",
        "tagline": "Visually build your apps frontend right inside your browser on localhost.",
        "body": "# **TL;DR**\n\n**stagewise is a frontend coding agent for production codebases**\n\n→ ❌ No more tedious context switching\\\n→ 🤝 Works with all kinds of web app frameworks\\\n→ 🚀 Integrates into existing, production-grade apps\n\nGet started now on [stagewise.io](https://stagewise.io#quickstart) and use the code **STAGELAUNCH** to **get 25% off for 3 months**! 🎉\n\n‎\n\n# **WATCH THE DEMO**\n\nhttps://youtu.be/q7JFZBEfyjo\n\n---\n\n---\n\n# **ABOUT US**\n\nWe’re **Julian** and **Glenn**, and we’ve built **stagewise** because we wanted to quickly iterate on app frontends with AI - even if they’re not just simple prototypes anymore, but real projects.\n\n‎\n\n# **THE PROBLEM**\n\n**AI-powered app builders work great - until they don’t.**\n\nOnce you move into a production-grade project setup on your local machine, you lose the awesome experience of visually building your apps frontend with simple prompts.\n\nYou move from tools like **v0 or Lovable** to tools like **Cursor and Claude Code**, but there’s a catch.\n\n**AI code editors are** **not good at building frontends**, because:\\\n→ They don’t understand your apps user experience\\\n→ They don’t see your browser content, but only the codebase\\\n→ You have to switch between browser and IDE all the time\n\n‎\n\n# **THE SOLUTION**\n\nWith stagewise, we’ve developed an **open-source** and **framework-independent** toolbar that brings our frontend coding agent **right into your web app on localhost**.\\\n\\\nHere’s how it works:\\\n→ You prompt changes by clicking and commenting on elements in your app\\\n→ We automatically collect browser and app metadata\\\n→ The agent makes precise changes to your local codebase\n\nThe toolbar has already surpassed **4,800 GitHub-stars** ⭐️ and **130,000 downloads 📈**\n\n‎\n\n# **OUR VISION**\n\n_We believe that the best user experiences are built by **iterating fast** and putting yourselves **in the shoes of your user**._\n\n_Our product enables teams to do exactly that - and we continue to work on a future, where awesome production-grade user experiences can be built lightning-fast and without coding skills._\n\n‎\n\n# **JOIN OUR COMMUNITY**\n\n👾 [**Join us on Discord**](https://discord.gg/DjMqMnUVCh)\\\n𝕩 [**Follow us on X**](https://x.com/stagewise.io)\\\n**📬 Contact [Julian](https://mailto:julian@stagewise.io) or [Glenn](https://mailto:glenn@stagewise.io) via mail**\n\n![uploaded image](/media/?type=post&id=92464&key=user_uploads/2819631/ef40781f-3dfc-45ed-984e-f347f6c60e0c)\n\n",
        "url": "https://www.ycombinator.com/launches/O3M-stagewise-the-frontend-coding-agent-for-production-codebases",
        "votes": 88,
        "created_at": "2025-07-25T20:30:11.898Z"
      }
    ]
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    "id": 30789,
    "name": "Interfere",
    "slug": "interfere",
    "former_names": [
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    "all_locations": "New York City, NY, USA",
    "long_description": "Interfere empowers engineers, product managers and designers with real-time understanding of previously unseen bugs and issues.",
    "one_liner": "Give engineering, product, and design teams insight into unseen issues",
    "team_size": 8,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1752094986,
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      "Developer Tools",
      "Design",
      "AI"
    ],
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    "nonprofit": false,
    "batch": "Summer 2025",
    "status": "Active",
    "industries": [
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      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/interfere",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/interfere.json",
    "year_founded": 2025,
    "city": "New York City",
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        "title": "Semiotic: AI Design Firm",
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        "full_name": "Don Muir",
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        "founder_bio": "Co-Founder / CEO @ F2\nCo-Founder @ Arc\n\nEx-PE investor turned entrepreneur, passionate about AI applications in finance",
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        "full_name": "Girish Radhakrishnan",
        "title": "Founder/CEO",
        "founder_bio": "Building AI agents for hardware test data analysis\nex-Tesla, 10 years of experience in the automotive industry working with my co-founder Bruno Finco",
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        "full_name": "Bruno Finco",
        "title": "Founder/CTO",
        "founder_bio": "Building AI agents for sensor data analysis. 10 years in automotive as a lead forward-deployed engineer, working with my cofounder Girish.",
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        "id": 95237,
        "title": "MOVEdot: AI Agents for Hardware Engineering",
        "tagline": "Cursor for Engineering Analysis - From Race Cars to Factory Floors",
        "body": "Hey everyone, we’re [**Bruno**](https://www.linkedin.com/in/bruno-finco-610999b6/) and [**Girish**](https://www.linkedin.com/in/girish-radhakrishnan/), founders of [**MOVEdot**](https://www.movedot.ai/).\n\n# TL;DR\n\n* When developing any sort of hardware, engineers are the bottleneck due to data/information overload, creating huge inefficiencies and waste\n* We built a Cursor-like interface that allows humans and AI agents to work together on multi-modal data, achieving 10-100x efficiency\n* We started with race cars and are now expanding to other industries\n* [**Book a demo**](https://www.movedot.ai/) or email us ([founders@movedot.com](mailto:founders@movedot.com))\n\nhttps://youtu.be/tA-4cdiJ5tI\n\n# ❌ The Problem\n\nEvery engineer says the same thing:\n\n> “Too much data, not enough time.”\n\nData collection has grown 10x, but the **same human brain** still has to make sense of it. Engineers spend days digging through spreadsheets and KPIs to find what failed. Or more realistically, they give up, leaving most data unused.\n\n# ⚙️ The Solution\n\nWe built **MOVEdot**, an AI agent platform that allows you to use 10x more data to make decisions. It connects to data, video, and test standards, automating reports or answering questions like:\n\n> _When did temperature spikes cause mechanical failures, and what were early signs?_\n\nAgents process the data and produce interactive dashboards and mind maps.\n\n![uploaded image](/media/?type=post&id=95237&key=user_uploads/1931404/3f0d742e-35f8-4d25-8c7a-ccd153474570)\n\n# 🌍 The Vision\n\nPhysical-world testing is a **$250B market** across development, durability, and validation. Our goal: give every engineering team **thousands of AI teammates** that helps them use **100%** of their data, increasing performance and shortening time to market. From racing to robotics. From proving grounds to production lines.\n\n# 🏎️ Race Cars - Why We Started Here\n\nWe began in motorsports: time-sensitive environment with short sales cycles. Closed our first 30k deal within 2 weeks of the POC. Well, we were also race car engineers…\n\n![uploaded image](/media/?type=post&id=95237&key=user_uploads/1931404/590dddb8-083c-4492-a213-a4695df7a028)\n\nSince then, we’ve onboarded dozens of racing teams and have expanded into manufacturing, with a POC at [**Tractian**](https://tractian.com/en) (YC W21).\n\n# 👥The Team\n\n[**Bruno**](https://www.linkedin.com/in/bruno-finco-610999b6/) and [**Girish**](https://www.linkedin.com/in/girish-radhakrishnan/) worked together for 8 years as forward-deployed engineers in an automotive consulting firm, where we realized we were the bottleneck. Girish also had a stint at Tesla, seeing the same challenges.\n\n![uploaded image](/media/?type=post&id=95237&key=user_uploads/1931404/d3d6577b-ae0c-4715-803e-1ad78a09d2a6)\n\n# 🔥 Our Ask\n\n* Are you an engineer working with a ton of data? [**Book a demo!**](https://www.movedot.ai/)\n* Know someone who is? Share this post!\n\nContact us at [founders@movedot.com](mailto:founders@movedot.com)",
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    "launched_at": 1761607655,
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        "full_name": "Gurish Sharma",
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        "founder_bio": "Founder at Aspect, building agents for enterprise content teams. Prev scaled infra and AI at (the same) post-production company to ingesting and indexing 50TB+ a day",
        "is_active": true,
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        "full_name": "Bright Xu",
        "title": "Founder",
        "founder_bio": "Founder at Aspect, prev founding engineer at (the same) post-production company. Built and managed entire desktop/web clients. ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/brightxu/",
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        "id": 96768,
        "title": "Founding Engineer",
        "url": "https://www.ycombinator.com/companies/aspect-inc/jobs/uxITHnV-founding-engineer",
        "location": "New York, NY, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$120 - $175",
        "equity_range": "1.50% - 2.50%",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
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      {
        "id": 116460,
        "title": "Founding Designer",
        "url": "https://www.ycombinator.com/companies/aspect-inc/jobs/jOu5iU0-founding-designer",
        "location": "New York, NY, US / Remote (US)",
        "type": "Full-time",
        "role": "Design",
        "role_type": "Brand/graphic design",
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      {
        "id": 101753,
        "title": "Aspect: Intelligent media storage for creative teams.",
        "tagline": "Aspect is the creative asset management platform that lets teams store, stream, review, and archive media in one place.",
        "body": "# TL;DR\n\nYour editor shouldn't have to download 100GB to start cutting. Your producer shouldn't have to re-upload that same file to review it. And nobody should be Slacking “which Dropbox folder is the latest version?” at 11pm. Aspect is the single platform where footage goes from upload, to local editor timeline, to client review link, without touching a second tool. Oh, and every workspace has an AI agent that knows every face, every word, and every frame across your entire library.\n\n# What Aspect does:\n\n[**Cloud storage that connects like a hard drive:**](https://aspect.inc/features/instant-access) Aspect mounts to your desktop like an SSD, and streams the bytes your application needs, so a 200GB R3D timeline plays back the moment you double-click it, even if your laptop only has 50GB free. Every project change syncs in real time across your team, so everyone can work on the same timeline.\n\n**Agentic search and work:** For the first time, a media platform comes with an AI agent that actually understands your content. Say _“collect everything from the Chicago shoot with the client’s logo, add it to a collection, and send a view-only link to the client”_ and it just does it.\n\n[**Review and approve:**](https://aspect.inc/features/review-and-approve) Every asset your team uploads or exports to the Aspect drive is instantly reviewable. Frame-accurate commenting, markup tools, version comparison, and customizable share links are built into every file.\n\n# How do I actually use this?\n\nUse Aspect as your team’s single source of truth for media files on the cloud and locally on your desktop. Our team will copy over any files your team already has on Dropbox, Google Drive, Frameio, or any other platform for free.\n\n**1)** Start by mounting a project from Aspect to your local desktop. Your project shows up as a hard drive on your computer. Open any file, no matter how large, and we will stream the bytes your computer needs to play back the video instantly. Any changes you make in a Premiere, Resolve, or Final Cut project show up for everyone else on your team in their timeline as well.\n\n![uploaded image](/media/?type=post&id=101753&key=user_uploads/1087643/f374bc9d-a686-414a-9a8e-4547c8f89e92)\n\n**2)** When you are looking for a piece of media, ask the Aspect agent to retrieve it for you. Right click on a file and open it directly in Finder:\n\n![uploaded image](/media/?type=post&id=101753&key=user_uploads/1087643/60636a50-1da5-4665-bd15-603f12eae6bd)\n\n**3)** When you are done with a rough or final cut, export the file back to the Aspect drive. New files sync across everyone who has the project mounted, and a preview will be generated automatically for your team to view the file on any browser:\n\n![uploaded image](/media/?type=post&id=101753&key=user_uploads/1087643/6eb26f19-ec05-4d2e-b8e7-1136fcc3224f)\n\n**4)** Review, markup, comment, and share this file the same way you would on any platform:\n\n![uploaded image](/media/?type=post&id=101753&key=user_uploads/1087643/f20bd7b5-59d4-4552-8a00-c4aa63037f10)\n\nAnd when you are done with a project or campaign, move them to archive storage with one click where your team can still view, search, and share assets.\n\n# Aspect is how teams save dozens of hours and thousands of dollars working with their media.\n\nMedia teams today are forced to stitch together multiple point solutions because there wasn't a platform that could do it all. Files lived in Dropbox, reviews live in Frameio, and editors streamed from LucidLink. That’s three subscriptions, three sources of truth, none of them connected. Aspect replaces all three, built with an agent that’s like having a DIT who’s already watched every frame.\n\n### **Do us a favor**\n\nIf you know someone that works in post-production, **send them this post!** If you are someone who works at a post-house, creative agency, or an in-house creative team, let’s see how we can help your team ship content faster: <https://cal.com/team/aspect/aspect-for-teams>\n\n![uploaded image](/media/?type=post&id=101753&key=user_uploads/1087643/71f8d28c-dea4-4d5c-9012-fe1236587b07)\n\n",
        "url": "https://www.ycombinator.com/launches/QTB-aspect-intelligent-media-storage-for-creative-teams",
        "votes": 22,
        "created_at": "2026-05-22T02:59:09.771Z"
      },
      {
        "id": 94992,
        "title": "🎥 Aspect: AI platform for enterprise media content",
        "tagline": "We help enterprise content teams go from ingest, to rough cut, to final delivery faster by automating non-creative work",
        "body": "Hey! We’re Edison, Gurish, and Bright - founders of [Aspect](https://aspect.inc) 🎥 💥\n\n### **TL;DR**\n\nWe’ve spent **10,000+ hours** with in-house content teams as the founding members of a media asset management company, learning every broken part of their workflow. Post-production supervisors and assistants still have to organize folders, check revisions, comb through old content, and update data across project management tools, not to mention constant upkeep with clients. These are just a few of the manual tasks keeping creatives from doing what they love.\n\n**Aspect takes care of everything and more.**\n\n<https://www.youtube.com/watch?v=1EwHnYKPWBo>\n\n### What Aspect Does:\n\n* Ingests media from traditional post-production storage apps and NAS storage\n* Crawls every frame of video to create a humanlike understanding of whole libraries\n* Connects to other business tools to keep data in sync without human intervention\n* Searches for second-accurate clips, assembles rough cuts, reviews footage, creates folder trees - anything a post-production expert can do, Aspect can do\n\nAspect is the single source of truth from ingest, to rough cut, and final delivery, with agents you can send off to do the mundane work you hate.\n\n### How do I actually use this?\n\nAsk Aspect to pull your latest storyboard from an external app, or upload a PDF and ask it to assemble a rough cut from your latest shoot:\n\n![uploaded image](/media/?type=post&id=94992&key=user_uploads/1087643/8622bede-339a-44b8-bcde-f48fa6304dc7)\n\nUse the @ in a comment like you would with a teammate and ask Aspect to review a video based on revision notes from a previous version or another app:\n\n![uploaded image](/media/?type=post&id=94992&key=user_uploads/1087643/de627308-8f5b-4e4d-8dc5-b14fa894a57a)\n\n…and so much more.\n\n### Aspect is the Future of media Production:\n\nPrevious waves of media-tech only focused on simplifying media retrieval with brittle tagging and non-actionable semantic search. The reality is that searching for files is just a fraction of the time wasted by post-production teams. Aspect is built on agents with humanlike **visual-temporal understanding**, so they _go beyond_ _just search_ - they work with video like any post-production teammate and can scale infinitely.\n\n### Our Story:\n\nWe’re [Edison](https://www.linkedin.com/in/edison-chiu/), [Gurish](https://www.linkedin.com/in/gurish-sharma-/), and [Bright](https://www.linkedin.com/in/brightxu/)! We spent 3 years learning about every role in post-production teams across thousands of companies. Post-production is by far the most human labor concentrated task in the creative journey, which is why we are building _the autonomous layer_ for the $200B video production industry.\n\n![uploaded image](/media/?type=post&id=94992&key=user_uploads/1087643/80f3db12-ae95-4e7b-afbf-1e6e14e5d0e9)\n\n### Do us a favor:\n\nIf you know someone that works in post-production, **send them this post!** If you are someone who works at a post-house or within an in-house media team, let’s see how we can make your team move faster: <https://cal.com/team/aspect/aspect-for-teams>\n\nWe are available whenever you are at 📫 [founders@aspect.inc](mailto:founders@aspect.inc) and 🌐 [aspect.inc/](https://aspect.inc)\n\n![uploaded image](/media/?type=post&id=94992&key=user_uploads/1087643/53e175e2-728b-4b53-b931-6e7628c70249)\n\n",
        "url": "https://www.ycombinator.com/launches/Oi8-aspect-ai-platform-for-enterprise-media-content",
        "votes": 23,
        "created_at": "2025-10-29T01:25:45.072Z"
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    "id": 30859,
    "name": "Locus",
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    "website": "https://paywithlocus.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "We make your agents pay.\r\n\r\nAs agents evolve from tools into dependable, autonomous actors, they’ll need the ability to execute open-ended workflows end-to-end.\r\n\r\nThis inevitably means payments: accessing paywalled data, transacting for services or with other specialist agents. But autonomy requires guardrails. Businesses and developers will need a way to ensure their agents only spend how much and on what they’re supposed to.\r\n\r\nThe machine economy is coming, and Locus (YC F25) is building the connector businesses will need to participate. We connect agents securely to funds, letting you define permissions and limits for every transaction. Each payment is traceable, auditable, and fully reconcilable with your existing financial stack.",
    "one_liner": "Payment infrastructure for AI agents",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1761342337,
    "tags": [
      "Finance",
      "AI"
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    "nonprofit": false,
    "batch": "Fall 2025",
    "status": "Active",
    "industries": [
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    "regions": [
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      "America / Canada"
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    "stage": "Early",
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/locus",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/locus.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/paywithlocus/",
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      "name": "Aaron Epstein",
      "url": "https://www.ycombinator.com/people/aaron-epstein"
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    "founders": [
      {
        "user_id": 2656097,
        "full_name": "Cole Dermott",
        "title": "Founder/CEO",
        "founder_bio": "I like moving money. ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/coledermott/",
        "x_url": "https://x.com/coledermo",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/52c3bdc2a2434f4dbceafbdc97c3d23d62ce9210.jpg"
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      {
        "id": 103214,
        "title": "Locus Founder",
        "tagline": "An AI agent that builds and runs an internet business for you",
        "body": "![uploaded image](/media/?type=post&id=103214&key=user_uploads/2656097/bfeee97f-7eb2-42d3-ad2e-b02cfc5ee724)\n\nHey everyone 👋\n\nOn Monday, June 15th, at 8am PST we're launching **Locus Founder** (<https://locusfounder.com/>), an AI agent stack that builds and runs an internet business for you. You bring the idea, it does the rest, and you drive the whole thing by texting it (iMessage, SMS, Telegram, or web).\n\n**What it does**\n\nText it an idea and it goes to work. It researches you and proposes a business aligned to who you are, does market research across 40+ paid data APIs, generates a full brand kit, and builds and deploys a real full-stack website (frontend, backend, database, the works). From there it sources products (print-on-demand, digital goods, or a curated catalog of 500+ dropshippable products), runs outbound across email and social, sources leads from Apollo, Google Maps, Reviews, Instagram, YouTube, and Yelp, generates short-form video ads and posts them to Meta, and handles payments (USDC direct transfers, card in/out). Loki, our mascot, is the face guiding you through all of it.\n\n**Demo video:** <https://www.loom.com/share/3796f2a13afb48d69e83a92d9debe963>\n\n**The backstory**\n\nA lot of you watched the earlier pieces ship, so the arc will be familiar.\n\nWe started with **Pay With Locus**, non-custodial wallet infrastructure so AI agents could spend money safely, with spending controls and auditability built in. The feedback was consistent: why would we give an agent money when there's nothing for it to buy?\n\nSo we built the supply. **Build With Locus** (full-stack deployments for agents via pay-per-use API endpoints), a catalog of 40+ pay-per-use data APIs, and **Checkout With Locus** (a Stripe-style, machine-readable payment SDK that takes USDC, is human-or-agent payable, and settles funds straight back into the agent's Locus wallet).\n\nThen users hit us with the real one: why would I still give it money if it can't earn me any back? I'm not comfortable handing my agent a dollar knowing it can't reasonably make me one.\n\n**_That question is the entire reason Locus Founder exists:_** the AI agent that earns you a dollar by running your business, just by texting it. And it's an evolution of everything we've built. Every Locus Founder user is a Pay With Locus user (credits run off our wallets), a Build With Locus deployment (sites deploy on BWL), and a consumer of our pay-per-use API suite. It's the first app anyone can pick up and use, sitting on top of all of our infrastructure.\n\n**_The honest why underneath it:_** the K-shaped economy framing has never sat right with me. The tools to build aren't so expensive that people are fully priced out yet. There's still a window where someone can make an active effort to change their trajectory. Locus Founder is our effort. It's for the people who always wanted to start something but kept running out of time, money, skills, or resources. We're bringing the same AI tools us folks in tech have been bragging about for two years directly to everyone else, in a form they can actually use. Above all else, our goal is to earn our users a dollar.\n\n**Launch video:** <https://youtu.be/cjFsHAWvv7w>\n\n**Pricing (kept honest):** We’re doing limited daily free usage so people can try the product instantly. Additionally, we have a subscription for $50/mo which includes effectively unlimited access. We take 5% of profits only above $1,000/mo, and nothing under that. Our goal is truly for our users to earn.\n\n**My asks**\n\n1. **Try the onboarding and tell me where it's rough.** I want the brutal version. [locusfounder.com](http://locusfounder.com)\n2. **Intros to anyone who's always wanted to start something but never had the time.** That's exactly who we built this for.\n\nThank you all. This community has been a huge part of getting us here.\n\nCole",
        "url": "https://www.ycombinator.com/launches/Qqk-locus-founder",
        "votes": 7,
        "created_at": "2026-06-14T23:16:28.675Z"
      },
      {
        "id": 95052,
        "title": "Locus – Payment infrastructure for AI agents",
        "tagline": "Give AI agents spending power without losing control",
        "body": "![uploaded image](/media/?type=post&id=95052&key=user_uploads/2656097/b9c1fd17-80cf-4a84-b400-34fc2577f0db)\n\nHey YC! We’re Cole and Eliot, and we’re building **Locus,** which is payment infrastructure for AI agents. We help developers safely connect agents to funds and define exactly how those funds can be used, with agent identities, budgets, permissions, and full audit trails.\n\n# Our Story\n\nWe came to this problem from opposite ends of the same frontier. Cole spent last summer at Coinbase, building B2B payment products and seeing firsthand how control and compliance shape financial infrastructure. Eliot was working at Scale AI, maintaining data pipelines for the world’s largest AI labs. He watched as models began to tackle sustained, open-ended tasks. Both of us realized that as agents grow more capable, the next bottleneck isn’t intelligence: it’s _trust_.\n\nPayments are a web primitive. And as we task agents with increasingly long and noisy workflows, they will _inevitably_ need to make payments. This might mean ordering parts to complete a physical repair, paying another agent for design work, hiring a contractor for a one-off task, or making micropayments to access private data.\n\nBut today’s payment rails were built for humans, not autonomous systems. There’s no safe way to say, “this agent can spend $500/day on these vendors,” and have that rule enforced. No audit trail showing which agent authorized what and why.\n\n# Make Them Pay — Today!\n\nRecently, OpenAI, Google, Visa, and Coinbase all released their own agentic payment protocols. But while everyone’s racing to build the next payment rails, nobody’s building the _control_ layer: the foundation that actually gives you power over how your agents use these rails. **Locus is building exactly this.**\n\nLocus currently supports USDC on Base, with support for ACH and wire transfers coming soon. You can give your agents spending power and start building today.\n\n# Demo\n\nWe built a micro-task payment system where an agent evaluates work submissions, scores quality, and pays contributors automatically. You set rules like \"max $50 per payout, $500/day, must include a justification.\" The agent handles the rest. No manual approval needed, but you have full audit trails showing who got paid, when, and why.\\\nhttps://youtu.be/ICSzoZTq9JE\n\n# Join Us!\n\nIf you build agents, join our beta and help shape the future of agent-driven finance! Learn more and sign up at [paywithlocus.com](http://paywithlocus.com). We'll give you $10 in USDC to experiment with.\n\nWe’re also building a community of builders in the space and would love for you to join. If agents with spending power sound at all interesting to you, join here to stay in the loop: https://discord.gg/TGnjUceXwE\n\n# [https://youtu.be/6rntHGR475U\\\\](https://youtu.be/6rntHGR475U%5C)\n\n# Contact Us\n\nEmail [founders@paywithlocus.com](mailto:founders@paywithlocus.com), or find us on [LinkedIn](https://www.linkedin.com/company/paywithlocus/) or [X](https://x.com/PayWithLocus).\n\n**Cole Dermott:** [LinkedIn](https://www.linkedin.com/in/coledermott), or DM [@coledermo](https://x.com/coledermo) on X.\n\n**Eliot Lee:** [LinkedIn](https://www.linkedin.com/in/eliotlee3/), or DM [@eliotlee33](https://x.com/eliotlee33) on X.",
        "url": "https://www.ycombinator.com/launches/Oj6-locus-payment-infrastructure-for-ai-agents",
        "votes": 84,
        "created_at": "2025-10-31T16:24:24.218Z"
      }
    ]
  },
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    "id": 30861,
    "name": "Caddy",
    "slug": "caddy",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4a18ef62feeed4267cb16429f2de1d3e6abbb159.png",
    "website": "https://caddy.app/",
    "all_locations": "New York City, NY, USA",
    "long_description": "If you’ve got a lot to do, we believe AI can make things feel doable. Caddy is our core product: a Personal AI that helps you stay on top of everything going on. All you have to do is text. \r\n\r\nOn overwhelming days, it’s super simple to just drop any task in a text thread, and Caddy will help you handle it. Caddy also keeps an eye on your calendars, chats and tasks to make sure you stay focused on what matters. If something needs you, Caddy will nudge you, or can just do it if you don’t have time. \r\n\r\nThe best part is, no two Caddys are alike. The more you use Caddy, the more it learns your vibe, how you work, and what you care about. ",
    "one_liner": "Your Personal AI for everyday work. Lives in your texts.",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1761153567,
    "tags": [
      "Automation",
      "AI",
      "AI Assistant"
    ],
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Fall 2025",
    "status": "Active",
    "industries": [
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    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/caddy",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/caddy.json",
    "year_founded": 2025,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/try-caddy/",
    "x_url": "https://x.com/try_caddy",
    "fb_url": null,
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    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/4a18ef62feeed4267cb16429f2de1d3e6abbb159.png",
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    "primary_partner": {
      "name": "Aaron Epstein",
      "url": "https://www.ycombinator.com/people/aaron-epstein"
    },
    "founders": [
      {
        "user_id": 816824,
        "full_name": "Connor Waslo",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder of Caddy. Building the operating system that understands your workflows and gets work done for you. Previously led product for Loom's AI Suite and Monetization team.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/connor-waslo/",
        "x_url": "https://x.com/ConnorWaslo",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/8d8d8643232c2dbf39e1033e522507a22d616968.jpg"
      },
      {
        "user_id": 2945950,
        "full_name": "Rajiv Sancheti",
        "title": "Founder/COO",
        "founder_bio": "Co-founder of Caddy. Building the operating system that understands your workflows and gets work done for you. Previously led design for Loom’s AI suite, and before that, worked at Airbnb and KP Fellows.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/rajivsancheti/",
        "x_url": "https://x.com/sanchetio",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f880b5dcccfb7e73d449f8caaeb35326d129e32f.jpg"
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    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 95249,
        "title": "Caddy: The Voice Interface for Your Computer",
        "tagline": "Changing how people work across their computer and apps with voice",
        "body": "Hey everyone, we’re [Connor](https://www.linkedin.com/in/connor-waslo/) and [Rajiv](https://www.linkedin.com/in/rajivsancheti/).\n\nWe led Loom’s AI suite and saw firsthand how natural language was changing how people work. Now we’re building Caddy, the voice interface for your computer that lets you automate work across all your apps.\n\nJoin the waitlist at [trycaddy.ai](http://trycaddy.ai)\n\n**Launch video:** https://www.youtube.com/watch?v=v1HwM9mBYHU\n\n### **The problem**\n\nWork today happens across a maze of apps. Slack for messaging. Linear for tickets. Gmail for communication. Calendar for scheduling. Every task requires jumping between tabs and tools.\n\nEven with AI everywhere, we are still using the same old interfaces. Voice assistants like Siri or Alexa can answer trivia but cannot do real work. They do not understand what is on your screen, what app you are in, or what you mean when you say “follow up on this.”\n\nThe result is constant context switching, lost flow, and hours wasted on work that should happen automatically.\n\n### **What we are building**\n\nCaddy lives on your desktop and lets you operate your computer with your voice. It has two simple modes.\n\n**Action mode:** You speak your intent, and Caddy takes action.\n\nAsk Caddy to create a ticket in Linear, send a message in Slack, or schedule a meeting in Calendar. Caddy sees what is on your screen and connects it to your apps, so you can stay focused on the work that matters.\n\n**Dictation mode:** Never type again\n\nWrite emails, respond to messages, or leave comments anywhere text input exists. It is a direct replacement for typing that works globally across your computer.\n\nTogether, these two modes let you automate work and control your computer completely with your voice.\n\n![uploaded image](/media/?type=post&id=95249&key=user_uploads/2945950/d99dbe1c-8793-4405-a7ca-568f05c831fd)\n\n### **Who Caddy is for**\n\nWe are starting with founders, operators, productivity power users and the voice first generation who spend their days moving between tools and losing time to repetitive work. If that sounds like you, we would love to get you early access.\n\nTo join our waitlist add your email at [trycaddy.ai](http://trycaddy.ai) or shoot us a message [founders@trycaddy.ai](mailto:founders@trycaddy.ai)\n\n### **The team**\n\nBefore starting Caddy, [Connor](https://www.linkedin.com/in/connor-waslo/) and [Rajiv](https://www.linkedin.com/in/rajivsancheti/) spent four years at Loom where they led product and design for Loom’s AI suite and core product.",
        "url": "https://www.ycombinator.com/launches/OmH-caddy-the-voice-interface-for-your-computer",
        "votes": 149,
        "created_at": "2025-11-06T16:34:46.562Z"
      }
    ]
  },
  {
    "id": 30863,
    "name": "The Context Company",
    "slug": "the-context-company",
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    "website": "https://www.thecontextcompany.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "We analyze every conversation between your customers and your AI agent to find what's losing you customers and money. Then we help ship the fix and prove it worked.\r\n\r\nNobody on the team can read every conversation once an agent is in production. TCC does, and turns them into patterns tied to the accounts they affect: where customers get stuck, what they wish the agent could do, and where it's spending more than it needs to.\r\n\r\nEngineers ask about a pattern from their IDE through our MCP, get the conversations and traces behind it down to the tool call or prompt that went wrong, ship the fix, and benchmark cost and quality before and after. Product sees what customers are actually trying to do with the agent and where it falls short, broken out by topic and account, which becomes the backlog for what to build next. Customer success sees which accounts the agent is struggling with before the customer says anything, and steps in with the full conversation on hand.\r\n\r\nAny agent framework, a few lines of code. If you're running an agent in production or about to launch, ping us.",
    "one_liner": "Find what's losing you customers and money in your AI agent and fix it",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1759953898,
    "tags": [
      "Developer Tools",
      "B2B",
      "Analytics",
      "Monitoring",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Fall 2025",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/the-context-company",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/the-context-company.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/the-context-company/",
    "x_url": "https://x.com/thecontextco",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/897cd2d31bc7dc869e170422ebc8e24a66f3e2bc.png",
    "app_video_url": null,
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    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
    },
    "founders": [
      {
        "user_id": 2357695,
        "full_name": "Arman Kumaraswamy",
        "title": "Founder",
        "founder_bio": "Cofounder at The Context Company (Monitoring for AI agents)\n\nI've been in love with startups since I was in high school :)\n\nPrev studied CS+Math at UF, and engineered at Mintlify, Apten, RevisionDojo, and Solace Health",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/armankumaraswamy/",
        "x_url": "https://x.com/ksw_arman",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/8401e71daab0e1115cff57cc14f4453c2bce6052.jpg"
      },
      {
        "user_id": 2579624,
        "full_name": "Rohil Agarwal",
        "title": "Founder",
        "founder_bio": "What is up! Previously studied EECS + Business at UC Berkeley M.E.T. and worked on Gmail Intelligence at Google, where I built models powering intent detection for 26B+ daily emails.\n\nNow building The Context Company, where we are powering developers to ship AI agents they can trust. I'm excited about solving context engineering 🙃\n\nOh, and I take one selfie every day!",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/rohil-ag/",
        "x_url": "https://x.com/rohil_ag",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4d30f11084359006ce25e5cf6c97ee26d09cb543.jpg"
      }
    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 94947,
        "title": "The Context Company - Catch Silent AI Failures Before They Break Production",
        "tagline": "Full observability for AI agents, from bad tool calls, loops, and hallucinations to latency and cost, in 10 lines of code.",
        "body": "What is up! We’re [Arman](https://www.linkedin.com/in/armankumaraswamy/) and [Rohil](https://www.linkedin.com/in/rohil-ag/) - cofounders of [The Context Company](https://thecontextcompany.com)\n\n**TL;DR**\n\n![uploaded image](/media/?type=post&id=94947&key=user_uploads/2579624/129e5656-94c6-42e6-a2ba-6ac545b0ef94)\n\nSetup takes under 10 lines of code, and we now support Vercel AI SDK, LangChain, and LangGraph, with more frameworks coming fast.\n\n**Our Ask**\n\n* If you’re building with Vercel AI SDK, LangChain, or LangGraph, use The Context Company for observability.\n* Setup takes just a few lines - DM us on Bookface or Slack, or email [founders@thecontextcompany.com](https://mailto:founders@thecontextcompany.com), and we’ll personally onboard you in 15 minutes.\n* Not using those frameworks yet? Tell us what you’re building with, and we’ll add support fast.\n\n<https://youtu.be/5FVesVO9egg>\n\n**The Problem**\n\nAI agents often fail quietly. Traditional observability tools only show latency or stack traces. They miss the silent layer of failures that happen inside reasoning steps or tool calls.\n\nMost teams end up waiting until users report issues, and by then, it’s already too late. As a developer, I know you’ve been there scrolling through endless logs, trying to piece together what an agent actually did and why it failed (because trust us, we have too 🙏🏽).\n\n**We’re rethinking observability from the ground up and making silent failures a first-class primitive in agent monitoring.**\n\n\\*\\*Our Solution:\\*\\*\\\nInstead of just visualizing traces, we analyze them and detect reasoning breakdowns across runs. In addition to traditional metrics like latency, cost, and token usage, The Context Company surfaces failures in a clean, developer-friendly dashboard.\n\n![uploaded image](/media/?type=post&id=94947&key=user_uploads/2579624/861e36d0-5a8b-4555-a738-e2489729f99f)\n\nAnd we’ve gone beyond the cloud:\n\nYou can now run our developer package locally to debug traces on your machine, even when you’re offline or iterating fast.\n\n![uploaded image](/media/?type=post&id=94947&key=user_uploads/2579624/b7722f3f-a018-4c46-806c-7ef4be35bd44)\n\n**Our Progress**\n\n* Framework support: Vercel AI SDK, LangChain, and LangGraph.\n* Instant setup: &lt;10 lines of code - no refactoring or modifying your agent needed. This is what it looks like:\n\n![uploaded image](/media/?type=post&id=94947&key=user_uploads/2579624/560baa96-5818-4d20-bf82-43f2d3775ca3)\n\n* Local debugging: Run observability locally on your laptop for real-time trace analysis.\n* Dashboards: Full visibility into agent runs, tool calls, latency, costs, and semantic failures.\n\n**The Team**\\\nArman and Rohil have been best friends since 6th grade (8+ years now!). \n\nArman optimized the public-facing AI agent at Mintlify, where he cut failure rates by 82%, and worked with enterprise design partners to build custom agents. Rohil worked on Gmail Intelligence at Google, reducing hallucinations in intent detection by 27% across 26B+ daily emails. \n\n![uploaded image](/media/?type=post&id=94947&key=user_uploads/2579624/70e7935c-7606-4e8f-a7af-4ebf44cf5514)\n\nhttps://www.thecontextcompany.com\n\nP.S. Even if you’re not using AI SDK, LangChain, or LangGraph, we’re adding support for other frameworks soon. Tell us what you need 😎\\\n\\\n\\\nDashboard:\n\n![uploaded image](/media/?type=post&id=94947&key=user_uploads/2579624/e9425baf-3e5f-4098-b64f-497a74232f5a)\n\n![uploaded image](/media/?type=post&id=94947&key=user_uploads/2579624/ece01a4a-5089-46dd-a12a-eeef441f5cd3)\n\n",
        "url": "https://www.ycombinator.com/launches/OhP-the-context-company-catch-silent-ai-failures-before-they-break-production",
        "votes": 34,
        "created_at": "2025-10-27T21:36:21.070Z"
      }
    ]
  },
  {
    "id": 30864,
    "name": "dari.dev",
    "slug": "daridev",
    "former_names": [
      "Dari"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/db1cb9787e09629b6ccb1639f659a5f8d0bb21b1.png",
    "website": "https://dari.dev",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "We let developers run more agents while keeping your token bill low. We train custom models to determine how we can maintain performance while reducing your token bill. \r\n\r\nIntegrate into your own apps, or use our router with Claude Code, Codex, or any agent of your choice. ",
    "one_liner": "The Routing Layer for AI Agents",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1759188885,
    "tags": [
      "Developer Tools",
      "B2B"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Fall 2025",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/daridev",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/daridev.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/usedari/",
    "x_url": "https://x.com/daridotdev",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/db1cb9787e09629b6ccb1639f659a5f8d0bb21b1.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "Harj Taggar",
      "url": "https://www.ycombinator.com/people/harj-taggar"
    },
    "founders": [
      {
        "user_id": 870512,
        "full_name": "Avyay Varadarajan",
        "title": "Founder/CEO",
        "founder_bio": "Building dari.dev. Previously CS @ Caltech, SWE @ Uber, ML @ Lakers, startups. ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/avyayv/",
        "x_url": "https://x.com/avyvar",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/884b1b579b56379ff3af578d2418d837f1073468.jpg"
      },
      {
        "user_id": 2528047,
        "full_name": "Benjamin Hong",
        "title": "Founder/CTO",
        "founder_bio": "Building dari.dev",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/benjaminyhong/",
        "x_url": "https://x.com/benhong03",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2c2c7ad088a41bdb8bec806722ed8ec8077d89ce.jpg"
      }
    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 101252,
        "title": "dari.dev - The easiest way to deploy your agents to production",
        "tagline": "Get a versioned, stateful API for your long-running agent in 5 minutes",
        "body": "Point our CLI at your agent project, run `dari deploy`and get a production-ready agent API.\n\n<https://youtu.be/Y6CdktXcF24>\n\n## What it is\n\n[dari.dev](http://dari.dev) turns an agent project into a **versioned, stateful API endpoint**. We’re building on top of the best open-source harnesses starting with **Pi**. Support coming soon for **Hermes** Agent. Book a call to deploy your proprietary harness.\n\n### How it works:\n\n* Drop a dari.yml + tools + skills at your repo root\n* “dari deploy .” uploads a snapshot and publishes a new version behind a stable agent URL\n* Clients open a **durable session** and stream multimodal events (text, files, images)\n* The platform runs the harness, spins up a sandbox workspace per session, and handles logs, retries, and credentials\n* New publishes create new versions. In-flight sessions stay pinned to the version they started on\n\n## The problem:\n\nIf you're building an agent right now, you're probably:\n\n* Stitching together durable execution + a sandbox provider + Postgres + a secret store yourself\n* Losing state when a turn crashes mid-execution\n* Shipping “agents” that can’t survive a 30-minute task\n* Rebuilding the same infra (auth, retries, workspace, logs) on every project\n\nMost agents break mid-task.\n\n## With [dari.dev](http://dari.dev):\n\n* **Durable sessions:** Long-running tasks survive crashes, restarts, and redeploys. Resume from the same session_id days/months/years later.\n* **Versioned deploys:** Every publish is a new version behind one stable URL. Roll forward without breaking live sessions.\n* **Bring your own sandbox:** Sandboxes run under your provider account and API key. You control limits and data. E2B today, Daytona / Blaxel / Modal coming soon.\n* **BYOK with OpenRouter / any OpenAI-compatible API endpoint:** Use your own key, pick your model, control spend, keep logs.\n* **Custom tools**: Drop Python or TypeScript tools under tools/&lt;name&gt;/. We run them with retry policies you define.\n\n**The API:**\n\nPublish once. Then, create a session and send messages + stream responses.\n\nWe provide full observability, session-level event logs, per-turn state, and workspace file outputs attached to the session lifecycle.\n\n## Why we built this\n\nWe started building browser automation agents and kept hitting the same missing primitive, a durable control plane underneath.\n\nWe built it for ourselves, then realized every other team shipping agents (coding, research, ops) is rebuilding the same layer.\n\nIf you’ve wired together durable execution + a sandbox provider + Postgres + a secret store just to run one agent in prod, this is for you.\n\n## Get access\n\n* App: [app.dari.dev](http://app.dari.dev), docs: [docs.dari.dev](http://docs.dari.dev)\n* Install the CLI, run `dari auth login`then publish from your repo\n* Pricing: Either you pay your providers directly (E2B + OpenRouter/OpenAI) or use our managed Anthropic/OpenAI/OpenRouter offerings. No markup from us initially.\n\nBook a call: calendly.com/avyay-dari/30min or email me at [avyay@dari.dev](mailto:avyay@dari.dev).",
        "url": "https://www.ycombinator.com/launches/QL6-dari-dev-the-easiest-way-to-deploy-your-agents-to-production",
        "votes": 4,
        "created_at": "2026-05-12T22:10:48.140Z"
      },
      {
        "id": 94481,
        "title": "Dari - The easiest way to build reliable browser use agents",
        "tagline": "Build browser agents that can cache workflow steps and handle two-factor authentication. ",
        "body": "Hey everyone,\n\nWe’re [Ben](https://www.linkedin.com/in/benjaminyhong/) and [Avyay](https://www.linkedin.com/in/avyayv/), the cofounders of [Dari](https://www.usedari.com)!\n\n**Tl;dr**\n\nhttps://youtu.be/qE8wWHLhcv0\n\nWe've built the first browser automation platform reliable enough for production. While other agents fail on repetitive tasks, Dari caches successful workflows and handles 2FA automatically, making browser automation actually work for real businesses.\n\n![uploaded image](/media/?type=post&id=94481&key=user_uploads/870512/3189ec11-b583-4b3e-94a8-a489ace5f2a0)\n\n❌ **The Problem** / ✅ **Our Value**\n\nRunning regular browser use agents as-is has limited viability for repetitive tasks. They're too slow, too expensive, and too unreliable. And forget about authenticated sites: most agents can't handle 2FA at all.\n\nDari is different. We're purpose-built for production use, combining intelligent caching with automatic 2FA handling so your automations actually run reliably, day after day.\n\n![uploaded image](/media/?type=post&id=94481&key=user_uploads/870512/3282af1a-0e2b-4e5b-a6ef-24962de4c65e)\n\n**💪 Our 3 Core Strengths**\n\n**1. 🔒 2FA That Actually Works: Automate Authenticated Workflows**\n\n* **Universal 2FA support:** Automatically handles text message codes, TOTP authenticators, and email verification.\n\n**2. ⚡ Intelligent Caching: Fast and Reliable**\n\n* **Run once, cache forever:** After running a workflow with an LLM once, Dari can replay the workflow using deterministic DOM steps\n* **Fallback intelligence:** If a site changes, Dari automatically detects it, adapts, then caches the new path\n* **Why other agents fail:** Regular browser-use agents call LLMs on every single run. Dari only uses AI when needed.\n\n**3. 🧩 Built for Developers: Real Integration, Not Toys**\n\n* **Chat-to-automation:** Describe your workflow in plain English and get a working automation in seconds.\n* **API-first triggers:** Start workflows via POST request, integrate directly into your stack.\n* **Webhook & Wait:** Call your backend mid-workflow, run custom code, and continue the automation seamlessly.\n\n**💥 Real Impact**\n\n* A voice AI company automated data entry and form filling tasks, saving 10+ hours per week.\n\n**🧑‍💻🧑‍💻 How we got here**\n\nWe’re two Caltech CS grads who have previously worked on software at Amazon and Uber. \n\nWe’ve been building with browser use agents since the initial model releases and were constantly frustrated by how unreliable they were for production use-cases. We built Dari to fix the problems we’ve noticed since the start. \n\n**🎉 Get Started**\n\nSign up or schedule a demo at [usedari.com](http://usedari.com) or contact us at [founders@usedari.com](mailto:founders@usedari.com). ",
        "url": "https://www.ycombinator.com/launches/OZt-dari-the-easiest-way-to-build-reliable-browser-use-agents",
        "votes": 21,
        "created_at": "2025-10-08T16:09:36.103Z"
      }
    ]
  },
  {
    "id": 30874,
    "name": "Minro",
    "slug": "minro",
    "former_names": [
      "Iris"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f77542ef92b9a995fd50ddb381187d909ec7f5fd.png",
    "website": "https://minro.com/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Minro helps companies stay close to their users as they scale.\r\n\r\nToday, most startups have thousands of product events flowing through tools like PostHog, but still have no real understanding of who their users actually are, which users are quietly about to churn, or what outreach actually brings them back. Founders care deeply about their users, but staying close to them becomes operationally impossible very quickly.\r\n\r\nMinro plugs directly into a company’s analytics stack and turns product activity into living customer intelligence. We enrich every user with context like their company, role, LinkedIn/GitHub/Twitter, background, and likely use case, currently matching users to the correct online identity with ~80% accuracy starting from just name + email.\r\n\r\nWe then identify which users are most likely to churn based on behavioral patterns, persona similarity, and historical retention signals, and help founders proactively reach out before those users disappear. Minro drafts highly contextual founder-style outreach, tracks which conversations actually convert into retention, and continuously improves the system over time.\r\n\r\nThe result is a customer intelligence and retention layer that helps companies understand their users better, build stronger relationships, and reduce churn before it happens.",
    "one_liner": "Identify churn risk and stay close to users at scale",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1762405247,
    "tags": [
      "B2B",
      "Customer Success"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Fall 2025",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": [
      {
        "question": "How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)",
        "answer": "We’re cousins who’ve been building things together since we were kids. Samika had already founded a company before Iris building scalable enterprise agents. Siddhant has been coding since he was 11 years old and loves building complex systems in the form of consumer applications (12 apps in production, 2500+ active users)\r\n\r\nIris started as something we built for ourselves. We were constantly overwhelmed by scattered calendars, inboxes, and tasks and every “assistant” tool felt either too rigid or too dumb. So we decided to build one that actually understood us, combining the reliability of deterministic systems with the intuition of LLMs."
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        "question": "What's the history of your company from getting started until the present day? What were the big inflection points?",
        "answer": "We started Iris as a side project to fix our own scheduling chaos with a good user experience. The first prototype synced our calendars and emails, and within hours it was already making our days smoother. That’s when we realized how big this could be.\r\n\r\nA major inflection point was meeting Adam Cheyer, the founder of Siri. His advice reframed how we thought about the problem - it wasn’t just a UX challenge, it was an engineering problem. We then brought on one of Siri’s founding engineers as a technical advisor, which shaped our architecture around deterministic logic combined with adaptive LLM reasoning.\r\n\r\nThat shift (from “AI wrapper” to hybrid intelligent system) became the foundation of Iris. "
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        "question": "What is the core problem you are solving? Why is this a big problem? What made you decide to work on it?",
        "answer": "The core problem is cognitive overload because people are drowning in context switching between calendars, emails, and apps just to stay organized. Productivity tools today still expect you to manage them. They don’t understand how you work and make you configure rules and routines that fall apart when real life changes.\r\n\r\nWe felt that pain deeply ourselves. Both of us are neurodivergent so motivation wasn’t the issue, context was. We didn’t need another to-do list but we needed something that understood our rhythm and made intelligent decisions for us.\r\n\r\nIris exists to eliminate that friction. It learns how you work, automates the repetitive decisions, and keeps you focused on what actually matters. This problem is universal, everyone struggles to stay on top of their time. Solving it unlocks human attention at scale."
      },
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        "question": "What is your long-term vision? If you truly succeed, what will be different about the world?",
        "answer": "In the future, everyone will have their own Iris: an assistant that actually knows them - how they work, who they meet, where they go and helps them stay a step ahead. When two people both use Iris, their assistants can coordinate directly, handle logistics, and clear out the noise before it reaches them.\r\n\r\nAt scale, this becomes the foundation for how individuals and teams organize time - from one person’s calendar to entire companies. Iris is how people will work when AI truly understands context."
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        "user_id": 2525740,
        "full_name": "Samika Sanghvi",
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    "long_description": "AtlasGrid automatically builds a visual graph of your mobile app UI and displays analytics directly on your screens. Additionally, our fleet of AI-powered agents will continuously analyze thousands of mobile apps, gathering design insights and identifying growth opportunities + actionable product improvements.",
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        "full_name": "Oleg Kostour",
        "title": "Founder/CEO",
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        "full_name": "Aram Aghababyan",
        "title": "Founder",
        "founder_bio": "Ex-Meta - Superintelligence Labs, AI Infra. Data and compute resource management platform for ML training jobs.\nPrior to Meta, worked on DC infrastructure for large-scale software-defined networks at Insieme Networks (acquired by Cisco).\n",
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        "title": "Founder",
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      {
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        "title": "AtlasGrid - Accelerate Product Iteration",
        "tagline": "The Future of Analytics & Growth Intelligence",
        "body": "https://www.youtube.com/watch?v=W-VDeXPeNCA\n\n**TLDR**\n\nAtlasGrid automatically builds a visual graph of your mobile app UI and displays analytics directly on your screens. Additionally, our fleet of AI-powered agents will continuously analyze thousands of mobile apps, gathering design insights and identifying growth opportunities and actionable product improvements.\n\n![uploaded image](/media/?type=post&id=95857&key=user_uploads/32432/63720cfd-c630-4559-a683-55aa9a607eeb)\n\n**The Problem**\n\nProduct teams today operate in an increasingly fragmented environment. As organizations scale, documentation becomes scattered across PRDs, design files, JIRA tickets, and BI dashboards.\n\nThe lack of an up-to-date data dictionary causes analysts to have to track down subject-matter experts or ask engineers to audit the code to confirm the implementation of events. Designers creating new experiment variants find it hard to understand what users do on their existing screens before changing them (_“I wish Figma had a **data mode**”_). There’s often no single, authoritative ‘**source of truth**’ file for the interface design that can be referenced to understand what a user _actually_ sees, and in some cases, there is no Figma file at all (as designers adopt tools like Cursor to prototype). Oftentimes, product personnel resort to manually annotating Figma files with analytics found in their BI tools, or manually screenshotting parts of their own app.\n\nThese obstacles make it difficult to form a coherent, end-to-end understanding of a complex app. As a result, teams operate with partial or conflicting information, leading to missed growth opportunities.\n\n**Introducing AtlasGrid, an easy way to see your data in context**\n\nAtlasGrid uses an AI agent to go through your iOS and Android app, building a graph of the app architecture. It captures your analytics events, and builds a searchable graph of your app. You can easily find app screens, flows, events and even see funnel + CTA conversion rates directly on your UI. This makes it easy to get answers to questions like _“which upsells drive most of my trials”_ or _“where am I losing most of my users in onboarding”_. By tracking changes across every version of your app, every feature flag, we will become a source of truth for your product development cycle.\n\n![uploaded image](/media/?type=post&id=95857&key=user_uploads/32432/ae6d9a35-971a-41d8-b6a3-dde2df305631)\n\n**Our Vision**\n\nAtlasGrid is building towards a future in which generative design is commoditized, and the primary differentiator for teams will be performance. How quickly they can identify opportunities, ship improvements, and measure results. Our platform will integrate directly with AI code-generation tools, enabling developers to rapidly launch design variations suggested by “the grid,” dynamically reconfiguring their app for growth.\n\nWe believe the future of product development is self-improving applications, as more stages of today’s iteration process become automated. AtlasGrid will accelerate one of the most costly and time-consuming parts of that lifecycle.\n\n**Our founding team**\n\n[**Oleg Kostour**](https://www.linkedin.com/in/olegkostour/) is a 2nd time YC founder and Waterloo alum. He founded Pair (YC W12), a messaging app that received 10M installs and reached the top charts in the iOS social networking category. He closed 2 acquisitions - with Dropbox, then Life360 - and ran the Growth team at Life360 from \\~3M rMAU through to their IPO (\\~90M MAU).\n\n![uploaded image](/media/?type=post&id=95857&key=user_uploads/32432/d6267f91-4de3-49fc-be7a-06438679c1b5)\n\n[**Anton Krutiansky**](https://www.linkedin.com/in/antonkrutiansky/) is a second-time YC founder, Waterloo alum, and former tech lead at Dropbox. He co-founded Pair (YC W12) and played a key role in its acquisition by Dropbox. At Dropbox, he served as a tech lead on growth and mobile teams, building growth and experimentation infrastructure and leading mobile engineering across several product teams.\n\n[**Aram Aghababyan**](https://www.linkedin.com/in/aaghababyan/) was an Engineer at Meta Superintelligence Labs, developing the AI training platform for managing data and compute resources for ML training jobs. Prior to Meta, he specialized in data center infrastructure for large-scale software-defined networks at Insieme Networks (later acquired by Cisco).",
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        "created_at": "2025-11-29T06:03:01.423Z"
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    "id": 30883,
    "name": "hillclimb",
    "slug": "hillclimb",
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "We work with frontier AI labs to help train their agents to become AI research scientists",
    "one_liner": "Training Data for Recursive Self-Improvement",
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        "full_name": "Jun Park",
        "title": "Founder/CEO",
        "founder_bio": "hillclimb / prev deepmind, pro valorant, georgia tech",
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      {
        "id": 95533,
        "title": "hillclimb - Training data derived from human superintelligence",
        "tagline": "Building the human superintelligence community to advance AI",
        "body": "Hello! We’re Jun Park and Ibrakhim Ustelbay, founders of[ hillclimb](https://www.hillclimb.ing).\n\n\\_TLDR: To close the gap between today and the arrival of artificial superintelligence, we’re building a community of the world’s brightest minds to create the next generation of training data. Starting with math, we’ve formed the world’s densest cluster of IMO medalists, lean experts, and other math talent to design **RL environments** for frontier labs.\\_\\\n\\\n[Launch Video](https://youtu.be/30y3-SbRfZM)\n\n# The Problem - Data is accelerating on every axis\n\n**3 years ago,** we were impressed that ChatGPT could get good SAT scores. Today, GPT-5 and other frontier models assist meaningfully in coding, research, and tool use. Within two years, AI systems will autonomously [extend the frontier of science](https://x.com/SebastienBubeck/status/1958198661139009862?s=20).\n\n**Behind every leap in capability is a leap in the sophistication of data:**\n\n* From simple supervised fine-tuning → to richly structured RL environments → to world models and beyond\n* From mass labor → to curated, deeply intellectual data generation\n* From “labeling tasks” → to capturing the reasoning processes of domain experts\n\n![uploaded image](/media/?type=post&id=95533&key=user_uploads/1934623/128c37ee-f8e8-411b-9826-4b1b4492a9e2)\n\n_If AI reflects the intelligence of the people who shape its training data, the next era of progress requires the smartest humans on the planet._\n\n# The Solution - The world’s first _human superintelligence_ community\n\n![uploaded image](/media/?type=post&id=95533&key=user_uploads/1934623/1e971272-cd2e-46d9-9814-f81268047155)\n\n**In our first 2 months, we’ve:**\n\n* Built the densest cluster of elite math talent in the industry (IMO medalists, [Putnam Top 50](https://maa.org/wp-content/uploads/2025/03/2024-William-Lowell-Putnam-Competition-Announcement-of-Winners.pdf), Lean formalization experts, etc.)\n* Created _training data_ pipelines that faithfully capture their problem-solving intelligence\n* Partnered with [Nous Research](https://nousresearch.com) to help train a model that’s SOTA for math competitions.\n\n**We recruit top talent with a 85% winrate** against incumbents because we treat them as partners, not gig workers. For our work with Nous, we’ve negotiated co-authorship for our mathematicians because the data they produce has become a critical component of AI research.\n\n**Researchers love working with us** because we drop them in our community, allowing the iteration loop to become radically tighter. Instead of waiting for dataset revisions, they collaborate directly with world-class minds and see improvements in minutes, not months.\n\n# Our Story  **🎮 → 👨‍💻 → ⛰️**\n\nIt was only two years ago that we retired from competing professionally in esports. We taught ourselves to code and within a year, I became a research engineer at **DeepMind**, and Ibrakhim founded **Headstarter**, the first AI interviewer, scaling it to 100k+ users.\n\nIn the business of connecting the world’s smartest people to frontier labs, I understand the AI researcher’s perspective on what makes good training data, and Ibrakhim understands how to properly vet talent.\n\n![uploaded image](/media/?type=post&id=95533&key=user_uploads/1934623/08897fc4-b9c0-4dfd-913f-61f4bebd1998)\n\n# Our Ask\n\nIf you work at a frontier lab and need data (or know anyone who does), please reach out! Email us at [founders@hillclimb.com](mailto:founders@hillclimb.com).\n\nAlso, check out our site at [hillclimb.com](https://www.hillclimb.com/). Thanks for the support!\n\n![uploaded image](/media/?type=post&id=95533&key=user_uploads/1934623/797938d1-6d99-44f5-ad7d-1d302f0193fe)\n\n",
        "url": "https://www.ycombinator.com/launches/Oqr-hillclimb-training-data-derived-from-human-superintelligence",
        "votes": 155,
        "created_at": "2025-11-15T03:38:57.742Z"
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        "full_name": "Arnav Jain",
        "title": "Founder",
        "founder_bio": "CS and Business at Berkeley. Prev. Bespoke Labs, Jeeva Clinical Trials, FHL Vive Research Lab.\n",
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        "linkedin_url": "https://www.linkedin.com/in/arnavjain053/",
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        "full_name": "Yash Jain",
        "title": "Founder",
        "founder_bio": "Ex-Mercor, Databricks Amazon. Berkeley Computer Science.",
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        "linkedin_url": "https://www.linkedin.com/in/yashjain75/",
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        "user_id": 2555233,
        "full_name": "Nithik Yekollu",
        "title": "Founder",
        "founder_bio": "Co-Founder of Bellman AI. Prev Mercor, Berkeley EECS, Google, RISE Lab, LMSYS\n",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/nithik-yekollu-7298671a8/",
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    "id": 30921,
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        "body": "**TL;DR**\n\nCompyle is the coding agent that actually collaborates. It doesn’t just guess what you mean - it asks, plans, and checks in before writing a single line of code. That means you can trust it with bigger and more ambiguous projects than any other coding agent.\n\nhttps://youtu.be/iNQ8G4k03gc\n\n🙏 **Our ask**\n\n**Try our beta today at [compyle.ai](http://compyle.ai)** and let us know what you ship! \n\nJust connect your Github, select your repos, and create a task to get started.\n\n❌ **The Problem**\n\nToday’s coding agents - like Codex, Claude Code, and Devin - excel at small, well-defined tasks. Their autonomous design works best for jobs that need little clarification, such as updating libraries or making simple UI edits.\n\nBut full autonomy becomes a weakness for open-ended work like building new features or products. These agents often press ahead despite unclear or conflicting requirements - and even when they succeed, the resulting code may be hard for teams to understand.\n\nGood engineers know to clarify requirements before coding, check in with product owners to confirm goals, and collaborate with peers to ensure quality. Coding agents should do the same.\n\n🚀 **How Compyle solves this**\n\nCompyle keeps you in full control through a question-driven approach. You describe the task, then Compyle asks questions until it understands what you want to build. It produces research and planning artifacts before writing any code.\n\nDuring implementation, Compyle validates its changes against your decisions. If something doesn't match up, it stops and asks rather than pushing forward. You stay in the driver's seat the entire time.\n\n![uploaded image](/media/?type=post&id=94565&key=user_uploads/2234809/82738600-0f9c-4de5-ab79-57f7cb4424bb)\n\n\n**Our story**\n\nBefore Compyle, we were building SmartAppetite (AI agents for insurance). Using tools like Claude Code and Cursor, we had a demo in days - then spent weeks cleaning up a codebase we no longer fully understood.\n\nWe had to pause feature development just to refactor. That pain is why we built Compyle.",
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    "long_description": "Radius is a browser where developers can orchestrate agents from their tabs. Ship 100x from a single place where agents can see, navigate, and act on your workspace.",
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        "full_name": "Michael Sukkarieh",
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        "url": "https://www.ycombinator.com/companies/sourcebot/jobs/WVbwFeV-founding-engineer",
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        "title": "Sourcebot: The Code Understanding Platform",
        "tagline": "Helping developers and AI agents understand massive codebases.",
        "body": "**TL;DR**: Sourcebot is an open source code understanding platform. It’s used by thousands of engineers in some of the largest companies in the world (including **NVIDIA, Red Hat, Wikimedia, and Arista Networks)** to help developers and AI agents understand massive codebases.\n\n[https://youtu.be/YJIi-gcAM3g](https://youtu.be/YJIi-gcAM3g%5C)\n\n\\\n**The problem:**\n\n* Large engineering teams manage **millions of lines of scattered and undocumented code**.\n* Individual engineers must regularly find and understand code across this complex environment to do their job. Existing tooling to do so is **inadequate, rudimentary, and often nonexistent.**\n* **AI agents have this problem too.** They need this context to provide usable results within an enterprise environment\n\n**The solution:**\n\nSourcebot solves this by providing the following tools:\n\n* **Code Search -** instantly search across millions of lines of code. Supports regex, boolean logic, and repo/file/branch filters.\n\n![uploaded image](/media/?type=post&id=94687&key=user_uploads/1449228/70c891b0-cfec-4ff6-b070-fc1f212c29da)\n\n* **Ask -** ask questions in natural language across thousands of repos. Like asking in Cursor, but across all your repos and in a web app with inline citations.\n\n![uploaded image](/media/?type=post&id=94687&key=user_uploads/1449228/b97e4beb-83cb-4d8d-b6b0-ed53a2a973c8)\n\n* **MCP -** gives both of the above tools to AI agents, allowing them to fetch context from code across your organization.\n\nAdditional features:\n\n* We integrate with any **code host** (e.g., GitHub, GitLab, BitBucket, etc.) as well as any **LLM model** (e.g., OpenAI, Anthropic, Bedrock, etc.). Bring your own LLM key.\n* Sourcebot is **open source** and **self-hosted** - none of your code leaves your deployment. Deploy and index all your repos in minutes with a single docker container.\n* We have a community edition that’s **free to use**, and a paid enterprise edition with advanced navigation features, analytics, and security/compliance features.\n\n**Our story:**\n\nBrendan and I met 10 years ago during our first week at McGill University 🇨🇦. We were both into game engines, which led us to work at Ubisoft Montreal on the largest game engines in the world. Afterwards, we worked on some of the most complex systems out there: Visual Studio at Microsoft, a cloud-first game engine at Google, VR operating systems at Meta, and cloud-streaming infrastructure at Xbox. Ramping up and understanding these systems was always a long, painful process - which is what led us to build tools to help developers understand this complexity.\\\n\\\nLearn more here: https://www.sourcebot.dev/\n\n![uploaded image](/media/?type=post&id=94687&key=user_uploads/1449228/4ef682b8-0ac6-48a4-937d-8a64d62f34d3)\n\n",
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        "full_name": "Fabian Lindfors",
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      {
        "id": 95350,
        "title": "Specific: production-ready backends from natural language",
        "tagline": "Create and scale production-ready backends without configuration or coding",
        "body": "Hi! 👋\n\nWe’re [Fabian](https://www.linkedin.com/in/fabian-lindfors/) and [Iman](https://www.linkedin.com/in/iman-radjavi/), and we’re building [Specific](https://specific.dev/) — an agent that builds and deploys backends from natural language.\n\nSpecific makes it effortless to create, scale, and manage production-ready backends, without configuration or coding. Just describe what you need, and Specific builds it.\n\n# Why we are working on this\n\nWe’ve spent our careers as engineers building and maintaining complex backend systems, and learning firsthand what it takes to make them reliable, secure, and scalable.\n\n* **Fabian** spent three years at **Stripe**, where he was tech lead for systems that processed tens of billions of dollars each year.\n* **Iman** spent four years at startups like **Fever** and **Braive**, building software that balanced national energy grids and managed sensitive healthcare data under strict regulatory requirements.\n\nAs AI unlocks software building at an entirely new scale and speed, backends need to keep up in reliability, security and scalability. Specific is our way of making that possible.\n\n---\n\nSee it in action: https://youtu.be/62QGL3drU44\n\n# Backends are hard\n\nBackend-as-a-service platforms have made backend development much easier, but not easy enough for a new era where AI lets anyone build software in minutes.\n\nThey still require deep understanding of concepts like database schemas, migrations, security and APIs to use effectively. That limits how powerful and flexible non-technical users can be. Ambitions often exceed what the platforms make possible.\n\nThis gap becomes particularly clear for AI coding platforms. Their agents can generate impressive web and mobile apps, but still rely on users to sign up for and connect to an external backend provider. Integrating those providers can take weeks, and maintaining them is an ongoing effort to make sure the agent truly understands how to use them.\n\n# How Specific helps\n\nSpecific offers a backend-as-a-service that’s entirely generated and maintained by our own expert coding agent. We designed it to understand user needs from natural language prompts, and to build a tailor made backend automatically.\n\nYou can connect any coding agent to Specific in minutes through our MCP server. Once connected, you can now generate fully featured, secure, and scalable backends to match any frontend.\n\nBecause the backend is built and managed by our own agent, there’s no need to teach your agent how to use an external platform or maintain fragile integrations. Specific handles everything end-to-end, scaling seamlessly as projects grow.\n\n![uploaded image](/media/?type=post&id=95350&key=user_uploads/122815/3655d431-5a32-424d-9a95-7d8f6f6f6eab)\n\nFor our initial launch, we are working with AI coding platforms like [Natively](https://natively.dev/) that create thousands of new projects _every day_. We are hearing from these platforms that they want to focus on what they do best, designing and building great apps, without worrying about backends.\n\nWith Specific, they can:\n\n* **Launch new isolated projects in seconds** through our API. Fully white-label, end users don’t need to configure anything.\n* **Scale automatically.** Projects scale up based on usage, and down to zero when idle.\n* **Integrate in minutes** by connecting through our MCP server. No need to spend weeks teaching their agents how to build and maintain backends.\n* **Enable common integrations instantly**. Authentication, payments and LLMs work out of the box with no API keys or setup required from users.\n\n# Come talk to us\n\nGet in touch at [hello@specific.dev](mailto:hello@specific.dev).\n\nWe are excited to talk to everybody who needs backends, whether you have years of experience building software, have just discovered vibe coding, or are building a coding platform for others.\n\nWe also have a waitlist that you can sign up for on our site: [specific.dev](https://specific.dev/). We will be inviting folks from the waitlist to a private beta of Specific soon. Sign up early to be one of the first to get access!",
        "url": "https://www.ycombinator.com/launches/Onu-specific-production-ready-backends-from-natural-language",
        "votes": 154,
        "created_at": "2025-11-10T02:28:02.906Z"
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    "website": "https://perseus.computer",
    "all_locations": "Bengaluru, KA, India",
    "long_description": "Perseus takes an iterative branching approach to search in high dimensional spaces.\r\n\r\nOur first product helps coding agents find the right codebase context before they write. It searches files, symbols, and dependencies in parallel, so models can make better changes with less trial and error. Perseus Search gives Mythos-level programming ability to Opus-level coding agents.",
    "one_liner": "Applied Lab focused on Search in Latent Spaces.",
    "team_size": 4,
    "industry": "B2B",
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    "country": "IN",
    "linkedin_url": "https://www.linkedin.com/company/perseus-computer",
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        "full_name": "Samrath Chadha",
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      {
        "id": 94906,
        "title": "Mantle - Automate your back office",
        "tagline": "Build internal agents to automate back office work with one prompt",
        "body": "Hey! We’re building Mantle - a clear-cut way to do your repetitive work on autopilot.\n\n**TL;DR**: We think you’re wasting human potential on boring shit. [Book a call here.](http://cal.com/team/mantle/customer-meeting)\n\nWe do this by:\n\n1. **connecting to your tools:** pulling information securely, and building a constantly updating context layer for agents to operate on\n2. **creating and managing your agents:** enter in one prompt, and our system will make the perfect agent to do your work. no fixed workflows, we focus on the goal and allow agents to move dynamically like a human would\n3. **handling updates, schedules and everything else:** whether a new lead pops up in your CRM, a new support ticket rolls into your email, or it’s Friday and you need a report on which leads are the most likely to churn - Mantle handles it all and runs the agents in the background\n\nHere’s Mantle doing a few cool things:\n\n1\\. Searches Stripe for invoices, PostHog for product usage data, and HubSpot for the customer profile - it then uses its context to **generate a report with action items for your customers and sends them to you in Slack.** We recommend putting this on a daily schedule!\n\n![uploaded image](/media/?type=post&id=94906&key=user_uploads/2522177/5cbfd593-9504-4a94-9400-d5cf9c6591d1)\n\n2\\. **Triggers automatically when you get an inbound meeting -** goes through your past calls with the person (if any), searches the web and your Notion for information about them - and writes the information directly into your calendar app (it edits the invite only for you)!\n\n![uploaded image](/media/?type=post&id=94906&key=user_uploads/2522177/4809c2a8-1d5f-4018-8980-4748c5af23e3)\n\n3\\. When you get an email - if valid (not spam/promotion), **we auto-draft a reply to it and store it in your email client.** This draft matches your exact tone and has insights from your past emails, Notion, and whatever else you give it access to. It uses the context layer to learn and search about the person through these tools extremely efficiently, quickly finding all relevant data.\n\n![uploaded image](/media/?type=post&id=94906&key=user_uploads/2522177/384c4258-c5ff-4101-b3c1-de2a4bcb9f56)\n\nWe’ll boost your team’s efficiency 10x in a week. [Book a call here to make that happen.](http://cal.com/team/mantle/customer-meeting)\n\n![uploaded image](/media/?type=post&id=94906&key=user_uploads/89898/24d9fe9b-6bc5-4300-8fc1-63a8e5c24951)\n\n",
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        "full_name": "Jerry Zhang",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder @ Lemma (YC F25) | Reliability platform for AI agents",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jerry-n-zhang/",
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        "full_name": "Cole Gawin",
        "title": "Founder/CTO",
        "founder_bio": "developing the next generation of intelligent systems @ lemma (f25) | ex-USC",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/colegawin",
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        "title": "Product Engineer",
        "url": "https://www.ycombinator.com/companies/uselemma/jobs/wrFU6bU-product-engineer",
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        "experience": "Any (new grads ok)",
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        "title": "Lemma: Continuous Learning for AI Agents",
        "tagline": "We enable AI agents to continuously improve by turning real user feedback into automated prompt optimizations. ",
        "body": "**TL;DR:**\n\nLemma is the first evaluation + observability platform built not just to measure performance, but to improve it automatically. We help AI agents learn from real user feedback and production data, closing the loop so your prompts and agents continuously optimize themselves over time.\n\n**Launch Video:** https://www.youtube.com/watch?v=E4_v-pY_4fs\n\nHey everyone! We’re [Jerry](https://www.linkedin.com/in/jerry-n-zhang/) and [Cole](https://www.linkedin.com/in/colegawin/), co-founders of [Lemma](https://www.uselemma.ai/) (YC F25).\n\n**The Problem:**\n\n**AI agents don’t learn from their mistakes. In fact, they get worse with use.**\n\nIn production, prompts and agents continuously degrade due to real-world input drift (new user behaviors or unseen edge cases). Agent performance can often **drop \\~40% in a few weeks**, and suddenly what worked in testing breaks in front of customers.\n\nWhen that happens, engineers are forced to dig through logs, collect failing examples, and manually tweak prompts rather than building core product features.\n\n**Solution:**\n\nThat’s why we built **Lemma: the first end-to-end system that closes the loop between agent deployment and improvement.**\n\n**Here's what that means:**\n\n**Step 1:** Lemma detects failed outcomes directly from live traffic, and it automatically identifies the exact cause in an agent chain.\n\n**Step 2:** Lemma alerts you, and with one click, it runs targeted prompt optimizations to fix the failing behavior without any manual tracing or guesswork.\n\n**Step 3:** We give you back an improved prompt and automatically open a PR in your codebase so your prompts can live where you want them. Alternatively, you can also fetch your prompt from the Lemma dashboard.\n\n**Plus, Lemma provides all the LLM eval and observability features you rely on, just reimagined for continuous learning:**\n\n* Data-ingestion pipeline to bring your existing eval sets and automatically flag inconsistencies and gaps\n\n![uploaded image](/media/?type=post&id=95219&key=user_uploads/1798805/4f862c09-dce0-48da-91fe-1a152a5d82da)\n\n* Prompt editor and inference support for any closed & open-source model for prompt iteration.\n\n![uploaded image](/media/?type=post&id=95219&key=user_uploads/1798805/92464a28-ab54-4511-bc79-fd3e4f9d4823)\n\n* Agent tracing observability with live drift detection, regression alerts, and performance visibility across real user interactions.\n\n![uploaded image](/media/?type=post&id=95219&key=user_uploads/1798805/2b82ecee-1965-4fc0-831d-36b76db3f064)\n\nTeams using Lemma cut manual prompt iteration by 90%, resolve production drifts in minutes instead of days, and improve model performance \\~2–5% every optimization cycle.\n\n**Our Story:**\n\nWe met freshman year at USC and have been building together ever since instead of going to classes.\n\nBefore starting Lemma, we were engineers at two high growth, AI-native startups: Tandem (AI for healthcare) and Chipstack (AI agents for chip design). At both companies, setting up evaluations looked like clunky Retool dashboards and multiple engineers manually tweaking experiments. We built internal systems that automated both running the evaluations themselves, as well as the error-driven feedback loop. The result: 2x accuracy improvement and speed of iteration.\n\nWe soon realized every AI company was reinventing the same internal tooling in-house. So we left college, joined YC, and are now bringing continuous learning infrastructure to everyone else.\n\n![uploaded image](/media/?type=post&id=95219&key=user_uploads/1798805/53754495-215a-47aa-884d-bae4a59f9a68)\n\n**Ask**\n\n**Try our platform** - If you’re building with LLMs and run a ton of prompt or eval experiments, we’d love for you to work with us.\n\n**Introductions** - If you know a Head of AI/Eng or CTO at a pre-seed to Series A startup, we owe you lunch :)\n\nPlease reach out at [jerry@uselemma.ai](mailto:jerry@uselemma.ai) or book a live demo on our website [uselemma.ai](http://uselemma.ai). All help is appreciated - thank you!\n\n![uploaded image](/media/?type=post&id=95219&key=user_uploads/1798805/53c71689-276c-4993-b693-50aa8a492566)\n\n",
        "url": "https://www.ycombinator.com/launches/Oln-lemma-continuous-learning-for-ai-agents",
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        "created_at": "2025-11-05T19:58:08.940Z"
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    "website": "https://antigen.sh/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Antigen is an AI adversary for the enterprise. It maps, exploits, and secures your attack surface through nightly automated offensive testing and monthly human red team assessments. Every finding is delivered with traces, reproduction steps, and remediation directly in GitHub, Linear, or the Antigen Platform.\r\n\r\nWe work with companies in financial services, healthcare, retail, and government where security is trust.\r\n\r\nWe're backed by Lightspeed, DST Global, and Susa Ventures.",
    "one_liner": "Continuous offensive security for the enterprise.",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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        "full_name": "Saad Jamal",
        "title": "Founder/CTO",
        "founder_bio": "co-founder @ antigen. prev. ml infra at tesla autopilot. law school dropout.\n\nBefore Zag, Saad trained reasoning models with Ashish Vaswani, author of the famous Attention Is All You Need paper. At Nuro, he developed an ML Compiler framework that enabled running the perception layer across multiple GPU's. And at Tesla he built infrastructure that halved the time it took to train Planning & Controls models. \n\nHe also served at the Supreme Court of Pakistan and dropped out of UChicago Law.",
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      {
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        "full_name": "Abdullah Nauman",
        "title": "Founder",
        "founder_bio": "Co-Founder @ Antigen. Previously product at Google Ads and ML at Google Search.\n\nPreviously at Google, shipped product features for new advertisers and built large-scale ML infrastructure for measuring cross-site conversions on Search.\n\nTook a year off college to join as second employee at a YC startup. Separately scaled a bootstrap SaaS to $30k MRR. Also wrote low-level imaging software for silicon wafer manufacturing.",
        "is_active": true,
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        "title": "Security Researcher",
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        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Devops",
        "salary_range": "$150K - $220K",
        "equity_range": "0.50% - 1.00%",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
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        "id": 94551,
        "title": "Zag: AI Review Agents for Every PR",
        "tagline": "Custom review agents that build, test, and run your code before it lands.",
        "body": "Hey everyone, we’re Abdullah and Saad - cofounders of [Zag](https://zag.dev/) 👋\n\n**TL;DR**\n\n**Zag** is a platform for building and running AI review agents. You describe agents in TypeScript or Swift as composable Tasks, and Zag runs them in **real sandboxed environments** on every pull request. Agents don't just read diffs. They build your project, run your tests, boot your app, and verify that it actually works.\n\n_We've opened early access to teams building for Apple platforms (iOS, iPadOS, macOS), running on dedicated Apple Silicon with Xcode, simulators, and the full native toolchain._\n\n<https://www.youtube.com/watch?v=MuIK1woknhc>\n\n**_The Problem_**\n\nCoding agents are producing changes faster than humans can review them. Tools like Claude Code and Codex are accelerating how code gets written, but the review side hasn't kept up. Teams are merging changes they haven't fully validated, or creating bottlenecks where a handful of senior engineers review everything.\n\nStatic AI code review (inline comments on diffs) helps, but it requires more human-in-the-loop than teams can sustain. Reading AI-generated suggestions about AI-generated code doesn't scale. The kind of confidence that lets teams merge fast comes from actually building, testing, and running the code.\n\n**_Our Solution_**\n\nZag lets teams build custom review agents that run in real environments on every PR.\n\nWe believe that as human engineering work moves up a layer of abstraction, a tech lead's primary job will be tuning better review agents. Not reading diffs line by line, but shaping the automated judgment that enforces their team's engineering culture at the scale of AI-authored code.\n\nThe primary unit of work is a Task: a composable, dependency-aware unit that describes an environment and the logic that runs inside it. Tasks can spin up Claude Code, Codex, or custom agents with access to real build tools, simulators, and full operating systems. Every Task runs in an ephemeral session on dedicated Apple Silicon that boots in seconds from pre-warmed snapshots.\n\nUse built-in utilities for common checks (build verification, test execution, crash detection, App Store compliance), or write your own agents for the specific behaviors your team cares about. When applied to every PR, this helps teams merge changes as fast as they author them.\n\n**Why Apple Developers First**\n\nApple developers need macOS to build and test their code. You can't meaningfully validate an iOS app without Xcode, a simulator, and Apple Silicon. Most CI providers treat macOS as an afterthought. Zag provisions dedicated M4 hardware with no queue at $0.015/minute, priced at AWS cost. If you already have GitHub Actions or Cirrus workflows, a one-line runner swap points them at Zag compute, even before you adopt the review agents.\n\n**_Our Ask_**\n\n1. Connect us with iOS/macOS teams that are frustrated with their CI or are already using coding agents and feeling the review bottleneck.\n2. If you lead an engineering team and want to try custom review agents on your codebase, book a demo at zag.dev/book. A dedicated engineer will embed with your team to set up agents you can trust on every PR.\n3. Share this with anyone building for Apple platforms.\n\n**_The Team_**\n\n![uploaded image](/media/?type=post&id=94551&key=user_uploads/919490/d4e60f0f-0558-48f6-b318-f404ec638358)\n\n**Abdullah** built ML infrastructure at Google powering core Search systems that directly drove **$1B+ in revenue**.\n\n**Saad** spent three years training video models at Tesla Autopilot and later built training infrastructure with **Ashish Vaswani** (author of _Attention Is All You Need_).\n\nTogether, we’ve also collected **$200k+ in bug bounties** from security research.",
        "url": "https://www.ycombinator.com/launches/Ob1-zag-ai-review-agents-for-every-pr",
        "votes": 66,
        "created_at": "2025-10-10T07:18:24.526Z"
      }
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    "id": 31001,
    "name": "Fastshot",
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    "website": "https://www.fastshot.ai/",
    "all_locations": "Thessaloniki, Greece",
    "long_description": "Fastshot is a no-code mobile development platform.\r\nOur mission is to \"Democratize mobile app creation with AI\"\r\nAnyone can develop a mobile app from idea to App Stores within minutes just by chatting with AI. Start at https://fastshot.ai/ai-app-builder\r\n\r\n",
    "one_liner": "Lovable for mobile apps",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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    "url": "https://www.ycombinator.com/companies/fastshot",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/fastshot.json",
    "year_founded": 2025,
    "city": null,
    "country": "GR",
    "linkedin_url": "https://www.linkedin.com/company/fastshot",
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      "name": "Tom Blomfield",
      "url": "https://www.ycombinator.com/people/tom-blomfield"
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      {
        "user_id": 370264,
        "full_name": "Dmitry Fatkhi",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder @ Fastshot, ex AI/ML engineer @ Google, focus on multi-agent architecture and AI coding quality",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/fatkhi",
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        "user_id": 370260,
        "full_name": "Elvira Dzhuraeva",
        "title": "Founder/CPO",
        "founder_bio": "Co-founder @ Fastshot, ex-Google Gen AI Developer tools, ex-Kubeflow AIOps, ex-Cisco Computer Vision",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/dzhuraeva",
        "x_url": "https://x.com/elvirafortune",
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    "launches": [
      {
        "id": 95041,
        "title": "Fastshot – Lovable for mobile apps",
        "tagline": "Build powerful mobile apps in minutes, just by chatting with AI.",
        "body": "**TL;DR;** Fastshot is an end-to-end mobile development platform that lets anyone build and ship beautiful mobile apps 10x faster and 100x cheaper — no code, just by prompting AI.\n\nhttps://youtu.be/diN3yEdoJbo\n\n### The Problem\n\nThe world runs on mobile. Yet over half of businesses still don’t have a mobile app.\n\nWhy? Because building one is still seen as a luxury — expensive, complex, and slow.\n\nToday, users have three options:\n\n1. Hire a Mobile Development Agency\\\n   Agencies handle everything: from design to app store launch.\\\n   But at a steep cost: $60K–$120K for an MVP, taking 3–6 months before the first users see it.\n2. Build an In-House Team\\\n   Hiring a developer costs about $130K/year, not including design, backend, and QA.\\\n   Expect similar timelines: 3–6 months to launch.\n3. Use traditional No-Code Builders (Adalo, Bubble, etc.)\\\n   These platforms promise simplicity - but fail to deliver real scalability, design quality, and functionality.\n\n### Introducing Fastshot\n\nFastshot is redefining how mobile apps are built.\n\nWith Fastshot, anyone, even non-technical teams, can design, build, and ship mobile apps just by chatting with AI.\n\n🙅No engineers.\\\n🙅No designers.\\\n🙅No project managers.\\\n🙅No 6-month timelines or 6-figure costs.\n\nEngineered by Google developers.\n\nYou can have your first MVP in customers’ hands the same day.\n\n### How It Works\n\nFastshot is an end-to-end mobile development platform that covers the entire lifecycle:\n\nIdeation → Design → Development → Deployment\n\nWe provide:\n\n* Beautiful out-of-the-box designs and templates\n* Built-in authentication, payments, and storage\n* Plug-in any AI providers to your app\n\nEverything your app needs: from concept to app store, powered by conversation.\n\nhttps://youtu.be/92yFPZuJPUY \n\n### Why Fastshot\n\nIsn’t \\_\\_ already doing this?\n\nYes – and no.\n\nFastshot isn’t just another no-code builder. We employ a multi-agent workflow that differentiates us from how simple vibe coding wrappers operate today, ensuring the best in class, high quality, modern design mobile apps.\n\nNo more brittle, half working mobile app scaffolds. Just working mobile apps in app stores. Our agents take care of everything that goes into mobile development processes end-to-end: from planning, to design, to implementation and shipment to stores.\n\nWe’re building the next generation of mobile app development platform, transforming how the industry will operate for the next decade.\\\nWith Fastshot, you can start building your app 10x more affordably and 10x faster than traditional methods.\n\n## We care about you\n\nWe win together. **Your success is our success.**\n\n**We want to make sure your app is lovable and goes viral.** Our goal is to build a long-term, meaningful partnership with every creator, founder, and business that chooses Fastshot. You grow - we grow with you.\n\nSo, if you’re ready to turn your idea into a real mobile app – **start using** [fastshot.ai](http://fastshot.ai?utm_source=yclaunch).\\\nShare your vision, and we’ll bring it to life.\n\n### About Us\n\nFastshot is built by experts with over a decade of experience creating AI developer tools and mobile apps, with backgrounds at companies like Google, Meraki, Cisco.\n\nDmitry: With 10+ years in AI and mobile development, spent years at Google building AI agents across Core ML and Google Cloud. Before that, as a Engineer, he kept seeing the same problem repeat: brilliant ideas slowed down by slow shipping. Fastshot is his solution to that — a way to turn ideas into apps instantly.\n\nElvira: With 10+ years in software engineering and product management, Elvira built and shipped GenAI developer tools at Google to millions of users. She’s also a developer advocate, speaker, and led the launch of the open-source Kubeflow 1.0 MLOps platform. Having witnessed firsthand how AI can unlock limitless potential, she’s now making that power accessible to everyone through Fastshot.\n\nTogether, they’re on a mission to empower anyone with an idea to bring it to life, instantly, with zero code.\n\n![uploaded image](/media/?type=post&id=95041&key=user_uploads/370260/b08873f3-e446-46f4-9d20-6ca7c3ab87dc)\n\n",
        "url": "https://www.ycombinator.com/launches/Oiv-fastshot-lovable-for-mobile-apps",
        "votes": 137,
        "created_at": "2025-10-30T20:19:02.131Z"
      }
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    "id": 31013,
    "name": "Rivet",
    "slug": "rivet-design",
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/28bd19a3fc057798d00b7402f78d585553560d40.png",
    "website": "https://rivet.design/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Rivet helps designers explore dozens of directions from their agent.  \r\n\r\nLearn more at rivet.design",
    "one_liner": "Explore dozens of design directions with your agent",
    "team_size": null,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1759433421,
    "tags": [
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      "Design Tools",
      "AI"
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Fall 2025",
    "status": "Active",
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      "Engineering, Product and Design"
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    "regions": [
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      "America / Canada"
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    "stage": "Early",
    "app_video_public": false,
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    "url": "https://www.ycombinator.com/companies/rivet-design",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/rivet-design.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/rivetdesign",
    "x_url": "https://x.com/designrivet",
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    "primary_partner": {
      "name": "Aaron Epstein",
      "url": "https://www.ycombinator.com/people/aaron-epstein"
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    "founders": [
      {
        "user_id": 206350,
        "full_name": "Sam Gorman",
        "title": "Founder/CEO",
        "founder_bio": "Founder of Rivet.  Previously led product engineering teams as an early engineer at Snorkel AI.  Built an app & grew it to 100,000+ users.  Studied Product Design & Computer Science at Stanford. ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/gormansam",
        "x_url": "https://x.com/gormankind",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/809eda01806b6cef902bda76b7f9f496fefafcb6.jpg"
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      {
        "id": 94987,
        "title": "Rivet - Burn down your design backlog",
        "tagline": "Product designers use Rivet to own the UI of their codebase. ",
        "body": "**TLDR:** Product designers own the look and feel of their app’s interface with Rivet’s visual AI tools. No more waiting for engineers. Point at any element in your live product, change it, and ship it yourself. Rivet translates precise design intent into clean, reviewable code you can merge.\n\n# [→ Try Rivet today at rivet.design](https://rivet.design)\n\n# **Watch a customer polish their product with Rivet:**\n\nHere’s an example of how [Item](https://www.item.app/) (a design-first, AI native CRM) used Rivet to refine details in their UI.\n\n1. **Select any element** on a web application. Use your styles to change it.\n\n![uploaded image](/media/?type=post&id=94987&key=user_uploads/206350/344678ec-87c2-4928-a80d-fed1f623d329)\n\n2. **Refine your UI**. Change spacing, colors, layouts. Get it pixel-perfect.\n\n![uploaded image](/media/?type=post&id=94987&key=user_uploads/206350/6d172766-1402-44fa-952a-9d3d5dd067ae)\n\n3. **Ship it.** When you’re done, Rivet pushes quality code to your repo just like a frontend engineer on your team would.\n\n![uploaded image](/media/?type=post&id=94987&key=user_uploads/206350/2da40da6-c814-4bb7-90d3-396c4995a894)\n\n# **The problem: Design debt piles up, even at the best companies.**\n\nEvery software company has a growing list of polish issues that never get fixed.\n\n* Broken loading states\n* Buttons that look wrong on mobile\n* Colors that don't match your app’s styles\n* Spacing that's off by 4px\n\nProduct designers live in these details, and they’ve been gated out of making real changes to real apps. Instead, they spend time crafting details that get lost when it comes to implementation.\n\nRivet helps designers own the quality of their interface, and frees up engineers to do more engineering work.\n\n## **Why I built Rivet**\n\nI’m a repeat founder and former early product engineer at Snorkel AI. I owned AI products for non-technical users as Snorkel scaled to Series D over 3 years. I started my career as a product designer and built at the intersection of design & engineering for the last 7 years.\n\nI built Rivet because I watched the work of brilliant designers get diluted. I think product designers today are like artists without a paintbrush. They have to ask others to paint for them instead. We should just give product designers a brush, and let them paint their masterpiece in code.\n\n![uploaded image](/media/?type=post&id=94987&key=user_uploads/206350/c566632e-8fc8-40c4-9d4c-a867bbfaa557)\n\n# **Designers → Start shipping today!**\n\n![uploaded image](/media/?type=post&id=94987&key=user_uploads/206350/4616fcce-815a-4ee8-b1d4-885386e67fe9)\n\n**Are you a product designer?** \n\n# **🎨  [Go to rivet.design and sign up](https://rivet.design)**\n\n**Not a designer? That’s great too!**\n\nSend [rivet.design](https://rivet.design) to your designer and let them start burning down your polish items\n\nYC startups and design studios are already using Rivet to shortcut design handoffs and fix every UI polish item they can think of. Designers are shipping their own work. And engineers are getting their time back.\n\n🟧 **YC deal:** We'll fast-track you off the waitlist & apply a YC discount\n\n✏️ Want to just rant about design handoffs or your growing backlog? Send your worst story to [sam@rivet.design](mailto:sam@rivet.design)",
        "url": "https://www.ycombinator.com/launches/Oi3-rivet-burn-down-your-design-backlog",
        "votes": 48,
        "created_at": "2025-10-29T01:26:52.491Z"
      }
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    "id": 31022,
    "name": "Coasts",
    "slug": "coasts",
    "former_names": [
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    "website": "https://coasts.dev",
    "all_locations": "",
    "long_description": "A Coast (containerized host) is a local development runtime. Coasts let you run multiple isolated environments for the same project on one machine. As AI coding agents increasingly work in parallel across git worktrees, developers hit painful conflicts — clashing ports, duplicated databases, and fragile per-branch setup. Coasts solve this by giving each worktree its own fully isolated runtime, so multiple agents can build and test side by side without stepping on each other.",
    "one_liner": "Localhost service isolation and orchestration for git worktrees",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1762549706,
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      "B2B",
      "Productivity",
      "Design",
      "Web Development"
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    "isHiring": false,
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    "batch": "Fall 2025",
    "status": "Inactive",
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      "Unspecified"
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/coasts",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/coasts.json",
    "year_founded": 2025,
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    "primary_partner": {
      "name": "Pete Koomen",
      "url": "https://www.ycombinator.com/people/pete-koomen"
    },
    "founders": [
      {
        "user_id": 179922,
        "full_name": "Jamie Sunderland",
        "title": "Founder/CEO",
        "founder_bio": "Second time YC founder. Former YC Product Engineer (I made the YC investor CRM). I like weird front end things a lot. In a former life I started Cheqout (YC W21), a QR-based ordering platform that grew to over 250 restaurants and $30M GMV during the pandemic. Before that I was a developer on Airbnb's China Risk Team.",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/jamesrainersunderland/",
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      },
      {
        "user_id": 3082625,
        "full_name": "Dan Hyman",
        "title": "Founder/CTO",
        "founder_bio": "Senior Engineer and Cloud/AWS expert with experience leading teams building enterprise applications and infrastructure.  In a past life, I was a chef at a James Beard award winning restaurant.",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/dan-hyman-dev/",
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        "id": 95312,
        "title": "JSX Tool: In-Browser React IDE",
        "tagline": "The AI first IDE for React development",
        "body": "**tl;dr**\n\nJSX Tool is an in-browser IDE that creates a common language between developers and AI for building React UIs. Click any element in the browser to jump straight to the relevant line of code and edit it yourself, or provide precise context to an LLM to make updates.\n\nhttps://www.youtube.com/watch?v=JIIXvN7vhrs\n\n---\n\n---\n\n---\n\n**The Problem**\n\nLLMs have transformed how we write code, yet they consistently struggle with precise UI updates. The common belief is that AI simply doesn’t do well with visual tasks, but the real problem is that we're asking LLMs to understand UI without giving them proper context. They’re great at vibe styling but not great at producing precise UIs.\n\nWhen you prompt an LLM about styling or component changes today, you're describing visual elements through text alone. It's like giving directions without a map. Meanwhile, developers juggle between browser DevTools, their code editor, screenshot tools, and component explorers just to gather enough context to make AI useful for these kinds of tasks.\n\n**Our Solution**\n\nJSX Tool addresses this by letting you click on any element and prompt your LLM with precise DOM context, the exact source component, its styles, and its position in the React hierarchy. Everything happens in one place: inspect, prompt, edit, and see changes instantly. \n\nAnd when AI suggestions aren't quite right, our full IDE is right there in the browser with that same context, so you can jump to the exact line of code you want to edit with a single click. You get the benefits of AI, while keeping the creative control and the nuanced decision-making that UI development demands.\n\nNow developers and AI models share a common language for UI; both can reference the exact same visual elements with clarity, turning LLMs from guessing machines into powerful UI collaborators.\n\n**@Tagging:** In your prompts, you can either type @ and click on a section of your webpage to reference another element relative to the one you’re focused on OR you can type @/ to mention files and directories you want the LLM to have as context in your prompt.\n\n![uploaded image](/media/?type=post&id=95312&key=user_uploads/3082625/2b76e7e0-6efc-4bb5-8b16-86f1cffd6f08)\n\n**CSS Editor:** JSX Tool has a CSS editor that is nearly as feature-complete as the native CSS style editors found in browser element inspectors. Instead of applying your changes to a single element, you can see how your change to a line of JSX code would be applied globally.\n\n![uploaded image](/media/?type=post&id=95312&key=user_uploads/3082625/f911aeb0-3a85-4e30-9042-d49fd4a06d61)\n\n**LSP Integrations:** JSX Tool ships with a lightweight IDE for manually editing code, but still an IDE that does some heavy lifting. The JSX Tool IDE integrates in language servers for common React development tasks, so you can have things like type-checking, auto-complete, and linting upon save. We currently ship with LSPs for Typescript, Tailwind, ESLint, and Prettier.\n\n![uploaded image](/media/?type=post&id=95312&key=user_uploads/3082625/57a590b7-b2c0-41e1-90c3-336c839b7219)\n\nTo learn more or start using the extension, go to [jsxtool.com](https://jsxtool.com)!\n\n_Note: IDE features are currently in app review and will be available in our next release._\n\n**Team**\n\nJamie and Dan grew up in New York City and have been working on projects together for nearly 20 years. Before JSX Tool, we most recently built a mobile app for bypassing news site paywalls.\n\nJamie is a second-time YC founder. Prior to starting JSX Tool, he worked as a Software Engineer at YCombinator on their investor software. He previously co-founded Cheqout, a restaurant technology company that was a part of the YC W21 batch. Prior to his first startup, Jamie worked on Airbnb's China Risk Team.\n\nJamie has had a deep interest in higher-order and visual programming for a while. He previously built a version control system to diff and merge structured, non-textual assets. Many of the technical problems encountered in that project were very similar to those encountered in JSX Tool.\n\nDan worked most recently as a Senior Software Engineer at Everblue, where he led engineering teams building workflow applications to power US government systems. Prior to that, he worked as a Senior Cloud Engineer at Sela US. He got his start in tech in the world of React and has since returned to his roots. In a former life, he was a Chef at a James Beard award-winning restaurant.\n\n![uploaded image](/media/?type=post&id=95312&key=user_uploads/89898/dc4d88be-c544-45e6-9936-8dd8f08e80aa)\n\n",
        "url": "https://www.ycombinator.com/launches/OnI-jsx-tool-in-browser-react-ide",
        "votes": 53,
        "created_at": "2025-11-09T16:01:49.332Z"
      }
    ]
  },
  {
    "id": 31046,
    "name": "Linzumi",
    "slug": "linzumi",
    "former_names": [
      "[Placeholder] Sean Grove NewCo"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/5cfae971c0f6dc34ce7d88e4c9086b3ed9aa19e2.png",
    "website": "https://linzumi.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Linzumi is the chat your engineering team uses to direct dozens of AI coding agents.\r\n\r\nKick off work, review it, ship it. All from chat.\r\n\r\nSee every agent's work. Unblock the agents that need you from your laptop, your phone, the coffee line. Your teammates see it too.\r\n\r\nEvery decision your team makes compiles into a source of truth - what to build, why it changed, how your agents should act. That same source generates new work and verifies completed work.\r\n\r\nDeliberative alignment, repurposed from aligning LLMs to aligning companies.",
    "one_liner": "Team chat to command all your company's coding agents",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1781215175,
    "tags": [
      "Developer Tools",
      "Chat",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Spring 2026",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Partly Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/linzumi",
    "api": "https://devasheeshg.github.io/yc-api/batches/spring-2026/linzumi.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/linzumi",
    "x_url": "https://x.com/linzumi_ai",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/linzumi/",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/5cfae971c0f6dc34ce7d88e4c9086b3ed9aa19e2.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "Garry Tan",
      "url": "https://www.ycombinator.com/people/garry-tan"
    },
    "founders": [
      {
        "user_id": 19683,
        "full_name": "Sean Grove",
        "title": "Founder/CEO",
        "founder_bio": "Sean Grove builds systems that turn human intent into reliable software. At OpenAI he spent years in post‑training and alignment reasoning, helping develop model‑spec infrastructure and deliberative‑alignment techniques. He founded OneGraph (acquired by Netlify), was Principal Architect at Netlify, and now builds Linzumi.\n\nSean enjoys writing about himself in the third person. Sean hungry. Sean work hard.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/segrove/",
        "x_url": "https://x.com/sgrove",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/191f665e0d237b1ec833317705481175705c4b40.jpg"
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    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 103435,
        "title": "Linzumi: team chat for directing AI coding agents",
        "tagline": "Team chat for directing dozens of AI coding agents",
        "body": "# Hi everyone, I'm Sean, and I’m launching Linzumi today\n\n**Linzumi is the team chat your engineering team uses to direct dozens of AI coding agents at once.** Kick off work, review it, ship it: all from chat. Try it at <https://linzumi.com>.\n\n> For a limited time, every team chat account also gets free daily access to state of the art open-weights intelligence, GLM 5.2 at high speed, through our partnership with [Wafer.ai](http://Wafer.ai).\n\n<https://www.youtube.com/watch?v=EM53ACaIHyg>\n\n## The problem\n\nThe bottleneck in software has moved. Execution is basically free now: AI agents can write, test, and ship code 24/7. _The new constraint is human decisions and verification_. Whoever surfaces the right decision to the right person at the right moment unlocks 10x throughput. Whoever doesn't watches their agent fleet stall.\n\nIf you've ever tried to keep three coding agents productive at once, you know the feeling. You jump between PR tabs, miss approvals buried in Slack, and find one agent has sat idle for 20 minutes waiting on a one-line decision. It's a fascinating moment to be building software: vastly easier and vastly harder at the same time.\n\n![uploaded image](/media/?type=post&id=103435&key=user_uploads/19683/9019e12e-5088-4b41-9321-28a417dade5a)\n\n## How Linzumi works\n\nConnect your machine, kick off work in chat, and review what every agent is doing from your laptop, your phone, or the coffee line. Works with Codex today, Claude Code coming soon. Your teammates see it all too: agent work is no longer buried in invisible terminals.\n\n<https://www.youtube.com/watch?v=AQP5tQGZ9Jc>\n\nBut the real unlock is underneath. As your team works, Linzumi keeps every decision close to the work itself: what to build, why it changed, who approved it, and what the agents should do next. The decision inbox surfaces only the calls that need a human, so instead of reconstructing context from terminals, PRs, chats, and memory, your team has one shared place to steer the whole fleet.\n\n_Continuous Context Compilation_\n\n<https://www.youtube.com/watch?v=TNJbWKYiDyc>\n\n## Backstory\n\nI'm a 3x YC founder. Before Linzumi I was at OpenAI on post-training and alignment research, where I worked on systems for making models follow written specs and produce more reliable reasoning. Working with coding agents on my own projects showed me the same kind of coordination problem at the team level: the agents could execute, but the bottleneck was deciding what should happen next and checking whether the result matched intent.\n\nThe mission now is to make everyone the CEO of their own 1,000-agent company: able to direct more work, make better decisions, and become the best version of themselves as a builder.\n\nWhen you combine that shared context with calibrated decisions, even the smallest form factor can do surprising amounts of work, like shipping a customer feature from your phone on the way to the meeting.\n\n_Hands-free work_\n\n<https://www.youtube.com/watch?v=pmqf3kwuOqI>\n\n## What we're asking for\n\nIf you run AI coding agents (or want to), try Linzumi at <https://linzumi.com>. It's free to get started and we'd love your feedback.\n\nWe're especially looking for:\n\n• Engineering teams running multiple coding agents who want to scale to dozens (honestly, thousands by end of year)\n\n• Founders who feel like the bottleneck in their own dev cycle\n\n• Anyone curious about better human-agent coordination for company-scale work\n\nDM me on X (@sgrove) or email [sean@linzumi.com](mailto:sean@linzumi.com). I read every reply.",
        "url": "https://www.ycombinator.com/launches/QuJ-linzumi-team-chat-for-directing-ai-coding-agents",
        "votes": 25,
        "created_at": "2026-06-23T16:43:17.655Z"
      }
    ]
  },
  {
    "id": 31057,
    "name": "Valgo",
    "slug": "valgo",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6c34fbe5d783459ff37f7c664b24ff15cf5e7843.png",
    "website": "https://valgo.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Insurers struggle to price autonomous systems because the historical data simply doesn't exist. Your car insurance draws from over 30 billion claims records, but autonomous trucks and robots have nearly zero. Valgo is the risk quantification platform that closes that gap. We are building probabilistic models of routes, tasks, and environments from the bottom up. We output a simulated loss estimate that insurers need to price coverage. Valgo is the foundational layer that gives insurance providers confidence to properly price autonomy risk.\r\n\r\nOur team combines expertise in risk estimation for autonomy with deep experience in the insurance industry. Sydney and Robert are Stanford PhDs with leading expertise in safety of physical AI systems. Sydney wrote the textbook on validating safety-critical systems and teaches the course at Stanford. Robert spent 7 years at MIT Lincoln Laboratory on the core team that designed and validated an FAA-certified aircraft collision avoidance system, now a worldwide standard. Jon is a Sloan Fellow from the Stanford GSB and an actuary who spent over 12 years in insurance leadership and led over $5 billion in M&A as head of corporate development for one of the largest insurers in Asia-Pacific.",
    "one_liner": "Insurance risk layer for physical AI",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1763584142,
    "tags": [],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2026",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/valgo",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/valgo.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/valgorithmic",
    "x_url": "http://x.com/valgorithmicinc",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/6c34fbe5d783459ff37f7c664b24ff15cf5e7843.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [
      "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/40cd37dfa9a6ac03a5a2859a89fb37afa73e8a9d.png"
    ],
    "primary_partner": {
      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
    },
    "founders": [
      {
        "user_id": 3135423,
        "full_name": "Robert Moss",
        "title": "Co-Founder",
        "founder_bio": "Stanford CS PhD with thesis on algorithms to validate safety-critical systems. Former research staff at MIT Lincoln Laboratory on the core team that designed and validated the aircraft collision avoidance system (ACAS X), now a worldwide standard. Other relevant experience working at Xwing (an autonomous aircraft startup now part of Joby Aviation), and NASA Ames Research Center.\n\n",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/robert-j-moss",
        "x_url": "http://x.com/mossrj",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9605b91100758c2571fc6440abbd53f466fd2bed.jpg"
      },
      {
        "user_id": 3152351,
        "full_name": "Sydney Katz",
        "title": "Founder/Technology",
        "founder_bio": "Stanford Aero/Astro PhD with thesis on safe machine learning. Author of \"Algorithms for Validation\" textbook. Lecturer for \"Validation of Safety-Critical Systems\" course at Stanford. Industry experience at Reliable Robotics, MIT Lincoln Laboratory, Johns Hopkins Applied Physics Laboratory, and NASA.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/smkatz/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d6dd238264acb2b3b6e034f6d17a8588547dffdb.jpg"
      },
      {
        "user_id": 3484361,
        "full_name": "Jon Qian",
        "title": "Founder/President",
        "founder_bio": "Stanford GSB Sloan Fellow.\n12+ years in leadership positions for one of the largest insurer in Asia-Pacific.\nResponsible for over $5 billion in insurance company mergers and acquisitions.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jon-qian-82b63046/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3bfb51bc84982e803b6d46c8e1c8f28f5bb58847.jpg"
      }
    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 98558,
        "title": "Valgo — Risk quantification for insurance of physical AI",
        "tagline": "The risk quantification platform that insurers need to price the autonomous future.",
        "body": "_TL;DR — Valgo is the risk quantification layer for insurance of physical AI. Since historical claims data doesn’t exist for autonomy, we turn simulations into loss estimates that insurers need to price coverage._\n\n<https://youtu.be/td2uzvldFPY>\n\nInsurers face challenges pricing physical AI systems because the historical data simply doesn't exist. Your car insurance draws from over 30 billion claims records, but autonomous trucks and robots have nearly zero. Valgo is the risk quantification platform that closes that gap. We are building probabilistic models of routes, tasks, and environments from the bottom up. We output simulated loss estimates that insurers need to price coverage. **Valgo is the foundational layer that gives insurance providers confidence to properly price autonomy risk.**\n\n**Team.** Our team combines expertise in risk estimation for autonomy with deep experience in the insurance industry. [Sydney](https://www.linkedin.com/in/smkatz/) and [Robert](https://www.linkedin.com/in/robert-j-moss/) are Stanford PhDs who wrote the [textbook](https://algorithmsbook.com/validation) on validating safety-critical systems and teach the [course](https://youtube.com/playlist?list=PLoROMvodv4rOq1LMLI8U7djzDb8--xpaC&si=G0EqPyi8SMDcQO3Q) at Stanford. Robert spent 7 years at MIT Lincoln Laboratory on the core team that designed and validated an FAA-certified aircraft collision avoidance system, now a worldwide standard. [Jon](https://www.linkedin.com/in/jon-qian-82b63046/) is a Sloan Fellow from the Stanford GSB who spent over 12 years in insurance leadership and led over $5 billion in M&A as head of corporate development for one of the largest insurers in Asia-Pacific.\n\n**Our Ask.** We would love to talk with you if:\n\n* you work at a robotics and autonomy company\n* you work with insurance brokers, agents, insurers, and reinsurers\n* you know talented individuals in robotics systems, safety validation, and insurance\n\nContact us at [founders@valgo.ai](mailto:founders@valgo.ai)\n\n![uploaded image](/media/?type=post&id=98558&key=user_uploads/3135423/bf14aade-05d8-4b09-ba35-a9ec543171c3)\n\n",
        "url": "https://www.ycombinator.com/launches/Pde-valgo-risk-quantification-for-insurance-of-physical-ai",
        "votes": 17,
        "created_at": "2026-03-06T22:40:59.899Z"
      }
    ]
  },
  {
    "id": 31096,
    "name": "shortkit",
    "slug": "shortkit",
    "former_names": [
      "Embassi"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cd6943aa08a6062cd8e0e6aba456f3d77558d5e3.png",
    "website": "https://www.shortkit.dev",
    "all_locations": "",
    "long_description": "ShortKit lets any consumer app launch a TikTok-grade media expereinces. \r\n\r\nMichael, spent 6 years at YouTube building the infrastructure that powers YouTube Shorts. Neil, prev. scaled a SaaS company from 0 to $6M ARR as employee #1. \r\n\r\nWe handle the full media stack, starting with short form video - client SDKs, video infrastructure, rec systems, and monetization - so product teams don't have to.",
    "one_liner": "Media infra for consumer apps",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1771985375,
    "tags": [],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Winter 2026",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "Unspecified"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/shortkit",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/shortkit.json",
    "year_founded": 2026,
    "city": null,
    "country": null,
    "linkedin_url": "https://www.linkedin.com/company/shortkit/",
    "x_url": "",
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    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/cd6943aa08a6062cd8e0e6aba456f3d77558d5e3.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [
      "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/b8abf8b07e5c5b5f722d6ee1878e72041216f8fc.png"
    ],
    "primary_partner": {
      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
    },
    "founders": [
      {
        "user_id": 1590155,
        "full_name": "Neil Bhammar",
        "title": "Founder/CEO",
        "founder_bio": "Making it really easy to deploy and scale best-in-class video experiences. \n\nI previously built a transportation technology company from 0 through our Series B.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/neilbhammar/",
        "x_url": "https://x.com/neilbhammar",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/22367adf021bb12107b2e6ad23f6a9aada9b6cc6.jpg"
      },
      {
        "user_id": 2541340,
        "full_name": "Michael Seleman",
        "title": "Founder/CTO",
        "founder_bio": "Making enterprise short-form video systems simple. Prev. Spent 6 years building infrastructure that powers YouTube Shorts.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/michael-seleman-541509122/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4c9ae77035400a0d09b11ff261937c10fda232b5.jpg"
      }
    ],
    "jobs": [
      {
        "id": 113204,
        "title": "Full-Stack Engineer",
        "url": "https://www.ycombinator.com/companies/shortkit/jobs/FdAm5KK-full-stack-engineer",
        "location": "Remote (US)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$120K - $250K",
        "equity_range": "0.50% - 2.50%",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Google Cloud",
          "Kotlin",
          "PostgreSQL",
          "Python",
          "React",
          "React Native",
          "Redis",
          "Swift",
          "TypeScript",
          "Flutter",
          "Next.js",
          "FastAPI"
        ]
      }
    ],
    "news": [],
    "launches": [
      {
        "id": 98172,
        "title": "ShortKit – The SDK for Short Form Video Feeds",
        "tagline": "We help every app roll their own TikTok-quality video feed.",
        "body": "**tl;dr** ShortKit lets consumer teams and publishers ship best-in-class vertical video feeds _(playback, infra, monetization, rec systems, content networks, and more)_ without needing their own video eng orgs. [Michael Seleman](https://linkedin.com/in/michael-seleman-541509122) spent years at YouTube building the infrastructure behind Shorts. Now, we're packaging that for everyone else.\n\n**Short-form video is eating the world**\n\nVertical video is the most retentive format on the internet (with the highest ad spend), but it's captive on the three major platforms. The best publishers and consumer companies want to participate (see [Glassdoor](https://techcrunch.com/2024/10/09/glassdoor-takes-a-leaf-out-of-linkedins-book-launches-short-videos-polls-and-images/), [DoorDash](https://techcrunch.com/2025/09/30/doordash-rolls-out-creator-program-for-short-form-videos-adds-new-app-features-and-dine-in-rewards/), and [CNN](https://www.theverge.com/news/816638/cnn-app-shorts-feed-videos-launch)’s recent feed launches). Companies are desperate to own first-party data, engage their users more deeply, and drive ad revenue within their own experiences.\n\n**But it's still really hard at scale**\n\nTeams today either spend millions to ship quality short-form feeds, roll out poor-quality ones that fail to retain, or don't ship them at all because they don't know where to start. It's a massive missed opportunity for consumer companies, and an existential one for companies built on attention, like news-media.\n\n**So we're making it really easy**\n\nShortKit is a drop-in short-form video system. Product teams get:\n\n* **Managed SDKs** that deliver best-in-class short-form feeds. We've obsessed over the mechanics that make these competitive with the major platforms - ML driven buffer management, feed aware player mechanics, buttery-smooth tactiles, and much more.\n* **Video infrastructure** they never have to think about. Powering global video distribution that always works, optimized specifically for short-form content.\n* **Monetization** like native ads & first party data collection.\n* **Rec systems** with baseline configurations and ML-driven feed ranking algos.\n* **Admin tools** and APIs to manage feeds, integrate your CMS/database, and view analytics.\n\n**Our ask:**\n\nIf you know product or growth leaders at:\n\n* Media companies - NYT, ESPN, TMZ, Condé Nast, etc.\n* Consumer companies - TripAdvisor, Ticketmaster, Zillow, Yelp, etc.\n\nWe'd love to talk to them. You can reach out at [neil@shortkit.dev](mailto:neil@shortkit.dev) or book time with us at [shortkit.dev](http://shortkit.dev).\n\n<https://youtu.be/_W2qBGRnBaM>",
        "url": "https://www.ycombinator.com/launches/PXQ-shortkit-the-sdk-for-short-form-video-feeds",
        "votes": 20,
        "created_at": "2026-02-26T08:03:51.086Z"
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    "id": 31097,
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "REV1 is Claude code for mechanical engineers, starting with automating the process of turning 3D designs into 2D manufacturing drawings – which is more than 25% of all of what a mechanical engineer does - our software does it in minutes. \r\nCompressing hours of work into minutes while delivering consistent, higher quality results.",
    "one_liner": "Claude Code for Mechanical Engineers",
    "team_size": 2,
    "industry": "B2B",
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      "name": "Gustaf Alstromer",
      "url": "https://www.ycombinator.com/people/gustaf-alstromer"
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      {
        "user_id": 2150068,
        "full_name": "Alex Rivero",
        "title": "Founder/CEO",
        "founder_bio": "CEO of REV1 (W26) | Former Mechanical Engineer at Apple and Tesla\nBuilding AI for mechanical engineers, starting with engineering drawings",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/alex-rivero-sabiote",
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      {
        "user_id": 1691893,
        "full_name": "Louis Liu",
        "title": "Founder/CTO",
        "founder_bio": "Building AI for mechanical engineers, starting with engineering drawings",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/sp-louis-liu/",
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      {
        "id": 97401,
        "title": "REV1 - Automating engineering drawings for Mechanical Engineers",
        "tagline": "It's time for Mechanical Engineers to automate their workflows",
        "body": "**TL;DR:** REV1 turns 3D CAD models into manufacturing-ready 2D drawings in minutes instead of hours.\n\n[**https://youtu.be/rlGxyHiPOW4**](https://youtu.be/rlGxyHiPOW4)\n\n**The Problem:**\n\nEvery manufactured part – whether it's for aerospace, robotics, medical devices, or consumer electronics – needs a 2D engineering drawing that defines the manufacturing specs to ensure the part functions as designed. Mechanical engineers spend **over 25% of their time** creating these drawings manually. It's tedious, error-prone, and unavoidable. It's also deeply technical – the standard that governs tolerancing is **over 300 pages of rules**.\n\nThe real cost isn't just time – it's innovation. Engineers should be designing the next iteration and solving hard problems, not manually specifying tolerances.\n\n**Our Solution:**\n\nREV1 automates drawing creation. Start with a 3D CAD file, specify your design intent, and we generate a fully annotated drawing with proper GD&T. Review and edit in our native interface before sending to manufacturers. All that while staying synced with your source files in your PLM system.\n\n**Communicate your design intent in 3D:**\n\n![uploaded image](/media/?type=post&id=97401&key=user_uploads/2150068/bd8b20b4-1f27-48fa-8c11-9d4c803c4a63)\n\n**Drawing generation in minutes instead of hours:**\n\n![uploaded image](/media/?type=post&id=97401&key=user_uploads/2150068/d425df48-2074-4e7e-a29f-8515dd864f62)\n\n**Who are we**\n\n* **Alex** – Mechanical engineer who shipped products at scale at Tesla and Apple (worked on Cybertruck, Robotaxi and iPhone 17 lineup). Lived this problem for years.\n* **Louis** – Software engineer; solo built Tesla's global Supercharger & Robotaxi planning platform. Studied mechanical engineering in school; published ML researcher\n\n**Who it's for**\n\nMechanical engineering teams at hardware companies – especially those designing parts that need detailed manufacturing specs. Think robotics, aerospace, automotive, medical devices, and consumer electronics.\n\n**Our ask**\n\n* Intros to mechanical engineering leads or hardware founders who feel this pain\n* If you're an ME, we'd love your feedback on the product\n* Spread the word to anyone building physical products",
        "url": "https://www.ycombinator.com/launches/PKz-rev1-automating-engineering-drawings-for-mechanical-engineers",
        "votes": 15,
        "created_at": "2026-02-02T17:24:31.586Z"
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    "id": 31100,
    "name": "Sentrial",
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    "website": "https://sentrial.com/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Sentrial is the monitoring platform for AI products in production. \r\n\r\nWhen your AI product/agent loops indefinitely, hallucinates, or frustrates users, Sentrial detects it in real-time, diagnoses the root cause, and recommends specific fixes. We provide the monitoring, evaluation, and debugging infrastructure that traditional tools weren't built for, so teams iterate based on production reality, not just offline evals.",
    "one_liner": "Datadog for Agent Reliability",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1770083112,
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    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/sentrial",
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      "name": "Ankit Gupta",
      "url": "https://www.ycombinator.com/people/ankit-gupta"
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    "founders": [
      {
        "user_id": 3199067,
        "full_name": "Neel Sharma",
        "title": "Founder/CEO",
        "founder_bio": "Neel is the founder of Sentrial - production monitoring for AI products. \n\nHe studied Computer Science at UC Berkeley and worked on agentic optimization at Sense. He saw firsthand that traditional evaluation frameworks break down once agents hit production. That insight led to the creation of Sentrial, a platform built to monitor, evaluate, and improve agent performance in real-world, production environments.\n\ncontact: neel@sentrial.com",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/neelshar",
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      {
        "id": 97540,
        "title": "Sentrial: Production Monitoring for AI Agent Behavior",
        "tagline": "Sentrial helps engineering teams detect, diagnose, and fix AI agent issues in production.",
        "body": "Hi all! [Neel](http://linkedin.com/in/neelshar) and [Anay](https://www.linkedin.com/in/anayrshukla/) here - we’re building **Sentrial**, production monitoring for AI agent behavior.\n\n**TL;DR:** [Sentrial](https://sentrial.com) semantically detects when agents loop, hallucinate, misuse tools, or frustrate users in production, then helps engineering teams diagnose the root cause and fix it fast.\n\n[Sentrial Launch Video](https://www.youtube.com/watch?v=fiRRBG9NIE4)\n\n## The problem\n\nAI agents are becoming core infrastructure - handling customer support, automating workflows, and making decisions on behalf of users. But when something goes wrong, teams are flying blind. Traditional monitoring catches errors and latency, not failures like hallucinations or user frustration. No alert fires when an agent goes off the rails, and agents that were meant to scale operations end up requiring constant oversight.\n\n## What Sentrial does\n\nSentrial gives engineering teams real-time visibility into how their agents actually behave in production. We automatically detect failure patterns: loops, hallucinations, tool misuse, and user frustrations the moment they happen. When issues surface, Sentrial diagnoses the root cause by analyzing conversation patterns, model outputs, and tool interactions, then recommends specific fixes.\n\n## Ask\n\nIf your internal or customer-facing agents are looping, hallucinating, or frustrating users in production and it’s hard to diagnose, we’d love to talk. Email [neel@sentrial.com](mailto:neel@sentrial.com) or book a call [here](https://cal.com/neel-sharma) to learn more!\n\n## Team\n\n**Neel:** CS @ UC Berkeley, worked on Agentic Optimization at Sense.\\\n**Anay:** CS @ UC Berkeley, deployed DevOps agents at Accenture.\n\n![uploaded image](/media/?type=post&id=97540&key=user_uploads/3199067/0481c129-5b98-4e2b-91bf-42b10678ffac)\n\n",
        "url": "https://www.ycombinator.com/launches/PNE-sentrial-production-monitoring-for-ai-agent-behavior",
        "votes": 27,
        "created_at": "2026-02-05T18:35:42.482Z"
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    "id": 31123,
    "name": "21st",
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    "one_liner": "UI building blocks for the agentic internet",
    "team_size": 3,
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      "Partly Remote"
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    "url": "https://www.ycombinator.com/companies/21st",
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    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/21st-dev/",
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      "name": "Ankit Gupta",
      "url": "https://www.ycombinator.com/people/ankit-gupta"
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        "user_id": 736150,
        "full_name": "Serafim Korablev",
        "title": "Founder/CEO",
        "founder_bio": "One of the first full-time vibe-coders (since October 2023).  \n\nCo-founder of 21st.dev, a UI components registry with over 1m users.  \n\nPreviously co-founded Rork.com (then a web app builder for Next.js), the first Telegram-native memecoin launchpad (multi-million exit), and Via, a cross-chain crypto routing protocol with $1.5B GTV backed by Naval, Safe, Sandeep, and others.  \n\nPassionate about design and basketball.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/serafimkorablev",
        "x_url": "https://x.com/serafimcloud",
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      {
        "user_id": 564249,
        "full_name": "Sergey Bunas",
        "title": "co-founder",
        "founder_bio": "CS dropout. Senior Software Engineer at Deel (W19). Built Perplexity before Perplexity (Suggesty, 2022 — #1 Product Hunt, featured in Google's internal newsletter). Solo-built a Figma competitor pre-AI (Stage, 10K users). Cambridge AI hackathon winner (solo)",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/s-bunas/",
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      {
        "id": 98841,
        "title": "21st - Infrastructure for AI agents",
        "tagline": "The production layer for shipping frontier AI agents inside your product - sandboxing, streaming, billing, UI, and observability out of the box.",
        "body": "**tl;dr:** We make it stupid easy to deploy frontier AI agents (Claude Code, Codex, others) inside your product. Define your agent in TypeScript, deploy with one command, ship it to your users.\n\n<https://youtu.be/1WcdHbyik18>\n\n### How we got here\n\nLast year we built [21st.dev](http://21st.dev) - a React component registry that 1.4M developers use to build UI for AI apps.\n\nWe also built our own AI agents from scratch to power the product. All custom. 15,000+ GitHub stars.\n\nThen Claude Code arrived. We rewrote our agents on top of it - and they got better overnight than in months of our own work. That was a humbling moment.\n\nBut here's the thing - getting Claude Code into production was brutal. These agents aren't API calls. They're runtimes. They rely on bash, filesystem, persistent sandboxes. So you can't just run them on Vercel (timeouts, no fs). Then the questions start piling up. How do you sandbox securely? How do you make sure your env vars aren't stolen from the sandbox? How do you handle streaming? Billing? Observability? You end up building way more infrastructure than you planned for.\n\nWe spent 2 months deep in these problems. And then we realized - every team building on frontier agent SDKs is facing the exact same wall we just climbed over.\n\nSo we turned our infrastructure into a product.\n\n### 21st Agents SDK\n\nThe agent SDKs give you the brain. We give you everything else.\n\nWhat you get out of the box:\n\n* Sandboxed code execution (powered by E2B) - secure, persistent\n* Credential security - proxy layer so your keys never touch the sandbox\n* SSE streaming, compatible with AI SDK\n* Crafted agent chat UI with themes\n* Usage limits & billing\n* Observability\n\nHow it works: you define your agent in code - custom tools, hooks like onFinish, sandbox configuration (which files, which CLI tools, which tokens). Then you deploy with our CLI. And you have a hosted agent you can manage via API. It's AI SDK compatible so you can just plug and play on the client side.\n\nSDK supports React, Next.js, Node, and Python.\n\n### Why this matters now\n\nThe best agents aren't being built from scratch anymore. They're being built on top of frontier agent runtimes from Anthropic, OpenAI, and others. But shipping them to real users? That's still a mess. The gap between \"agent works on my machine\" and \"agent works for my customers\" is enormous.\n\nWe already closed that gap for ourselves. Now we're the infra layer so you don't have to.\n\n### Try it\n\n<https://21st.dev/agents>\n\nIf you're building with frontier AI agents and hitting production walls - we want to hear about it. DM us on X (@serafimcloud, @sergeybunas) or email [founders@21st.dev](mailto:founders@21st.dev)\n\n---",
        "url": "https://www.ycombinator.com/launches/PiD-21st-infrastructure-for-ai-agents",
        "votes": 19,
        "created_at": "2026-03-16T08:16:04.714Z"
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    "id": 31131,
    "name": "Zatanna",
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "Zatanna creates APIs for software that doesn't have any, by reverse engineering back ends of web-based cloud and on-prem software. ",
    "one_liner": "Turning all software into agent-first APIs",
    "team_size": 2,
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    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
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      "name": "Jared Friedman",
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        "user_id": 1805672,
        "full_name": "Tarun Vedula",
        "title": "Founder/CEO",
        "founder_bio": "CEO @ zatanna | uw madison ",
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        "linkedin_url": "https://www.linkedin.com/in/tarunvedula/",
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        "user_id": 2956000,
        "full_name": "Alex Blackwell",
        "title": "Founder/CTO",
        "founder_bio": "CTO @ Zatanna (w26). Prev at Pikkit bypassing anti-bots",
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        "id": 98664,
        "title": "Zatanna | APIs for AI agents",
        "tagline": "Zatanna creates faster, cheaper, and more reliable APIs for AI agents",
        "body": "Hey YC!\n\nWe’re [Rithvik](https://www.linkedin.com/in/rithvik-vanga-0824a5225/), [Alex](https://www.linkedin.com/in/alex-blackwell-506228206/), and [Tarun](https://www.linkedin.com/in/tarunvedula/), the team behind [Zatanna](https://www.linkedin.com/company/usezatanna/).\n\n**TL;DR:** Today, most AI companies rely on slow, brittle, and unreliable computer-use agents to interact with software that has no API.  Zatanna solves this with faster, cheaper, and more reliable APIs for AI agents by reverse engineering requests and taking care of antibot infrastructure. \n\n[Video Link](https://www.youtube.com/watch?v=HUCOKVn-atM)\n\n**The Problem:**\n\nA huge amount of valuable business software still has no usable API. So when AI companies need their agents to interact with ERPs, PMS systems, portals, marketplaces, or other operational websites, they often fall back to browser automation.\n\nThat means the agent is stuck looking at screens, clicking buttons, waiting for pages to load, dealing with logins, handling UI changes, and breaking every time the workflow shifts. It is fine for showing that something is possible. It is terrible when the workflow actually matters.\n\nTeams end up spending an absurd amount of engineering time maintaining brittle browser automations instead of building product and serving customers.\n\n**The Solution:**\n\nZatanna runs these workflows at the request layer.\n\nWe observe how a workflow works once, reconstruct the underlying request sequence, and host it as a clean API that any agent can call. Instead of navigating a browser, the agent just hits an endpoint.\n\nThat makes the workflow:\n\n* faster\n* cheaper\n* more reliable\n* much easier to maintain at scale\n\nWe also handle the painful infrastructure required to keep these workflows alive in production:\n\n* session and credential management\n* request sequencing\n* proxy networks and traffic distribution\n* retries, monitoring, and recovery\n\nToday we’re already supporting customers where either throughput or reliability is mission-critical, from high-volume consumer platforms to operationally sensitive industries like logistics.\n\n**Where we’re seeing this most:**\n\n* ERPs like SAP\n* PMS / POS systems\n* insurance/benefits/claims portals\n* marketplaces(checkout flows)\n* operational websites with no APIs\n* basically anywhere the current solution is scraping or browser automation\n\n**Why we’re doing this:**\n\nWe started in vertical AI and ran into this problem ourselves. The model layer kept getting easier. Software access was the real bottleneck. A huge amount of engineering effort went into keeping integrations alive instead of improving the actual agent.\n\nSo we decided to build the thing we wished we had.\n\n**What we’re looking for:**\n\nIf you’re building something that depends on browser automation or computer-use agents for integrations, especially where reliability, speed, or cost matter, we’d love to take a look at the workflow.\n\nBook a call [here](https://zatanna.cal.com/tarun/30min?user=tarun&overlayCalendar=true) or email [**tarun@zatanna.ai**](mailto:tarun@zatanna.ai)",
        "url": "https://www.ycombinator.com/launches/PfM-zatanna-apis-for-ai-agents",
        "votes": 11,
        "created_at": "2026-03-10T17:01:30.330Z"
      }
    ]
  },
  {
    "id": 31133,
    "name": "Skillsync",
    "slug": "skillsync",
    "former_names": [],
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    "website": "https://skillsync.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Skillsync gives you one place for everything your agents have ever done, and makes all of it portable. Move a full session between Claude Code, Cursor, Codex, and any other agent with nothing lost, including the entire conversation, the model's reasoning, and every tool call, not just a summary, so the next agent picks up like it was there the whole time. Because your sessions are portable, they stack up instead of disappearing. Every past session stays searchable and feeds your next agent automatically, so you never re-explain yourself or redo work you have already done. Everything stays on your machine and nothing leaves unless you choose to send it. Skillsync is local-first and yours, and its core engine, txcript, is open source, a portable session format that no single provider owns.",
    "one_liner": "Notion for AI chats",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1765356952,
    "tags": [
      "Developer Tools"
    ],
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2026",
    "status": "Active",
    "industries": [
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    "regions": [
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      "America / Canada"
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    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/skillsync",
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    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
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    "primary_partner": {
      "name": "Tyler Bosmeny",
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    "founders": [
      {
        "user_id": 2980881,
        "full_name": "Narayana Aaditya Ganeshkumar",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder & CEO of Skillsync. I helped take an open-source Rust project from zero to 30k+ GitHub stars and saw firsthand how many world-class engineers are hiding in the long tail of open source. My background is at the intersection of engineering, product, and organizational psychology. Software is a team sport and I'm building Skillsync to bring the best out of engineering teams!",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/narayanaaaditya/",
        "x_url": "https://x.com/narsagna",
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      {
        "user_id": 3203680,
        "full_name": "Nishant Joshi",
        "title": "Founder/CTO",
        "founder_bio": "Co-Founder CTO @ SkillSync Inc. | Top 1% Rust dev. Went from building type-safe payment infra to people search. Now fixing how companies find engineers like me.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/nishantjosh",
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    "launches": [
      {
        "id": 112177,
        "title": "Skillsync: Move your context across every coding agent",
        "tagline": "Meet Skillsync, your context made portable across Claude Code, Cursor, Codex, and every agent you use.",
        "body": "👋 We're Nars and Nishant, founders of Skillsync (W26).\n\n**TL;DR:** Skillsync lets you move your context (sessions, memory, and skills) across every coding agent you use, with nothing lost. Start in Claude Code, continue in Codex, sync it with your team. Say it once; every agent &amp; teammate has it.\n\n![uploaded image](/media/?type=post&id=112177&key=user_uploads/2980881/daf33474-9f03-4b30-ae87-d2d5de4efb88)\n\nAI chats are annoying. Your context is trapped inside whatever agent you're using. You plan everything out in the Claude app, then open Claude Code to build, and none of that thinking comes with you. Switch from Claude Code to Cursor or Codex and it's the same story: you start from zero, re-explaining everything. And sharing your best skills with your team means zip files and Slack messages nobody can find.\n\nSkillsync is a **local-first desktop app** that frees your context from any single agent:\n\n* 🔁 **Move a session between agents with nothing lost**, including the full conversation, reasoning, and tool history.\n* 🧠 **KYC: Know Your Context.** Keep your skills and memory in one place, searchable from any agent via MCP.\n* 👥 **Sync your skills across your team**, edit once and everyone stays current. No zip files, no stale copies.\n\nEverything runs on your machine, so your context stays yours.\n\nWe spent years building open source payments infra that connected dozens of payment processors, and scaled it to 30k+ GitHub stars. Making all those systems talk to each other taught us what real interoperability takes.\n\n**One more thing…** \n\nThe hard part, the engine that translates sessions across different agent formats without losing anything, is **open source**. It's written in Rust and it's called **txcript:** <https://github.com/skillsynchq/txcript/>. Don't take our word for it: **read the code**.\n\nWe're on a mission to set your context free. If this resonates, try Skillsync at <https://skillsync.com>\n\nYou can also reach us at [founders@skillsync.com](mailto:founders@skillsync.com)\n\n![uploaded image](/media/?type=post&id=112177&key=user_uploads/2980881/15b075ff-755b-4bcc-8040-f3a9d58744ec)\n\n",
        "url": "https://www.ycombinator.com/launches/TBJ-skillsync-move-your-context-across-every-coding-agent",
        "votes": 7,
        "created_at": "2026-08-25T17:29:16.975Z"
      }
    ]
  },
  {
    "id": 31151,
    "name": "Sparkles",
    "slug": "sparkles",
    "former_names": [
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      "Flics"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2fa726d414c3f4d378fa6af116bb14e3abb29e0f.png",
    "website": "https://sparkles.dev",
    "all_locations": "London, England, United Kingdom",
    "long_description": "Sparkles is like Lovable for existing projects, so even Sharon from Marketing can change the button styling on the front page without going back and forth with the dev team.\r\n\r\nSomeone technical connects their GitHub to Sparkles, sets up the repository and environment variables, and then anyone on the team with a @yourcompany.com email can log in on Sparkles and create pull requests without needing to know what Git is.",
    "one_liner": "Make everyone on your team an engineer",
    "team_size": 1,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1768436882,
    "tags": [],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Winter 2026",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United Kingdom",
      "Europe"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/sparkles",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/sparkles.json",
    "year_founded": 2025,
    "city": "London",
    "country": "GB",
    "linkedin_url": "https://www.linkedin.com/company/sparkles-dev",
    "x_url": "https://x.com/Sparklesdotdev",
    "fb_url": null,
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    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/2fa726d414c3f4d378fa6af116bb14e3abb29e0f.png",
    "app_video_url": null,
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    "company_photos": [],
    "primary_partner": {
      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
    },
    "founders": [
      {
        "user_id": 2590397,
        "full_name": "Ai Daniil Bekirov",
        "title": "Founder/CEO",
        "founder_bio": "20 | 🇺🇦\n\nI dropped out of University College London to build Sparkles (W26).\n\nPreviously worked at Iterate.com (founded by Jonas who was previously the co-founder and CTO of Monzo. Backed by OpenAI, Index etc.) and StructuredAI (F25)",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/aidaniilbekirov/",
        "x_url": "https://x.com/aidaniil",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f07af39014457a4d2ff63358c4e3ccd33c6c034a.jpg"
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    ],
    "jobs": [
      {
        "id": 107152,
        "title": "Founding Engineer (London)",
        "url": "https://www.ycombinator.com/companies/sparkles/jobs/ttwqpbX-founding-engineer-london",
        "location": "London, England, GB / San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "£100K - £150K GBP",
        "equity_range": "1.00% - 2.00%",
        "experience": "Any (new grads ok)",
        "visa": "Will sponsor",
        "skills": [
          "TypeScript"
        ]
      },
      {
        "id": 107153,
        "title": "Founding GTM (London)",
        "url": "https://www.ycombinator.com/companies/sparkles/jobs/vDlglwX-founding-gtm-london",
        "location": "London, England, GB / San Francisco, CA, US",
        "type": "Full-time",
        "role": "Marketing",
        "role_type": null,
        "salary_range": "£70K - £100K GBP",
        "equity_range": "0.50% - 0.70%",
        "experience": "Any (new grads ok)",
        "visa": "Will sponsor",
        "skills": []
      }
    ],
    "news": [],
    "launches": [
      {
        "id": 97488,
        "title": "Sparkles - Lovable for existing projects",
        "tagline": "Make everyone on your team an engineer ✨",
        "body": "Hey, I’m **Dan** - Founder of **Sparkles (W26)**\n\n![uploaded image](/media/?type=post&id=97488&key=user_uploads/2590397/2522ae4d-df6f-4327-bdf4-03a05bc9493b)\n\n**Sparkles is like Lovable for existing projects**, so even your hypothetical Sharon from Operations can change the button styling on the front page without going back and forth with the dev team.\n\n[Sparkles launch video](https://youtu.be/v6u7wlGYPIU)\n\n**The problem**\n\nIf you’ve ever tried onboarding a non-technical person onto Claude Code / Cursor / Codex, you’ve definitely heard at least one of these:\n\n* “I think I pushed the `.env` to GitHub… is that bad?”\n* “Terminal is asking for my password but nothing is showing—my keyboard broke.”\n* “It tells me to run `git push --force`… is that like a Star Wars thing ?”\n* “Do I run `npm install` every time I open the laptop?”\n\nThis is what happens when a non technical person interacts with the CLI and dev server. It is a non user friendly environment that takes time to learn.\n\n**The Solution**\n\n![uploaded image](/media/?type=post&id=97488&key=user_uploads/2590397/943d834c-9a37-4152-b3ec-3c015f87bb9f)\n\nSparkles is a web platform that fully abstracts from local development. Your GTM/Designer/Marketing team don’t need to know what is git, what is a cli, what is a dev server etc. They will see a lovable-like UI with the preview and the chatbox, so they can ship the updates as fast as they can type ✨\n\nWhen someone makes a change on Sparkles they have an option to “upload” the changes, which essentially creates a Github PR for your engineer to review.\n\nWe are working on Enterprise level rulesets for PR creation, commit batching etc, so you don’t have to review thousands of PRs if you have a bigger team.\n\n**The Team**\n\n* Ai Daniil Bekirov - CEO\n\n  Legally AI. UCL dropout. Prev @ [iterate.com](http://iterate.com), StructuredAI (F25)\n\n**The ask**\n\nIf you want to cut down your backlog, or have non engineers who want to use cutting edge AI tools without the _steep_ learning curve, we’d love to talk. Intros to VPs of Operations, Marketing and Sales are appreciated 🙏\n\n**Email:** [dan@sparkles.dev](mailto:dan@sparkles.dev)\n\n![uploaded image](/media/?type=post&id=97488&key=user_uploads/2590397/84685a34-3e29-4220-a0d6-474197cc61ff)\n\n",
        "url": "https://www.ycombinator.com/launches/PMO-sparkles-lovable-for-existing-projects",
        "votes": 164,
        "created_at": "2026-02-04T07:27:06.748Z"
      }
    ]
  },
  {
    "id": 31181,
    "name": "Synthetic Sciences",
    "slug": "synthetic-sciences",
    "former_names": [
      "InkVell"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d12b5cddde967f28e71a5bdfa173bbd8e7a0b10c.png",
    "website": "https://syntheticsciences.ai/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Synthetic Sciences is a research lab building infrastructure for scientific superintelligence. Empirical science is bottlenecked by verification that is slow, expensive, and imperfect. We work on tooling, evals, training environments, algorithms, and labs that make autonomous science possible.",
    "one_liner": "Infrastructure for Autonomous Science",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1770489645,
    "tags": [
      "Reinforcement Learning"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2026",
    "status": "Active",
    "industries": [
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      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/synthetic-sciences",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/synthetic-sciences.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/synsci",
    "x_url": "https://x.com/SynScience",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/synthetic-sciences",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/d12b5cddde967f28e71a5bdfa173bbd8e7a0b10c.png",
    "app_video_url": null,
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    "primary_partner": {
      "name": "Gustaf Alstromer",
      "url": "https://www.ycombinator.com/people/gustaf-alstromer"
    },
    "founders": [
      {
        "user_id": 1441373,
        "full_name": "Ishaan Gangwani",
        "title": "Co-Founder",
        "founder_bio": "Prev: IOAI '25 (HM), USACO Platinum, Z-Fellows, Emergent Ventures",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/ishaan-gangwani-3a7792241/",
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      },
      {
        "user_id": 2581686,
        "full_name": "Aayam Bansal",
        "title": "Co-Founder",
        "founder_bio": "Built COVID-19 helpline infrastructure for Indian govt serving 50k+ people daily\nPatented (US, SG, IND) and Sold Orthopaedic AISock for 5-figures at 17\nPublished at NeurIPS, ICML, ICLR, AAAI, CVPR & other A* conferences\n\nPrev: aisock (Acq.), Z-Fellows, Emergent Ventures",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/aayambansal/",
        "x_url": "https://x.com/aayambansal",
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      }
    ],
    "jobs": [],
    "news": [
      {
        "title": "Indian teens among youngest founders to get accepted into Y Combinator W26 - The Economic Times",
        "url": "https://economictimes.indiatimes.com/ai/ai-insights/indian-teens-among-youngest-founders-to-get-accepted-into-y-combinator-w26/articleshow/125788177.cms?from=mdr",
        "date": "Dec 08, 2025"
      }
    ],
    "launches": [
      {
        "id": 98217,
        "title": "Synthetic Sciences – AI Co-Scientists for End-to-End Scientific Research",
        "tagline": "Cursor for Scientific Research.",
        "body": "Hi! We’re Aayam and Ishaan, co-founders of [Synthetic Sciences](https://syntheticsciences.ai/).\n\n# **TL;DR**\n\nSynthetic Sciences is a platform where scientists delegate complex research tasks to AI co-scientists that handle the full research loop: **literature → hypotheses → experiments → results → paper drafts**.\n\nOver the last year, AI has been showing some traction in math research. Math gets the coverage because it’s easy to measure. But there is a non-trivial unlock to be made in accelerating the rest of science – ML research, computational biology, proteomics - where the tooling hasn't caught up yet.\n\n**Launch Video:** <https://www.youtube.com/watch?v=uHOmeCnV1HU>\n\n# **The Problem**\n\nScientific research is a marathon of iterations. Read hundreds of papers. Form hypotheses. Design and run experiments. Wait. Analyze. Write. Revise. Submit. Each cycle compounds.\n\nThe existing tooling doesn't help. AI “literature review” tools surface papers but don't carry context forward into your code or experiments. Jupyter, W&B & others track runs but are siloed from your literature and writing. Writing happens in isolation, even though it could be steering decisions earlier.\n\nResearch is a long chain of context-dependent steps, and our tools treat each one like it’s isolated. Every iteration forces you to rebuild state: what you read, what you tried, why you chose this method, what failed, what changed.\n\nA single research question becomes months of fragmented work scattered across tools, tabs, and time zones. And it's all on you. Every step requires your attention, your context, your time.\n\nYou can't parallelize yourself. If we could accelerate scientific research the way we’ve accelerated software engineering in the last 24 months we are guaranteed to see science breakthroughs that will massively benefit humanity.\n\n# **Our Solution**\n\nPoint synsci at a research question, a repo, or a dataset. Our AI co-scientists autonomously:\n\n* Search + synthesize literature grounded in your project\n* Generate high-quality hypotheses + idea trees tied to prior work\n* Design experiment plans + GPU job specs\n* Write and run code (Python, R, ML pipelines) in containerized environments\n* Launch and monitor experiments on serverless GPUs & GPU clusters\n* Output publication-ready drafts: LaTeX, figures, slides\n\nWe’ve mostly tested synsci on ML research so far, but we’re rapidly expanding across domains. It’s already strong in computational biology research: on BixBench Verified, our biology mode achieves state-of-the-art performance (92%).\n\n![uploaded image](/media/?type=post&id=98217&key=user_uploads/1441373/0d71bacf-1ac6-4ee5-973e-42a543973d04)\n\n# **Flywheel Mode: Own Your Models**\n\nIf you have users, you already have the rarest ingredient in AI: proprietary signal. Every correction, accept/reject, trace, and outcome becomes training data. Everyone has access to the same models and can buy the same tokens. Nobody else can buy your users, your logs, and your feedback loops. \n\nStrong open-weight models now make it possible to beat frontier performance on your specific tasks through post-training (SFT + RL). However, the problem is everything around the model: data plumbing, evals, deployment, and compute. That friction keeps most teams renting intelligence by the token instead of owning it.\n\nFlywheel Mode makes the loop painless. We handle the glue code and ship the workflow end-to-end across 20+ compute providers and hundreds of built-in skills. Use your AI co-scientists to run the full loop: train, evaluate, deploy, iterate.\n\n![uploaded image](/media/?type=post&id=98217&key=user_uploads/1441373/ea6a1549-dd1f-40e3-bd36-ae627be085b0)\n\n# **Our Story**\n\nWe met doing ML research at NUS, CMU and MIT CSAIL & published together at NeurIPS, ICML, and AAAI workshops. Ishaan came from competitive programming (top-ranked in India for IOAI Team Selection, USACO Platinum). Aayam previously built, patented & sold an AI orthopaedic sock and built COVID-19 infra serving 50k+ users daily. \n\n# **Our Ask**\n\n* **Try it:**[ ](https://app.syntheticsciences.ai)[syntheticsciences.ai](http://syntheticsciences.ai) - $5 in free credits when you sign up!\n* **If you’re a CTO / Head of R&D / research lead** and want to accelerate R&D with AI co-scientists, we’d love to talk.\n* **RL environments for scientific research:** We're building LHRL environments to post-train models on ML research workflows. If you're an AI lab interested in process-oriented data, let's talk.",
        "url": "https://www.ycombinator.com/launches/PY9-synthetic-sciences-ai-co-scientists-for-end-to-end-scientific-research",
        "votes": 20,
        "created_at": "2026-02-26T18:00:26.592Z"
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    "id": 31182,
    "name": "Visibl Semiconductors",
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "Visibl Semiconductors makes custom silicon accessible to hardware companies, starting with power electronics. We are an AI-native custom-silicon design partner that cuts ASIC development cost and timeline on mature nodes, helping teams deliver better performance and lower BOM cost.\r\n\r\nWe work with data-center and AI-infrastructure power, motor drives, industrial automation and robotics, industrial power supplies and conversion, battery systems and e-mobility powertrains, EV charging, solar, energy storage, grid power, HVAC, heat pumps, and appliances.\r\n\r\nV1 boards built from off-the-shelf parts are great for getting to market quickly, but scaling to v2+ volume requires optimizing cost, size, and manufacturability. Visibl folds those parts into custom silicon built around the product: a simpler BOM, reclaimed board space, fewer supply constraints, and automation-ready assembly.\r\n\r\nWe manage the full path from architecture and design through verification, fabrication, packaging, and production-ready silicon, working alongside hardware teams so they do not need an in-house chip team.",
    "one_liner": "Custom silicon for power electronics",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1767637338,
    "tags": [
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      "Enterprise",
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      "Semiconductors",
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    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/visiblsemi/",
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      "name": "Tyler Bosmeny",
      "url": "https://www.ycombinator.com/people/tyler-bosmeny"
    },
    "founders": [
      {
        "user_id": 931842,
        "full_name": "Bryce Neil",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder & CEO at Visibl Semiconductors. Passionate technologist and recipient of two of Canada’s most competitive academic scholarships. Bryce is a computer engineer with experience across engineering, data, and business. He has built production software and data systems for Deloitte’s OmniaAI team, healthcare, and the public sector. His work has run in leading U.S. hospitals and supported teams globally.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/bryceneil/",
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      {
        "user_id": 2574530,
        "full_name": "Jordon Kashanchi",
        "title": "Founder/CTO",
        "founder_bio": "Co-founder & CTO of Visibl Semiconductors. Jordon previously worked at Microsoft, Arm, and Intel, building expertise in AI accelerators, autonomous vehicle hardware, and graphics. Most recently at Microsoft, he designed digital logic and microarchitecture for next-gen custom AI silicon. He holds an MS in ECE from UT Austin and is published in PNAS and ACM.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jordon-kashanchi-46357b143/",
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    "jobs": [
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        "id": 113109,
        "title": "Senior Digital IC Engineer — RTL Design & Verification",
        "url": "https://www.ycombinator.com/companies/visibl-semiconductors/jobs/o2iGDo7-senior-digital-ic-engineer-rtl-design-verification",
        "location": "Remote (US)",
        "type": "Contract",
        "role": "Engineering",
        "role_type": "Hardware",
        "salary_range": "$180K - $250K",
        "equity_range": "",
        "experience": "6+ years",
        "visa": "US citizen/visa only",
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    "launches": [
      {
        "id": 97968,
        "title": "Visibl Semiconductors: The First AI-Enabled Coordination Layer for Chip Design",
        "tagline": "Meet Visibl, The First AI-enabled Coordination Layer for Chip Design",
        "body": "Hey everyone 👋\\\nWe’re Bryce and Jordon, co-founders of VISIBL SEMICONDUCTORS™\\\n\\\n**Launch video:** <https://youtu.be/l_0BcKIIU3Q>\n\n---\n\n**TL;DR**\\\n_Visibl is the first coordination layer for chip design._ Requirements, architectural intent, and implementation drift out of sync as designs and teams scale. Visibl surfaces drift early, opens cases with evidence, and delivers review-ready fixes enabling improved schedule, cost, and risk outcomes in chip design.\n\nCheck out LinkedIn post here:\\\n<https://www.linkedin.com/posts/y-combinator_visibl-semiconductors-yc-w26-is-building-activity-7430280268252590081-UBoI/>\n\n**Problem**\\\nCoordination has always been a human job: monitoring drift, triaging failures, keeping the schedule aligned. It demands constant vigilance, reacting to failures, proactively scanning for issues, always watching.\n\nAs designs scale, no one can hold all that context: the specs, the implementation, the test results, the decisions scattered across Slack, Jira, and docs. Issues slip through. Drift compounds. We saw this firsthand. There was no software to solve it. So we're building it.\n\nOur experience spans chip design and high-stakes production systems. We're solving a problem there was never enough human bandwidth to address, but one that directly impacts the most important outcomes in chip design: schedule, cost, and risk.\n\n**What Visibl Does**\\\n\\\n**Monitors** - specs, implementation, CI, and all design collateral to detect drift early\n\n**Investigates** - creates cases with evidence: spec sections, RTL refs, CI logs, historical decisions\n\n**Proposes** - agents suggest fixes, run verification, package review-ready diffs\n\n**Gates** - human approval required, nothing ships without explicit sign-off\n\n### —\n\n\\\n**Results**\\\n\\\n**Schedule** - Eliminate weeks lost waiting for the one engineer with context to debug failures\n\n**Cost** - 10x less engineering overhead on triage; your team builds instead of firefighting\n\n**Risk** - Catch issues early to minimize rework; avoid late-stage surprises that lead to $10M+ respins\\\n\\\n\\\n\\\n\\\n**Instant Dispatch & Case Creation**\n\n![uploaded image](/media/?type=post&id=97968&key=user_uploads/931842/d732540d-c0f2-416d-9402-378b41735ffe)\n\nAgents spin up immediately on regressions, failing PR checks, spec updates, and more. Visibl opens a case automatically.\n\n---\n\n# \n\n—\n\n\\\n**Evidence Bundle**\n\n![uploaded image](/media/?type=post&id=97968&key=user_uploads/931842/e869a320-410e-4c42-9126-535bd4c9b4be)\n\n\\\nEach case comes preloaded with spec sections, RTL refs, CI logs, and decision history.\n\n# \n\n—\n\n\\\n**Recommended Fix**\n\n![uploaded image](/media/?type=post&id=97968&key=user_uploads/931842/d5e63a58-2b58-4e78-8278-652a0808b651)\n\nVisibl proposes three fix paths and recommends the best one for approval. User can also clarify and specify their own intent.\n\n# \n\n—\n\n\\\n**Verified Review-Ready Diff**\n\n![uploaded image](/media/?type=post&id=97968&key=user_uploads/931842/45650b40-9fc2-477a-8ffa-8c29cf6bac09)\n\nApproved changes are applied, verified, and packaged as a review-ready diff with results.\\\n\\\n\\\n\\\n**Role-Based, Team-Based, and Individual Views**\n\n![uploaded image](/media/?type=post&id=97968&key=user_uploads/931842/2c568efd-b5a0-42db-be95-97f9cbfde4d8)\n\nRole-specific views surface the same underlying truth at the right level of detail. For example, the executive view shows how Visibl ambiently ingests signals across the org and distills them into what leaders care about most—readiness, schedule impact, and top tapeout risks—so they can take action quickly. **Visibl also lets executives (and every role) act directly on these insights, drill into the underlying evidence, assign owners, and drive cases to resolution.**\n\n\\\n**Our Ask**\\\n\\\n**If you have a friend who designs chips at a semiconductor or hardware company, we would really appreciate an intro.** Even a quick forward of this post helps.\\\n\\\nIf you are a:\n\n* _DV / CI owner_\n* _Design methodology / flow owner_\n* _Team heading into integration, freeze, or pre-tapeout_\n\n…we’d love to talk.\n\n**Schedule a demo:** [**founders@visiblsemi.com**](mailto:founders@visiblsemi.com)\n\n---",
        "url": "https://www.ycombinator.com/launches/PU8-visibl-semiconductors-the-first-ai-enabled-coordination-layer-for-chip-design",
        "votes": 13,
        "created_at": "2026-02-19T15:43:41.410Z"
      }
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    "id": 31192,
    "name": "Approxima",
    "slug": "approxima",
    "former_names": [
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      "SideKit"
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    "website": "https://approxima.ai",
    "all_locations": "Toronto, ON, Canada",
    "long_description": "Human-assisted development should be for novel ideation, not routine maintenance, bug fixes or incremental updates. Approxima is bringing you that future with agents that can scope work, code, validate their fixes end-to-end in sandbox environments and merge to production. Book a demo: https://calendly.com/ashish-selvaraj/approxima",
    "one_liner": "Your software should build itself.",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1767593677,
    "tags": [
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      "Infrastructure",
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    "batch": "Winter 2026",
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    "year_founded": 2025,
    "city": "Toronto",
    "country": "CA",
    "linkedin_url": "https://www.linkedin.com/company/approximai/",
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    "github_url": "https://github.com/appsidekit/",
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      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
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        "user_id": 3229135,
        "full_name": "Ethan Pronev",
        "title": "Founder",
        "founder_bio": "Co-founder at Approxima, building the trust layer to help software development scale with AI. Previously worked on trading systems at Jane Street and Citadel Securities. Computer Science graduate from the University of Waterloo, class of 2025.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/ethan-pronev/",
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      {
        "user_id": 2960509,
        "full_name": "Ashish Selvaraj",
        "title": "Founder",
        "founder_bio": "Co-founder at Approxima, building the trust layer to help software development scale with AI. Previously worked on delta live tables at Databricks, an infra testing engine at Microsoft and graduated with a double degree in Computer Science and Business from Waterloo in 2025.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/ashish-selvaraj/",
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        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b55ae2511335d9eef1ee99bbf880a8b7585339e1.jpg"
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  },
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    "id": 31195,
    "name": "Reframe",
    "slug": "usereframe",
    "former_names": [
      "Milotic AI"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cf91d138b76358671fb6075cfe46848aa81bd6cc.png",
    "website": "http://usereframe.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Reframe is the only AI-native marketplace for hardware teams to procure both COTS and custom manufactured components. We have access to trusted suppliers that have made parts for the most reliable hardware products that people use today (iPhones, Teslas, and more). We use Agents to automate end-to-end procurement so that hardware teams can scale while remaining lean.",
    "one_liner": "AI-native, hardware procurement marketplace",
    "team_size": 1,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1770935313,
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    "isHiring": false,
    "nonprofit": false,
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    "status": "Active",
    "industries": [
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      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
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    "url": "https://www.ycombinator.com/companies/usereframe",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/usereframe.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/usereframe",
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    "primary_partner": {
      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
    },
    "founders": [
      {
        "user_id": 2629859,
        "full_name": "Bryan Zin",
        "title": "Founder",
        "founder_bio": "Founder at Reframe, prev. Product Design Engineer at Apple (iPhone PD)",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/bryan-zin",
        "x_url": "https://x.com/bryanzin7",
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    "launches": [
      {
        "id": 97967,
        "title": "Reframe: Automate end-to-end hardware procurement",
        "tagline": "Designing parts is an engineer's job, procurement is ours.",
        "body": "tl;dr: One of the most manual parts of the hardware supply chain is procurement logistics. [Reframe](http://usereframe.ai/) makes getting your components painless and automated, exactly how it should be. Instead of spending precious engineering time manually tracking down parts or figuring out build schedules, Reframe takes over **end-to-end procurement** so **hardware teams can stay lean**. We coordinate with your vendors to automatically order your components, resolve any delays or component shortages, and ensure that your parts arrive on time. [Book a call](https://cal.com/bryan-zin/reframe-demo) with us to start **automating procurement** today.\n\n[Launch Video](https://youtu.be/ArVtij87hJA)\n\n👋 Hey everyone, [Eric](https://www.linkedin.com/in/eric-wiener/) and [Bryan](https://www.linkedin.com/in/bryan-zin/) are from Reframe (W26) and we’re bringing automation to the hardware supply chain.\n\nSpecifically, we’re starting with procurement. Designing components is just half the battle when it comes to making physical products. After an engineer finishes designing the parts, they then have to figure out the right people to source their parts and navigate through the logistics of payment, shipping, and delivery.\n\nRight now, most procurement teams at large enterprises, medium stage companies, and early start-ups are still using _emails, spreadsheets, and WeChat_ to manage billions of dollars of components that need to be shipped from all over the world. It’s an archaic process that is unfortunately part of either a start-up engineer’s job or costs a full-time role at larger companies. \n\nOur solution automates away all of the tedious work behind getting your parts delivered on time. We take your BOM as input, and track down each part in their individual supply chain, from the raw material vendor all the way to the assembly line. Whether it’s as simple as placing an Amazon order, or coordinating with an overseas manufacturer to fabricate parts and ship them across the world, our AI agents handle all the communication, coordination, and logistics. \n\nWhen parts are delayed, or when specs change, the Reframe Assistant dynamically update the BOM and build plans to provide clarity and transparency between different teams. When there is a part change that creates conflict between teams, Reframe creates a group chat between the relevant stakeholders and provides them with context to make fast decisions. \n\nOur native integration with Slack ensures that Reframe exists where you are. Simply tag the Reframe Assistant in the relevant thread or channel, and it will answer questions about your parts without you having to go through giant spreadsheets or emails. \n\n📞 [Book a call](https://cal.com/bryan-zin/reframe-demo) with us so we can **automate procurement** and you can keep shipping great products.",
        "url": "https://www.ycombinator.com/launches/PU7-reframe-automate-end-to-end-hardware-procurement",
        "votes": 9,
        "created_at": "2026-02-19T16:55:51.716Z"
      }
    ]
  },
  {
    "id": 31222,
    "name": "Superset",
    "slug": "superset",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/9c4aa01fc589ba1d208558f7b720c6081f672b08.png",
    "website": "https://www.superset.sh/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Superset is an open-source IDE that helps engineers run 100s of coding agents in parallel.\r\n\r\nOur desktop app is loved by tens of thousands of engineers, and we're scaling out our effort to build a collaborative, cross-platform tool to allow users to code anywhere.",
    "one_liner": "Building self-improving software",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1772696752,
    "tags": [
      "Developer Tools",
      "Consumer",
      "B2B",
      "Enterprise Software",
      "AI"
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    "batch": "Spring 2026",
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    "regions": [
      "United States of America",
      "America / Canada"
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        "body": "**_TL;DR_ [Superset](https://superset.sh/)** is a terminal-first IDE with built-in agents management, PR review, and remote workspaces; built for running coding agents in parallel.\n\nSuperset is a daily driver for great teams including YC companies, engineers at Wix, DoorDash, Netflix, and major OSS products/projects including [homebrew](https://github.com/Homebrew/brew), [mastra](https://github.com/mastra-ai/mastra), [browser-use](https://github.com/browser-use/browser-use) and many more\\\n\\\nCheck out our fun video interviewing some of our users 👇\n\n<https://www.youtube.com/watch?v=r_d_eYBV8cI>\\\n\\\nWe're Avi, Kiet and Satya\\\n\\\nThe future workspace for software development looks less like a text editor based IDE and more like a tool to help devs manage multiple Claude Code or Codex sessions, setup automations and workflows for coding agents, aggregate context from tickets, logs, etc, and efficiently review changes.\\\n\\\nSince launching just 5 months ago:\n\n* **11K+ Github stars** and **75+ contributors,**\n* Used as the daily driver in great teams including YC companies, engineers at OpenAI, Google, Vercel, and major OSS products/projects including [homebrew](https://github.com/Homebrew/brew), [mastra](https://github.com/mastra-ai/mastra), [browser-use](https://github.com/browser-use/browser-use) and many more\n* A thriving community with **5K+ followers on X**, **1K+ members on Discord.**\n* Got **#1 on Product hunt** and **top 4 on HN twice**\n\n![uploaded image](/media/?type=post&id=101973&key=user_uploads/230159/5bfff019-f7dd-4262-b872-67641385eb17)\n\nX has been very supportive:\n\n![uploaded image](/media/?type=post&id=101973&key=user_uploads/230159/42ce6b2b-21fd-4d1b-9bcb-a00fecd85d52)\n\n\\\nCTO of Mastra:\n\n![uploaded image](/media/?type=post&id=101973&key=user_uploads/230159/3e7afc9f-1023-4d20-a701-324ecbc44273)\n\nVercel about Superset:\n\n![uploaded image](/media/?type=post&id=101973&key=user_uploads/230159/66749d1b-feea-4eb0-a2ba-3afb1a84e76a)\n\nPrinciple Engineer at Cloudflare\n\n![uploaded image](/media/?type=post&id=101973&key=user_uploads/230159/12c60756-7b29-45e8-96d4-72d9563979bb)\n\nCTO of Browser Use:\n\n![uploaded image](/media/?type=post&id=101973&key=user_uploads/230159/54080db5-f070-4d19-bf19-f9782075b1b0)\n\n\\\n**Superset Product Tour**\\\n<https://www.youtube.com/watch?v=YWDHn7gUwfg>\\\n**\\\nPlease try us and give us your feedback:**\n\nStar the repo: <https://github.com/superset-sh/superset>\\\nsend us your feedback: [hello@superset.sh](mailto:hello@superset.sh)\n\nTry superset: <https://superset.sh/>",
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        "title": "Corelayer: AI on-call engineer for regulated industries",
        "tagline": "Detect and fix production issues 15x faster",
        "body": "Hey everyone! 👋\n\nWe’re [Mitch](https://www.linkedin.com/in/mitchellradhuber/) and [Shipra](https://www.linkedin.com/in/shipra-jha-9b021859/) - before Corelayer, we built data infrastructure at Goldman Sachs where we spent many late nights and weekends debugging systems that processed 100s of billions of rows a day.\n\n**TL;DR**\n\nWhen you’re on call in data-heavy, regulated industries like fintech, healthcare, or insurance, you need to inspect underlying data to debug production issues. We built a platform that monitors both infrastructure and data for anomalies and uses AI agents to debug and suggest fixes in minutes.\n\n[Corelayer Launch Video](https://youtu.be/yFZKJ9QRrr4)\n\n**On-call support is painful and expensive**\n\nAll engineers hate being on call. Production issues kill velocity, erode user trust, and become more and more costly as companies scale.\n\nFortune 100s spend **$100M+/year** on first-line-of-defense production support.\n\nSmaller companies can’t afford to burn **scarce engineering resources** on time-consuming support and maintenance.\n\n**The (sensitive) data problem**\n\nIf you’re a backend engineer at a fintech, you probably own a service that queries data, applies some business logic, and stores the result somewhere (i.e., a data pipeline).\n\nWhen this service is running in production, you’ll see two failure modes:\n\n1. Exceptions in logs and/or failing jobs\n2. Bad data produced by your service\n\n“Bad data” can mean anything from incorrect values to entirely missing or duplicated rows.\n\n**This is really common** in certain products and industries, but you’re totally blind to these errors without monitoring data for anomalies and querying data while debugging.\n\nIn regulated environments where this problem is prevalent, **production data is sensitive**, which is another constraint we have to solve for.\n\n**Corelayer solves this**\n\nWe continuously monitor logs, metrics, **and data** for anomalies and use AI agents to debug, root-cause, and suggest fixes for issues.\n\n![uploaded image](/media/?type=post&id=96772&key=user_uploads/2897480/fce0b569-7a89-41f5-8225-625e86092a04)\n\nWe also filter out false positives and group related issues to reduce alert noise.\n\n![uploaded image](/media/?type=post&id=96772&key=user_uploads/2897480/6b91dd40-c7c7-4ca9-97a4-f80eaaff537d)\n\nEvery team is different. We take feedback from human engineers so our agents learn your systems and improve over time.\n\n![uploaded image](/media/?type=post&id=96772&key=user_uploads/2897480/f5384b34-039b-40f5-ba00-4c1ede356893)\n\nData is especially sensitive in regulated industries. We’re SOC 2 compliant, offer **BYOC and** **on-prem deployments**, flexible LLM inference options, and expose an audit trail of each step performed by the agent with citations.\n\n**Our Asks**\n\nDoes your team deal with data or integrations and spend more time on production support than you’d like? [Let’s chat](https://cal.com/mitchrad/30min). \n\nCan you connect us with an engineering leader at a finserv, fintech, healthcare, or insurance company? Reach out at [founders@corelayer.com](mailto:founders@corelayer.com).\n\nThank you!\n\n![uploaded image](/media/?type=post&id=96772&key=user_uploads/2897480/18ce5a17-9fb2-42d6-8a39-0314da2f5f5d)\n\n",
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        "title": "Canary 🐥: The first AI QA Engineer that understands your codebase",
        "tagline": "The validation layer for AI generated code.",
        "body": "Hey everyone, we're the founding team behind Canary, ex-Windsurf and Google engineers.\n\n# **TL;DR**\n\n[Canary](https://www.runcanary.ai) is the first AI QA engineer that understands your codebase. Built by a team of ex-Windsurf and Google engineers, Canary reads your source code to understand what your app is supposed to do, then tests it like a real user would. Teams using Canary have caught broken auth flows, slow page loads, and drifts in AI responses before users hit them. Chat with us [here](https://cal.com/runcanary/founders-canary)\n\n<https://youtu.be/IeP7H_E8yCM>\n\n# **The Problem**\n\nAI coding tools have made every engineering team 5–10x faster. Code generation is a solved problem. Code validation is not.\n\nCustomer-facing incidents are up 43% year over year. PRs are bigger, code reviews still happen in file diffs, and nobody is testing real user journeys before merge. Changes that look clean in review break checkout, auth, and billing in production.\n\nQA teams are either non-existent or underwater. Manual testing can't keep up with AI-generated code volume. E2E test suites don't scale. The gap between shipping speed and validation is widening every sprint.\n\n# **How Canary Works**\n\nCanary connects to your codebase to understand how your app is built — routes, controllers, validation logic, API schemas. When it runs tests, it uses your code as the reference point to verify and understand how to execute them.\n\n**PR Testing**\n\nPush a PR. Canary reads the diff to know what changed, uses your codebase to understand the intent behind your application and the changes, then generates and runs tests against your preview app, checking real user flows end to end.\n\n**_Step 1: Canary analyzes your PR and comments what it found_**\n\n![uploaded image](/media/?type=post&id=97890&key=user_uploads/1465952/5a5754e8-e0f2-4c5b-bd10-fc1ab314ed3b)\n\n**_Step 2: Canary runs tests and reports results directly on the PR_**\n\n![uploaded image](/media/?type=post&id=97890&key=user_uploads/1465952/001bd6ff-fd2b-4344-b272-e3fd630ea3d8)\n\n**_Step 3: Click into any failed test to see exactly what broke_**\n\n![uploaded image](/media/?type=post&id=97890&key=user_uploads/1465952/d0ca3915-0fb2-4226-9f78-05647886bb46)\n\n**_Step 4: Want a specific user flow tested? Trigger it through a PR comment_**\n\n![uploaded image](/media/?type=post&id=97890&key=user_uploads/1465952/cf303da1-9272-461e-83e6-206f45569cfb)\n\n**Regression Testing**\n\nMove any PR test into a regression suite for ongoing use. Or describe what you want to test in plain English on our platform.\n\nCanary generates a full test suite from your codebase, schedules it, and runs it continuously. Regression suites also run on every PR, catching bugs from new code changes before they ship.\n\n![uploaded image](/media/?type=post&id=97890&key=user_uploads/1465952/a070c92d-dda3-47d8-8b92-a1ae26b05f3b)\n\n# **Run Canary**\n\nTeams using Canary have caught broken auth flows, slow page loads, and drifts in AI responses as well.\n\nWe're now working directly with engineering and product teams to customize Canary to their codebase and workflows. If your team is shipping with AI coding tools and quality feels like it's falling behind, we'd love to work with you.\n\nReach out at [founders@runcanary.ai](mailto:founders@runcanary.ai) or chat with us directly [here](https://cal.com/runcanary/founders-canary)\n\n# **The Team**\n\nThe founding team comes from Windsurf and Google, with deep experience building AI coding tools, AI inference systems, and enterprise-scale infrastructure.\n\nWe've built the AI tools engineers use to ship faster. We've built the enterprise systems those tools ship into. We've built both sides, Canary sits at the intersection.",
        "url": "https://www.ycombinator.com/launches/PSs-canary-the-first-ai-qa-engineer-that-understands-your-codebase",
        "votes": 13,
        "created_at": "2026-02-17T21:18:29.099Z"
      }
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  },
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    "id": 31292,
    "name": "Aurorin CAD",
    "slug": "aurorin-cad",
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    "website": "https://aurorincad.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "There are 2 problems:\r\n\r\nThe first, CAD software is slow and the second, designing with it is a tedious process with many steps. Aurorin solves both of these problems by being a CAD software built from the ground up on a modern tech stack with AI at its heart.\r\n\r\nBuilding the CAD kernel lets us fully leverage AI while modernizing execution speed. Almost all existing CAD software (Solidworks, NX, Creo, Catia, Fusion 360, Onshape etc) use the same couple of underlying CAD kernels built in the 80's. It's common for these programs to take 4 hours to open a file.\r\n\r\nAurorin uses a custom parametric and B-Rep driven CAD Kernel built to take full advantage of modern CPUs and GPUs and be AI native.",
    "one_liner": "Claude code for Mechanical Engineers",
    "team_size": 1,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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        "full_name": "Michael Baron",
        "title": "Founder/CEO",
        "founder_bio": "Founder of Aurorin, 3x SpaceX intern, prev Apple Intern.\n\nBefore starting Aurorin, Michael worked on Raptor combustion simulation, Dragon Guidance, Navigation & Control, and Starshield flight software at SpaceX, as well as GPU driver performance at Apple.",
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        "linkedin_url": "https://www.linkedin.com/in/michael-andrew-baron/",
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    "jobs": [
      {
        "id": 92565,
        "title": "Founding Engineer",
        "url": "https://www.ycombinator.com/companies/aurorin-cad/jobs/R3tKam9-founding-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$120K - $160K",
        "equity_range": "3.00% - 4.00%",
        "experience": "Any (new grads ok)",
        "visa": "Will sponsor",
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      {
        "id": 98144,
        "title": "Aurorin CAD - The Next Generation Mechanical CAD Software",
        "tagline": "Create in seconds what takes over 20 minutes in SolidWorks or NX",
        "body": "# \\*\\*\\*\\*\n\n**TL;DR**: New native CAD software with crazy fast execution speed and a tightly integrated agent to help engineers design way faster. Download for Mac or Windows at[ ](https://www.aurorincad.com/)<https://www.aurorincad.com>\n\n<https://youtu.be/BkNunCBk_3o>\n\nHey everyone, I’m [@Michael Baron](https://bookface.ycombinator.com/user/2811605), the founder of [@Aurorin CAD](https://bookface.ycombinator.com/company/31292), a new CAD software built from the ground up to fix 2 major problems:\n\n* CAD is really slow\n* CAD is tedious\n\n**No more tedious work**\n\nAurorin can create parts in seconds that takes 20 minutes with Solidworks.\n\nBuilding the CAD kernel from the ground up lets us create a much better AI interface than is possible in a traditional kernel. That is why we have decided to build a new kernel instead of using an existing one or making a plugin for existing software. This approach allows us to seamlessly combine traditional UI editing with a chat interface to design even highly complex parts at incredible speed.\n\n**Speed**\n\nIt’s common for existing software to take 4 hours to open CAD assemblies.\n\nAlmost all existing CAD software (Solidworks, NX, Creo, Catia, Fusion 360, Onshape etc) use the same couple of underlying CAD kernels built in the 80s.\n\nAurorin uses a custom parametric and B-Rep driven CAD Kernel built to take full advantage of modern hardware.\n\n**The team** \n\nBefore starting Aurorin, I worked at SpaceX on Raptor combustion simulation, Dragon guidance, navigation & control, and Starshield flight software. I also worked on GPU driver performance at Apple.\n\n**The Asks**\n\nDo you know a hardware company that wants to ship faster? We’re looking for more companies to use Aurorin for rapid prototyping alongside their existing CAD or make the switch for a much faster hardware development cycle.\n\nAre you a design engineer who’s annoyed with CAD? We’d love to hear your feedback on what we’re building.\n\nI’d really appreciate an email at [michael@aurorincad.com](mailto:michael@aurorincad.com)",
        "url": "https://www.ycombinator.com/launches/PWy-aurorin-cad-the-next-generation-mechanical-cad-software",
        "votes": 39,
        "created_at": "2026-02-24T18:07:44.660Z"
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    "id": 31306,
    "name": "Martini",
    "slug": "martini",
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    "website": "https://martini.film",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Martini is a collaborative, AI-native platform for professional filmmaking in the era of generative media.\r\nBy integrating the best generative models into professional workflows, we enable world-class creatives to harness generative AI as a legitimate medium for film.",
    "one_liner": "AI Video Production for Professionals",
    "team_size": 2,
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    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1768440972,
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    "url": "https://www.ycombinator.com/companies/martini",
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    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/martini-film/",
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      "name": "Jared Friedman",
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      {
        "user_id": 2701033,
        "full_name": "Koh Terai",
        "title": "Founder/CEO",
        "founder_bio": "Cannes-screened cinematographer. Stanford Design. CS background.\n\nBuilding professional filmmaking tools for the generative era of film.\n\nwww.kohterai.com",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/kohterai/",
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      {
        "user_id": 3120681,
        "full_name": "Long Hoang",
        "title": "Founder/CTO",
        "founder_bio": "Turns Martinis into Films.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/longh/",
        "x_url": "https://x.com/beertocode",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/40688ee2ac0332a852379ed14c725913d4ade66a.jpg"
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      {
        "id": 97320,
        "title": "Martini: AI Video Production for Professionals",
        "tagline": "Your Film Set for AI Videos",
        "body": "**TLDR:** _Martini is a collaborative, professional workspace for creating high-quality AI videos. It’s a film set for AI video production._\n\n<https://youtu.be/E4-astm3zyI>\n\n# **🍸 Introduction**\n\nWe’re [Koh](https://www.linkedin.com/in/kohterai/) and [Long](https://www.linkedin.com/in/longh/) from Martini.\n\nGenerative AI video still feels like the wild west.\n\nBrave members of the creative community are embracing this new medium.\\\n\\\nBut making a great AI video still feels like fighting the tool rather than using it. Most AI tools are built around prompting and seeds—not the way filmmakers actually think.\n\nKoh is a [professional cinematographer](https://www.quinzaine-cineastes.fr/en/film/grand-bouquet). He knows filmmakers live and breathe on film sets – a space for intentionality, collaboration, and control. Not endless prompts. So we built Martini to give filmmakers an environment to direct and shoot their generative AI films.\n\nWe shared Martini with a few filmmaker friends. Then more. Today over [200 films](https://www.madewithmartini.com/) have been made with Martini. They’ve aired as TV Commercials, been displayed as artwork, and have gone viral online.\n\n![uploaded image](/media/?type=post&id=97320&key=user_uploads/2701033/3a701a0c-9b24-4e63-bdf0-96cac0be92bf)\n\nOur users are filmmakers, artists, serious production teams, and anyone daring enough to take on the challenge of creating AI video.\n\n---\n\n---\n\n# **🍸 Martini is the go-to platform for AI video production**\n\n**Professional Control**\\\nGet the exact shot you want, not just the one the model hands you. Step into virtual worlds and compose shots using camera position, lenses, and movement — not just prompts and frames.\n\n![uploaded image](/media/?type=post&id=97320&key=user_uploads/2701033/41b4eb79-44ac-41fc-948f-dcde5b23ad60)\n\n_Step into any image or video to reframe and reshoot_\n\n**Streamlined Production Pipeline**\\\nTeams are forced to MacGyver their workflows across a mess of tools. Martini brings image, video, and world models directly into the editing process.\n\n![uploaded image](/media/?type=post&id=97320&key=user_uploads/2701033/3791bdb8-2631-4b1e-8ecf-e0165913cf3f)\n\n_Built in timeline for creating rough assemblies, exportable as XML_\n\n**Production as a Team Sport**\\\nVideo production is collaborative. Different professionals bring different expertise. Martini supports real-time collaboration—sharing prompts, edits, and feedback—so teams can explore ideas together the way they do in tools like **Figma, but for generative film**.\n\n![uploaded image](/media/?type=post&id=97320&key=user_uploads/2701033/f2e831c6-9f6a-4336-9df0-2b6799d6210a)\n\n# Interested?\n\nIf you’re a filmmaker, studio, or creative agency taking AI video seriously, book a demo session with us.\\\n\\\n👉 [**\\[ Book Demo Session \\]**](https://form.typeform.com/to/VVwyeUrj) 👈",
        "url": "https://www.ycombinator.com/launches/PJg-martini-ai-video-production-for-professionals",
        "votes": 23,
        "created_at": "2026-01-30T05:50:02.004Z"
      }
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    "id": 31332,
    "name": "Stage",
    "slug": "stage",
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    "website": "https://www.tryluke.dev/",
    "all_locations": "New York City, NY, USA",
    "long_description": "Stage is a new code review platform designed to help engineers better understand and review AI generated code.\r\n\r\nEngineering teams are shipping faster than ever with agents, but now they’re drowning in an endless backlog of PRs to review. Stage reorganizes the code review process around how engineers naturally think, enabling you to review (and merge!) PRs 5x faster. \r\n\r\nUsed by top engineers at Legora, n8n, Branch, and more. ",
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    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1774297910,
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    "batch": "Spring 2026",
    "status": "Active",
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      "America / Canada"
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    "url": "https://www.ycombinator.com/companies/stage",
    "api": "https://devasheeshg.github.io/yc-api/batches/spring-2026/stage.json",
    "year_founded": 2026,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/stagereview",
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    "primary_partner": {
      "name": "Pete Koomen",
      "url": "https://www.ycombinator.com/people/pete-koomen"
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    "founders": [
      {
        "user_id": 327595,
        "full_name": "Charles Pan",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder and CEO of Stage. Stanford CS '22 and varsity men's fencing. Previously early engineer at Yuzu Health, Five Rings Capital.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/charleslpan",
        "x_url": "https://x.com/ceefryingpan",
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      },
      {
        "user_id": 1219322,
        "full_name": "Dean Stratakos",
        "title": "Founder/CTO",
        "founder_bio": "Co-founder and CTO of Stage. Stanford CS '22 and varsity men's tennis. Prev developer @ Five Rings Capital.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/dean-stratakos",
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      {
        "id": 101617,
        "title": "Stage - Code review platform for humans and agents",
        "tagline": "Stage helps engineering teams understand and review PRs 5x faster",
        "body": "Hey everyone! We’re Charles and Dean - cofounders of Stage.\n\n**👉 tldr:** Drowning in AI generated PRs? Tired of using GitHub? Us too. Stage is a code review platform designed to help you understand and review changes 5x faster.\n\n<https://youtu.be/EjMjGAqSLvo>\n\n**💻 How to get started**\n\nTry it out today at[ https://stagereview.app/](https://stagereview.app/) - all you need is your GitHub account.\n\nIt’s free for your first 14 days, and then you can use _LAUNCH_ to get 25% off for 3 months :)\n\nOther ways to try it out:\n\n* Try our demo on any public GitHub PR [here](https://stagereview.app/try)\n* Download our open source CLI [tool](https://github.com/ReviewStage/stage-cli) - runs locally and works with any coding agent\n\n**❌ The Problem**\n\nEngineering teams are shipping faster than ever, but now they’re drowning in an endless backlog of PRs to review. The bottleneck isn't writing code anymore, it's reviewing it.\n\nThis leads to:\n\n* PRs being rubber stamped without getting closely looked at\n* Unexpected behaviors slipping through to production\n* Your engineers merging changes they don’t really understand\n\nCode review bots are great at catching surface level bugs but don’t solve the root problem.\n\nEngineers need a faster way of understanding changes and giving meaningful feedback, and GitHub’s UI hasn’t changed in over a decade.\n\n**🧠 How it works**\n\nWe’re redesigning the code review experience around the way that engineers naturally read PRs.\n\n* When you open a PR or push a new commit, Stage groups your changes into small logical “chapters”\n* These chapters get ordered in the way that makes most sense to read\n* For each chapter, Stage tells you what changed and specific things to double check\n* Once you review all the chapters, you’re done reviewing the PR!\n\nEverything is synced seamlessly with GitHub (commenting, approving, etc) so it fits right into the workflows you’re already used to.\n\n![uploaded image](/media/?type=post&id=101617&key=user_uploads/327595/5004c374-be1f-47fa-a182-638252d50cf6)\n\n**❤️ Why did we start Stage?**\n\nWe're two engineers who got frustrated with using GitHub for code review. \n\nAs coding agents started taking off, we saw our PR backlog pile up faster than we could handle. Not only that, the PRs themselves were getting larger and harder to understand, and we spent most of our time trying to build a mental model of what a PR was actually doing.\n\nWe built Stage to make reviewing a PR feel more like reading chapters of a book, not an unorganized set of paragraphs. We use it every day now (not just to review each other's code, but also our own!) and at this point we can't really imagine going back to using GitHub.\n\n**👋 About Us**\n\nCharles and Dean met in their very first class at Stanford freshman year, and have been best friends ever since.\n\nThey ended up taking every class together, worked at the same quant trading firm after graduating, and were roommates in New York before joining YC. They saw firsthand how AI caused code review to break down and started Stage to rebuild the experience for how teams operate today.\n\n![uploaded image](/media/?type=post&id=101617&key=user_uploads/327595/91328354-5de7-4d17-9ac6-4c48954f1e15)\n\n",
        "url": "https://www.ycombinator.com/launches/QQz-stage-code-review-platform-for-humans-and-agents",
        "votes": 43,
        "created_at": "2026-05-20T01:40:49.081Z"
      }
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  },
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    "id": 31345,
    "name": "Replicas",
    "slug": "replicas",
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "Replicas is a cloud coding agent that allows you to delegate tasks to Claude Code or Codex from the app, Slack, Linear, and more. Each task works inside of a sandboxed virtual machine, allowing teams to heavily parallelize work and burn through tickets.\r\n\r\nReplicas agents output higher quality PRs via feedback loops - each task automatically is notified and fixes CI failures and reads all code reviews. With Environments, engineering teams can configure agents to run their entire codebase locally, verify its work, and provide preview URLs.",
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        "full_name": "Connor Loi",
        "title": "Founder/CEO",
        "founder_bio": "Building the best way to use cloud coding agents ;)\nprev helicone, td bank, and cohere :)",
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        "linkedin_url": "https://www.linkedin.com/in/connor-loi/",
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        "full_name": "Saai Arora",
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      {
        "id": 99287,
        "title": "Replicas - End-to-End Background Coding Agents",
        "tagline": "Background coding agents for engineering teams",
        "body": "Hi there, I'm Connor from [Replicas](https://replicas.dev/) :)\n\nRecently, you might have seen Stripe and Ramp release blogs outlining their in-house background coding agents. This showed us that background agents, with the proper tooling, can be relied on to ship critical production code.\n\nReplicas is a background coding agent that can run your codebase locally.\n\nWe’re used by 20+ YC startups at all team sizes.\n\n![uploaded image](/media/?type=post&id=99287&key=user_uploads/1688990/b35f4253-6fd0-478b-a04f-26f73a18b625)\n\n**The Problem**\n\nBackground coding agents are a huge productivity boost for clearing tickets and shipping faster.\n\nThe existing solutions - CC/Codex on Cloud, Cursor Agents - lock you into one harness and give you **no control over the environment**.\n\nThis defeats the entire point of \"background\" agents. A powerful background agent should run everything locally, verify its work, and iterate until it's satisfied.\n\n**How Replicas Works**\n\n**Replicas** helps you delegate to as many background agents as you need:\n\n\\- Bring your own Claude/Codex credentials\n\n\\- Each agent gets a sandbox VM with your code cloned\n\n\\- The agent installs deps, spins up databases, runs services, and verifies its work locally\n\n\\- When it's done, it opens a PR for you to review\n\n![uploaded image](/media/?type=post&id=99287&key=user_uploads/1688990/e20b6968-523d-4376-a05c-ba175cc61611)\n\nReplicas can be triggered from Slack, Linear, GitHub (PR reviews, CI/CD failures), the Dashboard, or API.\n\nThe biggest difference is **Environments**. You can configure the following:\n\n\\- Files\n\n\\- Env vars\n\n\\- Start hooks\n\n\\- Warm hooks\n\n\\- Skills/MCPs\n\nIt's built so that its flexible to any kind of codebase, allowing Replicas to run everything locally just like a human engineer would.\n\n![uploaded image](/media/?type=post&id=99287&key=user_uploads/1688990/df185d7b-b90e-455f-9ff7-10dcefcfd8c7)\n\nReplicas can also create **Previews**:\n\n![uploaded image](/media/?type=post&id=99287&key=user_uploads/1688990/7be01ba9-b653-43f2-975d-234002802e15)\n\nMeaning you can check out services (e.g web app on `3000`) running on the sandbox's VM from your computer with just a click :)\n\nCheck out this writeup for Replicas V1 for more details:\n\n<https://www.replicas.dev/notes/replicas-v1>\n\n**Demo Video**\n\n<https://youtube.com/watch?v=uyH77T-pcXc>\n\n**What's Next**\n\n\\- **Automations + API**: Improving our API and adding an automations menu, e.g having Replicas run every night.\n\n\\- **Recursive**: Replicas can break down super complex tasks by creating more Replicas instances.\n\n\\- **Lowering Latency**: For larger teams, improving our warm pool and snapshotting infrastructure to make spinning up Replicas feel _instant_ (more than it already does)\n\n\\- **Long-term Memory**\n\n\\- and what our customers ask for :p\n\n**What I'm asking from you**\n\n\\- Sign up (<https://replicas.dev>) or reach out ([connor@replicas.dev](mailto:connor@replicas.dev))\n\n\\- Check out \\[this writeup\\](<https://www.replicas.dev/notes/replicas-v1>) for Replicas V1\n\n\\- Upvote if this resonates with you!",
        "url": "https://www.ycombinator.com/launches/PpP-replicas-end-to-end-background-coding-agents",
        "votes": 87,
        "created_at": "2026-04-01T17:38:42.126Z"
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    "all_locations": "San Francisco, CA, USA",
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        "question": "What is your long-term vision? If you truly succeed, what will be different about the world?",
        "answer": "Every person at a company will be able to ship product changes, not just engineers. The barrier between having an idea and shipping it disappears.   \r\n\r\nPMs won't file tickets. Designers won't hand off mockups and wait. Founders won't choose between learning to code or hiring an engineer for a copy change. Engineering backlogs will shrink from bottleneck to review queue. Review comments get aggregated and fed back to the agent, which self-heals before an engineer steps in.\r\n\r\nEngineers will focus on architecture, infrastructure, and the hard problems - while everyone else ships the changes they're closest to the customer to make. Software development becomes a team sport. We think this is as big a shift as when spreadsheets let non-finance people work with data, or when Canva let non-designers create graphics. Product agents will do the same for software."
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        "full_name": "Ben Ong",
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        "full_name": "Benedict Chan",
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        "founder_bio": "Founder at Lightsprint, an AI-native loop for building products: decide → spec → ship → learn → repeat. \nPast: Engineering leadership — CTO @ BitGo (NYSE: BTGO), Head of Eng @ Chainlink, SDE2 @ Microsoft",
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        "full_name": "Heng Hong Lee",
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        "url": "https://www.ycombinator.com/companies/lightsprint/jobs/XUrAD20-senior-software-engineer",
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        "title": "This Y Combinator startup raised $6.1 million to let product managers and designers ship code. See its pitch deck.",
        "url": "https://africa.businessinsider.com/news/this-y-combinator-startup-raised-dollar61-million-to-let-product-managers-and/x2hx28k",
        "date": "Oct 13, 2026"
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        "title": "The 11 standout startups from YC's Demo Day, according to VCs | TechCrunch",
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        "title": "Lightsprint - The Collaborative Product Development Platform",
        "tagline": "Lightsprint lets teams plan visually, preview live and ship with an army of cloud agents",
        "body": "**tldr:** We are building a collaborative platform for software teams to plan visually, preview live and ship with an army of cloud agents. Your whole team, including non-engineers, can now ship end to end reliably.\n\n<https://youtu.be/P9e-5Mg72fc>\n\n**The problem**\\\nSoftware is built by teams. But AI coding agents run alone on one developer’s IDE or terminal.\\\nThe result: teammates are out of sync, planning stays buried in docs, and reviewers approve changes with little context. Execution has never been faster. But coordination has never been more painful. \\\n\\\nThe SDLC was built around coding. Coding has changed, and the SDLC must be updated.\\\n\\\n**The solution**\\\nLightsprint makes agentic software development collaborative. It completes the entire AI loop - not just code gen, but the full cycle from requirements to shipped code, with your whole team in the game.\n\n1. **Visual Plan Mode**: Write a simple requirement. Lightsprint breaks it into a structured plan with tasks, dependencies, and visual options to choose from. Your whole team collaborates with the agent on the plan: see it, annotate it, and approve it. No more blind execution.\n2. **Infinite Parallel Cloud Agents**: Hit execute and Lightsprint spins up multiple agents working your codebase simultaneously. One’s building the frontend component, another is building a dashboard, a third is writing tests. Anyone can steer the agent. What takes a team days gets compressed into hours.\n3. **PR Preview Environments**: Every PR automatically gets a live preview URL. Not a diff. A running instance of the code. Your designer clicks through it and says “yes, ship it” or “change the layout” without reading a single line of code. Everyone on your team ships code now.\n\nWe’ve been using Lightsprint to build Lightsprint, and it has dramatically increased our engineering velocity. Lightsprint is also mobile-friendly so you can fire tasks from wherever you are. That has been a game-changer for us!\n\n\\\n**About Us**\\\nThe team is made of Ben Chan who was the previous CTO of Bitgo (NYSE: BTGO) and has led engineering teams of 300; Heng Hong, an engineering leader from Meta who built FB messenger; and Ben Ong, an ex VC who was part of the venture building arm at Temasek (300B AUM fund) and led products at SEA group (NYSE: SE). \n\n\\\n**Ask**\\\nIf you're shipping with AI agents and want to improve coordination, accelerate feature development, or let non-technical teammates help build — we'd love to chat. Book a demo on <https://lightsprint.ai>",
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        "full_name": "Julius Lipp",
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    "id": 31373,
    "name": "Atrisa",
    "slug": "atrisa",
    "former_names": [
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      "Refortifai",
      "Atrisa (formerly Refortifai)"
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    "website": "https://atrisa.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "AI Agents to build, debug and automate analog circuit design",
    "one_liner": "AI Agents for Analog Circuit Design",
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    "launched_at": 1774743443,
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        "full_name": "Sayan Mitra",
        "title": "Founder/CEO",
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        "id": 115582,
        "title": "Founding Analog Design Engineer",
        "url": "https://www.ycombinator.com/companies/atrisa/jobs/bQRwY6B-founding-analog-design-engineer",
        "location": "Bengaluru, KA, IN",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Electrical",
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        "visa": "US citizenship/visa not required",
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      {
        "id": 115583,
        "title": "Founding AI / ML Engineer",
        "url": "https://www.ycombinator.com/companies/atrisa/jobs/we9oeZy-founding-ai-ml-engineer",
        "location": "Bengaluru, KA, IN",
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        "id": 102384,
        "title": "Atrisa: Agents for Analog Circuit Design",
        "tagline": "Enabling analog circuit designers to tokenmaxx",
        "body": "Hello World!\\\nWe are [Sayan Mitra](https://www.linkedin.com/in/sayanmitra9/), [Atman Kar](https://www.linkedin.com/in/atman-kar/) and [Rithik Jain](https://www.linkedin.com/in/rithik--jain/), the team behind Atrisa!\n\nWe are launching **Atrisa**, an AI agent for analog circuit design - enabling analog circuit designers to tokenmaxx!\n\nAtrisa is the AI-native way to build analog circuits.\n\nRight now, frontier LLMs struggle making analog circuits. Designing industry grade analog circuits relies on “tribal knowledge” and internal company data - which LLMs have never seen.\n\nAtrisa has internalized the intuition of an analog engineer - enabling you to design, understand, and debug analog circuits with natural language!\\\n[https://youtu.be/YupbVdchblk](https://youtu.be/YupbVdchblk?si=HJebBGL3UqALNAXh)\n\n\\\nAtrisa hierarchically reasons about your circuit, finds the right topologies to match your specifications, and does deep-dive debugging and experimentation.\n\nIt takes into context everything an analog engineer would need: Reusability across older designs, possible interference, parasitics, and physical layout context. It can talk to other instances, so you don't get blocked by another engineer’s availability.\n\nAlong with providing a modern chat-based interface, Atrisa fits seamlessly into your existing workflows. You can bring your existing toolkit, PDKs, design docs, and Atrisa will understand and adopt.",
        "url": "https://www.ycombinator.com/launches/QdM-atrisa-agents-for-analog-circuit-design",
        "votes": 13,
        "created_at": "2026-06-02T16:20:45.709Z"
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    "id": 31380,
    "name": "Superlog",
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      "Deepengage",
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      "Singlevox",
      "deep engage",
      "Pulsent"
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    "website": "https://superlog.sh/",
    "all_locations": "Paris, Île-de-France, France",
    "long_description": "Sentry and Datadog dump a stream of alerts. Most are duplicates, most lack context, and you still have to solve the issue yourself.\r\n\r\nSuperlog is AI-native observability that's meant not to be opened. A wizard scans your repo and installs proper OpenTelemetry instrumentation, then runs daily to keep up as you ship new code. When something breaks, Superlog groups the errors into a single incident, investigates with full context (logs, traces, recent deploys, past Slack threads), and posts one mergeable PR in Slack. You merge it, ignore it, or open it as a Claude Code session and modify it.\r\n\r\nTelemetry is vendor-neutral, so you keep every log, trace, and metric we install, even if you leave.",
    "one_liner": "Make software self-healing",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1775225049,
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      "Open Source",
      "Kubernetes",
      "Enterprise Software",
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      "Europe"
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    "country": "FR",
    "linkedin_url": "https://www.linkedin.com/company/superlogyc",
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      "url": "https://www.ycombinator.com/people/david-lieb"
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      {
        "user_id": 1660276,
        "full_name": "Nicolò Magnante",
        "title": "Founder/CEO",
        "founder_bio": "ex-BCG, math olympiad winner, scaled two startups to millions in ARR. now working to make the world bug-free.  \n\nlife goals:\n1 - build a decacorn\n2 - get italy to top 5 ww gdp\n3 - win an oscar",
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        "linkedin_url": "https://www.linkedin.com/in/nicolo-magnante/",
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        "user_id": 2807293,
        "full_name": "Arseniy Shishaev",
        "title": "Founder/CTO",
        "founder_bio": "Co-founder and CTO of Superlog, previously co-founder & CTO at Bluco (top 40 startup in France in 2025). CS @ École 42 Paris '22, built data pipelines and tooling at Datadog. National olympiad winner in high school, electronics and hardware nerd, coding interview prep & first aid volunteer.",
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        "linkedin_url": "https://linkedin.com/in/arseniy-shishaev",
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      {
        "id": 101239,
        "title": "Superlog: The self-installing observability tool that fixes your bugs",
        "tagline": "A wizard sets up your telemetry every day. An agent investigates incidents and ships mergeable PRs.",
        "body": "Hey YC! We're Nicolò and Arseniy, co-founders of Superlog ([superlog.sh](https://superlog.sh/)).\n\n**TL;DR:** Superlog is the observability tool you're not supposed to open. A wizard scans your repo and instruments it with OpenTelemetry, and re-runs daily to keep your logs, alerts, and dashboards in sync with your code. When something breaks, an agent investigates with full context and posts one mergeable PR per incident into Slack.\n\n<https://www.youtube.com/watch?v=AeX3pnHCMHg>\n\n## **The Problem**\n\nArseniy spent years at Datadog, getting paged during the night to debug production incidents. In our first startups, we tried Sentry, Datadog, Grafana, Dash0, and nothing was good enough. \n\n* **Setup never ends.** Proper telemetry takes days of manual work and breaks the moment you ship new features. Half the dashboards end up empty or outdated.\n* **Alert fatigue is constant.** Sentry floods Slack with duplicates and no context. The Saturday #ops ping is the worst feeling of the week.\n* **The bill climbs.** Datadog invoices keep growing while engineers still spend hours configuring dashboards, chasing three AWS metrics that disagree, and copy-pasting stack traces into Claude at 11pm.\n\n## **Our Solution**\n\n**1. Telemetry that sets itself up.** Tell your agent:\n\n```\nRun npx skills add superloglabs/skills --all and use the skills to install Superlog in this project\n```\n\nThis skill instruments your code with native OTel SDKs: proper semantic conventions, service and environment tagging. We cover all failure modes, endpoint performance, usage per tenant, and LLM/upstream cost (by callsite, tenant, and model). We run observability check-ins that keep adding logs, alerts, and dashboards as your code grows.\n\n**2. An agent that investigates and ships PRs.** Errors get prioritised and grouped into incidents. The agent investigates with full context (logs, traces, metrics, recent deploys) and either produces a short tested PR, or posts its findings and pulls in the engineers who own the system (based on docs, prior investigations, Slack threads). One mergeable PR per incident in Slack. Merge it, ignore it, or open it as a Claude Code/Codex session and tweak.\n\n**3. No alert fatigue.** Our custom eval setup makes sure incident summaries in your #ops channel are dense and correct, with severity and impact upfront. Every LLM-enhanced metric ships with a confidence score, so wrong guesses don't get boosted.\n\nThe telemetry you get is vendor-neutral: you keep all the OTel logs, metrics, and traces we install, even if you choose to switch providers.\n\n## **Where We're Going**\n\nEvery engineering team in the world burns nights and weekends debugging production. We want to delete that loop. Observability should install itself, alert intelligently, and fix what it can.\n\n## **About Us**\n\n* **Nicolò (CEO)** — ex-BCG, math olympiad winner, scaled two startups to millions in ARR, with international enterprise contracts at Bluco (McDonald’s, Volkswagen, Dufry, etc).\n* **Arseniy (CTO)** — coding since 12yo, won school olympiads, worked on high-performance data systems at Datadog and built engineering teams from scratch at Bluco.\n\n![uploaded image](/media/?type=post&id=101239&key=user_uploads/1660276/b630a0c3-d186-4f4c-95c0-6832f7893f47)\n\n## **Our Ask**\n\nWe'd love intros to:\n\n* Engineering leaders drowning in Sentry alerts or Datadog bills\n* Startups that rolled their own observability and want to throw it away\n\n**Try it:** [superlog.sh](https://superlog.sh/)\\\n**Email:** [nicolo@superlog.sh](mailto:nicolo@superlog.sh)",
        "url": "https://www.ycombinator.com/launches/QKt-superlog-the-self-installing-observability-tool-that-fixes-your-bugs",
        "votes": 69,
        "created_at": "2026-05-12T14:37:58.734Z"
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    "id": 31421,
    "name": "Lamina Labs",
    "slug": "lamina-labs",
    "former_names": [
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    "website": "https://laminalabs.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Lamina Labs is building infrastructure for near-real-time structured video generation.\r\n\r\nMost AI video is built for cinematic clips. Lamina is built for useful videos that break down ideas, workflows, and AI answers. Our first product, Simi, turns prompts and documents into whiteboard-style explainer videos in seconds",
    "one_liner": "Near-real-time video infrastructure for LLMs",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1773199517,
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    "nonprofit": false,
    "batch": "Spring 2026",
    "status": "Active",
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      "America / Canada"
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    "stage": "Early",
    "app_video_public": false,
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    "url": "https://www.ycombinator.com/companies/lamina-labs",
    "api": "https://devasheeshg.github.io/yc-api/batches/spring-2026/lamina-labs.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/lamina-labs/about/",
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    "primary_partner": {
      "name": "Pete Koomen",
      "url": "https://www.ycombinator.com/people/pete-koomen"
    },
    "founders": [
      {
        "user_id": 2592448,
        "full_name": "Sudip Rokaya",
        "title": "Founder/CEO",
        "founder_bio": "Sudip is co-founder of Lamina Labs, building the video infrastructure for LLMs. He studied CS and Math at MIT and did ML research at MIT's McGovern Institute. He represented Nepal at the International Olympiad on Astronomy & Astrophysics as his team's top scorer, and has published two math papers.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/sudip-rokaya-675604279/",
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      },
      {
        "user_id": 1099724,
        "full_name": "Kartikesh Mishra",
        "title": "Founder/CTO",
        "founder_bio": "Co-founder of Lamina Labs (YC P26) | EECS @ MIT BSc' 24 MEng' 25 ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/mk314k/",
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      {
        "id": 104668,
        "title": "Simi: The Fastest AI Whiteboard Explainer Video Generator",
        "tagline": "The Fastest Way to Generate Whiteboard Explainer Videos from a Single Prompt or Documents",
        "body": "**TL;DR:** Simi is the fastest, easiest, and most cost-effective way to create whiteboard explainer videos. You give it a prompt or a document. It writes the script, draws the illustrations, animates them, adds narration, and hands you a finished video in seconds. Anything from a one minute short to a full hour, in one shot, in 80+ languages. Built by Lamina Labs (YC P26). Use it through the app or the API for training, onboarding, product walkthroughs, sales, marketing, and education at <https://laminalabs.ai>.\n\nHere is an explainer video about Lamina Labs: <https://www.youtube.com/watch?v=RLuOCdamcHE>\n\n## Why we built this\n\nAI video right now is built to look like a movie, not to explain something.\n\nBut most of the video people actually need at work is the boring kind. A training module. An onboarding flow. A walkthrough of the feature you shipped last week. And making one of those is absurdly slow. You either pay an agency thousands of dollars and wait weeks, or you sit in a template editor dragging boxes around for an afternoon and it still looks like you dragged boxes around.\n\nThat is fine if you need one video. It falls apart the moment you need a hundred. A course. Every feature documented. Onboarding in every language your customers speak. Anyone who has priced that out knows the math does not work.\n\n## How it works\n\nYou type what you want. Simi writes the script, draws and animates it, and gives you a properly narrated video in seconds.\n\nThat is the whole thing. No storyboard, no timeline, no boxes to drag. Type \"explain how photosynthesis works,\" or hand it a long compliance doc, and you get a finished video, not a draft. And it does not choke on length. One minute to a full hour, generated in a single shot.\n\nIf your team makes videos, you should be using this.\n\n## What people make with it\n\nTraining and onboarding videos from the docs you already have. Product walkthroughs, one per feature, updated as fast as the product changes. Sales and marketing explainers, in every market you sell into. Course and lecture videos in the Khan Academy style. Faceless YouTube channels and localized social video at volume. Agencies run it through the API to produce explainer videos for their clients.\n\n## What makes it different\n\nAn agency gives you a video in weeks for thousands of dollars. Simi gives you the same video in seconds for a fraction of that. That is the whole pitch, and it is enough.\n\nA few things worth knowing beyond speed. It generates anything from a minute to an hour in one shot. It speaks 80+ languages, so you write once and localize everywhere. And it is built to plug in. Use the app, call the API from your own product, or run it inside agent frameworks like OpenClaw and Nous Research's Hermes.\n\n## Who we are\n\nWe are Sudip and Kartikesh, the founders of Lamina Labs, and Simi is the first thing we have built. We are both from Nepal. We met at MIT and started building together there. We are the first Nepalese founding team to go through YC.\n\nSimi is named after Simikot, the Himalayan village where Sudip grew up. We started with education because that is where this problem hurt us personally. But it is everywhere. Any time someone needs to turn an idea into a clear picture, that is us.\n\n![uploaded image](/media/?type=post&id=104668&key=user_uploads/2592448/ddd4246e-1dae-4302-8e33-7c51d0264d6b)\n\n## Our asks\n\nIf your team spends real money or real time making explainer, training, or onboarding videos, talk to us: [founder@laminalabs.ai](mailto:founder@laminalabs.ai)\n\nWe would love intros to L&amp;D leaders, to agencies making video at volume, and to founders who want video generation inside their own product through the API.\n\nAnd if you just want a video explaining your own startup, **try it:** <https://app.laminalabs.ai> \\\n**Learn more:** <https://laminalabs.ai>",
        "url": "https://www.ycombinator.com/launches/REC-simi-the-fastest-ai-whiteboard-explainer-video-generator",
        "votes": 32,
        "created_at": "2026-07-04T06:24:17.819Z"
      }
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  },
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    "id": 31429,
    "name": "Oddpool",
    "slug": "oddpool",
    "former_names": [
      "Oddpool",
      "Benchspan"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cbb613ad9cc7cb217457623774de2039f44ba7d6.png",
    "website": "https://www.oddpool.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Oddpool is a platform that helps quant funds and trading desks harness the power of prediction markets.\r\n\r\nAvi and Ritesh have been roommates since freshman year at Georgia Tech. Avi has a Master's in ML and saved Microsoft $6M/year by building a more accurate model on half the hardware. Ritesh has a Master's in Distributed Systems and made buy-side trading systems at Bloomberg 40% faster.",
    "one_liner": "Institutional infrastructure for prediction markets",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1773859660,
    "tags": [],
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Spring 2026",
    "status": "Inactive",
    "industries": [
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      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
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    "url": "https://www.ycombinator.com/companies/oddpool",
    "api": "https://devasheeshg.github.io/yc-api/batches/spring-2026/oddpool.json",
    "year_founded": 2026,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/oddpool/",
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    "primary_partner": {
      "name": "David Lieb",
      "url": "https://www.ycombinator.com/people/david-lieb"
    },
    "founders": [
      {
        "user_id": 1579438,
        "full_name": "Ritesh Malpani",
        "title": "Founder/CEO",
        "founder_bio": "Founder, CTO @ Oddpool | Prev. SWE @ Bloomberg\nArchitected systems processing 100K+ TPS across trading infrastructure\n\nCS @ Georgia Tech\n",
        "is_active": false,
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        "full_name": "Avi Arora",
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    "long_description": "Coding agents like Claude Code, Codex and Cursor now decide which tools get installed in a codebase. Armature runs the real agents inside a panel of realistic repositories, measures whether they pick you, and works with your team on the docs, SDK and content that make them choose you.\r\n\r\nWe call this Agent-Led Growth (~coding agents GEO for dev tools).\r\n\r\nAnd once agents use your product, Armature shows you what users do with it through AI, with self-serve MCP analytics and evals that catch regressions before your users see them.",
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        "full_name": "Louis Scremin",
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        "id": 101594,
        "title": "Armature - Making your app finally usable by AI agents",
        "tagline": "Armature helps companies monitor, analyze, and optimize how AI agents experience their products.",
        "body": "Hey everyone, we’re [Theodore](https://www.linkedin.com/in/theodore-otzenberger-895345131/) and [Louis](https://www.linkedin.com/in/louis-scremin/) - Co-Founders of [Armature](https://armature.tech/) 👋\n\n### TL;DR\n\n**Armature helps companies monitor, analyze, and optimize how AI agents experience their products.**\n\n* We discover your product through MCP and CLI, **run the real workflows your customers’ AI agents do** and let you finally see your customers’ agents thinking **traces**.\n* We provide analytics, run **benchmarks**, and turn this into **concrete actions** to improve your MCP and CLI.\n* This is only the beginning: we are reinventing the building blocks of the ~~User~~ **Agent Experience**.\n\n**_The Ask:_** _If you are building a product that is increasingly used by AI agents or if you want to ensure agents can use your product but don’t know where to start, we’d love to hear about your challenges! You can also try our product self-serve **for free** directly at [armature.tech](http://armature.tech)._\n\n<https://www.youtube.com/watch?v=3Gtc5RzGxJ0>\n\n### ❌ The Problem: The Missing Agent Experience (AX)\n\nWe have 30 years of tooling to optimize User Experience (UX), from session replays and funnel analytics to live support chat. But as products are increasingly operated by **AI agents** rather than humans, we lack the equivalent tooling for **Agent Experience (AX)**.\n\nRight now, companies have **zero visibility** into how each agent (Claude, Codex, ChatGPT, OpenClaw, etc.) interacts with their products. And when a bad AX causes an agent to fail silently, the end-user simply churns.\n\nBut it goes deeper. As agents become the primary users, the fundamental mechanics of software products simply stop working. Because if a human isn’t looking at the screen:\n\n* _How do you upsell a premium feature to an AI?_\n* _How do you build brand loyalty with a user that doesn’t feel emotions?_\n* _How do you offer customer support when an agent fails?_\n\nWe are building Armature to solve these exact problems and so many more questions related to this shift!\n\n### 💡 Our Solution: Armature\n\nArmature helps companies monitor, analyze, and optimize how AI agents experience their products.\n\n**What we do today:**\n\n* **Automated testing:** We run complex sessions against your MCPs/CLIs across all major harnesses and models to catch broken workflows before your users do.\n* **AX analytics &amp; benchmarking:** No more black boxes. We trace agent sessions to show you exactly what the model \"thought\", what context it missed, and why it failed. We measure your AX against competitors to ensure you remain the preferred platform for agents to use.\n* **Auto-remediation:** Our MCP lets your internal coding agents plug into Armature to autonomously fix your product's AX based on our run data.\n\n![uploaded image](/media/?type=post&id=101594&key=user_uploads/3408440/5642c5dd-a3b1-46e1-865d-a0425ceba1d5)\n\n**Our vision for tomorrow:**\n\nReaching full understanding of how agents use your product and how you can improve it is only step one. \n\nThe next step is to provide the **foundational infrastructure for the Agent Experience**, powering agent-native revenue, lifecycle marketing, and customer support for the next generation of software.\n\n### 🙏 Our Ask: If you’re building apps for agents, let’s talk!\n\n1. **Audit your MCP or CLI:** If you are building for agents, you can start by running your first audit &amp; benchmark on [**armature.tech**](http://armature.tech) **for free** to see how they actually experience your app.\n2. **Let’s chat:** If you are facing challenges to make your app usable by agents or optimize the agent experience, please reach out to [**founders@armature.tech**](mailto:founders@armature.tech). We’d love to discuss and help you with this!\n\n### 👬 The Team: why we are working on this\n\nBefore founding Armature, Louis scaled **AI agents at Joko, a 6M user consumer app**. Theo was a **FDE at Palantir** and then built petabytes-scale **observability** from scratch as a Founding Engineer at Tsuga, a Datadog spin-off.\n\n**Blindly shipping a self-tested MCP to 6M of edge cases drove us crazy so we decided to build the solution.**\n\n![uploaded image](/media/?type=post&id=101594&key=user_uploads/3408440/bdb32e65-c048-467e-aa62-0e67c8f1fff7)\n\n",
        "url": "https://www.ycombinator.com/launches/QQc-armature-making-your-app-finally-usable-by-ai-agents",
        "votes": 25,
        "created_at": "2026-05-19T20:45:48.490Z"
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        "id": 101949,
        "title": "TesterArmy: Test your app with natural language",
        "tagline": "Automated testing for web and mobile apps",
        "body": "Hey everyone [👋\\\n\\\n](https://emojipedia.org/waving-hand)**TL;DR: TesterArmy is an AI-powered QA agent that tests your web or mobile app by actually using it - clicking, typing, navigating like a real user.** \\\n\\\n<https://youtu.be/G4zBvz9ZGac>\n\n### **Launch Day Deal 🚀**\n\nAs part of launch day, we’re offering **30% off every subscription** after [signup](https://tester.army/sign-in) with code: **LAUNCH30**.\n\n### **Problem**\n\nEvery dev team knows they should test more, but writing and maintaining automated tests is painful.\n\nTests take time to build; they break when the UI changes, and when a team is shipping fast, QA is usually the first thing to get skipped.\n\nAnd even when tests pass, they only verify what you explicitly told them to verify. They do not notice confusing flows, broken layouts, misleading copy, or weird UI states that a real user would catch in seconds.\n\n### **Solution**\n\nTesterArmy is an AI agent that **tests your app as a real user would.** You describe what to test in natural language, and the agent clicks, types, and navigates through your app using vision. It catches broken flows, rendering bugs, misleading copy, and confusing UX. No selectors, no scripts, nothing to maintain.\n\nEvery run produces screenshots, recordings, and actionable bug reports. Setup takes minutes: paste your URL or upload a mobile app build, and describe what to test. Done.\n\n![uploaded image](/media/?type=post&id=101949&key=user_uploads/3414052/1f12e0be-1909-4295-b7b0-497898669f63)\n\n### **Meet the team**\n\nWe’re a team of three from Poland 🇵🇱 - [Szymon Rybczak](https://x.com/SzymonRybczak), [Oskar Kwaśniewski](https://x.com/o_kwasniewski) and [Piotr Matyjasik](https://x.com/p_matyjasik). \\\n\\\nSzymon and Oskar have worked closely together for years across **4 companies**, while Piotr and Oskar go even further back, having studied computer science together in Poland. We’ve spent years shipping web and mobile products used by millions, from open source and developer tools to production apps. We came together around a problem we knew firsthand: teams ship fast, but QA still slows everything down.\n\n![uploaded image](/media/?type=post&id=101949&key=user_uploads/3414052/0007b5a1-3c33-4194-b65a-f85dc0f65593)\n\n### **🤝 Our Ask**\n\n**If this is a problem you face, try us out!**\n\n\\- Book a [demo](https://tester.army/meet)\n\n\\- [Sign up now!](https://tester.army/sign-in) We are live and used in production by 20+ companies\\\n\\\n**Thank you! 🙏**\n\nSzymon, Oskar and Piotr",
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        "full_name": "Gus Trigos",
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        "founder_bio": "Gus Trigos is CEO and co-founder of Runtime, the agent harness for payment and risk teams. Runtime powers some of the fastest-growing fintechs in the world like Rain and Finix. He's a two-time YC founder, previously co-founding Mentum (acquired by Nuvocargo), and started his career as a quant at BlackRock's AI Quantitative Investment Group.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/gustavoatrigos",
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      },
      {
        "user_id": 952396,
        "full_name": "Carlos Volante",
        "title": "Founder",
        "founder_bio": "Carlos is the co-founder and CTO of Runtime, with a track record of scaling high-volume financial infrastructure at Modern Treasury, Finix, and Hulu. His experience spans billions in transaction volume, near-perfect uptime, and billing systems for tens of millions of users.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/carlos-volante-49bb86145",
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    "jobs": [
      {
        "id": 114062,
        "title": "Forward Deployed AI Engineer",
        "url": "https://www.ycombinator.com/companies/runtime/jobs/exm704T-forward-deployed-ai-engineer",
        "location": "San Francisco, CA, US / Remote",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "AI engineer",
        "salary_range": "$100K - $200K",
        "equity_range": "0.25% - 1.00%",
        "experience": "1+ years",
        "visa": "Will sponsor",
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      },
      {
        "id": 114063,
        "title": "Founding AI Ops",
        "url": "https://www.ycombinator.com/companies/runtime/jobs/pNjYg79-founding-ai-ops",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Operations",
        "role_type": null,
        "salary_range": "$120K - $165K",
        "equity_range": "0.25% - 0.75%",
        "experience": "3+ years",
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    "news": [],
    "launches": [
      {
        "id": 99699,
        "title": "Runtime - Let your whole team ship safely with coding agents",
        "tagline": "Guardrails and observability for all your coding agents.",
        "body": "**Runtime ([runtm.com](http://runtm.com)) lets your whole team ship safely with any coding agent.** It gives your team the guardrails, sandboxes, context, and visibility to go from idea to PR or deployment, with any model, on any infra.\\\n\\\nOur coding agents set your repo environments automatically:\n\n![uploaded image](/media/?type=post&id=99699&key=user_uploads/362619/2951e500-e6ea-4b0a-99de-287fe024a749)\n\nYou can use Runtime through our web interface:\n\n![uploaded image](/media/?type=post&id=99699&key=user_uploads/362619/a7b5c7bd-7ed7-45fa-9684-cacae9d396fd)\n\nOr anyone on your team can trigger it from Slack, Linear, and many other connectors:\n\n![uploaded image](/media/?type=post&id=99699&key=user_uploads/362619/86c3a4fe-5b77-470b-982b-3a01405a7836)\n\nLaunch video:\\\n<https://www.youtube.com/watch?v=m3H8yUbdIHY>\n\n**The problem**\n\nAfter my last company was acquired, I led our coding agents rollout and personally shipped 4+ full-stack products in the first 3 months. I then started enabling the rest of the team to do the same. But we hit a lot of friction fast: we needed to create working environments, we didn’t have any control or context to ensure agents contributed correctly, and nobody had visibility of what was being shipped. And because we'd gone deep on one provider's tooling, when their reliability dipped, the whole team slowed down.\n\nEveryone rolling out coding agents across their team hits the same walls:\n\n* **No environment setup:** No easy way to give engineering and product teams production-like environments where agents can safely run.\n* **No guardrails:** No access controls, system instructions, or secrets management for agents.\n* **No visibility:** No way to see what agents are doing, what they're changing, or where things break.\n* **Vendor lock-in:** Go all-in on one model provider's agent infra and your whole team is exposed when reliability, pricing, or model quality shifts.\n\nWithout these, you end up either moving slower than your competition or causing major downtimes on your product.\n\n**What we built**\n\nRuntime sits between your team and the coding agents they use. It works with Claude Code, Codex, OpenCode, Gemini, Copilot, and others, and can be called programmatically or used through Slack, Linear, Jira, Asana, Teams, CLI, and more.\n\n\\\nHere's what that looks like in practice:\n\n* **Environment templates:** Import any repo and set up a replica of your environments once. Our agents handle the setup for you, even for monorepos and microservices.\n* **Sandboxed environments:** Anyone on the team can spin up a sandbox in milliseconds with a live preview of your product, make changes with their preferred coding agent, and open a PR.\n* **Configurable guardrails:** System instructions, skills, allowlists, encrypted secrets, and role-based access control for both humans and agents.\n* **Observability:** See exactly what every human and agent is doing across every interaction, down to the tool call and chain of thought.\n* **One-click deploys / PRs:** Anyone can deploy from their sandbox. Coding agents auto-fix build errors and verify the deployment is healthy before it goes live. You control what gets deployed and can roll back or destroy deployments at any time.\n\nRuntime can be fully self-hosted.\\\n\\\nCheck our product demo:\n\n<https://youtu.be/Gqdzfo7a8IM>\\\n\\\n**Asks**\n\n**Use Runtime at your company.** Sign up at [app.runtm.com](http://app.runtm.com). If you're a CTO, head of platform, or eng / product leader rolling out coding agents, our team will personally set up your environments and help you set up best practices to your team is shipping within the first days.\n\n**Book a demo** at <https://cal.com/gustavo-trigos-q80bop/runtime-demo-meeting>\n\n**Upvote this** and connect with me to follow the journey:\n\n* <https://www.linkedin.com/in/gustavoatrigos/>\n* <https://x.com/gustrigos>",
        "url": "https://www.ycombinator.com/launches/Pw3-runtime-let-your-whole-team-ship-safely-with-coding-agents",
        "votes": 29,
        "created_at": "2026-04-13T22:39:14.227Z"
      }
    ]
  },
  {
    "id": 31547,
    "name": "InsForge (InstaCloud)",
    "slug": "insforge-instacloud",
    "former_names": [
      "InsForge"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/de52713fe1552551dbe8aa2a5e60202c09bfc0d7.png",
    "website": "https://insforge.dev/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "InstaCloud is the agent-native serverless cloud: deploy any code or service instantly, with automatic scaling and zero DevOps required.",
    "one_liner": "The agent-native serverless cloud",
    "team_size": 6,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1776234676,
    "tags": [
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      "DevSecOps",
      "Cloud Computing",
      "Infrastructure"
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    "isHiring": false,
    "nonprofit": false,
    "batch": "Spring 2026",
    "status": "Active",
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    "regions": [
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      "America / Canada"
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    "stage": "Early",
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/insforge-instacloud",
    "api": "https://devasheeshg.github.io/yc-api/batches/spring-2026/insforge-instacloud.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/insforge/",
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    "primary_partner": {
      "name": "Andrew Miklas",
      "url": "https://www.ycombinator.com/people/andrew-miklas"
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    "founders": [
      {
        "user_id": 967495,
        "full_name": "Hang Huang",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder & CEO at InsForge (YC P26). Ex-Amazon PM, Yale MBA. Former professional League of Legends player.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/hang-huang-oliver",
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      },
      {
        "user_id": 2376097,
        "full_name": "Tony Chang",
        "title": "Founder",
        "founder_bio": "Co-founder & CTO at InsForge. Previously Software Engineer at Databricks(Networking Infra). \nInterned @ Meta(Ads ML Infra) & Amazon(Backend Infra) \n\nHackathon Addict :) 10x Wins + 9x judge",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/tony-chang-0430/",
        "x_url": "https://x.com/tonychang430",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d9ae957713ee880ded3c7c44a66eb2110e1fd999.jpg"
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    "launches": [
      {
        "id": 101500,
        "title": "InsForge: The backend platform for AI-native developers",
        "tagline": "Let your coding agent deploy, operate, and debug your backend end-to-end",
        "body": "Hey YC! We’re [Hang Huang](https://linkedin.com/in/hang-huang-oliver) and [Tony Chang](https://www.linkedin.com/in/tony-chang-0430/) from [InsForge](https://insforge.dev/).\n\n**TL;DR:** InsForge lets your AI coding agent deploy and operate the full backend (servers, database, auth, storage, and more) from one consistent CLI. Instead of stitching together separate tools and dashboards, your agent manage entire backend infrastructure end-to-end.\n\n<https://youtu.be/7Bax5qz0IfM>\n\n**The Problem**\n\nThe way software gets built is changing fast. Coding agents are now the primary builders, but every backend platform today was designed for human developers, with dashboards, manual configs, and workflows that require a person at every step.\n\nWe tried MCP servers like Supabase, Vercel, GitHub, and Context7, but kept running into the same problems: tools bloated the context window, payloads came back at 10K+ tokens, and core backend state like telemetry, configs, logs, and runtime behavior still wasn’t accessible in a way agents could reliably use.\n\n**Our Solution**\n\nSo we built InsForge as one backend platform your coding agent can actually operate. Install our CLI and Skills with one command, and your coding agent can build, run, debug, and scale full-stack apps end to end on InsForge.\n\nEvery primitive returns structured outputs and readable errors the agent can act on. And because agents make mistakes, branching, scoped permissions, and reversible writes let you review or discard changes safely.\n\n**Where We're Going**\n\nWe believe that coding agents won’t stop at writing code. They’ll run your entire application and infrastructure autonomously as well. For that to work, backend infrastructure needs to become agent-native: CLI-first, observable, permissioned, reversible, and designed around agents as operators.\n\n**About Us**\n\n![uploaded image](/media/?type=post&id=101500&key=user_uploads/967495/90d7cdcf-0682-408c-bf3c-c5f192edf89b)\n\n* **Hang (CEO)** — ex-Amazon PM, previously professional League of Legends player.\n* **Tony (CTO)** — ex-Databricks network infrastructure engineer.\n\n**Our Ask**\n\n1. **Try it and break it**: [**insforge.dev**](http://insforge.dev). If you found there’s anything missing or you think some features are poorly designed, let us know! We read every piece of feedback. We’re also open source, here’s our [**GitHub repo**](https://github.com/InsForge/InsForge).\n2. **Design partners**: if you want your coding agent to handle everything, and believe that’s the future, drop a comment or email [**founders@insforge.dev**](mailto:hang.huang@insforge.dev). We'll get you set up directly.\n3. **Intros:** we're a day-0 infra company, so we need to find top developers before they get locked in elsewhere. If you know any developers or founders just / about to get started, we’d love an intro!",
        "url": "https://www.ycombinator.com/launches/QP6-insforge-the-backend-platform-for-ai-native-developers",
        "votes": 33,
        "created_at": "2026-05-18T15:39:09.065Z"
      }
    ]
  },
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    "id": 31557,
    "name": "Amorphic Labs",
    "slug": "amorphic-labs",
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    "website": "https://www.agentmuxer.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "The next billion software users are AI agents, yet agents still can't act on their own: every paid tool they need runs through a human making accounts, managing API keys, and guessing which provider is best. We are the capability marketplace built for agents: one MCP and one balance through which agents find, pay for, and use APIs, data, skills, other agents, and software at runtime, with every request routed to the best provider based on benchmarks from real tasks and outcome feedback from the agents themselves.",
    "one_liner": "OpenRouter for Agent Tools",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1785536963,
    "tags": [
      "Marketplace",
      "B2B",
      "AI"
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    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2026",
    "status": "Active",
    "industries": [
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      "Engineering, Product and Design"
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    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/amorphic-labs",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/amorphic-labs.json",
    "year_founded": 2026,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/amorphic-labs",
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    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/d15b721a8d0e299e74b3561f196bb056b93f1fd9.png",
    "app_video_url": null,
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    "primary_partner": {
      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
    },
    "founders": [
      {
        "user_id": 2352421,
        "full_name": "Dylan Kelly",
        "title": "Founder/CEO",
        "founder_bio": "Founder & CEO @ Amorphic Labs. CS @ Georgia Tech, prev. Quant Trading intern @ UBS. World Schools Debating Championship 2022 finalist & 8th best speaker, 2x National Team Debater, co-author of NeurIPS paper.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/dylankelly04/",
        "x_url": "https://x.com/dylanpkel",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/59de0da571ebd5d687beb82c703b9a0283c8df2f.jpg"
      },
      {
        "user_id": 2599670,
        "full_name": "Frank Li",
        "title": "Founder/CTO",
        "founder_bio": "Founder & CTO @ Amorphic Labs. Prev. Member of Technical Staff & Project Lead @ OpenAI, Auto-vehicle ML infra @ NVIDIA, Quant Dev @ Two Sigma, and Amazon. First open-source contribution at 15. CS @ UW Seattle.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/anglifrank",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/66c1679cfcd65063496dd8ef47dc43e9aaadaa3b.jpg"
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    ],
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    "launches": [
      {
        "id": 112178,
        "title": "Agentmuxer by Amorphic Labs - OpenRouter for Agent Capabilities",
        "tagline": "One MCP and one wallet for agents to find, pay for, and use the best tools for any task",
        "body": "**tl;dr: OpenRouter became the router for model spend; we're building that layer for agent capabilities, starting with paid tools: web search, scraping, extraction, enrichment, and more from top providers in each category. No provider accounts or API keys, one balance, pay per use. We benchmark every provider on real tasks and route each request to the one that performs best, with fallbacks when a provider fails. We're looking for early users to try it out with free credits, email us at [founders@amorphiclabs.com](mailto:founders@amorphiclabs.com) if you want to check it out!**\n\n**Launch Video:**\n\n<https://youtu.be/-dxc8ZAUfFc>\n\n**The problem:**\n\nAgents can only use the tools a human wired up in advance, and they won't tell you what they're missing: they quietly make do, failing at anything they weren't hand-equipped for. Even when you do the wiring, you're picking blind: nobody actually knows which search API is better for this query, or which scraper will survive this site. The \"best setup\" frontier moves daily, so keeping up means hours of trawling MCP directories, X threads, and blog posts. Agents stay only as capable as their setup, and the more autonomous they get, the more that ceiling costs.\n\n**What we do:**\n\nYour agent asks for what it needs (\"structured data from this page\", \"research this with citations\"). We route the request to the best provider for that specific task, based on benchmarks on real tasks and outcome feedback from the agents using them: success rates, result quality, latency, and cost. If a provider fails, we cascade to the next, so your agent gets a result instead of an error. Every request makes the routing smarter. One balance pays for all of it, and it's the same MCP whether it's your own coding agent or agents you're shipping in a product.\n\nAPIs are just the start. The same marketplace will let agents acquire skills, hire other agents for specialized tasks, and sign up for software directly through MCPs, all from one balance.\n\n**Our team:**\n\nWe're Frank and Dylan, friends of 10 years who have been building together since middle school. Frank was a Member of Technical Staff at OpenAI and interned at Two Sigma, NVIDIA, and Amazon. Dylan was a quant trading intern at UBS, co-authored a NeurIPS paper, and was a grand finalist and 8th-best speaker in the world at WSDC 2022. We built this because we kept hitting the problem ourselves: agents stuck mid-task waiting for us to make accounts and guess at providers.\n\n**Our ask:**\n\n1. Want to be an early user? Email us at [founders@amorphiclabs.com](mailto:founders@amorphiclabs.com) and we'll onboard you with free credits.\n2. If you sell an API, dataset, or agent-facing service and want agents as customers, we'd love to talk about listing you. Email us at [founders@amorphiclabs.com](mailto:founders@amorphiclabs.com)\n3. If you want more information or want to join the waitlist, check out [agentmuxer.com](http://agentmuxer.com)\n\n_Make something agents want!_",
        "url": "https://www.ycombinator.com/launches/TBK-agentmuxer-by-amorphic-labs-openrouter-for-agent-capabilities",
        "votes": 13,
        "created_at": "2026-08-25T19:30:05.588Z"
      },
      {
        "id": 108806,
        "title": "Amorphic Labs - Agentic, Personalized Product Demo Videos for Sales",
        "tagline": "AI agents that create personalized demos at scale for outbound, inbound, and call follow-ups without your team recording a thing.",
        "body": "**tl;dr: We build AI agents that create personalized product demo videos for outbound, inbound qualification, and post-call follow-ups. Just give us a demo account for your app and a list of prospects, and our agent researches each prospect, uses its own computer to record a tailored workflow in your app with seeded personalized data, then edits and narrates the video so it is ready to send as a link to each prospect.**\n\n**Launch Video:**\n\n<https://youtu.be/uq9LyHYYyOU>\n\n**Our Ask:**\n\n* If you’re a founder or part of a startup that sells software, we can help you give every prospect a tailored product experience while saving your team hours of recording time. Book a demo at [amorphiclabs.com](http://amorphiclabs.com)!\n* If you know any sales or RevOps leaders, we would love introductions or referrals to them.\n\n**The Problem:**\n\nRecording a personalized product demo is one of the clearest ways to communicate your value and show someone how your product solves their problems, but preparing a demo environment, seeding data, and recording a high-quality video for every prospect takes too long. As a result, teams skip personalized demos in situations where they could be highly effective, such as outbound, and spend hours every week creating them for inbound requests and post-call follow-ups. This means teams miss opportunities to show prospects exactly how their product fits their needs, while wasting hours that could have been spent talking to and selling to prospects.\n\n**The Solution:**\n\nWe use AI agents to create personalized product demo videos at scale, bringing tailored demos to parts of the sales process where they were previously too time-consuming to produce. All you need to provide is a demo account for your app and a list of prospects.\n\nOur agent then:\n\n* Learns and interacts with your app on its own computer like a real sales engineer.\n* Researches each prospect to determine which workflow and data best fit their needs.\n* Seeds personalized data in your app.\n* Records itself completing the relevant workflow.\n* Edits the video to remove long waits and adds effects such as zooms.\n* Narrates the video with a script tailored to the prospect.\n* Gives you a finished video link ready to send.\n\nYou remain fully in control of how the videos are created: you can clone your own voice, define the workflows the agent can choose from, control the narration style and how each video begins and ends, and regenerate videos by giving the agent feedback.\n\n**Sample video our agent generated:**\n\n<https://youtu.be/QONd3u3NoGo>\n\n**Where you can use it:**\n\nTailored Outbound: You can import a list of leads you want to reach out to and ask our agent to create personalized demos for each one, showing prospects exactly how your product fits their needs through data, workflows, and narration tailored directly to them.\n\nQualifying Inbound: Add a request-a-demo form to your landing page so prospects who are not yet convinced enough to spend 30 minutes on a discovery call can spend 20 seconds requesting a personalized demo video and receive an email showing exactly how your product solves their problems.\n\nCall Follow-ups: After understanding a prospect’s key use cases and pain points during a discovery call, you can create multiple personalized demo videos showing how you address their needs. You can even create additional videos tailored to different stakeholders that your champion can use to sell your product internally.\n\nWe are initially focused on sales, but the same technology can also create walkthrough videos for onboarding, customer support, and documentation.\n\n**Our team:**\n\nWe have been best friends for close to a decade, have competed together in competitions spanning math, debate, pitching, business, and hackathons, built countless projects, and are now building Amorphic Labs together.\n\nFrank worked as a software engineer for three years while graduating from UW. He was a Member of Technical Staff at OpenAI and previously interned at Two Sigma, NVIDIA, and Amazon.\n\nDylan was a quantitative trading intern at UBS and recently graduated from Georgia Tech. He represented Team China twice at WSDC, was a grand finalist and the eighth-best speaker in the world in 2022, and co-authored a paper published at NeurIPS.\n\n**If you sell software and want to see what our agent could create for one of your prospects, book a demo at [amorphiclabs.com](http://amorphiclabs.com).**",
        "url": "https://www.ycombinator.com/launches/SIw-amorphic-labs-agentic-personalized-product-demo-videos-for-sales",
        "votes": 33,
        "created_at": "2026-08-03T21:11:17.469Z"
      }
    ]
  },
  {
    "id": 31570,
    "name": "Rindler",
    "slug": "rindler",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ba85eb3919f954ce9bf661f9b9ee195327c93ceb.png",
    "website": "https://maxxwell.dev",
    "all_locations": "Boston, MA, USA",
    "long_description": "We build Maxxwell, a desktop app for people who run several coding agents at once.\r\n\r\nPast two or three sessions, you become the bottleneck. Every session asks you something, most of it small, and you spend the day answering instead of deciding. It is also hard to tell which sessions are making progress, which are stuck on something trivial, and which have quietly started building the wrong thing.\r\n\r\nMaxxwell puts every session in one window and marks each one working, idle, or waiting on you. On top of that sits an orchestrator, a real coding-agent session of its own that reads the others and reports back. You talk to it instead of to twelve terminals. It tells you what landed, what it decided for you, and what actually needs your call.\r\n\r\nEvery worker is your own tool, unmodified. Claude Code, Codex and Cursor Agent run in real terminal sessions you can attach to and take over at any point",
    "one_liner": "The IDE for Tokenmaxxers",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1783408799,
    "tags": [
      "Developer Tools",
      "SaaS",
      "Infrastructure",
      "AI"
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        "full_name": "Michael Serrano",
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        "full_name": "Arthur De Los Santos",
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        "title": "Rindler - Turn Any Website Into An API For AI Agents",
        "tagline": "Reliable web actions for AI agents, without integrations or scripts",
        "body": "**TL;DR:** Rindler turns websites into deterministic APIs for AI agents. We map a site once into screens, actions, and structured outputs, so agents can read data and take actions quickly and reliably.\n\n**Ask:** If you’re building an agent that needs to browse the web, compare products, fill forms, search listings, use authenticated portals, or act on third-party websites without an API, we’d love to help.\n\n<https://youtu.be/V_nCIxYD-so>\n\n## Problem\n\nMore products are starting to depend on AI agents that can do real work on the web: shop across retailers, pull housing listings, use job boards, submit forms, monitor prices, update back-office systems, and operate inside customer portals.\n\nBut most browser agents still treat every website visit like a new puzzle. On every run, they need to decipher the page, infer what matters, decide what to click, and recover when the page behaves differently.\n\nThat works for demos, but it breaks down in production. Real websites have pop-ups, login gates, cookie banners, bot defenses, slow-loading forms, dynamic filters, fragile dropdowns, layout changes, and pages that look similar but behave differently.\n\nThe result is slow execution, high token cost, and workflows that are hard to trust.\n\n## Solution\n\nRindler maps websites into deterministic APIs for agents.\n\nInstead of forcing an agent to re-explore a site every time, Rindler captures the site as structured screens, available actions, and typed outputs. Agents can then call actions like **search,** **add_to_cart**, or **download_records,** depending on the mapped site.\n\nAt runtime, Rindler handles the browser work through a remote MCP endpoint:\n\n* Returning structured data\n* Applying dynamic filters\n* Managing popups, bot defenses, and layout changes\n* Supporting authenticated flows\n\n## Background\n\nWe started Rindler because “AI agent uses a browser” is compelling, but the current browser-agent loop is too brittle for teams building real products.\n\nIf an agent needs to use the same third-party site hundreds or thousands of times, it should not have to rediscover that site from scratch on every run.\n\nRindler is still a work in progress. Some sites map cleanly, others require more in-depth mappings, and bot-defended or logged-in sites may need a one-time credential or cookie capture.\n\nWe’re looking for feedback from founders building products where reliable web actions are part of the core workflow.\n\nIf there’s a website you wish your agent could use reliably, send it to us!\n\n![uploaded image](/media/?type=post&id=104865&key=user_uploads/3137449/b115d309-9711-4e65-b4c8-bb9b13e0b8b5)\n\n",
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        "full_name": "Ryan Morrissey",
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        "full_name": "Bence Redmond",
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        "founder_bio": "Founder & CTO at Hoplite, prev. AWS",
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        "linkedin_url": "https://www.linkedin.com/in/bence-redmond",
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      {
        "id": 108274,
        "title": "Hoplite - Effortless cloud agents for programming",
        "tagline": "Hoplite runs autonomous coding agents in cloud sandboxes. Spin up tasks manually from Slack, Linear, iMessage, or automatically from Sentry.",
        "body": "Cloud coding agents are painful to set up, lacking ergonomics, and don't allow you to move as fast as possible. We let you bring your local set up to the cloud.\n\n![uploaded image](/media/?type=post&id=108274&key=user_uploads/2563241/28db62de-d65b-4498-84ac-12e2683c65f2)\n\n**The Problem** \n\nIn the next 10 years the best software startups will be those who can effectively deploy tokens. \n\nRight now that's significantly harder than it needs to be. If you’ve ever ran multiple agents locally you immediately know this pain.\n\nLaptop crashes, wrangling gitwork trees, juggling ports, and more headaches.\n\n![uploaded image](/media/?type=post&id=108274&key=user_uploads/2563241/6f320e85-ccbb-4fb4-a5e9-6ec3cb0206c7)\n\nSo cloud is the obvious answer right? \n\nBut setting up with these existing providers is quite a hassle, and oftentimes they miss some key feature that your local config has.\n\n**What we do**\n\nWe deploy software factories into businesses that want to **tokenmaxx** but don't have the time or the resources to set up the infrastructure.\n\nDuring onboarding, we transfer all of your local sessions and MCP servers to Hoplite, meaning you can pick up right from where you left off. We also configure all the required dependencies and CLIs that your projects require, letting you see instant previews of what your agent is doing.\n\nOur bet is that as models improve, we’re going to start caring less about the code that they output (we’ll implicitly trust it), and shift our focus towards the product itself. Hence, a platform that prioritizes iteration on product rather than code will ultimately win. \n\nWe also have an iMessage integration so you can prompt on the go.\n\nWe installed in our first business last week and we saw an immediate result, from sentry logs going from largely ignored to fully proactive PRs when something breaks. \n\nThey have significantly faster iteration cycles and lower priority tickets have been continuously getting merged. \n\nThey wanted faster iterations but didn't have the infrastructure to support a software factory, so we went in and built it.\n\nIf this sounds like you reach out! \n\nP.S. – If you love Vim, this is for you. It was built with keyboard navigation in mind 🙂\n\ndemo vid: <https://x.com/ryan_morr/status/2078240892738224292?s=20>\n\nsign up: <https://hoplite.sh>\n\n**How we got here**\n\nPreviously, we were building an agentic harness for financial markets; letting retail investors trade with AI. The product worked well, but we never truly had founder market fit. \n\nWe found that our true passion was in talking to founders and developers – and oftentimes when pitching our old product, I’d spend 5x longer explaining our potential pivot 😅\n\nAnd so we set out to commercialize a product that we’d built internally, one that’d let us deploy the $1.5 million in OpenAI credits effectively.\n\n**Our Ask:** Let us Collison install! Bence and I will come to your apartment and set up everything for you (and bring some matcha &amp; assorted sweet treats). We want to build the best possible product for developers to move faster and care deeply about peoples setups. Partially because we have very strong opinions of our own… \n\n**The Team** \n\nBence &amp; I are both from Ireland 🇮🇪. We met in college in a course called Immersive Software Engineering. \n\nWe have been building projects &amp; doing freelance work tg for the past 2 years, but got sick of building other people's visions. \n\nWe previously interned at AWS (Bence) &amp; [@Stripe](https://bookface.ycombinator.com/company/240) (Ryan). After that experience, we were fed up and decided to drop out to build. \n\nWe are best friends &amp; just want to build a product that people truly love. ",
        "url": "https://www.ycombinator.com/launches/SAM-hoplite-effortless-cloud-agents-for-programming",
        "votes": 11,
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    "name": "Palisade",
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    "long_description": "Palisade spins up a personal sales agent for every single visitor to your website. Marketplaces like trading card platforms, vintage stores, and short-term rental operators sell more when each customer works with a personal agent that remembers them.",
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        "full_name": "Jonathan Salama",
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        "title": "Palisade: Personalized sales agents for online marketplaces",
        "tagline": "We spin up a dedicated sales agent for every single visitor to your marketplace.",
        "body": "**Palisade builds agents to run your online marketplace. Our agents have driven over $2.7M in GMV since the start of the batch.**\n\n<https://youtu.be/cuVQHgQ9yHg>\n\n**The problem:** The best marketplaces in the real world run on salespeople. The real estate agent who takes you house to house and texts you the moment the right listing is about to hit the market. The Sephora beauty advisor who finds your exact shade. The jeweler who walks you through diamond cuts for an engagement ring. **Online marketplaces skipped that person entirely** and left the selling to search bars and filters.\n\n**What we do:** Palisade builds the missing **sales agent**. Every single visitor to your marketplace gets their own dedicated agent, and conversion goes up massively.\n\n**How it works:** Agents can take any action possible on your platform. They know every listing, every UI component, and every flow. They navigate for users with their own cursor, help them discover, add to cart, and complete the purchase or booking. They build custom pages and reshape the UI around how each person actually uses the platform, remembering each user and tailoring the experience to their behavior and preferences. Each dedicated agent can naturally text and email with their customer as well.\n\n**Is this another chatbot?** Each agent is proactive with much richer, customized components than an idle chatbot. It’s like giving every customer an omnipotent Claude embedded into the platform. Palisade agents get to know each customer personally and build relationships over time. They keep working after customers leave, remember them when they return, and reach out proactively over email and text with personal messages. And everything they learn flows back: agents aggregate their conversations into reports, insights, and recommendations for sellers, and offer to make concrete optimizations themselves, to the listings and even to the marketplace platform itself.\n\n**Integration**: Start by adding just one line of code to your existing platform, whether your marketplace sells yachts, vacation rentals, rare collectibles, or anything else.\n\n**Backstory:** After studying CS at Princeton, I spent years at Amazon building software for influencers to sell more products. I then became a founding engineer at Sage AI Labs, where I worked on some of the very first iMessage agents for consumer shopping. That work left me with a deep understanding of consumer habits and marketplace dynamics.\n\n**If you’re looking to transform your marketplace:** Reach out at [jonathan@runpalisade.com](mailto:jonathan@runpalisade.com)\n\n![uploaded image](/media/?type=post&id=110474&key=user_uploads/1155886/7772b584-f4ce-425c-93a3-eb36c96aaa46)\n\n2 days before the batch started. run palisade.",
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        "votes": 84,
        "created_at": "2026-08-14T16:00:00.301Z"
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    "website": "https://prized.dev",
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    "long_description": "Prized is a cloud development environment that feels local on your Mac. \r\n\r\nDevelopers get a dedicated, persistent machine with their repos, dependencies, and tools already configured. \r\n\r\nFiles sync into a real local folder, remote ports appear on localhost, and terminals persist through tmux, so developers and coding agents can keep working even after the laptop closes. \r\n\r\nMachines can be resized or cloned as workloads grow, without rebuilding the development environment.",
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        "full_name": "Hudson Griffith",
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        "full_name": "Marinos Eliades",
        "title": "Founder",
        "founder_bio": "Marinos is the co-founder of Prized. He studied Mechanical Engineering at Stanford University. Most recently he was an engineer at Gander (F24), a 0-to-1 fleet-management platform for the private jet industry and was acquired by Archer Aviation (NYSE: ACHR). He previously served in the National Guard of Cyprus.",
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      {
        "id": 112144,
        "title": "Prized: A cloud devbox that feels local",
        "tagline": "The fastest way to run coding agents in the cloud without giving up your local workflow.",
        "body": "Hey everyone 👋 We're Marinos and Hudson, co-founders of Prized.\n\n**TL;DR:** Prized gives developers a dedicated devbox in the cloud that still feels local. Your files stay synced to a real folder, ports show up on [localhost](http://localhost), and coding agents keep running when you close your laptop.\n\nLaunch video: <https://youtu.be/JmaxNhEdLdc>\n\n**The problem**\n\nCoding agents can work for hours now. But only if you keep your laptop open.\n\nYou start a refactor, a migration, or a big build. Then you need to leave. Close the lid and the agent dies with it.\n\nYou can move everything to a VM, but now you're doing remote dev. Your files live somewhere else. Your ports need forwarding. Your terminal disappears when the connection drops.\n\nRemote development still feels remote.\n\nit shouldn't…\n\n**The solution**\n\nWith Prized, one command puts your project on a dedicated devbox without giving up local development:\n\n* **Real files on your Mac.** Prized syncs both ways into a normal folder, so everything keeps working the way it already does.\n\n\n* [**Localhost**](http://Localhost)** stays [localhost](http://localhost)**. Servers running on the box appear on your Mac automatically, including loopback-only services and hot reload.\n\n\n* **Sessions stay alive.** SSH lands in a persistent terminal session on the box, so disconnecting or closing your laptop doesn't stop the work.\n\n\n* **Compute grows with the task.** Resize the box without rebuilding your environment or moving your project again.\n\n\n* **Secrets stay out of the agent's hands.** For brokered secrets, the agent only sees a placeholder.\n\n**The team**\n\nWe worked together at Gander (F24) building fleet management software for private jets. After the company's acquisition by Archer Aviation (NYSE: ACHR), Marinos continued school at Stanford, and Hudson went on to be an engineer at Suno.\n\nWe built Prized for ourselves after getting tired of having to keep our laptops cracked open all the time. A raw VM kept the process alive but gave up the local workflow we actually wanted.\n\nCheck Prized out at [https://prized.dev](https://prized.dev/), or reach out at [founders@prized.dev](mailto:founders@prized.dev).",
        "url": "https://www.ycombinator.com/launches/TAm-prized-a-cloud-devbox-that-feels-local",
        "votes": 17,
        "created_at": "2026-08-25T17:00:00.790Z"
      },
      {
        "id": 105647,
        "title": "Prized: Lovable for internal tools",
        "tagline": "The fastest way for non-engineers to ship secure internal tools.",
        "body": "Hey everyone 👋 We're Marinos and Hudson, co-founders of Prized.\n\n**TL;DR:** Prized lets anyone at your company build and ship secure internal tools with AI. Company data comes pre-connected and scoped to what each person should see, every access is audited, and finished tools deploy behind your company's sign-in.\n\n**Launch video:** <https://www.youtube.com/watch?v=WILimoqemD4>\n\n**The problem**\n\nBuilding software has never been easier. And the people who need internal tools most, in ops, support, and finance, are done waiting on engineering.\n\nSo they build it themselves. They rip Claude Code or Cursor, pull straight from company data, and ship a working tool in an afternoon. No permissions. No audit trail. No one watching where the data goes.\n\nSecurity is assumed to be fine because the tool is \"just internal.\"\n\nit's not…\n\n**The solution**\n\nPeople aren't going to stop building with AI. So we built them a place where it's safe.\n\nWith Prized, anyone can spin up a sandbox that comes with company data already attached, scoped to what they should see, with an audit trail on every access. \n\nFrom there it's whatever building style they like: describe the tool in our app builder and watch it take shape, or bring a coding agent like Claude Code and build it themselves. Shipping is one click, and the finished tool sits behind your company's sign-in.\n\nThe person who runs the workflow finally gets to build the tool for it. Safely, this time.\n\n![uploaded image](/media/?type=post&id=105647&key=user_uploads/2485896/e426b427-8a79-4ca5-b462-b26b98db43e0)\n\n**Secure by default**\n\nSecurity is enforced in the infrastructure, not left to the person building the tool:\n\n* **Least privilege per tool.** Every tool gets its own database role and integration scopes; it can read and write only what it was granted.\n* **Credentials stay out of reach.** Secrets live in a broker and never touch the tool's code or the agent's context, so they can't leak or cross workspace boundaries.\n* **Outbound traffic proxy.** External calls only go to explicitly allowed hosts, and integrations are read-only until someone turns writes on.\n* **Admin visibility.** IT sees every tool in the org: who built it, what data it reads or writes, who can use it, and risky changes (like a destructive migration) need explicit approval before they ship.\n\n**Your agent, our sandbox**\n\nAlready have a favorite coding agent? Bring it. It plugs into the same governed sandbox and ships the same way.\n\n![uploaded image](/media/?type=post&id=105647&key=user_uploads/2485896/fcfa68c5-8c9f-4d13-b37c-d526e733539a)\n\n**The team**\n\nWe worked together at Gander (F24) building fleet management software for private jets. After the company's acquisition by Archer Aviation (NYSE: ACHR), Marinos continued school at Stanford, and Hudson went on to be an engineer at Suno.\n\n**Our ask**\n\nIf any of these describe you, we'd love to talk:\n\n* You work in ops, support, finance, or RevOps and keep waiting on engineering for small tools.\n* You lead engineering and one-off tool requests keep eating your roadmap.\n* You're in security or IT, wondering where AI-built tools are showing up at your company.\n\nCheck us out at[ https://prized.dev/](https://prized.dev/), or reach out at [founders@prized.dev](mailto:founders@prized.dev).\n\n![uploaded image](/media/?type=post&id=105647&key=user_uploads/2485896/223239da-19fa-44fb-9bd5-d18f5ecfdc74)\n\n",
        "url": "https://www.ycombinator.com/launches/RTz-prized-lovable-for-internal-tools",
        "votes": 10,
        "created_at": "2026-07-14T13:45:51.146Z"
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    "name": "Alkera AI",
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    "website": "https://alkera.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Alkera is a data engineering/analysis/science agent that works in your IDE or CLI. If you’re tired of agents that produce false, or even dangerous, reports about your data, then Alkera is for you. Our agent is equipped with your data’s history and lineage, your team’s knowledge, and tailored plugins for data apps such as Snowflake and dbt. Simply install and connect your services to begin doing trusted agentic data work. We also offer VPC & on-prem deployment options for when data can't leave your boundary.",
    "one_liner": "Reliable and safe data engineering and data science agents",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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        "full_name": "Rick Gao",
        "title": "Founder/CEO",
        "founder_bio": "Founder at Alkera AI, Inc. Previously at Verition Fund Management where he built financial models and optimizations for treasury financing. Previous computational biology research at Yale's Gerstein Laboratory. ",
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        "full_name": "Tony Li",
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        "founder_bio": "Founder at Alkera AI, Inc. Previously Agentic Software Engineer at ByteDance, where he built a Python framework for multi-agent AI workflows and deployed production bots used across company teams. Former Quantitative Developer at Carthage Capital. BS in Computer Science and Mathematics from Yale.",
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      {
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        "full_name": "Andrew Tran",
        "title": "Founder/CTO",
        "founder_bio": "Cofounder at Alkera AI. Prev SWE intern at Ramp and HRT, working closely with data teams. CS B.S/M.S from Yale. Prev ML research at Yale's Gerstein Lab developing biology reasoning models.",
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      {
        "id": 106204,
        "title": "Alkera - The data agent that you can trust",
        "tagline": "Alkera is an agent that replaces your coding agent to reliably and safely perform real data engineering/analysis/science work.",
        "body": "**TL;DR:** Data teams adopting AI agents want speed, but one wrong step can quietly ripple through your dbt models, dashboards, and business decisions before anyone notices. [Alkera](https://alkera.ai) **is an AI data agent for data engineers/analysts/scientists or anyone who wants to gather data insights that actually understands your data stack** (column-level lineage, graph-based planning, and a living knowledge base), so it ships data work you can trust. It's **#1 on UC Berkeley's [DataAgentBench](https://ucbepic.github.io/DataAgentBench/),** which tests complex, data-oriented tasks.\n\n<https://www.youtube.com/watch?v=fQEVpQPYNxg>\n\nCoding agents can write data code that runs. **For data engineering, knowing it's correct is the hard part.** This is knowing that a transformation didn't quietly redefine a column three models downstream and corrupt the revenue dashboard that the exec team checks every Monday. **For data analysis and data science, beyond data access and lineage problems, coding agents struggle with highly parallel work spread across multiple machines.** When interacting with remote computing nodes, they do so only via fragile chains of SSH commands. Long processing and training runs have you more as a babysitter than a scientist.\n\n**Alkera is a data agent that works natively across your entire data stack, with the context and guardrails coding agents lack.** Every change it makes to a query, transformation, model, or notebook is backed by a real understanding of your pipeline.\n\nIt's **#1 on UC Berkeley's DataAgentBench,** which tests complex, data-oriented tasks. You reach it through an IDE extension (VSCode, Cursor), a CLI, or the browser — wherever you already work.\n\nWhat makes it different:\n\n* **Column-level lineage across your data stack.** Trace a single row from Snowflake, through your dbt models, to your Hex dashboard. Before the agent changes anything, it maps the _blast radius_ — every downstream table and dashboard the change would touch.\n* **Graph-based planning with flexible computation.** Plan complex data tasks with parallel agents from a quick analysis to days-long modeling experiments to run across your machine and remote CPU/GPU nodes.\n* **A living knowledge base.** Alkera learns your schema docs, trusted queries, and the tribal conventions that never make it into documentation — written by both agents and humans, with humans verifying what the agent adds.\n* **Production protection.** Fine-grained permissions over every tool, including bash and SQL. Block a seemingly innocent SQL query with a dangerous UPDATE hidden away in a subexpression. Enforce OAuth to connect your warehouses to maintain existing data permissions.\n\n# **Try it**\n\nDownload Alkera at <https://alkera.ai> or read the docs at <https://docs.alkera.ai>. For data engineering, point it at your stack and **watch it trace a change through your pipeline**, lighting up everything downstream. For data analysis and data science, have it **spin up parallel research agents** to explore your data. Reach out to [contact@alkera.ai](mailto:contact@alkera.ai) to see how we can tailor Alkera to your specific data apps/tools and computing environment.\n\n# **Our team**\n\n* Andrew Tran studied CS at Yale. At Yale, he trained LLMs to reason over multi-modal biological data. At Ramp and Hudson River Trading, he worked closely with data teams to build out ergonomic tooling for data engineers and researchers.\n* Rick Gao studied CS at Yale. He was previously at Verition Fund Management, where he worked with internal data teams and counterparties to develop ingestion pipelines and internal financial models.\n* Tony Li studied CS and Math at Yale. During his time at Carthage Capital and ByteDance, he worked with data engineering teams to build data pipelines, data analysis, and agentic tooling.\n\n# **Our ask**\n\nIf you:\n\n* perform data engineering work on production pipelines with tools like dbt and Apache Airflow\n* perform data analysis/data science work in Python/R and with tools like Jupyter notebooks\n* manage a data team – engineers, analysts, or scientists\n* want to enable non-data experts to create data insights\n\nCheck out <https://alkera.ai> and reach out at [contact@alkera.ai](mailto:contact@alkera.ai). We’d love to showcase a demo, learn more about your data teams’ pain points, and share more about how Alkera can help supercharge them.",
        "url": "https://www.ycombinator.com/launches/Rcy-alkera-the-data-agent-that-you-can-trust",
        "votes": 12,
        "created_at": "2026-07-17T18:50:58.787Z"
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    "id": 32583,
    "name": "Graphify Labs",
    "slug": "graphify-labs",
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    "website": "https://www.graphify.com/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Graphify is a Knowledge Graph control plane for enterprise software. The open-source tool has 116K+ GitHub stars and 6.5M+ downloads, and is used in production by engineers at Shopify, Datadog, JP Morgan, American Express, Harvey, Automation Anywhere, and Vanguard.\r\n\r\nOn top of that graph, our enterprise layer reviews every pull request and formally verifies each code change: it proves the new behavior matches the old, or hands back the exact input that breaks it. That makes it built for the changes teams fear most, like refactors, framework upgrades, and large-scale migrations, where you need proof that nothing broke, not a guess.\r\n\r\nThe graph updates itself as the code changes and keeps context instead of forgetting it, so your whole team and their coding agents work from one shared, always-current view of the codebase instead of a thousand private threads.\r\n\r\nIt runs entirely inside your perimeter, fully air-gapped on-premise or self-hosted in your own cloud, so no code or data ever leaves your environment.",
    "one_liner": "On-device Knowledge Graph engine for Enterprise Software",
    "team_size": 1,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1785106297,
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        "full_name": "Safi Shamsi",
        "title": "Founder/CEO",
        "founder_bio": "Founder/CEO at Graphify Labs (YC S26). Built Graphify, an open-source knowledge graph engine that reached 116K+ GitHub stars and 6.5M+ PyPI downloads in about five months. Published researcher and author of The Memory Layer. MS Data Science, University of Birmingham; thesis on knowledge-graph-powered RAG systems achieving a 50% improvement in retrieval and 67% reduction in hallucinations.",
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        "title": "Your AI Agents Can Write Code. Can They Understand Your Business?",
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        "date": "Oct 01, 2026"
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      {
        "id": 111176,
        "title": "Graphify Labs: Knowledge Graph Engine for Enterprises 🧠",
        "tagline": "Shared memory of your codebase, for humans and agents.",
        "body": "Hey everyone, I'm [Safi](https://www.linkedin.com/in/safi-shamsi/), founder and CEO of [Graphify Labs](https://www.linkedin.com/company/graphify-labs/).\n\nFor fifty years, the hard part of software was writing it. AI flipped that overnight. It writes more code than any team can read, and a lot of it is slop. That leaves two **hard problems**: no one can hold the whole codebase in their head, and no one can be sure an AI's change didn't quietly break something. **Graphify solves both.**\n\n**By the numbers**\n\n\\- **108K+ GitHub stars**: one of the top five open-source projects ever from a YC company, and the first to cross 100K⭐ mid-batch\n\n\\- **5M+ downloads** of the open-source engine\n\n\\- **6,000+ signups** on the platform in its first weeks\n\n\\- Enterprises already running it in production\n\n**The memory.** One shared, always-current knowledge graph of your whole codebase, across every language and every repo, plus its docs and tickets, so a change in one service shows its impact across all the others. Instead of grepping through files one at a time, your engineers and their AI agents trace how everything connects, who calls what and what a change touches, and answer questions across the entire system, at a **fraction of the tokens**. Agents connect over a single **MCP endpoint**, so the graph works inside Claude Code, Cursor, and every major coding tool. It groups the code into communities, the real subsystems, so teams can plan, onboard, and understand the architecture across the whole **SDLC**.\n\n**The proof.** Graphify reviews every pull request, including changes that span **multiple repositories**, and verifies each one. It writes and runs a test that reproduces the bug, proves the new code behaves exactly like the old, or hands back the exact input that breaks it. Most AI reviewers just have one model comment on another model's code, which is still a guess. **Graphify proves its findings**, because it runs on a real **code graph and formal verification**.\n\n![uploaded image](/media/?type=post&id=111176&key=user_uploads/3674994/e7f719ea-bca0-4c12-a922-12c728426dd4)\n\n**It learns.** Graphify remembers what your team ships and what it rejects, and feeds that back in, so its reviews get sharper over time and stop flagging what your team has already decided is fine.\n\n> Migrating a large codebase with AI is like changing a train's engine while it is moving. Graphify lets you do it without stopping the train, and proves the new version does exactly what the old one did.\n\n**Here's the launch film**:\n\n<https://youtu.be/nvJ1M_GRj8Q>\\\n\\\nIt also proposes a fix and keeps it only if it re-verifies through the fix loop. Graphify connects to **Jira, Linear, and Sentry** so it knows the ticket a change should satisfy and the production bug it should resolve.\n\nThe enterprise layer runs on-prem, so your code never leaves your environment.\n\n**The founder.** [Safi Shamsi](https://www.linkedin.com/in/safi-shamsi/) is a published knowledge graph researcher and the author of The Memory Layer. His research on knowledge-graph retrieval improved retrieval 50% and cut hallucinations 67%. Now he's applying that work to one of the hardest problems in software: giving every engineer and AI agent a shared memory of the codebase, and a way to prove their changes still work.\n\nSoon every line of software will be written or reviewed by an agent. That software will need a memory of itself and proof that it works. **We're building both.**\n\n![uploaded image](/media/?type=post&id=111176&key=user_uploads/3674994/439244a1-338f-46cc-8594-b7c2a74bffcb)\n\n**The ask:** Before September 10 we're taking 10 design partners: a free 14-day build where we deploy the enterprise graph on-prem, with your team \\\n**Reach us at [founders@graphify.com](mailto:founders@graphify.com)**\n\n**Dig in**\n\n**- Run it yourself: [https://app.graphify.com](https://app.graphify.com)**\n\n**- Open-source engine: [https://github.com/Graphify-Labs/graphify](https://github.com/Graphify-Labs/graphify)**\n\n**- Docs: [https://graphify.com/docs](https://graphify.com/docs)**\n\n**- Connect any agent over MCP: [https://api.graphify.com/mcp](https://api.graphify.com/mcp)**\n\n**- Benchmarks and methodology: [https://github.com/Graphify-Labs/graphify/blob/v8/BENCHMARKS.md](https://github.com/Graphify-Labs/graphify/blob/v8/BENCHMARKS.md)**\n\n**- Talk to us: [founders@graphify.com](mailto:founders@graphify.com)**\n\n![uploaded image](/media/?type=post&id=111176&key=user_uploads/3674994/6068aaba-5948-422b-b5ef-b74b60a9504f)\n\n",
        "url": "https://www.ycombinator.com/launches/SvA-graphify-labs-knowledge-graph-engine-for-enterprises",
        "votes": 66,
        "created_at": "2026-08-19T15:00:00.223Z"
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    "id": 32618,
    "name": "Click",
    "slug": "click",
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    "website": "https://www.useclick.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Click serves agents over an API. Bring your model keys, tools, and context - Click runs the agent and streams back events.\r\nAsk your coding agent about useclick.ai/reference!",
    "one_liner": "Managed Agents API",
    "team_size": 1,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1785963586,
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        "body": "**TLDR:** Click is an MCP that provides extensive research connectors to give external context that the built-in web search misses.\n\n![uploaded image](/media/?type=post&id=110141&key=user_uploads/1995988/91aff538-41b1-4c8b-96eb-c1bf84bd5e47)\n\n**Video:** <https://youtu.be/IgcAy86cPls>\n\n**Problem:**\n\nClick is largely motivated by a change in my own behavior:\n\nCodex &amp; Claude are amazing products. I live inside their surface now - using it more than my browser. It feels like home, to the point that I’m annoyed to have to leave. Most often, I’m stepping outside to do external-facing tasks, like researching my leads on LinkedIn or comparing flight options. I want my agents to do these tasks as well.\n\nCurrently, those can’t be completed because their gateway to the world (in-built web search) has limited access. Often the agent also asks to use the browser with a logged-in session, which I’m uncomfortable with.\n\nSo, I built the connector layer that I wish existed.\n\n**Solution:**\n\nClick’s MCP is a single installation that provides your agent with an ever-growing bundle of the best data connectors. The current set of connectors enable new use cases inside the chat, like:\n\n* Lead research &amp; enrichment\n* Researching ad campaigns from competitors\n* Analyzing sentiment around a topic across social media\n* Planning travel with live fares &amp; availability\n\n**Team:**\n\nI’m Aditya, the founder of Click. Previously, I helped build Ethereum, with a vision to create a platform that enables new kinds of applications. \n\nNow, I’m focusing on the next application platform - the AI chat surface. Click builds useful services that meet users right inside the conversation. I’m building one trusted service at a time, and research is the first one.",
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        "full_name": "Nour Zahzah",
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        "title": "Gradon: Legora for AEC (Architecture, Engineering, & Construction) firms",
        "tagline": "The AI partner that makes every engineer 10x.",
        "body": "Hey everyone 👋 We're Nour and Yousef, co-founders of Gradon.\n\nTL;DR: Gradon is the AI partner for AEC (Architecture, Engineering, Construction) firms. Engineers send it work the way they'd message a teammate, and it works across every workflow and tool the firm runs on, from CAD design and calculations, to reports and full plan sets. Firms using it today have decreased average project times by more than 75%.\n\n<https://www.youtube.com/watch?v=aTg6ne4z_aU>\n\n### How Gradon Works\n\n* Message it like a teammate. Type or talk to it, or share your screen and walk it through a problem. It takes the task from there.\n* It works the firm's way. Before Gradon ever touches a project, a firm brain is built, that learns the firm's past work and standards, so everything comes out just the way their team would do it.\n* It works inside their tools, from CAD design, to analysis software, and anything in between. No new system to move into.\n* Engineers stay in charge. Every deliverable comes back for review, and nothing changes until the engineer approves it.\n* Every discipline. Civil, structural, MEP, architecture and more.\n\nWe're also each firm's AI partner, not just another piece of software. We fly out and work one-on-one with each firm's engineers until they're getting the most out of it. After that, we continuously host office hours, lunch-and-learns and more, to make sure firms always stay on the frontier.\n\n### Why Now\n\nAI is the biggest change to engineering since CAD. The demand to build has never been higher, and the number of engineers can't keep up. The next great engineering firms will be the ones where every engineer has Gradon behind them.\n\n### Who We Are\n\nWe've known each other since kindergarten.\n\n* Nour (CEO) studied Mechanical Engineering at Berkeley and worked as a mechanical design engineer. Before startups, he played professional academy soccer for the San Jose Earthquakes for 7 years.\n* Yousef (CTO) graduated high school at 15, then earned a Bachelor's in EECS from Berkeley and a Master's from Stanford. He previously built FPGA infrastructure at Apple and worked on chip design at AMD.\n\n### Our Ask\n\n* If you run an engineering firm, book a demo today to see how Gradon can transform your firm to become AI-native.\n* Intros to owners and principals at civil, structural, MEP or architecture firms. We compensate for successful referrals.\n\nReach us at [heygradon.com](http://heygradon.com) or [nour@heygradon.com](mailto:nour@heygradon.com)",
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        "full_name": "Shailendra Singh",
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        "full_name": "Karan Raina",
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        "title": "Hyperprobe: On-call Agent for engineering teams",
        "tagline": "The fastest way for coding agents to debug incidents live in production.",
        "body": "# \\*\\*\\*\\*\n\n**TL;DR:** AI writes most of our code now. Debugging it when it breaks in production is still slow, because the value that explains the failure was never logged. HyperProbe is an on-call agent for engineering teams. It takes an open incident to a confirmed root cause by dropping read-only probes into your running service and capturing the exact variable state logs don't have. No redeploys, no restarting the app. \\\n\\\n📹 **Launch Video: [https://youtu.be/QtaZrQ8_Uk8](https://youtu.be/QtaZrQ8_Uk8)**\n\n**🚧 The Problem**\n\nTeam ships faster than ever with agents that write most of our code. This is already shrinking the useful context engineers need to debug AI written code. Not helped by the limited telemetry added in the same code by AI. So when something breaks in prod, the first instinct for engineers is to open logs or throw them to agents. But if the line you are looking for is not there, agents will start guessing the root cause on limited data, forcing engineers to collect more logs by redeploys.\n\nThe result: our best engineers become our on-call team, incidents stay open longer, and patches come from data that never capture production context, so issues recur.\n\nYou can see where that leads. In September last year, a public fintech in India paid out $5 million after failed transactions were incorrectly marked successful. NYSE the same year miscalculated price bands for 40 symbols, printing trades so wrong they had to be reversed. Same pattern: the code ran clean, wrote the wrong state, and neither logs nor traces could show it.\n\n ✅ **What Hyperprobe does**\n\nHyperProbe gives engineering teams an on-call agent that works the incident and takes it to a confirmed root cause, live in production.\n\n* **Plan:** the agent picks up the alert from PagerDuty, Datadog, or Slack, then reads your logs and traces to locate the file and line. The easy incidents resolve right here.\n* **Probe:** logs not enough? places read-only virtual breakpoints on the suspect lines and captures the exact variable state live, across services. No redeploys, no restarts. \n* **Confirm:** the diagnosis is verified against real captured evidence, not a guess. Your engineer gets a confirmed RCA and commits the fix.\n\nThere are two pieces. An SDK that runs inside your service, and an MCP server your coding agent talks to. The SDK is what makes setting probes (virtual breakpoints, log or metric) possible without a redeploy. \n\n### **🔍 A few examples**\n\n* **An intermittent 500 that won't reproduce locally:** catch it live with full variable state \n* **A third-party API misbehaving:** see the exact payload and response\n* **A function returns a wrong value with no error:** see what it computed and why\n* **Anything that only happens in prod:** stop redeploying with console.logs\n\n🚀 **The team**\n\nWe've both lived this problem. Shailendra ran production at scale. Karan was a senior architect at a SaaS company. Before this, both spent three years building production SDKs for a testing product, learning the hard parts of pulling real runtime state out of a running service without breaking it.\n\nEvery incident we watched came down to the same question: what was the actual value at the moment it broke. Nobody built it for the way engineers debug with coding agents now. So we did.\n\n![uploaded image](/media/?type=post&id=110401&key=user_uploads/3173209/ddf3d8d0-2bd4-4a8c-9547-fa5ea2496469)\n\n### **🎁 Why now**\n\nFor thirty years the expensive part of software was writing it, and every tool got built for that. Generation is now nearly free, but the cost didn't disappear. It moved downstream, to figuring out why the generated code broke in production.\n\nAnd that system is now mostly code no human wrote or holds in their head. When it breaks, the engineer has less context than ever, and their first move is already to hand it to the coding agent. That agent only has your logs and traces, so it guesses. We give it the evidence instead, captured live from the running code at the point of failure.\n\n### **🙏 Our ask**\n\n* If you're an engineer tired of the redeploy loop, debugging code you didn't write at 2 AM, try it on your own service.**,** first investigation in 10 min:[ https://docs.hyperprobe.co/quickstart](https://docs.hyperprobe.co/quickstart)\n* If your best engineers have become your on-call team and you want that fixed, let us work one real incident from your stack, free: <https://calendly.com/shailendra-hyperprobe/30min>",
        "url": "https://www.ycombinator.com/launches/Sif-hyperprobe-on-call-agent-for-engineering-teams",
        "votes": 82,
        "created_at": "2026-08-17T15:30:20.732Z"
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        "full_name": "Jaden Wang",
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        "full_name": "Prashant Patel",
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        "title": "OpenRelay: The Inference Delivery Network",
        "tagline": "One API for inference across every chip.",
        "body": "**TL;DR:** OpenRelay is building an Inference Delivery Network (IDN) on top of its CDN for GPUs. We provide one entrypoint for inference across every chip. \n\nSend us a workload and we’ll cut your costs up to 20% by running it through our network, balancing the best available accelerator (NVIDIA, TPU, Trainium, AMD) across clouds and handing back a single endpoint. You never pick the hardware, chase quotas, or rebuild your stack per provider. And if you run GPUs or other AI accelerators (an NVIDIA cluster, TPUs, a reserved fleet), you can plug your capacity into our rails and we'll bring the inference demand. Get started [here](https://openrelay.inc/).\n\nP.S. sign up for our Luma page to be notified of our Launch Party!\n\n<https://luma.com/s6x8cx5x>\n\n\\\n<https://youtu.be/7uNhqcjBXJg>\n\n## The Team\n\nHey guys! We're **Jaden and Prashant**, the founders of OpenRelay. We came at the same problem from opposite sides.\n\n* Jaden built a half-megawatt data center at 20 from a warehouse shell, then joined Voltage Park early, where he ran virtualization and helped stand up HPC.\n* Prashant built accelerator infra at AWS, where he ran custom model deployments and wrote custom kernels to squeeze out Trainium performance.\n\n \n\nWe kept seeing the same thing: there's more AI compute than ever, and you still can't reach it. We left our jobs to fix that.\n\n## The Problem\n\nCompute is everywhere; liquidity is nowhere. Accelerators are scattered across dozens of clouds, chip vendors, and operators, each behind its own quotas, drivers, contracts, and console. Teams that want to run inference can't reach the capacity, and the capacity can't reach them.\n\nRunning inference naively is easy; running it at scale is hard. Any operator can spin up a model on a box. Turning idle GPUs into a production endpoint (load balancing, isolation, autoscaling, failover, metering, billing) is a software platform most individual operators won't build. So capacity sits stranded behind their own front door, and developers either overpay for scarce reserved GPUs or hand-stitch a fragile multi-provider stack.\n\n## Solution\n\nWe built one set of rails across all of it.\n\nSend a workload (any container or model) and we schedule it onto the best-fit accelerator, attach a production endpoint, and scale it. We route to the cheapest accelerator that meets your latency and throughput targets, and we benchmark continuously. If the market can't beat renting yourself, we backstop with our own inference demand, so you’re never on the hook. \n\nYou never pick the chip, cloud, or region; we handle routing, isolation, failover, metering, and billing across 4+ clouds and every major chip family. We're language- and framework-agnostic (no SDK lock-in), and you can drive everything from our CLI and REST API.\n\nIt's two-sided: if you run GPUs or other accelerators (a neocloud, a data center, a pay for an underutilized reserved fleet), you can connect that capacity to our rails and we'll bring the inference demand, turning hardware into a revenue-generating endpoint without building a platform yourself.\n\n## Traction\n\nWe're **live in production**, generating 100 billion tokens a week across 22 physical locations across Europe, APAC, North America, and the Middle East running on 8 different accelerator SKUs.  \n\n## Asks\n\nWe'd love to hear from you!\n\n* **Run GPUs, or know someone who does?** This is who we most want to talk to: companies running their own nodes for inference, data centers, reserved fleets, even a crypto or mining cluster looking to move into AI. Plug your capacity into our rails and we'll bring the demand. Reach us at [founders@openrelay.inc](https://mailto:founders@openrelay.inc).\n* **Shipping inference and tired of picking chips?** Bring a workload and we'll get you on the best available hardware today.\n* **Feedback, intros, or just want to chat?** Book a call with us, or email [founders@openrelay.inc](mailto:founders@openrelay.inc) for anything else.",
        "url": "https://www.ycombinator.com/launches/SUY-openrelay-the-inference-delivery-network",
        "votes": 12,
        "created_at": "2026-08-07T17:00:00.601Z"
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    "id": 33573,
    "name": "hardware intelligence",
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    "website": "https://hardwareintelligence.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Hardware Intelligence makes chip design tools that cut simulation and debugging time by an order of magnitude. When a chip test fails, engineers need a recording of every internal signal - a waveform. We’ve developed WaveZip, which captures waveforms 500x smaller with 200x less overhead, and Wave, which beats frontier models on industry chip debugging benchmarks. We’re Rishov Sarkar (Georgia Tech Ph.D. in chip simulation) and Athreya Anand (ex-Google, M.S. ML/AI), YC S26. https://hardwareintelligence.ai",
    "one_liner": "AI tools for the chips your AI runs on",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1784052551,
    "tags": [
      "Developer Tools",
      "Hardware",
      "Enterprise Software",
      "Semiconductors",
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    "regions": [
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      "America / Canada"
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/hardware-intelligence",
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    "year_founded": 2026,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/hardwareintelligence/",
    "x_url": "https://x.com/hwintelligence",
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    "primary_partner": {
      "name": "Jon Xu",
      "url": "https://www.ycombinator.com/people/jon-xu"
    },
    "founders": [
      {
        "user_id": 551607,
        "full_name": "Athreya Anand",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder & CEO of Hardware Intelligence. Athreya was a tech lead at Google where he led AI efforts across orgs from agentic workflow management tools to prediction models for Google Ventures. He has a Master's from Georgia Tech in Machine Learning and A.I., with technical expertise in agentic tools and chip design through his time at Google, AWS Inferentia, and Tesla. ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/athreyaanand",
        "x_url": "https://x.com/athreyaanand",
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      },
      {
        "user_id": 2565323,
        "full_name": "Rishov Sarkar",
        "title": "Founder/CTO",
        "founder_bio": "Co-founder & CTO at Hardware Intelligence. Rishov graduated with his PhD in Electrical & Computer Engineering from Georgia Tech with six published first-author/co-first-author conference papers, including one best paper runner-up. He also developed simulators for AMD's AI Engine accelerator and worked on LLVM-based compilation flows at Siemens EDA. He earned his MS and BS in Computer Engineering from Georgia Tech.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/rishovsarkar/",
        "x_url": "https://twitter.com/ArkaneMoose",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d7666af58a4a49fbf9b8355cdffcb981f5df6505.jpg"
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    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 107661,
        "title": "hardware intelligence: AI tools for the chips your AI runs on",
        "tagline": "Bringing the $20B chip tooling industry into this decade",
        "body": "---\n\n---\n\n**Update:** We’ve just launched our second tool, WaveZip - a genuine breakthrough method for capturing and storing waveforms. Read more at <https://hardwareintelligence.ai/wavezip/>\n\n---\n\n---\n\n<https://www.youtube.com/watch?v=KJTH-nNl6qQ>\n\n—\n\nWe’re Athreya and Rishov - the founders of [@hardware intelligence](https://bookface.ycombinator.com/company/33573). We’re here to pick a fight with the $20B industry whose debuggers suck and won’t open until an ancient license server gives it permission.\n\n**TL;DR: Our first product, Wave, is a SOTA waveform debugger that lives completely in the terminal, built for the agentic era.** An agent can jump you to the moment a design breaks, drag in waveforms and manipulate them, trace bad signals to its source and even prove its fix against the simulation - all visual. We allow teams to build better chips in less time.\n\n**The quick ask:** If you or anyone you know builds or verifies chips (ASICs/FPGAs), please email us! We would love to talk :)\n\n<https://www.youtube.com/watch?v=5nXvicwWONQ>\n\n❌ **The Problem**\n\nThe AI boom is a chip boom - more companies and teams than ever are designing silicon. However, the reality is hardware is not software: you can’t patch a chip after it ships. A bug that reaches manufacturing can be a nine-figure mistake. That’s why **companies spend 70% of the entire chip design process just on verification**.\n\nHardware verification engineers run thousands of simulated tests first on their code (simulation) which typically can take **hours to days**. If one of these tests fail, debugging means reading a waveform - a log of every signal, millions of ticks long, hiding the tick where a value went wrong. It’s literally a needle in a haystack… a big haystack. It’s common for these waveform files to be several gigabytes large. **Finding this needle is the single largest activity in verification.**\n\n**The current tools are dinosaurs.** 20-year-old GUIs behind license servers whose seats run six figures a year sold by our favorite incumbents: Synopsys, Cadence, and Siemens. Free tools are even worse.\n\n![uploaded image](/media/?type=post&id=107661&key=user_uploads/551607/fd100b13-f0dd-45f0-8ee4-395edf96fcae)\n\nYes. This is from 2026.\n\nSoftware engineers got coding agents. Chip engineers got a queue for a license and whatever this is.\n\n👋 **What Wave actually does**\n\n![uploaded image](/media/?type=post&id=107661&key=user_uploads/551607/a75818b0-b001-466b-9586-705d26deb5f9)\n\nWave is the first of its kind! **A fully terminal-native waveform debugger with a verification agent built in.** Wave opens files before Verdi, the industry-standard viewer, finishes its license check. Let’s do a quick dive!\n\n![uploaded image](/media/?type=post&id=107661&key=user_uploads/551607/ac7e5c75-8abb-4a6d-881f-a2a9b883a8b3)\n\n**Why the terminal?** Surprisingly, most hardware engineers are terminal power users - typically doing all their coding in Vim. We wanted to meet them where they are and make our product extremely intuitive to use - we even employ Vim bindings across the interface.\n\n![uploaded image](/media/?type=post&id=107661&key=user_uploads/551607/d4063fbc-2f57-4b5c-a421-bfaa697433d6)\n\n**Ask in plain english.** _Why is a wave x at 12.4us?_ The agent will pull in signals, act on them and trace the root cause. Everything happens in front of your eyes.\n\n![uploaded image](/media/?type=post&id=107661&key=user_uploads/551607/8f37dd5c-22f0-4271-b665-a096c5dbfbd2)\n\n**Pick your fix and see it.** Wave will propose different approaches with tradeoffs. The definition of “best” in hardware design depends on the use case. Maybe you want to optimize for performance? Maybe for power? Pick the one for you! Wave re-simulates and re-reads the new waveform. See a diff of how the waveform changed and a visual indication of where the fix was implemented.\n\n![uploaded image](/media/?type=post&id=107661&key=user_uploads/551607/b0875bc9-fb55-4275-8c7e-11f926bc597d)\n\nNow watch it fix a bug end to end with Rishov!\n\n<https://www.youtube.com/watch?v=eTycCILW6Jk>\n\n🙏 **Asks &amp; Offers**\n\nIf you design chips or lead a team, email us! We’d love to work with you and speed up your RTL development.\n\nKnow someone who does? Email us!\n\nJust want to chat about hardware? **EMAIL US!!**\n\n👬 **The Team**\n\nWe met in our freshman dorm at Georgia Tech nearly a decade ago! We became best friends and roommates for all four years of college - after, Athreya went to NYC to work at Google and Rishov stayed to do his PhD. We promised each other that once we’re free, that we’ll go all-in and work on something we’re passionate about together. Turns out, Rishov’s deep PhD thesis on chip simulation and compilers was the perfect spark.\n\nToday we announce our company and are roommates once again ❤️\n\n![uploaded image](/media/?type=post&id=107661&key=user_uploads/551607/eef30a82-c606-494a-a093-3649920c7857)\n\n—\n\nSay hi 👋 [hi@hardwareintelligence.ai](mailto:hi@hardwareintelligence.ai) · [hardwareintelligence.ai](http://hardwareintelligence.ai)\n\n[@Athreya Anand](https://bookface.ycombinator.com/user/551607) · [athreya@hardwareintelligence.ai](mailto:athreya@hardwareintelligence.ai)\n\n[@Rishov Sarkar](https://bookface.ycombinator.com/user/2565323) · [rishov@hardwareintelligence.ai](mailto:rishov@hardwareintelligence.ai)\n\nP.S. Wave is just the start 👀 We got some super cool things coming to close the loop of hardware engineering. ",
        "url": "https://www.ycombinator.com/launches/S0T-hardware-intelligence-ai-tools-for-the-chips-your-ai-runs-on",
        "votes": 50,
        "created_at": "2026-07-27T16:00:24.675Z"
      }
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  },
  {
    "id": 33738,
    "name": "CoArena",
    "slug": "coarena",
    "former_names": [
      "Coasty"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/1543623e6506eaf893b1c43e614688a6b2a32bda.png",
    "website": "http://coarena.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "CoArena is a live arena where anyone can use the world's top computer-use models racing two of them on the same real computer task and judging which one did it better. Every battle becomes something the AI labs can't build themselves, an honest test of their agents on real work, and the data to make them better.",
    "one_liner": "The biggest crowdsourced benchmark for Computer-Use",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1782294083,
    "tags": [
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      "Machine Learning",
      "Reinforcement Learning",
      "Data Labeling",
      "AI"
    ],
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    "nonprofit": false,
    "batch": "Summer 2026",
    "status": "Active",
    "industries": [
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    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/coarena",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/coarena.json",
    "year_founded": 2026,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/coastyai",
    "x_url": "https://x.com/coastyai",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/coasty",
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    "primary_partner": {
      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
    },
    "founders": [
      {
        "user_id": 1194042,
        "full_name": "Prateek Jannu",
        "title": "Founder/CEO",
        "founder_bio": "Prateek Jannu, Co-founder & CEO - Stanford (MS. EE) and Purdue (BE. CE). Invented Solo-Synth-GAN, which generates labeled training data from a single example. Built Coasty to #1 on the OSWorld benchmark (82%), beating Agent S3, UiPath, Kimi K2.5, and Claude Sonnet 4.5. Now building CoArena.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/prateekjannu",
        "x_url": "https://x.com/prateekjannu",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/26ed45c60c34293a10373502e615a8c6499d356f.jpg"
      },
      {
        "user_id": 2457255,
        "full_name": "Nitish Kovuru",
        "title": "Founder",
        "founder_bio": "Co-founder and CTO/COO of Coarena, launched Coasty prev, SOTA CUA framework on OSWorld at 83% accuracy. Did CS at Columbia (Vision track) and hold a BS in Computer Engineering from Purdue, where I TA'd a graduate-level AI course as an undergrad and later went on to build enterprise sales automation agentic systems for my previous company.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/nitish-kovuru-2423351b4",
        "x_url": "https://x.com/llmhubdev",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/29f588d1c332c655eee8ea69c5e1c27e9ec4fce9.jpg"
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    "launches": [
      {
        "id": 111689,
        "title": "Coarena - The biggest crowdsourced benchmark for Computer-Use",
        "tagline": "We build the most advanced and biggest benchmark for computer use",
        "body": "We are officially launching CoArena (YC S26). Released 2 weeks ago, users have doubled every week since, and the arena went from $0 to $60,000 in revenue since. It's a live arena where the world's top Computer-Use models race to finish the same real computer task, and real people judge which one did it better, blind.\n\n<https://youtu.be/TB_9YMYCWw4>\n\n![uploaded image](/media/?type=post&id=111689&key=user_uploads/1194042/43ddaa95-1f50-4b30-b0a4-9b085433ec3c)\n\n**The problem**\n\nEvery AI lab says their agent is the best at using a computer, and every claim points at a benchmark score. We know those scores well: earlier this year we built the #1 agent on OSWorld (82%). That's exactly how we learned the scores mean very little. Benchmarks are static, agents memorize them, and they say nothing about the messy tasks people actually need done.\n\n**What we built**\n\nOn CoArena, anyone can type a real task (\"find me the cheapest flight,\" \"assemble this expense report\"), watch two anonymous frontier agents race it live, and vote on the winner. Names are revealed only after you vote, so the judging is blind. Every battle becomes a fresh eval no model has ever seen, and the failure cases labs never catch: prompt injection, spending money when it should ask, silent side-effects.\n\n**What the arena has already shown**\n\n\\- Only \\~66% of agent runs finish their task at all 1 in 3 dies to a failure before any score exists\n\n\\- On identical tasks, the best frontier agent completes \\~87% of runs; the worst completes \\~42%\n\n\\- One major frontier model times out in roughly a third of its runs\n\n\\- In \\~7% of battles, human judges ruled that BOTH agents failed\n\n\\- The #1 spot on our leaderboard changed hands three times in three days, real tasks don't saturate\n\n**What you get**\n\nIt's completely free, including models you can't use anywhere else (Fable, Sol, and unreleased previews). Run your real errands with frontier agents, keep whatever they produce, and find out which model is actually best at YOUR kind of work, not the benchmark's.\n\n**Our asks**\n\n1\\. Use it, it's free. Bring your daily work: the flights, the spreadsheets, the research. Two frontier agents will race it, you keep the result, and your vote makes the leaderboard more honest: <https://coarena.ai>\n\n2\\. If you're an AI lab working on computer use or vision, or a robotics company building on vision, we'd love to talk. We can send you sample evals and data today: [founders@coasty.ai](mailto:founders@coasty.ai)",
        "url": "https://www.ycombinator.com/launches/T3R-coarena-the-biggest-crowdsourced-benchmark-for-computer-use",
        "votes": 59,
        "created_at": "2026-08-22T19:00:00.303Z"
      },
      {
        "id": 105157,
        "title": "Coasty: The computer-use agent that doesn't break on real software",
        "tagline": "Coasty helps developers kill RPA.",
        "body": "**TL;DR: Coasty gives developers a computer-use agent that reliably automates back-office work in legacy desktop software where RPA scripts and other CUAs fail. It’s achieved 82.81% on OSWorld and it’s great at automating workflows where quiet mistakes cost the most: regulatory filings, patient records, payments, and gives developers precise control and observability over its work.**\n\n<https://www.youtube.com/watch?v=3EwLfqlgDEM>\\\n(_The portals and the data in it, are mockups_)\n\n**Replayable audit trail (real run):** <https://coasty.ai/share/5b3320fc-0e64-4f1b-b684-9fd6e8cd8960> \n\n**OSWorld submission (Coasty scored 82.81% on OSWorld Verified, confirmed by the OSWorld team, with our latest internal run at 85.60%.):**[ https://github.com/coasty-ai/coasty-osworld](https://github.com/coasty-ai/coasty-osworld)\\\n\\\n**The Problem**\n\nMost back-office work doesn't happen in clean web apps. It happens in legacy desktop software, full of surprise pop-ups, wandering menus, and impenetrable UIs.\n\nToday, developers automating this back-office “real” work are stuck choosing between brittle RPA scripts and CUAs that demo beautifully and score high but break on contact.\n\nThe problem isn't getting an agent to click. It's trusting it when a silent mistake gets someone fired.\n\n### **Why Coasty is reliable where others aren't**\n\n**It recovers mid-task.** Coasty catches its errors and fixes them mid-run. If it’s crunching on a 20-step workflow and makes a misclick at step 3, it will recover and start from the error. First-pass accuracy is vanity. Recovery keeps a run alive.\n\n**It survives messy software.** Pop-ups, modals that steal focus, legacy desktop apps. Coasty doesn’t record clicks, it reads the screen. So when the UI changes overnight and every RPA script breaks, Coasty looks at the new screen and keeps going.\n\n**It knows when it's done.** An agent that thinks it finished but didn't is worse than one that fails loudly. Coasty verifies its own output and leaves a timestamped audit trail you can replay.\n\n**It swarms.** One task across forty state portals, each with its own ancient interface, all at once. Forty agents, one verified result set. What takes a team a week, is done overnight.\n\n### **Traction**\n\nCoasty has been verified by the OSWorld team and will be published soon, but also another internal benchmark we published (85.60%): &lt;<https://github.com/coasty-ai/coasty-osworld> >.\n\nWe have paying customers on four continents, a few thousand active users, and we have actually grown 24x since Claude Cowork came out.\n\n### **Why us**\n\nWe started working on this idea when models weren’t good enough for computer use (last summer), so we’ve built frameworks to test and run the perfect combination of models and harnesses to see what works in practice. Prateek worked as an ML engineer at multiple startups and dropped his Stanford admit while I did CS at Columbia and built my previous company’s entire agentic sales automation. We’ve grown with this field and have been working on it even before it got much attention, so we understand where CUAs mess up and how to deal with these messes realistically.\n\n### **The ask**\n\nSend us one workflow your team runs by hand. We’ll tell you straight whether Coasty can run it reliably today. If it looks automatable, we’ll build a working proof of concept on your real software before a long sales process.\n\nWe’re especially looking for intros to operators and executives in accounting, tax, insurance, healthcare, compliance, and data privacy - anywhere teams are still babysitting RPAs, clicking through legacy portals, reconciling records, filing forms, or moving data across old desktop software.\n\nHere's our Calendly:[ https://cal.com/coasty/15min](https://cal.com/coasty/15min)",
        "url": "https://www.ycombinator.com/launches/RM5-coasty-the-computer-use-agent-that-doesn-t-break-on-real-software",
        "votes": 12,
        "created_at": "2026-07-10T17:30:25.886Z"
      }
    ]
  },
  {
    "id": 33838,
    "name": "Simantic",
    "slug": "simantic",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/12eef74104b6e57636a6f0d2305e3a2d18d5c2e5.png",
    "website": "https://simantic.com",
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