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        "full_name": "Vivek Ravisankar",
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        "id": 79073,
        "title": "HackerRank (YC S11) | Hiring Senior Software Engineer | Santa Clara CA - Hybrid",
        "url": "https://www.ycombinator.com/companies/hackerrank/jobs/6yom11r-hackerrank-yc-s11-hiring-senior-software-engineer-santa-clara-ca-hybrid",
        "location": "Santa Clara, CA, US",
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        "title": "Forward Deployed Engineer",
        "url": "https://www.ycombinator.com/companies/hackerrank/jobs/PUBbnNs-forward-deployed-engineer",
        "location": "Santa Clara, CA, US",
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        "title": "Manager, Forward Deployed Engineering",
        "url": "https://www.ycombinator.com/companies/hackerrank/jobs/RXN2BRu-manager-forward-deployed-engineering",
        "location": "Santa Clara, CA, US",
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        "title": "HackerRank, a platform for recruiters to test coders and coders to hone skills, raises $60M at ~$500M valuation – TechCrunch",
        "url": "https://techcrunch.com/2022/03/29/hackerrank-a-platform-for-recruiters-to-test-coders-and-coders-to-hone-their-skills-raises-60m-at-a-500m-valuation/",
        "date": "Mar 29, 2022"
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        "id": 97749,
        "title": "Chakra: AI interviewer that finally works",
        "tagline": "An AI interviewer that's trained to evaluate AI-first skills across roles with integrity built-in",
        "body": "I’m Vivek, Co-founder and CEO at HackerRank (YC S11). We’re launching a new product - Chakra: an AI Interviewer that actually helps hiring teams screen candidates faster with evidence-backed interview reports.\n\n**The problem we see**\n\nWe’re seeing recruiters and hiring managers are dealing with:\n\n* Too many applicants and too much scheduling overhead for early rounds.\n* Lower signal-to-noise because many applications are polished by AI or outright fabricated .\n* Rising interview integrity issues — including tools marketed to “cheat” during interviews.\n\nTeams spend tons of valuable human time on the wrong candidates - and hiring managers don’t trust early-round signals.\n\n**What Is Chakra**\n\n![uploaded image](/media/?type=post&id=97749&key=user_uploads/10668/d2057e04-0171-4320-9e63-77ae90329042)\n\n\\\n\\\nChakra is an AI Interviewer by HackerRank that runs structured, voice/video screening interviews based on your rubric and delivers decision-ready reports backed by evidence.\n\nDemo video - <https://youtu.be/6v5h-7Q4O2c>  \n\n**How it works**\n\n1. Configure the role, competencies, and rubric in a chat-based setup.\n2. Invite candidates easily via email, a simple link, or directly through your ATS\n3. Chakra conducts a voice/video based interview on your behalf, intelligently adapting to get the signals you need.\n4. You get an instant report with an actionable recommendation, skill-level feedback aligned with your rubric, transcript references, and full session replay.\n\n**What makes it different**\n\nThere are a lot of “AI interviewers” right now, but most fall into one of two buckets:\n\n1. Niche / single-skill evaluators, or\n2. Single-modal experiences that don’t generate robust, trustworthy signal\n\nChakra is designed to be multi-modal (voice, video, IDE, whiteboard etc.) and versatile across roles, while still producing grounded, auditable evidence in the report.\n\n![uploaded image](/media/?type=post&id=97749&key=user_uploads/10668/43e35ddd-bdde-4c00-b579-324bdc45b650)\n\n**YC community asks / offers**\n\n* If you’re hiring right now, you can try [this sample FDE interview](https://www.chakra.sh/interviewer/1enskc0p2qs/session), I’d love feedback on:\n  * Rubric setup (does it match how you actually hire?)\n  * Candidate experience (does it feel fair and natural?)\n  * Report quality (is it truly decision-ready?)\n* You can request access at [chakra.sh](http://chakra.sh)\n* Or simply reach me at @rvivek on X or via email at [vivek@hackerrank.com](mailto:vivek@hackerrank.com)",
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    "one_liner": "Engage customers through personalized omni-channel messaging",
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    "fb_url": "https://www.facebook.com/onesignalapp/",
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        "full_name": "George Deglin",
        "title": "Founder/CEO",
        "founder_bio": "Technical Founder & CEO of OneSignal (YC S11 and YCG S20). OneSignal helps businesses send Push Notifications, Email, SMS, and In-App messaging to develop engaged and loyal customers.\n",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/gdeglin",
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        "id": 72052,
        "title": "Senior Software Engineer, Journeys Team (Fullstack)",
        "url": "https://www.ycombinator.com/companies/onesignal/jobs/BOlyPRY-senior-software-engineer-journeys-team-fullstack",
        "location": "United States (Remote) / Remote (US)",
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        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "",
        "equity_range": "",
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        "title": "Staff Software Engineer, SMS Team (Fullstack)",
        "url": "https://www.ycombinator.com/companies/onesignal/jobs/DNhTi7U-staff-software-engineer-sms-team-fullstack",
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        "url": "https://www.ycombinator.com/companies/onesignal/jobs/ZwwdPw4-senior-software-engineer-email-team",
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        "id": 92756,
        "title": "Product Marketing Manager",
        "url": "https://www.ycombinator.com/companies/onesignal/jobs/06T3lN5-product-marketing-manager",
        "location": "United States - Remote / Remote (US)",
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        "title": "OneSignal Secures Investment From ServiceNow Ventures",
        "url": "https://www.cmswire.com/the-wire/onesignal-secures-investment-from-servicenow-ventures/",
        "date": "Feb 02, 2023"
      },
      {
        "title": "OneSignal Launches Support for iOS Live Activities",
        "url": "https://onesignal.com/blog/new-live-activities-support-to-help-you-drive-loyalty-faster/",
        "date": "Dec 14, 2022"
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      {
        "title": "OneSignal lands $50M to automatically optimize SMS, in-app and email campaigns – TechCrunch",
        "url": "https://techcrunch.com/2022/09/01/onesignal-lands-50m-to-automatically-optimize-sms-in-app-and-email-outreach/",
        "date": "Sep 01, 2022"
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        "id": 105807,
        "title": "OneSignal is powering Autonomous Lifecycle Marketing for B2C Companies",
        "tagline": "Announcing our Autonomous Lifecycle Marketing Vision and new products including OneSignal AI, Brand Center, MCP, and Slack Agent",
        "body": "Hi Launch YC,\n\nI'm the founder and CEO of OneSignal. Today, we're announcing our new AI vision, and I'm excited to share it with the Launch YC community.\n\n<https://www.youtube.com/watch?v=r7ccDbGVJ5U>\n\n**The problem**\n\nOneSignal first went through YC as a mobile gaming company called Hiptic Games.\n\nAfter pivoting away from mobile games, we used our experience to uncover an opportunity to truly \"Make something people want,\" and began working toward a mission to Democratize Customer Engagement for B2C companies.\n\nFor years, most B2C marketing automation products have had lengthy implementation processes, dated interfaces, and a learning curve steep enough that many teams hire a full-time expert. Many of them were also built in a world where email was the dominant channel, and have zero or weak support campaigns that span across Email, Mobile Push, SMS/RCS, and other channels.\n\nIn contrast, we made OneSignal incredibly easy to use from the start: customers can get going for free with an intuitive product experience, a powerful suite of tools for omni-channel messaging, and the performance to support some of the largest brands in the world. Today, OneSignal sends billions of daily messages for hundreds of thousands of active apps.\n\nBut no matter how easy and powerful we made the product, marketers still needed to bring a lot of their own time and expertise to get the best results from their campaigns.\n\n**The solution**\n\nToday, I'm excited to announce our vision and the products that will make lifecycle marketing autonomous. Our mission is still to Democratize Customer Engagement, but with AI we can achieve it in ways that were never possible before. This AI vision enables us to empower under-resourced marketing teams with the time and expertise that has seemed always out of reach.\n\nWe've broken this mission into phases, which we think of as an autonomy ladder. Most marketers don't want to hand the keys to an autonomous system on day one, so we'll roll out features that build the systems and trust needed at each step.\n\n![uploaded image](/media/?type=post&id=105807&key=user_uploads/5571/09a43a18-3ca8-4268-bd70-ab1798220546)\n\n**Level 0 — Manual.** The dashboard. A marketer drives every click, and the team scales by hiring. This is where the entire category has lived.\n\n**Level 1 — Assistance.** AI drafts copy, suggests audiences, and explains your analytics in plain language. You review and ship. This is live today.\n\n**Level 2 — Expert Assist.** AI becomes proactive. It recommends campaigns to fill lifecycle gaps, flags mistakes, and checks your work. Your input is still required.\n\n**Level 3 — Agentic Autopilot.** You delegate bounded work, and AI does it within the scope and rules you've defined. You approve work in batches.\n\n**Level 4 — Full Operator.** You set the goals and the guardrails. AI plans, sends, tests, and improves campaigns against them, reaching out only when it needs you.\n\n**What we're launching today**\n\n![uploaded image](/media/?type=post&id=105807&key=user_uploads/5571/da0aff66-9335-4ac3-87bf-d61aaa95b014)\n\n**OneSignal AI** — An in-product agent that can do everything a person can: generate message copy, design emails, analyze message performance, and recommend next steps to maximize user engagement. Best of all, it can create and analyze complex multi-step Journeys, saving hours of work.\n\n![uploaded image](/media/?type=post&id=105807&key=user_uploads/5571/f96522b2-51f9-404c-83fe-5b8bcbf4618a)\n\n**Brand Kit** — Define your audience, voice and tone, industry, and visual assets on a centralized configuration page or pull them automatically from your website. Set guardrails for language to avoid. OneSignal AI uses your Brand Kit when generating copy, email designs, and in-app messages.\n\n![uploaded image](/media/?type=post&id=105807&key=user_uploads/5571/b4c791bc-66cd-4849-afbf-d6921338d492)\n\n**OneSignal MCP** — Brings OneSignal's capabilities to the AI tools and agents you already use. The MCP is available now on the ChatGPT and Cursor marketplaces, coming soon to the Claude marketplace, and available through Smithery for any other AI client. Together, the MCP and the OneSignal API make it possible to use the platform in a fully headless way.\n\n![uploaded image](/media/?type=post&id=105807&key=user_uploads/5571/16f8ec08-92f4-4612-b342-555017d5082b)\n\nSoon, we'll also release a OneSignal Slack Agent, bringing the capabilities of OneSignal AI and the OneSignal MCP to where your team already spends its time. And we'll be rolling out an API to create, edit, and analyze Journeys, so your team can set up complex campaigns without ever logging into the OneSignal dashboard.\n\n**Try it today**\n\nAll of these features are available on OneSignal's free plan. Small companies can send unlimited push notifications and up to 10,000 emails per month for free. Paid plans start at $19/mo plus affordable usage-based pricing. Installing OneSignal is as simple as copying a prompt into Claude Code. You can get started at https://onesignal.com",
        "url": "https://www.ycombinator.com/launches/RWZ-onesignal-is-powering-autonomous-lifecycle-marketing-for-b2c-companies",
        "votes": 5,
        "created_at": "2026-07-14T22:59:31.042Z"
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    "all_locations": "San Francisco, CA, USA; Palo Alto, CA, USA",
    "long_description": "Proxino is a cloud platform for monitoring and debugging client-side JavaScript.",
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    "long_description": "Nobody should have to employ expensive imaging scientists and engineers for their business to get the most out of their visual media. This is where imgix has your back. imgix is a platform for managing, processing, rendering, optimizing, and delivering your existing visual assets so that you can meet the demands of your business and your team can stay focused on what they do best.\r\n\r\nThe business demands on web visual media can blindside even the most hyper-aware content teams and developers. Just to be competitive on the Internet, you need your images to be sized perfectly to every device, served in one of any of a half dozen web formats, optimized to the absolute best perceptual quality while maintaining pinpoint performance, and distributed to wherever your users are, anywhere in the world. And that is just the baseline. Next-level imaging concerns like copyright, licensing, accessibility, moderation, illegal or explicit content, \"fake news\", and more, can threaten your business at any moment if not handled properly. Get any of these things wrong and you are shedding revenue, ceding ground to competitors, and potentially exposing your business to extreme liability.\r\n\r\nBy working with imgix's powerful APIs, SDKs, user interfaces, and integrations, you can rest assured that any demands on your images and videos will always be met, now and into the future, without you having to invest in building it yourself or patching together a mishmash of open source and third-party technologies. Our platform is designed to ensure that your images are always working for your business and never against it.\r\n\r\nimgix was launched through the famed Y Combinator accelerator program. Its customers include Google, Lyft, Kickstarter, AirBnb, Coursera, Bonobos, Spotify, Vimeo, Bustle, and many others.",
    "one_liner": "The platform for your visual media.",
    "team_size": 34,
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    "long_description": "It's a better way to build frontend. It connects your Stories, Tokens, & Figma components. It lets you inspect designs with confidence and speed. And you can use it in Storybook.",
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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": "A close friend and classmate in graduate school, Lee Lin, encouraged us to apply. Lee went through YC in S09 (incidentally, the same batch as Stripe!) and supported us throughout our entire YC journey by providing valuable feedback on our application, giving us practical advice on the interview, and even flying into California just to attend our Demo Day! The written application itself was very straightforward. YC makes it extremely easy with their online application. If you are working on a startup or even just an idea, you having absolutely nothing to lose by writing and submitting an application! I will admit that the interview (in-person at YC’s HQ in Mountain View, CA) was quite stressful. The nervous energy that permeated the air of the lobby and lounge area, mere steps away from the rooms in which interviews were taking place, was palpable. Naturally, the interview was the classic 10-min rapid fire format. I recall one of the first questions we were asked was quite pointed: “Many have tried to build what you two are doing and failed. How are you guys different?” Deep breathe. Do not get defensive. Answer the question succinctly and confidently. The 10 min were over before we knew it. It was stressful, but fair. Afterwards, we went to Castro street in downtown Mountain View to have dinner. In the middle of dinner, we received the call that would forever change our lives (“We would love to fund you guys!”). We immediately accepted YC’s offer of funding over the phone. We ended up having about a month from our acceptance into YC until the actual start of the batch. In the interim, there were some housekeeping items to attend to such as sending copies of our startup’s incorporation documents and other legal documents to YC’s Legal team and Finance team for review so we could receive YC’s investment! While still in the Bay Area, shortly after our interview, I remember attending a pre-batch kick-off event where Michael Seibel welcomed us to YC. I recall Michael said (paraphrasing), “So, technically the ‘batch’ has not started yet officially… but ‘YC itself’ has already started. So… I suggest you all get started! Like, right now! You can literally start booking office hours today! Start building and talking to your customers! We’ll see you this summer!”) Before long the summer came and the formal programming of the batch began. Things moved fast and we quickly settled into what would become a familiar rhythm: Write code. Talk to customers. Write more code. Talk to more customers. Write even more code. Talk to even more customers. Rinse and repeat. The weekly small group office hours and dinner events were highlights of each week that served to inspire and invigorate. The first dinner event featured the co-founder of Airbnb as a guest speaker, and subsequent dinner guests included Garry Tan (now president of YC!), Brian Armstrong (Coinbase), and even a special guest appearance from the legends themselves - Paul Graham and Jessica Livingston! Demo Day and fundraising were the culmination of our three months of hard work during the batch. The event would be split over two days and held at the venerable Computer History Museum in Mountain View, CA. Sadly, our batch (S18) would be the last batch to be hosted by the museum for Demo Day (due to the larger sizes of subsequent batches). Much like the lobby and lounge of YC’s HQ on interview day, the nervous energy in the backstage green room of the Computer History Museum auditorium was palpable with people pacing back and forth, meditating, or silently rehearsing their pitch one last time. Before long, it was our turn, and the Batch Director fitted the one of us who would be speaking (Olivier) with a microphone and sent us out on stage. The pitch exceeded our own expectations and was delivered with gravitas, poise, and even a touch of humor. The successful pitch was all thanks to the generous time and support of many partners, most notably our group partners Aaron Harris, Adora Cheung, and Yuri Sagalov, but also other partners including Dalton Caldwell. As soon as we finished our pitch, the “likes” from investors came flooding in through the Demo Day software. Fundraising is usually a tough slog and one has to usually deal with many rejections for every “yes” that they receive. The whole process can take several months to upwards of an entire year. We were very fortunate to be in the top-third of our batch in terms of ease of fundraising, with far more “yes” than “no” responses and we were ultimately able to wrap up our fundraising in less than a week. I will note that success in fundraising at Demo Day is not necessarily predictive of future success as a company - so do not get lulled into a false sense of security just because fundraising comes relatively easier to you at Demo Day. There is a quite a vast distance between the moment that one decides to start a company and the moment that one actually sees it get off the ground. Unfortunately, the reality of startup life is that the journey across this distance (and beyond) can often be emotionally brutal; rife with feelings of intense loneliness which have to be balanced against a massive faith in what you are doing – a faith that is hard to sustain alone. We can truly think of no other partner we would want more than YC in embarking on such a journey. Special thanks to our group partners Aaron Harris, Adora Cheung, and Yuri Sagalov. They did NOT read drafts of this write-up, but we can unequivocally say that we would not have made it this far if it were not for their support and wise counsel."
      },
      {
        "question": "How have you kept in touch with the YC community and continued to use YC resources & programs since the batch ended?",
        "answer": "After our YC batch formally concluded in Sep 2018, we have kept in touch with the YC community through YC’s internal social network Bookface (think of it as a combination of LinkedIn, Quora, and Wikipedia). > Olivier: “I check Bookface at least once a day and it has been an invaluable source of knowledge, tips & tricks, and sometimes much needed humor/relief from the occasional ennui that comes with the territory of being a founder.”Alumni Demo Days (a dress rehearsal / practice-run of Demo Day in which the audience is made up of YC alumni / affiliates instead of professional investors) are also another excellent way for alumni to remained connected with the YC community. > Olivier: “I have attended every single Alumni Demo Day since becoming an alum. For the W19 and S19 batches, I was fortunate to attend in-person in San Francisco. These were very fun, well organized events and doubled as a kind of ‘YC mini-reunion’ of sorts - I miss them greatly. All subsequent batches (W20, S20, W21, S21, W22, S22) I have attended were done remotely through Zoom. Remote Demo Days have also been well organized (and with great music!), but naturally, they cannot compete with the experience of being in-person!”"
      },
      {
        "question": "What's the history of your company from getting started until the present day? What were the big inflection points?",
        "answer": "Alpha Vantage began as a passion project created over winter break while the co-founders were in grad school together. Our first major inflection point came less than two months after Alpha Vantage went live, when a large incumbent/competitor called Yahoo Finance abruptly pulled the plug on their market data API, resulting in a massive influx of self-proclaimed “Yahoo Finance shipwreck survivors” (users who were previously using the Yahoo Finance market data API) coming to Alpha Vantage. Seemingly overnight the number of our active users and the number of API queries processed jumped by over 10x. We have never looked back since."
      },
      {
        "question": "What is the core problem you are solving? Why is this a big problem? What made you decide to work on it?",
        "answer": "High quality financial market information (e.g. stock price data of publicly traded companies) has traditionally been available only to large organizations/institutions and generally inaccessible (or very high friction to access) for individual end users. Companies such as Bloomberg and Thomson Reuters have created multi-billion dollar businesses catering to these large organizations/institutions and a specific type of user: the Wall Street trader. Traders in the modern day; however, are different. Traders today more closely resemble software developers who would prefer to access data via API as opposed to a closed-system such as a Bloomberg terminal (an expensive piece of financial hardware that one would find in virtually every financial institution). We know this for a fact because the exponential adoption and the intensity of usage of our APIs from the earliest days of our company all the way to the present have proven this time and time again."
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    "long_description": "Cosmic is an AI-powered headless CMS built for teams that move fast. We combine flexible content infrastructure with AI Agents that live in Slack, write content, build features, fix bugs, and deploy apps autonomously.\r\n\r\nDevelopers get a REST API with sub-100ms response times, a TypeScript SDK, CLI, and MCP Server that plugs directly into Cursor, Claude Code, and GitHub Copilot. Content teams get an intuitive dashboard with 20+ metafield types, AI image and video generation, and no migrations ever.\r\n\r\nTeams use Cosmic because it eliminates the need to build and maintain CMS infrastructure while giving them AI capabilities most platforms haven't shipped yet. Used by teams in 150+ countries, 50M+ API requests per month, 99.9% uptime SLA.\r\n\r\nForever free plan. No credit card required.",
    "one_liner": "Cosmic is an AI-powered headless CMS",
    "team_size": 5,
    "industry": "B2B",
    "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"
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    ],
    "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"
      }
    ]
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    "id": 12356,
    "name": "Memfault",
    "slug": "memfault",
    "former_names": [
      "Memfault",
      "Inc"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/69aff41aabfb54d70629bb4411a828953bd10011.png",
    "website": "https://memfault.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Memfault is the first IoT reliability platform that empowers teams to build more robust devices with software at scale. We believe that device reliability engineering will transform how developers build and operate IoT and edge devices with more productivity and more collaboration. As IoT applications continue to grow in complexity, it is more important than ever for developers to have Memfault’s performance monitoring, device debugging, and OTA update capabilities built into their fleet of devices for proactive device operations. We built Memfault to enable developers with a more scalable and sustainable process to accelerate go-to-market, de-risk product launches, cut product costs, and deliver overall superior products.",
    "one_liner": "First IoT reliability platform for debugging, monitoring, OTA updates",
    "team_size": 80,
    "industry": "B2B",
    "subindustry": "B2B -> Analytics",
    "launched_at": 1545442498,
    "tags": [
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    "top_company": false,
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    "nonprofit": false,
    "batch": "Winter 2019",
    "status": "Acquired",
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      "America / Canada",
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    "app_video_public": false,
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    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/memfault",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2019/memfault.json",
    "year_founded": 2018,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/memfault/",
    "x_url": "https://twitter.com/Memfault",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/memfault",
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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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        "full_name": "François Baldassari",
        "title": "Founder",
        "founder_bio": "",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/francois-baldassari-63a8b91a/",
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      },
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        "user_id": 305559,
        "full_name": "Christopher Coleman",
        "title": "Founder",
        "founder_bio": null,
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/christopher-coleman-812aa06b/",
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        "user_id": 305533,
        "full_name": "Tyler Hoffman",
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        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/tyhoff/",
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    "jobs": [],
    "news": [
      {
        "title": "Memfault raises $24M to help companies manage their growing IoT device fleets • TechCrunch",
        "url": "https://techcrunch.com/2023/01/24/memfault-raises-24m-to-help-companies-manage-their-iot-devices/",
        "date": "Jan 24, 2023"
      },
      {
        "title": "Memfault Raises $8.5M To Level The Playing Field For Hardware Developers – Crunchbase News",
        "url": "https://news.crunchbase.com/news/memfault-raises-8-5m-to-level-the-playing-field-for-hardware-developers/",
        "date": "Jun 30, 2021"
      },
      {
        "title": "Monitoring, Debugging and Updating Nordic-Powered IoT Products Made Easy with Device Observability Platform Partnership | IoT For All",
        "url": "https://www.iotforall.com/press-releases/nordic-powered-iot-device-observability-platform",
        "date": "Jun 30, 2021"
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  {
    "id": 12502,
    "name": "Bun",
    "slug": "bun",
    "former_names": [
      "Codeblog",
      "Webthing"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6cf9201e83fba23f5038d47b722860fb10f40642.png",
    "website": "https://bun.sh",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Bun is an incredibly fast all-in-one toolkit for building, installing, running, and testing JavaScript and TypeScript. We were born out of frustration with the fragmented, slow JavaScript ecosystem and are on a mission to make JavaScript development faster and more productive.",
    "one_liner": "Bun is an incredibly fast all-in-one JavaScript toolkit",
    "team_size": 13,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1746486339,
    "tags": [
      "Developer Tools",
      "Open Source"
    ],
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2019",
    "status": "Acquired",
    "industries": [
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      "Infrastructure"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Growth",
    "app_video_public": false,
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/bun",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2019/bun.json",
    "year_founded": 2019,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/ovensh/",
    "x_url": "https://x.com/bunjavascript",
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    "github_url": "https://github.com/oven-sh",
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    "primary_partner": {
      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
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    "founders": [
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        "user_id": 22277,
        "full_name": "Jarred Sumner",
        "title": "Founder",
        "founder_bio": "Bun is an all-in-one JavaScript runtime, bundler, package manager, test runner. We're making JavaScript faster. Our current goal is to replace Node.js as the default JavaScript runtime.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/profile/view?id=88385287&trk=spm_pic",
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  {
    "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"
    ],
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    "top_company": false,
    "isHiring": false,
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        "body": "**TLDR -** [Porter](https://porter.run) is a Platform as a Service (PaaS) that runs in your own cloud. It brings the magical experience of deploying your applications with a few clicks into your own cloud account. After a year since we closed down our self-serve flow, we are opening Porter back up for self-serve today.\n\n* [Sign up here](https://dashboard.getporter.dev) and start deploying applications on your own infrastructure that scales with you.\n* [Claim $10,000 in credits](https://gcpjnf9adme.typeform.com/to/lHMQdJYb) if your company is enrolled in YC Startup School. Along with the AWS credits you can claim from Startup School, this deal effectively lets you deploy on a PaaS for free - it’s like using Heroku with your AWS credits!\n\n![uploaded image](/media/?type=post&id=71916&key=user_uploads/323071/cc2f3fac-340f-4f39-9e4d-533f7ab40053)\n\n## **What is Porter?**\n\nHi everyone,\n\nWe are Trevor and Justin from [Porter](https://porter.run/). 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Moving off production applications off a PaaS is time-consuming and difficult, and hosting all of your infrastructure on in-house solutions of a single PaaS vendor comes with the risk of getting locked in.\n\nPorter hits the sweet spot between simplicity and flexibility by allowing startups to deploy into their own cloud infrastructure with the convenience of a PaaS. Get started on Porter just as easily as you would on a traditional PaaS, then customize your infrastructure freely as you grow. 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        "body": "Hey, we’re Ben and Jason! (S11 / W20)\n\nWe’re announcing [**Enveloop**](https://enveloop.com) — a developer-focused **message builder** and **API** that makes it easy to design & send beautiful emails and texts from your app using one simple implementation. And you don’t have to be a designer — we’re focused on making developers look awesome. 🤩\n\n### **📣 Why We Built Enveloop**\n\nDevelopers create apps. Apps need to talk to users. Simple, right? Unfortunately — multiple APIs, maintaining message content, design standards, delivery standards, handling failure/retry -- you have to figure it all out, and, over time, **it all becomes scattered in your code.**\n\n_Worse_ — the content is inaccessible to those that need to edit it because it’s mixed with the design & implementation — buried in your code with all that other complexity. That puts **you** in the middle of any update, big or small. Gross. \n\nWe’ve built a graceful service that solves this. It’s simple for developers, collaborative for consultants and their clients, and ready for fast-moving product & development teams. **It’s Enveloop.**\n\n### **💪 Our Solution**\n\nWith Enveloop, we offer developers:\n\n* A powerful & friendly-to-use message builder.\n* Loads of elegantly-designed templates to get you started quickly.\n* Intuitive formatting built with developers in mind (markdown, mustache, etc.)\n* A single API that supports multiple message types and providers.\n* Easy delegation of message content to others on your team (or to your clients!)\n\nAll this helps to **remove unnecessary code/complexity** from your app and **reduces superficial deployments**. And more is on the way, including support for additional message types and useful message analytics.\n\n![uploaded image](/media/?type=post&id=67598&key=user_uploads/24221/8b766f45-e4c3-4014-ac55-1c5b6cd8d23d)\n\n### **🙏 Our Ask**\n\nWe would love to have you try out **Enveloop**! We’ll automatically upgrade you to our Pro plan for three (3) months at no charge. \n\nAlso, **Share this Post!** Let us know at [founders@enveloop.com](mailto:founders@enveloop.com), and we’ll send a couple of extra goodies your way — just for spreading the word and trying us out!\n\nYou can [sign up for Enveloop](https://app.enveloop.com/auth/new) and get started now!\n\nJason & Ben\n\nFounders, [Enveloop.com](http://Enveloop.com)\\\nW20 / S11",
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        "title": "🤖 SmartTests: AI powered Contract Testing",
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        "body": "Hey everyone! We’re [Arjun](https://www.linkedin.com/in/arjun-iyer-916332/) and [Anirudh](https://www.linkedin.com/in/anirudhrx/), co-founders of [Signadot](https://www.signadot.com/) and we’re simplifying the lives of developers building distributed cloud native applications.\n\n# **🎯tl;dr**\n\nSmartTests automatically catch breaking API changes in microservices without writing contracts or maintaining mocks. AI compares your new code against baseline behavior using real traffic and only flags changes that actually matter.\n\nDemo video: https://youtu.be/HHGgSKk2K_k\n\n# ❗️Problem\n\nMicroservices break each other all the time. A team changes their API response format, and suddenly three downstream services start failing in production. The usual solution is contract testing, but here's the reality: most teams either skip it entirely or abandon it after a few months.\n\nWhy? Current tools put the entire burden on developers. You have to write consumer contracts for every API interaction, maintain mock servers, and keep updating tests every time contracts change. It's exhausting busywork that pulls focus from shipping features. Teams know they should do it, but the tooling makes it feel like a second job.\n\n# **💡** Solution\n\nSmartTests flip the script on contract testing. Instead of forcing developers to predict every possible breaking change, we observe real API interactions and automatically catch contract violations. Write a simple test in Starlark, and our AI compares baseline behavior against your changes to spot what actually matters.\n\nNo mock servers to maintain. No contract files to update. No noise about irrelevant changes. Just fast, accurate feedback in your PRs that tells you when you're about to break something downstream.\n\n# 🏃How does it work?\n\nWhen you push code, SmartTests spin up lightweight sandboxes in your Kubernetes cluster and run your test scripts against both the new version and the baseline. These aren't mocked interactions—they're real API calls hitting real services in isolated environments.\n\nThe magic happens in the comparison. Our AI analyzes the responses from both versions and figures out which differences actually matter. Did you add a new optional field? Probably fine. Did you change a required field's data type? That's going to break things. The AI surfaces only the changes that could affect downstream services, so you get signal instead of noise.\n\n![uploaded image](/media/?type=post&id=90673&key=user_uploads/47401/298831aa-1812-4117-8461-1a77db646e8c)\n\n# **💯** Why did we build this?\n\nWe kept hearing the same story from engineering teams: \"We tried existing tools, but it was too much work to maintain.\" When developers abandon tools that should make their lives easier, the tool is the problem, not the developers.\n\nThe breaking point was talking to a team at a Series B company who had spent three months setting up comprehensive Pact tests, only to disable them six months later because they couldn't keep up with the maintenance burden. That's when I realized we needed to completely rethink the approach—AI could handle the heavy lifting leaving developers to focus on what they do best: building great software.\n\n# 👍 How do I get access?\n\nJust sign up using https://www.signadot.com/ and try our [Quickstart](https://www.signadot.com/docs/tutorials/quickstart/contract-testing) guide. Feedback is much appreciated!",
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        "body": "**tl;dr**: If you’re running microservices, you can now use Signadot to help developers ship features faster using lightweight dev environments. These environments spin up in seconds within a Kubernetes cluster **that you run** and scale well across hundreds of developers and microservices without incurring large infrastructure costs or maintenance burdens. These environments are built on top of “Sandboxes”, a new approach that is used in companies like [**Uber**](https://www.uber.com/blog/simplifying-developer-testing-through-slate/) and [**Lyft**](https://eng.lyft.com/scaling-productivity-on-microservices-at-lyft-part-3-extending-our-envoy-mesh-with-staging-fdaafafca82f) and we’re excited to make that available to everyone.\n\nWe launched about a year ago, with a focus on preview & test environments in Kubernetes. With our latest update, we’re adding the following new capabilities:\n\n* Developers can now run the **dev version of a microservice on their laptop** and seamlessly connect it to a shared Kubernetes cluster and start testing as though the whole application were running locally. They get 10x faster feedback by testing their changes in a live Kubernetes environment during active development. \n* Multiple such dev environments can be combined together to **test different microservices with each other** as they're being developed. This means developers can collaborate and get a feature spanning different microservices working end-to-end long before their code gets merged or hits a staging/production environment.\n\n### **How does it work?**\n\nJust as before, we use request routing (using a Service Mesh like [**Istio**](https://istio.io/) or a sidecar-based system that we built) to isolate these environments from one another in a shared Kubernetes cluster.\n\n![](https://ph-files.imgix.net/f5efe69b-ed3c-4306-af3e-c5d757877d7a.png?auto=compress&codec=mozjpeg&cs=strip&auto=format&fit=max)\n\nRead more about our launch [**here**](https://www.signadot.com/blog/bridging-the-gap-local-testing-in-shared-kubernetes-clusters), or watch a video of how teams use these dev environments here: [**https://www.youtube.com/watch?v=HXUmPJTdwm0**](https://www.youtube.com/watch?v=HXUmPJTdwm0\\*\\*)\n\n### **How do I get access**\n\nJust sign up using [**https://www.signadot.com/signup**](https://www.signadot.com/signup\\*\\*) and try one of our [**quickstart**](https://www.signadot.com/docs/quickstart) guides. Feedback is much appreciated!",
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        "tagline": "Spin up lightweight environments to enable pre-merge testing for microservices. Discover issues before merging code and ship new features faster.",
        "body": "### 😎 **TL;DR**\n\nWe’re building a Kubernetes-based solution that enables environments, called Sandboxes, to test your microservices early in the development lifecycle. Unlike traditional environments, Sandboxes are lightweight and spin up in seconds. This makes it cost-effective to create test environments for every pull request, branch, and commit.\n\n### 🤔 **The problem with traditional environments**\n\nMost engineering teams use pre-production environments, called staging environments, to test against real-world conditions. However, testing on staging introduces the following challenges:\n\n1. Staging environments are typically shared among engineering teams and regressions introduced here block other developers. This results in frequent roll backs to unblock others.\n2. Since commits from various teams are co-mingled on staging, breakages take a long time to troubleshoot and fix. As the engineering team grows, this problem only gets worse and development slows down.\n\n### **😅 Enter Signadot**\n\nWith Signadot, DevOps teams can set up lightweight environments, called Sandboxes, that can be used to test each pull request/commit. Teams run a suite of integration and end-to-end tests for each PR without impacting others. This helps find issues early that would otherwise be found in staging (or worse … in production!).\n\nOur CLI/YAML integrates with CI pipelines to automate the testing of Pull Requests. As shown in the image below, Sandboxes encapsulate “services-under-test” connected to other dependencies running in Kubernetes. Sandboxes are lightweight to spin up and cost-efficient at scale.\n\n![uploaded image](/media/?type=post&id=65752&key=user_uploads/47401/edb398f0-819b-43f3-9152-9ba015164069)\n\n### **🤓 How this helps your team:**\n\n* Minimize rollbacks on staging and production\n* Increase the frequency of production deployments\n* Save on infrastructure costs using lightweight Sandboxes\n\n### **🤩 Try us out!**\n\n1. [**Sign up for free**](https://www.signadot.com?utm_campaign=Launch%20YC&utm_source=yc&utm_medium=launchyc) **to start testing your microservices today**\n2. Join the discussion on testing strategies for microservices in our [Slack Community](https://signadotcommunity.slack.com/) or [GitHub Repo](https://github.com/signadot). You can also book a time to chat with one of our founders [here](https://calendly.com/signadot/demo).",
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        "title": "Release AI — Talk to your Infrastructure",
        "tagline": "Engage in meaningful conversations with your AWS account and your K8s infrastructure.",
        "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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        "title": "Instant Datasets — Production data for development",
        "tagline": "The easiest way to develop with production data",
        "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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        "body": "# **Say goodbye to soul-sucking tech vendor evaluations.**\n\n![uploaded image](/media/?type=post&id=81316&key=user_uploads/429966/3d1eaab4-19dd-4a32-8d03-d24ef138f7c4)\n\n### **Why**\n\nWe built [Taloflow](https://www.taloflow.ai) to solve technology and software vendor selection–CRM, ERP, HRIS, Internal Developer Portals, Object Storage, API Gateways, etc. Having been deeply involved in the tech scene, I saw firsthand how a wrong or slow decision could make or break any project or company. The endless options, opaque pricing, ambiguous features, and subjective and biased reviews make evaluating vendors challenging.\n\n**“Wait, but isn’t this solved?”** you may ask. Nope. Gartner (if you can afford the subscription), G2, and the like offer mostly generic insights. You’re on your own to determine exactly the solution that’s most relevant to you.\n\n### **What**\n\nSince our last launch, we’ve done extensive research into the needs of enterprise customers. This new platform is designed to be collaborative from the ground up, delivers clear, data-driven recommendations tailored to specific use cases, and comes with all the CYA you could imagine. We’ve also leaned in on AI to allow our analysts to assess, curate, and refresh vendor data much faster and in more categories for our customers.\n\n![uploaded image](/media/?type=post&id=81316&key=user_uploads/429966/fb671e0a-75df-4a8f-ae65-89332a95374c)\n\n**Key Features**\n\n1. Use case questionnaire to pinpoint your exact needs.\n2. AI and expert-assessed feature ratings for solutions.\n3. Real-time feedback based on your changing inputs.\n4. Over 100,000 AI and expert-curated data points.\n5. Real-time collaboration (Notion or Google Doc-like UX) and audit logs.\n6. Tailored reports based on detailed user inputs and needs.\n\n![uploaded image](/media/?type=post&id=81316&key=user_uploads/429966/bf97e132-5355-412a-af2a-ae7bf6ca2415)\n\nTaloflow helps its customers succeed by bringing transparency and precision to a process mired in confusion and subjectivity. We aim to change how businesses select technology by helping them skip the frustrating parts–like requirements gathering, vendor demos, prioritizing, and scoring–and presenting the best, unbiased insights.\n\n![uploaded image](/media/?type=post&id=81316&key=user_uploads/429966/236b0f02-9afd-46d7-b1c5-20ad4c2a7964)\n\nLooking forward to hearing about the kinds of technology selection projects we can help you with!\n\n[Book a demo](https://www.calendly.com/taloflow/demo) or [try the product](https://use.taloflow.ai/signup) for free.\n\nUpside,\n\nLV",
        "url": "https://www.ycombinator.com/launches/L9Y-taloflow-2-0-evaluate-tech-vendors-10x-faster",
        "votes": 6,
        "created_at": "2024-06-05T14:19:49.094Z"
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        "id": 68621,
        "title": "SigNoz - Open source alternative to DataDog, New Relic",
        "tagline": "Open Source Metrics, Traces and Logs in a single pane of glass",
        "body": "Hey folks 👋\n\nWe are thrilled to share SigNoz with the YC community today!\n\n[SigNoz](https://signoz.io?utm_source=launchYC&utm_medium=homepage) is an open source alternative to DataDog, New Relic which helps developers monitor their applications, trouble shoot problems and get proactive alerts\n\nWe have quite an active dev community with **11,000+** github stars, **1800+** members in our slack community and **80+** contributors across our repos.\n\n**😫 Problem**\n\n* Engineering teams are frustrated with using different tools for different telemetry signals like metrics, traces and logs. Correlating across different tools is super critical for teams to get value out of their telemetry data and solve issues faster.\n* Using proprietary vendor instrumentation code, locks you in to a vendor as it is difficult to change your instrumentation at a later stage.\n* Sending all data to vendor cloud may have privacy and security concerns for some users esp. who have customer PII data or have to maintain a tighter security posture\n\n**🚀 Why SigNoz?**\n\n1. Single pane of glass for metrics, traces and logs in a single application. Ability to correlate across different telemetry signals very easily.\n2. Natively based on [OpenTelemetry](https://opentelemetry.io) - and emerging open source standard for instrumentation and telemetry collection.\n3. Uses OLAP datastore (ClickHouse) which makes aggregation queries 10x faster compared to traditional DBs. \\\n   More than 50-60% of observability related queries are aggregation queries like group by, sum, count where users want to aggregate their data\n4. Can be self hosted easily. Keep all observability data in your own cloud.\n\n💻 **Demo**\n\nHere’s a quick demo of the product\n\n[Demo Video](https://youtu.be/Tl3Cz8tz4R8)\n\n💪 **Logs Performance Benchmark**\n\nWe also published a performance benchmark recently on how SigNoz logs product performs compared to other open source logs solutions like Elastic\n\n[https://signoz.io/blog/logs-performance-benchmark/](https://signoz.io/blog/logs-performance-benchmark/?utm_source=launchYC&utm_medium=logs-benchmark)\\\n\\\n**🙏 Asks**\n\nTry out SigNoz and share your feedback on how it can be improved. Here’s our github repo - <https://github.com/signoz/signoz>\n\nHave any questions? Join our [slack community](https://signoz.io/slack?utm_source=launchYC&utm_medium=slack-community) and drop a note\n\n😎 **What do we do for fun?**\n\nWe are a lean team constantly re-imagining the future of observability. Here’s a picture of our team from a recent workation at Goa\n\n![uploaded image](/media/?type=post&id=68621&key=user_uploads/95650/4a4d8bd7-7975-4e43-bc1e-394c7859d63d)\n\n![uploaded image](/media/?type=post&id=68621&key=user_uploads/95650/02c70ae9-d6a7-4fc3-97d5-5edd635dc5b9)\n\n",
        "url": "https://www.ycombinator.com/launches/Hqn-signoz-open-source-alternative-to-datadog-new-relic",
        "votes": 47,
        "created_at": "2023-01-23T13:19:49.300Z"
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        "linkedin_url": "https://www.linkedin.com/in/will-ernst-71557297/",
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    "one_liner": "Communication and publishing tools for scientists",
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        "answer": "Platform to build, remix, share & explore science"
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        "answer": "We are creating an online platform for writing, sharing and re-using scientific content. iooxa is connecting the building blocks that make up documents and presentations to their computational origins, so that they can remain linked and interactive -- enabling interrogation, adaptation, organization and extension of ideas.\r\n\r\nOur approach is to create small, meaningful “blocks” of content (e.g. figures, equations, paragraphs, code) that track versioning, licensing and attribution. These blocks can be composed into traditional, linear documents or pulled apart and rearranged. We enable collaboration across a spectrum of computational abilities, through integrations with Jupyter Notebooks to track experimental progress and “import” interactive outputs into reports, documents, and presentations."
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        "full_name": "Rowan Cockett",
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        "full_name": "Steve Purves",
        "title": "Founder",
        "founder_bio": "An engineer with 20+ years industry experience building software for scientists and engineers. Deep technical expertise in computer vision, data science and machine learning. Led product development and R&D teams and managed multi-year R&D projects with Oil & Gas majors. In 2013, he founded a consultancy and leading distributed technical teams in both startups and enterprise in energy, healthcare, finance and electronic manufacturing. Founding member of an open geoscience society.",
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    "id": 22743,
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    "all_locations": "Brussels, Brussels, Belgium; Remote",
    "long_description": "[Segments.ai](http://segments.ai/) is helping robotics and automotive companies label their multi-sensor data for AI training and validation. Our platform enables customers to efficiently annotate their point cloud and image data, accelerating their path to autonomy.\r\n\r\nWe're a fast-growing, remote-first YC startup with a lean team and healthy runway. [Segments.ai](http://segments.ai/) is used by large organizations as well as innovative startups building the next generation of autonomous drones, delivery robots, self-driving cars, and more.",
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      "Fully Remote"
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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": "In 2020, [Segments.ai](http://Segments.ai) launched as a data labeling solution designed explicitly for segmentation. Initially, we had many customers in the robotics and autonomous driving industries. This stimulated us to address the complex needs of autonomous navigation, leading us to introduce point cloud support.Through close collaboration with our customers, we quickly realized that manually labeling multiple modalities can be time-consuming, costly, and ineffective. Therefore, we shifted our focus towards providing multi-sensor support by integrating built-in projection steps and automation.HISTORY* Founded in early 2020 by Otto Debals (CEO) and Bert De Brabandere (CTO) after finishing their PhDs and gaining experience in the (automotive) industry* Funded in 2021 by YCombinator and other VC funds, including Merus Capital, Volta Ventures.* [Segments.ai](http://Segments.ai) is ISO27001 certified, GDPR compliant and EU based* We hired our first employee in 2021 and our first employee in the USA (where the majority of our customers are based) in 2023."
      },
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        "full_name": "Gustav Westling",
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        "id": 64214,
        "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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        "founder_bio": "Ali Khajeh-Hosseini is the co-founder of Infracost, where he leads Product and Customer Success. He has spent over a decade at the intersection of cloud infrastructure and cost optimization, including earning a PhD in cloud cost modeling—before \"FinOps\" was even a term. Prior to Infracost, Ali co-founded two cloud startups that were acquired. Today, he works closely with some of the world’s largest enterprises to make cloud costs actionable, automated, and developer-first.",
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        "user_id": 314766,
        "full_name": "Alistair Scott",
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        "founder_bio": "Co-founder of Infracost. Developer at heart. Love to ski and cook. Currently on a mission to cook a dish from every country in the world.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/aiscott/",
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        "title": "The next chapter in Shifting FinOps Left: Infracost has raised a $15 Million Series A - Infracost",
        "url": "https://www.infracost.io/blog/infracost-has-raised-a-15-million-series-a/",
        "date": "Nov 18, 2025"
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      {
        "title": "Infracost: The “DevFinance” Cloud Cost-Management Solution We Were Looking For | by Bogomil Balkansky | Sequoia Capital Publication | Sep, 2021 | Medium",
        "url": "https://medium.com/sequoia-capital/infracost-the-devfinance-cloud-cost-management-solution-we-were-looking-for-1cd75300a600",
        "date": "Sep 23, 2021"
      },
      {
        "title": "Infracost Raises $2.2m From Sequoia To Help Engineers Lower Their Cloud Computing Costs",
        "url": "https://www.forbes.com/sites/frederickdaso/2021/09/23/infracost-raises-22m-from-sequoia-to-help-engineers-lower-their-cloud-computing-costs/",
        "date": "Sep 23, 2021"
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    "id": 23290,
    "name": "Kitemaker",
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/31e1e3cc75ece89e87204c189c3bac074fa63d7b.png",
    "website": "https://kitemaker.co",
    "all_locations": "Oslo, Oslo, Norway; Remote",
    "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.",
    "one_liner": "A faster and more collaborative alternative to Jira for remote teams",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1614618589,
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      "Team Collaboration",
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    "country": "NO",
    "linkedin_url": "https://www.linkedin.com/company/kitemaker",
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        "user_id": 396937,
        "full_name": "Kevin Simons",
        "title": "Founder",
        "founder_bio": "Managed software development teams for about 10 years. Big believer in autonomous, cross-functional, self-organizing teams that are obsessed with delivering value to users.\n",
        "is_active": true,
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      {
        "id": 76035,
        "title": "Kitemaker - Build better software. Together.",
        "tagline": "Everything you need to organize the product development process",
        "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.",
        "url": "https://www.ycombinator.com/launches/JmN-kitemaker-build-better-software-together",
        "votes": 68,
        "created_at": "2023-11-07T16:16:30.689Z"
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    "url": "https://www.ycombinator.com/companies/galaxy",
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    "primary_partner": {
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        "full_name": "Adam Neuwirth",
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        "founder_bio": "Co-founder at https://launchpointhq.com",
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        "linkedin_url": "https://www.linkedin.com/in/adambn/",
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        "id": 70127,
        "title": "Galaxy 🕹️ - Social multiplayer for games",
        "tagline": "Add clans & community to any game in under an hour.",
        "body": "**The Problem:** Mobile games are fun for a while, but players get bored quickly (especially when it’s singleplayer)\n\n**The Solution:** Competing with friends makes games way more interesting\n\n![uploaded image](/media/?type=post&id=70127&key=user_uploads/263116/31b26d16-89c8-4088-80a4-8d47611a6919)\n\nGalaxy is a free SDK that adds **community** to any single or multiplayer game (in less than an hour). \n\n* _Clans_: Players can create, join, and recruit teams. They compete against other teams and can chat with the group.\n* _Real Friends_: Players can sync their contacts and easily see/interact with their friends on leaderboards.\n* _Avatars_: Demonstrating the authenticity of opponents amplifies the feeling of winning. It also provides an optional revenue stream to games who want to sell cosmetics.\n* _Powerful Leaderboards:_ Configure & manage leaderboards from a dashboard. Set up automatic prizes, repeating tournaments, ban users, customize UI, and more.\n\nPlayers love it. Session length increases by \\~1m55s and D7 retention rises by as much as 37%. Additionally, teams encourage players to invite their friends who don’t already play the game - leading to free user growth as well. Here’s a graph from one of our customers after they added Clan leaderboards:  \n\n![uploaded image](/media/?type=post&id=70127&key=user_uploads/263116/a21e9395-7c8f-4bdd-b6bf-48c1949b33a9)\n\nBut what about implementation? We’ve worked hard to make it as simple as possible to implement. Here’s the steps:\n\n1. Call ReportScore()\n2. Call ShowLeaderboard()\n\nThat’s it! The UI is customizable, localized and works on mobile or web.\n\nWe’re already working with 115 games and serving over 250,000 end users. You can [sign up](https://galaxysdk.com) for free or [book a call](https://calendly.com/adambn/galaxy-sdk) if you’re interested.",
        "url": "https://www.ycombinator.com/launches/IF5-galaxy-social-multiplayer-for-games",
        "votes": 49,
        "created_at": "2023-03-10T02:32:14.148Z"
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    "long_description": "Svix is the enterprise ready and open source webhooks service.\r\n\r\nWebhooks are a pain. Developers need to worry about deliverability, retries, monitoring and security. All of which are different for webhooks compared to the rest of the stack. We turn all of that into a simple API call.\r\n\r\nSvix is sending billions of webhooks for customers both large (Fortune 500) and small (startups), and is backed by Y Combinator, Andreessen Horowitz (a16z), Aleph, and founders and CTOs of companies such as Github, PagerDuty, Segment and Lookout.",
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    "team_size": 12,
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    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1614619070,
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        "full_name": "Tom Hacohen",
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        "url": "https://www.svix.com/blog/new-round-of-funding-led-by-a16z/",
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    "id": 23370,
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        "full_name": "Sol Eun",
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        "linkedin_url": "https://www.linkedin.com/in/soleun/",
        "x_url": "https://twitter.com/soleun",
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    ],
    "jobs": [],
    "news": [
      {
        "title": "Uiflow secures cash and Freshworks partnership to bolster its app dev platform",
        "url": "https://techcrunch.com/2022/09/07/uiflow-secures-cash-and-freshworks-partnership-to-bolster-its-app-dev-platform/",
        "date": "Sep 07, 2022"
      },
      {
        "title": "Uiflow Raises $15M Series A, Transforming All Enterprises to Become Software Companies",
        "url": "https://blog.uiflow.com/posts/uiflow-raises-15m-series-a-transforming-all-enterprises-to-become-software-companies",
        "date": "Sep 07, 2022"
      }
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    "launches": []
  },
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    "id": 23412,
    "name": "Axolo",
    "slug": "axolo",
    "former_names": [
      "Chaos"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e88055a4e50a63fdeebdd7a8e460ccd4727ddf5a.png",
    "website": "https://axolo.co",
    "all_locations": "Paris, Île-de-France, France; Remote",
    "long_description": "Better Code Reviews, Less Hassle, All in Slack\r\n\r\nAxolo takes your team's code review practices to the next level, integrating seamlessly with Slack to deliver real-time notifications and natural discussions.",
    "one_liner": "Improving Developer Experience with Streamlined Code Reviews",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1628179871,
    "tags": [
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      "SaaS"
    ],
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2021",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "France",
      "Europe",
      "Remote",
      "Fully Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/axolo",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2021/axolo.json",
    "year_founded": 2021,
    "city": "Paris",
    "country": "FR",
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        "user_id": 549618,
        "full_name": "Arthur Coudouy",
        "title": "Founder",
        "founder_bio": "Co-founder & CEO @ axolo.co",
        "is_active": true,
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    "launches": [
      {
        "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"
      }
    ]
  },
  {
    "id": 23415,
    "name": "Friz",
    "slug": "friz",
    "former_names": [
      "Feige"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e03c6972dbbb7bfad3e7b3234b4c293d71b365cc.png",
    "website": "https://www.usefriz.com",
    "all_locations": "Singapore, Singapore",
    "long_description": "Brainstorm, create, publish and manage content and advertisements on social media using 1 tool.\r\n",
    "one_liner": "AI Social Media Manager",
    "team_size": 4,
    "industry": "Consumer",
    "subindustry": "Consumer -> Job and Career Services",
    "launched_at": 1614407757,
    "tags": [
      "Developer Tools",
      "SaaS",
      "Design Tools",
      "Social Media",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2021",
    "status": "Acquired",
    "industries": [
      "Consumer",
      "Job and Career Services"
    ],
    "regions": [
      "Singapore",
      "Southeast 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/friz",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2021/friz.json",
    "year_founded": 2020,
    "city": "Singapore",
    "country": "SG",
    "linkedin_url": "https://www.linkedin.com/company/usefriz",
    "x_url": "https://twitter.com/usefrizcom",
    "fb_url": "https://www.facebook.com/UseFriz/?ref=page_internal&path=%2FUseFriz%2F",
    "cb_url": "https://www.crunchbase.com/organization/feige-27e7",
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    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/e03c6972dbbb7bfad3e7b3234b4c293d71b365cc.png",
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    "founders": [
      {
        "user_id": 576527,
        "full_name": "Nirali Zaveri",
        "title": "Founder",
        "founder_bio": "Cofounder and CEO of Friz \n\nI started my career at Mastercard, building credit card for small businesses. My experience working with large SME credit card issuers like DBS, OCBC, UOB , BNI and BNP helped me realise the struggle freelancers face with financial services. I am passionate about empowering freelancers in Asia, a large percentage of whom are women. I have also filed 2 patents; in digital payments and credit scoring and love working to innovate in fintech. ",
        "is_active": true,
        "linkedin_url": "http://www.linkedin.com/in/niralizaveri",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/bc96bfac2843dd31e222af8141b9266cb4c16388.jpg"
      },
      {
        "user_id": 576540,
        "full_name": "Ash Rhazaly",
        "title": "Founder",
        "founder_bio": "Co-founder & CTO of Friz. Prior to Friz, Ash has been working at PPRO and DBS Bank as a Software Engineer on various financial products and services.  He was the first engineer in PPRO APAC and was integral in setting up the initial technical infrastructure and building the engineering team.\n",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/ash-rhazaly/",
        "x_url": "https://twitter.com/ashrhazaly",
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    "news": [
      {
        "title": "Y Combinator joins $1.5m fundraise by ex-Mastercard exec’s startup",
        "url": "https://www.techinasia.com/y-combinator-joins-15m-exmastercard-execs-startup-friz",
        "date": "Sep 30, 2021"
      },
      {
        "title": "Friz raises seed funding from YC, 500 Durians to help freelancers manage their finances better | e27",
        "url": "https://e27.co/friz-raises-seed-funding-from-yc-500-durians-to-help-freelancers-better-manage-their-finances-20210405/",
        "date": "Aug 28, 2021"
      },
      {
        "title": "Tech in Asia - Connecting Asia's startup ecosystem",
        "url": "https://www.techinasia.com/exmastercard-execs-startup-lands-sixfigure-funding-combinator",
        "date": "Aug 28, 2021"
      }
    ],
    "launches": [
      {
        "id": 77520,
        "title": "Friz - AI social media manager",
        "tagline": "Friz helps DTC brands automate brainstorming, creating, editing and scheduling content and ads.",
        "body": "Friz is an AI social media manager that helps DTC brands automate brainstorming, creating, editing and scheduling content and ads.\n\n![uploaded image](/media/?type=post&id=77520&key=user_uploads/576527/c61426a8-205d-4ef8-a6da-32408fd9b912)\n\n👨‍💻 Receive contextual posts and ads for your target audience and industry\n\n💡 Go from prompt to post with visuals and captions in your brand style\n\n🚀 Manage your entire calendar across various social media accounts from 1 place\n\nOur mission is to save your marketing teams time and money while growing conversions and revenue ([www.usefriz.com](http://www.usefriz.com)).\\\nSupport us on Product Hunt: <https://www.producthunt.com/posts/friz-2> \n\n![uploaded image](/media/?type=post&id=77520&key=user_uploads/576527/6d955ecd-ce30-4a74-b56d-548328e8f09b)\n\n![uploaded image](/media/?type=post&id=77520&key=user_uploads/576527/e92e063c-3ef5-4c20-9fe1-7b3f188643ca)\n\n![uploaded image](/media/?type=post&id=77520&key=user_uploads/576527/38812ee0-3ce2-4748-81d2-f75d23418220)\n\n![uploaded image](/media/?type=post&id=77520&key=user_uploads/576527/794ea688-b6b1-46e3-98f2-7f2f6fe146ee)\n\n![uploaded image](/media/?type=post&id=77520&key=user_uploads/576527/fe100627-d416-4917-b3f3-fa70b95d5bbe)\n\n",
        "url": "https://www.ycombinator.com/launches/KAK-friz-ai-social-media-manager",
        "votes": 4,
        "created_at": "2024-01-15T20:46:39.651Z"
      }
    ]
  },
  {
    "id": 23430,
    "name": "Mystic",
    "slug": "mystic",
    "former_names": [
      "Neuro AI",
      "Neuro",
      "Mystic",
      "Mystic AI"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f860b32ddb9b39b9b1ae8c22f0c17f140dc5e9d4.png",
    "website": "https://www.mystic.ai/",
    "all_locations": "Austin, TX, USA",
    "long_description": "Mystic’s platform allows companies to easily and reliably deploy ML models on our serverless cloud or on their own infrastructure without requiring a team of MLOps engineers. With our Python SDK, data-scientists immediately get an endpoint from their own model, or any open-source models.\r\nOnce uploaded, our platform handles routing, multi-cloud scaling, caching, GPU optimization and other features to provide the ultimate ML inference platform.",
    "one_liner": "Low latency API to run and deploy ML models",
    "team_size": 11,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1614265935,
    "tags": [
      "AIOps",
      "Developer Tools",
      "Machine Learning",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2021",
    "status": "Inactive",
    "industries": [
      "B2B",
      "Infrastructure"
    ],
    "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/mystic",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2021/mystic.json",
    "year_founded": 2019,
    "city": "Austin",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/mystic-ai",
    "x_url": "https://twitter.com/mysticdotai",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/neuro-ai",
    "github_url": "https://github.com/mystic-ai/pipeline",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/f860b32ddb9b39b9b1ae8c22f0c17f140dc5e9d4.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": 316612,
        "full_name": "Paul Hetherington",
        "title": "Founder",
        "founder_bio": "Founder and CEO of Hlabs (W26), Prev Founder and CEO of Mystic (W21).",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/paul-hetherington/",
        "x_url": "https://x.com/paulcjh_",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b0a028873ab868127c0bbf011e8d660b44e256b4.jpg"
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        "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",
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        "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!",
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        "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.",
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    "long_description": "Build beautiful knowledge portals that are easy to navigate, search, share and contribute to.",
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        "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)",
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        "full_name": "Quentin Rousseau",
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        "full_name": "JJ Tang",
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        "url": "https://techcrunch.com/2023/08/10/incident-response-management-platform-rootly-secures-12m/",
        "date": "Aug 10, 2023"
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      {
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        "url": "https://techcrunch.com/2021/07/08/rootly-nabs-3-2m-seed-to-build-sre-incident-management-solution-inside-slack/",
        "date": "Jul 08, 2021"
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        "title": "🚒 Rootly - AI SRE, On-Call, Status Pages",
        "tagline": "Top YC companies like DoorDash, Webflow, Dropbox, Replit, and 100s more all trust Rootly.",
        "body": "## **TL;DR**\n\nRootly is the AI-native on-call and incident management platform that helps teams detect, manage, learn from, and resolve incidents faster—without leaving Slack or MS Teams. It brings Incident Response, On-Call, AI SRE agents, Status Pages, and Retrospectives into one purpose-built, end-to-end platform.\n\n![uploaded image](/media/?type=post&id=66512&key=user_uploads/642689/d1b534a4-b1f0-444d-b767-aab1d221e1cb)\n\n## **Problem**\n\nWe met at Instacart 🥕—where Quentin was the first SRE and JJ was leading product management efforts. As Instacart grew from a $1B to a $40B company, everything had to scale with it: infrastructure, teams, and the processes that keep the business running when things go wrong. With millions of orders flowing through the platform, incidents weren’t rare edge cases—they were an inevitable part of operating at that level. Checkout issues, platform outages, weird cascading failures at the worst possible times… we saw it all.\n\nWhat surprised us wasn’t that incidents happened. It was how quickly the _process_ broke down under pressure. Our manual way of responding—jumping between Slack, PagerDuty, Datadog, and a dozen dashboards—just wasn’t enough. Every incident started with the same scramble: spinning up channels, pulling people in, figuring out who’s running point, trying to keep comms coherent, and stitching together context from different tools and threads. It worked when the team was small and the system was simpler. At scale, it turned chaotic and inconsistent.\n\nAnd the hardest part wasn’t even the debugging. It was the inconsistency. You’d rely on runbook checklists and tribal knowledge, hoping someone remembered what to do next—who to page, which workflow to follow, how to communicate internally and externally, what steps to capture for the retrospective. In the moment, that’s a lot to ask. Afterward, it meant retros were slow (or skipped), action items drifted, and the same classes of incidents kept coming back because learning didn’t keep pace with growth.\n\n## **Solution**\n\nRootly gives you an end-to-end incident lifecycle—from first page to resolution to post-incident learning—built where teams actually operate (Slack & MS Teams), and it’s all powered by AI.\n\n<https://www.youtube.com/watch?v=56oyjjeNzqY>\n\n**Incident Response**\n\nRootly helps you declare incidents, spin up the right Slack channels and roles, coordinate responders, track tasks, and keep communication structured—while automating the operational “busywork” that normally slows teams down.\n\n**On-Call**\n\nRootly On-Call is built to notify the right person the first time, with scheduling and escalation that scales from a small team to a global org. It’s designed to be reliable and easy to use, with a beautiful mobile experience that makes getting paged somewhat enjoyable.\n\n**AI SRE Agents**\n\nRootly’s AI SRE agents help teams move faster during incidents by connecting the dots across signals like recent code changes, telemetry, and past incidents. Instead of starting from scratch every time, responders can quickly narrow in on probable causes, understand what changed, and get suggestions for fixes and next steps—along with the reasoning behind them.\n\n**Status Pages**\n\nRootly makes it easy to keep customers and stakeholders updated with public and private status pages, so incident comms don’t become another manual process during a high-stress event.\n\n**Retrospectives**\n\nRootly helps you turn incidents into learning. Create collaborative retros that teams can edit together, draft timelines and summaries faster, and track action items so the work actually gets done—not just written down.\n\n**AI everywhere responders actually feel it**\n\nDuring incidents, the biggest tax is cognitive load: listening, typing, summarizing, updating, and repeating yourself. Rootly uses AI to take that off the responder:\n\n* **AI Meeting Bot scribing:** Rootly can join your incident bridge, transcribe in real time, and capture key context so nothing gets lost.\n* **Instant catch-up:** Tag **@Rootly** in the incident channel to get a private, personalized summary of what’s happened so far, what’s been tried, and what’s next.\n* **Draft updates that match the audience:** Generate incident updates tailored to the recipient—customer-friendly language for external comms, crisp executive summaries for leadership, or detailed handoffs for engineering—so you’re not rewriting the same update five different ways.\n* **AI-generated retros:** Auto-draft retrospectives with timelines and context, then collaboratively refine and track action items to completion.\n* **Automated RCA:** Alerts, code changes, past incidents all analyzed at the speed of AI to determine probable root cause in minutes.\n\n**A full platform, or just what you need**\n\nUse Rootly as a complete incident management platform—or adopt products individually based on where you are today (Incident Response, On-Call, AI SRE, Status Pages, Retrospectives).\n\n## **Offer & Ask**\n\n* If you want to see how Rootly modernizes incident management end-to-end, book a demo and we’ll tailor it to your current stack and workflows.\n* If you’re a team with **&lt;25 employees**, we also offer **Pay What You Can** so you can get world-class incident management without the “enterprise price tag.”",
        "url": "https://www.ycombinator.com/launches/HIm-rootly-ai-sre-on-call-status-pages",
        "votes": 86,
        "created_at": "2022-10-05T05:45:37.027Z"
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    "name": "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,
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    "name": "Dailybot",
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    "website": "https://www.dailybot.com/",
    "all_locations": "Remote, OR, USA; Remote",
    "long_description": "Dailybot is the coordination platform for software teams where people and AI agents work side by side.\r\n\r\nAs engineering teams increasingly operate alongside multiple AI agents — coding agents, incident responders, research assistants — the gap between what's being worked on and what the team can actually see has become a critical problem. Dailybot closes that gap.\r\n\r\nTeams use Dailybot to run async standups, check-ins, retros, and custom workflows directly inside Slack, Microsoft Teams, Google Chat, and Discord. In Dailybot 3, those capabilities now extend to AI agents: every agent can report progress, surface blockers, and be monitored in a dedicated observability layer — all attributed to the humans who delegated the work.\r\n\r\nThe platform combines four capabilities: structured check-ins and forms in chat, AI-powered summaries and blocker detection, no-code workflow automation, and agent infrastructure (API, CLI, open-source skill pack, fleet monitoring). Leaders get a proactive view of what people and agents accomplished together — without adding meetings or dashboards to check.\r\n\r\nDailybot is SOC 2 and GDPR compliant, backed by Y Combinator (S21), and trusted by teams at IBM, Samsung, Pixar, and 8,000+ teams worldwide.",
    "one_liner": "Make all team work visible — people and AI agents",
    "team_size": 11,
    "industry": "B2B",
    "subindustry": "B2B -> Productivity",
    "launched_at": 1625092395,
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        "full_name": "Mauricio Morales",
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        "full_name": "Sergio Florez",
        "title": "Founder",
        "founder_bio": "CTO at DailyBot — leading and building unique conversational experiences for asynchronous work. \n\nSergio is a computer science engineer, MSc in data science and passionate entrepreneur, with talent and more than 10y of experience building digital businesses. He's in the search of the ideation of disruptive business models as agents of change and success.",
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    "news": [
      {
        "title": " DailyBot 2.0 - Make your chat 10x better | Product Hunt",
        "url": "https://www.producthunt.com/posts/dailybot-2-0",
        "date": "Jul 07, 2021"
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      {
        "id": 109411,
        "title": "Dailybot CLI: Your AI agents now report to the team",
        "tagline": "An open-source CLI and skill that turns private agent work into team updates, approvals, and workflows in chat",
        "body": "Hey everyone! we’re Mauricio and Sergio, co-founders of Dailybot (YC S21).\n\n**What Dailybot is**: a place for team updates, check-ins, and coordination inside Slack, Microsoft Teams, Discord, and Google Chat. For people and AI agents.\n\n**TL;DR**: we built an open-source CLI so people, scripts, and AI agents can drive Dailybot from the terminal. Updates, check-ins, chat messages, forms, and more land where the team already works: Slack, Microsoft Teams, Discord, or Google Chat. **Ask:** ask your agent to try our skill ([**www.dailybot.com/skill.md**](http://www.dailybot.com/skill.md)), run one workflow that matches how your team actually works, and tell us which one helped you move forward today.\n\nDailybot skill: [**https://www.dailybot.com/skills/agent-skill/#install**](https://www.dailybot.com/skills/agent-skill/#install)\n\n**Demo**\n\n[**Dailybot CLI + Agent Skill: Connect your AI coding agent to your team**](https://www.youtube.com/watch?v=rwopfsPzgSQ)\n\n\\\n**The problem**\n\nTeams are getting real work done with coding agents and scripts. A lot of that work still finishes in a private session. The rest of the team only hears about it if someone rewrites it into Slack or a standup.\n\nSo you get the usual mess: invisible agent work, stale status during a release, approvals bouncing between tools, and check-ins that someone rebuilds by hand for every new project.\n\n**What we shipped**\n\nDailybot CLI. Same Dailybot account and team feed you already use, now from the command line. A few workflows we’re highlighting:\n\n1. Agent update to team chat — done / next / blockers show up in the feed, without a human rewrite\n2. One status message that stays current — one release/status message you keep updating, instead of a pile of outdated posts\n3. Simple approvals in chat — approve/reject in Slack or Teams; your system gets the result and work continues\n\nThere’s more under the hood (forms, check-in creation, agent inbox, activity into reports, kudos, teams, workflows). We’re leading with the ones that produce a visible team result fast.\n\n**Installing the CLI**\n\nEasiest path: pass the skill to your agent and ask it in plain language, e.g. “post a team update that we finished the CLI install path” – [**https://www.dailybot.com/skill.md**](https://www.dailybot.com/skill.md)\n\n**How we got here**\n\nWe’ve been building Dailybot for hybrid teams for a while: async check-ins, reports, and coordination inside chat. As our own team (and customers) started running agents all day, the gap got obvious: agents ship work, humans still retype the update.\n\nThe CLI is our answer to that gap. A bridge into the place the team already coordinates.\n\n**Our ask**\n\n1. Install and try one workflow: [**https://www.dailybot.com/skills/agent-skill/#install**](https://www.dailybot.com/skills/agent-skill/#install)\n2. Reply with the workflow you’d want documented/explored next\n3. If useful, intros to eng teams already running agents in production (contact our founders)\n\nThanks,\\\nMauricio &amp; Sergio",
        "url": "https://www.ycombinator.com/launches/SSh-dailybot-cli-your-ai-agents-now-report-to-the-team",
        "votes": 22,
        "created_at": "2026-08-05T16:22:36.120Z"
      },
      {
        "id": 70494,
        "title": "Dailybot+ AI 🧠 The assistant and toolkit for modern teams",
        "tagline": "Meet Dailybot, a ChatGPT assistant and AI workflow builder for your work chat",
        "body": "Hi! We are Mauricio Morales and Sergio Florez, the founders of [Dailybot](https://www.dailybot.com/product/ai?utm_source=YCLaunch).\n\nDailybot+ AI is a toolkit for modern work: a ChatGPT Assistant and an AI Workflow automation tool that takes asynchronous work and in-chat collaboration to another level. Compatible with Slack, Microsoft Teams, Google Chat, or Discord.\n\n### **The Problem**\n\nAI is the future, yes. But many people lack the knowledge and resources to effectively incorporate AI into their daily workflow, resulting in missed opportunities for creating impactful use cases.\n\n### **Our Solution**\n\nDailybot provides a chat assistant and platform that simplifies the integration of AI into daily workflows. With our technology, anyone can access an AI assistant (ChatGPT) in the work chat, and can also implement use cases that leverage the power of AI.\n\n![uploaded image](/media/?type=post&id=70494&key=user_uploads/207324/1d5a25dc-bc23-4f36-8315-61af16175cf6)\n\nWe provide key building blocks for you to combine and build multiple use cases on top of your chat workspace.\n\nThe building blocks of Dailybot are: **Check-ins** for stand-ups or recurring surveys; **Forms** for any data collection; **Chat Commands** for in-chat customization; **Workflows** for setting up triggers/actions; and the **AI engine**.\n\nThe Dailybot Workflows provide a Zapier-like interface where users can define triggers and actions (one or multiple) that should run.\n\n![uploaded image](/media/?type=post&id=70494&key=user_uploads/207324/7c533a87-fd19-4145-a9c9-4450a49a0e53)\n\nThe Actions can be AI content generation, sending messages (DMs or channels), sending emails, or triggering other building blocks of Dailybot.\n\n![uploaded image](/media/?type=post&id=70494&key=user_uploads/207324/dc811400-636e-4ffb-8773-aaefa373ddc2)\n\n### **A Few Examples**\n\n* You run a **Daily Stand-up** (built with Check-ins), then, **when a blocker is reported**, an **AI Workflow is run**. It analyzes the blocker and then suggests the employee ideas for solving the issue/bocker.\n* You create a **Form** that will be triggered with the in-chat command named “**product release**”, when the Form is completed an **AI Workflow is run**. It analyzes all the content of the release form **and generates a press release** that is posted into the #releases channel.\n* You create an **anonymous survey to monitor team morale**. The **AI analyzes all the responses** and sends a summary to the head of HR (via email or DM).\n\nWe're passionate about making remote work easier and more efficient and our goal is to make DailyBot the best companion for your team’s work.\n\n**Our Ask:**\n\nWe’d love to hear your ideas on what type of AI-powered daily workflows (in chat) will add value to your team, feel free to share the feedback at [support@dailybot.com](mailto:support@dailybot.com)\n\nWe offer a Free Trial, [**Try Dailybot here**](https://www.dailybot.com/product/ai?utm_source=YCLaunch).",
        "url": "https://www.ycombinator.com/launches/IL0-dailybot-ai-the-assistant-and-toolkit-for-modern-teams",
        "votes": 40,
        "created_at": "2023-03-23T15:06:42.817Z"
      },
      {
        "id": 64310,
        "title": "DailyBot 🤖 daily stand-ups, automation and chat assistant for work",
        "tagline": "⚡️ On a mission to provide one-click workflows for team collaboration and productivity via chat",
        "body": "👋 Mauricio and Sergio from [@DailyBot](https://www.dailybot.com/) here.\n\n### **TL;DR**\n\nDailyBot is a bunch of useful add-ons for your chat platform. Plug it into your chat and make Async Work a breeze for your team:\n\n* 1- Running async Daily Stand-ups, natively integrated in the chat\n* 2- Cutting unnecessary meetings with more types of recurring check-ins\n* 3- Spreading love and team recognition with DailyBot Kudos\n* 4- Socializing better with watercooler prompts and random 1:1 coffees\n\nAnd developers can build simple in-chat functions for their day-to-day operations, without the need to learn chat-platform-specific APIs.\n\nAvailable on Slack, Discord, MS Teams, G Chat.\n\n### **The problem**\n\nAsync work is the new way of working for many teams. Most teams use chat in any form with tools like Discord, Slack and others. As chat becomes the main app that workers interact with everyday, it becomes necessary to give it more purposes.\n\nNew purposes include workflows like team check-ins, surveys, platform notifications, tools for social engagement, or custom commands to trigger actions.\n\nCreating all this setup is a hustle:\n\n* 1- You have to use many apps, bots, plugins\n* 2- There is a lot of context switching, management overhead, more subscription fees, and more app fatigue for workers\n* 3- Most bots are not designed for protecting security and privacy\n\n# **DailyBot is the solution**\n\nWe are building the first super-bot for your chat. DailyBot comes with a bunch of use cases and features, all-in-one. Some workflows include:\n\n**Check-ins:** track automatically what your team is up to. You can run async and written updates, agile daily stand-ups, retrospectives, or periodic check-ins like 1:1s.\n\n![uploaded image](/media/?type=post&id=64310&key=user_uploads/207324/06136816-f0a8-4324-8e8b-db4bb9a0aa81)\n\n**Kudos**: give kudos and celebrate actions that contribute to better team culture. Create rewards and have fun activities with your team based on our leaderboard.\n\n![uploaded image](/media/?type=post&id=64310&key=user_uploads/207324/b523b354-332f-4d1e-9617-996320210eb7)\n\n**Forms**: create all-purpose forms that people can respond to in chat or on the web. Automate vacation requests, recurring feedback forms, and more.\n\n![uploaded image](/media/?type=post&id=64310&key=user_uploads/207324/91614956-ebf2-45e0-b746-678fac7349ec)\n\n**Custom commands**: create commands to increase your team’s productivity in less than a minute. Virtual coffees, birthday reminders, watercoolers, pomodoro timers, your own chat-ops and more.\n\n![uploaded image](/media/?type=post&id=64310&key=user_uploads/207324/974d041a-a4b9-4c5a-a1c0-2b810e40ec29)\n\n### **Security by design and SOC2 compliance**\n\nMost apps take a lot of permissions to access data from your chat. This becomes concerning when you are using dozens of apps to build your team workflows. We are designing DailyBot as a privacy & security first company.\n\nDailyBot only requests the minimal API permissions from your chat. It can only process messages that are directed to the bot.\n\nWe are SOC2 Type II compliant, giving confidence to small and big companies about our work and data management practices.\n\n**Join Us!**\n\nGet started for free. Go to [www.dailybot.com](http://www.dailybot.com) and install DailyBot on your chat (2-min setup). We have a bookface deal for our fellow YC members.\n\nSee you on the other side!\n\nPs: Join our [Discord community](https://discord.gg/StjtJ5u7QF) and follow us on [Twitter](https://twitter.com/dailybot) and [LinkedIn.](https://www.linkedin.com/company/dailybot) ;)",
        "url": "https://www.ycombinator.com/launches/GjG-dailybot-daily-stand-ups-automation-and-chat-assistant-for-work",
        "votes": 50,
        "created_at": "2022-07-04T18:21:28.389Z"
      }
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    "website": "https://www.jovian.com",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "Jovian is an online university for software development and data science. We offer practical and industry-focused programs that help professionals learn technical skills, build real-world projects, and advance their careers.\r\n\r\nStudents learn practical skills, build real-world portfolio projects, and undergo job readiness training. Our tutors offer 24x7 guidance & mentorship over Slack & Zoom. Students also get access to jobs with 200+ hiring partners.",
    "one_liner": "Online University for Tech Professionals",
    "team_size": null,
    "industry": "Education",
    "subindustry": "Education",
    "launched_at": 1625134988,
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    "year_founded": 2019,
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    "name": "Hyperbrowser",
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        "full_name": "Shri Sukhani",
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        "title": "HyperAgent: Open Source AI Browser Automation Framework",
        "tagline": "Automate the Web with LLMs",
        "body": "**TL;DR / Summary:**\n\nHyperagent is the AI-native browser automation framework - think Playwright supercharged with AI. No more brittle scripts, just powerful natural language commands.\n\nHyperAgent gives you:\n\n* 🤖 **AI Commands**: Simple APIs like [page.ai](http://page.ai)(), page.extract() and executeTask() for any AI automation\n* ⚡ **Fallback to Regular Playwright**: Use regular Playwright when you don’t need AI\n* 🥷 **Stealth Mode** – Avoid detection with built-in anti-bot patches\n* ☁️ **Cloud Ready** – Instantly scale to hundreds of sessions via [Hyperbrowser](https://app.hyperbrowser.ai/)\n* 🔌 **MCP Client** – Connect to external tools for full workflows (e.g. writing web data to Google Sheets)\n\n⭐ **Check it out and give it a star on Github!**\n\n<https://github.com/hyperbrowserai/HyperAgent>\\\n\\\n<https://www.youtube.com/watch?v=0bHC1i1aRhI>\\\n\\\n**Browser Automation Is Broken**\n\nWe built HyperAgent because **browser automation is broken.** We've all been there – spending hours writing scripts that shatter the moment a website changes. With AI agents becoming mainstream, we need automation that's as adaptive as they are, and doesn’t break every time a css class changes.\n\nWith HyperAgent, we’re adding AI to your existing toolkit, wrapping playwright in simple, natural language commands that just work. So you can have the best of both worlds - keep what you love about playwright and automate the rest with AI.\n\n**HyperAgent Quickstart**\n\nTo use HyperAgent on an existing page, you can simply call [**page.ai**](http://page.ai):\n\n```\nawait page.ai(\"Find a route from Miami to New Orleans, and provide the detailed route information.\")\n```\n\n![uploaded image](/media/?type=post&id=89908&key=user_uploads/556017/f6d70ca6-70cf-4dff-a206-9263341cd681)\n\nThis will go to google maps, enter in the origin and destination, then return the route back.\n\nTo extract information from a page, call **page.extract:**\n\n```\nawait page.extract(“find the major cities that this path goes through\")\n```\n\n![uploaded image](/media/?type=post&id=89908&key=user_uploads/556017/2ca8cdba-b651-44e4-af20-9bdc7d1e0393)\n\n**Built-in Stealth Mode**\n\nHyperAgent comes with patches for stealth browsing so you don’t have to worry about getting blocked. For maximum stealth, use Hyperbrowser - it’s free to start.\n\n**Infinitely Extensible with MCP servers**\n\nWant to give HyperAgent access to custom tools or integrate with other apps? HyperAgent is an MCP client and offers infinite extensibility with any MCP server.\n\n**Scale to 100s of Concurrent Agents**\n\nUsing HyperAgent on HyperBrowser you can scale to 100s of concurrent agent runs in seconds. No need to worry about the underlying infrastructure.\n\n# Try It Today\n\n🚀 GitHub: <https://github.com/hyperbrowserai/hyperagent>\n\n![uploaded image](/media/?type=post&id=89908&key=user_uploads/556017/6aa560db-eee6-4bb6-9a9c-38c51fadb03d)\n\n",
        "url": "https://www.ycombinator.com/launches/NO8-hyperagent-open-source-ai-browser-automation-framework",
        "votes": 19,
        "created_at": "2025-04-28T15:08:07.451Z"
      },
      {
        "id": 89020,
        "title": "Hyperpilot: AI Browser Agent Playground by Hyperbrowser",
        "tagline": "Experience the future of the Agentic Web for Free with HyperPilot",
        "body": "# **TL;DR / Summary:**\n\nAI Browser Agents are powerful but costly/hard to access. HyperPilot lets you try all the leading browser agents (CUA, Claude CU, Browser Use) for free. It's built on Hyperbrowser, our infra that lets you build agents with a free API key + 5 lines of code.\n\n<https://www.youtube.com/watch?v=1AbjFhf2T0k>\n\n**Why**\n\nAI browser agents like OpenAI's CUA and Anthropic's Claude Computer Use promise to revolutionize web automation. But getting hands-on experience is tough. Tools are limited, complex, or expensive – OpenAI's Operator preview costs $200/month just to try. How can you explore this future without breaking the bank?\n\n# **What**\n\nWe're launching [HyperPilot](http://pilot.hyperbrowser.ai): A free, easy-to-use playground where you can directly interact with and compare different AI browser agent models. See firsthand what they can really do.\n\nHyperPilot isn't just a demo; it’s a fully functional browser agent playground that runs entirely on [Hyperbrowser](https://hyperbrowser.ai) - our robust and scalable browser infrastructure designed specifically for AI agents.\n\n# **Who is this for? What should you do with it?**\n\n### **Everyone**\n\nTry it out for yourself. See what the future of Browser Agents actually holds. Check out Claude Computer Use, OpenAI’s CUA, and more. If you get inspired by what you see, we’d love to hear from you and help in any way we can! Reach out to us at [founders@hyperbrowser.ai](mailto:founders@hyperbrowser.ai)\n\n_(Hyperbrowser booking Kendrick Lamar concert tickets)_\n\n![uploaded image](/media/?type=post&id=89020&key=user_uploads/233736/c8e39379-b378-45a7-a97b-7caafc1df810)\n\n### **Developers**\n\nUse HyperPilot to rapidly prototype your agents, prompts, and automations. Everything you see in HyperPilot is powered by Hyperbrowser infrastructure along with OpenAI, Anthropic, and Google DeepMind’s models.\n\nWant to build this magic into your own apps? With Hyperbrowser, you can get started using OpenAI’s CUA, Anthropic’s Claude Computer Use, and more with just a free API key and 5 lines of code.\n\nCheck out the docs here:\n\n* [Claude Computer Use on Hyperbrowser](https://docs.hyperbrowser.ai/agents/claude-computer-use)\n* [OpenAI CUA on Hyperbrowser](https://docs.hyperbrowser.ai/agents/openai-cua)\n\nGet your free API key here: <https://hyperbrowser.ai>\n\n_(Claude computer use on Hyperbrowser in 5 lines of code)_\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXcqYG4wQaP9VTtLxvuXkLewpbDHxUCaWa2JU8rfhb9HYJBzLjuSViGyIoV-0jhpI8-w113eSxlPbYeQpQveCIKKX25CKV1DkgyCJ9DN1PTeoQf9cU1PX-T-QvuimhOskpAY1aIF?key=SWtClCBzkj7TSIatblqhIGY5)\n\n# **Our Asks**\n\n🆓 Try the leading AI browser agents for FREE on HyperPilot: [pilot.hyperbrowser.ai](http://pilot.hyperbrowser.ai)\\\n🛠️ Developers, get your free API key and start building: <https://hyperbrowser.ai>\\\n🔥 Share your favorite models and use cases with us on [LinkedIn](http://linkedin.com/company/hyperbrowser) and [X](http://x.com/hyperbrowser)",
        "url": "https://www.ycombinator.com/launches/N9o-hyperpilot-ai-browser-agent-playground-by-hyperbrowser",
        "votes": 78,
        "created_at": "2025-03-26T21:21:30.836Z"
      },
      {
        "id": 88849,
        "title": "Hyperbrowser MCP Server - Connecting AI to the Web 🌐 🤖",
        "tagline": "Connect LLMs to the web for research, coding, and automation",
        "body": "**TL;DR:**\n\nGive your LLMs / IDEs superpowers by connecting them to the web with Hyperbrowser's MCP. Unlock deep research, coding with live documentation, data extraction, and browser automation capabilities in 2 minutes. Install in seconds with `npx -y hyperbrowser-mcp` and use with Claude Desktop, Cursor, Windsurf, or your favorite MCP client.\n\n**ASK:** Building AI agents, developer tools, or research applications? Email us at [shri@hyperbrowser.ai](mailto:shri@hyperbrowser.ai) or [akshay@hyperbrowser.ai](mailto:akshay@hyperbrowser.ai)\n\n<https://www.youtube.com/watch?v=HUA4uPwcS8U>\n\n## ❌ The Problem\n\nLLMs are powerful but isolated. They can't:\n\n* Access real-time web information\n* Interact with websites to complete tasks\n* Generate code using up-to-date documentation (even OpenAI API calls are sometimes botched)\n* Extract structured data from multiple sources in real-time\n\n## 🛠️ Our Solution\n\nHyperbrowser MCP Server connects LLMs directly to the web through Anthropic's Model Context Protocol.\n\n`$ npx -y hyperbrowser-mcp`\n\n**Our MCP Server exposes 7 powerful tools:**\n\n\\- **Web data tools:** scrape_webpage, crawl_webpages, extract_structured_data, search_with_bing\n\n\\- **Browser automation:** browser_use_agent, openai_computer_use_agent, claude_computer_use_agent\n\nYour favorite MCP client can use the web data tools to surf the web for real-time information and data + use the browser automation tools to take actions like ordering a pizza or commenting on a GitHub pull request.\n\n## 💡 What You Can Build\n\n* **Deep Research in Cursor:** Claude, Cursor, and Windsurf can use Hyperbrowser's MCP server to do extremely deep research on any topic. No need for $200/mo ChatGPT Pro.\n* **Faster coding with AI:** Generate working code with current API docs, automate code reviews, build integrations\n* **Extract Data:** Convert web content to structured datasets, right in your claude app\n* **Automate Tasks:** Test applications, submit forms, automate UI tests\n\nCheck out this video of my cofounder vibe coding a whole game with Cursor and Hyperbrowser's MCP Server:\n\n<https://www.youtube.com/watch?v=wT89pY6zW4o>\n\n## 🙏 Our Asks\n\n* **Try it out!** Get a free API key at [app.hyperbrowser.ai](http://app.hyperbrowser.ai) and install in your clients (instructions here - [github.com/hyperbrowserai/mcp](http://github.com/hyperbrowserai/mcp))\n* **Share this post** with AI devs and researchers\n* **Connect with us** at [shri@hyperbrowser.ai](mailto:shri@hyperbrowser.ai) and [akshay@hyperbrowser.ai](mailto:akshay@hyperbrowser.ai)\n* **Follow us** at [x.com/hyperbrowser](http://x.com/hyperbrowser) and [linkedin.com/company/hyperbrowser](http://linkedin.com/company/hyperbrowser)\n* **Join our community** on Discord - <https://discord.gg/zsYzsgVRjh>\n\n![uploaded image](/media/?type=post&id=88849&key=user_uploads/233736/98d7ef01-89f4-475b-af5b-90679a5f3097)\n\n",
        "url": "https://www.ycombinator.com/launches/N73-hyperbrowser-mcp-server-connecting-ai-to-the-web",
        "votes": 93,
        "created_at": "2025-03-21T00:51:31.528Z"
      },
      {
        "id": 87074,
        "title": "Hyperbrowser - Web infrastructure for AI agents",
        "tagline": "AI’s Gateway to the Web",
        "body": "## TL;DR\n\nHyperbrowser is AI's gateway to the web. We make it dead simple to give your AI agents reliable, scalable scraping and browser automation capabilities without getting blocked or dealing with infra headaches. One API call to HB gives you a browser session with built-in stealth mode, proxy rotation, automatic CAPTCHA solving, session management, session recordings etc. Hyperbrowser is the only browser platform that lets your agents spin up 100s of concurrent browsers with sub-second start times.\n\n<https://www.youtube.com/watch?v=LZIPzjyEuGU>\n\n## Why is this important? And why now?\n\nThe web wasn't built for AI—but AI needs the web. In 2025, Agents are finally here. We've met so many companies building web-based agents who keep running into the same problems:\n\n* They keep getting blocked\n  * Websites detect and shut down automation, making it hard to scale AI-driven browsing.\n* Web automation at scale is a nightmare to manage\n  * Managing browser infrastructure is expensive, slow, and unreliable—especially when running thousands of concurrent sessions\n* High latency\n  * High latency creates a terrible user experience and leads to frustration\n\nThe future is AI-driven agents that browse, transact, and take action. Hyperbrowser enables Agents to reliably interact with the web.\n\n## Our Solution\n\n**Core Infrastructure**\n\n* Launch thousands of undetectable browsers in <1s\n* Built-in anti-detection & stealth mode - bypasses anti-bot systems and fingerprinting\n* Automated CAPTCHA solving\n* Ultra-low latency globally distributed infrastructure\n\n**Developer Experience**\n\n* Multiple levels of abstraction:\n\n```\n// High-level API for instant results\nconst data = await client.scrape.startAndWait({\n  url: \"https://example.com\",\n  solveCaptchas: true\n});\n\n// Or fine-grained control when you need it\nconst session = await client.sessions.create();\nconst browser = await connect({ \n  browserWSEndpoint: session.wsEndpoint \n});\n```\n\n* Full compatibility with Puppeteer, Playwright, and Selenium\n* Comprehensive session management and monitoring\n* Live stream APIs for real-time session data\n* Native integrations with LangChain, LlamaIndex, and more\n\n**Infrastructure & Scaling**\n\n* Instant browser session startup (<1s)\n* Scale from 1 to 1000s of concurrent sessions\n* Flexible pricing tiers to match your needs\n* No infrastructure management required\n\n## What People Are Building with Hyperbrowser\n\n* Web research agents automating sales and marketing research\n* AI agents booking flights and analyzing markets in real-time\n* Testing teams running 500+ concurrent browser sessions\n* Companies collecting training data for AI models at scale\n* Automated KYC/KYB processes with built-in compliance\n\n## Get Started\n\n* Try it free at <https://hyperbrowser.ai> \n* Join our Discord - <https://discord.com/invite/zsYzsgVRjh>\n* Follow us on X - [x.com/hyperbrowser](http://x.com/hyperbrowser)\n* Follow us on LinkedIn - [linkedin.com/company/hyperbrowser](http://linkedin.com/company/hyperbrowser)\n* Email us directly: [akshay@hyperbrowser.ai](mailto:akshay@hyperbrowser.ai) or [shri@hyperbrowser.ai](mailto:shri@hyperbrowser.ai)\n\n![uploaded image](/media/?type=post&id=87074&key=user_uploads/556017/8dc23770-3861-4ce3-8426-ef5be417d5d6)\n\n",
        "url": "https://www.ycombinator.com/launches/MeQ-hyperbrowser-web-infrastructure-for-ai-agents",
        "votes": 92,
        "created_at": "2025-01-23T02:44:54.888Z"
      }
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    "long_description": "testRigor is an executable specifications engine to help companies to empower their manual QA to be able to build automation 15X than QA engineers and spend 200X less time maintaining the code.",
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    "year_founded": 2015,
    "city": "San Francisco",
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    "linkedin_url": "https://www.linkedin.com/company/testrigor",
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        "linkedin_url": "https://www.linkedin.com/in/agolubev/",
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    "all_locations": "New York City, NY, USA; New York, NY, USA; Remote",
    "long_description": "ScratchDB is a platform that automates all aspects of managing an analytical database: server configuration, data ingestion, queries, replication, and sharding. We are built on top of Clickhouse with a developer experience that you'll love.",
    "one_liner": "Analytics for builders. Record and query billions of datapoints with…",
    "team_size": 1,
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    "id": 24344,
    "name": "WarpBuild",
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    "long_description": "Accelerate software development with WarpBuild.\r\nGet 2x faster, up to 90% cheaper CI in 30 seconds using WarpBuild for Github Actions.",
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        "title": "WarpBuild: Blazing fast x86-64 and ARM64 runners for Github actions",
        "tagline": "Supercharge your development cycle with 30% faster runners in 2 minutes",
        "body": "**WarpBuild provides blazing fast cloud CI runners that speed up of your builds by over 30%.**\n\nThis is a drop-in replacement for Github-hosted Actions runners (_including all pre-installed dependencies)_ that takes one line of code change to get started.\n\nOur mission is to deprecate this:\n\n![](https://imgs.xkcd.com/comics/compiling.png)\n\n## **Key benefits:**\n\nYour existing github actions will run without any changes. You will also get:\n\n* **x86-64 and arm** architecture runners\n* **30% faster** than GitHub Actions at half the price\n* **Secure** VM-level isolation for your workloads\n* **Easy debugging** - SSH into running Github actions workflows\n* **Fast IO** with SSD backed volumes\n* **Unlimited parallelization** for eliminating job queueing delays\n* **Automatic updates** of pre-installed toolchains saving maintenance if you are self-hosting runners\n* **Runs as a VM**, not in a container, for workloads that don’t work in `dind` or `kind` environments\n\n## **Use cases:**\n\n* **Plain ol’ Github actions**, but faster, cheaper, and awesomer\n* **Easy debugging:** ssh into a running workflow using `Action-Debugger`\n* **Nested virtualization** for running firecracker, VMs, custom hypervisors, inside of your workflow\n* **Running android emulators** in CI\n* Spinning up kubernetes clusters in testing pipelines",
        "url": "https://www.ycombinator.com/launches/K0P-warpbuild-blazing-fast-x86-64-and-arm64-runners-for-github-actions",
        "votes": 9,
        "created_at": "2023-12-14T06:22:01.182Z"
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    "name": "Cloudthread",
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    "website": "https://cloudthread.io",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Cloudthread is an analytics platform that helps engineering teams build cost efficiently in the cloud. We were behind Lyft's internal cloud cost management system and now we use that deep expertise to help organizations save hours of engineering time, reduce cloud bills, and prevent costly re-architectures.",
    "one_liner": "Eliminate Cloud Waste. Attribute and Track Savings. Engage Engineers.",
    "team_size": 8,
    "industry": "B2B",
    "subindustry": "B2B -> Analytics",
    "launched_at": 1628208703,
    "tags": [
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    "batch": "Summer 2021",
    "status": "Acquired",
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    "url": "https://www.ycombinator.com/companies/cloudthread",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2021/cloudthread.json",
    "year_founded": 2020,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/cloudthread",
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        "user_id": 738583,
        "full_name": "Ilia Semenov",
        "title": "Founder",
        "founder_bio": "🚀ex-Lyft (2016-2020): Data Engineering + Cloud Cost Management\n🎮ex-EA (2014-2016): Cloud Cost Management\n🎓Carnegie Mellon University\n🏡Saint-Petersburg, Russia\n🌁San Francisco, USA",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/iliavsemenov/",
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    "jobs": [],
    "news": [
      {
        "title": "Cloudthread Raises $3M to Help Engineering Teams Build in the Cloud With Cost Efficiency - Grit Daily News",
        "url": "https://gritdaily.com/cloudthread-raises-3m-to-help-engineering-teams-build-in-the-cloud-with-cost-efficiency/",
        "date": "Dec 15, 2021"
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    "launches": [
      {
        "id": 71628,
        "title": "Cloudthread ☁️🧘‍♂️ Your Cloud Cost Savings Hub",
        "tagline": "Meet Cloudthread, the radical cloud waste reduction platform for modern teams",
        "body": "Hey YC! We're thrilled to announce the launch of [**Cloudthread Savings Hub**](https://www.cloudthread.io/), brought to you by [**@Ilia**](https://www.cloudthread.io/), [**@Daniele**](https://www.linkedin.com/in/danielepackard/), and [**@Thomas**](https://www.linkedin.com/in/thomasyopes/)! 🎉\n\n# TL;DR\n\n**Cloudthread Savings Hub** empowers you to identify and eliminate wasted cloud spend, streamline optimization workflows, and **maximize savings**.\n\nDiscover optimization opportunities, prioritize based on expected savings and implementation complexity, gain detailed context, group and share through Jira and Slack, track progress, and analyze realized savings.\n\nSupports **AWS** and **GCP**.\n\n![uploaded image](/media/?type=post&id=71628&key=user_uploads/738583/733b2dec-ae3d-411f-af62-46349eb8bdc0)\n\n# **The Problem**\n\nDespite various tools, sources, and techniques to manage cloud costs, achieving actual savings remains challenging. Many tools are expensive and charge a percentage of your total bill.\n\n# **The Solution**\n\nCloudthread Savings Hub disrupts the market by offering a combination of product and services laser-focused on eliminating cloud waste. We aggregate cost savings insights from various sources (including native cloud provider data), enrich it with valuable context, and facilitate workflow creation to effectively implement recommendations. We charge a **flat fee** for our product and a percentage of savings for service engagements.\n\n# **How It Works**\n\n<https://youtu.be/0j12fiXDgYc>\n\n### **💰 Special Deal + Ask**\n\n💰 For the next two weeks, find over $500 in monthly AWS savings with Cloudthread’s Savings Hub or receive a **$100 Amazon Gift Card** 🎁\n\n[**www.cloudthread.io/aws-save-or-get-paid**](https://www.cloudthread.io/aws-save-or-get-paid)\n\nJoin us in revolutionizing cloud cost management with Cloudthread Savings Hub!\n\n# **About Us**\n\nAt [**@Cloudthread**](https://bookface.ycombinator.com/company/24348), we're committed to making cloud cost analytics accessible for businesses of all sizes. Our platform enables engineering teams to lower cloud costs easily and effectively. We've helped enterprises with 8-figure cloud bills, high-growth startups, and everything in between achieve cloud cost efficiency.\n\nA few months ago, [**we launched our cloud cost saving services on Bookface**](https://bookface.ycombinator.com/posts/70004) for the YC community. Since then, we've helped companies reduce their AWS spend by **10-50%**!\n\nOur team has been working in cloud cost management since **2014**. [**@Ilia Semenov**](https://bookface.ycombinator.com/user/738583) managed cloud costs at Electronic Arts before leading Lyft's cloud cost management efforts ahead of their IPO, resulting in a **40% reduction** in AWS spend ([**case study**](https://aws.amazon.com/solutions/case-studies/lyft-cost-management/) and [**AWS Re:Invent talk**](https://youtu.be/ChupgIbZr5Q?t=2479)). Through Cloudthread, we've tackled cloud cost challenges across numerous AWS services.",
        "url": "https://www.ycombinator.com/launches/IdI-cloudthread-your-cloud-cost-savings-hub",
        "votes": 19,
        "created_at": "2023-05-17T15:50:55.737Z"
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    "website": "https://mergent.co",
    "all_locations": "Austin, TX, USA; Remote",
    "long_description": "Mergent is a task scheduling API that makes it super easy for developers to schedule and manage background tasks like notifications, data processing, and third-party integrations.\r\n\r\nWe provide a simple well-documented API that any developer can instantly start using straight from our website.",
    "one_liner": "Incredibly reliable background task queues and cron jobs",
    "team_size": 1,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1626707067,
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    "top_company": false,
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    "nonprofit": false,
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    "regions": [
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/mergent",
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    "year_founded": 2021,
    "city": "Austin",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/mergentlabs",
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        "full_name": "James Martinez",
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        "founder_bio": "Founder of Mergent (https://mergent.co)",
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        "linkedin_url": "https://www.linkedin.com/in/jamescmartinez",
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    "id": 24379,
    "name": "Formance",
    "slug": "formance",
    "former_names": [
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      "Numary (ex Goldilocks)",
      "Numary",
      "Formance (fka Numary)"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d2bd98c7cb8de435d88c71bda24056e4db21bc5f.png",
    "website": "https://formance.com",
    "all_locations": "Paris, Île-de-France, France",
    "long_description": "Formance Platform is building open-source infrastructure for the next wave of financial services. It enables fintech engineers to build and operate complex flow of funds, weaving together multiple payment rails with internal ledger accounts.\r\n\r\ngithub.com/formancehq/stack",
    "one_liner": "Open Source Infrastructure for the Financial Internet",
    "team_size": 33,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1626469942,
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      "Partly Remote"
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    "stage": "Growth",
    "app_video_public": false,
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/formance",
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    "year_founded": 2021,
    "city": "Paris",
    "country": "FR",
    "linkedin_url": "https://www.linkedin.com/company/formancehq",
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        "full_name": "Clément Salaün",
        "title": "Founder",
        "founder_bio": "Founder of Formance, making complex payments workflows work. Previously @Selency.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/clementsalaun",
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        "title": "Senior Software Engineer ",
        "url": "https://www.ycombinator.com/companies/formance/jobs/C2HMJfN-senior-software-engineer",
        "location": "Paris, IDF, FR / Remote (FR)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Backend",
        "salary_range": "€60K - €90K EUR",
        "equity_range": "",
        "experience": "3+ years",
        "visa": "US citizenship/visa not required",
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        "title": "Senior Account Executive (NYC)",
        "url": "https://www.ycombinator.com/companies/formance/jobs/ovlW1Xn-senior-account-executive-nyc",
        "location": "New York, NY, US",
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        "role_type": null,
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        "title": "Business Development Representative",
        "url": "https://www.ycombinator.com/companies/formance/jobs/M2Vc5Mh-business-development-representative",
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        "url": "https://www.ycombinator.com/companies/formance/jobs/ISOaDNE-solutions-engineer",
        "location": "London, England, GB / Remote (GB)",
        "type": "Full-time",
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        "role_type": null,
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        "url": "https://techcrunch.com/2025/01/29/formance-raises-21-million-to-build-the-aws-of-fintech-infrastructure/",
        "date": "Jan 29, 2025"
      },
      {
        "title": "French fintech Formance secures €2.9 million to help companies build and track payment flows | EU-Startups",
        "url": "https://www.eu-startups.com/2022/06/french-fintech-formance-secures-e2-9-million-to-help-companies-build-and-track-payment-flows/",
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        "id": 64456,
        "title": "💸 Formance: Open, modular foundation for unique payment flows",
        "tagline": "Build, operate and track money movements of any size and shape on a solid and open-source system-of-record (ledger)",
        "body": "Hi everyone!\n\nWe’re developing an open-source solution to enable fintechs, marketplaces and platforms to build, operate and track money movements of any size and shape on a solid system-of-record (also known as a financial ledger)\n\n**✌️ Check out our main Github repository here:** [**https://github.com/numary/ledger**](https://github.com/numary/ledger\\*\\*)\n\n## **The problem**\n\nFintechs, marketplaces, and platforms growth is closely tied to their ability to:\n\n1. Process an increasing volume of transactions, and\n2. Implement competitive payment scenarios, which can become increasingly complex, e.g. complex commission models, improved time-to-money and creative payout schedules, embedded fractional ownership of various investment assets, omnibus accounts and the likes.\n\nEngineering teams spend valuable time building themselves these money flows and the way they are broken down; then making them evolve according to the development and the strategy of the company. Additionally, tracking and reconciliating these flows from pay-ins to payouts quickly upgrades itself from an small annoyance to a _did-we-lost-10millions-type-of-problem™️_\n\nFormance is tackling this particular segment in the payment value chain which is still painful for engineering teams, yet critical: the break-down and tracking of money between inflows and outflows.\n\n## **The solution**\n\n**✌️ Check out our main Github repository here:** [**https://github.com/formancehq/stack**](https://github.com/numary/ledger\\*\\*)\n\nFormance solution is based on four products designed to **improve your economics, save time and limit costly errors:**\n\n**1/ A simple and open-source programming language for money**: designed for engineering and payments teams, this low-code language enables the creation of reliable and unique payment scenarios in a few hours, rather than days, without any particular technical expertise related to payments;\n\n![uploaded image](/media/?type=post&id=64456&key=user_uploads/144945/882aa901-0827-41c2-9dfc-4fecdbe29c8d)\n\n**2/ Pre-built and extendable use-case templates**: these templates allow to quickly implement new business strategies or product features, check them out here: <https://www.formance.com/use-cases-library>\n\n![uploaded image](/media/?type=post&id=64456&key=user_uploads/144945/731eced2-67fb-4c65-8762-26d0214a61d3)\n\n**3/ An open-source financial ledger**: working in tandem with our language and designed for reliability, this immutable system-of-record enables the track financial flows that move value through various merchants, intermediaries, parties and the extraction of data for business analysis and decision-making\n\n**4/ Real-time transaction tracking tools**: designed for finance and operations teams, these tools enable the reconciliation of pay-ins and payouts, and the identification of issues related to transactions.\n\n![uploaded image](/media/?type=post&id=64456&key=user_uploads/144945/037dee85-7949-4b3a-85bd-3156b0285bdf)\n\nWe believe that open-source and low-code go hand-in-hand with the diversity of money flows, payment scenarios and strategies that will make your company win.\n\n**🤙 Ping us anytime, we’re always more than happy to help and have a chat!**\n\n→ **Schedule a call here**: <https://calendly.com/numary/chat-with-numary?month=2022-07>\n\n→ **Drop us an email**: [founders@formance.com](mailto:founders@formance.com)\n\n→ **Check out use-cases library**: <https://www.formance.com/use-cases-library>\n\n→ **Download Formance Open Source Main Repo**: [**https://github.com/formancehq/stack**](https://github.com/numary/ledger)",
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        "votes": 23,
        "created_at": "2022-07-08T10:26:05.510Z"
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        "title": "Founder",
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        "tagline": "Build compliant, auditable, production-ready permissions, role based access control, and more in minutes instead of months.",
        "body": "![uploaded image](/media/?type=post&id=70447&key=user_uploads/234741/7662bcdc-8497-4a8c-a0c6-428ddc3bffe0)\n\nHey everyone! We’re Aditya and Karan! 👋\n\nWarrant is an open source **authorization service** that **helps developers implement and enforce secure, compliant access control in their applications.** It abstracts away the complexity of building application authorization and access control so developers can instead focus on building core product features.\n\nOur cloud-first, API-first approach has enabled us to build a highly-scalable and performant service that now processes millions of customer API calls per month. Today, we’re excited to announce that Warrant is officially [open source](https://github.com/warrant-dev/warrant)! ⭐️\n\n### The Problem\n\nDevelopers, we’ve all been there. What started as a simple _isAdmin_ flag to distinguish between internal and external users — just so you could release that _one_ internal-only feature — has grown into a nightmare to maintain. It’s now a hodgepodge of booleans, database flags, and a halfway built role based access control system that not only slows down your team’s day-to-day development velocity, but also opens up your company to a slew of [costly security vulnerabilities waiting to be exploited](https://www.hackerone.com/press-release/organizations-paid-hackers-235-million-these-10-vulnerabilities-one-year-4).\n\n![uploaded image](/media/?type=post&id=70447&key=user_uploads/234741/60544231-1dac-4013-8872-c97b83878da3)\n\nWhat’s more? Your customers are now requesting the ability to self-manage their team’s roles and permissions, so you’ll be spending another 1-2 months building the APIs, UIs, etc. for this risky, non-differentiating feature.\n\nIn short, application authorization and access control is difficult to build and even trickier to maintain as a company’s product evolves and its needs change.\n\n### The Solution\n\nTo help developers quickly build world-class access control, Warrant provides three things:\\\n(1) **A centralized datastore for storing your application’s authorization policies and related data.** Warrant’s management dashboard and APIs make it dead-simple to safely modify authorization policies globally or for a single user or tenant in real-time. With Warrant, updating policies for all users as your product changes becomes a breeze.\n\n(2) **A real-time, low latency access control service for enforcing authorization policies in your application at runtime.** With official Warrant SDKs available for the most popular server-side languages and frontend frameworks, checking if a user has access becomes as easy as a call to Warrant’s _check_ method.\n\n(3) **A library of thoughtfully designed, authorization-specific UI components** that help with building self-service permission management flows, granting/denying access to privileged pages/UIs, displaying audit logs to users, and more. These components are **customizable and _permission-aware_**, so developers can drop them into any application.\n\n### What’s Next?\n\nJoin us on our journey to solve authorization and access control for all developers:\n\n* Give us a 🌟 [on GitHub](https://github.com/warrant-dev/warrant) and tell us what you’d like us to build next\n* Give us a follow [on Twitter](https://twitter.com/warrant_dev) to keep up with the latest Warrant features\n* Come discuss everything authz/access control in our [Slack community](https://join.slack.com/t/warrantcommunity/shared_invite/zt-12g84updv-5l1pktJf2bI5WIKN4_\\~f4w)\n* Try out our managed cloud service, [Warrant Cloud](https://app.warrant.dev/signup)",
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        "body": "Hey there!\n\nI'm Gabe and I'm super excited to share [Meticulous](https://meticulous.ai/) with you today, the easiest way to create end-to-end tests, without writing (or maintaining) any code.\n\nWhat is Meticulous?\n\nMeticulous is a CLI tool with ‘record’, ‘simulate’ and ‘test’ commands. The record command opens an instrumented browser which records your actions as you interact with your web application. Watch the record command below:\n\n![uploaded image](/media/?type=post&id=64757&key=user_uploads/155134/7b3e6754-07fe-424f-9896-1ba0b78f513a)\n\nThe simulate command re-executes the recorded sequence of actions on a URL of your choice, like localhost . A test consists of a recording ID (which identifies the recording to simulate on the new version of code) and a simulation ID. Tests are defined and maintained in a meticulous.json file. Meticulous takes a visual snapshot at the end of each simulation and a test fails if there is a discrepancy between the two snapshots.\n\n![uploaded image](/media/?type=post&id=64757&key=user_uploads/155134/cda27a4d-831e-4a25-b884-20583a4832f2)\n\nWatch the test command in action below:\n\n![uploaded image](/media/?type=post&id=64757&key=user_uploads/155134/484ba0aa-628b-4885-a341-f55e4a2daf2b)\n\n### What about flows that mutate state?\n\nImagine a test that simulates a user signing up to your application. You can't sign up twice with the same email address. Traditionally you have two options: 1) Write a mock for the network call 2) Introduce a mechanism for resetting state after each test execution. Meticulous solves this problem by providing an option to automatically mock out all network calls, eliminating the need for either of these approaches. This option should be used if you wish to isolate the frontend.\n\n### How can I try this?\n\nSign up [here](https://app.meticulous.ai/) and try out the product (no credit card required), or check out the [docs](https://docs.meticulous.ai) here.\n\nOn a related note, I started offering testing office hours to YC founders. I’d be happy to help you out, even if you’re not a YC founder and it's just to strategize around your testing strategy. Just email [gabe](mailto:gabe@meticulous.ai) with the title ‘Testing office hours request’.",
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        "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.",
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      {
        "id": 65609,
        "title": "👾 Hyperbeam - Embed third-party apps, games, and websites anywhere",
        "tagline": "We make third-party embeds easy​​. Multiplayer supported out-of-the-box.",
        "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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    "name": "Unlayer",
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    "website": "https://unlayer.com",
    "all_locations": "Dubai, Dubai, United Arab Emirates",
    "long_description": "Unlayer helps companies add AI-powered content creation into their products without building it from scratch. Developers can embed visual builders for emails, pages, popups, and documents, then connect them to AI agents, templates, asset storage, exports, and APIs. We give teams the building blocks to let users and AI workflows create, edit, personalize, translate, and ship content directly inside their own product.",
    "one_liner": "AI-powered content creation infrastructure for apps",
    "team_size": 35,
    "industry": "B2B",
    "subindustry": "B2B -> Productivity",
    "launched_at": 1644263477,
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    "url": "https://www.ycombinator.com/companies/unlayer",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2022/unlayer.json",
    "year_founded": 2017,
    "city": "Dubai",
    "country": "AE",
    "linkedin_url": "https://www.linkedin.com/company/unlayer/",
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      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
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        "full_name": "Adeel Raza",
        "title": "Founder",
        "founder_bio": "I'm a serial technology entrepreneur with strong product focus.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/adeelr/",
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        "full_name": "Muhammad Umair Siddique",
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      {
        "id": 105004,
        "title": "Elements by Unlayer - Open-source React components for emails, pages, and PDFs",
        "tagline": "Elements lets developers and AI agents create emails, web pages, and PDFs from the same React codebase.",
        "body": "**TL;DR:** We’re launching Unlayer Elements, an open-source React content layer that lets developers and AI agents create emails, web pages, and PDFs from the same codebase. Write once in React, render everywhere.\n\nToday, we’re launching something new and open source:\n\n# Unlayer Elements\n\nAn open-source React content layer for developers and AI agents to create emails, web pages, and PDFs from the same codebase.\n\nGitHub: <https://github.com/unlayer/elements>\\\nDocs: <https://docs.unlayer.com/elements>\\\nDemo: <https://youtu.be/-ZoMlPYUbtk>\n\n## **The Problem**\n\nEvery SaaS product eventually needs content creation.\n\nAt first, it’s just one transactional email.\n\nThen it becomes welcome emails, password resets, receipts, invoices, reports, landing pages, PDFs, internal templates, previews, exports, and visual editing.\n\nMost teams end up maintaining separate systems for each output:\n\n* one system for email templates\n* one system for web pages\n* one system for PDFs\n* one system for visual editing\n* one system for exports\n\nThe content is often similar, but the implementation is different.\n\nThis becomes even more important now that AI agents are generating more code and content. Agents can create fast, but teams still need the output to be structured, reusable, version-controlled, and production-ready.\n\n![uploaded image](/media/?type=post&id=105004&key=user_uploads/105300/5911c2cd-ca33-48e8-86ff-72e1ce4fcfe7)\n\n## **What We Built**\n\nWe built Unlayer Elements: open-source React components for creating emails, web pages, and PDFs from the same codebase.\n\nDevelopers can use familiar components like:\n\n* &lt;Email>\n* &lt;Page>\n* &lt;Document>\n* &lt;Row>\n* &lt;Column>\n* &lt;Heading>\n* &lt;Paragraph>\n* &lt;Button>\n* &lt;Image>\n* &lt;Custom>\n\nEach output mode is tuned for where the content will live:\n\n* &lt;Email> renders email-safe table HTML\n* &lt;Page> renders responsive web HTML\n* &lt;Document> renders print-ready HTML for PDFs and documents\n\nSame component system. Different surfaces.\n\nA few examples of what you can build:\n\n* Transactional emails\n* Landing pages\n* Web versions of emails\n* Invoices\n* Receipts\n* Reports\n* Internal template galleries\n* PDF documents\n* AI-generated content flows\n\nElements also connects with the broader Unlayer platform. Developers can define content structure in code, and when visual editing is needed, teams can bring that work into Unlayer’s Builder so marketers, admins, or end users can edit without touching code.\n\n## **Our Ask**\n\nWe’re open sourcing this early because we want feedback from people building with React, Next.js, email, PDFs, templates, and AI-generated content.\n\nWe’d love for you to:\n\n1. Try it and tell us what feels useful or missing.\n2. Star the GitHub repo if you want to support the project.\n3. Share examples of emails, pages, PDFs, invoices, reports, or AI-generated content workflows you’d want Elements to support.\n\nGitHub: <https://github.com/unlayer/elements>\\\nDocs: <https://docs.unlayer.com/elements>\n\nWould love feedback from the YC community.\n\nEmail: [founders@unlayer.com](mailto:founders@unlayer.com)",
        "url": "https://www.ycombinator.com/launches/RJc-elements-by-unlayer-open-source-react-components-for-emails-pages-and-pdfs",
        "votes": 5,
        "created_at": "2026-07-08T19:42:04.469Z"
      },
      {
        "id": 102816,
        "title": "Unlayer: AI-powered content creation for your product",
        "tagline": "Let your users create beautiful emails, pages or documents with AI.",
        "body": "**TL;DR:** [**Unlayer**](https://unlayer.com) is an AI-powered content creation platform for developers. It gives you **embeddable builders**, templates, APIs, and AI toolkit so your users can create **emails**, **pages**, **documents**, and other content directly **inside your product**.\n\n<https://youtu.be/qp9t74G4VyM>\n\n—\n\n## The Problem\n\nAlmost every software product eventually needs users to create content.\n\nEmails, landing pages, proposals, invoices, documents, announcements, templates, PDFs, and more.\n\n![uploaded image](/media/?type=post&id=102816&key=user_uploads/105300/df31db0c-923c-4ac3-977d-bd881f9586d1)\n\nAt first, this looks like “just add an editor.” Then you need responsive rendering, templates, merge tags, asset management, permissions, versioning, exports, personalization, localization, and now AI generation.\n\nA small feature quietly becomes an entire content creation platform.\n\n—\n\n## What We Built\n\n**Unlayer gives developers the building blocks to add AI-powered content creation into their own products.**\n\nYou can embed visual builders for emails, pages, popups, and documents, then connect them to templates, file storage, exports, APIs, and AI workflows.\n\nYour users can visually create and edit content. Your AI agents can generate, personalize, translate, and modify that content through APIs and skills.\n\n![uploaded image](/media/?type=post&id=102816&key=user_uploads/105300/c9995728-e131-44cd-93cc-d295f255cf1b)\n\nOver time, Unlayer has grown to **1,000+ customers**, from startups to teams at **Netflix**, **Fidelity**, **Bank of America**, **Mastercard, Twilio, Chargebee**, and others.\n\nThat has given us a front-row seat into the same pattern: almost every product eventually needs users or AI to create content inside the product itself.\n\n—\n\n## Why AI Changes This\n\nContent creation is moving from manual editing to assisted and automated workflows.\n\nA user should be able to say:\n\n* **_“Create a launch email for this feature.”_**\n* **_“Translate this landing page into Spanish.”_**\n* **_“Turn this proposal into a branded PDF.”_**\n* **_“Personalize this announcement for each customer segment.”_**\n\n![uploaded image](/media/?type=post&id=102816&key=user_uploads/105300/639a8626-7790-4094-b684-c4800407a6c6)\n\nBut for AI to do this well inside a product, it needs more than a text box. It needs access to templates, design structure, brand rules, assets, exports, and the final builder where humans can review and edit.\n\nThat is what we are building with Unlayer.\n\n—\n\n## Our Vision\n\nWe think the future of content creation inside software has two interfaces:\n\n1. A visual builder for people\n2. An action layer for AI agents\n\nPeople should be able to drag, drop, edit, approve, and fine tune.\n\nAI should be able to create, rewrite, personalize, translate, export, and eventually ship content automatically.\n\nUnlayer is the infrastructure layer that connects both.\n\n—\n\n## Backstory\n\nWe started Unlayer because we kept seeing teams rebuild the same content creation stack over and over.\n\n**Email HTML is painful**. Landing pages need **forms** and scripts. Documents need **PDF generation**. Templates need **permissions**. Assets need **storage**. Every product needs customization. And now AI needs to work across all of it.\n\nWe have spent years solving these problems so other teams do not have to.\n\n![uploaded image](/media/?type=post&id=102816&key=user_uploads/105300/87ce4023-46cd-4d48-8e8a-06774d6c6bc4)\n\n—\n\n## Our Ask\n\nIf your product has users creating emails, pages, documents, templates, or customer-facing content, Unlayer will be useful for you. [Try it out](https://unlayer.com/)",
        "url": "https://www.ycombinator.com/launches/QkK-unlayer-ai-powered-content-creation-for-your-product",
        "votes": 17,
        "created_at": "2026-06-09T21:37:01.868Z"
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    "name": "Elementary",
    "slug": "elementary",
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    "website": "http://elementary-data.com/",
    "all_locations": "Tel Aviv-Yafo, Tel Aviv District, Israel",
    "long_description": "Elementary enables data teams to detect problems in their data before their users do. An open-source solution that any data engineer can deploy in minutes without sharing sensitive data.",
    "one_liner": "Open-source data observability for data teams",
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    "industry": "B2B",
    "subindustry": "B2B -> Analytics",
    "launched_at": 1647515701,
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      "Open Source",
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    "batch": "Winter 2022",
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    "regions": [
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    "year_founded": 2021,
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    "country": "IL",
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        "full_name": "Maayan Salom",
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        "linkedin_url": "https://www.linkedin.com/in/maayansa/",
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        "title": "Head of GTM and Growth",
        "url": "https://www.ycombinator.com/companies/beam/jobs/6rKakUF-head-of-gtm-and-growth",
        "location": "New York, NY, US",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$120K - $160K",
        "equity_range": "0.25% - 1.00%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
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        "title": "Distributed Systems Engineer",
        "url": "https://www.ycombinator.com/companies/beam/jobs/lwlKfNI-distributed-systems-engineer",
        "location": "New York, NY, US / San Francisco, CA, US / Remote (US)",
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        "role": "Engineering",
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        "title": "Superflow AI: QA agents for your website",
        "tagline": "AI agents that QA every page of your website",
        "body": "## TL;DR\n\nAI made creating websites fast. Checking still costs what it always did. [Superflow](https://usesuperflow.ai/) closes that gap: it turns your QA checklist into AI agents.\n\n* They sweep every page of your site and handle the black and white issues: a dead link, a typo, a form that doesn't submit, a layout that breaks a written brand guideline.\n* You handle taste: the calls with no reference to check against, like whether a design direction is right or a page is good enough to ship. An agent can flag a page. Only a person can approve one.\n* They learn from every review, so the hundredth site gets checked better than the first.\n* Teams tell us the agents catch about 90% of what they used to find by hand. The other 10% needed a person all along.\n\n## Demo\n\n<https://www.youtube.com/watch?v=x8g5jZ2vKno>\n\n## The problem\n\nAn agency founder told us, \"We're never changing our QA process. It's tight.\"\n\nThen he sent us the checklist: 400 rows. Ten people clicking through every page by hand.\n\nWe ran our agents on one of his live sites. First finding: placeholder text, live for months. It was on the checklist. Row 212.\n\nChecklists don't fail because they're wrong. They fail because a human is on row 212 at 9pm on a Friday.\n\nAnd the misses that hurt aren't broken links:\n\n* A phone number in the header that doesn't match the footer.\n* \"Award winning\" on a site with no award. In dental, that's a regulator problem.\n* A previous client's name in a testimonial because the page was cloned.\n\nCreating a site collapsed to an afternoon. Checking it didn't budge.\n\n## How it works\n\n* Upload your checklist as is: spreadsheet, PDF, or doc. No reformatting.\n* Superflow turns it into a set of agents, including any custom checks on your list.\n* They run in parallel on every page, phone and desktop. A full site takes minutes.\n* Every finding is pinned on the page with a screenshot, so if the layout shifts later you still have the picture.\n* It fits your process: custom statuses, private team comments (agent findings stay team-only until you clear them), two way sync with your task tool, and a daily recap.\n* Agents learn. Reject a finding and it stops coming back. Catch a miss yourself and it becomes a check on every site after.\n\n## Backstory\n\nLast week we moved our own site from Framer to Next.js.\n\nThe step that used to eat the timeline, clicking through every page to catch what silently broke, our own agents did before sign off.\n\nThe build took a week. We were live in two, start to finish.\n\nCreating done by AI. Checking done by agents. Judgment kept by people.\n\n## Ask\n\nTry [Superflow](https://usesuperflow.ai/) on one page of your own site. No card, no login for reviewers.",
        "url": "https://www.ycombinator.com/launches/Swz-superflow-ai-qa-agents-for-your-website",
        "votes": 2,
        "created_at": "2026-08-18T15:55:44.561Z"
      },
      {
        "id": 99540,
        "title": "Velt Cursor plugin: Add Real-Time Collaboration to your App in 10 mins",
        "tagline": "/install-velt. One command. Add CRDT, comments, activity logs, and notifications to your app in one command.",
        "body": "Type **/install-velt**. The agent reads your codebase, asks which features you want, and scaffolds everything.\n\nComments that attach to specific elements. Real-time editing (CRDT). Presence. Cursors. Notifications. Activity logs. All wired up. Working app.\n\nAdding collaboration features looks like a weekend project. It's not.\n\nComments that anchor to elements. CRDT editing that doesn't corrupt data. Live cursors. Notifications. Activity logs. Each one is simple alone. Together they touch auth, state, routing, permissions, websockets. Get the order wrong and nothing works.\n\nMost teams skip it or spend months on it. Regret both.\n\nWe encoded 140+ implementation rules into the plugin so the agent doesn't make those mistakes. It also includes two MCP servers and a velt-expert agent persona for architecture questions.\n\n→ Watch the demo: <https://www.youtube.com/watch?v=-7we6P5w6I8>\n\n→ Cursor Directory: <https://cursor.directory/plugins/velt>\n\n→ Cursor plugin: <https://github.com/velt-js/velt-plugin-cursor>\n\n→ Claude Code plugin: <https://github.com/velt-js/velt-plugin-claude>\n\n→ Docs: <https://docs.velt.dev/get-started/plugins>\n\nIf you try **/install-velt** on an existing project and something breaks, tell us. That's the case we most want to stress test.",
        "url": "https://www.ycombinator.com/launches/PtU-velt-cursor-plugin-add-real-time-collaboration-to-your-app-in-10-mins",
        "votes": 6,
        "created_at": "2026-04-07T20:19:13.619Z"
      },
      {
        "id": 99380,
        "title": "Velt Activity Logs: Audit trail for humans and AI agents",
        "tagline": "One audit trail for every action in your product. Who did what, and when.",
        "body": "\n![uploaded image](/media/?type=post&id=99380&key=user_uploads/195692/08763c82-d915-4369-8e0d-2d5a820be7de)\n\nRight now, most products have no idea what their AI agents did yesterday.\n\nThat's going to seem crazy in two years.\n\nEvery SaaS product is adding AI agents that write, edit, and approve things. But only human actions produce an audit trail. AI agents just act. No record. No attribution. No proof a human reviewed the output.\n\nThis breaks the moment a customer's compliance team asks one question: \"Did a human approve this?\"\n\n**What we built:**\n\nVelt is a collaboration infrastructure SDK. Comments, presence, real-time editing (CRDT), recording, notifications. Activity Logs is the newest piece.\n\n→ Auto-captures comments, reactions, recordings, CRDT edits. Zero config. \n\n→ createActivity() for your own events. One function call. \n\n→ AI agents produce the same record as humans. Same schema. Same attribution. \n\n→ Immutable by default. SOC 2 Type II. HIPAA with BAA.\n\nAgent acted → Human reviewed → Decision recorded. The pair is the proof.\n\n**Ask:**\n\nIf your enterprise buyers are asking for proof of human oversight over AI, we built this for you. Try it and tell us what's missing.\n\n<https://velt.dev/activity-logs>",
        "url": "https://www.ycombinator.com/launches/Pqu-velt-activity-logs-audit-trail-for-humans-and-ai-agents",
        "votes": 5,
        "created_at": "2026-04-02T19:32:54.147Z"
      },
      {
        "id": 98498,
        "title": "Velt Claude plugin: Add Real-Time Collaboration to your App in 10 mins",
        "tagline": "Claude Code plugin that adds CRDT, comments, presence, and notifications to your app in one command.",
        "body": "Building collaboration features from scratch is one of those problems that looks simple and isn't.\n\nCRDT for live sync. Presence to show who's online. Comments that attach to specific elements. Notifications. Permissions. \n\nIt compounds fast. Most teams either skip it or spend months on it and regret both decisions.\n\nWe've been building this infrastructure for 4 years. Varonis, Pendo, HeyGen, Freshworks, Trumpet already use it in production.\n\nToday we're launching a Claude Code plugin that installs all of it in under 10 minutes.\n\nYou run one command. It asks which features you want. \n\nYou give it your API key. It installs, configures, and wires everything together.\n\nThat's it.\n\n→ Watch the demo: <https://www.youtube.com/watch?v=JpfKRu65DTk>\n\n→ Get started: <https://velt.dev/>\n\n→ Docs: <https://docs.velt.dev/get-started/plugins>\n\nWe're a small team and we read every message. \n\nIf you try it and something doesn't work, tell us.",
        "url": "https://www.ycombinator.com/launches/Pcg-velt-claude-plugin-add-real-time-collaboration-to-your-app-in-10-mins",
        "votes": 3,
        "created_at": "2026-03-05T17:38:44.587Z"
      },
      {
        "id": 94308,
        "title": "Velt: Multiplayer Editing Toolkit for React Flow (Build Multiplayer Agent Workflows)",
        "tagline": "Add multiplayer editing capability in minutes.",
        "body": "If you are building AI agents and AI workflow builders inside your product, then you are most likely using[ React Flow](https://reactflow.dev/) to power these experiences. Now with[ Velt](https://www.linkedin.com/company/veltjs/), within a few minutes you could make these workflows multiplayer just like Figma's FigJam! We’ve created a purpose-built plugin for React Flow that makes any react flow implementation multiplayer out of the box.\n\n![uploaded image](/media/?type=post&id=94308&key=user_uploads/195692/38bab09b-d530-458b-9c03-25444a9d5758)\n\n**Velt does the heavy lifting:**\n\n* fully managed ultra low latency backend\n* real-time merges and conflict resolution (CRDT via Yjs)\n* offline support\n* presence indicators\n* slack-style huddle\n* figma-style comments and notifications\n* custom encryption for additional security\n\nYou can focus on delivering epic value to your users. No more building complex infra from scratch.\n\n**Demo**\n\n* [Demo video](https://www.youtube.com/watch?v=mgz0jOCLyUA)\n* [Live Demo](https://velt-reactflow-crdt-demo.vercel.app/)\n* [Sample code](https://github.com/velt-js/velt-reactflow-crdt-demo)\n* [Docs](https://docs.velt.dev/realtime-collaboration/crdt/setup/reactflow)\n\n**Customers**\n\nWe power multiplayer experiences for companies like **Heygen**, **Pendo**, **Runway**, **Vellum** etc\n\n### [**Try today**](https://velt.dev/multiplayer-editing)",
        "url": "https://www.ycombinator.com/launches/OX6-velt-multiplayer-editing-toolkit-for-react-flow-build-multiplayer-agent-workflows",
        "votes": 8,
        "created_at": "2025-10-03T01:06:50.117Z"
      },
      {
        "id": 84853,
        "title": "Velt: Tiptap Comments",
        "tagline": "Enable comments and collaboration in your Tiptap editor.",
        "body": "With [**Tiptap Comments Extension**](https://www.npmjs.com/package/@veltdev/tiptap-velt-comments), you can add Google Docs-style overlay comments to your Tiptap editor. Here is a [**demo video.**](https://www.youtube.com/watch?v=PIWBwV3IHok) You can [**try it here.**](https://documentation-app-demo.vercel.app/)\n\n![](https://bookface.ycombinator.com/media/?type=post&id=84853&key=user_uploads/195692/d711f012-f784-4ed9-b481-5ee328b75f07)\n\nIt's fully customizable and comes with a lot of powerful built-in features like attachments, mentions, recording, notifications and more.\n\nAdding comments and notification features have shown to boost engagement and growth with platforms. If you use Tiptap in your product, you could enable powerful collaborative experiences using [Velt](https://velt.dev/).\n\n### **Installation**\n\nYou can install the NPM package [here.](https://www.npmjs.com/package/@veltdev/tiptap-velt-comments)\n\n### **Supported Frameworks**\n\nAll major JS frameworks like React, Next, Angular, Vue, Svelte.\n\n### **More about Velt SDK**\n\nWith Velt SDK you can add powerful collaboration features to your product extremely fast.\n\nThe SDK provides **fullstack components**:\n\n* UI and behavior are fully customizable to match your product's needs\n* fully-managed on a scalable realtime backend\n\nFeatures include:\n\n* **Comments** like Figma, [Frame.io](http://Frame.io), Google Docs, Sheets and more\n* **Recording** like Loom (audio, video, screen)\n* **Huddle** like Slack (audio, video, screensharing)\n* In-app and off-app **notifications**\n* **@mentions** and assignment\n* **Presence**, **Cursors**, **Live Selection**\n* **Live state sync** with Single Editor mode\n* **Multiplayer editing** with conflict resolution\n* **Follow mode** like Figma\n* ... and so much more",
        "url": "https://www.ycombinator.com/launches/M4b-velt-tiptap-comments",
        "votes": 14,
        "created_at": "2024-10-17T22:07:51.992Z"
      },
      {
        "id": 84000,
        "title": "Embedded Recording SDK by Velt",
        "tagline": "Add AI powered Loom-style recording to your product!",
        "body": "We're excited to launch [**Embedded Recording in the Velt SDK**](https://velt.dev/recording). Build AI-powered Loom-style recording features (voice, video, and screen) **into your product** in minutes. It automatically generates summaries and transcriptions.\n\n![uploaded image](/media/?type=post&id=84000&key=user_uploads/195692/5f8d698a-2c7e-4d5e-bba5-4add9671cbee)\n\n# **Why this matters:**\n\nYour users are probably already using tools like Loom to communicate. That's time and data they could be spending in your product. Keep your users in your product with native communication features and boost engagement. It's a win for everyone.\n\n# **Products that benefit:**\n\n* Ticketing tools _(Jira, Linear)_\n* Project management tools _(Asana, ClickUp)_\n* Email marketing tools _(Apollo, Customer.io )_\n* Sales tools _(Salesforce, Hubspot)_\n* Development tools _(Github for code reviews)_\n\n# **How it works:**\n\nVelt is a JS SDK that handles everything—UI/UX, full functionality, backend server, and storage. No configuration is needed. You can fully customize it to fit your brand. It works with Next.js, React, Angular, and more.\n\n4 easy steps to get started (see [docs](https://docs.velt.dev/async-collaboration/recorder/setup)):\n\n1. Initialize Velt SDK\n2. Add the recorder components\n3. Customize\n4. That's it!\n\n# **Key Features:**\n\n* Native voice, video, and screen recording\n* AI transcriptions and summaries\n* Built-in recording and playback UI\n* Cross-browser and device compatibility\n* Fully customizable\n* Fully managed and scalable storage and backend",
        "url": "https://www.ycombinator.com/launches/Lqq-embedded-recording-sdk-by-velt",
        "votes": 10,
        "created_at": "2024-09-13T02:03:03.103Z"
      },
      {
        "id": 79688,
        "title": "Velt: Full-stack Comments SDK",
        "tagline": "Build powerful commenting features into your SaaS product crazy fast.",
        "body": "**TL;DR:** Build powerful commenting features into your SaaS product crazy fast. Make it just as collaborative as the big dogs—Google Docs, Sheets, Figma, Frame io... Keep your users collaborating in your app instead of Slack or Zoom. Watch your engagement soar.\n\n[**Demo Video**](https://www.youtube.com/watch?v=27tIG8jEAbc)\n\n![uploaded image](/media/?type=post&id=79688&key=user_uploads/195692/3b9b3bc9-6a81-4e98-82e8-abb2d917f9b5)\n\n### **🤔 Why?**\n\nYour customers want to have discussions within your product – feedback, questions, ideas. Since they can’t do it in your product, they move off-platform to slack, emails, zoom etc.. It's friction for your customers (and you'll watch their engagement drop.)\n\nLuckily, the solution is simple. Add a comment layer across your product. Let customers comment and discuss anywhere, without opening up Slack or Gmail.\\\n\\\nI know what you're thinking. \"How am I going to build that? That's months of engineering and product effort we haven't scoped in.\"\n\n### **✅ Solution**\n\nWe built a complete full-stack Comments feature components for any SaaS product. Embed it anywhere and enable experiences you see in your favorite products like Google Docs, Figma, Sheets and more.\n\nBackend, Frontend - all included.\n\n### **✅ Products that benefit from commenting**\n\n* _Video tools: Frame-by-frame feedback on videos_\n* Documentation tools: Inline comments for better edits\n* _Analytics / Data tools: Questions answered directly on charts and tables_\n* Design tools: Review design assets\n* Form builders, CRMs and so many more\n\n### **🚀 Key Features**\n\n* Commenting Styles: Google Sheets, Google Docs, Notion, Figma, [Frame.io](http://Frame.io), Charts, etc.\n* Loom-style audio, video, screen recording\n* Task management: Statuses, Priority, approval, @ mention\n* Intelligence: AI categorization, AI transcription\n* Customize layout, css & behavior\n* In-app notifications, email notifications, realtime Webhooks\n* Performant and Robust: Buttery smooth. Binds and adapts to changes in your DOM and data.\n\n### **🚀 Try here:** [**https://velt.dev/comments**](https://velt.dev/comments)",
        "url": "https://www.ycombinator.com/launches/KjI-velt-full-stack-comments-sdk",
        "votes": 8,
        "created_at": "2024-03-25T21:40:45.302Z"
      },
      {
        "id": 79200,
        "title": "Superflow: Frame by frame review on Lottie files",
        "tagline": "Get approvals with fewer rounds of reviews and ship more assets fast!",
        "body": "We fixed the mess of Lottie animation reviews. Frame-by-frame comments mean you ship more animations faster. [Here](https://drive.usesuperflow.com/lottie?id=YVUxTXhLUDByY2EyVVh3S2k4YmxfXzMzYmQzYjg3ZWM3ZjI2NTUxOTQxYjMyMjQ2ZjJhOTAxX19sb3R0aWU%3D&version=v1&_gl=1\\*59beb5\\*_gcl_au\\*MTc5OTQ4OTk4OS4xNzA3NzA3MTc4) is a live demo.\n\n![uploaded image](/media/?type=post&id=79200&key=user_uploads/195692/caa35638-b3e5-4704-9cf3-be7fc8e57db9)\n\nOur mission is to make every creator 10x. We believe creators build the future and your time is precious. Superflow makes you a 10x creator: create 10x more, create 10x better work, grow 10x.\n\n**🤔 Why are we building this?**\n\nWe built this because the old way sucked. Screenshots, endless emails, live meetings just to tweak an animation... that's not how things should work in 2024. So we fixed it!\n\n**✅ Solution**\n\nSuperflow lets creative teams review and provide frame-by-frame feedback on Lottie files.\n\nThis enables you to get approvals with fewer rounds of reviews so that you can get back to animating. With Superflow, you deliver more beautiful animations at light speed.\n\n**🚀 Key Features**\n\n* Pinpoint feedback on frames and individual elements.\n* Voice, Video + AI notes for when typing is too slow.\n* Built-in task management to streamline the process.\n* Works on all devices and browsers.\n* Integrates with your existing tools: Asana, ClickUp, Monday, Slack, you name it.\n* Built-in approval flow just like Docusign.\n* Share easily with a click and get notified when someone visits.\n\n[**Get started**](https://usesuperflow.com/lottie-files-review), it’s free.",
        "url": "https://www.ycombinator.com/launches/KbQ-superflow-frame-by-frame-review-on-lottie-files",
        "votes": 7,
        "created_at": "2024-03-08T03:28:50.378Z"
      },
      {
        "id": 66899,
        "title": "Superflow: Comment and collaborate directly on your product!",
        "tagline": "Comment and collaborate on your staging and prod websites.",
        "body": "![uploaded image](/media/?type=post&id=66899&key=user_uploads/195692/536286e1-bb3b-475f-a06a-b7a9d275aac7)\n\n_(_[_demo video)_](https://www.youtube.com/watch?v=cdnfBEw8TfI)\n\n[SuperFlow](https://usesuperflow.com/) makes it super easy to comment on live websites just like you comment on Figma. You can use is to get Copy or UI feedback right on the website you are building. Feedback can be provided in rich formats like audio and video. The best part is that you and your clients don’t need a browser extension.\n\nSuperFlow brings collaboration to wherever you are. Everything is just weaved into one cohesive experience. We have curated the best features of top products like Slack, Loom, Figma into one tool.\n\n### **👩🏼‍💻Who this is for**\n\nWeb agencies, freelancers, product or design teams.\n\n### **Key problems**\n\n* Scattered feedback across emails, slack etc.\n* Endless back and forth, screenshots, unnecessary meetings etc.\n* Clients have to install & learn new tools.\n\n### **📝 Use cases**\n\n* Get copy or UI feedback from clients.\n* Assign tasks to internal team members.\n\n### **💵 Value**\n\n* Reduce website review cycles and ship faster.\n\n### **🙏 Our ask**\n\n* Try our product [**usesuperflow.com**](http://usesuperflow.com) before 31st oct and get 40% off for a year.\n* Share this post with web agencies or freelancers you know build websites.\n\n### **Setup**\n\n**Step 1: Install JS tag on client website in 10 secs.**\n\nYou can just install a JS tag in the footer of the website. \n\n![image.png](https://codahosted.io/docs/TJ6E9cySHQ/blobs/bl-XGbnRxc0Ty/6140d41636b973449d24659aeacab52fd67900c5654c7c113ffc4ad3bf5306eeed19b1162a8b3ccde2cfa635c642722135a4d4a2a87642b35d5f4ec7b6325a88fecd86969d39bd8043dde97a4cf4f9c00515efb075c175855fcb3da704047bd6edbd9efc)\n\n**Step 2: Turn on review mode by adding ?review=true to the URL.**\n\nYou can then turn the review mode on or off on demand by adding **“?review=true”** to the URL. The comments will not be visible to a regular website visitor.\n\n![image.png](https://codahosted.io/docs/TJ6E9cySHQ/blobs/bl-WB9sVT7ZmM/5570471db96e4ea68d9d74f0835939d91e707a467094fd00c51b9eb97542df4a9a84996faeccd683f74aab60fda711f099cf8e9568c42c86c9dd28eef6ef1b80a1ac503d3fb04104fa11b10b749058363a6b3ad58d51f58a20f1483ca8f276fe07d44cfc)\n\n### **🔥 Top features**\n\n**1. Comment on live website, just like Figma:**\n\n![image.png](https://codahosted.io/docs/TJ6E9cySHQ/blobs/bl-NDI5rEj4Ae/8c9caf47c3a53155af4d62231f4d767096816c6d91ba0306fce57e04b642ecb3e5bd70514556c11fb51189d028ea5cb34356c5a0eeff686a40289176667f86af011dd92122307ac44176b1b46c7d7c449652d008714c34e435bc8b41f9fa0bb810973eb3)\n\n**2. Record your screen & camera just like Loom (& attach it to a DOM element).**\n\n![image.png](https://codahosted.io/docs/TJ6E9cySHQ/blobs/bl-JCblThJt6X/57029764bf3d09a31f0a0d1bcaadfac8a927f26b8a63a34ab1236ca4490454ad7c70a081861e6e4b277d5e920e409af0c7a18a6db1be2ac823ba50e3cfc9a5a957bf8ae09430389015c9c72d969ff467cbc01a75320a63735e073d370371dc2d59dc52e9)\n\n**3. Manage tasks across projects in one place.**\n\n![image.png](https://codahosted.io/docs/TJ6E9cySHQ/blobs/bl-eFWGPbIP0M/2e74eaed9a5b399778c9521b9c65a0682fdd12c879322c8dcf4a8ce5e403f5a9b53516680ed1f4b1ad3655c55820b95a233b0a9e074aa9c8fcd4b56fa355607e6648216389a985f7a0a240dd0a55840bbb78b2225e2fea42c0970ace85763b76f8785c7e)\n\n**4. Start live audio/video huddle or screensharing just like Slack.**\n\n![image.png](https://codahosted.io/docs/TJ6E9cySHQ/blobs/bl-XBrG5e-yJd/fa5e98c2123e926dd9f3199da059dbc03e0dfd31c1f25ffdfa582150df6b53b92847bd8a7c005cfdba9c1cdbf0b375e0a757e59679d39f62c465c6a3f0b4936077e41ba5155058db8dae976623f327f1f68288483a1eef47751f1d252e09fb9712d85c8c)\n\n**5. Personalized Slack & email notifications.**\n\n![image.png](https://codahosted.io/docs/TJ6E9cySHQ/blobs/bl-OkDBML4l8F/f1bb3bd394f220a23f2e7b454de8ec767c322dac395eddbffdcf0beece7775d08797d40c89282e889abb5e5915b492b8db98cb12a1847492859dfc18bafa94fd06df75266314f7e71aa5b7a8bcc122e919cbc5f5280aceb9b31c90e13f32a269da77cef5)\n\n**6. Add internal comments for team & external ones for clients.**\n\n![image.png](https://codahosted.io/docs/TJ6E9cySHQ/blobs/bl-ECwdHMSTuh/81021b5d9a38077d7650507ff098d256af6cee5751f22b1c0da8f08b027eb0ef49ba9545316ee9b4ed4d70c17f7e0f98c41d78a7524437b660e213ba2f623b0e01834ef467c04069952f603cc48837e657130abd66a548c3e92ba6a5812574862ec11e5e)\n\n",
        "url": "https://www.ycombinator.com/launches/HP1-superflow-comment-and-collaborate-directly-on-your-product",
        "votes": 14,
        "created_at": "2022-10-25T03:03:03.856Z"
      }
    ]
  },
  {
    "id": 25690,
    "name": "Requestly",
    "slug": "requestly",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/397665634f98c5b29320b633cf76ae515930481f.png",
    "website": "https://requestly.com",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "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.",
    "one_liner": "Open-Source Postman alternative",
    "team_size": 19,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1639034757,
    "tags": [
      "Developer Tools",
      "SaaS",
      "Open Source",
      "API"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2022",
    "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": [
      {
        "question": "Describe what your company does in 50 characters or less.",
        "answer": "Developer Tool for APIs debugging & testing"
      },
      {
        "question": "How long have each of you been working on this? How much of that has been full-time? Please explain.",
        "answer": "I started Requestly as a side project along with my full-time job where I got to know about the use case, discovered the problem space and market size. Now, Both of us are working on this full-time."
      }
    ],
    "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": "Sachin worked at a tech company where he needed a way to test his JavaScript code changes quickly. Instead of waiting to test changes in the staging environment, he wanted to see how his local code would work in the live production website. To solve this problem, he built a Chrome browser extension in his free time and published it on the Chrome Web Store.The extension started becoming popular with other developers. Seeing this interest, Sachin added more useful features like advanced URL matching, request blocking, and script injection.Around this time, Sagar was studying for his master's degree and looking for an interesting project. He reached out to Sachin, and they met at a co-working space to discuss working together. They saw the potential to turn this simple browser extension into a complete debugging platform.Sachin believed so strongly in their project that he quit his full-time job to focus on it.. Both Sachin and Sagar were inspired by the Startup School, so they applied to the W22 Batch and were accepted."
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        "full_name": "Sachin Jain",
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        "is_active": true,
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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",
        "url": "https://yourstory.com/2022/03/indian-startups-y-combinator-winter2022-cohort",
        "date": "Mar 21, 2022"
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      {
        "id": 85821,
        "title": "Requestly - Open-Source API Mocking & Testing Tool for Developers 🚀",
        "tagline": "A better alternative to Postman & Charles Proxy",
        "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",
        "url": "https://www.ycombinator.com/launches/MKD-requestly-open-source-api-mocking-testing-tool-for-developers",
        "votes": 28,
        "created_at": "2024-11-25T07:44:19.492Z"
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    "id": 25720,
    "name": "Convoy",
    "slug": "convoy-2",
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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",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1643184279,
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    "country": "GB",
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        "full_name": "Subomi Oluwalana",
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        "founder_bio": "Subomi Oluwalana is the Co-founder and CEO of Convoy. Subomi is a software engineer and entrepreneur. Nothing excites him more than bringing ideas to life. Originally, He graduated from Landmark University where he received a Bachelor in Accounting & Finance.",
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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.",
        "url": "https://www.ycombinator.com/launches/Isv-nohooks-webhooks-for-platforms-without-webhooks",
        "votes": 12,
        "created_at": "2023-06-28T13:40:13.909Z"
      },
      {
        "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!",
        "url": "https://www.ycombinator.com/launches/H77-convoy-open-source-webhooks-proxy",
        "votes": 36,
        "created_at": "2022-09-01T20:15:33.795Z"
      }
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    "id": 25738,
    "name": "Hydra",
    "slug": "hydra",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/87c0954c151aa7067e034d8de33b3174d43f5ff0.png",
    "website": "https://hydra.so",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "Hydra is a real-time analytics database management system for Postgres. We seperate compute from storage to offer software engineers serverless analytics with autoscale, write isolation, automatic caching, and more.\r\n\r\nShipping scalable projects on time series and event data has never been easier. Hydra is available for local development, cloud, and bare metal deployment.",
    "one_liner": "Serverless Analytics on Postgres",
    "team_size": 6,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1642199733,
    "tags": [
      "Developer Tools",
      "Analytics",
      "Open Source",
      "Data Engineering"
    ],
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2022",
    "status": "Acquired",
    "industries": [
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      "Infrastructure"
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    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Fully Remote"
    ],
    "stage": "Early",
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    "app_answers": null,
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    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2022/hydra.json",
    "year_founded": 2021,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/hydradatabase",
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    "primary_partner": {
      "name": "Tom Blomfield",
      "url": "https://www.ycombinator.com/people/tom-blomfield"
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        "user_id": 54309,
        "full_name": "Joseph Sciarrino",
        "title": "Founder",
        "founder_bio": "CEO, Hydra\nFormer PM @ MSFT Azure Open-Source Databases team.\nHeroku (W08) and Citus Data (S11) alum",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jsciarrino12/",
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      {
        "title": "Microsoft backs open source PostgreSQL analytics extension • The Register",
        "url": "https://www.theregister.com/2024/08/20/postgresql_duckdb_extension/",
        "date": "Aug 20, 2024"
      },
      {
        "title": "Hydra aims to be the open cloud data warehouse alternative to Snowflake – TechCrunch",
        "url": "https://techcrunch.com/2022/07/01/hydra-aims-to-be-the-open-cloud-data-warehouse-alternative-to-snowflake/",
        "date": "Jul 01, 2022"
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    ],
    "launches": [
      {
        "id": 88443,
        "title": "Hydra: Serverless Realtime Analytics on Postgres",
        "tagline": "Unlock realtime analytics on live data in seconds",
        "body": "![uploaded image](/media/?type=post&id=88443&key=user_uploads/54309/fc2a33f3-1607-4213-bee9-7fb9693b0f5f)\n\n**Hydra is Serverless Realtime Analytics on Postgres.**\n\nBy separating compute from storage, Hydra enables compute-isolated analytics and bottomless storage. It is designed for low latency applications built on time series and event data.\n\n# [**Try Now! (free)**](https://start.hydra.so/get-started)\n\n<https://youtu.be/mib8ehnMmC8>\n\n# **Enable in seconds**\n\n![uploaded image](/media/?type=post&id=88443&key=user_uploads/54309/42f17c01-89e7-47ae-ba01-f76bc23c864e)\n\nSet up is simple. To unlock serverless realtime analytics on Postgres, run:\n\n```\npip install hydra-cli\n```\n\nFor setup\n\n```\nhydra\n```\n\n1. fetch your hydra token, paste in to enable Hydra\n2. create analytics schema / tables and insert data ([**quickstart docs**](https://docs.hydra.so/intro/quickstart))\n3. _voila_ - run queries, get insights in milliseconds\n\n# **Problem**\n\nFor decades, there’ve been two core problems with analytics on Postgres:\n\n**Slow** - aggregates and complex queries can take minutes to return results from large data sets.\n\n**Resource Contention** - Expensive analytics queries hog Postgres’ RAM / CPU resources and impair transactional performance. In other words, the entire app slows down, which makes users unhappy.\n\n# **Solution**\n\n### **Fast**\n\nHydra returns analytics queries 400X faster than standard Postgres. Hydra uses duckdb to perform isolated serverless processing on these tables in Postgres. In fact, Hydra is faster than most specialized analytics databases.\n\nIf you’re running AWS RDS, AWS Aurora, Heroku Postgres, Supabase, Fly Postgres, Render Postgres, GCP Cloud SQL, etc.. you can improve expensive analytics queries by 400X by using Hydra.\n\n![uploaded image](/media/?type=post&id=88443&key=user_uploads/54309/3fb7dc1e-622a-4303-ba7a-f729f18ab019)\n\nfun fact: the Snowflake instance (128x4XL) in the benchmark is $100k / month.\n\n![uploaded image](/media/?type=post&id=88443&key=user_uploads/54309/5db5d184-2a69-4811-b14e-5ad433f4038c)\n\nThese are results from clickbench which represents a typical workload in the following areas: clickstream and traffic analysis, web analytics, machine-generated data, structured logs, and events data. The table consists of exactly 99 997 497 records — rather small by modern standards but allows tests to be performed in a reasonable time.\n\n### **Isolated, serverless processing**\n\nUsing Hydra there is no impact on Postgres’ RAM / CPU resources when reading from or writing to an analytics tables.\n\nAs a result, here are more cool things Hydra can do: zero-copy clones for scaling read replicas, automatic caching, write isolation, bottomless storage with high data compression, and more.\n\n# **How it works**\n\n![uploaded image](/media/?type=post&id=88443&key=user_uploads/54309/8d8999aa-a370-4f0f-9d99-badfe4621c97)\n\nHydra integrates duckdb execution and features with Postgres using [**pg_duckdb**](https://github.com/duckdb/pg_duckdb), an open-source project we co-developed with the creators of DuckDB.\n\n**FAQ:**\n\nyes, you can join between an analytic table and a standard row-based table.\n\nyes, you can write (insert & update) to analytics tables.\n\nyes, Hydra is identical to using standard postgres.\n\nyes, data inserted into an analytics table is automatically converted into analytics-optimized columnar format.\n\ntell Hydra you are creating an analytics table by including the ‘using duckdb’ keyword - that’s it.\n\n# **Hydra is best for**\n\nHydra is both a row and columnstore, so you can use it for standard Postgres work, like multitenant apps, as well as analytical work, like monthly reporting. Here are several cool Hydra use cases that blend both transactional & analytics — more in our [**use case docs**](https://docs.hydra.so/guides/usecase).\n\n* time series, logs, events, traces\n* monitoring & telemetry\n* financial services\n* observability & metrics\n* cybersecurity & fraud detection\n* web & product analytics\n* iot\n* realtime ml / ai\n\n# **ok, but why use postgres instead of … \\[insert favorite tech\\]?**\n\nIt’s true, there are many specialized analytics databases. reviewing the benchmark above, the majority of analytics databases are actually _slower_ than Hydra. Regardless, isolated analytics databases produce their own set of challenges and costs.\n\n### **data pipelines (etl)**\n\nTraditionally, an analytics database is isolated, and in most cases, engineers must set up data pipelines for data movement and transformation between Postgres, S3, and the analytics db. Pipelines aren’t cheap. Also, there’s pipeline latency bottlenecking how stale the analytics are. And when pipelines break — because they do — you’re stuck with downtime and wrong results.\n\nHydra side-steps the latency and costs of data pipelines entirely with full support for inserts and updates on columnar files in analytics tables.\n\n### **overweight design**\n\nMany use cases don’t justify a heavy setup. From our time working at Heroku, we saw many transactional apps that only need a couple high level aggregates and a few complex analytical queries to return quickly. Hardly OLAP (online analytical processing) and not really HTAP (hybrid transactional and analytical processing) - just apps in need of a speed boost.\n\nThe most heavyweight option, data warehouses like BigQuery, are good at “big queries”, but not great at smaller, rapid analytics queries that’re more common with applications, rather than monthly reporting.\n\nThese traditional approaches are too heavy, can be brittle, and introduce extra costs and latency your startup doesn’t need.\n\n# **do we have a hosted cloud offering?**\n\nYes, and [it’s awesome](https://start.hydra.so/get-started).\n\n# [**Try now!**](https://start.hydra.so/get-started)\n\n## **useful links**\n\n[**website**](https://www.hydra.so/), [**docs**](https://docs.hydra.so/overview), [**local dev guide**](https://docs.hydra.so/guides/local_development), [**analytics guide**](https://docs.hydra.so/guides/analytics), [**architecture**](https://docs.hydra.so/intro/architecture), [**changelog**](https://docs.hydra.so/changelog/changelog)\n\nIf you’ve made it this far here’s a pic of me (joe) and my cofounder (jd) in hood river, oregon. Building Hydra has been a wild ride, but we found a way to have fun.\n\n![uploaded image](/media/?type=post&id=88443&key=user_uploads/54309/69da46c2-bfc2-48c6-8ed3-2364e71c34fd)\n\n",
        "url": "https://www.ycombinator.com/launches/N0V-hydra-serverless-realtime-analytics-on-postgres",
        "votes": 8,
        "created_at": "2025-03-11T12:27:09.916Z"
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    "id": 25777,
    "name": "BotCity",
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7c9d51d01f280768899d76eff8f510583a2e1614.png",
    "website": "https://botcity.dev",
    "all_locations": "Campinas, SP, Brazil; Remote",
    "long_description": "BotCity is a centralized platform that unifies Python scripts generated by AI or humans under a single governance framework, enabling organizations to scale with orchestration, observability, security and governance.",
    "one_liner": "Observability and Governance for AI-Generated Python scripts.",
    "team_size": 35,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1644846609,
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    "year_founded": 2020,
    "city": "Campinas",
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        "full_name": "Lorhan Caproni",
        "title": "Founder",
        "founder_bio": "Co-founder and CEO of @BotCity. BotCity is a centralized platform that unifies RPA and AI under a single governance framework, enabling organizations to rapidly build, orchestrate, and scal\n\nI have a background in Molecular Biology and Administration, passionate about sales, business development, learning, scientific method, tech, astronomy, sci-fi, and entrepreneurship. BotCity is my 2nd startup, after Phomenta, a successful social business, a social impact edtech that operates in 11 countries.",
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        "full_name": "Gabriel Archanjo",
        "title": "Founder",
        "founder_bio": "Co-founder an CTO at @BotCity, a computer vision powered automation tool for developers.\n\nI've spent the last 15 years in the software industry as software developer, tech lead and CTO. My first position was developer in game studio working with Nintendo, Sega and PC platforms. After pursuing a Master’s Degree in Artificial Intelligence, I've worked for a few companies that were addressing real-world problems with AI-based solutions. ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/gabrielarchanjo/",
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        "title": "BotCity Secures $12 Million Series A Funding to Address \"Shadow Automation\"",
        "url": "https://finance.yahoo.com/news/botcity-secures-12-million-series-190000792.html",
        "date": "Sep 30, 2025"
      },
      {
        "title": "BotCity extends its $2.5M seed funding round to build RPA solution for devs | VentureBeat",
        "url": "https://venturebeat.com/2022/02/11/botcity-extends-its-2-5m-seed-funding-round-to-build-rpa-solution-for-devs/",
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      {
        "title": "Astella Investimentos and SoftBank Lead ~USD3m Seed Round for  BotCity",
        "url": "https://www.lavca.org/2021/12/20/astella-investimentos-and-softbank-lead-usd3m-seed-round-for-brazilian-automation-platform-botcity-em-portugues/",
        "date": "Feb 11, 2022"
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        "title": "Brazilian computer-vision automation BotCity raises $2,5 million seed round from Softbank - London Tech News | londonlovestech.com",
        "url": "https://londonlovestech.com/brazilian-computer-vision-automation-botcity-raises-25-million-seed-round-from-softbank/",
        "date": "Dec 16, 2021"
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    "name": "Nullstone",
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    "long_description": "Nullstone is a suite of tools delivered as a single product that enables developer self-service while accommodating flexibility and control that platform engineers need to maintain secure, compliant, performant, and reliable infrastructure.\r\n\r\n\r\nNullstone provides a simple developer experience that guides developers through the architecture and release of cloud apps. By default, infrastructure launched through Nullstone is compliance-certified and vetted for security best practices. The software delivery process can be customized per app through external CI/CD tools or IaC tools like Terraform to meet the specific needs of customers or to optimize developer workflow.\r\n\r\n\r\nNullstone comes with many quality-of-life features that are hard to build with an in-house DevOps/Platform team: Auto-Build/Deploy, Preview Environments, GitOps, and Automatic Secrets Management.\r\n",
    "one_liner": "An easier way to deploy and manage cloud apps",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1642179452,
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    "city": "Atlanta",
    "country": "US",
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        "full_name": "Brad Sickles",
        "title": "Founder",
        "founder_bio": "Brad is currently Founder and CEO of Nullstone. \nBrad spent the first part of his career as a software engineer at various-stage startups and as an independent consultant.\nIn 2013, he joined McKinsey where he launched startups inside large enterprises. He also built and led an internal developer platform serving 1000 engineers hosting ~300 services.\nIn 2018, he joined Bishop Fox where he incubated and founded an offensive security platform.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/bradsickles/",
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        "full_name": "Scott Sickles",
        "title": "Founder",
        "founder_bio": "Scott is the co-founder and CTO of Nullstone. Early in his career as a developer, he fell in love with the ability of software to empower people. As CTO of IdentityStream, he helped banks across Asia and Africa serve people without forms of ID through the use of biometrics. As CTO of Listen360, he led successful cloud migrations, digital transformations, and help lead the company to 5x growth and a successful exit. He earned a degree in Computer Science from Georgia Tech.",
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        "linkedin_url": "https://www.linkedin.com/in/scottsickles",
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        "id": 73668,
        "title": "Nullstone: ☁️ Better dev experience for cloud providers",
        "tagline": "We improve developer productivity with a better dev experience, modern automation workflows, and composable tooling.",
        "body": "### tl;dr\n\nNullstone improves developer team productivity with quality-of-life features that are difficult and costly to build with an in-house DevOps/Platform team: Auto-Build/Deploy, Preview Environments, GitOps, and Automatic Secrets Management.\n\n### 🌩️ Problem\n\nLaunching and managing cloud apps is tedious and distracting for product teams. On average, building, maintaining, and orchestrating cloud infrastructure accounts for \\~25% of a software team’s budget. The current solutions are inflexible, require significant expertise, and/or are costly:\n\n* Platform-as-a-service (PaaS) are black boxes and don’t provide flexibility and control to achieve security, compliance, and reliability.\n* Hiring DevOps Engineers to build custom infrastructure and automation is costly and distracting from a team’s primary purpose.\n* Hiring Platform Engineers to build a custom, internal developer platform requires an enormous upfront build with a long-term maintenance cost of the platform that rarely provides an intuitive experience to developers.\n\nThe most precious resource for a software product are developers focused on building a fantastic product — a great developer experience is the [primary driver for productivity](https://queue.acm.org/detail.cfm?id=3595878).\n\n### ☀️ Solution\n\nNullstone is a suite of tools delivered as a single product that enables developer self-service while accommodating the flexibility and control that platform engineers need to maintain secure, compliant, performant, and reliable infrastructure.\n\n![uploaded image](/media/?type=post&id=73668&key=user_uploads/850501/1fe8a18b-3ecb-48ab-8023-983d9f2f6826)\n\nFor developers, Nullstone provides an easy-to-use developer experience to deploy and observe apps on major cloud providers using containers, serverless, static sites, or servers.\n\n![uploaded image](/media/?type=post&id=73668&key=user_uploads/850501/99e0b94f-0672-4777-aa43-484f94961d06)\n\nFor platform engineers and architects, Nullstone provides a simple mechanism to provide modern delivery workflows and infrastructure building blocks to developers. Using familiar tools like Terraform ensures company policies are followed without needing to build a developer experience.\n\n![uploaded image](https://bookface.ycombinator.com/media/?type=post&id=73668&key=user_uploads/850501/53d30583-a275-4694-bd33-25b505012695)\n\n### ⚙️ How it works\n\n* Developers pick from an extensive, curated catalog of open-source, compliance-certified infrastructure modules or from company-built infrastructure modules.\n* Developers choose to auto-build/deploy or use custom CI.\n* Developers launch preview (ephemeral) environments from a pull request, through the UI, or through the API.\n* Developers can use ClickOps or GitOps to control infrastructure.\n* Developers can observe and monitor applications without accessing a cloud console.\n* Platform Engineers build reusable infrastructure components for developers to self-serve through an easy-to-use UI.\n* Platform teams customize networks, clusters, and datastores while providing the right level of access for developer self-service.\n* Platform teams connect third-party log and metrics providers for developers.\n* Platform Engineers perform automated rollouts of infra upgrades and bug fixes.\n\nThe flexibility allows Nullstone to support monoliths, monorepos, microservices, and everything in between.\n\n### 🙏 Asks\n\n* [Launch an app](https://app.nullstone.io/) for free!\n* Want to learn more, [check us out](https://www.nullstone.io/) and [book a demo](https://www.nullstone.io/book-demo)!",
        "url": "https://www.ycombinator.com/launches/JAC-nullstone-better-dev-experience-for-cloud-providers",
        "votes": 31,
        "created_at": "2023-08-01T20:05:56.367Z"
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    "name": "Vimmerse",
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    "website": "https://vimmerse.net",
    "all_locations": "San Francisco, CA, USA; San Jose, CA, USA; Remote",
    "long_description": "Designers, branding agencies, and on-line stores can use Vimmerse’s AI creators platform, Apps, and API to animate their images at scale making their business stand out from the crowd.",
    "one_liner": "Bring your photos to life with Vimmerse",
    "team_size": 10,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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    "year_founded": 2021,
    "city": "San Francisco",
    "country": "US",
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        "full_name": "Basel Salahieh",
        "title": "Founder",
        "founder_bio": "Basel Salahieh is a founder and CEO of Vimmerse, Inc. with over 18 years of experience and 20+ patent in immersive media, and a Ph.D. in Electrical and Computer Engineering. Prior to Vimmerse, Basel worked as an immersive media algorithms and standards architect at Intel and served as the lead editor for MPEG Immersive Video Test Model. Through Vimmerse, Basel is helping businesses, marketplaces, and designers to animate their visuals and expand their digital branding capabilities.",
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    "name": "mutable.ai",
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    "long_description": "Mutable.ai is automating corporations starting by automating software and software understanding. Our product auto wiki (https://wiki.mutable.ai/kubernetes/kubernetes, https://twitter.com/mutableai/status/1744426997575553413) turns code into wikipedia style articles with citations to the code is the best way to understand complex technologies",
    "one_liner": "Artificially Intelligent Corporations",
    "team_size": 7,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1645727988,
    "tags": [
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      "AI"
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    "nonprofit": false,
    "batch": "Winter 2022",
    "status": "Acquired",
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    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/mutableai/",
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        "full_name": "Omar Shams",
        "title": "Founder",
        "founder_bio": "Omar is the founder of Mutable.ai. He was a researcher at DeepMind, publishing on Reinforcement Learning & GraphNets in NeurIPS. Omar was also part of a small team that developed a music recommender, which tied with Amazon Music in a live bake-off, and he has three patents in the recommender space. In a previous life, Omar was a theoretical physicist working on black holes and particle physics.",
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      {
        "id": 82174,
        "title": "Mutable.ai: A living expert on your codebase",
        "tagline": "A living expert on your repo with full awareness of your codebase",
        "body": "# Mutable ai is a living expert on your repo with full awareness of your codebase\n\nWe created an AI expert on your codebase with _infinite effective context length_ by creating an always up-to-date wiki on your codebase (language models are really good at using language to navigate codebases it turns out!)\n\nSee the chat in action on [ollama](https://wiki.mutable.ai/ollama/ollama):\n\n![uploaded image](/media/?type=post&id=82174&key=user_uploads/904867/ac16cfe8-73d9-45ea-93b4-bc0666ee73a7)\n\nThe wikis have citations to your code, code diagrams, ability to revise it with AI, and it’s always up to date. Here is an [example](https://wiki.mutable.ai/ollama/ollama):\n\n![uploaded image](/media/?type=post&id=82174&key=user_uploads/904867/2dab2550-772e-4987-bd8d-95aa105bfb1d)\n\nPR bot that summarizes changes to the wiki with a nice diff view:\n\n![uploaded image](/media/?type=post&id=82174&key=user_uploads/904867/73d44099-d131-494a-9420-3a1a9ebf213b)\n\n![uploaded image](/media/?type=post&id=82174&key=user_uploads/904867/6de4274c-3880-457d-83a2-431cfc99ffca)\n\n",
        "url": "https://www.ycombinator.com/launches/LNO-mutable-ai-a-living-expert-on-your-codebase",
        "votes": 6,
        "created_at": "2024-07-16T16:57:06.712Z"
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      {
        "id": 80195,
        "title": "Auto Wiki v2 by Mutable.ai: Convert your codebase into a wiki style article now with diagrams",
        "tagline": "Now featuring code diagrams and the ability to use AI to revise your wiki.",
        "body": "[Mutable.ai](http://Mutable.ai) is excited to introduce Auto Wiki v2! Our technology transforms your codebase into Wikipedia-style articles. Now featuring code diagrams and the ability to use AI to revise your wiki, it’s our favorite way to learn about new codebases and maintain up-to-date documentation.\\\n\\\nCheck out our release video for more information: <https://www.youtube.com/watch?v=HiP563Q9Sws>\n\nGetting started is easy: simply visit [wiki.mutable.ai](http://wiki.mutable.ai/), pick the repo you are interested in, and let our AI take care of the rest. Our new basic tier costs just $2/repo/month, and for a limited time, you can use the coupon code XDOTCOM to generate them for $1/mo.\n\nWe made a number of improvements with your feedback in mind, including:\n\n* Code diagrams generated in Mermaid\n* Filter and search for your wiki\n* AI revision with instruction\n* Manual edits to revise wikis\n* Better underlying model\n* Private repo support that follows the permissions of the repo\n* Wiki is updated automatically every month and with each commit with our upcoming PR bot.\n\nPlease note you will only be able to edit a wiki if you’re a contributor or sponsor of a repo.\n\nThank you!\n\nPS Here are some more example v2 wikis:\n\n<https://wiki.mutable.ai/princeton-nlp/SWE-agent>\n\n<https://wiki.mutable.ai/bitcoin/bitcoin>\n\n<https://wiki.mutable.ai/karpathy/llm.c>\n\n<https://wiki.mutable.ai/openai/transformer-debugger>\n\n<https://wiki.mutable.ai/tensorflow/tensorflow>\n\n<https://wiki.mutable.ai/Significant-Gravitas/AutoGPT>",
        "url": "https://www.ycombinator.com/launches/KrT-auto-wiki-v2-by-mutable-ai-convert-your-codebase-into-a-wiki-style-article-now-with-diagrams",
        "votes": 7,
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        "id": 77591,
        "title": "Auto Wiki: Turn your repo into a wiki with AI",
        "tagline": "Auto Wiki generates a wiki style website based on your repo",
        "body": "Mutable.ai is proud to introduce Auto Wiki, which lets you generate a Wiki-style website to document your codebase. Citations link to code, with clickable references to each line of code being discussed. Here are some examples of popular projects: \\\n\\\nReact: <https://wiki.mutable.ai/facebook/react>\\\nOllama: <https://wiki.mutable.ai/jmorganca/ollama>\\\nKubernetes: <https://wiki.mutable.ai/kubernetes/kubernetes>\\\nD3: <https://wiki.mutable.ai/d3/d3>\\\nBitcoin: <https://wiki.mutable.ai/bitcoin/bitcoin>\\\nTerraform: <https://wiki.mutable.ai/bitcoin/bitcoin>\n\n![uploaded image](/media/?type=post&id=77591&key=user_uploads/904867/af4c7637-aa61-4979-97ee-35370632ed8a)\n\nAuto Wiki makes it easy to see at a high level what a codebase is doing and how the work is divided. In some cases, we’ve identified entire obsolete sections of codebases by seeing a section for code that was no longer important. Auto Wiki relies on our citations system which cuts back on hallucinations. The citations link to a precise reference or definition, meaning the wiki generation is grounded on the basis of the code being cited rather than free-form generation. \n\n[ ](https://www.youtube.com/watch?v=HiP563Q9Sws])\n\\\nWe're running Auto Wiki on the most popular 1,000 repos on GitHub. If you want us to generate a wiki of a public repo for you, send us a note at [info@mutable.ai.](mailto:info@mutable.ai) The wikis take time to generate as we are still ramping up our capacity, but we’ll reply that we’ve launched the process and then come back with a link to your wiki when it’s ready. \\\n\\\nFor private repos, you can use [wiki.mutable.ai](http://wiki.mutable.ai) to generate them simply by signing in, authorizing the repo, and paying for generation. We also offer private deployments with our model for enterprise customers; ping us at [info@mutable.ai](mailto:info@mutable.ai). \\\n\\\nAnyone who already has access to a repo through GitHub will be able to view the wiki, only the person generating the wikis needs to pay to create them. Pricing starts at $4 and ramps up by $2 increments depending on how large your repo is. In an upcoming version of Auto Wiki, we’ll include other sources of information relevant to your code and generate architectural diagrams. Please check out Auto Wiki and let us know your thoughts! Thank you!",
        "url": "https://www.ycombinator.com/launches/KBT-auto-wiki-turn-your-repo-into-a-wiki-with-ai",
        "votes": 6,
        "created_at": "2024-01-18T18:58:45.562Z"
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      {
        "id": 73630,
        "title": "Mutable.ai: The AI-powered platform for software teams",
        "tagline": "Build and understand software using just English",
        "body": "Introducing [app.mutable.ai](http://app.mutable.ai) for codebases. We help you develop software by using (1) AI codegen to create features, (2) AI enhanced explanation and search, (3) Suggest improvements to your code, (4) Seamlessly switch from your laptop to the cloud and back with our cli tool.\n\nComing soon: auto standup, auto bug identification, auto wiki creation, and a revamped VS Code extension + a new Jetbrains extension.\n\n[ ](https://youtu.be/SdAteyB4-Uw)",
        "url": "https://www.ycombinator.com/launches/J9a-mutable-ai-the-ai-powered-platform-for-software-teams",
        "votes": 10,
        "created_at": "2023-08-01T01:31:03.790Z"
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        "linkedin_url": "https://www.linkedin.com/in/robakidzeana/",
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        "title": "Start-up Theneo vence PITCH da Web Summit 2022 - Forbes Portugal",
        "url": "https://www.forbespt.com/start-up-theneo-vence-pitch-da-web-summit-2022/",
        "date": "Nov 04, 2022"
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      {
        "title": "Web Summit | Theneo wins PITCH contest at Web Summit 2022",
        "url": "https://websummit.com/blog/theneo-pitch-2022-siemens",
        "date": "Nov 04, 2022"
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      {
        "title": "Theneo wants to bring Stripe-like API documentation to all developers • TechCrunch",
        "url": "https://techcrunch.com/2022/10/19/theneo-wants-to-bring-stripe-like-api-documentation-to-all-developers/",
        "date": "Oct 19, 2022"
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      {
        "title": "Startup World Cup Winner THENEO has a Chance to Earn $1 Million in Silicon Valley - Startup - CBW",
        "url": "https://cbw.ge/startup/startup-world-cup-winner-theneo-has-a-chance-to-earn-1-million-in-silicon-valley?fbclid=IwAR0ZflaYZimPN5v9sQcQqF0Xz_t5meVFe4J2a49-SWUtLRyMsPLQiWvKDnk&utm_medium=social&utm_source=linkedin.company&utm_campaign=simplified&utm_content=simplified50176",
        "date": "Sep 26, 2022"
      },
      {
        "title": "Our favorite startups from YC’s Winter 2022 Demo Day, part 2 – TechCrunch",
        "url": "https://techcrunch.com/2022/03/30/our-favorite-startups-from-ycs-winter-2022-demo-day-part-2/?guccounter=1",
        "date": "Mar 30, 2022"
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        "title": "Theneo - Generate Stripe-like API Docs & Developer Portals",
        "tagline": "Theneo is the quickest, simplest way to generate high-quality, interactive API docs. Just import your API collection and we'll take care of the rest.",
        "body": "Hey there,\n\nAna from Theneo. Theneo is a tool for generating Stripe-like API Docs. Using AI, we are the first company to automate the full life cycle of documentation, from generating content to publishing. Theneo was built with the belief that generating high-quality, interactive documentation should not be tedious and we provide the tool to do just that. Theneo is used in production by more than 8000 companies\n\nUsing Theneo you can:\n\n* Build interactive API docs\n* Taylor your documentation\n* Update docs automatically (via IDE extensions and github integration)\n* Built for everyone\n* Bring all of your docs together with the Developer Portal\n* Let your users test APIs using the API Explorer\n\nSome of the APIs and Developer Portals generate in Theneo\n\n* Developer Portal for Uome , perfect example how your API catalague can look like in Theneo <https://developers.myuome.com/> \n* <https://developers.paymob.com/> Paymobs interactive docs and developer portals, all built in Theneo \n\nFor Startup Community we are offering 6 months free access to our business package. Email us at [hello@theneo.io](mailto:hello@theneo.io), email subject YC Startup Community",
        "url": "https://www.ycombinator.com/launches/Ghp-theneo-generate-stripe-like-api-docs-developer-portals",
        "votes": 167,
        "created_at": "2022-06-30T09:31:20.121Z"
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        "full_name": "Chafik Belhaoues",
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        "full_name": "Andrew Israel",
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        "role_type": null,
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      },
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        "title": "Fullstack Engineer",
        "url": "https://www.ycombinator.com/companies/propelauth/jobs/gHlDUgm-fullstack-engineer",
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        "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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        "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",
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        "created_at": "2024-01-11T18:56:39.083Z"
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        "title": "Ploomber: Heroku for AI",
        "tagline": "A platform to deploy AI and data applications quickly",
        "body": "**tl;dr; **[**Ploomber**](https://www.platform.ploomber.io/register)** is a cloud platform that quickly deploys container-based AI and data applications (Streamlit, Shiny, Panel, Flask, FastAPI, etc.)**\\\n—\n\nHey all! We're [Eduardo](https://www.linkedin.com/in/edublancas) and [Ido](https://www.linkedin.com/in/ido-michael) from Ploomber, and we're excited to launch our cloud platform!\n\n**Problem**\n\nWith the rise of AI and data, many companies are deploying applications whose requirements differ from typical web applications. The most common differences are larger computational resources and libraries that many PaaS platforms do not allow to install (case in point: one of our customers migrated to our platform after several failed attempts to install a C++ library required for their Python app to run). These restrictions hinder the ability of many companies to ship complex AI and data applications.\n\n**Our Solution**\n\nOur container-based platform provides greater flexibility when deploying applications: you can quickly provision more resources and install anything your app requires to run.\n\nWe provide official support for frameworks like Streamlit, Shiny, Panel, Flask, and FastAPI, but you can use any framework you want.\n\nWe also provide a feature that stops your application automatically if it doesn't receive traffic and starts it again on an incoming request; this offers significant savings for many of our customers who deploy low-traffic applications.\n\n**How it works**\n\n![uploaded image](/media/?type=post&id=78826&key=user_uploads/564961/8070baa6-6dc5-468e-8041-cb35cf860f53)\n\nYou can deploy applications with the UI or via the command-line interface (you can also use the CLI to deploy on each commit to your git repository).\n\n**Live examples**\n\n![uploaded image](/media/?type=post&id=78826&key=user_uploads/564961/50219f4a-395d-4d0d-98cb-4e123ad50efa)\n\n[Arxiv Chat:](https://summer-wind-5194.ploomberapp.io/) a chatbot that allows you to search, ask questions, and download papers from Arxiv. \n\n[Analytical dashboard](https://broad-fire-8217.ploomberapp.io) built with Panel.\n\n[Flask app](https://wild-bonus-9050.ploomberapp.io/) with user authentication and API key management.\n\n**Try it out!**\n\n[Create an account](https://www.platform.ploomber.io/register) and check our [documentation](https://docs.cloud.ploomber.io/en/latest/intro.html) to get started!\n\n**We can help you migrate!**\n\nIf you already deployed an application, we can help you migrate at no cost! Please email us at [contact@ploomber.io](mailto:contact@ploomber.io)! We also have discounts for the YC community, so contact us!",
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    "long_description": "Poko enables seamless transfers from local payment rails to web3 infrastructure enabling web3 wallets, marketplaces, games and DApps to acquire more users. With Poko’s SDK, web3 builders can easily enable fiat-to-crypto onramping with 100+ common local payment methods or easily pay for NFTs with local payment methods. Poko's fiat-to-cryptoonramp aggregator reduces onramping costs by up to 70% and increases transaction success rates by up to 5x through a smart routing logic and a single integration to multiple onramps. It's Direct Checkout solution enables one step purchasing from fiat payment rails from any smart contract for 79% higher user conversion. The co-founders’ experience includes being chief strategy officer of a $2.4B coincap protocol, leading technical implementation of Singapore’s central bank’s experiment in cross-border payments on blockchain rails, policy experience as payments task force member at the World Economic Forum, ex-Ethereum Foundation Fellow, and CTO of a 2M+ user play to earn game.",
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        "answer": "Geoffrey See was CSO and founding team member of a $2.4B coin-cap protocol in 2018-2019. He led technical implementation for Singapore’s central bank’s experiment with cross-border payment settlement on blockchain rails and was a taskforce member on Cross-Border Digital Payments and the Digital Currency Governance Consortium at the World Economic Forum. Van Tran headed growth and strategy for Netflix in Southeast Asia, Australia, New Zealand, Hong Kong and Taiwan with $1B+ in annual revenue. Daniel Le was a banking and payments engineer at a YC unicorn before becoming CTO of a Play to Earn game, scaling it to 2M gamers and a 100+ team within 1 year. They met in Vietnam through their common interest in cross-border payment problem in the gaming and entertainment sector and have worked together for over 2 years."
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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 went through a pivot post-YC demo day from building DAO tooling to focusing on frictionless payments for web3. We saw that this was a pain point as more web3 products and services tried to reach a wider audience. We also had to navigate significant industry turmoil (Terra, FTX, Silvergate, Signature, Celsius…etc.) and were glad that we were able to do so with no direct impact on us or our finances."
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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": "Enabling cross-border payments that is cheap, fast and efficient on blockchain rails is a multi-trillion dollar industry with high take rates. We believe crypto wallets will be the financial infrastructure of the future - especially for a global community."
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        "question": "What is your long-term vision? If you truly succeed, what will be different about the world?",
        "answer": "The internet of money will be the financial infrastructure Gen Z and beyond grow up with. It will be democratic, accessible and deeply integrated into core internet infrastructure."
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        "user_id": 641685,
        "full_name": "Sean Ang",
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        "founder_bio": "Experienced community builder, obsessed over customer service excellence. \n\nBuilt a community for thousands of youth in mental health to communicate under one platform.  Started a podcast on Facebook and Youtube to interview experts on healthcare communications and psychological well-being and brought together healthcare professionals to propose changes to the practice for healthcare professionals in Singapore.     \n\nPassionate about human connection, customer service and an avid squash player. ",
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        "full_name": "Van Tran",
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        "founder_bio": "Van Tran has spent the last 3 years leading marketing strategy and growth for Netflix Southeast Asia and Australia to establish Netflix presence and build up fan communities in the region. Previously, she worked on building student communities for the first liberal art college in Singapore Yale-NUS. She also has experience working in management consulting at Bain & Co. and product manager at Amazon.",
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        "title": "Poko - Onramp aggregator and direct checkout for web3 wallets & marketplaces",
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        "body": "Hi all! Geoffrey and Van from [**Poko**](https://Pokoapp.xyz) here! \\\n\\\nI (Geoffrey) was at Devcon in Bogota trying to top up my wallet. Used Moonpay - transaction failed. Used Transak - transaction failed. Used Coinbase Pay - transaction failed. Fiat to Crypto onramps [fail anywhere from 30% to 90% of the time around the world](https://www.pokoapp.xyz/post/success-rates-fiat-onramps). We solve this problem through our Onramp Aggregator and Direct Checkout.\n\n**TLDR**\n\nWe provide wallets and marketplaces infra providers with an [Onramp Aggregator](https://www.pokoapp.xyz/onramp-aggregator) - a single integration for all localized onramps enabling them to onramp with **local payments,** at up to **6x transaction success rates** and [**70% lower costs** than Moonpay/Transak](https://www.pokoapp.xyz/post/problems-with-onramps-fees). We also provide a [Direct Checkout](https://www.pokoapp.xyz/direct-checkout) on local payment rails for users to pay seamlessly into a smart contract (e.g. for NFT purchasing) without the user needing to onramp. This enables far higher user conversion and transaction success rates. Our payment solutions reach 16M+ active wallets.\n\n**Who is it for**\n\nOur users are wallets, marketplaces, wallet- and marketplace-infra providers, and games/DApps seeking a better payments experience and monetization from their end users. For infrastructure partners, we provide features that serve them especially well (e.g. dashboards and data/flexibility to meet multiple use cases) and a revenue share for them to scale with transaction volume.\n\n# \n\n# 💵 **How does it work?**\n\n**Onramp Aggregator**\\\nWe route users to onramps with the highest success rates and lowest transaction costs for a particular currency, payment method, and token for Everytime Lowest Prices. We bring onboard onramps focused on a single country as they provide the highest success rates. This is because localized onramps provide rates, payment methods, and KYC processes that work best for their market. Onramps compete to provide the best rate and highest transaction success. \\\n\\\n_Check out a live demo (and live rates) here:_ \\\n<https://www.pokoapp.xyz/onramp-aggregator>\\\n_Read the product docs:_\\\n<https://pokoapp.gitbook.io/documentation/onramp-aggregator/what-is-onramp-aggregator>\n\n![uploaded image](/media/?type=post&id=71045&key=user_uploads/855612/147e959f-afd1-43fa-9f66-4ff5088da633)\n\n_Live rates with a **1400 basis point difference** between the lowest cost and highest cost onramp (Brazil)!_\n\n**Direct Checkout**\\\nOne-step NFT purchasing using cards and popular payment rails from any wallet or on any marketplace. This enables users to frictionlessly purchase gaming NFTs or other digital goods without onramping (we automate the onramp and swaps and hide this from users). This increases paid user conversion in web3 by 79% as users use the payment rails most available to them and avoid unnecessary friction like KYC or complicated token purchasing and swaps.\\\n\\\n_Check out a demo in staging here:_ <https://stg.marketplace.checkout.pokoapp.xyz/>\\\n_Product documentation:_ \\\n<https://pokoapp.gitbook.io/documentation/direct-checkout/what-is-direct-checkout>\n\n![uploaded image](/media/?type=post&id=71045&key=user_uploads/855612/21f3d0f0-3b86-42a1-9133-13a2e1f90175)\n\n**Why we built** [**Pokoapp.xyz**](http://Pokoapp.xyz)\\\nWe believe in giving web3 wallets, marketplaces, and DApps bank-like superpowers by connecting them with local payment rails so that assets can move between tradfi payment rails to crypto rails seamlessly. We believe we are helping builders build the banks of the future - and better ones!\\\n\\\n**Our Ask**\n\nKnow a wallet, marketplace or DApp needing onramps? **Put us in touch** or better yet, **send them our demo** so that they can see for themselves how much their users can save using our Onramp Aggregator!\\\n\\\n**Contact us**\\\nReach out via TG (<https://t.me/geoffreysee>), email ([geoffrey@pokoapp.xyz](mailto:geoffrey@pokoapp.xyz)) or schedule something here: <https://www.pokoapp.xyz/onramp-aggregator>",
        "url": "https://www.ycombinator.com/launches/ITt-poko-onramp-aggregator-and-direct-checkout-for-web3-wallets-marketplaces",
        "votes": 7,
        "created_at": "2023-04-18T19:24:33.277Z"
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    "name": "Karate Labs",
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    "long_description": "Karate is an open-source unified test automation platform combining API testing, API performance testing, API mocks & UI testing. \r\n1.5 million monthly downloads, used by 500+ companies including 76 of the Fortune 500, are a testimony of Karate removing friction from the developer experience (DX). We did this by making it exceptionally simple to write tests (low code), simulating end-user workflows accurately, re-using API tests as performance tests, parallel execution, and collaboration via Git. \r\nStaying true to Karate’s “LOCAL-FIRST” approach (user data remains within the customer's firewall, ensuring security and addressing any concerns), we launched the official Karate plugins (IntelliJ and VS Code) for frictionless onboarding, simplified installations, configuration, and maintenance. Our plugins include all Karate open-source features, including exploring of APIs, and premium features (testing for Async APIs, API documentation, API data importer and more).",
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        "full_name": "Kapil Bakshi",
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        "full_name": "Peter Thomas",
        "title": "Founder",
        "founder_bio": "Creator of the Karate test-automation framework adopted by enterprises world-wide. Previously at Intuit as Distinguished Engineer, he has had a long career with stints at Yahoo! and other top IT companies. With a track record of creating successful open-source projects, he is recognized as a visionary and expert in the field of test-automation and developer productivity.",
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        "title": "Karate Labs Joins Guidewire PartnerConnect as First Solution Partner for Testing",
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        "date": "Nov 07, 2023"
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        "title": "Launch HN: Karate Labs (YC W22) – Open-Source API and UI Test Automation | Hacker News",
        "url": "https://news.ycombinator.com/item?id=31724838",
        "date": "Dec 15, 2022"
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        "title": "The test automation capability map | EuroSTAR Conference",
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        "title": "Karate Labs, Testing Automation Framework, is Joining the OpenAPI Initiative",
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        "user_id": 920899,
        "full_name": "Cory O'Daniel",
        "title": "Founder",
        "founder_bio": "CEO / Co-founder @ Massdriver. DevTools and platform engineering enthusiast. I've been building teams/startups, developing, and managing cloud operations for over 20 years. Creator of the Bonny, an Elixir-based Kubernetes operator framework. A proponent of Friday deploys.",
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        "linkedin_url": "https://linkedin.com/in/coryodaniel",
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      {
        "user_id": 922334,
        "full_name": "Chris Hill",
        "title": "Founder",
        "founder_bio": "Software developer and operations engineer with extensive experience in Kubernetes and cloud-based technologies (AWS and GCP). Passionate about scalable system design - declarative, repeatable infrastructure, automated testing, monitoring and observability.",
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        "title": "Announcing our $8m Series Seed - Massdriver Blog",
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        "title": "Massdriver wants to abstract away infrastructure to let devs focus on coding – TechCrunch",
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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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        "full_name": "Cody Ebberson",
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        "title": "Software Engineer",
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        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
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        "equity_range": "0.01% - 0.20%",
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        "location": "San Francisco, CA, US",
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        "body": "Reshma, Cody and Rahul 👋 - Medplum in YC announcement is extra special for us because this fall marks **10 years of YC** for our team.  We were the founding team of [MedXT](https://www.ycombinator.com/companies/medxt) (W13) and I (Reshma) spent 2021 as a [Visiting Group Partner](https://www.ycombinator.com/blog/welcome-w21-visiting-group-partners/) for the W21 and S21 batches.\n\n![uploaded image](/media/?type=post&id=65117&key=user_uploads/57511/44a369bc-67bc-49f9-ab2e-8f58c722e03d)\n\nWe are back and building [Medplum](https://www.medplum.com/)! Why?\n\n**Medical apps are notoriously hard to build and maintain**, largely due to all the stakeholders involved and the byzantine incentive system.  **We were inspired** by trailblazing open source YC companies [Gitlab](https://about.gitlab.com/), [PostHog](https://posthog.com/), [Airbyte](https://airbyte.com/) and [many others](https://www.ycombinator.com/companies/?tags=Open%20Source) who solve similar complex problems in other domains. We believe the open source model will be **especially impactful for healthcare**.\n\nOur ask: use us to build your next medical app!\n\n* Read our [docs](https://docs.medplum.com/)\n* Browse the [code](https://github.com/medplum)\n* A [sample app](https://foomedical.com/), with [source code](https://github.com/medplum/foomedical) \\\n  \\\n  \\- Reshma, Cody and Rahul\n\n![uploaded image](/media/?type=post&id=65117&key=user_uploads/57511/8928e216-9e5c-4b7b-9925-305011d6fa16)\n\n",
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        "votes": 54,
        "created_at": "2022-08-03T22:36:27.859Z"
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    "website": "https://www.simplehash.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "SimpleHash allows developers to query all blockchain data from a single platform. We index multiple blockchains, take care of edge cases, and can be integrated in a few lines of code. We make the lives of developers working with token data easier by abstracting away all the complexity.\r\n\r\nWe serve some of the leading names in crypto, including Coinbase, Phantom and Uniswap. We're growing quickly, are well-funded, and have an ambitious vision to organize the world of digital assets.\r\n\r\nJoin us if you're excited by a high impact role on a lean, fast paced team at the forefront of the revolution in digital assets.",
    "one_liner": "Multi-chain token data platform",
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        "full_name": "Stepan Parunashvili",
        "title": "Founder",
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        "title": "The Instant team joins OpenAI",
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        "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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        "body": "**TL;DR –** [**Sematic**](https://sematic.dev) **is an** [**open-source**](https://github.com/sematic-ai/sematic) **framework to build and run arbitrary end-to-end ML/DS pipelines developed by two ex-Cruisers.**\n\nWhen COVID hit and restaurant parklets popped up around San Francisco, the Cruise robotaxis needed to update their ML models in a matter of days.\n\nThis fast turnaround in data processing > model training > evaluation > simulation > metrics generation > deployment was enabled by talented ML Engineers using **state-of-the-art pipelining tools**.\n\n## Your problem\n\nIf you are an **ML/DS developer** 🧑‍💻, you likely spend a lot of time battling obscure infrastructure instead of leveraging your core competency: extracting insights and predictions from data.\n\nIf you are a **business leader** 🧑‍💼, you likely want more models to grow and optimize your business; and retrain them frequently to adapt to ever-changing world conditions (hello COVID!).\n\nExisting solutions (e.g. Kubeflow, Argo, Airflow, Prefect) are still too low-level and not usable by ML/DS developers.\n\nTools such as Ruby on Rails and Heroku enabled generations of web developers to build prototypes into unicorns. **Where is that experience for ML/DS development?**\n\n## Our solution\n\n[Sematic Beta Launch Demo](https://www.youtube.com/watch?v=G0Hj0T-bbiY)\n\n[Sematic](https://sematic.dev/) is **a lightweight** [**open-source**](https://github.com/sematic-ai/sematic) **ML/DS pipeline development and execution framework based on learnings from working at Cruise**.\n\nWith easy-as-pie onboarding, simply **use native Python** to develop and run arbitrary end-to-end pipelines that track and version all your assets and artifacts (models, datasets, plots, metrics, etc.), and visualize them in a slick UI.\n\nRun locally or **leverage your cloud resources** (GPUs!!) seamlessly without infrastructure work.\n\n**Collaborate with your team** in Sematic to keep the conversation close to the data context.\n\n**Sematic aims to facilitate the journey from Notebook prototypes to automated production-grade pipelines.**\n\n## Our ask\n\n⭐ [Star our Github repo](https://github.com/sematic-ai/sematic)\n\nTry us out:\n\n```\n$ pip install sematic\n$ sematic start\n```\n\nJoin our [Discord](https://discord.gg/4KZJ6kYVax) **and give us your feedback to make the product more useful to you and your company**.\n\n## Early Bird offer\n\nWe offer a white-glove onboarding service and dedicated support to build out your end-to-end pipelines.\n\n[Try us out](https://sematic.dev/), reach out on [Discord](https://discord.gg/4KZJ6kYVax), or email us at [emmanuel@sematic.dev](mailto:emmanuel@sematic.dev).",
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        "body": "### TLDR\n\nWe’re excited to announce the release of The SuperStack alongside our new Chat endpoint. Now, you can easily deploy conversational LLM applications with knowledge retrieval built-in. Our SuperStack suite of technologies directly targets common RAG failure modes, like hallucinations caused by out-of-context search results. Dive in and test it using our [Playground](https://superpowered.ai/), [Python SDK](https://github.com/SuperpoweredAI/superpowered-python-sdk), or [clone these examples](https://github.com/SuperpoweredAI/superpowered-examples).\n\n### Problem 🤔\n\nMany uses for LLMs, including most customer support and employee productivity applications, require effectively connecting LLMs to external knowledge sources. Doing this well is very hard. Current retrieval augmented generation (RAG) methods just take existing information retrieval methods and stuff the results into an LLM prompt. This works for simple demos, but usually isn’t reliable enough for real-world production applications.\n\n### Solution 🧠\n\nSuperpowered AI offers a simple API that lets you connect external data sources (like product documentation, for example) to LLMs. We leverage proprietary RAG technology we’ve developed (we call it the [SuperStack](https://superpowered.ai/blog/the-superstack)) to dramatically improve performance and reliability for a wide variety of use cases.\n\n![uploaded image](/media/?type=post&id=76118&key=user_uploads/733585/063e897c-eaa8-4a3a-874c-f0bad5249909)\n\nOur solution is end-to-end, so you don’t have to worry about stringing together different APIs for different parts of the retrieval and generation pipeline. Here are some key features:\n\n* Support for uploading various types of text files, PDFs, website content, and audio files\n* 94 languages supported\n* Use our knowledge retrieval pipeline on its own with our Query endpoint, or take advantage of our Chat endpoint for a fully end-to-end solution for building conversational applications connected to external knowledge sources.\n* Usage-based pricing, so you only pay for what you use, and $50 in free credits to all new users!\n\n### The SuperStack 🦸\n\nThe SuperStack has three components that directly tackle the problems with standard RAG pipelines:\n\n[**AutoQuery**](https://superpowered.ai/blog/introducing-auto-query) → Convert user inputs into well-formed search queries for better retrieval results.\n\n[**Relevant Segment Extraction (RSE)**](https://superpowered.ai/blog/introducing-relevant-segment-extraction) → Dynamically group clusters of relevant results into longer sections of contiguous text to provide better context to the LLM. This is especially useful for more complex questions, where the answer isn’t contained in a single sentence or paragraph.\n\n[**AutoContext**](https://superpowered.ai/blog/introducing-auto-context) → Automatically inject descriptive context into text chunks and embeddings, to capture the full context of each chunk of text, reducing the likelihood of poor search results and hallucinations.\n\n### Chat Endpoint 💬\n\nGiven that LLM applications often involve conversational interactions, we recently launched our Chat endpoint to make it easy to configure and deploy chat applications that utilize our knowledge retrieval pipeline. We currently support GPT-3.5-Turbo and GPT-4, with more models coming soon.\n\n<https://youtu.be/3bnS3ppoRtM?feature=shared>\n\n### Custom Solutions 🌐\n\nFor companies that don’t have the resources or expertise to build their own LLM-based solutions, we’re here to help. Whether you're looking to enhance internal productivity or launch innovative new products with LLMs, we will work with you to bring your vision to life. Our team is dedicated to helping businesses of all sizes leverage the potential of AI to drive efficiency and customer love.\n\n### Ask 🙏\n\n* Test it out and share your feedback. If it isn’t working well for your use case, please let us know! We love diving in and solving difficult problems for our customers.\n* If you know developers/founders who are looking to build an LLM-based app, please send intros. We love learning about different use cases and the challenges developers are facing.\n* [Retweet](https://twitter.com/superpowered_ai/status/1722691291891298586)",
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        "created_at": "2023-11-09T19:01:41.875Z"
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        "title": "Superpowered AI - Knowledge Base as a Service for LLM applications",
        "tagline": "Superpowered AI is an end-to-end knowledge retrieval solution that makes it easy to add external knowledge and long-term memory to your LLM application. ",
        "body": "Hey everyone! We are Zach McCormick, Dillon Martin, Justin Clark, and Nick McCormick from [Superpowered AI](https://superpowered.ai/).\n\n### **TLDR**\n\nSuperpowered AI is an end-to-end knowledge retrieval solution designed specifically for LLM applications (i.e. retrieval-augmented generation). We turn complex infrastructure into a few simple API calls, making it easy to retrieve the right information and deliver highly relevant responses to your users. \n\n### 🦉 Who is it for?\n\nWhether you’re using LLMs to improve your customer experience, increase efficiency within your company, or launch an LLM-based application for end-users, **Superpowered AI can provide your app with external knowledge and long-term memory without requiring you to be an AI expert** – all at a low cost. How low? We’ve set our pricing at half the cost of popular alternatives like OpenAI embeddings + Pinecone. Please note, our product is completely free for now, so feel free to query your heart out!\n\n### 💡 How does it work?\n\nSimply upload files (including audio) to a Knowledge Base, and then you can begin querying! We handle the text splitting, embeddings calculation, vector database uploading, etc. for you. **When you query your Superpowered AI Knowledge Bases, we return a list of the most relevant snippets of text from your Knowledge Bases, along with an LLM-generated summary of the results (with citations).** This output can then be added to the prompt of your LLM-based application to dramatically improve your LLM responses. Accepted file types: .pdf, .docx, .txt, .md, .mp3, .m4a, .wav\n\nYou can check this out in our web app right now[!](https://www.youtube.com/watch?v=4R_qoQvuNL8&ab_channel=ArtForYourTVBy%3A88Prints)\n\nOr, you can use our [SDK](https://github.com/SuperpoweredAI/superpowered-python-sdk/blob/main/README.md) 🤓 :\n\n**Step 1**: Install Superpowered SDK\n\n![uploaded image](/media/?type=post&id=71445&key=user_uploads/733585/bc0b3af2-2a71-4e13-abfd-31c6f952e913)\n\n**Step 2**: Create a Knowledge Base\n\n![uploaded image](/media/?type=post&id=71445&key=user_uploads/733585/1d26ab88-cd54-42af-9d61-4064109a9835)\n\n**Step 3**: Query from Knowledge Base\n\n![uploaded image](/media/?type=post&id=71445&key=user_uploads/733585/bdc760ee-8337-4dc2-86e7-2cc496c7a47c)\n\n### 👊 Why we built Superpowered AI\n\nLLMs have emerged as a groundbreaking new technology and we are thrilled to be part of this revolution! But when LLMs are used on their own they have major shortcomings. For real-world use cases, we could see the importance of integrating additional functionality into them to overcome these issues.\n\n1. **Access to external knowledge**. LLMs lack reliable knowledge and have none of your files to work with, but providing them access to knowledge will change your LLM app from a “neat toy” to a powerful tool for real-world use.\n2. **Long-term memory**. Want to build a chatbot that remembers users’ preferences over long periods of time? You’ll need to store conversations and retrieve them later on.\n\n### 🙏 Our Ask\n\n1. Check out [Superpowered AI](https://superpowered.ai/) and join our [Discord](https://discord.gg/s2bE3MfG)!\n2. Talk to us about your use case. If you’re building any kind of LLM application, there’s a very good chance we can help!\n\n### 🚀 Sign up & chat with us:\n\nCreate your account and/or book a demo at [superpowered.ai](http://superpowered.ai), or email me at [dillon@superpowered.ai](mailto:dillon@superpowered.ai)",
        "url": "https://www.ycombinator.com/launches/IaL-superpowered-ai-knowledge-base-as-a-service-for-llm-applications",
        "votes": 14,
        "created_at": "2023-05-09T00:14:35.634Z"
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    "id": 26710,
    "name": "Tailor",
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    "website": "https://www.tailor.tech/",
    "all_locations": "Tokyo, Tokyo, Japan",
    "long_description": "Tailor is the headless ERP that gives fast-growing retail brands a composable, API-first platform to run operations with speed, flexibility, and control.\r\n\r\n🧱 Legacy ERP is too rigid: Systems like NetSuite and SAP take months (or years) to implement and break with every change. Tailor is modular, headless, and easy to adapt.\r\n🧩 Point solutions don’t scale: Tools like inventory or order management software solve one problem, but can’t talk to each other or keep up with growth.\r\n📊 Spreadsheets are everywhere: From demand planning to purchase orders, even $100M+ brands still rely on Excel. Tailor replaces duct-taped workflows with ops modules you can tweak, combine, or scale\r\n⚡️ Complex workflows need custom logic: Whether it's multi-location inventory, DTC + B2B orders, or light manufacturing (like kitting or lot tracking), Tailor supports flexible automations out of the box.\r\n👟 Operators can move faster: Launch backend modules in minutes, not months. Tailor's low-code tools let teams build, automate, and adapt without waiting on engineering or implementation agencies.\r\n\r\n\r\nBuilt for composable retail:\r\n- Headless backend with GraphQL APIs\r\n- 50+ integrations (Shopify, QuickBooks, 3PLs, etc.)\r\n- Custom automations via Pipelines, Functions, and Event Triggers\r\n- State machines for approvals and multi-step workflows\r\n- AI features like OCR and vector search built in\r\n\r\nTailor is already powering operations at fast-growing omnichannel brands and modern manufacturers.\r\nWe’re proud to be the first Japan-based company to join Y Combinator. \r\n\r\nLearn more at [tailor.tech](https://www.tailor.tech)\r\n",
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        "full_name": "Yo Shibata",
        "title": "Founder",
        "founder_bio": "Yo Shibata is co-founder/CEO of Tailor. Previously, Yo founded Smapo (Acquired by Rakuten, RetailTech), Shoppi (Acquired by IMJ, mobile app),  co-founded Funds (FinTech), and Watashikampo (HealthTech). Prior to being a serial entrepreneur, he worked for McKinsey.",
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        "user_id": 1013665,
        "full_name": "Misato Takahashi",
        "title": "Founder",
        "founder_bio": "Co-founder/CTO of Tailor, previously co-founder/CTO of Speee (TSE IPO in 2020), CTO of Spotlight (Acquired by Rakuten), engineer at Rakuten and GREE, and head of R4D, a research institute at Mercari.",
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        "title": "Senior Bilingual Software Engineer (English/Japanese) – West Coast (U.S.)",
        "url": "https://www.ycombinator.com/companies/tailor/jobs/BFTH1SA-senior-bilingual-software-engineer-english-japanese-west-coast-u-s",
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        "title": "Tailor Omakase: Curated, Headless ERP for Fast-Growing Retail Brands",
        "tagline": "🛍️We help fast-growing retail brands replace rigid legacy systems, brittle point solutions and spreadsheet hell",
        "body": "Hello YC from Yo, Misato, and the team at Tailor 👋 We built Tailor as the headless ERP to replace monolithic, legacy tools — and today we’re launching Tailor Omakase. \n\n# **TL;DR**\n\nTailor Omakase is an opinionated, lightning-fast “ERP lite” for retail operators tired of rigid legacy systems, brittle point solutions and spreadsheet hell. \n\nSee how it works in this demo: [**https://youtu.be/tzSZw3MEIk0?feature=shared**](https://youtu.be/tzSZw3MEIk0?feature=shared)\n\n### **❌ The Problem: Retail ops software is stuck in the 90s**\n\nLegacy ERP software (think Netsuite and SAP) is rigid, monolithic, and difficult to implement and customize. This hits **retail operations** especially hard because of the industry’s unique operational makeup of supply chains, online marketplaces, and varying sales channels. \n\n![uploaded image](/media/?type=post&id=91217&key=user_uploads/965414/c28e51ee-4b3f-4f22-80b3-8ac011720893)\n\nRetail operators basically must choose between:\n\n* **Legacy ERP**: Bulky, monolithic systems that take several months or years to implement.\n* **Point solutions that don’t scale**: Tools for inventory, order management, or light manufacturing can solve short-term pain but aren’t API-first and break easily ops need to scale.\n* **Spreadsheets or homegrown**: Even fast-growing brands run core ops on Google Sheets, Airtable, or in-house tools held together by duct tape.\n\n \n\n### **✅ The Solution: Tailor Omakase**\n\n**Tailor Omakase** is a curated, customizable ERP lite built for fast-growing retail brands. It helps operations teams manage purchasing, inventory, and orders across DTC, wholesale, and 3PL — without needing a full-time ERP admin, multi-year contracts, or expensive agency support.\n\n[Product Demo](https://youtu.be/tzSZw3MEIk0)\n\n🟣 **Fast to deploy:** Launch your first module in weeks — not months or years — with preconfigured views for purchasing, inventory, and order workflows \n\n🟣 **API-first & low-code:** Seamlessly integrate with any tool like Shopify or ShipStation, or easily build custom modules.\n\n🟣 **Flexible**: Don’t change your operations to accommodate your software. Whether you're juggling DTC + wholesale orders or creating products in-house, Tailor’s modular and headless architecture adapts to you.\n\n🟣 **Modern UI**: An intuitive frontend that ops teams love to use, plus the flexibility to ship beautiful customer-facing experiences \n\n**HubSpot** filled a gap for SMBs who couldn’t compete with **marketing** from enterprise giants using enterprise tools and budgets. **Tailor Omakase** does the same for **retail and ecommerce brands** when it comes to **operations**.\n\n### **🔧 What’s under the hood**\n\nTailor Omakase runs on the same powerful [platform](https://www.tailor.tech/platform) we use to build internal tools and custom workflows for global enterprises.\n\n* **Instant CRUD APIs**: Generate GraphQL/REST APIs from schema definitions in seconds, complete with validation, filtering, pagination, and relationships.\n* **Composable backend**: Launch headless apps with custom logic, workflows, and event triggers without writing boilerplate code.\n* **50+ pre-built integrations**: Seamlessly connect to Shopify, QuickBooks, 3PLs, and more using Tailor’s API-first architecture.\n* **Automation-ready**: Use Pipelines, Functions, and Event Triggers to automate business logic and cross-system workflows.\n* **State machine support**: Handle complex approval flows and record-level transitions using schema-defined states.\n* **AI-native tools**: Enable vector search, parse documents with OCR, and integrate LLMs from OpenAI, Anthropic, or open-source models like Llama.\n* **_Coming soon —_** **_Fabrix_**: Auto-generate UI components from GraphQL schemas using Tailor’s open-source framework, Fabrix\n\n### **🏅 Our early customers**\n\n* A strategic textile supplier to a $20B+ global clothing retailer\n* A Japan-based hospitality company generating nearly $1B in annual revenue\n* A custom jewelry company growing sales across Shopify, Pinterest, Etsy, TikTok and Amazon\n\n### **🙏 Asks**\n\nKnow a **retail brand** trying to scale operations and growth? Send them our way at [yo@tailor.tech](mailto:yo@tailor.tech) or [patrick@tailor.tech](mailto:patrick@tailor.tech), share this post or book a demo [here](https://www.tailor.tech/demo)!\n\n🎁 We’re offering Tailor Omakase **free for the first year** (core modules) to any company that mentions they heard about us from YC.\n\nTailor Omakase is especially helpful for:\n\n* Companies **managing inventory** and orders in spreadsheets or Airtable\n* **Shopify** stores selling both DTC and wholesale/B2B\n* **Light manufacturing** or **kitting** **operations** (think skincare, make-up, customizable apparel/jewelry, made-to-order products)\n* Teams using **QuickBooks** that need better financial visibility into COGS, PO, or inventory",
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        "votes": 28,
        "created_at": "2025-06-11T14:07:08.560Z"
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    "long_description": "We’re retool for data pipelines. We allow less-technical people to edit data pipelines, with easy to use tools.",
    "one_liner": "Confidently ship analytics code faster with fewer errors",
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    "launched_at": 1657474709,
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        "full_name": "Luke Singham",
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        "founder_bio": "Formerly, Data Platform Engineer and data lead at Monzo, previously at Palantir working across the commercial and government sectors. Over 10 years in the data industry.",
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        "id": 64710,
        "title": "ilumadata - Confidently ship analytics code faster with less errors",
        "tagline": "ilumadata is a single workspace for the modern data stack, enabling data teams to ship 3x more analytics code with fewer errors",
        "body": "Hey YC,\n\nWe’re [Luke Singham](https://www.linkedin.com/in/lukesingham/) and [Matt Sutton](https://www.linkedin.com/in/matthew-sutton-02290984/), co-founders of [ilumadata](http://ilumadata.io).\n\nilumadata helps data teams make changes faster, with confidence. Catch mistakes before shipping. And when debugging, pinpoint the source of failures–fast.\n\n## 🤓 Who is it for?\n\nData teams in large organisations feeling the pain of scaling data teams: struggling with broken pipelines, or taking too long to make changes.\n\n## ❓The ask + can I try it?\n\nIf you fit this 👆category or know someone who does, we’d love to talk to you!\n\nEmail us at [founders@ilumadata.io](mailto:founders@ilumadata.io) or request a demo at [ilumadata.io](http://ilumadata.io)\n\n## 😩 The problem - why we built ilumadata\n\nAt Monzo, I experienced a growing number of pains as we scaled the data team:\n\n* Onboarding new team members took days to weeks\n* Debugging broken pipelines took hours to fix because information was hard to piece together\n* It was hard to know the impacts downstream of changes you made\n* Difficult to know who owns the data, who uses it or if it is even used at all\n\n## ✅ The solution\n\nilumadata is a single workspace for the modern data stack, enabling data teams to ship 3x more analytics code with less errors:\n\n* Onboard new team members in under 60 seconds with a cloud hosted environment.\n* Learn, manage, version control, validate and test your pipeline in one workspace.\n\n  ![uploaded image](https://www.ilumadata.io/img/demos/modify-pipeline.gif)\n\n* Mock out pipeline architecture like you would in a flow chart tool, with code you can use!\n\n  ![uploaded image](/media/?type=post&id=64710&key=user_uploads/89898/8359ad36-b8a2-4985-9f4d-396a3b54062f)\n\n* Debug, optimise and resolve your pipelines issues, fast.\n\n  ![uploaded image](/media/?type=post&id=64710&key=user_uploads/89898/29a51ad9-2ba1-4ee0-b44d-9377c600eeba)\n\n",
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        "full_name": "Spike Lu",
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        "full_name": "Donovan So",
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        "founder_bio": "hi",
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        "title": "🧱 BricksAI Cloud - Simple cost control & monitoring for LLMs",
        "tagline": "We help engineers protect and track their GenAI expenses",
        "body": "**Tl;dr**: Are you finding it difficult to track your LLM costs per project/user? Do you want to set a custom rate/spend-limit for each project/user?\n\n**Create a **[**free account**](https://www.trybricks.ai/sign-in)** and try us out today 😄**\n\nHey everyone, this is [**@Spike Lu**](http://linkedin.com/in/spike-lu-38227b105) and [**@Donovan So**](https://www.linkedin.com/in/donovanso/)! We're excited to share that we've launched [BricksAI Cloud](https://www.trybricks.ai/).\n\n# **The Problem**\n\nA lot of enterprise features are still missing from today's LLM providers, particularly:\n\n1. there isn't a good way of controlling LLM spendings in a granular way (e.g. per user/project/env/feature etc.)\n2. there isn't a good way of monitoring LLMs in a granular way\n\nBut building an LLM wrapper in-house takes away valuable engineering time from shipping features that actually drive business value.\n\n# **The solution**\n\nBricksAI Cloud is an [open-core](https://github.com/bricks-cloud/BricksLLM) SaaS solution that protects and monitors your LLM usage. We're a proxy, so instead of using API keys from your providers, you'd create and use Bricks API keys that come with custom limits (e.g. expiry date, rate-limit, or spend-limit).\n\n[**Demo video**](https://www.loom.com/share/fe0553312e8a4378b3467c12f22e8714?sid=39bbbec1-da60-4054-899a-9ce991b068a9) ⭐\n\n![uploaded image](/media/?type=post&id=76778&key=user_uploads/1109574/8811f428-392d-4533-973d-516979be917d)\n\nWe currently have official support OpenAI and Anthropic, meaning you’ll be able to accurately track your token usage and cost without any configuration. We also support integrations with custom models.\n\nOver the past few months, we have streamlined LLM operations for a wide range of clients, including a late-stage sustainability tech startup, a major leadership training nonprofit, a top European travel agency, and multiple AI startups.\n\nNow, we're opening up our tool to the world with the launch of BricksAI Cloud. We'd love to see how it can transform your GenAI stack.\n\n# **The ask**\n\n1. Star us on [**Github**](https://github.com/bricks-cloud/BricksLLM) ⭐\n2. Create a [free account](https://www.trybricks.ai/sign-in) and try us out today. _Heads up: we require a 15-min account activation call, this helps us get to know your use case better. Don’t worry, it’s super quick and casual!_\n3. Questions? Feedback? Feature requests? [Book a call with us](https://calendly.com/spike-at-bricks/coffee-chat-with-spike) or email [founders@bricks-tech.com](mailto:founders@bricks-tech.com).",
        "url": "https://www.ycombinator.com/launches/JyM-bricksai-cloud-simple-cost-control-monitoring-for-llms",
        "votes": 9,
        "created_at": "2023-12-11T21:19:06.212Z"
      },
      {
        "id": 74841,
        "title": "BricksAI🔐: A simple OpenAI access manager for enterprises",
        "tagline": "BricksAI helps enterprises develop LLM apps more securely",
        "body": "**Tl;dr:** [BricksAI](https://www.trybricks.ai/) helps enterprises develop LLM apps more securely. We do this through an access manager that can set a spend limit, rate limit and expiration date on individual API keys. \n\n**The Problem: OpenAI does not provide enterprise level security features**\n\n> _“You wouldn’t believe how many organizations are building OpenAI wrappers.”_\n>\n> _\\- A machine learning director at a unicorn startup._\n\nOpenAI does not have enterprise-level security features. A lot of companies need to build enhanced security features on top of what OpenAI offers before using them.\n\n> “We simply assign each team an OpenAI key”\n>\n> \\- A senior engineer working at a public fintech company.\n\nDeveloping OpenAI applications often means that developers have to share OpenAI key credentials with each other to speed up development.\n\nThere are several risks and drawbacks associated with this approach:\n\n* **Increased likelihood of security breaches**: more than 50% of breaches happen due to shared secrets\n* **No cost visibility**: no way of knowing what constitutes a $20k OpenAI bill\n* **No access control**: no source of truth for OpenAI access\n* **Degraded production performance**: OpenAI has an organization-level rate limit. One team’s experimentation with OpenAI could impact the performance of production OpenAI applications if not properly rate limited.\n\nAzure OpenAI service helps fill some of the gaps but this product is simply not available to users of GCP and AWS for competitive reasons.\n\n**The Solution: A self-hosted OpenAI access manager**\n\n[BricksAI](https://www.trybricks.ai/) checks all requests between your applications and different LLMs. We ensure every call is authorized, and does not exceed any traffic and cost limits.\n\nYou can create a custom API key with a **rate-limit**, **spend-limit**, and **expiration date** either programmatically or through our UI:\n\n![](https://lh6.googleusercontent.com/2PBxx_RzNu9dsiySB2IXD4ySeziMayS-afN25SnUBofJEuRla9tBclCHbLg1OGdj_87mHcr3NSI4SMgTkEUtSRHIQr0yLgK1Ty0ZZWnvKSAi4tCEcktVTexY0RkVakz6krMl7mU2m2CO0tvGxJ3W_7g)\n\nThen use the API key to access an LLM like you normally would. When a key reaches its limit (e.g. has expired), our gateway blocks off your requests:\n\n![](https://lh3.googleusercontent.com/nJ4yb431KR5fhWm-5SHhrxEddPFtRWb5kUD4z7Gw2i3gnn3IO4_p7a2aeIqPQhLyW2l1XOx_0J-nv_rVmPv8KHR7adRa3uVd6bzgBbYPPmlfCOhjUoIZe9qIOqrEX3Kd4A8kOmcH9zqcC9yonuZich8)\n\nIn addition, our enterprise offering includes \n\n* **SSO**: SSO integration\n* **Dashboard**: Dashboard view of the keys created\n* **Analytics**: Analytics on usage and cost by team and service\n* **Access Control**: Access control over who can view and create keys\n\n![](https://lh6.googleusercontent.com/B1ecI3KdyzeqrdPU6JRoYflPXpt-y3YiRGuf3wE0_n6gJZxKZX6bxnHCFXFvSh4Rf5MsCTXNWpZEEIsXnsSiEyBqCJ9_GIVaRyWb8BoT6xjITG2pN1SMtiuDLJCryMENyfbPY_Y-2vAfW0fgUjMRuZg)\n\n**Who are we?**\n\n![](https://lh3.googleusercontent.com/QVEctbu3DQ5cZPDkK_P_-9KGBcMg64t7qzcFlEpbO_EpUefLvVcu5ApqHH6oZYx0x8hBDxZdX7PdngRjIkCXp_6ALUFsAn9ZCrB636TWAQ2o5pr1J7z-GVEoYgplvK__JBvVpVnXdnv7Fq5KQXqQJdI)\n\n[Spike](https://www.linkedin.com/in/spike-lu-38227b105/) (on the right) was a senior software engineer at Unity for three years. He worked on an internal API gateway used by hundreds of developers.\n\n[Donovan](https://www.linkedin.com/in/donovanso/) (on the left) was a software engineer at Credit Suisse, building internal tools dealing with financial instruments used by institutional investors.\n\nWhile working on our previous [AI powered Figma to code idea](https://www.figma.com/community/plugin/1178847414663679049/Bricks---AI-Powered-Design-to-TailwindCSS-Code), we realized that developing applications using OpenAI credentials is easy to get started but poses huge security risks. After constantly hearing news about [leaked OpenAI keys](https://www.darkreading.com/application-security/cybercrooks-scrape-openai-keys-pirate-gpt-4), we are inspired to create a solution that helps make OpenAI development safer at enterprises.  \\\n\\\n**Interested in learning more?**\n\n* 📅 [Book a call](https://calendly.com/spike-at-bricks/quick-chat?month=2023-09)\n* ✉️ Email us at [spike@bricks-tech.com](mailto:spike@bricks-tech.com)\n* 🤝 Connect with us on [LinkedIn](https://www.linkedin.com/in/spike-lu-38227b105/)",
        "url": "https://www.ycombinator.com/launches/JT7-bricksai-a-simple-openai-access-manager-for-enterprises",
        "votes": 50,
        "created_at": "2023-09-13T21:28:53.172Z"
      }
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    "id": 26781,
    "name": "CodeCrafters",
    "slug": "codecrafters",
    "former_names": [
      "CodeCrafters",
      "Visafrog",
      "visafrog",
      "CodeCrafters",
      "Lobbyside"
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    "website": "https://codecrafters.io",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "Build your own Git, Redis, SQLite — in Go, Rust, Python, etc.",
    "one_liner": "Programming courses for experienced engineers",
    "team_size": 10,
    "industry": "Consumer",
    "subindustry": "Consumer -> Job and Career Services",
    "launched_at": 1656483075,
    "tags": [
      "Developer Tools",
      "Education",
      "eLearning",
      "Careers"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2022",
    "status": "Active",
    "industries": [
      "Consumer",
      "Job and Career Services"
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    "regions": [
      "United States of America",
      "America / Canada",
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      "Fully Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/codecrafters",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2022/codecrafters.json",
    "year_founded": 2022,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/codecraftersio",
    "x_url": "https://twitter.com/codecraftersio",
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    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/2fbe2f8faf8c91d41cd8099b3a53511fa45c4635.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": 6782,
        "full_name": "Sarup Banskota",
        "title": "Founder",
        "founder_bio": "CEO @ CodeCrafters. ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/sarupbanskota/",
        "x_url": "https://twitter.com/sarupbanskota",
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      },
      {
        "user_id": 484990,
        "full_name": "Paul Kuruvilla",
        "title": "Founder",
        "founder_bio": "CTO @ CodeCrafters.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/rohitpaulk/",
        "x_url": "https://twitter.com/rohitpaulk",
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    "jobs": [],
    "news": [
      {
        "title": "TechCrunch | CodeCrafters wants to challenge seasoned developers with hard-to-build projects ",
        "url": "https://techcrunch.com/2024/11/19/codecrafters-wants-to-challenge-seasoned-developers-with-hard-to-build-projects/",
        "date": "Nov 19, 2024"
      }
    ],
    "launches": [
      {
        "id": 64173,
        "title": "🤯 CodeCrafters — Advanced code challenges for senior engineers →",
        "tagline": "We help engineers get really good at their craft. Build your own Redis, Git, Docker, SQLite from scratch. Become a top engineer.",
        "body": "> Hey everybody — it’s Sarup and Paul, the founders of [CodeCrafters.io](http://CodeCrafters.io).\n\n![uploaded image](/media/?type=post&id=64173&key=user_uploads/286989/672fcd25-74e0-49e0-b93f-8111386d6840)\n\n# \n\n# We once built our own Git from scratch\n\nAnd ever since, we’ve been obsessed with how popular devtools work.\n\nWe’d binge on books, blogs, videos to learn the internals of Docker, Redis, SQLite… but it just never felt adequate. Nothing could really provide us with the same level of confidence as building an actual project.\n\n# \n\n# So we created the experience we wanted\n\nWe launched 4 hands-on challenges of the _Build-your-own-X_ format on our site, and had 1000s of engineers go through them. We also began maintaining GitHub’s 15th most ⭐️ repo, [build-your-own-x](https://github.com/codecrafters-io/build-your-own-x).\n\n![uploaded image](https://bookface.ycombinator.com/media/?type=post&id=64173&key=user_uploads/286989/052818e0-2fab-4d57-8ed4-81dc336d4053)\n\n# Turns out, it’s a great way to master languages\n\nSenior engineers don’t come across many resources suitable for their skill level, so especially for them, CodeCrafters was a worthy investment of time. In addition to learning about how various devtools worked, they were:\n\n* Advancing their language skill (e.g idiomatic approaches)\n* Learning to design and refactor large code in a robust manner\n* Bonding with their teammates as they discussed approaches\n\n![uploaded image](https://bookface.ycombinator.com/media/?type=post&id=64173&key=user_uploads/286989/dc589502-0ed5-4f1a-815f-5ce0069fa9de)\n\n# So we re-imagined the learning experience\n\nThe experience is now organised around languages. The challenges now come with recommended approaches from language experts. Once you implement a feature, you can ask — _how would a Pro do it?_\n\n![uploaded image](https://bookface.ycombinator.com/media/?type=post&id=64173&key=user_uploads/286989/4a2972b2-654c-4696-8041-f8e5c489887a)\n\nEngineers at companies like GitHub take advantage of their L&D budget to pay for CodeCrafters. To support teams that care about investing in their growth, we’ve introduced Private Leaderboards, a Slack app, and expensing workflows.\n\n# Asks\n\nWe can’t wait to help teams bond and grow with [CodeCrafters](https://codecrafters.io).\n\n* **Engineer**? Give CodeCrafters a shot, in your [favorite language](https://app.codecrafters.io/tracks)!\n* **Work in Engineering Enablement**? I’d love to learn about the different education initiatives at your company\n* **Well-wisher /** **existing customer**? Please send us a hi! It’s what keeps us going.\n\nI can be reached at [sarup@codecrafters.io](mailto:sarup@codecrafters.io) and over Twitter.\n\n— [@sarupbanskota](https://twitter.com/sarupbanskota)\n\nP.S. Think we’re the only ones crazy to build our own Git for fun?\n\n![uploaded image](/media/?type=post&id=64173&key=user_uploads/286989/1c81f82a-7e46-4115-9d74-8230e6cd6207)\n\nWe asked Pete Koomen, co-founder of Optimizely, about [how he’s learning Rust](https://codecrafters.io/videos/pete).",
        "url": "https://www.ycombinator.com/launches/Gh3-codecrafters-advanced-code-challenges-for-senior-engineers",
        "votes": 152,
        "created_at": "2022-06-29T13:09:34.080Z"
      }
    ]
  },
  {
    "id": 26793,
    "name": "Windmill",
    "slug": "windmill",
    "former_names": [
      "Windmill.dev"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/65ba001ab4d9a51e57b2d599e1b3c910c0a39b01.png",
    "website": "https://windmill.dev",
    "all_locations": "Paris, Île-de-France, France",
    "long_description": "Windmill is an open-source developer platform that turns scripts into workflows, internal tools, and full-stack apps.\r\n\r\nWrite scripts in Python, TypeScript, Go, Bash, Rust, SQL - Windmill auto-generates UIs from their parameters, handles dependencies, credentials, permissions, and scheduling so you focus on business logic, not infra.\r\n                                                                                     \r\nOpen-source alternative to Airflow, Temporal, Retool and n8n. Chain scripts into flows with branching, parallelism, retries. Build dashboards with the app builder. Trigger via cron, webhook, or UI. All-in-one runtime, editor, secret manager, and OAuth platform - enterprise-ready out of the box.\r\n                                                                                                                            \r\nStack: Rust / TypeScript + Svelte / PostgreSQL. Self-hostable, easy to deploy, built for performance and DX.",
    "one_liner": "Open-source platform to turn scripts into internal apps & workflows",
    "team_size": 7,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1651798285,
    "tags": [
      "Developer Tools",
      "SaaS",
      "B2B",
      "Workflow Automation",
      "Open Source"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2022",
    "status": "Active",
    "industries": [
      "B2B",
      "Infrastructure"
    ],
    "regions": [
      "France",
      "Europe",
      "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/windmill",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2022/windmill.json",
    "year_founded": 2022,
    "city": "Paris",
    "country": "FR",
    "linkedin_url": "https://www.linkedin.com/company/windmill-dev",
    "x_url": "https://x.com/WindmillDev",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/windmill-labs/windmill",
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    ],
    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
    },
    "founders": [
      {
        "user_id": 229730,
        "full_name": "Ruben Fiszel",
        "title": "Founder",
        "founder_bio": "Ruben was top of his class MSc in CS at EPFL, did research on compilers from Scala to Hardware at Stanford, built the first open-source library for reinforcement learning for Java, , built distributed systems at scale at Palantir and ran the engineering team at a Multi-Party Computation startup. He is now building Windmill, an  open-source alternative to Retool, Pipedream, Airplane that contains the infra to run it and that you can deploy at scale.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/rubenfiszel/",
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      }
    ],
    "jobs": [
      {
        "id": 93198,
        "title": "Founding Growth & Developer Marketing",
        "url": "https://www.ycombinator.com/companies/windmill/jobs/t7ToQBK-founding-growth-developer-marketing",
        "location": "Paris, Île-de-France, FR / Remote (FR; DE; GB; ES; IT)",
        "type": "Full-time",
        "role": "Marketing",
        "role_type": null,
        "salary_range": "€50K - €100K EUR",
        "equity_range": "",
        "experience": "Any (new grads ok)",
        "visa": "US citizenship/visa not required",
        "skills": []
      },
      {
        "id": 93199,
        "title": "Product Software Engineer",
        "url": "https://www.ycombinator.com/companies/windmill/jobs/aXpL7BC-product-software-engineer",
        "location": "Paris, Île-de-France, FR / Geneva, GE, CH / Remote (FR; CH)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "€50K - €95K EUR",
        "equity_range": "",
        "experience": "Any (new grads ok)",
        "visa": "US citizenship/visa not required",
        "skills": [
          "PostgreSQL",
          "Rust",
          "TypeScript",
          "Machine Learning",
          "Svelte",
          "LLMs",
          "AI Agents",
          "Generative AI"
        ]
      }
    ],
    "news": [],
    "launches": [
      {
        "id": 65264,
        "title": "Windmill: Turn scripts into internal apps and workflows",
        "tagline": "Fully open-source developer platform to turn any python, typescript, SQL into internal apps, integrations and workflows",
        "body": "## Developer platform for APIs, background jobs, workflows and UIs\n\nWindmill is an open-source developer platform to quickly build production-grade internal apps, workflows and integrations from scripts in Python, Typescript, Go, Bash, SQL.\n\nOpen-source alternative to Airplane and Pipedream. Simplified Temporal with automatic app generation. Usable as a self-hosted AWS Lambda.\n\nSync your scripts from your GitHub repo or write them directly on Windmill, have them be converted to apps and no-code modules automatically. Use those apps as standalone (triggered on demand, by webhook or schedule) or build powerful flows using those scripts. The experience is similar to no-code tools except that at any point, any module can have its code inspected and tweaked. Leveraging the open-source community, we will build an exhaustive library of scripts for all APIs and generic tasks on [hub.windmill.dev](https://hub.windmill.dev/).\n\nYou may also wrap Windmill with your own frontend to provide automation as a feature on top of your own SaaS.\n\nFocus on your business logic for all kind of flows, Windmill is the platform to build, share and run them.\n\n## Active Founders\n\n**Ruben Fiszel**\n\nRuben was top of his class MSc in CS at EPFL, did research on compilers from Scala to Hardware at Stanford, built the first open-source library for reinforcement learning for Java, built distributed systems at scale at Palantir and ran the engineering team at a Multi-Party Computation startup. He is now building Windmill, an open-source alternative to Retool, Pipedream, Airplane that contains the infra to run it and that you can deploy at scale.\n\n### The sweet spot between low-code and code from scratch\n\n### Open-source and self-hostable alternative to Pipedream and Airplane. Simplified Temporal\n\nTo build internal apps for ops, integrations between services that cannot talk to each other directly, or to run background jobs that run your business logic and analytics, the two main options today are no-code solutions and old-fashioned, roll-your-own scripting. Both have problems, and our goal with Windmill is to find a new sweet spot between the two. No-code solutions are productive _if_ your problem matches the tool exactly - but if not, they are rigid, hard to extend and quickly become tech debt, annihilating their initial time advantage. Indeed, no-code is just code but made by an opinionated someone else and hidden as a blackbox with an UI.\n\nThe alternative is to do it the old-fashioned way, writing everything from scratch, both backend and frontend, perhaps deploying it on the latest flavor of serverless, and pray to never have to touch it again because that took way too much time and it has now became a burden that the ops and business team might poke you about regularly.\n\nFurthermore, the landscape of SaaS is specialized tools for everything—alerting, data analytics, administration panels, support management, integration between services—when it feels like a few scripts and some SQL would have been as good or even better and spared you the need of depending on one yet another tool. This could be even further facilitated if there was a way to import the right bunch of scripts from a fellow community of engineers, tweak it and deploy it like you can do in communities where automation can be shared as simple JSON files, for instance in the node-red or home assistant community… That’s the idea of Windmill: to bring back the power of scripting in an easy but high-scale production-grade way.\n\n## What are good use cases for Windmill\n\n1\\. The biggest pain we solve is to turn scripts that you would run on your own laptop as internal apps that you can share with your team.\n\n2\\. Avoid SQL queries to production in favor of templatized SQL made into apps instead (automatically!). Making live SQL queries is common in DevOps, support and ops in general. It can be very error-prone, stressful and inconvenient.\n\n3\\. Integrations between tools you already use but that are unable to talk to each other.\n\n4\\. Workflows, background jobs: code that runs very frequently to react to new events, transform data and run your business logic. Many companies are a frontend on top of a database, and that database is updated in the background. We make it possible to build those workflows from simple scripts so that you can build it faster, more reliable and easier to maintain.\n\n5\\. The last one only apply if you are a SaaS that wants to provide automation as a feature of your product, or a no-code tools yourself. Because we focused very much on the hard-engineering of orchestration and specs for workflows, you might simply want to wrap Windmill to offer it to your own clients.\n\n### Where is the catch, how do you make money\n\nWe make money from support, dual licensing of commercial licenses (for SaaS wrapping Windmill or for clients requiring it) and the hosted solution. On self-hosted, our Enterprise plan embedds:\n\n* SLA & Priority Support 24/7\n* Design partners for roadmap (priority on feature requests)\n* Enterprise-specific features (Audit logs, Distributed dependency cache backed by S3, SAML support etc.)\n\nWe are workflows experts and would be happy to support you to transition to clean code working on open-source software.\n\nYou can however self-host it for free forever as long as you do not go against the AGPL license (keep open-source or do not provide it as your service).\n\n![uploaded image](/media/?type=post&id=65264&key=user_uploads/229730/0fe6dab5-5378-4e2e-ad66-930378bbe8ac)\n\n![uploaded image](/media/?type=post&id=65264&key=user_uploads/229730/5d176de7-2303-49de-adb4-9bb98c559506)\n\n![uploaded image](/media/?type=post&id=65264&key=user_uploads/229730/e1d39016-bd36-4241-b0df-a5f7799ef4f5)\n\n**Docs:** [https://windmill.dev](https://windmill.dev/)\n\n**Hosted app:** [https://app.windmill.dev](https://app.windmill.dev/)\n\n**Self-host (star us!):** <https://github.com/windmill-labs/windmill#how-to-self-host>\n\n**Discord to chat with the team/community:** <https://discord.com/invite/V7PM2YHsPB>\n\n**Schedule a demo:** <https://www.windmill.dev/book-demo>\n\n**Windmill on HackerNews:**\n\n* [Aug 9 2022, HN Launch](https://news.ycombinator.com/item?id=32400849)\n* [May 12 2023, Before v2](https://news.ycombinator.com/item?id=35920082)\n* [Nov 22 2023, Why Windmill is the fastest self-hostable workflow engine?](https://news.ycombinator.com/item?id=38383138)",
        "url": "https://www.ycombinator.com/launches/Gye-windmill-turn-scripts-into-internal-apps-and-workflows",
        "votes": 17,
        "created_at": "2022-08-10T13:00:24.836Z"
      }
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    "id": 26811,
    "name": "Payload",
    "slug": "payload",
    "former_names": [
      "Payload CMS"
    ],
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    "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": [
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      "Open Source",
      "API"
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    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2022",
    "status": "Acquired",
    "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,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "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",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/0f0a550c10525505849576c534b00a71c9d71c7e.png",
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      {
        "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.",
        "is_active": true,
        "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",
        "x_url": "https://twitter.com/elliothimself",
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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.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/danribbens/",
        "x_url": "https://twitter.com/DanielRibbens",
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    "jobs": [],
    "news": [
      {
        "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"
      }
    ],
    "launches": [
      {
        "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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  },
  {
    "id": 26847,
    "name": "Slauth.io",
    "slug": "slauth-io",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/004f2f17d69c6a7d9b09c060c1c5711e24251d97.png",
    "website": "https://slauth.io/",
    "all_locations": "Tel Aviv-Yafo, Tel Aviv District, Israel",
    "long_description": "Slauth.io generates and rightsizes IAM policies in order to save engineering time and secure the organization. We use PR's to suggest what good functional and secure IAM policies should look like and integrate with IaC (Terraform)  to have a seamless end-to-end IAM policy creation and deployment. Save hundreds of DevOps engineering time each year and increase your security to scale faster. \r\n",
    "one_liner": "The IAM Policy Copilot",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1659357857,
    "tags": [
      "Developer Tools",
      "DevSecOps",
      "Productivity",
      "Compliance",
      "Security"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2022",
    "status": "Inactive",
    "industries": [
      "B2B",
      "Infrastructure"
    ],
    "regions": [
      "Israel",
      "Middle East and North Africa",
      "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/slauth-io",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2022/slauth-io.json",
    "year_founded": 2022,
    "city": "Tel Aviv-Yafo",
    "country": "IL",
    "linkedin_url": "https://www.linkedin.com/company/slauth-io",
    "x_url": "",
    "fb_url": null,
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    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/004f2f17d69c6a7d9b09c060c1c5711e24251d97.png",
    "app_video_url": null,
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    "company_photos": [],
    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
    },
    "founders": [
      {
        "user_id": 910442,
        "full_name": "Daniel Haven",
        "title": "Founder",
        "founder_bio": "Born and Raised in Amsterdam, Currently residing in Tel Aviv. Founded ProctorExam in 2014 and led it to become one of the biggest global online proctoring company. Sold it successfully to US leading EdTech company Turnitin. \nNow working on Slauth.io which is aiming to simplify and secure access management for the cloud infrastructure.",
        "is_active": false,
        "linkedin_url": "https://linkedin.com/in/danielhaven",
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      {
        "user_id": 1014400,
        "full_name": "Tal Auslander",
        "title": "Founder",
        "founder_bio": "TLV. Ex-8200. 1st CTO at ProctorExam (EdTech), acquired by TurnItIn. Chief Architect at SignifAI (AIOps), acquired by New Relic.",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/talaus",
        "x_url": "",
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      },
      {
        "user_id": 1047403,
        "full_name": "Moti Elkayam",
        "title": "Founder",
        "founder_bio": "Extensive SW engineering & Product background. \nGraduated computer science (B.Sc.) in the Technion (Israeli MIT). \nLeading product management in the last 10 years (inc MLNX switch software product  -acquired by Nvidia).\nSlauth.io is our venture in the space of Identities and Access Management (IAM). \nWe secure and streamline organizations' multi-cloud human and machine identities' permissions.\nLove to hike and run.",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/moti-elkayam-6a6a06/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4e6915a8e37882e206cd531e4e82ccd1a25a9c25.jpg"
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    ],
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  },
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    "id": 26872,
    "name": "Neosync",
    "slug": "neosync",
    "former_names": [
      "Nucleus"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0f9b88ea0ac50da754bbb784bc3e860890a742e2.png",
    "website": "https://neosync.dev",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Neosync is an open-source platform that allows you to create anonymized or synthetic data and sync it across all environments for testing and machine learning. Companies in highly regulated industries such as FinTech, HealthTech, InsureTech and those with sensitive data can use Neosync to create production-like data to use for debugging and building features in lower-level environments without the security and privacy risk of using production data. ",
    "one_liner": "Neosync is an open-source anonymization and synthetic data platform.",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1656362334,
    "tags": [
      "Developer Tools",
      "SaaS",
      "B2B"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2022",
    "status": "Acquired",
    "industries": [
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      "Infrastructure"
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    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Partly Remote"
    ],
    "stage": "Early",
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/neosync",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2022/neosync.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/neosync",
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    "cb_url": null,
    "github_url": "github.com/nucleuscloud/neosync",
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    "primary_partner": {
      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
    },
    "founders": [
      {
        "user_id": 2062726,
        "full_name": "Evis Drenova",
        "title": "Founder",
        "founder_bio": "Evis is the CEO/Co-founder of Nucleus. Before Nucleus, he was one of the first Product hires at Skyflow, a data privacy and security company, and led Product and GTM for the Fintech market from Seed -> Series B. Prior to Skyflow, he was Head of Product at Truedata, a Managing Consultant at IBM and started his career in Enterprise Sales at Experian and Oracle. He was born in Albania, grew up in Boston and currently resides in San Francisco.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/evisdrenova",
        "x_url": "https://twitter.com/evisdrenova",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a9794d66ff66b64605d665552bec291fda9e4897.jpg"
      }
    ],
    "jobs": [],
    "news": [
      {
        "title": "Nucleus aims to simplify the process of managing microservices • TechCrunch",
        "url": "https://techcrunch.com/2023/01/16/nucleus-aims-to-simplify-the-process-of-managing-microservices/",
        "date": "Jan 16, 2023"
      }
    ],
    "launches": [
      {
        "id": 85312,
        "title": "Neosync - PII Detection and Anonymization in Free-form Text",
        "tagline": "Real time PII detection and redaction in structured and unstructured data.",
        "body": "We’re an open source data anonymization and synthetic data platform that companies like Intel, Siemens, C2FO, Alasco and others use to anonymize their sensitive production data and sync it to lower-level environments.\n\nToday, we’re launching a new product designed to detect and anonymize PII data in free-form text.\n\nThese are two main use cases:\n\n1. **Detecting and redacting PII data before sending it to an LLM for inference**. If you’re building agentic systems or working with LLMs and sensitive data, you shouldn’t be sending your sensitive data to those LLMs. You can now use our API to first detect and anonymize that data and then send it to your LLM provider.\n2. **Detecting and redacting PII data before training.** You generally want to avoid training a model on PII (especially if others will be using it). You can use our API to detect and redact free-form text in training data so that you’re not training it on PII.\n\nFor example:\n\nThe text:\n\n```\n{ text: \"Dear Mr. John Chang, your physical therapy for your rotator cuff injury is approved for 12 sessions. Your first appointment with therapist Jake is on 8/1/2024 at 11 AM. Please bring a photo ID. We have your SSN on file as 246-80-1357. Is this correct?\"}\n```\n\nWould be transformed to:\n\n```\nAnonymization result: '{\"text\":\"Dear Mr. \\u003cREDACTED\\u003e, your physical therapy for your rotator cuff injury is approved for 12 sessions. Your first appointment with therapist \\u003cREDACTED\\u003e is on \\u003cREDACTED\\u003e at \\u003cREDACTED\\u003e. Please bring a photo ID. We have your SSN on file as \\u003cREDACTED\\u003e. Is this correct?\"}' \n```\n\nYou can also customize this with custom allow/deny lists and even custom recognizers.\n\nWe’re already working with companies in Healthtech and Fintech on this and would love to open it up to more companies. If you’re interested in trying it out, shoot me a note at [**evis@neosync.dev**](mailto:evis@neosync.dev), and I can get you a sandbox and free credits to trial it.\n\n![uploaded image](/media/?type=post&id=85312&key=user_uploads/89898/ea3d02aa-68e7-4a21-8bd0-c35f9786490e)\n\n",
        "url": "https://www.ycombinator.com/launches/MC0-neosync-pii-detection-and-anonymization-in-free-form-text",
        "votes": 10,
        "created_at": "2024-11-06T01:45:44.699Z"
      },
      {
        "id": 64124,
        "title": "Nucleus - The Modern Backend Platform for Microservices",
        "tagline": "Nucleus automates security, observability, secrets management and more for microservices in a single platform.",
        "body": "**Nucleus is a platform that helps developers build, deploy and manage a production-grade microservices architecture in minutes.**\n\n### **Problem**\n\nBuilding a microservices architecture is complex and can easily take 6+ months. From our experience at our own companies and from talking with many engineering teams, we see that most engineering teams try to build this platform from scratch by piecing together AWS or GCP building blocks. The problem is that this is difficult, incredibly time consuming and if not done right, can be a massive security risk. You shouldn’t have to be an infrastructure and security expert to have a secure, scalable architecture. That’s where Nucleus comes in. \n\n**Who uses Nucleus?**\n\nCompanies that want to use microservices but don’t want to spend months building out their infrastructure. These can be early stage companies that are just starting out, to mid-market companies that are architecting for growth.\n\n**How it works**\n\nNucleus is delivered through an interactive CLI that helps you declaratively define your service. Here is an example of the declarative file:\n\n![uploaded image](/media/?type=post&id=64124&key=user_uploads/980900/fb0612aa-3ab3-4e0f-8a48-aa76dd40fb8b)\n\nHere is how to deploy a microservice:\n\n1. Install the CLI through homebrew and sign up for an account.\n2. Write your service’s code or use one of our example repos to quickly get started.\n3. Declaratively define your service using the interactive Nucleus CLI. All services are automatically authenticated and secured. Manage things like environment variables, secrets, and logging, all from the CLI.\n4. Deploy your service, and it will be available in less than 2 minutes.\n\n**Can I try it?**\n\nYes! We just kicked off our private beta and would love to have you test the system to the limits. To get started, just shoot us your email so we can add you to the allowlist. Easy as that!\n\n**The Ask**\n\n1. Try us out and give us feedback. We obsess over with the developer experience, and want to make it as intuitive and magical as possible.\n2. Talk to us about your backend :) We’re focused on microservices and want to learn more about what you like, don’t like or don’t know about them. Collectively, we have 25 years of experience in engineering & product. We can be a sounding board or help you design your architecture.\n\nHave questions? Shoot me an email at [evis@usenucleus.cloud](mailto:evis@usenucleus.cloud) or feel free to book some time directly here: <https://calendly.com/evis1/30min>",
        "url": "https://www.ycombinator.com/launches/GgG-nucleus-the-modern-backend-platform-for-microservices",
        "votes": 39,
        "created_at": "2022-06-28T01:18:30.749Z"
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    "id": 26900,
    "name": "Pluralith",
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    "website": "https://www.pluralith.com",
    "all_locations": "Vienna, Vienna, Austria; New York, NY, USA",
    "long_description": "Pluralith automates compliance by documenting cloud infrastructure directly from the codebase. Companies like Jefferson Health pay us to automate their infrastructure compliance and save 5h a week per infrastructure engineer.\r\n\r\nMore simply put: We generate infrastructure diagrams directly from Terraform state.",
    "one_liner": "Automated infrastructure compliance and documentation",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1657804203,
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    "year_founded": 2022,
    "city": "Vienna",
    "country": "AT",
    "linkedin_url": "https://www.linkedin.com/company/pluralith",
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      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
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        "full_name": "Daniel Putzer",
        "title": "Founder",
        "founder_bio": "dev",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/danielputzer/",
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        "user_id": 1012880,
        "full_name": "Philipp Weber",
        "title": "Founder",
        "founder_bio": "Building Pluralith",
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      {
        "id": 65103,
        "title": "Pluralith - Automated Terraform Infrastructure Visualization & Documentation",
        "tagline": "Never spend a second drawing infra diagrams again. Completely automate your infra docs and compliance materials.",
        "body": "Hi we are Dan and Phi…\n\n![uploaded image](/media/?type=post&id=65103&key=user_uploads/690046/00d3f03c-7be2-4245-be6a-b1ac5931d882)\n\n… and we are building Pluralith!\n\n![uploaded image](/media/?type=post&id=65103&key=user_uploads/690046/f7d9a731-4769-423f-9dfd-7bdf920137e6)\n\n### **TL;DR**\n\nTitle says it all. Pluralith lets you generate instant infrastructure diagrams from your Terraform codebase, locally (for development) and in CI (for documentation). [**Try it out here!**](https://docs.pluralith.com)\n\n![uploaded image](/media/?type=post&id=65103&key=user_uploads/690046/9884a243-92d0-46ea-92f7-7dcd0cedb91c)\n\n### **Watching > Reading**\n\nSo here’s a [freshly baked demo](https://youtu.be/Jbbil9kA-EE) just for you!\n\n![uploaded image](/media/?type=post&id=65103&key=user_uploads/690046/42257960-a912-40f1-acb6-f089d4da1153)\n\n### **The Problem(s)**\n\n**Problem 1**: Infrastructure documentation is super important and often even required for proper compliance, but can be really time intensive and nobody wants to do it. So you’ve got two options:\n\n→ Stay compliant and have good docs **BUT** loads of dev hours spent on them\n\n→ No/few dev hours spent on docs **BUT** break compliance and no docs when you need them\n\n**Problem 2**: Terraform is awesome, but can become quite messy and intransparent at scale. Understanding what is actually going on requires digging through loads of code and terminal output. Again, lots of dev hours lost here.\n\n![uploaded image](/media/?type=post&id=65103&key=user_uploads/690046/1fc7af56-e700-4227-bcb9-0fc872b49446)\n\n### **The Solution: Enter Pluralith**\n\n**_Pluralith completely automates problem 1 away._**\n\nRun it in CI, automate parts of your compliance process and always have up-to-date infra diagrams whenever you need them. We throw them into PR comments and have a dedicated markdown integration so you can plug it straight into your existing docs (ReadMes, Confluence etc.). We do change highlighting, drift detection, cost calculations and compliance checks (coming soon) and keep a history of all this stuff in your Dashboard for you so you have a perfect record on how your infra changes over time.\n\n**_Pluralith alleviates problem 2._**\n\nReplace miles of terminal output on a terraform plan with a comprehensive diagram that shows you what your infrastructure looks like, how it’ll change on apply, how much it’ll cost and wether it breaks compliance (coming soon). All you have to do is run `pluralith plan` instead.\n\n![uploaded image](/media/?type=post&id=65103&key=user_uploads/690046/079e25e0-225e-443b-b052-3eaab564aa50)\n\n### **How It Works**\n\n**Locally**: Download our desktop app and follow it’s setup guide. In a minute you should be able to run `pluralith plan` in any of your Terraform project directories and get a diagram instantly.\n\n**In CI**: The illustration below says it all. Set up Terraform in your pipeline, run Pluralith and there you go. Right now we have dedicated integrations for _GitHub Actions_ and _Gitlab CI._ (Many more to come)\n\n![uploaded image](/media/?type=post&id=65103&key=user_uploads/690046/42ca4f68-1bff-48c5-a0c0-e9b1c3786746)\n\n![uploaded image](/media/?type=post&id=65103&key=user_uploads/690046/0f6a5cbc-52d6-4a6c-bfdf-bb4672190d94)\n\n### **Help Us Out?**\n\n→ [**Give it a run**](https://docs.pluralith.com) (either in CI or locally) and let us know all the ways our stuff broke through the emails below!\n\n→ Our open source CLI is looking for some stars. [**Give it a star!**](https://github.com/Pluralith/pluralith-cli)\n\n→ If you are a DevOps professional → [**Pick any slot on here!**](https://calendly.com/dantheputzer/meet) We’d be stoked to chat about the infra landscape!\n\nIf there are any questions or anything else we can assist with, shoot us an email at [dan@pluralith.com](mailto:dan@pluralith.com) or [phi@pluralith.com](mailto:phi@pluralith.com)!\n\nCheers,\n\nDan and Phi\n\n![uploaded image](/media/?type=post&id=65103&key=user_uploads/690046/952c66c1-40c8-41b8-a31c-50dbbacb5c7b)\n\n",
        "url": "https://www.ycombinator.com/launches/Gw3-pluralith-automated-terraform-infrastructure-visualization-documentation",
        "votes": 48,
        "created_at": "2022-08-03T16:42:45.345Z"
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    "name": "Grai",
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    "website": "https://www.grai.io",
    "all_locations": "San Francisco, CA, USA; London, England, United Kingdom; St. Louis, MO, USA",
    "long_description": "Grai is open source version control for metadata. We can determine how database changes will affect deployed machine learning models, apis, and dashboards because we understand how data relates across systems which don’t otherwise talk to each other.",
    "one_liner": "Open source version control for metadata",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1660014966,
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    "year_founded": 2021,
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    "country": "US",
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        "full_name": "Ian Eaves",
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        "founder_bio": "Ian is a recovering ex-physicist turned machine learning engineer with experience building MLE teams everywhere from startups (Bellhops) to fortune 50 companies (Centene). An active open source contributor he's written software with over 11M downloads (Visions). Grai was born from the pain of working on distributed data particularly within enterprise settings.",
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        "title": "✨ Grai - Open-source version control for metadata",
        "tagline": "Grai knows how a database migration will impact deployed ML models, APIs, and more because it understands how data relates across systems.",
        "body": "![uploaded image](/media/?type=post&id=65887&key=user_uploads/696649/b51bcf0a-5353-4db3-b9c4-8836f2ea423a)\n\n**TL;DR Grai makes developers smarter by bringing metadata from across their stack into their development tools. We make testing data flows between applications painless.**\n\nGo to 👉 [grai.io](http://grai.io)\n\n### 😭 **Problem**\n\nTracking (let alone testing) data once it leaves a production environment is challenging. Whether in a data engineers transformation pipeline, an ML model, or the CFO’s metrics dashboard, that data _will_ be used elsewhere. Without visibility on those use cases data changes remain risky and outage prone.\n\n### 🚀 **Solution**\n\nGrai is an open-source data management platform designed to help you better use your data.\n\n* **Automated data lineage** - Pre-built connectors to keep metadata fresh.\n* **Integrated with git** - Changing a column in your DB? Run data integration tests for all downstream users as part of your standard CI/CD process.\n* **One-stop-shop** - A unified model of your entire data stack.\n* **Your data belongs to you** - Grai is open-source & self-hosted with a cloud option coming soon.\n\n### 🎉 **Closing thoughts (and asks!)**\n\nMy ask: give it a shot!\n\n* Browse the [code](https://github.com/grai-io/grai-core)\n* Check out the [demo](https://github.com/grai-io/grai-core/tree/master/examples/quick_start_postgres)\n* Reach out! [ian@grai.io](mailto:ian@grai.io)\n\n\\~ Ian\n\n![uploaded image](/media/?type=post&id=65887&key=user_uploads/696649/7ecc72b3-40f5-4473-ae0f-157159a139eb)\n\n",
        "url": "https://www.ycombinator.com/launches/H8h-grai-open-source-version-control-for-metadata",
        "votes": 51,
        "created_at": "2022-09-07T00:00:00.601Z"
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    "id": 27092,
    "name": "Lamin",
    "slug": "lamin",
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    "one_liner": "Open data platform for traceable, multimodal AI",
    "team_size": 12,
    "industry": "B2B",
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    "launched_at": 1655969538,
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        "full_name": "Alex Wolf",
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        "founder_bio": "Building open-source data infra for biology at Lamin.\n\nPreviously, created Scanpy and led the build-up of Cellarity’s compute platform.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/falexwolf/",
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        "user_id": 1014442,
        "full_name": "Sunny Sun",
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        "linkedin_url": "http://linkedin.com/in/sunnyosun",
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    "id": 27146,
    "name": "Sunpia",
    "slug": "sunpia",
    "former_names": [
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      "Sunpia",
      "Cloudless"
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    "website": "http://sunpia.io",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "Sunpia lets developers easily experience the cost and speed benefits of serverless infrastructure, without having to rewrite their code. Developers annotate their code and Sunpia automatically designs a microservice version of it they can deploy on their own cloud.",
    "one_liner": "Deploy serverless without rewriting code",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1662145175,
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        "full_name": "Alan Pham",
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        "full_name": "Ivy Pham",
        "title": "Founder",
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      {
        "user_id": 1018726,
        "full_name": "Vikranth Srivatsa",
        "title": "Founder",
        "founder_bio": "I graduated from UC Berkeley EECS doing systems and machine learning research. I do research as part of the UC Berkeley SKY Lab. I am interested in cloud/edge computing.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/vikranth-srivatsa-921067126",
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    "id": 27152,
    "name": "Firecrawl",
    "slug": "firecrawl",
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      "SideGuide",
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    "all_locations": "San Francisco, CA, USA",
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        "title": "/extract by Firecrawl - Get structured website data with just a prompt",
        "tagline": " Turn entire websites into structured data with AI",
        "body": "Hey everyone! We’re Eric, Caleb, and Nick from Firecrawl (S22). Today, we’re launching **/extract** — an endpoint that turns entire websites into structured data with a prompt.\n\n**TL;DR**\n\nWith Firecrawls' new /extract endpoint, any website can be turned into structured data with a simple API call and prompt. We handle the complexity so you can focus on building your company.\\\n\\\n**The Problem.**\n\nIf you need to pull data from websites - maybe to enrich your CRM, track competitors, or onboard users - you're stuck with:\n\n1. Manually researching and copy-pasting from multiple sources \\\\\n2. Building and maintaining scrapers that break at the slightest site change\n3. Stitching together scraping services and complex LLM pipelines with limited context windows\\\n   \\\n   Each approach wastes the engineering time you could spend shipping a product. :\n\n## **Our Solution:**\n\n/extract is an API that turns a prompt into structured web data.\n\n![uploaded image](/media/?type=post&id=86973&key=user_uploads/1045172/62c44a11-9011-4ae0-82ac-8151a9c57c1b)\n\nHere's how to use it: \n\n1. **Give us URLs + Prompt**\\\n   Write what data you want, and point us at websites. Use wildcards like [example.com/\\*](http://example.com/\\*) to scan entire sites.\n2. **We Find Relevant Content**\\\n   Our crawler finds and ranks the pages that matter, automatically.\n3. **AI Extracts Data**\\\n   Intelligent agents split, search and parallelize the work, handling sites of any size.\n4. **Get Clean JSON**\\\n   Receive structured data ready to use - no post-processing needed.\n5. **Integrate anywhere via API**\\\n   With our API, you can use firecrawl anywhere, whether its in your applications or no-code tools like Zapier\n\n## **Why It Works**\n\n* **Handle Any Website:** Built on proven scraping infrastructure that just works\n* **Natural Language Input:** Describe what you want in plain English - we figure out the schema\n* **No Size Limits:** Process massive sites by automatically splitting the work\n* **Use It Anywhere:** Full API + ready-made integrations for Python, Node, and Zapier\n\n## **Limitations - (and the road ahead)**\n\nLet's be honest - while /extract is pretty awesome at grabbing web data, it's not perfect yet. Here's what we're still working on:\n\n1. Big sites are tricky - It can't (yet!) grab every single product on Amazon in one go\n2. Complex searches need work - Things like \"find all posts posted after 2024\" aren't quite there\n3. Sometimes, it's a bit quirky - Results can vary between runs, though it usually gets what you need\n\nBut here's the exciting part: we're seeing the future of web scraping take shape. \n\n## **Get Started**\n\n1. **Try the Open Beta**\n   * For a limited time, get **500,000 free** tokens to get you started\n   * Explore the [www.firecrawl.dev/playground?mode=extract](http://www.firecrawl.dev/playground?mode=extract) \n   * Read the docs => <https://docs.firecrawl.dev/features/extract>\n2. **Join Our Community**\n   * Star us on [www.github.com/mendableai/firecrawl](http://www.github.com/mendableai/firecrawl) - we're open-source!\n   * Share your use cases and feedback.\n\nReady to turn web data into your competitive advantage? Get started in less than 5 minutes.\n\nGet your API key at [www.firecrawl.dev/app](http://www.firecrawl.dev/app)\n\n— Eric, Caleb, and Nick at Firecrawl 🔥",
        "url": "https://www.ycombinator.com/launches/Mcn-extract-by-firecrawl-get-structured-website-data-with-just-a-prompt",
        "votes": 14,
        "created_at": "2025-01-20T16:54:10.692Z"
      },
      {
        "id": 82563,
        "title": "Firecrawl 🔥: Open source crawling and scraping for AI-ready web data",
        "tagline": "The easiest way to connect web data to your AI apps",
        "body": "Hey everyone! We're Caleb, Nick, and Eric, the founders behind [Firecrawl](https://www.firecrawl.dev/) - an all-in-one developer platform for crawling & scraping web data for AI applications.\n\n**TLDR:** Firecrawl is an open source API that transforms any web data into a clean, LLM-ready format for RAG, agentic tasks, or training. Since launching in April we gained 8000 stars on GitHub ⭐️\n\n![uploaded image](/media/?type=post&id=82563&key=user_uploads/1045172/59b29329-b168-42b9-9642-0e11f99699de)\n\n\\\n**The Problem:** Our story began while building [Mendable.ai](http://Mendable.ai), one of the first managed RAG platforms used by companies like Coinbase, Snap, and MongoDB. We quickly discovered that web data was not only a popular source for AI applications but that its quality was crucial for successful deployments.\n\nBuilding a reliable stack that worked for almost any URL presented numerous challenges, and as we expanded, we encountered countless edge cases. While some great tools existed, none handled the entire process reliably. We envisioned an API that could take a URL, crawl its pages, and provide up-to-date, easy-to-use markdown.\n\nConversations with industry peers revealed that they were rebuilding similar infrastructure. This inspired us to create Firecrawl— a developer-friendly solution we wish we'd had from the start.\n\nWe launched a cloud offering over a weekend in April, and in just three months, we've garnered over 8,000 GitHub stars and empowered thousands of developers to transform web content into AI-ready data.\n\n**Our Solution:**\n\n![uploaded image](/media/?type=post&id=82563&key=user_uploads/1045172/14099b5d-73e8-4661-8ce4-65bb4623852f)\n\nOur open-source, developer-focused platform simplifies scraping & crawling for AI apps by handling:\n\n* Bypassing JavaScript rendering\n* Enriching metadata\n* Crawling without consistent sitemaps\n* Parallel scraping jobs\n* Hosting headless browsers and managing proxies\n* Bot blocking\n* Formatting LLM-friendly markdown\n\nWith Firecrawl, developers at companies like [Gamma](https://gamma.app/), [StackAI](https://www.stack-ai.com/), and [Zapier](https://zapier.com/) are delegating scraping to us so they can focus on their core tasks - be it RAG, agents, or data processing.\\\n\\\nNow scraping a whole website and retrieving the markdown is as simple as this:\n\n![uploaded image](/media/?type=post&id=82563&key=user_uploads/1045172/0c55112e-cd7a-4420-bd79-cbb07e4acaf3)\n\n**Our Asks:**\n\n* Give [Firecrawl](https://www.firecrawl.dev/) a try 🧑‍💻\n* Explore our [GitHub repository](https://github.com/mendableai/firecrawl) and consider leaving a star ⭐️\n* Drop me a line at [eric@firecrawl.com](mailto:eric@firecrawl.com) if you want to chat (we are super excited about collaborations) 🔥",
        "url": "https://www.ycombinator.com/launches/LTf-firecrawl-open-source-crawling-and-scraping-for-ai-ready-web-data",
        "votes": 60,
        "created_at": "2024-07-30T17:47:16.926Z"
      },
      {
        "id": 69730,
        "title": "🔍 Mendable - Embeddable chat powered search for your developer products",
        "tagline": "An easily embeddable search component that allows developers to search and chat, trained on your docs and resources. ",
        "body": "Hey YC!\n\nIt’s Garrett, Eric, Caleb, and Nick from SideGuide - Today we are launching Mendable, a chat-powered search tool embeddable in your docs, product, or community to answer developer questions and reduce their time to hello world. Check out our [live search demo with LangChain](https://hwchase17.github.io/langchainjs/docs/modules/indexes/document/) and shoot us a message at [garrett@sideguide.dev](mailto:garrett@sideguide.dev) if you want to chat! :)\n\n**Problem:**\n\nWe’ve spent over a year in the developer experience space, building tools to make the lives of founders and developer relations folks easier. During this journey, we learned developers have a hard time navigating documentation and understanding the capabilities of a product in an efficient way. In response, developer communities and support forums become overloaded with questions, and dropoffs and onboarding times grow.\n\n**Solution:**\n\nWe’re building [Mendable](https://www.mendable.ai/), a chat-powered search tool leveraging cutting edge LLM models to accelerate a developer’s time to hello world and improve developer experience. We ingest your company’s resources (documentation, support forums, community messages, etc.) and give developers custom responses to their questions with direct links to sources via a chat interface. This interface can be easily embedded anywhere via a javascript component or accessed via slack/discord, allowing our search to be put in your docs, product, community, or wherever else you see fit.\n\n**What does it look like?**\n\n![uploaded image](/media/?type=post&id=69730&key=user_uploads/1045324/4b531b27-de01-4e68-abea-2014a4088e8c)\n\n* **Continuous Improvements -** With our intuitive thumbs-up and down rating system and the ability for admins to edit answers, Mendable's search functionality continually learns and improves.\n* **Integrates Everywhere -** Mendable offers a chat-powered search bar to add anywhere in your docs or website. Support for Discord, Slack, Github, and more is coming soon.\n* **Resources Condensed** - Mendable’s generations are based on your resources - including docs, support Q/A, and community messages - condensed into powerful answers.\n\n**The ask:**\n\nInterested? Shoot us a message at [garrett@sideguide.dev](mailto:garrett@sideguide.dev) or schedule a meeting with us [here](https://calendly.com/garrett-sideguide)!",
        "url": "https://www.ycombinator.com/launches/I8g-mendable-embeddable-chat-powered-search-for-your-developer-products",
        "votes": 43,
        "created_at": "2023-02-27T21:51:26.203Z"
      },
      {
        "id": 65638,
        "title": "🚀 SideGuide - Let developers test-drive your API with an online editor",
        "tagline": "Embeddable code editors designed to show developers why your product rocks",
        "body": "Hi YC!\n\nIt’s Eric, Caleb, Nick, and Garrett from SideGuide - We are building a lightweight, embeddable, online code environment that lets developers play with your API use cases and tutorials with zero setup. Interested? Check out our [live example with Hyperbeam here](https://app.sideguide.dev/hyperbeam/threejs/) and shoot us a note at [founders@sideguide.dev](mailto:founders@sideguide.dev) to chat :)\n\n**Problem:**\n\nDuring college, we started SideGuide as a B2C coding education platform, where we watched hundreds of developers struggle to learn from API documentation, then waste hours re-inventing the wheel instead of using an off-the-shelf solution. We found that API and SDK documentation is often, to be frank, not engaging. This leads to an incomplete understanding of the implementation process and product value, resulting in lost sales. Basically, developers forget your product instead of falling in love with it.\n\nIt’s 2022, developers and technical PMs should be able to quickly play with the real code before investing time and money in a product. That is why we built SideGuide.\n\n**Solution:**\n\nWe are building SideGuide: a lightweight, embeddable, online code editor that lets developers play with your API without **setup.** Our format integrates guides directly into the editor, giving users the context they need to understand your use-cases while experimenting immediately. We give developers and technical PMs an easy way to test, understand and evaluate your products. As a bonus, we also provide analytics and insights from sessions so you can improve the implementation process and understand your customers.\n\n**What does it look like?**\n\n![uploaded image](/media/?type=post&id=65638&key=user_uploads/1045172/1e47388e-3f04-4540-b374-1d1bad6b1dc2)\n\n* **Fully interactive** - Our web-based sandbox makes it quick and easy for developers to try your examples out with minimal friction.\n* **Integrated tutorial - Step-by-step instructions for different sections of the code.**\n* **Trackable - See how users are interacting with your use-cases so you can identify avenues for improvement** \n* **Embed anywhere - Embed in your docs or send via link.**\n\nCheck out our updated website at <https://sideguide.dev> and the live example using Hyperbeam’s amazing API here: <https://app.sideguide.dev/hyperbeam/threejs/>\n\n**The Ask:**\n\nInterested? Shoot us a note at [founders@sideguide.dev](mailto:founders@sideguide.dev) or schedule a meeting with us [here](https://calendly.com/eric-ciarla)! We are looking for launch partners for demo day :)",
        "url": "https://www.ycombinator.com/launches/H4g-sideguide-let-developers-test-drive-your-api-with-an-online-editor",
        "votes": 217,
        "created_at": "2022-08-26T16:51:14.086Z"
      }
    ]
  },
  {
    "id": 27184,
    "name": "Taro",
    "slug": "taro",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d4584cf3fa0e1a05a89a63ceaa8dab2f4c2d68d0.png",
    "website": "https://joinTaro.com/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Taro is a community of 150k+ software engineers looking to grow their careers. High-growth tech companies leverage the Taro platform to hire engineers who can grow the company. \r\n\r\nTaro's education platform offers online courses and discussions with leaders at top tech companies. These resources attract many top engineers seeking their next career move.\r\n\r\nTaro supports the hiring process at startups through sourcing and feedback on engineers. If you're looking to expand your engineering team quickly, without compromising on quality, book time here: https://www.jointaro.com/enterprise/",
    "one_liner": "Help high-growth tech companies hire strong engineers",
    "team_size": 6,
    "industry": "B2B",
    "subindustry": "B2B -> Recruiting and Talent",
    "launched_at": 1658437017,
    "tags": [
      "Developer Tools",
      "Education",
      "Community",
      "Video",
      "Creator Economy"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2022",
    "status": "Acquired",
    "industries": [
      "B2B",
      "Recruiting and Talent"
    ],
    "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/taro",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2022/taro.json",
    "year_founded": 2022,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/jointaro",
    "x_url": "https://twitter.com/join_taro",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/joinTaro/",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/d4584cf3fa0e1a05a89a63ceaa8dab2f4c2d68d0.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": 192956,
        "full_name": "Rahul Pandey",
        "title": "Founder",
        "founder_bio": "Founder of Taro (joinTaro.com) to enable better careers for engineers. Taught mobile dev at Stanford, ran a YT channel with 120K subscribers, and taught courses on Taro, LI Learning, and  Codepath.\n\nI previously worked at Meta + Pinterest, and I spend most of my free time playing pickleball.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/rpandey1234/",
        "x_url": "https://twitter.com/rpandey1234",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5c35826c7e784f88099e8cb4948cf93231c4abeb.jpg"
      },
      {
        "user_id": 823798,
        "full_name": "Alex Chiou",
        "title": "Founder",
        "founder_bio": "Founder of Taro (joinTaro.com), which provides engineers with bite-sized actionable advice from top tech talent. Content is organized by company, level, and problem area. \n\nI love to build: I've published ~30 apps with 3 million installs combined in my free time. In high school, I built a YT channel with 50M+ video views.\n\nMy cofounder Rahul and I organically built a community of 17K+ people called \"Tech Career Growth\", which inspired Taro. Prior, I was a TL at Robinhood, Meta, and Course Hero.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/alexander-chiou/",
        "x_url": "https://twitter.com/AlexChiou",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c008b4de02e11ebbd9322634414fd98e5cb3cc4e.jpg"
      }
    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 65087,
        "title": "🧋 Taro - Faster Career Growth for Software Engineers",
        "tagline": "We get software engineers onboarded and promoted faster",
        "body": "**tl;dr**: Your career growth shouldn’t depend on your ability to find a good mentor or manager. Taro brings together top SWEs with proven insights to scale your career. **Check out our** [**website**](https://bit.ly/taro_app_web) **and** [**YouTube channel**](https://bit.ly/rahul_yt)**.**\n\nTaro helps full-time engineers get onboarded and promoted faster. We do this through Q&A and case studies from tech veterans, organized by company and level.\n\n### **⛔️ The Problem**\n\nAs a software engineer, you already know how to code. But **software engineering is so much more than coding**.\n\nOver the last 2 years, Alex and I built a community of 50K software engineers on [YouTube](https://youtube.com/rpandey1234), [Slack,](https://join.slack.com/t/techcareergrowth/shared_invite/zt-1ctxuq8h2-b3nnkQG0MtXyBpvrEFpgqQ) and [LinkedIn](https://www.linkedin.com/company/71614174/admin/). We talked to hundreds of engineers and found that their career bottleneck was not their coding ability, but how effectively they managed projects, understood the context, and communicated blockers.\n\n![uploaded image](/media/?type=post&id=65087&key=user_uploads/192956/5ded8a2b-c6e4-4a8f-b6e8-039c9d7335a8)\n\nLeft to right:\n\n[📱 Alex](https://www.linkedin.com/in/alexander-chiou/) has mentored dozens of engineers to Senior+ levels across his time at Meta and Robinhood.\n\n[🎓 Rahul](https://www.linkedin.com/in/rpandey1234/) has taught thousands of engineers through his role as a Stanford lecturer, LinkedIn Learning instructor, and YouTube creator.\n\nWhat separates an average engineer from a great engineer is the ability to independently create business impact, and that doesn’t get taught in a CS degree or a bootcamp. Taro fills the gap.\n\n### **💡 Our Solution**\n\n1. A Q&A database from real engineers, with answers from industry experts. **All questions are tagged by company + level, which makes it easy to find relevant content.** [Here’s a sample](https://app.jointaro.com/question/mvMQj8228kuUe38BvdT9).\n2. Case studies from eng leads + managers at top tech companies.\n3. A community of software engineers at top companies who share insights + advice.\n\n![uploaded image](/media/?type=post&id=65087&key=user_uploads/192956/62f78267-822d-4ab1-a232-5c3f586b48d9)\n\n### **💁🏽‍♀️ Target Audience**\n\nWe already have 100+ Taro Premium members from companies like Meta, Google, TikTok, and Amazon (along with thousands of free users).\n\nTaro is a great fit for **full time engineers at fast-moving tech companies**. Taro is **not** a good fit for freelancers or students who are still exploring software engineering.\n\n### **❓Our Ask**\n\n1. Reach out if you’re an engineer starting a new role, or are aiming for a promotion.\n2. Tell us what upskilling products you’ve used for engineers!\n\nShoot us an email at [team@jointaro.com](mailto:team@jointaro.com) — our app is available for web, Android, and iOS at <https://joinTaro.com>.",
        "url": "https://www.ycombinator.com/launches/Gvn-taro-faster-career-growth-for-software-engineers",
        "votes": 62,
        "created_at": "2022-08-03T02:02:51.171Z"
      }
    ]
  },
  {
    "id": 27195,
    "name": "Vizzly",
    "slug": "vizzly",
    "former_names": [
      "Vizzly Technology Ltd"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/22e8f105fb29e8957dec4db2a7b28a0c24a20539.png",
    "website": "https://vizzly.co/",
    "all_locations": "London, England, United Kingdom; Remote",
    "long_description": "Vizzly provides customer-facing analytics for modern SaaS.\r\n\r\nThe platform offers the same level of flexibility as an in-house development process with minimal technical overhead required. ",
    "one_liner": "Customer-Facing Analytics for Modern SaaS.",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Analytics",
    "launched_at": 1659723878,
    "tags": [
      "Developer Tools",
      "SaaS",
      "B2B",
      "Analytics",
      "API"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2022",
    "status": "Acquired",
    "industries": [
      "B2B",
      "Analytics"
    ],
    "regions": [
      "United Kingdom",
      "Europe",
      "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/vizzly",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2022/vizzly.json",
    "year_founded": 2022,
    "city": "London",
    "country": "GB",
    "linkedin_url": "https://www.linkedin.com/company/vizzlyco",
    "x_url": "",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/22e8f105fb29e8957dec4db2a7b28a0c24a20539.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": 858781,
        "full_name": "Matt Williamson",
        "title": "Founder",
        "founder_bio": "Co-Founder & CEO @ Vizzly | Skyscanner & Duffel Alumni",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/williamsonmatt/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/020be053bd21ed69d336f67e7f4829063555ad3b.jpg"
      },
      {
        "user_id": 968222,
        "full_name": "James Bowers",
        "title": "Founder",
        "founder_bio": "Co-founder & CTO of Vizzly",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/james-matthew-bowers/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/da0448f402c7d09b0d4981be04d2e1d195f87ba1.jpg"
      }
    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 65280,
        "title": "Vizzly ⚡️ Customer-Facing Analytics for Modern SaaS",
        "tagline": "Build, embed, share and delight your users with data.",
        "body": "**✨ TL;DR**\\\n[Vizzly](https://www.vizzly.co/) is customer-facing analytics for modern SaaS.\n\nOur primary goal is to help SaaS companies build beautiful customer-facing analytics without compromising the user experience or product quality.\n\nVizzly offers a semantic layer, works with your authentication setup, and provides a powerful visualization layer that's extensible with code for those who want more control.\n\nWith Vizzly, customers can build and deliver anything from simple user-facing insights to advanced custom reporting and everything in between.\n\n**❌ The problem**\n\nOver 75% of B2B SaaS companies have (or will need) customer-facing dashboards or reporting capabilities, but embedded analytics tools are stereotypically rigid and force a lot of compromise.\n\nFor example, many of these tools offer simple iFrame embeds, instantly limiting flexibility, programmability, and impacting performance.\n\nIf SaaS companies do build in-house, they end up committing precious time to building a large product feature that’s often not core to their unique value proposition.\n\nThe maintenance overhead is often overlooked until customers begin asking for new cuts of data or other views, meaning the SaaS company needs to extend the backend API and build new visualizations if they want to satisfy the request.\n\n**💡 How we help**\n\nVizzly provides customer-facing analytics for modern SaaS; offering the same level of flexibility as an in-house development process with minimal technical overhead required.\n\nKey product areas include:\n\n* Ultra low-code experience: get setup in hours.\n* JS-based embedding (React, Angular, Vue & Svelte).\n* Extensible with code and highly flexible.\n* Native to your UI (we offer a lot of control).\n* Works with normalized and dynamic customer data structures.\n* Direct API access via our React or Vanilla JS Hook.\n* A powerful Custom Reporting option.\n\n**❓How do I sign up?**\n\nSign up link [**here**](https://app.vizzly.co/sign-up)**.**\n\nAlternatively, feel free to schedule a demo with us [**here**](https://calendly.com/mswilliamson/call-with-matt)**.**\n\nThank you! Vizzly Team ✌️",
        "url": "https://www.ycombinator.com/launches/Gyu-vizzly-customer-facing-analytics-for-modern-saas",
        "votes": 71,
        "created_at": "2022-08-10T17:11:57.727Z"
      }
    ]
  },
  {
    "id": 27250,
    "name": "Axle",
    "slug": "axle",
    "former_names": [
      "Axle (Axle Labs",
      "Inc.)"
    ],
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        "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",
        "votes": 241,
        "created_at": "2022-07-20T23:49:02.445Z"
      }
    ]
  },
  {
    "id": 27261,
    "name": "Integrated Reasoning",
    "slug": "integrated-reasoning",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7abc96adeb32772a65759b3c7fb44df00a0e11db.png",
    "website": "https://integrated-reasoning.com",
    "all_locations": "San Diego, CA, USA; Kilauea, HI, USA; Remote",
    "long_description": "Integrated Reasoning builds efficient computer processors that are tailored to the memory access patterns of Karp's 21 NP-complete problems. We’re making it 100x - 10,000x faster to perform computations like scheduling airline pilots or optimizing packing layouts for shipping containers.",
    "one_liner": "Faster processors for solving NP-complete problems",
    "team_size": 1,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1656696534,
    "tags": [
      "Developer Tools",
      "Hard Tech",
      "Hardware",
      "SaaS",
      "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",
      "Fully Remote"
    ],
    "stage": "Early",
    "app_video_public": true,
    "demo_day_video_public": false,
    "app_answers": [
      {
        "question": "Describe what your company does in 50 characters or less.",
        "answer": "Insanely fast silicon for NP-complete algorithms."
      },
      {
        "question": "How long have each of you been working on this? How much of that has been full-time? Please explain.",
        "answer": "I founded Integrated Reasoning in December of 2021. I started working on the idea full-time as of March 2022."
      },
      {
        "question": "What is your company going to make? Please describe your product and what it does or will do.",
        "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."
      }
    ],
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/integrated-reasoning",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2022/integrated-reasoning.json",
    "year_founded": 2021,
    "city": "San Diego",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/integrated-reasoning",
    "x_url": "https://twitter.com/IntegrateReason",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/integrated-reasoning",
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        "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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        "title": "Infisical: The Open Source Security Stack",
        "url": "https://www.youtube.com/watch?v=qDumDlXcMkg",
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        "title": "Infisical raises $16 million Series A led by Elad Gil to safeguard secrets | Fortune",
        "url": "https://fortune.com/2025/06/06/infisical-raises-16-million-series-a-led-by-elad-gil-to-safeguard-secrets/",
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        "title": "Google's Gradient backs YC alum Infisical to solve secret sprawl | TechCrunch",
        "url": "https://techcrunch.com/2023/07/03/googles-gradient-backs-yc-alum-infisical-to-solve-secret-sprawl/",
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        "title": "💚 Infisical - The open source secrets manager for developers",
        "tagline": "Open source, end-to-end encrypted tool that lets you securely sync secrets and configs across your team, devices, and infrastructure",
        "body": "Hey there, this is team Infisical 🏂\n\n[Infisical](https://infisical.com/) is an open-source, end-to-end encrypted platform for developers to centralize their application secrets and configs, and sync them across their whole development life cycle.\n\nWe launched 3 months ago, and already have 4.2K+ stars on GitHub, 50 contributors, and 220+ community members 🚀\n\n![uploaded image](/media/?type=post&id=69599&key=user_uploads/942802/00941739-4c42-44c8-92e8-e8fc55f7cb1b)\n\n\n**Imagine this**: You add a new environment variable to your team’s codebase, push it up to GitHub, and head out for dinner. Shortly after, your teammate pulls the latest changes and everything crashes because they're missing that variable.\n\nYou come back to angry messages from your teammate and quickly send them the variable over text, risking a security vulnerability. Everything seems to be working until the next day when you deploy to production, and once again, everything crashes because you forgot to add the environment variable to the production environment.\n\nSounds relatable?\n\n![uploaded image](/media/?type=post&id=69599&key=user_uploads/942802/d8e6a881-8412-4baf-8f54-b8defb0ecd46)\n\n\n## **Problem**\n\nSecrets play a critical role in every stage of the software development lifecycle, from local development to staging, testing, and production. Even so, teams routinely run into challenges dealing with secret management:\n\n* **Missing secrets across infrastructure**: Having secrets sprawled across infrastructure with no central visibility and control often leads to missing secrets. In turn, applications crash in production and developers lose precious time debugging what’s missing.\n* **Leaking secrets to source control**: Even the biggest companies accidentally expose hardcoded secrets and .env files. When it happens, the consequences are grave.\n* **Lacking self-hosted alternatives**: Many great solutions are not self-hostable or end-to-end encrypted, a challenge for companies requiring it. In a world where security and privacy are increasingly paramount, having these options are essential.\n\n## **Solution**\n\nInfisical provides an open-source, end-to-end encrypted platform for developers to manage their application secrets and sync them across their team and software development lifecycle.\n\nWith Infisical, you can:\n\n* **Securely store and deliver** application secrets to your infrastructure with integrations available for Docker, Kubernetes, AWS, Vercel, GitHub Actions, etc.\n* **Inject secrets** into applications instead of using .env files that often get leaked.\n* **Self-host** Infisical on your own infrastructure.\n* **Enhance observability** of secrets and teammates with secret versioning, rollbacks, and audit logs for every action taken.\n\n![uploaded image](/media/?type=post&id=69599&key=user_uploads/942802/afe74cca-1292-4f25-b0d5-03ae9fc21327)\n\n\n## **Asks**\n\n* Check out Infisical at <https://infisical.com>\n* Contact [tony@infisical.com](mailto:tony@infisical.com) if your company needs help with secret management\n* Intros to companies that in your experience may benefit from Infisical",
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        "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,
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        "body": "**TLDR**: [Traceloop](https://www.traceloop.com/?utm_source=YCLaunch) helps teams test, troubleshoot, and improve AI agents with automated performance evaluations, ensuring reliability before and after every release. We bring the same rigor to AI that developers expect from the rest of their stack.\n\n---\n\nHi everyone, we’re Nir and Gal, co-founders of [Traceloop](https://www.traceloop.com/?utm_source=YCLaunch), and we're part of the Y Combinator Winter 2023 batch.\n\n🚨 **Problem**\n\nBuilding and deploying AI agents today often feels like guesswork. Public model benchmarks don’t predict how well an AI will perform in real-world applications, and businesses are stuck in a cycle of trial and error, tweaking prompts and manually testing. But as AI agents become more complex and critical, these outdated methods just don't cut it. When AI misfires — hallucinating, taking wrong actions, or producing unpredictable outputs — users disengage instead of filing bug reports.\n\nAt [Traceloop](https://www.traceloop.com/?utm_source=YCLaunch), we believe **prompt engineering shouldn't be a guessing game**. We need to bring the same quality assurance processes to AI that we’ve come to expect from software engineering.\n\n🧠 **Solution**\n\n![uploaded image](/media/?type=post&id=90818&key=user_uploads/1024399/2e0c1c99-adce-411c-948b-1e0263e8ca47)\n\nTraceloop provides **evaluations** and **real-time monitoring** for AI agents, reducing the guesswork and ensuring performance is consistent before reaching end users. Our open-source foundation, [OpenLLMetry](https://github.com/traceloop/openllmetry) and [Hub](https://github.com/traceloop/hub), collects LLM interactions at scale and our our commercial platform is now helping businesses:\n\n* **Train evaluators** to catch hallucinations and detect quality issues.\n* **Experiment** with different models to choose the right one for your use case.\n* **Monitor and Evaluate AI agent performance** in real-time or during CI.\n\nWe help teams **reduce risk, accelerate iteration**, and ensure that their agents behave as expected in production environments.\n\n🎯 **Asks**\n\n⭐ Star us [OpenLLMetry](https://github.com/traceloop/openllmetry) and [Hub](https://github.com/traceloop/hub) on GitHub and follow us on [Twitter](https://x.com/traceloopdev)!\n\nIf you're building LLM apps, we'd love to show you how Traceloop can help improve your agent’s performance and reliability. [Reach out](https://calendly.com/d/cq42-93s-kcx) and let’s explore how we can help.\n\nIf you know teams working with AI, please forward this to them!",
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        "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"
      },
      {
        "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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    "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",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1668798140,
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      "SaaS",
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      "South Asia"
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    "year_founded": 2022,
    "city": "Bengaluru",
    "country": "IN",
    "linkedin_url": "https://www.linkedin.com/company/dr-droid/",
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    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
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    "founders": [
      {
        "user_id": 1073547,
        "full_name": "Siddarth Jain",
        "title": "Founder",
        "founder_bio": "Co-Founder & CEO at Doctor Droid. \n\nPreviously investor at Accel, Data Scientist & Chief of Staff at Shadowfax. Studied Electrical Engineering from IIT Delhi ",
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        "user_id": 1160488,
        "full_name": "Dipesh Mittal",
        "title": "Founder",
        "founder_bio": "Founder and architect of Doctor Droid, building on 10 years in software engineering across logistics (Shadowfax), healthcare (Labstreet) and fintech (Paypal).\nPersonally a big fan of science & fantasy fiction, enjoy cycling and traveling to historical monuments.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/dipesh-mittal/",
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    "launches": [
      {
        "id": 78159,
        "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))",
        "url": "https://www.ycombinator.com/launches/KKd-alertops-slack-bot-by-doctor-droid-identify-poorly-configured-and-noisy-alerts",
        "votes": 10,
        "created_at": "2024-02-05T16:26:00.463Z"
      },
      {
        "id": 69760,
        "title": "Doctor Droid: Proactively detect issues before it impacts your customers",
        "tagline": "Monitor critical paths spanning across APIs, webhooks, cron jobs and lambda functions",
        "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)",
        "url": "https://www.ycombinator.com/launches/I9A-doctor-droid-proactively-detect-issues-before-it-impacts-your-customers",
        "votes": 52,
        "created_at": "2023-02-28T17:13:07.152Z"
      }
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  },
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    "id": 27693,
    "name": "Depot",
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    "website": "https://depot.dev",
    "all_locations": "Remote",
    "long_description": "Depot gives engineering teams the fast source control, builds, CI runners, sandboxes, caches, and registries they need to ship reliable software they trust at AI speed. Companies like PostHog, Inference, Wistia, PlanetScale, Poolside, Astral, and Semgrep use Depot to power their entire software delivery stack.\r\n\r\nKyle and Jacob worked together as staff engineers for 4.5 years at Thorn and Era Software, before founding Depot. Depot is their take on what software delivery and a replacement for GitHub could look like in the world of AI.\r\n",
    "one_liner": "Software delivery built for machine scale.",
    "team_size": 22,
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    "launched_at": 1669037258,
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      "Fully Remote"
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      "name": "Nicolas Dessaigne",
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    "founders": [
      {
        "user_id": 600738,
        "full_name": "Kyle Galbraith",
        "title": "Founder",
        "founder_bio": "Kyle Galbraith is the Co-Founder & CEO of Depot. He and Jacob Gillespie (CTO) built Depot after being faced with the same challenges time and time again surrounding slow CI builds across all generic providers. He is originally from Portland, Oregon but relocated to Montpellier, France in October 2022 to immerse himself in French culture with his wife who is originally from the area.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/kylegalbraith459",
        "x_url": "https://twitter.com/kylegalbraith",
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      },
      {
        "user_id": 956934,
        "full_name": "Jacob Gillespie",
        "title": "Founder",
        "founder_bio": "Cofounder and CTO of Depot. US expat living in the UK.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jacobwgillespie/",
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    "news": [
      {
        "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!",
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        "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",
        "votes": 37,
        "created_at": "2022-12-07T14:37:25.884Z"
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        "full_name": "Shanelle Roman",
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        "user_id": 595906,
        "full_name": "Vishnu Menon",
        "title": "Founder",
        "founder_bio": "Vishnu Menon is the Co-founder & CTO of Nebula, where he builds tools that help engineers be productive in microservice architectures. Previously, he was co-founder at an ML startup (Toucan AI) and lead data & platform projects at a MarTech software provider (AddShoppers). He earned a degree in Computer Science from Duke University.",
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        "id": 69881,
        "title": "Nebula 🌌 - Understand & debug enterprise-scale codebases",
        "tagline": "Simplifying microservice development ",
        "body": "### TL;DR\n\n[**Nebula**](https://www.trynebula.com/) **is a code navigation tool that helps developers quickly understand & debug distributed systems. We make it easy to follow service dependencies & the flow of data across your microservice architecture, saving developers tens of hours per week. Request early access** [**here**](https://mzgq3tvfxmu.typeform.com/to/DD8HB5A5)\n\nHey everyone, we're the founders of Nebula!\n\n![uploaded image](/media/?type=post&id=69881&key=user_uploads/888634/dd916b21-6237-4b46-ab5b-91a02851586a)\n\n**Shanelle** was previously a PM at Google, where she saw firsthand the productivity loss that came with complex microservice architectures.\n\n**Vishnu** is a second-time founder who has previously built developer platforms & ML-based document retrieval systems.\n\nWe've experienced the frustration of seemingly simple features taking months to launch because of the complexity of unwieldy microservice architectures. Building on open-source tooling designed to handle Google-scale codebases, Nebula aims to make it simple and painless to develop microservices.\n\n### Problem 😔\n\n[85% of enterprise companies](https://www.statista.com/statistics/1236823/microservices-usage-per-organization-size/) use a microservice architecture. However, as these codebases scale in size & complexity, developer velocity often slows drastically:\n\n1\\. **trivial changes take weeks to implement** because they impact multiple services or teams across the org\n\n2\\. it takes **longer to debug** issues because it's hard to track the flow of data across your system\n\n3\\. **onboarding** a new developer onto your codebase can take weeks, if not months\n\nCompanies that switch to microservice architecture often see a dramatic increase in the cognitive overhead required for their engineers to be productive.\n\nWe've done deep dives with best-in-class companies like Netflix and Linkedin to learn how they dealt with the growing complexity of their codebases. We're combining their most effective strategies with insights from Shanelle's experience at Google to build Nebula.\n\n### How it works [🥳](https://emojipedia.org/partying-face/)\n\nNebula deploys in your cloud & continuously analyzes your codebase to generate an index of inter-service communication, then exposes this info in three ways:\n\n1\\. An **IDE extension** that shows how a line of code fits into the overall system (e.g. service dependencies, cross-references, recent traces, etc.)\n\n2\\. An **auto-generated service catalog** that includes service interfaces, usage examples, and service contributors (no maintenance required)\n\n3\\. A **GraphQL endpoint** that exposes all this data for integration with your existing DevTools\n\n![uploaded image](/media/?type=post&id=69881&key=user_uploads/888634/69cc9b1f-5205-402a-9317-48b163d68832)\n\n![uploaded image](/media/?type=post&id=69881&key=user_uploads/888634/a714fb97-d518-478a-9952-aa58ed4d1dd9)\n\n### Our Ask [🙏](https://emojipedia.org/folded-hands/)\n\n1\\. If you're a company with >100 microservices or engineers that is looking to boost its development velocity, you can [email me](mailto:shanelle@trynebula.com?subject=YC%20Launch%20-%20interested%20in%20Nebula) or schedule a [quick chat](https://book.vimcal.com/p/z5RvBJx51onH1zTj).\n\n2\\. Know any teams that are struggling to wrangle their microservice architecture? [Intro us](mailto:shanelle@trynebula.com?subject=YC%20Launch%20-%20Nebula%20customer%20intro)! **If your referral becomes a paying customer, we'll send you a $500 Amazon gift card**",
        "url": "https://www.ycombinator.com/launches/IB7-nebula-understand-debug-enterprise-scale-codebases",
        "votes": 130,
        "created_at": "2023-03-02T19:58:46.522Z"
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    "name": "Lynx",
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        "full_name": "Max Lu",
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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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        "id": 73764,
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        "experience": "11+ years",
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        "visa": "US citizenship/visa not required",
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        "location": "San Francisco, CA, US / Remote (US; CA)",
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        "location": "San Francisco, CA, US / Remote (US; CA)",
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        "id": 116345,
        "title": "Enterprise Account Executive (Founding)",
        "url": "https://www.ycombinator.com/companies/nango/jobs/JgJmIN7-enterprise-account-executive-founding",
        "location": "San Francisco",
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        "title": "Growth & Marketing Lead (Founding)",
        "url": "https://www.ycombinator.com/companies/nango/jobs/sNXjkGq-growth-marketing-lead-founding",
        "location": "San Francisco",
        "type": "Full-time",
        "role": "Marketing",
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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"
      },
      {
        "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"
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    "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",
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    "year_founded": 2022,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/double-ai",
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        "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/",
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      {
        "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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    "website": "https://www.cakework.com",
    "all_locations": "Seattle, WA, USA",
    "long_description": "We make it possible to build a serverless cloud platform that hosts custom user code with just APIs and no infrastructure team. For example, an open source framework can build a cloud offering that deploys their users code from Github or local dev environments in days instead of months. ",
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    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1673854005,
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    "status": "Inactive",
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      "America / Canada"
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    "country": "US",
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        "full_name": "Eric Chen",
        "title": "Founder",
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        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/ericchen90/",
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      {
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        "full_name": "Jessie Young",
        "title": "Founder",
        "founder_bio": "CEO of Cakework",
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        "linkedin_url": "https://www.linkedin.com/in/jyoung73/",
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      {
        "id": 70142,
        "title": "Cakework - Custom user code in any developer product",
        "tagline": "Build your own serverless platform in days instead of months",
        "body": "**tldr**\n\n_We make it easy to run custom user code using APIs instead of infrastructure. Build extensibility directly into your developer product, or launch your own serverless cloud solution._\n\nHi friends, we're Jessie and Eric from [Cakework](https://www.cakework.com). We're ex-AWS engineers that got tired of managing infra and wanted our tools to do it for us. We started Cakework to bake serverless into every developer product and never have to host our own code again.\n\n![uploaded image](/media/?type=post&id=70142&key=user_uploads/461027/608b19e2-7cf0-4402-8173-aa280ba89b58)\n\n[Jessie](https://www.linkedin.com/in/jyoung73/) - Senior Engineer that led development of AWS call center AI analytics and NLP services.\n\n[Eric](https://www.linkedin.com/in/ericchen90/) - Engineering Manager that led a team of engineers, scientists, and clinicians in building AWS services for healthcare.\n\n**Problem**\n\nModern developer experiences let users run custom code natively, so users can build extensions and applications without any devops. This can be anything from in-browser scripting to webhook handlers or web services that deploy from Github.\n\nBuilding a platform to do this is hard because cloud services like AWS are designed by default to run your code, not your users'. You need to package your users code, handling dependencies and multiple languages. You need to provide logging, metrics, and metering. Serverless options like Lambda help with security and cost, but have restrictions on timeout and prevent you from using protocols like gRPC.\n\nYou’re basically building your own Heroku.\n\nOne of our early customers had given up on building their own serverless cloud solution. With us, they were able to launch in a week.\n\n**How did we do it?**\n\nCakework is a set of simple APIs for building serverless directly into your developer product. You describe how you want to package and run your users' code, and use Cakework to build images from Github, CLI, or even a browser. You use our APIs to run that code securely, and show logs and metrics back to your users.\n\nHere's a gif of Cakework in action with a developer SaaS tool that wanted their users to be able to run custom code on webhooks in their system.\n\n![uploaded image](/media/?type=post&id=70142&key=user_uploads/461027/72dd917a-6381-4859-8341-6d278385f1d0)\n\nYou can build your own in-browser scripting with multiple languages!\n\n![uploaded image](/media/?type=post&id=70142&key=user_uploads/461027/7a15ec40-7de5-4641-8a73-87b612c1ba7c)\n\n**Asks**\n\nWe're onboarding customers in early access now. If you or someone you know is working on a developer product and want to run your user's code, reach out at [eric@cakework.com](mailto:eric@cakework.com)!",
        "url": "https://www.ycombinator.com/launches/IFK-cakework-custom-user-code-in-any-developer-product",
        "votes": 57,
        "created_at": "2023-03-10T17:19:23.787Z"
      }
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  },
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    "id": 27813,
    "name": "Omnistrate",
    "slug": "omnistrate",
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        "id": 122341,
        "title": "Deploy your product in your customer VPC  or Single-tenant SaaS or AirGapped",
        "tagline": "BYOC, BYO-K8s, BYO-VPC, Single-tenant SaaS, Dedicated SaaS, Hosted SaaS",
        "body": "Omnistrate helps software companies to build their own private-label control plane to deliver your product inside customer cloud accounts/VPCs/Kubernetes clusters, on-premises, air-gapped environments, single-tenant SaaS and through cloud marketplaces.\n\n**A simple way to think about it:** when an enterprise customer asks, “Can this run in our AWS account?”, or “Can we self-host this?”, or “Do you have a isolated SaaS with XYZ requirements”, “Can we buy this through our cloud marketplace?”, Omnistrate generated control plane enables you say **yes** without turning every customer into a custom engineering project.\n\n### **Why we built Omnistrate:**\n\nWe experienced firsthand how difficult it is to deploy and operate software across customer environments. Every enterprise deployment became a custom engineering project, slowing down sales, consuming engineering resources, and creating ongoing operational complexity.\n\nWe built Omnistrate to change that — enabling software companies to deploy, manage, and scale their products in any customer environment without building and maintaining their own control plane.\n\n### **Three common use cases**\n\n**1. Support BYOC, self-hosted, on-prem, and air-gapped customers**\n\nEnterprise customers increasingly want software to run inside infrastructure they control due to data sovereignty or leveraging their cloud commits.\n\nWith Omnistrate you can support:\n\n* **Customer cloud accounts:** Deploy the complete stack into your customer's AWS, GCP, Azure, or other cloud account — including networking, Kubernetes, compute, storage, and your application.\n* **Customer VPCs:** Run inside an existing customer network with private connectivity and customer-controlled security.\n* **Customer Kubernetes:** Deploy and operate your software on Kubernetes infrastructure the customer already manages.\n* **On-prem and air-gapped:** Support environments with limited or no connectivity to your SaaS control plane.\n\nYou can operate these deployments as a managed service or enable customers to self-serve through your private-label portal. To learn more, see this blog: <https://omnistrate.com/blog/why-byoc-is-the-future-of-enterprise-software-deployment>\n\n**2. Build and distribute your Single-tenant SaaS  (or Hosted SaaS)**\n\nUse the same control plane to run your single-tenant SaaS across clouds, regions, tenancy models, and infrastructure configurations.\n\nStart with hosted SaaS to support simple dedicated deployments, add dedicated K8s, dedicated network, dedicated account, or multi-tenant your customers over the shared infrastructure.\n\nThis is particularly useful when your first few customers have very different requirements but you don't want to maintain separate platforms for every deployment configuration. Also - allows you to enable free trial cost-effectively or figure out the right distribution model as you unlock your GTM. To learn more, please see this blog: <https://omnistrate.com/blog/why-enterprise-saas-is-moving-toward-isolated-tenancy-models>\n\n**3. Sell through AWS, Azure, and Google Cloud Marketplaces**\n\nLaunch and transact through the major cloud marketplaces without building separate fulfillment and billing integrations for each provider.\n\nOmnistrate helps with the end-to-end motion including marketplace enablement, fulfillment, subscriptions, metering, billing, and integration with your product. We also work with you on the listing (we partner with Suger, another YC company) and cloud co-sell motion.\n\nTo learn more, please see this blog: <https://omnistrate.com/blog/the-hidden-fulfillment-problem-killing-your-cloud-marketplace>\n\n### **What Omnistrate handles**\n\nYour generated control plane can automate:\n\n* Infrastructure provisioning and configuration\n* Application deployment, scaling, and upgrades\n* Customer self-service deployments\n* Tenant and subscription management\n* Observability and health monitoring\n* Backups, recovery, drift detection, and Day-2 operations\n* Security, governance, RBAC, and auditability\n* Metering, billing, licensing, and entitlements\n* Cloud Marketplace fulfillment\n* Fleet-wide operations across customer environments\n* and more: [**https://docs.omnistrate.com/**](https://docs.omnistrate.com/)\n\n### **How does it work?**\n\nBring what you already have — container images, Docker Compose, Helm charts, Kustomize manifests, Kubernetes Operators, Terraform/IaC, or your existing deployment artifacts.\n\nDefine how your product should be deployed and operated in Claude (or your favorite codex), and we will translate that into a declarative spec and then use that to generate your **private-label control plane running in your account**.\n\nThat control plane manages the infrastructure and application lifecycle across your different customer environments.\n\nFor customer-hosted deployments, your customer's workloads and data stay in their environment. Your customers interact with your product and brand — not Omnistrate.\n\nAlready have a control plane or customer portal? You don't have to replace it. Omnistrate can extend what you already built to support additional clouds, BYOC, Kubernetes, on-prem, air-gapped environments, and operational capabilities.\n\n### **Our ASK:**\n\nIf you are looking to build one or would like to discuss more on the topic, we would love to chat more. Here is our calendly: <https://calendly.com/omnistrate>\n\nIf you would like to interested to learn more about Agent deployments, check out: <https://agentic-saas-talks.com/>",
        "url": "https://www.ycombinator.com/launches/VpF-deploy-your-product-in-your-customer-vpc-or-single-tenant-saas-or-airgapped",
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        "created_at": "2026-10-15T15:50:12.811Z"
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        "id": 91525,
        "title": "Omnistrate: CoPilot for Platform teams to go from app to product in days, not years",
        "tagline": "Build software distribution aka Control Plane",
        "body": "Going from (Agentic) App to Product, organizations have to build multiple distribution engines. The Control Plane is nothing but an **operating system for those distribution models**.\n\nOmnistrate is a developer platform to build software distribution aka Control Plane — the \"operating system\" that powers deployment models like On-Prem / AirGapped, BYOC, PaaS, SaaS, AaaS distributions.\n\nWe achieve this by building and running your Control Plane in your account, so that you don't have to spend years to build and army to operate on undifferentiated things.\n\n![uploaded image](/media/?type=post&id=91525&key=user_uploads/1159729/a13a9237-8faa-4f5d-b232-b8fecb82ce62)\n\n### **What will your Control Plane do?**\n\n* OnPrem Installs: Packaging, versioning, deployment templatization, seamless upgrade paths, collecting basic troubleshooting data (logs/metrics), and enforcing licensing to prevent unauthorized use. Its effectively similar to building your terraform scripts for infrastructure, L5 K8s operator on top, writing the deployment script to stitch everything together.\n* BYOC CoPilot: If you want to extend OnPrem model by automating deployments within the customer’s cloud account — across any cloud or region. You have to automate deployments, build the ability to deploy in customers’ account, support Offline mode for security conscious customers\n* PaaS: If you want to extend OnPrem and BYOC to offer self-serve deployments (aka PLG motion) including tenant management, usage-based billing and, automated operations at massive scale — reliably, securely, and cost-effectively\n* SaaS: for companies looking to provide seamless experience by just giving an endpoint that just works. The endpoint is smart enough to handle a broad range of use cases and automatically adjust based on usage to optimize for the cost, scale, performance without compromising on the security or reliability\n* AaaS: If you are looking to build next-gen experience where each customer gets a **personalized experience** based on their organization, workloads, and data or distribute your agents\n\nTo learn more more about different distribution models, see this blog: https://blog.omnistrate.com/posts/152\n\nTo learn more on how we are different than CI/CD, IaC, or PaaS systems: https://omnistrate.com/control-plane-demystified\n\n### **Why we built Omnistrate:**\n\nGiven the complexities of Control Plane, most DIY control planes become fragile, siloed, and a blocker to innovation. Hence, we have built Omnistrate to build your control plane running in your account, so that you don't have to spend years to build and army to operate on undifferentiated things.\n\n### **How does it work:**\n\n![uploaded image](/media/?type=post&id=91525&key=user_uploads/1159729/b3f750a5-13d3-4db1-bded-a6dcc79a186f)\n\nWe take your container images and your cloud account id to run your control plane. From there you can provide the control plane specification using docker compose (we have added extensions) or use our native DSL (domain specific language) to describe your control plane.\n\nWhat if you already started? - No problem. You can start at any point in the journey very easily. We integrate with your existing control plane stack irrespective of your current state. You can keep control of the pieces you like, leave the rest on us and have the peace of freedom to expand into new areas with ease at one-tenth the cost. Examples:\n\n* We can import your Terraform (used for infrastructure management)\n* We can import your Helm, Kustomize, Operator (used for packaging, templatization,\n* We can take your existing automation for deployments to extend you across clouds or regions, build beautiful SaaS and AaaS experiences.\n* and much more..\n\nTo learn more, see our technical blogs:\n\n* https://blog.omnistrate.com/posts/151\n* https://blog.omnistrate.com/posts/150\n* https://blog.omnistrate.com/posts/149\n\nQuick Product Intro videos:\n\n* BYOC CoPilot: https://youtu.be/3D08uFN6ugc\n* PaaS: https://youtu.be/4vDdVf9x_nU, [https://youtu.be/\\_S0UXJh516M](https://youtu.be/_S0UXJh516M%EF%BF%BC-), https://youtu.be/8gUrqrMcjdM\n* For OnPrem, SaaS and AaaS demo, reach out to &lt;[support@omnistrate.com](mailto:support@omnistrate.com)&gt;\n\n### **Use-cases:**\n\n* Build OnPrem Installer, BYOC, PaaS, SaaS or AaaS Products as mentioned above.\n* BYOC CoPilot for your support teams to streamline deployments to accelerate customer onboarding, manage upgrades/versioning to keep track of your customers in an automated way, streamline operations to reduce MTTR and bring consistency in handling the issues. We also support offline mode for security conscious customers to only connect during operational time otherwise they can stay completely disconnected\n* Multi-cloud & BYOC expansion for teams with existing control planes to extend it across clouds — deploy globally and support any deployment model, including BYOC, to run seamlessly in your customers’ accounts\n* Open-source Project to Open-core: Monetize your open-source project without compromising your community-driven values by offering value-added services like streamlined deployments across any cloud/region in your own account or deploy in customers’ accounts, automated operations, seamless infrastructure management\n* Internal PaaS to save cost by using your cloud credits, streamlining deployments and operations, infra management\n\n### **Our ASK:**\n\nIf you are looking to build one or have any questions or would like to discuss more on the topic, we would love to chat more. Here is our calendly: https://calendly.com/omnistrate\n\nIf you would like to stay connected, follow us here: https://www.linkedin.com/company/omnistrate/ or join our community group: http://saasmondays.com/",
        "url": "https://www.ycombinator.com/launches/NoD-omnistrate-copilot-for-platform-teams-to-go-from-app-to-product-in-days-not-years",
        "votes": 17,
        "created_at": "2025-06-22T18:13:13.639Z"
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      {
        "id": 70134,
        "title": "Omnistrate - Cloud platform to SaaSify your open-source project 🚀",
        "tagline": "From your docker image to your multi-cloud SaaS in 1 minute",
        "body": "![uploaded image](/media/?type=post&id=70134&key=user_uploads/1159729/250b8d8a-7e84-40d5-80c6-deb4f4645c83)\n\n### **✨ TL;DR**\n\nOmnistrate is a control-plane as-a-service that **transforms your docker image into a multi-cloud SaaS service**. Let’s say you have an open-source software (e.g. MongoDB), and you want to monetize your invention by building a multi-cloud SaaS solution (e.g. MongoDB Atlas), you can either spend years doing it yourself, or use Omnistrate to do it in no time.\n\nHello everyone - it’s Kamal and Alok here introducing [Omnistrate](https://www.omnistrate.com)!\n\n### **🤯 Problem**\n\n* Going from Software to SaaS can **take months or even years**. Moreover, it can take several attempts for enterprises to find their product-market fit making it **extremely costly** to experiment.\n* Cloud is **complicated** with so many different services, cloud providers, and a rapidly evolving landscape.\n* Building a SaaS service from scratch to do undifferentiated heavy-lifting **distracts** enterprise from the core innovation and adds significant **risk** to their business.\n\n### **💡 Solution**\n\n* Omnistrate makes it **simple, quick** and **cost-effective**, saving years of development time and resources. And we do this, for every cloud provider across the globe out of the box.\n* Omnistrate abstracts away all the cloud complexities and make it **super** **easy** to build cloud-native services.\n* In a fast moving world, enterprises need a platform that allows them to **successfully experiment**, without shifting their focus or taking a massive business risk.\n\n### **📜 Our Story**\n\nI was part of the AWS founding team, and built **more than half-a-dozen cloud services** over the years (2007-2020) across different domains. During my early days at AWS, I was one of the **original authors of AWS control plane** that was used to host open-source technologies by numerous AWS services.\n\nAlok and I met at AWS Aurora when I was running the database engineering for a **billion dollar SaaS business**, managing millions of databases. Alok was the original technical author of Aurora Serverless, which revolutionized the data systems space. He then went to Cisco to scale networking pipeline (packets-per-second) on AWS by 10-15x.\n\nWe reunited again at Confluent in 2020 where I ran the Kafka engineering at Confluent and grew their multi-cloud Kafka offering to **200MM+ ARR business managing over 100,000 containers**. Alok played a key role there in scaling Kafka Cloud throughput by 5x, and reducing Kafka Cloud latencies by 10x to really distinguish Confluent Kafka offering from other vendors.\n\nWith Omnistrate, we want to **share our learnings into a fully automated platform** by getting rid of the undifferentiated work and making it simple for anyone to build a SaaS service.\n\n### **⚒️ How it works**\n\n![uploaded image](/media/?type=post&id=70134&key=user_uploads/1159729/57ff5a13-a71a-4853-8370-f46493442817)\n\nYou start by simply bringing your docker image. Omnistrate, from then on, will seamlessly build your SaaS and runs it on auto-pilot. At every step of the process, you retain full control, the ability to innovate on your product and the ability to integrate with your favorite tools or services.\n\n### **🫶 Ask**\n\nIf you are **looking to SaaSify your open-source (or any other software)**, please sign-up [here](https://omnistrate.com/demo) and we will create an account for you to provide a white glove experience. We will then come on a quick call to get you up and running in a few minutes.\n\nIf you know someone who could benefit, please reach out to us at: [founders@omnistrate.com](mailto:founders@omnistrate.com)\n\nIf you are excited about the SaaS space, please join our [Slack](https://join.slack.com/t/cloudnative-u5h1399/shared_invite/zt-1qf3cgi37-lCV1vKJlrBioqGuVjKBtyw) community\n\n### **⭐️ Our YC deal:**\n\nPlease see this: <https://bookface.ycombinator.com/deals/1677>\n\nFor any questions on the deal, please reach out to us at [yc@omnistrate.com](https://mailto:yc@omnistrate.com)\n\nThank you! Omnistrate Team ✌️\n\nCEO, Kamal Gupta",
        "url": "https://www.ycombinator.com/launches/IFC-omnistrate-cloud-platform-to-saasify-your-open-source-project",
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        ]
      },
      {
        "id": 85769,
        "title": "Senior Platform Engineer",
        "url": "https://www.ycombinator.com/companies/cosine/jobs/dUj3uLp-senior-platform-engineer",
        "location": "London, England, GB",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Backend",
        "salary_range": "£75K - £100K GBP",
        "equity_range": "",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Amazon Web Services (AWS)",
          "Kubernetes"
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      },
      {
        "id": 85770,
        "title": "Senior Infrastructure Engineer",
        "url": "https://www.ycombinator.com/companies/cosine/jobs/yBOX3vI-senior-infrastructure-engineer",
        "location": "London, England, GB",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Devops",
        "salary_range": "£75K - £100K GBP",
        "equity_range": "",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Amazon Web Services (AWS)",
          "Kubernetes"
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      },
      {
        "id": 85772,
        "title": "Product Engineer",
        "url": "https://www.ycombinator.com/companies/cosine/jobs/9KEolFw-product-engineer",
        "location": "London, England, GB",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$70K - $90K",
        "equity_range": "",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 88029,
        "title": "Senior Developer Evangelist",
        "url": "https://www.ycombinator.com/companies/cosine/jobs/12jJ07r-senior-developer-evangelist",
        "location": "London, England, GB / Remote",
        "type": "Full-time",
        "role": "Marketing",
        "role_type": null,
        "salary_range": "£60K - £90K GBP",
        "equity_range": "0.10% - 0.20%",
        "experience": "3+ years",
        "visa": "US citizenship/visa not required",
        "skills": []
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    ],
    "news": [
      {
        "title": "Move over, Devin: Cosine's Genie takes the AI coding crown | VentureBeat",
        "url": "https://venturebeat.com/programming-development/move-over-devin-cosines-genie-takes-the-ai-coding-crown/",
        "date": "Aug 12, 2024"
      }
    ],
    "launches": [
      {
        "id": 99817,
        "title": "Cosine 3.0  - one coding agent across every surface your team uses",
        "tagline": " (use your existing Claude, OpenAI, Copilot subscription)",
        "body": "\n![uploaded image](/media/?type=post&id=99817&key=user_uploads/797223/28afdae8-76ad-49c1-a761-3e89100fea74)\n\nTLDR: Cosine is built for the point where coding agents usually start to break down: longer tasks, multiple threads of work, team handoff, and code you still need to maintain later.\n\nPS. you can use your Claude Code, OpenAI and Copilot subscriptions (Don’t tell OpenCode or OpenClaw :P )\n\n```\nFor OpenAI and Copilot subscriptions:\nLaunch Cosine CLI \nCtrl+p and choose ChatGPT or Copilot subscription model \nYou'll get redirected to ChatGPT or Copilot website for auth\n\n_____\n\nFor Claude: \nMake sure you have a Claude Pro or Max subscription and have it installed on your local environment\n\nInstall the Cosine CLI — cosine.sh/cli (mac, windows and Linux supported)\n\nCtrl+p and choose the Claude Max Subscription (it works with both Claude pro and max)\n\nYour Claude Code subscription is recognised automatically — Cosine uses the actual Claude Code binary, so no API key needed\n\nRun cos in any repo — your Claude subscription quota is used directly, no extra Cosine billing for model usage)\n```\n\n<https://youtu.be/F61PCXvXd3Y>\n\n**More info:**\n\nIf you’re already deep into AI coding tools, you probably know the feeling:\n\nYou start with quick wins in terminal, then pretty soon you want the same speed on bigger tasks, across more than one thread of work, without losing track of what the agent is actually doing or ending up with code your team has to clean up later.\n\nThat’s basically why we built Cosine 3.0\n\nCosine is one coding agent across CLI, VS Code, desktop, and cloud. So you can start with a quick local task, pick it up somewhere else later, or spin up parallel agents when the job gets bigger, without hopping between separate tools or losing context.\n\nWhat we kept caring about as we built it was pretty simple:\n\nWe wanted something that still feels fast and direct, but gives you more visibility and more control once the work stops being a toy problem.\n\nSo you can inspect changes properly.\n\nSo you can follow what happened.\n\nSo you can undo things cleanly.\n\nSo you can run multiple threads of work when one agent is not enough.\n\nSo the whole thing still makes sense when other people on your team have to touch the code.\n\nA lot of tools feel great right up until you want them to do more than one thing, in more than one place, on code that actually matters.\n\nWe wanted to build the version that keeps working after that point.",
        "url": "https://www.ycombinator.com/launches/Pxx-cosine-3-0-one-coding-agent-across-every-surface-your-team-uses",
        "votes": 5,
        "created_at": "2026-04-16T15:03:34.648Z"
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    "id": 27844,
    "name": "Cloudchipr",
    "slug": "cloudchipr",
    "former_names": [
      "Cloudchipr Inc"
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    "website": "https://cloudchipr.com/",
    "all_locations": "Berlin, Berlin, Germany",
    "long_description": "Cloudchipr is an actionable FinOps platform that keeps multi-cloud spend under control 24/7 with AI agents.",
    "one_liner": "The #1 Actionable FinOps Platform",
    "team_size": 25,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1667473991,
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    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2023",
    "status": "Active",
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    "regions": [
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      "Europe",
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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/cloudchipr",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/cloudchipr.json",
    "year_founded": 2022,
    "city": "Berlin",
    "country": "DE",
    "linkedin_url": "https://www.linkedin.com/company/cloudchipr",
    "x_url": "https://twitter.com/cloudchipr",
    "fb_url": "https://facebook.com/cloudchipr",
    "cb_url": "https://www.crunchbase.com/organization/cloudchipr",
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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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        "user_id": 1159850,
        "full_name": "Ashot Ayvazyan",
        "title": "Founder",
        "founder_bio": "Ashot is an engineer and entrepreneur with a computer science background and 14 years of experience in the design, implementation, and operations of distributed computing systems based on cloud and bare metal infrastructures. Now he is the Co-founder and CEO at Cloudchipr, which helps companies to reduce their cloud costs with infrastructure optimisation automation workflows. ",
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        "linkedin_url": "https://www.linkedin.com/in/ashotayvazyan/",
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      {
        "user_id": 1161211,
        "full_name": "Suren Marashlyan",
        "title": "Founder",
        "founder_bio": "Suren is a software engineer and entrepreneur with a math and computer science background. He has 10+ years of experience in computer software design and development. Now he is the Co-founder and VP of Engineering at Cloudchipr, which helps companies to reduce their cloud costs with infrastructure optimization automation workflows.",
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    "news": [],
    "launches": [
      {
        "id": 69761,
        "title": "Cloudchipr streamlines the cloud operations",
        "tagline": "Cloudchipr - cloud costs observability, management and automation platform",
        "body": "### **TL;DR Instead of wasting runway on the cloud, sweating about your bottom line and limiting your developers, let Cloudchipr take care of optimizing your cloud usage and getting the most out of it.**\n\nHey everyone we are the founders of [Cloudchipr](https://cloudchipr.com/) 🙂\n\n![uploaded image](/media/?type=post&id=69761&key=user_uploads/1159850/9a6a6c4e-e473-4927-823b-28d84a6d8e1f)\n\n**Ashot** (left) managed some of the largest cloud infrastructures in the world. A distributed computing systems and cloud guru, who can smell coffee ☕ and sniff expensive infrastructures 📈 from at least 1000 feet away 😄\n\n**Suren** (right) worked on platforms serving 100,000,000s users from all over the world while at Picsart, AWS and Wayfair. A foodie with the power of Spring Boot as his spirit animal 🐩 😄\n\nWe got a lot of battle scars figuring out what’s the best way to operate your cloud. Now we’ve built Cloudchipr so that you don’t have to! 🚀\n\n### ❌ **The Problem**\n\nAll clouds make it very easy to start using resources. That’s how they are designed and that’s why they won. Problem is, that freedom very quickly turns into a mess eventually hurting the bottom line and becoming an operational hurdle.\n\n**Where it hurts Product and Engineering:**\n\n* Services and resources sprawl out of control across various geographies and cloud regions.\n* Resources get wasted to ensure developer convenience (dev machines run over weekends, holidays and non-working hours alike).\n* Routine operational maintenance becomes a burden and a time consuming activity for expensive DevOps and SRE engineers.\n* Every launched resource in the cloud becomes a monument - once it’s there no one risks to touch and it lingers around forever.\n\n**Where it hurts the Business side:**\n\n* Accountability and trackability becomes an issue: ask any series B (or later stage) company startup CFO how much a particular project costs on a cloud and see them roll their eyes.\n* Cloud is treated as a black box. Although being one of the largest cost centres finance has little visibility into what is actually going on. They are expected to foot the bill with 0 insights or understanding how the money is actually spent.\n* Very hard to forecast spend and act on if it gets out of hand.\n\n### **🪄 The Solution**\n\nWatch our [Demo Video](https://www.youtube.com/watch?v=0QLy74eGnLg)\n\nCloudchipr is an AWS qualified SaaS platform (we also support GCP and Azure) which provides a suite of powerful tools for cost tracking, resource management, and automation. It simplifies cloud operations, streamlines DevOps workflows while giving financial visibiliy, predictability and control. \n\n✅ **Cost Optimization by granular cost tracking and reporting.** It allows to monitor cloud expenses in real-time and optimize their usage to reduce waste. \n\n✅ **Resource Management:** Cloudchipr provides a centralized dashboard that provides full visibility into their cloud infrastructure across all geographies and cloud regions.\n\n✅ **Automation workflows:** Cloudchipr's automation features enable teams to streamline their DevOps workflows and automate routine operational tasks. With Cloudchipr, businesses can set up notifications and actions based on their criteria and free up valuable time and resources for other important tasks.\n\n**For example:**\n\n* If a resource is underutilized, Cloudchipr will notify the owner to take an action.\n* If there are resources without an owner, a slack message will be sent.\n* Stops expensive GPU nodes based on configurable usage criteria (e.g. idle more than 3 hours)\n* Stops/Starts the selected dev databases and virtual machines at night and on weekends\n* Takes care about resources being properly tagged.\n\n✅ **LAST BUT NOT LEAST:** It’s 2023, so you should be able to talk to your cloud and your cloud should talk back!  We are launching the first version of **CloudChat -** an interactive Natural-Language interface for querying, reporting and setting automations for your cloud. \n\nCloudchipr automates the cloud cost saving and reporting, and helps the finance and engineering departments save money and time by removing the friction around the costs saving. We do that by automation workflows which constantly check all the cloud resources, take configurable actions and report about the progress.\n\n### **Get started now:**\n\n* Try it for free at [cloudchipr.com](http://cloudchipr.com)",
        "url": "https://www.ycombinator.com/launches/I9B-cloudchipr-streamlines-the-cloud-operations",
        "votes": 888,
        "created_at": "2023-02-28T17:28:41.075Z"
      }
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  },
  {
    "id": 27867,
    "name": "DataSuite",
    "slug": "datasuite",
    "former_names": [
      "Extensional AI",
      "Extensional",
      "Extensional AI",
      "Anarchy AI",
      "Anarchy",
      "Anarchy Labs",
      "TruthSuite"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/98dc541fc5fbbef1e6c9baee61264602e4e64531.png",
    "website": "https://truthsuite.com",
    "all_locations": "New York City, NY, USA; Remote",
    "long_description": "DataSuite provides a way to manage and collect multi-terabyte multi-media datasets, and train generative models (diffusion, gan, interactive video) models based on them.  \r\n\r\nWe make it trivial for non-technical builders to create their own networks by providing an instant way to collect with AI without worrying about data formats, unzipping power, caching, or data locality.",
    "one_liner": "Dataset Management for AI Trainers",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Legal",
    "launched_at": 1669080392,
    "tags": [
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      "Generative AI",
      "Machine Learning",
      "DevOps",
      "AI"
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    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2023",
    "status": "Active",
    "industries": [
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      "Legal"
    ],
    "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": [
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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": "Developers need an easy way to collaborate on the step-by-step process of gathering data and training AI models. Out of the box, LLMs can be **&gt;100b** parameters and require **trillion** token datasets. This is more than most organizations are equipped to handle: a few years ago, few had heard of LLMs, and now organizations are scrambling to get ahold of GPUs to train and run them. The famous models are furthermore _proprietary_. Privacy, quality and efficiency needs are leading organizations to _train their own models._ \\\\While training these models, developers are constantly adjusting their datasets. As their projects grow, it becomes harder to keep track of the changes, and figure out what data and models to use and track these things in production."
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    "url": "https://www.ycombinator.com/companies/datasuite",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/datasuite.json",
    "year_founded": 2022,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/datasuite",
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    "github_url": "https://github.com/anarchy-ai",
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        "user_id": 129728,
        "full_name": "Matthew Mirman",
        "title": "Founder",
        "founder_bio": "Before founding DataSuite, Matt received his PhD in AI from ETH Zurich in 2022 where he scaled verified machine learning from working on 10 neuron toy nets in hours to 100m neuron nets in milliseconds and invented differentiable abstract interpretation and provable training.  Before this, he worked at apple on JS compiler optimizations that saved the world a billion dollars in time wasted waiting for pages to load, and before that got an MS from CMU on meta-programming CoC logic languages.",
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        "linkedin_url": "https://www.linkedin.com/in/matthewmirman/",
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      {
        "user_id": 1151451,
        "full_name": "James Spoor",
        "title": "Founder",
        "founder_bio": "A Generalist, with a passion for learning! After living in multiple countries hustling, building and creating, I ended up in Switzerland diving into the deep tech world where I worked at DeepCode, ml on static analysis which was then acquired by Snyk a cyber security unicorn. A fun fact about me is I was once a professional climber. My superpower is caring deeply and understanding through questions... there will be many questions!\n",
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      {
        "id": 69294,
        "title": "Anarchy 🧪 - LLM infrastructure for building conversational applications 🏗️",
        "tagline": "Anarchy provides companies with their own LLM endpoints that can call any APIs",
        "body": "Greetings YC community! We’re Matt and James, the founders of Anarchy. We’ve been working in AI for a long time (Matt just finished a PhD working on formal methods in deep learning) and have become experts in taming LLMs. We started Anarchy to share these advances with devs who want to use LLMs in production.\n\n### **Problem**\n\nWhile LLMs are beginning to be used as universal text interfaces, developers and prompt engineers are beginning to want consistent and reliable LLMs with agency: LLMs which can search through their ever-changing databases, be able to book meetings, and generally make calls to their APIs. However, coaxing LLMs to behave consistently is black magic requiring constant vigilance, and relying on a single provider can be a risky point of failure.\n\n### **Solution**\n\nOur platform abstracts away the unpredictable work of researching ideal prompts so developers can focus on building business logic: Provide your API and its description, and your LLM-keys, and anarchy will provide you an LLM endpoint (or web-interface chatbot) that can answer questions and solve problems using your API and load-balance between LLMs.\n\n[Here's a short product demo](https://www.youtube.com/watch?v=Qcv_wrCYRds)\n\n![uploaded image](/media/?type=post&id=69294&key=user_uploads/129728/2ecd3d46-6642-49b8-bdf7-8f655f59078e)\n\n### **Ask**\n\nIf this excites you (or anybody you might know, YC or not) and you’d like to try our product, please contact us by [signing up.](https://forms.gle/5rqU282gUKmKPmjm9)\n\nIf you want to have a chat about LLM tech or ask us questions directly, feel free to join our discord: <https://discord.gg/qaFf7S373c> \n\nWe’re also in the process of building up our [twitter](https://twitter.com/anarchy_ai_inc) and [linkedin](https://www.linkedin.com/company/extensional) and would appreciate a follow 🙂!",
        "url": "https://www.ycombinator.com/launches/I1e-anarchy-llm-infrastructure-for-building-conversational-applications",
        "votes": 28,
        "created_at": "2023-02-15T01:33:56.036Z"
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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,
    "tags": [
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    "status": "Acquired",
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    "year_founded": 2022,
    "city": "Pittsburgh",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/outerbase",
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        "user_id": 1247130,
        "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",
        "x_url": "https://www.twitter.com/burcs",
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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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        "linkedin_url": "https://www.linkedin.com/in/brayden-wilmoth/",
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        "id": 69291,
        "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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    "website": "https://co.dev/?ref=YC",
    "all_locations": "",
    "long_description": "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.",
    "one_liner": "Turn your ideas into full-stack apps",
    "team_size": 2,
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        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/uladzislauradkevich/",
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        "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.",
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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",
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        "votes": 22,
        "created_at": "2024-11-29T23:15:00.169Z"
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    "name": "Langfuse",
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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.",
    "one_liner": "Open source LLM engineering platform",
    "team_size": 26,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1673911015,
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    "year_founded": 2022,
    "city": "Berlin",
    "country": "DE",
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    "primary_partner": {
      "name": "Gustaf Alstromer",
      "url": "https://www.ycombinator.com/people/gustaf-alstromer"
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      {
        "user_id": 860580,
        "full_name": "Marc Klingen",
        "title": "Founder/CEO",
        "founder_bio": "Marc has diverse experience across Product, Sales, Business Intelligence and full-stack engineering at companies from large (Google, DHL) to early stage startups. He graduated within the top 1% of his Masters in Management and Computer Science from Technical University Munich. Besides that, he loves to hack on personal project and connect with other builders (something he does not get to too much right now).",
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        "full_name": "Maximilian Deichmann",
        "title": "Founder",
        "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",
        "title": "Founder",
        "founder_bio": "co founder of langfuse with max & marc!",
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        "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"
      },
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        "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"
      }
    ],
    "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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    "id": 27871,
    "name": "Extend",
    "slug": "extend",
    "former_names": [
      "CrowdView"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/184d30d91903380caada7f52cd7cd7992759e07b.png",
    "website": "https://www.extend.ai/",
    "all_locations": "New York City, NY, USA",
    "long_description": "Parse, extract, and split your hardest documents with unmatched accuracy. Read any layout with specialized vision models, and ship reliable pipelines in minutes, not months.",
    "one_liner": "Production-ready document processing",
    "team_size": 25,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1679062598,
    "tags": [
      "Documents",
      "Developer Tools",
      "B2B",
      "AI"
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    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2023",
    "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/extend",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/extend.json",
    "year_founded": 2023,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/extend-app",
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    "primary_partner": {
      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
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        "user_id": 137869,
        "full_name": "Kushal Byatnal",
        "title": "Founder",
        "founder_bio": "2x technical founder interested in making it easy to build internal tools. Previously, I worked as an early engineer at Brex and then cofounded Stir, a creator fintech company that grew to hundreds of millions in payment volume.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/kushal-byatnal-92a33085/",
        "x_url": "https://twitter.com/kushalbyatnal",
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      {
        "user_id": 1121959,
        "full_name": "Eli Badgio",
        "title": "Founder",
        "founder_bio": "Co-founder @ Extend",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/eli-badgio/",
        "x_url": "https://twitter.com/ebadgio_",
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    "jobs": [],
    "news": [
      {
        "title": "Extend Raises $17 Million to Build the Document Processing Cloud | Extend",
        "url": "https://www.extend.ai/resources/series-a",
        "date": "Jun 17, 2025"
      }
    ],
    "launches": [
      {
        "id": 87403,
        "title": "📄 Extend - Unified Document Processing Platform",
        "tagline": "Turn messy documents into high quality data, achieve > 95% accuracy, and ship custom document pipelines in days, not months.",
        "body": "![uploaded image](/media/?type=post&id=87403&key=user_uploads/137869/a0dc2100-5072-45e4-92c3-d6088bf15bdf)\n\n# What is Extend in a nutshell?\n\nExtend provides document processing infrastructure, tooling, and APIs that enable technical teams to handle complex documents with state-of-the-art accuracy and reliability.\n\nCompanies like Chime, Brex, Flatiron Health, Opendoor, and Checkr use Extend for mission-critical document pipelines to achieve &gt; 95% accuracy on their hardest docs, and go live in days (not months).\n\n[Sign up to get started](https://dashboard.extend.ai/)\n\n# The Problem\n\nProcessing complex documents **is hard.** You have to deal with:\n\n* Difficult layout elements like tables, charts, handwriting, and signatures\n* Lengthy documents needing chunking and merging strategies\n* Extracting structured data with &gt; 95% accuracy across a variety of input formats\n* Optimizing outputs for LLM readability\n* Ensuring accuracy and reliability in production for critical use cases\n\n# Our Solution\n\nThere are plenty of OCR and document parsing options on the market. However, we noticed customers still struggling to deploy complex use cases when accuracy requirements are high (&gt; 95%). This is because OCR and parsing is only one part of the problem, and real world use cases need to bridge the gap between raw outputs and production-ready data.\n\nExtend uniquely solves this by unifying models, infrastructure, and tooling into a single platform for end to end document processing.\n\nThis includes:\n\n* Process any document format with state-of-the-art parsing powered by VLMs and OCR\n* Capture precise data with multi-step extraction powered by semantic chunking, bounding boxes, and citations\n* Tackle the most complex use cases with processing modes for document parsing, classification, extraction, and splitting\n* Deploy faster with low code tooling that empowers your entire team to quickly iterate, review results, and improve accuracy\n* Continuously improve results with fine-tuning pipelines that turn reviewed corrections —&gt; custom models\n\nFor example, Extend’s built-in evaluation tools to help you benchmark performance, improve accuracy, and deploy with confidence.\n\n![uploaded image](/media/?type=post&id=87403&key=user_uploads/137869/801788f4-a72c-4d1a-8dd0-d4e9f9f18436)\n\nOur customizable document splitter identifies each distinct section and their relationships according to your instructions. This is critical when ingesting lengthy documents (or multi-document packages).\n\n![uploaded image](/media/?type=post&id=87403&key=user_uploads/137869/f0c2726e-b58f-42fc-8a9a-2b5294c5751d)\n\nHere’s an example of zero-shot table extraction on a complex healthcare doc. What enables this is vision models specialized for tabular structures, working alongside our bounding box citations & human-in-the-loop review system.\n\n![uploaded image](/media/?type=post&id=87403&key=user_uploads/137869/df2d9e80-2ade-4730-98ed-f0a15f942450)\n\n# Hear it from our customers\n\nMatt Hodgson, CTO at Vendr:\n\n> We did a bakeoff, and Extend had the best results of any solution on the market. It eliminates an entire class of engineering problems around accuracy we don’t want to worry about.\n\nAdam Litton, Staff Engineer at Checkr:\n\n> Extend eliminates the maintenance cost of model tuning, scoring, evaluations, and more. We’re able to focus on our core experience instead of managing the infra.\n\nFabio Fleitas, CTO at Tesorio:\n\n> I don’t know what you guys are doing under the hood, but it’s so much more accurate than any other tool we’ve tried.\n\n# Get Started\n\nIf you’re building document processing pipelines with high accuracy requirements, get in touch with us!\n\n* [Book a demo](https://extend.cal.com/extend/extend-intro-call)\n* Email us at [founders@extend.app](mailto:founders@extend.app)",
        "url": "https://www.ycombinator.com/launches/Mjj-extend-unified-document-processing-platform",
        "votes": 34,
        "created_at": "2025-02-04T15:46:20.176Z"
      },
      {
        "id": 73038,
        "title": "Extend - Build AI-powered workflows for unstructured data",
        "tagline": "Intelligently process documents, emails, images, and more with powerful tools for extraction, classification, and analysis.",
        "body": "**TLDR;** Extend makes it easy to process unstructured data in the form of PDFs, images, emails, and more. Build workflows that combine LLMs, business logic, integrations, and human-in-the-loop confidence - all without a line of code.\n\n![uploaded image](/media/?type=post&id=73038&key=user_uploads/137869/8f86f279-0f42-4ab8-891d-a0ef4df19126)\n\n**The problem**\n\nVast amounts of data is often locked away inside messy PDFs, images, or emails and companies often build entire operational workflows around trying to manage and understand it. Humans have to do the tedious manual work of organizing and parsing all of it, but that’s just the start. To make use of that data, workflows have to be built around classification, validation, deduplication, fraud & spam checks, anomaly detection, manual audits, and so much more.\n\n**How Extend works**\n\nExtend comes with a set of building blocks to manage workflows around unstructured data. It can be used both:\n\n* **internally** to manage and automate complex operations (e.g. back office ops/fraud/support/finance use cases)\n* **externally** in your product (e.g. drop in a embeddable component to collect, classify, and validate documents uploaded by your end users in real time)\n\nHere’s how:\n\n**Combine** LLMs with business logic, validations, and integrations.\n\n![uploaded image](/media/?type=post&id=73038&key=user_uploads/137869/ff3801ab-d622-4938-92bd-417d55d22fec)\n\n**Build** custom workflows that mirror your internal operations, and let them run on autopilot.\n\n![uploaded image](/media/?type=post&id=73038&key=user_uploads/137869/caccc352-e74d-45cb-a579-581746f4bc00)\n\n**Deploy** confidently into production with built-in confidence scoring and human-in-the-loop flows.\n\n![uploaded image](/media/?type=post&id=73038&key=user_uploads/137869/2c18cecb-152f-4c89-9d2f-0b9648b07aba)\n\n**Integrate** via our API, dashboard, or even embed Extend natively in your user-facing product.\n\n![uploaded image](/media/?type=post&id=73038&key=user_uploads/137869/3f48afc3-0b2f-46a0-b066-bf3ded6cf8c6)\n\n\n### **Get Started**\n\n[**Sign up**](https://www.extend.app/) on our website! Right now, we’re running a special deal + priority onboarding and support.\n\n### **Asks**\n\n* We’re growing quickly and looking to hire ex-founders (please reach out)!\n* Follow us on [**Twitter**](https://twitter.com/extendhq) and [**LinkedIn**](https://www.linkedin.com/company/extend-app/?viewAsMember=true) to stay in touch\n* We love any and all kinds of feedback",
        "url": "https://www.ycombinator.com/launches/J02-extend-build-ai-powered-workflows-for-unstructured-data",
        "votes": 26,
        "created_at": "2023-07-13T19:36:11.447Z"
      },
      {
        "id": 70372,
        "title": "Extend - Build internal Chrome extensions that give your team superpowers",
        "tagline": "Ship internal tools that reduce context switching, eliminate copy/pasting, and customize any website your team relies on.",
        "body": "### **TL;DR**\n\nExtend is a low code developer tool that makes it easy to build internal chrome extensions for your company.\n\nFor example, **support teams** can solve tickets faster with custom buttons that call internal APIs, draft responses, and bring GPT-4 into the loop.\n\n![uploaded image](/media/?type=post&id=70372&key=user_uploads/137869/d1322b76-0479-474e-b51d-96e26317ce37)\n\n**Sales teams** can customize their CRM with real-time database queries and UI overlays.\n\n![uploaded image](/media/?type=post&id=70372&key=user_uploads/137869/7db4d9cb-69f4-4308-a918-71f49991ffc5)\n\n**Give your company superpowers in 15 minutes.**\n\nExtend gives your developers building blocks so they can build these types of workflows in 15 minutes.\n\nWe provide:\n\n1. tons of pre-built modules (e.g. extract info from the page via GPT-4, inject a button in to the DOM)\n2. beautiful UI components\n3. secure connections to your database + internal APIs\n4. one-click instant deployment to your team\n\nJust write your custom business logic and wire up the flow, we’ll handle the rest.\n\n**Extend is a better way of building internal tools.**\n\nI’ve spent years working in fintech and built a ton of internal tooling for support and operations teams. But using most internal tools today requires a ton of copy/pasting and context switching, which any support or operations team will tell you is the bane of their existence. Chrome Extensions enable your internal tools to live _inside_ the apps where your teams already spend 90% of their time today.\n\nAnd now with GPT-4, your teams can activate supercharged workflows within the context of your existing tools.\n\n**Get Started**\n\n* For the first 5 companies that [sign up](https://tally.so/r/w2Xx5L), we’ll build your internal chrome extension for you with **no engineering resources needed on your end**!\n* Send a note to [kushal@extend.app](mailto:kushal@extend.app) if you have feedback / want to chat",
        "url": "https://www.ycombinator.com/launches/IJ2-extend-build-internal-chrome-extensions-that-give-your-team-superpowers",
        "votes": 75,
        "created_at": "2023-03-17T14:16:56.849Z"
      }
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    "id": 27875,
    "name": "Aqueduct",
    "slug": "aqueduct",
    "former_names": [
      "Iliad"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/9942f88e0ad31a3c3da6a0f408886f28f73dabbd.png",
    "website": "https://aqueduct.sh",
    "all_locations": "Pittsburgh, PA, USA",
    "long_description": "Aqueduct is a browser-based procedural material engine and editor.\r\n\r\nThink Substance Designer, with live-sync to Unreal, agents that can read and edit material graphs, and shareable links to those graphs.",
    "one_liner": "Create, edit, and share procedural material graphs.",
    "team_size": 1,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1674524413,
    "tags": [
      "Developer Tools",
      "Gaming",
      "Design Tools",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2023",
    "status": "Active",
    "industries": [
      "B2B"
    ],
    "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/aqueduct",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/aqueduct.json",
    "year_founded": 2022,
    "city": "Pittsburgh",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/92719250/",
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        "full_name": "Matthew Turnshek",
        "title": "Founder",
        "founder_bio": "Matthew Turnshek is the founder and CEO of Aqueduct.",
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        "linkedin_url": "https://www.linkedin.com/in/matthew-turnshek-4bb618174/",
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    "id": 27876,
    "name": "Propexo",
    "slug": "propexo",
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    "website": "https://propexo.com",
    "all_locations": "Boston, MA, USA",
    "long_description": "Propexo lets engineers build, test, and launch CRE software integrations in days, not months. We modernize the developer experience for our customers, providing clear documentation and robust infrastructure to support the needs of property owners, property managers, & proptechs.",
    "one_liner": "Plaid for Commercial Real Estate",
    "team_size": 6,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1667590103,
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      {
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        "answer": "Plaid for the Property Management Industry"
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    "url": "https://www.ycombinator.com/companies/propexo",
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    "year_founded": 2022,
    "city": "Boston",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/getpropify/",
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      "name": "Brad Flora",
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    "founders": [
      {
        "user_id": 970556,
        "full_name": "Nick Johnson",
        "title": "Founder",
        "founder_bio": "Hacker & builder. Currently focused on building the unified API to accelerate innovation in real estate.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/nickolasjohnson/",
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        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/322b52181abcab3499663c8c57b5b28260ed3079.jpg"
      },
      {
        "user_id": 997737,
        "full_name": "Ben Keller",
        "title": "Founder",
        "founder_bio": "Started my career in real estate private equity before getting the tech bug. Was the first PM building HubSpot's CRM, now trying to change the proptech landscape with Propify. In my free time I love to run, read, play golf, and travel to new places.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/ben-keller-24309644/",
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    "news": [
      {
        "title": "Property Management Startup Propify Closes $3.3M Seed Funding Round – Commercial Observer",
        "url": "https://commercialobserver.com/2023/10/property-management-propify-seed/",
        "date": "Oct 10, 2023"
      }
    ],
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      {
        "id": 69838,
        "title": "Propify: Plaid for Real Estate 🏢",
        "tagline": "Propify's API enables companies to integrate with the data that powers the world of professionally managed real estate.",
        "body": "# 📚 TL;DR\n\n**The professionally managed real estate market is massive**. Unfortunately, it is difficult to sell products or services to this market because the systems of record are legacy software vendors with bad APIs. Propify's API allows companies to integrate with these systems in weeks, not years.\n\n![uploaded image](/media/?type=post&id=69838&key=user_uploads/997737/fbfa8b9c-aac6-449d-af99-d9696611c11e)\n\nHey everyone! We're Remen, Nick, and Ben from [Propify](http://www.getpropify.com). We entered the proptech world in 2020 and quickly realized the single biggest problem was accessing the data from the major systems of record.\n\n# ⚠️ **The Problem: Fragmentation and Legacy Software** \n\nThe managed real estate market includes 290k companies, 80M tenants, and $300B in rent payments. This market is not only for \"proptechs.\" Amazon, Lowes, and Progressive Insurance actively sell into the space. \n\nThe most significant headwind to innovation has been the effort to integrate with the systems of record: Property management software. \n\nIt is a fragmented market where SOAP APIs are the norm and documentation is rarely available. In addition, companies like Zuma (S21) have entire teams managing these integrations - they often take years to build the complete list.\n\n  \n\n# 👨‍🔬 **The Solution: A unified API**\n\nPropify's API and unified data model allow a company to integrate with the six most prominent players in weeks.\n\nAdditionally, we provide modern developer tooling like Webhooks, which is largely missing from the native integrations.\n\n# 👨‍🔬 **How it works:**\n\nWith Propify, you integrate once to access all of our supported integrations. In addition, our REST API is well documented, and we simplify integrating and scaling your company with additional tooling that your engineers will love!\n\n![uploaded image](/media/?type=post&id=69838&key=user_uploads/997737/49132478-7f99-47d2-985d-562b77f4f415)\n\nA company can manage the systems and integrated buildings through its Propify Portal. They can also manage users, export datasets, and set up Webhooks.\n\n![uploaded image](/media/?type=post&id=69838&key=user_uploads/997737/d543d0d9-66a4-43af-91b1-774a8a9867e1)\n\n\n# 🙋 **Propify is for: Almost Everyone**\n\nThis market is significant - tens of millions of renters live in professionally managed housing + hundreds of thousands of property management companies that need services. Examples of tools that do well in the space:\n\n🏢 Proptech\n\n🏗 Construction tech\n\n💸 Payments\n\n👨‍💼 Insurance\n\n🖥 Marketing\n\n🏷 Sales\n\n🎧 Support\n\n✅ Productivity\n\n📈 Reporting\n\n📞 Communication tooling\n\n🚗 Transportation\n\n❓ Unsure? Reach out at [hello@propifyapp.com](mailto:hello@propifyapp.com)\n\n# 😇 **Our Ask:**\n\n* Reach out to [sales@propifyapp.com](mailto:sales@propifyapp.com) and say hi!\n* Send any proptech company you know our way.",
        "url": "https://www.ycombinator.com/launches/IAQ-propify-plaid-for-real-estate",
        "votes": 21,
        "created_at": "2023-03-01T20:02:16.632Z"
      }
    ]
  },
  {
    "id": 27881,
    "name": "Inkeep",
    "slug": "inkeep",
    "former_names": [
      "inkeep"
    ],
    "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"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Winter 2023",
    "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/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": [
      "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/c9c0852fd8b6bce98922c3f075583b77aa63e8d4.png"
    ],
    "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",
    "x_url": "",
    "fb_url": null,
    "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": [
      "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/3225de93482728857cea8dcee7b643093fc1979c.png"
    ],
    "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",
        "x_url": "",
        "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": 27893,
    "name": "BuildJet",
    "slug": "buildjet",
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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.",
    "one_liner": "High-performance computing cloud",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1677520362,
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      "Fully Remote"
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    "stage": "Early",
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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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        "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.",
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        "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!",
        "url": "https://www.ycombinator.com/launches/I8w-buildjet-change-1-line-get-2x-faster-cheaper-github-action-builds",
        "votes": 45,
        "created_at": "2023-02-28T15:31:40.834Z"
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    "id": 27909,
    "name": "Magicflow 𐂂",
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      "SAPI 𐂂"
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    "website": "https://magicflow.ai",
    "all_locations": "Tel Aviv-Yafo, Tel Aviv District, Israel",
    "long_description": "Prompt engineers, visual artists and AI data scientists are using Magicflow to run experiments at scale and perfect their pipelines\r\n\r\nOur product is ready to use: https://console.magicflow.ai try it out! we have some preloaded examples you can try.\r\n\r\n🤟 Talk to us about anything! We love meeting new people https://calendly.com/magicflowai/",
    "one_liner": "The Gen AI evaluation and curation platform",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1673392871,
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      "Generative AI",
      "AI"
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    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2023",
    "status": "Inactive",
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    "regions": [
      "Israel",
      "Middle East and North Africa",
      "Remote",
      "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/magicflow",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/magicflow.json",
    "year_founded": 2022,
    "city": "Tel Aviv-Yafo",
    "country": "IL",
    "linkedin_url": "",
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    "primary_partner": {
      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
    },
    "founders": [
      {
        "user_id": 1006285,
        "full_name": "Yarden Shem Tov",
        "title": "Founder",
        "founder_bio": "Yarden likes to build stuff from scratch, he is the founder of a tech-oriented short-term rental company in Tel Aviv and of what was one of the most popular cars websites in Israel (200K+ visitors per month)\n\nI have been coding since I was 9 years old and have served as a founding team engineer for several start-ups building the MVPs\n",
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        "linkedin_url": "https://linkedin.com/in/yardenst",
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      {
        "user_id": 1006424,
        "full_name": "Yotam Hamiel",
        "title": "Founder",
        "founder_bio": "Software engineer with 15+ years of experience building products, ETLs  & ML infra.\n\nEx-Flexport, Ex-Facebook, Ex-8200",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/hyotam/",
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      {
        "id": 70432,
        "title": "Magicflow - Webflow for AI development",
        "tagline": "A no-code tool to design and run AI workflows, optimized for cost and speed",
        "body": "Hey! We are [Yotam Hamiel](https://www.linkedin.com/in/hyotam/) and [Yarden Shem Tov](https://www.linkedin.com/in/yardenst/), the founders of [Magicflow](https://magicflow.ai/)!\n\nMagicflow is a no-code drag-and-drop tool to design and run AI workflows that easily integrate into your app.\n\nComplex workflows tend to be expensive and slow. We can optimize them for cost and speed so you don’t have to deal with the painful infrastructure work.\n\n![uploaded image](/media/?type=post&id=70432&key=user_uploads/1006285/cf3b8f4e-4f92-40a4-b9f3-bb02603a99f8)\n\n### The Problem:\n\nAI capabilities such as ChatGPT and Stable Diffusion are more accessible than ever. However, they still require a fair amount of technical know-how to deploy and orchestrate, particularly when combining multiple models to create optimized and cost-efficient workflows.\n\n### Our Solution:\n\nMagicflow — a no-code AI model orchestration solution.\n\nWe provide a user-friendly playground that integrates models from top services like [HuggingFace](https://huggingface.co/), [OpenAI](https://openai.com), and [Replicate](https://replicate.com).\n\nWith Magicflow anyone can easily stitch together various models without requiring any DevOps or code.\n\nOnce ready to deploy, workflows are cost/speed optimized and made ready for production.\n\n![uploaded image](/media/?type=post&id=70432&key=user_uploads/1006285/e84b74b9-a806-4ad6-9421-5995b02caa08)\n\nAn example of a workflow built with [Magicflow](https://magicflow.ai).\n\nWe came up with Magicflow by talking to our pre-pivot customers (who were mostly using us as a proxy for AI services). They told us that they needed a way to quickly iterate on their workflows, debug them and deploy them to production in a scalable and cost-efficient way.\n\nOur goal is to provide an accessible solution, for both engineers and non-engineers, to utilize the vast AI capabilities available to enhance their own products.\n\nSuhail (Mixpanel founder) [described it best](https://twitter.com/Suhail/status/1632064689466376194?lang=en):\n\n![uploaded image](/media/?type=post&id=70432&key=user_uploads/1006285/f8ef6c1a-849e-40cb-bf30-2a13db968340)\n\n### How you can help:\n\nWe’re looking to work with companies who rely on AI workflows, and are looking to make them cheaper and faster. If you know someone please contact us at [founders@magicflow.ai](mailto:founders@magicflow.ai)",
        "url": "https://www.ycombinator.com/launches/IK0-magicflow-webflow-for-ai-development",
        "votes": 71,
        "created_at": "2023-03-20T23:38:40.099Z"
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    "id": 27911,
    "name": "IcePanel",
    "slug": "icepanel",
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    "all_locations": "North Vancouver, BC, Canada",
    "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.",
    "one_liner": "Design and explain complex software architecture.",
    "team_size": 9,
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    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1669087724,
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      "America / Canada"
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    "year_founded": 2021,
    "city": "North Vancouver",
    "country": "CA",
    "linkedin_url": "https://www.linkedin.com/company/icepanel/",
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    "fb_url": "https://www.facebook.com/icepanel",
    "cb_url": "https://www.crunchbase.com/organization/icepanel",
    "github_url": "https://github.com/IcePanel",
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      "name": "Brad Flora",
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    "founders": [
      {
        "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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      {
        "id": 72555,
        "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",
        "skills": [
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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"
      }
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  },
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    "id": 27919,
    "name": "Helicone",
    "slug": "helicone",
    "former_names": [
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      "TableTalk",
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    "long_description": "Helicone.ai is creating an advanced observability platform tailored for developers working with Large Language Models (LLMs). Our goal is to simplify and enhance the operational side of deploying these models, making it easier for developers to monitor, manage, and optimize their AI applications at scale. Helicone provides a unified view of performance, cost, and user interaction metrics for various LLM providers, like OpenAI, Anthropic, and LangChain, empowering developers to make their LLM deployments more efficient, reliable, and cost-effective.\r\n\r\n### Key Features\r\n\r\n1. **Centralized Observability**: Our platform captures and visualizes detailed logs and metrics across all LLM deployments. With tools for prompt management, performance tracing, and debugging, Helicone provides real-time insights into the inner workings of your LLMs.\r\n\r\n2. **LLM Performance Optimization**: Helicone supports prompt experimentation, success rate tracking, and fine-tuning, allowing you to continuously improve response quality and efficiency. This level of insight makes it easier to deliver high-performing, cost-effective AI applications.\r\n\r\n3. **Flexible Data Management**: We understand that data privacy is critical. Helicone supports deployment options for dedicated instances, hybrid cloud integrations, or self-hosted environments, allowing clients to maintain control over their data and ensuring compliance with privacy standards.\r\n\r\n### Built for Developers and Data Scientists\r\n\r\nHelicone is designed to meet the needs of engineers and data scientists who require transparency and control over their LLMs. From chatbots to document processing systems, Helicone equips you with the insights needed to track costs, understand user interactions, and optimize outputs—all from one intuitive platform.\r\n\r\nBy combining observability with LLM-specific insights, Helicone is redefining AI monitoring, empowering developers to deploy and scale their AI models with confidence.",
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      {
        "id": 69629,
        "title": "Helicone - Open-source observability platform for generative AI",
        "tagline": "Log requests made to OpenAI and track costs, result quality, and latency with one line of code",
        "body": "**TL;DR Instead of building tools to monitor your generative AI product, use Helicone to get instant observability of your requests.**\n\nHey everyone, we are the team behind [Helicone](http://www.helicone.ai/).\n\n**Scott**  brings UX and finance expertise: 4+ years across Tesla, Bain Capital, and DraftKings.\n\n**Justin** brings platform and full-stack expertise: 7+ years across Apple 🍎, Intel, and Sisu Data.\n\nWe’re on a mission to make it extremely straightforward to **observe** and **manage** the use of language models.\n\n## **❌ The Problem**\n\nYou’re using generative AI in your product and your team needs to build internal tools for it:\n\n* You want an **admin mode** to **visualize** outputs, conversations, or prompt chains\n* You don’t know the **unit economics** of your product, like the average cost of a user or conversation\n* Your usage grows and you’re quickly **running into rate limits** with your provider, but your errors are opaque\n* You don’t know **when it’s time to fine-tune** your model and when you would get cost-savings from it\n\n## 🪄 **Our Solution**\n\nHelicone logs your completions and tracks the metadata of your requests. It is an analytics interface for understanding your metrics broken down by users, models, and prompts with visual cards. It caches your completions to save on bills, and helps you overcome rate limits with intelligent retry techniques.\n\n![uploaded image](/media/?type=post&id=69629&key=user_uploads/1203799/6118a1c6-83ab-4f6d-a671-6c835bda3698)\n\n## ⚙️ How it works\n\n🎩 **Integrate Helicone with one line of code**\n\nHelicone is a proxy service that executes and logs your requests, secured by Cloudflare workers around the globe to add [less than a scratch](https://docs.helicone.ai/how-it-works/latency) to your overall latency.\n\nPlug Helicone into wherever you are calling OpenAI with a [**single line of code**](https://docs.helicone.ai/quickstart/integrate-in-one-line-of-code) by changing the base URL, and immediately get a visual experience for your requests.\n\n![uploaded image](/media/?type=post&id=69629&key=user_uploads/1203799/6230af56-0e40-4c3e-a72c-996b6cc142dd)\n\n🔖 **Customize requests with properties**\n\nAppend custom information like the user, conversation or session id to group requests, then instantly get metrics like the total latency, the users disproportionately driving your OpenAI costs, or the average cost of a user session.\n\n📥 **Setup caching and retries**\n\nEasily cache your completions so that duplicate requests don’t drive up your bill. Customize your cache for your application’s unique requirements. This removes the latency overhead when you’re experimenting to make development faster.\n\nConfigure retry rules when you run into rate limits, or even route your request to another provider when your service is down.\n\n![uploaded image](/media/?type=post&id=69629&key=user_uploads/1203799/00d73946-0303-4024-9fc3-da961f05275b)\n\n## Get started **in seconds**\n\n* Try it **for free** at [helicone.ai](http://helicone.ai)\n* Book a call with the team [on our calendly](https://calendly.com/d/4hs-9jb-b96/helicone-intro)\n* Join our [Discord community](http://discord.gg/zsSTcH2qhG)\n* Email the team at [help@helicone.ai](mailto:help@helicone.ai)\n* We’re open source! Check out and support our repository at [github.com/Helicone/helicone](http://github.com/Helicone/helicone) ⭐",
        "url": "https://www.ycombinator.com/launches/I73-helicone-open-source-observability-platform-for-generative-ai",
        "votes": 52,
        "created_at": "2023-02-23T23:15:47.567Z"
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    "id": 27938,
    "name": "Boundary",
    "slug": "boundary",
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    "all_locations": "Seattle, WA, USA",
    "long_description": "Boundary is building BAML -- a programming language to build AI agents.\r\n\r\nWe used to code in assembly, and moved on to C.\r\nFrom C, we moved on to higher level languages like Python.\r\nNow we are going from Python to natural language.\r\n\r\nWhat does the code look like when 50% of the business decisions is decided by an AI agent / prompts? How do you test these AI components? We made BAML to address these problems.\r\n\r\nBAML helps has built-in tools to test, observe, and work with structured LLM outputs / tool calling natively in the language 10x faster. With BAML you can also instantly parallelize LLM Calls, or react to certain events or changes in your pipelines, without having to write any boilerplate. It's like using 'React' for AI.\r\n\r\nBAML code can used from any other language -- providing a standardized way to organize and declare any LLM or AI code.",
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    "team_size": 10,
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        "full_name": "Vaibhav Gupta",
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        "founder_bio": "Vaibhav is a software engineer with over 7 years of experience building innovative products. At Microsoft, he worked on realtime 3D reconstruction for HoloLens, gaining expertise in computer vision and 3D graphics. At Google, he led performance optimization on ARCore and Face ID, significantly improving latency and quality. Now he's bringing that same experience to help bring better quality and speed to Generative AI technology. For talking anything Computer Vision/AI/Performance, reach out!",
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        "title": "Engineers that enjoy hard things (like compilers)",
        "url": "https://www.ycombinator.com/companies/boundary/jobs/f31pAPu-engineers-that-enjoy-hard-things-like-compilers",
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      {
        "id": 70071,
        "title": "Gloo: Empower LLM’s with domain-specific knowledge",
        "tagline": "We help LLMs like ChatGPT connect to knowledgebases and add mechanisms to stop them from hallucinating..",
        "body": "**tl;dr** LLMs are awesome, but they have no knowledge about your data, and when you give it to them, they’re prone to make stuff up. We help developers build a searchable knowledgebase that LLMs can understand, and validate their responses are legit.\n\nHey everyone! We’re Aaron and Vaibhav from Gloo and we’re on a mission to help LLMs understand your data and get them to stop hallucinating all over the place.\n\n![uploaded image](/media/?type=post&id=70071&key=user_uploads/855521/fefa49cf-6a22-4913-ac9e-da9550da9e69)\n\n### **The problem**\n\nBuilding a knowledge graph isn’t as easy as calling OpenAI embeddings API, storing them in a VectorDB and calling it a day. Developers have to choose from a myriad of parameters like chunking algorithm, embedding type (even based on the content), vectorDB, whether to fine-tune or not, how to securely store the data — and the list goes on and on.\n\nOnce you feed everything into the LLM, you’re only halfway there, as getting rid of hallucinations is tricky, and confidently incorrect answers to customer questions will give you headaches in the long-term.\n\nOn top of that, you still have your actual customer problems to still fix: getting the customer data, building flows on top of the LLM, writing the right prompts, getting more customers.\n\n### **The solution**\n\nGloo is the managed solution to building your knowledge graph — built for LLM context-windows from the ground-up. **We stand up a search API for your data that supports both keyword and semantic search**, and we smartly index and compute embeddings for you based on the content type. Once that’s setup, you can call our **_Check-_GPT API to check LLM answers** against your knowledgebase to ensure trustworthiness.\n\n![uploaded image](/media/?type=post&id=70071&key=user_uploads/855521/4c3b7bd2-6924-427b-a1f6-6aa194ae500f)\n\nWe built our search with a security-first approach. Your data is always server-side encrypted, and never actually stored in 3rd party Vector DBs. We are also supporting new transformations search engines couldn’t do before, like generating document summaries (powered by LLMs!), so you don’t have to spend precious time computing this at query time.\n\nAll of your data is viewable in your own personal dashboard where you can track embedding jobs, play around with different search parameters, and search query performance and analytics.\n\n![uploaded image](/media/?type=post&id=70071&key=user_uploads/855521/3e191b7a-73b1-4b36-983c-8852002a646e)\n\n### **Asks**\n\nReach out to us at **founders@gloo.chat**\n\n* If your AI keeps making shit up ☠️\n* If you want your LLM to stop saying “Sorry I dont know 😵‍💫”\n* If you’re worried about data security and VectorDBs / LLMs 🔒",
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        "title": "Sage AI - Your self-generating, self-maintaining code knowledge base",
        "tagline": "We provide a platform that creates and updates symbol-level documentation with language-specific, cross-program context that you can talk to",
        "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)",
        "url": "https://www.ycombinator.com/launches/KKh-sage-ai-your-self-generating-self-maintaining-code-knowledge-base",
        "votes": 39,
        "created_at": "2024-02-05T17:43:51.471Z"
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        "title": "Semantic Finance: Real-time AI-powered financial news data",
        "tagline": "We help firms understand the markets faster and better",
        "body": "TL;DR: Semantic provides financial institutions a real-time news insights API for events that affect the financial markets. We use trade data, articles, social media engagement data, and breakthroughs in language models to filter the 99% of noise faster than the markets can react.\n\n—\n\n---\n\nHey YC, we’re Josh and Akhil, and we’re building Semantic.\n\nJosh (CEO) met Akhil (CTO) in high school and share a similar interest in how underutilized qualitative data is in financial markets.\n\nWe reconnected after a combined 7 years of experience in Software Engineering at companies such as Google, IBM, Squarespace, and Charles Schwab.\n\nWe’ve been studying how news impacts markets from a quantitative standpoint independently for years. Joshua developed an event-based trading algorithm that Ematiq proposed to implement during his time at Google.\n\n### **The Problem**\n\n\\\nAs trading firms spend tens of millions on microwave networks, racing for the fastest market data and order execution, GPT-4 has introduced a new race for relevant financial information retrieval and processing. Existing news feeds are too slow, unactionable, and noisy. They provide no additional information or filtering on the context, urgency, and market impact.\n\n### **The Solution**\n\n\\\nWe provide a novel insights layer on top of aggregated news and social media feeds, leveraging breakthroughs in LLMs’ (large language models) incredible semantic understanding of text to structure and automatically find the news that matters.\n\nWe monitor clustered mentions across multiple sources, engagement metrics over time, and anomalous price/volume changes to determine the market impact of events in real-time.\n\nOur primary offering is the **Semantic API**, which is article and tweet data that has been cleaned, filtered, and structured using LLMs.\n\n![uploaded image](/media/?type=post&id=70729&key=user_uploads/1192337/9ba82b9b-98ae-4ce5-8295-6a7c25e81ce5)\n\nYou can also receive alerts ahead of the market on events that matter with **Semantic Alerts**. Configure which priority levels activate Discord, Telegram, SMS, email, and phone calls.\n\n![uploaded image](/media/?type=post&id=70729&key=user_uploads/1192337/6a2d288e-0eb9-4eda-95cc-34045e4a01a2)\n\n### **Asks**\n\n* Do you know people at any trading platforms or institutions (hedge funds, prop shops, trading firms) that might benefit from low-latency financial news insights and alerting system?\n* Are you a trading platform or financial institution looking for configurable real-time financial news insights to surface to your customers?\n\n[Sign up for early access](https://semanticfinance.com/)!\n\nSemantic Team (Josh, Akhil)",
        "url": "https://www.ycombinator.com/launches/IOn-semantic-finance-real-time-ai-powered-financial-news-data",
        "votes": 30,
        "created_at": "2023-04-03T23:14:29.451Z"
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        "body": "Hey everyone, we’re Micah and Jackson, and we’re building Arroyo. Arroyo is the easiest way to build powerful streaming ⚡️ data pipelines. Just connect your Kafka, then you can filter, aggregate, window, and join your event data in real time with sub-second results. We fully manage the infrastructure, autoscale with your data, and charge based on usage with no fixed costs.\n\n![uploaded image](/media/?type=post&id=69175&key=user_uploads/61370/f468f5b0-8088-4982-abd8-a45e143f02a8)\n\n## **💥 The problem: real-time data processing is too hard.**\n\nMany companies have adopted Kafka to collect and route their event data. But if they want to actually _do_ anything complex with that data, their options today are to use a complex solution like Flink or dump it in a data warehouse for batch processing.\n\n## **⚡️ The solution**\n\nAfter leading streaming teams at Lyft and Splunk, we’ve seen how critical real-time data can be. At Lyft this infrastructure was vital to the operation of the product, powering features like dynamic pricing, ETAs, safety, and fraud. We’re working to bring it to everyone by solving the hard infrastructure and UX problems of existing solutions.\n\nIt’s three steps to get started writing real-time queries:\n\n1. Tell us how to connect and authenticate against your Kafka cluster\n2. Configure the source and sink topics\n3. Write SQL\n\nFrom there, our system will compile your query into an efficient dataflow program that responds to events within milliseconds and pushes results to Kafka. We charge purely on usage (based on data in, query complexity, and window sizes) with no minimums. Our system automatically scales with your data volume, and there’s no need to manage clusters or provision fixed infrastructure.\n\n![uploaded image](/media/?type=post&id=69175&key=user_uploads/61370/8789103e-9032-4cf3-bc1e-3f9bcf03a026)\n\n## **What can you use this for?**\n\n* Compute real-time ML features\n* Detect fraud and abuse as it happens\n* Turn your daily analytics jobs into real-time queries\n* Filter/redact/aggregate your logs before indexing, or turn them into metrics\n* Reduce costs in your data warehouse by pre-aggregating before ingestion\n\n## **The backstory**\n\nMicah spent four years at Lyft and Splunk building streaming platforms on top of Apache Flink and Kubernetes. Teams shipped impactful features backed by that infrastructure, but it still wasn’t easy enough for non-experts to adopt. Users wanted the same UX they had for batch: just write SQL, don’t worry about operations, scale, or the nuances of the infra. But the underlying tech wasn’t good enough.\n\nWe started Arroyo because we believe this goal is now achievable, but it requires looking beyond existing technology like Flink. That’s why we’re building a new, cloud-native stream processing engine in Rust. We’ve designed it from the ground up for near-instant rescaling and recovery even with very large windows (something that can take hours with Flink!) by separating storage and compute. And by leveraging WASM for user-defined functions, we can run user code efficiently and securely.\n\n## **Get in touch!**\n\nIf you use a stream processing system like Flink or Spark Streaming, or would like to make use of your event data in Kafka, we’d love to talk! We’re excited help you solve your real-time data problems or turn an existing batch workflow into a streaming pipeline. Reach us at [founders@arroyo.systems](mailto:founders@arroyo.systems).",
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        "full_name": "Charly Poly",
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        "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) 🧠",
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        "created_at": "2023-02-16T14:56:47.173Z"
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        "founder_bio": "Dropped out of college to build Blair (YC S19) where we raised a +100M to build income-based financing solutions for students in the US. At Blair, I led the engineering team to build audit-proof software that moved millions of dollars in student funds on a weekly basis. Two fun facts about me: I built autonomous drones for Porsche and was mining crypto to pay for college (and other things). ",
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        "id": 70265,
        "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"
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    "id": 28081,
    "name": "DAGWorks Inc.",
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    "website": "https://www.dagworks.io/",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "We’re on a mission to enable everyone to build reliable AI agents & AI applications. We're fully open source, and provide a unique integrated development & observability experience for those building anything in the AI space. This is the first step towards laying the foundations for Composable AI Systems; all AI systems need observability and introspection to be first class for them to be reliable.\r\n\r\nHow? We're standardizing how people write python to express data, ML, LLM, & agent workflows/pipelines/applications with lightweight frameworks. So that no matter the author, it'll be easy to collaborate, connect, and importantly in one line integrate observability and datastore needs. This speeds up time to production and reduces TCO because code remains easy to maintain and your data flywheel stays manageable. So you can increase the top line & bottom line of your business by delivering on AI that is reliable.\r\n\r\nWe've got two open source projects:\r\n- one focused on AI applications, called Burr (https://github.com/dagworks-inc/burr).\r\n- one focused on AI pipelines/workflows, called Hamilton (https://github.com/dagworks-inc/hamilton) see https://www.tryhamilton.dev\r\n\r\nBoth Hamilton & Burr come with self-hostable UIs (+ enterprise & SaaS offerings). With a one-line code change, you get versioning, lineage / tracing, cataloging, and observability out of the box with Hamilton. With Burr you get tracing, observability and persistence in a single line addition.\r\n",
    "one_liner": "Open source tools & services for reliable AI Agents & AI Applications",
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    "industry": "B2B",
    "subindustry": "B2B",
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        "answer": "Collaborative ML ETL platform for data scientists"
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        "question": "What is your company going to make? Please describe your product and what it does or will do.",
        "answer": "An open-core platform for data science teams to develop, productionize, and maintain machine learning ETLs, using a company’s existing MLOps & data infrastructure."
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    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/dagworks-inc",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/dagworks-inc.json",
    "year_founded": 2022,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/dagworks-inc/",
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    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
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    "founders": [
      {
        "user_id": 1208898,
        "full_name": "Stefan Krawczyk",
        "title": "Founder",
        "founder_bio": "A hands-on leader and Silicon Valley veteran, Stefan has spent the last 15 years working on data and machine learning systems at companies like Stitch Fix, Idibon, Nextdoor, and LinkedIn.\n\nBefore DAGWorks Inc., Stefan led the Model Lifecycle team at Stitch Fix, where its mission was to streamline the model productionization process for over 100+ data scientists. That's when he co-created https://github.com/dagworks-inc/hamilton, which he's excited to continue driving today with DAGWorks Inc.",
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        "linkedin_url": "https://www.linkedin.com/in/skrawczyk/",
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        "user_id": 1209559,
        "full_name": "Elijah ben Izzy",
        "title": "Founder",
        "founder_bio": "Elijah has spent his career building tools for Data Scientists, Quantitative-minded engineers, and AI researchers. Prior to founding DAGWorks, Inc., Elijah built out Stitch Fix's machine learning platform, which was used and loved by over 100 data scientists. A core component of this was Hamilton (https://github.com/dagworks-inc/hamilton), an open-source framework for managing dataflows that DAGWorks's is now driving forward.",
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      {
        "id": 69876,
        "title": "DAGWorks: Avoid Machine Learning Pipeline horror stories 😱",
        "tagline": "From creation to maintenance, DAGWorks is building a more human capital efficient way for Data Science teams to build and own Machine Learning Pipelines.",
        "body": "👋 Hi, Stefan & Elijah here from [DAGWorks](https://dagworks.io).\n\n![uploaded image](/media/?type=post&id=69876&key=user_uploads/1208898/cf51f7bb-c9a2-495e-91d8-afb1ddfc0192)\n\n### **TL;DR:**\n\n(1) At DAGWorks Inc. our goal is to make Machine Learning (ML) initiatives more human capital efficient. (2) Our solution is an open source SaaS platform for Data Science teams to build and maintain model pipelines, plugging into as much of your existing MLOps and data infrastructure as you want. (3) Star our open source project [Hamilton on github](https://github.com/dagworks-inc/hamilton) and get started with it via [tryhamilton.dev](https://www.tryhamilton.dev).\n\n### **❌ The Problem:**\n\nAsk a Data Scientist whether they like inheriting someone else’s ML pipelines. 99% of the time, they’ll say no. Why? Getting ML to production is easy when you’re small, but when your team and codebase start to grow, maintaining these pipelines becomes challenging:\n\n* 😕 understanding code you didn’t write\n* 🐛 debugging production issues\n* 🏗️ migrating to new infrastructure\n* 🥼 handling personnel changes\n\nThis causes teams to spend far more time keeping existing ML pipelines afloat than innovating and driving their business forward.\n\nTo get out of/avoid such a mess, you need a high (and expensive) software engineering skill set, but for many that’s not an option. In our experience, this phenomenon is the biggest blocker to leveraging machine learning in your business as it grows.\n\n### **✨ Our Solution**\n\n(1) We leverage our open source project [Hamilton](https://github.com/dagworks-inc/hamilton), which is an opinionated way to write python code (akin to what DBT did for SQL), that naturally helps teams follow software engineering best practices.\n\n(2) Using the DAGWorks Client on top of Hamilton, we can give you full insight into how your pipelines operate on the DAGWorks Platform, including:\n\nA **catalog of functions** - feature catalog anyone?\n\n![](https://lh5.googleusercontent.com/lDX_3El7R6_OdBZg_tfBekfl--qUUmsmm10wBFcZcE59wrTn01e2_U8Ns-LC73fCfsJ1kmGirfbZ6XT_T_uqniK7SyJsPPZt6BXb8byJCq_C6HNlFhsdOLdiPdyVWAwS18x4D2bAQhN19AVX4Ouga6w)\n\n**Lineage** - see upstream and downstream dependencies:\n\n![](https://lh5.googleusercontent.com/-EwfBtPJB1OkF3JtS_JATLshDFHTnudGU5qyn9TqZJ3i29LcZGw0pU4Xed3Yb-apaRETO2HqQY_mDCD1ucOt8MQA5VH0D7Q_uCW99uh90c72nbKEeY8dvn5ppH5zhM0i-PtKJHDfxEYwaojPezU1ZlE)\n\n**Debugging insights** - e.g. know exactly what code failed given an airflow task failure:\n\n![](https://lh3.googleusercontent.com/j6gqllKW9oDbC9r8KC4_TRusN3MxSemIySmHq8PhSZnwOYGDwQ5ckwe-LIW4MFdtKtRfjpyCXlE_qTpQTT5boMbIDNfMgOz9huOG01UK0RuGQLFxTIR7YMuEAy5OfDuQJc-qDqdaGFLUy_9NR4nl3mo)\n\nAnd more like **data observability**, and **links with materialized artifacts** (like data sources, models, features, etc.).\n\n(3) The DAGWorks Platform becomes your ML Pipeline control plane. Use it to manage integrations with your existing infrastructure, as well as providing any reporting and compliance insights you need.\n\n### **⚙️ How it works**\n\nWith [Hamilton](https://github.com/dagworks-inc/hamilton), users logically express what should happen, which helps avoid vendor and infrastructure lock in. Then with the DAGWorks Platform & Client, we make your Hamilton code run on your existing infrastructure, providing out of the box connectors to common systems, and provide insights post execution. By building on a solid foundation that clearly decouples concerns, we can avoid the problems that plague traditional ML Pipelines. This enables Data Science teams to move faster and do more themselves, making ML projects more human capital efficient.\n\n**👪 Founding Team**\n\n[Stefan](https://www.linkedin.com/in/skrawczyk/) and [Elijah](https://www.linkedin.com/in/elijahbenizzy/) worked together at Stitch Fix where they built the self-service ML Platform for over 100 data scientists. They learned firsthand the troubles that occur building and maintaining ML Pipelines over a diverse set of modeling disciplines. Their work has been recognized by industry and included in books, newsletters, and was even the topic of a lecture at Stanford. Previously Stefan built data and ML systems at Nextdoor and LinkedIn and graduated from the Stanford CS Masters program with a Distinction in Research. Elijah built tools for quants at Two Sigma and studied Math and CS at Brown.\n\n### **🙏 Asks**\n\n1. Start with Hamilton open source today!\n   * ⭐️ Star [Hamilton on Github](https://github.com/dagworks-inc/hamilton)! Download it from [PyPI](https://pypi.org/project/sf-hamilton/).\n   * Checkout out [www.tryhamilton.dev](http://www.tryhamilton.dev) for an in browser overview of Hamilton. A common use case is to start using it for feature engineering.\n   * Don’t know how to leverage Hamilton – [book time](https://calendly.com/stefan-dagworks/15-minute-intro-call-with-stefan) and we’ll walk you through it!\n2. We’re looking for more leads to larger organizations that have ML Pipeline struggles, in particular if they have compliance/auditing needs for them. Know someone, or perhaps you’re the right person? Please email us - [founders@dagworks.io](mailto:founders@dagworks.io) or book [15 minutes here](https://calendly.com/stefan-dagworks/15-minute-intro-call-with-stefan).\n3. We’re still currently in closed beta for the DAGWorks Platform, but you can sign up for early access via [www.dagworks.io](http://www.dagworks.io).\n4. Follow us on Twitter for updates:\n   * [DAGWorks](https://twitter.com/dagworks)\n   * [Hamilton_OS](https://twitter.com/hamilton_os)",
        "url": "https://www.ycombinator.com/launches/IB2-dagworks-avoid-machine-learning-pipeline-horror-stories",
        "votes": 91,
        "created_at": "2023-03-02T18:05:42.420Z"
      }
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  {
    "id": 28096,
    "name": "OpenInt",
    "slug": "openint",
    "former_names": [
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      "Ally",
      "Evefan"
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    "website": "https://openint.dev",
    "all_locations": "Remote",
    "long_description": "OpenInt helps teams ship product integrations in hours, not weeks, using no or low code. Read and write data using unified APIs or sync it straight to your database. ",
    "one_liner": "Open Source Embedded Product Integrations",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Analytics",
    "launched_at": 1673267479,
    "tags": [
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      "Open Source",
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    "nonprofit": false,
    "batch": "Winter 2023",
    "status": "Acquired",
    "industries": [
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    "regions": [
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      "Fully Remote"
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/openint",
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      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
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        "user_id": 702191,
        "full_name": "Amadeo Pellicce",
        "title": "Founder/CEO",
        "founder_bio": "Founded OpenInt (W23), acquired by Replit (W18). Investor in YC startups via https://www.batch.ventures/yc-fund. \n\nHe has an MS in Computer Science. In 2013, he co-founded the UK’s first professional crypto exchange, Coinfloor (which was acquired). Subsequently, he led multiple product areas at Blockchain.com before founding Openint (W23), which was acquired by Replit (W18). Outside of work, Amadeo enjoys wind sports and long-distance running.",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/amadeopellicce/",
        "x_url": "https://twitter.com/amapel",
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      {
        "user_id": 733318,
        "full_name": "Philip London",
        "title": "Founder",
        "founder_bio": "Phil is a co-founder and Lead Engineer at Map3. Before Map3, he worked at Blockchain.com as Staff Engineer on the non-custodial Wallet team, which served over 30 million users and over 1/3 of all bitcoin transactions. Phil also founded codeamigo.dev, which helps developers level up their coding skills and reached #1 on Hacker News when it launched.",
        "is_active": false,
        "linkedin_url": "https://linkedin.com/in/philiplondon",
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        "full_name": "Mark Pfluger",
        "title": "Founder",
        "founder_bio": "Mark is the co-founder and CTO of Map3. Previously he worked at Blockchain.com as Head of Crypto Engineering, where he built and ran multiple engineering teams, contributed to the non-custodial wallet across all platforms (iOS, Android and Web), and led the effort to build the custody infrastructure across both Hot and Cold systems. Originally from Munich, Germany, Mark has been an entrepreneur since high school and holds a Master's degree in Computer Science.",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/mark-pfluger-14734650/",
        "x_url": "https://twitter.com/markpfluger",
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      {
        "id": 83175,
        "title": "⭐️ Evefan — Self-hosted Segment alternative — 99% savings w/ Cloudflare Workers (OSS)",
        "tagline": "Self-host your own internet scale events infrastructure.",
        "body": "**TLDR;** Evefan enables developers to privately capture, transform, and deliver customer events at internet scale. Evefan is open source and self-hosted on Cloudflare workers. It can be configured either via our Evefan Console or via Wrangler. With Evefan, organizations can save > 99% when scaling events.\n\n**Need help scaling events**? Let’s talk! <https://cal.com/amadeo-evefan>\n\n![uploaded image](/media/?type=post&id=83175&key=user_uploads/702191/93a130d5-d424-4400-aa4b-cf7b7873e01c)\n\n### ❌ Problem: Scaling Customer Events IS HARD\n\nBefore joining YC, I led a large portion of the Blockchain.com consumer product. At the time, we had the most popular crypto wallet with over 60M accounts. We only made money on a subset of users who used our ‘premium’ features. \n\nAs a result, **we could not afford to understand how free users used our product**. We got seven-figure quotes (😱) from the top vendors in the Customer Data Platform (CDP) space and tried to self-host several alternatives. Imagine a PM team considering whether adding an event is worth XXXX dollars. Silly. \n\nAll the products we self-hosted then fell over at our scale. We had to build our own, more narrow version for our use case. There’s a reason for it—you could even say that it’s a dark industry secret.\n\n**😭 Self-Hosting Is Meant To Be Practical**\n\nExisting OSS alternatives in the market are all built with massive multitenancy in mind. **They’re not meant to be practically self-hosted**. Most of them tell you in their docs to only self-host for toy projects or require overly expensive closed source ‘high availability’ add-ons that they can only configure for them to work correctly. That’s OK; they serve a different use case. \n\nLook at the architecture of the top self-hostable alternatives in the space. Imagine asking your SRE team to ‘simply’ set these up and keep them highly available (even with Docker & Kubernetes, it's not core work).\n\n![uploaded image](/media/?type=post&id=83175&key=user_uploads/702191/e695acc0-3cd3-4580-9e0e-38cfdcc543ac)\n\n### ⭐️ The Solution: Evefan\n\n1. **Segment compatible**: this means you can use the battle-tested Segment SDKs in your preferred programming language.\n2. **Deploy to Cloudflare**: Configure Evefan instance via our console with your Cloudflare API key or yourself via Wrangler. Evefan will create a bundle with just your destinations small enough to run on Cloudflare. \n3. **Transform and Deliver To Your Destinations**: We’ve made Bigquery and Postgres work so far. We also added Mixpanel just for fun. We’ve reviewed the top data warehouses and are confident we will natively support them.\n\nOver time, Evefan will become an indispensable part of your async events delivery infrastructure. Use cases like in-and-out webhooks, queues, pub-sub, and jobs are coming! \n\n![uploaded image](/media/?type=post&id=83175&key=user_uploads/702191/6a355a35-8aa4-4410-8701-72aef7a364e0)\n\n**😻 It’s 99% Cheaper Than Alternatives & Built For Scale**\n\nHere’s why: We follow a Bring Your Own Compute (BYOC) model. When Evefan runs in your infra, it roughly incurs $70 of Cloudflare worker compute for every 100 million events processed. This is 99.5% cheaper than Segment and similar alternatives! Of course, price is not the only reason people self-host. In Finance and Healthcare, for example, it is often the only practical option.\n\n### 🙌 Our Asks\n\n1. **Please Star** our Github repo ⭐️<https://github.com/evefancom/evefan>   \n2. **Let's Partner**: We’ve been working with our first two design partners and are searching for our next three! Does your organization process over 10M monthly events and struggle to scale? Let’s chat! <https://cal.com/amadeo-evefan>\n\n![uploaded image](/media/?type=post&id=83175&key=user_uploads/702191/2c6b777e-4227-4b61-b4b2-5d4e0b270ba1)\n\n",
        "url": "https://www.ycombinator.com/launches/LdX-evefan-self-hosted-segment-alternative-99-savings-w-cloudflare-workers-oss",
        "votes": 21,
        "created_at": "2024-08-19T16:12:51.893Z"
      }
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    "id": 28103,
    "name": "Fern",
    "slug": "fern",
    "former_names": [
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      "fern"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4f48c426b67826bae7fd3fded6bfc3e891fd72d2.png",
    "website": "https://www.buildwithfern.com",
    "all_locations": "New York City, NY, USA",
    "long_description": "APIs underpin the internet but are still painful to work with. They are often untyped, unstandardized, and out-of-sync across multiple sources of truth.\r\n\r\nFern helps companies deliver SDKs and API documentation that they’re are proud to share with their customers. Since launching in 2023, we’ve been trusted by over 200 customers, including industry leaders like Square, Webflow, ElevenLabs, Auth0, and Intercom, to power their developer and agent experiences.\r\n\r\nWe’re fewer than 40 people, based in Brooklyn, NY, and are building open source.",
    "one_liner": "Instantly offer SDKs and API Docs",
    "team_size": 30,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1674979441,
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        "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.",
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        "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",
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        "body": "### **✨ TL;DR**\n\nSuperAPI is a programmable API gateway that makes all your fetch APIs cacheable, and makes sure your cached API responses never goes stale.\n\nHey everyone - it’s Aditya and Adithya here introducing **SuperAPI**.\\\n\\\n—\n\n### **🤯 Problem**\n\nA lot of application APIs are considered non-cacheable either because:\n\n1. the underlying data changes frequently\n2. they use GraphQL making it difficult to cache\n3. they’re REST APIs that fetch using POST because they have their search parameters within the body\n\nMost applications in this situation do not cache their API responses, and end up serving APIs with a high latency, or setup multiple clusters close to their users to give them low latencies.\n\n# **💡 Solution**\n\nSuperAPI makes such APIs cacheable by monitoring your incoming **POST / PUT / PATCH** API calls, and your database updates to invalidate stale data and keep your API cache fresh.\n\nBecause we listen to your database changes, SuperAPI can also update your cache in-place. This means, any updates in your database will only modify the relevant portions of your cached API responses.\n\nThis reduces the amount of computations on your database & compute instances, helping reduce your cloud spend.\n\n# **🚀 How does SuperAPI work?**\n\nSuperAPI can either be deployed as a separate API gateway, or can run on top of other caching providers like **Cloudflare & Cloudfront.**\n\nThis API gateway listens to all incoming update API calls (POST / PUT / PATCH), and invalidates any API cache that could go stale as a result of this incoming update API call.\n\nWe also have a tiny docker container running within your network that listens to your database updates (using the replication stream or database triggers), which helps us catch any invalidations coming from internal cron jobs & batch processes.\n\nRead more about how SuperAPI works [here](https://trysuperapi.com/blog/how-does-superapi-work-clet0rvf1446071ko73x4q6qtr).\n\n![uploaded image](/media/?type=post&id=70198&key=user_uploads/11606/c7fdb60e-043e-49d6-b23b-e6123de076e6)\n\n# **📜 How did we get here?**\n\nBoth of us founders worked together at a Tiger Global backed Indian tech company before starting on SuperAPI.\n\nI was the first engineer there, and built out majority of the product & platform for the first couple of years. For the next 2 years, I was heading the engineering team, growing the team from 6 engineers to \\~55 engineers, designers & PMs.\n\nAditya was heading the platform engineering team, where he built a majority of the infrastructure to scale the platform and bring down the API latencies to less than 50ms.\n\nWe’ve been obsessed with API latencies since our time working together, and are using a lot of learnings from back then to build out SuperAPI.\n\n# ❓ **Asks**\n\nIf you are looking to **reduce your API latencies**, let’s talk. Drop us a note at: [founders@trysuperapi.com](mailto:founders@trysuperapi.com).",
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        "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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    "id": 28118,
    "name": "Vocode",
    "slug": "vocode",
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    "website": "https://vocode.dev",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Open source voice AI.\r\n\r\nCheck out our docs for more information: https://docs.vocode.dev",
    "one_liner": "Open source Voice AI",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1677630945,
    "tags": [
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      "Open Source",
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    "batch": "Winter 2023",
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    "url": "https://www.ycombinator.com/companies/vocode",
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        "full_name": "Kian Hooshmand",
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        "founder_bio": "Working on something new. Formerly @Vocode, @Brex, and Berkeley.",
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        "linkedin_url": "https://www.linkedin.com/in/kianhooshmand/",
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        "date": "Feb 08, 2024"
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      {
        "id": 69813,
        "title": "🤖 Vocode: Open source voice AI on top of LLMs",
        "tagline": "Build conversational agents in less than 10 lines of code",
        "body": "**TLDR:** Vocode makes it easy for developers to build voice-based LLM applications. Using Vocode, developers can integrate realistic voice AI in product flows or to automate interactions like phone calls in 10 lines of code. [**Watch our demo**](https://vocode.dev?utm_source=bookface&utm_medium=website&utm_campaign=launch_yc)😀\n\nHi everyone! Ajay and Kian here representing Vocode – we are on a mission to build the most realistic, production-ready conversational voice AI to power the future of human <> computer interactions.\n\n![uploaded image](/media/?type=post&id=69813&key=user_uploads/782661/2d32781c-f34c-4c26-8f70-c018e66a4255)\n\n### Problem: voice interfaces are useful but hard to build\n\nTo build a realistic voice interface, you have to orchestrate several pieces – speech recognition, AI/Natural Language Understanding, and speech synthesis – in real time while managing the asynchronous and imperfect nature of human conversation.\n\nBut voice is our most natural communication medium and is applicable in practically every industry (healthcare, sales, customer service, etc). Many products and services _would_ have voice interfaces or voice automation.. but don’t due to the complexity.\n\n### Vocode makes it easy\n\nVocode makes it easy for developers to build voice interfaces through composability. Vocode orchestrates everything in real time and provides tools out-of-the-box for common workflows.\n\nCompanies can now focus on their core product/vertical and use our library to dramatically reduce the complexity and engineering time required to build voice into their applications.\n\n### Why now?\n\nWe’re at an inflection point where speech recognition/synthesis/AI are all improving at breakneck speed and we think this will lead to a massive boom in voice interfaces. Vocode wants to be the developer platform for building these voice interfaces.\n\nThe existing market is either too focused on custom enteprise use cases or not easy enough to use. Vocode will make it 10x faster to build voice apps through composability and the developer ergonomics we’re used to with other dev focused products (eg Stripe).\n\nIf you’re interested in what we’re building, check us out at [vocode.dev](https://www.vocode.dev/) and drop us an email/request access to our private beta!",
        "url": "https://www.ycombinator.com/launches/IA1-vocode-open-source-voice-ai-on-top-of-llms",
        "votes": 29,
        "created_at": "2023-03-01T15:49:57.823Z"
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    "id": 28141,
    "name": "highlight.io",
    "slug": "highlight-io",
    "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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    "status": "Acquired",
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/highlight-io",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/highlight-io.json",
    "year_founded": 2023,
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    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/highlightrun",
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        "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",
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        "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/",
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        "url": "https://venturebeat.com/programming-development/highlight-launches-full-stack-application-monitoring-platform-raises-8m/",
        "date": "Aug 15, 2023"
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    "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",
    "slug": "skyhook",
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        "full_name": "Nadav Erell",
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        "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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    "id": 28216,
    "name": "Escape",
    "slug": "escape",
    "former_names": [
      "Escape",
      "Escape - GraphQL Security",
      "Escape",
      "Escape - GraphQL Security",
      "Escape - Modern Application Security"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0210bbcb75b7ba7c4519705bd24c324666b9538b.png",
    "website": "https://escape.tech",
    "all_locations": "Paris, Île-de-France, France",
    "long_description": "Replace legacy scanners and manual offensive security processes with AI agents that discover, test, and remediate directly in your engineering workflows.",
    "one_liner": "Offensive security for the teams that are 100x outnumbered",
    "team_size": 29,
    "industry": "B2B",
    "subindustry": "B2B -> Security",
    "launched_at": 1674779031,
    "tags": [
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      "Security",
      "API",
      "GraphQL"
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    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Winter 2023",
    "status": "Active",
    "industries": [
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    "regions": [
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      "Europe",
      "Remote",
      "Partly Remote"
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    "stage": "Growth",
    "app_video_public": false,
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    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/escape",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/escape.json",
    "year_founded": 2020,
    "city": "Paris",
    "country": "FR",
    "linkedin_url": "https://www.linkedin.com/company/escapetech",
    "x_url": "https://twitter.com/escapetechhq",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/escape-b74e",
    "github_url": "https://github.com/Escape-Technologies/",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/0210bbcb75b7ba7c4519705bd24c324666b9538b.png",
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    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
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    "founders": [
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        "user_id": 1709764,
        "full_name": "Tristan Kalos",
        "title": "Founder",
        "founder_bio": "Building Escape (YC W23) to help AppSec and Engineering teams secure their Single Page Apps, APIs, and Microservices. Previously ML engineer at source{d} and researcher at UC Berkeley. Passionate about solving complex business problems with creative technology or user experiences. ",
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        "linkedin_url": "https://linkedin.com/in/tkalos",
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      {
        "user_id": 1167886,
        "full_name": "Antoine Carossio",
        "title": "Founder",
        "founder_bio": "🇫🇷 • Engineer • UC Berkeley • Apple",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/acarossio",
        "x_url": "https://twitter.com/icarossio",
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        "id": 84153,
        "title": "Head of Sales ",
        "url": "https://www.ycombinator.com/companies/escape/jobs/yfEXoM2-head-of-sales",
        "location": "New York, NY, US / Remote (US)",
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        "role": "Sales",
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        "equity_range": "",
        "experience": "6+ years",
        "visa": "US citizen/visa only",
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    "news": [
      {
        "title": "Escape raises $18M Series A to replace legacy scanners with AI agent-driven discovery, pentesting, and remediation",
        "url": "https://escape.tech/blog/escape-raises-18m-series-a/",
        "date": "Mar 09, 2026"
      },
      {
        "title": "New Security Research: We discovered over 2k high-impact vulnerabilities and PII in apps built with vibe coding platforms",
        "url": "https://escape.tech/blog/methodology-how-we-discovered-vulnerabilities-apps-built-with-vibe-coding/",
        "date": "Oct 29, 2025"
      },
      {
        "title": "Meet Escape Copilot: Automate App and Scan Management via MCP",
        "url": "https://escape.tech/blog/meet-escape-copilot-automate-app-and-scan-management-via-mcp/",
        "date": "Jun 05, 2025"
      },
      {
        "title": "Escape DAST Now in Beta: Front-End & SPA Testing Made Easy",
        "url": "https://escape.tech/blog/front-end-dast-beta/",
        "date": "Dec 10, 2024"
      },
      {
        "title": "Fortune 1000 at risk: How we discovered 100k vulnerabilities",
        "url": "https://escape.tech/blog/fortune-1000-at-risk-30k-exposed-apis-100k-vulnerabilities/",
        "date": "Nov 20, 2024"
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    "launches": [
      {
        "id": 69497,
        "title": "🛡 Escape - Secure your GraphQL APIs",
        "tagline": "We help companies create Fast, Secure, and Reliable GraphQL APIs",
        "body": "### **tl;dr:** **Securing GraphQL is hard.** Escape makes it easy for developers to build secure and reliable GraphQL APIs. **You can test it for free and get your results in seconds** using this link: <https://app.escape.tech/ycw23>\n\nHello everyone, we are Antoine and Tristan, the founding team behind Escape.\n\n![uploaded image](/media/?type=post&id=69497&key=user_uploads/1231138/4111cf07-557b-4da5-ad36-d2336aa3913a)\n\n🧠 **Tristan** (left) previously worked as a **GraphQL Developer** and experienced himself the need for better tooling in this ecosystem. 💪 **Antoine** (right) previously worked as a security engineer for the French Government and **Apple** 🍎 which led him to the journey of helping developers secure their code.\n\n### 🛡 Why are we building Escape?\n\nGraphQL has seen exponential growth in the past years and is now used by 20% of all developers. Companies like **Paypal**, **Walmart**, **Twitter**, and **Airbnb** are now all relying on GraphQL APIs for **their** **core businesses**.\n\nYet, we observed that most - as in like **95%** - of GraphQL APIs that exist today are insanely vulnerable to cyberattacks.\n\nThe reason is simple: GraphQL has an entirely different structure than traditional APIs like REST.\n\nExisting security tools do not support it, leaving GraphQL developers and organizations completely blind to the security of what they release and **putting their business at risk**.\n\n### 🎯 Our solution\n\nWe aimed to build the GraphQL Security Testing tool that devs would love. As developers ourselves, we think such a tool would\n\n*  _be_ **fast to run in CI/CD**\n*  _be super_ **easy to set up** and maintain\n*  _give_ **relevant results**\n\nExisting tools fail at achieving the latter because they rely on brute-forcing API requests. Thus, most requests are blocked at the validation layer, failing to test the actual code.\n\nAt Escape, **we developed a new approach called _feedback-driven API exploration_**. We crafted a graph traversal algorithm that learns from the API's responses how to generate requests that actually make sense from a business standpoint.\n\n![uploaded image](/media/?type=post&id=69497&key=user_uploads/1231138/4d4ffbf4-e5af-46b9-927d-904530700300)\n\n_Requests generated by bruteforce (left) vs. **Escape’s feedback-driven exploration** (right)_\n\nUsing this technique, we are able to pass the validation layer and test the code of the application at a deeper level than previous solutions. So far, we have achieved **more than 80% coverage** in most applications without fine-tuning.\n\n### 🚀 let us assess the security of your GraphQL API for free in seconds\n\nIn only 6 months, we partnered with **Snyk** and **Postman**, got into the GraphQL foundation, and worked with companies like **Neo4j** and **ArangoDB**.\n\n👉 If you are using GraphQL yourself, you are welcome to try our platform and **get your application's security report for free**, as **we unlocked all the features for the YC community**: <https://app.escape.tech/ycw23>!",
        "url": "https://www.ycombinator.com/launches/I4v-escape-secure-your-graphql-apis",
        "votes": 1096,
        "created_at": "2023-02-21T19:45:54.930Z"
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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,
    "tags": [
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      "Generative AI",
      "SaaS",
      "B2B"
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    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2023",
    "status": "Active",
    "industries": [
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    "regions": [
      "United States of America",
      "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/lightski",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/lightski.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "",
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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",
        "x_url": "https://www.twitter.com/hansenq",
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    "jobs": [],
    "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"
      }
    ],
    "launches": [
      {
        "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"
      },
      {
        "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": 28368,
    "name": "Second",
    "slug": "second",
    "former_names": [
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    "all_locations": "",
    "long_description": "AI-native enterprise codebase maintenance, including automated migrations and codebase intelligence for engineering teams who need to get stuff done.",
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    "subindustry": "B2B",
    "launched_at": 1675964720,
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    "batch": "Winter 2023",
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/second",
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    "year_founded": 2023,
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    "country": null,
    "linkedin_url": "https://www.linkedin.com/company/secondhq",
    "x_url": "https://x.com/SecondDevHQ",
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    "primary_partner": {
      "name": "Gustaf Alstromer",
      "url": "https://www.ycombinator.com/people/gustaf-alstromer"
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    "founders": [
      {
        "user_id": 602008,
        "full_name": "Eric Rowell",
        "title": "Founder",
        "founder_bio": "Co-founder & CTO of Wayline (YC S25). I was previously the founder & CEO of Second (YC W23) where I raised $1.9M to build enterprise codebase maintenance tools.  Before that, I was the co-founder and CTO of Uiflow (YC W21) where I raised $21M, built a no-code platform for enterprises, and was acquired by Workday.  Before that, I was the Head of Data Visualization at Workday, UI architect at LinkedIn and Yahoo, author of HTML5 Canvas Cookbook, and created several popular open source libraries.",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/errowell/",
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    "jobs": [],
    "news": [
      {
        "title": "Second Has Raised $1.9M in Pre-seed Funding",
        "url": "https://www.second.dev/blog/second-has-raised-1-9m-in-pre-seed-funding-to-automate-codebase-maintenance-with-a-novel-approach-to-ai-agents",
        "date": "Jun 12, 2024"
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    "id": 28409,
    "name": "LiteLLM",
    "slug": "litellm",
    "former_names": [
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      "LiteLLM",
      "BerriAI"
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    "website": "https://www.litellm.ai/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "LiteLLM is an open-source LLM Gateway with 50K+ stars on GitHub and trusted by companies like Rocket Money, Samsara, Lemonade, and Adobe. LiteLLM provides an open source Python SDK and Python FastAPI Server that allows calling 100+ LLM APIs (Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic) in the OpenAI format\r\n\r\nWe have raised a $1.6M seed round from Y Combinator, Gravity Fund and Pioneer Fund",
    "one_liner": "Call every LLM API like it's OpenAI [100+ LLMs]",
    "team_size": 20,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1675814900,
    "tags": [
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      "Generative AI",
      "Open Source",
      "AI"
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    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/berri-ai/",
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        "title": "Automat Raises $15.5M Series A | Automat",
        "url": "https://www.runautomat.com/blog/automat-raises-15-5m-series-a",
        "date": "Nov 19, 2025"
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        "title": "Y Combinator-backed Automat turns videos into workflow automations | TechCrunch",
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      {
        "title": "These Y Combinator-backed startups are trying to build 'ChatGPT for X'",
        "url": "https://techcrunch.com/2023/04/04/these-y-combinator-startups-are-trying-to-build-chatgpt-for-x/",
        "date": "Apr 04, 2023"
      },
      {
        "title": "The Top 34 Companies of the W23 Program with a focus on AI",
        "url": "https://www.cerebralvalley.com/post/a-synopsis-of-y-combinator-companies-in-the-w23-batch-of-startups",
        "date": "Mar 15, 2023"
      },
      {
        "title": "AI-led change means businesses must adopt more quickly.",
        "url": "https://russmalz.com/ai-led-change-is-forcing-businesses-to-adapt-quickly-and-the-pace-is-accelerating/",
        "date": "Feb 26, 2023"
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        "id": 117458,
        "title": "Ace from Automat: it's instinct, but for work",
        "tagline": "Hire an AI teammate with its own computer, phone number, inbox, and logins. It works inside the tools you already use and hands back finished work, not status updates.",
        "body": "Hi! Lucas here from Automat. Stoked to share what the team's been heads-down on: Ace. It's instinct, but for work. **The TL;DR: you can now hire an AI teammate.**\n\nEvery team we talk to wants AI teammates, but doesn't know how to actually put one to work. Maybe you've tried homebrewing OpenClaw or Hermes. The two usual options both whiff: traditional automation (UiPath) makes you sign up for a months-long integration project before it does one useful thing, and AI \"assistants\" hand you a wall of text, and you still go do the work yourself.\n\n**Ace is different.** You onboard it like any new hire, and it shows up where the work happens:\n\n• Forward it an email or cc its own inbox, and the draft lands in your Drive with the judgment calls left as comments.\n\n• @Ace in Slack after a call, and the summary + action items land on the opportunity.\n\n• Text it between meetings (\"move Thursday to Friday and tell them why\"), and it updates the invite, emails everyone, and confirms.\n\n• Ping it in a doc comment, or have it make a call on its own line.\n\nWhat comes back is finished work: CRM updated, email sent, invoice reconciled. When it hits a real fork in the road, it hands you the open questions instead of guessing.\n\n**Why trust it?** We spent two years automating high-volume work in mortgage, lending, and insurance, where a wrong answer is a compliance problem. Ace pairs a deterministic engine for must-be-identical work with AI for the fuzzy stuff. Every run is logged step by step, you set what needs approval, and you can revoke access like any employee's. SOC 2, encrypted credentials, role-based access.\n\n\"I really tried hard not to like this product, and I'm in love.\" — Asa Block, COO, Near Space Labs\n\n\"It's a no-brainer… Monday to Friday you won't believe how much more stuff you get done.\" — Jack Miller, President &amp; CEO, T3 Sixty\n\n## Our asks 🙏\n\n• Try Ace: One month free with unlimited usage for the YC community only. Sign up here:(<https://runautomat.com/workforce>) Use the promo code: ACEYC30\n\n• Intros: Know a team drowning in admin across a dozen systems? Send them our way.\n\n• We're hiring! <https://runautomat.com/careers#roles>",
        "url": "https://www.ycombinator.com/launches/UYU-ace-from-automat-it-s-instinct-but-for-work",
        "votes": 1,
        "created_at": "2026-09-30T16:33:11.033Z"
      },
      {
        "id": 69615,
        "title": "Automat RPA  - Robotic process automation for Chrome using ChatGPT and computer vision",
        "tagline": "Automate anything in Chrome using natural language",
        "body": "### **TLDR: Traditional automation software is slow and expensive, Automat is 10X faster and 1/10th the price. It lets operations teams automate using natural language.**\n\nHowdy y’all! Lucas here from [Automat](https://www.getlassoai.com/) - excited to share what my cofounder Gautam and I have been working on!\n\n**🧐 The problem: Traditional Robotic Process Automation is slow and expensive.**\n\nIt’s extremely time consuming and expensive to build out robot process automations using traditional tools like UiPath (\\~$66,000 per yearly license - Yikes!) not to mention the initial consultant setup fees which most people are forced to pay if they don’t have the resources in house (at the lowest end we’re talking $50,000+ per project - Double Yikes!!)\n\n💡 **Our Solution: Automat makes it 10X cheaper and faster to build any robotic process automation using natural language on chrome.**\n\nWe’re solving this by creating a platform that enables robotics process automation for Chrome using large language models and computer vision.\n\nCurrently our customers send us descriptions or videos of the processes they’d like us to automate and we use our internal tooling to quickly build out those automations.\n\nHere is one of our customer’s attended bots in action, scraping an email, looking through a prospecting tool, and saving it to a spreadsheet.\n\n![uploaded image](https://bookface.ycombinator.com/media/?type=post&id=69615&key=user_uploads/415306/a547a684-faee-4c6e-b3db-88cef800940a)\n\n\\\nWe want to let anyone regardless of timeline or budget automate the work they do by using natural language or simply sending Automat the workflow in a screen recording.\n\n**👯 A little more about us**\n\n![uploaded image](/media/?type=post&id=69615&key=user_uploads/415306/e82023cd-a7c1-4be3-8446-f2e0c2eae6f6)\n\nGautam and Lucas met on the first day of Design school at Carnegie Mellon University and have been roommates ever since:\n\n* At Google, their team was tasked with finding product applications of [LaMDA](https://blog.google/technology/ai/lamda/) in early 2020, and they built over 50+ prototypes integrating LaMDA across Google’s products and services. Eventually Gautam would go on to implement multiple demos for Google’s [first public Demonstration of LaMDA](https://www.theverge.com/2022/5/11/23065072/google-ai-app-test-kitchen-future-io-2022), the AI test kitchen.\n* They were hired together at Google’s Creative Lab as part of the [Creative Lab 5](https://www.creativelab5.com/), at Google they spent the following three years launching products like the [AI Test Kitchen](https://blog.google/technology/ai/join-us-in-the-ai-test-kitchen/), [Everyday Helper Robots](https://everydayrobots.com/), [Teachable Machine](https://teachablemachine.withgoogle.com/), the [Google Pixel Buds Pro](https://store.google.com/product/pixel_buds_pro?hl=en-US&pli=1), and most importantly a [high speed lucky charms cereal sorter](https://coral.ai/projects/teachable-sorter) 🍀\n* At Carnegie Mellon they studied Human Computer Interaction and Design. During their Junior year they created an adorable [AI robotic assistant](https://vimeo.com/270823057) that caught Google’s attention which awarded them a grant during their senior year to [research Robotics and AI](https://vimeo.com/393172151).\n\n**🙏 Our asks**\n\nAre you struggling in a deluge of repetitive or complex tasks that you wish you could hire someone for (or automate) but don’t have the budget? Send an email to [lucas@runautomat.com](https://lucas@runautomat.com) or submit a request on our [website](https://www.getlassoai.com/).\n\nDoes the above sound like someone you know? We’d appreciate intros to anyone. Let us know and we can send you over a quick intro blurb to make it an easy email to forward.\n\n**YC Special Offer:** For the first 10 YC companies that reach out we’ll waive the setup fee associated with building your automation!",
        "url": "https://www.ycombinator.com/launches/I6p-automat-rpa-robotic-process-automation-for-chrome-using-chatgpt-and-computer-vision",
        "votes": 91,
        "created_at": "2023-02-23T19:08:21.664Z"
      }
    ]
  },
  {
    "id": 28415,
    "name": "moonrepo",
    "slug": "moonrepo",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3de25b12e8aab670255b22d53c12d30ccd142ae5.png",
    "website": "https://moonrepo.dev",
    "all_locations": "Portland, OR, USA; Remote",
    "long_description": "moonrepo is a developer tool that reduces build/test/deploy times, and maintenance costs for companies. We’ve achieved this through moon, our open source build system and repository management tool. moon can be paired with moonbase, our paid service that provides cloud caching, CI insights, code ownership, and health score related metrics. The company is founded by Miles Johnson and James Pozdena who have a combined 25+ years in the software development industry with tenure at Airbnb and Coinbase.",
    "one_liner": "Open source build tool for monorepos and large codebases",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Productivity",
    "launched_at": 1675878806,
    "tags": [
      "Developer Tools",
      "SaaS",
      "Productivity",
      "Open Source",
      "Enterprise"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2023",
    "status": "Inactive",
    "industries": [
      "B2B",
      "Productivity"
    ],
    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Fully Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": [
      {
        "question": "Describe what your company does in 50 characters or less.\n",
        "answer": "We build solutions for common devx/tool problems."
      },
      {
        "question": "What is your company going to make? Please describe your product and what it does or will do.\n",
        "answer": "We plan to make a suite of tools and services to solve common developer experience and company workflow problems. These are problems that all companies deal with at some point in time, and range from solutions like a configuration service, code ownership, repository management, deploy/merge locks, CI insights and metrics, deployboard, and much more.\r\n\r\nMany companies custom build in-house solutions to these problems, as there are non-viable or no alternatives. This diverts focus and resources away from their mission. We hope to provide solutions to these problems, so that companies can focus solely on their mission.\r\n\r\nThe first tool in this suite is moon, which is a language agnostic build system (built in Rust), with first class support for CI pipelines and the developer experience. In the future, this will be expanded to also support CD workflows. To expand upon moon, we are currently building a service called moonbase, which supports remote caching of build artifacts, and in the future will aggregate CI insights to generate dashboards, and provide a user interface for CD deployments.\r\n\r\nLooking to the future, we have plans for a large array of tools and services to build, as mentioned above. Our goal is to provide a holistic developer/infra platform."
      }
    ],
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/moonrepo",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/moonrepo.json",
    "year_founded": 2022,
    "city": "Portland",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/moonrepo/",
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    "github_url": "https://github.com/moonrepo",
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    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
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    "founders": [
      {
        "user_id": 1247217,
        "full_name": "Miles Johnson",
        "title": "Founder",
        "founder_bio": "I'm very passionate about developer tooling and the developer experience.\n\nWith 15 years of industry experience under my belt working across the entire web stack, I enjoy testing my skills and knowledge against complex problems, but what I really love is supporting my fellow peers by building solutions to improve their developer experience and productivity.",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/mileswjohnson/",
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      },
      {
        "user_id": 1251045,
        "full_name": "James Pozdena",
        "title": "Founder",
        "founder_bio": "Technical co-founder from Portland, OR",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/jpozdena",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0c79a10657798606f022dca11f21324af6fa3421.jpg"
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    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 69492,
        "title": "🌑 moonrepo - Simplifying codebase management and organization",
        "tagline": "From build to deploy, moonrepo is a better way to manage codebases, save developer time, and boost your business.",
        "body": "Hey YC!\n\nMiles and James here from [moonrepo](https://moonrepo.dev). Are you struggling with large codebases? Well, look no further! We built moonrepo to simplify repository management, project ownership, task running, and everyday developer and productivity workflows.\n\n### 🧑‍💻 Who is it for\n\nFor companies or individuals that maintain monorepos or large codebases (or any size really), and want to reduce build and CI times, and ensure their repository stays healthy.\n\n### 🚀 How we’re solving it\n\nAfter more than a decade in the industry, with many of those years working on infrastructure and developer tooling-related products, we weren’t happy with the status quo of tooling or ad-hoc solutions that companies are required to build. As such, we set out to build moon, a language-agnostic task runner that is smart enough to only run against affected code changes, and [moonbase](https://moonrepo.dev/moonbase), an upstream service for monitoring CI pipelines. We wanted our products to be enjoyable to use and easy to understand.\n\n![uploaded image](/media/?type=post&id=69492&key=user_uploads/1247217/8945b4a3-e49c-410b-ae5f-5c59794fbbea)\n\n### 🛰️ How it works\n\nAt a high level, we are putting an immense focus on the developer experience. For example, the configuration is in YAML, which everyone is familiar with, and is **_not_** a proprietary syntax. Tasks are defined and run as if you were running them in the terminal; there are no more abstractions. We automate common and everyday workflows. We manage a toolchain, ensuring the correct version of languages is used (no more “works on my machine”). And lastly, our foundation is built on Rust and Tokio, so performance is first-class, the runtime is reliable, and memory safety is guaranteed.\n\n![uploaded image](/media/?type=post&id=69492&key=user_uploads/1247217/c5d3c251-0768-493b-8bed-28c9fc60bc6a)\n\n### Try it today!\n\nOur moon task runner is free and open source, and will always be! Start adopting today and see the immediate benefits in your codebase. <https://moonrepo.dev/moon>\n\nOur moonbase service is also available under our free tier (with reasonable limits). Join today in 1-click! <https://moonrepo.dev/moonbase>\n\nIf you have any questions or would like a demo, feel free to join our Discord community and follow us on [Twitter](https://twitter.com/tothemoonrepo)!",
        "url": "https://www.ycombinator.com/launches/I4q-moonrepo-simplifying-codebase-management-and-organization",
        "votes": 21,
        "created_at": "2023-02-21T19:13:22.175Z"
      }
    ]
  },
  {
    "id": 28416,
    "name": "Pierre",
    "slug": "pierre",
    "former_names": [
      "Umbrella Company"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b78dca2b9a7dd83a3f06b2d4efd75eb21f68233b.png",
    "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": [
      "AI-Enhanced Learning",
      "Developer Tools",
      "B2B",
      "Productivity",
      "Collaboration"
    ],
    "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",
      "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/pierre",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/pierre.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "",
    "x_url": "https://x.com/pierredotco",
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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": 1253715,
        "full_name": "Jacob Thornton",
        "title": "Founder",
        "founder_bio": "Jacob Thornton has been doing software development in the bay area for over a decade, as an early employee at startups like Twitter, Medium, and Coinbase.\n\nDuring this time he contributed to several large open source projects (most notably as the co-creator of Twitter Bootstrap), given talks around the world (https://www.youtube.com/watch?v=UIDb6VBO9os), and written several chapters in technical books (beautiful javascript, if Hemingway wrote javascript).",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jacob-thornton-13a6a5162/",
        "x_url": "https://twitter.com/fat",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/12170102c839a10c7f7a28f061f7b97c3d70f378.jpg"
      },
      {
        "user_id": 46928,
        "full_name": "Ian Ownbey",
        "title": "Founder",
        "founder_bio": "I have worked for a number of consumer tech companies ranging from Twitter in 2010 to Coinbase in 2018. I started as a backend engineer using Ruby on Rails and then eventually moved up the stack to iOS engineering, React Native engineering and now mostly React. I enjoy hanging out with my cat when not working.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/ian-ownbey-4aa5ba117",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/beda0dcd17ad0f5ebb42b391b4c8c1b7cc8560f1.jpg"
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      {
        "id": 69619,
        "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.**",
        "url": "https://www.ycombinator.com/launches/I6t-pierre-a-new-way-to-review-code",
        "votes": 67,
        "created_at": "2023-02-23T20:27:31.367Z"
      }
    ]
  },
  {
    "id": 28650,
    "name": "Artie",
    "slug": "artie",
    "former_names": [
      "Artie Technologies"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/973d2f0c6c4d07505113e974a08d18864eb95d54.png",
    "website": "https://www.artie.com/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Artie is software that streams data from databases to data warehouses in real-time. Today, most companies run their ETL process every few hours or overnight, so their data warehouse is always out of date; with Artie, the warehouse always has live production data.",
    "one_liner": "Software that streams data from databases to warehouses in real-time",
    "team_size": 20,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1684375922,
    "tags": [
      "Developer Tools",
      "SaaS",
      "Data Engineering",
      "Enterprise Software"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2023",
    "status": "Active",
    "industries": [
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      "Infrastructure"
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    "regions": [
      "United States of America",
      "America / Canada"
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    "stage": "Growth",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/artie",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/artie.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/artie-technologies/",
    "x_url": "https://x.com/artie_labs",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/artie-a438",
    "github_url": "https://github.com/artie-labs/transfer",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/973d2f0c6c4d07505113e974a08d18864eb95d54.png",
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    "primary_partner": {
      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
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    "founders": [
      {
        "user_id": 1276059,
        "full_name": "Jacqueline Cheong",
        "title": "Founder",
        "founder_bio": "Co-founder and CEO at Artie. Building the real-time data streaming platform for AI. \n\nWe give companies the kind of streaming pipelines and deep observability that Netflix, DoorDash, and Instacart built in-house - without hiring 10+ engineers and spending 1-2 years on platform work. Artie automates the entire data ingestion lifecycle, from capturing changes to merges, backfills, and observability, and scales to billions of change events per day. ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jacqueline-cheong/",
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      {
        "user_id": 674147,
        "full_name": "Robin Tang",
        "title": "Founder",
        "founder_bio": "CTO @ Artie. Software engineer with a background in distributed systems.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/tang8330/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7cdcac4bb146b8aabcbb1bc6751fee1c6c37d9b5.jpg"
      }
    ],
    "jobs": [
      {
        "id": 85441,
        "title": "Enterprise Account Executive",
        "url": "https://www.ycombinator.com/companies/artie/jobs/HyaHWUs-enterprise-account-executive",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$240K - $320K",
        "equity_range": "",
        "experience": "6+ years",
        "visa": "Will sponsor",
        "skills": []
      },
      {
        "id": 94613,
        "title": "Solutions Engineer",
        "url": "https://www.ycombinator.com/companies/artie/jobs/APdtYeH-solutions-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$175K - $200K",
        "equity_range": "",
        "experience": "3+ years",
        "visa": "Will sponsor",
        "skills": [
          "SQL Server",
          "Oracle",
          "Data Warehousing",
          "Kafka"
        ]
      },
      {
        "id": 99179,
        "title": "Product Engineer",
        "url": "https://www.ycombinator.com/companies/artie/jobs/A5udo6A-product-engineer",
        "location": "San Francisco",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$150K - $250K",
        "equity_range": "",
        "experience": "6+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 99181,
        "title": "Senior Software Engineer ",
        "url": "https://www.ycombinator.com/companies/artie/jobs/7KTFRRy-senior-software-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Backend",
        "salary_range": "$150K - $250K",
        "equity_range": "",
        "experience": "6+ years",
        "visa": "Will sponsor",
        "skills": []
      },
      {
        "id": 100518,
        "title": "Senior Business Development Representative - Enterprise ",
        "url": "https://www.ycombinator.com/companies/artie/jobs/vv6SEu9-senior-business-development-representative-enterprise",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Sales",
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    ],
    "news": [
      {
        "title": "Artie: Real Time Data Streaming For The AI Age",
        "url": "https://www.youtube.com/watch?v=M57MeOY-n3g",
        "date": "Jan 26, 2026"
      },
      {
        "title": "Artie helps companies put data to work faster with real time syncing | TechCrunch",
        "url": "https://techcrunch.com/2024/02/14/artie-helps-companies-put-data-to-work-faster-with-real-time-syncing/",
        "date": "Feb 14, 2024"
      }
    ],
    "launches": [
      {
        "id": 111491,
        "title": "Artie Free Plan: real-time data replication for $0/mo",
        "tagline": "Stream data to your warehouse or another database, free forever – up to 1M rows a month.",
        "body": "### TL;DR\n\nArtie streams production data into your warehouse or another database in real time, so your downstream systems and workflows never run on stale data.\n\nWe launched Artie’s Free plan so startups and solo builders can get real-time database replication without a card, sales call, or CDC infrastructure project.\n\n[Check out our launch video:](https://www.youtube.com/watch?v=jXPNzOyPVH0)\n\n### The problem\n\nA solo developer wiring Supabase or Postgres into a warehouse doesn’t want to take on a CDC project. A startup’s first data hire needs fresher data for a product workflow, payments, or support, but doesn’t have a data platform team to build it. A larger company wants to test a narrow use case before pulling in procurement and security.\n\nAll three have the same initial question: will this work with our database, our destination, and our data? Answering that should take less than an afternoon, without needing to put down a credit card or join a sales call.\n\nFor Keep, a fintech startup, setting up a connector on Artie took around 10 minutes. Their team wanted Postgres and MongoDB data in Snowflake, but didn’t want to spend months building and maintaining pipelines. Their CTO’s reason for that was straightforward: he wanted the team differentiating on product, not babysitting data infrastructure. [Read Keep’s story](https://www.artie.com/customer-stories/keep-enables-real-time-data-stack-and-audit-logs?utm_source=ycombinator&utm_medium=organic&utm_campaign=free_plan).\n\n### Why now\n\nStartups are building products and operating workflows around production data with smaller teams than ever. They want that data in their warehouse (or another database) in real time, but need a way to test a real workload without building and running Kafka, Debezium, connectors, and monitoring.\n\n### What's included\n\nArtie Free includes:\n\n* Two active pipelines\n* 1 million billable rows per month\n* Backfills, not counted toward the monthly row limit\n* Sources: Postgres, MySQL, MongoDB, DynamoDB, CockroachDB, DocumentDB, Amazon Keyspaces, and PlanetScale\n* Destinations: Snowflake, BigQuery, Redshift, Databricks, MotherDuck, Postgres, S3, GCS, and ClickHouse\n\n[See the full plan details](https://www.artie.com/pricing?utm_source=ycombinator&utm_medium=organic&utm_campaign=free_plan).\n\n### Artie’s MCP Server\n\nArtie also has [an MCP server,](http://mcp.artie.com/?utm_source=ycombinator&utm_medium=organic&utm_campaign=free_plan) so you can manage pipelines from Claude or Codex instead of switching to the dashboard. You can list and create pipelines, inspect schema changes, manage backfills and connectors, and search the Artie data catalog, all from a conversation.\n\nThe MCP server is now a [ChatGPT Plugin](https://chatgpt.com/plugins/plugin_asdk_app_6a62a153d4088191a5e551ec94e025da?q=artie) and listed in [Claude's connector directory](https://claude.ai/directory/artie). You can also use another MCP-compatible client, such as Cursor, by pointing it at `https://mcp.artie.com/mcp` with an API key from your Artie dashboard. [Full setup docs here](https://www.artie.com/docs/api/mcp?utm_source=ycombinator&utm_medium=organic&utm_campaign=free_plan).\n\n### Our ask\n\nIf you are a founder, solo developer, or first data hire, [try Artie’s Free plan](https://app.artie.com/signup?utm_source=ycombinator&utm_medium=organic&utm_campaign=free_plan) with one real workload. Tell us what gets in the way: permissions, configuration, schemas, or getting the first row through.",
        "url": "https://www.ycombinator.com/launches/T0F-artie-free-plan-real-time-data-replication-for-0-mo",
        "votes": 33,
        "created_at": "2026-08-20T16:50:12.222Z"
      },
      {
        "id": 102815,
        "title": "Artie - Real-time data replication to your data warehouse",
        "tagline": "Give your AI agents fresh data they can actually act on",
        "body": "**TL;DR:** Artie is a fully managed, real-time data replication tool that streams every row-level change from your production database to your warehouse in under 60 seconds. You can now sign up and start replicating today, no call required. Most teams run their first sync in under an hour.\n\n<https://www.youtube.com/watch?v=BYgz9NaIBLg>\n\n**The Problem**\n\nGetting data from your production database to your warehouse in real time has always meant picking your poison.\n\nYou build it yourself: Kafka, Debezium, custom merge logic, months of engineering, and years of maintenance as schemas evolve and the engineers who built it move on.\n\nYou use an existing CDC tool: usually something inherited, unreliable at scale, and not built for the warehouse destinations you're actually running.\n\nOr you accept stale data: dashboards refreshing every 3-24 hours, AI pipelines reasoning over yesterday's snapshot, analytics teams filing 9 am tickets asking why the numbers don't add up.\n\nMost teams are somewhere on this spectrum – either maintaining a pipeline they didn't want to build, or working around data they can't trust. That was a manageable problem when stale dashboards just annoyed your analytics team, but it becomes a bigger beast when AI agents are making pricing decisions, routing support tickets, and scoring risk off the same lagged data.\n\nA warehouse that's 12 hours behind isn't a minor inconvenience anymore – it's a liability.\n\n**The Solution**\n\nSee it work: <https://www.youtube.com/watch?v=xp0Yp77_Z9w>\n\nArtie handles the entire replication layer so you don't have to. No self-built Kafka stack to maintain, no unreliable CDC tool to babysit, no stale data to apologize for. Connect your source, choose your destination, and your warehouse stays in sync with production continuously.\n\nAI agents are only as good as the data they act on. If your warehouse is hours behind, your agents are too. Artie gives your AI layer what it actually needs: a warehouse that reflects production in real time, without engineering overhead.\n\n**How It Works**\n\nArtie uses change data capture (CDC) to read directly from your database's replication logs – capturing every insert, update, and delete as it happens. Those changes stream continuously to your warehouse, landing in under 60 seconds. There's no bulk export, no scheduled job, no polling. Just a live, accurate reflection of your production data.\n\nUnder the hood, Artie handles the operational complexity: schema changes propagate automatically, delivery is exactly-once even through failures, and your destination tables stay in sync without any pipeline code on your end. The things that take most teams a year or two to get right are already solved.\n\n**Sources:** PostgreSQL, Amazon Aurora/RDS, GCP CloudSQL, Supabase, MySQL, Microsoft SQL Server, MongoDB, DocumentDB, DynamoDB, Oracle, CockroachDB, Amazon Keyspaces (Cassandra), and an Events API\n\n**Destinations:** Snowflake, BigQuery, Redshift, Databricks, ClickHouse, PostgreSQL, MySQL, Microsoft SQL Server, MotherDuck, S3, GCS, Iceberg REST Catalog, and Amazon S3 Tables\n\n**The Team**\n\nRobin (co-founder and CTO) has been building large-scale data pipelines his entire career – from processing 14 billion daily events at [Outbound.io](http://Outbound.io), to filing patents on event streaming at Zendesk, to running data infrastructure at Opendoor. He started Artie because he kept hitting the same ceiling: pipelines that worked until they didn't, and teams spending years maintaining infrastructure that should have been solved.\n\nBefore co-founding Artie, I covered enterprise software at Bank of America and Balyasny Asset Management and kept running into the same gap: companies burning engineering cycles on data pipelines that shouldn't require a team to maintain. We've been building Artie together for three years, went through YC S23, and closed a $12M Series A led by Dalton Caldwell at Standard Capital.\n\n**Our Ask**\n\nIf you're a data engineer or engineering manager tired of stale warehouse data, [try it yourself](https://go.artie.com/launch) today. See real-time replication running in your own environment – not a demo, not a sandbox, but against your actual data.\n\nIf you need private networking, dedicated infrastructure, or compliance support, [book a demo](https://go.artie.com/2822ee) and we'll walk you through what an enterprise setup looks like.\n\n[Try Artie today](https://go.artie.com/launch)",
        "url": "https://www.ycombinator.com/launches/QkJ-artie-real-time-data-replication-to-your-data-warehouse",
        "votes": 43,
        "created_at": "2026-06-09T17:12:18.002Z"
      },
      {
        "id": 88730,
        "title": "🐘 Artie for Enterprise - Data Replication at Petabyte Scale",
        "tagline": "High-volume, low-latency data replication that scales effortlessly",
        "body": "# TL;DR\n\n[Artie](https://www.artie.com/?utm_campaign=launch-week-q125&utm_source=yc-launch) streams data from databases to data warehouses in real-time and more reliably than traditional ETL solutions. Many companies are still running their ETL process every few hours, so their data warehouse is constantly out of date; with Artie, the data warehouse always has live production data.\n\nArtie was founded to solve an enterprise data movement problem. Today, we’re launching Artie for Enterprise, for teams requiring high-volume, low-latency data replication that scales effortlessly. Whether dealing with massive volumes, strict security requirements, or mission-critical workloads, Artie ensures data is always live, accurate, and easy to manage. 🚀\n\n![uploaded image](/media/?type=post&id=88730&key=user_uploads/89898/675b1398-6b54-40a0-888f-a3f4f487ffc3)\n\n# Problem\n\nEnterprises need real-time, reliable, and secure data replication—but existing solutions make this far more painful than it should be.\n\nTraditional ETL pipelines often run on fixed schedules, updating data warehouses hours behind reality and leaving teams with outdated insights. Many replication tools try to brute-force data movement by running expensive, inefficient queries that **increase load on production databases**, slowing down applications and, in extreme cases, even **bringing them down entirely**. Scaling these systems across thousands of tables typically requires **manual, error-prone configurations**, forcing teams to spend countless hours debugging pipelines just to keep data flowing.\n\nOn top of that, many enterprises operate in highly regulated environments where data can’t be fully offloaded to the cloud. Traditional replication solutions struggle to support hybrid deployments, forcing teams to choose between security and ease-of-use.\n\n# Artie for Enterprise provides reliable, secure, and high-volume data replication\n\n### Terraform support\n\n_“Um, we have thousands of tables to configure. Do I really need to click thousands of times on your dashboard to get connectors set up?”_ We hear this question a lot and our answer is “**Absolutely not”**, which is where our Terraform provider comes in. \n\nJust because your data volume is high does not mean management needs to be equally complex. No more endless clicks—just code it, deploy it, and go.\n\n![uploaded image](/media/?type=post&id=88730&key=user_uploads/1276059/ed2daad8-2763-4dfc-aaad-ea336ba4daf0)\n\n### Multi-step merge\n\nMerging large, frequently updated tables can be expensive and slow. We wanted to solve this problem without forcing customers to increase compute costs or scale up their virtual data warehouses.\n\nWith multi-step merge, Artie now loads data into a staging table in multiple bursts, allowing updates to accumulate before merging into the target table. This reduces latency and improves efficiency. Customers can now control how often data lands in the staging table before triggering a final merge—giving them real-time syncs with more flexibility and cost savings.\n\n![uploaded image](/media/?type=post&id=88730&key=user_uploads/1276059/0dcc6696-60c9-4ab8-a301-9764abbb5756)\n\n### Hybrid deployment\n\nEnterprise-grade replication means deployment flexibility is non-negotiable. There are many organizations out there that handle data containing sensitive information and are required to operate under strict regulations.\n\nOur hybrid deployment model ensures the security of on-premise data processing with the ease of use of cloud services. What’s more? Artie’s fully-managed service allows for zero-maintenance, and removes the need to install and manage client-side agents.\n\n![uploaded image](/media/?type=post&id=88730&key=user_uploads/1276059/5464e25f-5c07-4bbc-8926-ea10fc6c48e1)\n\n### MySQL Connector upgrade\n\nWe’ve made major improvements to our MySQL connector, making it enterprise-grade with improved performance, efficiency, and automation. These updates streamline database operations, reduce disk usage and I/O load, and automates data synchronization without complex configuration requirements and management overhead. \n\nKey improvements include full DDL and gh-ost migration support for seamless, non-disruptive schema changes, automatic fan-in for partitioned tables, and GTID support for reliable transaction replication.\n\n### PostgreSQL CTID scanning\n\nBackfills can be disruptive and resource-intensive. That’s why Artie is built to seamlessly recover from errors and avoid backfills unless absolutely necessary. \n\nHowever, in the event that backfills are required, how do we minimize disruption? Enter PostgreSQL CTID; an alternative backfill method that is **10-20x faster** than traditional methods.\n\n### Datadog integration\n\nAt Artie, we’ve always been big on observability. What good are your data pipelines if nobody has visibility into them? We prioritize accurately monitoring your pipeline performance and making sure you know what’s up. \n\nWith our Datadog integration, you can now track all Artie-exposed metrics directly from your Datadog dashboard. This allows you to **proactively monitor pipeline performance, set up custom alerts**, and build dashboards for deeper insights.\n\nStay on top of your data pipeline health—effortlessly.\n\n![uploaded image](/media/?type=post&id=88730&key=user_uploads/1276059/38889e0e-30ca-495f-b777-4af640e9aa3b)\n\n# Curious to learn more?\n\nFollow our journey on [LinkedIn](https://www.linkedin.com/company/artie-technologies), [X](https://x.com/artie_tech) and reach out to us [here](https://www.artie.com/contact?utm_campaign=launch-week-q125&utm_source=yc-launch) to see how you can benefit from enterprise-grade replication!",
        "url": "https://www.ycombinator.com/launches/N58-artie-for-enterprise-data-replication-at-petabyte-scale",
        "votes": 17,
        "created_at": "2025-03-18T14:06:08.364Z"
      },
      {
        "id": 76461,
        "title": "Artie’s Analytics Portal - Real-time data pipeline observability",
        "tagline": "Real-time observability into database pipelines and peripheral infrastructure",
        "body": "# TL;DR\n\n[Artie](http://www.artie.so) is a real-time database replication solution. We leverage change data capture (CDC) and stream processing to perform data syncs in a more efficient way, which enables sub-minute latency and helps optimize compute costs. Today, we’re launching our Analytics Portal to provide visibility into our streaming pipelines and offer production-level monitoring for related system infrastructure out-of-the-box.\n\nWith the Analytics Portal, we hope to help alleviate some of the challenges that data teams face when running their data stack. By offering real-time observability into database pipelines and peripheral infrastructure, we hope companies can increase their understanding of how systems impact one another, reduce downtime/debug issues faster, and generate proactive alerts to maintain robust infrastructure. \n\n# **Visibility related to database replication is lacking**\n\nThe core of database replication is transferring data in a timely, accurate, and reliable manner. This is table stakes. In addition, there is a lot more happening in the peripheral, such as database monitoring, data pipeline visibility, data latency monitoring, and others. Data engineers need visibility to answer questions like: \n\n* How many rows have been synced in the past hour? How does that compare to the average/median/last month? \n* What is the data latency for our organization’s three most important tables? What are the factors that impact data latency and how are those metrics trending? \n* How are my systems performing?\n  * Are there any database permission errors that may cause my data pipeline to go down? \n  * Are my databases sized correctly? How is CPU, memory, and storage utilization? \n  * Is my replication slot growing? By how much?\n\n \n\nSetting up these metrics and monitors is important to help with debugging and maintaining a robust database replication solution. However, this requires expertise and domain knowledge that may not be accessible at every company. There is also no standardization of which metrics to track and what benchmarks to follow. To make matters worse, when it comes to adopting cloud solutions, database/pipeline visibility is severely limited. When pipelines break down, customers are often left in the dark, not knowing what broke, why it broke, and how to fix it. \n\n# **Artie’s Analytics Portal unlocks visibility & reduces MTTD**\n\nWe are extremely excited to announce our Analytics Portal to increase the visibility and observability of our streaming pipelines. This will provide insights into system-level infrastructure and help with monitoring database and pipeline health. When identifying and resolving issues, one of the most important metrics is to reduce MTTD (mean time to detection). With Artie’s streaming pipelines and periodic jobs like [Postgres Watcher](https://docs.artie.so/real-time-sources/postgresql#postgresql-watcher), metrics are being sent to our Analytics Portal in flight, as the underlying data is still being processed. \n\n![uploaded image](/media/?type=post&id=76461&key=user_uploads/1276059/f4fe85ba-5ced-4892-9653-ed030638826d)\n\nWith the first iteration of our Analytics Portal, we are providing industry-standard telemetry to streaming pipelines and related infrastructure. Data teams will be able to observe the following: \n\n* Data ingestion latency by table and database/deployment\n* Operation distribution by table and database/deployment\n* Rows synced by table and database/deployment\n* Database monitors that are related to and can impact pipeline performance: \n  * Permission errors that may interfere with data replication\n  * Replication slot size\n  * Free disk space\\*\n  * CPU utilization\\*\n  * Memory and Disk I/O (input/output)\\*\n  * Average transaction time\\*\n  * Existence of long-running queries\\*\n\n\\*coming soon\n\n# Production level monitoring out-of-the-box\n\nThe Analytics Portal initially comes with a set of pre-built charts and monitors. Customers are able to drill down to get deployment, database, and table-level statistics.\n\n![uploaded image](/media/?type=post&id=76461&key=user_uploads/1276059/bcbbd68a-9808-48c5-92e5-1f61b53f9d86)\n\n![uploaded image](/media/?type=post&id=76461&key=user_uploads/1276059/b5ec3d58-4f94-4af0-89d3-14ab920b2003)\n\nThe pre-built monitors that we are launching with include alerts for database permission errors and replication slot growth (for Postgres users). Over time, we will add alerting for the other monitors we mentioned above and more. This enables customers to have production-level monitoring set up out-of-the-box for their business-critical data. \n\nFor example, an e-commerce company might be watching its `online transactions` table closely during the holidays. Let’s say they observe data ingestion latency going up for `online transactions`. They zoom out and realize it’s not just the `online transactions` table that is experiencing higher latency, but all tables under their Postgres connector are impacted and very few rows have been synced in the past 5 minutes. To troubleshoot this, they look over to the database monitors and realize their database’s replication slot has been growing and the culprit is a long-running query that has locked the table and is preventing Postgres from advancing the replication slot. After a quick Slack message to their internal DevOps team, the query is killed and the issue is resolved. \n\n# Making the Analytics Portal more actionable & customizable over time\n\nOver time, we will make the data more actionable and customizable. In the near future, we plan to enable row-based monitoring such that customers can monitor custom business logic. In addition to the pre-built charts and monitors that we provide out-of-the-box, we want to allow customers to create custom charts and configure views based on metrics that matter to their business. \n\nFor example, say you are working at a Fintech company that wants to monitor live transactions to detect fraud and abuse on your platform. You have a `transactions` table and this table is being synced to your Snowflake instance. You should be able to generate a chart to plot the average, median, p95, and max transaction sizes across various lookback periods (30 minutes, 1 hour, 24 hours, 7 days, etc). Then you can set up business logic monitors such as:\n\n* Flag transactions that are 1.5 standard deviations above average coming from a merchant who signed up on the platform less than one week ago\n* Flag key accounts where transaction volume has increased above or fallen below a certain threshold in the past hour\n\n![uploaded image](/media/?type=post&id=76461&key=user_uploads/1276059/1a22097c-f925-43c4-9fac-c5bf5035b55d)\n\nDepending on how you’d like to be notified, Artie plans to support the following escalation channels:\n\n* Email\n* Slack\n* Webhooks\n\nIn this example, the escalation channel is a webhook to your API server so you can then run a more rigorous machine-learning fraud model against a particular merchant account or transaction.\n\n# **Contact us at **[**hi@artie.so**](http://www.artie.so)** to learn more!**",
        "url": "https://www.ycombinator.com/launches/JtF-artie-s-analytics-portal-real-time-data-pipeline-observability",
        "votes": 24,
        "created_at": "2023-11-27T17:42:21.200Z"
      },
      {
        "id": 72536,
        "title": "Artie - real-time data streaming for databases ⚡",
        "tagline": "We transfer data from databases to data warehouses in real-time with CDC streaming",
        "body": "# _TL;DR_\n\n_Artie is an open-source, streaming version of Fivetran - we transfer data from databases to data warehouses in real-time. Setting up a connector takes minutes and Artie leverages change data capture (CDC) to help companies reduce their data warehouse costs by 50%! We enable organizations to unlock real-time insights for better decision making. _[_Star us on GitHub_](https://github.com/artie-labs/transfer)_!_\n\n![uploaded image](/media/?type=post&id=72536&key=user_uploads/1276059/60958f68-f519-4d78-bb98-c2c33974cb39)\n\nHi everyone, we are Jacqueline and Robin and we’re the team behind [Artie](https://www.artie.so/?utm_source=YC&utm_medium=newsletter&utm_campaign=launchYC&utm_id=launchYC). We’re on a mission to eliminate data latency and make it easy for every company to enable real-time data streaming!\n\nData is typically synced from production databases to the data warehouse once every X hour(s)/day(s) - this is a constraint that companies have lived with for decades. Robin personally felt the pain of not having access to production data in real-time and there were no easy to use out-of-the-box solutions, so we decided to build one! \n\n# **❌ The Problem**\n\nDoes your company sync data to the data warehouse every 6 hours, or worse, once a day? Are your analytics always lagged and filled with stale insights? **Why settle for a data platform that’s barely good enough when you can have real time data AND reduce your data warehouse costs?!** Not to mention you can have Artie set up in minutes!\n\nTraditional ETLs are based on **batched processes** that operate on a cron schedule (DAGs, Airflow) and **cannot achieve real-time data syncs**.\n\nBuilding and managing streaming data pipelines is hard. Most companies have a small team of data engineers and they often spend all day maintaining their data pipelines, which is not productive.\n\nFactors companies should consider if they want to self-manage pipelines:\n\n* Can the solution scale to multiple different data sources?\n  * How easy is it to add new data sources?\n  * How easy is it to manage across all the data sources?\n* Can the solution scale to handle 1m+ queries per second?\n  * Is the solution horizontally scalable?\n  * Do workers require coordination? Or are they stateless and distributed?\n* How do you ensure there are no out of order or missing events (even when the system crashes)?\n* Can the solution handle schema evolution without creating breaking changes downstream?\n\n# **🎉 Solution**\n\nArtie leverages change data capture (CDC) and stream processing to achieve **sub-minute data latency (\\~typically 10-20 seconds)**. Since we **only transfer changed data**, Artie is more efficient than traditional ETLs and can help you **cut down on your data warehouse cost by 50%!**\n\nSetting up a connector requires no programming. Just follow the setup guide and deploy in minutes! After the initial snapshot, any changes in your database will be reflected in your data warehouse in real-time.\n\n![uploaded image](/media/?type=post&id=72536&key=user_uploads/1276059/879c552d-7c8a-402e-9378-56f55380308a)\n\n# **🎯 Who Needs Artie?**\n\n**Engineers** that are exhausted stitching together Airflow + AWS Glue + Apache Spark + AWS Kinesis/Kafka + Apache Flink 😵‍💫\n\n**Companies that are using traditional ETLs or batched processes**. Once you enable real-time, there is no going back (your data engineers/BI analysts won’t let you)! Think of all the previously unattainable use cases that you can now implement without data latency.\n\n**Companies that have a cost cutting initiative.** Adopt Artie’s CDC streaming capabilities to reduce your data warehouse costs!\n\n# **🙏 Ask**\n\nEmail [hi@artie.so](mailto:hi@artie.so) or sign up [here](https://artie.so/contact?utm_source=YC&utm_medium=newsletter&utm_campaign=launchYC&utm_id=launchYC) to try Artie today! \n\nWant to use open source? Install Artie at <https://github.com/artie-labs/transfer> (give us a ⭐!) and ping us on [Slack](http://artie.so/slack?utm_source=YC&utm_medium=newsletter&utm_campaign=launchYC&utm_id=launchYC), we’re happy to help you get started.",
        "url": "https://www.ycombinator.com/launches/Irw-artie-real-time-data-streaming-for-databases",
        "votes": 108,
        "created_at": "2023-06-26T15:13:53.399Z"
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    "id": 28659,
    "name": "PeerDB",
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    "long_description": "At PeerDB, we are building a fast, simple and the most cost effective way to stream data from Postgres to Data Warehouses, Queues and Storage engines. If you are running Postgres at the heart of your data-stack and move data at scale from Postgres to any of the above targets, PeerDB can provide value.\r\n\r\n\r\nWe support different modes of streaming - log based (CDC), cursor based (timestamp or integer) and XMIN based. Performance wise, we are 10x faster than existing tools. Features wise, we support native Postgres features such as comprehensive set of data-types incl. jsonb/arrays/postgis, efficiently streaming toast columns, schema changes and so on.",
    "one_liner": "Fast, native ETL for Postgres 🐘 🚀",
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    "industry": "B2B",
    "subindustry": "B2B -> Analytics",
    "launched_at": 1686776037,
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    "founders": [
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        "user_id": 728174,
        "full_name": "Sai Srirampur",
        "title": "Founder",
        "founder_bio": "Building world’s best data-movement experience for Postgres. Ex-Microsoft - Headed Solutions Engineering all up for PostgreSQL on Azure, Ex-Citus Data (YCS11 acq. Microsoft) - Early Engineer, IIIT-H Alumnus, He/His",
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        "user_id": 311868,
        "full_name": "Kaushik Iska",
        "title": "Founder",
        "founder_bio": "Working on PeerDB to make the Postgres ETL story stellar. Previous work experience includes leading teams at Google, Palantir, Safegraph.",
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      {
        "title": "Real-time database startup ClickHouse acquires PeerDB to expand its Postgres support | TechCrunch",
        "url": "https://techcrunch.com/2024/07/30/real-time-database-startup-clickhouse-acquires-peerdb-to-expand-its-postgres-support/",
        "date": "Jul 30, 2024"
      },
      {
        "title": "PeerDB raises $3.6 million seed funding to revolutionize data movement for PostgreSQL",
        "url": "https://blog.peerdb.io/peerdb-raises-3-6-million-seed-funding-to-revolutionize-data-movement-for-postgresql",
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      },
      {
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        "url": "https://siliconangle.com/2024/04/11/peerdb-raises-3-6m-accelerate-postgresql-data-movement/",
        "date": "Apr 11, 2024"
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      {
        "title": "Launch HN: PeerDB (YC S23) – Fast, Native ETL/ELT for Postgres | Hacker News",
        "url": "https://news.ycombinator.com/item?id=36895220",
        "date": "Jul 26, 2023"
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      {
        "id": 72937,
        "title": "PeerDB - Modern ETL in minutes, with SQL",
        "tagline": "Data store-first ETL/ELT, enabling 10x faster syncs and transforms",
        "body": "## **TL;DR**\n\nPeerDB is a Postgres-compatible SQL interface to seamlessly integrate multiple data stores. It enables data engineers to sync, transform and query data across their stores using simple SQL commands. PeerDB takes a data store native approach in engineering — enabling 10x faster ETL/ELT.\n\n## **Problem**\n\nExisting ETL/ELT tools primarily focus on supporting a wide range of connectors at the expense of delivering high-quality ones. This becomes evident when your workloads need scale or have demanding feature requirements. While Sai was working at Microsoft, it was common to see large enterprise customers try out the existing ETL tools and fail – as the tools were not meeting performance and reliability SLAs or were lacking the required features. Customers spent significant time and resources to build and manage in-house data pipelines.\n\n## **Our Solution**\n\n### Data-store nativity at its core, enabling 10x faster ETL/ELT\n\nPeerDB takes a data store-first approach to data movement. It supports highly adopted stores and implements multiple infrastructural and data store native optimizations – providing a blazing-fast and feature-rich ETL experience.\n\nWe are starting our journey by providing the world's best data integration/ETL experience for **PostgreSQL,** [one of most used and popular databases](https://db-engines.com/en/ranking_trend/system/PostgreSQL). For example, on Postgres we parallelize initial load for larger tables using CTID scans. This yields orders of magnitude speedups - Syncing 100s of GB reduces from days to minutes.\n\nOur architecture is designed for real-time syncs, which enables 10x faster Change Data Capture with data freshness of a few seconds even at large throughputs (10k+ tps). For example, in a sync from Postgres to BigQuery or Snowflake, PeerDB is 10 times faster than other tools and provides <30s data-freshness guarantees.\n\n![uploaded image](/media/?type=post&id=72937&key=user_uploads/728174/dc134471-e0d0-48c5-bbda-6d2ec339c421)\n\n### SQL as the ETL/ELT standard\n\nThe Postgres-compatible SQL layer for ETL makes the life of data engineers very easy. They can develop pipelines using a framework they are familiar with, without needing to deal with custom UIs and REST APIs. They can use [Postgres' 1000s of integrations](https://github.com/PeerDB-io/peerdb#postgres-compatible-sql-interface-to-do-etl) to build and manage ETL.\n\nWe extend Postgres' SQL grammar with a few new intuitive SQL commands to enable real-time data streaming across stores. As we evolve, we will make this grammar richer and the standard for ETL/ELT.\n\n## **Our Asks**\n\nIf PostgreSQL is a critical component of your data stack and you are running into challenges moving data in and out of Postgres, reach out to us at [founders@peerdb.io](mailto:founders@peerdb.io) or join our waitlist at <http://peerdb.io/> We would love to collaborate!\n\nAlso check out PeerDB’s Open Source repo - <https://github.com/PeerDB-io/peerdb> (don’t hesitate to leave us a star!)\n\n## **Finally, a bit about us**\n\nWe are Sai and Kaushik. We've been best buddies for the past 15 years now. We were roommates back in undergrad and actively collaborated since then. Now we have decided to start a business together! 🙂\n\n![uploaded image](/media/?type=post&id=72937&key=user_uploads/728174/4795901c-d1ac-4e3e-b565-7113c9ef3ca0)\n\nPrior to PeerDB, Sai worked at Microsoft leading Solutions Eng. for all PostgreSQL services on Azure. He was an early engineer at Citus Data (YC S11) and saw it through the Microsoft acquisition. Prior to PeerDB, Kaushik built operating systems and led data teams at Google, Safegraph and Palantir. He also represented India in ACM ICPC World Finals. With our diverse and complementary experiences, we are excited and confident to build the next-generation ETL/ELT!",
        "url": "https://www.ycombinator.com/launches/IyP-peerdb-modern-etl-in-minutes-with-sql",
        "votes": 60,
        "created_at": "2023-07-11T16:24:18.528Z"
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    "id": 28812,
    "name": "Cedana",
    "slug": "cedana",
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    "website": "https://cedana.ai",
    "all_locations": "New York City, NY, USA; Remote",
    "long_description": "Cedana (YC S23) brings hyperscaler and frontier-lab orchestration capabilities for AI workflows. Our core capability is live migration for CPUs and GPUs workloads. This increases cost savings up to 80%, accelerates time to first token 2-10x, and enables stateful reliability of training jobs even through catastrophic GPU failures. We've integrated our solution into K8s, and support Kueue and Slurm for training distributed jobs, and Kserve for serving inference.    \r\n\r\nOpenAI, Meta and Microsoft have flavors of these capabilities internally and we’re bringing them to everyone. \r\n\r\nOur vision is to transform cloud compute into a real-time, arbitraged commodity. \r\n\r\nhttps://www.cedana.ai",
    "one_liner": "Fast, reliable, reproducible AI with GPU live migration",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
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        "full_name": "Neel Master",
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        "full_name": "Niranjan Ravichandra",
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        "visa": "US citizen/visa only",
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        "title": "Systems Engineer: Linux Kernel Test and Validation",
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        "type": "Full-time",
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      {
        "id": 73681,
        "title": "Cedana - Real-time save, move and resume for compute",
        "tagline": "Solving critical GPU performance, reliability, capacity and cost problems",
        "body": "Hey, we’re Neel and Niranjan from [Cedana](https://cedana.ai/?utm_source=cedana&utm_medium=yc&utm_campaign=launch).\n\n![uploaded image](/media/?type=post&id=73681&key=user_uploads/77597/b1097aa9-66f2-4253-8243-63e63d5c23e9)\n\n### **The Problem**\n\nLosing work because of infra problems is painful. Imagine you have a long-running compute job and the instance fails. Your 20-hour job finished but because your pipeline was misconfigured you have to restart it from scratch.  \n\nBurning cash is stressful.  Poor utilization results in your inference jobs costing more.  If you’re managing a cluster of 1,000s of GPUs, poor utilization leaves money on the table even while demand is skyrocketing.    \n\nCold start times impact your customer satisfaction and their reliance on your solution.  \n\nLimited GPU access makes it difficult for you to innovate, and finding GPUs can be a full-time job of constantly identifying, evaluating, and adapting different vendors.    \n\n### **Our Solution**\n\nCedana is real-time migration for compute.  We automatically schedule and move workloads across instances and vendors without interrupting progress or breaking anything.\n\nThere are several critical benefits:\n\n* Utilization is maximized to save costs and eliminate idle resources.  \n* Job-level SLAs dynamically allocate compute between inference and training, prioritizing costs, latency, and performance based on preferences.  \n* Avoid re-running jobs from scratch due to infra, pipeline, or memory failures. Jobs continue their progress in the event of infra failure or spot revocation.\n* Access planet-scale compute through vendor aggregation\n* Solve the cold start problem by enabling fast auto-suspend-resume \n* Spot management that migrates and provisions new instances automatically upon revocation or failure.\n\n  \n\nOpenAI, Meta, Microsoft, and Databricks employ some of these methods internally and we’re bringing them to everyone.\n\n### **How it works**\n\n[Cedana](https://cedana.ai/?utm_source=cedana&utm_medium=yc&utm_campaign=launch) is available as an [open-source package](https://github.com/cedana/cedana-cli) and as a [managed service](https://www.ycombinator.com/launches/JAP-cedana-real-time-save-move-and-resume-for-compute). \n\n* Cedana needs no code modification and works with Linux processes or containers\n* Current use cases and customers range from AI Training and Inference, High-Performance Compute, DevTools, ML Ops platforms, and Computational Biology.\n* It automatically provisions and manages infra with your existing credentials. Our managed service can leverage our vendor relationships if preferred.\n\nHere’s a 1m30s [demo video](https://www.youtube.com/watch?v=KC4STzSQ_DU)\n\n### **Our Team**\n\nOur team has built real-world robotics and large-scale computer vision systems across a number of places including 6 River Systems/Shopify and MIT.  We’ve led the development, commercialization, and scale of NLP for clinical workflows used in the delivery of patient care.   Our team’s publications span computer vision, computer graphics, robotics optimization, and spacecraft/aerospace controls, with patents in AI use cases for grid energy management, optimal battery control, and healthcare. \n\n### **We kindly ask**\n\n* Give Cedana a try! [Check out our Github Repo](https://github.com/cedana/cedana-cli)\n* Please support us with a Github star",
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        "votes": 26,
        "created_at": "2023-08-01T22:03:04.520Z"
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    "name": "Atla",
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    "all_locations": "London, England, United Kingdom",
    "long_description": "Find and fix your agent’s most critical failures in hours, not days.\r\n\r\nAtla helps developers cut time spent on manually reviewing traces. Atla’s LLM judge evaluates your agent step-by-step, uncovers error patterns across runs, and suggests specific fixes—so you know exactly what to fix and why.\r\n\r\nAtla supports the most popular agent frameworks teams build with, including LangChain, CrewAI, and OpenAI Agents. With real-time monitoring, automated error detection, and prompt experimentation, Atla gives teams the visibility and control needed to confidently ship agentic systems that work. \r\n\r\nWe’re a team of researchers, engineers, entrepreneurs and operational leaders. Our expertise in evals was honed through training our own purpose-built LLM Judges, Selene and Selene Mini, which are available open-source and have been downloaded 60,000+ times.",
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        "full_name": "Maurice Burger",
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        "id": 93580,
        "title": "Atla: The improvement engine for AI agents",
        "tagline": "We help teams building AI agents find and fix recurring failures.",
        "body": "Hey everyone! [Roman](https://www.linkedin.com/in/roman-engeler-54416212b/) here, cofounder of Atla.\n\n# **TL;DR**\n\nAtla helps teams building AI agents find and fix recurring failures. Instead of just surfacing endless traces, Atla automatically identifies the patterns behind failures and suggests targeted fixes.\n\n**Ask:** Building agents? Try us at [atla-ai.com](http://atla-ai.com) to find your agent’s most critical issues and ship improvements in hours, not days. \n\n# https://youtu.be/LtvKBJKPxKE?feature=shared\n\n# **❌ The Problem**\n\nAgents are complex black boxes, chaining together plans, tool calls, and agent-to-agent interactions. For this reason:\n\n* Failures hide inside long traces and are difficult to spot at scale.\n* Current solutions that just display traces without identifying issues are not enough.\n\nWe’ve spoken to over 100 teams who experience similar pains of digging through thousands of traces without clear signal, and fixing one issue only to have another pop up. This slows down shipping and erodes trust in the system.\n\n# **🛠 Our Solution**\n\nAtla turns all that noise into actionable insights:\n\n1. **Error annotation**: We automatically flag errors at the step level to find the root cause of a failed run.\n2. **Pattern detection**: We cluster those errors across traces to surface the recurring, high-impact failures.\n3. **Actionable fixes**: For each failure mode, Atla generates targeted recommendations specific enough to implement as small pull requests.\n\nThe result: instead of chasing symptoms, you can focus on the 2–3 failures that actually move the needle.\n\n# 📈 **Impact so far**\n\n* A legal AI startup used in over 15 countries now spots prompt failures in days instead of weeks with Atla.\n* A fast-growing productivity AI startup doubled the number of improvements shipped with Atla.\n\n# **👷 Why Us**\n\nBefore starting Atla, I led product and engineering at two fast-growing startups and researched iterative self improvement of large language models at the Stanford Existential Risks Initiative.\n\nAt Atla, we’re a small, highly technical team of AI researchers and engineers obsessed with evaluation and reliability. We previously trained Selene, an LLM-as-a-Judge model downloaded 60k+ times.\n\n![uploaded image](/media/?type=post&id=93580&key=user_uploads/946667/61832c56-f4fa-4c93-a623-eb6c31f5b1f8)\n\n# 🙏 **Our Ask**\n\nIf you’re building agents, we’d love for you to **try Atla**: https://www.atla-ai.com/\n\nKnow teams building agents? Please **share this post** with them!\n\nThank you!",
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        "body": "### **TL;DR**\n\nMeet Selene, a state-of-the-art LLM Judge trained specifically to evaluate AI responses. Selene is the best model on the market for evals, beating all frontier models from leading labs across 11 commonly used benchmarks for evaluators. Today, we are releasing:\n\n* API/SDK - Integrate Selene into your AI workflow\n* Alignment Platform - Build custom evaluation metrics for your use case\n\n[Get started using Selene for free.](https://www.atla-ai.com/sign-up?utm_source=ycombinator&utm_medium=community&utm_campaign=SU_YC_launchyc_communitypost_sel1launch_)\n\n![uploaded image](/media/?type=post&id=88045&key=user_uploads/1125799/e44a5253-3117-4849-9c36-3f55ea2345a3)\n\nWatch our demo [here](https://youtu.be/5A8-XqUoNBc).\n\n### **The Problem**\n\nGenerative AI is unpredictable. Even the best models occasionally hallucinate, contradict themselves, or produce unsafe outputs. Many teams rely on the same general-purpose LLMs to evaluate AI outputs, but these models weren’t trained to be judges. That leads to:\n\n* **Inaccurate evaluations** and inefficient iteration cycles in development\n* **Risky, unpredictable** AI behavior in production\n\n### **Our Solution**\n\n* **A SOTA model for evals**: Selene outperforms all frontier models (OpenAI’s o-series, Claude 3.5 Sonnet, DeepSeek R1, etc.) across 11 benchmarks for scoring, classifying, and pairwise comparisons.\n\n  ![uploaded image](/media/?type=post&id=88045&key=user_uploads/1125799/8aec7a55-9ec9-4c98-86ae-ed3293fa3988)\n\n* **A platform to align our evaluator**: Adapt Selene to your exact evaluation criteria—like “detect medical advice,” “flag legal errors,” or “judge whether the agent upgraded its workflow correctly.”\n\n  ![uploaded image](/media/?type=post&id=88045&key=user_uploads/1125799/ae45cd9b-5315-4d1b-a5e5-971c1da285d4)\n\n\nSelene works seamlessly with popular frameworks like DeepEval (YC W25) and Langfuse (YC W23) — just add it to your pipeline. And it runs faster than GPT-4o and Claude 3.5 Sonnet.\n\n### **Who We Are & Why We’re Building This**\n\nWe’re a small, highly technical team of AI researchers and engineers, with folks from leading AI labs and startups. Our mission is to enable the safe development of AGI. As models grow more powerful, **we need a ‘frontier evaluator’ that keeps pace with frontier AI**. We see Selene as a stepping stone toward scalable oversight of powerful AI.\n\n![uploaded image](/media/?type=post&id=88045&key=user_uploads/1125799/c1aa726d-219c-46ca-b99f-e14279c499b2)\n\n### **Our Ask**\n\n[**Try Selene for free**](https://www.atla-ai.com/api) → Integrate our API into your eval pipeline.\n\n[**Try our Alignment Platform**](https://www.atla-ai.com/sign-up?utm_source=ycombinator&utm_medium=community&utm_campaign=SU_YC_launchyc_communitypost_sel1launch_) → Craft a custom eval for your application.\n\n[**Discord**](https://discord.com/invite/qFCMgkGwUK?utm_source=ycombinator&utm_medium=community&utm_campaign=_YC_launchyc_communitypost_sel1launch_) → Leave feedback, get to know us, and brainstorm cool ideas.\n\n![uploaded image](/media/?type=post&id=88045&key=user_uploads/1125799/8b5d8436-9914-4e22-a4d6-47f4fdf842fe)\n\n",
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        "created_at": "2025-02-26T12:41:49.232Z"
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      {
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        "full_name": "Joschka Braun",
        "title": "Founder",
        "founder_bio": "Published my first paper in the highest-ranked number theory journal at age 17. Continued to pursue math until my M.Sc. from NYU as a Fulbright scholar. Noticed AI has more real world applications than math and started researching applications of deep learning to medical imaging at Covera Health. Built semantic search systems and automatic code generation software at Jina AI.\n\nhttps://joschkabraun.com",
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        "title": "Y Combinator Demo Day 2023: Our favorites Day 2 | TechCrunch",
        "url": "https://techcrunch.com/2023/09/07/ycombinator-demo-day-two-summer-2023/",
        "date": "Sep 07, 2023"
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      {
        "id": 82145,
        "title": "Parea AI - Aligned & reliable LLM evaluations",
        "tagline": "Automatically create LLM-based evals aligned with human judgement",
        "body": "**tl;dr:** [Parea AI](https://www.parea.ai/) automates the creation of evals for your AI products. We achieve this by bootstrapping an evaluation function with human annotations. Allowing you to automagically turn “vibe checks” into scalable and reliable evaluations aligned with human judgment.\n\n# **😩 The Problem**\n\n![uploaded image](/media/?type=post&id=82145&key=user_uploads/501039/78024ed1-9aa2-4be8-a022-359d82b9ac59)\n\nEvaluating free-form text is often only possible by humans reviewing outputs or using LLMs to evaluate them. The former is laborious, slow, and expensive, while the latter often fails to evaluate the outputs correctly. For LLM evaluations to work properly, one needs to prompt engineer them; i.e., they require their own optimization process.\n\n# **🚀 The Solution**\n\n![uploaded image](/media/?type=post&id=82145&key=user_uploads/501039/b7c1f4c7-b654-40e6-9e1d-84ab93f4ad5f)\n\nThe best [LLM evals](https://joschkabraun.com) are adapted to your particular business use case & data. We've developed a method for uploading human annotations (via CSV or using our [Annotation Queue](https://docs.parea.ai/manual-review/queue)) and bootstrapping an evaluation to mimic the annotations. To create a human-aligned eval, you need as few as 20 sample annotations. Using your new LLM eval is as easy as copying the code into your codebase or using it directly via Parea's API. Check out [our docs](https://docs.parea.ai/manual-review/bootstrapped-eval) to see the complete workflow.\n\n# **🙏 Our Ask**\n\n* **Get started** on [**our free tier,**](https://app.parea.ai/sign-up) or [**book a chat**](https://calendly.com/parea-ai/chat) to discuss how we can help you evaluate your AI app!\n* **Support our** [**launch** **tweet**](https://x.com/JoschkaBraun/status/1812884216444510233) and follow us on [**LinkedIn**](https://www.linkedin.com/company/parea-ai/) and [**Twitter**](https://x.com/PareaAI)\n* **Share Parea** **AI** with anyone you know who is facing challenges [evaluating AI & LLM systems](https://joschkabraun.com).",
        "url": "https://www.ycombinator.com/launches/LMv-parea-ai-aligned-reliable-llm-evaluations",
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        "title": "Parea AI – DataDog for LLM apps",
        "tagline": "Parea AI helps developers ideate, evaluate, and manage LLM-powered applications to consistently deliver quality user experiences.",
        "body": "**TL;DR:** [**Parea AI**](https://www.parea.ai/?utm_source=yc&utm_medium=post&utm_campaign=launch_yc&utm_content=tldr) is the essential developer platform for debugging and monitoring every stage of LLM application development. We provide debugging, testing, evaluation, and monitoring in one unified platform. These capabilities help developers get visibility into LLM responses, quickly test and optimize prompts, and ensure customers get the best user experience.\n\n![uploaded image](/media/?type=post&id=73431&key=user_uploads/699950/7cd2fa60-436e-46c0-b266-b88f3fd66b8c)\n\n### 🤔 **The Problem**\n\nLLMs hold infinite promise, but translating this potential into practical applications can be complex. Crafting precise prompts or building effective chains, tracking their performance, and optimizing them currently involves a disparate array of tools and a steep learning curve, leading to decreased productivity and increased time to market. This trial-and-error process can become taxing; in the words of one of our customers, **\"reading 1000s of words from ChatGPT outputs a day takes the fun out of building**.**\"**\n\n### 💡 **The Solution**\n\nParea was conceived to streamline this journey by simplifying the entire process of creating and managing LLM-powered systems. Our intuitive UI enables developers to **debug and test** their **prompts/chains**, offering deep visibility into the best-performing changes that dramatically improve LLM responses. The built-in Lab module lets you **compare various prompts, models, and parameter configurations side by side**, transforming rigorous testing into an insightful and fun task. Post-deployment, our robust **API ensures you have comprehensive analytics**, performance insights, and a complete tracking system for optimizing your application to excel in delivering user experiences.\n\n### 🚀 **Who is it for:**\n\nParea is for developers, AI enthusiasts, and organizations with a vision to leverage the power of LLMs. Whether you're a small team working on an LLM-driven product or a large company developing complex LLM-powered applications, **Parea simplifies the process and accelerates your time-to-productivity**.\n\n### 🎉 **Meet the Parea team**\n\nJoel and Joschka met in New York City and bonded over philosophy, learning, and of course, start-ups!\n\nJoel is a true Renaissance man. His quest has led him from a published microbiology researcher to International Politics at the Council of Foreign Relations, to learning Russian in Moscow, working on &gt;$100B of M&A deals at J.P Morgan, and most recently honing his self-taught coding skills as a SWE at Lyft. With Parea AI, he's committed to enhancing the productivity of every AI builder.\n\n[Joschka](https://joschkabraun.com) is our Wunderkind. He published a paper in the highest-ranked Journal for Number Theory at age 17, graduated college at 19, took a gap year to do Kung Fu in China, then completed his Master's at NYU as a Fulbright scholar. Joschka spent the last 3 years on the AI/ML frontline doing computer vision at Covera Health, and semantic search & LLMs at Jina. Parea was born to tackle the issues he'd faced in debugging and building LLM applications like DevGPT.\n\n![uploaded image](/media/?type=post&id=73431&key=user_uploads/699950/4bdf0da2-6bfd-4139-8f0c-ea7e826fd062)\n\n### ❤️ **Our Ask**\n\nWe invite you to explore [Parea’s](https://www.parea.ai?utm_source=yc&utm_medium=post&utm_campaign=launch_yc2&utm_content=cta) capabilities for your LLM solution and join our welcoming community. Follow us on [Twitter](https://twitter.com/PareaAI) and on [LinkedIn](https://www.linkedin.com/company/parea-ai/).\n\nIf you have any questions or would like a personalized onboarding session for your team, write us at [founders@parea.ai](mailto:founders@parea.ai)",
        "url": "https://www.ycombinator.com/launches/J6N-parea-ai-datadog-for-llm-apps",
        "votes": 128,
        "created_at": "2023-07-26T03:34:53.972Z"
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    "id": 28860,
    "name": "Terminal",
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    "all_locations": "Toronto, ON, Canada",
    "long_description": "Terminal builds telematics data infrastructure for the commercial fleet industry. Commercial auto insurers and fleet software companies, including industry leaders like Intact Insurance, depend on our platform to access GPS, speeding, and vehicle data from 330+ telematics providers. We recently raised our Series A led by Battery Ventures and are backed by Y Combinator, Golden Ventures, Penske Transportation Solutions, and Intact Private Capital. Our team works together in person in Toronto, combining early-stage speed with late-stage maturity while processing many terabytes of vehicle data every day.",
    "one_liner": "Plaid for Telematics Data in Commercial Trucking",
    "team_size": 17,
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        "full_name": "Raghav Midha",
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        "id": 101997,
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        "title": "Semi-Related Podcast - Integration innovation | Raghav Midha of Terminal",
        "url": "https://optym.com/semi-related-podcast/integration-innovation-raghav-midha-of-terminal",
        "date": "Apr 24, 2025"
      },
      {
        "title": "Terminal raises $3.1M, wants to be the ‘Plaid of trucking’ - FreightWaves",
        "url": "https://www.freightwaves.com/news/terminal-raises-3-1m-wants-to-be-the-plaid-of-trucking",
        "date": "Dec 12, 2023"
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      {
        "title": "Meet the Y Combinator Summer 2023 cohort startups with Canadian connections | BetaKit",
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        "id": 72500,
        "title": "Terminal: Plaid for Telematics 🚚",
        "tagline": "Companies building insurance products and fleet software for trucking can use our API to access GPS data, speeding data and vehicle stats.",
        "body": "![uploaded image](/media/?type=post&id=72500&key=user_uploads/1241796/74a6448c-c325-45e1-be23-8766bfd032e7)\n\n## **📌 TL;DR**\n\n_Companies building products for transportation, logistics and fleet management spend 30%-40% of their engineering capacity on integrations - this is expensive, undifferentiated work that takes their time away from working on actual customer problems. Terminal (_[_withterminal.com_](http://withterminal.com)_) is a Universal API for Telematics that makes it easy for these teams to integrate all of the top telematics platforms into their application without needing to worry about the complex underlying details._\n\n## 😰 **Problem**\n\nOur customers include (but are not limited to): insurance companies, fuel cards, invoice factorers, fleet management systems, digital freight brokers, load boards and transportation management systems. These folks need access to telematics data to support their end-users who are trucking companies and commercial fleets. Integrating telematics is often a must-have for them and there’s typically a direct correlation between their number of supported integrations and their sales closure rate.\n\nThe telematics market is fragmented, with hundreds of available platforms, each with their own type of integration (REST, SOAP, etc.), and documentation that is not always available. Companies that need to integrate into these vendors have large integration teams and are still unable to meet their customers' demand.\n\n## **🔮 Solution**\n\nTerminal's Universal API for Telematics enables companies to support all of the leading telematics platforms through a single integration. Similar to Plaid and Stripe - our mission is to increase the innovation velocity of transportation, logistics and fleet management through making fleet data more accessible.\n\nWe provide a white-labelled **User Interface** for fleet managers to grant access to telematics data like GPS, vehicle stats, driver hours and safety events.\n\n![uploaded image](/media/?type=post&id=72500&key=user_uploads/1241796/c7ebf48f-6014-4192-adc8-5eed6aef0aa9)\n\nOnce a fleet manager grants access, we extract, normalize, enrich, and sync the data for our customer. We also offer common data models, webhooks and access to raw telematics data to make it easy for customers to integrate. You can learn more about how it works in our [**API Documentation**](https://terminal.stoplight.io/docs/terminal).\n\n![uploaded image](/media/?type=post&id=72500&key=user_uploads/1241796/9b511455-57e1-4ced-a523-df860d3e67a8)\n\nCustomers also receive a **Support Portal** for managing their integrations, customer connections and data syncs.\n\n![uploaded image](/media/?type=post&id=72500&key=user_uploads/1241796/42b9409c-1fbe-4a22-bb93-5d685c91598d)\n\n## **😇 Ask**\n\nIf you know any companies that currently integrate or are looking to integrate with telematics, please let us know at [**founders@withterminal.com**](mailto:founders@withterminal.com).",
        "url": "https://www.ycombinator.com/launches/IrM-terminal-plaid-for-telematics",
        "votes": 62,
        "created_at": "2023-06-24T00:00:20.370Z"
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    "one_liner": "Corgea finds, and fixes insecure code and packages autonomously. ",
    "team_size": 6,
    "industry": "B2B",
    "subindustry": "B2B -> Security",
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        "full_name": "Ahmad Sadeddin",
        "title": "Founder",
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        "location": "San Francisco, CA, US / San Mateo, CA, US / Remote (CA, US)",
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        "title": "Software engineer - California",
        "url": "https://www.ycombinator.com/companies/corgea/jobs/Fj7nVVP-software-engineer-california",
        "location": "San Francisco, CA, US / San Mateo, CA, US / Remote (CA, US)",
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        "title": "Security Researcher",
        "url": "https://www.ycombinator.com/companies/corgea/jobs/flq0ShW-security-researcher",
        "location": "San Francisco, CA, US / San Mateo, CA, US / Remote (US)",
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        "location": "San Francisco, CA, US / Remote (US; CA, US)",
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        "title": " Introducing PolicyIQ: Contextual Security Analysis for Smarter, More Accurate Results - Corgea - Home",
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        "id": 103899,
        "title": "Corgea: Agentic Pentesting",
        "tagline": "An autonomous penetration testing engine that runs in hours and not weeks",
        "body": "[**Corgea AI Pentesting**](https://corgea.com/products/ai-pentest): an autonomous penetration testing engine that uses AI agents to plan, execute, validate, and report security tests. It doesn’t run a checklist. It reasons about your application.\n\n<https://www.youtube.com/watch?v=wzvUiEr8I2c>\n\n## The numbers\n\nIn a recent pentest:\n\n* **Corgea found 25 findings.** The human pentester found 6.\n* **Delivery time: 4-8 hours.** The human pentest took 2 weeks.\n\n![Corgea AI Pentesting findings overview](https://corgea.com/cms/blog/introducing-ai-pentesting/image-3.png)\n\n## How it works\n\nMost autonomous pentesting tools are black-box scanners with better marketing. They probe endpoints against a generic vulnerability checklist and produce a PDF full of theoretical findings that security teams have to triage manually.\n\nCorgea takes a fundamentally different approach. The engine operates like a real pentesting team.\n\n**Multi-agent architecture.** Not a single scanner. Corgea spawns a coordinator agent that assigns specialized sub-agents (an authentication discovery agent, an API exploration agent, a SQL injection expert agent) based on what it discovers. These agents collaborate, share findings, and build on each other’s discoveries. For complex targets, Corgea can spawn hundreds of agents.\n\n![Corgea AI Pentesting multi-agent execution view](https://corgea.com/cms/blog/introducing-ai-pentesting/image-1.png)\n\n**Code-aware, not black-box.** The engine ingests code context, dependency data, infrastructure configuration, and business logic. It uses your existing [AI SAST](https://corgea.com/products/ai-sast) findings for white-box pentesting, exploiting vulnerabilities at runtime that static analysis already identified. This combination of static insight and dynamic testing dramatically amplifies what the engine can find.\n\n**Dynamic adaptation.** Corgea’s agentic architecture is not fixed. The system continuously adapts its strategy based on what it learns about the target, dynamically scaling the number of agents, their responsibilities, and their specialization. It doesn’t follow a one-size-fits-all workflow.\n\n**Exploitability validation built in.** Corgea doesn’t report theoretical vulnerabilities. Agents validate exploitability during the test itself, confirming a finding can be triggered, capturing evidence, and explaining business impact. This eliminates the triage burden that makes traditional pentest reports a firehose of unverified findings.\n\n![Corgea AI Pentesting exploit reproduction script](https://corgea.com/cms/blog/introducing-ai-pentesting/image-2.png)\n\n## The pipeline\n\n1. **Environment setup.** Corgea provisions a Linux-based sandbox with a full suite of security tools for crawling, discovery, reconnaissance, and exploit validation.\n2. **Scope and context ingestion.** Target scope, endpoints, API documentation, auth flows, user roles, business logic context, and optional code/repo context. Both authenticated and unauthenticated.\n3. **Attack surface discovery.** Maps reachable routes, APIs, parameters, forms, auth boundaries, authorization-sensitive workflows, and exposed services.\n4. **Autonomous test planning.** AI agents reason about application structure and generate test plans for broken access control, IDOR, authentication bypass, injection, SSRF, insecure file handling, sensitive data exposure, and business logic abuse.\n5. **Safe execution and validation.** Hundreds of sub-agents execute probes, observe responses, adapt based on application behavior, and validate exploitability.\n6. **Evidence generation.** For confirmed issues: affected endpoint, payload or request sequence, response evidence, exploitability reasoning, severity, business impact, and remediation recommendation.\n7. **Developer-native remediation.** Findings go directly into developer workflows (PR comments, Jira tickets, Slack notifications, CI/CD pipelines) with reproduction steps, code context, and suggested fixes.\n8. **Reporting.** Findings converted into reports for management, auditors, and customers.\n\n## Supervised autonomy\n\nAutonomous doesn’t mean uncontrolled. Humans remain in control of:\n\n* Defining and approving test scope\n* Setting rules of engagement\n* Approving aggressive or potentially disruptive testing\n* Reviewing sensitive findings\n* Accepting final pentest reports\n* Making risk decisions for production environments\n\nCorgea automates the repetitive and technically complex parts. Humans own the risk decisions.\n\n## Continuous, not point-in-time\n\nTraditional pentesting delivers a PDF report weeks after testing begins. By the time you read it, your application has changed.\n\nCorgea supports both one-time and continuous autonomous pentesting. Retesting is automatic after remediation. Findings close the loop between discovery, fix, and verification in hours, not waiting for the next quarterly cycle.\n\n## Ready to Ditch Security Theater?\n\nIf you're tired of checkbox pentests:\n\nBook a call: <https://corgea.com/demo> \n\nEmail us: sales@corgea.com",
        "url": "https://www.ycombinator.com/launches/R1n-corgea-agentic-pentesting",
        "votes": 18,
        "created_at": "2026-06-24T15:40:00.793Z"
      },
      {
        "id": 77558,
        "title": "🐕 Corgea - Easily and quickly fix vulnerable code using AI",
        "tagline": "We make it easy for companies fix vulnerable code by automating away 80% of the engineering work needed. ",
        "body": "**TL;DR**: Corgea helps companies fix vulnerable source code. It is an AI-powered security platform that writes security patches for engineer approval, saving 80% of the engineering effort needing and $$$. Having Corgea is like having a security engineer on staff constantly focused on making your code more secure. \n\nHi YC! This is Ahmad, and along with Adam, Pratik and Tamara we’re building [Corgea](https://corgea.com/).\n\n![uploaded image](/media/?type=post&id=77558&key=user_uploads/65616/fd08a653-a912-4b81-8d59-cfb4c56e0d95)\n\n### 🕳️ Unresolved holes in software\n\nCompanies scan their code for security vulnerabilities, and are often met with a big pile of findings. On average, companies take 3 months to fix a vulnerability, and 60% of breach victims were aware of the unpatched vulnerability that was exploited.\n\nWhy? This is because engineers prioritize revenue-generating work, often leaving security fixes lower in priority. It is also really expensive for companies to fix vulnerabilities, costing them between $400 - $4,000 per fix. Unacceptable in today’s environment of more frequent security breaches and increasingly sophisticated attacks.\n\nSecurity teams kept complaining to us that all of their hundreds (yes hundreds) of security tools alert them about issues without giving them a way to actually resolve the issues automatically. This leaves security teams hanging high and dry.\n\n### 🐕 What does Corgea do?\n\nWe’re approaching one of the hardest problems in security with an entirely new approach. Unlike other tools that have been vehemently obsessed with just reporting on vulnerabilities, Corgea fixes them.\n\nCorgea connects to your existing SAST (Static application security testing) tools, like Snyk and Semgrep, and automatically writes code fixes for the reported vulnerabilities. Security teams can issue a pull request for the fix with a single click without disrupting any workflows. Engineers get the code fix for review, and well written descriptions helping them understand the changes.\n\nFor example, Corgea can rewrite code and issue PRs to fix SQL injection, path traversal, SSRF, or hundreds of other vulnerabilities. Here’s a brief demo to show Corgea’s capabilities.\n\n[Fixing Issues using Corgea - Watch Video](https://www.loom.com/share/318f06b97dac48628971bb52db372fb8)\n\n![](https://cdn.loom.com/sessions/thumbnails/318f06b97dac48628971bb52db372fb8-1702061376925-with-play.gif)\n\n### ✅ Empowering Security and Freeing up Engineering\n\nSecurity is often perceived as a blocker to engineering, and vice versa. With Corgea, we’re empowering security teams to be able to take action while also accelerating engineering velocity. This fundamentally changes the dynamic between teams.\n\n* **💪 Stronger code:** companies can now secure their products and reduce their fix times to hours without taxing engineering. Many prospects we spoke to have tens of thousands of vulnerabilities that now has a fighting chance in reducing them.\n* **🚀 Increase engineering velocity:** since Corgea is issuing the code fix, we see up to an 80% savings in time engineers spend fixing security issues. Security can now be an enabler to engineering rather than a blocker.\n* **💰 Slash Costs:** Research shows that a single vulnerability takes about $400 - $4,000 to fix. Corgea reduces these costs by up to 80%. Many enterprises can expect to save at least $10m in direct development costs. This doesn’t account for breach cost savings.\n\nOften, security software lacks a clear return on investment or value proposition. They are frequently bought due to fear, uncertainty, and doubt. At Corgea, our belief is that security software needs to lead first with real value and a clear ROI.\n\n### 🌟 How is Corgea different than existing solutions?\n\nThe current market is flooded with tools that overwhelm security teams with alerts and are not effective at fixing what they’re reporting.\n\n* General code-gen tools do not specialize in security and we’ve seen them inadvertently introduce security issues unbeknownst to the engineer. Additionally, they often do not integrate into a wider ecosystem of tools, preferring to focus solely on their own findings.\n* Most SAST & SCA vulnerability scanners do not remediate issues. Many tout this but it’s mostly limited to upgrading packages from one version to another to reduce a CVSS. This often introduces downstream challenges. If they do offer CWE remediation capabilities their success rates are very low because they’re often based on traditional AI methodologies. Finally, they do not integrate into a wider ecosystem of tools because they want to only serve their own findings.\n\nEnterprises often use multiple scanners like Snyk, Semgrep, Checkmarx, and may have multiple repository tools like Github, Gitlab and Bitbucket for their code. They need a solution that consolidates across their existing tools.\n\n### 👩🏽‍💻 Who is building Corgea?\n\nEach member of the Corgea team has experienced the challenges of addressing vulnerabilities in both security and engineering. We first hand witnessed the frustration of teams in wanting to deliver on high quality feature-rich secure software. Our goal is to shatter the silos between the teams and empower both of them rather than empower one at the expense of the other.\n\nIn our prior roles, we designed, secured and built mission-critical software products at companies like of Coupa, Autodesk, and PlanGrid.\n\n### 🎉 Want to try it?\n\nWe’re really excited to help companies in automating the security of their source code. [Use Corgea today](https://www.corgea.app/registration/) for free and without a credit card. Setup takes less than a few minutes. Feel free to [reach out to us](https://calendly.com/asadeddin/30min?month=2024-01) to chat and get a more in-depth demo.",
        "url": "https://www.ycombinator.com/launches/KAw-corgea-easily-and-quickly-fix-vulnerable-code-using-ai",
        "votes": 24,
        "created_at": "2024-01-16T16:32:31.262Z"
      },
      {
        "id": 73406,
        "title": "🐕 Corgea - Enterprise data security and privacy",
        "tagline": "Empowering enterprises to secure sensitive data",
        "body": "Hi everyone!\n\nWe’re building [Corgea](https://corgea.com?utm_source=yc&utm_medium=cpc&utm_campaign=yc_launch&utm_id=yc_launch) - a data security and privacy platform that automates sensitive data protection and compliance in the products companies make.\n\n### [**🚩**](https://emojipedia.org/triangular-flag/) **The Problem**\n\nCompanies process sensitive data, but don't know what it is, and who they share it with. They can’t protect and make private what they don’t know they have and what it is. Additionally data protection requires a lot of different stakeholders to come together, and they lack the proper tools to collaborate around it.\n\n### [**⚡**](https://emojipedia.org/high-voltage/) **How does it work?**\n\nCorgea monitors data traffic, classifies sensitive data (e.g., PII, PHI, payment data), and maps where it came from and who it's being shared with. It then tells you which data protection and privacy policies you need to comply with.\n\nCorgea is unique because you can set it up using 300+ out-of-the-box connectors in hours with no IT integration work.\n\n![uploaded image](/media/?type=post&id=73406&key=user_uploads/65616/f206fe9c-e12f-4749-9946-5567453cecb7)\n\n### [**🧰**](https://emojipedia.org/toolbox/) **What can you do with Corgea?**\n\nHaving this information at your fingertips gives you super powers to be able to:\n\n* Unlock revenue by making data protection your competitive advantage\n* Reduce your attack surface vector of your infrastructure\n* Accelerate breach response\n* Know which 3rd parties receive sensitive data\n* Understand your data compliance requirements\n* Receive alerts for out-of-policy data events\n* Perform data minimization\n\n![uploaded image](/media/?type=post&id=73406&key=user_uploads/65616/dad1dd93-4e77-4560-95b3-cda61b090fc6)\n\n### [**📖**](https://emojipedia.org/open-book/) **The Story**\n\nOne day, Ahmad received a massive excel sheet to fill out for a data privacy initiative. By the end of it, he had curated hundreds of data fields manually, and identified where they came from and where they were sent to. Feeling how inefficient this was for the company, he decided to automate it by building Corgea.\n\nAhmad previously led the payments product at Coupa and founded 2 other companies before Corgea. His last company was acquired by Coupa.\n\n![uploaded image](/media/?type=post&id=73406&key=user_uploads/65616/437a87ab-4bc7-47d8-b8a8-9c81c8f0d034)\n\n### **🚀 Team**\n\nAhmad is joined by an amazing team all with experience in working and building software in regulated data environments such as HIPAA, FedRamp, PCI, ITAR, and data privacy.\n\n![uploaded image](/media/?type=post&id=73406&key=user_uploads/65616/c345a149-ae43-472e-a09c-ff7895239bf9)\n\n### [**❤️**](https://emojipedia.org/red-heart/)**Interested?**\n\nIf you are a company processing sensitive data, and want to unlock revenue while being compliant then [**schedule a call with us**](https://l.linklyhq.com/l/1rIbH)!\n\nCompanies that sign up before Aug 30th are eligible for **50% off**!",
        "url": "https://www.ycombinator.com/launches/J5y-corgea-enterprise-data-security-and-privacy",
        "votes": 43,
        "created_at": "2023-07-25T14:47:43.101Z"
      }
    ]
  },
  {
    "id": 28868,
    "name": "Briefer",
    "slug": "briefer",
    "former_names": [
      "Ergomake"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/1e589854f66150c916444527d7f4aa314d3961ed.png",
    "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"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2023",
    "status": "Inactive",
    "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/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/",
    "x_url": "https://twitter.com/briefercloud",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/briefercloud",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/1e589854f66150c916444527d7f4aa314d3961ed.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": 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",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3c67c3654b38517081d8943217dd52f520daa16d.jpg"
      },
      {
        "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": 28885,
    "name": "Hiro",
    "slug": "hiro",
    "former_names": [
      "Santiago Labs, Inc.",
      "Telophase"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d1d128fbe59c627f74405a0637c6a9692cc736f0.png",
    "website": "https://hirosecure.com",
    "all_locations": "New York City, NY, USA",
    "long_description": "",
    "one_liner": "Agents that handle security work",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Security",
    "launched_at": 1684532337,
    "tags": [
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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. 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        "title": "🪐 Pluto – OSS experiment tracker for Neptune users",
        "tagline": "Neptune-compatible experiment tracking, built for teams running AI workloads",
        "body": "[**→ Try the live playground**](https://demo.pluto.trainy.ai/o/dev-org/projects/my-ml-project) – explore Pluto with real sample experiments, no signup required.\n\nNeptuneAI is shutting down on March 5th after being acquired by OpenAI. We built Pluto so you can migrate safely without rushing.\n\n---\n\n### **👋 Who we are**\n\nHey YC, we're Roanak and Andrew! We founded Trainy to help AI teams efficiently manage and utilize GPU infrastructure. When we heard Neptune was shutting down, our customers started panicking about losing years of experiment history and having to rewrite their logging code on a tight deadline.\n\nSo we built Pluto.\n\n![uploaded image](/media/?type=post&id=97424&key=user_uploads/509361/6cbcdb3e-6f5f-4f7f-8855-58001d921c66)\n\n### **🔥 The problem**\n\nNeptune's March 5th shutdown is forcing research teams into one of the worst kinds of migrations: rushed, high-stakes, and hard to verify.\n\nMost alternatives require you to:\n\n* Rewrite your logging code\n* Lose your historical runs (or spend days exporting and reformatting)\n* Hope the new tool handles your multi-GPU workloads the same way\n\nAnd you have to do all of this before March 5th or your data gets deleted.\n\n### **🛠 How Pluto solves it**\n\n**1. Dual-log to both platforms simultaneously**\n\n[Add one import](https://docs.trainy.ai/pluto/neptune-migration), keep your existing Neptune code running, and Pluto logs side-by-side. Validate that everything matches on your real training workloads before you cut over.\n\n**2. Export your Neptune history**\n\nPluto includes [a Neptune exporter](https://docs.neptune.ai/transition_hub/migration/to_pluto) that brings your old runs into Pluto. Years of experiment data, preserved.\n\n**3. Built for the workloads Neptune users actually run**\n\nWe're optimizing for what Neptune users loved: UI responsiveness at scale, reliable logging throughput under multi-node/multi-GPU workloads, and the ability to track thousands of per-layer metrics without lag.\n\n**Deployment options:**\n\n* **Self-hosted** – for sensitive data or air-gapped environments, instructions in [server readme](https://github.com/Trainy-ai/pluto-server)\n* **Hosted** – $250/seat/month (free for existing Trainy customers)\n\n---\n\n### **🙏 Our ask**\n\n**If you're a Neptune user, please try Pluto with dual-logging before the March shutdown.**\n\nWe're specifically looking for feedback on:\n\n* Anything that would block your cutover\n* Features you rely on that we're missing\n* UI/performance differences at scale\n\n**Early Bird offer:** Start dual-logging in the next 2 weeks → **3 months hosted free**.\n\n👉 Once you’ve made an account on [pluto.trainy.ai](http://pluto.trainy.ai), email [roanak@trainy.ai](mailto:roanak@trainy.ai) or [grab a time to chat](https://calendly.com/roanak/trainy-demo) and we’ll add seats/storage.\n\n---\n\n### **🔗 Links**\n\n* [**Playground**](https://demo.pluto.trainy.ai/o/dev-org/projects/my-ml-project) – try it now\n* [**Quickstart**](https://docs.trainy.ai/pluto/quickstart) – get running in 5 minutes\n* [**GitHub**](https://github.com/Trainy-ai/pluto) – Apache-2.0 (client), AGPL-3.0 ([server](https://github.com/Trainy-ai/pluto-server)) ⭐\n\nWe're listed on[ **Neptune's official transition hub**](https://docs.neptune.ai/transition_hub/migration/to_pluto).\n\nThank you!",
        "url": "https://www.ycombinator.com/launches/PLM-pluto-oss-experiment-tracker-for-neptune-users",
        "votes": 10,
        "created_at": "2026-02-04T22:26:06.748Z"
      },
      {
        "id": 72587,
        "title": "🚅 Trainy - Identify bottlenecks, boost training",
        "tagline": "Dashboards to help ML engineers training large models isolate performance bottlenecks and boost training speed.",
        "body": "**tl;dr** We help ML engineers training large models isolate performance bottlenecks during training. Trainy summarizes profiling information during large distributed training so that you know exactly what is limiting the speed of your model training.\n\nHello everyone, we are Andrew and Roanak, ML engineers from the bay. We’ve experienced firsthand the challenges of distributed training and getting the most out of your compute resources. That’s why we are building tools to help ML engineers training large models optimize training speed and take the guesswork out of estimating the time and cost of training.\n\n![uploaded image](/media/?type=post&id=72587&key=user_uploads/1404133/cde44cc9-7436-422f-b0fd-c7c3f2a94ff2)\n\n# **The Problem**\n\nDistributed training has enabled the training of ever-growing generative AI models. However, gains in speed are not simply proportional to the number of GPUs recruited and can quickly have diminishing returns depending on infrastructure and the model being trained. Tools now mainly focus on profiling a few GPUs, but become unwieldy the moment you scale beyond the 10 GPU mark.\n\n# **Our Solution**\n\nWe created a dashboard to display timing information across many GPUs. It’s a graph interface built on top of Tensorboard and PyTorch Profiler, existing tools familiar to ML engineers.\n\n![uploaded image](/media/?type=post&id=72587&key=user_uploads/1404133/729377af-3ca9-499b-acf7-1e2f1f569940)\n\n# **How it works**\n\nWe summarize profiling information over many GPUs in a few key views that help ML developers identify where in the ensemble of GPUs there are inefficiencies. Statistics about computation, communication, and memory operations across many GPUs isolate straggling GPUs. Distributed training can only proceed as fast as the slowest GPU participating. By isolating slow outliers, an ML developer can zoom in on the operations running on the straggling GPU and make optimizations to their code to balance timings across GPUs and lower resource idling.\n\n# **The Ask**\n\nWe’d love for you to try out our profiler if you are training your own models. <https://github.com/Trainy-ai/nodify>\n\nAlso join our community if you want to stay up to date with the development of our tools. <https://discord.com/invite/d67CMuKY5V>",
        "url": "https://www.ycombinator.com/launches/Isl-trainy-identify-bottlenecks-boost-training",
        "votes": 21,
        "created_at": "2023-06-27T19:06:48.265Z"
      }
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    "id": 28994,
    "name": "Vango AI",
    "slug": "vango-ai",
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "We built Vango excited by the future where generative visual AI models like stable diffusion dramatically reduce the barrier to create content. While spending 8 months building products for creatives, we found ourselves building hacky tools to address many of frustrations we had with visual AI. \r\n\r\nSo we decided to build the devtool we needed: Vango is a flexible evaluation platform that makes it 10x improve visual models. Developers using visual AI models at scale use Vango to learn quantitative ways to improve their model, saving them ~10 hours per week. \r\n\r\nMajor companies building visual products have already begun integrating diffusion models, including Adobe, Disney, Activision Blizzard, Canva, and Snap. By 2025, it is estimated that 1 billion images per day will be AI-generated. ",
    "one_liner": "Development platform that makes it 10x easier to improve visual models",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1692068150,
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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/vango-ai",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/vango-ai.json",
    "year_founded": 2022,
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      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
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    "founders": [
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        "full_name": "Eshaan Moorjani",
        "title": "Founder",
        "founder_bio": "Berkeley CS",
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        "full_name": "Rajen Dey",
        "title": "Founder",
        "founder_bio": "Founder at vango.ai",
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      {
        "id": 74170,
        "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).",
        "url": "https://www.ycombinator.com/launches/JII-vango-build-with-evaluate-stable-diffusion-fast",
        "votes": 33,
        "created_at": "2023-08-16T21:38:41.929Z"
      }
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    "id": 28998,
    "name": "Automorphic",
    "slug": "automorphic",
    "former_names": [
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    "website": "https://automorphic.ai/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Automorphic has invented a way to infuse knowledge into LLMs via fine-tuning (surpassing context window limitations), enabling developers to rapidly iterate on and successively improve custom models cheaply and efficiently.",
    "one_liner": "Infuse knowledge into language models with just 10 samples",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1691588844,
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    "batch": "Summer 2023",
    "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/automorphic",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/automorphic.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/automorphic",
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      "name": "Harj Taggar",
      "url": "https://www.ycombinator.com/people/harj-taggar"
    },
    "founders": [
      {
        "user_id": 1146368,
        "full_name": "Govind Gnanakumar",
        "title": "Founder",
        "founder_bio": "Often running away from robots (that I created). Building the next generation of artifical narrow intelligence.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/govind-gnanakumar",
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      {
        "user_id": 1381983,
        "full_name": "Maaher Gandhi",
        "title": "Founder",
        "founder_bio": "When not working on Automorphic, I'm building AI to beat me at chess",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/maaher-gandhi-31b40928b",
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      {
        "user_id": 1160097,
        "full_name": "Mahesh Natamai",
        "title": "Founder",
        "founder_bio": "Building AI agents that can remember and self-improve like we can at Automorphic.",
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        "linkedin_url": "https://linkedin.com/in/mahesh-natamai-b17683188",
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      {
        "title": "Computer Science Was Too Slow, so I Dropped Out to Focus on My AI Startup",
        "url": "https://www.businessinsider.com/computer-science-major-dropped-out-georgia-tech-build-ai-startup-2023-9",
        "date": "Sep 24, 2023"
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      {
        "id": 74582,
        "title": "Automorphic: Infuse knowledge into language models with just 10 samples",
        "tagline": "Rapidly build and improve custom LLMs",
        "body": "**TL;DR** - [Automorphic](https://automorphic.ai) enables developers to rapidly build and improve custom fine-tuned models. Using our LLM improvement platform, you can turn raw data into a secure, production-ready, self-improving LLM in minutes.\n\n—\n\nHey everyone! We’re Govind, Maaher, and Mahesh, from Automorphic. After experiencing the challenges of fine-tuning and refining language model systems, we’re on a mission to build an interactive LLM improvement platform that turns a tedious process into an addictive one.\n\n![uploaded image](/media/?type=post&id=74582&key=user_uploads/1381983/14e3e547-96a5-4a74-91b1-3ad11af28680)\n\n### **❌ The Problem:**\n\nIt takes engineers at companies like Google and Meta 12 to 18 months to take a model from research to production – and this isn’t because they run one tuning job and call it a day.\n\nThey apply a series of successive improvements that may start by supervised fine-tuning, then aligning to human preferences, then distillation and pruning unnecessary weights, and then once it’s met a certain quality threshold, they don’t just say it’s good enough. They continuously improve it with RLHF, periodic re-tunings to control for data drift, and so on.\n\nUnfortunately, such an elaborate process is unrealistic for most companies—they can’t wait a year to get a custom LLM to production even if they have the engineering talent.\n\n### **⭐️ Our Solution**:\n\nAutomorphic makes it easy for developers to continuously improve their custom LLMs.\n\n1. Upload your raw text data\n2. Start an initial fine-tuning run with your data, and continue to fine-tune as needed\n\n   ![uploaded image](/media/?type=post&id=74582&key=user_uploads/1381983/00398557-fca1-471a-9483-b5b75e506f0f)\n\n3. One line switch from the OpenAI API endpoint to ours\n4. Try inference on your model and improve it using RLHF\n\n   ![uploaded image](/media/?type=post&id=74582&key=user_uploads/1381983/cc6a2fe8-2b30-4a72-ada2-eeb960f6afc2)\n\n5. Use additional data to train adapters and combine and commute them however you want\n6. Publish your custom models to the [hub](https://automorphic.ai/hub), and try out existing models there\n\n   ![uploaded image](/media/?type=post&id=74582&key=user_uploads/1381983/fc5a26f7-f7aa-4984-bb8f-1e1fc8db427b)\n\n\nYou own the model weights, so you can train and run inference in your own cloud if you’d like.\n\n# **🙌** Our Ask:\n\nSign up for our [platform](https://automorphic.ai/signup) and train your first three models for free! We’d love feedback on how we can make your language model improvement experience better.\n\nIf there’s someone in your network like an ML engineer who works with LLMs, or folks looking to replace OpenAI / implement custom LLMs, we’d love to chat with them.\n\nHere’s a short blurb you can send them:\n\n> Automorphic, a YC-backed startup, enables developers to go from raw data to a continuously improving custom language model usable in production in minutes. They’d love to chat with ML engineers and companies looking to implement custom LLMs. Email them at [founders@automorphic.ai](mailto:founders@automorphic.ai), or book a meeting [here](http://calendly.com/automorphic)",
        "url": "https://www.ycombinator.com/launches/JOw-automorphic-infuse-knowledge-into-language-models-with-just-10-samples",
        "votes": 176,
        "created_at": "2023-09-01T21:50:34.474Z"
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    "id": 28999,
    "name": "Baserun",
    "slug": "baserun",
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    "website": "https://baserun.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "LLMs are incredibly powerful, but latency, cost, and unpredictable outputs have made productionizing LLM features challenging. Baserun is a testing and observability platform that helps AI teams streamline their development cycle from identifying an issue to evaluating their solution, so that teams ship faster with confidence.",
    "one_liner": "Observability and evaluation platform for LLM apps.",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1691548192,
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    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
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    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/baserun",
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      "name": "Harj Taggar",
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        "user_id": 1038083,
        "full_name": "Effy Zhang",
        "title": "Founder",
        "founder_bio": "Building something new",
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        "user_id": 815071,
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        "full_name": "William Zeng",
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        "user_id": 1343086,
        "full_name": "Kevin Lu",
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        "founder_bio": "Previously: top of class at UWaterloo CS, built the first ML-based skin weight generation model for UGC avatars at Roblox, and NLP researcher on common sense reasoning (in the Bart/T5 era). Now building an AI-powered junior dev and interested in code gen and automated code gen orchestration.",
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        "role_type": "Full stack",
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        "equity_range": "1.00% - 4.97%",
        "experience": "Any (new grads ok)",
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        "title": "Sweep aims to automate basic dev tasks using large language models | TechCrunch",
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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",
        "url": "https://www.ycombinator.com/launches/Omv-sweep-cursor-tab-for-jetbrains-ides",
        "votes": 12,
        "created_at": "2025-11-07T17:26:45.064Z"
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        "id": 88553,
        "title": "Sweep: JetBrains AI Coding Assistant",
        "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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        "full_name": "Carlos Feliciano",
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        "id": 91358,
        "title": "Terracotta AI - AI agents for Infrastructure as Code workflows",
        "tagline": "Intelligent preflight checks for your Infrastructure as Code workflows inside of your PR",
        "body": "# **tl;dr**\n\nPlatform and DevOps teams are still catching Terraform issues after they break production. Terracotta AI brings AI-powered review directly into PRs, analyzing your code, state, and live cloud resources to prevent problems before any workflow triggers.\n\n**Try Terracotta AI for free at [https://tryterracotta.com](https://tryterracotta.com)!**\n\nhttps://www.youtube.com/watch?v=QyzyiJVeZqU\n\nhttps://www.youtube.com/watch?v=GuSfvcYllZo&t\n\n# **Problem**\n\nEven the simplest Terraform changes can break production in unexpected ways and can take a significant amount of time to debug and fix.\n\nPlatform teams have developed sophisticated DevOps practices, including module catalogs, compliance policies, and continuous integration/continuous delivery (CI/CD) pipelines.\n\nHowever, even with senior engineers reviewing pull requests (PRs), critical issues still slip through, including drift conflicts, hidden dependencies, and blast radius across services that you didn't know were connected.\n\nThe problem isn't a lack of processes. It's that humans can't consistently analyze Terraform changes against live cloud state, remote state, and downstream dependencies simultaneously. Traditional tools catch problems after the PR is approved or deployed, not before.\n\n# **Solution**\n\n![uploaded image](/media/?type=post&id=91358&key=user_uploads/925045/89ae62a4-eb80-4d9e-95d5-e2af0684740a)\n\nWe created a purpose-built AI agent for Infrastructure as Code (IaC) workflows that seamlessly integrates into your IaC pipeline, contextualizing and providing real-time feedback directly within your pull requests.\n\nTerracotta AI analyzes every Terraform change against the most critical contexts in your IaC deployment pipeline and provides accurate, contextual, actionable feedback inside of your PR:\n\n* **Your IaC code** — syntax, structure, linting, and more\n* **Local plan state** — what Terraform thinks will happen\n* **Live remote state** — What should be deployed\n* **Live cloud resources** — what actually is deployed\n\nWe instantly surface the issues that break production:\n\n* Drift and state mismatches\n* Threat vectors and misconfigurations\n* Hidden blast radius and downstream risk\n* Cost anomalies and compliance violations\n* Cross-PR conflicts for resource modifications\n\nEverything happens as soon as the PR opens, before any CI/CD workflow triggers, and serves as an early detection system for hidden risks and issues that might enter your production environment.\n\n# **Traction**\n\nWe're working with platform engineering and DevOps teams at SupportLogic, LaminatedLabs, and others who are catching issues they would have missed and deploying with confidence rather than crossing their fingers.\n\n\"Terracotta has helped my DevOps team ship Terraform faster and with more clarity. It catches cost impacts, exposed secrets, potential threat vectors, and even cross-PR conflicts before we trigger our CI/CD pipelines. It's been a huge win for both speed and compliance and an overall boost in confidence in helping manage Terraform across all our environments.\" - **Tyler Pinckard - Head of Software Engineering, DevOps & Security at SupportLogic**\n\n**SupportLogic Case study:** https://tryterracotta.com/case-study/supportlogic\n\n# **Our ask**\n\nIf your team is tired of Terraform, OpenTofu, and CDK-TF surprises in production, let's show you a 15-minute demo or sign up for a free 14 day trial at https://tryterracotta.com.\n\nEmail us: [founders@tryterracotta.com](mailto:founders@tryterracotta.com)",
        "url": "https://www.ycombinator.com/launches/NlW-terracotta-ai-ai-agents-for-infrastructure-as-code-workflows",
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      {
        "id": 82694,
        "title": "OpsBerry AI - Secure your identity sprawl",
        "tagline": "Defending against identity-driven breaches with AI. ",
        "body": "![uploaded image](/media/?type=post&id=82694&key=user_uploads/925045/926203d7-e2a0-45cd-b97b-d38419a524b4)\n\n**TL; DR** —[OpsBerry AI](https://d2lssd04.na1.hs-sales-engage.com/Ctc/ZW+23284/d2LsSd04/Jks2-6qcW69sMD-6lZ3lyVmsNqH4X0sgdW5TPVYB7bLMr0W6gCpW-7YVgsNW1bvyKV6VTFTXVcRKMB84G-_WW68Bq2C90_lXpW6_BGLs6C_-0yW4lQkxg4FflCWW8rtXpw1ppdmgW2NfKVX6P8tfhW5nXNYm10nsb3W4lyMqq6LVSVZV_cQzJ8LnY0rW5Vt27w62FFv5W2Q4pWc4Z67KLW3kFQKk6ZC34bW68q3RQ3jfwPVW1ztCL98bbKldW685KMM36rzGDW8SMnJ02zDZD_f5nZ8xj04) is an Identity Security Posture Management Platform that uses AI trained with the latest cybersecurity and compliance frameworks to help organizations proactively control, secure, and defend their human and non-human identity sprawl against identity-driven attacks. We help security and engineering teams quickly unify, analyze, and remediate critical vulnerabilities in their identity sprawl into a single pane of glass across central cloud, identity, and ZeroTrust providers.\n\n# **The team**\n\n![uploaded image](/media/?type=post&id=82694&key=user_uploads/925045/f8edf5e2-f5ee-4acb-8df8-3284f47601f0)\n\n[**Carlos**](https://www.linkedin.com/in/carlosfelicianoii/) is the company's CEO. He handles the business end, infrastructure, security, architecture, and technical operations. He has over 15 years of experience in Cloud infrastructure, architecture, and observability. Before Y Combinator, Carlos was Director of Solutions Architecture and technical customer success at [OpsRamp](https://opsramp.com), multi-cloud and hybrid observability, and ITSM (acq. by HPE), helping enterprises like Micron, Dolby, Epsilon, and others architect end-to-end observability across their multi-cloud environments. Before that, Carlos was an engineering and technical support manager for [LogDNA](https://mezmo.com) (YC S15).\n\n[**Casey**](https://buildspace.so/) is the company's CTO. With over 16 years of experience architecting and shipping code for his business ventures, Casey started by building and selling Runescape bots when he was 12. This eventually led him into various software engineering roles at YC-backed startups like [Buildspace](https://buildspace.so) and Farmstead. Casey runs the product side of the house, handling UIUX design, software architecture, and development, and ultimately, shipping amazing enterprise code.\n\n# **What is causing the rapid increase in identity-driven breaches and why?**\n\nIdentity security is often overlooked and underestimated, leaving organizations vulnerable to unauthorized access, data breaches, and compliance failures. User-based identities are steadily growing annually at a 30% rate, with most employees having two or more identities that allow access to critical business and engineering systems, which is only part of it. NHIs, or Non-Human identities (think OAuth apps, API keys, Service Accounts, etc.), are increasing even faster at 50%, or said otherwise, four or more NHIs per every employee.\n\nIn 2023 alone, 84% of organizations suffered at least one identity-based attack, which averaged $4.5 million in cost. The number of breaches has grown at a steady 50% yearly since 2020 (Source: ISDA). That's not all; unrealized fallout from these breaches after the fact tends to include legal repercussions, loss of customers, increased security costs, higher insurance premiums, reputational repair, loss of intellectual property, and more.\n\n![](https://www.idtheftcenter.org/wp-content/uploads/2024/01/ITRC-DataBreachReport-2023-Infographic-H-1024x791.jpg.webp)\n\nUser identities are only one attack vector in your identity security posture; machine-based identities like API keys, OAuth apps, service identities, and other NHIs are critical attack vectors for businesses. Partially offboarded identities, orphaned human and non-human identities, identity privilege creep, overprivileged access, and shadow accounts that fly under the radar, like non-sso access, gen-AI tools, and other IT internal systems, eventually snowball out of control and exponentially increase the potential for identity-driven breaches across critical engineering and business environments.\n\nFor businesses struggling to maintain compliance and adhere to regulatory requirements, these unchecked identity issues lead to significant compliance and regulatory problems. Organizations face increased risks of failing audits, substantial fines, and even reputational damage due to their inability to manage and secure their identity sprawl effectively.\n\n# **How does OpsBerry solve this with AI?**\n\nOpsBerry AI defends against human and non-human identity breaches using AI to continuously discover, prioritize, and remediate vulnerabilities and risks in your identity sprawl. Our AI-powered identity security posture management platform, trained with popular cyber security and compliance frameworks, provides comprehensive visibility and contextualization across your user accounts, service accounts, API keys, OAuth apps, and more, keeping your organization safe from identity-driven attacks.\n\n# **How it works**\n\n![uploaded image](/media/?type=post&id=82694&key=user_uploads/925045/41846940-aa9e-44ae-948b-39ed31b48d7a)\n\n👀 **Automated Identity risk assessments**—We automatically gather all information about each identity and generate in-depth risk assessments with AI, instantly surfacing gaps, vulnerabilities, and threats.\n\n![uploaded image](/media/?type=post&id=82694&key=user_uploads/925045/019721bf-ba26-4e5d-abd6-af44511dabae)\n\n👥 **Shadow identities**—let AI surface the identities that hide in the shadows and quickly identify “unknown unknown” identity risks in your identity secure posture. Quickly surface and remediate shadow accounts across human and non-human identities, such as non-sso user accounts, API Keys and tokens, service accounts, orphaned identities, unmonitored privileged accounts, and more. This is the quickest way to transform hidden risks into strategic cost savings.\n\n![uploaded image](/media/?type=post&id=82694&key=user_uploads/925045/ecaaaa23-83bd-40d6-9f1e-d2c3a169e380)\n\n**🌱 Lifecycle management and remediation** are the easiest ways to control and secure your human and non-human identity posture. Drop-and-drop no-code automation lets you build streamlined self-service workflows to quickly onboard and offboard identities, remediate risks, and defend against identity-driven breaches.\n\nAnd much more in the works!\n\n![uploaded image](/media/?type=post&id=82694&key=user_uploads/925045/968ba4e4-c7d3-4379-b992-3f6781f46563)\n\n![uploaded image](/media/?type=post&id=82694&key=user_uploads/925045/dda6bfd7-7e40-42e1-aca1-1c14c25ec780)\n\n![uploaded image](/media/?type=post&id=82694&key=user_uploads/925045/119b7479-a979-48a4-ac8b-2d3b7c3a0fb0)\n\n# **Our ask**\n\nNeed help wrangle your identity sprawl with an identity security platform that’s like having your very own in-house identity security expert? We’d love to work with you!\n\nRegardless of your company size, industry, or role, if you’re serious about protecting against identity breaches and want to take real control of your identity sprawl, we’d love to chat and show you a demo! Email [carlos@opsberry.ai,](mailto:carlos@opsberry.ai) or you can even set a time on our [Calendly](https://calendly.com/opsberry/opsberry).\n\n# Socials\n\n[OpsBerry AI (Y S23)](https://opsberry.ai)\n\n[X](https://x.com/opsberryai)\n\n[Linkedin](https://www.linkedin.com/company/opsberryai)",
        "url": "https://www.ycombinator.com/launches/LVm-opsberry-ai-secure-your-identity-sprawl",
        "votes": 34,
        "created_at": "2024-08-02T19:49:51.530Z"
      }
    ]
  },
  {
    "id": 29078,
    "name": "RecipeUI",
    "slug": "recipeui",
    "former_names": [
      "Convi",
      "Toph",
      "RecpeUI",
      "RecipeUI",
      "RecipeUI`",
      "RecipeUI",
      "RecipeUI`"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7580790de28f6334e2dd731c6927dfdedd2ba02a.png",
    "website": "https://recipeui.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "The first version of RecipeUI was a viral project at Robinhood that reached 100% adoption from all engineering and QA teams. When an API broke, anyone from Frontend to QA to PMs could debug without relying on backend engineers",
    "one_liner": "The open source Postman alternative.",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1691613832,
    "tags": [
      "Developer Tools",
      "Open Source",
      "API"
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    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2023",
    "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": null,
    "url": "https://www.ycombinator.com/companies/recipeui",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/recipeui.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/recipeui/",
    "x_url": "",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/RecipeUI/RecipeUI",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/7580790de28f6334e2dd731c6927dfdedd2ba02a.png",
    "app_video_url": null,
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    "company_photos": [],
    "primary_partner": null,
    "founders": [
      {
        "user_id": 1139854,
        "full_name": "Samuel San",
        "title": "Founder",
        "founder_bio": "Hey! I was a product manager at Coinbase and Apple and studied software engineering at the University of Waterloo. I also did a bunch of internships at Meta, Microsoft, Shopify, and startups.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/samuelsan",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7865a458ddd4da163252205d598f22c4eba5d6ae.jpg"
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    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 74274,
        "title": "RecipeUI - Open source Postman alternative",
        "tagline": "The API tool for teams",
        "body": "Hey, this is Jeane and Samuel from RecipeUI.\n\nWe’re building an API testing experience that works for the whole team (Devs, PMs, QA, Ops). Try it out at <https://recipeui.com>.\n\n![uploaded image](/media/?type=post&id=74274&key=user_uploads/1139854/36a01c9b-6c4c-4b88-a87d-a9575cf0bd33)\n\nJeane built the first version of this at Robinhood when he saw his colleagues struggle to use and test internal APIs. It went viral and was adopted by near 100% of the engineering org, QA, and support teams, saving countless hours in testing.\n\n**Problem ❌**\n\nWe rarely hear: “Wow, this API was easy to run.”\n\nInstead you have..\n\n* **Complex onboarding:** Each teammate onboards onto an API differently. Some struggle with auth, some with params.\n* **Designed for developers only:** API tools are not built to be easily used by the whole team. Non-engineering teams need access to API tooling as well like QA, support, and product.\n* **Poor documentation:** Documentation is scattered across code, slack, and wikis. You shouldn't need a meeting just to figure out how an API works.\n\n**Solution ✅**\n\nEnable anyone to test APIs in seconds with a click of a button. \n\n* **Easy setup:** Quickly use new APIs with user-friendly forms for parameter input. \n* **Designed for collaboration:** Create and share Recipes (example API use cases) that run without needing any authentication.\n* **Add APIs in minutes:** Just import your YAML files and we’ll auto convert them into documented APIs for anyone to test.\n\nWatch our [demo](https://www.youtube.com/watch?v=Ce9g7N1V76U):\n\n**Our Asks:**\n\n📢 Book a demo to see how RecipeUI can work for your team: <https://calendly.com/jeane-nfi/30min>\n\n🌟 Star our GitHub: <https://github.com/RecipeUI/RecipeUI>\n\n🚀 Test out some APIs on RecipeUI. Create Recipes and share them on social!",
        "url": "https://www.ycombinator.com/launches/JJy-recipeui-open-source-postman-alternative",
        "votes": 36,
        "created_at": "2023-08-21T19:10:28.054Z"
      }
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  },
  {
    "id": 29079,
    "name": "Tiptap",
    "slug": "tiptap",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/5ea1ff4314cdf63ee3867e1d262f8d1119847e40.png",
    "website": "https://tiptap.dev/",
    "all_locations": "Berlin, Berlin, Germany",
    "long_description": "Tiptap 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 LinkedIn, GitLab, Axios, and Anthropic.",
    "one_liner": "The open-source document editor for humans and AI agents.",
    "team_size": 20,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1687103873,
    "tags": [
      "Developer Tools",
      "Open Source",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2023",
    "status": "Active",
    "industries": [
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      "Engineering, Product and Design"
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    "regions": [
      "Germany",
      "Europe",
      "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/tiptap",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/tiptap.json",
    "year_founded": 2022,
    "city": "Berlin",
    "country": "DE",
    "linkedin_url": "https://www.linkedin.com/company/tiptapdev/",
    "x_url": "https://twitter.com/tiptap_editor",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/tiptap-75b3",
    "github_url": "https://github.com/ueberdosis/tiptap",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/5ea1ff4314cdf63ee3867e1d262f8d1119847e40.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": 1335640,
        "full_name": "Philip Isik",
        "title": "Founder",
        "founder_bio": "Philip is the co-founder and co-CEO of Tiptap, where he is responsible for the company's strategy, sales, and business development. With a decade of industry experience, Philip's passion for creating intuitive and transformative digital experiences led him to grow Tiptap from an open source side project at his digital consultancy into a venture-backed startup.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/philip-isik-688307123",
        "x_url": "https://twitter.com/PhilipIsik",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e2f831917fb4b95a1977e2df5882a6791f2c6484.jpg"
      },
      {
        "user_id": 1350130,
        "full_name": "Sven Adlung",
        "title": "Founder",
        "founder_bio": "Sven is a co-founder and lead frontend developer at Tiptap, where he brings over twenty years of experience in app and web development. Specializing in frontend development, he focuses on the Tiptap Editor and its cloud services.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/sven-adlung-b343b696",
        "x_url": "https://twitter.com/svenadlung",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c99fee3341fe98fa622c37677d3c5e637ef72efe.jpg"
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      {
        "user_id": 1347229,
        "full_name": "Patrick Baber",
        "title": "Founder/Lead Cloud Engineer",
        "founder_bio": "Patrick is the co-founder and DevOps of Tiptap, which he started with five other founders in 2022. With more than a decade of experience, he is responsible for the IT infrastructure, defines the software architecture, and drives the mission to simplify the development of collaborative apps. Originally from East Germany, Patrick earned a degree in business economics.\n",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/patrick-baber-a0247027b/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/86129959b360198f49a86d9319fc409c8a62ac90.jpg"
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      {
        "user_id": 1351520,
        "full_name": "Nick Hirche",
        "title": "Founder",
        "founder_bio": "Nick is a co-founder and lead UX/UI designer at Tiptap, where he is responsible for the visual appearance and product conception. With more than a decade of experience in the industry, he can quickly grasp complex problems and turn them into new product ideas. These are garnished with amazing design.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/nick-hirche-622a2a216",
        "x_url": "https://twitter.com/NickHirche",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b43debffb0162e46f06762c20031fdcf8546c92d.jpg"
      },
      {
        "user_id": 1341997,
        "full_name": "Timo Isik",
        "title": "Founder",
        "founder_bio": "Timo is a co-founder and lead backend developer at Tiptap where he mainly works on collaboration and cloud services. He holds over ten years of diverse experience in software engineering and specializes in the backend part of applications.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/timo-isik-6b2956197",
        "x_url": "https://twitter.com/timoisik",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/8d22e3026f7082a839141c7266be88dab70b9e19.jpg"
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      {
        "user_id": 1350259,
        "full_name": "Sebastian Schrama",
        "title": "Founder",
        "founder_bio": "Sebastian is the co-founder and co-CEO of Tiptap. With over a decade of experience in the freelance and entrepreneurial world, he has honed his skills in finance and operations. His diverse expertise has shaped his role at Tiptap, where he navigates the company’s financial health and operational efficiency.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/sebastian-schrama-0a1112255",
        "x_url": "https://twitter.com/JohnnySchlecker",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/20175ab29eae3b6deea06ae3ebba22760fae3df1.jpg"
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    "launches": [
      {
        "id": 94631,
        "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"
      }
    ]
  },
  {
    "id": 29087,
    "name": "ParadeDB",
    "slug": "paradedb",
    "former_names": [
      "Retake"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6668d68dbb65664dcc7f40eff60e4ee586f09132.png",
    "website": "https://paradedb.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "One Postgres for your application data, full-text search, vector retrieval, and aggregations.",
    "one_liner": "You should just use Postgres.",
    "team_size": 11,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1689280457,
    "tags": [
      "Developer Tools",
      "Analytics",
      "Open Source",
      "Infrastructure",
      "Databases"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2023",
    "status": "Active",
    "industries": [
      "B2B"
    ],
    "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": [
      {
        "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 (Phil and Ming) previously built Whist, a cloud-hybrid browser, together with an amazing team of 20 from 2020 to 2023. We originally met at university, in 2016, during the earliest days of orientation, and quickly became close friends, pitching each other startup ideas throughout college, until we decided to make the jump during our senior year.The idea for ParadeDB came from building on the experience acquired in the cloud infrastructure market during our Whist days, and from talking with 50+ customers in the beginnings of YC S23. We initially applied to YC with a completely different idea, but pivoted into what became ParadeDB after seeing more customer interest for the infrastructure we had built to service our prior idea, a sustainability platform, than the idea itself; and thus ParadeDB was born."
      },
      {
        "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 were looking for an environment that would help us make something people want and not get caught in all the other non-essential parts of building an early-stage company. Our experience with YC was shaped by this mindset from application to fundraising and we had a great experience."
      },
      {
        "question": "How have you kept in touch with the YC community and continued to use YC resources & programs since the batch ended?",
        "answer": "We’ve made a bunch of friends in YC, are still in touch with our Group Partner and batchmates, and frequently interact on Bookface."
      },
      {
        "question": "What's the history of your company from getting started until the present day? What were the big inflection points?",
        "answer": "ParadeDB started during the YC batch, in Summer of 2023. We first released `pg_search`, our full-text search product in Postgres. A few months later we released `pg_analytics`, our analytics product in Postgres. We eventually combined them both into a single Postgres extension to offer full-text search and analytics in Postgres. Today, we’re productionizing both in ParadeDB and working to serve increasingly large customers."
      },
      {
        "question": "What is the core problem you are solving? Why is this a big problem? What made you decide to work on it?",
        "answer": "Postgres’ full-text search and analytics capabilities, two critical workloads for SaaS, finance, retail, and countless more industries, are a far cry from dedicated data stores like Elasticsearch. ParadeDB is fixing that."
      },
      {
        "question": "What is your long-term vision? If you truly succeed, what will be different about the world?",
        "answer": "ParadeDB is part of the “Postgres for everything” movement, enabling companies to run increasingly larger parts of their data infrastructure on Postgres in an open-source, free of vendor lock-in world."
      }
    ],
    "url": "https://www.ycombinator.com/companies/paradedb",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/paradedb.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://linkedin.com/company/paradedb",
    "x_url": "https://twitter.com/paradedb",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/paradedb",
    "github_url": "https://github.com/paradedb",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/6668d68dbb65664dcc7f40eff60e4ee586f09132.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [
      "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/ce5ca15131669146d463d97b0579fcdc2d4b71e2.png"
    ],
    "primary_partner": {
      "name": "Harj Taggar",
      "url": "https://www.ycombinator.com/people/harj-taggar"
    },
    "founders": [
      {
        "user_id": 317980,
        "full_name": "Philippe Noël",
        "title": "Founder/CEO",
        "founder_bio": "Founder @ ParadeDB. Previously @Whist, @Microsoft. Harvard CS'20. From Québec.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/philippemnoel",
        "x_url": "https://twitter.com/philippemnoel",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e6ca7eedf6383c2ebb46a29a5f9e96a6e976add1.jpg"
      },
      {
        "user_id": 1341340,
        "full_name": "Ming Ying",
        "title": "Founder",
        "founder_bio": "Founder @ ParadeDB",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/ming-ying",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/19af7b14da5cf743d9de76ee556ebaf69adc3ebb.jpg"
      }
    ],
    "jobs": [
      {
        "id": 74017,
        "title": "Database Engineer — Storage & Query Execution",
        "url": "https://www.ycombinator.com/companies/paradedb/jobs/GCpYraM-database-engineer-storage-query-execution",
        "location": "San Francisco, CA, US / Remote (CA; US)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Backend",
        "salary_range": "$150K - $250K",
        "equity_range": "0.15% - 0.40%",
        "experience": "3+ years",
        "visa": "Will sponsor",
        "skills": [
          "Rust",
          "Distributed Systems"
        ]
      },
      {
        "id": 74019,
        "title": "Distributed Systems Engineer — Postgres Platform",
        "url": "https://www.ycombinator.com/companies/paradedb/jobs/yWsaLaN-distributed-systems-engineer-postgres-platform",
        "location": "San Francisco, CA, US / Remote (US; CA)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Backend",
        "salary_range": "$150K - $250K",
        "equity_range": "0.15% - 0.40%",
        "experience": "3+ years",
        "visa": "Will sponsor",
        "skills": [
          "Amazon Web Services (AWS)",
          "Bash/Shell",
          "Go",
          "Kubernetes",
          "PostgreSQL",
          "Elasticsearch",
          "RDS/Aurora",
          "Distributed Systems",
          "Docker"
        ]
      }
    ],
    "news": [
      {
        "title": "ParadeDB takes on Elasticsearch as interest in Postgres explodes amid AI boom | TechCrunch",
        "url": "https://techcrunch.com/2025/07/15/paradedb-takes-on-elasticsearch-as-interest-in-postgres-explodes-amid-ai-boom/",
        "date": "Jul 15, 2025"
      }
    ],
    "launches": []
  },
  {
    "id": 29103,
    "name": "Inconvo",
    "slug": "inconvo",
    "former_names": [
      "ten.dev",
      "Ten"
    ],
    "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": [
      "Developer Tools",
      "Analytics",
      "API",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2023",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "Ireland",
      "Europe"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "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",
    "x_url": "",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/42126d50fed615bc74167d22b4985b25e9d25fad.png",
    "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"
      }
    ],
    "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"
      }
    ]
  },
  {
    "id": 29105,
    "name": "FlowiseAI",
    "slug": "flowiseai",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/430a7c6b91b2b976c63ca3ebab6cfe4e2a6371d4.png",
    "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": [
      "Developer Tools",
      "Generative AI",
      "Open Source",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2023",
    "status": "Acquired",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "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": "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!"
      }
    ],
    "url": "https://www.ycombinator.com/companies/flowiseai",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/flowiseai.json",
    "year_founded": 2023,
    "city": null,
    "country": null,
    "linkedin_url": "https://www.linkedin.com/company/flowiseai",
    "x_url": "https://twitter.com/FlowiseAI",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/FlowiseAI",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/430a7c6b91b2b976c63ca3ebab6cfe4e2a6371d4.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [
      "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/710e491e2514993ee7527b8a9fd11894a7721990.png"
    ],
    "primary_partner": {
      "name": "Harj Taggar",
      "url": "https://www.ycombinator.com/people/harj-taggar"
    },
    "founders": [
      {
        "user_id": 1358352,
        "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",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b0ff871bb8ebe5923516f186dd30fa89a1b27661.jpg"
      },
      {
        "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",
        "x_url": "https://twitter.com/ChungYauOng",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f43413f8d8df9a38d744580487818074e61ed022.jpg"
      }
    ],
    "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": 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": [
      "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/structured-labs",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/structured-labs.json",
    "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",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/e8dd08fd61491d9efffabb3dff787320791e2421.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": 1194855,
        "full_name": "Amrutha Gujjar",
        "title": "Founder",
        "founder_bio": "Structured",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/amruthagujjar/",
        "x_url": "https://twitter.com/amruthagujjar",
        "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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    "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"
      }
    ]
  },
  {
    "id": 29120,
    "name": "Morph",
    "slug": "morph",
    "former_names": [
      "AutoInfra",
      "Lingtual",
      "innkeeper"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/dedc5ca68422aae62a4f58f3a0823d0903b71997.png",
    "website": "https://morphllm.com",
    "all_locations": "Columbus, OH, USA",
    "long_description": "Specialized inference, built for agent workloads\r\n\r\nFast Open-Source models: Kimi k3, Deepseek v4 flash, qwen 397b, at 200+ tps\r\nSpecialized models for applying edits, code search, compaction, and model routing",
    "one_liner": "Fast Models Optimized for Coding Agents",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1686706939,
    "tags": [
      "Developer Tools",
      "Generative AI",
      "API",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2023",
    "status": "Active",
    "industries": [
      "B2B",
      "Infrastructure"
    ],
    "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/morph",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/morph.json",
    "year_founded": 2025,
    "city": "Columbus",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/morphllm",
    "x_url": "https://twitter.com/morphllm",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/dedc5ca68422aae62a4f58f3a0823d0903b71997.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": 405977,
        "full_name": "Tejas Bhakta",
        "title": "Founder",
        "founder_bio": "inference thats optimized for agents",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/tejas-bhakta",
        "x_url": "https://twitter.com/tejasybhakta",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c6f50e938c0f7e3a90a8e68bbcc0f5d615160f77.jpg"
      }
    ],
    "jobs": [
      {
        "id": 81462,
        "title": "Founding Account Executive",
        "url": "https://www.ycombinator.com/companies/morph/jobs/PSesvJB-founding-account-executive",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$80K - $140K",
        "equity_range": "0.50%",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Growth design"
        ]
      },
      {
        "id": 102427,
        "title": "Member of Technical Staff",
        "url": "https://www.ycombinator.com/companies/morph/jobs/0Z8vI3K-member-of-technical-staff",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Machine learning",
        "salary_range": "$180K - $350K",
        "equity_range": "0.40%",
        "experience": "6+ years",
        "visa": "US citizen/visa only",
        "skills": []
      }
    ],
    "news": [],
    "launches": [
      {
        "id": 108269,
        "title": "Kimi K3 on Morph: near-Fable performance at 1/5 the cost",
        "tagline": "Live on OpenRouter and Vercel's AI Gateway",
        "body": "Kimi K3 is now live on Morph.\n\n![uploaded image](/media/?type=post&id=108269&key=user_uploads/405977/9bf53656-3db4-42fe-92a9-48a4a412df40)\n\nMost open-weight models look promising in benchmarks, then fall apart in production: unreliable tool calls, weak long-context performance, or inconsistent outputs.\n\nGLM-5.2 and Kimi K3 are the first two I’ve tested that feel genuinely production-ready.\n\nIn our benchmarks, Kimi K3 approaches Fable-level performance at roughly half the cost of Opus. On Morph, it comes with:\n\n* 1M-token context\n* 90–200 output tokens/sec\n* Tool calling and structured outputs\n* OpenAI- and Anthropic-compatible APIs\n\nWe want to see how it performs on real workloads, not toy demos.\n\nIf you currently run Anthropic or OpenAI models in production, we’ll cover the cost of routing 5% of your production traffic to Kimi K3. Compare quality, latency, and cost against your existing model with minimal integration work.\n\nWe’d love brutally honest feedback: where it works, where it breaks, and what it would take for you to route more traffic to it.\n\nTry it here: <https://docs.morphllm.com/sdk/components/fast-models>\n\nComment or DM me if you want us to fund your production test.\n\n![uploaded image](/media/?type=post&id=108269&key=user_uploads/405977/cd809dfe-c7e5-406f-9707-f7c250c7113a)\n\n",
        "url": "https://www.ycombinator.com/launches/SAH-kimi-k3-on-morph-near-fable-performance-at-1-5-the-cost",
        "votes": 2,
        "created_at": "2026-07-29T06:05:58.276Z"
      },
      {
        "id": 104095,
        "title": "Reflexes API: Catch what agent logs miss",
        "tagline": "Most Agent failures are behavioral. Catch them at scale ",
        "body": "Behavioral observability for AI agents, built and priced to run on millions of production turns.\n\nMost agent failures don’t show up as errors.\n\n![uploaded image](/media/?type=post&id=104095&key=user_uploads/405977/00b2cef4-ce0d-4a93-a145-0209d28eb3a6)\n\n\nThe API returns 200.\\\nThe tool call succeeded.\n\nBut the agent is looping. The user is frustrated. A jailbreak slipped through. The answer technically completed, but the experience failed.\n\nThat is the problem Reflexes solves.\n\nReflexes are fast classifiers that run on every turn of every agent conversation and catch the behavioral signals normal observability misses:\n\n* user frustration\n* infinite loops\n* jailbreak attempts\n* refusals\n* hallucinations\n* task failures\n* policy violations\n* custom signals specific to your product\n\nTraditional observability tells you when software breaks. Reflexes tells you when the agent experience breaks.\n\nThe reason this has not worked before is cost and latency. Frontier-model LLM-as-judge is fine for offline evals, but it is too slow and expensive to run across production traffic.\n\nReflexes are built and priced to run at scale: millions of turns, inline, across 100% of production conversations.\n\nUnder the hood, Reflexes uses a shared backbone with many small heads, so multiple behavioral signals can run on the same conversation without multiplying latency or cost.\n\nYou can use our default reflexes out of the box, or train a custom reflex for the failure modes that matter to your agent.\n\nWe built this after working with production agent teams and seeing the same pattern repeatedly: agents usually fail long before they throw an error.\n\nThey fail in the behavior.\n\nTry Reflexes: <https://www.morphllm.com/products/reflex>",
        "url": "https://www.ycombinator.com/launches/R4x-reflexes-api-catch-what-agent-logs-miss",
        "votes": 5,
        "created_at": "2026-06-27T14:31:15.899Z"
      },
      {
        "id": 98898,
        "title": "FlashCompact: A specialized model for context compaction",
        "tagline": "33k tok/sec context compaction for coding agents",
        "body": "We built **FlashCompact** because context compaction is one of the most broken parts of modern coding agents.\n\nRight now, compaction is:\n\n* slow (often 2+ minutes)\n* lossy (kills useful context)\n* expensive (wastes tokens and steps)\n\nSo people avoid it… and agents degrade over time.\n\n---\n\n![uploaded image](/media/?type=post&id=98898&key=user_uploads/405977/77e4cb4f-c326-4f2b-8602-2aca1e0fa9c3)\n\n\n### What we built\n\nA **specialized model for context compaction**:\n\n* **33,000 tokens/sec throughput**\n* **200k → 50k tokens in \\~1.5s**\n* Designed specifically for agent workflows, not general summarization\n\nCompaction should feel invisible. This actually does.\n\n---\n\n### Why this matters\n\nWe analyzed **200+ real agent sessions** across **40+ top coding agent harnesses**.\n\nThe core insight:\n\n> Most context bloat comes from tool responses, not model generation.\n\nThat means naive summarization fails, because it compresses the wrong things.\n\nFlashCompact:\n\n* removes redundant tool output\n* preserves execution-relevant state\n* reduces context without hurting task performance\n\nResult:\n\n* no performance drop\n* fewer tokens\n* fewer steps\n\n---\n\n### The deeper point\n\nAgents don’t fail because models are weak.\n\nThey fail because their **context degrades over time**.\n\nIf you want agents to:\n\n* run longer\n* take more steps\n* stay coherent across complex tasks\n\nYou need **clean, compressed context**.\n\n<https://docs.morphllm.com/sdk/components/compact>",
        "url": "https://www.ycombinator.com/launches/Pj8-flashcompact-a-specialized-model-for-context-compaction",
        "votes": 6,
        "created_at": "2026-03-18T14:42:28.223Z"
      },
      {
        "id": 98329,
        "title": "WarpGrep v2: Code Search Subagent -> #1 on SWE-Bench Pro",
        "tagline": "Code search limits coding capabiltiies. Moving it out to a specialized model wins.",
        "body": "### WarpGrep v2 is a fast code search subagent that works via parallel tool calls. Runs up to 36 grep/read tool calls in under 5s.\n\n![uploaded image](/media/?type=post&id=98329&key=user_uploads/405977/ba17c624-92ca-4502-8c56-00c22e31ad4e)\n\n### SWE-Bench Pro: WarpGrep v2\n\n#### Scores\n\n* Opus 4.6 → 55.4\n* GPT-5.3 Codex → 56.0\n* MiniMax 2.5 → 55.4\n* Opus 4.6 + WarpGrep → **57.5** (**+2.1**)\n* Codex 5.3 + WarpGrep → **59.1 (+3.1)**\n* MiniMax 2.5 + WarpGrep → **57.6** (**+3.7**)\n\n#### Efficiency\n\nTokens:\n\n* Input tokens: **\\~17% less** (Opus, Codex, MiniMax, etc..)\n* Output tokens: **13% less** (fewer turns)\n\nTurns (MiniMax):\n\n* Avg turns per task: **157 → 135**\n\nRuntime (Opus):\n\n* Opus 4.6: **518s**\n* Opus 4.6 + WarpGrep: **545s**\n* **178s saved** (**12% faster**)\n\nCost (Opus):\n\n* Opus 4.6: **$3.06**\n* Opus 4.6 + WarpGrep: **$2.51**\n* **$0.55 saved** (**15.6% cheaper**)\n\n#### TLDR\n\nWarpGrep v2 raises SWE-Bench Pro scores (**+2.1 Opus**, **+3.7 MiniMax**) while using **\\~17% fewer input tokens**, **13% fewer turns**, running **12% faster**, and costing **15.6% less**. The median WarpGrep codebase search takes 5s end to end compared to 75s for the Claude Code Explore subagent\n\nOn normal usage on production repos these numbers improve across the board \\~40% faster\n\n\\\ninstall it in your favorite coding agent here <https://www.morphllm.com/mcp>\n\nor integrate it into your product here <https://docs.morphllm.com/sdk/components/warp-grep/tool>",
        "url": "https://www.ycombinator.com/launches/PZx-warpgrep-v2-code-search-subagent-1-on-swe-bench-pro",
        "votes": 4,
        "created_at": "2026-03-02T15:39:58.078Z"
      },
      {
        "id": 95846,
        "title": "WarpGrep: A 20x faster subagent to grep for code",
        "tagline": "50% faster than Cognition's SWE-grep - improve Claude Code or Codex via MCP ",
        "body": "**Problem**\\\nCoding agents don’t feel fast because they aren’t.\n\nIn our benchmarks, agents spend **60%+ of their time searching for the right code**, not generating any. They why they do more than you want, and break developer flow.\n\nThe bottleneck isn’t “agent intelligence.”\\\nIt’s **speed, context retrieval** and the **irrelevant code** that gets shoved into the prompt.\n\nMost agent stacks today are basically **sequential grep pipelines**:\n\n1. Ask the model where to look\n2. Call a tool\n3. Read output\n4. Repeat 10–20x\n\nIt’s slow, noisy, and compounds latency every step.\n\nWarpGrep is built to do that dirty job correctly and fast.\n\n**Our Insight**\n\n\\*\\*We value human attention.\\*\\*\\\nYou can’t build responsive coding agents until retrieval is treated as its own learning and inference optimization problem.\\\nWe optimized for a simple goal: keep both the developer and the agent inside the sub-10-second “flow window.” Anything slower and usage collapses.\n\n**What we built**\\\nWarpGrep is an RL-trained retrieval model designed specifically to be used as a tool by a coding agent. It operates under a strict budget:\n\n![uploaded image](/media/?type=post&id=95846&key=user_uploads/405977/cbc2f17d-1ff9-4d7c-bfa1-38d3d36b3ac7)\n\n* Up to eight parallel tool calls per turn (grep, glob, file read, semantic search)\n* A reward function that only cares about two things: did it fetch the correct files and did it hit the correct line ranges.\n\nWarpGrep is an expert at deciding what to grep, and what context is relevant for the task. That’s it. This combination reduces context rot by more than fifty percent in production and eliminates the “forty irrelevant files in your prompt” failure mode.\n\n**Performance**\\\nSWE-Grep runs at around 650 tokens per second on Cerebras.\\\nWarpGrep hits around 900 tokens per second on B200.\\\n\\\nWe worked closely with NVIDIA to optimize WarpGrep. CUDA gives us the stability and customization ability to push non-standard inference workloads for parallel search.\n\n![uploaded image](/media/?type=post&id=95846&key=user_uploads/405977/8e04cd3d-9646-4f25-a0f6-96d2a440471b)\n\n**RL Training**\\\nRL for MOEs is notoriously inefficient, so we built infrastructure to eliminate dead time:\n\n* Dedicated inference and training GPU pools, continuous rollout streaming to the trainer\n* Controlled policy staleness without collapsing effective sample size\n* Partial rollout interruption so slow sequences don’t stall sync\n* In-flight weight updates so vLLM workers ingest new weights mid-generation with only millisecond pauses\n\nThose optimizations delivered a 1.6 to 2.35 times training throughput boost with essentially no sample efficiency loss.\n\n**Why this matters**\\\nEvery company building coding agents is running into the same wall.\\\nOnce your agent touches a large codebase, retrieval dominates latency and derails reasoning.\\\nYou solve it by giving the agent a retrieval system that behaves like a specialist, not a bottleneck.\n\nIf you want an agent that actually performs on large codebases, doesn’t have crippling context rot, and stays within real-time latency, reach out!\n\nhttps://docs.morphllm.com/api-reference/endpoint/mcp\n\nhttps://docs.morphllm.com/sdk/components/warp-grep",
        "url": "https://www.ycombinator.com/launches/Ovu-warpgrep-a-20x-faster-subagent-to-grep-for-code",
        "votes": 17,
        "created_at": "2025-11-28T19:27:09.731Z"
      },
      {
        "id": 90352,
        "title": "Morph: The \"other models\" you need to build coding agents like Cursor",
        "tagline": "Instantly apply AI output into code and files (5000+ tok/sec). Build your own coding agents. ",
        "body": "**TLDR: Morph: the “other models” you need to build the best coding agents like Cursor and Windsurf.**\n\n**Retrieve and rerank code, stuff context, and apply edits to files FAST. Relevant context, fast applies, every time.**\n\n**Morph Apply:** The fastest way to apply updates from Claude, GPT-4o, and others into any file - codebases, docs, etc - 5000+ tok/sec\n\n[Try API for Free →](https://morphllm.com/dashboard)\n\n![uploaded image](/media/?type=post&id=90352&key=user_uploads/405977/887a632b-bd61-4ace-9af5-d6abc166c319)\n\n> Benchmarked on a 9,000 token file, \\~2 seconds\n\n# **The Problem**\n\nThere’s no good way to apply edits that models want to make into files. Outputting the full file again is slow and expensive. Diff/Patch edits are brittle and a poor product experience.\n\nIn a production setting, AI agents need to update thousands of files. What about when you have a 50k token docx to update? Or when you need to be world-class at retrieving relevant info from a 500+ file repo?\n\n# **Solution:**\n\nMorph is the foundational infrastructure for AI Coding Agents that **_work and feel amazing_** _-_ not a quick demo.\n\n**~~Tired~~**~~: Chunked RAG and having Claude re-output full files~~\n\n**Wired**: Syntax-aware embeddings, reranking, and Fast Apply models = the perfect product experience\n\n**Cursor and Windsurf _roughly_ do this:**\n\n1. For a query, search for top-k relevant embeddings.\n2. Re-rank the corresponding content with a re-ranking model → stuff prompt using Claude/Gemini tool calls\n3. Use Claude/Gemini to generate small, focused changes\n4. Use a Fast Apply model to apply those changes back to the original file\n\n**We provide:**\n\n**Morph Apply**: _Fast Apply_ model: Merge updates from GPT-4o, Claude, and others into your files in under 2s (5000+ toks/second) \\\n**Morph Embeddings:** Syntax-aware embeddings, built for code\n\n**Morph Reranking:** Rerank functions/classes or file snippets to stuff your context with only the relevant context - every time.\n\n[Try it Now →](https://morphllm.com/dashboard)\n\n**Morph SDK:** Intelligently watch for file changes + smarter embeddings.\n\n![uploaded image](/media/?type=post&id=90352&key=user_uploads/405977/20ff3242-a426-4ec3-8c62-4e8633a5cc74)\n\n> Morph Fast Apply dropped errors by 8x vs. patch-based edits in our internal IDE and worked on our largest files - **Staff Eng @ Fortune-50**\n\nIf you’re building the Cursor for \\__\\_, or building agents that modify code:\n\nEmail us: [info@morphllm.com](mailto:info@morphllm.com)\n\n[Grab a Time Here](https://calendar.app.google/PW4nayCdGanN9iEKA)\\\nGet Started for Free: https://morphllm.com\n\n[Self Host Morph](https://morphllm.com/blog/self-hosting)",
        "url": "https://www.ycombinator.com/launches/NVI-morph-the-other-models-you-need-to-build-coding-agents-like-cursor",
        "votes": 31,
        "created_at": "2025-05-13T16:56:19.950Z"
      }
    ]
  },
  {
    "id": 29123,
    "name": "Glide",
    "slug": "glide-2",
    "former_names": [
      "WalletKit"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d1c76d50e7b1ba3c361d312f4e312c3e5f8f54b3.png",
    "website": "https://buildwithglide.com",
    "all_locations": "New York City, NY, USA; Remote",
    "long_description": "Glide lets apps accept crypto deposits from any chain, wallet, or exchange using pre-built wallet funding flows. Users can fund wallets directly — no bridges, no swaps, no repeated KYC.",
    "one_liner": "Crypto Deposits, Wallet Funding, and Pay-with-crypto Infra",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1689702823,
    "tags": [
      "Developer Tools",
      "Crypto / Web3",
      "B2B",
      "API",
      "Infrastructure"
    ],
    "tags_highlighted": [
      "Crypto / Web3"
    ],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2023",
    "status": "Acquired",
    "industries": [
      "B2B",
      "Infrastructure"
    ],
    "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/glide-2",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/glide-2.json",
    "year_founded": 2023,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/paywithglide",
    "x_url": "https://twitter.com/tusharsoni1205",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/usewalletkit",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/d1c76d50e7b1ba3c361d312f4e312c3e5f8f54b3.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": 139706,
        "full_name": "Tushar Soni",
        "title": "Founder",
        "founder_bio": "Co-founder, CEO @ Glide (buildwithglide.com)\n\nPrior to starting Glide, I was a tech lead at Robinhood Crypto building the Robinhood Wallet app. Previously, I worked on large-scale consumer apps such as Uber Eats, Apple Music, and App Store.\n\nI also created and maintain Copper (https://gocopper.dev) - a fullstack toolkit to build web apps in Go.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/tusharsoni",
        "x_url": "https://twitter.com/tusharsoni1205",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4eaba884107d19c2cd6d94abab93483bc503a360.jpg"
      },
      {
        "user_id": 1440060,
        "full_name": "Qinyu Tong",
        "title": "Founder",
        "founder_bio": "I'm the co-founder at WalletKit building the best developer platform for web3 consumer app developers. Prior WalletKit, I was at Robinhood Crypto building the Robinhood Wallet. Previously, I worked at LinkedIn on enterprise infra such as Ads API, AI Infra. ",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/tongqinyu",
        "x_url": "https://twitter.com/qtofrivia",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/111d623f397ce92074da29e898a8e59f7e8bd78f.jpg"
      }
    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 73221,
        "title": "WalletKit — Developer platform for building consumer-friendly web3 apps",
        "tagline": "Build web3 apps with wallets, tokens, and NFTs using simple HTTP APIs",
        "body": "**_⏳ TLDR;_** WalletKit is a developer platform, that helps you build decentralized apps without any crypto knowledge. It is best used for building user-friendly consumer apps aimed at mass adoption. Come talk to us if you’re building in this space or if you’re curious about adding decentralized features to your product.\n\nHey everyone! This is [**@Tushar Soni**](https://bookface.ycombinator.com/user/139706) and [**@Qinyu Tong**](https://bookface.ycombinator.com/user/1440060) from [**@WalletKit**](https://bookface.ycombinator.com/company/29123), and we are super excited to tell you what we’ve been working on.\n\n![uploaded image](/media/?type=post&id=73221&key=user_uploads/139706/1b7b6d81-ebee-42dd-a5bf-c926342dc9d6)\n\n---\n\n### **🤔 Problem**\n\nCrypto has gone through several ups and downs in its decade-long history. However, we have yet to build meaningful use cases outside of trading. There are a few reasons that are slowing us down:\n\n1. **Low Adoption**: People find crypto products hard to use, confusing, risky, or scammy. We believe this is because it is incredibly difficult to build trusted brands and high-quality user experiences that everyone has come to expect from the products they use.\n2. **High Complexity**: Blockchain is a collection of really complicated technology and building consumer products directly on top of it will take a lot of expertise and a long time.\\\n   Imagine trying to build a Rewards & Loyalty Program - you have to pick a chain, work with smart contracts, figure out how users will manage their wallets, handle transactions, reorgs, gas management, and so much more. You have to do this while making sure everything is done securely so you and your users don’t lose their digital assets.\n3. **Developer Tooling**: The popular developer platforms are too low-level. They are usually a mirror of Blockchain Node APIs aimed at node operations, not building consumer apps.\n\nOur goal is to elevate the developer experience for building decentralized consumer apps and enable builders to focus on their use case, not blockchain infrastructure.\n\n---\n\n### **🔧 Solution**\n\nWe are rethinking how to build decentralized apps by providing engineers with simple high-level abstractions to create amazing products.\n\nWalletKit wraps popular blockchain building blocks into easy-to-use HTTP APIs. Today, we support building with wallets, tokens, and NFTs.\n\n![uploaded image](/media/?type=post&id=73221&key=user_uploads/139706/77b906df-a7b3-4387-ad5f-43630e739bdf)\n\nWe took it a step further with WalletKit Dashboard - a digital asset management tool for your app-related digital assets. Use WalletKit Dashboard to create wallets, tokens, mint NFTs, make transfers, and interact with user wallets.\n\n![uploaded image](/media/?type=post&id=73221&key=user_uploads/139706/feafd2f1-3d58-493f-bc5e-3ee76bf2f14e)\n\n---\n\n### **👽 Founders**\n\nQinyu and I met at Robinhood, where we led the Web3 team responsible for building Robinhood Wallet. We experienced firsthand the lack of tools and infrastructure needed to build a consumer-friendly product.\n\nIt became clear to us that this gap in infrastructure is holding back the entire community from creating amazing products that have a chance at mass adoption. It acts as a barrier for founders to build decentralized products. WalletKit aims to remove this barrier entirely.\n\n---\n\n### **🤝 Ask & Deal**\n\nConnect us with founders/builders who are building decentralized apps or want to add decentralized features! Feel free to send an intro email to [**tushar@usewalletkit.com**](mailto:tushar@usewalletkit.com). We would love to help out.\n\nFor all YC companies and connections that come through the YC network, we offer a white-glove service and discounted rates :)",
        "url": "https://www.ycombinator.com/launches/J2z-walletkit-developer-platform-for-building-consumer-friendly-web3-apps",
        "votes": 31,
        "created_at": "2023-07-19T15:30:20.915Z"
      }
    ]
  },
  {
    "id": 29150,
    "name": "Tempo",
    "slug": "tempo-2",
    "former_names": [
      "Tempo Labs"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/860f478b7cd2ea33eefb86e90c9c693abef2997f.png",
    "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,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1689887097,
    "tags": [
      "Developer Tools",
      "B2B",
      "Design Tools",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2023",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "Canada",
      "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/tempo-2",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/tempo-2.json",
    "year_founded": 2023,
    "city": "Toronto",
    "country": "CA",
    "linkedin_url": "https://www.linkedin.com/company/tempo-labs/",
    "x_url": "https://twitter.com/Tempo_Labs",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/860f478b7cd2ea33eefb86e90c9c693abef2997f.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": 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",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/8c7830f8663eab5c6d02ae78b8d45d215d44e638.jpg"
      },
      {
        "user_id": 187455,
        "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",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/736fd7198b0fd99e0e711bdeb7288da5fbf5e458.jpg"
      }
    ],
    "jobs": [
      {
        "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": [
          "Node.js",
          "React"
        ]
      },
      {
        "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": [
          "React",
          "TypeScript",
          "Figma",
          "Tailwind"
        ]
      }
    ],
    "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"
      }
    ],
    "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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    "id": 29156,
    "name": "CodeStory",
    "slug": "codestory",
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    "all_locations": "London, England, United Kingdom",
    "long_description": "We're building Aide, an AI-native IDE designed for engineers to enjoy problem-solving with agents by their side.\r\n\r\nWe're currently a team of two, based in London, United Kingdom. Between us, we have been tech leads with experience building testing infrastructure at Meta, payment systems for 150k merchants in India, been an ACM ICPC world finalist and Open-Source contributor to critical infrastructure including gRPC and the Bazel build system. We love dev tooling, and enjoy thinking about the future of programming.",
    "one_liner": "Aide is an AI-native , privacy-first IDE built on top of VSCode",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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        "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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      {
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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.",
        "is_active": false,
        "linkedin_url": "https://linkedin.com/in/naresh-ramesh",
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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"
      },
      {
        "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",
        "votes": 38,
        "created_at": "2023-08-04T22:58:55.458Z"
      }
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    "id": 29182,
    "name": "Upsolve AI",
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    "website": "https://upsolve.ai/",
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    "long_description": "Upsolve AI is the analytics platform for deploying governed, grounded, and trustworthy data agents that know your business. Data teams use Upsolve's Agent Studio to get to AI-ready data foundations fast, unify and curate their context layer, and test, tune and monitor their Upsolve Data Agent to their benchmark. The company is founded by Ka Ling Wu and Serguei Balanovich, who built a similar product at Palantir before (featured in Palantir's S-1), growing it to 50+ enterprise customers and 8-figures of annual revenue in 2 years.",
    "one_liner": "Deploy trustworthy data agent that know your business",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Analytics",
    "launched_at": 1699320905,
    "tags": [
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      "B2B",
      "Analytics",
      "Big Data",
      "AI"
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    "isHiring": true,
    "nonprofit": false,
    "batch": "Winter 2024",
    "status": "Active",
    "industries": [
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      "Analytics"
    ],
    "regions": [
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      "Partly Remote"
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/upsolve-ai",
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    "year_founded": 2023,
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    "country": null,
    "linkedin_url": "https://www.linkedin.com/company/upsolveai/",
    "x_url": "https://twitter.com/upsolveai",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/upsolve",
    "github_url": "https://github.com/Upsolve-Labs",
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    "primary_partner": {
      "name": "David Lieb",
      "url": "https://www.ycombinator.com/people/david-lieb"
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    "founders": [
      {
        "user_id": 1148602,
        "full_name": "Ka Ling Wu",
        "title": "Founder/CEO",
        "founder_bio": "Ka Ling is the Co-founder & CEO of Upsolve AI. Before Upsolve, Ka Ling led product solution development at nPlan, a Series A AI & Construction tech startup, focusing on client expansion. Before her stint at nPlan, she spent four years at Palantir where her responsibilities ranged from managing client engagements and stakeholder relationships to spearheading the creation of Palantir's HyperAuto product from inception to market launch. Ka Ling also opened the Korea market for Palantir.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/wukaling",
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      {
        "user_id": 1428286,
        "full_name": "Serguei Balanovich",
        "title": "Founder/CTO",
        "founder_bio": "Serguei is the Co-founder & CTO of Upsolve. Before Upsolve, Serguei spent seven years at Palantir where he pioneered early Supply Chain and Manufacturing commercial work, and later productized this work into Palantir HyperAuto. Serguei also worked on Palantir Apollo as a dev lead.\nOutside of software, Serguei loves puzzles, board games, and teaching.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/sbalanovich",
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    "jobs": [
      {
        "id": 82224,
        "title": "Founding AI Engineer",
        "url": "https://www.ycombinator.com/companies/upsolve-ai/jobs/WCoJcdG-founding-ai-engineer",
        "location": "London, England, GB",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "£100K - £140K GBP",
        "equity_range": "1.00% - 3.00%",
        "experience": "6+ years",
        "visa": "US citizenship/visa not required",
        "skills": []
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    ],
    "news": [
      {
        "title": "Here's the pitch deck that secured $1.5 million from Hubspot",
        "url": "https://www.smartcompany.com.au/exclusive/pitch-deck-upsolve-ai-secured-1-5-million-hubspot/",
        "date": "Sep 18, 2024"
      }
    ],
    "launches": [
      {
        "id": 103717,
        "title": "🐳 Upsolve AI - Agent Studio for Data Team",
        "tagline": "Deploy trustworthy and governed analytics agent that know your business and data.",
        "body": "**🏆 TL;DR:** Upsolve AI is context infrastructure for analytics agents. We help data teams ship analytics agents that non-technical users actually trust. Agents that pull the _right_ numbers and explain them in your business's context, not just generate plausible SQL. If you've ever tried to put an analytics agent in front of your team and quietly killed it after it gave two different answers to the same question, this is for you.\n\n<https://youtu.be/2bXZb6D-cNA>\n\n## ❌ **The Problem**\n\n\"Let's just build an analytics agent.\" Every data team drowning in requests has this thought. The beta feels like magic until a non-technical user asks the same question three times and gets two different answers. Trust dies. The project quietly joins the 95% of AI POCs that never reach production.\n\nYou already know it's not the model, GPT and Claude write fine SQL. The model just has no idea how _your_ business works:\n\n* **Governance and permission can't live in a prompt.** You can't trust an LLM to implement row- and column-level access or enforce who sees what. Without governance that an agent can't override, you can't put it in front of anyone outside the data team.\n* **It pulls the wrong data and joins the wrong tables.** “gross_revenue” vs “net_revenue”, “customers” vs “users”. A semantic layer problem dressed up as a text-to-SQL one.\n* **Technically correct, practically wrong.** Your fiscal year ends in March, not December. The number is \"correct\" and still useless.\n* **Your semantic layer and context goes stale.** \"User\" got redefined twice since you scoped the project. Your semantic layer and context didn't keep up.\n* **No observability, no improvement.** If you can't trace and root-cause a bad answer, you can't improve it.\n\nThese aren't LLM model problems. They're context problems, and context lives in docs, Slack threads, validated SQL from 2021, and your analysts' heads. No amount of SQL generation skill recovers it.\n\n## ⚒️ What Agent Studio gives you\n\nA builder surface to encode context across three layers: **Structure** (schema, lineage, semantic model), **Meaning** (metrics, KPIs, business rules), and **Trust** (verified answers, usage signals, golden sets), then deploy and tune against it:\n\n![uploaded image](/media/?type=post&id=103717&key=user_uploads/1148602/44acebc6-4f8c-4fb2-86e0-cc9959bbd2df)\n\n* **Software-defined, granular permissioning** baked into the data model, enforced beneath the agent.\n* **A self-updating context layer** that captures institutional knowledge across your files and systems, so metric redefinitions and new launches don't silently break answers.\n* **End-to-end tracing, an eval harness, and a staging sandbox**. Golden query sets and LLM-as-judge scoring before a single user sees an answer, plus prompt and SQL provenance for every response in production.\n* **A compounding accuracy loop**. Wrong answers and poor behavior get flagged from real conversations and fed back, so the agent gets _more_ trustworthy over time.\n\n**End result:** No existing semantic model required to start. Your team deploys analytics agents they don't have to babysit, and your non-technical users get answers they trust, wherever they already work (Slack, your product, internal portal, or any MCP surface).\n\nTeams hit production-grade eval accuracy, clear 60–80% of their ad-hoc backlog in 7 days, and move stakeholders from a 3–5 day queue to answers in seconds.\n\n![uploaded image](/media/?type=post&id=103717&key=user_uploads/1148602/79a3a29c-482f-4119-92f5-38612bd34bdb)\n\n## 🤝 Why trust us\n\nWe’re already in production with Fortune 500 users, 100+ person BI teams, and growth-stage companies. We are the team that built HyperAuto at Palantir, and encoding messy institutional context into systems is the problem we've spent years on.\n\n## 🙏 Our ask\n\nThis is for you if you own a data or BI function and you're either:\n\n* Drowning in ad-hoc requests, where **repeat questions eat your analysts' week** and a generic GPT-on-the-warehouse attempt already fizzled, or\n* A **B2B SaaS team whose customers keep asking for deeper analytics and insights** and you don't want to spend two quarters of engineering effort building it.\n\nIf you're a Head of Data, BI lead, analytics engineer, or VP Product who lives this, [**book a demo here**](https://calendly.com/kaling-aqk/upsolve-initial-exploration) or reach me directly at [kaling.wu@upsolve.ai](mailto:kaling.wu@upsolve.ai). We'll stand up a POC against your real data warehouse, not a sandbox.",
        "url": "https://www.ycombinator.com/launches/Qyr-upsolve-ai-agent-studio-for-data-team",
        "votes": 14,
        "created_at": "2026-06-23T03:55:11.309Z"
      },
      {
        "id": 89121,
        "title": "🐳 Upsolve AI - Embed GenBI in Your App",
        "tagline": "Spoil your users with hyper-personalized customer-facing analytics and insights that adapt on demand and “Just-Works”.",
        "body": "# 🏆 **TL;DR**\n\nGeneric dashboards in SAAS platform suck. Some might even say they’re dead.\n\nBut nearly all SaaS apps need a dashboard to show proof of value to stakeholders. With [Upsolve AI](https://upsolve.ai/), delight your end users with customer-facing analytics that “Just Works”, Make them want to use the analytics and love your product more.\n\nOnce you Upsolve your platform with our GenBI solution, your end users get to access adaptive and hyper-personalized analytics simply by telling your platform their persona and what kind of KPIs they care the most. They can easily drill down into the data at the speed of thought via natural language prompting. Our AI also interprets the data and provides guided insights, shedding light on what matters the most. Our AI can then investigate the data further, provide additional insights to optimize decision making.\n\n# **🤨 Problem - Generic Dashboards in SaaS apps suck.**\n\n🗺️ Can you imagine planning a cross-continent trip with nothing but a paper map?\n\n⁉️ \"Duh.\" Of course not.\n\n😵‍💫 Yet this is precisely what SaaS users endure with traditional dashboards every day. They're like paper maps showing only major highways and cities—filled with generic metrics and charts that, for the most part, have zero relevance to your customer’s unique destination.\n\n**Users get no value out of generic dashboards.** CFO, Regional directors and store managers stare at identical metrics in your expensive SaaS platform that took months to implement. Both search for answers to different questions to achieve different objectives. Both get lost. Their mission controls shouldn’t look the same.\n\n**Your teams feel this pain too.** They’ve heard “can you get this chart for me?” from their end users way too many times. Visionaries become data query processors right when product innovation matters most. You end up building the infamous “Download CSV” button in your product or exposing an API to allow your customer to extract a data cut. As a result, you lose in-product user engagement prematurely.\n\n**Dashboards should give the end user that “it gets me” feeling without the overhead.** It should create moments of delight and clarity that elevate decision-making from burden to superpower. It should be part of the reason your customers choose your product. It should turn your customers into your advocates.\n\n# **💡 Solution - With Upsolve AI, you demonstrate and enhance your value to customers**\n\nIn a world of paper-map dashboards, Upsolve delivers the magic of Modern Map Apps for your customers' data to your end users. Give each end-user intelligent dashboards tailored to their goals and objectives, real-time alerts, and highlighting trends and insights worth doing something about— an all-in-one experience that transforms static metrics into operational brilliance. [Watch the demo video below](https://youtu.be/K6GiczydAQI):\n\nWe’re ready to power your customer-facing analytics and give your users those “aha!” moments with our AI features below:\n\n1. **AI Report Generator: Adaptive, Hyper-personalized Analytics and Dashboard** 🪄\\\n   Give every end user that bespoke experience they deserve. Upsolve’s next-gen dashboard spins up analytics and interfaces dynamically based on user’s unique role, surfacing precisely the KPIs that drive decisions, at the right time.\n\n   ![uploaded image](/media/?type=post&id=89121&key=user_uploads/1148602/9fb2c6dd-b242-44fd-9995-6aba0933bdb2)\n\n2. **AI Drill Down: Natural Language Slice & Dice**\\\n   Built to make data-driven decision more accessible to less tech-savvy users. Applying 5 filters? Text to SQL? Skip these all together. Let you users query in natural language and watch the magic happen at the speed of thought.\n\n   ![uploaded image](/media/?type=post&id=89121&key=user_uploads/1148602/6fe57514-06d4-44d2-b1ff-4d78ec735a1e)\n\n3. **AI-Guided Insights: Interpretation**\\\n   An AI that picks up the signs for you 🎏 Upsolve flags important data signals and anomalies and push alerts to the user automatically, with no need to set up any automations up front.\n\n   ![uploaded image](/media/?type=post&id=89121&key=user_uploads/1148602/c946ad6b-36bc-4f63-bfb7-e732ede6178b)\n\n4. **AI-powered Investigation: Great analysts identify what users DIDN’T ask for but what they actually need**\\\n   Upsolve connects the dots, spots the trends, and asks questions you didn’t even think of to get the big “whys” answered. Guide your team’s decisions with AI-powered nudges.\n\n   ![uploaded image](/media/?type=post&id=89121&key=user_uploads/1148602/26a6d178-c603-4cc0-aeab-0df6614289a0)\n\n\nGive your users a dashboard, along with a customer success manager, AND a data analyst that proactively provides intelligence without them asking. That’s Upsolve AI, the all-in-one data experience your customers deserve, without you lifting a finger.\n\n# **🙏 Ask**\n\nTempted to Upsolve your product and embed GenBI in your product? Grab a time slot [here](https://calendly.com/kaling-aqk/upsolve-initial-exploration) with us today or reach us at kaling.wu@upsolve.ai!\n\n![uploaded image](/media/?type=post&id=89121&key=user_uploads/1148602/2c9606ff-c549-4c9d-a83d-15ec22fb82ce)\n\n",
        "url": "https://www.ycombinator.com/launches/NBR-upsolve-ai-embed-genbi-in-your-app",
        "votes": 45,
        "created_at": "2025-03-31T15:41:46.714Z"
      },
      {
        "id": 84312,
        "title": "🐳 Upsolve AI - Embedded Business Intelligence (BI)",
        "tagline": "Allow yours users to build and customize their dashboards and reports within your platform.",
        "body": "🏆 **TLDR**\\\n[Upsolve AI](https://upsolve.ai/) allows you to build and deliver customer-facing analytics to your end-users via an embeddable dashboard.\n\nWe’ve just released our newest feature: **Personal Workspace for dashboards. This allows your end users to build their own dashboards and reports within your product.** Your users no longer need to wait for your customer success manager or product team to get the metrics or reports they need! 📈\n\nSome examples of how our customers enable their end users with this Upsolve feature:\n\n* An expense management platform allows their end users to build out customized receipt audit reports\n* An AI observability platform enables their solution engineers and enterprise customers to build tailored observability metrics report\n* A supply chain risk management platform empowers their Fortune 500 customers to build out targeted supply chain visibility dashboard\n\n**🤨 Problem**\\\nMost B2B SaaS companies need to build dashboards. [**A true dashboard communicates your product value to all stakeholders of your customers, even — and especially — those who never use the app.**](https://www.saastr.com/want-go-upmarket-need-great-dashboard/) This is especially true for enterprise software.\n\nHowever, most, if not all, traditional dashboards failed to achieve this. Traditional dashboards are highly restrictive. Customers cannot customize the dashboard to fully understand their unique state of the world. This leads to frequent ad-hoc data cuts and reporting requests, causing operational friction with your customer support, product, and engineering teams. What’s worse, this means your users can’t get their questions answered right away, resulting in a subpar product experience.\n\n**💡 Solution - Personal Dashboard Workspace**\\\n“Upsolve your product” by embedding our component in your product. Your users gain the superpower to build out their own version of dashboards, either by building them from a blank canvas or by modifying the dashboard template you ship out. [Watch the demo below](https://youtu.be/hj7VJSC_LyU?feature=shared):\n\n1. Chart Explorer:\\\n   Your end users will now have access to all the verified/published charts your organization has provided. This means you can produce dozens of charts but leave it up to your end users to choose which of these charts they actually care to see and in which positions on their dashboard.\n\n   ![uploaded image](/media/?type=post&id=84312&key=user_uploads/1148602/09a4f16d-2f03-40e2-96b8-07e272beedd4)\n\n2. Point and Click Builder:\\\n   If none of the published charts are good enough for your end users' use cases, your end users can access a point-and-click chart builder. Any charts they produce will be surfaced back to you for potential reuse/sharing among your other users.\n\n   ![uploaded image](/media/?type=post&id=84312&key=user_uploads/1148602/743ca11c-4cb9-4144-bf34-1a260c049b9e)\n\n\n**🙏 Ask**\\\nIs this a problem you are facing, and do you want to solve it at the root? Tempted to Upsolve your product? Grab a time slot [here](https://calendly.com/kaling-aqk/upsolve-initial-exploration) with us!",
        "url": "https://www.ycombinator.com/launches/Lvs-upsolve-ai-embedded-business-intelligence-bi",
        "votes": 57,
        "created_at": "2024-09-26T15:01:45.124Z"
      },
      {
        "id": 78495,
        "title": "🐳 Upsolve AI - The new way to build and offer analytics to your customers",
        "tagline": "Build customer-facing analytics that get your users to take in-product actions and become obsessed with your product!",
        "body": "### **🏆 Tl;dr:**\n\n[**Upsolve AI**](https://upsolve.ai/) **helps companies build and offer analytics to their customers**, with AI answering any additional data questions. Ship analytics using an AI-powered builder, and embed them as native frontend components in your product. The dashboard shows your customers insights about your product and guides them with action recommendations to boost your product’s effectiveness. For example, [marketing companies](https://upsolve.ai/impact-study/fiber) use Upsolve to help users optimize their campaigns, and fintech companies use it to help users manage their accounts. [Watch our demo!](https://youtu.be/Vobh2hw_Pgk)\n\n### **💯 The Team**\n\nTogether, [Ka Ling](https://www.linkedin.com/in/wukaling/) and [Serguei](https://www.linkedin.com/in/sbalanovich/) have over 15 years of experience in data engineering and analytics. We took Palantir's Hyperauto (mentioned in Palantir's DPO S-1) from inception to launch, scaling the product to serve more than 50 enterprise customers in less than 2.5 years and generating eight figures in annual revenue.\n\nHaving experienced firsthand the challenges of building customer-facing analytics at startups and working alongside users from over 100 companies, including Fortune 10 (we’ve been on the frontlines at factories and assembly lines with users!), we're determined to simplify data analytics. That's why we created Upsolve AI - to automate and augment analytics. We're committed to ensuring that no business is limited by its analytics-building capabilities and enabling every end user to make informed decisions based on their data.\n\n![uploaded image](/media/?type=post&id=78495&key=user_uploads/1148602/0496fa95-d371-4744-bc52-895cb3457400)\n\n## **❌ The Problem**\n\n🔨 **Building customer-facing analytics is hard:** As a founder or SaaS product owner, you understand the importance of data-driven decision-making. However, developing customer-facing analytics dashboards that empower your end users to make decisions requires expertise and can get complex.\n\n⏳ **Traditional dashboards go stale and are highly restrictive:** Customers need customized and dynamic analytics to fully understand their unique state of the world. Traditional dashboards quickly lose value and become outdated as customers seek analytics customization, leading to frequent ad-hoc data cuts and reporting requests, causing operational friction.\n\n⚙️ **Seeing analytics doesn’t mean better action:** Your customers are likely slammed with data from various products and services that they consume and, as a result experiencing decision paralysis due to information overload.\n\nBuilding effective analytics becomes a strain on your engineering resources, hindering user engagement, retention, and revenue growth.\n\n## **📈 The Solution**\n\n🛠️ **Build fast**\n\nUsing Upsolve AI, you can build customer-facing analytics dashboards simply by asking questions or via point-and-click, and theme them to your company’s design system.\n\n![uploaded image](/media/?type=post&id=78495&key=user_uploads/1148602/2f388753-7ee0-4153-a747-737274cc8f97)\n\n**🚀 Instantly deploy**\n\nOnce that is built, you can embed the dashboard natively in your product as a React or Vue component. “WYSIWYG”, the dashboard will look like it’s been built from scratch by your software engineers and will seamlessly fit into your existing design system.\n\n![uploaded image](/media/?type=post&id=78495&key=user_uploads/1148602/b2a830ed-644f-49cb-b817-25ad2eff3fc6)\n\n❤️ **Help your customers**\n\nYour customers can ask questions of the data and customize their own version of the dashboard based on their unique needs. Upsolve AI will also guide them with analytics insights and in-platform actions. Customers will appreciate what your product is doing well for them and will make the most of it, without your team lifting a finger.\n\n![uploaded image](/media/?type=post&id=78495&key=user_uploads/1148602/d27b8d34-7ccf-432b-bc33-c79de8ede425)\n\n🔐 **Enterprise security**\n\nComing from Palantir, we understand the importance of keeping your data secure. Upsolve secures your data in transit and at rest and supports multi-tenancy support that works natively with your existing auth system. Simply drop the Upsolve SDK into your auth flow and users will see the version of their dashboard that’s configured for them.\n\n![uploaded image](/media/?type=post&id=78495&key=user_uploads/1148602/f05fb5b8-2560-488f-ba63-7f72b25102b8)\n\n# 🙏 Ask\n\nWe are live with our customers now! If you are looking to build your customer-facing analytics in your product, email [kaling.wu@upsolve.ai](mailto:kaling.wu@upsolve.ai) to try [Upsolve AI](https://upsolve.ai/).\n\nIf you know any B2B business in your network that’s looking to unlock their customer-facing analytics and reporting capability, we would greatly appreciate any warm introductions using the above email as well!",
        "url": "https://www.ycombinator.com/launches/KQ3-upsolve-ai-the-new-way-to-build-and-offer-analytics-to-your-customers",
        "votes": 532,
        "created_at": "2024-02-17T09:57:38.096Z"
      }
    ]
  },
  {
    "id": 29186,
    "name": "Tesseral",
    "slug": "tesseral",
    "former_names": [
      "Codomain Data",
      "Okapi",
      "SSO Ready",
      "ssoReady",
      "SSOReady"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/85992f888276408373d1f33710dd92fd60ae187a.png",
    "website": "https://tesseral.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Tesseral is the open source platform for managing identity and access in business software. It provides enterprise-grade capabilities, including SAML single sign-on, SCIM provisioning, role-based access control, managed API keys, and audit logs, implemented in just a few lines of code. \r\n\r\nTesseral unifies access management for employees, customers, services, and AI agents, giving organizations the flexibility to adapt to any deployment model and the authority to enforce security policies with precision.\r\n\r\nYou can learn more by reading our docs at https://tesseral.com/docs or by checking out our GitHub at https://github.com/tesseral-labs/tesseral.",
    "one_liner": "The open source platform for managing identity in business software",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1708399745,
    "tags": [
      "Developer Tools",
      "SaaS",
      "Security",
      "Open Source",
      "API"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2024",
    "status": "Inactive",
    "industries": [
      "B2B"
    ],
    "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/tesseral",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/tesseral.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://linkedin.com/company/tesseral",
    "x_url": "https://x.com/tesseralhq",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/tesseral-labs",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/85992f888276408373d1f33710dd92fd60ae187a.png",
    "app_video_url": null,
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    "company_photos": [
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      "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/d4b0121f1fee45a4beb038578ef9331a9bc86340.png"
    ],
    "primary_partner": {
      "name": "David Lieb",
      "url": "https://www.ycombinator.com/people/david-lieb"
    },
    "founders": [
      {
        "user_id": 1519710,
        "full_name": "Ned O'Leary",
        "title": "Founder",
        "founder_bio": "Cofounder / CEO at Tesseral",
        "is_active": false,
        "linkedin_url": "https://linkedin.com/in/nedoleary",
        "x_url": "https://twitter.com/nedoleary",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/32798834b53872ec8c2fb1c744cbfa357d1b1e61.jpg"
      },
      {
        "user_id": 710191,
        "full_name": "Ulysse Carion",
        "title": "Founder",
        "founder_bio": "Cofounder/CTO at Tesseral.\n\nFormerly of Segment and Gem. I built Segment's permissions and identity resolution system. Editor of IETF RFC 8927. 🇫🇷🇺🇸",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/ucarion/",
        "x_url": "https://x.com/ucarion",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f9978e896bb1cbde625ea8af8a36535a813f8d28.jpg"
      }
    ],
    "jobs": [],
    "news": [
      {
        "title": "Tesseral launches with $3.3M to simplify B2B authentication for software developers - SiliconANGLE",
        "url": "https://siliconangle.com/2025/05/06/tesseral-launches-3-3m-simplify-b2b-authentication-software-developers/",
        "date": "May 06, 2025"
      }
    ],
    "launches": [
      {
        "id": 90141,
        "title": "Tesseral: the open source auth infrastructure for B2B SaaS",
        "tagline": "Everything you need to manage users in business software, from a login page to session management to SSO and RBAC!",
        "body": "Tesseral is open source auth infrastructure for business software. You can use it to authenticate your users, and manage their access to resources.\n\nIt’s similar to products like Auth0, but it’s open source and built specifically for B2B apps.\n\nIt comes with enterprise features like single sign-on, directory provisioning, user impersonation, and multi-factor authentication, as well as beautiful login pages and self-service settings for customers.\n\nYou can experiment with Tesseral using our hosted service for free at [console.tesseral.com](http://console.tesseral.com) or learn more by reading the docs at tesseral.com/docs!\n\nhttps://www.youtube.com/watch?v=hawD-4PWy4Y\n\n![uploaded image](/media/?type=post&id=90141&key=user_uploads/1519710/328d4d9e-4a18-4dbe-ae6e-231ae3002b1c)\n\n",
        "url": "https://www.ycombinator.com/launches/NRt-tesseral-the-open-source-auth-infrastructure-for-b2b-saas",
        "votes": 16,
        "created_at": "2025-05-06T17:28:04.050Z"
      },
      {
        "id": 84774,
        "title": "SSOReady: Open source developer tools for enterprise single sign-on",
        "tagline": "SSOReady makes it safe and easy for developers to offer SAML SSO and SCIM directory sync in their software.",
        "body": "**TLDR: set up SAML and SCIM in less than a day:** <https://www.youtube.com/watch?v=_HVtFkW8xCI>.\n\n# Context: customers want SAML\n\nThere are lots of different ways to authenticate (i.e. log in) users in software.\n\nCompanies often require their employees to use single sign-on (SSO) to access business software, both for convenience and security.\n\nFor the most part, especially in large companies, SSO relies on an old, complicated protocol called SAML. (If you’ve used a service like Okta before, you’ve likely used SAML without realizing it!)\n\nIf you make business software, you probably will need to support SAML at some point.\n\n# Problem: SAML is hard\n\nBut SAML is really hard, even for experienced developers. It just doesn’t work like most modern software, making implementations slow and risky. Companies as sophisticated as GitLab can make [very costly mistakes](https://ssoready.com/blog/engineering/ruby-saml-pwned-by-xml-signature-wrapping-attacks/).\n\n# What we do: we make SAML easy\n\nSSOReady makes SAML safe and easy enough that developers can often finish an implementation in [less than a day](https://blog.runreveal.com/we-shipped-sso-support-in-a-day-how/).\n\nSSOReady is an open-source (MIT) service that helps developers implement SAML single sign-on without ever touching SAML directly. Devs just need to implement two API endpoints: one to initiate SAML logins and another to receive incoming SAML messages. And then they’re pretty much done.\n\nSSOReady also offers a similar tool for SCIM, a protocol often used alongside SAML to provision and de-provision users. Developers can use SCIM to establish a live sync between their database of users and their customers’ central IT systems.\n\n# Get in touch\n\n* Our website: <https://ssoready.com>\n* Our github: <https://github.com/ssoready>\n\n![uploaded image](/media/?type=post&id=84774&key=user_uploads/89898/5ad4c15a-246b-4e47-86ba-96e87cabf198)\n\n",
        "url": "https://www.ycombinator.com/launches/M3K-ssoready-open-source-developer-tools-for-enterprise-single-sign-on",
        "votes": 14,
        "created_at": "2024-10-15T19:58:22.889Z"
      }
    ]
  },
  {
    "id": 29206,
    "name": "Stitch Technologies",
    "slug": "stitch-technologies",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/9a179ac34a5ab0366ecb80a5a4abbd3ccc101dbe.png",
    "website": "https://www.stitch.tech",
    "all_locations": "London, England, United Kingdom",
    "long_description": "",
    "one_liner": "-",
    "team_size": 0,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1701712974,
    "tags": [
      "Developer Tools",
      "SaaS"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2024",
    "status": "Inactive",
    "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": [
      {
        "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": "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."
      }
    ],
    "url": "https://www.ycombinator.com/companies/stitch-technologies",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/stitch-technologies.json",
    "year_founded": 2023,
    "city": "London",
    "country": "GB",
    "linkedin_url": "https://www.linkedin.com/company/stitch-tech",
    "x_url": "",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/9a179ac34a5ab0366ecb80a5a4abbd3ccc101dbe.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": 1550772,
        "full_name": "Till Kern",
        "title": "Founder",
        "founder_bio": "Builder, part-time ski instructor, Co-founder & CEO of Stitch",
        "is_active": false,
        "linkedin_url": "https://linkedin.com/in/tillkern",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/fc39a1de5dfd085090b52c89fd803fd3972d8e63.jpg"
      },
      {
        "user_id": 384778,
        "full_name": "Yuriy Oparenko",
        "title": "Founder",
        "founder_bio": "",
        "is_active": false,
        "linkedin_url": "https://uk.linkedin.com/in/oparenko",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a6a852bdfa700332c05cdd33e0576ff5bd6fe2dd.jpg"
      }
    ],
    "jobs": [],
    "news": [],
    "launches": []
  },
  {
    "id": 29226,
    "name": "Greptile",
    "slug": "greptile",
    "former_names": [
      "Onboard AI"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/16a991d8af835ae196b30e656796c7aa6805c9d1.png",
    "website": "https://www.greptile.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Greptile reviews pull requests with full context of the codebase. \r\n\r\nTop YC companies like PostHog, Raycast, Vouch, Podium, and YC's own internal software team use Greptile to review millions of changes every week. \r\n\r\nWhen companies start using Greptile, they catch more bugs and merge PRs 4x faster, on average\r\n\r\nGreptile can be used via the cloud, or be hosted 100% on your cloud in an air-gapped VPC.",
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        "founder_bio": "Founder @ Greptile. CS from Georgia Tech, minor in Linguistics.",
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        "title": "Series B and The War on Bugs",
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        "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"
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      {
        "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/",
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        "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",
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        "created_at": "2024-03-11T20:06:39.485Z"
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    "long_description": "Nuanced is a desktop app for building software. \r\n\r\nAgents help developers turn rough ideas into clear specs, then stay connected to the work as agents build.",
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        "full_name": "Ayman Nadeem",
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        "founder_bio": "Founder and CEO of Nuanced. Formerly at GitHub for 7+ years. \n\nMSc in CS from University of Oxford + engineering valedictorian from University of Waterloo. \n\nhttps://www.aymannadeem.com/about/",
        "is_active": true,
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      {
        "id": 78200,
        "title": "🚀 Nuanced — Detect AI-generated images",
        "tagline": "We help companies like dating apps, ad platforms, news sites, and marketplaces distinguish human-authored materials from AI-generated content. ",
        "body": "Hi, We’re [Ayman](https://linkedin.com/in/aymannadeem) and [Dylan](https://linkedin.com/in/dylan-drover), co-founders of [Nuanced](https://www.nuanced.dev/). \n\n**TL;DR:** Nuanced detects AI-generated images. We help companies like dating apps, ad platforms, news sites, and marketplaces distinguish human-authored materials from AI-generated content. \n\n![](https://lh7-us.googleusercontent.com/L399NC0PSyrui-w5rRnJiBPSd_V0eoiaQKJcDB291blx6uiGn9NdkJA8ByQGESJXSJNsMFmZ_AmRodnNG9sygxAP3dPKKCk7o7DKhkTpoVOeVj4SchRZixQPmXJw7pLX4C0sMTwpD-U-zHVPZ7GDmd8)\n\n# \n\n# **We’re solving the authenticity crisis**\n\nNo one wants to lose users because of fake AI content. Consumers lose trust in a platform flooded with AI-generated content, risking churn and reputational damage.\n\nAs AI-generated content surges, distinguishing it from human-made material becomes vital for trust and authenticity. Existing detection technologies fall short, resulting in a $78B annual deepfake expense, and amplify growing problems such as misinformation and identity verification. \n\nOur solution has three parts: \n\n1. Easy integration via our [API](https://nuanced.stoplight.io/docs/nuanced-api/4l8bca59wmrl5-nuanced-api). \n2. Privacy-first, [custom zero PII models](https://blog.nuanced.dev/blog/2024/01/07/the-glossily-rendered-elephant-in-the-room-or-why-we-are-building-our-own-models/). \n3. Staying ahead of [AI-generated threats](https://blog.nuanced.dev/blog/2023/11/05/how-generative-ai-has-transformed-the-online-spam-and-abuse-landscape/) with our dedicated research team.\n\nWith Nuanced, you’ll never have to compromise user privacy, build costly internal systems, or take on complex integrations.\n\n# **How it works**\n\nNuanced provides a service that identifies AI-generated image content. Our models are trained on a wide array of architectures, such as Dalle-3, Midjourney, and SDXL, with continuous integration of data from the latest AI image generators. As AI-generated images evolve, so do we.\n\n![](https://lh7-us.googleusercontent.com/uBHUedbK3fR5oYpkxcyfrG4DBjLVjYL0Jni83s8CbQK0G0y6vCJgt6ebZJGxUHHV6G8T5HjRWVh568IkHDNKkOI_0uphQitm6AOfet8zKv4hudJciLCYucpUiUSvoYe4OAC7KoBbgts-UJlQRlZJQmE)\n\n# **Our story**\n\nDylan and I met while studying engineering at the University of Waterloo. Each of us brings over a decade of tech industry experience. I was on GitHub's engineering team for over 7 years, addressing challenges like scaling abuse mitigation for 100+ million users. While at GitHub, I saw AI-driven threats evolve and evade traditional detection techniques, which led me to found Nuanced.\n\nDylan has a decade of machine learning experience spanning industry and academia, culminating in a 6-year tenure as an Applied AI Scientist at Amazon. \n\nWe both agreed that online content creation and consumption were rapidly changing, making it harder to discern reality from convincing hallucinations. \n\n![uploaded image](/media/?type=post&id=78200&key=user_uploads/1552616/4be4899f-ab76-47c2-a484-1aa39add3b41)\n\n# **Our asks**\n\n* **Give it a try:** use [this playground](http://13.59.173.43:7860/) to see Nuanced in action, and check out our [developer docs](https://nuanced.stoplight.io/docs/nuanced-api/zza4t0r053k8d-verify-image) to learn more. \n* **Flag incorrect results.** If we get something wrong [here](http://3.140.239.1:7860/), flag whether it was real or fake to help us improve our outcomes over time. We have provided a GIF below outlining how to flag incorrect results. \n* **Schedule a call:** to learn more, book a live 1:1 demo using [this link,](https://calendar.google.com/calendar/u/0/appointments/schedules/AcZssZ1oDN9pRF-xSoO2NiV-mUZP4lwg7RJI1fd-W6v1WyJX5rt_b9gJyBx5goNLX9xF4nuAILLBOzix) or by emailing us at [demo@nuanced.dev](mailto:demo@nuanced.dev).\n* **Customer intros:** we’d love intros to companies that have image verification needs, such as user-generated content platforms. Feel free to make intros directly to [ayman@nuanced.dev](mailto:ayman@nuanced.dev).\n\n \n\n![](https://lh7-us.googleusercontent.com/RobYeCSZ51B1S7hlokDlDtBRijqImf1AW53-CH5coPIOqKZXtkC1v7US15o03rvtPAf8oYFo6z1qnxA4W-tml1EgXE6KHjviB2eTOv9j3tG3ZWQBTtUV3zsWv8Q8ZPpJzuC3z1a7ojvdqPdp-dB5A74)\n\n",
        "url": "https://www.ycombinator.com/launches/KLI-nuanced-detect-ai-generated-images",
        "votes": 25,
        "created_at": "2024-02-06T16:44:25.814Z"
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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",
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    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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        "full_name": "Wei-Wei Wu",
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        "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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        "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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        "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"
      }
    ]
  },
  {
    "id": 29266,
    "name": "nCompass Technologies",
    "slug": "ncompass-technologies",
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    "website": "https://www.ncompass.tech",
    "all_locations": "New York City, NY, USA; Remote",
    "long_description": "Identifying performance bottlenecks and strategizing ways to solve them takes 4-8x longer than actually writing the code to fix them. We're building an agent that is an expert at analyzing the performance GPU systems like inference engines at all levels of the stack - from CPU-GPU interactions down to GPU kernels. \r\n\r\nPairing our agent with Cursor / Claude Code allows you to automate both the reasoning and code implementation steps of performance optimization. What used to take weeks can now be done in days. \r\n\r\nAlong with our AI agent, we have features such as running diffs on system traces as well as sharing and collaboration features that make our VSCode extension the most powerful way to work on performance optimization. ",
    "one_liner": "Optimize performance on GPUs - 10x faster",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1708296726,
    "tags": [
      "Developer Tools",
      "Hardware",
      "Open Source",
      "AI"
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/ncompass-technologies",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/ncompass-technologies.json",
    "year_founded": 2024,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://linkedin.com/company/ncompass-technologies",
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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",
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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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    "launches": [
      {
        "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"
      },
      {
        "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"
      }
    ]
  },
  {
    "id": 29270,
    "name": "Keystroke",
    "slug": "keystroke",
    "former_names": [
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    "website": "http://keystroke.ai",
    "all_locations": "Salt Lake City, UT, USA",
    "long_description": "Keystroke is an all-in-one platform for building internal agents and workflows. \r\n\r\nIt's built from the ground up with coding agents in mind. Build agents and workflows as TypeScript in your own repo, then deploy them to a web app where your whole team can use them.",
    "one_liner": "An all-in-one platform for building internal agents & workflows",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Analytics",
    "launched_at": 1698776495,
    "tags": [
      "Developer Tools",
      "Generative AI",
      "Workflow Automation",
      "Automation",
      "AI"
    ],
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    "top_company": false,
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    "nonprofit": false,
    "batch": "Winter 2024",
    "status": "Active",
    "industries": [
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      "Analytics"
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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/keystroke",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/keystroke.json",
    "year_founded": 2023,
    "city": "Salt Lake City",
    "country": "US",
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    "primary_partner": {
      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
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    "founders": [
      {
        "user_id": 699099,
        "full_name": "Blake Rouse",
        "title": "Founder/CEO",
        "founder_bio": "Blake Rouse is the co-founder and CEO of Keystroke. Previously, he led product development at a bootstrapped analytics startup (DataSpark, acqd by Threecolts). Blake is originally from South Carolina. He studied Product Management and Computer Science at BYU for three years before dropping out to start Keystroke.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/cblakerouse",
        "x_url": "https://twitter.com/cblakerouse",
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      },
      {
        "user_id": 830598,
        "full_name": "Dallin Bentley",
        "title": "Founder",
        "founder_bio": "All things AI",
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        "id": 105225,
        "title": "Keystroke - open sourcing our internal agents & automations platform",
        "tagline": "An all-in-one platform for building internal agents & workflows.",
        "body": "**_tl;dr:_** Keystroke is an all-in-one platform for building internal agents and workflows. It's built from the ground up with coding agents in mind. Build agents and workflows as TypeScript in your own repo, then deploy them to a web app where your whole team can use them.\n\nTry it free: <https://keystroke.ai/> \\\nGitHub: <https://github.com/keystrokehq/keystroke>\n\n### why we built keystroke (our pivot story)\n\nHey everyone, we’re [Blake](https://x.com/cblakerouse) and [Dallin](https://x.com/dalbentley) from [Keystroke](https://keystroke.ai/home). Keystroke is a recent pivot from Buster, our original YC W24 idea.\n\n![uploaded image](/media/?type=post&id=105225&key=user_uploads/699099/e5ee8874-7b36-45d5-b9cd-f0f96cd14846)\n\nAt Buster, we spent a lot of time building internal agents and automations. We used visual platforms like n8n and Gumloop, as well as code-first tools like Trigger.dev, Mastra, and several of Vercel’s open frameworks. We genuinely liked many of them, but kept encountering two different problems:\n\n1. Visual tools gave us integrations, credentials, hosting, and an application the rest of the team could use. They were fast initially, but became difficult to maintain as the systems grew. Tests and typechecks were limited, JSON blobs were hard to review, and debugging failures was painful.\n2. Code-first tools gave us ordinary TypeScript, tests, npm packages, and a codebase that coding agents could work with directly. But after building something, we were deploying it to infrastructure rather than an application people could use. We still needed to configure the chat UI, streaming, credentials, integrations, run history, permissions, and sharing ourselves.\n\nSo, we started building the thing we wish existed: a code-first framework that made it stupid easy to build complex agents and AI systems, with a web app for teams to collaborate on top.\n\nWe liked it so much that we decided to pivot away from Buster and focus on building Keystroke full time.\n\n## keystroke rebuilt our W24 idea in 5 minutes\n\nWith Keystroke, I was able to rebuild our original startup’s product (an AI data analyst) in \\~5 minutes.\n\nI pointed Cursor at our old Buster repo and it was able to:\n\n* spin up a local Keystroke project\n* rebuild the OG Buster agent w/ memory, its own file system, etc\n* connect our Postgres DB, PostHog, Metabase, and Slack\n* build skills for using each of the data sources\n* explore our DB and add schema docs to the file system\n* build a workflow to keep schema docs synced\n* name the agent \"Delbert\"\n* then pushed him up to the Keystroke app\n\nSince then, Delbert has been answering ad-hoc questions for me in Slack on a regular bases. He builds me metabase dashboards when I need them. He sets his own triggers, reviews key metrics periodically, and pings me in Slack if anything looks off.\n\n## how keystroke works\n\nIn Keystroke, workflows are ordinary async TypeScript: a ‘for’ loop is an actual ‘for’ loop, inputs use Zod schemas, and everything you build can be tested with Vitest. Our managed runtime makes workflows durable across errors, sleeps, approval steps, and process restarts.\n\nAgents wrap Vercel’s AI SDK and can use workflows, actions, other agents, MCP servers, and integrations as tools. They also include memory, a persistent filesystem, web search, triggers, and optional VM sandboxes.\n\nDeployed agents and workflows instantly appear in the web app with a chat UI, workflow visualizations, input forms, sharing, credential management, integrations, and logs.\n\n**The entire platform was built from the ground of with coding agents in mind**. Your coding agent can use the CLI to scaffold a local directory with a Keystroke project and an [AGENTS.md](http://AGENTS.md). Then, it can build whatever agent or AI system you want, search our docs, run tests, and push what you build up to the Keystroke platform.\n\n## \n\n![uploaded image](/media/?type=post&id=105225&key=user_uploads/699099/d6f73f5f-ba9d-43e4-8c8e-167b770bbe65)\n\n## **our asks**\n\n**Try it:** get started at [keystroke.ai](http://keystroke.ai) with $20 in free credits\n\n**Share feedback:** we’re in open alpha, please tell us what breaks\n\n**Star us on Github:** we’re open source, check out the code on [GitHub](https://github.com/keystrokehq/keystroke)\n\n**Reach out:** want to chat? email us at [team@keystroke.ai](mailto:team@keystroke.ai)",
        "url": "https://www.ycombinator.com/launches/RNB-keystroke-open-sourcing-our-internal-agents-automations-platform",
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        "created_at": "2026-07-10T19:26:21.580Z"
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    "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,
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        "full_name": "Maksim Ivanov",
        "title": "Founder/CEO",
        "founder_bio": "Building self-assembling software. Previously at hedge funds and doing ML research",
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        "linkedin_url": "https://linkedin.com/in/maksivanov",
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        "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)",
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        "created_at": "2024-02-22T16:11:40.986Z"
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    "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",
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    "year_founded": 2024,
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    "linkedin_url": "https://www.linkedin.com/company/leapinglabs",
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        "full_name": "Adrien Philardeau",
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    "name": "Tusk",
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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,
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        "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.",
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        "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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    "long_description": "Celest is a backend-as-a-service for Flutter and Dart developers. It empowers Flutter developers with the tools and capabilities they need to become full-stack developers. We are introducing \"Cloud Widgets\", a set of primitives which enable you to declaratively define every piece of your backend and infrastructure in Dart.\r\n\r\nAs the role of the front-end developer evolves towards full-stack proficiency, we recognize that existing tools have fallen short for those specializing in Flutter. Using the programming language and patterns Flutter developers already know from building their frontend, Celest enables developers to build and connect their apps to their backend with no additional tooling.\r\n\r\nWe enable Flutter developers to concentrate on building features and delivering value to their customers rather than learning additional domains and fragmenting themselves across disparate toolchains.",
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        "answer": "Dillon has been a member of the Flutter community since 2018 and worked at AWS on the Amplify Flutter product for two and a half years. At AWS, he created the first comprehensive Dart SDK, aimed at helping Flutter developers connect their apps to AWS. This SDK received positive reception within the Flutter community. However, he identified a persistent challenge: Flutter developers were still facing difficulties in crafting their backends, since it required them to spread themselves across different toolchains and programming languages. Recognizing this gap, Dillon left AWS with the idea of creating a dedicated platform for Flutter developers to unlock their ability to build every part of their apps in Dart. He submitted an application to Y Combinator only an hour before the deadline and was accepted into the Winter 2024 batch. Now, he’s able to realize the vision started at AWS: significantly improving the Flutter development landscape."
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        "question": "What is your long-term vision? If you truly succeed, what will be different about the world?",
        "answer": "Our vision is centered on expanding the capabilities and reach of Flutter and Dart developers. By providing a solution that facilitates backend development in Dart, we are enhancing and completing the story for the Flutter and Dart ecosystem by making Dart a comprehensive language for building full-stack applications. Dart's strong typing and sound design patterns make it an attractive alternative for those currently using JavaScript/TypeScript for web development. Ultimately, we aspire to make Flutter and Celest synonymous with app development in general, revolutionizing the way apps are built regardless of the platform or device types being targeted."
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        "full_name": "Dillon Nys",
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        "founder_bio": "Founder & CEO at Celest. Previously, I wrote the Amplify Flutter framework at AWS.",
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      {
        "id": 79354,
        "title": "Celest 💙 turning every Flutter developer into a full-stack developer",
        "tagline": "Write once, deploy literally anywhere",
        "body": "When I was at AWS building Amplify Flutter, I found myself wanting to write more and more of my code in Dart. I loved being able to maintain my flow state and use a single programming language—one I’d grown quite fond of—for everything. CLIs, tooling scripts, HTTP servers… if I needed a piece of code, I would find a way to write it in Dart.\n\nThe ecosystem for these use cases was immature but that just made it a challenge, which I loved. _Use the right tool for the job_, you may say. Nah… I want to use Dart. I thought I was alone in this quest but, I was okay being the crazy one.\n\nAnd then, to my surprise, our customers began asking\n\n“When can I write my Lambdas in Dart?”\n\n“When is AWS going to release an SDK for Dart so I can use it in my backends?”\n\nIt dawned on me that there was perhaps something deeper we were all experiencing, something more fundamental about coding being expressed.\n\nJavaScript is one of the most popular server-side languages in use today. A reasonable person with no knowledge of JavaScript may conclude from this that it’s because JavaScript is performant, efficient, or otherwise designed for the server.\n\nThe reality, though, is that developers will often seek the path of least resistance in an environment replete with friction. It’s easy to deride a choice in language, but it’s hard to downplay the numbers. Software engineers are human, after all—and humans are constantly optimizing their flows.\n\nFlutter was born from a desire to solve this age-old quest of optimization—first, as a way to build iOS and Android apps from the same codebase, saving teams the burden of managing two separate products. Then, to desktop and web applications, dramatically reducing the barrier to entry for these platforms too. The vision is largely realized. And, thanks to Dart, it’s been done without sacrificing performance.\n\n![uploaded image](/media/?type=post&id=79354&key=user_uploads/251048/d2f6624a-21cf-4080-93ba-a61020b1070b)\n\nOur mission with [Celest](https://celest.dev/) is to fill in the last piece of this puzzle—the cloud. We do that, simply, by starting and ending with Dart.\n\nHere’s how you define a cloud function with Celest.\n\n![uploaded image](/media/?type=post&id=79354&key=user_uploads/251048/78043071-9e1e-4349-907e-ffc1c1f08c3e)\n\nAnd here’s how you add authentication.\n\n![uploaded image](/media/?type=post&id=79354&key=user_uploads/251048/8ca2deb1-8964-4b0b-b08b-734e58a02c6b)\n\nTo test it out, you run `celest start` and iterate on your backend locally as you build your Flutter app. Your functions hot reload as you save your changes, and integration comes free with an auto-generated client library.\n\n![uploaded image](/media/?type=post&id=79354&key=user_uploads/251048/6222b983-d692-43f1-8f83-58c42a131053)\n\nAnd when you’re ready to turn this into a fully managed and auto-scaled backend, you run `celest deploy`. That’s it.\n\n![uploaded image](/media/?type=post&id=79354&key=user_uploads/251048/ad25a06e-a7c8-4fb9-b6d9-b591519c8b98)\n\nAs a Flutter developer, I’ve never left the Dart programming language, never thought about the many layers of abstraction beneath, and didn’t even need to leave my IDE to solve an otherwise laborious and flow-breaking task. I’m back to writing my app in less than 5 minutes. It feels like I’d never left.\n\n---\n\nCelest is the product I always wanted as a Flutter developer, the tool I had felt crazy for wanting at one point. It feels a little less crazy now, but only time will tell :-)\n\nYou can try and play with Celest for free today. Our cloud offering has started rolling out to the waitlist and will be publicly available in the coming weeks. For this and all the other goods in store, check us out @ [celest.dev](https://celest.dev?utm_source=ycombinator&utm_medium=blog&utm_campaign=launch_yc)\n\nAnd if this story rings true for you (or not), I’d love to hear your thoughts\n\n[dillon@celest.dev](mailto:dillon@celest.dev)\n\nTo the crazy ones 😎 🎯\n\nDillon, Chief Celestial",
        "url": "https://www.ycombinator.com/launches/Kdu-celest-turning-every-flutter-developer-into-a-full-stack-developer",
        "votes": 45,
        "created_at": "2024-03-13T14:29:37.676Z"
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    "team_size": 23,
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        "user_id": 927016,
        "full_name": "Andy Li",
        "title": "Founder/CEO",
        "founder_bio": "Founder @ Respan - AI gateway with built-in observability & automated evals.\n\nPreviously @ UIUC (dropped out) and Apple Product Design.",
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        "url": "https://www.ycombinator.com/companies/respan/jobs/ABWSs0E-senior-software-engineer-frontend",
        "location": "Alameda, CA, US / Remote (IN)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Frontend",
        "salary_range": "$1 - $200K",
        "equity_range": "",
        "experience": "6+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 95524,
        "title": "Software Engineer, AI",
        "url": "https://www.ycombinator.com/companies/respan/jobs/9L4xvXt-software-engineer-ai",
        "location": "Alameda, CA, US / Remote (IN)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$1 - $200K",
        "equity_range": "",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 95525,
        "title": "Software Engineer, Full-Stack",
        "url": "https://www.ycombinator.com/companies/respan/jobs/8s4G7k6-software-engineer-full-stack",
        "location": "Alameda, CA, US / Remote (IN)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$1 - $200K",
        "equity_range": "",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 95526,
        "title": "Software Engineering Intern, Frontend (fall co-op)",
        "url": "https://www.ycombinator.com/companies/respan/jobs/apjciy1-software-engineering-intern-frontend-fall-co-op",
        "location": "Alameda, CA, US",
        "type": "Internship",
        "role": "Engineering",
        "role_type": "Frontend",
        "salary_range": "$3K - $6K / monthly",
        "equity_range": "",
        "experience": null,
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 95570,
        "title": "Chief of Staff",
        "url": "https://www.ycombinator.com/companies/respan/jobs/KaaccJS-chief-of-staff",
        "location": "Alameda, CA, US",
        "type": "Full-time",
        "role": "Operations",
        "role_type": null,
        "salary_range": "$1 - $250K",
        "equity_range": "",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
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    ],
    "news": [
      {
        "title": "Respan raises $5M to bring proactive observability to AI agents - SiliconANGLE",
        "url": "https://siliconangle.com/2026/03/18/respan-raises-5m-bring-proactive-observability-ai-agents/",
        "date": "Mar 18, 2026"
      }
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    "launches": [
      {
        "id": 79874,
        "title": "Keywords AI - Unified DevOps platform to build AI applications",
        "tagline": "Dead simple way to deploy & monitor AI apps with 2 lines of code.",
        "body": "### **‼️ The Problem**\n\nLLM developers face many challenges that hinder the ability to quickly build and scale high-quality products that people love:\n\n* Time-consuming infrastructure setup and maintenance for deploying and scaling LLM applications\n* Difficulty collaborating on prompt engineering and evaluating models for specific use cases\n* Challenges monitoring and ensuring consistent performance in production for optimal user experience\n* Tedious process of creating datasets for fine-tuning and iteratively improving output quality\n\n  ![uploaded image](/media/?type=post&id=79874&key=user_uploads/927016/d44261ea-e426-4e84-9f5f-5e5c9e217417)\n\n\n### **🌟 Our Solution**\n\nKeywords AI is built for developers. It has every feature needed to build, deploy, and scale LLM applications:\n\n**Infrastructure and Deployment**\n\n* OpenAI-compatible integration with 2 lines of code\n* Supports 100+ LLMs with built-in load balancing, error handling, and dynamic routing\n\n  ![uploaded image](/media/?type=post&id=79874&key=user_uploads/927016/60b64a75-0987-4bbb-93e2-f946760abbee)\n\n\n**Model Playground**\n\n* Interactive playground for comparing prompts and A/B testing different models\n* Find the best LLM for your use case through experimentation and evaluation\n\n  ![uploaded image](/media/?type=post&id=79874&key=user_uploads/927016/bc21dd8f-740b-4600-8930-f887a86c81fa)\n\n\n**Prompt Management**\n\n* Intuitive prompt management system for versioning and deploying prompts\n* Collaborative workspace for teams to share and iterate on prompts\n\n  ![uploaded image](/media/?type=post&id=79874&key=user_uploads/927016/d943ff84-f908-4744-80b9-4b5dcafc4ac7)\n\n\n**Request Logging**\n\n* Request logs for tracing and debugging user-model interactions\n* Automated output evaluation for detecting hallucination and other quality issues\n\n  ![uploaded image](/media/?type=post&id=79874&key=user_uploads/927016/9761abd2-48c2-4dfd-92df-5f6b054f02ec)\n\n\n**Performance Evaluations**\n\n* Comprehensive evaluations to compare model performance with customized metrics\n* Monitor response quality over time to build product confidence\n\n  ![uploaded image](/media/?type=post&id=79874&key=user_uploads/927016/59f074ba-0d90-4eae-93f8-3fa2328d5750)\n\n\n**Usage Dashboard**\n\n* Real-time monitoring of model performance and user analytics\n* Comprehensive overview of product usage trends and user behavior\n\n  ![uploaded image](/media/?type=post&id=79874&key=user_uploads/927016/cc4903db-9d46-4c98-a44a-babe133fc848)\n\n\n**User Analytics**\n\n* Track growth, retention, and unit economics with detailed usage analytics\n* Sentiment analysis and topic/intent classification for user insights\n\n  ![uploaded image](/media/?type=post&id=79874&key=user_uploads/927016/eec04dbb-d665-4bee-8333-285de818a6bc)\n\n\n**Data Curation and Fine-Tuning**\n\n* ​Easily collect and curate production golden dataset for model optimization\n* One-click model fine-tuning for improved performance and cost savings​\n\n  ![uploaded image](/media/?type=post&id=79874&key=user_uploads/927016/d44261ea-e426-4e84-9f5f-5e5c9e217417)\n\n\n### **🤠 The Team**\n\n[Andy](https://linkedin.com/in/hanheli) and [Raymond](https://www.ycombinator.com/companies/www.pareon.com) both studied mechanical engineering at UIUC and have been best friends since college. \n\nAndy took a gap year to work as a product design engineer at Apple after freshman year, where he designed parts for the next-gen & next-next-next-gen AirPods. He dropped out after realizing his dream job wasn’t that fun.\n\nRaymond is so good at learning things. He graduated with the highest honor in just three years and self-mastered software engineering within a year. He dropped his robotics PhD offers from top schools.\n\nWe’ve worked on a bunch of very bad ideas together in the past year. Now we think we've stumbled upon a good one :)\n\n![uploaded image](/media/?type=post&id=79874&key=user_uploads/927016/b3ead780-3541-4b92-9e26-df04c3e891cc)\n\n![uploaded image](/media/?type=post&id=79874&key=user_uploads/927016/d44261ea-e426-4e84-9f5f-5e5c9e217417)\n\n### **🔥 Keywords AI is available today!**\n\n* [Get started free](https://keywordsai.co) with $15 in credits\n* [Chat with us](https://cal.com/keywordsai/demo) if you’re building with LLMs - we’d love to be helpful\n* Join our [Discord community](https://discord.com/invite/KEanfAafQQ) of AI builders\n* Follow us on [LinkedIn](https://www.linkedin.com/company/keywordsai/) and [X](https://twitter.com/keywordsai)\n\n  ![uploaded image](/media/?type=post&id=79874&key=user_uploads/927016/d44261ea-e426-4e84-9f5f-5e5c9e217417)\n\n\n[team@keywordsai.co](mailto:team@keywordsai.co)",
        "url": "https://www.ycombinator.com/launches/KmI-keywords-ai-unified-devops-platform-to-build-ai-applications",
        "votes": 20,
        "created_at": "2024-04-02T14:24:37.708Z"
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    "id": 29332,
    "name": "Polished",
    "slug": "polished",
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      "Pillar"
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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.",
    "team_size": null,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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    "batch": "Winter 2024",
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      "name": "Garry Tan",
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        "user_id": 1289064,
        "full_name": "JJ Maxwell",
        "title": "Founder",
        "founder_bio": "Building Polished. \n\nFormer CEO @ Double Finance, CTO of Liftoff Influence, co-founder of Jetfuel (acquired by Liftoff 2021), Facebook Messenger",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/jj-maxwell-753b5026",
        "x_url": "https://x.com/jjmaxwell4",
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        "user_id": 376672,
        "full_name": "Mark Wai",
        "title": "Founder",
        "founder_bio": "Building Polished\n\nPreviously Growth @ Tesla, Facebook",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/markwai",
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    "news": [
      {
        "title": "Direct indexing platform Double Finance raises $3.9M seed",
        "url": "https://www.axios.com/pro/fintech-deals/2024/12/10/direct-indexing-platform-double-finance-raises-seed",
        "date": "Dec 10, 2024"
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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"
      },
      {
        "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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    "id": 29334,
    "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",
    "launched_at": 1708738486,
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    "batch": "Winter 2024",
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    "regions": [
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    "url": "https://www.ycombinator.com/companies/decipher-ai",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/decipher-ai.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/decipher-ai/",
    "x_url": "https://twitter.com/decipher_ai",
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        "user_id": 1073351,
        "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",
        "x_url": "https://twitter.com/_mrosenfield",
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        "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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    "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,
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    "nonprofit": false,
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    "regions": [
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      "South Asia"
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    "url": "https://www.ycombinator.com/companies/toolify",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/toolify.json",
    "year_founded": 2023,
    "city": "Bengaluru",
    "country": "IN",
    "linkedin_url": "https://www.linkedin.com/company/trytoolify",
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    "primary_partner": {
      "name": "Harj Taggar",
      "url": "https://www.ycombinator.com/people/harj-taggar"
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    "founders": [
      {
        "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": 29347,
    "name": "Vibrant Labs",
    "slug": "vibrant-labs",
    "former_names": [
      "Exploding Gradients",
      "Ragas"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b03fadf62fa443c473d34c31148c9785ea34dceb.png",
    "website": "https://vibrantlabs.com/",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "We work on methods to autonomously scaling evals/environments for post-training agents. ",
    "one_liner": "Autonomously scaling environments",
    "team_size": 6,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1709606147,
    "tags": [
      "Developer Tools",
      "Generative AI",
      "Reinforcement Learning",
      "Open Source",
      "AI"
    ],
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2024",
    "status": "Active",
    "industries": [
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      "Infrastructure"
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    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Fully Remote"
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    "stage": "Early",
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/vibrant-labs",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/vibrant-labs.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/vibrant-labs-ai",
    "x_url": "https://x.com/vibrantlabsai",
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    "github_url": "https://github.com/vibrantlabsai",
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    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
    },
    "founders": [
      {
        "user_id": 387451,
        "full_name": "Jithin James",
        "title": "Founder/CEO",
        "founder_bio": "Jithin James (jjmachan), believes that life's purpose is found in the toil in mastering a craft and the fulfilment one gets from using it for the greater good. For him, this means excelling in software development, particularly in open-source and AI tooling, to empower fellow developers and help materialize their ambitious visions into reality. His journey is a testament to skill, dedication, and a commitment to community enrichment.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/jjmachan",
        "x_url": "https://twitter.com/jjmachan",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/bcdfd4732c2b0bbf0b007a1d8cae49d902d64f71.jpg"
      },
      {
        "user_id": 889503,
        "full_name": "Shahul ES",
        "title": "Founder/CTO",
        "founder_bio": "Shahul (aka ikka) discovered his fascination for AI in his sophomore year while pursuing his computer science degree. This early interest laid the foundation for his journey to becoming a Kaggle GrandMaster and led to his significant contributions to open-source AI, particularly in initiatives like OpenAssistant AI.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/shahules",
        "x_url": "https://twitter.com/Shahules786",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5bdaa55aa2f773d9e6e61c8bbd6944d8661b5a80.jpg"
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    "launches": [
      {
        "id": 79074,
        "title": "Ragas: Open-source evaluation and testing Infrastructure for LLM applications",
        "tagline": "Deploy your LLM application with confidence. ",
        "body": "### **TL;DR**\n\nWe are building [Ragas](https://www.ragas.io/) — an open-source evaluation and testing infrastructure for LLM application developers to deploy their applications in production with confidence.\n\n### About us\n\n![uploaded image](/media/?type=post&id=79074&key=user_uploads/889503/21a941e3-4798-4628-95cc-15332facb47e)\n\nWe’re [Jithin](https://linkedin.com/in/jjmachan) and [Shahul](https://linkedin.com/in/shahules)! Having met in college, we’ve collaborated on various projects for almost a decade now.\n\nJithin takes care of building the software and infrastructure. He was an early employee at Bento ML, where he built and maintained tools like [Bentoctl](https://github.com/bentoml/bentoctl), [Bentoml](https://github.com/bentoml/BentoML), and [Yatai](https://github.com/bentoml/Yatai). Shahul is responsible for AI research and engineering. He is a [Kaggle Grandmaster](https://www.kaggle.com/shahules) and a lead contributor to different open-source AI projects, including [Open-Assistant AI.](https://github.com/laion-ai/open-assistant)\n\n### Problem\n\nBefore 2023 software used to be written in code but with the emergence of foundational models software and applications are going to be compound systems containing code, prompts, and other components. This introduces several new problems\n\n* How do you select the best model or component suitable for your application from the abundance of available resources?\n* How do you test these systems and ensure continuous quality?\n* How do you derive insights from production to measure and improve your system?\n\nAs early adopters of this technology to build applications, we faced this problem while we were building RAG systems early last year.\n\n### Solution\n\nWe at [Ragas](https://docs.ragas.io/) make use of model-graded evaluations and testing techniques to ensure quality. This includes automated synthesis of test data points, explainable metrics, and adversarial testing.\n\nWe started by building this for RAGs, which is the most popular application of LLM as of today. Ragas is now the default open-source standard for evaluating RAG applications, processing over 4.7 million responses last month and used by engineers from enterprises like AWS, Microsoft, Databricks, Moody’s, UHG, and Tencent.\n\n![uploaded image](/media/?type=post&id=79074&key=user_uploads/889503/4da2d427-8bfe-4e4b-a76e-01c7a28ce747)\n\n### Our Ask\n\n* Checkout ragas on [GitHub](https://github.com/explodinggradients/ragas)\n* If you’re building RAG applications, consider [applying](https://forms.gle/TnqUHuY176m2juqL9) for the Ragas office hours program",
        "url": "https://www.ycombinator.com/launches/KZO-ragas-open-source-evaluation-and-testing-infrastructure-for-llm-applications",
        "votes": 94,
        "created_at": "2024-03-05T18:38:36.494Z"
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    "id": 29362,
    "name": "Pazi",
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    "one_liner": "Platform where autonomous companies are built",
    "team_size": 7,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1709274350,
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      "Security",
      "Web Development",
      "AI"
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2024",
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    "industries": [
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      "Engineering, Product and Design"
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    "regions": [
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      "Partly Remote"
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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": "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",
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      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
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    "founders": [
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        "user_id": 170713,
        "full_name": "Zvonimir Sabljić",
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      {
        "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.",
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    "news": [
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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"
      }
    ],
    "launches": [
      {
        "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"
      },
      {
        "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)!",
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        "votes": 36,
        "created_at": "2024-03-05T15:19:41.894Z"
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    "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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    "stage": "Early",
    "app_video_public": false,
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    "url": "https://www.ycombinator.com/companies/ellipsis",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/ellipsis.json",
    "year_founded": 2023,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/ellipsis-dev/",
    "x_url": "https://twitter.com/ellipsis_dev",
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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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        "id": 73519,
        "title": "Founding AI Engineer",
        "url": "https://www.ycombinator.com/companies/ellipsis/jobs/hOLJHSp-founding-ai-engineer",
        "location": "New York, NY, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Backend",
        "salary_range": "$100K - $200K",
        "equity_range": "0.50% - 5.00%",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
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    "news": [
      {
        "title": "AI Coding Startups That Have Raised the Most From VCs Like A16z - Business Insider",
        "url": "https://www.businessinsider.com/ai-code-startups-that-have-raised-the-most-vcs-a16z-2024-10#ellipsis-raised-a-2-million-seed-round-in-april-2024-as-part-of-y-combinators-w24-batch-12",
        "date": "Oct 13, 2024"
      },
      {
        "title": "Ellipsis raises a $2M Seed Round - Ellipsis.dev | Automated code reviews",
        "url": "https://www.ellipsis.dev/blog/ellipsis-raises-a-2m-seed-round?utm_source=ycseedround",
        "date": "Jun 19, 2024"
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    "launches": [
      {
        "id": 78871,
        "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.",
        "url": "https://www.ycombinator.com/launches/KW7-ellipsis-automated-code-reviews-bug-fixes",
        "votes": 81,
        "created_at": "2024-02-28T22:06:45.566Z"
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    "id": 29375,
    "name": "Preloop",
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    "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",
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      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
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        "full_name": "Tejas Hosangadi",
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        "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.",
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        "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.",
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        "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"
      }
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    "id": 29379,
    "name": "Trieve",
    "slug": "trieve",
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    "website": "https://trieve.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Infrastructure for search teams building retrieval and RAG. Trieve combines search language models with tools for tuning ranking and relevance.\r\n\r\nBuilding excellent search is difficult and can take months to implement then even more time to maintain. Trieve offers production-ready infrastructure that works out of the box to help search teams build adjustable AI search and RAG into their products. With tools for custom models, relevancy weighting, date-recency biasing, semantic full-text hybrid search, recommendations, and more Trieve covers the full spectrum of what a team wants from their discovery infrastructure. ",
    "one_liner": "All-in-one API for search, RAG, & recommendations",
    "team_size": 7,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1709233497,
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    "batch": "Winter 2024",
    "status": "Acquired",
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    "regions": [
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      "America / Canada"
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    "stage": "Early",
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    "app_answers": null,
    "question_answers": [
      {
        "question": "What is your long-term vision? If you truly succeed, what will be different about the world?",
        "answer": "Power every retrieval experience on the internet"
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    "url": "https://www.ycombinator.com/companies/trieve",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/trieve.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/trieveai/",
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    "cb_url": null,
    "github_url": "https://github.com/devflowinc/trieve",
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    "primary_partner": {
      "name": "Pete Koomen",
      "url": "https://www.ycombinator.com/people/pete-koomen"
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    "founders": [
      {
        "user_id": 1655076,
        "full_name": "Nick Khami",
        "title": "Founder/CEO",
        "founder_bio": "Find me at https://github.com/skeptrunedev . My primary hobbies are reading progression fantasy, riding motorcycles, and running. ",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/nicholas-khami-5a0a7a135",
        "x_url": "https://twitter.com/skeptrune",
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      {
        "user_id": 1655175,
        "full_name": "Denzell Ford",
        "title": "Founder/CTO",
        "founder_bio": "Find me at https://github.com/cdxker. I'm mostly active on x",
        "is_active": true,
        "linkedin_url": "https://linkdin.com/in/denzell-ford",
        "x_url": "https://twitter.com/cdxker",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/cd5cbf22ed11a4cfd6f8c6a76af57272a04a0299.jpg"
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    "news": [
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        "title": "Trieve Secures $3.5M to Power AI Search and RAG — Trieve",
        "url": "https://trieve.ai/trieve-fundraise-announcement/",
        "date": "Sep 11, 2024"
      }
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    "launches": [
      {
        "id": 78949,
        "title": "Trieve 🔎 Infrastructure for search teams",
        "tagline": "We want to power every search bar on the internet.",
        "body": "Howdy, y’all!\n\nWe’re [Denzell](https://linkedin.com/in/denzell-ford) and [Nick](https://github.com/skeptrunedev), founder engineers of [Trieve](https://trieve.ai/).\n\n![uploaded image](/media/?type=post&id=78949&key=user_uploads/1655175/c03dd5a8-16e9-4d39-8885-fdbb3d7e0626)\n\n**Trieve offers source-available all-in-one infrastructure for entire search teams. Engineers implement a pipeline that connects their data source to our backend then non-technical staff can fine-tune relevance using included frontends.**\n\nCustomers have the option to either **(1)** use the managed cloud version of the software suite or **(2)** buy a license to host it themselves in their own cloud or on-premise.\n\nWe want to power every search bar on the internet.\n\n### Problem - Poor search quality, lack of modularity, inaccessibility\n\n1. Engineers first have to build APIs on top of DBs and AI models which then need to be maintained, scaled, and improved.\n2. Engineers then need to build UI's for tuning which then need to be maintained, scaled, and improved.\n3. Improving retrieval quality requires hiring more engineers such that you have enough bandwidth to both maintain and improve your custom and complex infrastructure.\n4. Ineffective spend of your search budget as you have to hire engineers to build and maintain things before you can even start adjusting retrieval quality.\n\n### Solution - Quality retrieval & source-available license\n\nTrieve provides a complete infrastructure suite that is both easy for a single engineer to integrate and allows businesses to hire more non-technical staff who can use the included front-end tools for fine-tuning relevance.\n\nWith Trieve's solution, businesses can get more value out of their search budget whether it's $10k or $10M.\n\n### WE have two asks!\n\n1. Could you introduce us to developers and teams building search and relevancy into their products?\n2. [Can you star our GitHub](https://github.com/devflowinc/trieve)?\n\n![uploaded image](/media/?type=post&id=78949&key=user_uploads/1655175/b72dc26d-867b-4637-8df5-111b2f869fa0)\n\n### About us\n\nDenzell and I are software engineers who walked into this problem trying to build semantic search for a knowledge management system that helped business teams argue better.\n\nWhen we went to go sell the arguing app we found out that the underlying search infrastructure was what people really wanted to buy.\\\n\\\n[founders@trieve.ai](https://mailto:founders@trieve.ai)",
        "url": "https://www.ycombinator.com/launches/KXN-trieve-infrastructure-for-search-teams",
        "votes": 137,
        "created_at": "2024-03-01T18:52:01.827Z"
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    "id": 29399,
    "name": "Centauri AI",
    "slug": "centauri-ai",
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2909e97f1b5b60712aa5c9853c288e7c547ac289.png",
    "website": "https://centauri-ai.tech",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "We build coSlash, a management layer for AI coding agents. Our platform enables teams to orchestrate parallel Claude Code and Codex sessions, track project progress, team knowledge, and seamlessly transfer context between developers.\r\n\r\nhttps://coslash.io/\r\n",
    "one_liner": "Helps teams work effectively with AI coding agents.",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1711328630,
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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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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/centauri-ai",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/centauri-ai.json",
    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/101369147/",
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    "github_url": "https://github.com/centauri-ai",
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    "primary_partner": {
      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
    },
    "founders": [
      {
        "user_id": 415692,
        "full_name": "He Lu",
        "title": "Founder",
        "founder_bio": "co-founder and CEO of Centauri AI\nco-founder and CTO of Blue Water Fintech(acquired)\n",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/he-lu-63666852",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b2bc7c59ce0aed345cef18bcdf1264febbfe271c.jpg"
      },
      {
        "user_id": 1522478,
        "full_name": "Milan Shen",
        "title": "Founder/CPO",
        "founder_bio": "Milan is co-founder and Chief Product Officer at Centauri AI. Milan has expertise in Data and AI over 10 years with both research and product development. After obtaining a PhD in Statistics from Stanford, she led DS for Pricing and Forecasting powering over 1 million listings at Airbnb. More recently at Meta as a research scientist manager, she led the team to deploy Facebook Ads system’s first privacy-preserving AI solution (approx $0.5B+ yearly incremental revenue).",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/milan-shen-860b5062",
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        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b11a45260614c613ef647e9e48b369b7ed6dbb98.jpg"
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    "launches": [
      {
        "id": 79657,
        "title": "❇️ Centauri AI - Modernizing ETL for Finance 🏦",
        "tagline": "Evaluate assets faster and win more deals with our modern data platform",
        "body": "**TL;DR**: [Centauri AI](https://centauri-ai.tech/) is a modern data platform for institutional investors to process and analyze complex investment asset data, starting with Structured Finance. We help investment teams evaluate assets faster and win more deals by turning 2-3 hours of data extracting, mapping, and analysis work under minutes. [Contact us here](https://centauri-ai.tech/).\n\nCheck out our latest demos here:\n\n* Clean and validate complex loan files effortlessly\n* [Draft a deal memo under 10 minutes](https://www.loom.com/share/387a38a2908543a8a90590c87a2358ba?t=22&sid=733daefd-dd1a-496a-b68d-cc6fc6c234b4)\n* Validate growth numbers from multiple docs\n* Covenant compliance certificate analysis\n\n### [🔥](https://emojiterra.com/fire/) The Problem\n\nThe Structured Finance industry suffers from antiquated technology, particularly in mortgage securitization. Lenders and investors deal with inefficient processes, using emails and Excel files to exchange complex information on mortgage-backed securities and other assets. This requires manual or outdated software for data mapping and transformation, consuming significant time (2-3 hours daily) even for experienced professionals. Similar inefficiencies are present in other Alternative Investment sectors like Private Credit, Private Equity, and Real Estate, where analysts wade through extensive documents for deal analysis and portfolio updates.\n\n### ✨ Our Solution\n\nWe envision bringing a modern ETL and data science platform built natively with AI to this traditional industry. Traders and analysts can centralize, standardize, and gain insights quickly from all the data they handle without wrangling with copy-pasting between numerous PDFs and Excel files. We believe that equipped with the right tools purpose-built for data in structured finance, AI agents can perform on par or better than humans on these mundane tasks.\n\n### [⚙](https://emojiterra.com/fire/)️ How it works\n\n**Extract**\n\nDrop your CSV, PDF, or Excel files into our upload hub. The agent automatically detects the structured tables and indexes unstructured text. Later, these tables are ready for data-cutting and modeling.\n\n**Transform**\n\nOur AI agent is built for data mapping. It identifies and explains data fields in natural language and writes code to map them to the desirable output format. \n\n**Analyze**\n\nOur first-of-its-kind analysis agent is equipped with features designed for ad-hoc exploratory analysis. You can auto-run, rewind, or branch out a generative report at any given time to get more insights easily.\n\n![uploaded image](/media/?type=post&id=79657&key=user_uploads/1522478/a89bdb32-0d3f-452e-9985-e5eafc99bb18)\n\n**Present**\n\nWe support exporting the transformed data and analysis findings as a nice dashboard or customized in your way, such as in well-formatted Excel sheets. More customized-style exporting is on the roadmap!\n\n![uploaded image](/media/?type=post&id=79657&key=user_uploads/1522478/60fba13c-b340-4ac1-8b6b-abe23f589b28)\n\n### Our Team\n\nWe are [He](https://www.linkedin.com/in/he-lu-63666852/), [Milan](https://www.linkedin.com/in/milan-shen-860b5062/), and [James](https://www.linkedin.com/in/jameswu1991/). \n\nHe was the co-founder and CTO of Blue Water Fintech, which generated $18M ARR before being acquired in 2022. He experienced the inefficiency of data processing and analytics tasks firsthand when he managed 5 institutional trading books as a portfolio manager.\n\nAfter obtaining a PhD in Statistics from Stanford, Milan led DS for Pricing and Forecasting, powering over 1 million listings at Airbnb. More recently, at Meta, as a research scientist manager, she led the deployment of Facebook Ads system’s first privacy-preserving AI solution (approx $0.5B+ yearly incremental revenue).\n\nJames is a UC Berkeley Alumni in Computer Science and was a Director of Engineering at Tubi, hired the Platform Eng Team managing a >1500c autoscaling K8s cluster and oversaw costs for a $x0M/year tech budget. He was also Principal Engineer at Minted as a full-stack DevSecOps developer.\n\nTogether, we’re excited to help bring the modern data stack powered by AI to financial firms.\n\n![uploaded image](/media/?type=post&id=79657&key=user_uploads/1522478/136f0f03-3e33-4551-8cce-f80795f5dca9)\n\n### 🙏 Asks\n\n* If you are in the financial industry and processing large amounts of Excel and PDF files is part of your daily life, we would love to hear your product feedback! Please [book a demo here](https://docs.google.com/forms/d/e/1FAIpQLScu7V4vCg8vpWBolMrHT2HgxXujsOyeKt41IG3vqMJteJGMgQ/viewform).\n* If you know any leaders in investment firms such as private credit or private equity, please connect us!\n* If you know any Directors or VPs responsible for trading or managing Whole Loans, Mortgage Backed Securities (MBS), Collateralized Mortgage Obligations (CMO), or Asset Backed Securities (ABS) in any banks or asset management firms, please connect us! Email us at [he.lu@centauri-ai.tech](mailto:he.lu@centauri-ai.tech)",
        "url": "https://www.ycombinator.com/launches/Kin-centauri-ai-modernizing-etl-for-finance",
        "votes": 23,
        "created_at": "2024-03-25T02:43:00.680Z"
      }
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    "id": 29425,
    "name": "Zep AI",
    "slug": "zep-ai",
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      "Zep Software",
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    "website": "https://www.getzep.com/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Zep unifies business data, documents, and conversations into shared, governed context so agents can complete tasks correctly. Its Context Lake manages millions of Context Graphs as one system, with access controls, retention policies, source traceability, and audit logs. Teams use Zep to build enterprise context graphs, agent memory, and customer and account context. Zep retrieves context in under 200 milliseconds. Graphiti, Zep’s open source framework for temporal knowledge graphs, has more than 30,000 GitHub stars.",
    "one_liner": "The unified context layer for enterprise data",
    "team_size": 10,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1709681560,
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      "Conversational AI",
      "AI Assistant"
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    "status": "Active",
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    "year_founded": 2023,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/zep-ai/",
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        "full_name": "Daniel Chalef",
        "title": "Founder/CEO",
        "founder_bio": "Founder, Zep AI. Engineer turned startup founder (previously KnowledgeTree) and late-stage operator (SparkPost acquired MessageBird), with detours as a Data Science, Marketing, and Corp Dev guy. \n\nStill an engineer at heart and have a soft spot for Go.",
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        "linkedin_url": "https://linkedin.com/in/danielchalef",
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        "id": 102880,
        "title": "Head of Forward Deployed Engineering",
        "url": "https://www.ycombinator.com/companies/zep-ai/jobs/mVon3qA-head-of-forward-deployed-engineering",
        "location": "San Francisco, CA, US / Remote (US)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$220K - $270K",
        "equity_range": "1.20% - 1.75%",
        "experience": "11+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Amazon Web Services (AWS)",
          "Go",
          "Kubernetes",
          "Python",
          "TypeScript",
          "Terraform",
          "AI Agents"
        ]
      },
      {
        "id": 105318,
        "title": "Member of Technical Staff: Research",
        "url": "https://www.ycombinator.com/companies/zep-ai/jobs/8YxqiAO-member-of-technical-staff-research",
        "location": "San Francisco, CA, US / Remote (US)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Machine learning",
        "salary_range": "$180K - $250K",
        "equity_range": "1.00% - 1.50%",
        "experience": "6+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Amazon Web Services (AWS)",
          "Python",
          "Torch/PyTorch",
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      {
        "id": 83738,
        "title": "Graphiti by Zep AI : A library for building dynamic Knowledge Graphs",
        "tagline": "Accurate, Current Data for AI Agents",
        "body": "Hey! We're Paul, Preston, and Daniel from Zep AI. We've just [open-sourced Graphiti](https://git.new/graphiti), a Python library for building temporal Knowledge Graphs using LLMs.\n\n<https://youtu.be/sygRBjILDn8>\n\nGraphiti helps you create and query graphs that evolve over time. Think of a knowledge graph as a network of interconnected facts, such as _“Kendra loves Adidas shoes.”_ Each fact is a “triplet, represented by two entities, or nodes (_”Kendra,” “Adidas shoes”_), and their relationship, or edge (_”loves”_). Knowledge Graphs have been explored extensively for information retrieval. What makes Graphiti unique is its ability to autonomously build a knowledge graph while handling changing relationships and maintaining historical context.\n\nAt Zep, we build a [memory layer for LLM applications](https://www.getzep.com). Developers use Zep to recall relevant user information from past conversations without including the entire chat history in a prompt. Accurate context is crucial for LLM applications. If an AI agent doesn't remember that you've changed jobs or confuses the chronology of events, its responses can be jarring or irrelevant, or worse, inaccurate.\n\n# Zep’s Suboptimal Fact Pipeline\n\nBefore Graphiti, our approach to storing and retrieving user “memory” was, in effect, a specialized RAG pipeline. An LLM extracted “facts” from a user’s chat history. Semantic search, reranking, and other techniques then surfaced facts relevant to the current conversation back to a developer for inclusion in their prompt.\n\nUnfortunately, this approach became problematic. Reconciling facts from increasingly complex conversations challenged even frontier LLMs such as gpt-4o. We saw incomplete facts, poor recall, and hallucinations. Our RAG search also failed at times to capture the nuanced relationships between facts, leading to irrelevant or contradictory information being retrieved.\n\nWe tried fixing these issues with prompt optimization but saw diminishing returns on effort. We realized that a graph would help model a user’s complex world, potentially addressing these challenges.\n\n# Building Graphiti\n\nWe were intrigued by Microsoft’s GraphRAG, which expanded on RAG text chunking with a graph to better model a document corpus. However, it didn't solve our core problem: GraphRAG is designed for static documents and doesn't natively handle temporality.\n\n![uploaded image](/media/?type=post&id=83738&key=user_uploads/808515/db4712c7-1171-4115-ad7b-67896c754a65)\n\nSo, we built Graphiti, a [temporal Knowledge Graph](https://github.com/getzep/graphiti) library, which is designed from the ground up to handle constantly changing information, hybrid semantic and graph search, and scale:\n\n* **Temporal Awareness**: Tracks changes in facts and relationships over time. Graph edges include temporal metadata to record relationship lifecycles.\n* **Episodic Processing**: Ingests data as discrete episodes, maintaining data provenance and enabling incremental processing.\n* **Hybrid Search**: Semantic and BM25 full-text search, with the ability to rerank results by distance from a central node.\n* **Scalable**: Designed for large datasets, parallelizing LLM calls for batch processing while preserving event chronology.\n* **Varied Sources**: Ingests both unstructured text and structured data.\n\n# Getting Started\n\nGraphiti is open-source and available on GitHub: <https://git.new/graphiti>\n\nQuick Start: `pip install graphiti-core`\n\nWhile we developed Graphiti for our needs at Zep, we believe it could be useful for any application dealing with evolving, interconnected data, such as:\n\n* Personal AI assistants that need to maintain user context over time\n* Knowledge management systems for rapidly changing domains\n* Social network analysis tools\n* Financial systems tracking changing relationships and transactions\n\nIf you try, we'd love to hear your thoughts, questions, and experiences. Please also consider contributing!\n\n![uploaded image](/media/?type=post&id=83738&key=user_uploads/808515/3d306962-fad2-44fd-9232-862ddd961d0d)\n\n",
        "url": "https://www.ycombinator.com/launches/Lmc-graphiti-by-zep-ai-a-library-for-building-dynamic-knowledge-graphs",
        "votes": 19,
        "created_at": "2024-09-04T15:35:06.052Z"
      },
      {
        "id": 81733,
        "title": "Zep: Fast, accurate structured data extraction for AI assistant apps",
        "tagline": "10x faster than GPT-4o, with field format and validity guarantees.",
        "body": "Many business and consumer apps must extract structured data from conversations between an LLM-powered Assistant and a human user. Often, the extracted data is the objective of the conversation. Consider completing a sales order, making a reservation, or requesting leave. All of these tasks require progressively collecting data from the conversation.\n\nLatency and correctness are important. You will often want to identify the correct data values you have collected and those you still need. You’ll then prompt the LLM to request the latter.\n\n<https://youtu.be/k8e8NsoVzFo>\n\nIf you’re making multiple calls to an LLM to extract and validate data on every chat turn, you’re likely adding significant latency to your response. This can be a slow and inaccurate exercise, frustrating your users.\n\nZep’s new Structured Data Extraction feature is a low-latency, high-accuracy tool for extracting the data you need from Chat History stored in Zep's Long-term Memory service.\n\n> **Up to 10x faster than gpt-4o.** For many multi-field extraction tasks, you can **expect latency of under 400ms,** with the addition of fields increasing latency sub-linearly.\n\n## Comparing Zep with LLM JSON Mode\n\nMany model providers offer a JSON inference mode that guarantees the output will be well-formed JSON.\n\nHowever:\n\n* There are no guarantees that the field values will conform to the JSON Schema you define or that they are correct (vs. being hallucinated).\n* All fields are extracted in a single inference call, with additional fields adding linearly or greater to extraction latency.\n\n#### Preprocessing, Guided LLM Output, and Validation\n\nTo ensure that the extracted data is in the format you expect and is valid given the current dialog, Zep uses a combination of:\n\n* dialog preprocessing, which, amongst other things, improves accuracy for machine-transcribed dialogs;\n* using guided output inference techniques on LLMs running on our own infrastructure;\n* and post-inference validation.\n\nYou will not receive back data in an incorrect format when using a Zep field type such as email, zip code, or date time.\n\nWhile there are limits to the extraction accuracy when the conversation is very nuanced or ambiguous, carefully crafting field descriptions can achieve high accuracy in most cases.\n\n#### Up to 10x Faster than OpenAI gpt-4o\n\nWhen comparing like-to-like JSON Schema model extraction against gpt-4o, Zep is up to 10x faster.\n\n![uploaded image](/media/?type=post&id=81733&key=user_uploads/808515/7adc0720-a2ed-43d9-88ed-1bd883f819c7)\n\nZep's extraction latency scales sub-linearly with the number of fields in your model. That is, you may add additional fields with a low marginal increase in latency.\n\n## Support for Partial and Relative Dates\n\nZep understands various date and time formats, including relative times such as _“yesterday”_ or _“last week.”_ It can also parse partial dates and times, such as _“at 3pm”_ or _“on the 15th.”_\n\n## Extracting from Speech Transcripts\n\nZep can understand and extract data from machine-transcribed transcripts. Spelled-out numbers and dates will be parsed as if they were written language. Utterances such as “uh” or “um” are ignored.\n\n![uploaded image](/media/?type=post&id=81733&key=user_uploads/808515/8ab99f7f-0672-42dc-9d35-b06c37a33c7a)\n\n## Using Progressive Data Extraction To Guide LLMs\n\nYour application may need to collect several fields to accomplish a task. Since Zep's SDE is so fast, you can guide the LLM through this process by calling the extractor on every chat turn. This enables you to identify which fields are still needed and then direct the LLM to collect the remaining data.\n\n```\nYou have already collected the following data:\n- Company name: Acme Inc.\n- Lead name: John Doe\n- Lead email: john.doe@acme.com\n\nYou still need to collect the following data:\n- Lead phone number\n- Lead budget\n- Product name\n- Zip code\n\nDo not ask for all fields at once. Rather, work the fields \ninto your conversation with the user and gradually collect the data.\n```\n\n## Next Steps\n\n1. Learn more in the [Zep Structured Data Guide](https://help.getzep.com/structured-data-extraction).\n2. Sign up for Zep's [Long-term Memory Service for AI Assistants](https://www.getzep.com/).\n\n![uploaded image](/media/?type=post&id=81733&key=user_uploads/808515/0a1d48ed-3bde-4b77-b3e7-08ffe0fa3deb)\n\n",
        "url": "https://www.ycombinator.com/launches/LGH-zep-fast-accurate-structured-data-extraction-for-ai-assistant-apps",
        "votes": 17,
        "created_at": "2024-06-25T16:05:02.992Z"
      },
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        "id": 79302,
        "title": "Zep - Long-term memory for AI assistants",
        "tagline": "Build Assistants that know your users.",
        "body": "[Zep](https://www.getzep.com/) is the easiest way to add long-term memory to your AI Assistant. With Zep, you can recall, understand, and extract data from chat histories, enabling you to build rich, personalized experiences. \n\n**Sign up for the **[**Zep Cloud**](https://www.getzep.com/)** and get a Zep Bot T-Shirt when you go live!**\n\ntl;dr\n\n* Zep ensures your Assistant **remembers relevant facts and nuance** from historical conversations, no matter how distant in the past.\n* **Zep makes dialog useful**: Control program flow, extract structured data, select the right prompts or tools, build customer segments, and more.\n* **Fast**! Minimize the number of LLM calls keeping your users waiting. Zep completes tasks in a 1/10 of the time compared to similar functionality built with OpenAI.\n\n![uploaded image](/media/?type=post&id=79302&key=user_uploads/808515/c1ac513c-7ef4-4406-b98a-3e3b4ff94134)\n\n<https://www.youtube.com/watch?v=qVspUE_R-iI>\n\n**Zep In Action: The Amazing ShoeStoreBot**\n\nManaging sales, returns, and order inquiries is all in a day’s work for this hard-working ShoeStoreBot. It remembers past customers, their budgets, brand preferences, shoe size, and more.\n\n<https://www.youtube.com/watch?v=AC4VTqLYYhM>\n\n**Perpetual Memory:  Your Assistant will never forget a user.**\n\nAutomagically populate prompts with relevant facts and summaries extracted from past conversations, no matter how distant.\n\n![uploaded image](/media/?type=post&id=79302&key=user_uploads/808515/6672d796-e8c6-46de-9f65-53dcae5b54ea)\n\n**Dialog Classifier: Instantly and accurately understand chat dialog.**\n\nIdentify user intent, emotion, segmentation, and more. Control program flow with semantic context, using the right prompts, tools, and agents depending on the current dialog.\n\n![uploaded image](/media/?type=post&id=79302&key=user_uploads/808515/5967ab25-86e6-4526-8fc0-aba4c87c6c58)\n\n**Extract Structured Data from Dialog**\n\n![uploaded image](/media/?type=post&id=79302&key=user_uploads/808515/89656e21-5687-4d6d-a8b8-f4a728e19562)\n\nQuickly extract business data from chat conversations. Understand what your Assistant should ask for next to complete its task.\n\n**Support for Your Favorite Languages and Frameworks**\n\nAre you a Python, TypeScript, LangChain, LangChain.js, Chainlit, or FlowWise person? We got you covered.\n\n**The Zep Team**\n\nZep was founded by [Daniel](https://www.linkedin.com/in/danielchalef/) (hi!), who was recently joined by 2 engineers he worked with previously (Peter & Paul!). Daniel led ML at SparkPost (acquired by MessageBird), and previously founded KnowledgeTree (another popular open source project from the 2000s). Despite taking on marketing and corp dev roles in previous lives, he remains an engineer at heart.\n\nDaniel accidentally started Zep when he got frustrated that no delightful software existed to do what Zep does today. He built an early version and stuck it up on GitHub, and one thing led to another.",
        "url": "https://www.ycombinator.com/launches/Kd4-zep-long-term-memory-for-ai-assistants",
        "votes": 70,
        "created_at": "2024-03-12T13:34:56.206Z"
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        "full_name": "Alexander Belanger",
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        "founder_bio": "Co-founder & CEO at Hatchet (W24), previously co-founder & CTO at Porter (S20). M.S. in Physics, B.A. in Physics and Computer Science from the University of Pennsylvania. \n\nAlways happy to chat anything devtools, OSS, infrastructure!  ",
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        "full_name": "Gabe Ruttner",
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        "founder_bio": "Co-founder & CTO at Hatchet (W24), previously co-founder & CTO at ClearMix (S20). Masters in CS/AI from Cornell. Always game to chat anything dev tools, OSS, AI Architecture!\n\n",
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      {
        "id": 79258,
        "title": "Hatchet - Background task orchestration and visibility platform",
        "tagline": "We help engineers run fast and reliable background tasks",
        "body": "**tl;dr** - At a certain scale, all applications need a task queue - think Celery for Python, BullMQ for Node.js, and Sidekiq for Rails. [Hatchet](https://hatchet.run) is an [open-source](https://github.com/hatchet-dev/hatchet), managed task queue focused on scale, reliability, and improved developer experience. \n\n<https://youtu.be/3myPYVyaqwM>\n\n**The problem**\n\nBuilding a reliable application is difficult — network connections can fail or be interrupted, the application could run out of memory, or a bad commit on production can take down your entire service. To reduce the pressure on APIs, task queues are typically used to offload different parts of the application logic to other services in the system.\n\nHowever, these queues introduce more points of failure — they require new infrastructure, a new set of integrations to monitor and debug your tasks, and are difficult to use in development. As applications begin to scale, application developers are forced to implement solutions to avoid queue overflow and overcrowding and to think about how to optimize their queues.\n\nWith LLM APIs — which are high latency and highly variable in response quality — these problems are even worse. It’s now typical to ingest, sync, vectorize, and index the entirety of multiple data sources on account creation, and as LLM systems get more agentic, developers need to chain together unreliable LLM calls to fulfill requests. These requests are often slow and without the right architecture delivering a responsive and reliable user experience is challenging.\n\n**The solution**\n\nHatchet is an **end-to-end platform** for task orchestration. It includes a web UI for monitoring tasks, an API for interacting with tasks and workflows, and SDKs for Python, Typescript, and Golang.\n\n![uploaded image](/media/?type=post&id=79258&key=user_uploads/363082/1617c928-fc04-4482-9b13-98c342e14694)\n\nHatchet has all the features you’d expect — like **retries, timeouts**, and **cron schedules** — along with features that developers are usually asked to build, like handling different **fairness and concurrency patterns**, **durable execution**, and **result streaming**.\n\n**The team**\n\nWe’re both ex-CTOs and founders of multiple YC-funded companies — [Alexander](https://linkedin.com/in/alexander-belanger-aa3974135) was co-founder and CTO at [Porter](https://porter.run) (S20) while [Gabe](https://linkedin.com/in/gruttner) was co-founder and CTO at [Clearmix](https://www.ycombinator.com/companies/clearmix) (also S20). Before that, Alexander got his Master’s in Physics from UPenn while Gabe got his Master’s in AI from Cornell.\n\nAlexander started working on this after years of wrangling task queues and distributed systems at both Porter and [Oneleet](https://oneleet.com), where he experienced the issues of building complex task orchestration and workflows. Gabe came at this from another perspective, having spent the last few years working with ML and more recently LLM stacks, where he saw the architectural problems that many of these applications have.\n\nWe immediately bonded over our excitement about what infrastructure will look like as AI becomes core to nearly every business.\n\n![uploaded image](/media/?type=post&id=79258&key=user_uploads/363082/e77d894d-1e99-4128-9bff-65f905d97571)\n\n**How do I get started?**\n\nHatchet is fully open source with an [invite-only cloud offering](https://hatchet.run/request-access). Feel free to request access or check out the [self-hosting Hatchet](https://docs.hatchet.run/self-hosting) docs.\n\nIf you’re dealing with observability problems in your queue, are running batch processing of documents for LLM workflows, or are experiencing queue fairness problems in multi-tenant apps, we’d love to chat.\n\nAnd if you have any questions — or you’re just interested in distributed systems, task queues, and scheduling — we have a [public Discord](https://discord.gg/ZMeUafwH89). See you there!",
        "url": "https://www.ycombinator.com/launches/KcM-hatchet-background-task-orchestration-and-visibility-platform",
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        "created_at": "2024-03-11T14:21:38.752Z"
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "Downlink is a platform that continuously improves your AI.\r\n\r\nBoost rate limits, slash latency, and raise accuracy.\u0003All through one simple API.",
    "one_liner": "Make your LLMs 3x faster.",
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    "subindustry": "B2B -> Infrastructure",
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        "founder_bio": "Titouan Launay, formerly at the helm of a 6-figures software consulting company, is now channeling his expertise into Fileforge, his latest venture. Coding since high school and with a solid background in civil engineering and architecture from INSA Lyon, he's adept at tackling complex challenges with a creative twist. He is passionate about photography, and previously built a successful software consulting company.",
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        "full_name": "Auguste Lefevre",
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        "founder_bio": "Co-founder at Fileforge. Background in Computer Science from ETH Zurich and Quantitative Finance as PhD (dropout) from the National University of Singapore. Interested in tech, finance and history.",
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        "linkedin_url": "https://www.linkedin.com/in/augustelefevre/",
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    "launches": [
      {
        "id": 78258,
        "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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    "id": 29472,
    "name": "Silogy",
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    "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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    "nonprofit": false,
    "batch": "Winter 2024",
    "status": "Active",
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    "regions": [
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    "url": "https://www.ycombinator.com/companies/silogy",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/silogy.json",
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    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/100808053/",
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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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        "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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    "website": "https://www.spurtest.com/",
    "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"
    ],
    "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"
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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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      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
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        "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/",
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        "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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      {
        "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",
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      {
        "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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    "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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    "github_url": "https://github.com/Integuru-AI/",
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      "name": "Gustaf Alstromer",
      "url": "https://www.ycombinator.com/people/gustaf-alstromer"
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      {
        "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",
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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": 29502,
    "name": "renderlet",
    "slug": "renderlet",
    "former_names": [
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      "Renderlet"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/8c34b0727ce76497f1f02b8f378c53e7f5d7ab8f.png",
    "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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    "nonprofit": false,
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    "status": "Active",
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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/renderlet",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/renderlet.json",
    "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": [
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        "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",
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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,
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    "city": "New York City",
    "country": "US",
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    "primary_partner": {
      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
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    "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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      {
        "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"
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      {
        "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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  },
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    "id": 29524,
    "name": "Coval",
    "slug": "coval",
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    "website": "https://coval.dev",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Coval is a simulation & evaluation platform for autonomous AI agents, helping engineers launch dependable assistants across chat, voice, and other modalities. \r\nWe simulate thousands of scenarios engineers don't have to manually test their agents. Our CI/CD evaluations automatically simulate and detect regressions.",
    "one_liner": "Simulation & Evaluation that scales voice and chat AI agents",
    "team_size": 10,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1725341816,
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    "isHiring": true,
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    "status": "Active",
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    "regions": [
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    "stage": "Early",
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/coval",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/coval.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/covaldev",
    "x_url": "https://x.com/covaldev",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/coval-ai",
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    "primary_partner": {
      "name": "Harj Taggar",
      "url": "https://www.ycombinator.com/people/harj-taggar"
    },
    "founders": [
      {
        "user_id": 1019731,
        "full_name": "Brooke Hopkins",
        "title": "Founder",
        "founder_bio": "Building evaluation for AI agents, previously led eval infra at Waymo 🚙",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/bnhop",
        "x_url": "https://twitter.com/bnicholehopkins",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0577036f83dc9c8cd80e528eaf8740bdbf2cd06f.jpg"
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        "id": 92828,
        "title": "Account Executive",
        "url": "https://www.ycombinator.com/companies/coval/jobs/sFLtjLc-account-executive",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$110K - $350K",
        "equity_range": "",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 92854,
        "title": "Founding Product Engineer",
        "url": "https://www.ycombinator.com/companies/coval/jobs/ILkSK7r-founding-product-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$100K - $300K",
        "equity_range": "0.01% - 1.00%",
        "experience": "6+ years",
        "visa": "US citizen/visa only",
        "skills": [
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          "Python",
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          "Distributed Systems",
          "Data Modeling"
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      },
      {
        "id": 92860,
        "title": "Forward Deployed Engineer",
        "url": "https://www.ycombinator.com/companies/coval/jobs/ITTPluu-forward-deployed-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
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        "title": "Deployment Strategist",
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        "location": "San Francisco, CA, US",
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        "title": "Business Development Representative ",
        "url": "https://www.ycombinator.com/companies/coval/jobs/KAYIxhg-business-development-representative",
        "location": "San Francisco, CA, US",
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        "role_type": null,
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        "title": "Solutions Engineer",
        "url": "https://www.ycombinator.com/companies/coval/jobs/tZSJGPI-solutions-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$180K - $250K",
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    "news": [
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        "title": "What It Actually Takes to Deploy a Voice Agent to a Fortune 500",
        "url": "https://www.youtube.com/watch?v=eSm_9tb5ZbY",
        "date": "Jun 24, 2026"
      },
      {
        "title": "Coval raises $28M to make better voice agents",
        "url": "https://www.axios.com/pro/enterprise-software-deals/2026/06/24/coval-ai-voice-agents-enterprise",
        "date": "Jun 24, 2026"
      },
      {
        "title": "Coval evaluates AI voice and chat agents like self-driving cars | TechCrunch",
        "url": "https://techcrunch.com/2025/01/23/coval-evaluates-ai-voice-and-chat-agents-like-self-driving-cars/",
        "date": "Jan 23, 2025"
      }
    ],
    "launches": [
      {
        "id": 83700,
        "title": "Coval - Simulation & Evaluation for AI Agents",
        "tagline": "Ship AI agents faster with a simulation and evaluation platform for chat and voice assistants.",
        "body": "Teams are racing to market with AI agents, but slow manual testing processes are holding them back. Engineers currently spend hours manually evaluating and playing whack-a-mole just to discover that fixing one issue introduces another.\n\nAt Coval, we build automated simulation and evaluation for AI agents inspired by the autonomous vehicle industry to boost test coverage, speed up development, and validate consistent performance.\n\nWe have a waitlist, but YC companies go first! Grab some time here: <https://bit.ly/coval-demo>\n\n![uploaded image](/media/?type=post&id=83700&key=user_uploads/1019731/e39b0b4e-22ea-4e62-85a4-d5421cafb7d5)\n\n# **Our Story**\n\nHey! I’m [Brooke](https://www.linkedin.com/in/bnhop/), the founder of [Coval](https://www.coval.dev/). 👋\n\nBefore starting Coval, I led the evaluation job infrastructure team at [Waymo](https://waymo.com/). I coded the first versions of our dataset storage and other foundational simulation systems, and my team built all of the dev tools for launching and running evals.\n\nThrough my conversations with hundreds of engineering teams at startups and enterprises, I've seen that AI agents—models that operate independently and handle complex tasks—are facing similar challenges to those in self-driving. \n\nIn the early days, autonomous vehicle companies relied heavily on manual evaluation, testing the self-driving cars on racetracks and city streets (remember when autonomous cars still had safety drivers?). However, as startups scaled, a significant shift happened: we moved towards simulating every code change in a “virtual” environment, using the vast amounts of data we collected. The new approach dramatically improved vehicle behavior, leading to hundreds of autonomous cars zipping around the San Francisco streets today!\n\nThis story mirrors what's happening today with AI agents across various industries. Teams are coming up with promising prototypes but often hit a wall when it comes to their reliability. \n\nAs we build for the future, where AI agents execute much of our work, ranging from sending emails to prescribing medication, the risks posed by untested systems could severely throttle the progress.\n\nAt Waymo, I developed tools that tested each code modification made by engineers, ensuring that every change improved the Waymo Driver's performance. I believe this methodical approach was key in helping our team address edge cases and maintain peak performance, and it ultimately cemented Waymo's status as a leader in the autonomous vehicle space.\n\nNow, at Coval, we’re taking these proven strategies and adapting them in a completely new way to speed up the development of AI agents. Our goal is to help engineers build agent experiences that genuinely work for users in the real world.\n\nAutomated simulation and evaluation are critical to trusting agents with impactful tasks across industries.\n\n# **Working With Us**\n\nBuilding agents or know someone? Let’s talk! [Grab time with me here](https://bit.ly/coval-demo) for a quick intro, or message me at [brooke@coval.dev](mailto:brooke@coval.dev).",
        "url": "https://www.ycombinator.com/launches/Lm0-coval-simulation-evaluation-for-ai-agents",
        "votes": 81,
        "created_at": "2024-09-03T12:43:30.586Z"
      }
    ]
  },
  {
    "id": 29569,
    "name": "Miru",
    "slug": "miru-ml",
    "former_names": [
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      "Miru",
      "Miru ML"
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    "website": "https://www.mirurobotics.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Miru makes it easy for robotics teams to manage, version, and deploy robot configurations. Developers use our well-documented APIs and UI components to automate configuration updates for both engineers and operators.\r\n\r\nIn the long term, we're building software infrastructure to accelerate the automation of the physical world.",
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    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1722117145,
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      "Robotics",
      "DevOps"
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    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2024",
    "status": "Active",
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      "America / Canada"
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    "url": "https://www.ycombinator.com/companies/miru-ml",
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    "city": "San Francisco",
    "country": "US",
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    "primary_partner": {
      "name": "Aaron Epstein",
      "url": "https://www.ycombinator.com/people/aaron-epstein"
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      {
        "user_id": 620575,
        "full_name": "Armel Talla",
        "title": "Founder/CEO",
        "founder_bio": "Armel is the Co-Founder and CEO of Miru.\n\nHe graduated from UT Austin with a B.S. in Computer Science and Mathematics. He previously founded Clips AI, an AI video dev tool that automatically repurposes long videos into clips. During college, Armel interned at Google and YouTube, focusing on building internal tools.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/armeltalla",
        "x_url": "https://twitter.com/armelwtalla",
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      },
      {
        "user_id": 1035647,
        "full_name": "Vedant Nair",
        "title": "Founder",
        "founder_bio": "Vedant is the Co-Founder and COO of Miru.\n\nHe graduated from UT Austin, where he studied Business and Computer Science. He previously founded Clips AI, an AI video developer tool that automatically repurposed long videos into clips. During college, he interned at Bain & Co. and EY-Parthenon, doing GTM consulting for software companies.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/vedantnair",
        "x_url": "https://x.com/vedantnair__",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2bf4c979b9371b48d25473b333207ae536ec3e6b.jpg"
      },
      {
        "user_id": 1521401,
        "full_name": "Benjamin Smidt",
        "title": "Founder/CTO",
        "founder_bio": "Ben is the Co-Founder and CTO of Miru. \n\nHe holds a B.S. in Electrical and Computer Engineering from UT Austin, where he initially spent two years studying Mechanical Engineering, igniting his passion for hardware and robotics. Prior to Miru, Ben founded Clips AI, where he developed production-ready AI models and video processing servers using Kubernetes.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/benjamin-smidt",
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        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/dd7148f07187d171dea5d0364ead07b775dc74f5.jpg"
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      {
        "id": 82564,
        "title": "Miru - Deployment infrastructure for Robotics and IoT 🦾",
        "tagline": "Deploy software updates over the air to fleets of devices",
        "body": "**tl;dr:** Miru helps robotics and IoT teams painlessly deploy software over the air, provision devices, and manage versioning for their fleets.\n\nFor engineers using Miru, _updating software on thousands of devices is as easy as pushing a change to GitHub._\n\n**Our Ask:** Engineers in robotics and IoT, [get started with Miru today!](https://www.miruml.com/)\n\n![uploaded image](/media/?type=post&id=82564&key=user_uploads/1035647/c64f81c9-695b-472e-bab9-5687c4eef19f)\n\n**❌ The Problem**\n\nRobotics and IoT companies don’t have robust, off-the-shelf DevOps tools.\n\nAs a result, to deploy their software, they’re forced to manually SSH/SCP into their devices or build a hacky solution internally.\n\n**But building this infrastructure is costly.** These companies often need to dedicate more than half of their software team to build and maintain their custom internal tools. This balloons engineering costs and decreases product velocity.\n\nIt’s one of the reasons **why many of these companies die.**\n\n**🦾 Miru**\n\nMiru helps engineers build and maintain their deployment pipelines, saving them months of work.\n\nWith Miru, you can:\n\n1. Push changes to GitHub, and let Miru handle building, staging, and deploying your software to your devices across the world\n2. Manage devices and track software versioning on a centralized dashboard\n3. Enjoy obsessive, fast, 24/7 customer support 🫡\n\n**Installation is easy.** If your device already uses Ubuntu, the Miru installation is just one command **🪄**\n\nMiru users have an unfair advantage. They enjoy reliable, scalable, and secure deployments _without all the pain of building it themselves_.\\\n\\\n<https://youtu.be/N0N6R5Gtjx4?si=2P6385myxlbDnB2j>\n\n🧍🏼🧍🏿🧍🏾 **About Us**\n\nHi 👋🏾 - we’re [Vedant](https://linkedin.com/in/vedantnair), [Armel](https://linkedin.com/in/armeltalla), and [Ben](https://linkedin.com/in/benjamin-smidt)!\n\n![uploaded image](/media/?type=post&id=82564&key=user_uploads/1035647/a48e7554-cf3c-493b-b5c7-d8aa5a03eb84)\n\nAfter meeting at our freshman dorm at UT Austin, we instantly clicked and became best friends. Whether we were playing intramural basketball or scaling our previous startup, [Clips AI](https://www.clipsai.com/), to 7000 MAUs in just three months, we've proven we make an exceptional team.\n\nOutside of Clips AI, Armel worked as a software engineer at Google and YouTube, focusing on building internal tools and infrastructure. Vedant brings experience in software GTM consulting from Bain & Co. and EY-Parthenon. Ben, our hardware fanatic, has a background in mechanical and electrical engineering, and he’s built production-ready AI and video processing infrastructure using Kubernetes.\n\nWe’re passionate about a future where robots can free humans from doing the dull, dirty, and dangerous tasks that dominate billions of people’s lives. We founded Miru to provide the infrastructure to accelerate this transition.\n\nWe’re obsessed with solving this problem. If you’re a software engineer in robotics or IoT who is struggling with deployment, we’d LOVE to make your life easier.\n\nJust reach out at \\[vedant\\] @ miruml \\[dot\\] com, or better yet, [start using Miru today](https://www.miruml.com/)",
        "url": "https://www.ycombinator.com/launches/LTg-miru-deployment-infrastructure-for-robotics-and-iot",
        "votes": 235,
        "created_at": "2024-07-30T16:20:31.446Z"
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  },
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    "id": 29575,
    "name": "Doublezero",
    "slug": "doublezero",
    "former_names": [
      "SuperFilter",
      "Superfilter",
      "Ceejay"
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    "website": "https://doublezero.tech",
    "all_locations": "Remote",
    "long_description": "Doublezero is a platform that provides developers with everything they need to build, operate, and monetize autonomous agents. Developers can focus on creating tools while Doublezero handles reasoning frameworks, state management, analytics, monetization, and a runner UI.\r\n\r\nUsers can interact with agents through a powerful UI that allows play, pause, rewind, and human intervention, and discover or share agents and tools through an integrated marketplace.",
    "one_liner": "Platform to build, use, and monetize fully autonomous agents",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1724163637,
    "tags": [
      "Developer Tools",
      "Infrastructure",
      "AI"
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    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2024",
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      "Fully Remote"
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        "title": "Ceejay - Give Your Inbox and Calendar a Brain",
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        "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)",
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        "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/)",
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        "title": "Mem0 - Open Source Memory Layer for AI Apps",
        "tagline": "Mem0 adds memory to AI applications, solving the problem of repetitive, stateless interactions and enabling personalized, cost-efficient AI experiences.",
        "body": "**TL;DR**\n\n[Mem0](https://mem0.ai) is an open-source memory layer for AI applications. It solves the problem of stateless LLMs by efficiently storing and retrieving user interactions, enabling personalized AI experiences that improve over time. Our hybrid datastore architecture combines graph, vector, and key-value stores to make AI apps personalized and cost-efficient. Watch our explainer video [here](https://youtu.be/Rg3_Mpr3Kcs).\n\n—\n\nHey everyone! We're Taranjeet and Deshraj, and we built [Mem0](https://github.com/mem0ai/mem0) to solve a big problem we faced with LLMs while building Embedchain (an open-source RAG framework with 2M+ downloads). LLMs don’t have memory, so they forget everything after each session. This leads to inefficient and repetitive interactions, making it hard to create personalized AI experiences. Think about having to repeat your preferences over and over again, and how frustrating that gets! Mem0 changes that.\n\n❌ **The Problem**\n\nLLMs are stateless—they don’t remember anything between sessions. Every time you interact with them, you have to provide the same context, which gets repetitive and wastes computational resources. This makes AI apps less useful and personalized over time.\n\n✨ **Our Solution**\n\n![uploaded image](/media/?type=post&id=83896&key=user_uploads/661173/ed531d50-421e-4d2f-a361-088587c27198)\n\nMem0 adds a **memory layer** to AI applications, making them stateful which allows them to store and recall user interactions, preferences, and relevant context. This way, AI apps evolve with every interaction, delivering more personalized and relevant responses without needing large context blocks in each prompt.\n\nTo make this possible, we needed to create a system that could efficiently manage and retrieve all the relevant information AI apps collect over time. That’s where Mem0’s **hybrid datastore architecture** comes in, making AI smarter and more efficient as it learns.\n\n⚙️ **How it works**\n\n[Mem0](https://mem0.ai) employs a hybrid datastore architecture that combines graph, vector, and key-value stores to store and manage memories effectively. Here’s the breakdown:\n\n* **Adding memories:** When you use Mem0 with your AI App, it automatically detects and stores the important parts of your messages or interactions.\n* **Organizing information:** Mem0 categorizes memories in three ways:\n  * **Key-value stores** for quick access to structured data (facts, preferences).\n  * **Graph stores** for understanding relationships (like people, places, objects).\n  * **Vector stores** for capturing the overall meaning and context of conversations, allowing AI apps to find similar memories later.\n* **Retrieving memories:** When an input query is received, Mem0 searches for and retrieves relevant memories using a combination of graph traversal techniques, vector similarity, and key-value lookups. It prioritizes the most important, relevant, and recent information, ensuring that the AI has the right context, no matter how much memory is stored.\n\nWatch this video for a demo of our playground in action [here](https://youtu.be/VtRuBCTZL1o)\n\n🙏 **Our Asks**\n\n* Try out [Mem0](https://mem0.ai)! We guarantee that your users will have personalized interactions after adding Mem0 in your AI apps. Moreover, you will save on your LLM costs.\n* If you are looking for a memory provider for your AI app and want to schedule a demo, please feel free to block some time on [my calendar](https://cal.com/taranjeetio/mem0) or email me at [taranjeet@mem0.ai](mailto:taranjeet@mem0.ai)\n* Checkout our platform and open-source offering and give feedback:\n  * Platform: <https://app.mem0.ai/playground>\n  * GitHub: <https://github.com/mem0ai/mem0>",
        "url": "https://www.ycombinator.com/launches/LpA-mem0-open-source-memory-layer-for-ai-apps",
        "votes": 634,
        "created_at": "2024-09-10T14:36:03.296Z"
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    "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!",
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        "full_name": "Daniel Han",
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        "founder_bio": "I was at NVIDIA making algorithms like TSNE 2000x faster. I also found and fixed 20+ bugs in open source LLMs like Gemma, Llama, Mistral and Phi. I also maintain the OSS package Hyperlearn making ML faster for NASA & Microsoft engineers.",
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        "linkedin_url": "https://linkedin.com/in/danielhanchen",
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        "title": "Founder",
        "founder_bio": "Hi guys - love building, designing and more. If you ever want help with fine-tuning or LLMs be sure to reach out!",
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        "linkedin_url": "https://linkedin.com/in/michaelhan3",
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        "title": "Founding ML Engineer",
        "url": "https://www.ycombinator.com/companies/unsloth-ai/jobs/3RB3eaY-founding-ml-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Machine learning",
        "salary_range": "$200K - $500K",
        "equity_range": "0.30% - 0.70%",
        "experience": "Any (new grads ok)",
        "visa": "Will sponsor",
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    "name": "Random Labs",
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "Random Labs is building Slate. Slate is a coding agent designed to work with you for long hours on hard problems.",
    "one_liner": "Random labs is building long running autonomous coding agents.",
    "team_size": null,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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      {
        "question": "What is your long-term vision? If you truly succeed, what will be different about the world?",
        "answer": "If we succeed, everyone will be able to code, and the number of software jobs available with grow by an insanely large number (10-20 million more devs)."
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    "country": "US",
    "linkedin_url": "https://www.linkedin.com/in/mihir-chintawar-95008a1b9/",
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        "full_name": "Kiran (Random Labs)",
        "title": "Founder/CEO",
        "founder_bio": "Building code generation tools",
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        "full_name": "Mihir Chintawar",
        "title": "Founder/CTO",
        "founder_bio": "CTO@Random Labs",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/mihir-chintawar-95008a1b9",
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    "launches": [
      {
        "id": 83813,
        "title": "Random Labs: An open source software agent that lives in your codebase",
        "tagline": "A 1,155,075 line codebase should feel like Playdough.",
        "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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        "created_at": "2024-09-06T05:56:13.070Z"
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    "name": "Invaria",
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    "country": "GB",
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        "user_id": 1666763,
        "full_name": "Ben Hall",
        "title": "Founder",
        "founder_bio": "Working on something new - keen to connect with hardware-turned-software engineers.\n\nPrior to Invaria, Ben spent almost 5 years at Palantir, mixing code and sales. Most recently he led the company's zero-to-one effort in the EMEA Utilities sector – an engineer in the deep end of sales. He was founding Principal Engineer at deep tech startup, Oxford Flow. The startup spun out of Oxford Uni's aerospace lab, where he had carried out his PhD research in jet engine aerodynamics. ",
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        "user_id": 1709643,
        "full_name": "Sam Kramer",
        "title": "Founder",
        "founder_bio": "Prior Invaria, Sam spent six years at Palantir, splitting his time equally between product and business development. Sam has done everything from fixing availability bugs in Paxos protocol implementations to running relationships with customer IT. ",
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        "linkedin_url": "https://www.linkedin.com/in/samuel-kramer-4263189a/",
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      {
        "user_id": 1977434,
        "full_name": "Alex Maass",
        "title": "Founder",
        "founder_bio": "Prior to Invaria, Alex spent 9 years at Palantir as a Forward Deployed Engineering Lead and as a Production Engineering Manager. He has led globally distributed teams to deliver client facing projects across diverse industries. As a Production Engineering Manager, Alex led and grew the EMEA team and was responsible for special projects with some of Palantir's most critical clients. Prior to Palantir, Alex had hardware engineering internships at Nvidia and MSI.",
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      {
        "id": 83144,
        "title": "Patchwork Technologies: Automated logging from code to storage",
        "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",
        "votes": 29,
        "created_at": "2024-08-17T00:34:12.169Z"
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    "id": 29647,
    "name": "Party",
    "slug": "party",
    "former_names": [
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    "website": "https://party.build",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Party is the secure workspace for your team and agents to build together, in the open. Agent Flows handle 95% of the work and your team can see it all happen and step in when needed to steer. It's built for teams and collaboration first, but caters to the solo builder as well. Use any harness/model - your keys or ours. Cost observability. Memory. Dual-level session sandboxing.\r\nSlack/Teams are comm-first with agents as second-class citizens. Party is work-first and the communication happens where the work is being done. Party is for teams who want to build better and faster than their competition. ",
    "one_liner": "Secure multiplayer workspace for teams building with agents",
    "team_size": 8,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1716914094,
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        "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)",
        "url": "https://www.ycombinator.com/launches/LhL-ideate-xyz-ai-design-co-pilot-for-content-teams",
        "votes": 51,
        "created_at": "2024-08-26T18:12:14.426Z"
      }
    ]
  },
  {
    "id": 29660,
    "name": "Hyrex",
    "slug": "hyrex",
    "former_names": [
      "Kura"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c33003b33c54f32f641d1dd6956b58f331c3842d.png",
    "website": "https://www.hyrex.io",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Hyrex is a task orchestration framework that uses PostgreSQL (or Hyrex Cloud) as a durable task queue. Define tasks in Python or TypeScript, send them to be processed asynchronously, and let Hyrex handle the rest.\r\n\r\nHyrex tasks are COLD: Controllable, Observable, Large-Scale, and Durable!",
    "one_liner": "The COLD Task Framework",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1724200248,
    "tags": [
      "AIOps",
      "Developer Tools",
      "Cloud Computing",
      "Infrastructure"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2024",
    "status": "Active",
    "industries": [
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      "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/hyrex",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/hyrex.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/hyrex-labs",
    "x_url": "https://x.com/hyrex_io",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/hyrex-labs",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/c33003b33c54f32f641d1dd6956b58f331c3842d.png",
    "app_video_url": null,
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    "company_photos": [
      "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/29c89a57406f27700f9b8b7efac971895519ec3f.png"
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    "primary_partner": {
      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
    },
    "founders": [
      {
        "user_id": 668182,
        "full_name": "Mark Dawson",
        "title": "Founder/CEO",
        "founder_bio": "Software Engineer. Second time founder. Currently focused on AI + Cloud infrastructure.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/markedwarddawson/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/6790b0a938ff2f969081aec2eac59e12ba759360.jpg"
      },
      {
        "user_id": 1967655,
        "full_name": "Trevor Reed",
        "title": "Founder/CTO",
        "founder_bio": "Co-founder at Hyrex, building the COLD task orchestration framework. Former Mars Rover driver at JPL with over 1km of drive distance on Mars and software engineer at Google processing worldwide YouTube data.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/trevorar",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0f6e2f6d5eafc4fc06afb8ca024e54677782c091.jpg"
      }
    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 93335,
        "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"
      }
    ]
  },
  {
    "id": 29665,
    "name": "Cloudglue",
    "slug": "cloudglue",
    "former_names": [
      "Aviary",
      "CloudGlue"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/83e6dd01545303c123ca60f1dcf8bdc7566497c5.png",
    "website": "https://cloudglue.dev",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Cloudglue is the video context layer for AI. We make it easy for your AI to understand video.\r\n- Tinycloud - your AI agent for video, now open for beta: https://tinycloud.cloudglue.dev\r\n- Developer API Platform: https://cloudglue.dev\r\n",
    "one_liner": "The video context layer for AI.",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1723146818,
    "tags": [
      "Developer Tools",
      "Machine Learning",
      "Video",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2024",
    "status": "Active",
    "industries": [
      "B2B"
    ],
    "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/cloudglue",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/cloudglue.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/cloudgluedev/",
    "x_url": "https://x.com/cloudgluedev",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/cloudglue",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/83e6dd01545303c123ca60f1dcf8bdc7566497c5.png",
    "app_video_url": null,
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    "company_photos": [],
    "primary_partner": {
      "name": "Gustaf Alstromer",
      "url": "https://www.ycombinator.com/people/gustaf-alstromer"
    },
    "founders": [
      {
        "user_id": 473205,
        "full_name": "Amy Xiao",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder & CEO at Cloudglue. Ex ML & infrastructure @ Snapchat, AWS, Arize AI, math/physics @ UofT",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/amyxiao",
        "x_url": "https://x.com/amyxst",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c735026b5678820f760811967dd225533d1d4713.jpg"
      }
    ],
    "jobs": [
      {
        "id": 89577,
        "title": "Founding Engineer, Full Stack",
        "url": "https://www.ycombinator.com/companies/cloudglue/jobs/j9Xc587-founding-engineer-full-stack",
        "location": "San Francisco, CA, US / Remote (Seattle, WA, US; Los Angeles, CA, US)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$120K - $250K",
        "equity_range": "0.50% - 2.50%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Amazon Web Services (AWS)",
          "Node.js",
          "PostgreSQL",
          "React",
          "TypeScript",
          "Serverless",
          "Prototyping"
        ]
      },
      {
        "id": 89578,
        "title": "Founding Engineer, Infrastructure",
        "url": "https://www.ycombinator.com/companies/cloudglue/jobs/pqyktS0-founding-engineer-infrastructure",
        "location": "San Francisco, CA, US / Remote (Seattle, WA, US; Los Angeles, CA, US)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Backend",
        "salary_range": "$120K - $250K",
        "equity_range": "0.50% - 2.50%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Amazon Web Services (AWS)",
          "Go",
          "Node.js",
          "PostgreSQL",
          "Python",
          "Distributed Systems",
          "Docker",
          "Serverless",
          "Search"
        ]
      },
      {
        "id": 90063,
        "title": "Research Engineer",
        "url": "https://www.ycombinator.com/companies/cloudglue/jobs/7Rf6hB8-research-engineer",
        "location": "San Francisco, CA, US / Remote (Seattle, WA, US; Los Angeles, CA, US)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Machine learning",
        "salary_range": "$120K - $250K",
        "equity_range": "0.50% - 2.50%",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Torch/PyTorch",
          "Machine Learning",
          "Reinforcement learning (RL)",
          "Natural Language Processing",
          "Computer Vision",
          "Search",
          "Prompt Engineering"
        ]
      }
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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,
    "tags": [
      "Developer Tools",
      "Machine Learning",
      "SaaS",
      "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,
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    "url": "https://www.ycombinator.com/companies/storia-ai",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/storia-ai.json",
    "year_founded": 2023,
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        "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",
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        "body": "**TL;DR:** CodeViz builds a visual map of your codebase that makes it easy to understand and navigate. Software engineers spend 70% their day reading existing code to gather context - we’re fixing that. \n\n**Our Ask:** Try our [VS Code Extension](https://marketplace.visualstudio.com/items?itemName=CodeViz.codeviz#review-details), [tell us](https://calendly.com/liam-codeviz/15min) what you think, or [set up](https://calendly.com/liam-codeviz/15min) CodeViz for your team!\n\n![uploaded image](/media/?type=post&id=83115&key=user_uploads/885544/6ee8d3c7-0363-426c-ac46-c0a861aa4f7e)\n\n---\n\n---\n\n---\n\n—\n\nHi everyone, we’re [Liam](https://www.linkedin.com/in/liam-prevelige/) and [Will](https://www.linkedin.com/in/williamlmccall/), and we’re building CodeViz, the dev tool we wish we had at Tesla. From potato cannons to arbitrage bots, we’ve been hacking projects together since we met at Dartmouth 5 years ago.\n\n### ❗The Problem:\n\nLike most developers, Will and I were frustrated that 70% of our time was spent reading existing code to gather context, instead of actually writing code.\n\n### 🛠️ Our Solution:\n\nOur VS Code extension creates an interactive map of codebases - from high-level system architecture to function calls. Our goal is to give all developers the deep contextual knowledge that’s core to 10x engineers.\n\nEngineers from Amazon, Roblox, and Microsoft are already using CodeViz to quickly understand and navigate code.\n\n![uploaded image](/media/?type=post&id=83115&key=user_uploads/885544/c3dbf88d-250b-4976-a701-375f4883d2cc)\n\nNavigate through the actual flow of your code, rather than file structure.\n\n### Our Ask: Try Codeviz!\n\n* Install [CodeViz](https://marketplace.visualstudio.com/items?itemName=CodeViz.codeviz#review-details) from the VS Code Marketplace and give it a spin in your projects.\n* Schedule a [chat](https://calendly.com/liam-codeviz/15min) to learn about our business and enterprise packages.\n\nIf you hear your friends or co-founders complaining about navigating, organizing, or understanding code, please send them our way!\n\nReach out anytime:\n\n[liam@codeviz.ai](mailto:liam@codeviz.ai) | [will@codeviz.ai](mailto:will@codeviz.ai)\n\n![uploaded image](/media/?type=post&id=83115&key=user_uploads/885544/427fd052-e909-40cc-ba4a-e103353612ac)\n\nWill and I at Dartmouth’s graduation last year",
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        "title": "cmux: the open source terminal built for coding agents",
        "tagline": "Native macOS Ghostty-based terminal with vertical tabs, notifications, and built-in browser",
        "body": "**TL;DR**\n\ncmux is a Ghostty-based terminal with vertical tabs, notifications, and in-app browser, built for multitasking with coding agents.\n\ncmux is trusted by thousands of builders from Nvidia, Google, OpenAI, and more. In two weeks, we’ve gained 3.5k GitHub stars.\n\n<https://github.com/manaflow-ai/cmux>\n\n<https://www.youtube.com/watch?v=i-WxO5YUTOs>\n\n**Hey, we’re Austin and Lawrence.**\n\nThe future is pointing towards an IDE-less world. In fact, the best engineers have already stopped using VS Code and Cursor.\n\nBoris Cherny, the creator of Claude Code, has not opened an IDE since last November. No one knows what the best workflow looks like yet, but it has never been more urgent to experiment with AI or be left behind.\n\nBut our current tools aren’t built for this. If you try running multiple Claude Code or Codex sessions in a standard terminal, you’ll find yourself in the midst of chaos. On the flip side, GUI orchestrators lock you in and lack the flexibility for experimentation.\n\n**That’s why we built cmux: an open-source terminal primitive for exploring the future of agent-driven workflows.**\n\n![uploaded image](/media/?type=post&id=98405&key=user_uploads/760906/db7fb781-3b9c-464d-9363-8f25a7b4aa3c)\n\nWe wanted a lightning-fast native macOS (Swift/AppKit) terminal with features you need for managing fleets of coding agents:\n\n* Vertical tabs\n* Blue rings around panes that need attention\n* Built-in browser\n* Based on Ghostty\n\n![uploaded image](/media/?type=post&id=98405&key=user_uploads/760906/3128b3c6-1fba-4b9c-a287-13ef7c2d04ce)\n\n![uploaded image](/media/?type=post&id=98405&key=user_uploads/760906/0e4d8185-428a-458d-9b92-987a7189f889)\n\n![uploaded image](/media/?type=post&id=98405&key=user_uploads/760906/2d0b0af2-5317-419a-84af-c920874d961d)\n\ncmux also has a built-in CLI that allows coding agents to command cmux’s browser, create new workspaces, and start off other agents in new terminals. AI can use cmux exactly like you would.\\\n\\\n<https://www.youtube.com/watch?v=XKc1cVCFLDQ>\n\n**The zen of cmux**\n\ncmux is not prescriptive about how developers hold their tools. It's a terminal and browser with a CLI, and the rest is up to you.\n\ncmux is a primitive, not a solution. It gives you a terminal, a browser, notifications, workspaces, splits, tabs, and a CLI to control all of it. cmux doesn't force you into an opinionated way to use coding agents. What you build with the primitives is yours.\n\nThe best developers have always built their own tools. Nobody has figured out the best way to work with agents yet, and the teams building closed products definitely haven't either. The developers closest to their own codebases will figure it out first.\n\nGive a million developers composable primitives and they'll collectively find the most efficient workflows faster than any product team could design top-down.\n\ncmux is free, open-source (AGPL), and already trusted by thousands of builders from Nvidia, Google, OpenAI, and more. Developers build or port their own custom harnesses and orchestrators on top of cmux.\n\n<https://github.com/manaflow-ai/cmux>\n\n**Traction**\n\nIn two weeks, cmux grew from zero to 3.5k GitHub stars.\n\n![uploaded image](/media/?type=post&id=98405&key=user_uploads/760906/67e21a8c-3bc8-44e2-b310-9584a238775b)\n\nWe peaked at #2 on Hacker News: <https://news.ycombinator.com/item?id=47079718>\n\n![uploaded image](/media/?type=post&id=98405&key=user_uploads/760906/97569e3c-fdf9-4955-a675-4b64cc0919c2)\n\nOur X launch went viral: <https://x.com/lawrencecchen/status/2026729219154378912>\n\n![uploaded image](/media/?type=post&id=98405&key=user_uploads/760906/829277d1-b53c-4800-9f5c-1f449b2bbe62)\n\nMitchell Hashimoto, the creator of Ghostty and founder of HashiCorp, shouted out cmux on X.\n\n![uploaded image](/media/?type=post&id=98405&key=user_uploads/760906/ad536752-35d4-4ee0-9282-06d3a8feca23)\n\nNick Schrock, the creator of Dagster and GraphQL:\n\n![uploaded image](/media/?type=post&id=98405&key=user_uploads/760906/000699e9-4c69-471c-9096-678bd2ccd121)\n\nEdward Grefenstette, Director of Research at Google DeepMind:\n\n![uploaded image](/media/?type=post&id=98405&key=user_uploads/760906/e9c2b0b5-a3f5-4cee-bf61-87411a167143)\n\nMany Japanese fans:\n\n![uploaded image](/media/?type=post&id=98405&key=user_uploads/760906/4aa84dec-c312-4ad9-af6e-db89184e2f2f)\n\n**How you can help**\n\nStar our GitHub repo: <https://github.com/manaflow-ai/cmux>\n\nTry cmux: [https://www.cmux.com/](https://www.cmux.dev/) \n\nShare cmux with your friends: send feedback to [founders@manaflow.ai](mailto:founders@manaflow.ai).",
        "url": "https://www.ycombinator.com/launches/PbB-cmux-the-open-source-terminal-built-for-coding-agents",
        "votes": 735,
        "created_at": "2026-03-03T17:31:16.700Z"
      },
      {
        "id": 82289,
        "title": "Manaflow - Build and manage your dream AI operations team",
        "tagline": "Automate workflows involving data analysis, API calls, and business actions. ",
        "body": "### **🛎️ TL;DR**\n\n* [**Manaflow**](https://manaflow.ai/) empowers **operation managers** to automate workflows involving data analysis, API calls, and business actions.\n* You can **command Manaflow agents in English** to execute recurring tasks and manage them on a spreadsheet interface. \n* Think of us as an **AI-first Zapier alternative** but with natural language and spreadsheets. \n* **Frustrated with repetitive manual tasks** in your business? We’ll automate them all for you. [**Let’s chat**](https://cal.com/team/manaflow/meeting)**.**\n\n### **🗂️ The Problem: Too much Excel, too much manual stuff, too much repetition**\n\nAre you tired of **juggling countless Excel files and manual workflows for your business**? Do these workflows prevent your business from scaling up?\n\nAfter **conducting over 250 calls**, we've discovered a recurring problem: **small-to-mid-sized businesses (SMBs)** rely heavily on folders of Excel files and third-party apps to **manually execute their day-to-day operations**, which is **time-consuming, error-prone, and a huge bottleneck to scaling**. \n\nFor instance, in freight forwarders, operations include managing client communications, inventory oversight, and coordinating delivery schedules, most of which are done manually. These **manual processes** not only **decelerate business growth** but also **heighten the risk of mistakes**.\n\nToday’s operation managers are blocked by a lack of **technical knowledge,** **customization,** **and** **simplicity** in current workflow automation builders.\n\n### **💡 Introducing MANAFLOW: Automate operations workflows with AI**\n\nWe are building **Manaflow** specifically for **underdog SMBs to scale** like their tech-enabled, big corporation counterparts, transforming manual spreadsheet and software tasks into **automated end-to-end workflows**.\n\nThe ideal way to execute workflows is not for a human to manually operate Excel sheets or interface with different software apps but for a human to **merely click a button**. \n\n**AI can own end-to-end technical workflows** and convert them into features, while **humans can oversee** them, update them as the business evolves, and tackle higher-level automations. Let’s see this in **action**.\n\n### **📕 Building a Basic Workflow on Manaflow**\n\nWe’ll begin by building a fun, basic workflow on Manaflow to **send payment reminders to clients** via email.\n\n[Manaflow Demo: Building Sending Payment Reminders Workflow](https://www.youtube.com/watch?v=TGbJN7pNb30)\n\nNext, we’ll go into more specific examples of potential use cases for business customers.\n\n### **📸 Manaflow Workflow #1: Watermark videos and send them to your clients via Gmail**\n\nOne of our customers uses Manaflow to take in unpolished videos from Google Drive, process them, watermark them with their logo, and then email the final products to their clients — **all in one click of a button**. \n\n[Manaflow Demo: Watermarking Video Workflow](https://www.youtube.com/watch?v=tTTTRrzICVg)\n\nThis has **cut their** **20-hour weekly manual workflow down to 20 minutes**, and Manaflow has become a core part of their operations.\n\n### **🛻 Manaflow Workflow #2: Find and email truckers for your shipment logistics**\n\nAnother customer uses Manaflow to find and email local trucking companies based on the shipment origin and final destination. \n\n[Manaflow Demo: Finding Truckers for Logistics Workflow](https://www.youtube.com/watch?v=9GsBHG3zm_I)\n\nThis has allowed them to gather rate quotations faster for their clients and has **reduced their manual operations by over 50%.**\n\n### **🙌 One more thing: Collaborate with all stakeholders, including us, to build automations**\n\nThere are countless workflow automations that you can build on Manaflow. We understand that people have many different ideas and love working in teams. So, we made **real-time collaboration** so all of you can build and automate workflows together on Manaflow.\n\n![uploaded image](/media/?type=post&id=82289&key=user_uploads/760906/1e1b585b-aa0e-4fa6-abf9-c3774e9bdfba)\n\nPartnering with us, you will also have **24/7 access to Manaflow’s engineering support staff.**\n\n### 👥 **OUR TEAM**\n\n[**Austin Wang**](https://www.linkedin.com/in/austinwang115/): Yale Physics, CS & Econ; Prev. SWE @ Google, NASA JPL, Chess.com, ML @ Datacy\\\n[**Lawrence Chen**](https://www.linkedin.com/in/lawrencecchen/): Berkeley CS; Prev. Founding Eng @ Minion AI, Berkeley RISE Lab\\\n[**Wesley Tjangnaka**](https://www.linkedin.com/in/wesleytjangnaka/): Stanford Math & CS; Prev. Stanford AI Research, ML @ Juniper Networks\n\n![uploaded image](/media/?type=post&id=82289&key=user_uploads/89898/2d6a0806-b347-4d6d-ac7f-cc69dae86325)\n\n**🙏 Our Ask**\n\n**If you are or know any** **operation managers or businesses** **that run on spreadsheets**, **please let us know or schedule a time with us** [**here**](https://cal.com/team/manaflow/meeting). Any intros or shoutouts would be super awesome and greatly appreciated.\n\nWe’d really appreciate a like and subscribe on our [YouTube](https://www.youtube.com/channel/UCAa89_j-TWkrXfk9A3CbASw), a follow on our [Twitter](https://x.com/manaflowai) and [LinkedIn](https://www.linkedin.com/company/manaflow-ai/), and some feedback on our [product](https://manaflow.ai/). \\\n\\\nThank you!",
        "url": "https://www.ycombinator.com/launches/LPF-manaflow-build-and-manage-your-dream-ai-operations-team",
        "votes": 918,
        "created_at": "2024-07-19T22:13:47.678Z"
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    "id": 29728,
    "name": "expand.ai",
    "slug": "expand-ai",
    "former_names": [
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    "website": "https://expand.ai/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Let your agent fetch and crawl with SOTA extraction.",
    "one_liner": "Lossless web data.",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1725734595,
    "tags": [
      "Developer Tools",
      "Infrastructure"
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    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2024",
    "status": "Active",
    "industries": [
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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": "Tim has been working on developer tools for the last 8 years, being founding engineer at [Prisma](https://prisma.io/) and then founding [Stellate](https://stellate.co/).When building AI apps, he found that oftentimes getting the right data was the blocker to get started with the project.That’s why he’s building [expand.ai](http://expand.ai) - to enable anyone to use the web as a data source to power their AI apps."
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    ],
    "url": "https://www.ycombinator.com/companies/expand-ai",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/expand-ai.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/use-expand-ai/",
    "x_url": "https://x.com/getexpandai",
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    "github_url": "https://github.com/expandai",
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    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
    },
    "founders": [
      {
        "user_id": 12878,
        "full_name": "Tim Suchanek",
        "title": "Founder/CEO",
        "founder_bio": "Founder expand.ai",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/tim-suchanek-08219346",
        "x_url": "https://twitter.com/timsuchanek",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/979e8c187da289c0e6acea569cad855a4e310b8f.jpg"
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    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 121522,
        "title": "Expand Fetch: Reading glasses for your AI agent",
        "tagline": "Send a URL. Get accurate Markdown, the hidden JSON and a snapshot you can cite.",
        "body": "Hi everyone! 👋 I'm Tim, founder of Expand, and today we're launching Expand Fetch.\n\n**TL;DR:** Send a URL, get back Markdown written by Iris, our own vision model. It keeps the tables, icons and hidden JSON other tools drop, and every line links back to where it came from. On our benchmark, agents answer 74% of questions from our Markdown. The next best API gets 55%. Live today, $1 per 1,000 fetches.\n\n<https://youtu.be/qQCqpShmrLA>\n\n## **🚨 The problem**\n\nYour agent has an IQ of 500, but fails at basic questions about the web.\n\nWeb Markdown APIs drop icons, break tables and miss the JSON in the page. So your agent answers wrong, with confidence. And you can't tell whether the page didn't load or the conversion dropped it. The workaround is a full browser per page, which is slow and expensive.\n\nWe tried fixing it with heuristics. It's whack-a-mole. The rule that drops a footer deletes a company's address on one page and ships 100,000+ tokens of trash on the next.\n\n## **🚀 Expand Fetch**\n\nOne API call gets you:\n\n* **👁️ Iris:** our vision model sees the rendered page and writes frontier quality Markdown. Tables stay tables. Navigation and footers go to an appendix.\n* **🩻 X-Ray:** finds the useful JSON hidden in the page, like coordinates or flight gates.\n* **🕰️ Wayback Machine:** every fetch is a snapshot you own. Every line links back to its spot on the page.\n* **🔦 Highlights:** ask a question, get only the passages that answer it. Over 95% fewer tokens.\n\nPlus **Crawl** for whole sites and **WebSync** to follow every change.\n\n![uploaded image](/media/?type=post&id=121522&key=user_uploads/12878/bc51849e-4cb3-44e4-9301-fecce93b599f)\n\nOr paste this into your coding agent and it sets itself up:\n\n> Set up <https://expand.ai/start.md>\n\n## **📊 Benchmarks**\n\nExisting Markdown benchmarks assume a page has one main content, like reader mode. The web doesn't work like that. Iris sorts every element into preserve, prune or appendix, and on our validation set it beats Jev on F1, 92.7% to 69.6%.\n\n![uploaded image](/media/?type=post&id=121522&key=user_uploads/12878/b146a886-44d4-45de-bf32-953958a5360c)\n\nThen the test that matters. We built MDBench with our customers: 1,094 questions on 326 hard pages. Expand is also the only API we tested that returns the hidden JSON.\n\n![uploaded image](/media/?type=post&id=121522&key=user_uploads/12878/100dfebd-bfad-4abd-96cb-a4d5afb61b24)\n\n## **👶 About us**\n\nExpand is an applied research lab. We want to make the web queryable like a database, and found we first need to see it. Iris took us a year of sweat and tears. I've spent 10 years in developer tools, as founding engineer at Prisma and founder of Stellate.\n\n## **📢 Ask**\n\nIf you, or anyone you know, has struggled with the quality of web data, including for your own agents, please reach out at [tim@expand.ai](mailto:tim@expand.ai). Send me a page your agent gets wrong, and I'll show you what Expand returns.\n\nTry it at [expand.ai](http://expand.ai) with $10 in free credits, or [join the waitlist](https://expand.ai/blog/announcing-expand-fetch#waitlist) if you want to query the web like a database.",
        "url": "https://www.ycombinator.com/launches/Vc2-expand-fetch-reading-glasses-for-your-ai-agent",
        "votes": 4,
        "created_at": "2026-10-12T00:25:58.796Z"
      }
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    "id": 29734,
    "name": "Vibe",
    "slug": "vibe",
    "former_names": [
      "Focal"
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    "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": [
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      "SaaS",
      "B2B",
      "Web Development",
      "AI"
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2024",
    "status": "Active",
    "industries": [
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      "Engineering, Product and Design"
    ],
    "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/vibe",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/vibe.json",
    "year_founded": 2024,
    "city": "San Francisco",
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        "user_id": 55641,
        "full_name": "Ray Morgan",
        "title": "Founder/CEO",
        "founder_bio": "Ray is the CEO of Vibe, making everyone a software engineer\n\nBefore Vibe, Ray spent 10 years at Stripe leading and scaling the core payments engineering teams (<$10B payments volume to well over $100B a year), launching new products (Stripe Issuing, new payment methods), and worked on Stripe’s enterprise readiness efforts to enable enterprise accounts like Amazon. Prior to Stripe, Ray started a company that got acquired by Ebay and led the frontend engineering team at Zappos.",
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        "linkedin_url": "https://www.linkedin.com/in/raycmorgan/",
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      {
        "user_id": 1937354,
        "full_name": "Katia Bazzi",
        "title": "Founder/CTO",
        "founder_bio": "Katia is the CTO of Vibe\n\nPreviously, Katia was an engineering leader at Stripe -- there, she launched new financial products such as credit cards and banking as a service, processing >$6B per year. Before that, she led engineering teams at a distributed tracing startup (Lightstep) and Eventbrite after graduating from CMU.",
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    "name": "MagiCode",
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    "long_description": "MagiCode is an AI-powered frontend agent that writes, reviews, and rigorously tests code before pushing a PR—helping busy frontend teams offload complex, repetitive tasks from their workload.",
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        "user_id": 1857814,
        "full_name": "Jeff He",
        "title": "Founder/CEO",
        "founder_bio": "Before founding MagiCode, Jeff earned a Master’s degree from Stanford, where he contributed to the Stanford AI Lab, and an undergraduate degree from UC Berkeley, where he was part of the Berkeley AI Research Group (BAIR). He has published four papers on self-driving cars and reinforcement learning in top conferences like NeurIPS and ICRA. Previously, Jeff also worked as an SDE & a quant, where he developed his expertise in AI and machine learning.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jeff-he-99a96b163/",
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      {
        "user_id": 1256805,
        "full_name": "Anirudh Sriram",
        "title": "Founder/CTO",
        "founder_bio": "Before founding MagiCode, I earned a Master’s degree from Stanford University, where I contributed to the Stanford AI Lab and Stanford Vision and Learning Lab. I also hold an undergraduate degree from IIT Madras. I have published six papers on large language models (and NLP in general) in prestigious conferences such as NeurIPS, ACM, and ACL. Prior to MagiCode, I gained extensive experience through my work at Google Research, Microsoft, Walmart Labs, etc.",
        "is_active": true,
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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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        "body": "![uploaded image](/media/?type=post&id=82910&key=user_uploads/1276433/30b5b896-6109-4aa6-8a05-fb9a138f61a8)\n\n### **The backstory**\n\nHi everyone, we’re Carl and Brian, aka the team behind [Thunder Compute.](https://thundercompute.com)\n\n![uploaded image](/media/?type=post&id=82910&key=user_uploads/1276433/07db7c92-f1f2-4356-80f8-9dabf9c2fbcd)\n\nBefore Thunder Compute, [Carl](https://www.linkedin.com/in/cpeterson42) was a Management Consultant at Bain & Company, and [Brian](https://www.linkedin.com/in/brian-model/) was a Quantitative Developer at Citadel Securities. Carl and Brian met at Georgia Tech and have been close friends for over 6 years.\n\n### **Problem**\n\nGPU access sucks. Today’s options are expensive and hard to use. Developers are crowded out of the market by large corporations and can’t get the GPUs they need for reasonable prices. Even if you can afford GPUs, they are scarce and hard to use.\n\n### **Solution**\n\nThunder Compute sells cloud GPUs for the lowest rates on the market and provides a simple interface to access them.\n\nYou can connect in one click through VSCode, without SSH. We have “prototyping” mode, with prices 50% lower than anywhere else, and “production” mode, with higher uptime and multi-GPU nodes.\n\n### **Our offer**\n\nSimple: low-cost, easy GPUs. \\\n\\\nIf you’re looking for a better GPU cloud, join Thunder Compute’s public beta today at [www.thundercompute.com](https://www.thundercompute.com).\\\n\\\nIf you have questions, need technical support, or want to rant about the current state of GPUs, join our discord at [**https://discord.gg/nwuETS9jJK**](https://discord.gg/nwuETS9jJK) or contact us at [**founders@thundercompute.com.**](https://mailto:founders@thundercompute.com/)",
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        "title": "Ember Robotics: Datadog for Robots",
        "tagline": "From prototype to scale, we keep robots running",
        "body": "# **tldr; Fast-track your robotics development**\n\nAt [**Ember**](https://www.emberrobotics.com/), we make it easy for robotics teams to catch and fix issues fast. Our edge-first robot diagnostics platform helps you stay on top of system performance—whether you're prototyping, scaling, or deploying in the field. \\\n\\\nWith instant insights and built-in reliability, we help you move faster, build smarter, and launch with confidence. Ready to try it out? Book a demo [**here**](https://www.emberrobotics.com/) or reach out to us at [**founders@emberrobotics.com**](mailto:founders@emberrobotics.com)!\n\n# **The problem**\n\n1. **No Visibility in Low-Network Zones** – When robots lose connectivity, **cloud-based diagnostics fail**, making it hard to track performance or troubleshoot failures in real time.\n2. **Slow, Costly Root-Cause Analysis** – Debugging is painful, with teams sifting through **dense logs and complex graphs** instead of getting clear, actionable insights.\n3. **Inefficient DIY Monitoring Stacks** – Robotics teams **waste months building custom diagnostics** because existing tools don’t work for their needs.\n4. **Reactive Debugging Leads to System Failures** – Without **proactive monitoring**, small issues snowball into major downtime and expensive repairs.\n\n# **Our solution**\n\n### **🌐 Works Offline**\n\n* **Edge-first diagnostics** to store and analyze data even when the network is down.\n* **Smart caching & prioritized sync** ensure no critical insights are lost.\n\n### **🔍 Faster, Clearer Troubleshooting**\n\n* **Instant anomaly detection** surfaces failures before they escalate.\n* **Real-time sensor & system health analytics** (cameras, IMU, LiDAR, CPU, memory).\n* No more digging through logs—just **straightforward insights** when you need them.\n\n### **⚡ Seamless Integrations**\n\n* **Built-in Sensor Plugins & Robotics Middleware Support** – Off-the-shelf support for **Intel® RealSense™, Luxonis®, Orbbec®**, and more. Easy integrations for **ROS and e-Cal** —no extra setup required.\n* **Deploy in minutes with standard Linux packages**—skip the custom integrations.\n* **API-first design** lets you access diagnostics effortlessly and extend with your own **custom metrics plugins**.\n\n### **📈 Scale up to Fleet-Wide Monitoring**\n\n* Grow reliably from 1 to 10,000 robots with **consistent, structured data collection**.\n* Identify **trends & patterns across groups of sensors and devices**.\n* Works in **low-bandwidth environments**, ensuring continuous insights.\n\n# **Check it out**\n\n![uploaded image](/media/?type=post&id=87515&key=user_uploads/1932951/8cd43030-d313-4ade-af0d-f7fe7197ac0d)\n\n[**\\[dashboard demo\\]**](https://www.tella.tv/video/ember-robotics-dashboard-gvog)\n\n[**\\[real-time diagnostics demo\\]**](https://www.tella.tv/video/ember-real-time-diagnostics-walk-through-dcdf)\n\n### **Meet the team**\n\nWe built software at Simbe Robotics and Tesla Autopilot to optimize robot reliability—covering real-time diagnostics, sensor calibration, field service alerts, and low-latency data pipelines. From early R&D to fleet-scale deployment, we ensure robots stay operational, efficient, and ready for any environment.\n\n![uploaded image](/media/?type=post&id=87515&key=user_uploads/1932951/b82857af-566f-465a-8212-74965d060e03)\n\n# \n\n# **Our ask**\n\nStruggling with blind spots in your fleet? Drowning in logs while root-causing issues? **Ember streamlines troubleshooting and ensures reliable performance—no matter the network conditions.**\n\n🔹 **Book a demo** → [**here**](https://www.emberrobotics.com/)\n\n🔹 **Know someone working with robots, drones, or multi-camera systems?** Send them our way!\n\n🔹 **Just love talking robots?** Same—let’s chat!\\\n\\\nLet’s make **robot monitoring effortless.** Hit us up at [**founders@emberrobotics.com**](mailto:founders@emberrobotics.com)! 🚀",
        "url": "https://www.ycombinator.com/launches/MlX-ember-robotics-datadog-for-robots",
        "votes": 25,
        "created_at": "2025-02-07T22:07:48.510Z"
      },
      {
        "id": 82673,
        "title": "Ember Robotics: Camera diagnostics for robots",
        "tagline": "Reducing vision failures from the source",
        "body": "# **tldr; Got camera problems? We’ve got solutions.**\n\n[Ember](https://www.emberrobotics.com/) builds software to monitor and resolve robot camera issues - so you can reduce vision failures from the source.\n\nIs robot camera reliability or degraded vision driving you nuts? Book a demo [here](https://www.emberrobotics.com/) or reach out to us at [founders@emberrobotics.com](mailto:founders@emberrobotics.com)!\n\n### **The problem**\n\nWe’ve spent years working on vision systems for autonomous robots and found similar issues everywhere:\n\n![uploaded image](/media/?type=post&id=82673&key=user_uploads/1932951/335dd4a4-e0b6-4c6b-bb64-a4c9c0c60f7f)\n\n☐ Robotics companies work on lean teams that have to do lots of things super fast - **hardware reliability is often secondary to core product features**\n\n☐ **Camera failures cause large fires** because they float up the stack to critically damage perception, controls, and safety\n\n☐ **Digging through layers of software / hardware to figure out what went wrong is painful** (ex. sometimes you spend hours goose-chasing a “perception issue” just to find a loose cable)\n\n### **Our solution**\n\n![uploaded image](/media/?type=post&id=82673&key=user_uploads/1932951/9c181ef2-e04a-498d-a839-35bfa75fd1dc)\n\n**A camera diagnostics framework that ties in real-time data, logs, and reports to contextualize your robot’s vision health.** Support the full life-cycle of your robot with features like:\n\n✅ Out-of-the-box tracking for common issues (disconnection, frame drops, time sync)\n\n💬 Automated suggestions for error resolution\n\n⏱️ Real-time alerts\n\n🖌️ Image quality analysis tools to optimize computer vision\n\n📈 Historical data analysis for predictive maintenance\n\n### **Try it out: Plug-and-play camera testing**\n\nBench-test cameras or diagnose issues in the field with one easy tool. **Fill a config file, launch our service, and get fast metrics on camera health.**\\\n[demo](https://www.youtube.com/watch?v=OnoCmdVEzzM)\n\nCurrently we support Intel® RealSense™ D400 cameras and ROS - more cameras and pub-sub models coming soon!\n\n### **Meet the team**\n\n![uploaded image](/media/?type=post&id=82673&key=user_uploads/1932951/cc554985-1fa2-4bd8-9d16-96609bb82645)\n\nHi, we are [Shivani](http://linkedin.com/in/shivanicm) & [Ritika](https://www.linkedin.com/in/ritikashrivastava/)! We built software at Tesla Autopilot to optimize camera performance for autonomy. We’ve covered the camera stack end-to-end (low-latency image capture, real-time camera monitoring, online camera calibration, multi-trip reconstruction, and SLAM) - we’re passionate about helping robots see!\n\n### **Our ask**\n\nIs robot camera reliability or degraded vision driving you nuts? Book a demo [here](https://www.emberrobotics.com/) or reach out to us at [founders@emberrobotics.com](mailto:founders@emberrobotics.com)!\n\nIf you know anyone working on robots, drones, or other multi-camera systems (surveillance, manufacturing, etc.) we would love a warm intro.\n\nAnd for those who are just generally robot-curious - always happy to chat!",
        "url": "https://www.ycombinator.com/launches/LVR-ember-robotics-camera-diagnostics-for-robots",
        "votes": 101,
        "created_at": "2024-08-02T13:50:39.909Z"
      }
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    "name": "Pinnacle",
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    "website": "https://pinnacle.sh/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Pinnacle is an API for RCS, the new standard for SMS for app-like text messages.",
    "one_liner": "API & SDK for RCS (the next-generation of texting)",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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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/pinnacle",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/pinnacle.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/trypinnacle/",
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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": 1439340,
        "full_name": "Sean Roades",
        "title": "Founder/CTO",
        "founder_bio": "Sean is co-founder of Pinnacle (S24). After graduating from Harvard College where he studied computer science and econometrics, Sean worked at YouTube where he built machine learning models that handled billions of dollars of ad spend.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/sr19943/",
        "x_url": "https://twitter.com/SeanRoades",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9450ce473a71ddcfb1f7e3216fb20327c9bdf7bf.jpg"
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      {
        "user_id": 854039,
        "full_name": "Ivan Zhang",
        "title": "Founder",
        "founder_bio": "Ivan is the cofounder and CEO of Pinnacle.\n\n\nHe studied Computer Science and Statistics at Harvard College and previously worked as a software engineer at Amazon where he built internal tools. Most recently, he was a software engineer at General Catalyst’s Customer Value Fund where he built an open-source data library with over 25,000 downloads.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/aivanzhang/",
        "x_url": "https://twitter.com/aivanzhang",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/56ebc3ff505aec72cf1a59be28d391a44f7b7e51.jpg"
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      {
        "id": 84168,
        "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"
      }
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    "id": 29782,
    "name": "Laminar",
    "slug": "laminar",
    "former_names": [
      "Laminar AI"
    ],
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    "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": [
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      "Engineering, Product and Design"
    ],
    "regions": [
      "United Kingdom",
      "Europe"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
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    "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/",
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    "github_url": "https://github.com/lmnr-ai/lmnr",
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    "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",
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        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c56af6f86306ce69d00244d2229612165fb00abc.jpg"
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      {
        "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"
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    "id": 29797,
    "name": "Haystack",
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    "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": [
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      "B2B",
      "Productivity",
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    "batch": "Summer 2024",
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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/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",
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    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/988853e97230d398301aa8250ff990964f2f4620.png",
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    "primary_partner": {
      "name": "David Lieb",
      "url": "https://www.ycombinator.com/people/david-lieb"
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    "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/",
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        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/472b417ade90b938dedd2e61598178f0fd4ab91c.jpg"
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      {
        "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/",
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        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f833acc97764c214609c48402678478634c1e8b4.jpg"
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    "jobs": [],
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      {
        "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"
      }
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    "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",
    "launched_at": 1716301435,
    "tags": [
      "Developer Tools",
      "SaaS",
      "Design Tools",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "Argentina",
      "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/heroui",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/heroui.json",
    "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",
    "app_video_url": null,
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    "company_photos": [],
    "primary_partner": {
      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
    },
    "founders": [
      {
        "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": 29812,
    "name": "ZeroPath",
    "slug": "zeropath",
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    "website": "https://zeropath.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "ZeroPath is a developer tool that autonomously detects, verifies, and submits fixes for vulnerabilities in your code. Engineers can use ZeroPath to find security problems that they might only otherwise catch in pentests or from bug bounty researchers.",
    "one_liner": "Automatically find and fix your software vulnerabilities",
    "team_size": 10,
    "industry": "B2B",
    "subindustry": "B2B -> Security",
    "launched_at": 1718222641,
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      "B2B",
      "Security",
      "Cybersecurity",
      "AI"
    ],
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    "isHiring": false,
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    "batch": "Summer 2024",
    "status": "Active",
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    "regions": [
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      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
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    "url": "https://www.ycombinator.com/companies/zeropath",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/zeropath.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/zeropathai",
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      "name": "David Lieb",
      "url": "https://www.ycombinator.com/people/david-lieb"
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    "founders": [
      {
        "user_id": 2021206,
        "full_name": "Dean Valentine",
        "title": "Founder",
        "founder_bio": "ZeroPath founder",
        "is_active": true,
        "linkedin_url": "",
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        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d4aa118f45ea9f67b3ca5bb4aa5d886701b03b48.jpg"
      },
      {
        "user_id": 2049348,
        "full_name": "Raphael Karger",
        "title": "Founder",
        "founder_bio": "CTO at ZeroPath. Former Google Security Engineer and BishopFox Consultant.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/raphael-karger/",
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        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/db088b311094bb1d324eed9d1fde67f15d0cd2f6.jpg"
      },
      {
        "user_id": 2021191,
        "full_name": "Etienne Lunetta",
        "title": "Founder",
        "founder_bio": "COO at ZeroPath. Former Co-Founder at Mevlink, acquired by bloXroute Labs in 2023.",
        "is_active": true,
        "linkedin_url": "",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/69f8b695e026ab2db3939b185d23a01ceef56eb8.jpg"
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    ],
    "jobs": [],
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    "launches": [
      {
        "id": 82258,
        "title": "🛡️ ZeroPath - Autonomous vulnerability patching",
        "tagline": "Detect and fix your web application's exploitable security issues without config.",
        "body": "📝 TL;DR: [ZeroPath](https://zeropath.com/) is a GitHub app that detects, verifies, and issues pull requests for security vulnerabilities in your code.\n\n![uploaded image](/media/?type=post&id=82258&key=user_uploads/2021206/183871ce-a1b3-4db9-a320-ce73defc63c3)\n\n### 💡 Why We Built This:\n\nAs security engineers and developers, we've seen firsthand how challenging it is for businesses to secure their products. Existing Static Application Security Testing (SAST) tools overwhelm teams with false positives and fail to remediate the real vulnerabilities they do find. We built ZeroPath to allow fast-moving teams to write secure code without having to configure or review a scan dashboard.\n\n![uploaded image](/media/?type=post&id=82258&key=user_uploads/2021206/9f2ff51d-2c6b-4ad5-b7c3-4c48e26fc0e9)\n\n### 🛠 How It Works:\n\n1. Executes regular vulnerability scans of your source code\n2. Integrates with GitHub to scan pull requests for vulnerabilities\n3. Uses advanced LLMs to significantly reduce false positives\n4. Generates patches for vulnerabilities identified\n5. Automatically issues pull requests to patch them\n\n### 💪 Why ZeroPath:\n\n* Integrates with your existing SAST - **removes** **85% of false positives**\n* Reduces vulnerability remediation time by up to **90%**\n* Enables natural language modification of patches, just tag @zeropath-ai in PRs (including your own!)\n* Supports complex, multi-file changes seamlessly\n* Prevents SAST vendor lock-in\n\n### 👥 Our Team:\n\n* [Nathan](https://linkedin.com/in/nathan-hrncirik): Ex-Tesla Red Team Engineer, $100k+ in bug bounties\n* [Raphael](https://linkedin.com/in/raphael-karger): Ex-Google Security Engineer, 12 security researcher hall of fames\n* [Dean](https://www.linkedin.com/in/dean-valentine-3b7583313/) & [Etienne](https://www.linkedin.com/in/etienne-lunetta-574065313/): Founders of Mevlink (acquired by Bloxroute in 2023)\n\n## 💰 YC Launch Deal: 50% off for 12 months\n\n* $20/month per contributing developer (reg. $40)\n* Use code LAUNCHYC at checkout, **valid until 8/15**\n\n### 🙏 How You Can Help:\n\nWe're eager for your insights on our product, feature ideas, and security needs - whether through trying our GitHub app, scheduling a meeting, or sharing feedback.\n\n* [Install our GitHub app](https://zeropath.com/)\n* [Schedule a meeting to discuss your application security needs](https://cal.com/zeropath/30min)\n* [Share your feedback](mailto:hello@zeropath.com)\n\n### 🚀 Get started in 30 seconds: <https://github.com/apps/zeropath-ai/installations/new>\n\n📅 Want to learn more? Schedule a demo: <https://cal.com/zeropath/30min>\n\n![uploaded image](/media/?type=post&id=82258&key=user_uploads/2021206/c947eed7-8cdb-43e0-b330-0c5e36c86ef5)\n\n",
        "url": "https://www.ycombinator.com/launches/LOk-zeropath-autonomous-vulnerability-patching",
        "votes": 47,
        "created_at": "2024-07-18T18:38:13.935Z"
      }
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    "id": 29835,
    "name": "Voker",
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    "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.",
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    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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    "city": "Los Angeles",
    "country": "US",
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        "full_name": "Tyler Postle",
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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",
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    "name": "Void",
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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.",
    "one_liner": "The open source Cursor alternative",
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        "linkedin_url": "https://linkedin.com/in/andrew-pareles",
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        "full_name": "Mathew Pareles",
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      {
        "id": 84053,
        "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",
        "votes": 80,
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    "website": "https://www.freestyle.sh",
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    "long_description": "Freestyle builds the most powerful VMs for AI Agents. \r\n\r\n- **Instant Startup**: Freestyle VMs provision in milliseconds, with p99s under 400ms.\r\n- **Persistence**: Freestyle VMs can run forever, they can be hibernated with their exact memory in place and come back to life weeks later instantly, in that exact state.\r\n- **Powerful**: Freestyle VMs go up to 64GB of RAM for public tiers and much further for enterprise. Freestyle does high quality hardware virtualization supporting nested virtualization, FUSE, eBPF, full Linux networking and more. If it can run in an EC2, it can run in a Freestyle VM.\r\n- **Cheaply Snapshottable and Branchable**: Freestyle VMs are instantly and cheaply snapshottable (sub 1ms interruption, sub 50ms to snapshot ready). These snapshots can be used to create new VMs in the exact state of the original VM (memory and disk). This enables powerful workflows like branching, cloning, and rapid recovery from failures.\r\n\r\n",
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    "url": "https://www.ycombinator.com/companies/freestyle",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/freestyle.json",
    "year_founded": 2024,
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        "full_name": "Benjamin Swerdlow",
        "title": "Founder/CEO",
        "founder_bio": "I learned to code in elementary school.\n\nIn high school I served as a code owner and technical lead for the World Health Organization COVID-19 App Collective Team.\n\nI did a year of college, then took a job as a consultant for Apple. In 3 months I became a senior. \n\nI left Apple to found Freestyle. ",
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        "linkedin_url": "https://www.linkedin.com/in/benswerdlow/",
        "x_url": "https://x.com/benswerd",
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      {
        "user_id": 1860855,
        "full_name": "Jacob Zwang",
        "title": "Founder/CTO",
        "founder_bio": "I dropped out of college and became an Apple senior full-stack engineer in Conversational Engineering at 19. During the year and a half I worked there, I delivered multiple projects to production at scale.\n\nI love building products that inspire and delight customers, but I'm frequently frustrated by poor back-end developer tools. My co-founder and I are building a new cloud and backend workflow so that we and others can build exceptional software in a fraction of the time.",
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      {
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        "title": "Freestyle: A new way to build fullstack TypeScript apps",
        "tagline": "Empowering TypeScript developers to build with TypeScript",
        "body": "Today, most new apps are written with Fullstack TypeScript, but the tooling around them is still built as though the frontend and backend are separate codebases. We built an open source framework, runtime, and cloud that acknowledges this and removes these unnecessary layers from the development process.\n\n**What?**\n\nAny JavaScript class can be marked as [@cloudstate](https://github.com/freestyle-sh/cloudstate), and:\n\n1. The data in it is now persisted. You query the data with regular JavaScript.\n2. The methods on it can now be called from the front end. No Express/API Routes/tRPC needed!\n\n**Coolest Side Effect:** By building our tooling around Fullstack TypeScript, we enable **full-stack feature packages,** a way for JavaScript developers to package any feature they build and share it in a way that it can be embedded in other projects. Think **npm install mui**, except it’s **npm install chat**, or **npm install auth**. Imagine a world where every third-party SaaS provider today can be an open source package that runs in your application.\n\n**Our Ask:**\n\n**Build with us!** Contribute to our [Open Source Repository,](https://github.com/freestyle-sh/cloudstate) or try [deploying an app with us](https://docs.freestyle.dev)!\n\n![uploaded image](/media/?type=post&id=83627&key=user_uploads/89898/0a2412f8-6b6e-4906-9d8f-256badd8b332)\n\n",
        "url": "https://www.ycombinator.com/launches/Lkp-freestyle-a-new-way-to-build-fullstack-typescript-apps",
        "votes": 22,
        "created_at": "2024-08-30T19:44:46.817Z"
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      {
        "id": 81748,
        "title": "Freestyle: TypeScript for EVERYTHING",
        "tagline": "A fundamental shift in how we approach web development",
        "body": "# **TLDR; You can use TypeScript for EVERYTHING**\n\n[**Freestyle**](https://www.freestyle.sh) is a fundamental shift in how we approach web development. With Freestyle, you write your entire application—frontend and backend—in TypeScript. No context switching. No mental gymnastics. Just pure, consistent TypeScript throughout.\\\n\\\nRight now, building an application has a ton of disjointed layers. Imagine you’re writing a book in English for English readers. Now, imagine being told that all the connecting words—the “ands,” “buts,” and “ors”—must be written in Latin. Sounds absurd, right? Yet, this is often what web development feels like: you write your frontend in one language, only to switch to another for the backend, another for your database, and yet another to let your app connect to others.\n\n![alt](https://blog.freestyle.dev/images/blogs/multiplayer-infinite-craft/meme-backend-frontend.png)\n\nDuring our work for Apple, we lost hundreds of hours trying to integrate different layers and teams together to make our application run. That time should’ve been spent on features, but instead was spent on stitching features together. We created [Freestyle](https://www.freestyle.sh) not as a new stitching tool but as a way for whole organizations to not need those tools and instead function as a single unit.\n\nWhen you use Freestyle, you write your frontend and backend in JavaScript. Then, when you wanna call functions from your backend on your frontend, you just use them — no more dealing with REST APIs. When you want to store data, you just mark your JavaScript as [@cloudstate](https://docs.freestyle.dev/guides/cloudstate/) and when you’re ready to deploy, you run **_npx freestyle deploy_** — and in one command you’re up and running.\n\nNo more SQL, no MongoDB, no Firebase, no GraphQL or REST, or anything else taking time away from building features. With Freestyle, all you need is TypeScript.\n\n### Ready to try it? [**Sign up for a demo here**](https://www.freestyle.sh/join), or [**CHECK OUT THE DOCS HERE**](https://docs.freestyle.dev/getting-started/astro)",
        "url": "https://www.ycombinator.com/launches/LGW-freestyle-typescript-for-everything",
        "votes": 87,
        "created_at": "2024-06-25T22:12:58.661Z"
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    "id": 29989,
    "name": "Conductor",
    "slug": "conductor",
    "former_names": [
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      "Chorus"
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    "website": "https://conductor.build",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Run parallel agents in isolated workspaces. See at a glance what they’re working on, then review and merge their changes. ",
    "one_liner": "Run a team of coding agents on your Mac",
    "team_size": 8,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1725301012,
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    "regions": [
      "United States of America",
      "America / Canada"
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    "stage": "Growth",
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    "url": "https://www.ycombinator.com/companies/conductor",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/conductor.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/meltylabs",
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    "primary_partner": {
      "name": "Aaron Epstein",
      "url": "https://www.ycombinator.com/people/aaron-epstein"
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        "user_id": 331436,
        "full_name": "Charlie Holtz",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder & CEO at Conductor\n\nPreviously led growth at Replicate, where I built apps with millions of users. Before that I was a quantitative dev at a team at Point72.\n\nI studied cognitive neuroscience at Brown, where I also played Ultimate Frisbee (and met my co-founder, Jackson).",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/charlieholtz",
        "x_url": "https://x.com/charlieholtz",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0832de4ad456e90d50a49e9108006d6efd4c55c5.jpg"
      },
      {
        "user_id": 229410,
        "full_name": "Jackson de Campos",
        "title": "Founder",
        "founder_bio": "Conductor lets you run a team of coding agents on your Mac. We’re building the human interface to AI organizations.",
        "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",
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      },
      {
        "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": []
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    ],
    "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"
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    "one_liner": "The Developer tool for Designers",
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    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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    "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,
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    "github_url": "https://github.com/onlook-dev",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/4c023f9010fb3a7f3e550c56a9283c477e6ca096.png",
    "app_video_url": null,
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    "company_photos": [],
    "primary_partner": {
      "name": "Aaron Epstein",
      "url": "https://www.ycombinator.com/people/aaron-epstein"
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    "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": [
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          "PostgreSQL",
          "React",
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    "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"
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  {
    "id": 30028,
    "name": "Gait",
    "slug": "gait",
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    "website": "https://getgait.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Ever been confused by a block of AI-generated code? Gait is a Cursor and VS Code extension that will let you view the prompt that generated code. Continue off of your coworker's conversations, view analytics on your AI codegen use, and more!",
    "one_liner": "Building Dev Infra for AI Software Engineers",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1728969633,
    "tags": [
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    "isHiring": false,
    "nonprofit": false,
    "batch": "Fall 2024",
    "status": "Inactive",
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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 over the summer while interning together at Jane Street! "
      },
      {
        "question": "What is your long-term vision? If you truly succeed, what will be different about the world?",
        "answer": "In a future with gait, AI-coding will be a multiplayer experience"
      }
    ],
    "url": "https://www.ycombinator.com/companies/gait",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/gait.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/gaitinc/",
    "x_url": "https://twitter.com/getgait",
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    "github_url": "https://github.com/gait-ai",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/7dd4a0ac111eef37a235327e872f43f243700db2.png",
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    "primary_partner": {
      "name": "Pete Koomen",
      "url": "https://www.ycombinator.com/people/pete-koomen"
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    "founders": [
      {
        "user_id": 2250609,
        "full_name": "Alex Hsia",
        "title": "Founder",
        "founder_bio": "Former Dev at Jane Street, Mercury, and CMU CS. Building better devtools to connect developers and AI codegen ",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/ahsia/",
        "x_url": "https://twitter.com/AlexYHsia",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d804a117dac0c081e88a5ca5692a7727bc00f06c.jpg"
      },
      {
        "user_id": 887567,
        "full_name": "Kyle Li",
        "title": "Founder",
        "founder_bio": "Former dev at Jane Street, Stripe, and Columbia CS. Building better tools to connect developers and AI codegen.",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/kyleli626/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/654aef32533998157d4b99b87b1ab59bfea22f1e.jpg"
      }
    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 84753,
        "title": "gait - The open-source collaboration layer for AI coding assistants",
        "tagline": "Share AI codegen chats, continue off of coworker's conversations, and view analytics on AI codegen use.",
        "body": "# **TL;DR**\n\nGait is the open-source collaboration layer for AI codegen. With gait, developers can view the prompts that generated a piece of code, continue off of coworker's conversations, and view analytics on AI codegen use. Watch our demo [here](https://youtu.be/GcQMSbYBS28) (1:35)\n\n# **The Problems**\n\nAI codegen tools are built for individuals, not teams, and code is read more than it is written. Increasingly, understanding and editing become the limiting factors in a team’s velocity, not generation.\n\n🧐 AI-generated code is hard to understand\n\n* We use Cursor to ship quickly, but AI diffs are often destructive, large, and opaque. **Prompts serve as automatic documentation.**\n\n📈 It’s hard to understand AI’s impact on your codebase\n\n* gait is the first layer of observability, giving oversight into your and your team’s use of AI and its impact on productivity.\n\n# **Our Solution**\n\n**Code annotations** - Have you ever been confused by a block of AI-generated code? Hover over any piece of AI-generated code to see the prompts that created it. It’s like a better git blame. Coming soon: Github integration.\n\n![uploaded image](/media/?type=post&id=84753&key=user_uploads/2250609/9c4f6b1e-7e49-46bb-9d80-f1adcd4e2101)\n\n**Analytics on your AI Codegen -** Use gait to analyse and understand your AI codegen usage. Find out your stats here: <https://getgait.com/getting-started>\n\n![uploaded image](/media/?type=post&id=84753&key=user_uploads/2250609/3ef7f787-3fc8-4d90-b605-057da669ed7e)\n\n**Manage chats like diffs** - choose which chats you’d like to include with git-like semantics. Stage and unstage chats, and view the chats associated with a commit or a PR. \n\n![uploaded image](/media/?type=post&id=84753&key=user_uploads/2250609/05602727-387c-4be5-b162-e336ebdec8fb)\n\n# **Our vision**\n\nAI coding assistants are single-player right now and focus only on generating new code. **AI coding tools produce flashy demos and v0s but are not as helpful for coding in production**. We want to improve collaboration and the entire software lifecycle: not just generating code but also reviewing and editing it. \n\nWe also want to redefine the code repository - what would your repo look like if it were designed for AI? We think this means incorporating all the context AI needs to make edits. This includes your prompts right now, but imagine your SWE agent making edits with automatic access to design docs, Jira tickets, and API specs. \n\n# **The Team**\n\nHi everyone! We’re [Alex](https://www.linkedin.com/in/ahsia/) and [Kyle](https://www.linkedin.com/in/kyleli626/), the cofounders of gait.\n\nWe’re CMU and Columbia dropouts who met this summer while working at Jane Street. We’ve also worked at Stripe (Kyle) and Mercury (Alex). \n\nKyle’s looking for a squash partner, and you can find Alex at the 3rd Street Boxing Gym.  \n\n![uploaded image](/media/?type=post&id=84753&key=user_uploads/2250609/9d203bd8-4685-431f-af13-31a9c6adec53)\n\n# **Our ask**\n\n**Try us out!** \n\nSearch “gait” in the extension marketplace. Click install.\n\nStart coding, and gait will capture your chats automatically!\n\n**Keep in touch!** \n\nIf you’re building a coding assistant or AI agent, we’d love to integrate with you. Please reach out! \n\nIf you manage a team of engineers and think this could be helpful, let’s talk! If you have any questions or feedback or want to just talk shop, we’d love to hear from you.\n\nFor more information: [getgait.com](https://getgait.com)\n\nEmail us at [founders@getgait.com](mailto:founders@getgait.com). \n\nJoin our discord: <https://discord.gg/yKvt3mWyM4>\n\nContribute to gait: <https://github.com/gait-ai/gait>",
        "url": "https://www.ycombinator.com/launches/M2z-gait-the-open-source-collaboration-layer-for-ai-coding-assistants",
        "votes": 17,
        "created_at": "2024-10-15T07:42:04.586Z"
      }
    ]
  },
  {
    "id": 30041,
    "name": "Revyl",
    "slug": "revyl",
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/1eca61dd3b32e7b0f7174161cd567ec823504e49.png",
    "website": "https://www.revyl.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Revyl is the mobile development platform for agents, developers, product, and design. It brings development, build infrastructure, verification, and application intelligence together in one platform, giving teams and agents a shared source of truth for every mobile application.\r\n\r\nTeams can build and run mobile applications in the cloud, understand how their applications work, collaborate across functions, and verify changes against the running app. AI agents gain the context and runtime they need to move beyond simply generating code and understand whether their work actually works.\r\n\r\nBy connecting the people and agents building software to the application itself, Revyl helps teams move faster, collaborate more effectively, and build mobile with confidence.",
    "one_liner": "The Mobile Development Platform",
    "team_size": 16,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1729643205,
    "tags": [
      "Developer Tools",
      "B2B",
      "Infrastructure",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Fall 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Infrastructure"
    ],
    "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/revyl",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/revyl.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/revylai/",
    "x_url": "https://x.com/tryrevyl",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/RevylAI/",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/1eca61dd3b32e7b0f7174161cd567ec823504e49.png",
    "app_video_url": null,
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    "company_photos": [],
    "primary_partner": {
      "name": "Andrew Miklas",
      "url": "https://www.ycombinator.com/people/andrew-miklas"
    },
    "founders": [
      {
        "user_id": 1321343,
        "full_name": "Landseer Enga",
        "title": "Founder/CEO",
        "founder_bio": "Building the mobile source of truth @ Revyl",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/landseerenga",
        "x_url": "https://x.com/landseerenga",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/610a94112586436ed1f68e60566a57df17956a1a.jpg"
      },
      {
        "user_id": 1432741,
        "full_name": "Anam Hira",
        "title": "Founder/CTO",
        "founder_bio": "building proactive observability - catching bugs before they reach production @ Revyl. \n\n\nex Uber AI - dragoncrawl team \n\n\nUBC cs + stat\n\n\n\n",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/anam-h-5b37a2125",
        "x_url": "https://x.com/anamhira",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9f711adc18ebc09fe193cac71ac8fd0504054be3.jpg"
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    ],
    "jobs": [
      {
        "id": 93254,
        "title": "Engineering Intern",
        "url": "https://www.ycombinator.com/companies/revyl/jobs/SduBVhc-engineering-intern",
        "location": "San Francisco, CA, US",
        "type": "Internship",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$5K - $10K / monthly",
        "equity_range": "",
        "experience": null,
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 104528,
        "title": "GTM Intern",
        "url": "https://www.ycombinator.com/companies/revyl/jobs/d5wDFIK-gtm-intern",
        "location": "San Francisco, CA, US",
        "type": "Internship",
        "role": "Marketing",
        "role_type": null,
        "salary_range": "$5K - $10K / monthly",
        "equity_range": "",
        "experience": null,
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 105186,
        "title": "Staff Infrastructure Engineer — Device Cloud",
        "url": "https://www.ycombinator.com/companies/revyl/jobs/7csBGxt-staff-infrastructure-engineer-device-cloud",
        "location": "San Francisco, CA, US / Remote (US)",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Devops",
        "salary_range": "$150K - $250K",
        "equity_range": "",
        "experience": "6+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Amazon Web Services (AWS)",
          "Android",
          "Go",
          "Google Cloud",
          "iOS",
          "Kubernetes",
          "MacOS",
          "AI Agents"
        ]
      },
      {
        "id": 106901,
        "title": "Software Engineer",
        "url": "https://www.ycombinator.com/companies/revyl/jobs/E3sb54p-software-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$125K - $200K",
        "equity_range": "",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
        "skills": []
      }
    ],
    "news": [],
    "launches": [
      {
        "id": 85015,
        "title": "Revyl - Proactive observability",
        "tagline": "Automatically catch and triage bugs before they reach production.",
        "body": "# **TL;DR:**\n\n[Revyl](https://www.revyl.ai/) creates resilient end-to-end tests linked to telemetry traces to catch and triage bugs before they reach production.\\\n<https://www.youtube.com/watch?v=Zy7yXTomh7M&ab_channel=AnamHira>\n\n# **Problem:**\n\n* E2E tests frequently break due to UI changes\n* Finding the root cause of a bug can be extremely time-consuming\n* Bugs in production cause revenue loss and erode customer trust\n* Testing practices are fragmented across web and mobile\n\n![uploaded image](/media/?type=post&id=85015&key=user_uploads/1321343/0b6d5568-fd23-4cd7-8d5f-1feca7fc1d57)\n\n# **Solution:**\n\nRevyl was developed to simplify your QA pipeline. Provide us with your user flows, and we'll handle the rest.\n\nAt its core, Revyl uses resilient end-to-end tests connected to telemetry traces to enable companies to catch and triage bugs before they reach production. Revyl supports tests across Web, iOS and Android.\n\nThis approach:\n\n1. Catches bugs across your whole tech stack\n2. Prevents bugs from reaching production\n3. Accelerates triaging by pinpointing UI and/or microservice failures\n4. Cuts test maintenance to near zero\n\n![uploaded image](/media/?type=post&id=85015&key=user_uploads/1321343/07c6f0c2-6d2f-4cc2-882c-edd303380eb4)\n\n# **Why Us?:**\n\n* [**@Anam Hira**](https://linkedin.com/in/anam-h-5b37a2125): Built [**DragonCrawl**](https://www.uber.com/en-CA/blog/generative-ai-for-high-quality-mobile-testing/), an LLM-based mobile testing framework, while working as a machine learning engineer at Uber. Dragoncrawl saved $25M in 4 months, detecting 11 P0 incidents.\n* [**@Landseer Enga**](https://linkedin.com/in/landseerenga): Experienced in growth-stage startups (PM/Engineer), did some web scraping for PE firms.\n\n# **Our Ask:**\n\n1. [**Book a meeting**](https://cal.com/landseer-enga/book-a-demo) or email us at [founders@revyl.ai](mailto:founders@revyl.ai) if you struggle with testing and want to start pushing to prod on Fridays.\n2. If you know anyone on QA/Observability teams we would love to talk to them!\n\n![uploaded image](/media/?type=post&id=85015&key=user_uploads/1321343/d2cbf495-3460-4f97-98e8-6ca8154ef8b8)\n\n",
        "url": "https://www.ycombinator.com/launches/M7D-revyl-proactive-observability",
        "votes": 122,
        "created_at": "2024-10-24T13:35:15.397Z"
      }
    ]
  },
  {
    "id": 30043,
    "name": "Vespper",
    "slug": "vespper",
    "former_names": [
      "Merlinn"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/8071a4dd821b17c48fe53b21be58c8dd37534c31.png",
    "website": "https://vespper.com/?utm_source=ycombinator.com",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "The best DOCX MCP for agents. \r\nread and edit docx without having you agents deal with XML. Save on cost, enjoy improved performance.\r\nPerfect for regulatory, compliance and legal agent builders dealing with documentation",
    "one_liner": "The best DOCX MCP for agents to edit microsoft word documents",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Productivity",
    "launched_at": 1729555399,
    "tags": [
      "Documents",
      "Developer Tools",
      "B2B",
      "API",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Fall 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Productivity"
    ],
    "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/vespper",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/vespper.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/vespper",
    "x_url": "https://twitter.com/vespperdotcom",
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    "primary_partner": {
      "name": "Garry Tan",
      "url": "https://www.ycombinator.com/people/garry-tan"
    },
    "founders": [
      {
        "user_id": 316431,
        "full_name": "Topaz Turkenitz",
        "title": "Founder/CEO",
        "founder_bio": "Background in computer science and design. At Snyk, led the company’s top growth experiment and spearheaded the project that secured a Fortune 500 bank. Previously, worked at 99designs (a Vista-owned global e-commerce marketplace), driving end-to-end product initiatives.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/topaz-t",
        "x_url": "https://www.twitter.com/topaz_tee",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/793dcbb4e83aab40f95df04118dd19ce49f43a88.jpg"
      },
      {
        "user_id": 978949,
        "full_name": "Dudu Lasry",
        "title": "Founder/CTO",
        "founder_bio": "Co-founder & CTO at Vespper\nI’m a passionate software engineer with over seven years of experience, focused on building solutions that make a real difference. Before starting my own venture, I worked at Google, Viz.ai, and SafeBreach, where I took on key projects, collaborated closely with teams, and supported initiatives that mattered to both developers and the business. \n\nIn my spare time, I like playing the guitar, working on side projects and travel the world (most recently Japan 🇯🇵)",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/dudu-lasry-05022879",
        "x_url": "https://twitter.com/DavidLasry17164",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e321d837b1fc79b61321540437f26a50938fbde3.jpg"
      }
    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 113233,
        "title": "Vespper DOCX MCP",
        "tagline": "The first SOTA level model to allow agents to edit DOCX documents",
        "body": "Today we're launching **Vespper DOCX MCP**.\\\n\\\nThe first model fine-tuned specifically for editing Word documents, shipped as an MCP. \\\n\\\nOn our internal benchmark, it lets agents run 3x faster, 2x cheaper, and more accurately than the closest alternative.\\\n\\\nThere are 1.2–1.5B Knowledge workers globally, with Word as the default tool for the majority of them. 150–250M people open/edit a Word doc on a given weekday, and soon there will be an agent alongside each one.\\\n\\\nTry it now: [https://app.vespper.com](https://app.vespper.com/?utm_source=yc_launch)\\\n\\\nRead our technical blog post here: [https://www.vespper.com/blog/launching-vespper-docx-mcp](https://www.vespper.com/blog/launching-vespper-docx-mcp/?utm_source=yc_launch)\\\n\\\n<https://youtu.be/5v570mnPEJQ?si=qLa2xNTLSlp7UyOl>",
        "url": "https://www.ycombinator.com/launches/TSL-vespper-docx-mcp",
        "votes": 5,
        "created_at": "2026-09-01T17:40:35.005Z"
      },
      {
        "id": 85173,
        "title": "Vespper: 24/7 AI on-call engineer",
        "tagline": "An agent that is triggered by alerts and surfaces relevant information that helps you troubleshoot",
        "body": "⭐ Star us on [Github](https://github.com/vespperhq/vespper) & follow us on [Twitter](https://x.com/vespperdotcom) & [LinkedIn](https://www.linkedin.com/company/vespper)!\n\n**📜 TL;DR**\n\n[Vespper](https://www.vespper.com?utm_source=yc&utm_campaign=yclaunch&utm_id=1) is an on-call engineer that helps engineers troubleshoot alerts by surfacing the right data at the right time.\\\n\\\n<https://youtu.be/uN888sOaIig>\n\n**🎯 What is Vespper?**\n\nVespper is an on-call engineer running 24/7 to troubleshoot your alerts and surface the right data to help you resolve your issue so incidents never falls through the cracks.\n\nWhether your company is going through growing pains, needs a better handle at dealing with SEV0 or has too many low priority unsolved issues - Vespper will adapt to your needs to democratize expert knowledge across your organization.\n\n**❌ The problem**\n\nMost companies drown in alerts and there are too many alerts to handle.\n\n* **Engineers** hate waking up at 3am to go investigate an issue, one person is familiar with one specific thing and they aren’t around, there is a constant need to check for false positives.\n* **Product managers** are left playing hot potato when trying to figure out the impact of incidents and bugs but engineers are too busy triaging the issue itself.\n* **Customer support** are left asking “who owns” which service when triaging tickets.\n* **Engineering leaders** need to constantly ensure engineers are escalating quickly, they rely on service specialists to debug an issue other engineers aren’t familiar with but they aren’t always around during critical times.\n\n**💰 The solution**\n\nVespper is a multi-agent system that triages alerts, troubleshoots them and sends findings in seconds to Slack. It’s connected to internal tools (observability, incident management, knowledge management, codebases and more) and can surface problems & identify patterns in the oceans of data you have.\n\nAt the moment, we support popular tools such as:\n\n* **Observability** - DataDog, Grafana, Prometheus, Jaeger, SigNoz, Coralogix\n* **Incident management** - PagerDuty, Opsgenie\n* **Codebases** - Github\n* **Knowledge management** - Notion, Confluence, Jira\n* **Communication** -  Slack, Teams (TBD)\n\n**⚒️ How does it work?**\n\nVespper is a system that’s comprised of multi-agents and AIOps models. Behind the scenes, we run & coordinate multiple agents and tools that help identify suspicious patterns from your environment.\n\nUsing Vespper is easy.\n\n1. Signup & create an organisation.\n2. Connect the tools you work with when triaging/troubleshooting. This means observability, knowledge, incident management and communication tools.\n\nOnce the integrations are connected, we automatically trigger advanced data ingestion pipelines that starts scraping data from your environment. This is used to train the bot. You can see the status of the ingestion & training in our web UI.\n\nOnce the system is ready, it will start triaging alerts for you, post an hypothesis on Slack and show you all the automatic checks it made!\n\n**👨‍👨‍👦 About the team**\n\n![uploaded image](/media/?type=post&id=85173&key=user_uploads/316431/58991bfd-e2eb-49f3-a915-31300d54e458)\n\nHi, we are Topaz & Dudu 😊 We co-founded Vespper with the mission of making on-call stress-free. \\\n\\\n**Topaz (CEO)** - Spent years at Snyk (a hyper-growth unicorn) building and maintaining large distributed systems, leading PLG experiments and achieving 99.9% uptime for her teams services.\n\n**Dudu (CTO)** - has seven years of experience working at rapidly-growing technology startups, including Google, Viz.ai and SafeBreach. Dudu was a deep-learning algorithm engineer at Viz.ai. He contributed to cutting-edge projects that leverage computer vision for healthcare applications and also worked on large-scale distributed systems.\n\nWe both dealt with daily alerts and the daily monotony of triaging, tuning and maintaining services observability.  This time spent all came at the expense of working on more impactful customer focused work.\n\nWe believe that pairing the strength of AI to pattern-match, classic AIOps and heuristics from our own experience can unlock a new experience for developers.\n\n**🙏 Our ask**\n\n1. Book a meeting with us <https://cal.com/callwithtopaz/vespper> or email us at [**founders@vespper.com**](mailto:founders@vespper.com)**.**\n2. Star us on [GitHub](https://github.com/vespperhq/vespper) + follow along on [Twitter](https://x.com/vespperdotcom) & [LinkedIn](https://www.linkedin.com/company/101636115/).",
        "url": "https://www.ycombinator.com/launches/M9l-vespper-24-7-ai-on-call-engineer",
        "votes": 74,
        "created_at": "2024-10-31T03:20:04.045Z"
      }
    ]
  },
  {
    "id": 30045,
    "name": "Archil",
    "slug": "archil",
    "former_names": [
      "Neptune Storage",
      "Regatta Storage"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0695554aaa43f831a6d970c73486aad8f7a9101f.png",
    "website": "https://archil.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Archil transforms S3 buckets into a 30x faster, unlimited, local disk. Archil enables AI, analytics, and serverless applications to instantly access massive data sets without waiting for data transfer. Researchers use Archil for shareable, local storage of data set and model versions that never runs out of capacity.",
    "one_liner": "The high-performance file system that connects AI to data",
    "team_size": 11,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1727196277,
    "tags": [
      "Developer Tools",
      "Machine Learning",
      "Big Data",
      "Infrastructure",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Fall 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Infrastructure"
    ],
    "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/archil",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/archil.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/archil",
    "x_url": "https://x.com/archildata",
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        "full_name": "Hunter Leath",
        "title": "Founder/CEO",
        "founder_bio": "I'm building Archil, a cloud file system with unlimited capacity, local-like performance, and instant access to massive data sets in your S3 buckets. I've spent the past 9 years building cloud storage products at AWS and Netflix, and I'm thrilled that teams can finally stop managing disks.",
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        "url": "https://archil.com/post/archil-file-system-to-data-company",
        "date": "Jun 02, 2025"
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      {
        "title": "The Quest for a Distributed POSIX-Compatible Filesystem",
        "url": "https://materializedview.io/p/the-quest-for-a-distributed-posix-fs",
        "date": "Dec 05, 2024"
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    "launches": [
      {
        "id": 85093,
        "title": "Archil: Transform S3 into an infinite, local file system",
        "tagline": "AI and analytics teams use Archil to instantly access massive S3 data sets, without waiting for data transfer or worrying about capacity.",
        "body": "_TL;DR:  Archil transforms S3 buckets into infinite, local file systems. It’s 30x faster than accessing S3 directly, and 90% cheaper than manually managing EBS disks. Archil provides instant access to data in S3, and it powers AI applications that can’t wait for massive data sets to download. Archil doesn’t require code changes because it’s just a file system. You can try it today at [archil.com](https://archil.com)._\n\nI’m Hunter, the founder of Archil. I’ve spent the past 9 years building cloud storage products on the frontier of what’s possible – leading both Amazon’s Elastic File System product and Netflix’s cloud storage team. During this time, I worked with thousands of application developers, cloud teams, and software providers to deeply understand how they use storage.\n\nHere's the problem: I found that AI and analytics teams love storing their data in S3 because it’s low-cost and scalable, but their applications can only use this data once it’s in a local file system. As a result, these teams are constantly moving data back and forth from their local instance file systems to S3. For larger data sets, applications can wait for hours to download and decompress data before starting. Unlike S3, local file systems have a limited amount of capacity that you can’t easily change after creation, they don’t support sharing data, and they’re 10x more expensive.\n\nArchil transforms your existing S3 buckets into a new kind of infinite, local file system. With Archil, your applications can instantly use petabyte-scale data sets in S3 without waiting for manual data download. Archil automatically scales with your data, and you only pay for the data you’re actively using – 90% cheaper than using EBS. With Archil’s shared, high-speed cache, all your instances and containers can take advantage of 30x faster, consistent reads and writes. When you’re done editing data, it automatically flows back to S3 within a few minutes, so you can easily share results with teammates. Archil has full POSIX compatibility (including renames, appends, and locking), so it’s already compatible with your applications – no code changes needed. Teams move faster when they use Archil because they don’t have to build custom data movement infrastructure.\n\n[Check out how easy Archil is to set up and use.](https://www.tella.tv/video/cm2num964000e03jng6jl5d9c/view)\n\nWe are really excited about how Archil will help teams simplify their data management. We are currently working with: AI teams who want to start model inference without waiting for downloads to complete, researchers who want to experiment on models and create new versions without running out of disk capacity, analytics teams who want to speed up their batch pipelines, and cloud teams who want lower-cost local storage without worrying about utilization. We’d love to work with you, too. If you have any questions, feel free to email me at [hleath@archil.com](https://mailto:hleath@archil.com). You can try Archil today by signing up at [archil.com](https://archil.com).\n\nLet’s build the future of the cloud together.\n\n![uploaded image](/media/?type=post&id=85093&key=user_uploads/2542/df85a282-87df-4986-b3c7-9cb58acc84ab)",
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        "full_name": "Tarush Agarwal",
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        "full_name": "Shashij Gupta",
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        "full_name": "Sidhant Kabra",
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        "title": "Forward Deployed Engineer (US)",
        "url": "https://www.ycombinator.com/companies/cekura-ai/jobs/AiWwUxI-forward-deployed-engineer-us",
        "location": "San Francisco, CA, US",
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        "location": "San Francisco, CA, US",
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        "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"
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      {
        "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"
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        "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"
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        "url": "https://www.businessinsider.com/read-pitch-deck-y-combinator-startup-used-seed-funding-2025-6",
        "date": "Jul 01, 2025"
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      {
        "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"
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      {
        "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"
      },
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        "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"
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    "id": 30047,
    "name": "Endstack",
    "slug": "endstack",
    "former_names": [
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    "website": "https://www.endstack.com",
    "all_locations": "Los Angeles, CA, USA",
    "long_description": "Endstack is a full desktop, collaborative workspace built for humans and agents running in the cloud available on web, desktop, and mobile.\r\n\r\nEach workspace powered by endOS, giving you a familiar channel-based experience augmented by a real desktop environment. The desktop is backed by Linux and ships with a built-in Chrome browser. Files, notes, browser tabs, native apps, terminal, and all your agents in a single beautiful, unified interface. \r\n\r\nAt the center of it all you get a powerful agent running 24/7 that you can also reach via Slack, email, or SMS. ",
    "one_liner": "The complete, collaborative workspace for humans and agents",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1731874326,
    "tags": [
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      "Generative AI",
      "AI",
      "AI Assistant"
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    "nonprofit": false,
    "batch": "Fall 2024",
    "status": "Active",
    "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/endstack",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/endstack.json",
    "year_founded": 2024,
    "city": "Los Angeles",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/endstack-com",
    "x_url": "https://x.com/endstack",
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    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/3b2d3d74e1b66a985b5ff4da594128358d243158.png",
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    "founders": [
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        "user_id": 1758131,
        "full_name": "Sam Park",
        "title": "Founder/CEO",
        "founder_bio": "Building cloud desktops and operating systems for humans and agents!",
        "is_active": true,
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        "id": 85640,
        "title": "Lune AI - Better LLMs for code and technical tasks",
        "tagline": "A replacement to standard LLMs for coding tasks - eliminate hallucinations with a marketplace of expert LLMs trained on hundreds of technical topics.",
        "body": "[ ](https://www.youtube.com/watch?v=iPCixKBJiZI)\n\nHey everyone! We’re Sam and Josh, and we’re building a platform for better LLMs for code and technical tasks.\n\n## **TLDR:**\n\n[Lune AI](https://www.lune.dev/) is a platform to find and train Lunes, or expert LLMs on any technical topic for code. We outperform the accuracy of standalone foundational models by [37%](https://www.lune.dev/blog/lune-evaluation).\n\nHere’s a [**demo**](https://www.youtube.com/watch?v=Zwokp23C3ek):\n\n## **The Problem:**\n\nLLMs **hallucinate** on material outside their training data, which often leads to inaccurate answers to technical questions related to code. Whether it’s working with a new library, or the ever changing nature of software documentation, every developer has **wasted time** on hallucinated LLM outputs.\n\n## **Lune Web:**\n\nOn Lune Web, users can find a [marketplace](https://chat.lune.dev/explore) of community trained Lunes on **hundreds** of the most popular libraries and Github repositories for developers. In a concept similar to OpenAI’s GPT store, users that train popular Lunes receive monthly payouts in a **revenue share program**.\n\n![uploaded image](/media/?type=post&id=85640&key=user_uploads/1758131/9b8e2428-b02e-4247-a5bc-f8746504e7f1)\n\nWhen interacting with Lunes on the web, users can also **receive payouts** for leaving feedback on Lune performance and contributing their own expertise to specific Lunes. This direct community driven feedback loop continuously improves the accuracy of our models.\n\n![uploaded image](/media/?type=post&id=85640&key=user_uploads/1758131/0a27c84c-44d0-477a-a4db-3d3ccf8c6da1)\n\n## **Lune API:**\n\nIn addition to Lune Web, we offer API access to our proprietary automatic context switching model, Tycho as well as all public Lunes. Tycho is our context switching model that **automatically determines** the right Lunes to retrieve information from given a user query, in order to provide the most accurate answer. \n\n![uploaded image](/media/?type=post&id=85640&key=user_uploads/1758131/0fb0ab51-5d7c-4578-8174-21d5e9563ff0)\n\nOur API is hot swappable with OpenAI, which means our users can [integrate](https://docs.lune.dev/docs/external-integrations/cursor) Tycho into any IDE, tool, or client that **supports OpenAI compatible APIs** with a personal API key, such as Cursor, Continue, and other AI client SDKs. \n\n![uploaded image](/media/?type=post&id=85640&key=user_uploads/1758131/4de9c6f0-f8a8-4015-99ef-18034e454ede)\n\nProject keys with our API can be used to easily integrate backend applications and workflows where **superior accuracy and minimized hallucinations** for technical topics are necessary. For example, generating compliable, front-end code with context from various pip packages or libraries.\n\n## **About Us:**\n\nWe are brothers who have been working together our whole lives, starting out with Lego projects. We both dropped out of Harvard because we believed that there is a very near future where AI + Coding can lead to 10x better productivity for the world. We want to make that a reality.\n\n![uploaded image](/media/?type=post&id=85640&key=user_uploads/1758131/da7c5a23-106f-4f64-bf42-1dfa460be8ca)\n\n## **Our Ask:**\n\nIf you code and you have experienced LLM hallucinations, hate reading through dense documentation and Github repos, give [Lune AI](https://www.lune.dev/) a try!\n\nIf you are building a product that uses LLMs for generating code or other technical tasks and want a hot-swappable, more accurate alternative, reach out to me at [sam@lune.dev](mailto:sam@lune.dev)\n\n![uploaded image](/media/?type=post&id=85640&key=user_uploads/1758131/d27e21bd-d15d-4a94-aa1f-28e0c1d7a1d9)\n\n",
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        "user_id": 209148,
        "full_name": "James Grugett",
        "title": "Founder/CEO",
        "founder_bio": "I'm building Codebuff — the CLI tool that writes code for you.\n\nPreviously, I founded Manifold Markets, a site with 150,000 user-created prediction markets that gets millions of views per month.\nI'll be applying lessons learned from growing a consumer app for nerds (Manifold) to growing Codebuff, a dev tool for software nerds.\n\nI bring passion and intensity to my work. With Codebuff, I've jumped into a new field, AI code generation, and built something state of the art within a couple months.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/james-grugett",
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        "user_id": 1399924,
        "full_name": "Dawson Chen",
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        "founder_bio": "Building a free coding agent. Prev co-founder at Letterbook (YC S23). Yale dropout",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/dawson-chen-9b62a8183",
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        "id": 95411,
        "title": "Founding Growth Marketer",
        "url": "https://www.ycombinator.com/companies/freebuff/jobs/VwKy5Xq-founding-growth-marketer",
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        "title": "Founding Advertiser Success Manager",
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        "location": "San Francisco, CA, US / Remote",
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        "equity_range": "0.05% - 0.10%",
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      {
        "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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    "id": 30079,
    "name": "Moonshine",
    "slug": "moonshine",
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      "Moonshine",
      "Chicory"
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    "website": "https://usemoonshine.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Moonshine creates a platform that connects to applications where hiring, employment, and contracting decisions are made and takes care of notices, explanations, recourse, and risk assessments. ",
    "one_liner": "The platform for automated hiring and workforce decisions.",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1729546253,
    "tags": [
      "Developer Tools",
      "Compliance",
      "AI"
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    "country": "US",
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      "name": "Pete Koomen",
      "url": "https://www.ycombinator.com/people/pete-koomen"
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      {
        "user_id": 1225142,
        "full_name": "Ganesh Pimpale",
        "title": "Founder",
        "founder_bio": "Formally @ Formlabs and SRI",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/ganesh-pimpale/",
        "x_url": "https://x.com/Ganeshmpimpale",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7464b0deca497cd6785c5288e75aef53d705340e.jpg"
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      {
        "user_id": 1215698,
        "full_name": "Harsha Gundala",
        "title": "Founder",
        "founder_bio": "Working on making video easier to use. Love technology and creative tooling!",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/harshagundala",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/fd623544db34fc7302a093e1951da2bfc5886193.jpg"
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    "launches": [
      {
        "id": 85752,
        "title": "Moonshine: Video Understanding APIs",
        "tagline": "Your eyes and ears to understand every pixel in a video.",
        "body": "**TLDR:** Video is hard. Moonshine watches your videos for you allowing you to understand thousands of hours of video through an API you can build into your own tools. Checkout [api.usemoonshine.com](http://api.usemoonshine.com)\n\n<https://youtu.be/oO332ljpqvs>\n\n# Video never has to suck again\n\nCurrent video analysis focuses on transcriptions and captioning services that miss the majority of valuable data that videos have to offer. Moonshine allows you to harness the full potential of a video by understanding it like a human would. Best of all, you can build it right into your own applications.\n\nTo get started:\n\n```\npip install magic-moonshine\n```\n\nRefer to the [docs](https://api.usemoonshine.com/docs) to get up and running in just 3 lines of code!\n\n# Features\n\nMoonshine has two main ways to interact with videos: search and inquire.\n\n**Search**\n\nMoonshine’s search allows you to find a needle in a haystack of footage. Using natural language, you can find any moment in thousands of hours of footage. Through the API, running a search is one line of code:\n\n```\nmoonshine.search([your_index], 'blue car driving across the street')\n```\n\nAnd it returns all the relevant clips to your search.\n\n**Inquire**\n\nInquire allows you to ask questions about your videos. It draws upon the context from every video in your index and answers with the same knowledge as a human who watched them all would have:\n\n```\nmoonshine.inquire([your_index], 'How many times did a blue car drive across the street ')\n```\n\nAnd it will return the number of times a blue car drove across the street.\n\n# The Ask\n\n* Checkout [api.usemoonshine.com](http://api.usemoonshine.com) and start building with free credits!\n* Start ups can qualify for up to $10,000 in credits to get started!\n* If you want a demo reach out to us over email (contact info below)\n\nContact: [team@usemoonshine.com](mailto:team@usemoonshine.com)\\\nX: <https://x.com/usemoonshine>\\\nDiscord: <https://discord.gg/aCgjDqbJNr>\\\nLinkedIn: <https://www.linkedin.com/company/usemoonshine>\n\n![uploaded image](/media/?type=post&id=85752&key=user_uploads/1225142/1e432b01-f96f-4cb5-8b27-8ca160ff5746)\n\n",
        "url": "https://www.ycombinator.com/launches/MJ6-moonshine-video-understanding-apis",
        "votes": 30,
        "created_at": "2024-11-26T18:35:38.537Z"
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    "id": 30095,
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    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "Consus is an API that routes all AI requests to secure and compliant infrastructure. Aerospace and defense companies use the API to access the latest models without worrying about paperwork or infrastructure engineering. Consus manages the compliance and backend work so you can plug AI into an application and get to work. ",
    "one_liner": "The fastest and cheapest way to use AI with ITAR or CUI data. ",
    "team_size": 1,
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    "subindustry": "Industrials -> Aviation and Space",
    "launched_at": 1732222348,
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        "full_name": "Eric Magliarditi",
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        "id": 85782,
        "title": "Consus - The Github for Government Documents",
        "tagline": "Stop pulling your hair out when working with government specs and requirements",
        "body": "**TLDR:**\n\nConsus eliminates the chaos of government documents. We automatically verify active revisions, alert you to updates, and extract relevant requirements from complex documents. Help your team win more contracts and execute faster with Consus.\n\n<https://youtu.be/ouFe09NHTo4>\n\n**The Problem**\n\nGovernment requirements slow companies down, particularly in aerospace & defense. When handed stacks of government requirements, program managers are expected to figure it out - with no guidance. Currently, they:\n\n   ❌ Waste hours searching for the correct document version (often government counterparts don’t know)\n\n   ❌ Sort through thousands of pages to find relevant information or requirements\n\n   ❌ Avoid the headache by offloading to busy engineering teams\n\n   ❌ Cross their fingers that they didn’t miss any requirements that will hurt the team in the future\n\n**The Solution**\n\nConsus transforms document compliance from a burden to a competitive advantage:\n\n   ✅ Instant access to verified, active documents\n\n   ✅ Automatic alerts for document updates affecting your projects\n\n   ✅ AI-powered insights that surface relevant requirements in minutes\n\n   ✅ One-click requirement extraction \n\nWe work directly with government organizations to identify active document revisions. Our extraction tools get you the information you care about, and you will never have to guess the source of a requirement. \n\nIf you are struggling to find and understand government documents, let’s [chat](https://calendly.com/eric-consusindustries/30min)!\\\n\\\n**The “Team” 🚀**\n\nI spent the bulk of my career at SpaceX where I launched critical national security missions. Government requirements are important, but they need to be dramatically changed in form & distribution to unlock critical capabilities. If you resonate with the pain, let me know!\n\n_Standing under a big rocket 🙂_\n\n![uploaded image](/media/?type=post&id=85782&key=user_uploads/274840/0f7a315b-2352-43b4-b4de-001299104a93)\n\n",
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        "full_name": "Axel Peytavin",
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        "full_name": "Vignesh Anand",
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        "founder_bio": "Former Stanford robotics graduate student. Former flight sciences intern at Archer. Also built high-powered rockets and underwater robots. Currently building the future of embodied AI with Innate",
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        "title": "Content & Marketing Intern",
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        "title": "Innate 🤖 Teach your own general-purpose robots",
        "tagline": "Shipping assembled AI robots for builders of Silicon Valley!",
        "body": "Innate builds **AI brains for general-purpose robots**, and **affordable embodiments** for consumers to experience the first AI robots.\n\nOur first product, **Maurice**, is a mobile robot with a trainable arm, designed for Silicon Valley builders to play with, customize and build on. It runs our AI brain that can navigate, perform physical tasks, interact with people, and reason.\n\n<https://youtu.be/gxRLFx4JjcQ>\n\nThe brain is **completely teachable**: You can prompt it, chat with it, and teach it physical tasks.\n\nIt takes **only 5 minutes** for you to write another prompt for Maurice to behave very differently, for example, performing security at home:\n\n<https://youtu.be/hGK0lIGT49E>\n\n# ⚙️ Under the hood\n\nIn the past 3 months, we created **our brain, an AI orchestrator** leveraging several of the most recent research publications in AI for manipulation, navigation, reasoning and planning.\n\nIt combines **9 different models** to create something that feels innately intelligent - like GPT, Gemini, Claude and Llama (Groq) got a body and learned to move. Maurice **constantly understands its environment**, makes decisions, remembers what is sees and where, and learns from you.\n\n![uploaded image](/media/?type=post&id=85667&key=user_uploads/938249/cc03013d-d569-4272-93d8-e7a3c7f0a6b8)\n\n**This system comprises:**\n\n🧠 A **multi-agent** orchestrator running specialized models locally and in cloud 🤖 **Real-time manipulation** models controlled by our own transformers\n\n🦾 A **full data pipeline** to collect arm data, train in the cloud, run inference on the platform\n\n💬 **A 100% interactive platform**, that can be steered vocally or through its prompts\n\n📈 An **eval pipeline** for our brain’s decision making, to progressively make it better\n\nMaurice learns your space, remembers context, and makes autonomous decisions about where, what to do next.\n\n**It’s also ready to build on:**\n\n* **All the compute required** is onboard (uses a Jetson Orin Nano)\n* Shipped with a **teleop arm** to train it quickly\n* **SDK to access the agent**, steer it, give it new functions to call\n\n  ![uploaded image](/media/?type=post&id=85667&key=user_uploads/938249/1459c238-8aff-4226-acec-5c3c3770f57c)\n\n\nAnd as a user, you can customize it, collect data quickly to train it, and even change the hardware.\n\n![uploaded image](/media/?type=post&id=85667&key=user_uploads/938249/1039d908-0523-43d5-a70e-8d6d00971063)\n\nThis allows Maurice (and future robots) to learn several kinds of physical tasks.\n\n![uploaded image](/media/?type=post&id=85667&key=user_uploads/938249/ed3e71f0-37cb-498d-8448-57f2ebb47178)\n\nFinally, Maurice is already reliable enough for us to do live, autonomous demos!\n\nWe're also developing a larger robot that can reach countertops. Our interoperable software ensures quick capability matching across all future embodiments using the Innate brain.\n\n# Our Ask: Join us into the **future**\n\nWe're making teachable robots accessible to builders now, because we believe it is the right way to tailor robots people want, for a reasonable price. Furthermore, the data we collect along the way, teaching our robots, will be useful for all future robots.\n\nOur first platform is for Silicon Valley builders who want to shape what teachable robots can do. Sign up for our waitlist [on our website.](https://innate.bot)\n\n1. **Join the community:** Builders, if you want to know more, join our Discord and / or get one, send us a DM at [@ax_pey](https://x.com/ax_pey) on X or at [axel@innate.bot](mailto:axel@innate.bot)\n2. **Intro us:** Our AI brain could be useful to an individual or company you know making robots? We’d love to chat!\n3. **I just want to chat! :** Great! Happy to! The best way is still through [X](https://x.com/ax_pey), [LinkedIn](https://www.linkedin.com/in/axel-peytavin/) or [email](https://mailto:axel@innate.bot)!\n\n# Who we are\n\nWe are Vignesh and Axel, two former Stanford grad students and researchers in AI for robotics and AI for HCI. We met almost a year ago working on a previous idea, and through several iterations of this project, we have come to trust our shared abilities to face the hard problems ahead to make general-purpose robotics accessible to everyone.\n\nThis company embodies our vision of bringing a technology that will be a major game-changer for humanity, in the hands of everyone. So that robots are made for humans, taught by humans.\n\n![uploaded image](/media/?type=post&id=85667&key=user_uploads/938249/8d097e3a-cf0a-4ef9-ac06-4b6397935231)\n\n_Us, 10mn before a successful live demo of our robot in front of 40 people, fixing an unexpected bug_\n\nThe future of robotics is teachable. It’s time to build it!",
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        "full_name": "Christopher Schlaepfer",
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        "title": "Senior Platform Engineer",
        "url": "https://www.ycombinator.com/companies/kilvin/jobs/s3b5Le2-senior-platform-engineer",
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        "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"
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        "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": [
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      "SaaS",
      "API",
      "Telecommunications",
      "Infrastructure"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Fall 2024",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
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    "regions": [
      "United States of America",
      "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/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",
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    "fb_url": null,
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    "github_url": "https://github.com/surgeapi",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/1f4a489f75647f08676e6de181d0f4d27016b18f.png",
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    "founders": [
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        "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"
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      {
        "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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    "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": [
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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/struct-ai",
    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/struct-ai.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/trystruct",
    "x_url": "https://x.com/trystruct",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/struct-dot-ai",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/f292fd64c9e2943d040e390cd2700e19b243bb8c.png",
    "app_video_url": null,
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    "company_photos": [],
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    "founders": [
      {
        "user_id": 1655136,
        "full_name": "Nimesh Chakravarthi",
        "title": "Founder/CEO",
        "founder_bio": "Nimesh is a Co-Founder at Struct, building the new way to do oncall. He led the consumer messaging team at LinkedIn, where reduced messaging support volume by >80% by overhauling reliability & observability. He's an EECS Berkeley grad and a real estate agent.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/nimesh-chakravarthi-68238749",
        "x_url": "https://x.com/nimeshmc",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/889b5b0e370cd6d28b3c5d3373c2734925f4c0f0.jpg"
      },
      {
        "user_id": 950535,
        "full_name": "Deepan Mehta",
        "title": "Founder",
        "founder_bio": "Deepan is building.\n\nPreviously he spent 4 years as a Sr. PM at LinkedIn, where he launched an AI-powered revamp of messaging, video posting, and messaging stories while driving 10s of millions in ARR. Before that, he launched LiveRamp's first self-serve distribution UXs and APIs. He graduated from Georgia Tech with a BS in computer science and is a Mexican Pizza enthusiast. ",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/deepanmehta",
        "x_url": "https://x.com/meksikanpijha",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1de2aedf852b59725f17ed62e7ba8db7f1eb39d3.jpg"
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    ],
    "jobs": [],
    "news": [
      {
        "title": "AI agent platforms look to find their stride in 2025",
        "url": "https://www.housingwire.com/articles/ai-real-estate-agent-platforms-2025-realpha-homa-modern-realty-bramble/",
        "date": "Jan 23, 2025"
      }
    ],
    "launches": [
      {
        "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",
        "url": "https://www.ycombinator.com/launches/NyD-edgedive-understand-what-your-customers-are-actually-saying",
        "votes": 61,
        "created_at": "2025-07-14T22:31:50.649Z"
      },
      {
        "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"
      }
    ]
  },
  {
    "id": 30111,
    "name": "x1",
    "slug": "x1",
    "former_names": [
      "FoundryAI",
      "Foundry"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c86ce92c78b4bd9698a823b31a8ee51eff7418e7.png",
    "website": "https://x1.new/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "x1 is an AI app builder that helps anyone create real, App Store-ready iOS apps. Users start with a structured product plan, design polished iPhone screens in a visual canvas, build features step by step, and prepare launch assets like App Store listings, screenshots, monetization, and analytics. Instead of generating one-shot AI demos, x1 gives builders a guided system for turning an idea into a real app.",
    "one_liner": "AI app builder for creating and launching iPhone apps",
    "team_size": 5,
    "industry": "Consumer",
    "subindustry": "Consumer",
    "launched_at": 1731963387,
    "tags": [
      "AI-Enhanced Learning",
      "Developer Tools",
      "Generative AI",
      "No-code",
      "Automation"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Fall 2024",
    "status": "Active",
    "industries": [
      "Consumer"
    ],
    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Partly Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
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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 first hour with an AI app builder is misleading. A user enters a prompt, gets polished screens and a functional first version, and thinks the app is nearly finished. The hard part begins later, when they add authentication, payments, user data, permissions, subscriptions, analytics, and the next 20 changes.\r\n\r\nThe problem is not that AI cannot generate code. It is that a real app is a connected system of product, design, data, and engineering decisions. When those decisions are not made explicitly, the AI guesses. Each guess may work on its own while conflicting with another part of the app, so every new feature makes the product harder to fix, test, and launch.\r\n\r\nThis matters because AI has opened app development to people who should not need to act as a product manager, designer, engineer, and QA lead at the same time. Existing tools give them generation without the structure needed to turn an idea into a durable product.\r\n\r\nWe started x1 after seeing the same pattern repeatedly: people could create an impressive demo quickly, then became trapped in prompt-and-fix loops. x1 asks the important questions first, turns the answers into a plan, lets users design the screens before development, builds in milestones, and verifies each step before moving on.\r\n\r\nThe goal is not just a faster demo. It is a working iPhone app that can keep improving."
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        "answer": "Our long-term vision is to make it possible for one person to build and run a serious app company.\r\n\r\nToday, launching an app requires product planning, design, mobile engineering, backend infrastructure, testing, App Store operations, monetization, analytics, marketing, customer support, and ongoing iteration. AI can generate pieces of that work, but the founder still has to coordinate disconnected tools and repeatedly explain the product from scratch.\r\n\r\nx1 will become the shared system for the entire app lifecycle. It will remember the product, users, design, data, and prior decisions, then carry that context into future releases, App Store assets, subscriptions, analytics, experiments, marketing, and customer feedback.\r\n\r\nA founder should be able to go from an idea to an app, from an app to a launch, and from a launch to a growing business without assembling a traditional software team.\r\n\r\nIf we succeed, people with strong ideas, taste, domain expertise, or distribution will be able to create durable app businesses on their own. x1 will be the operating system for one-person app companies."
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        "full_name": "Albert Lam",
        "title": "Founder/CEO",
        "founder_bio": "CEO at Ryvn, making cloud and on-prem deployment, monitoring, and management simple. Previously led AI and infrastructure teams at Palantir.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/simplyalam",
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        "full_name": "Shardool Patel",
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        "url": "https://www.ycombinator.com/companies/ryvn/jobs/qg0OM1Q-founding-software-engineer",
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        "type": "Full-time",
        "role": "Engineering",
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        "equity_range": "0.50% - 2.00%",
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        "id": 85379,
        "title": "🚢 Ryvn - Deploy applications to customer clouds, on-prem",
        "tagline": "Like Vercel but for deploying to your own cloud and customer clouds",
        "body": "**TL;DR:** [**Ryvn**](https://ryvn.ai) **_empowers SaaS startups to seamlessly deploy, monitor, and manage their applications within customer clouds_** _and on-premises environments. We streamline on-prem delivery with integrated logging, monitoring, and simplified updates and rollbacks across all customer installations._ [_Watch our demo_](https://youtu.be/1wTY1a0KKPU)\n\n   \n&nbsp;\n# **🔥 The Team**\n\n[Albert](https://www.linkedin.com/in/simplyalam/) and [Shardool](https://www.linkedin.com/in/sp97/) collectively bring over a decade of expertise in infrastructure and DevOps.\n\nAt Palantir, Shardool led engineering teams building deployment infrastructure for managing **hundreds of environments**, including cloud, on-premises, and air-gapped systems—facilitating over 10,000 deploys per day.\n\nAlbert led engineering teams at Palantir, developing disaster prevention products that secured $xxM in contracts. At Capital One, he architected modular deployment pipelines and resource management tools.\n\n   \n&nbsp;\n# **❌ The Problem**\n\n**Building infra is not building product**\\\nSetting up infrastructure for each customer—learning tools like Terraform and Kubernetes, creating configurations, and making Docker images—is time-consuming. Instead of building new features, your team is tied up with these tasks just to get deployments working.\n\n**Customer DevOps slows you down**\\\nIf you're sending code, docker images, or Helm charts to customers, you're relying on their DevOps team to prioritize your updates and correctly follow installation instructions. This can lead to **delays of 4-6 weeks** before updates are applied, hurting your delivery cycle.\n\n**Support sucks without monitoring and logging**\\\nHearing about outages or bugs over email or Slack leaves you scrambling to react, putting customer trust at risk. Secure access to logs and metrics is critical to providing reliable service.\n\n   \n&nbsp;\n# **🔮 Our Solution**\n\n**🚢 Easily Install and Ship Updates**\\\nRyvn handles on-prem and VPC deployments automatically from your GitHub code, like Vercel, allowing you to push updates **multiple times a day** with little to no customer involvement.\n\n![uploaded image](/media/?type=post&id=85379&key=user_uploads/1690248/a32c6ee9-98c9-4289-b62f-83ec48cda238)\n \\\n**🎮 Controlled Updates & Instant Rollbacks**\\\nRoll out updates with ease across release stages, including **instant rollbacks** to previous stable versions, ensuring uptime and customer confidence.\n\n![uploaded image](/media/?type=post&id=85379&key=user_uploads/1690248/a6862582-b463-415b-9239-39ff5d161cf0)\n \\\n**👁️ Integrated Logging & Monitoring**\\\nSecure, **centralized access to logs** and health metrics across customer environments. Logs are streamed to your cloud or accessible on-demand from your customer’s cloud.\n\n![uploaded image](/media/?type=post&id=85379&key=user_uploads/1690248/1bffb4e3-5a28-44d0-a75c-8e92ebf639d6)\n\n   \n&nbsp;\n# **💭 Why Deploy to Customer Clouds?**\n\n**💸 Charge more, bigger markets**\n\n* Charge **3–10x** more for customer cloud / on-prem deployments\n* Sell to regulated industries — health, finance, enterprise, etc.\n\n**🥷 Skip the security review & SOC 2**\n\n* Land **PoCs** _faster_ by deploying on-prem to bypass lengthy security reviews\n* You don’t need SOC 2 or HIPAA to deploy on-prem\n\n**❤️ Make your bank and lawyers happy**\n\n* Customers pay directly for infrastructure cost\n* Not hosting customer data reduces your liability\n\n   \n&nbsp;\n# **📣 Our Ask**\n\n**Follow** - we’re on [LinkedIn](https://www.linkedin.com/company/105480942/)\\\n**Share** - If you know any startups looking to deploy to customer clouds, we’d appreciate a warm intro using our email [founders@ryvn.ai](mailto:founders@ryvn.ai)\\\n**Demo** - [book here](https://cal.com/albertlam/ryvn-demo)\n\n![uploaded image](/media/?type=post&id=85379&key=user_uploads/1690248/7b4e5b4d-30d0-4b34-8762-1f8664c960b6)\n\n",
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    "long_description": "Relvy provides AI-powered debugging notebooks that help software engineers investigate and resolve incidents faster. It finds the root cause in over 70% of alerts automatically, and when it doesn’t, engineers can easily guide or correct the investigation - saving valuable time across the team.",
    "one_liner": "AI powered debugging notebooks for incident response",
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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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      "name": "Nicolas Dessaigne",
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        "url": "https://www.ycombinator.com/companies/humanlayer/jobs/oBCZzc7-founding-product-engineer",
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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"
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      {
        "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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        "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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    "id": 30160,
    "name": "Quantstruct",
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    "long_description": "Quantstruct automatically creates and improves product documentation, implementation guides, and changelogs for API & SDK products, web-based enterprise software, and internal applications.\r\n\r\nQuantstruct identifies gaps in your knowledge base based on each product release or unfulfilled customer query. It uses multiple AI agents to search existing knowledge sources, test existing docs for validity and style guidelines, and clicks, scrolls, and uses enterprise software through a web browser to generate docs with embedded screenshots and video recordings. Quanstruct is available as a cloud service to start, targeting technical writers, content writing, professional services, and product teams.\r\n\r\nTraditional generative AI tools risk hallucinating critical API & SDK fields, even with RAG based approaches. Purely agent-based approaches risk providing unpredictable output that can diverge from desired documentation processes. Finally, no company’s review and publishing workflow is the same. Quantstruct is the easiest way to onboard and customize AI agents to continuously improve your documentation based on your customer needs and product evolution. https://quantstruct.com",
    "one_liner": "AI documentation engineer – test & autoimprove stale product docs",
    "team_size": 2,
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        "full_name": "Sarthak Srinivas",
        "title": "Founder/CEO",
        "founder_bio": "Cofounder of Quantstruct (YC W25). Building robot housekeepers for hotels.\n\nPreviously shipped agent developer platform from 0 to mid-$X million as product lead while onboarding multiple Fortune 100 companies at Moveworks. Published research with Google Glass inventor (who coined “wearable computing”) at Georgia Tech.",
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        "user_id": 1091044,
        "full_name": "Newman Hu",
        "title": "Founder/CTO",
        "founder_bio": "Co-founder of Quantstruct. We're building AI agents to create the best documentation for your product. Newman previously built search infrastructure at Moveworks and Replit (YC W18), where he managed mission critical platforms powering Gen AI experiences for Fortune 500 companies. EECS @ Berkeley",
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      {
        "id": 87136,
        "title": "Quantstruct 🤖 – Improve Your Technical Docs 24x7 with AI Agents",
        "tagline": "Kill documentation debt, update docs automatically, research & validate docs",
        "body": "# **tl;dr**\n\nQuantstruct is an AI technical writer that improves your documentation 24x7 with agents to research, test, and update your docs. We already work with hypergrowth companies like [Vapi (YC W21)](https://vapi.ai) and enterprises who build API & SDK products, visual software, and platforms where nurturing a vibrant developer and partner community with bespoke docs helps you win.\n\n[Sign up to get onboarded](https://quantstruct.com) today!\n\n<https://youtu.be/smbT-M3F1vs>\n\n## **Problem**\n\nThe best product & customer teams stomach some difficult truths to serve their customers today:\n\n1. **Product & customer education demands active effort** from product and engineering experts with limited time\n2. **Teams need to understand too much** source code, support, communication threads & product specs to properly guide customers\n3. **High-quality docs require 100% validation** to test code snippets, external links, accessibility guidelines, take screenshots, and other references. Traditional Gen AI falls short.\n4. **Helping customers supersedes keeping docs up to date**\n\nThe result? **Documentation debt** - where your product and technical docs & implementation plans go increasingly out of sync.\n\nWe felt this pain thousands of times previously, when we helped Fortune 500 customers integrate with 100s of enterprise software platforms that were poorly documented. We saw how **documentation debt** could escalate customer support issues and lead to customers not adopting and championing the platform.\n\nWe also saw how paying down documentation debt could amplify each team’s impact, inspire customer love, and help nurture a community of strongly activated champions.\n\n## **Solution**\n\nQuantstruct connects to your docs platform, GitHub, and Slack to continuously update your docs\n\n1. When a **PR** occurs, Quantstruct works behind the scenes and notifies you about a companion docs update\n2. Each type of doc update can be configured with tools and agents to\n   * _Check WCAG accessibility guidelines_\n   * _Check broken links_\n   * _Take screenshots and videos_\n   * _Generate system architecture diagrams_\n   * _Validate code blocks_\n   * _and much, much more._\n3. You can manually edit the doc or provide high-level instructions, and Quantstruct updates and publishes the necessary sections without work\n4. Quantstruct’s platform will take care of the hard bits of coordinating multiple agents, self-evaluating and improving performance, following your specific review & publishing workflows\n\n## **The ask**\n\nSign up for [Quantstruct](https://quantstruct.com), and install our GitHub and Slack apps to get started! You can also reach out to [founders@quantstruct.com](mailto:founders@quantstruct.com) to guide you through the onboarding process.\n\n# **The team**\n\n**Sarthak** has worked at growth-stage companies like Moveworks as a Kleiner Perkins product fellow, where he built an agent developer platform from 0 to $2+ million.\n\n**Newman** has built search infrastructure at Moveworks and Replit (YC W18), where he managed mission-critical platforms powering Gen AI experiences for Fortune 100 companies.\n\nBoth are published researchers and patent holders from **Georgia Tech CS** and **Berkeley EECS,** respectively.\n\nWe’ve spent our careers building for developers at enterprise software companies and deeply empathize with the pressures that support, customer success, product, and GTM teams face to build world-class developer products and ecosystems.\n\n![uploaded image](/media/?type=post&id=87136&key=user_uploads/120963/9b5326c4-b1e2-4845-ae3f-1ac50417a262)\n\n",
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    "long_description": "Docs 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 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.\r\n\r\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.\r\n\r\nWith Promptless, documentation becomes a strategic advantage for growth, not a bottleneck or a liability. ",
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    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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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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        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
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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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        "votes": 106,
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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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        "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)!",
        "url": "https://www.ycombinator.com/launches/MuD-truffle-ai-ai-agents-that-work-in-any-software-application",
        "votes": 24,
        "created_at": "2025-02-26T15:01:48.086Z"
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    "id": 30216,
    "name": "Sublingual",
    "slug": "sublingual",
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    "website": "https://sublingual.ai/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Our desktop app helps teams stay focused on shipping.",
    "one_liner": "Daily productivity tracker",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1740613527,
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        "full_name": "Matthew Tang",
        "title": "Founder/CEO",
        "founder_bio": "recommendation systems, computer vision, deep learning theory",
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        "linkedin_url": "https://www.linkedin.com/in/mhtang2/",
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        "user_id": 2000233,
        "full_name": "Dylan Bowman",
        "title": "Founder",
        "founder_bio": "Background: LLM research in defense contracting and deployment safety.",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/dylan-bowman-68a56218b/",
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        "id": 88096,
        "title": "Sublingual: LLM evals for lazy devs",
        "tagline": "Sublingual is an open-source LLM observability and evals platform that requires zero code changes to integrate. Instantly plug into a full suite of analysis tools with just one pip install—nothing else.",
        "body": "We've all done it: skipping evals, testing on vibes, and ripping it straight to prod. Integrating observability and evals can be a lot of work, which is why **Sublingual** gives you deep insights into how your LLMs perform without touching your code. It works across a wide range of environments, capturing extensive logs including LLM interactions, inputs, outputs, and server call data. Just pip install subl and you’re live.\n\n<https://www.youtube.com/watch?v=yoki32IJXBg>\n\n# **How we got here:**\n\nWe’ve spent years building and researching LLM applications, and we’ve seen firsthand how developers handle evaluation: sifting through logs, relying on intuition, and struggling with the friction of integrating existing observability tools when they just want to focus on building. Through conversations with numerous founders, we've learned that they're often too busy building to establish robust evaluation systems. So, they end up relying on a couple vibe tests before crossing their fingers and pushing to prod.\n\nThat’s why we built **Sublingual**—effortless LLM observability that works out of the box. No code changes, no distractions, just the insights you need to ship with confidence.\n\n# **Our approach:**\n\n* **Minimize onboarding overhead:** We’ve hacked away at the complexity of automating integration so you can start collecting insights instantly. Our design prioritizes minimal friction, ensuring observability works out of the box without interrupting your workflow.\n* **Minimize intrusiveness:** Disentangle logging and LLM serving logic to ensure logging server failures never impact LLM serving reliability. Sublingual is designed to be plugged in or removed without affecting any functionality of your code.\n* **Easy local hosting:** Our tool and stored logs are entirely local, so there’s no risk of data leakage.\n* **Code insights:** We use a mix of static and dynamic code analysis to deeply understand your program, extracting details that other platforms can’t like automatically finding prompt templates.\n\n# **Our ask:**\n\nTry it out right now, it will take less than a minute! If you don’t like it, just uninstall and your code will be exactly the same as before.\n\n⭐ Give our project a star 😊\n\n🧑‍💻 **GitHub:** <https://github.com/sublingual-ai/sublingual> \n\n🔗 **Website:** <https://sublingual.ai>\n\n![uploaded image](/media/?type=post&id=88096&key=user_uploads/2378452/c93b335e-b796-4b1d-92e8-db8367a16634)\n\n# **Our team:**\n\n![uploaded image](/media/?type=post&id=88096&key=user_uploads/2378452/8af49103-a15c-4959-b35d-d7aea830135f)\n\n[Dylan](https://www.linkedin.com/in/dylan-bowman-68a56218b/) (CTO): previously LLM research at UIUC Kang Lab and Dept. of Defense\n\n[Matthew](https://www.linkedin.com/in/mhtang2/) (CEO): previously TikTok ML on the recommendation algorithm and ads engine, LLM research for rec-sys at Nextdoor\n\nContact us:\n\n📧 founders@sublingual.ai",
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    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1737327618,
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    "city": "San Francisco",
    "country": "US",
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        "full_name": "Seth Setse",
        "title": "Founder/CEO",
        "founder_bio": "Co-Founder @ a0.dev | CMU ‘23 | Serial App Developer",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/seth-setse-0641b6175",
        "x_url": "https://twitter.com/SethSetse",
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        "full_name": "Ayomide Omolewa",
        "title": "Founder/CTO",
        "founder_bio": "a0.dev, Nvidia, Paramount, Google, Lockheed Martin",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/omolewa",
        "x_url": "https://www.twitter.com/TheDonAyo",
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        "title": "Founding Growth Lead (Contract-to-Hire)",
        "url": "https://www.ycombinator.com/companies/a0-dev/jobs/V7cGC6Z-founding-growth-lead-contract-to-hire",
        "location": "San Francisco, CA, US",
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        "id": 91846,
        "title": "a0.dev - Phase 1: We're all gonna make apps (WAGMA)",
        "tagline": "Build mobile apps in minutes using AI.",
        "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.",
        "url": "https://www.ycombinator.com/launches/NtO-a0-dev-phase-1-we-re-all-gonna-make-apps-wagma",
        "votes": 11,
        "created_at": "2025-07-03T18:24:33.801Z"
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      {
        "id": 87417,
        "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)",
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    "name": "Lucidic AI",
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "Lucidic is trying to find a new paradigm to teach models. The last decade made models intelligent, but intelligence is not the same as experience. Humans do not get better by memorizing thousands of examples; we build learning systems around ourselves: skills, memories, critique, practice, tools, and guidance. And every person learns differently because every task is different. Lucidic brings that idea to AI agents by training a custom learning system for each agent, so it learns what to remember, what skills to build, when to ask for help, and how to improve from experience. The model provides the intelligence, Lucidic gives it a way to learn.",
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        "full_name": "Abhinav Sinha",
        "title": "Founder/CEO",
        "founder_bio": "Hi, I’m Abhinav the founder and CEO for Lucidic AI! I’m from Stanford where I studied Computer Science with an AI specialization (both bachelor's and master's) and did research at Stanford's AI Lab.  I’ve worked at Apple as a software engineer and at Citadel Securities and Susquehanna International Group as a quant. \n\nIn my free time, I like to play basketball, pickleball, lift, and rewatch Christopher Nolan movies!\n\nFeel free to reach out, would love to chat -- abhinav@lucidic.ai ",
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        "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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        "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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        "title": "♾️ Infinite: Global Stablecoin Payment Processor",
        "tagline": "Fast, affordable global payments.",
        "body": "[Infinite](https://youtu.be/L0Zho4tT8w8)\n\n#### **TL;DR: Fast-track your stablecoin integration**\n\nInfinite makes it easy for developers to embed global stablecoin payment rails through a turnkey SDK. Our customers use us to move money cross-border on same-day with low fees, all without crypto complexity.\n\n#### **The problem**\n\nAfter talking to over hundreds of merchants and payment processors, we found that global payments are slow, expensive, and unreliable. Traditional financial rails such as SWIFT result in high fees and multi-day delays with little transparency on the state of their transfer. Yet companies, both big and small, struggle to adopt stablecoins due to complex compliance requirements and fragmented vendor integrations.\n\n#### **Our solution**\n\nWe're building what merchants worldwide need: fast, affordable global payment rails that can be integrated in days instead of months. Infinite can process same-day payments to over 170 countries, enabling businesses to leverage stablecoins as a settlement network (a la SWIFT) for cross-border payments. Our network of on and off-ramps provides connectivity to local fiat funding and payout flows, enabling faster global money movement and our turnkey SDKs and APIs allow businesses to embed stablecoins into their applications faster. Today, our platform supports:\n\n* **Customer Bank to User Bank** — US bank -> International bank (e.g., USA to LATAM), allowing businesses to send local currency payments with instant settlement to LATAM, Europe, Africa, and SEA\n* **Customer Bank to User Wallet** — US bank -> user wallet, allowing businesses to send USD stablecoin payouts globally and instantly\n* **Customer Bank to User SDK** — Embedded wallet and hosted links experience for payment beneficiaries to seamlessly receive and manage stablecoin payments without dealing with crypto complexity\n* **Treasury Management** — Store balances in USD-denominated stablecoins earn a competitive yield and issue cards against wallet balances\n\n![uploaded image](/media/?type=post&id=88276&key=user_uploads/39977/7323ca79-3e4d-4e27-8a2d-7417c40b06c4)\n\n#### **Our wedge**\n\nWe partner with early-stage to mid-market companies with global payments, contractor payouts, and treasury management workflows, including:\n\n* **Creator Economy** – Creator payouts for platforms looking to reduce payment costs, increase successful delivery rates to their global creator base, and offer USD-based payout options\n* **Global Payroll** – Global payroll platforms looking to increase coverage, streamline tax compliance, and move money faster.\n* **Logistics** – Import/export payments for businesses struggling with slow settlement times and high fees in cross-border trade\n* **Marketplaces** – Marketplace payouts for platforms needing to send frequent, low-cost payments to sellers and service providers worldwide\n* **Neobanks:** Traditional banks for SMBs or neobanks in emerging markets looking to hold stablecoin-backed treasuries and remit globally\n* **Gaming** – eSports and gaming audiences are increasingly global, and consumers demand instant off-ramping options in their local markets\n\n#### **About us**\n\nWe’re building this platform to solve pain points we experienced building financial products at scale at companies like [Sardine](https://sardine.ai) and [Coinbase,](https://coinbase.com) where we learned about customers’ needs firsthand.\n\n![uploaded image](/media/?type=post&id=88276&key=user_uploads/39977/da6a2143-8cec-4854-b28a-5b2123b88f15)\n\n**Ready for instant global payments that just work?** Book a demo [here](https://cal.com/infinite) or reach out to us at [founders@infinite.dev](mailto:founders@infinite.dev)!\n\n![uploaded image](/media/?type=post&id=88276&key=user_uploads/39977/f12c7d30-ed73-413a-8d57-a08bc1f459b1)\n\n",
        "url": "https://www.ycombinator.com/launches/Mxo-infinite-global-stablecoin-payment-processor",
        "votes": 48,
        "created_at": "2025-03-06T04:43:08.672Z"
      }
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    "name": "Mastra",
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    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "Mastra is the easiest way to build a production AI application, built by the team that brought you Gatsby. We provide a complete set of AI primitives: workflows for complex operations, agents for autonomous decisions, RAG for knowledge integration, and evals for quality & accuracy. Mastra is open-source, modular, and built in Typescript for product developers. You can deploy Mastra on any cloud, and it gives you a straightforward syntax to solve the hardest problems building with AI: human-in-the-loop workflows, agent memory and tool selection, and output quality. ",
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    "team_size": 30,
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        "full_name": "Sam Bhagwat",
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        "full_name": "Abhi Aiyer",
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        "full_name": "Shane Thomas",
        "title": "Founder",
        "founder_bio": "Founder/CPO of Mastra. Prev: built Audiofeed (AI podcasting). Staff eng / head of product @ Gatsby. 15+ years in open source. State wrestling champion.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/smthomas3",
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        "title": "We raised a $22M Series A to help every developer build agents - Mastra Blog",
        "url": "https://mastra.ai/blog/series-a",
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      {
        "id": 88086,
        "title": "Mastra: the open-source JavaScript framework for building agents",
        "tagline": "If you hate Langchain, you'll love Mastra :) ",
        "body": "Hey everyone 🙂 we’re Sam, Shane and Abhi.\n\n![mastra co-founders](https://mastra.ai/_next/image?url=%2Fabout%2Fmastra-founders.png&w=1200&q=75)\n\n**What we’re building:** Mastra (<https://mastra.ai>) is an open-source JavaScript SDK for building agents on top of Vercel’s AI SDK.\n\n<https://www.youtube.com/watch?v=8o_Ejbcw5s8>\n\n**Our backstory:** Previously, we built Gatsby, the open-source React web framework.\n\nWe noticed our friends building AI applications getting stuck debugging prompts, figuring out why their agents called (or didn’t call) tools, and writing lots of custom memory retrieval logic.\n\nIn October, we started building Mastra, and last week we went viral on Hacker News and Github and went from 1,500 to 7,500 stars.\n\n**Mastra use-cases:** Fireworks AI is using us to build agentic workflows. YC companies are using Mastra to automate support, build CAD diagrams, scrape the web for contact info, automate medical transcriptions, generate financial documents, and create code generation products.\n\nMastra allows you to create workflow graphs that can suspend/resume, build RAG pipelines, write evals, give agents memory, create multi-agent workflows, and test it all in a local playground.\n\nHere’s a weather agent and the agent playground (with tracing built in!):\n\n![uploaded image](/media/?type=post&id=88086&key=user_uploads/153911/2af3d557-eda5-4e84-9e3d-8ca9f89ba3b4)\n\nYou can deploy Mastra agents and workflows to a serverless platform like Vercel, Cloudflare, Netlify, any cloud service that can run Node.js, or our [own hosting platform](https://mastra.ai/waitlist) with evals and tracing.\n\n**How to get started:** Just head over to the command line and install:`npm create mastra`\n\nHappy building 🙂 \\\n\\\nPS: we’ve spent a lot of time this batch doing AI engineering whiteboarding sessions with other batch startups, walking through architecture and best practices, so we decided to write a book to help people get up to speed faster: [Principles of Building AI Agents](https://www.amazon.com/dp/B0DYH5GHDD/ref=tmm_pap_swatch_0?_encoding=UTF8&dib_tag=se&dib=eyJ2IjoiMSJ9.xOCgmaLViBdLwSFuscVMKTz0vTJBUua4OTJbmgz-H-ZCHIxUUBdjGogX4uyU7T6V.kAblDRv1ODXGF3V-QgC6-AVQCrcuYiDicC-BYx4cYXc&qid=1740435997&sr=8-1).\n\nFollow [@mastra_ai](https://twitter.com/mastra_ai) on Twitter/X and tweet at us and we’ll get you a physical copy!\n\n![uploaded image](/media/?type=post&id=88086&key=user_uploads/153911/3fe20638-050c-463d-b8cd-f23b7ce91592)\n\n",
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        "votes": 172,
        "created_at": "2025-02-27T15:40:16.256Z"
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    "website": "https://www.corsair.dev",
    "all_locations": "New York City, NY, USA; Remote",
    "long_description": "Corsair connects your app to any other API. \r\n\r\nUse Corsair to build custom agents, dashboards, and workflows with hundreds of different integrations. \r\n\r\nGet started here: https://docs.corsair.dev/quick-start",
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    "city": "New York City",
    "country": "US",
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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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        "votes": 1544,
        "created_at": "2026-08-27T20:55:14.055Z"
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    "name": "TensorPool",
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    "long_description": "Our CLI makes ML model training effortless - just describe your job, and we handle GPU orchestration and execution at half the cost of major cloud providers.",
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        "full_name": "Tycho Svoboda",
        "title": "Founder",
        "founder_bio": "Co-founder & CEO of Tensorpool. Ex-Blackstone, Stanford",
        "is_active": true,
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        "full_name": "Joshua Martinez",
        "title": "Founder/CTO",
        "founder_bio": "Co-Founder & CTO of TensorPool (W25)\nPreviously NVIDIA, Apple, Chan Zuckerberg Initiative\nStanford BS & MS in Computer Science + Statistics",
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        "full_name": "Hlumelo Notshe",
        "title": "Founder/CPO",
        "founder_bio": "Co-Founder & CPO of TensorPool\nEx-DeepMind & NextDoor\nStanford BS & MS in Computer Science + Mathematics",
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      {
        "id": 87792,
        "title": "TensorPool: the easiest way to use GPUs 🌊",
        "tagline": "With TensorPool, just describe your job and we handle all the GPU orchestration and execution at half the cost",
        "body": "Hi Everyone! We’re [Joshua](https://bookface.ycombinator.com/user/969804), [Hlumelo](https://bookface.ycombinator.com/user/1709047), and [Tycho](https://bookface.ycombinator.com/user/2359695) - cofounders of TensorPool!👋\n\n**TLDR;** Our CLI makes ML model training effortless - just describe your job, and we handle GPU orchestration and execution at half the cost of major cloud providers.\n\n[Get setup in 3 minutes](https://github.com/tensorpool/tensorpool)\n\nHere’s a quick demo of how easy it is to train ML models with TensorPool!\n\n[**TensorPool Demo -- Fine-Tuning DeepSeek**](https://youtu.be/RqqLIVzP780)\n\n# **Problem**\n\nSince high school, when we trained our first ML models, **accessing remote compute has always been a massive hurdle**. As the years went by and we moved further into academia/industry, a good solution never came. Whether it was AWS EC2’s absurd amount of configuration, or Google Colab’s inability to run jobs without your computer being on, nothing left us satisfied. We talked to our co-workers and friends and they all felt the same. We wanted using GPUs to be as easy as programming locally.\n\n# **Solution**\n\nWe got together and built a way to **access industry-scale compute from your IDE**. No more SSHing. No more massive data migrations. No more ML Ops headache. Just a simple CLI. \\[We also **cut your costs by 50%** which will be explained below :)\\]\n\n# **How It Works**\n\nTensorPool has 2 main advantages:\n\n1. **Ease of Use:** \n   * **Don’t leave your IDE:** TensorPool deploys your code directly to GPUs and ships the results back, just as if you were developing locally. \n   * **Intuitive CLI & Configuration:** With TensorPool you can run your job with a single command, kick off several experiments with different tp.config.toml configurations, and version control training jobs with your code.\n2. **Price Advantage**\n   * **Multi-cloud integration:** We’ve developed technology to do a real time analysis of all available GPU cloud providers, and put your job on the cheapest one.\n   * **Spot node resummation tech:** We’ve created a way to give users the price advantage of spot nodes with the reliability of on-demand instances. This leads to \\~50% savings!\n\n# **Our ask**\n\nWe’re currently giving away $5/week of **free compute** to early users, and would love for you all to **try us out**! Whether your start-up needs an ML infra upgrade or you love messing around with models in your free time – reach out to us we’d love to chat ([team@tensorpool.dev](mailto:team@tensorpool.dev))! You can find all the information to get started [on our GitHub](http://github.com/tensorpool/tensorpool) (**drop us a star while you’re there** 😊) or [our website](https://tensorpool.dev).\n\n**We would also love intros to enterprises** that you believe could benefit from cheaper / easier access to GPUs.\n\n# **Try TensorPool today!**\n\nBelow is a quick start:\n\nAfter completing [the prerequisites](https://github.com/tensorpool/tensorpool?tab=readme-ov-file#prerequisites), we create a “tp.config.toml” ([explained here](https://github.com/tensorpool/tensorpool?tab=readme-ov-file#configuration)), either manually with: \n\n```\ntp config new\n```\n\nOr auto-generate one with natural language: \n\n```\ntp config <describe your task>\n```\n\nTo then deploy and run your job – simply run:\n\n```\ntp run\n```\n\nand that’s it! Your model is training on cloud GPUs! \n\n# **About Us**\n\nJoshua, Tycho, and Hlumelo all met their freshman year at Stanford where they got placed on the same dorm floor. Since then, they’ve taken all their classes together and have worked at companies like Apple, Blackstone, DeepMind, Nextdoor, CZI, and PIMCO.",
        "url": "https://www.ycombinator.com/launches/Mq0-tensorpool-the-easiest-way-to-use-gpus",
        "votes": 697,
        "created_at": "2025-02-18T22:18:38.093Z"
      }
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  },
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    "id": 30345,
    "name": "Codevisor",
    "slug": "codevisor",
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    "all_locations": "San Francisco, CA, USA",
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    "one_liner": "The fastest native app for agentic engineering.",
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    "city": "San Francisco",
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      "url": "https://www.ycombinator.com/people/jared-friedman"
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        "full_name": "Alexandru Turcanu",
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        "linkedin_url": "https://linkedin.com/in/pondorasti",
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      {
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        "full_name": "Dylan Player",
        "title": "Founder/CTO",
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        "is_active": true,
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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"
      }
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    "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",
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    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1738700190,
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    "year_founded": 2025,
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        "full_name": "Jackson Stokes",
        "title": "Founder/CEO",
        "founder_bio": "Cofounder at TrainLoop, previously Google Gemini & AlphaFold performance ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jacksonstokes/",
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      {
        "user_id": 681927,
        "full_name": "Mason Pierce",
        "title": "Founder/CTO",
        "founder_bio": "My background is in applying AI models to business use-cases and have always found fine-tuning to be way harder than it should be - My mission is to unlock fine-tuning for all builders :)",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/malapier",
        "x_url": "https://x.com/mlpierce22",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e0708b326a808512f74417ba49da6268c9d5777f.jpg"
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        "title": "Head of Enterprise",
        "url": "https://www.ycombinator.com/companies/trainloop/jobs/elVnWkD-head-of-enterprise",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$150K - $250K",
        "equity_range": "0.50% - 1.50%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 116538,
        "title": "Research Engineer",
        "url": "https://www.ycombinator.com/companies/trainloop/jobs/WABE7WW-research-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Machine learning",
        "salary_range": "$150K - $250K",
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        "title": "Research Scientist",
        "url": "https://www.ycombinator.com/companies/trainloop/jobs/1ni2P0Y-research-scientist",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Science",
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        "experience": "3+ years",
        "visa": "US citizen/visa only",
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      {
        "id": 116540,
        "title": "UX / Product Designer",
        "url": "https://www.ycombinator.com/companies/trainloop/jobs/OtdpMKl-ux-product-designer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Design",
        "role_type": "Product design",
        "salary_range": "$150K - $250K",
        "equity_range": "0.50% - 1.50%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
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      {
        "id": 87957,
        "title": "TrainLoop: Unlock Next-Level Reasoning through Fine-Tuning",
        "tagline": "Eliminate unwanted responses and match ideal outputs for your product. ",
        "body": "# Unreliable RAG or code generation? We can help.\n\nReasoning models have been all the rage lately because they beat generic benchmarks. The problem is that your business isn’t a generic benchmark - it’s a set of specific vertical tasks like codegen, compliance, legal or healthcare. Massive companies like Google and OpenAI have internal tools to train their models, but those aren’t available to the people that need it: the developers deploying these models into production.\n\nWe’ve personally been involved on both sides: Jackson optimized the Gemini models at Google and Mason hit the limits of off shelf models while leading engineering at Second (YC W23).\n\nSo we created **TrainLoop**, packaging the same RL techniques big AI labs use into an accessible platform. Our process is three simple steps:\n\n1. **Data Curation:** Our lightweight SDK (just three lines of code) gathers training signals from actual usage.\n2. **Training:** We build a reward model that teaches your LLM what output you prefer.\n3. **Inference:** Deploy automatically and call your model via standard APIs.\n\n<https://youtu.be/XhbxHOzsxRE>\n\n# Ready to Level Up Your Model?\n\nIt’s time to move past “prompt-hell” and unreliable outputs. [**Join our alpha**](https://app.trainloop.ai/waitlist) to make your language model an expert in your business and unlock production-ready performance.",
        "url": "https://www.ycombinator.com/launches/Msf-trainloop-unlock-next-level-reasoning-through-fine-tuning",
        "votes": 32,
        "created_at": "2025-02-24T16:02:19.658Z"
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    "id": 30355,
    "name": "assistant-ui",
    "slug": "assistant-ui",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/11f41b527f94c63e7d0ee1e19db038344f713a8f.png",
    "website": "https://assistant-ui.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "assistant-ui helps frontend developers add AI chat to their apps. Our product is used by several dozen companies, like LangChain, Stack AI, Browser Use, and Athena Intelligence. We're building an open source Typescript/React library and a backend as a service, with first class integrations into popular agent frameworks like LangGraph and Vercel AI SDK.",
    "one_liner": "Open Source React.js Library for AI Chat",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1738873528,
    "tags": [
      "Developer Tools",
      "Generative AI",
      "Chat",
      "Web Development",
      "AI Assistant"
    ],
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2025",
    "status": "Active",
    "industries": [
      "B2B",
      "Infrastructure"
    ],
    "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/assistant-ui",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/assistant-ui.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://linkedin.com/company/assistant-ui",
    "x_url": "https://x.com/assistantui",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/assistant-ui",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/11f41b527f94c63e7d0ee1e19db038344f713a8f.png",
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      "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/ad1f668d6df40ad631ffb47c3e83f2c68a3d35a3.png"
    ],
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      "name": "Jared Friedman",
      "url": "https://www.ycombinator.com/people/jared-friedman"
    },
    "founders": [
      {
        "user_id": 1152943,
        "full_name": "Simon Farshid",
        "title": "Founder/CEO",
        "founder_bio": "Simon is the Founder and CEO of assistant-ui. He previously co-founded READO, a book recommendation engine, and grew it to 140k MAUs. Simon started coding at age 12 and has won 8 hackathons in 5 countries.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/simon-farshid",
        "x_url": "https://twitter.com/simonfarshid",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/af1d0d9c7c17a63007af5dd69ffcd511a7d9bd4e.jpg"
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    "launches": [
      {
        "id": 87644,
        "title": "💬 assistant-ui - Open Source Typescript/React Library for AI Chat",
        "tagline": "The UX of ChatGPT in your own app, connected to your own AI agents.",
        "body": "Hi YC! I’m Simon, building **assistant-ui**, an open source Typescript/React library for AI chat.\n\nHundreds of projects use assistant-ui to build in-app AI assistants, including companies like:\n\n![Logos of LangChain, AthenaIntelligence, Browser Use, Stack AI](https://bookface.ycombinator.com/media/?type=post&id=87644&key=user_uploads/1152943/d3eda556-de8c-4404-b4be-c0295f9aeb8e)\n\nWith >50k+ monthly downloads, assistant-ui is the most popular UI library for AI chat.\n\n## **Getting Started**\n\nYou can get started by running **\\`npx assistant-ui create\\`** (new project) or **\\`npx assistant-ui init\\`** (existing project) in your terminal.\n\n![Gif showing the setup process, which takes under 30 seconds](https://bookface.ycombinator.com/media/?type=post&id=87644&key=user_uploads/1152943/17c78ae1-d8cf-4fc4-a8aa-056fe449da02)\n\n## **Features**\n\n* **Pre-built components**, fully customizable\n* **Connects to your backend**\n  * We have first class integration for **AI SDK** and **LangGraph** or build your own\n* **Generative UI**: Map LLM tool calls and JSONs to custom UI components\n* **Frontend Tool Calls:** Let LLMs take action in your frontend app\n* **Human Tool Calls:** Human approvals and input collection\n* **Chat history and analytics** via assistant-cloud (the hosted offering)\n\n## **Customization**\n\nThe API of assistant-ui is inspired by libraries like **Radix UI** and **cmdk**. Instead of a single monolithic chat component, we give you composable primitives and a great starter configuration. You have full control over the look and feel of every pixel while leaving auto-scrolling, LLM streaming and accessibility to us.\n\n![Photo showing the modular component structure. ComposerPrimitive.Input is the chat input field, ComposerPrimitive.Send is the send button.](/media/?type=post&id=87644&key=user_uploads/1152943/d8eacc69-2d94-4c43-8fab-2dcac5e7f029)\n\nSample customization to make a perplexity lookalike:\n\n![Perplexity lookalike Chat UI](/media/?type=post&id=87644&key=user_uploads/1152943/16e96ae2-d563-4f6c-9047-6c3485a1cb3d)\n\n## **Demo Video**\n\n[Demo Video](https://youtu.be/9eLKs9AM4tU?si=jm9GzoFAcyM_tPT-)\n\n## **About**\n\nI’ve wanted to build my own dev tool company since high school. Last year, I built the first version of assistant-ui because I needed the UX of ChatGPT in my own app. The app I was building didn’t work out, but few friends asked me about the chat UI. Since then, AI chat has became increasingly popular as a means for delegating tasks to AI agents. My focus is on enabling human <> agent collaboration through better UX and AX (agent experience).\n\n![Photo of Simon, the founder](https://bookface.ycombinator.com/media/?type=post&id=87644&key=user_uploads/1152943/d43c8332-b160-40d8-8f27-849bd82806e3)\n\n## **Ask**\n\n* [Check out example demos](https://www.assistant-ui.com/)\n* [Star us on GitHub](https://github.com/assistant-ui/assistant-ui)\n* [Join our Discord](https://discord.com/invite/S9dwgCNEFs)\n* [Book a sales call](https://cal.com/simon-farshid/assistant-ui)",
        "url": "https://www.ycombinator.com/launches/Mnc-assistant-ui-open-source-typescript-react-library-for-ai-chat",
        "votes": 30,
        "created_at": "2025-02-13T15:37:24.704Z"
      }
    ]
  },
  {
    "id": 30356,
    "name": "Artil",
    "slug": "artil",
    "former_names": [
      "Fira"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e50d8dfa254f692b3d51a22620ca8519141e9ed2.png",
    "website": "https://artil.dev/",
    "all_locations": "London, England, United Kingdom",
    "long_description": "Artil gives AI agents their own email addresses and phone numbers so they can communicate and use online services. Agents can send and receive emails and text messages, sign up for services, and complete email and SMS verification. We’re building the identity and communication infrastructure for teams developing agents and people putting them to work.",
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    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
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        "full_name": "Alex Tkachenko",
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        "founder_bio": "CEO at Artil. Previously founded Hashscan, blockchain analytics startup. Created Hodler, crypto portfolio tracker app (sold in 2022).",
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        "linkedin_url": "https://linkedin.com/in/alextcn",
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      {
        "id": 100809,
        "title": "Fira MCP: Financial datasets in Claude and Excel",
        "tagline": "Connect SEC filings, UK Companies House, market data and earnings transcripts to your AI with source-cited answers",
        "body": "Reliable financial data access and trust in outputs are still the bottleneck in adopting AI in banking, consulting and investment firms. We built Fira MCP to solve that, starting from for teams adopting Claude. Our data connector lets your AI read and cite SEC and international filings, UK Companies House, market data, and earnings transcripts. It works with Claude, Claude for Excel, ChatGPT, and Copilot, while setup takes 3 minutes and it's free to try - <https://firaresearch.com/mcp>.\n\n<https://youtu.be/JoEY1imdVhw>\n\n### Problem\n\nMany banking, consulting, and investment firms are moving day-to-day AI work to Claude. But reliable data access and trust in the outputs are still the bottleneck.\n\n### Solution - Fira MCP\n\nFira MCP plugs directly into Claude, ChatGPT, Copilot, and Claude for Excel as a data connector. Your AI gets access to filings, transcripts, and market data, with numbers linked back to the exact paragraph or row in the source document. It handles scanned PDFs, nested tables, and works across tens of documents in a single research thread.\n\n## Available datasets\n\n* **SEC Filings** — 8,000+ active US companies (10-K, 10-Q, 8-K, and more)\n* **UK Companies House** — 5M+ private companies, including scanned accounts\n* **International filings** — 10,000+ companies across 50+ countries\n* **Earnings call transcripts** — full transcripts with analyst Q&A\n* **Market data** — 20+ years of daily stock and FX, US and global\n* **Custom datasets** — proprietary and third-party integrations for enterprise\n\n### Use cases\n\n**I. Peer comparison in Excel** — pull financials, strategy, and risk factors across competitors directly from filings.\n\n![uploaded image](/media/?type=post&id=100809&key=user_uploads/626328/99b5fdce-2a4b-4053-a6c1-6b94ec87d578)\n\n**II. Corporate structure mapping** — trace ownership and financials through complex group structures from UK filings.\n\n![uploaded image](/media/?type=post&id=100809&key=user_uploads/626328/c1665625-8a07-414d-ac76-b7ecd356b12b)\n\n**III. Earnings call analysis** — review management commentary and analyst Q&A for sentiment and evasive answers.\n\n![uploaded image](/media/?type=post&id=100809&key=user_uploads/626328/7fb98502-0b18-4486-b7f7-5b6655161588)\n\n**IV. Document verification** — cross-reference every number against source, catch rounding deltas and inconsistencies.\n\n![uploaded image](/media/?type=post&id=100809&key=user_uploads/626328/c11d5c2d-d1d3-4328-a4bb-63dd13aba8d6)\n\n### Asks\n\nLooking to connect with finance professionals (banking, PE, credit, hedge funds, wealth) who want their AI assistant to actually do useful work.",
        "url": "https://www.ycombinator.com/launches/QDx-fira-mcp-financial-datasets-in-claude-and-excel",
        "votes": 14,
        "created_at": "2026-05-05T19:11:01.299Z"
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      {
        "id": 88048,
        "title": "Fira: Agentic AI Analyst",
        "tagline": "Accelerating financial analysts with source-cited insights and verified calculations from complex company filings",
        "body": "**Fira** is building an agentic AI analyst for financial research and automation, starting with UK investment firms. Today, we accelerate analysts with source-cited insights and verified calculations from complex company filings.\n\n<https://youtu.be/a8C9TifdUOg>\n\n# Problem\n\nAnalysts at investment banks and boutique M&A firms waste tons of time digging through hundred-page annual reports to prepare pitch decks and models. General LLM tools aren't good enough for the job — lacking accuracy, domain-specific data, and output verification. The problem extends to senior professionals who need to quickly understand new topics deeply while staying grounded in truthful data sources.\n\n---\n\n# Solution\n\nFira saves analysts time by instantly searching, analyzing and citing UK company filings. It reads multiple filings and reports (including 500 page long and scanned documents) to provide source-cited answers and verifiable calculations. We cover hundreds of public UK companies, integrate with Companies House for private company data, and allow to upload your documents.\n\n---\n\n# Use cases\n\n**I. Breakdown detailed financial and operational KPIs in seconds**\n\n![uploaded image](/media/?type=post&id=88048&key=user_uploads/626328/d03ed2eb-89ea-49f2-af3e-895cf89dd3a7)\n\n**II. Perform general research on data scattered across reports and filings**\n\n![uploaded image](/media/?type=post&id=88048&key=user_uploads/626328/af63b5d1-c1ba-4551-9168-91c8b3a8ca8f)\n\n**III. Fira calculates financial metrics it can't find, providing transparency in formula and variables used**\n\n![uploaded image](/media/?type=post&id=88048&key=user_uploads/626328/d65b3dba-a6ce-4653-86e9-9ddedcb5d0a4)\n\n# Asks\n\nLooking to connect with senior professionals and analysts at investment banks, M&A advisory firms, hedge funds, and wealth management firms. Especially in the UK. If you work in finance or know someone who does, we'd love an intro. Book a demo [here](https://firaresearch.com) or email us at [alex@firaresearch.com](mailto:alex@firaresearch.com).\n\n# About us\n\nAlexey and Alex are both technical founders, met 9 years ago at university and been close friends since.\n\nAlexey was CTO and co-founder of [resume.io](http://resume.io), one of the largest resume builder websites (acquired in 2021). He’s also an author of wouter, a React router library with 7k stars and 580k downloads/month, and a regular tech conference speaker.\n\nAlex was the founder and CEO of Hashscan, on-chain user analytics startup. Previously, he built a popular crypto porftolio tracker app Hodler (sold in 2022).\n\n![uploaded image](/media/?type=post&id=88048&key=user_uploads/626328/13c0b9c8-06c4-4307-b446-8edc81b35aab)\n\n# Links\n\nWebsite: <https://firaresearch.com>\n\nLinkedIn: <https://www.linkedin.com/company/fira-ai/>",
        "url": "https://www.ycombinator.com/launches/Mu8-fira-agentic-ai-analyst",
        "votes": 35,
        "created_at": "2025-02-26T01:51:02.509Z"
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "BlindPay is a stablecoin API that enables companies to send and receive money worldwide using fiat money, stablecoins and multiple blockchains. We handle all the complex compliance and regulatory requirements, so companies can focus on their core business.",
    "one_liner": "Stablecoin API for global payments",
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    "industry": "Fintech",
    "subindustry": "Fintech -> Payments",
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        "linkedin_url": "https://www.linkedin.com/in/joaoborgesjr/",
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        "full_name": "Gustavo Marinho",
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        "title": "BlindPay - Stablecoin API for Global Payments",
        "tagline": "Core Infrastructure for LatAm Payments",
        "body": "### **TL;DR**\n\nBlindPay is a stablecoin API that helps companies navigate LatAm's complex financial regulations while enabling fast and affordable global payments. Watch our demo [here](https://www.youtube.com/watch?v=N9hHISlGp9Y).\n\n### **The Problem**\n\nBusinesses face significant hurdles when sending and receiving global payments:\n\n* Traditional methods rely on correspondent banks, adding fees (1.5-6% for B2B) and delays of 2-5 business days or more. Bank transfers typically require 2-4 intermediaries between smaller countries, with costs reaching hundreds of dollars. \n* Frequent fluctuations in Latin American currencies, coupled with extreme inflation rates (over 50% annually in some countries), make international payments unpredictable and risky. \n* Complex regulations and strict compliance rules across jurisdictions require different documentation for each institution. \n* Fragmented payment landscapes across countries require integration with multiple local payment systems (like SPEI, Pix, PSE), making implementation resource-intensive\n\n### **Our Solution**\n\nOur API integrates seamlessly with your existing workflows. With BlindPay you can:\n\n* Send and receive payments using fiat money and stablecoins\n* Get competitive FX quotes and low transaction fees\n* Connect directly to local instant payment systems across Latin America\n* 24/7 payments with instant settlement\n* Ensure compliance through blockchain screening, tiered KYC/KYB levels, and continuous transaction monitoring\n\nExpand your global reach while reducing costs and transaction times by up to 80%. Powered by stablecoins and blockchain, our platform eliminates the delays, high fees, and regulatory barriers of traditional payment systems.\n\n![uploaded image](/media/?type=post&id=87070&key=user_uploads/2098545/f81c874e-a8e7-4a92-ab1e-de8897529a63)\n\n### **Developer Experience**\n\nAdd fiat gateways to your apps with minimal code. Our SDKs support multiple languages and frameworks, backed by a developer-friendly REST API with public OpenAPI documentation.\n\n* Support for multiple blockchains and major stablecoins\n* Direct integration with local payment systems like SPEI (Mexico), Pix (Brazil), PSE (Colombia) and Transfers (Argentina)\n* Separate sandbox and production environments with unique API keys and webhooks\n* Real-time payment tracking and transaction monitoring\n\n### **Team**\n\n![uploaded image](/media/?type=post&id=87070&key=user_uploads/2098545/d3fdd3f4-c653-427c-8e06-159b1ac4809f)\n\n**Bernardo Simonassi (CEO)** has been shaping the stablecoin payments industry for the past 3 years, where he developed the first payroll platform powered by stablecoins. Previously at PicPay, he developed instant payment solutions serving 60M+ users.\n\n**Gabriel Lyra (CTO)** led software engineering at LendingClub, where he architected and implemented critical financial infrastructure handling $50B in monthly loan transactions. Previously at AWS, he optimized infrastructure scripts that reduced monthly costs from $15M to $1M.\n\n**João Borges (COO)** is a prominent leader and entrepreneur, best known for founding one of Brazil's largest blockchain startups. In its first year of operation, he successfully scaled the company to seven-digit revenue and raised millions of dollars from top-tier venture capitalists. João is also an active contributor to the Nouns DAO ecosystem and has been recognized on the Forbes 30 Under 30 list.\n\n**Gustavo Marinho (CPO)** is a former product leader at top-tier Brazilian fintechs, where he specialized in consumer-facing financial solutions for Latin America. Previously at PicPay, he built instant payment solutions and credit products, successfully growing a personal loan portfolio to over $100M within six months of launch. \n\n### **Our Ask**\n\nHey founders, are you building a product that needs global payment functionality? Email us at [founders@blindpay.com](mailto:founders@blindpay.com)\n\nBlindPay is the simplest way to integrate global payments into your product:\n\n* Neobanks & fintech\n* Payroll solutions\n* Remittance providers\n* Wallet infrastructure providers\n* Traditional FX industry\n* Stablecoin aggregators\n* Marketplaces & platforms\n* Gaming & crypto apps\n* Billing & invoicing software\n* Freelancer & gig economy tools",
        "url": "https://www.ycombinator.com/launches/MeM-blindpay-stablecoin-api-for-global-payments",
        "votes": 66,
        "created_at": "2025-01-22T22:26:34.751Z"
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    "long_description": "Blaxel is the infrastructure foundation for autonomous agents.\r\n\r\nEngineered for the way agents actually run, Blaxel gives builders deep control over compute (sandboxes), storage (shared filesystem), and networking as built-in infra primitives.\r\n\r\nUnlike traditional sandboxes that expire or suffer from cold starts, our sandboxes automatically scale to zero after 1s of inactivity and resume in under 25ms with full memory state preserved — allowing you to keep millions of secure sandboxes on standby indefinitely.",
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        "is_active": true,
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        "title": "Blaxel — AWS for AI agents",
        "tagline": "Powering the next trillion AI agents.",
        "body": "**tl;dr**: Yesterday’s cloud can’t power tomorrow’s AI. Blaxel is a cloud infrastructure built for AI agents. Our computing platform gives AI Builders tools, infra, and developer experience optimized to build and deploy agentic AI — with a twist: your agents can also take the wheel.\n\nhttps://www.youtube.com/watch?v=aISExQg14qg\n\n### Problem\n\nOur team of 6 co-founders previously built and sold a data platform to OVHcloud, which eventually became their entire Analytics product suite. What we saw during that time is that **the current world’s infrastructure** **wasn't built for the AI revolution that's coming**.\n\nTraditional clouds were built almost 20 years ago. Their architecture and service sprawl weren't designed for agentic workloads. Nor was the UX thought for the developers who build them.\n\nNot only that, but the economics don't make sense anymore. As AI agents become more autonomous, they're racking up huge bills from LLM calls, serverless tasks, and network bandwidth.\n\nIn the next decade, we're looking at billions or even trillons of AI agents coming online, each needing computing power, memory, and connectivity in every direction. The world’s current infrastructure isn't just unprepared, it's completely inadequate.\n\n### Solution **💡**\n\nWe're creating **a new kind of infrastructure**. One that's not only built to make agents, but also to be operated by them.\n\nBlaxel is a complete computing platform with all services designed and optimized for both AI Agents and their Developers — from the hardware to the user experience.\n\nWe offer two levels of APIs to give you full flexibility:\n\n**1-** Our **high-level platform** lets developers to fast-track deploying agents without reinventing the wheel:\n\n* Agent deployments as serverless autoscalable APIs — fully framework-agnostic\n* MCP servers hosting\n* AI gateway — with features like token rate limiting or model routing and fallbacks\n* Built-in observability\n* GitHub synchronization\n\n![uploaded image](/media/?type=post&id=90942&key=user_uploads/2264960/665aa3c9-5d63-4ce6-8c16-bbb6e2c6537e)\n\n**2-** Our flexible **low-level API** gives both builders and agents access to our core compute infrastructure to run agentic workloads fast and reliably:\n\n* Sandboxes with &lt;25ms boot time — designed for agents to execute code or commands\n* Batch processing jobs\n* Headless browser VMs _(coming soon!)_\n* Programmable AI gateway _(coming soon!)_\n\n![uploaded image](/media/?type=post&id=90942&key=user_uploads/2264960/8e2c837d-f329-44b4-beec-0f80d75daa10)\n\nPioneering teams are already building the next wave of agents on Blaxel. Don't get left behind:\n\n* Email us: [founders@blaxel.ai](mailto:founders@blaxel.ai)\n* Book a demo: [blaxel.ai/contact](http://blaxel.ai/contact)",
        "url": "https://www.ycombinator.com/launches/Neo-blaxel-aws-for-ai-agents",
        "votes": 75,
        "created_at": "2025-06-02T15:53:06.496Z"
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    "id": 30402,
    "name": "Kashikoi",
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    "website": "https://www.getkashikoi.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Kashikoi is a simulation engine to benchmark AI agents. We generate CPU friendly world models that autonomously interview agents and generate deep behavioral assessments. We built a similar technology at Moveworks which was used to ship 250+ enterprise agents to customers daily.",
    "one_liner": "Simulation Engine for Benchmarking AI Products",
    "team_size": 2,
    "industry": "B2B",
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    "launched_at": 1748454120,
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        "full_name": "Aaksha Meghawat",
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        "founder_bio": "Founder, Kashikoi. Aaksha led the Simulation & Evaluation stack at Moveworks(ServiceNow) shipping 250+ customized enterprise ready agents to Fortune 500 and federal agencies. Aaksha has done award winning NSF sponsored research in Transformers at CMU (long before OpenAI made them cool). She shipped edge speech recognition models on 1bn+ iPhones (for the most esoteric dialects you can think of) at Apple. The innovation behind this was nominated for a Best Paper at Interspeech 2021.",
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      {
        "id": 90990,
        "title": "Kashikoi - Simulation Engine for Benchmarking AI Agents",
        "tagline": "Autonomously interview your Agents!",
        "body": "Hey YC! \\\nWe are [Tim](https://www.linkedin.com/in/timmichaud/) and [Aaksha](https://www.linkedin.com/in/aaksham/) - cofounders of Kashikoi. [Kashikoi](https://www.getkashikoi.com) is a simulation engine to benchmark GenAI Agents. We generate CPU friendly world models that autonomously interview agents and generate deep behavioral assessments.\n\n# **The Problem**\n\nBuilding high-performing AI agents is becoming increasingly complex. Teams face many challenges:\n\n* Managing prompt bloat and keeping up with endless prompt tuning cycles.\n* Evaluating their agents (or competitors') meaningfully and efficiently.\n* Understanding agent performance in ways that reflect real-world values and expectations—not just public benchmarks.\n\nDespite growing interest and investment, most solutions rely heavily on prompt engineering, public benchmarks, or surface-level observability. These approaches often mislead more than they inform, creating a false sense of progress.\n\n# **The Solution**\n\n![uploaded image](/media/?type=post&id=90990&key=user_uploads/267393/5573f5c1-baf0-4fc5-b58f-d6fc289fb8f2)\n\nToday’s “LLMs” are adaptive systems which run test time adaptation loops behind that tiny “Thinking…” blinking on the screen. We are building a scalable version of test time adaptation and inference scaling a.k.a World Models that bring the power of these techniques to you.\n\nSimply put you can simulate highly customized benchmarks, diverse data and align your evaluations while maintaining all of these for the long run, all without writing prompts! Our world models unlock automatic prompt optimization and detecting regression test staleness as fun side effects.\n\nLLM based Systems are getting smarter and so should you using our World models!\n\nCheck out our simulation engine adaptively interviewing RAG Agents and multi-turn evaluation in action [here](https://www.loom.com/share/7b3bdb899b06433fbc0636df487c6133?sid=6dd87cdc-495e-48e4-bb7a-971b1430cae5).\n\n# Why Us\n\n* Tim and Aaksha used similar world models tech at Moveworks to massively reduce dev cycles for shipping 250+ customized enterprise ready agents.\n* Aaksha has done cutting edge research in Transformers at CMU (long before OpenAI made them cool). She shipped edge speech models on 1bn+ iPhones. The innovation behind these models was published as a paper at Interspeech 2021 and nominated for a Best Paper Award that same year.\n* Tim has found many high impact security vulnerabilities throughout his career. One of his top bug discoveries was in all Qualcomm GPS chips leading to a 50 mile 0-click exploit that had no mitigations. Tim has many [public CVEs](https://www.inulledmyself.com/2023/05/using-ai-to-find-software.html) for a variety of Apple products, including: Safari, MacOS, iOS, tvOS, & iTunes.\n\n# Our Ask\n\nSign up for our waitlist at [getkashikoi.com](http://getkashikoi.com), or email us at [founders@getkashikoi.com](mailto:founders@getkashikoi.com) if you or someone you know wants:\n\n* Instant evals on your agent (or a competitor’s 😉) and we’ll generate [such a report](https://www.notion.so/NewAgent-Benchmark-Report-1db104cde9e88066b62ac3d68fb6c878?pvs=21) for you.\n* Making advanced features—like automatic prompt optimization, world models, and inference scaling—work seamlessly for you.\n* Reliable prompt free evaluations that are aligned with your values and expectations (which we auto-encode in a special edge-friendly world model for you).\n* Don’t come to us if:\n  * You love writing prompts\n  * You trust public benchmarks\n  * You think that good observability is enough to make your agent win\n  * You aren’t ready to have an honest conversation about your agents’ performance\n* Jokes aside 😅, if you know enterprises building agents suffering from prompt bloat, please (pretty please 🥺) send them our way!",
        "url": "https://www.ycombinator.com/launches/Nfa-kashikoi-simulation-engine-for-benchmarking-ai-agents",
        "votes": 18,
        "created_at": "2025-06-03T21:48:35.068Z"
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    "website": "https://golf.dev/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Golf gives enterprises visibility into shadow AI and control over AI agents and MCP. See what's connected, enforce policies, and generate audit trails - all from one place.",
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    "subindustry": "B2B -> Security",
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        "full_name": "Wojciech Błaszak",
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        "founder_bio": "Wojciech is the cofounder & CEO @ Golf.\n\nWojciech started building first company at 14, scaling it to $200k rev. He dropped out of university after one semester to keep building full-time. He has previously worked on multiple AI products, including an AI SDR and infrastructure for AI agents. Wojciech also started a community for young Polish hackers and scientists.",
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        "full_name": "Antoni Gmitruk",
        "title": "Founder/CTO",
        "founder_bio": "Antoni is the cofounder & CTO @ Golf.\n\nAntoni started building at 15 by creating a fully automated 3D printer. He dropped out of university after one semester to keep building full-time. He has previously worked on multiple AI products, including an AI SDR and infrastructure for AI agents. Antoni also started a community for young Polish hackers and scientists.",
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        "title": "Golf:  Open-source platform for shipping production MCP servers",
        "tagline": "We provide the tooling to build and operate MCP servers in production - auth, tracing, and a deployment pipeline included.",
        "body": "Hi YC,\n\nWe’re Wojciech and Antoni -  high school friends who’ve been building together since we were 14. We're incredibly bullish on a future where AI agents have their own internet through which they access our services - so much so that we dropped out of university to build Golf.\n\n**Golf lets you ship a production-ready MCP server without worrying about the plumbing.** You just write the tools, prompts, and resources you want agents to call. Golf handles everything else - routing, auth, telemetry, error reporting, and deployment. Then you can observe and manage it through our gateway.\n\nhttps://youtu.be/u9ar4w2uE7E\n\n# **The problem**\n\nOver the past few weeks, we spoke with over 40 teams building MCP servers. Everyone hit the same walls: wiring up authentication, figuring out how to trace agent calls, setting up working transports, and debugging behavior in production. The MCP spec doesn’t cover these parts. Teams told us it takes **2-4 weeks** to get that to production.\n\n# **What we built**\n\n**GolfMCP** is an open-source framework that gives you a clear, file-based structure to define what your agent can call. No decorators, no spec knowledge, no boilerplate - just write your logic.\n\n**Golf Gateway** is the hosted layer that runs and observes your server. golf deploy gives you a live server in under 60 seconds, with real-time traces, tool usage, and error monitoring built in.\n\n![uploaded image](/media/?type=post&id=90569&key=user_uploads/1366358/b035bdc4-02c2-42d5-a230-ad38be34dfa9)\n\n# **Early traction**\n\nWe’re already running Golf in production with companies, and we’ve got more landing this week. \n\n**CTAs**\\\nIf you are looking to ship server for your company, schedule a demo of our platform here: https://golf.dev\\\nAlso we’d love to get your feedback, and we’re happy to help teams get to production faster. Reach us at [founders@golf.dev](mailto:founders@golf.dev)",
        "url": "https://www.ycombinator.com/launches/NYn-golf-open-source-platform-for-shipping-production-mcp-servers",
        "votes": 74,
        "created_at": "2025-05-21T01:15:30.127Z"
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    "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",
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    "country": "GB",
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        "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",
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        "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%",
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      {
        "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",
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        "votes": 110,
        "created_at": "2025-05-21T13:07:32.512Z"
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    "one_liner": "The data gateway for agents.",
    "team_size": 2,
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    "launched_at": 1746399469,
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        "body": "**TL;DR:**\n\nCapacitive lets anyone build agents that work on their behalf. Connect your platforms to us once, “chat” freely with your data, and automate workflows using only your words.\n\n[Launch Video](https://youtu.be/7d0EwiiHirQ)\n\n**🔋 Capacitive, the solution:** \n\nWork happens in what can feel like a million places — Slack, Confluence, Google Drive, HubSpot, Jira… you name it. Capacitive is a delightfully taut web platform that allows you to run work across all of those platforms and hundreds more, all from one place.\n\nConnect your platforms to us once and “chat” with your data freely… we make asking one-off questions like “what’s my monthly burn?” or performing tasks like “find all clients in my pipeline who haven’t created an account and follow up with them” brilliantly simple. And building lightweight agents for repetitive tasks happens with just a few sentences.\n\nWith granular tool filtering, robust role-based access controls, and airtight security permissioning, Capacitive allows knowledge workers and companies alike to turbocharge their operations using AI worry-free.\n\n🤝 **The Team**\n\nKevin and Rohan have known each other for five years, having attended the Phillips Exeter Academy and subsequently Yale together.\n\n🎯 **Asks**\n\nOur Public Beta is going live on May 30th. Visit [www.capacitive.ai](http://capacitive.ai) to get started today, for free!\n\n![uploaded image](/media/?type=post&id=90842&key=user_uploads/2250726/87ff870c-427a-4e35-a81d-cba6a09a323f)\n\n",
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        "full_name": "Shreyash Nigam",
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        "id": 90330,
        "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! 🦛✨",
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        "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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        "user_id": 429685,
        "full_name": "Xin Ding",
        "title": "Founder/CEO",
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        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Backend",
        "salary_range": "$150K - $200K",
        "equity_range": "0.50% - 1.00%",
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        "id": 90363,
        "title": "Attune - Faster Builds, Zero Effort",
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        "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).",
        "url": "https://www.ycombinator.com/launches/NVT-attune-faster-builds-zero-effort",
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        "created_at": "2025-05-13T17:46:08.929Z"
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    "team_size": 4,
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        "full_name": "Bereket Engida",
        "title": "Founder/CEO",
        "founder_bio": "I’ve spent the past few years building developer tools and contributing to open source projects, mostly in TypeScript - including libraries like Better Call, Better Fetch, Loglib and Better Auth. Before that, I worked across several products, which is where I first got obsessed with making dev infra more usable. I care a lot about good DX, clean APIs, and building things that actually ship.",
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        "title": "Better Auth is joining Vercel",
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        "title": "Better Auth, an authentication tool by a self-taught Ethiopian dev, raises $5M from Peak XV, YC | TechCrunch",
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        "title": "Better Auth - The Authentication Framework for TypeScript",
        "tagline": "The fastest growing Auth framework for TypeScript: 13K stars + 100K weekly downloads!",
        "body": "Hey! 👋 We’re building Better Auth - a comprehensive, framework-agnostic authentication framework for TypeScript. It lets you roll your own auth directly on your backend and database, without relying on 3rd party services. From basic sign-ins to complex enterprise systems all with great DX.\n\nhttps://www.youtube.com/watch?v=j_HjHmprVOs\n\nAuth has been a pain point for many developers in the TypeScript ecosystem for a while. Other open-source libraries require a lot of additional code for anything beyond basic authentication. So, we set out to build a comprehensive auth library - framework-agnostic, with a robust set of features out of the box, a plugin ecosystem for everything else you might need, and great documentation.\n\n![uploaded image](/media/?type=post&id=90320&key=user_uploads/1184116/dec3dc74-8395-4d83-b062-c2f3271b8164)\n\nSince launching v1 just 5 months ago:\n\n* **13K+ GitHub stars** and **350K+ monthly npm downloads**\n* We've grown into one of the **most influential** and **well-loved** open source projects in the TypeScript ecosystem.\n* Used in production by great teams including YC companies and major OSS projects including [folo](https://github.com/RSSNext/Folo), [same](https://same.new/), [dokploy](https://github.com/Dokploy/dokploy), [zero](https://github.com/Mail-0/Zero), [onejs](https://github.com/onejs/one) and many more.\n* We’re the recommended auth library by **Next.js, Nuxt, Astro**, and other top JS frameworks.\n* A thriving community with **5K+ members on Discord,** **7K+ followers on X**, and a growing ecosystem of adjacent libraries built by community members.\n* Featured by creators like Theo, Dev Ed and more\n\nTo take it further, and after seeing the pain points of our current users, we're building an **infrastructure layer** on top of the framework to extend the library with functionality we can't offer through the framework alone:\n\n* A comprehensive admin dashboard with user management & analytics\n* Bot/fraud/abuse detection\n* Global session storage\n* and more…\n\nTo be clear – we’re not building a third-party auth service. Our goal is to make rolling your own auth so ridiculously easy that you’ll never need one.\n\nGet started with the library here: [better-auth.com/docs/installation](http://better-auth.com/docs/installation)\n\nJoin the waitlist for infra: http://better-auth.build/\n\nStar the repo: https://github.com/better-auth/better-auth",
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    "name": "Tinfoil",
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    "long_description": "Tinfoil makes it easy to make your AI workloads secure and provably private. You get the privacy of on-prem deployments, while running on the cloud. It's like end-to-end encrypted messaging but for your AI applications. \r\n\r\nWe’ve built a full-stack platform on top of the latest NVIDIA GPUs offering confidential computing capabilities, meaning that you don’t have to trade off performance for privacy. We integrate a suite of recent advances in secure hardware technologies, in particular NVIDIA’s confidential compute mode available on Hopper and Blackwell. When combined with Tinfoil’s software stack, companies can prove their security claims like \"we can't see and don’t log your queries.” Tinfoil guarantees that all data always stays private and cannot be accessed by anyone other than the end user -- not even by Tinfoil or the cloud provider it’s processed on. Everything can be made end-to-end encrypted and private with Tinfoil. \r\n\r\nThe founding team combines deep academic and industry experience in security and Internet protocols. Tanya was previously a systems engineer at Cloudflare, where she built Internet security protocols used by billions, and contributed to the Workers AI platform. Jules and Sacha hold PhDs from MIT, where they worked on secure hardware, cryptography, and privacy technologies. Jules has also worked at NVIDIA on their confidential computing team. Tinfoil was born from our personal frustration with the false choice between access to powerful AI and the massive data privacy implications of deeply integrated AI.\r\n\r\nAI is a universal tool that becomes part of our personal lives and business workflows. In the process, it needs access to all personal, private, and proprietary data. Right now, the only solutions are data processing agreements (i.e., \"pinky promises\"), band-aids like PII redaction that don't work in practice, or AI locally/on-prem, which doesn't scale. Tinfoil promises to unlock significantly deeper AI adoption and integrations by making it easy to obtain true privacy, just as TLS on the Internet enabled e-commerce to flourish by securing credit cards on the network.\r\n\r\nToday we offer several self-serve products: \r\n\r\n- A consumer-facing chatbot that keeps your chats end-to-end encrypted and provides zero-access inference with powerful open-source models like Kimi, Gemma, and GLM. You can try it out for free: https://chat.tinfoil.sh\r\n\r\n- A developer-friendly API that allows you to build AI applications where all user data is kept private and we as the inference provider cannot see any of the prompts. Our SDKs make sure that all relevant security measures are checked for you before even sending a single byte of data. Learn more:https://docs.tinfoil.sh \r\n\r\n- An advanced confidential computing platform we call Tinfoil Containers that allows you to secure any Docker application. We make it easy to deploy your own logic and applications inside secure enclaves and prove to the world what code is running inside. This enables attested workloads and publicly verifiable privacy policies for sensitive applications. Learn more: https://tinfoil.sh/containers ",
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    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/Tinfoil/",
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        "full_name": "Tanya Verma",
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        "founder_bio": "Co-founder @ Tinfoil | Systems, Cryptography and AI @ Cloudflare | CubeSats & CS @ UIUC",
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        "full_name": "Jules Drean",
        "title": "Founder",
        "founder_bio": "Jules has an MIT PhD in secure hardware and confidential computing. He has industry experience working at Microsoft Research and NVIDIA on the technologies underlying Tinfoil. During his PhD, Jules has built secure enclaves from the ground up and studied how to attack and defend these systems against advance microarchitectural attacks. His work also looked at using trusted hardware to securely deploy advanced cryptographic primitives such as FHE and MPC.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jdrean",
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        "user_id": 2540941,
        "full_name": "Sacha Servan-Schreiber",
        "title": "Founder",
        "founder_bio": "Co-founder of Tinfoil | PhD at MIT in cryptography\n\nPersonal website: sachaservanschreiber.com ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/sacha-servan-schreiber-308341305",
        "x_url": "https://x.com/sachaservan",
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      {
        "id": 90590,
        "title": "Tinfoil: Verifiable Privacy for Cloud AI",
        "tagline": "We host models and AI workloads on the cloud while guaranteeing zero data access and retention",
        "body": "Sending your most sensitive or proprietary data to OpenAI et al?\n\nSick of deals getting stalled during enterprise or government security reviews?\n\nHate deploying on various configurations of on-prem infrastructure environments?\n\nSay less ✋\n\nWe’re [Tanya](https://www.linkedin.com/in/tanya-verma-130a23124/), [Jules](https://www.linkedin.com/in/jdrean/), [Sacha](https://www.linkedin.com/in/sacha-servan-schreiber-308341305/) and [Nate](https://www.linkedin.com/in/nate-sales/) from[ Tinfoil](https://tinfoil.sh/). What we’re building at Tinfoil sidesteps these concerns because we can host models while guaranteeing zero data access and retention.\n\nWe let you run powerful models like Llama, Deepseek R1 on cloud GPUs without you having to trust us – or the cloud provider – with your private data.\n\nSince AI performs better the more context you give it, we think solving AI privacy will unlock more valuable AI applications, just how TLS on the Internet enabled e-commerce to flourish knowing that your credit card info wouldn't be stolen by someone sniffing internet packets.\n\nhttps://youtu.be/wnwI22qT-QQ\n\n**Who we are**\n\nWe come from backgrounds in cryptography, security, and infrastructure. Jules did his PhD in trusted hardware and confidential computing at MIT, and worked with NVIDIA and Microsoft Research on the same, Sacha did his PhD in privacy-preserving cryptography at MIT, Nate worked on privacy tech like Tor, and I (Tanya) was on Cloudflare's cryptography team.\n\n We were unsatisfied with band-aid techniques like PII redaction (which is actually undesirable in some cases like AI personal assistants) or “pinky promise” security through legal contracts like DPAs. We wanted a real solution that replaced trust with provable security, and addressed our personal frustration with the false choice between exploring cutting-edge AI capabilities and personal privacy.\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXcicUJrVGkJrvHFqW2CaNEpGzvSfbjySaAR3k-Q8fbf56JtXg8xAJa5MJrYn-RIdJjFirmZ4khWay_UpV6WhnZKZEE9ApI5HX97jRKGw4mJOTblXrujRY_9xcCvGPL139p2QaKd1g?key=xi6EV3GMAYXvlmorGP948w)\n\n**The magic sauce**\n\nRunning models locally or on-prem is an option, but can be expensive and inconvenient. Fully Homomorphic Encryption (FHE) is not practical for LLM inference for the foreseeable future. The next best option is using secure enclaves: a secure environment on the chip that no other software running on the host machine can access. This lets us perform LLM inference in the cloud while being able to prove that no one, not even Tinfoil or the cloud provider, can access the data. And because these security mechanisms are implemented in hardware, there is minimal performance overhead.\n\nUp until recently, secure enclaves were only available on CPUs. But NVIDIA confidential computing recently added these hardware-based capabilities to their latest GPUs, making it possible to run GPU-based workloads in a secure enclave.\n\nBelieve it when you see it, but Tinfoil has negligible performance overhead despite the strong security & privacy guarantees.\n\n**Getting Started**\n\n**The best part is you can start using confidential AI chat and inference with Tinfoil today!**\n\n**Try our private chat: [tinfoil.sh/chat](http://tinfoil.sh/chat).**\n\n[**https://www.youtube.com/watch?v=FuFszT0_vXk**](https://www.youtube.com/watch?v=FuFszT0_vXk)\n\n**Build with our API:** Drop-in replacement for the OpenAI chat-completions API with Tinfoil\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXfBq_bx4bvZAzdB9BTzMg9KSE8UB2bKQO5uqfF5eoZkEWZFUtlbFnZpeD-m_PwaCVgUWftTt3QDLTW-r84u2dvUEGQ0ddbbQuq082ClI48l2cY4jWX-kWG1G6ZfwjNh8GN-EdAVJg?key=xi6EV3GMAYXvlmorGP948w)\n\nWe support several popular open source models like Deepseek R1 70B, Llama3.3 70B, Mistral 3.1 24B. Missing your favorite model? Just ask us to add it!\n\nTry out our free version running Llama3.3 70B in [Colab](https://colab.research.google.com/drive/1DhpUSmSWjxERnEo3U0qyAyApfcdIhvMv?usp=sharing).\n\nSee how Nate psychoanalyzes himself by sending all his iMessage chats to Tinfoil!\n\nhttps://www.loom.com/share/2381c02ba51043528c6d3bdf61270bc0?sid=9ea0e955-ae68-4ce4-9c86-d06cab18d25c\n\n**Deploy your AI Application**: Make your AI application enterprise-ready in a matter of minutes. Here's a demo of how you can use Tinfoil to run a deepfake detection service that could run securely on people's private videos:\n\nhttps://www.youtube.com/watch?v=_8hLmqoutyk\n\nWe encourage you to be skeptical of our privacy claims. Verifiability is our answer. It’s not just us _saying_ it’s private; the hardware and cryptography let _you_ check. Here’s a guide that walks you through the verification process:[ ](https://docs.tinfoil.sh/verify)https://docs.tinfoil.sh/verification/attestation-architecture.\n\n**The Ask**\n\nIf you think this sounds interesting, or too good to be true, contact us at [**founders@tinfoil.sh**](mailto:founders@tinfoil.sh)**!**\n\nWe’d love to hear from you, whether you’re a:\n\n* startup looking to sell into regulated industries\n* government agency that does everything on-prem but doesn’t trust your AI team to handle sensitive data\n* neocloud trying to secure enterprise customers in regulated industries that don’t migrate from the big clouds to you\n* company providing your employees dead-simple confidential LLM chat app\n\nYou can also learn more on our [**blog**](https://tinfoil.sh/blog), and subscribe to our [**LinkedIn**](https://www.linkedin.com/company/tinfoil/) and [**Twitter**](https://x.com/TinfoilAI) to follow updates!",
        "url": "https://www.ycombinator.com/launches/NZ8-tinfoil-verifiable-privacy-for-cloud-ai",
        "votes": 44,
        "created_at": "2025-05-21T14:22:18.121Z"
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    "id": 30459,
    "name": "Chiron",
    "slug": "chiron",
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    "website": "https://projectchiron.org",
    "all_locations": "London, England, United Kingdom",
    "long_description": "Chiron is an iPad app that understands math as it’s written - like Grammarly for algebra. We’re both Oxford math grads, have tutored for a decade, and we’re creating the future of learning which will be entirely 1-on-1.",
    "one_liner": "Grammarly for Math ✏️",
    "team_size": 2,
    "industry": "Education",
    "subindustry": "Education",
    "launched_at": 1748069202,
    "tags": [
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      "Edtech"
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    "batch": "Spring 2025",
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    "city": "London",
    "country": "GB",
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        "user_id": 1522067,
        "full_name": "James Booth",
        "title": "Founder/CEO",
        "founder_bio": "English, 24, Oxford math grad. Figuring out neurosymbolics for math.",
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        "linkedin_url": "https://www.linkedin.com/in/max-booth-132928302/",
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    "launches": [
      {
        "id": 90706,
        "title": "Chiron - Grammarly for Math ✏️",
        "tagline": "The Booth Brothers are building an iPad app that understands math as it's written",
        "body": "Hey there 👋\n\nWe’re [James](https://x.com/J4mesBooth) and [Max](https://x.com/MaxB00th) - brothers and cofounders of [Chiron](https://projectchiron.org).\n\n# 📌 **TL;DR**\n\nChiron is an [iPad app](https://apps.apple.com/us/app/project-chiron/id6502346822) that understands math as it’s written - like Grammarly for algebra. We’re both Oxford math grads, have tutored for a decade, and we’re creating the future of learning which will be entirely 1-on-1.\n\n[Launch Video](https://youtu.be/Ec8Nwe0EaSU)\n\n# ❌ **Problem**\n\nWith AI that’s so great at math, why can’t it teach at near-human quality?\n\n* Math is handwritten ✏️\n* Math has to be practiced not read 🧮\n* AI is rubbish at spotting _your_ mistakes 🔍\n\n# ✅ **Solution**\n\n* Freeform writing on a whiteboard app ✍️\n* Accuracy of a calculator with symbolic logic 🔢\n* Real-time feedback on every stroke (&lt; 300ms) ⚡\n\n# ⚙️ **How we do it?**\n\nWith tens of thousands of lines of Python and Wolfram Language code. Writing on an iPad, we convert the stroke data to LaTeX, parse it, ask a million symbolic questions about it with reference to the problem’s _ground truth_ (the lines with a blue index), and assess whether it is right, wrong or something in between.\n\n![uploaded image](/media/?type=post&id=90706&key=user_uploads/1522067/b06893f5-bab0-4021-b09e-c8d38b33e4ee)\n\nWe do **not** rely on the vibes of a language model to assess the details of their working - too slow and unreliable. Many students give up on LLMs for genuine collaboration when they mislead them on topics the student finds difficult.\n\n**We can handle a lot of math already.**\n\n![uploaded image](/media/?type=post&id=90706&key=user_uploads/1522067/df464a12-f051-4c0a-8c03-90e660079c40)\n\n# **💡 Core insight**\n\nWe tried all the AI tutor desktop formulations we could imagine, but beyond the obvious interface challenge, AI is exceptionally poor at spotting the subtle mistakes students often make. LLMs are great at doing correct math, but much worse at pulling out an error within the many lines of messy student reasoning.\n\nWe started performing a symbolic analysis of the student’s working as context for the AI to boost accuracy - **but then we realised we could give this straight to the student.** This was when we started to feel the magic.\n\n# **🙏 Our Ask**\n\nSo far, _every_ single teacher we’ve demoed our iPad app to in person has immediately started work greenlighting a pilot. Let us know if you can introduce us to any math teachers teaching between Algebra I and Calculus I.\n\nAnd you can check out Chiron on the [App Store](https://apps.apple.com/us/app/project-chiron/id6502346822) now - or share with any students who might benefit from it!\n\n![uploaded image](/media/?type=post&id=90706&key=user_uploads/1522067/7b18b9c0-1e00-49fa-a8bb-d6ab7bb7d080)\n\nCheers, James & Max",
        "url": "https://www.ycombinator.com/launches/Nb0-chiron-grammarly-for-math",
        "votes": 105,
        "created_at": "2025-05-24T20:19:56.044Z"
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    "website": "https://clidey.com",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "WhoDB is an open-source platform for modeling organizations and running decisions on top of their data.\r\n\r\nIt lets teams define their core entities (customers, accounts, assets, workflows), the relationships between them, and the rules and objectives that govern how decisions should be made. WhoDB continuously ingests operational data and keeps this model up to date in real time.\r\n\r\nInstead of building dashboards, writing ad-hoc queries, or maintaining scattered business logic, teams express decisions declaratively—what should happen, under what conditions, and with what constraints. WhoDB evaluates those decisions automatically as data changes and produces actions, recommendations, or state updates.\r\n\r\nEverything is transparent and inspectable: data models, decision logic, and outcomes are fully auditable and can be extended in code.",
    "one_liner": "Turn scattered data into one platform for decision-making",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1747802459,
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    "isHiring": false,
    "nonprofit": false,
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    "demo_day_video_public": false,
    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/clidey",
    "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/clidey.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/clidey",
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    "primary_partner": {
      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
    },
    "founders": [
      {
        "user_id": 581232,
        "full_name": "Hemang Kandwal",
        "title": "Founder/CEO",
        "founder_bio": "He previously worked at Palantir and financial firms. Developed over 20 proof of concepts with many chosen for awards by BlackRock, J.P. Morgan, Craneware, and ARM.\n\nBuilding Clidey.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/hemangkandwal",
        "x_url": "http://x.com/hemangkandwal",
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      {
        "user_id": 1558575,
        "full_name": "Anguel Hristozov",
        "title": "Founder/CTO",
        "founder_bio": "Anguel has been solving tough problems for a long time. From fixing and managing his high school's laptop fleet to developing financial software with the goal of preventing another 2008 financial crisis, he's no stranger to experimentation, failure, and learning.\n\nBeyond code, he's dedicated to enriching his local community by organizing meetups, mentoring students, and continuously exploring new technologies and ideas.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/ahristozov",
        "x_url": "https://x.com/anguel_hh",
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        "title": "From Cloud IDE to DevOps: The Clidey Journey",
        "url": "https://podcasts.apple.com/us/podcast/32-peaking-with-anguel-hristozov-from-cloud-ide-to/id1804479570?i=1000720655588",
        "date": "Aug 05, 2025"
      },
      {
        "title": "The European startups that made it to Y Combinator’s spring batch | Sifted",
        "url": "https://sifted.eu/articles/y-combinator-spring-2025",
        "date": "Jun 23, 2025"
      },
      {
        "title": "Clidey 2025 Company Profile: Valuation, Funding & Investors | PitchBook",
        "url": "https://pitchbook.com/profiles/company/773945-20#research",
        "date": "Jun 15, 2025"
      },
      {
        "title": "Clidey X TBPN  - YouTube",
        "url": "https://www.youtube.com/watch?v=_lveZrvY2Jw&t=5441s",
        "date": "Jun 11, 2025"
      },
      {
        "title": "Can Clidey Become the Stripe Docs of Internal Developer Tools?",
        "url": "https://hiretop.com/blog4/clidey-automated-developer-documentation-docucod/",
        "date": "Jun 03, 2025"
      }
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    "launches": [
      {
        "id": 90620,
        "title": "Docucod 🐟 Automatically generate and maintain your project documentation",
        "tagline": "Write code, not documentation. Docucod auto-creates and updates docs from your codebase and PRs—so your team stays focused on shipping.",
        "body": "Hello world 🏄 we are [Hemang](https://www.linkedin.com/in/hemangkandwal/) and [Anguel](https://www.linkedin.com/in/ahristozov/) from [Clidey](https://www.linkedin.com/company/clidey/), and we are building [Docucod](https://docucod.com/)!\n\n**TL;DR:**\n\n**Docucod automatically generates and maintains complete, always-up-to-date documentation—straight from your codebase.**\n\nDemo video: https://youtu.be/SAaZq9UHAic\n\n# **❗** What is the problem?\n\nOn average, developers spend **20–30% of their time** maintaining documentation—and that doesn’t even include the time it takes to create it in the first place. That’s nearly **12 hours in a standard 40-hour week**, often more if you're part of a fast-growing team.\n\nMost tools are still manual and time-consuming, stealing hours better spent building, selling, or scaling.\n\nGreat documentation isn’t just helpful—it’s a **growth engine**. Look at Stripe: their docs earn trust and convert users.\n\nThe truth? At most companies, documentation is an afterthought (we haven’t written ours yet either!) And we get it—“documentation specialist” usually isn’t on anyone’s job title.\n\n# 💡 What is the solution?\n\n**Docucod auto-generates and maintains always-up-to-date documentation—straight from your codebase.** You continue building, we’ll focus on the documentation.\n\nIt fits effortlessly into your workflow, whether you’re a small team or managing complex repos.\n\nFrom onboarding guides to API references and system diagrams, Docucod delivers clear, comprehensive docs with zero manual work.\n\nFully editable and always in sync, it lets you ship fast **and** document well—without compromise.\n\n# 🧠 How it works:\n\n* Connect your GitHub account and select a repo.\n* Docucod scans your repo to understand its structure and functionality, building an intelligent knowledge graph that maps out components, features, code flow, and so on.\n* It creates a structured documentation plan, outlining sections, navigation, and individual pages.\n* Docucod generates rich content with diagrams and contextual clarity.\n* Finally, it automatically pushes the documentation back to your repo for deployment.\n\n# 😎 Want to see some real examples?\n\nhttps://github.com/clidey/whodb-docs - deployed at http://whodb-docs.docucod.com/\n\nhttps://github.com/clidey/todos-docs - deployed at https://todo-docs.docucod.com/\n\n# 💯 Who Are We and Why Did We Build This?\n\n![uploaded image](/media/?type=post&id=90620&key=user_uploads/1558575/1eddcff2-4b1a-4343-847d-eb35680c9693)\n\nWe’re Hemang and Anguel—friends, builders, and longtime hackathon teammates. After years working at places like Palantir, J.P. Morgan, and Morgan Stanley, we saw one issue everywhere: documentation gets rushed, postponed, or skipped—and the fallout is always the same.\n\nWe built Docucod because this isn’t a people problem—it’s a systems problem. The fix isn’t better habits. It’s automation.\n\n> **We’re here to make documentation sexy again.**\n\n# 🤔 Is Docucod right for you?\n\n**Don’t use Docucod if:**\n\n🚫 You enjoy rewriting GitHub auth instructions.\n\n🚫 You love writing and maintaining docs by hand.\n\n**Use Docucod if:**\n\n✅ You want docs that stay up to date—automatically.\n\n✅ You want new hires productive on Day 1.\n\n✅ You’d rather ship than document.\n\n# 🥹 Our ask:\n\nIf this resonates with you, **get in touch:**\n\n[hemang.kandwal@clidey.com](mailto:hemang.kandwal@clidey.com), [anguel.hristozov@clidey.com](mailto:anguel.hristozov@clidey.com), or\n\nhttps://calendly.com/clidey/conversation-with-clidey-15-min - if there’s a time that you’d like to speak but it shows as unavailable, please just message us!\n\nIf you owned documentation or know someone who owns it now, we would love to get a warm introduction.\n\nLet’s make documentation an asset—not a chore.\n\nThat’s our fish! 👇\n\n![uploaded image](/media/?type=post&id=90620&key=user_uploads/1558575/afe2507e-ada5-46a5-b9f8-93eb3ab48a36)\n\n",
        "url": "https://www.ycombinator.com/launches/NZc-docucod-automatically-generate-and-maintain-your-project-documentation",
        "votes": 164,
        "created_at": "2025-05-21T21:20:54.731Z"
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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",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1745261196,
    "tags": [
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      "Infrastructure"
    ],
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    "isHiring": false,
    "nonprofit": false,
    "batch": "Spring 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/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",
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        "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",
    "former_names": [
      "Dough"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f0529597ad1f6e8b51f9be309f911ce7bb268c67.png",
    "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,
    "tags": [
      "Developer Tools",
      "Analytics",
      "AI"
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    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Spring 2025",
    "status": "Active",
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    "regions": [
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      "America / Canada"
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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/human-behavior",
    "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/human-behavior.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
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    "primary_partner": {
      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
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    "founders": [
      {
        "user_id": 2397615,
        "full_name": "Amogh Chaturvedi",
        "title": "Founder/CEO",
        "founder_bio": "",
        "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"
      }
    ],
    "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": 30507,
    "name": "ParaQuery",
    "slug": "paraquery",
    "former_names": [
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/023b1fec88d11ac0cc00d33e137188a1088f80f1.png",
    "website": "https://paraquery.com",
    "all_locations": "New York City, NY, USA; Remote",
    "long_description": "ParaQuery is a fully-managed GPU-accelerated Spark solution providing double the performance at half the cost compared to solutions like Databricks and BigQuery. It is fully Spark-compatible, cloud agnostic, and has seamless integrations everywhere, all without vendor lock-in. ParaQuery makes it trivial to run large SQL and Spark workloads efficiently and serverlessly, without any data migrations.",
    "one_liner": "Managed GPU-accelerated Spark + SQL at 2x speed and half the cost",
    "team_size": 1,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1745603504,
    "tags": [
      "Developer Tools",
      "Analytics",
      "Big Data",
      "Enterprise Software",
      "Infrastructure"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Spring 2025",
    "status": "Active",
    "industries": [
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      "Infrastructure"
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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/paraquery",
    "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/paraquery.json",
    "year_founded": 2023,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/paraquery",
    "x_url": "http://twitter.com/paraquery_",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/paraquery",
    "github_url": null,
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    "primary_partner": {
      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
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    "founders": [
      {
        "user_id": 1091672,
        "full_name": "Win Wang",
        "title": "Founder/CEO",
        "founder_bio": "Focused on efficiency, effectiveness, and (user) experience.\nPreviously a tech lead @ Twitter, building massively-parallel distributed build systems.\nNow building a cheaper, faster big data platform by using the right hardware for job. Fully-managed, GPU-accelerated, petabyte-scale at double the speed and half the cost.\n",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/winwang",
        "x_url": "https://twitter.com/Winium",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3a5065a212f3a4dd12f6130ba83f67162fb66507.jpg"
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    "launches": [
      {
        "id": 90162,
        "title": "ParaQuery - 5x your data warehouse's efficiency",
        "tagline": "ParaQuery is the GPU-accelerated Spark + SQL engine for your big data needs.",
        "body": "![uploaded image](/media/?type=post&id=90162&key=user_uploads/1091672/94e086c6-918d-4975-94ca-5aece8bff85a)\n\nHey, I'm Win, founder of [ParaQuery](http://www.paraquery.com).\n\nWe're building a bigger query engine with up to 5x cost efficiency compared to BigQuery by using cost-efficient cloud GPUs.\n\n**Ask:** Do you know someone optimizing their data warehouse? Email [win@paraquery.com](mailto:win@paraquery.com) or sign up [here](https://paraquery.com/waitlist)!\n\n**4x'ing** BigQuery efficiency with ParaQuery: <https://www.youtube.com/watch?v=uu379YnccGU> \n\n# **The Problem**\n\nData is the new oil and you're feeding your products with a bunch of it. But to do so, you need to build, maintain, and optimize your data infra. That's either a huge timesink, or you're bleeding cash to ignore it, or someone is breathing down your neck about this month's cloud bill. Why can't we just ship features?\n\n![uploaded image](/media/?type=post&id=90162&key=user_uploads/1091672/419acb3d-1195-4842-a80e-df02ac0d332f)\n\nWhether it's those 20-minute+ Presto queries, or your exploding BigQuery bill (which happens to be tracked in real time), your data infra is letting you down.\n\n# **Our Solution**\n\nParaQuery runs on highly-parallel, throughput-optimized cloud-available hardware, perfect for data processing workloads: **GPUs**!\n\nOur system abstracts out the infra required to serverlessly accelerate your logic. With the extreme efficiency of GPUs, it's half the cost and double the performance of competing solutions like Databricks and BigQuery, without any platform commitments.\n\nFor SQL-based data warehouses like BigQuery, you can use ParaQuery with minimal changes to your queries. And since it's fully Spark-compatible, there's no vendor lock-in. It integrates with literally anything which has a Spark connector, on any major cloud. We can even deploy on GPU clouds.\n\nParaQuery makes data processing as simple as specifying:\n\n1. Inputs\n2. Output\n3. Logic\n4. Run!\n\n![uploaded image](/media/?type=post&id=90162&key=user_uploads/1091672/a6cded39-2da7-432b-9129-014a593caaae)\n\n# **Why?**\n\nI've been looking into GPUs and parallel programming for over 12 years – starting out with crypto. I left that field pretty fast, but I never stopped thinking about efficient compute and GPU acceleration. Even more so when, years later, I had to wait for my laptop to finish 18-hour physics simulations. And during my professional career, I've also had to wait on my fair share of 20-minute+ analytical queries.\n\nIn fact, I hate waiting. ParaQuery is productizing an arbitrage of hardware efficiency, and I'm not waiting any longer to do so.\n\n# **Ask**\n\n1\\. If you know anyone who is running any big data processing scenarios (including MLOps), I'd love to learn more about their use case and see if we're a fit! \n\n2\\. If you want to try it out, sign up for our waitlist at [www.paraquery.com](http://www.paraquery.com), or just email me ([win@paraquery.com](mailto:win@paraquery.com))",
        "url": "https://www.ycombinator.com/launches/NSE-paraquery-5x-your-data-warehouse-s-efficiency",
        "votes": 51,
        "created_at": "2025-05-07T02:14:51.329Z"
      }
    ]
  },
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    "id": 30510,
    "name": "Cactus Compute",
    "slug": "cactus-compute",
    "former_names": [
      "Cactus"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/38edcfba2831cce5f05a5da045992ae4f758e655.png",
    "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": [
      "Developer Tools",
      "Hard Tech",
      "Open Source",
      "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",
      "Remote",
      "Partly 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": "We met through YC co-founder matching in London four years ago!"
      }
    ],
    "url": "https://www.ycombinator.com/companies/cactus-compute",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/cactus-compute.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/cactus-compute/",
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    "github_url": "https://github.com/cactus-compute",
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    "primary_partner": {
      "name": "Andrew Miklas",
      "url": "https://www.ycombinator.com/people/andrew-miklas"
    },
    "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/",
        "x_url": "https://x.com/romanshemet",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1991f894485f13d07f1c9e71688c42ddf1c63296.jpg"
      },
      {
        "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",
        "x_url": "https://x.com/Henry_Ndubuaku",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/979686e7135b71cdb313d9af81830f6052dd572b.jpg"
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    "jobs": [],
    "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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  },
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    "id": 30527,
    "name": "MindFort",
    "slug": "mindfort",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/67f8fa73a583138ab0060e99d6a10e8341a0d040.png",
    "website": "https://mindfort.ai/?utm_source=ycombinator&utm_medium=referral&utm_campaign=yc",
    "all_locations": "Los Angeles, CA, USA",
    "long_description": "MindFort is building fully autonomous AI agents powered by their in-house models that can find, exploit, and patch complex vulnerabilities in web applications at massive scale. MindFort agents use the same principles as human penetration testers to understand their target and figure out the best ways to work together to exploit it. We can do fully autonomous AI web pentesting and bring offensive security to teams out numbered. \r\n\r\nWhile security teams were already behind with legacy tools and processes, AI coding is make the problem worse. AI generates code far faster than human teams can secure it; MindFort can match that speed and scale. Our agents will become critical as organizations scale up development with AI.\r\n",
    "one_liner": "Autonomous Security Agents",
    "team_size": 6,
    "industry": "B2B",
    "subindustry": "B2B -> Security",
    "launched_at": 1747245373,
    "tags": [
      "Developer Tools",
      "Cybersecurity",
      "Enterprise Software",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Spring 2025",
    "status": "Active",
    "industries": [
      "B2B",
      "Security"
    ],
    "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/mindfort",
    "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/mindfort.json",
    "year_founded": 2025,
    "city": "Los Angeles",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/106469568/",
    "x_url": "https://x.com/mindfort_ai",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/mindfort-ai",
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/67f8fa73a583138ab0060e99d6a10e8341a0d040.png",
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    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
    },
    "founders": [
      {
        "user_id": 525065,
        "full_name": "Brandon Veiseh",
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        "body": "![uploaded image](/media/?type=post&id=90555&key=user_uploads/525065/9bbd9d91-5dba-43e0-9412-2c45bac5782a)\n\nHey everyone! 👋 We're Brandon, Sam, and Akul - Co-founders of [MindFort.ai](http://MindFort.ai).\n\nWe're building fully autonomous AI security agents that find, validate, and patch vulnerabilities in web applications and networks at machine speed and scale.\n\nhttps://youtu.be/Oe-errlwaow\n\n## 🔥 The Problem\n\nSecurity is fundamentally broken for most engineering teams today:\n\n* **Scanners are unreliable** - They flood engineers with 30-50% false positives, wasting precious development time\n* **Traditional pen testing is too slow** - It happens quarterly at best, costs a fortune, and takes weeks to complete\n* **AI-accelerated development creates new risks** - Teams are shipping code faster than ever, but security reviews have become an even bigger bottleneck\n\nThe result? Companies are forced to choose between shipping fast or shipping secure. Engineering teams lose **\\~20%** of their time dealing with security issues or slowing down to accommodate outdated security practices.\n\n## 🚀 Our Solution\n\n[MindFort.ai](http://MindFort.ai)'s autonomous security agents work 24/7/365 to find, validate, and patch vulnerabilities:\n\n* **Find** complex vulnerabilities like a human tester would\n* **Validate** every finding to eliminate false positives\n* **Patch** with intelligent fixes that integrate directly with your codebase\n* **Scale** to thousands of tests in an instant, giving coverage never possible before\n\nUnlike solutions that slow development, MindFort accelerates it by eliminating security bottlenecks. Our platform is already finding vulnerabilities in production systems that other tools miss, identifying issues in bug bounty programs, and scoring high on human penetration testing benchmarks.\n\n## 💡 Our Story\n\nBrandon worked as a PM at ProjectDiscovery, a security scanner company where he led development of the Nuclei cloud platform from an open source tool to an enterprise ready product. He then joined NetSPI, one of the world’s largest penetration testing firms, to build generative AI tools for human testers. He sat with countless customers across both companies, learning about their struggles in securing attack surfaces at scale.\n\nAkul received his masters in computer science from the University of Illinois Urbana-Champaign, and was drawn to AI and security early on in his academic career. He co-authored multiple papers on using LLMs to perform various cybersecurity attacks, worked on creating novel benchmarks for hacking agents, and participated in red teaming and model safety programs at both OpenAI and Anthropic.\n\nSam worked as a senior engineer at Salesforce, where he led security for a large business unit, Tableau. During his time there, he worked first hand on keeping a large scale product secure. Between juggling security assessments, validating findings, and managing remediations inside of a large organization, he had seen it all. He began experimenting with ways to use AI to help solve some of the issues he faced at Salesforce and even worked on a demo of a tool to perform agentic code review through a DARPA program. He recently completed a master’s degree in cybersecurity at UC Berkeley.\n\nWe all met through our work and research. Early on, we all realized that the future of security was going to belong to AI agents, and that the coming tidal wave of new code generated with AI would need a solution of equal magnitude.\n\n![uploaded image](/media/?type=post&id=90555&key=user_uploads/525065/51cbc28d-9ff7-41b3-af19-d3e9fc23ef0a)\n\n## 🔮 Our Vision\n\nSecurity should accelerate your business, not slow it down. We're creating a world where security testing happens continuously and vulnerabilities are patched autonomously, **keeping your product and your users safe, while letting you ship faster.**\n\n## 👇 Our Ask\n\nReady to ship quickly and securely? 👉 **Visit [mindfort.ai](http://mindfort.ai) to request access**\n\n📧 Email us directly: [founders@mindfort.ai](mailto:founders@mindfort.ai)",
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        "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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        "created_at": "2025-05-16T15:08:07.425Z"
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      {
        "id": 90473,
        "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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        "title": "Amid the AI boom, Princetonians swap school for Silicon Valley - The Princetonian",
        "url": "https://www.dailyprincetonian.com/article/2026/04/princeton-features-profiles-dropout-school-startups-silicon-valley-ai-boom",
        "date": "Apr 10, 2026"
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      {
        "title": "Disrupting Industries: Highlights from the Latest YC Demo Day",
        "url": "https://nextunicorn.ventures/disrupting-industries-highlights-from-the-latest-yc-demo-day/",
        "date": "Sep 15, 2025"
      },
      {
        "title": "Y Combinator's Summer 2025 Demo Day Highlights Over 160 Startups with a Focus on AI Solutions",
        "url": "https://news.ssbcrack.com/y-combinators-summer-2025-demo-day-highlights-over-160-startups-with-a-focus-on-ai-solutions/",
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        "date": "Sep 14, 2025"
      },
      {
        "title": "Dedalus Labs Review: Is This The “Vercel for AI Agents” We’ve Been Waiting For?",
        "url": "https://medium.com/design-bootcamp/dedalus-labs-review-is-this-the-vercel-for-ai-agents-weve-been-waiting-for-d52e764f3756",
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        "title": "Dedalus Labs: Build & Deploy Complex Agents in 5 Lines of Code",
        "tagline": "Build and deploy complex AI agents with any model and any tool in just 5 lines of code. No Docker files. No YAMLs. No wasted weeks.",
        "body": "# [**TL;DR:**](https://www.youtube.com/watch?v=E0FR4LBTSZo)\n\n_We’re excited to launch [Dedalus Labs](https://www.dedaluslabs.ai/), an AI-native cloud platform for developers to build agentic AI applications. Our [SDKs](https://github.com/dedalus-labs/dedalus-sdk-python) allows you to connect any LLM to any MCP servers – local or remotely hosted by us. No Docker files or YAML configs required._\n\n* **Blog:** https://dedaluslabs.ai/blog/dedalus-seed-round\n* **Product Demos:**\n  * https://www.youtube.com/watch?v=s2khf1Monho\n  * https://www.youtube.com/watch?v=4B1xuRCgLgA\n\n# **The Problem: Building Agents Is Hard**\n\nBuilding tool-using agents ≠ calling **_v1/chat/completions._**\n\nToday, developers are still stuck with:\n\n* Running their MCP servers locally.\n* If deploying remotely, wiring up AWS and config hell.\n* Juggling model quirks, streaming issues, and auth across GPT-4o, Claude 3.5, Sonnet, Flash, etc. (♾️ API keys).\n* Rebuilding everything just to add a new tool.\n\nWe were **_tired_** of writing hundreds of lines of code and battling Docker files and infra—all for a spaghetti agent that breaks under stress.\n\n**So, we built the tool we wished existed.**\n\n# **What We Offer: Complex Agents in 5 Lines of Code**\n\nDedalus invented the simplest way to build and deploy agents—a drop-in infrastructure layer that unifies models, tools, and orchestration.\n\nOur open-source SDK supports:\n\n* Vendor-agnostic model handoffs\n* Chaining both local tools and hosted MCPs\n* Real-time streaming across any provider\n\n—all in 5 lines of code.\n\nAnd our managed infra lets you **deploy an MCP server in 3 clicks**, so anyone can equip their agent with tools. No Docker files, no setup.\n\n# **Why MCP: Tools Made for Agents**\n\n[MCP (Model Context Protocol)](https://spec.modelcontextprotocol.io/) is becoming the standard for how models talk to tools. Think of it as an API that AI models already know how to call—reliable, predictable, and language-agnostic.\n\nAs more companies adopt MCP, exposing your product as an MCP server means you’re not just serving humans anymore—you’re serving _agents._\n\nWe’re building the infrastructure that powers that shift.\n\n# **Our Story: Two Princeton CS Students with High Standards**\n\nWe’re **Cathy** (ex-Voyage AI / Salesforce) and **Windsor** (ex-DeepMind / Sentient AGI).\n\nWe first ran into this problem while working with MCP during Windsor’s time at Sentient AGI. Every solution felt wrong: drag-and-drop GUIs, brittle configs, frameworks that broke under real workloads. Nothing met our standards for what good developer infrastructure should be.\n\nSo we built what we always wanted—a developer-first platform that makes agentic workflows composable, scalable, and effortless to ship.\n\n**If no one else is going to build it right, we will.**\n\n# **Get Started + Early YC Deal**\n\n* **Quick install:** **_pip install dedalus-labs_**\n* **Docs:** [docs.dedaluslabs.ai](http://docs.dedaluslabs.ai)\n* **YC Deal:** we’re giving $200 free credits to every YC company. Email [founders@dedaluslabs.ai](mailto:founders@dedaluslabs.ai) to claim your deal!\n\n![uploaded image](/media/?type=post&id=94675&key=user_uploads/1126811/4a1b700a-a1ab-41a3-a730-7b9a88b65500)\n\n_Let us build your wings_ so your agents can fly. 🪽",
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        "votes": 23,
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        "full_name": "Xinwei He",
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        "type": "Full-time",
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        "id": 105076,
        "title": "Developer Marketing Intern",
        "url": "https://www.ycombinator.com/companies/traceroot-ai/jobs/dk1ep2K-developer-marketing-intern",
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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",
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        "votes": 27,
        "created_at": "2025-08-07T06:27:04.705Z"
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    "id": 30611,
    "name": "AgentMail",
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    "website": "https://agentmail.to",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "AgentMail is the email inbox API for AI agents. It gives agents their own email inboxes, like Gmail does for humans.",
    "one_liner": "Email Inboxes for AI Agents",
    "team_size": 10,
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    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1750990316,
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        "title": "AgentMail raises $6M to build an email service for AI agents | TechCrunch",
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        "full_name": "Paul Bae",
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        "full_name": "Vijit Dhingra",
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        "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.",
        "is_active": true,
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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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        "votes": 25,
        "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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        "votes": 43,
        "created_at": "2025-08-18T19:33:29.250Z"
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    "long_description": "Quantitative trading",
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    "launched_at": 1754374450,
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        "user_id": 1845082,
        "full_name": "Jorge Guerra",
        "title": "Founder/CEO",
        "founder_bio": "Founder/CEO Lotas — quantitative trading with AI\nHarvard '24",
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        "full_name": "William Nickols",
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        "founder_bio": "Founder/CTO Lotas — quantitative trading with AI\nHarvard '24",
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      {
        "id": 92746,
        "title": "Lotas — Cursor for Data Science",
        "tagline": "Building a secure, AI-native IDE for data scientists",
        "body": "Hey everyone! We’re Jorge and Will from Lotas. We’re building a secure, AI-native IDE for data science—and as a first step, we’ve built an AI coding assistant into RStudio (think Cursor for RStudio). We’re looking for RStudio users, data scientists, and students who want to code way faster and are excited to see AI integrated into data science workflows.\n\nhttps://www.youtube.com/watch?v=c47Ch1kB0eU\n\n❌ Problem\n\nRStudio is used by about 5 million data scientists and academics, but they currently lack a coding assistant within their IDE. Developers in other environments benefit from tools like Cursor and Windsurf, but R users don’t have an equivalent tool that’s truly integrated into their day-to-day workflow. And more broadly, data science teams need an AI-native environment that understands notebooks, dataframes, plots, and multi-language workflows—without forcing work into the cloud or tools they don’t use.\n\n✅ Solution\n\nWe’re building a secure, AI-native IDE for data science that is context-aware (files, variables, terminals), can read and write code, run analyses, and interpret textual or visual output across R and Python to start. While we build this IDE, we’ve shipped Rao: a fork of RStudio with an embedded AI assistant that is aware of the user’s local context (both files and variable environment), can read and write files, can run code or commands, and can interpret textual or visual output. It works with the file formats RStudio users already rely on (R, notebooks including RMDs and QMDs, Python, Stan, etc.), so you can iteratively perform entire data analyses inside your preferred IDE today—and help us design the next one.\n\n👨‍🎓 Who we are\n\nBoth of us were PhD students at Harvard. Jorge was in the biophysics program and Will was in the biostatistics program where most people used RStudio every day. We saw how integrated coding assistants were taking off in other IDEs, but RStudio integrations lagged behind. Many R users were copying and pasting code from ChatGPT to build their workflows, which was slow and fragile. Other AI data science tools are either (1) built on the web or in environments people don’t already use, (2) completely focused on Python notebooks, or (3) weak package-based assistants with limited functionality. We’re closing these gaps—first with Rao, and next with a purpose-built IDE for data science.\n\n🚀 Try Rao & get early access\n\nYou can download Rao, watch our demo, and work through example use cases. If you’re interested in a secure, AI-native IDE for data science, contact us for an early preview!\\\n\\\n✉️ **Contact**\\\nYou can reach us at [founders@lotas.ai](mailto:founders@lotas.ai) and follow us on [LinkedIn](https://www.linkedin.com/company/lotas/) and [X](https://x.com/lotas_ai).\n\n![uploaded image](/media/?type=post&id=92746&key=user_uploads/1845082/a6d066f2-358c-46b1-959e-6e2618b44df4)\n\n",
        "url": "https://www.ycombinator.com/launches/O7u-lotas-cursor-for-data-science",
        "votes": 14,
        "created_at": "2025-08-05T16:49:32.810Z"
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    "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,
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      "Enterprise Software",
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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 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. "
      },
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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": "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."
      },
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        "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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    "linkedin_url": "https://www.linkedin.com/company/cyberdeskhq",
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      "name": "Jon Xu",
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        "full_name": "Mahmoud Al-Madi",
        "title": "Founder/CEO",
        "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",
        "url": "https://www.ycombinator.com/launches/O4a-cyberdesk-the-computer-use-agent-for-developers-to-automate-legacy-windows-apps",
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        "created_at": "2025-07-29T15:47:24.669Z"
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    "name": "Alter",
    "slug": "alter",
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    "website": "https://alterauth.com",
    "all_locations": "New York City, NY, USA",
    "long_description": "Alter is a zero-trust identity and access control platform purpose-built for AI agents. It wraps every tool call in strong authentication, fine-grained authorization, and real-time guardrails, so agents can move fast without breaking things.\r\n\r\nEach request is verified at the parameter level, authorized against granular policies, executed with least-privilege access, and fully audited in real time. Unsafe actions, whether it’s a rogue DROP TABLE or a payment above policy limits, are blocked before they touch production. Behind the scenes, Alter manages credentials, issuing ephemeral, scope-narrowed access for every interaction, then rotating or expiring it in seconds. The result: no long-lived secrets, no blind spots, and no surprises in audit.\r\n\r\nWith Alter, teams can move fast on AI agent initiatives while staying fully compliant with SOC 2, HIPAA, GDPR, and internal security standards. A CISO-ready dashboard delivers real-time visibility, detailed audit logs, and compliance-ready controls, removing silos, eliminating excessive permissions, and providing complete oversight of every agent workflow.",
    "one_liner": "Privileged Access Management for AI Agents",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Security",
    "launched_at": 1752476002,
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/alter",
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    "year_founded": 2025,
    "city": "New York City",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/alterai-dev",
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        "full_name": "Srikar Dandamuraju",
        "title": "Founder/CEO",
        "founder_bio": "Co-Founder & CEO of Alter (YC S25), a zero-trust identity and access control platform for AI agents. Former Platform Lead at Goldman Sachs, where I scaled GSAM’s post-trade infrastructure from single to multi-cluster and helped launch the GM Card. Before that, software engineer at Addepar and Clear Street.\n",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/srikar-d-473390136",
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        "full_name": "Kevan Dodhia",
        "title": "Founder/CTO",
        "founder_bio": "Co-founder and CTO of Alter (YC S25), a zero-trust identity and access control platform for AI agents. Previously technical co-founder of Compute.ai, where we built a compute engine 5x faster than EMR Spark and sold into highly regulated enterprises like LSEG. Compute.ai was acquired by Terizza in 2025.",
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      {
        "id": 93044,
        "title": "Alter –  Identity and Access Control Platform To Secure Agents",
        "tagline": "Build secure, compliant agents without the fear of breaking production",
        "body": "### **TL;DR**\n\nAlter sits in the middle of every AI agent interaction, verifying identity and applying fine-grained RBAC & ABAC to check every parameter against policy. It instantly rejects dangerous actions and provides clear audit trails logging every request/response and decision.\\\n\\\nInterested? Learn more and request beta access at [alterai.dev](http://alterai.dev)\n\nDon’t want to read? Here is a video explaining what we do in a nutshell\n\n[Identity And Access Control Platform To Secure Agents | Alter (YC S25)](https://www.youtube.com/watch?v=UX0ACmMXpMg)\n\n**The Problem**\n\n**Dangerous:** Long-lived credentials and over-scoped service accounts mean a single leak can give an agent the keys to production letting it run destructive commands, exfiltrate sensitive data, or trigger costly transactions.\\\n**Opaque:** Scattered logs and siloed security make it impossible to trace “which agent did what, with which parameters” when something goes wrong, leaving teams blind in audits or incident response.\\\n**Slow:** Security reviews drag on for weeks because least-privilege and policy checks are hard to implement at scale, delaying projects and eroding velocity.\\\n**Overexposed:** Agents often get blanket root access, with no guardrails to stop prompt-injection or malicious payload swaps, so one bad input can become a catastrophic action.\\\n**The result:** enterprises face agents that _can_ and _do_ take unsafe actions in production, forcing teams to choose between unacceptable risk or shelving AI initiatives entirely.\\\n**\\\nOur Solution**\n\nAlter is the safest way to run AI agents in production without giving them blanket credentials or risking compliance breaches. From one central control layer, organizations can:\n\n* Host or connect to all their tools. We support MCP and Native tools (A2A coming soon)\n* Approve or deny any agent request in real time, with identity verification baked into every call.\n* Apply parameter-level RBAC & ABAC so dangerous actions like drop table commands in prod, during a freeze never reach production.\n* Instantly grant seconds-lived, scope-narrowed tokens so agents get only the access they need, only for that task.\n* Remove the need for long-lived API keys entirely, eliminating one of the biggest security liabilities.\n* See exactly what every agent did, when, and with what parameters, all in one CISO-ready dashboard.\n* Pass SOC 2, HIPAA, and GDPR audits without slowing down because compliance controls run automatically in the background.\n* Scale to any number of agents and tools without creating security silos or over-permissive access.\n\n### **The Team**\n\nWe are Srikar and Kevan.\\\n\\\nWe previously built enterprise-grade infrastructure at ComputeAI and Goldman Sachs, powering mission-critical systems for the London Stock Exchange and the Apple Card launch. Now we’re using that experience to make AI agents safe for production by giving them only the access they need and only for as long as they need it.\\\n**\\\nOur Ask**\n\nWe’re looking to connect with:\n\n* Engineering and security leaders running AI agents in production\n* Enterprises in regulated industries (finance, healthcare, government) with strict compliance requirements\n* Startups building AI-first products that need zero-trust access controls\n* Infosec teams looking to eliminate long-lived credentials and enforce least-privilege by default\n\nAs a bonus, we have also partnered with former OpenAI cybersecurity experts to provide you with ongoing red teaming, catching prompt-injection, data exfiltration, and other exploits before attackers can.\n\nIf you or someone you know is interested, please reach out to us at [**founders@alterai.dev**](mailto:founders@alterai.dev) or book a time to chat.",
        "url": "https://www.ycombinator.com/launches/OCi-alter-identity-and-access-control-platform-to-secure-agents",
        "votes": 30,
        "created_at": "2025-08-15T19:42:34.047Z"
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    "id": 30659,
    "name": "Proliferate",
    "slug": "proliferate",
    "former_names": [
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e9eb3892f113b924e1c5b9bdf6d120ba559a45ff.png",
    "website": "https://proliferate.com?utm_source=yc&utm_medium=referral&utm_campaign=profile",
    "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",
    "team_size": null,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1749673205,
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      "B2B",
      "AI"
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    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/107275953",
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        "body": "**TL;DR**\n\nWe are Lovable, but better because the backends we generate actually work and are easy to debug and evolve.\n\nhttps://youtu.be/bjpR5A-Ib6k\n\n## Who We Are\n\nWe're Alessia and Elia, Computer Science and Data Science graduates from Stanford and ETH Zürich. We've spent years as full-stack engineers building no-code tools that empower non-technical users to create complex systems. Now we're using that experience to help anyone become a full-stack developer through AI.\n\n## The Problem\n\nPrompt-to-app tools like Lovable are incredible at generating beautiful frontends, but they completely fall apart when you need real business logic, integrations, or debugging capabilities.\n\nHere's what every developer using these tools faces:\n\n* **Black box backends:** you can't see or understand what the AI actually built for your server-side logic\n* **Debugging nightmare:** when something breaks, you're stuck re-prompting the LLM and hoping it magically fixes the issue\n* **Integration hell:** you're forced to manually stitch together Lovable + n8n + Supabase + other tools, creating fragile workflows that break easily and are painful to maintain\n\nThis affects thousands of developers who want to build real applications but get stuck when they move beyond simple prototypes.\n\n## Our Solution\n\nVibeFlow transforms prompts into full-stack applications where every single component, frontend AND backend, is visible, understandable, and editable.\n\n### How it works:\n\n* **Visual Backend Editor:** See and edit your app's backend logic like you'd design a UI in Figma. You can edit visually or continue using prompts.\n* **Transparent AI Generation:** Unlike other tools, you can see and understand what the AI built, making debugging straightforward\n* **Powerful Integrations:** Built-in database and prewired service connections, no external tools required.\n* **All-in-One Platform:** Build, debug, deploy, and maintain everything in one cohesive environment\n\n## How We Got Here\n\nWe saw builders doing hacky workarounds, connecting n8n and Supabase to power Lovable frontends, creating Frankenstein apps where they didn't even own half the pieces. People were desperate for backend control but stuck with fragmented solutions.\n\n### Get in Touch\n\n* **Build your full-stack app with VibeFlow**: https://app.vibeflow.ai/\n* **Join our Discord**: https://discord.com/invite/Ctm2A2uEaq\n* **Book a 15-min call**: https://vibeflow.cal.com/founders/15min (we'll help you build something cool!)\n* **Newsletter**: https://vibeflow.ai\n\nReady to build full-stack apps that actually work? Try VibeFlow today and see the difference transparent AI development makes!\n\n![uploaded image](/media/?type=post&id=92712&key=user_uploads/1842260/003016ef-0945-43c2-a200-0dbc7bf703a4)\n\n",
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        "created_at": "2025-08-04T19:05:49.267Z"
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    "primary_partner": {
      "name": "Ankit Gupta",
      "url": "https://www.ycombinator.com/people/ankit-gupta"
    },
    "founders": [
      {
        "user_id": 1894718,
        "full_name": "Arlan Rakhmetzhanov",
        "title": "Founder/CEO",
        "founder_bio": "1) kicked out from high school for rizzing too many girls\n2) played a lot of video games (10,000 hours in valorant)\n3) scaled my first startup to 20k users at 15 for fun \n4) research @ stanford\n5) raised $1m from my principal's office",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/arlan-rakhmetzhanov/",
        "x_url": "https://x.com/arlanr",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2bb8aace61546bf991a03717994cd710ce3bbd11.jpg"
      }
    ],
    "jobs": [
      {
        "id": 95583,
        "title": "Founding Member of Technical Staff",
        "url": "https://www.ycombinator.com/companies/nozomio/jobs/EaWLjdN-founding-member-of-technical-staff",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$150K - $250K",
        "equity_range": "0.50% - 3.00%",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Google Cloud",
          "MongoDB",
          "Python",
          "React",
          "TypeScript",
          "LLMs",
          "AI Agents"
        ]
      },
      {
        "id": 95584,
        "title": "Founding Member of Marketing Staff",
        "url": "https://www.ycombinator.com/companies/nozomio/jobs/l0rxLyD-founding-member-of-marketing-staff",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Marketing",
        "role_type": null,
        "salary_range": "$150K - $250K",
        "equity_range": "0.50% - 1.00%",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 95585,
        "title": "Short-Form Content Creator",
        "url": "https://www.ycombinator.com/companies/nozomio/jobs/rZv0CK8-short-form-content-creator",
        "location": "Remote (US)",
        "type": "Contract",
        "role": "Marketing",
        "role_type": null,
        "salary_range": "$600 - $10K / monthly",
        "equity_range": "",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 96744,
        "title": "Founding Growth",
        "url": "https://www.ycombinator.com/companies/nozomio/jobs/bT2YpAU-founding-growth",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Marketing",
        "role_type": null,
        "salary_range": "$135K - $250K",
        "equity_range": "0.15% - 0.90%",
        "experience": "1+ years",
        "visa": "US citizen/visa only",
        "skills": []
      }
    ],
    "news": [
      {
        "title": "High School Dropout Founds YC Startup Nozomio, Raises $6 Million Seed - Business Insider",
        "url": "https://www.businessinsider.com/nozomio-high-school-dropout-y-combinator-6-million-seed-2025-9",
        "date": "Oct 01, 2025"
      },
      {
        "title": "18-year-old founder closes pre-seed funding round for AI startup - UKTN",
        "url": "https://www.uktech.news/ai/ai-startup-founded-by-18-year-old-nia-closes-localglobe-led-round-20250507",
        "date": "May 07, 2025"
      }
    ],
    "launches": [
      {
        "id": 92166,
        "title": "Nia: 10x the context of your coding agent",
        "tagline": "Improved Cursor's performance by 27%",
        "body": "### **TL;DR**\n\nStop hand‑feeding links and developer context to your agent. [**Nia**](https://www.trynia.ai/) is an MCP server that can index entire codebases & documentation sites, perform deep research, and more so agents like Cursor, Continue, and Cline “just know” the right answer.\n\n_In internal evals we improved Cursor’s performance by **27 %** once [**Nia**](https://www.trynia.ai/) had indexed external docs models couldn’t get from their training data or searching the web._\n\nhttps://youtu.be/WSqM5FmqFQM\n\n### **The Problem**\n\n* Coding agents are great with local files but fail when it comes to external context enrichment.\n* Agents are finally great at codegen, **terrible at retrieving the right context**.\n* You still copy‑paste GitHub and web links one‑by‑one and pray the model scrolls far enough.\n\nContext—not generation—is now the bottleneck.\n\n### **What Nia does**\n\n* **Indexes multiple repos & entire docs sites at once** via an MCP server.\n* Works as MCP server and can be used inside Cursor, Cline, Continue etc.\n* **Deep‑Research Agent**: ask “Compare LangChain, Llama Index, Haystack,” get an auto‑generated table (pros, cons, best pick) _and_ have all three repos pre‑indexed for later use.\n\n### **Get Started in &lt;3 minutes**\n\n1. Grab your API key at [**https://app.trynia.ai/**](https://app.trynia.ai/)\n2. Follow instructions at [**https://docs.trynia.ai/integrations/nia-mcp**](https://docs.trynia.ai/integrations/nia-mcp)\n3. Enjoy.\n\nhttps://youtu.be/5019k3Bi8Wo?si=ERmnmo01IJ3DQfrv\n\n### **My ask**\n\n1. Try Nia today and tell us what context your agent still misses.\n2. BOOK A **FREE** CALL → [**https://calendly.com/arlanrakh/nia-ai-demo**](https://calendly.com/arlanrakh/nia-ai-demo)\n\n👉 Contact me at [arlan@nozomio.com](mailto:arlan@nozomio.com)\n\n![uploaded image](/media/?type=post&id=92166&key=user_uploads/1894718/af79e074-2831-40ec-a7a6-e7f27f0be8f1)\n\n### **My story**\n\n* I’m **Arlan**, solo‑founder immigrant from Kazakhstan.\n* Launched my first edtech startup at 15.\n* I got kicked out of my math classes for taking investor calls, so I dropped out of high school to move to London where I raised my pre-seed in couple days.\n* I cold-emailed my way into research @ Stanford when I was 16, and worked closely with a Georgia Tech professor on a book called Cobra, a powerful interactive tool for finding defects or suspicious patterns in source code.\n\n![uploaded image](/media/?type=post&id=92166&key=user_uploads/1894718/d5b86613-0561-43b4-8c2d-2bec5ee03639)\n\n",
        "url": "https://www.ycombinator.com/launches/NyY-nia-10x-the-context-of-your-coding-agent",
        "votes": 221,
        "created_at": "2025-07-15T14:13:02.959Z"
      }
    ]
  },
  {
    "id": 30710,
    "name": "Manufact",
    "slug": "manufact",
    "former_names": [
      "mcp-use",
      "Manufact (formerly mcp-use)"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3838f80b214ed1fcda53a2778860e8be11cfdb0d.png",
    "website": "https://manufact.com",
    "all_locations": "ZH, Switzerland",
    "long_description": "Manufact is the MCP cloud platform to get your product ready for Claude Connectors marketplace, ChatGPT / Codex plugins store and any AI agent that supports MCP.\r\nWe're the team behind mcp-use SDK, the open-source framework for building MCP Apps with 10k github stars and 10M+ downloads across python and typescript.\r\n\r\nIt's the fastest and most complete solution for production-ready MCP servers.",
    "one_liner": "Cloud infrastructure for MCP servers and Claude / ChatGPT plugins.",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1752861544,
    "tags": [
      "Developer Tools",
      "B2B",
      "Open Source",
      "Infrastructure",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2025",
    "status": "Active",
    "industries": [
      "B2B",
      "Infrastructure"
    ],
    "regions": [
      "Switzerland",
      "Europe"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/manufact",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/manufact.json",
    "year_founded": 2025,
    "city": null,
    "country": "CH",
    "linkedin_url": "https://www.linkedin.com/company/mcp-use/",
    "x_url": "https://x.com/manufact",
    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/mcp-use",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/3838f80b214ed1fcda53a2778860e8be11cfdb0d.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [],
    "primary_partner": {
      "name": "Jon Xu",
      "url": "https://www.ycombinator.com/people/jon-xu"
    },
    "founders": [
      {
        "user_id": 909674,
        "full_name": "Pietro Zullo",
        "title": "Founder/CEO",
        "founder_bio": "Building Manufact (formerly mcp-use) (S25). ",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/pietrozullo",
        "x_url": "https://x.com/pietrozullo",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/20b195400b407be674253b1353993e19ad6323b2.jpg"
      },
      {
        "user_id": 859771,
        "full_name": "Luigi Pederzani",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder @ Manufact (fka mcp-use). \nPrev. Founding eng. @ Morgen (ETH spin-off AI startup used by teams at Spotify, GitHub, Linear, and Canva). \nLed a 12-engineer team to deliver $XXM projects @ Accenture Switzerland.\nMSc in Computer Science and Engineering from POLIMI (QS #1 IT, #5 EU, #13 World).\nFormer YouTube creator (150k subs, 15M+ views).\n",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/luigipederzani",
        "x_url": "https://x.com/pederzh",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/052187b02cbea99b02766098b2c86fcf33610ec4.jpg"
      }
    ],
    "jobs": [
      {
        "id": 97959,
        "title": "Developer Advocate & Partnerships (DevRel)",
        "url": "https://www.ycombinator.com/companies/manufact/jobs/4cyWd6S-developer-advocate-partnerships-devrel",
        "location": "San Francisco, CA, US / Remote",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$100K - $160K",
        "equity_range": "0.10% - 0.70%",
        "experience": "Any (new grads ok)",
        "visa": "Will sponsor",
        "skills": []
      },
      {
        "id": 97962,
        "title": "Senior Infrastructure Engineer",
        "url": "https://www.ycombinator.com/companies/manufact/jobs/Dh6PYP5-senior-infrastructure-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Devops",
        "salary_range": "$100K - $180K",
        "equity_range": "0.10% - 0.70%",
        "experience": "3+ years",
        "visa": "US citizen/visa only",
        "skills": [
          "Amazon Web Services (AWS)",
          "Microsoft Azure",
          "Google Cloud",
          "TypeScript"
        ]
      },
      {
        "id": 107000,
        "title": "Sales Development Representative (SDR)",
        "url": "https://www.ycombinator.com/companies/manufact/jobs/fWWRPrO-sales-development-representative-sdr",
        "location": "San Francisco, CA, US / Remote (US)",
        "type": "Full-time",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$60K - $100K",
        "equity_range": "0.05% - 0.20%",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
        "skills": []
      },
      {
        "id": 107005,
        "title": "Founding Software Engineer (Product / MCP) ",
        "url": "https://www.ycombinator.com/companies/manufact/jobs/ZyxwEJC-founding-software-engineer-product-mcp",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$100K - $160K",
        "equity_range": "0.10% - 1.00%",
        "experience": "1+ years",
        "visa": "Will sponsor",
        "skills": [
          "React",
          "TypeScript"
        ]
      },
      {
        "id": 116901,
        "title": "Founding Forward Deployed Engineer",
        "url": "https://www.ycombinator.com/companies/manufact/jobs/kp7OyFp-founding-forward-deployed-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$100K - $160K",
        "equity_range": "",
        "experience": "3+ years",
        "visa": "Will sponsor",
        "skills": [
          "Python",
          "TypeScript"
        ]
      }
    ],
    "news": [
      {
        "title": "Manufact raises $6.3M as MCP becomes the ‘USB-C for AI’ powering ChatGPT and Claude apps | VentureBeat",
        "url": "https://venturebeat.com/infrastructure/manufact-raises-usd6-3m-as-mcp-becomes-the-usb-c-for-ai-powering-chatgpt-and",
        "date": "Mar 11, 2026"
      },
      {
        "title": "Make Something Agents Want — Humans Are No Longer The Customer",
        "url": "https://www.forbes.com/sites/dariashunina/2026/03/11/make-something-agents-want---humans-are-no-longer-the-customer/",
        "date": "Mar 09, 2026"
      },
      {
        "title": "The Most Promising Startups To Watch From YC Summer 2025 Batch: mcp-use",
        "url": "https://www.forbes.com/sites/dariashunina/2025/09/04/the-most-promising-startups-to-watch-from-yc-summer-2025-batch/",
        "date": "Sep 04, 2025"
      }
    ],
    "launches": [
      {
        "id": 107462,
        "title": "Manufact: MCP Cloud for your Claude Connector & ChatGPT Plugin",
        "tagline": "Get your product on Claude and ChatGPT and usable by AI Agents ",
        "body": "Hey everyone, we're the team behind [**mcp-use**](https://github.com/mcp-use/mcp-use), the open-source MCP framework with **10k GitHub stars** and **\\~10M+ downloads**.\n\n[**Manufact**](https://manufact.com/) is the cloud platform that gets your product onto the **Claude Connectors marketplace** and the **ChatGPT (Codex) Plugin Store** via MCP.\n\n<https://youtu.be/Pyh_3tKDXuU>\n\n## The problem\n\nPaul Graham recently tweeted: \"_AI apps are the new browsers_\". \\\nYour customers now do most of their work inside Claude and ChatGPT, and the connector marketplaces are a new distribution channel: someone installs your product in one click and uses it inside the chat they already live in.\n\nWe listed Manufact on Claude and saw a **surge of signups** that is still going on now.\n\n![uploaded image](/media/?type=post&id=107462&key=user_uploads/859771/65a0b3fd-75cf-4eea-a2ee-02590e3256ba)\n\nBut shipping a production-ready MCP server is its own project:\n\n* MCP is a protocol evolving fast .\n* Auth is easy to get [wrong](https://manufact.com/blog/authentication).\n* Every client behaves differently.\n* The stores have their own conformance requirements, and review can block you for weeks.\n\n## How Manufact works\n\nManufact is the cloud built specifically for MCP:\n\n* **Push to deploy.** Connect the GitHub App once and [every commit ships a new version of your MCP server](https://manufact.com/platform/hosting), with a preview deployment for each PR.\n* **Test every MCP tool and MCP-UI widget** in the [cloud inspector](https://manufact.com/platform/cloud-inspector).\n* **Know the moment your MCP breaks** in ChatGPT or Claude with [automatic cross-client testing](https://manufact.com/platform/cross-client-testing).\n* [**Publishing checklists**](https://manufact.com/platform/publishing-checks) so your MCP app doesn't get stuck in marketplace review.\n* **Auto-generated submission assets** (logo, copy, screenshots).\n* **Analytics, session replay, and traces** built in for MCP, so you can see [how it's used and why tools fail](https://manufact.com/platform/analytics).\n\n![uploaded image](/media/?type=post&id=107462&key=user_uploads/859771/ee30e016-9fb5-4958-890f-74febc54de3c)\n\n## Your product's UI inside the chat\n\nA plain MCP server lets the agent read and write your data. \\\nAn **MCP App** goes further: it's an MCP server that can return a UI as the result of a tool call, so your actual product interface renders inside Claude or ChatGPT. The user sees your charts and forms instead of a wall of text.\n\nFerruccio Balestreri (Amplitude) [put it well](https://x.com/0xferruccio/status/2028966278971670979):\n\n> since mcp ui was released in claude we got a 2x boost in retention.\n\nWith the [mcp-use SDK](https://github.com/mcp-use/mcp-use) you write a normal React component, drop it in, and it registers as an MCP UI resource automatically.\n\n## Backstory\n\nWe've been building on MCP since the protocol shipped. It started with the mcp-use SDK, the full-stack framework for MCP servers and apps. We kept watching companies struggle to take those servers to production, so we built the cloud for it (mcp-use is to Manufact what Next.js is to Vercel).\n\nManufact is now the **#1 recommended deployment option in OpenAI's docs.** \n\n![uploaded image](/media/?type=post&id=107462&key=user_uploads/859771/ddba2350-67c4-43d5-8150-30847d4375a2)\n\nWe've helped startups from recent YC batches like **AgentMail** and **Item** get onto the Claude Connectors marketplace, and larger companies in finance, insurance, and marketplaces run their MCP apps on Manufact in production.\n\n## Our asks\n\n1. Have an MCP server? **Deploy it on [Manufact](https://manufact.com/)**.\n2. Thinking about building an MCP App? [Copy our prompt for agents](https://manufact.com/prompt.md) and your coding agent will guide you.\n3. Trying to get listed on the marketplaces? [Book a call with us](https://cal.com/team/manufact/chat). We have publishing checks and direct contacts on the MCP teams at Anthropic and OpenAI.\n\nHope to see your MCP on [manufact.com](http://manufact.com), or that you at least learned something new. 🙂\n\n![uploaded image](/media/?type=post&id=107462&key=user_uploads/859771/685643a6-ecd5-42b4-b55f-ec394967ca57)\n\n",
        "url": "https://www.ycombinator.com/launches/RxG-manufact-mcp-cloud-for-your-claude-connector-chatgpt-plugin",
        "votes": 47,
        "created_at": "2026-07-28T14:55:15.055Z"
      },
      {
        "id": 92418,
        "title": "Manufact (mcp-use) - Build and deploy MCP Servers for AI Agents & MCP Apps for ChatGPT / Claude users",
        "tagline": "Create MCP servers/apps in minutes, connect your GitHub repo, and make them immediately available to AI agents and ChatGPT / Claude.",
        "body": "### **TL;DR**\n\n[Manufact](https://manufact.com) is the MCP cloud for dev teams to ship MCP Apps and Servers in production. Connect a GitHub repo and Manufact handles deployment, security, observability, and scaling, so teams can ship in minutes instead of weeks.\n\nOne codebase, deployed everywhere users and agents already live: the ChatGPT Apps Store, Claude Connectors, Gemini, Cursor, Claude Code, and more.\n\nWe're also the creators of [mcp-use SDK](https://github.com/mcp-use/mcp-use), the most popular high-level MCP framework for building MCP Apps and Servers.\\\n(mcp-use SDK is to the Model Context Protocol SDKs what Next.js is to React!)\n\nIt’s open-source and used by developers at 20% of US500 and companies like 6sense, Elastic, IBM, Innovacer, Intuit, NVIDIA, Oracle, Red Hat, Tavily, and Verizon are building with us.\n\n### **The ask**\n\nIf you're building MCP Apps or Servers, or you know someone who is, we'd love to talk.\n\n<https://cal.com/team/manufact/chat> \\\nor shoot a message to us: +1 (628) 899-2498 \\\nor [founders@manufact.com](mailto:founders@manufact.com)\n\n### **Our story**\n\nWhen MCP came out, we couldn't believe such a powerful protocol was locked into IDEs and Claude Desktop.\n\nSo we built mcp-use, the open source framework that lets any developer build MCP Apps and Servers in code, in a structured and composable way.\n\nIt got adopted fast: 7M+ downloads across Python and TypeScript, almost 10k GitHub stars, and dev teams at top companies shipping with it.\n\nBut OSS is only half the story. Once teams had something working, they hit the wall every infra team knows: deployment, auth, secrets, observability, scaling. Stitching that together for MCP is a multi-week project. That's what Manufact solves.\n\n### **Make something agents want**\n\nMCP unlocks something most products have never had access to before: real estate inside ChatGPT and Claude.\n\n800M+ users already spend their day in those chats. \\\nWith MCP, a product can show up there as a native app or connector, with no separate UI to build, no app to install, no new login flow. \\\nThe user just asks, and your product does the work.\n\n### **Problem**\n\nThe catch is that \"build once, ship everywhere\" is its own infra problem. ChatGPT Apps, Claude Connectors, Gemini, and the long tail of agent surfaces (Cursor, Claude Code, Codex, OpenAI Agents, Mastra, LangChain, Vercel AI SDK) each have their own quirks, auth flows, and submission requirements. Manufact lets you build one codebase and ship it to all of them.\n\n### **What Manufact does**\n\nConnect your MCP repo once. Every push auto-deploys.\n\n1. **Build:** Scaffold a full MCP App or Server with _npx create-mcp-use-app_ or drop in existing MCP code unchanged.\n2. **Deploy:** GitHub App connects once. Every push auto-deploys to Manufact Cloud. Preview URL per branch. Custom domains with SSL handled.\n3. **Publish.** Get your app in front of users in the ChatGPT Apps Store and Claude Connectors. Submission assets, marketplace checklists, and an embeddable chat widget for your own site, docs, or campaign pages.\n4. **Iterate.** Cloud Inspector debugs from any browser against real clients. Swap models. Run evals on every deploy.\n5. **Monitor.** Analytics, session replay, JSON-RPC traces, and alerts on regressions, so you catch issues before users do. Less than 60 seconds from _git push_ to a live MCP App or Server, available across ChatGPT, Claude, Gemini, and any agent surface that speaks MCP.\n\n### **Ask**\n\nDo you know anyone already using MCP servers internally or building products powered by AI agents?\n\nFor the first few companies we will personally create/integrate MCP servers you need, have everything running through our platform, either on cloud or your own infrastructure. We even help you integrate our SDK into your code.\n\nWhat do you think? Can we help you?\n\nBook a call: <https://cal.com/team/manufact/chat>\n\nShoot a message to us: +1 (628) 899-2498 or [founders@manufact.com](mailto:founders@manufact.com)",
        "url": "https://www.ycombinator.com/launches/O2c-manufact-mcp-use-build-and-deploy-mcp-servers-for-ai-agents-mcp-apps-for-chatgpt-claude-users",
        "votes": 85,
        "created_at": "2025-07-24T17:55:36.172Z"
      }
    ]
  },
  {
    "id": 30720,
    "name": "Autosana",
    "slug": "autosana",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/5c7dda83aa113d5017c2cb187435ccccb356bd6a.png",
    "website": "https://autosana.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Autosana is the end-to-end testing layer for your coding agents, across iOS, Android, and Web apps.\r\n\r\nStep away from your laptop. Come back to full-stack features built and tested end-to-end, production ready.\r\n\r\nAutosana creates, updates, and runs tests automatically from your code diffs. Locally, it loops with your coding agent until every test passes. In PRs, it loops with cloud agents and shows video proof of your new feature or bug fix working end-to-end.\r\n\r\nNo setup, no maintenance, just tests evolving with your codebase. Ship with confidence.",
    "one_liner": "AI agents for E2E testing across mobile & web",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1751416575,
    "tags": [
      "Developer Tools",
      "B2B",
      "Enterprise Software",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "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/autosana",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/autosana.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/autosana/",
    "x_url": "https://x.com/autosanaai",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/autosana",
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/5c7dda83aa113d5017c2cb187435ccccb356bd6a.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [
      "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/4dc6458135f7441d899916ffc7de13b7663dc0b6.png"
    ],
    "primary_partner": {
      "name": "Tyler Bosmeny",
      "url": "https://www.ycombinator.com/people/tyler-bosmeny"
    },
    "founders": [
      {
        "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/",
        "x_url": "https://x.com/YSundrani79540",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/af4f532a5f0f722ad68b16cc54c824938e57bee3.jpg"
      },
      {
        "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.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jason-steinberg-6018261b6/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/254bd31ab6d07bc741353a9b74ea77d95aacdc15.jpg"
      }
    ],
    "jobs": [],
    "news": [],
    "launches": [
      {
        "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"
      }
    ]
  },
  {
    "id": 30722,
    "name": "Omnara",
    "slug": "omnara",
    "former_names": [
      "GroundDocs"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fd794dace414f8acdb113022db360874e7706519.png",
    "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",
    "launched_at": 1753676392,
    "tags": [
      "Developer Tools",
      "AI",
      "AI Assistant"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "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/omnara",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/omnara.json",
    "year_founded": 2025,
    "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",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/fd794dace414f8acdb113022db360874e7706519.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [
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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",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3f0f734f148a9e0481b772518abcd7959193178a.jpg"
      }
    ],
    "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"
      }
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    "id": 30756,
    "name": "Notte",
    "slug": "notte",
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    "website": "https://www.notte.cc/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Notte is cloud browser infrastructure for AI agents. Sessions with live view and replays, residential proxies, stealth and CAPTCHA solving, authenticated profiles with account creation and 2FA, payments in the browser, and serverless functions that run next to the browser, all through one API",
    "one_liner": "Browser infra for AI agents: sessions, auth, proxies, payments",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1752518156,
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    "stage": "Early",
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    "year_founded": 2025,
    "city": "San Francisco",
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      "name": "Harj Taggar",
      "url": "https://www.ycombinator.com/people/harj-taggar"
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    "founders": [
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        "full_name": "Andrea Pinto",
        "title": "Founder/CEO",
        "founder_bio": "Founder & CEO @ Nottelabs",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/pinto-andrea",
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        "user_id": 2782127,
        "full_name": "Lucas Giordano",
        "title": "Founder/CTO",
        "founder_bio": "Founder & CTO @ Nottelabs",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/giordano-lucas/",
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      {
        "id": 93601,
        "title": "Nottelabs: Web Agents for Enterprise",
        "tagline": "Reliable Web Agents that can act and scrape on any site at scale",
        "body": "**TLDR;** Notte provides a platform to build and deploy web AI agents that don’t break. We turn messy, repetitive web tasks into reliable, self-healing workflows so businesses can scale automation with confidence.\n\nhttps://www.youtube.com/watch?v=uwTOpQTUfyk\n\n**Context**\n\nWe built Notte because the web was made for humans, not AI agents. Our first product was a perception layer that helps LLMs parse and understand site structure, boosting agents’ performance. But 90% isn’t enough to scale enterprise workflows with confidence.\n\n**Agent Workflows**\n\nThat’s why we launched **Agent Workflows** - where web automation meets agentic reasoning. Start an agent to discover the workflow, freeze the routine into deterministic steps, and keep agents only where it’s needed to unlock new capabilities. If a site changes, agents dynamically close the gap to ensure workflows never break.\n\nLess tokens = Less expensive = More control = Faster automation\n\n**Full-stack Ecosystem**\n\n* **Hosted Sessions** - Stealth mode and auto-scaling browser\n* **Vaults** - Credentials, MFA tokens, SSO, and cookies securely\n* **Personas** - Emails and phone numbers for account creations\n* **Payments** - Credit card payments and agentic transactions\n* **Misc** - File IO, Replays, CDP compatibility, etc.\n\n**The founders**\n\n![uploaded image](/media/?type=post&id=93601&key=user_uploads/2385904/142c16f2-bc85-464a-9b5d-63f84caa5549)\n\nHey - We’re **Andrea Pinto** and **Lucas Giordano**. We’ve known each other for 6 years and bring deep technical expertise. We led ML and LLM research at MIT, Oracle, and IBM Research, and have spent years building in the web automation space.\n\n**Asks -** SIGN UP here: https://console.notte.cc/ and shoot us a message with the hard web workflows you’re trying to address and we’ll solve them with you. Email: [founders@notte.cc](mailto:founders@notte.cc)",
        "url": "https://www.ycombinator.com/launches/OLh-nottelabs-web-agents-for-enterprise",
        "votes": 82,
        "created_at": "2025-09-04T19:52:00.082Z"
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    "id": 30762,
    "name": "KERNEL",
    "slug": "kernel",
    "former_names": [
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    "website": "https://www.kernel.sh",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Kernel is crazy fast, open source infra for AI agents to access the internet 🧠🕸️\r\n- Built on unikernels for crazy fast cold starts and low resource usage\r\n- Sub-150ms cold starts on managed headful browsers\r\n- Built-in stealth mode with residential proxies and automatic CAPTCHA solving\r\n- Full observability: session recording, live view, and full logs\r\n- Persistent sessions that maintain cookies and auth across invocations\r\n- Native support for all browser and computer use frameworks\r\n- SOC 2 compliant and HIPAA-ready\r\n\r\nTrusted by Cash App, Rye, and 1000+ others. Backed by Accel & Y Combinator (S25).",
    "one_liner": "Crazy fast, open source infra for AI agents to use the Internet",
    "team_size": 22,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1753229701,
    "tags": [
      "Developer Tools",
      "Cloud Computing",
      "Infrastructure",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2025",
    "status": "Active",
    "industries": [
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      "Infrastructure"
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    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Partly Remote"
    ],
    "stage": "Growth",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/kernel",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/kernel.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/trykernel",
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    "fb_url": null,
    "cb_url": null,
    "github_url": "https://github.com/onkernel",
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    "primary_partner": {
      "name": "Tyler Bosmeny",
      "url": "https://www.ycombinator.com/people/tyler-bosmeny"
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    "founders": [
      {
        "user_id": 101761,
        "full_name": "Catherine Jue",
        "title": "Founder/CEO",
        "founder_bio": "Co-Founder and CEO @ Kernel. Previously co-founder @ Sway Finance (S16)",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/juecd",
        "x_url": "https://twitter.com/juecd__",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/76b95b6560f6faac427383c9b5fe708d1421927d.jpg"
      },
      {
        "user_id": 26604,
        "full_name": "Rafael Garcia",
        "title": "Founder/CTO",
        "founder_bio": "Co-founder and CTO at Kernel. We're making browser infra fast.\n\nPreviously co-founder and CTO at Clever (S12, exited for $500m).",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/rafgarcia/",
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        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/70c4b460440085cf060e26d5a87677498f80b80b.jpg"
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    "jobs": [],
    "news": [
      {
        "title": "We’ve raised $22m to scale our browser infrastructure platform for AI agents",
        "url": "https://blog.onkernel.com/series-a-announcement/",
        "date": "Oct 09, 2025"
      }
    ],
    "launches": [
      {
        "id": 92607,
        "title": "Kernel: Crazy Fast Browser Infrastructure",
        "tagline": "Browsers-as-a-service for web automations and AI agents",
        "body": "Hey everyone! We’re Catherine and Raf, the founders of Kernel.\n\nhttps://youtu.be/vexAn3_KYvc\n\n# **🤝 TLDR:**\n\nWe make an API to instantly launch browsers in the cloud so AI can use the internet just like humans do.\n\n# **🚀 What’s Kernel?**\n\nKernel is the best place in the world to launch web agents and browser automations. We handle the hard parts of running browser infrastructure in the cloud so you don’t have to: spinning up browsers quickly, responsive read/write live view, logs, headless vs. headful mode, residential proxies, and more.\n\nOur edge is an infrastructure platform that’s **flexible, observable, and insanely fast** from day one:\n\n* **Performance** - web automations and Computer Use agents can launch and connect to Kernel browsers in 300 milliseconds\n* **Isolation x telemetry** - Kernel browsers run in isolated virtual machines and ship with live views & replays so you can see exactly what your agent saw and take control when needed\n* **Agent runtime** - launch your web agent on Kernel’s code execution platform to seamlessly connect it to a browser in the cloud\n* **Simple, clear pricing** - pay only for the resources you use. Our straightforward pricing model makes it easy to predict usage costs\n\n![uploaded image](/media/?type=post&id=92607&key=user_uploads/101761/f06a340f-9752-48c9-a20a-f952e18c403e)\n\n# **⚡️ How does it work?**\n\nKernel’s API makes it simple to launch browsers in the cloud and automate anything on the internet. **We work with any browser/web agent framework**: **Playwright, Puppeteer, Browser Use, Magnitude, and more.** Users love our platform for:\n\n* Instant **browser spin-ups** on-demand\n* **VM logs & read/write live view**\n* Video **replays**\n* **Browser session** reuse\n* **Residential proxies** and auto-CAPTCHA solvers\n* **Turn any agent into a https endpoint** — we host your agent, you invoke it on-demand with a prompt\n* & much more soon!\n\n# **👨‍💻👩‍💻 The Team**\n\nRaf and Catherine started Kernel from the shared belief that cloud infrastructure can be 100x better. We believe that well-designed, opinionated tooling unlocks superpowers, and we’re passionate about building best-in-class infrastructure for the next generation of AI applications.\n\nBefore starting Kernel, Raf was the co-founder/CTO of Clever (YC S12), which exited for $500m in 2021. Catherine was the co-founder of Sway Finance (YC S16) and most recently led Cash App’s team of forward deployed engineers and Cash App’s docs platform.\n\n# **🙏 Our Ask**\n\nIf you:\n\n* Run **browser automations**\n* **Built a web agent locally** and want to run it in production\n* Maintain **browser containers** but want to outsource the infrastructure because it’s not core to your IP\n\nCheck out [our platform](https://www.onkernel.com/) to sign-up, or schedule a demo with us [here](https://calendly.com/d/cwr7-xxq-m45).\n\n![uploaded image](/media/?type=post&id=92607&key=user_uploads/101761/bdc37fff-37ff-4eea-8a25-8bb544e1ba51)\n\n",
        "url": "https://www.ycombinator.com/launches/O5f-kernel-crazy-fast-browser-infrastructure",
        "votes": 34,
        "created_at": "2025-07-31T16:55:43.448Z"
      }
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  },
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    "id": 30768,
    "name": "Okibi",
    "slug": "okibi",
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    "website": "https://okibi.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Okibi generates a CLI from any product's codebase, so AI agents can use it the way people do.\r\n\r\nAgents are becoming software's next customers. When one comes to a product to do a task or purchase and finds no doorway in, it moves on to the competitor whose CLI lets it through. Okibi turns products into CLIs and agents into customers.\r\n\r\nDoorDash, Mercury, Gusto, Ramp, and 30+ other companies have already launched first-party agent CLIs. Okibi is how every product gets one.",
    "one_liner": "Turns products into CLIs and agents into customers",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1752707566,
    "tags": [
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      "SaaS",
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    "isHiring": false,
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    "batch": "Summer 2025",
    "status": "Active",
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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/okibi",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/okibi.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/okibi-ai",
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    "primary_partner": {
      "name": "Gustaf Alstromer",
      "url": "https://www.ycombinator.com/people/gustaf-alstromer"
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      {
        "user_id": 539005,
        "full_name": "Mahyad Ghassemi",
        "title": "Founder/CEO",
        "founder_bio": "2x YC founder building a web app to create AI coworkers using natural language, think of it as Lovable but specifically designed for AI agents.\n\npreviously built the first web browser designed for work with AI agents built in @SigmaOS (S21), used by 100,000+ people with 75,000 LLM requests per day.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/mahyad-ghassemi/",
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      },
      {
        "user_id": 286297,
        "full_name": "Saurav Mitra",
        "title": "Founder/CTO",
        "founder_bio": "Building Okibi (S25) to create AI coworkers using natural language, like Lovable but specifically designed for agents.\n\nPreviously built SigmaOS (S21), the agentic browser built for work. Used by 100,000+ people.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/thesauravmitra/",
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      {
        "id": 114523,
        "title": "Okibi - Agent-ready CLIs",
        "tagline": "Turn your product into a CLI, and agents into customers",
        "body": "Hey everyone, we're Mahyad and Saurav, the founders of Okibi.\n\n**TL;DR** [Okibi.ai](http://Okibi.ai) turns your product into a CLI, so AI agents can use it just like your users do.\n\nAgents are becoming the main users of our apps and softwares, but most of those products still aren't designed to be fully usable by agents.\n\nDoorDash, Mercury, Gusto, and 30+ others have already launched agent-ready CLIs.\n\n**Okibi generates yours.**\n\n<https://youtu.be/LANzB5DZ7_s>\n\n### **Problem**\n\n**The shift.** Work has quietly moved into agentic tools like Claude and Codex. The person who used to open your app now sends their agent. Agents create 90% of new Supabase databases and 2/3 of Mintlify docs traffic.\n\n**The gap.** Agents can read everything, but signing up, configuring a project, or placing an order, is another story. With MCPs, you'll give the agent too many tools at once and it'll start using the wrong ones. With direct API calls, the agent has to individually call endpoints for complex workflows or polling loops.\n\n**The turn.** Claude Code and Codex proved it; agents do their best work in the terminal, and a CLI is how your product shows up there. No tools need to load up front, because agents can discover what they need when they need it through progressive disclosure with --help, and all complex workflows are pre-built so it doesn't have to figure it out on the fly.\n\n**The proof.** Companies are already shipping agent-ready CLIs. Even Notion, with one of the best-known MCP servers, shipped one.\n\nAn agent that struggles to use a product will go to a competitor that it won't struggle with.\n\n**Okibi is how you become that competitor.**\n\n### **How it works**\n\nBuilding a toy wrapper CLI is easy. Building an agent-ready production CLI is a different story.\n\n**Research.** Okibi **reads all of your APIs, SDKs, MCPs, and researches similar products** to yours and defines the standard for your product's commands.\n\n**Build.** We build your entire product as commands in a CLI, with structured JSON output, descriptive errors, and dry-runs with input validation.\n\n**Customize.** You can keep customizing the commands that are generated through our agent.\n\n**Verify.** This isn't just \"it compiles\". Commands run in a real sandbox, the outputs are checked, and **the CLI is fully evaled for agent use.**\n\n**Ship.** You get a compiled binary with a skill file baked in, so an agent that installs it already knows how to use your product.\n\n**Maintain.** Whenever your product updates, **Okibi mints the changes and maintains your CLI for you.**\n\n**Identity.** Even with a CLI, an agent can't set up an account for your user. With **Okibi Identity, the agent can set up the account** and continue working uninterrupted. And that's how you get agents as customers!\n\n![uploaded image](/media/?type=post&id=114523&key=user_uploads/539005/aaf9f512-390f-4a14-85ca-9bfb8db5a29c)\n\n### **About us**\n\nWe've been building software together for almost a decade, and this is our second YC startup. At SigmaOS (S21) we built the first browser with built-in agents. Since then, every time we wanted our agents to use a product, we generated a CLI for it, since MCPs weren't enough for the job. It happened enough times that we're now building it for everyone.\n\n### **Our ask to you**\n\nIf you are building a product that you want agents to use, **please reach out to us**! We would love to learn what you are building and how you are letting agents use your product.\n\nYou can also head over to [okibi.ai](http://okibi.ai) to turn your product into a CLI\n\nBook a call: <https://calendly.com/m-cal-uvfs/okibi-customer-call>\n\nEmail: [m@okibi.ai](mailto:m@okibi.ai)",
        "url": "https://www.ycombinator.com/launches/Tn9-okibi-agent-ready-clis",
        "votes": 34,
        "created_at": "2026-09-10T14:09:32.663Z"
      },
      {
        "id": 92336,
        "title": "Okibi | The agent that builds agents 🤖",
        "tagline": "Effortlessly build automations and agents using simple prompts",
        "body": "Hey everyone 👋\n\nWe are [Mahyad](https://x.com/MahyadGhassemi) and [Saurav](https://x.com/thesauravmitra), the co-founders of [Okibi](https://okibi.ai)\n\n# TL;DR\n\n**Okibi is a web app that lets you create AI agents using natural language**. You can think of it as Lovable for Agents.\n\n**Our ask:** try it out [@ijustwannabuild.ai](https://ijustwannabuild.ai), and [book a call with us](https://calendly.com/d/cq3k-yhy-g6d/user-interviews)! We’d love your feedback and what kind of agents you need for your company\n\nhttps://youtu.be/3cZWA9SAohM\n\n# ❌ The problem and why we care to solve it\n\n![uploaded image](/media/?type=post&id=92336&key=user_uploads/539005/cd13cafb-1a52-4dba-a8d7-92d71516dbfa)\n\nThe two of us have been **building software for over 10 years** and **working together for the past 7.** Actually, This is also **our second YC startup together**. At our previous company, SigmaOS (S21), where we built the first browser with built-in agents, we **ran into a ton of repetitive tasks** and **had to build many agents for our own product**. Automating those tasks was **slow and complicated**. We often ended up doing things manually or relying on partial solutions like Zapier, Lindy, custom scripts, or hacked-together LLM tools. The agents we did build for our product also eventually became **messy and hard to maintain**.\n\nCreating AI agents typically requires **complex**, **time-consuming** **setup**, including **tool calls**, **LLM syntax management**, **multi-agent orchestration**, **browser use**, **human in the loop**, **evals**, and **hosting deployments**.\n\nSo, when building agents two primary challenges always come up:\n\n* Evals\n* Architecture and Infrastructure\n\n# **✅ How Okibi solves it for you**\n\n![uploaded image](/media/?type=post&id=92336&key=user_uploads/539005/e323bc33-463f-42f7-ad7a-daf85d3ceb03)\n\n\nOur web app provides a **chat interface and toolkit to easily create AI agents**. Just describe your agent in natural language, similar to vibe coding, and our app **automatically generates your agent's tool calls, human in the loop, browser use, and runs an initial eval on your agent.**\n\nWhether you're building an **internal workflow automation** to remove repetitive or time consuming tasks, or **launching a product with** **agents**, Okibi can help you build it.\n\nWe are currently **working with** **15 YC companies** from the current and previous batches to automate tasks like:\n\n* Pre-qualify companies with the right person at those companies to sell your product to\n* Generate invoices and update their invoice trackers based on email and contract\n* Pre-meeting prep for client or sales lead call\n* Generate pricing and proposal based on meeting notes and existing contracts\n\nhttps://www.loom.com/share/2c038ed7243a4984a0b8224c2e24eacb?sid=cec442cb-88cf-4b75-b9bf-84b7fa3618de\n\n# 🤖 Ready to start automating with agents?\n\nHead over to [ijustwannabuild.ai](https://ijustwannabuild.ai), and…\n\n![uploaded image](/media/?type=post&id=92336&key=user_uploads/539005/3a716ad3-1715-4646-a37a-80045f928406)\n\n",
        "url": "https://www.ycombinator.com/launches/O1I-okibi-the-agent-that-builds-agents",
        "votes": 155,
        "created_at": "2025-07-21T21:10:06.804Z"
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        "full_name": "Glenn Töws",
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        "full_name": "Julian Goetze",
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      {
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        "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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        "full_name": "Aram Shatakhtsyan",
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      {
        "id": 92593,
        "title": "Modelence: all-in-one TypeScript platform for startups",
        "tagline": "Ship production AI apps 10x faster with built-in auth, database and LLM integration",
        "body": "You built the demo in a weekend. Now you need auth, a prod-grade database, real-time events, AI observability, cron jobs, email, monitoring… and you needed them yesterday.\n\nWe spent a decade building platforms while scaling to millions of users and enterprise customers. Now we put that into an open-source framework, so others wouldn’t have to do the same from scratch.\n\n![uploaded image](/media/?type=post&id=92593&key=user_uploads/2485356/d6404f4b-fb88-47d1-adcc-b895394e41af)\n\nModelence is a batteries-included framework that abstracts away boilerplate so you can just focus on building your product logic and nothing else - it’s like Next.js + Vercel + Supabase on a single platform, built for full-stack TypeScript.\n\nhttps://www.youtube.com/watch?v=S4f22FyPpI8\n\n**Why Modelence?**\n\nShipping production apps is much harder than building a prototype that runs locally and 95% of all production apps share the same building blocks. We did a massive amount of work on our previous platforms that was not specific to our product, and we’ve created Modelence to abstract that away:\n\n* Authentication\n* Database setup\n* Hosting / CDN\n* AI integration (LLM observability, prompts)\n* Real-time events\n* Cron jobs\n* Email service\n* Monitoring\n* Analytics\n* Admin dashboards\n\nAndrej Karpathy recently posted about this same exact problem - [**https://x.com/karpathy/status/1905051558783418370**](https://x.com/karpathy/status/1905051558783418370) and explained it further in his [**YC AI Startup School talk**](https://tinyurl.com/45xvsm3y).\n\n**Who is this for?**\n\nStartups that are shipping TypeScript production apps and want to focus on building their product without worrying about boilerplate, DevOps, infra and scaling.\n\n**Founders**\n\n* Aram S (ex-Principal Eng @ Intuit, co-founded [**CodeSignal**](https://codesignal.com/))\n* Eduard P, PhD (Founding Eng @ [**CodeSignal**](https://codesignal.com/))\n\n**Getting Started**\n\nModelence is open-source - go to https://modelence.com to create a free cloud environment and try it!",
        "url": "https://www.ycombinator.com/launches/O5R-modelence-all-in-one-typescript-platform-for-startups",
        "votes": 19,
        "created_at": "2025-07-30T23:49:26.229Z"
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        "full_name": "Luke Shiels",
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        "id": 101753,
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        "full_name": "Joe Fioti",
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        "title": "Luminal - PyTorch for Production",
        "tagline": "Luminal automatically speeds up and deploys your PyTorch models",
        "body": "Hey we’re Joe, Jake, and Matthew, cofounders of Luminal. \n\nLuminal is an [open-source](https://github.com/jafioti/luminal) ML compiler that generates blazingly fast CUDA kernels and makes deploying AI to production one line of code. We’re already powering research at Yale, production workloads at VC-backed startups and several research labs.\n\nhttps://youtu.be/Rgo15NY9K-8\n\n**TLDR:**\n\n* Our drop-in upgrade to PyTorch automatically generates complex GPU kernel code, like Flash Attention, with zero hand-engineering\n* We provide truly serverless deployments; no idle costs or cold starts.\n* By not relying on pretrained LLMs or hand-written optimizations, we can reliably speed up any model\n\n**Ask:**\n\n* [Book a meeting](https://calendly.com/accounts-luminalai/30min) if you write PyTorch and want your models to run fast\n* [Star us on github](https://github.com/jafioti/luminal) and try Luminal right now on your own laptop!\n* Email us if you know someone who runs custom models: [contact@luminalai.com](https://mailto:contact@luminalai.com)\n\n—\n\n### **The problem:**\n\nMost people running their own AI models are lighting money on fire and don’t even know it. AI teams are frustrated when moving their model from dev to production. They either fall into dependency hell or kill their model’s speed. Today, **companies waste millions of dollars on GPU engineering** teams to optimize new models before they can be served to users.\\\n—\n\n### **How Luminal solves it:**\n\n**Luminal replaces a process that companies pay GPU engineers $300k+ a year to do.**\n\nOur key insight is that by treating optimization as a search problem, we’re able to automatically discover extremely complex optimizations in minutes that would take a GPU expert weeks. We use a series of ‘rewrite rules’ to create millions of graphs to describe your model, generate kernel code for each and then search for the fastest one based on runtime.\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXfNzLo_zAkiYY_fsEQMseEQZXpdFjn0chhSJ8Wn-0WOkSHGblAi1XseXLIbZsiim6z8_AiWxx6wuzTuCQYfNe2ELulijuOBR5b_1x4-kzEoxEoxutW0qv127MHbl1Lu6YLIJBfP_A?key=gRJ545K4hfVVtN0eX-o_ZQ)\n\n_Example of a complicated kernel on the left that Luminal automatically sped up, on the right._\n\nLuminal is:\n\n1. **Closing the research → engineering gap.** Because we auto-generate optimized GPU code directly from your PyTorch, a brand-new model can go from research notebook to production in hours instead of weeks\n2. **Writing blazing fast models.** Luminal generates kernels that would take a seasoned GPU engineer weeks of painstaking profiling and tuning to write.\n3. **Future-proofing AI for new chips**. We can rerun our compiler on fresh hardware to get new optimal kernels so you're never out of date.\n\n—\n\n### **You should reach out if:**\n\n* You’re an AI researcher or ML engineer\n* You’d like to lower your compute bill by **tens of thousands of dollars a month**\n* You work at a company that runs their own **custom models**\n\nIf you want your team spending more time making the world’s best models and less time optimizing hardware and cloud infrastructure, we’re for you!\n\n—\n\n### **The Team:**\n\n[Joe](https://www.linkedin.com/in/joe-fioti-24a986189/) - ex Intel, every Intel chip sold has the AI accelerator Joe worked on. He has extensive experience optimizing performance at the silicon level.\n\n[Matt](https://www.linkedin.com/in/matthewjgunton/) - ex Amazon where his software handled finding and automatically fixing issues within the global inventory network 24/7\n\n[Jake](https://www.linkedin.com/in/jake-stevens-/) - ex Apple Jake worked on imaging at Apple for your iPhone. He’s been a founder (with an exit) and head of growth at another startup that he grew to \\~$5M ARR.\n\nSend us an email: [contact@luminalai.com](https://mailto:contact@luminalai.com)\n\n[Book a call with us](https://calendly.com/accounts-luminalai/30min)\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXd1hRLOasxYQ38r0AmMN9fTC9-BatUjGjE9-BXM21-w8PRvhBJVeYAc3pWlLPVlmTtnP3jG9Pa5HmUIGTYaZ93ClC-M-CRx0nkNw-DgS3Wh28xWXaUzXVwL_XPCNUL8JyTd_9FmBA?key=gRJ545K4hfVVtN0eX-o_ZQ)\n\n",
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        "votes": 127,
        "created_at": "2025-07-20T17:12:19.542Z"
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        "tagline": "Build APIs for any website that are 100X faster than browser automation",
        "body": "# **Launch BF: Parse - Build APIs for any website that are 100x faster than headless browsers**\n\nTLDR: [Parse](http://parse.bot/) reverse engineers websites and builds deterministic APIs for scraping and web automation. Instead of spinning up slow, expensive headless browsers, Parse makes deterministic APIs that use direct network requests that **cost fractions of a cent and return in milliseconds**.\n\n![uploaded image](/media/?type=post&id=95327&key=user_uploads/986516/c6b55ddc-9855-4030-84b7-a70e251330da)\n\n**The Problem**\n\nHeadless browsers are the default for web scraping and automation, but they're painfully slow and unreliable at scale. Scraping thousands of dynamic pages with Playwright or Puppeteer takes hours, often failing halfway through due to timeouts or memory issues. Repeat tasks become absurdly expensive at scale due to the cost of managing hundreds of concurrent browsers.\n\n**How Parse Works**\n\nWe reverse engineer the underlying network requests behind any action on a website and build a deterministic API to replicate it. Parse automatically handles dynamic values (session cookies, CSRF tokens, etc.), IP rotation, and antibot challenges.\n\nParse is able to build a set of endpoints to handle dynamic multi-turn interactions, such as getting the questions on a job application through one endpoint and submitting the job application through another endpoint, **even though every application has unique questions**.\n\nDemo: https://youtu.be/UZGYkH2vAS4\n\nAll of this means that the APIs that Parse generates execute in seconds and cost fractions of a cent to run.\n\n**Background**\n\nI started coding at 12 to build bots to purchase limited edition sneakers in seconds. After leaving that scene, I led engineering at a trading card market platform and researched political botnets at Berkeley. No matter where I went, I realized how crucial live web data and interaction is and how slow current solutions are. I launched the first version of Parse in August and got to 35k users in a month.\n\n**Asks**\n\n* **If you're using headless browsers for scraping or automation, let's chat.** We're launching document downloading and auth handling in the coming weeks and want to hear your pain points. If you need custom solutions build out, please email me at [alex@parse.bot](mailto:alex@parse.bot)\n* **Try Parse today** - [**Parse.bot**](http://Parse.bot)",
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        "full_name": "Rohil Agarwal",
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        "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!",
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      {
        "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"
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    "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. ",
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    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/usedari/",
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      "name": "Harj Taggar",
      "url": "https://www.ycombinator.com/people/harj-taggar"
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        "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/",
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        "full_name": "Benjamin Hong",
        "title": "Founder/CTO",
        "founder_bio": "Building dari.dev",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/benjaminyhong/",
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      {
        "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"
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      {
        "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"
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    "id": 30903,
    "name": "Kestrel AI",
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    "long_description": "Kestrel is the AI automation layer for platform engineering teams.\r\n\r\nPlatform teams use Kestrel to automate incident response, cloud provisioning, CI/CD, security, and developer requests across their stack.\r\n\r\nKestrel turns natural-language prompts into deterministic, production-ready workflows with 40+ integrations, 200+ pre-built actions, and support for custom HTTP and webhook actions.\r\n\r\nDeveloper-first, with a CLI, Python SDK, and MCP server to manage workflows from where platform teams already work.",
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      {
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        "full_name": "Raman Varma",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder & CEO. Prev: CS @ Berkeley; ML @ Sky Computing / BAIR labs, Square, Coursera; SWE @ Illumio.\nBuilding Kestrel – AI agents for platform engineering teams.",
        "is_active": true,
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      {
        "id": 104092,
        "title": "Kestrel - AI Agents for Platform Engineering",
        "tagline": "Automate incident response, CI/CD, developer requests, security, and more with AI agents that build deterministic workflows across your platform stack.",
        "body": "TL;DR: Kestrel turns natural-language prompts into deterministic, production-ready workflows that automate incident response, cloud provisioning, CI/CD, security, and developer requests. It supports 30+ integrations and is developer-first, with a CLI, Python SDK, and MCP server so you can manage workflows from where you (and your coding agents) already work. Build your first workflow in &lt;5 mins with $1,000 in usage credits at [usekestrel.ai](http://usekestrel.ai).\n\n<https://youtu.be/2y60CgQ-huM>\n\n**The Problem**\n\nCoding agents made every developer faster. But the platform team did not get faster with them.\n\nDevelopers now ship with Cursor/Claude/Codex and generate infrastructure, deployments, and provisioning requests at a rate no platform team was staffed for.\n\nAt illumio I once waited more than three weeks just to get Kafka clusters provisioned for a new service I was building. And provisioning is only part of it. The platform team is also on the hook for incident response when production breaks, repairing the CI/CD glue that ties the deployment pipeline together, platform security, and every \"can you just\" developer request in Slack.\n\nMost platform teams pick one of two bad options. They hand developers (and their agents) direct access to infra, CI/CD, and cloud accounts, and hope nothing breaks. Or they gatekeep and become the bottleneck every developer has to wait on.\n\nBuilding a platform that developers actually like has been a luxury only the largest engineering orgs could staff, and an understaffed platform effort usually does more harm than good.\n\n**The Solution**\n\nSee how it works: <https://youtu.be/g1dGUsuZgws>\n\nPlatform teams use Kestrel to automate incident response, cloud provisioning, CI/CD, security, developer requests, and more across their stack. You describe what you want to automate in plain English, and the Workflow Agent builds the whole thing. It draws from 140+ pre-built actions across 30+ integrations, plus custom HTTP APIs and webhooks for anything that isn't built in yet.\n\nOnce a workflow is configured it runs deterministically with no LLM deciding what to do at runtime.\n\nYou can define workflows that handle self-service developer requests without handing over the keys; scope who can trigger each workflow; fence it to specific clusters, cloud accounts, or repos; and require approval before anything touches production. Developers get a golden path without free rein, and the platform team keeps the guardrails without gatekeeping.\n\nKestrel analyzes your connected integrations and suggests ready-to-deploy workflows, and the Workflow Assistant turns your existing runbooks and scripts into production-ready automations, so you don't have to start from scratch: <https://youtu.be/IOoLb300rqE>\n\nEvery workflow you build in Kestrel is fully observable, with a dashboard that shows what's running, what's waiting on approval, and what failed; real-time step-level logs; and a failure diagnosis agent that fixes failed workflows for you: <https://youtu.be/SEInJ040ZVs>\n\nThe [Kestrel CLI](https://docs.usekestrel.ai/workflows/cli), [Python SDK](https://docs.usekestrel.ai/workflows/sdk), and [MCP server](https://docs.usekestrel.ai/workflows/mcp) let you and your coding agents build and manage workflows from the terminal and application code.\n\n**How It Works**\n\nFirst, connect your platform stack. Kestrel supports 30+ integrations across infrastructure, PaaS, AI compute, observability, on-call, networking, databases, CI/CD, and IaC:\n\n![uploaded image](/media/?type=post&id=104092&key=user_uploads/2950276/c11a044c-2df5-4c23-8035-5c23b99ad45c)\n\nThen, open the Workflow Agent and describe what you want to automate. Here are a few examples:\n\n* “When a PagerDuty alert fires for the production Kubernetes cluster, run root cause analysis, post the findings to #incidents in Slack, create a P1 Jira ticket, and apply the recommended fix after approval in Kestrel.”\n* “When a developer submits a cloud provisioning request in Slack, route it to the team lead for approval, provision the AWS resources with Terraform in the infra repo, and notify the developer once the pull request is merged.”\n\nEverything you do in the dashboard is available via the CLI/SDK/MCP. E.g. you can generate a workflow, activate it, and clear an approval from the terminal:\n\n![uploaded image](/media/?type=post&id=104092&key=user_uploads/2950276/e5c068f1-98e7-4e35-9e83-407f2d4807a6)\n\n**Ask**\n\nIf you're a platform engineer or eng leader tired of manually responding to developer requests, incidents, or CI/CD failures, you can try it yourself today with a 14-day free trial and $1,000 in usage credits. Use suggested workflows and the Workflow Assistant to build your first platform automations in minutes.\n\nIf you want to learn more about what onboarding looks like or dedicated infrastructure/on-prem deployment options, [book a demo](https://calendly.com/hello-usekestrel/30min) and I'll walk you through it.\n\n[Try Kestrel today](https://platform.usekestrel.ai/register)",
        "url": "https://www.ycombinator.com/launches/R4u-kestrel-ai-agents-for-platform-engineering",
        "votes": 20,
        "created_at": "2026-07-01T23:54:04.445Z"
      },
      {
        "id": 95330,
        "title": "Kestrel: AI Copilot for Kubernetes Ops & Security",
        "tagline": "Run Kubernetes securely and fix incidents in seconds, not hours.",
        "body": "Hey everyone, we’re [Raman](https://www.linkedin.com/in/ramanvarma/) and [Evan](https://www.linkedin.com/in/evanchopra/) from Kestrel 👋\\\n\\\n**TL;DR:** Kestrel helps teams using Kubernetes detect, investigate, and fix issues without manual firefighting. It monitors cluster health and security 24/7, finds root causes, and generates ready-to-apply YAML fixes - so incidents get resolved before you even reach for your laptop.\\\n\\\nLaunch video: https://youtu.be/HA2YziEBMVw\n\n**Ask:** If your team runs Kubernetes, we’d love to hear from you! You can reach out to us at [raman@usekestrel.ai](mailto:raman@usekestrel.ai) or [book a demo here](https://calendly.com/raman-usekestrel/demo). Or get started in minutes with a [14-day trial](https://platform.usekestrel.ai/register)!\n\n# **The** **Problem**\n\nRunning Kubernetes at scale is **chaos**.\\\n\\\nAs founding engineers on the Kubernetes Security team at Illumio, we saw both startups and large **organizations struggle with its complexity and scale**. For example, network policies are so tricky that many teams default to allowing everything, and even basic ops tasks like debugging failed rollouts mean spending hours digging through logs and events just to find where things went wrong.\\\n\\\nOver time, this complexity compounds and clusters begin to drift - configs diverge, policies break, and “temporary” workarounds become production. And when something goes wrong, **engineers are buried under alerts and reports** from disconnected tools, trying to debug blind at 3 a.m.\n\n# **Our Solution**\n\nKestrel is redefining how teams manage Kubernetes with the **first agentic platform that unifies ops and security**. It replaces manual triage with autonomous investigations and human-in-the-loop remediations - so issues that used to take hours to debug can be understood and fixed in seconds.\n\n💬 **AI Chat Assistant**: Investigate **any Kubernetes issue** across all of your clusters in plain English - skip the complex queries and context switching, and get answers with ready-to-apply YAML fixes from a single point of command.\n\n![uploaded image](/media/?type=post&id=95330&key=user_uploads/2950276/4cabf3fd-7053-4e7b-8562-4feaa5f72df4)\n\n🚨 **Incident Response**: Kestrel continuously monitors your clusters to detect incidents, trace root causes, and generate **YAML fixes that can be applied with a single click**. It's like having a dedicated on-call SRE team - without the burnout or headcount.\n\n![uploaded image](/media/?type=post&id=95330&key=user_uploads/2950276/218cbd5b-4100-4341-a02b-4b8ff04d5a26)\n\n🌐 **Topology Map**: Visualize your Kubernetes infra with classified intra-cluster, cross-cluster, and external traffic overlaid in real time.\n\n![uploaded image](/media/?type=post&id=95330&key=user_uploads/2950276/280f095a-4030-46bf-824e-1f0d421cf761)\n\n⚠️ **Risk Assessments**: Launch a swarm of specialized AI agents that discover vulnerabilities and provide **exact remediation steps** across network security, RBAC, privilege escalation, container image security and more. Validate fixes with a single click.\n\n![uploaded image](/media/?type=post&id=95330&key=user_uploads/2950276/53b80638-b9b4-4986-be1d-7a5ed6db5571)\n\n# **The Team**\n\n[Raman](https://www.linkedin.com/in/ramanvarma/) and [Evan](https://www.linkedin.com/in/evanchopra/) were founding engineers on Illumio’s Kubernetes team, where they built distributed systems to secure clusters for Fortune 500 companies.\\\n\\\nRaman previously worked on ML systems research at Sky Lab and BAIR. Evan was a security researcher during his Master’s in Computer Science, focusing on the Signal Protocol.\n\n![uploaded image](/media/?type=post&id=95330&key=user_uploads/2950276/7eeab8b1-9e35-4d4a-bac4-41b196c89fc7)\n\n",
        "url": "https://www.ycombinator.com/launches/Ona-kestrel-ai-copilot-for-kubernetes-ops-security",
        "votes": 37,
        "created_at": "2025-11-09T16:01:39.639Z"
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    "id": 30916,
    "name": "Rovr",
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "Rovr streamlines engineering operations by automating intake, triage, routing, and cross-team coordination. It replaces internal forms, manual Slack triage, and scattered docs with an AI front desk that understands requests, assigns owners, updates context, and posts status changes directly into Slack. Rovr’s built-in ops CRM gives teams a single system of record for eng requests — from tooling access to platform incidents to dev-infra workflows — reducing operational drag across the entire org.",
    "one_liner": "AI FDE Engine that runs your engineering workflows",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1761690618,
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        "user_id": 1694979,
        "full_name": "Arnav Jain",
        "title": "Founder",
        "founder_bio": "CS and Business at Berkeley. Prev. Bespoke Labs, Jeeva Clinical Trials, FHL Vive Research Lab.\n",
        "is_active": false,
        "linkedin_url": "https://www.linkedin.com/in/arnavjain053/",
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        "user_id": 2970156,
        "full_name": "Yash Jain",
        "title": "Founder",
        "founder_bio": "Ex-Mercor, Databricks Amazon. Berkeley Computer Science.",
        "is_active": false,
        "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,
    "name": "Compyle",
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    "website": "https://compyle.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Compyle is a less autonomous coding agent that asks before it acts. We're like Cursor or Claude Code - but you won't need to rewrite your codebase every time you use it for more than a small task.\r\n\r\nWe built Compyle because we were frustrated with the direction other coding agents are headed. They're all racing to be more autonomous, running for hours without human input.\r\n\r\nThis doesn't work for real production code. When agents run autonomously, they make countless small decisions that pile up in your codebase. Engineers lose ownership - they don't know what was implemented, can't effectively debug or maintain it, and struggle to build on top of it. The code becomes a black box, and they're forced to throw it away.\r\n\r\nCompyle keeps engineers in the driver's seat.",
    "one_liner": "The coding agent that actually collaborates with you",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1760115390,
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    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/compyle-ai",
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        "full_name": "Jonathan Miranda",
        "title": "Founder/CEO",
        "founder_bio": "Jonathan is co-founder and CEO of Compyle.\n\nHe studied Computer Science and Economics at Johns Hopkins University, where he led multiple AI research projects for the CS department and developed snake robots. He also founded Hopkins Deliveries, a campus food delivery service that built cost-effective tele-operated delivery robots. \n\nBefore Compyle, Jonathan was founding engineer #4 at Hadrius (YC W23), where he built core AI systems powering compliance at thousands of businesses today.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/miranda-jonathan/",
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      {
        "user_id": 2179876,
        "full_name": "Mark Nazzaro",
        "title": "Founder/CTO",
        "founder_bio": "Mark is the Co-founder and CTO of Compyle. \n\nPreviously the second engineer at Hadrius, he helped scale the company to its Series A, led engineers, and built much of the core AI product. Before that, at arXiv, he led the move to the cloud and launched its first major UI change in decades.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/marknazzaro/",
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      {
        "id": 94565,
        "title": "Compyle - Lovable for Software Engineers",
        "tagline": "The first coding agent that actually stops and asks questions",
        "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.",
        "url": "https://www.ycombinator.com/launches/ObF-compyle-lovable-for-software-engineers",
        "votes": 38,
        "created_at": "2025-10-10T21:28:16.037Z"
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    "id": 30929,
    "name": "Radius",
    "slug": "radiusbrowser",
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    "website": "https://www.radiusbrowser.com",
    "all_locations": "San Francisco, CA, USA",
    "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.",
    "one_liner": "Code and browse in the same place",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
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      "Design Tools",
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      "name": "Aaron Epstein",
      "url": "https://www.ycombinator.com/people/aaron-epstein"
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      {
        "user_id": 1748712,
        "full_name": "Quentin Romero Lauro",
        "title": "Founder/CEO",
        "founder_bio": "Previously @ Character.AI, Berkeley EECS, CMU HCII, and Pitt",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/quentinrl/",
        "x_url": "https://x.com/QRomeroLauro",
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      {
        "user_id": 1799847,
        "full_name": "Michael Klikushin",
        "title": "Founder/CTO",
        "founder_bio": "GT CS dropout. Prev @ Oracle, CMU HCII.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/mklikushin",
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      {
        "id": 95471,
        "title": "Inspector—AI IDE for front-end",
        "tagline": "Inspector helps front-end engineers ship faster with AI by automating the most frustrating part of the job — gathering context between the browser and the codebase.",
        "body": "https://www.youtube.com/watch?v=Bxd1kO10qz4\n\n\\\n\\\nWe’re [Michael](https://x.com/mkliku) and [Quentin](https://x.com/Qromerolauro) from **Inspector**, and we’ve spent the past few years building tools and interfaces that sit between humans and computers — from **HCI research** at **Carnegie Mellon** to products at **Character AI** and **Oracle.**\n\nWhen we started building web-based games, we were spending **12 hours a day tweaking front-ends** and going through the same loop over and over: wireframing in Figma, adding screenshots to Cursor, and debugging in Chrome DevTools. It felt like a constant game of telephone to get our agents the right context from the DOM, codebase, and how it actually looked.\\\n\\\nThat’s why we built **Inspector**, an AI IDE for front-end that connects your browser and codebase. Inspector lets you **select elements visually** and **prompt changes**, giving coding agents access to the same runtime context developers have: **visuals, elements, and logs**. With Inspector, you’re editing right in the front-end, not buried under tabs and screenshots.\n\n# \n\n# **Inspector lets you:**\n\n![uploaded image](/media/?type=post&id=95471&key=user_uploads/1799847/3679fe55-2611-4093-9ef5-bc6d6cfbe022)\n\n**Take DOM-aware screenshots** that snap to elements and **auto-attach to chat.**\n\n![uploaded image](/media/?type=post&id=95471&key=user_uploads/1799847/7673c2d3-c252-442c-8714-32468eeee92b)\n\nClick elements to use **their exact place in your codebase** as context for your agent run.\n\n![uploaded image](/media/?type=post&id=95471&key=user_uploads/1799847/4a9af745-7468-4584-88ae-3ad98c89a426)\n\nUse the terminal tool to **attach DevTools terminal output** straight to the conversation.\n\n# **Our Ask:**\n\n* If you’re a front-end dev, **check out Inspector** at [tryinspector.com](http://tryinspector.com) \n* Let us watch you code. If you’re a front-end developer email us at [founders@tryinspector.com](mailto:founders@tryinspector.com) so we can learn more about how you work!\n\n![uploaded image](/media/?type=post&id=95471&key=user_uploads/1799847/22f1298d-56d2-4949-a642-6443a28c4b0f)\n\n![uploaded image](/media/?type=post&id=95471&key=user_uploads/1799847/69870ad5-f57d-48f0-85fe-ef1b9382ea52)\n\n",
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        "created_at": "2025-11-12T23:10:49.777Z"
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    "name": "s2.dev",
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    "website": "https://s2.dev",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "S2 is an API for durable streams. We make working with streaming data dead simple and reliable.\r\n\r\nThe more we worked on data systems, the more we felt like there was a missing building block. The seamless experience of object storage simply did not exist for durable streams – so we set out to fix that!\r\n\r\nS2 reimagines streams as an unlimited and access-controlled web resource. Like if Kafka and S3 had a baby.\r\n\r\n- Building agents? Use granular streams to persist context in real time, make workflows auditable, and coordinate between agents.\r\n\r\n- Publishing fast-moving data? Streams support high fanout and can be accessed directly over the internet, so they are a great fit for broadcasting real-time feeds.\r\n\r\n- Sandboxing? Emit to per-instance streams, and read history or live events just as easily.\r\n\r\n- Local-first and multiplayer experiences? Propagate updates reliably and efficiently.\r\n\r\nStop dealing with clusters, and start streaming.",
    "one_liner": "API for unlimited, durable, real-time streams",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1759174945,
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      "Open Source",
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      "Infrastructure",
      "Databases"
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      "America / Canada",
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    "url": "https://www.ycombinator.com/companies/s2-dev",
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    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/streamstore/",
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      "name": "Nicolas Dessaigne",
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        "user_id": 235940,
        "full_name": "Shikhar Bhushan",
        "title": "Founder/CEO",
        "founder_bio": "Making streams plentiful and serverless. Hacked on retrieval systems at Etsy, a KV store at Facebook, and Kafka Connect at Confluent.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/shikhrr",
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      {
        "user_id": 1723893,
        "full_name": "Stephen Balogh",
        "title": "Founder/CTO",
        "founder_bio": "Loves Rust, and building systems that scale. Previously built novel infra for multi-modal product search at Etsy, and digital repository software at NYU",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/stephen-balogh-078a4995/",
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      {
        "id": 95319,
        "title": "s2.dev: Streams as a cloud storage primitive",
        "tagline": "The serverless API for unlimited, durable, real-time streams",
        "body": "Hi everyone! We are [Shikhar](https://www.linkedin.com/in/shikhrr/), [Stephen](https://www.linkedin.com/in/stephen-balogh-078a4995/), and [Dwarak](https://www.linkedin.com/in/dwarakgovindparthiban/), the co-founders of [s2.dev](http://s2.dev). S2 is the S3 for streams.\n\nhttps://www.youtube.com/watch?v=8-mUPf4P_8g\n\nMany of the most important features in products we love are powered by streaming data, from frontend UIs that go _brrr_ with real-time updates, to backends that store and process massive event flows. But building these sorts of real-time systems is really hard.\n\nWe are turning streams into a cloud storage primitive – just like object storage did for static files.\n\nS2 is a completely serverless datastore, offering unlimited streams and configurable (even bottomless) data retention. Streams can be appended to and followed in real-time, and since all writes are durable, you can also read from anywhere in a stream’s history, indexed by sequence number or timestamp.\n\nWe basically took the core abstraction of Kafka – [the log](https://engineering.linkedin.com/distributed-systems/log-what-every-software-engineer-should-know-about-real-time-datas-unifying) – gave it a URI, and brought it online with a dead simple API. And none of the bloat. 😀\n\nhttps://www.youtube.com/watch?v=2a1OdJ9l78A\n\n## Why we’re building S2\n\nWe built large-scale ML infra at Etsy and Meta, and always felt the lack of a system like S2. Serverless infra for data at rest has been seamless for a long time (S3 launched 20 years ago!) – but the ecosystem around streaming data, in comparison, felt stuck in the stone age.\n\n![uploaded image](/media/?type=post&id=95319&key=user_uploads/235940/72f8cb1e-a550-4458-b57b-d5936dc98191)\n\nWhen we [first introduced S2](https://news.ycombinator.com/item?id=42480105), we thought it would be most attractive to people already using streaming platforms like Kafka – but we’ve found that it resonates much more with builders in areas where these systems are entirely absent, who end up cobbling together general-purpose stores like Postgres and Redis and run into their limits.\n\nWe stand out on dimensions that are completely off the map for legacy systems: like the ability to have an unlimited number of streams backed by object storage, and to make them directly accessible [over REST](https://s2.dev/docs/rest/records/overview). This means S2 streams can be used as a serverless, reliable alternative to custom WebSocket or SSE infra.\n\n## S2 radically simplifies streaming\n\nIf you are dealing with a **high-cardinality of data sources** – for example, code execution sandboxes or IoT devices – S2 is for you. Streams can be instantly created on-demand. You don’t have to buffer or batch, just pipe into S2.\n\nhttps://www.youtube.com/watch?v=wsFiwxv_RY0\n\nWe recently [supercharged](https://news.ycombinator.com/item?id=45310294) read scalability to handle massive fanouts. You can broadcast a **real-time feed** with S2 such as market data without building any infra – publishing is just a matter of POST-ing to a stream’s URL.\n\nIf you are building **agents**, a common pain is **syncing** progress between the backend and frontend, while also being able to replay history. A lot of these agent state management challenges become simple with S2.\n\n## Try it out\n\nWe should talk if [s2.dev](http://s2.dev) resonates with you! You can [sign-up](https://s2.dev/sign-up) and follow the [quickstart](https://s2.dev/docs/quickstart) to start streaming in seconds with free credits.\n\nThere is a lot more we are cooking, including an ⭐ open source self-hostable S2 https://github.com/s2-streamstore/s2 ⭐\n\n## Talk to us\n\n**email**: [founders@s2.dev](mailto:founders@s2.dev)\n\n**discord**: https://discord.gg/JfTWJ5xxZ6\n\n**twitter**: https://x.com/s2_streamstore\n\n**bluesky**: https://bsky.app/profile/s2.dev\n\n![uploaded image](/media/?type=post&id=95319&key=user_uploads/89898/8c2da77e-e2c6-4bb6-bba6-9da0a09f87ef)\n\n",
        "url": "https://www.ycombinator.com/launches/OnP-s2-dev-streams-as-a-cloud-storage-primitive",
        "votes": 64,
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        "full_name": "Michael Sukkarieh",
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        "url": "https://www.ycombinator.com/companies/sourcebot/jobs/WVbwFeV-founding-engineer",
        "location": "San Francisco, CA, US",
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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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    "website": "https://specific.dev",
    "all_locations": "Stockholm, Stockholm County, Sweden",
    "long_description": "Specific lets your coding agent write code and build the infrastructure to deploy it. Connect your favorite coding agent and start building immediately. Run `specific dev` to get a full local environment running in seconds. Run `specific deploy` to go to production on our scalable cloud platform in minutes.",
    "one_liner": "The cloud platform built for coding agents",
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    "industry": "B2B",
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    "year_founded": 2025,
    "city": "Stockholm",
    "country": "SE",
    "linkedin_url": "https://www.linkedin.com/company/specific-dev",
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        "full_name": "Fabian Lindfors",
        "title": "Founder/CEO",
        "founder_bio": "Former tech lead at Stripe",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/fabian-lindfors",
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        "full_name": "Iman Radjavi",
        "title": "Founder/CTO",
        "founder_bio": "4+ years of experience building mission-critical backend systems. Most recently built and scaled energy grid systems that processed 1B+ data points daily. MSc in Computer Science.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/iman-radjavi/",
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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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        "full_name": "Jerry Zhang",
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        "id": 95219,
        "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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    "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",
    "launched_at": 1759962128,
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    "city": null,
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    "primary_partner": {
      "name": "Tom Blomfield",
      "url": "https://www.ycombinator.com/people/tom-blomfield"
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    "founders": [
      {
        "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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        "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,
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    "launches": [
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        "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": 31008,
    "name": "Moss",
    "slug": "moss",
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/631b5f054745e65be97bbf8459061215b1e4e693.png",
    "website": "https://moss.dev",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Moss is building the real-time semantic search runtime for conversational and multimodal AI. Our system enables voice agents, copilots, and chat interfaces to retrieve, reason, and respond in sub-10 ms, delivering the responsiveness that makes AI interactions feel truly natural.\r\n\r\nIf you’ve ever built a conversational or voice AI product, you’ve felt the lag. That moment when an agent pauses and the illusion of intelligence breaks. The bottleneck is almost always retrieval. Each query hops across networks and databases, adding delay and cost. Moss eliminates that gap by keeping retrieval close to where the agent runs.\r\n\r\nMoss runs natively across browsers, mobile devices, and servers with an optimized vector index built in Rust and WebAssembly. It enables teams to build AI products that feel instant, contextual, and adaptive. The experiences that sustain engagement and unlock new kinds of interaction. For our customers, this translates into tangible business value: stronger user retention, higher conversion, and entirely new product categories made possible by real-time understanding. Moss is already powering production pilots across voice AI and developer platforms, achieving sub-10 ms retrieval and 70–90% token savings compared to traditional pipelines.",
    "one_liner": "Real-time semantic search for Conversational AI",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1761590258,
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      "SaaS",
      "AI"
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    "regions": [
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      "America / Canada",
      "Remote",
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    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/moss.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/mossdev",
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      "url": "https://www.ycombinator.com/people/pete-koomen"
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        "full_name": "Sri Raghu Malireddi",
        "title": "Founder/CEO",
        "founder_bio": "Founder & CEO of Moss. We are developing real-time semantic search for conversational AI.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/r4ghu",
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        "id": 107565,
        "title": "Machine Learning Engineer",
        "url": "https://www.ycombinator.com/companies/moss/jobs/HmK9Iqk-machine-learning-engineer",
        "location": "San Francisco, CA, US / Remote",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Machine learning",
        "salary_range": "$60K - $300K",
        "equity_range": "0.10% - 0.50%",
        "experience": "6+ years",
        "visa": "Will sponsor",
        "skills": [
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          "Python",
          "Torch/PyTorch",
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          "Deep Learning",
          "Reinforcement learning (RL)",
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          "Vector Embeddings",
          "Vector Databases",
          "Fine-tuning",
          "Evals",
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          "Speech Recognition",
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    "launches": [
      {
        "id": 95036,
        "title": "Moss: Real-time Semantic Search for Conversational AI",
        "tagline": "We help conversational AI teams turn lagging, robotic interactions into natural, human-like experiences through sub-10 ms semantic search.",
        "body": "Hello YC! This is [**Sri Raghu Malireddi**](https://www.linkedin.com/in/r4ghu) from [**Moss**](https://usemoss.dev/).\n\n### **TL;DR**\n\nMoss is a high-performance runtime for real-time semantic search. It delivers sub-10 ms lookups, instant index updates, and zero infra overhead. Moss runs where your agent lives - cloud, in-browser, or on-device - so search feels native and users never wait. You connect your data once; Moss handles indexing, packaging, distribution and updates.\n\n![uploaded image](/media/?type=post&id=95036&key=user_uploads/2412081/c21db6f6-b453-40b6-a15d-5654971ab2ab)\n\n### **The Problem**\n\nIf you’ve ever built a conversational or voice AI product, you’ve felt it - that awkward pause when your agent lags or hesitates. The illusion of conversation breaks, and suddenly it feels less like talking to intelligence and more like waiting for a page to load.\n\nThe culprit is almost always retrieval. Every query hops across networks and cloud databases, adding seconds of delay. As usage scales, those small lags snowball into lost users, rising infra and egress costs. Teams spend weeks rebuilding embeddings and indexes, tuning search infra just to get “good enough” answers instead of focusing on what actually matters: building great AI experiences!\n\n### **Solution**\n\nMoss puts real-time semantic search in the same runtime as your agent and application, so you can -\n\n* **Keep retrieval close** - embed &amp; index right alongside your agents (docs, chat history, telemetry).\n* **Answer in &lt;10 ms** - local lookups, zero network hops.\n* **Manage at scale** - store, sync, and distribute indexes with our managed data layer at [**https://moss.dev**](https://usemoss.dev)\n* **Drop-in SDKs** - [**JavaScript**](https://www.npmjs.com/package/@moss-js/moss) and [**Python**](https://pypi.org/project/moss/).\n\n### **Our Story**\n\nMoss founding team knew each other for 8+ years and bring deep expertise in machine learning, high-performance computing and developer experience.\n\nSri was an ML Lead at Grammarly and Microsoft, where he shipped LLMs and personalization systems used by millions of users across Office, Bing, and Grammarly. His work on personalization drove 300% retention growth for Grammarly Keyboard and scaling models to 40M+ DAUs. He has published at top ML conferences such as ACL and holds multiple patents in real-time ML.\n\nThe idea for Moss came from our deep frustration with how slow “intelligent” systems actually felt in practice. While building large-scale agentic systems at Microsoft and Grammarly, we kept hitting the same wall - retrieval lag that made even the smartest models feel lifeless. Through evolution, humans are wired to expect instant replies; when AI hesitates, it breaks the illusion of intelligence. We started Moss to fix that by collapsing the multi-hop retrieval stack into a real-time, local-first runtime that lets AI think and respond at the speed of thought.\n\n<https://www.youtube.com/watch?v=7-PrunZVXTo>\n\n### **Who is it for?**\n\n* **Platform/Founding Eng:** Drop in realtime semantic search. No new service to run.\n* **Infra Leads:** Local retrieval to slash p95 and egress.\n* **Agent/Voice PMs:** Hit &lt;10 ms so conversations feel natural.\n* **Security/Compliance:** Keep sensitive context local (offline-ready).\n* **Data/ML Eng:** A/B embeddings &amp; index configs on your corpus - fast.\n\n### **How to onboard?**\n\n* Login to the portal - <https://moss.dev> \n* Start a new Project, create an index either through the portal or [JavaScript](https://www.npmjs.com/package/@moss-js/moss) and [Python](https://pypi.org/project/moss/) SDKs\n\n  ![uploaded image](/media/?type=post&id=95036&key=user_uploads/2412081/ecd79cf8-972e-4233-9987-e015ad49abd8)\n\n* Using our SDKs - **init**, **load** and **query** indexes in **sub-10ms**.\n\n  ![uploaded image](/media/?type=post&id=95036&key=user_uploads/2412081/60e783b7-d7d3-411a-91fd-05cbd678130a)\n\n\n### **Our Progress**\n\nWe’re seeing strong inbound pull from the market with 6 enterprise design partners and 3 paying customers actively building their products around Moss’s core tech, with 7 more actively evaluating. We’re working closely with Voice AI orchestration companies like Pipecat ([Daily.co](http://Daily.co)) and LiveKit, embedding Moss at the core of their real-time retrieval and context pipelines. Usage and revenue have been growing \\~100% week over week, and Moss is quickly becoming the foundational layer teams rely on to make AI feel instant, contextual, and truly responsive.\n\n### **Ask**\n\n* Building in Conversational AI and Voice AI?[ **Use Moss**](https://usemoss.dev) to bring real-time semantic search inside your agents to production\n* Developers -[ **Get free access**](https://form.typeform.com/to/XWeuMaar) to experiment with Moss and help shape the future of real-time conversational AI.\n\nOur contact information -\n\n* Email - [**founders@moss.dev**](mailto:founders@usemoss.dev)\n* Website - [**https:/moss.dev**](https://moss.dev)\n* Book a demo - [**Calendar Link**](https://cal.com/srimalireddi/30min)",
        "url": "https://www.ycombinator.com/launches/Oiq-moss-real-time-semantic-search-for-conversational-ai",
        "votes": 107,
        "created_at": "2025-10-30T19:54:21.747Z"
      }
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  },
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    "id": 31022,
    "name": "Coasts",
    "slug": "coasts",
    "former_names": [
      "JSX Tool"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/14423e406f790420f115f8958c1af6eb85b97201.png",
    "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,
    "tags": [
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      "Productivity",
      "Design",
      "Web Development"
    ],
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    "nonprofit": false,
    "batch": "Fall 2025",
    "status": "Inactive",
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      "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"
      }
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    "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,
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    "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",
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    "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"
      }
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    "id": 31047,
    "name": "Waddle Labs",
    "slug": "waddle-labs",
    "former_names": [
      "Waddle"
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    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f525546cff510b464f7877004fcc10c8f0b97843.png",
    "website": "https://www.waddlelabs.ai/",
    "all_locations": "San Francisco, CA, USA",
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    "one_liner": "LLMs that control robots",
    "team_size": 2,
    "industry": "Industrials",
    "subindustry": "Industrials -> Manufacturing and Robotics",
    "launched_at": 1784890498,
    "tags": [
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      "Generative AI",
      "Robotics",
      "Automation"
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    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Summer 2026",
    "status": "Active",
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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/waddle-labs",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/waddle-labs.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/waddlelabs/",
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    "primary_partner": {
      "name": "Ankit Gupta",
      "url": "https://www.ycombinator.com/people/ankit-gupta"
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    "founders": [
      {
        "user_id": 2132817,
        "full_name": "Hanming Ye",
        "title": "Founder",
        "founder_bio": "Interested in how natural intelligence arises. I also like machines such as 3D printers and robots. \n\nhttps://dozenducc.github.io/",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/hanming-ye-0467b01aa",
        "x_url": "https://x.com/DozenDucc",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5b813f423ca4b4732c54817689193d5602190bf5.jpg"
      },
      {
        "user_id": 1853600,
        "full_name": "Yiding Song",
        "title": "Founder",
        "founder_bio": "Interested in systems that learn theories about the world with human-like efficiency.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/yiding-song-vincent/",
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      {
        "id": 109947,
        "title": "Founding Research Engineer",
        "url": "https://www.ycombinator.com/companies/waddle-labs/jobs/RaRUAQK-founding-research-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Machine learning",
        "salary_range": "$175K - $350K",
        "equity_range": "1.00% - 2.00%",
        "experience": "Any (new grads ok)",
        "visa": "Will sponsor",
        "skills": [
          "ML",
          "Python",
          "Torch/PyTorch",
          "Distributed Systems",
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          "Evals",
          "AI Agents",
          "Diffusion Models"
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      {
        "id": 107821,
        "title": "Waddle Labs - Agents that control robots",
        "tagline": "Claude Code for robotics - prompt your robot to do physical tasks",
        "body": "Waddle is the Claude Code for robotics. Connect our API to your robot and type a prompt, then our agents write code to achieve the task in \\~20 minutes.\n\n![uploaded image](/media/?type=post&id=107821&key=user_uploads/2132817/afc74f28-33c6-450c-80c3-7f2d263f213d)\n\n### **Our Hypothesis**\n\nRobot intelligence today depends either on large end-to-end VLAs or classical approaches.\n\n\\- VLAs are difficult to customise and steer, require huge amounts of data to train, and don’t yet generalise across embodiments and environment. They face limited deployment.\n\n\\- Meanwhile, classical approaches are widely deployed for their reliability and explicit control, but are often brittle and costly to redevelop in new setups.\n\n_Does this tradeoff have to be inevitable?_\n\n**Our hypothesis:** By using agents to control robots, we combine the generalisation of VLAs with the speed and reliability of classical approaches. \n\n### **Our Solution**\n\nOur agents decomposes a goal into subtasks, and completes each subtask by viewing camera feeds, writing control code, and calling models like VLAs. The agent outputs a program that you can run and iterate on by talking to our agents. \n\n**Where we've been using Waddle internally:**\n\n\\- **Create a working policy in 20 minutes** (\"Write a program to package the box\")\n\n\\- **Generate data for model training** (\"Pick and place lego bricks at random positions 1000 times\")\n\n\\- **Facilitate robotics auto-research** (\"I am tuning a policy overnight. Reset the scene after each trial”)\\\n\\\nBecause our agents are LLMs, they inherit properties of the underlying models. Agents and the code they write are inherently generalist, so they work with any robot and any environment without additional data. Moreover, agents excel at long-horizon planning and can decompose a physical goal into subtasks, verify each stage, and re-plan on failure.\n\n**Interested in trying our agents via our preview API?** Sign up at \\[our website\\](<https://www.waddlelabs.ai/>) or email [founders@waddlelabs.ai](mailto:founders@waddlelabs.ai)\n\n### **Our Research**\n\nWaddle's agents enable new forms of scaling that we are very excited about:\n\n\\- **Scaling compositional generalization:** Our agent first wrote the “fold_grasp” skill while flipping a package; another agent later used it to fold a t-shirt. Over time, agents accumulate a library of skills, enabling future agents to compose them and achieve harder tasks.\n\n\\- **Scaling multi-robot cooperation:** Imagine an entire fleet of robots collaborating to achieve a task. For VLAs, this is a nightmare. For Waddle, simply hook up more agents. A master agent spawns subagents, coordinating multiple robots working concurrently.\n\n\\- **Scaling from scale:** We evaluated Opus 4.8, Fable 5, and GPT 5.6 Sol on a suite of manipulation tasks: larger models with larger thinking budgets consistently produce better policies. As foundation models improve, so do our robots.\n\n### **The Team**\n\nWe are @Yiding Song (Vincent) and @Hanming Ye. We met at MIT’s Research Science Institute, where Vincent was working on multimodal astrophysics models and Hanming was researching topology in the math department. Since then, we’ve become roommates at Harvard where we are either doing ML research or breaking robots - usually both.\n\nThere will be millions of robots in the future. Our mission is to enable everyone to take part in building them.",
        "url": "https://www.ycombinator.com/launches/S33-waddle-labs-agents-that-control-robots",
        "votes": 11,
        "created_at": "2026-07-27T17:45:25.918Z"
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    "id": 31082,
    "name": "Quotient Labs",
    "slug": "quotient-labs",
    "former_names": [
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    "website": "https://quotientlabs.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "You should only be paying frontier model prices for top-shelf reasoning. But 88% of your token bill is just tool I/O.\r\n Quotient Labs runs on top of Claude Code to reduce token spend, compress context, and optimize tool calls while preserving output quality. Same models, same workflow, no changes to how you work. Benchmarked 47% less cost on real, multi-step developer workflows, with no quality loss.",
    "one_liner": "Use Claude Code at 47% less cost in one line of installation.",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Productivity",
    "launched_at": 1772518250,
    "tags": [
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      "SaaS",
      "AI"
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2026",
    "status": "Active",
    "industries": [
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    "regions": [
      "United States of America",
      "America / Canada"
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/quotient-labs",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/quotient-labs.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/quotientlabs",
    "x_url": "https://x.com/syntropyio",
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    "primary_partner": {
      "name": "Ankit Gupta",
      "url": "https://www.ycombinator.com/people/ankit-gupta"
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    "founders": [
      {
        "user_id": 3146534,
        "full_name": "Saahil Sundaresan",
        "title": "Founder",
        "founder_bio": "Making coding agents cheaper @ Quotient Labs | Stanford CS & Linguistics | formerly at Apple, Amazon\n\nFeel free to reach out for anything! saahil@quotientlabs.com",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/saahil-sundaresan/",
        "x_url": "https://x.com/imsaahilsangye",
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      {
        "user_id": 3141216,
        "full_name": "Andrew Kuik",
        "title": "Founder",
        "founder_bio": "Making coding agents cheaper @ Quotient Labs. Stanford CS; previously at AWS, Accenture\n\nFeel free to reach out for anything!",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/andrew-kuik-109749238/",
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    "launches": [
      {
        "id": 114944,
        "title": "Quotient Labs: Stop overpaying Claude for tokens you don't need",
        "tagline": "We cut your Claude Code costs by 47% in one line of install. Same models, same workflow, half the price.",
        "body": "**TLDR**: **Tokenmaxxing is out. Tokenminning is in.** Quotient Labs sits on top of Claude Code and reduces the amount of context you pay for—without changing your models, prompts, projects, or workflow. Across real, multi-step developer workflows, we’ve benchmarked **47% lower token cost with no measured quality loss.** Get started today at <https://www.quotientlabs.com/>.\n\n**The Problem**\n\nCoding agents accumulate a lot of context.\n\nEvery file read, search result, test run, tool output, generated plan, and conversation turn gets added to the session. As the session grows, this history is repeatedly re-read (and re-billed) long after it has stopped being useful in its original form. The result? **You’re overpaying Claude for tokens your agent never needed.**\n\n**Fermat’s Last Token** (our main product) sits on top of Claude Code and optimizes what enters and remains in your model’s context. We do this in four ways:\n\n1. **Faster, more cost-efficient agent tools** that batch operations and return compact, information-dense results.\n2. **Bash output compression** that preserves the useless parts of long command and test outputs while removing the bloat.\n3. **Live text compression** that removes the information-sparse and irrelevant tokens in conversation turns before they ever compound in cost. \n4. **Idle context optimization** that compresses older conversation history as the prompt cache expires (this is more often than you think; only 5 minutes TTL) while preserving the freshest context verbatim.\n\nThe important part: **you keep using Claude Code exactly as you do today.**\n\n**Observability**: See real-time estimated cost and savings down to the session and request level, as well as manage your organizations and users, in the user dashboard: <https://console.quotientlabs.com/>. \n\n**Ready to go in 30 seconds.** Install Fermat, sign in, and continue using Claude Code normally:\n\n**curl -fsSL [https://downloads.quotientlabs.com/fermat/install.sh](https://downloads.quotientlabs.com/fermat/install.sh) | bash &amp;&amp; fermat login**\n\n**Fermat is compatible with both CLI and the VS Code extension.** Your existing projects, prompts, models, integrations, and interface are untouched.\n\nYou can bypass Fermat (if you really want) on a particular chat any time with _claude --vanilla._ You can also fully uninstall in one line with _fermat uninstall_ (though we don’t recommend either :)).\n\n**Our ask**\n\nWe’re looking for devs and engineering teams who use Claude Code heavily, especially on long-running, tool-intensive engineering tasks. \n\nWe’d love to get feedback on where Fermat helps the most, where compression could be better, and any features or changes you’d like to see.\n\nGet started: <https://quotientlabs.com/>\n\nOr message us directly: [founders@quotientlabs.com](mailto:founders@quotientlabs.com)\n\n**Founders**\n\nBefore Quotient Labs, we’ve been at Stanford (BS+MS CS/AI), industry (Apple, AWS, Accenture) and in academia (with multiple publications).\n\n![uploaded image](/media/?type=post&id=114944&key=user_uploads/3146534/39cb7ad4-595a-428f-aa75-7a0570a93673)\n\n",
        "url": "https://www.ycombinator.com/launches/Ttw-quotient-labs-stop-overpaying-claude-for-tokens-you-don-t-need",
        "votes": 9,
        "created_at": "2026-09-14T15:33:54.262Z"
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    "id": 31088,
    "name": "RunAnywhere",
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "RunAnywhere runs open-weight models at full speed wherever a company needs them. Wally is our inference stack for open models: serverless inference, BYOC, or on-prem, so code and data never leave their network. One command puts a Wally-served model inside Claude Code, DeepSeek Harness, OpenCode, Hermes, OpenClaw, etc. When a model fits on the device, the same tooling runs it locally through our open-source SDKs for iOS, Android, macOS, Windows, Linux, and web, built on kernels written by our agentic harness for Apple and Qualcomm silicon (10K+ GitHub stars).",
    "one_liner": "Fastest inference anywhere: open models on-prem, hosted or on-device",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1767296079,
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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/runanywhere",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/runanywhere.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/runanywhere/",
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    "primary_partner": {
      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
    },
    "founders": [
      {
        "user_id": 725397,
        "full_name": "Sanchit Monga",
        "title": "Founder/CEO",
        "founder_bio": "Former Intuit engineer building RunAnywhere, the infrastructure layer for deploying fast, private, multimodal AI on-device at scale.\n\nDeep background in mobile SDKs, platform tooling, and developer products, including systems used by 50M+ active users. Previously founded products across consumer discovery, context management, agentic documentation, and mobile testing, and now focused on making on-device AI production-ready across mobile, edge, and embedded devices.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/sanchitmonga22/",
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      },
      {
        "user_id": 2862507,
        "full_name": "Shubham Malhotra",
        "title": "Founder/CTO",
        "founder_bio": "Co-founder & CTO of RunAnywhere (W26). Built MetalRT: the first complete multi-modal inference engine for Apple Silicon. Custom Metal GPU kernels that pushed on-device voice AI from 900ms to ~110ms. Ex-Amazon EC2 Spot ($100M+ ARR), Ex-Microsoft Azure. Peer-reviewed researcher.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/shubham-malhotra-fg890a23a/",
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    "jobs": [
      {
        "id": 98717,
        "title": "Developer Relations & Technical Content Intern",
        "url": "https://www.ycombinator.com/companies/runanywhere/jobs/ZJD016N-developer-relations-technical-content-intern",
        "location": "Remote",
        "type": "Internship",
        "role": "Marketing",
        "role_type": null,
        "salary_range": "$750 - $1.5K / monthly",
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        "title": "MetalRT brings the first unified AI inference engine to Apple Silicon",
        "url": "https://www.msn.com/en-us/news/other/metalrt-brings-the-first-unified-ai-inference-engine-to-apple-silicon/ar-AA1YLTt1",
        "date": "Mar 17, 2026"
      },
      {
        "title": "RunAnywhere Is Building the Infrastructure Layer for On-Device AI at Scale ",
        "url": "https://techbullion.com/runanywhere-is-building-the-infrastructure-layer-for-on-device-ai-at-scale/",
        "date": "Mar 09, 2026"
      },
      {
        "title": "Regulated Industries Are Rewriting Their AI Architecture",
        "url": "https://nexttechtoday.com/tech/ai/regulated-industries-are-rewriting-their-ai-architecture/",
        "date": "Mar 09, 2026"
      },
      {
        "title": "From Cloud Dependence to Instant AI: The Rise of On-Device Voice Agents - New York Weekly",
        "url": "https://nyweekly.com/tech/from-cloud-dependence-to-instant-ai-the-rise-of-on-device-voice-agents/",
        "date": "Mar 09, 2026"
      },
      {
        "title": "Why the Next Wave of AI Will Run on Your Phone - CEOWORLD magazine",
        "url": "https://ceoworld.biz/2026/03/06/why-the-next-wave-of-ai-will-run-on-your-phone/",
        "date": "Mar 06, 2026"
      }
    ],
    "launches": [
      {
        "id": 117440,
        "title": "Wally by RunAnywhere: The fastest inference for open frontier models",
        "tagline": "Open-weight frontier models at real-time speed for voice and agent products, live on day one. Serverless, BYOC or on-prem.",
        "body": "Hi, we're Sanchit and Shubham, co-founders of RunAnywhere (W26), and we're launching Wally: our inference stack for open frontier models, hosted on our GPUs or deployed on yours.\n\n<https://youtu.be/m_T2Diow3_M>\n\n**TL;DR:** Wally serves GLM-5.3 Flash at 380 tokens per second with a 274 ms first token, faster than any endpoint on Artificial Analysis (Sep 28, 2026). New models land on day zero: Xiaomi's MiMo-V2.6-Pro was ready to serve about 8 hours after its weights dropped, and runs at 3x the speed of Xiaomi's own API (Artificial Analysis, Sep 21, 2026). The same stack deploys on-prem/BYOC at the same speed. [Sign up](https://runwally.com) and get $5 in free credits.\n\n## The problem\n\nFrontier models are slow and expensive, and you feel it most in products that run a model in a loop. A voice agent has a few hundred milliseconds before a turn feels broken. A coding agent waits for the first token on every tool call, dozens of times per task.\n\n## How Wally works\n\nWally is our inference stack for open frontier models: our own kernels, speculative decoding, and prefill kept off the decode path so a long prompt never stalls someone else's stream. We tune it per model and per traffic pattern. It runs in two places.\n\n**Hosted by us.** An OpenAI-compatible endpoint on our own GPUs, so anything that takes a base URL and a key works unchanged. Standard per-token pricing. Live today:\n\n* **GLM-5.3 Flash:** 380 tok/s\n* **DeepSeek V4.1 Flash:** 615 tok/s\n* **Qwen3.8-27B:** 485 tok/s\n* **MiMo-V2.6-Pro:** 320 tok/s\n* **GLM-5.3 Max:** 790 tok/s\n\n**Deployed for you.** The same stack on GPUs you own, in your cloud account, or on a dedicated instance we run. Same speed, your own models and fine-tunes, your traffic stays in your environment, and at token-heavy volumes it costs less than paying per token.\n\n## New models on day zero\n\nMiMo-V2.6-Pro, the top open-weights model on Artificial Analysis (Sep 21, 2026), was ready and running 3x faster than anyone else in 8 hours after Xiaomi published the weights.\n\n## The numbers\n\nArtificial Analysis lists 19 providers serving the same GLM-5.3 Flash weights (Sep 24, 2026), and Wally is 8.6x faster than Z.ai. Same model; the only difference is how it's served. Ours: 380 tok/s and a 274 ms first token, measured the same way.\n\n![uploaded image](/media/?type=post&id=117440&key=user_uploads/725397/e68127c0-8f31-4fe8-bbe2-44f587f09e67)\n\n## Beyond the benchmark\n\nBenchmarks don't always match reality, so we ran a real prompt on four providers, three times: GLM-5.3 Flash in the same OpenCode harness on Wally, Nebius, Fireworks and Z.ai, all building a game at once.\n\n<https://youtu.be/yc-KVBwuWC0>\n\n![uploaded image](/media/?type=post&id=117440&key=user_uploads/725397/eaf90b9c-3be5-405a-9177-cca618fe81ea)\n\nThe same model reasons more or less on the same prompt from run to run, on every provider, so finish times look close even when the work isn't. Tokens per second of wall clock is the stable number: Wally 213, Nebius 149, Fireworks 68, Z.ai 47, averaged across the runs.\n\n## Get started\n\nPaste this into your coding agent:\n\n```\nset up https://runanywhere.ai/SKILL.md\n```\n\nWorks with Claude Code, Claude Desktop and OpenCode. $5 free on signup, no card. Standard per-token pricing after that.\n\n## Why we built it\n\nWe spent nine months making open models fast on phones and laptops, with our own inference engines for Apple and Qualcomm chips ([runanywhere-sdks](https://github.com/RunanywhereAI/runanywhere-sdks?utm_source=launchyc&utm_medium=post&utm_campaign=wally-launch), 10K+ GitHub stars). Our users kept needing models too big for the device, and nobody served open frontier models fast enough for a real-time loop. None of our work was specific to phones, so we pointed it at data-center GPUs.\n\n## Our ask\n\n* **If you run a voice or agent product and latency or the inference bill hurts,** email [founders@runanywhere.ai](mailto:founders@runanywhere.ai) and we'll make it faster.\n* **If a customer has asked you for on-prem,** intro us. We deploy on their GPUs.\n* **Try it** and tell us what broke: [runwally.com](https://www.runwally.com/)\n\n[Docs](https://docs.runanywhere.ai/?utm_source=launchyc&utm_medium=post&utm_campaign=wally-launch) · [X @RunAnywhereAI](https://x.com/RunAnywhereAI)",
        "url": "https://www.ycombinator.com/launches/UYC-wally-by-runanywhere-the-fastest-inference-for-open-frontier-models",
        "votes": 12,
        "created_at": "2026-09-29T18:59:15.687Z"
      },
      {
        "id": 97041,
        "title": "RunAnywhere: The default way to run On-Device AI at scale",
        "tagline": "One SDK + Control Plane to Deploy, Route, Update, and Observe On-Device AI – Offline-First, Hybrid-Smart, Fleet-Managed",
        "body": "We're [Sanchit](https://www.linkedin.com/in/sanchitmonga22/) and [Shubham](https://www.linkedin.com/in/shubham-malhotra-fg890a23a/), co-founders of [RunAnywhere](https://runanywhere.ai/) (W26).\n\n**TL;DR:** Run Multi-modal AI fully on-device with one SDK and manage model rollouts + policies from a control plane.\n\nWe are already live and open source with [**\\~10.1k stars on GitHub**](https://github.com/RunanywhereAI/runanywhere-sdks).\n\n<https://youtu.be/N3x2bs4ri68>\n\n![uploaded image](/media/?type=post&id=97041&key=user_uploads/725397/86d47939-7caf-4e0f-8575-045ca2fd22bc)\n\n### The Problem\n\nEdge AI is inevitable — users want instant responses, full privacy (health, finance, personal data), and AI that actually works on planes, subways, or spotty rural connections.\n\nBut shipping it today is brutal:\n\n* Every device (iPhone 14 vs Android flagship vs low-end) has wildly different memory, thermal limits, and accelerators.\n* Teams waste quarters rebuilding model download/resume/unzip/versioning, lifecycle (load/unload without crashing), multi-engine wrappers (llama.cpp, ONNX, etc.), and cross-platform bindings\n* No real observability — you're blind to fallback rates, per-device perf, crashes tied to model version\n\n**Result:** most teams either give up on local AI or ship a brittle, hacked-together experience.\n\n### The Solution: Complete AI Infrastructure\n\nRunAnywhere isn't just a wrapper around a model. It is a full-stack infrastructure layer for on-device intelligence.\n\n**1. The \"Boring\" Stuff is Built-in** We provide a unified API that handles model delivery (downloading with resume support), extraction, and storage management. You don't need to build a file server client inside your app.\n\n**2. Multi-Engine & Cross-Platform** We abstract away the inference backend. Whether it's llama.cpp or ONNX etc, you use one standard SDK.\n\n* iOS (Swift)\n* Android (Kotlin)\n* React Native\n* Flutter\n\n**3. Hybrid Routing (The Control Plane)** We believe the future isn't \"Local Only\"—it's **Hybrid**. RunAnywhere allows you to define policies: try to run the request locally for zero latency/privacy; if the device is too hot, too old, or the confidence is low, automatically route the request to the cloud.\n\n![Voice AI Pipeline Demo](/media/?type=post&id=97041&key=user_uploads/725397/dfe1b180-e5d8-4c59-a4e8-2109d9f903f2)\n\n### Quick Links\n\n* **OSS SDKs:** [github.com/RunanywhereAI/runanywhere-sdks](https://github.com/RunanywhereAI/runanywhere-sdks) (star if it vibes!)\n* **Full Docs:** [docs.runanywhere.ai](https://docs.runanywhere.ai)\n* **Website:** [runanywhere.ai](https://runanywhere.ai)\n\n**Try our demo apps:**\n\n* [Android](https://play.google.com/store/apps/details?id=com.runanywhere.runanywhereai)\n* [iOS](https://apps.apple.com/us/app/runanywhere/id6756506307)\n\n### Our Ask\n\nWe're in full execution mode post-launch and hunting design partners + early feedback:\n\n* Building voice AI, offline agents, privacy-sensitive features (health/enterprise/consumer), or hybrid chat in your mobile/edge app?\n* Want to eliminate cloud inference costs for repetitive queries while keeping complex ones fast?\n* Have a fleet where OTA model updates + observability would save you engineering months?\n\n**Get in touch:**\n\n* Drop us a line: [san@runanywhere.ai](mailto:sanchit@runanywhere.ai)\n* Book a quick call: [calendly.com/sanchitmonga22](https://calendly.com/sanchitmonga22)\n* Or just tell us what sucks about your current on-device AI stack — honest war stories help us prioritize.\n\nExcited to hear what you're building and how we can make on-device AI actually shippable at scale.",
        "url": "https://www.ycombinator.com/launches/PFB-runanywhere-the-default-way-to-run-on-device-ai-at-scale",
        "votes": 25,
        "created_at": "2026-01-22T01:27:45.855Z"
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    "one_liner": "/dev/fast is the AI-native code forge",
    "team_size": 4,
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    "launched_at": 1771920641,
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        "full_name": "Sid Menon",
        "title": "Founder/CEO",
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        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/ketan-jay-agrawal/",
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        "title": "/dev/fast: Cursor for Code Review",
        "tagline": "Review is an open-source desktop app built for humans to understand AI-generated code. Critique interactive visualizations, diffs, and agent traces, all from one interface.",
        "body": "**TL;DR:** _Review is an open-source desktop app designed to give you confidence in your code. Critique interactive visualizations, diffs, and agent traces, all from one interface. It’s like Cursor, but purpose-built for code review._\n\n**Our Ask:** Try our app on your toughest code reviews; it is most illuminating for large, complicated changes. [Download the app](https://install.dev.fast/), [star the repo](https://github.com/devdotfast/review), &amp; ask your questions on our [Discord](https://discord.gg/dev-fast)!\n\n**Demo Video:** <https://youtu.be/mDgxhzrFi2Y>\n\n**The Problem:**\n\nNo one knows how much code we should be reading these days.\n\nIt feels tedious and old-fashioned to manually comb through thousands of lines of changes, and yet irresponsible to merge code you can’t confidently describe.\n\nWe’ve lost touch with how our own systems work.\n\nBuilding a company is a long game. Development is an iterative process. It takes accountability and code comprehension at every stage to build a great product that customers can count on ([ex 1](https://www.geoffreylitt.com/2026/07/02/understanding-is-the-new-bottleneck), [ex 2](https://margaretstorey.com/blog/2026/02/09/cognitive-debt/)).\n\n**Our Solution:**\n\nBefore AI, staff engineers understood massive software systems even when they didn’t have time to read all contributed code. They prioritized without sacrificing complexity by:\n\n\\- Scrutinizing RFCs and architecture diagrams\n\n\\- Skipping low-impact PRs\n\nReview treats you like a staff engineer. You can think of it as a ‘Cursor for code review.’ It helps you build programmatic, customizable RFCs from your PRs using coding agents.\n\nInstead of reviewing 1000+ line diffs you:\n\n1\\. Consult a variety of interactive diagrams built on our SDK:\n\n![uploaded image](/media/?type=post&id=112248&key=user_uploads/2724635/4db58f4d-cdcc-4825-966d-c92ffcfedeba)\n\n2\\. Chat with the authoring agent to leave comments on the change:\n\n![uploaded image](/media/?type=post&id=112248&key=user_uploads/2724635/5849e89e-3eb0-494d-a921-985402d16252)\n\n3\\. Audit the agent’s decisions by connecting traces to code:\n\n![uploaded image](/media/?type=post&id=112248&key=user_uploads/2724635/d0b141ce-fcb3-4392-b59f-6d16e4f10f1a)\n\n—\n\n**Team:**\n\n![uploaded image](/media/?type=post&id=112248&key=user_uploads/2724635/42caf723-b7dc-4ca1-a848-9bbce13cd39e)\n\n**Sid (CEO)** was a tech lead on Palantir’s cloud infrastructure team, where he built secure hybrid cloud deployment infrastructure. He studied CS at Harvard.\n\n**Milan (CTO)** was a cofounder of Bolto (YC S23) and previously worked on Palantir's ML infrastructure team, where he built tools for in-platform model deployment and evaluation. He studied CS at Harvard.\n\n**Ketan (CSO)** has worked as a machine learning engineer at Robust Intelligence where he red-teamed AI systems to make them fail, and at Snowflake where he built data-querying agents. He studied CS at Stanford.\n\n**Alex (CPO)** worked as a software engineer at Pinterest and at Flowcode where he led an effort to rearchitect the product for large enterprises. He studied CS at Harvard.\n\n—\n\n**We’re going all in on open-source. Our dream is to be the open-source code forge for the AI era.**\n\n**Install the app here:** <https://install.dev.fast>\n\nHave questions, comments, or interested in a design partnership for our hosted product? We’d love to hear from you!",
        "url": "https://www.ycombinator.com/launches/TCS-dev-fast-cursor-for-code-review",
        "votes": 4,
        "created_at": "2026-08-25T23:51:47.650Z"
      },
      {
        "id": 98162,
        "title": "Carson: More secure than OpenClaw, More capable than Cowork",
        "tagline": "An AI agent with enterprise-grade security that generates custom, task-specific interfaces.",
        "body": "**TL;DR:** AI agents are trapped in chat bubbles. Carson breaks free by generating dynamic interfaces like research dashboards or slide editors, customized to your current task. Carson is built for problem solvers pushing the bounds of AI in sales, marketing, and ops, with enterprise-grade security baked in.\n\n**Our ask:** Sign up to use Carson today at [usecarson.com](http://usecarson.com), it's free for your first 7 days.\n\n**Demo Video:** <https://www.youtube.com/watch?v=23sZGNMz3PU>\n\n### The Problem:\n\nAI tools today force you to choose between power and safety:\n\n**1) Openclaw is powerful but insecure** ([example](https://x.com/summeryue0/status/2025774069124399363))**:**\n\n![uploaded image](/media/?type=post&id=98162&key=user_uploads/2724635/b2f3f2f6-a15c-437b-840a-e8e2f075c2d4)\n\n**2) Claude Cowork is too limited:** Cowork is useful, but it could do much more. For example, if you use Cowork to source candidates, you need to bounce between LinkedIn, email, and the desktop app. Its permissions system is also clunky: you either approve every single action manually or skip permissions entirely with YOLO mode.\n\nOn some level security & autonomy are fundamental tradeoffs, but better tools should exist.\n\n### The Solution:\n\nCarson’s UI is generative, which means it changes to suit your use-case. Let’s walk through a common workflow as an example: **sales.**\n\n**Phase 1: Outbound**: Below, I first use Carson to research leads. It realizes that I want structured data, so it fills an editable spreadsheet with deep research. \n\nOnce that’s ready, I ask it to help me draft emails. Instead of switching between my LinkedIn, research, and my email, Carson generates a unified email workspace with all three in one pane.\n\n![uploaded image](/media/?type=post&id=98162&key=user_uploads/2724635/4d5a7add-b0dd-4189-be0c-2f296cc24915)\n\n**Phase 2: First Meeting Prep (“Vibe Sliding”):** when the emails turn into meeting invites, I can use Carson to generate a customized slide deck based on the response & deep research (complete with branding)! I can also “vibe slide” and make edits to the slides using natural language.\n\n![uploaded image](/media/?type=post&id=98162&key=user_uploads/2724635/c69368ec-fa33-4746-a005-ef640ff400d7)\n\n**Phase 3: Automations:** Carson can create and run automations in natural language. In this case, I ask Carson to send slides to me on Slack every time a new intro meeting comes up:\n\n![uploaded image](/media/?type=post&id=98162&key=user_uploads/2724635/7ec59f08-0a16-4bb4-aefd-e686923d5a21)\n\n### \n\n**Security Infrastructure**\n\n**TL;DR: You can actually install Carson at work.**\n\nWe weren’t happy at all with the primitives out there on agentic security. The compromises range from the uncomfortable (granting broad access to your entire email & calendar) to deeply concerning (giving an agent secret keys and telling it “\\_hey make no mistakes\\_”).\n\nInstead, Carson is built around a fine-grained authorization system. You can tell the agent “\\_it’s ok to send emails to these addresses, but ask me before interacting with those other ones\\_”, and it’s enforced at the runtime level – the agent literally cannot send emails to unintended recipients.\n\n### **Our Asks:**\n\nIf you’ve felt that Claude Cowork could be more capable or felt scared to try OpenClaw at work, Carson is right for you.\n\nContact us at +1-614-984-8423 or at [sid@usecarson.com](mailto:sid@usecarson.com). We’ll come over and install Carson for you (if you ask nicely, there may be a bag of sumo oranges provided, too).\n\n**The Team**\n\nAlex, Sid, and Milan met doing college projects together at Harvard, and Sid and Ketan go way back (to elementary school).\n\n![uploaded image](/media/?type=post&id=98162&key=user_uploads/2724635/275c90fc-a5a9-4199-a657-221b81dee677)\n\n**Sid (CEO)** was a tech lead on Palantir’s cloud infrastructure team, where he built secure deployment infrastructure for untrusted workloads. He studied CS at Harvard.\n\n**Milan (CTO)** was a cofounder of Bolto (YC S23) and previously worked on Palantir's ML infrastructure team, where he built tools for in-platform model deployment and evaluation. He studied CS at Harvard.\n\n**Ketan (CSO)** has worked as a machine learning engineer at Robust Intelligence where he red-teamed AI systems to make them fail, and at Snowflake where he built data-querying agents. He studied CS at Stanford.\n\n**Alex (CPO)** worked as a software engineer at Pinterest and at Flowcode where he led an effort to rearchitect the product for large enterprises. He studied CS at Harvard.",
        "url": "https://www.ycombinator.com/launches/PXG-carson-more-secure-than-openclaw-more-capable-than-cowork",
        "votes": 57,
        "created_at": "2026-02-26T01:04:36.863Z"
      }
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  },
  {
    "id": 31133,
    "name": "Skillsync",
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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": [
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2026",
    "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,
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    "url": "https://www.ycombinator.com/companies/skillsync",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/skillsync.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/skillsync-wiki/",
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    "primary_partner": {
      "name": "Tyler Bosmeny",
      "url": "https://www.ycombinator.com/people/tyler-bosmeny"
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      {
        "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"
      }
    ]
  },
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    "id": 31147,
    "name": "Salus",
    "slug": "salus",
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    "website": "https://www.usesalus.ai/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Your agent processed a refund without looking up the order ID, costing you thousands. You only found out three hours later from a support ticket. Evals, output scoring, and observability can reduce the likelihood of mistakes like these occurring - but there's no solution that inspects and prevents an action as it’s about to execute. Salus does that.\r\n\r\nWe’ve built an API that wraps around your agent and checks its actions at run time, blocking incorrect ones and providing immediate feedback to guide retries. ",
    "one_liner": "Guardrails to validate your agent's actions before they execute",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1770354850,
    "tags": [
      "Developer Tools",
      "B2B",
      "API",
      "Infrastructure",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Winter 2026",
    "status": "Active",
    "industries": [
      "B2B",
      "Infrastructure"
    ],
    "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/salus",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/salus.json",
    "year_founded": 2026,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/salus-dev/",
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    "primary_partner": {
      "name": "Ankit Gupta",
      "url": "https://www.ycombinator.com/people/ankit-gupta"
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    "founders": [
      {
        "user_id": 2134297,
        "full_name": "Vedant Singh",
        "title": "Founder/CTO",
        "founder_bio": "Building to validate your AI agent's actions before they execute\n\nAI researcher and formerly @Stanford CS",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/thevedantsingh/",
        "x_url": "https://x.com/thevedants1",
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    "jobs": [
      {
        "id": 95662,
        "title": "Founding GTM / BDR — AI Agent Infrastructure",
        "url": "https://www.ycombinator.com/companies/salus/jobs/S2nl2Hx-founding-gtm-bdr-ai-agent-infrastructure",
        "location": "San Francisco, CA, US / Remote (San Francisco, CA, US)",
        "type": "Contract",
        "role": "Sales",
        "role_type": null,
        "salary_range": "$35 - $45 / hourly",
        "equity_range": "",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
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        "id": 110168,
        "title": "Founding SWE / MLE",
        "url": "https://www.ycombinator.com/companies/salus/jobs/6xN06s6-founding-swe-mle",
        "location": "San Francisco, CA, US / New York, NY, US / Remote (US)",
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        "role": "Engineering",
        "role_type": "Machine learning",
        "salary_range": "$250K - $500K",
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      {
        "id": 97574,
        "title": "Salus - Runtime guardrails that validate AI agent actions before they execute",
        "tagline": "Salus checks your agent's actions, blocking incorrect ones and providing feedback to guide retries",
        "body": "### **TL;DR:**\n\n**Salus is an API that wraps around your agent and checks its actions at runtime, blocking incorrect ones and providing immediate feedback to guide retries.**\n\nWe’re Kevin and Vedant, former roommates at Stanford who studied CS, now building Salus full-time.\n\n### 😔**The problem:** \n\nYour agent processed a refund without looking up the order, costing you thousands. It emailed your top lead using hallucinated data, ruining the deal. You only found out three hours later from a support ticket or an angry email.\n\nEvals, output scoring, and observability are all necessary—but all reactive. They can reduce the likelihood of these problems occurring, but there's no solution that inspects an action as it’s about to execute. Salus does that.\n\n**Ask:** If you are deploying agents and want to improve their correctness we’d love to help. Book a demo [here](https://calendly.com/d/cycy-fbc-fyj/salus-demo), and we can onboard you immediately with just a pip install and a few lines of code.\n\n### 💻 **Our Solution:** \n\n<https://youtu.be/uyl5NJTY5Cg>\n\n**How Salus validates an action:**\n\n1. Actions must be **grounded in evidence**: Salus maintains an evidence cache for each run that every proposed action is validated against. Evidence includes all outputs from prior tool calls and the entire conversation history.\n2. It must **adhere to policy**: Write constraints in YAML, markdown, or plain English. Salus compiles them into runtime checks that are version-controlled, diffable, and shadow-testable\n3. And **more**: PII detection, budget/loop protection, idempotency, human-in-the-loop escalation, content moderation\n\n**Self-repairing:** When Salus blocks an action, the agent receives structured feedback to guide a retry. In our benchmarks, **58%** of blocked actions recover and complete the task correctly.\n\n### 📊 **Benchmarks:** \n\nWe tested Salus on τ²-bench and ODCV-Bench. On τ²-bench, agents with Salus follow policies more reliably, at up to **60% lower cost**. On ODCV-Bench, Salus **reduced misalignment by 52%** on average across 12 frontier models (see below).\n\n![uploaded image](/media/?type=post&id=97574&key=user_uploads/1940292/e48b27f6-2e13-4d40-a9a4-13135ff981bc)\n\n### ➕ **Other Features:** \n\nWhile we believe the missing piece is runtime validation, we know **evals and observability** are crucial. That’s why we incorporate all three in **one centralized product**. Using templates and LLMs, we generate thousands of both adversarial and realistic evals that have full context of your agent’s domain.\n\nContact us: [founders@usesalus.ai](https://founders@usesalus.ai)\n\n![uploaded image](/media/?type=post&id=97574&key=user_uploads/1940292/cc3d0be7-941f-46ef-be8f-1294b9148073)\n\n",
        "url": "https://www.ycombinator.com/launches/PNm-salus-runtime-guardrails-that-validate-ai-agent-actions-before-they-execute",
        "votes": 30,
        "created_at": "2026-02-06T11:20:42.138Z"
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  },
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    "id": 31165,
    "name": "IncidentFox",
    "slug": "brownie",
    "former_names": [
      "Brownie"
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    "website": "https://incidentfox.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "AI SRE agents that automatically learn each customer’s system so they work just like an in-house engineer.",
    "one_liner": "AI SRE agent that triages, coordinates, and fixes production incidents",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1771353224,
    "tags": [
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      "Developer Tools",
      "AI"
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    "top_company": false,
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    "nonprofit": false,
    "batch": "Winter 2026",
    "status": "Active",
    "industries": [
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      "Infrastructure"
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    "regions": [
      "United States of America",
      "America / Canada"
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/brownie",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/brownie.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/incidentfox/",
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    "primary_partner": {
      "name": "Diana Hu",
      "url": "https://www.ycombinator.com/people/diana-hu"
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    "founders": [
      {
        "user_id": 1146198,
        "full_name": "Jimmy Wei",
        "title": "Founder/CEO",
        "founder_bio": " Chiehmin (Jimmy) Wei is a co-founder of IncidentFox. Before IncidentFox, Jimmy was a software engineer at Roblox, where he architected a real-time communication feature reaching 11.7M+ users, and at Facebook AI Research (FAIR), where he built conversational AI infrastructure and set new research baselines with Transformer models. He holds an M.S. from Cornell University and a B.S. in Computer Science from Bucknell University.",
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      {
        "user_id": 2091321,
        "full_name": "Long Yi",
        "title": "Founder/CTO",
        "founder_bio": "Long Yi is the co-founder of IncidentFox, an AI-powered SRE platform for automated incident investigation and infrastructure management.\nPreviously, he built large-scale distributed systems at Roblox, managing database and search infrastructure handling over 1.5 million queries per second. \nHe holds a B.S. from Brandeis University, where he conducted research in audiovisual signal processing and neural modeling.",
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    "launches": [
      {
        "id": 97928,
        "title": "IncidentFox. The AI SRE who never drops context.",
        "tagline": "Auto-learns your stack, builds its own integrations, and gets smarter after every incident.",
        "body": "Hey everyone 👋\n\nWe're [Long](https://www.linkedin.com/in/long-yi-b221b2183/) and [Jimmy](https://www.linkedin.com/in/chiehmin-wei/) — co-founders of IncidentFox.\n\n**TL;DR**\n\nAI SRE tools fail without deep context about _your_ systems — and that context lives in integrations nobody has time to build. IncidentFox auto-discovers what each team needs, generates the integrations, and ships with 300+ tools built in. Setup takes less than a day, not months.\n\n👉 Try it: <https://incidentfox.ai>\n\n👉 Open source (Apache 2.0): <https://github.com/incidentfox/incidentfox>\n\n👉 Launch video: <https://youtu.be/TaTpN0JwNYE>\n\n**❌ The Problem: Without the right integrations, your AI has no context**\n\nEvery AI SRE tool connects to Slack, reads your Confluence, queries your Datadog. That part is solved.\n\nHere's what isn't: when the AI actually needs to debug something, it doesn't have the right tools.\n\nYour payments team runs a custom Kafka pipeline with internal dashboards. Your infra team uses a homegrown deployment system. Your ML team has proprietary model serving. Each team's stack is different — and the AI has no way to query any of it.\n\nThe traditional fix? Hand-build integrations (MCP servers) for every team.\n\nBut this creates a new problem:\n\n* Who decides what integrations each team needs? You might know your own team's stack — but when you're debugging another team's service at 3 AM, you don't know theirs.\n* So every team needs to sacrifice an engineer to build and maintain their own integrations. That's expensive, slow, and doesn't scale.\n* Most teams never get around to it. The AI stays half-useful.\n\n**Integration is the bottleneck.** Not the AI model. Not the monitoring data. The integrations.\n\n**🦊 IncidentFox: We auto-build the integrations for you**\n\nIncidentFox is an AI SRE that lives where your team already works — Slack, Microsoft Teams, or Google Chat. It doesn't just connect to your existing tools — it figures out what tools each team needs and builds them automatically.\n\n![uploaded image](/media/?type=post&id=97928&key=user_uploads/1146198/102ebfb0-a3c9-45c5-b993-89e39b94e13b)\n\n**1. Auto-discovers and generates integrations**\n\nIncidentFox analyzes your codebase, infrastructure, and incident history to identify gaps — then auto-generates the tools to fill them. No engineer needs to hand-build MCP servers. No team needs to sacrifice headcount on integration work.\n\nA new team onboards? IncidentFox studies their stack and proposes tools specific to their services — with human approval before anything goes live.\n\n**2. Per-team configuration — because every team is different**\n\nYour payments team and your ML team don't use the same stack. Why would they use the same AI SRE config?\n\nEach team gets their own:\n\n* Tools — enable only what's relevant; disable what isn't\n* Prompts — fully open source and exposed to engineers. Inject your domain knowledge directly\n* Knowledge base — learned from that team's incidents, runbooks, and services\n\nOne team's \"config drift\" is another team's \"model drift.\" IncidentFox understands the difference.\n\n**3. Continuously evaluates and self-improves**\n\nAfter every incident, IncidentFox:\n\n* Detects gaps — \"I couldn't query service X's health endpoint\"\n* Auto-generates the missing tool\n* Evaluates its own investigation quality against the actual resolution\n* Updates prompts and knowledge — with human review\n\nIt gets measurably better every week. Not because you tuned it — because it tuned itself.\n\n**4. 300+ integrations included on day one**\n\nWhile it auto-builds what's missing, you're not starting from zero. Kubernetes, AWS, Grafana, Prometheus, Datadog, Elasticsearch, PagerDuty, GitHub — all built in. Integration time is under a day, not months.\n\n**🧠 Why this matters**\n\n**Integrations** — Traditional: Hand-built per team. Each team sacrifices an engineer. IncidentFox: Auto-discovered and auto-generated. Human approves.\n\n**Multi-team scaling** — Traditional: Breaks — you can't know every team's stack. IncidentFox: Per-team config. Each team's AI knows their stack.\n\n**Domain knowledge** — Traditional: Black box prompts, hope it works. IncidentFox: Open source prompts. Engineers inject and edit freely.\n\n**Over time** — Traditional: Stagnates unless manually updated. IncidentFox: Self-evaluates, finds gaps, improves continuously.\n\n**Setup** — Traditional: Months of custom integration work. IncidentFox: &lt; 1 day. 300+ tools out of the box.\n\n**📊 Results**\n\n* 85–95% reduction in alert noise through intelligent correlation\n* Hours → minutes for incident investigation\n* Zero-config onboarding — Docker in 5 min, production K8s in 30 min\n\n![uploaded image](/media/?type=post&id=97928&key=user_uploads/1146198/844d70ec-e308-472c-9bc4-f212cd954153)\n\n**🔒 Enterprise-ready, open-source**\n\n* Open source — Apache 2.0, no vendor lock-in\n* SOC 2 compliant, SSO/OIDC, RBAC, audit logs\n* Self-hosted, on-prem, or managed SaaS\n* Bring your own LLM keys (OpenAI, Claude, Gemini, etc.)\n\n**👬 The Team**\n\n[**Jimmy (CEO)**](https://www.linkedin.com/in/chiehmin-wei/) — Previously at Roblox, where he built social communication features (in-experience calling for 100M+ DAU). Before that, worked at Meta FAIR on multiparty conversational AI, with published research. Cornell CS. Serial founder — previously CTO at a startup in Outlier Ventures' DeFi accelerator.\n\n[**Long (CTO)** ](https://www.linkedin.com/in/long-yi-b221b2183/)— Previously at Roblox, where he built database infrastructure supporting 100M+ daily active users on the Stateful Infra team. Experienced the chaos of on-call firsthand — which is why we're building this. Brandeis CS + Neuroscience + Business.\n\nWe've lived on both sides: Jimmy built the AI systems, Long was the SRE drowning in incidents. IncidentFox is what happens when you combine both.\n\n![uploaded image](/media/?type=post&id=97928&key=user_uploads/1146198/261f0711-50aa-4a0f-b6c9-9cdc7c853dbc)\n\n\n**🙏 Our Asks**\n\n* Try IncidentFox — self-serve at [incidentfox.ai](https://incidentfox.ai) or star us on [GitHub](https://github.com/incidentfox/incidentfox)\n* Intros to engineering teams spending too much time on on-call\n  * [Book a demo with us](https://calendly.com/d/cxd2-4hb-qgp/30-minute-demo-call-w-incidentfox)\n* Feedback from SREs and infra engineers — [founders@incidentfox.ai](mailto:founders@incidentfox.ai)\n\nThanks for reading ❤️",
        "url": "https://www.ycombinator.com/launches/PTU-incidentfox-the-ai-sre-who-never-drops-context",
        "votes": 5,
        "created_at": "2026-02-18T01:06:25.804Z"
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    "id": 31216,
    "name": "Archal",
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    "website": "https://www.archal.ai/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Archal provisions sandboxes with the API environments your CI, tests, and evals need. Your coding agent can start the sandbox & environments, connect to your API integrations, run tests, and inspect state changes. Sandboxes and environments are startable within seconds and take milliseconds to reset.",
    "one_liner": "API sandboxes, built for AI agents",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
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    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/archal.json",
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        "full_name": "Aidan Tiruvan",
        "title": "Founder/CEO",
        "founder_bio": "Founder at Archal; API sandboxes built for AI agents\nPrev ML research at Scale AI & NASA",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/aidantiruvan/",
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      {
        "id": 111649,
        "title": "Archal: API sandboxes, built for AI agents",
        "tagline": "Test API integrations without test accounts, rate limits, or messy state.",
        "body": "> **TLDR:** Create an API sandbox with the environments your CI, tests, and evals need. Your coding agent can start the API sandboxes (e.g Linear, Slack, Datadog), run tests, and inspect state changes. Ask your agent about archal.ai!\n\nHi everyone, I'm Aidan, the founder of Archal. I previously built agent environments at Scale AI and I've been an avid developer for most of my life, which led me to the problem Archal poses to solve.\n\n[https:/youtu.be/pUfu1RFDYVk](https://youtu.be/pUfu1RFDYVk)\n\n**What we found**\n\nCoding agents are getting much better at writing integrations, but testing those integrations is still painful. Many providers do not offer a usable sandbox, so developers fall back to throwaway accounts, shared test workspaces, or thin mocks. Those options are difficult to reset and make it hard to know whether an agent actually completed a task or only returned a plausible response.\n\nAs Adam Bender at Google put it, “But with 10x more code and 10x more services, integration tests are going to become the most important part of your quality strategy.” (Google, Software engineering is at the tipping point)\n\n**How Archal works**\n\nWith all of this in mind, I built Archal for a starting point of how the next generation of devs will do QA. It's a tool focused on giving agent developers and integration engineers API sandboxes of the SaaS platforms they use in prod pipelines. With Archal, a developer or their coding agent can start a sandbox, run the task, inspect what changed, and reset everything for the next test. We eliminate the need of separate test accounts, thin mocks and stubs, as well as overburdening rate limits on provider-owned sandboxes.\n\n**Our ask**\n\nWe're giving out $20 in Archal credits to each new developer that signs up and starts a sandbox. We’d love for you to give it a try and give us feedback, cheers to making testing easier in the era of coding agents!",
        "url": "https://www.ycombinator.com/launches/T2n-archal-api-sandboxes-built-for-ai-agents",
        "votes": 61,
        "created_at": "2026-08-22T21:00:00.317Z"
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    "subindustry": "B2B -> Engineering, Product and Design",
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    "regions": [
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    "url": "https://www.ycombinator.com/companies/superset",
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    "year_founded": 2026,
    "city": "San Francisco",
    "country": "US",
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    "primary_partner": {
      "name": "Nicolas Dessaigne",
      "url": "https://www.ycombinator.com/people/nicolas-dessaigne"
    },
    "founders": [
      {
        "user_id": 276516,
        "full_name": "Kiet Ho",
        "title": "Founder/CEO",
        "founder_bio": "Co-Founder at Superset\nprev cofounder at Onlook (W25), swe at Amazon, ServiceNow",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/kiet-ho",
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      {
        "user_id": 667926,
        "full_name": "Satya Patel",
        "title": "Founder/CTO",
        "founder_bio": "Co-founder at Superset\nformer CTO of Untether Labs (YC W23), Google, Amazon",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/saddlepaddle/",
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      {
        "user_id": 230159,
        "full_name": "Avi Peltz",
        "title": "Founder/CPO",
        "founder_bio": "Co-Founder @Superset. | Prev. Co-Founder CTO Adam(W25) and Cofounder@BioGlyph ",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/avipeltz",
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      {
        "id": 91489,
        "title": "Founding Engineer",
        "url": "https://www.ycombinator.com/companies/superset/jobs/Nd9luiP-founding-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "$175K - $225K",
        "equity_range": "1.00% - 1.50%",
        "experience": "2+ years",
        "visa": "Will sponsor",
        "skills": [
          "PostgreSQL",
          "React",
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      {
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        "title": "Founding Design Engineer",
        "url": "https://www.ycombinator.com/companies/superset/jobs/rp22UiM-founding-design-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Frontend",
        "salary_range": "$175K - $225K",
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        "experience": "Any (new grads ok)",
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        "id": 101973,
        "title": "Superset - the open source IDE for the AI Agents era",
        "tagline": "The fastest growing open source agentic IDE: 11K stars + thousands of daily active users",
        "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/>",
        "url": "https://www.ycombinator.com/launches/QWj-superset-the-open-source-ide-for-the-ai-agents-era",
        "votes": 12,
        "created_at": "2026-05-26T16:52:54.121Z"
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    "id": 31230,
    "name": "o11",
    "slug": "o11",
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    "website": "https://o11.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "o11 helps your AI agents access apis, tools, and other paid goods and services. Instead of hacky computer use, managing credit card permissions, assigning each agent a new email, we handle all the hard parts of accessing the paid web. o11 has zero markup and gives teams better prices, easy checkout, and full auditability when purchasing with AI agents. \r\n\r\nThe o11 wallet gives your AI agents access to the paid world.\r\n",
    "one_liner": "OpenRouter wallet for paid goods and services",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1765258468,
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    "batch": "Winter 2026",
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      "America / Canada"
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    "year_founded": 2025,
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    "country": "US",
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        "body": "tldr: your cookie banner is slowing down your site. Inth banners keep performance high, styled using your own components, and keeps you compliant using our open-source core, [c15t.com](http://c15t.com).\n\nInth is building cookie banners that don't cost your Core Web Vitals.\n\nFor years, cookie banners have plagued the internet with slow bloated scripts, that aren't aware of user locations or local laws, built for marketing and legal teams. Inth is fixing this with developer-first consent infrastructure.\n\n<https://youtu.be/RJ7cSk1QYi8>\n\nInth helps developers automate cookie consent and user data rights to ensure compliance with all jurisdictions, using the fastest and most composable cookie banner available, c15t.\n\nBundled into your website's code, c15t cookie banners have native SDKs, i18n, and are fully customizable to match your UI and brand. Built for developers who care about compliance and performance.\n\nSince Inth launched, c15t has grown over 2 million npm downloads, and is used by some of the top developer tools companies, luxury hotel chains, and online supermarkets.\n\nJoin the teams already using Inth to deploy faster, compliant websites at [inth.com](http://inth.com) or quickstart: npx @c15t/cli\n\nFind our docs here: c15t.com/docs",
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        "role_type": "Full stack",
        "salary_range": "$150K - $250K",
        "equity_range": "0.50% - 2.00%",
        "experience": "Any (new grads ok)",
        "visa": "Will sponsor",
        "skills": []
      },
      {
        "id": 116603,
        "title": "Founding Growth",
        "url": "https://www.ycombinator.com/companies/replicas/jobs/fmrVgOj-founding-growth",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Marketing",
        "role_type": null,
        "salary_range": "$150K - $250K",
        "equity_range": "0.50% - 2.00%",
        "experience": "Any (new grads ok)",
        "visa": "Will sponsor",
        "skills": []
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    ],
    "news": [],
    "launches": [
      {
        "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"
      }
    ]
  },
  {
    "id": 31380,
    "name": "Superlog",
    "slug": "superlog",
    "former_names": [
      "Swish",
      "Pulsend",
      "Pulsent",
      "Deep Engage",
      "Deepengage",
      "Openengage",
      "Deepengage",
      "Pulsending",
      "deep engage",
      "Singlevox",
      "deep engage",
      "Pulsent"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/96347d910b359b8008029da5fa69b30000efd6d0.png",
    "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,
    "tags": [
      "Developer Tools",
      "Open Source",
      "Kubernetes",
      "Enterprise Software",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Spring 2026",
    "status": "Active",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "France",
      "Europe"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "url": "https://www.ycombinator.com/companies/superlog",
    "api": "https://devasheeshg.github.io/yc-api/batches/spring-2026/superlog.json",
    "year_founded": 2026,
    "city": "Paris",
    "country": "FR",
    "linkedin_url": "https://www.linkedin.com/company/superlogyc",
    "x_url": "https://x.com/superlogyc",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/96347d910b359b8008029da5fa69b30000efd6d0.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [
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    ],
    "primary_partner": {
      "name": "David Lieb",
      "url": "https://www.ycombinator.com/people/david-lieb"
    },
    "founders": [
      {
        "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",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/nicolo-magnante/",
        "x_url": "https://x.com/nicolomagnante",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b8bcc3506b03fd18553c21a745fb1ca58549dc3d.jpg"
      },
      {
        "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.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/arseniy-shishaev",
        "x_url": "https://x.com/arseniyswish",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/dbbe5e3ee648431c9ed6c3b18cb41e7bfc059958.jpg"
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    "jobs": [],
    "news": [],
    "launches": [
      {
        "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"
      }
    ]
  },
  {
    "id": 31395,
    "name": "Deep Interactions",
    "slug": "deep-interactions",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2150b2f6e149aef04ef65b7381c3bd0b77037221.png",
    "website": "https://deepinteractions.ai/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Deep Interactions is a collaborative AI builder. We don't leave you with a spaghetti mess of a code. We bring product intelligence and power the context layer that enables your team to build in sync - saving companies tokens, time, and nerves. You give us a problem and we ship a working AI product in the same afternoon.\r\n",
    "one_liner": "Collaborative AI app builder for teams",
    "team_size": 6,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1778970590,
    "tags": [
      "Developer Tools",
      "Collaboration",
      "Design Tools",
      "No-code",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Spring 2026",
    "status": "Active",
    "industries": [
      "B2B"
    ],
    "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/deep-interactions",
    "api": "https://devasheeshg.github.io/yc-api/batches/spring-2026/deep-interactions.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/deep-interactions",
    "x_url": "https://x.com/deepintxns",
    "fb_url": null,
    "cb_url": null,
    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/2150b2f6e149aef04ef65b7381c3bd0b77037221.png",
    "app_video_url": null,
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    "company_photos": [],
    "primary_partner": {
      "name": "Tom Blomfield",
      "url": "https://www.ycombinator.com/people/tom-blomfield"
    },
    "founders": [
      {
        "user_id": 3138588,
        "full_name": "Sruthi Viswanathan",
        "title": "Founder/CEO",
        "founder_bio": "Founder at Deep Interactions (YC P26). PhD in Computer Science from Oxford. Prev. Built : AI Trainer as CTO at The Spaceship AI, AI Scientist at Autoscience Institute & AI Therapist at Limbic AI. Was Research Scientist at NAVER LABS Europe and Google. ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/sruvis",
        "x_url": "https://x.com/_sruvis",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a4593a7424e64f74828b20e0f15f5d406e007a3e.jpg"
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    "jobs": [],
    "news": [],
    "launches": [
      {
        "id": 101487,
        "title": "Deep Interactions — Collaborative AI Builder for Teams",
        "tagline": "We turn messy ideas, data, and agents into shipped products before your team logs off.",
        "body": "Hello! I'm [Sruthi Viswanathan](https://www.linkedin.com/in/sruvis/), founder of [Deep Interactions](https://www.deepinteractions.ai).\n\n### TL;DR\n\n### **Deep Interactions is a collaborative AI builder for teams. We turn messy ideas, data, and tools into working AI products in a single afternoon — so companies stop burning months and millions on pilots that never ship.**\n\n**_Ask:_** Intros to CEOs, CTOs, COOs, CFOs, or Heads of AI with an initiative stuck in pilot purgatory — especially in healthcare, fintech, consumer, applied AI, and ops-heavy businesses. → [sruthi@deepinteractions.ai](mailto:sruthi@deepinteractions.ai)\n\nLaunch video: <https://youtu.be/AuSnAHZP2lM>\n\n### The Problem\n\nProduct development hasn't changed in 20 years. Write a PRD, throw it at engineering, hope it matches what users actually need.\n\nNow teams have layered AI on top: vibe-coding through the night, stitching prompts, tools, and agents. Same problem, faster and more expensive:\n\n* Burned tokens\n* Burned out teams\n* Spaghetti code that still misses the customer\n\n**95% of businesses walk away from their AI pilots. Hundreds of billions in wasted AI spend, every year.**\n\nThe bottleneck isn't models or prompts anymore. It's shared understanding of the customer, the product, and the codebase. Until now, there was no way to keep humans, agents, and code in sync as a product is being built. With today's reasoning models and multi-agent orchestration, couple with situated context, there is.\n\n### Our Solution\n\nYou bring the problem. We ship the product the same afternoon — alongside your team, inside the tools they already use (Slack, Figma, GitHub, Vercel, Supabase, You name it).\n\nWe don’t leave you with a spaghetti mess of a code. We bring product intelligence and power the context layer that enables your team to build in sync.\n\nAlready live with **12 businesses and 50k+ real-world usage hits.** Saving companies months of work and millions in AI spend.\n\n![uploaded image](/media/?type=post&id=101487&key=user_uploads/3138588/8b1080f6-4249-41e9-856c-626cee704905)\n\n\n### **How can you help?**\n\nIf you can warmly introduce us to any of the following, I'd be grateful:\n\n* **Operators** with a stuck AI initiative (Heads of AI, CPOs, CTOs, VPs of Engineering)\n* **Healthcare &amp; wellness** companies looking to ship patient- or clinician-facing AI\n* **Consumer** companies (dating, fitness, fertility, social) ready to put AI in the product, not just the pitch deck\n* **Applied AI startups** burning tokens on coding agents that don't ship\n* **Angels and operators** who've shipped AI products at scale\n\nPlease contact me at [sruthi@deepinteractions.ai](mailto:sruthi@deepinteractions.ai)\n\n### Team\n\nI'm a Human-Centred AI researcher and DPhil in Computer Science at Oxford, with cutting-edge experience across Big Tech, AI labs, startups, and academia — spanning software engineering, UX, ML, and AI research. Recognised by 100 Women in AI (2025).\n\nAround me: a founding AI designer reshaping how humans and agents collaborate, a founding engineer with decades in production systems, and GTM operators who's built customer success from zero. Advised by leading Human-Centred Computing professors, AI scientists, and brilliant Angels.\n\nI started Deep Interactions because I kept watching brilliant teams ship broken AI. The future of AI work isn't more prompts — it's better human-AI collaboration.\n\nBook a call → 🕷️ [www.deepinteractions.ai](http://www.deepinteractions.ai)\n\n![uploaded image](/media/?type=post&id=101487&key=user_uploads/3138588/0004eb4a-4f58-4ffe-849a-c746c2d9c01c)\n\n",
        "url": "https://www.ycombinator.com/launches/QOt-deep-interactions-collaborative-ai-builder-for-teams",
        "votes": 98,
        "created_at": "2026-05-18T03:36:32.000Z"
      }
    ]
  },
  {
    "id": 31432,
    "name": "Keyframe Labs",
    "slug": "keyframe-labs",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ca6ef21e7c765ce2b9f612cc2ec833a2654c6bd4.png",
    "website": "https://keyframelabs.com",
    "all_locations": "Los Angeles, CA, USA",
    "long_description": "We build human foundation models. Our first family of models powers lifelike avatars that interact with users in real time, enabling AI agents and applications to go beyond text and voice with just a few lines of code. State-of-the-art realism with ultra-low latency at scale.",
    "one_liner": "Bring AI to life with the world's best interactive avatars",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1774290085,
    "tags": [
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      "SaaS",
      "B2B",
      "API",
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    "nonprofit": false,
    "batch": "Spring 2026",
    "status": "Active",
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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/keyframe-labs",
    "api": "https://devasheeshg.github.io/yc-api/batches/spring-2026/keyframe-labs.json",
    "year_founded": 2025,
    "city": "Los Angeles",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/keyframe-labs-inc",
    "x_url": "https://x.com/KeyframeLabs",
    "fb_url": null,
    "cb_url": "https://www.crunchbase.com/organization/keyframe-labs",
    "github_url": "https://github.com/keyframelabs",
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/ca6ef21e7c765ce2b9f612cc2ec833a2654c6bd4.png",
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    "primary_partner": {
      "name": "David Lieb",
      "url": "https://www.ycombinator.com/people/david-lieb"
    },
    "founders": [
      {
        "user_id": 3206626,
        "full_name": "Parth Radia",
        "title": "Founder/CEO",
        "founder_bio": "Parth is co-founder & CEO of Keyframe Labs. Before Keyframe, he spent 5 years at Ericsson on frontier AI, founding and leading a team of 35 building foundation models for voice & video synthesis on one of the world's first petascale human datasets, shipping Ericsson's first generative AI products. Before that, as a research scientist at AT&T Labs he developed novel neural architectures for photorealistic 3D telepresence, enabling the world's first 3D call over production networks. B.S. CS UCLA.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/parthradia/",
        "x_url": "https://x.com/parthnradia",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/19df1fc54bb17e3b127d5179247e82a7382c1774.jpg"
      },
      {
        "user_id": 569532,
        "full_name": "Kaahan Radia",
        "title": "Founder/CTO",
        "founder_bio": "Kaahan is co-founder and CTO of Keyframe Labs, building the world's first photoreal, emotionally expressive AI humans for real-time video agents. Previously, he spent five years at Zipline as a Perception Engineer, building their camera-based detect-and-avoid system for autonomous drone operations. His work spans computer vision and applied ML, with research at CVPR and JAMA.\n\nB.A. CS, UC Berkeley.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/kaahan-radia-2ba47354/",
        "x_url": "https://x.com/kradisme",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/69561b5971be202ad21208b2ba78d5cfb96772ba.jpg"
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    ],
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    "news": [],
    "launches": [
      {
        "id": 99738,
        "title": "Keyframe Labs - turn AI into lifelike video calls",
        "tagline": "Bring AI to life with photoreal, conversational humans",
        "body": "**tl;dr:** our real-time, generative models turn AI into lifelike video calls. Deploy in minutes with a few lines of embed code. Photorealism, emotion, and scale for just $0.06 per minute.\n\nWe’re [@Kaahan Radia](https://bookface.ycombinator.com/user/569532) and [@Parth Radia](https://bookface.ycombinator.com/user/3206626) from Keyframe Labs. Our interactive video models bring your AI agents and applications to life.\n\n<https://youtu.be/cIEP8OwTD4M>\n\nYou can try a video call for yourself here: <https://keyframelabs.com>. To get a sense for the interactivity and expressive range, try asking for a sad Shakespearean monologue. Or for a “funny” dad joke.\n\n**But why video agents?**\n\n![uploaded image](/media/?type=post&id=99738&key=user_uploads/3206626/ad0420da-db57-4562-a1a4-b5db0b0de005)\n\nFace-to-face interaction triggers responses that text and voice simply can’t. Video calls close more deals, language learning with video tutors outperforms audio-only, and human presence drives outcomes in high-stakes interactions (e.g., telehealth, tax prep).\n\nNow that voice has emerged as a primary conversational interface across industries, video is the next leap. Developers and enterprises already use Keyframe to easily deploy photoreal, conversational humans to a wide variety of use cases, including:\n\n* AI roleplay, for corporate training / learning and development\n* AI recruiting, for interview practice and automated screenings\n* Telehealth\n* High-touch customer support\n* AI sales and customer success reps\n* Always-on digital twins of influencers, to scale engagement and hyper-personalize interactions\n\n**How it works**\n\n![uploaded image](/media/?type=post&id=99738&key=user_uploads/3206626/34f670bd-7436-48e9-bd72-2d0f8bd73e44)\n\nSuper simple.\n\n1. Connect your agent or LLM, or choose from our supported providers\n2. Select a persona from our stock library\n3. Drop the embed code into your application\n\nNeed a custom persona or more control? Custom personas are available on enterprise plans, and our SDKs let you roll your own implementation.\n\n**Why Keyframe**\n\nOur research goals from day one have been:\n\n* Make meaningful progress towards beating the uncanny valley\n* Run at real-time, with world-scale efficiency\n\nThe result:\n\n* Industry-leading realism and concurrency limits\n* At a fraction of the cost of competitors\n\n**Get up and running**\n\n* [Sign up free](https://platform.keyframelabs.com/) (no credit card required) and build something cool\n* Have a use case? [Book time with us directly](https://keyframe-labs.cal.com/sales/intro-call)\n* Know a company that could benefit from face-to-face AI interactions? We’d love an intro",
        "url": "https://www.ycombinator.com/launches/Pwg-keyframe-labs-turn-ai-into-lifelike-video-calls",
        "votes": 24,
        "created_at": "2026-04-14T18:57:11.659Z"
      }
    ]
  },
  {
    "id": 31458,
    "name": "Reason Machines",
    "slug": "reason-machines",
    "former_names": [
      "EasyClaw",
      "Ara"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ac8d1fbd9622030ddfab1cc9a6fac1907350004f.png",
    "website": "https://reasonmachines.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Reason Machines builds Reason Agent, the autonomous software engineer for engineering teams. Reason connects to GitHub, reproduces bugs, writes code, passes tests, and ships review-ready pull requests with recordings and logs across cloud environments.",
    "one_liner": "Reason Machines builds Reason Agent, the autonomous software engineer…",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Productivity",
    "launched_at": 1775160352,
    "tags": [
      "Developer Tools",
      "Enterprise Software",
      "Cloud Computing"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Spring 2026",
    "status": "Active",
    "industries": [
      "B2B",
      "Productivity"
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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": null,
    "url": "https://www.ycombinator.com/companies/reason-machines",
    "api": "https://devasheeshg.github.io/yc-api/batches/spring-2026/reason-machines.json",
    "year_founded": 2026,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/reasonmachines",
    "x_url": "https://x.com/reasonmachines",
    "fb_url": null,
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    "github_url": null,
    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/ac8d1fbd9622030ddfab1cc9a6fac1907350004f.png",
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    "primary_partner": {
      "name": "Aaron Epstein",
      "url": "https://www.ycombinator.com/people/aaron-epstein"
    },
    "founders": [
      {
        "user_id": 1868530,
        "full_name": "Adi Singh",
        "title": "Founder/CEO",
        "founder_bio": "co-founder & ceo @ Reason Machines\nEECS @ UC Berkeley, Cybernetics NTNU\nPrev built a rust based IDE from scratch\n21\n",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/adisinghlink",
        "x_url": "https://x.com/xadisingh",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/39dc609171f30d0579beff3ad7feda1e12ddde45.jpg"
      },
      {
        "user_id": 3131989,
        "full_name": "Sven Myhre",
        "title": "Founder/CTO",
        "founder_bio": "co-founder @ Reason Machines (P26)\n-\nWith a background in EECS from UC Berkeley and scaling ML infra in industry, some notable milestones include winning 1st place in the Norwegian AI Championship 2025, having chaired Norway's largest AI student org and having ran ultramarathons (100km>).",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/svemyh",
        "x_url": "https://x.com/svemyh",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/fe32f68ce79ac76c83594b8ea44b35b153f2e132.jpg"
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    ],
    "jobs": [
      {
        "id": 102429,
        "title": "Engineering Internship",
        "url": "https://www.ycombinator.com/companies/reason-machines/jobs/r1SHuHh-engineering-internship",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Full stack",
        "salary_range": "",
        "equity_range": "0.50% - 2.00%",
        "experience": "Any (new grads ok)",
        "visa": "US citizen/visa only",
        "skills": [
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          "React",
          "Rust",
          "TypeScript",
          "Distributed Systems",
          "LLMs",
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      }
    ],
    "news": [],
    "launches": [
      {
        "id": 102348,
        "title": "Ara - The World's First Self-driving IDE",
        "tagline": "The IDE that thinks ahead of you",
        "body": "Hey everyone, we’re [Adi](https://www.linkedin.com/in/adisinghlink/) and [Sven](https://www.linkedin.com/in/svemy/) - cofounders of [Ara](https://ara.so/) 👋\\\n\\\n**tl;dr:** we built an IDE for the future\n\n<https://youtu.be/6ASb9QW2QEw>\\\n\\\n**the problem**\\\nThe bottleneck in development keeps moving. It used to be writing the code. Then agents solved that, and it became reviewing the code. Now what's left is planning the next step, and every IDE still waits.\n\n![uploaded image](/media/?type=post&id=102348&key=user_uploads/3131989/cb840d79-95f8-446d-b4cd-a60e9db72a85)\n\n**the solution** \\\nAra closes the loop. It proactively plans your next step, handing you proposals you can discard or send off to follow up on, with self-improving memory across all your tools and sessions, and full visibility across chats, files, browsers, terminals, and review panes.\n\n![uploaded image](/media/?type=post&id=102348&key=user_uploads/3131989/fc09658e-c84b-4e56-8b00-4485c3de72ae)\n\n\\\n**team**\\\nAdi and Sven both studied EECS at UC Berkeley. Adi worked in applied ML, at Scale AI and previously built an IDE company. Sven was an ML engineer on production systems and chaired Norway's largest student AI org. Serial hackathon winners, they've built and lived together across four cities and dropped out to build the IDE they always wanted.\n\nThe goal is an IDE that runs the development loop end to end, not one that waits for instructions.\n\n\\\n_The IDE for token-maxxers._\n\n![uploaded image](/media/?type=post&id=102348&key=user_uploads/3131989/eb3b255b-1cc1-4f77-a1c5-aa2f22227b7b)\n\n**our ask**\\\nTry it! [**Download Ara**](https://ara.so/) and email us at [founders@ara.so](mailto:founders@ara.so) with your feedback.",
        "url": "https://www.ycombinator.com/launches/Qcm-ara-the-world-s-first-self-driving-ide",
        "votes": 30,
        "created_at": "2026-06-01T00:32:45.864Z"
      }
    ]
  },
  {
    "id": 31495,
    "name": "Mentlio",
    "slug": "mentlio",
    "former_names": [
      "Adjoint"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f7a733c432ee3fbe8a11ed5dec1520431b7f8d09.png",
    "website": "https://mentlio.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Mentlio an applied research lab focused on optimizing AI ROI for the modern enterprise. We help engineering teams draw a line between their AI spend and delivery, per engineer. We then cut ~30% of AI spend via Mentlio's custom ML-based intelligent routing, context optimization, and prompt compression.",
    "one_liner": "Engineering Intelligence and Token Optimization for the AI-Coding Era",
    "team_size": 0,
    "industry": "B2B",
    "subindustry": "B2B",
    "launched_at": 1786589390,
    "tags": [
      "Developer Tools",
      "Machine Learning",
      "Productivity"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2026",
    "status": "Active",
    "industries": [
      "B2B"
    ],
    "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/mentlio",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/mentlio.json",
    "year_founded": 2026,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/mentlio/",
    "x_url": "",
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    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/f7a733c432ee3fbe8a11ed5dec1520431b7f8d09.png",
    "app_video_url": null,
    "dday_video_url": null,
    "company_photos": [
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    ],
    "primary_partner": {
      "name": "Pete Koomen",
      "url": "https://www.ycombinator.com/people/pete-koomen"
    },
    "founders": [
      {
        "user_id": 2693539,
        "full_name": "Ashank Shah",
        "title": "Founder/CEO",
        "founder_bio": "Building Mentlio | Prev. CS @ Caltech | Researched generative and graph-based DL for biomedical problems @ Dartmouth Health.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/ashank-shah/",
        "x_url": "https://x.com/ashankshah_x",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/758354f37ee3a77f1731eb04c7889b1d7bb48571.jpg"
      },
      {
        "user_id": 2587306,
        "full_name": "Ahmet Demirbas",
        "title": "Founder/CTO",
        "founder_bio": "Tokenmaxxing → ROImaxxing | Prev CS @ Caltech | 5x Published ML, NLP, Agents Research @ IEEE, ACM, BMC",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/ahmet-demirbas7/",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/078fa095bf49a870046553858e43d9b8fc0cb577.jpg"
      }
    ],
    "jobs": [],
    "news": [
      {
        "title": "Factory Acquires Mentlio: Building Intelligent Token Allocation for the Software Factory",
        "url": "https://factory.com/news/mentlio",
        "date": "Oct 09, 2026"
      }
    ],
    "launches": [
      {
        "id": 111055,
        "title": "Mentlio: Engineering Intelligence & Token Optimization for the AI-coding Era",
        "tagline": "The spend and ROI command center for the modern engineering org ",
        "body": "**TL;DR:** Mentlio is the engineering intelligence platform for the AI-coding era. We help engineering organizations cut AI costs by up to 30% and finally see what ROI that spend is actually producing. All without ever collecting your prompts or source code.\n\n**Launch Video**\n\n<https://youtu.be/-28j9HvTYV0>\n\n**Problem**\n\nEvery engineering org is now an AI org. Token usage is growing exponentially, and so is the bill. The following questions have been largely unanswered:\n\n* How can we cut our usage-based AI spend without bottlenecking usage or efficiency?\n* What ROI are we getting for every dollar of AI spend?\n* To what extent is AI-generated code creating quality debt?\n\nBrian Armstrong recently laid out how Coinbase is reducing AI spend while token usage grows exponentially on X: better defaults, smarter routing, cache awareness, lean context, and full visibility into usage and impact. \n\n![uploaded image](/media/?type=post&id=111055&key=user_uploads/2693539/7bf48740-dd37-4015-9da9-ec0f9bd900ed)\n\nCoinbase built a custom harness, LLM gateway, routing, and usage visibility internally. We believe they have the right thesis, but most engineering orgs don’t want to run on a custom harness. **Mentlio gives every eng team a better version of those savings &amp; visibility without changing any workflows.**\n\n**Solution**\n\nMentlio gives you:\n\n1. **ROI.** We translate every PR into normalized units of work: Delivery Points. We consider associated spend, code reusability, and historical patches to turn \"we spend $X on AI\"  -> \"we spend $X per impact point.” compared to industry data. \n2. **Cost intelligence + optimization.** See exactly where AI spend goes across teams, tools, and models. Optionally catch and cut waste across cache misses, oversized models on trivial tasks, bloated context and cut it without capping/bottlenecking accuracy. \n3. **Quality signal.** AI-assisted code that ships fast but breaks later isn't a win. We connect AI usage to delivery and quality outcomes so you can see the full picture\n\nWe’re the only platform with the above capabilities that never collects prompts or source code.\n\n**Our Asks**\n\nIf you are or know a Head of Eng, VP Eng, CTO, or platform lead at a 15+ engineer org with real AI spend, reach out! You can book a demo at[ mentlio.com/intro](http://mentlio.com/intro) or reach us at [founders@mentlio.com](mailto:founders@mentlio.com).\n\n**The Team**\n\nAshank and Ahmet met while studying Computer Science at Caltech while they were working part-time Founding Engineer roles at Series A and Seed stage startups. Ashank previously researched generative image AI &amp; graph deep learning for pathology, genomics, and drug design at Dartmouth &amp; Purdue and won internationally at the International Science &amp; Engineering Fair &amp; Junior Science &amp; Humanities Symposium. Ahmet previously published his research in transformers and AI in IEEE, BMC AI, and ACM and also won internationally at the National AI Olympiad, International Science &amp; Engineering Fair, and was named a Top 300 Science Scholar by Regeneron.   \n\n![uploaded image](/media/?type=post&id=111055&key=user_uploads/2693539/d04ec655-df84-4d43-836d-160313b4b133)\n\n",
        "url": "https://www.ycombinator.com/launches/StD-mentlio-engineering-intelligence-token-optimization-for-the-ai-coding-era",
        "votes": 88,
        "created_at": "2026-08-18T22:00:00.168Z"
      }
    ]
  },
  {
    "id": 31547,
    "name": "InsForge (InstaCloud)",
    "slug": "insforge-instacloud",
    "former_names": [
      "InsForge"
    ],
    "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": [
      "Developer Tools",
      "DevSecOps",
      "Cloud Computing",
      "Infrastructure"
    ],
    "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"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": null,
    "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/",
    "x_url": "https://x.com/Insforge",
    "fb_url": null,
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    "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/de52713fe1552551dbe8aa2a5e60202c09bfc0d7.png",
    "app_video_url": null,
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    "primary_partner": {
      "name": "Andrew Miklas",
      "url": "https://www.ycombinator.com/people/andrew-miklas"
    },
    "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",
        "x_url": "https://x.com/hanghuang_",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2058201598004fe3b3a6453fb39790a037aa9afc.jpg"
      },
      {
        "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"
      }
    ],
    "jobs": [],
    "news": [],
    "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"
      }
    ]
  },
  {
    "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",
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        "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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        "title": "GitCafe: A Git forge for teams and agents shipping hundreds of times a day, not twice.",
        "tagline": "The Git forge for agent-scale teams",
        "body": "Software development is becoming much more parallel. Coding agents let a team have dozens or hundreds of related changes moving at the same time, creating more branches, reviews, CI runs, and automation than existing workflows were designed to absorb.\n\nToday, we’re opening GitCafe in public beta. It is a Git forge built for teams where humans and coding agents may ship hundreds or thousands of changes a day. We’re building the hosting, review, CI, security, and automation layer for that way of working.\\\n\\\nHundreds of users are already on GitCafe, and we’re currently running trials with roughly a dozen YC companies.\n\n![uploaded image](/media/?type=post&id=109445&key=user_uploads/1920545/eecbfb4f-82f1-4660-8ee8-aeea5273a8b9)\n\nGenerating code is only part of the problem. Teams still need to understand what is changing, review it safely, keep CI moving, catch security issues, and coordinate work without becoming overwhelmed.\n\nWe’re not building GitCafe because putting repositories, code review, and CI in one product is new. We’re building it because we believe the workload those systems need to support is about to change dramatically.\n\nWe started by rebuilding the Git infrastructure itself. Now we’re closing the product gap feature by feature.\n\nRecently, we added secret scanning, Buildkite and Harmont CI support, stacked diffs with Jujutsu and Sapling integration, and beta support for GitHub Actions.\n\nThese are foundational capabilities, not the destination. Building them on infrastructure we own gives us a base we can keep extending for higher-volume, agent driven development.\n\nThe honest version is that GitCafe is behind GitHub today. GitHub has spent more than a decade building an enormous product, and GitCafe does not yet have every workflow, administrative control, or integration that mature teams need. Some features are missing, some are experimental, and some edges are rough. We expect to earn the broader product surface, not claim it on day one.\n\nWe’re opening GitCafe now because the fastest way to improve it is to put it in the hands of teams doing real work.\n\nIf your team is already using coding agents heavily, try GitCafe at <https://git.cafe> and tell us where the workflow breaks down.\\\n\\\n<https://www.youtube.com/watch?v=blHKFEOmoFg>",
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        "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",
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    "all_locations": "San Francisco, CA, USA",
    "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.",
    "one_liner": "A cloud devbox that feels local",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1782800618,
    "tags": [
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      "SaaS"
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    "regions": [
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/prized",
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    "year_founded": 2026,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/useprized",
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    "primary_partner": {
      "name": "Ankit Gupta",
      "url": "https://www.ycombinator.com/people/ankit-gupta"
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    "founders": [
      {
        "user_id": 2447160,
        "full_name": "Hudson Griffith",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder & CEO of Prized. Most recently he was an engineer at Suno where he shipped full-stack features to millions of users. Before that he was the first engineer at Gander (YC F24), a 0-to-1 fleet-management platform that was acquired by Archer Aviation (NYSE: ACHR), where he owned the core architecture and built AI voice and document agents. He studied Computer Science at the University of Florida.",
        "is_active": true,
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      {
        "user_id": 2485896,
        "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.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/meliades",
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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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    "id": 32169,
    "name": "Speko",
    "slug": "speko",
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    "website": "https://speko.ai/?utm_source=ycombinator&utm_medium=profile",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Speko is a router for voice models: one API key, and your voice agent runs on the speech-to-text, LLM, and text-to-speech models we measured as best for your language and use case. The measurements are public at benchmarks.speko.ai: we test new models the day they ship and re-route when the numbers change, so you rewrite nothing. We ran this bake-off by hand for four years at previous company, shipping production voice for Fortune 500s.",
    "one_liner": "OpenRouter for Voice AI: one API, every call on the best speech model",
    "team_size": 4,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1783393099,
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      "America / Canada",
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    "url": "https://www.ycombinator.com/companies/speko",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/speko.json",
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    "country": "US",
    "linkedin_url": "https://linkedin.com/company/speko-ai",
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    "primary_partner": {
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      "url": "https://www.ycombinator.com/people/tyler-bosmeny"
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        "user_id": 451241,
        "full_name": "Beknazar Abdikamalov",
        "title": "Founder/CEO",
        "founder_bio": "Founder and CEO of Speko (YC S26). Previously co-founder and CTO of Hupo (voice AI; $14M raised; backed by DST Global and Meta), where he spent four years shipping production voice AI for fortune 500s in 10+ languages. Earlier a software engineer at Amazon; MS in CS from UNIST, Korea.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/abdik/",
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      {
        "id": 108267,
        "title": "Speko: OpenRouter for Voice",
        "tagline": "Every speech model, benchmarked language by language, wired into one API.",
        "body": "Speko is a router for voice models. One API key, and your agent runs on the speech-to-text, LLM and text-to-speech models we measured as best for your language and use case.\n\n![uploaded image](/media/?type=post&id=108267&key=user_uploads/451241/2038963f-c769-47a9-8fd9-c59f3966027b)\n\n### I picked voice stacks by trial and error for four years\n\nA voice agent is three models in a row: speech-to-text, then an LLM, then text-to-speech. Three vendors, a dozen credible options each. You run a bake-off, you argue about whose numbers are real, and you ship the combination that felt best that month.\n\nThen next week another model drops. And another. Nobody has time to re-run the bake-off, so the stack you picked under deadline quietly becomes the stack you are stuck with for a year.\n\nThat is how most voice agents are running today. Not on the best models. On the models that were best whenever someone last had a free week.\n\nPublic leaderboards do not settle it either. They are averages over somebody else's audio, in somebody else's conditions.\\\n\\\n[https://drive.google.com/file/d/1AjC8WVA96kUBdD09RJMUgFfvxGfxPvL-/](https://drive.google.com/file/d/1AjC8WVA96kUBdD09RJMUgFfvxGfxPvL-/view?usp=sharing)\n\n### We measure, then we route\n\nWe benchmark the speech models people actually ship on, language by language, and publish everything at [benchmarks.speko.ai](http://benchmarks.speko.ai): word error rate, finalize latency, time to first token, cost per minute. When a vendor ships a new model we test it the same day and the board updates.\n\nPoint your agent at Speko and that measurement becomes routing. One API key across every provider we support. Tell us the language and the conditions, and your traffic runs on the stack our numbers say wins. When the numbers change, the routing changes and you rewrite nothing.\n\nIf a provider fails when we open the connection, the router drops to the next ranked model on its own.\n\n### Or build the agent with us\n\nYou do not need an existing agent to start. A few lines gets a working voice agent live on Speko, and it inherits the same routing from day one.\n\nIf you are picking a voice stack right now, start with the numbers at [benchmarks.speko.ai](http://benchmarks.speko.ai), then build on them at [speko.ai](http://speko.ai).",
        "url": "https://www.ycombinator.com/launches/SAF-speko-openrouter-for-voice",
        "votes": 14,
        "created_at": "2026-07-29T19:10:13.923Z"
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    "id": 32172,
    "name": "Jcode",
    "slug": "jcode",
    "former_names": [
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    "website": "https://jcode.sh/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Jcode is a high-performance coding-agent harness that makes it possible for developers to scale up multi-agent/swarm workflows. It's built from the ground up with a different architecture to solve the memory bottleneck (it's 20x more memory efficient than Claude Code) that has kept agent swarms from going mainstream. It has 20K GitHub stars, and throughputs $1mil per month of inference spend",
    "one_liner": "High performance coding agents",
    "team_size": 1,
    "industry": "Consumer",
    "subindustry": "Consumer",
    "launched_at": 1786012852,
    "tags": [
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    "batch": "Summer 2026",
    "status": "Active",
    "industries": [
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      "America / Canada"
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/jcode",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/jcode.json",
    "year_founded": 2026,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/in/jeremy1huang/",
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    "primary_partner": {
      "name": "Brad Flora",
      "url": "https://www.ycombinator.com/people/brad-flora"
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    "founders": [
      {
        "user_id": 2670902,
        "full_name": "Jeremy Huang",
        "title": "Founder/CEO",
        "founder_bio": "hacked github\ntop 500 monkey type\nhttps://github.com/1jehuang\nage 21",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jeremy1huang/",
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    "launches": [
      {
        "id": 109551,
        "title": "Jcode: High-performance coding agents",
        "tagline": "20x more agents, 20x more productivity, 20x less RAM",
        "body": "[ ](https://drive.google.com/file/d/1zthUpXW7Hi4L-RS7sdzT1gbcEoS-VlM5/view?usp=sharing)\n\\\nThis is me running 20 agents in parallel. This is my real everyday workflow, not a demo.\n\n**What we do** Jcode is an open-source coding agent that's 20x more memory-efficient than Claude Code, which means you can run 20x more agents in parallel on the same machine. It hits state-of-the-art results on coding benchmarks. Try it: <https://jcode.sh/>\n\n**The problem** Most coding agents are heavy. Each instance eats gigabytes of RAM, and because memory is the bottleneck, you can only run a handful at once. That caps how much work you can hand off at a time. The real power of agents is dispatching lots of different tasks in parallel and having them all worked on at once, and that's exactly what today's tools make too expensive to do.\n\n**Our solution** Jcode is engineered from the ground up to be lightweight, roughly 20x more memory-efficient than Claude Code. Since RAM is what caps how many agents you can run, cutting memory 20x lets you fire off 20x more tasks in parallel on the same hardware. It's fully open source, so you can run it yourself and inspect exactly what it does.\n\n**Who I am** I'm Jeremy, 21, building Jcode. I think running many agents in parallel is the single biggest lever in developer productivity. Previously I hacked GitHub Copilot for unlimited tokens, and I'm top 500 in the world on Monkeytype. GitHub: <https://github.com/1jehuang>\n\n**Developers:** Try Jcode today: <https://jcode.sh/>\n\n**Investors:** I'm raising around Demo Day. Reach out: [jeremy@solosystems.dev](mailto:jeremy@solosystems.dev)\n\n![uploaded image](/media/?type=post&id=109551&key=user_uploads/2670902/ee164e14-5c6a-4811-9e21-c0a80aa3c004)\n\n",
        "url": "https://www.ycombinator.com/launches/SUx-jcode-high-performance-coding-agents",
        "votes": 35,
        "created_at": "2026-08-10T16:49:30.145Z"
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    "id": 32198,
    "name": "Riften",
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    "website": "https://riften.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Riften builds model routing, evaluations, private models, and training environments for AI labs, AI-native companies, and enterprises.\r\n\r\nWe help teams choose models for their workloads, evaluate how they perform, and build private models around company-specific work. We’re also developing coding environments where agents learn through backend engineering tasks.",
    "one_liner": "Earned intelligence for every company",
    "team_size": 5,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1785872995,
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    "url": "https://www.ycombinator.com/companies/riften",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/riften.json",
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    "country": "US",
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    "primary_partner": {
      "name": "Harshita Arora",
      "url": "https://www.ycombinator.com/people/harshita-arora"
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      {
        "user_id": 2941426,
        "full_name": "Carl Stauffer",
        "title": "Founder/CEO",
        "founder_bio": "Founder and CEO of Riften. Former Palantir Forward Deployed Engineer. Former nuclear researcher at Jefferson Lab. CS and AMS at Johns Hopkins.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/carl-stauffer-314335262/",
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    "launches": [
      {
        "id": 110330,
        "title": "Riften: Route every AI request. Build the models your company owns.",
        "tagline": "Cut LLM spend with one endpoint that selects the lowest-cost model that works.",
        "body": "[Riften Launch Video](https://youtu.be/9T82XHysqsc)\n\n## What Riften does\n\nRiften is an OpenAI- and Anthropic-compatible gateway that routes each LLM request to the lowest-cost model capable of completing it.\n\nConnect your existing providers, change the base URL, and keep the product you already built. Riften works across customer-facing AI products and internal tools, including Claude Code and Codex.\n\n**Riften is already removing enterprise-scale model spend from production workloads.**\n\n## Why we built it\n\nMost AI products choose a model once and send nearly everything to it.\n\nA documentation lookup, a support classification, and a codebase migration do not require the same intelligence. Yet they are routinely sent to the same frontier model at the same price.\n\nFor customer-facing products, that cost cuts directly into gross margin. For internal agents, it limits how broadly the company can deploy them.\n\n## How it works\n\nRiften evaluates each request locally, applies the company’s cost, capability, latency, and reliability constraints, and selects among the models available to that organization.\n\nHard tasks can still reach frontier models. Routine work moves to lower-cost commercial or open-weight models. Teams can keep their provider accounts, pin a specific model when needed, and inspect the cost and routing decision behind every request.\n\nThe objective is not the cheapest token. It is the lowest expected cost of completing the work.\n\n## From routing to company-owned models\n\nThe router reveals which work is repeated. Outcomes reveal whether it was done correctly.\n\nA passing test, an accepted patch, a resolved ticket, or a completed workflow can become part of a customer-specific evaluation. Riften uses those evaluations to improve routing, post-train open models around recurring work, and test those models against the APIs they are intended to replace.\n\nModels earn production traffic through the same endpoint. Frontier APIs continue to handle novel work. Repeated workloads move onto models the company controls.\n\nThat creates a direct path from inference routing to evaluation, post-training, deployment, and the applications where the work happens.\n\nThe model labs are building intelligence every company can rent. Riften is building the path to intelligence every company can own.\n\n## Team\n\nRiften is founded by Carl Stauffer, a former Palantir Forward Deployed Engineer who shipped software into the purchasing and production systems of a nine-figure manufacturer. He was Palantir’s first Neurodivergent Fellow through Alex Karp’s program, conducted nuclear research at Jefferson Lab, studied computer science and applied mathematics at Johns Hopkins, and is an a16z Scout.\n\nThe rest of the team comes from Stanford Mathematics, Berkeley computer science, and Carnegie Mellon mathematics and computer science. Their work spans Oxford OATML, SPAR, CMU CyLab, Palo Alto Networks, Millennium, Amazon Search, NASA, UCSF Health, and industrial manufacturing systems.\n\nThey have built agent orchestration platforms, LLM evaluation and fine-tuning systems, cryptographic security software, production search infrastructure, CAD-matching systems, and autonomous QA for measuring agent performance. Their research includes an ICML acceptance and current work in review at NeurIPS.\n\nThe team also brings national-level recognition in mathematics and technical research spanning manufacturing, computational science, and new energy systems.\n\nRiften combines enterprise deployment, frontier evaluation research, competitive mathematics, agent systems, security, and production ML in one team built for the full path from request to outcome to model.\n\n## The ask\n\n**We are looking for companies with meaningful LLM usage across customer-facing products or internal agents.**\n\nIf most of your traffic still runs through one frontier model, send us:\n\n* Your current default model\n* Whether the traffic is internal or customer-facing\n* Your approximate monthly model spend or volume\n\nWe will show you what should remain on the frontier, what can move today, and whether Riften is worth testing.\n\nEmail us at [info@riften.ai](mailto:info@riften.ai).",
        "url": "https://www.ycombinator.com/launches/ShW-riften-route-every-ai-request-build-the-models-your-company-owns",
        "votes": 11,
        "created_at": "2026-08-17T15:12:03.010Z"
      }
    ]
  },
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    "id": 32230,
    "name": "Codag",
    "slug": "codag",
    "former_names": [],
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    "website": "https://codag.ai/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Codag compresses tool call outputs before agents read them, which reduces token spend by  20-30% while retaining output accuracy.\r\n\r\nGovern and see analytics on agent dollars across all model providers and internal agents. \r\n ",
    "one_liner": "The AI gateway for cheaper, faster, permissioned agents.",
    "team_size": 1,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1779593681,
    "tags": [
      "Developer Tools"
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    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2026",
    "status": "Active",
    "industries": [
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      "Infrastructure"
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    "regions": [
      "United States of America",
      "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/codag",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/codag.json",
    "year_founded": 2026,
    "city": "San Francisco",
    "country": "US",
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    "primary_partner": {
      "name": "Harshita Arora",
      "url": "https://www.ycombinator.com/people/harshita-arora"
    },
    "founders": [
      {
        "user_id": 2706494,
        "full_name": "Michael Zhou",
        "title": "Founder/CEO",
        "founder_bio": "Solo @Codag. ex. @Okta, @Shopify for infrastructure. BSc in Computer Science and Neuroscience from University of Toronto. Ex. Rank 80 Challenger LoL, Rank 200 TFT",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/mzxzhou/",
        "x_url": "https://x.com/michaelzixizhou",
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    "launches": [
      {
        "id": 110923,
        "title": "Codag: Compression and control for agent tools",
        "tagline": "Optimize agent costs without changing how developers work.",
        "body": "Hi everyone,\n\nI’m Michael, founder of Codag.\n\n**TL;DR:** Codag compresses tool results before models read them, lowering costs and improving accuracy without changing how developers work, while providing tool usage analytics.\n\n<https://youtu.be/eJbK3SezeXA>\n\n### The problem\n\nAgents consume huge amounts of output from searches, tests, builds, logs, file trees, and APIs.\n\nA single tool result can add thousands of mostly repetitive lines to a session. The model processes that output before provider-native compaction can help. Important evidence gets buried, so the agent searches again, retries, or rereads the same data.\n\nThis makes agent sessions slower and more expensive. Companies also lack a consistent view of which tools and MCP servers agents use across Claude Code, Codex, and other harnesses.\n\n### What Codag does\n\nCodag attaches to existing agent harnesses with one setup command.\n\nIt handles each result according to the action being performed:\n\n\\- Tests preserve failures, traces, file locations, and exit status.\n\n\\- Searches preserve exact file and line references.\n\n\\- Logs preserve chronology, causal evidence, and outliers.\n\n\\- Anything omitted remains selectively retrievable.\n\nOptimized tool results are 75% smaller on average, while preserving signal.\n\nDevelopers keep working normally. Codag reduces what reaches the model before the model pays to read it.\n\nCodag also reports which tools and MCP servers agents invoke, along with tokens, model-adjusted spend, savings, reducer cost, and latency across providers. Because Codag already sits in the tool path, it becomes the natural place for companies to control which tools agents can use, under what policies, and at what cost.\n\n### Results so far\n\nMore than 90 organizations use Codag, including teams of up to 35 people. I built and sold the product solo.\n\n### Where this goes\n\nOur bet is that agent activity will grow faster than model prices fall. As companies give agents more tools, longer tasks, and production access, they will need infrastructure that reduces, measures, and controls agent tool use across every provider.\n\nCodag starts with compression. The larger opportunity is becoming the gateway through which companies understand and control how agents use tools.\n\n### The ask\n\nIf your team uses agents, check out [codag.ai](http://codag.ai), or contact me at [michael@codag.ai](mailto:michael@codag.ai)",
        "url": "https://www.ycombinator.com/launches/Sr5-codag-compression-and-control-for-agent-tools",
        "votes": 6,
        "created_at": "2026-08-16T18:44:00.099Z"
      }
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    "id": 32262,
    "name": "Alkera AI",
    "slug": "alkera-ai",
    "former_names": [
      "Alkera AI, Inc.",
      "Alkera AI",
      "Alkera AI, Inc."
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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",
    "launched_at": 1783697969,
    "tags": [
      "Developer Tools",
      "Data Science",
      "Data Engineering",
      "Enterprise Software",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 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,
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    "url": "https://www.ycombinator.com/companies/alkera-ai",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/alkera-ai.json",
    "year_founded": 2026,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/alkera-ai",
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    "primary_partner": {
      "name": "Ankit Gupta",
      "url": "https://www.ycombinator.com/people/ankit-gupta"
    },
    "founders": [
      {
        "user_id": 3652826,
        "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. ",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/rgao09",
        "x_url": "",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/515662055ce684fc796921959375d09b477afbfa.jpg"
      },
      {
        "user_id": 3406186,
        "full_name": "Tony Li",
        "title": "Founder/COO",
        "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.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/tonyli4722",
        "x_url": "",
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      },
      {
        "user_id": 3673412,
        "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.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/andrewtran-cs/",
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    "launches": [
      {
        "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"
      }
    ]
  },
  {
    "id": 32518,
    "name": "Agency Tool Company",
    "slug": "agency-tool-company",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/244ddf9b0965c4c601170d71dd660ad1a89f8792.png",
    "website": "https://agencytool.com",
    "all_locations": "Denver, CO, USA",
    "long_description": "Agency Tool Company ships software to robots in the field 20x faster than a Docker pull with ATC Deploy, sending only the bytes that changed and resuming when the network drops. Deployment tooling is the connection between the lab & the field that continually bottlenecks robotics scaling and lacks a strong robotics-native solution. Deploy is live today with 3 launch partners across ag, construction, and logistics robotics.\r\n\r\nOur second product, ATC Build, offers embedded-compute as a CI service so devs can run tests and validate their software on the actual target hardware. Build supports the Nvidia Jetson lineup, Raspberry Pi, and a number of other embedded platform targets.\r\n\r\nJack Morrison and Davis Foster founded and sold Scythe Robotics after deploying hundreds of autonomous mowers across the country; Agency Tool Company is building the robotics deployment platform across hardware and software they wish they had.\r\n\r\nLearn more at https://agencytool.com",
    "one_liner": "Reliable infrastructure to build, deploy and manage real-world robots.",
    "team_size": 3,
    "industry": "Industrials",
    "subindustry": "Industrials -> Manufacturing and Robotics",
    "launched_at": 1784914207,
    "tags": [
      "Developer Tools",
      "Robotics",
      "Automation",
      "Infrastructure",
      "Self-Driving Vehicles"
    ],
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2026",
    "status": "Active",
    "industries": [
      "Industrials",
      "Manufacturing and Robotics"
    ],
    "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/agency-tool-company",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/agency-tool-company.json",
    "year_founded": 2026,
    "city": "Denver",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/agency-tool-company",
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    "primary_partner": {
      "name": "Harshita Arora",
      "url": "https://www.ycombinator.com/people/harshita-arora"
    },
    "founders": [
      {
        "user_id": 3668961,
        "full_name": "Jack Morrison",
        "title": "Founder/CEO",
        "founder_bio": "Founder and CEO at Agency Tool Company. Previously founder/CEO at Scythe Robotics, building autonomous electric outdoor equipment from 2018-2026 and successfully exiting to ASI. Earlier co-founded Replica Labs (mobile 3D scanning) and worked as a computer vision engineer at Occipital on the Structure Sensor. BA Computer Science from Bowdoin.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/morrisonjack/",
        "x_url": "https://x.com/jackmorrison",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/13172ea12c502ccffb1824b2ef8e356abeabdfae.jpg"
      },
      {
        "user_id": 253511,
        "full_name": "Davis Foster",
        "title": "Founder",
        "founder_bio": "Founder at Agency Tool Company - making it easier to scale robots. Previously co-founded Scythe Robotics ('18-26), made autonomous commercial mowers, acquired by ASI in 2026. Built and shipped hundreds of robots still operating across the country. Thiel Fellow.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/davisfoster",
        "x_url": "https://x.com/davistfoster",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3b4566280f9b3ba7c4ea23beb319e78fbf6db999.jpg"
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    ],
    "jobs": [],
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    "launches": [
      {
        "id": 107934,
        "title": "Agency Tool Company: The build and deployment platform for robotics",
        "tagline": "Field Robots Faster with ATC Deploy",
        "body": "Today we're sharing Agency Tool Company and our first product, ATC Deploy: a faster, more reliable way to ship software to robots wherever they are. It moves updates up to 20 times faster than docker pull or scp and works with any software stack already in use.\n\n<https://www.youtube.com/watch?v=jx0rLRVa06s>\n\n## The updates that took until 2 a.m.\n\nDavis and I spent eight years building Scythe Robotics and putting hundreds of autonomous mowers to work across the country. For years, we deployed software with a tool I'd cobbled together for our first few robots. As the fleet grew, deployment became an ordeal: engineers stayed up until 2 a.m., we coordinated with customers to move robots out of sheds and into LTE coverage at set times, and failed transfers restarted from zero. Shipping a fix could take more coordination than building it. We had models to train and customers to serve, so the tooling limped along with incremental bandaids.\n\nWe've since heard the same story from robotics teams across industries. That deployment becomes a hidden bottleneck: teams become release-averse, feedback loops slow and improvements stall. Stitched-together web and IoT tools barely work if you know which scripts to run and who to call, so they survive, even if it means every update is distracting from improving the product.\n\n## What we built\n\nATC Deploy ships whatever you already run: OS images, Docker images, or any file tree. Run “atc ota push user@robot”, and it sends only the changed bytes, then restarts your software through hooks you define—way faster than a docker push.\n\nInstall takes one “curl | sh” command and a config file so you can get back to work fast. Interrupted transfers resume where they stopped, and an offline robot can receive updates by USB if you need. There's no new runtime, packaging format, or operating system to adopt.\n\n## Shipping to robots today\n\nATC Deploy already ships software to robots at Burro, which has deployed more than 750 machines worldwide, Tempo, polishing concrete across several US states and Canada, and Gather, who is scaling their 99.9% accurate inventory drones nationwide. Their teams spend less time managing delivery and more time improving the robot.\n\n**Operate a robot fleet? Join the ATC Deploy waitlist at [agencytool.com](https://agencytool.com/).** Know a team that should be using it? Send them this post, or to [mailbox@agencytool.com](mailto:mailbox@agencytool.com).\n\nIt's time to build robots.\n\n![uploaded image](/media/?type=post&id=107934&key=user_uploads/253511/2f53d874-b652-4819-b734-bd52256958d8)\n\n",
        "url": "https://www.ycombinator.com/launches/S4s-agency-tool-company-the-build-and-deployment-platform-for-robotics",
        "votes": 6,
        "created_at": "2026-07-28T15:54:16.451Z"
      }
    ]
  },
  {
    "id": 32527,
    "name": "machine0",
    "slug": "machine0",
    "former_names": [],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0eb24a85015d2fd30115c143876496fed0a17210.png",
    "website": "https://machine0.io",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "machine0 is a CLI for agent compute: `machine0 new mybox` gives your agent a full cloud VM, billed by the minute, from small up to 60 vCPU / 240 GB and 8×H100s. Agents drive it themselves via CLI or MCP.\r\n\r\nAgent workloads are moving from ephemeral to always-on. A coding agent working on a hard feature runs 6-8 hours. Auto-research agents run for days. machine0 is the environment in which these agents run.",
    "one_liner": "AWS for Agents",
    "team_size": 1,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
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        "title": "machine0: Cloud computers for AI agents",
        "tagline": "One command spins up a persistent VM. Your agent drives it via CLI or MCP, building its own fleet from 1 vCPU up to 60 vCPU / 240 GB and 8×H100s.",
        "body": "TLDR: machine0 is a CLI for agent compute: “machine0 new mybox” gives your agent a full cloud VM, billed by the minute, from $0.013/hr up to 60 vCPU / 240 GB and 8×H100s. Agents drive it themselves via CLI or MCP.\n\n<https://www.youtube.com/watch?v=gyllkZ0M04E>\n\n## The Pain\n\nAgent workloads are moving from ephemeral to always-on. A coding agent working on a hard feature runs 6-8 hours. Auto-research agents run for days. OpenClaw &amp; Hermes run 24/7. As you run more in parallel:\n\n* **Resources**: a few agents on a big codebase saturate your RAM and CPU. Auto-research needs GPUs you don't have.\n* **Security**: “—yolo” on your personal machine is one prompt injection away from exfiltrated credentials.\n* **Availability**: close your laptop and the agent dies mid-task.\n* **Isolation**: there's no clean line between everything on your laptop and the minimum this agent actually needs.\n\n## The Solution\n\nmachine0 gives every agent its own computer. It's a CLI that both humans and agents can use without reading docs:\n\n* “machine0 new mybox” creates an SSH-ready VM with a static IP and HTTPS endpoint. Always on (99.99% uptime) until you switch it off.\n* **Billed by the minute.** 1 vCPU / 1 GB at $0.013/hr up to 60 vCPU / 240 GB, plus GPUs from RTX 4000 Ada to 8×H100s.\n* **Profiles.** Bundles of MCP connections, credentials, prompts, and env vars, injected at VM creation. Each agent gets exactly the capabilities (or personality) you choose, and nothing else.\n* **Agents self-serve.** Hand the CLI or MCP server to Claude, Codex, or OpenCode and it manages its own fleet: spin up a box for a build, snapshot it, tear it down.\n* **Suspend &amp; resume.** Pause an idle machine, stop paying for compute, resume exactly where it left off.\n* **Snapshot &amp; clone.** Configure one machine perfectly, then stamp out ten identical agents from it.\n* **NixOS is first-class.** Declarative, reproducible machines.\n\n## How people use it\n\n* **Compute for your agent**: give it the CLI and it spins up its own VMs for builds, tests, and long jobs instead of grinding your laptop.\n* **Hosting the agent itself**: run Claude, Codex or Hermes 24/7. Snapshot once, then clone as many as you want.\n* **Swarms of agents**: an orchestrator agent spawns worker machines, farms out subtasks, and tears them down when the work is done.\n* **Auto-Research on GPUs**: drop an agent on an H100 with a goal and let it run for days.\n\n## About me\n\nI'm a solo, second-time YC founder. I was CTO of Upflow (YC W20), where I scaled EPD post series A and personally owned DevOps, infra, and security for years because they were too high-stakes to delegate. Upflow handles sensitive accounting data for companies like Postman, ProductBoard, and Lattice, and is doing many millions in ARR.\n\nBefore that I built consumer payments at Hike Messenger (100M+ users) in India. Working with sensitive data and infra for years is what got me deep into the problems machine0 solves, security especially.\n\n## Asks 🙏\n\n* Try it: <https://machine0.io>\n* Let's talk about your agent fleets, software factory or auto-research: [hello@machine0.io](mailto:hello@machine0.io)",
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        "title": "Graphify Labs: Knowledge Graph Engine for Enterprises 🧠",
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        "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",
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        "title": "Inkbox: Give your AI agents email, phone, iMessage, and an internet address",
        "tagline": "The identity and communication layer for AI agents",
        "body": "**TL;DR:** Inkbox is the identity and communication layer for AI agents: giving agents their own email, phone, iMessage, and internet address. Inkbox pulls together what your agent sees across email, calls, iMessage, and more, so your agent can act on the full context.\n\nHey YC! We're Ray, Alex, and Dima building Inkbox.\n\n**How we got here**\n\nA few months ago we were building web-automation agents. Every time an agent needed to log into a portal, it had to receive a confirmation email or get a 2FA code. And when we were away from our desks, we wanted to seamlessly contact the agents themselves: text them, check in, get a reply. We ended up stitching together services like Gmail, Twilio, and ngrok: separate services, each built for humans, none of them sharing any identity or context. \n\nThat's the problem we set out to fix. We didn't need another email or voice API. We needed one service to tie its identity together with rich context. So we built it.\n\n[**Launch video**](https://www.youtube.com/watch?v=oJKl6tPHxRA)\n\n**What Inkbox does**\n\nOur API gives every agent:\n\n* A unique email inbox (+ custom domain)\n* A phone number that can call and text\n* iMessage\n* A persistent internet address (HTTPS tunnel) to receive internet traffic, like webhooks\n* An encrypted credential vault with TOTP/2FA\n\n**Who we are**\n\n* Ray (CEO): CS PhD from MIT; previously cofounded Empallo, an AI virtual clinic for cardiovascular patients.\n* Alex (CTO): MS in CS @ Northeastern. Previously ML engineering and computer networking research.\n* Dima (CAIO): built ML pipelines on gigapixel pathology images at Harvard Medical School; co-author on 6+ peer-reviewed publications.\n\n[**Quick demo with Claude**](https://www.youtube.com/watch?v=MTVkW_EG-Y4): Watch Claude Code provision an email, phone, and iMessage in a Minute.\n\n**Our ask**\n\n* **Try it**. Drop Inkbox into your preferred agent harness: we have plugins for[ Hermes](https://github.com/inkbox-ai/hermes-agent-plugin),[ OpenClaw](https://github.com/inkbox-ai/openclaw-plugin),[ Claude Code](https://github.com/inkbox-ai/claude-code-plugin), and[ Codex](https://github.com/inkbox-ai/codex-plugin). Each one runs a wizard that provisions Inkbox resources for your agent.\n* **Ask your agent to self signup**. _Sign up for an Inkbox email account by following the guide at[ https://inkbox.ai/docs/get-started/agent-signup.md](https://inkbox.ai/docs/get-started/agent-signup.md) and refer to[ https://inkbox.ai/llms.txt](https://inkbox.ai/llms.txt) for full documentation._\n* **Intros**. We'd love intros to teams running fleets of agents that each need their own identity to act in the real world: reaching out to people and businesses (email/phone/iMessage), holding their own accounts, and authenticating with a built-in credential vault.\n\nContact Ray at [ray@inkbox.ai](mailto:ray@inkbox.ai). Would love your feedback.",
        "url": "https://www.ycombinator.com/launches/RIu-inkbox-give-your-ai-agents-email-phone-imessage-and-an-internet-address",
        "votes": 21,
        "created_at": "2026-07-08T00:25:54.653Z"
      }
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  },
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    "id": 33019,
    "name": "Agnost AI",
    "slug": "agnost-ai",
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    "website": "https://agnost.ai",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Agnost AI reads every conversation a company's AI Agent has with its users to find where it's silently failing and then turns that same data into custom models that run the agent better, faster & cheaper than frontier models.",
    "one_liner": "We find where AI agents fail, then train better models to run them.",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Analytics",
    "launched_at": 1783481375,
    "tags": [
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      "Machine Learning",
      "Analytics",
      "Monitoring",
      "AI"
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    "isHiring": false,
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    "batch": "Summer 2026",
    "status": "Active",
    "industries": [
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      "Analytics"
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    "regions": [
      "United States of America",
      "America / Canada"
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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/agnost-ai",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/agnost-ai.json",
    "year_founded": 2025,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://linkedin.com/company/agnostai",
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    "primary_partner": {
      "name": "Tyler Bosmeny",
      "url": "https://www.ycombinator.com/people/tyler-bosmeny"
    },
    "founders": [
      {
        "user_id": 1987056,
        "full_name": "Shubham Palriwala",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder and CEO of Agnost AI.\nYoungest Engineer on Cisco's Analytics team, First Hire at Formbricks (Open-Source Qualtrics), wrote code in Bitcoin & other open-source projects across OWASP and the Linux foundation.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/shubhampalriwala/",
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      },
      {
        "user_id": 2055517,
        "full_name": "Parth Ajmera",
        "title": "Founder/CTO",
        "founder_bio": "Co-Founder/CTO at Agnost AI. Graduated in Computer Science from IIT Madras, ranking 159 among over 1 million candidates. Previously led graphics engineering at Infurnia and built terabyte scaled data pipelines at Microsoft",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/parthajmera/",
        "x_url": "https://x.com/prrthh132",
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    "jobs": [],
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    "launches": [
      {
        "id": 111310,
        "title": "Agnost AI: Turn Your Agent Traces Into a Faster, Cheaper, & more Accurate Custom Model",
        "tagline": "We use your agent’s production traces to train a specialized model that performs better, responds faster, and costs less.",
        "body": "Your agent logs aren’t just for debugging. They’re your training data.\\\nHey YC! We’re Shubham and Parth, childhood friends and founders of Agnost AI.\n\n**TL;DR**: Agnost AI uses your agent’s production traces to train a model specialized for your exact workload. Our first custom model for our customer delivered them a:\n\n* 22.9% higher task success,\n* 90.2% lower median latency, and\n* 94.5% lower cost than Opus 4.8.\n\nDemo: <https://youtu.be/R3NyWNYXHu4>\n\n### What we found\n\nA few weeks ago, we launched Agnost AI as product analytics for AI agents. We read conversations between users and agents to uncover failures, behavior drift, hallucinated links, frustration, and churn signals.\n\nWe expected to find bugs. Surprisingly, we also found a lot of infrastructure waste. Many customer-facing agents use frontier models for narrow, repetitive jobs:\n\n* Route a request to the correct tool\n* Have a narrow system prompt with the given inputs\n* Retrieve the relevant data from internal tool calls\n* Parse &amp; format the final response\n\nThe underlying frontier model can write code, solve advanced mathematics, understand biology, and reason across hundreds of domains. **Your agent uses a small, repeatable slice of that capability while paying frontier-model prices for every request.**\n\n### We trained a specialist\n\nWe used historical production traces to train our first workload-specific model for an early customer: **agnost-&lt;redacted>-0.1**\n\nWe evaluated it against Opus 4.8 on 780 held-out customer traces for an Identifier Extraction Agent. The results:\n\n* Task success: 71.5% → 87.9%, 22.9% relative improvement\n* Median latency: 4.80s → 0.47s, 90.2% lower\n* Tail latency: 11.20s → 1.35s, 87.9% lower\n* Cost per 1,000 completed tasks: $42.00 → $2.30, 94.5% lower\n\nThis is one model for one workload, not a claim that specialist models should replace frontier models everywhere.\n\nFrontier models remain the right choice for open-ended work. But once an agent’s production job becomes predictable, **paying for general intelligence on every request stops making sense**.\n\n### How it works\n\n1. Send your existing traces to Agnost through OpenTelemetry or our SDK.\n2. We identify the recurring workflows your agent performs.\n3. We create an eval set from held-out production traces.\n4. We train a specialist model on the historical workload.\n5. We benchmark it against your current model on success, latency, and cost.\n\nYou only consider switching when the specialist wins on your own workload. Your logs go from debugging data to evaluation data and finally to training data recursively.\n\n### Who we are\n\nWe’re childhood friends, eight years and counting.\n\n* Shubham: Youngest engineer on Cisco’s analytics team, first hire at Formbricks, and contributor to Bitcoin, OWASP, and the Linux Foundation.\n* Parth: IIT Madras CS, ranked 159 out of 1.5 million. Built Spark pipelines at Microsoft and led GPU technology at Infurnia.\n\n### Our ask\n\nIf you have meaningful daily traffic, send us an anonymized trace export. We’ll analyze the workload, build a held-out evaluation set, and tell you whether a specialist model is worth training. If it is, we’ll benchmark it against your current frontier model.\n\nEmail me at [shubham@agnost.ai](mailto:shubham@agnost.ai) or book a call at [call.agnost.ai](http://call.agnost.ai)\n\nMore about us at: [agnost.ai](https://agnost.ai)\n\n![uploaded image](/media/?type=post&id=111310&key=user_uploads/1987056/6599ed29-ddf9-4d02-9232-425af1535be7)\n\n",
        "url": "https://www.ycombinator.com/launches/SxK-agnost-ai-turn-your-agent-traces-into-a-faster-cheaper-more-accurate-custom-model",
        "votes": 97,
        "created_at": "2026-08-20T16:00:00.252Z"
      },
      {
        "id": 107260,
        "title": "Agnost AI: Product Analytics for AI Agents",
        "tagline": "We read every conversation your users have with your agents & chatbots and surface hidden insights & product feedback. We are working with teams at Google, Exa and Corgi",
        "body": "**Your users are telling your agent exactly why they churn! You’re not listening.**\n\nHey YC! We’re Shubham and Parth, childhood friends, founders of **Agnost AI**.\n\n**TL;DR: Agnost AI reads every conversation your chat or voice agent has with your users. We show you what your users want, where they get frustrated, and why they leave.**\n\n**The feedback hiding in your logs becomes discoveries, evals, and fixes ready to ship. We’re already processing over 1 million events every day and growing.**\n\nTry us out at[ agnost.ai](http://agnost.ai)\n\n### <https://www.youtube.com/watch?v=gKyhf6rUELg>\n\n### **The problem**\n\nTraditional product analytics were built for clicks.\\\nObservability was built for token costs, latencies, and deterministic errors.\n\nBut every product is rapidly moving from UI to conversation, and agent failures don’t look like traditional failures. The LLM returns 200 OK and says “sorry, I can’t do that.” The real failures are hiding in your conversations:\n\n* “can it remember this for next time?” → feature request\n* “you said it’s done, but nothing happened” → bug\n* “i’ve told you this three times already” → frustration\n* “nvm i’ll just do it myself” → churn\n\nToday teams throw more evals at this. But evals only tell you whether you fixed something, not what to fix. You can’t write a test for a problem you haven’t discovered yet.\n\n### **How it works**\n\n1. **Install our skill:** 3 lines of code, or point your OpenTelemetry exporter at us. Any LLM, any framework. Add any custom metadata like user tier, model versions, etc. We’re at:[ docs.agnost.ai](http://docs.agnost.ai)\n2. **Every conversation becomes a signal:** feature requests, bugs, frustration, churn risk, failed upgrades. Detected for your product, with the exact users &amp; conversations behind each.\n3. **The insight becomes action:** when hundreds of users rageprompt at your agent due to a specific bug, Agnost AI hands you the insight with the exact conversations behind it: \n   * create an eval from it\n   * debug it,\n   * or let Agnost fix it itself: our GitHub app opens a PR, tested against your past conversations, so you know it works before it ships.\n\n   Your agent gets better every week.\n\n### **Who we are**\n\nChildhood friends, 8 years and counting.\n\n![uploaded image](/media/?type=post&id=107260&key=user_uploads/2055517/e3c2eaad-8b6e-4ec0-abfa-b16074688963)\n\n**Shubham**: Youngest engineer on Cisco’s analytics team, First Hire at Formbricks, Wrote code in Bitcoin, OWASP, and the Linux Foundation.\n\n**Parth**: IIT Madras CS (ranked 159 of 1.5M), built Spark pipelines at Microsoft, Led GPU tech at Infurnia (\\~$1M ARR).\n\n### **Our Asks**\n\n1. **Building a chat or voice agent?** Sign up &amp; I’ll personally find 3 insane things going on in your agent traces that you’d have no idea about.\n2. **Know a founder whose product is an agent?** Intro us, 40’ monitors (to monitor your agents) on us: [shubham@agnost.ai](mailto:shubham@agnost.ai)\n3. **Try it:** Free tier:[ agnost.ai](http://agnost.ai)",
        "url": "https://www.ycombinator.com/launches/Ru0-agnost-ai-product-analytics-for-ai-agents",
        "votes": 191,
        "created_at": "2026-07-24T15:53:30.811Z"
      }
    ]
  },
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    "id": 33051,
    "name": "Tokenless",
    "slug": "tokenless",
    "former_names": [
      "Tokenless",
      "Touchy"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7f250ec6cc81104148d8bd5bafdd6b96bc77d023.png",
    "website": "https://usetokenless.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Tokenless is an applied AI research lab. Our goal is to end reward hacking. We do research and build tools to detect issues with environments and evals, understand model behavior in those environments, and prevent those issues from happening. Correcting them makes training more effective, makes model performance easier to interpret, and is crucial to solving the AI alignment problem.\r\n\r\nIf you’re training models with RL, building environments, or running agent evals, and want more confidence in your environments, we're here to help.",
    "one_liner": "We find flaws in RL environments and evals and help you fix them.",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1786732497,
    "tags": [
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      "Machine Learning",
      "Reinforcement Learning",
      "B2B",
      "AI"
    ],
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    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2026",
    "status": "Active",
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      "Infrastructure"
    ],
    "regions": [
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      "America / Canada"
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    "stage": "Early",
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    "url": "https://www.ycombinator.com/companies/tokenless",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/tokenless.json",
    "year_founded": 2026,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/usetokenless/",
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    "primary_partner": {
      "name": "Vivian Midha Shen",
      "url": "https://www.ycombinator.com/people/vivian-midha%20shen"
    },
    "founders": [
      {
        "user_id": 3697324,
        "full_name": "Rohit Agarwal",
        "title": "Founder",
        "founder_bio": "Founder at Tokenless (YC S26). CS PhD student at Princeton PLI, Hazan Lab, Google Deepmind. Previously at Duolingo and theory research at Berkeley, was EECS #1 BS grad in 2024.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/rohit-agarwal-b647951ba/",
        "x_url": "https://x.com/Rohit_Writes",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/86b74b1209c81d1d158af5587de149a3e8c2292c.jpg"
      },
      {
        "user_id": 3706728,
        "full_name": "Andrew Liu",
        "title": "Founder",
        "founder_bio": "Founder at Tokenless (YC S26). Formerly a researcher at UC Berkeley working on language documentation tools. BA in Computer Science, Mathematics, and Linguistics from UC Berkeley. Previously TA'd CS61C.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/andrew-liu-b50873261/",
        "x_url": "https://x.com/landrew7363",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/04017660afe1efc138b242cbcc7c4efffc5f5bc4.jpg"
      },
      {
        "user_id": 3732665,
        "full_name": "Kevin Wang",
        "title": "Founder",
        "founder_bio": "Founder at Tokenless. Prev MTS at SkyPilot building multi-cloud GPU infra for top neolabs, Founding Engineer at Eventual from seed to Series A building the data engine for physical AI, EECS at UC Berkeley.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/kevinzhiwang/",
        "x_url": "https://x.com/kevzwang",
        "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1a21a2cf6802cfdcf6769408ee9d25a254858622.jpg"
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    "launches": [
      {
        "id": 111407,
        "title": "Touchy 🙌: Voice-first AI Assistant for iPhone that understands the world around you",
        "tagline": "Your personal AI assistant that sees what you see, remembers what matters to you, and gets things done across all your tools. Just ask out loud.",
        "body": "**TL;DR:** We’re building Touchy 🙌, a voice and image-first AI assistant for the iPhone that personalizes itself to you. You can activate Touchy from your lock screen to instantly get things done across your apps or get answers about the world around you. Touchy is free to try, get it here: <https://apps.apple.com/us/app/touchy-ai-at-your-fingertips/id6798889392>\n\n<https://youtube.com/shorts/IJNucvAZ_-k>\n\n## **The Problem**\n\nYou probably know the feeling:\n\nYou ask the assistant on your phone, across the room, to send a colleague a message.\n\nIt cheerfully replies that it found 10 search results for “text Bob on Slack”.\n\nSo you trudge to your phone, find the app, open the DM, and begrudgingly type out your message instead.\n\nWe wanted a better personal assistant, one that had the intelligence and integrations we’ve come to expect from our AI agents, with the convenience of one that was native to your devices. We also believe that for AI to truly be personal, it needs to be deeply integrated into your life and the world around you. Right now, AI systems are constrained largely to using digital tools, yet the physical world is rich with audio and visual information that your phone is capable of receiving.\n\n## What We Built\n\nSo we built Touchy. One button press and you're instantly talking to an assistant that can see what you see, remember what you've said, and take action across all the tools you use. \n\nWhat sets Touchy apart:\n\n* **Reimagined UX.** Touchy is a fast, fully iOS-native app with a unique interface that is delightful to use and brings it closer to the world around you.\n* **Sees and hears the world around you**. Speak to Touchy and it can speak back. Easily snap a photo with the app’s camera to give Touchy access to what you’re seeing.\n* **Gets things done across your apps**. Touchy comes with built-in integrations with 1,000+ popular apps, as well as iOS-native capabilities such as you contacts and location.\n* **Make it yours over time**. You chat with Touchy in a single, continuous conversation. It automatically collects memories and preferences, and tailors itself to be more useful to you as you use it.\n\nIt's built to give you your attention back. Ask it something, let it act, and get back to your day — no app fighting for your attention.\n\n![uploaded image](/media/?type=post&id=111407&key=user_uploads/3697324/23ce7916-fce5-44c4-9ebf-f04049fee639)\n\n## The team\n\nWe’re Rohit, Andrew, and Kev. Before this, Rohit was doing a PhD on AI alignment at Google DeepMind Princeton and graduated #1 in Berkeley EECS. Andrew built educational software that scaled to half a million students worldwide. Kev was a startup founding engineer, developing data and GPU infrastructure that power many of the leading AI neolabs today. \n\nWe met during undergrad at UC Berkeley, and we’re coming back together to research, productionize, and scale the future of personal technology.\n\n## Our ask\n\nIf you have an iPhone, download Touchy and try it out: <https://apps.apple.com/us/app/touchy-ai-at-your-fingertips/id6798889392>\n\nWe would love to learn what people find themselves using Touchy for, and what they wish they could use it for. You can also report bugs by shaking your phone or just telling Touchy. You can also reach us at [founders@touchyapp.com](mailto:founders@touchyapp.com)",
        "url": "https://www.ycombinator.com/launches/Syt-touchy-voice-first-ai-assistant-for-iphone-that-understands-the-world-around-you",
        "votes": 24,
        "created_at": "2026-08-20T21:00:00.530Z"
      }
    ]
  },
  {
    "id": 33177,
    "name": "HyperProbe",
    "slug": "hyperprobe",
    "former_names": [
      "HyperTest inc"
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b4b91e0b78bbed1c83add57d22b06ab632567450.png",
    "website": "https://hyperprobe.co",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "With tools like Cursor and Claude Code, writing software is no longer the bottleneck. Debugging is. Agents cannot fix production crashes using logs and traces that were sized for human eyeballs. The gap is missing data.\r\n\r\nHyperProbe allows agents to debug live software autonomously. Our SDK drops non-breaking probes straight into running services to read exact variable states from memory at the moment of failure, instead of reasoning backwards from flat logs.\r\n\r\nZero redeploys. Under 1% CPU overhead. Automatic PII redaction.\r\n\r\nWe turn 4-hour production war rooms into 10-minute automated resolutions. As agents write and operate more of the world's software, HyperProbe is the runtime observability layer that lets them understand what they built.\r\n\r\n",
    "one_liner": "AI engineer that debugs and fixes production incidents in realtime",
    "team_size": 8,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1783455456,
    "tags": [
      "AIOps",
      "Developer Tools",
      "SaaS",
      "DevOps",
      "AI"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2026",
    "status": "Active",
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    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Partly Remote"
    ],
    "stage": "Early",
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    "app_answers": null,
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    "url": "https://www.ycombinator.com/companies/hyperprobe",
    "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/hyperprobe.json",
    "year_founded": 2026,
    "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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      {
        "user_id": 3173209,
        "full_name": "Shailendra Singh",
        "title": "Founder/CEO",
        "founder_bio": "Founder at HyperProbe. Also founded HyperTest. Previously headed and scaled engineering and product functions at a unicorn and few small startups.",
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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",
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        "created_at": "2026-08-17T15:30:20.732Z"
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "Autoresearch helps teams train agents for tasks where general models are not good enough. Give us a task, your current agent or model, and an evaluation. Autoresearch runs an autoresearch campaign across data, SFT and other post-training methods, continual learning, prompts, tools, harnesses, and systems, then returns the best verified improvement. It runs hosted or in your cloud.\r\n\r\nWe provide the research system around models: persistent memory, full experiment lineage, compute orchestration, and statistical verification. We’re starting with agent and model training, continual learning, and optimization.\r\n\r\nReach out to us for early access at founders@autoresearch.inc.",
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    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
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        "full_name": "Karan Brar",
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        "full_name": "Thomas Boser",
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        "founder_bio": "Founder at Autoresearch, Inc. Previously engineer at Reducto, founding engineer at Crosswise, senior ML engineer at Discord, ML at Sentropy & SoFi.",
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        "title": "hiloop: we run thousands of experiments to improve your models",
        "tagline": "Send us a hard task, your model or agent, and an eval. We run the research campaign and return a verified improvement.",
        "body": "We're Karan and Thomas, and we're building hiloop: **infrastructure for automated research**.\n\n**TL;DR: we gave two stock coding agents 50 B200s and our infra. They ran 4,188 experiments in two days and beat the published state of the art on [Karpathy's autoresearch benchmark](https://github.com/karpathy/autoresearch). The same machinery found a [NanoGPT speedrun](https://app.primeintellect.ai/speedrun/nanogpt) candidate that beats the best known result. [See](https://hiloop.ai/blog/search-is-enough/) full writeup.**\n\nNow we want to point it at your hardest problems.\n\n![uploaded image](/media/?type=post&id=108337&key=user_uploads/1714115/63396f7f-3e21-41ea-83ea-54cbaaa9f63f)\n\n**The results**\n\nOn Karpathy’s autoresearch benchmark, our final recipe reached **0.9016 val_bpb**. The previous best published result was [Recursive’s 0.9109](https://www.linkedin.com/pulse/first-steps-toward-automated-ai-research-recursive-si-kybtc) on B200 hardware. For NanoGPT, our implementation had **12.54% lower runtime** than upstream.\n\nThere was no bespoke research agent or elaborate scaffold. We used Claude and GPT-5.5 out of the box. What changed was the system around them.\n\n**What hiloop does**\n\nGive us a hard task, your current agent or model, and an evaluation criteria. Hiloop runs an autoresearch campaign across training, data, prompts, tools, harnesses, and systems, then returns the best verified improvement. It runs in your cloud or hosted by us.\n\nWe’re starting with agent and model training: SFT, post-training, continual learning, and optimization.\n\n[https://drive.google.com/file/d/1Rv8HttSHZ-yvSJk6hsWQsqCXWTHJQogK](https://drive.google.com/file/d/1Rv8HttSHZ-yvSJk6hsWQsqCXWTHJQogK/view?usp=sharing)\n\n**Who we are**\n\nWe met at Reducto, where we built its ML, post-training, and platform systems. Karan previously led ML infrastructure at DynamoAI . Thomas was a founding engineer at Crosswise and an MLE at Discord and SoFi.\n\n**Two asks**\n\n1. **Want your models or agents better, faster, or cheaper?** If you have a hard objective in post-training, continual learning, inference optimization, or classic ML, send us the task, your baseline, and the eval. We’ll personally run a campaign with you through verified improvement.\n2. **Building autoresearch or RSI loops?** Reach out to give our system a try! We’d love to compare notes.\n\nEmail [**founders@hiloop.ai**](mailto:founders@hiloop.ai) to get in touch with us!",
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    "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",
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        "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. ",
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        "full_name": "Rishov Sarkar",
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        "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.",
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      {
        "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": 33838,
    "name": "Simantic",
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    "website": "https://simantic.com",
    "all_locations": "Waterloo, ON, Canada",
    "long_description": "Simantic is modernizing the embedded firmware industry with hardware simulation developed for the adoption of AI in hardware engineering. Simantic gives both humans and AI the visibility into hardware previously limited by the physical world.",
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    "team_size": 4,
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    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1782327485,
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        "body": "Hi all 👋, We’re Michael and Charles, founders of Conifer.\n\n**TLDR:** Conifer is one interface for both local and cloud models, available today as **Juniper**, our consumer-facing app. It routes each request to the most cost-effective option, beginning with your own hardware. Most requests are processed locally without API fees, reducing paid token volume by up to 80%.\n\n**📺 Launch Video:**[ https://www.youtube.com/watch?v=QLVNISmtet0](https://www.youtube.com/watch?v=QLVNISmtet0)\n\n**❓ The problem**: Model labs direct every request to the cloud, with no incentive to route your queries to a cheaper competitor or a free, on-device model. That may benefit them, but it’s unnecessarily costly for you. Whether it’s a simple typo fix or a complex architecture problem, the request is sent to a data center, exposing your data to third parties and increasing your monthly spend. This quickly adds up for teams running coding agents, customer support, and other high-volume workloads. When handling financials, patient records, or customer data, teams must also trust that a cloud provider’s security is as robust as promised.\n\n![uploaded image](/media/?type=post&id=105897&key=user_uploads/3664042/6dbc9654-b4df-453d-a02e-3ea71302316d)\n\n**🔨 What Conifer does:** Conifer routes every request from the bottom up:\n\nTier 0: Your own hardware, with $0 in API fees\n\nTier 1: An efficient cloud model\n\nTier 2: A frontier model for the most demanding queries\n\nThe majority of requests are processed locally, ensuring that cloud pricing applies only when actually necessary, drastically reducing paid token volume. Additionally, Conifer consolidates disparate subscriptions, dashboards, and API keys within a single unified interface.\n\nFor sensitive workloads 🕵️, **local-only mode** disables cloud routing entirely, so all conversations and data remain completely on-device.\n\n🏃‍♂️ **Ensuring the local tier is fast enough:** This routing only works if the local tier is reliable, so we built Conifer's inference engine from the ground up in Rust. On Apple Silicon, decode speeds reach up to 60% faster than llama.cpp.\n\n![uploaded image](/media/?type=post&id=105897&key=user_uploads/3664042/79b464dc-667b-48af-a1ba-5cdd089b1dc8)\n\nOn-device operation with Conifer is now the default starting point for inference, rather than a feature limited to hobbyist use.\n\n**Asks:**\n\n1. Try Juniper with a one-click download @[ conifer.build](http://conifer.build), or reach out to us at [contact@conifer.build](mailto:contact@conifer.build) to have a model running in under two minutes.\n2. Introduce us to teams with high monthly token spend. If teams are incurring significant API costs and want to optimize unit economics without rebuilding their stack, we would like to connect.",
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        "title": "Agent37: Host any agent harness",
        "tagline": "Agent sandboxes that are 94% lower compute cost ",
        "body": "Hi everyone, I'm Vishnu, founder of Agent37.\n\n**TL;DR:** Agent37 hosts any agent harness (Hermes, OpenClaw, Claude Code, Codex, or your own) so you can give each customer their own agent in an isolated sandbox, for over 95% less than most sandbox providers charge.\n\n![uploaded image](/media/?type=post&id=117160&key=user_uploads/316679/28b659ef-29c9-4364-849c-04dc75b73de9)\n\n\\\n**The problem**\n\nEvery team building an AI agent product needs the same thing underneath it: a private, always-on computer for each agent that keeps its files, wakes when someone messages it, and costs almost nothing while idle. Today there are two ways to get one, and both are bad.\n\nSome teams do it by hand. Chris Nguyen at ETEC+ used to spin up a VPS with a Hermes agent on it for each client and email it over, more than 30 times. Others build it themselves. Wes Merrill at Boon spent close to six months building a provisioning pipeline on Render. In his words: \"it was not fun.\"\n\nEither way, the time goes into plumbing instead of the product.\n\n**What we built**\n\n* Pick a template for any popular agent harness, or bring your own Docker image.\n* Each agent gets its own sandbox with persistent files, a browser, and Gmail, Slack, Notion, GitHub and 1,000+ other apps through Composio.\n* Every customer's agent is fully isolated from everyone else's.\n* Billing is per minute. An idle sandbox only costs its disk.\n* Our open-source starter kit is a white-label app with sign-up, an agent per customer, chat, files and integrations. Rebrand it and launch your own Instinct-style product in your niche.\n\n**What customers have done with it**\n\nBoon writes grant applications for nonprofits. They gave every client their own Hermes agent in 3 days. Their cost per agent went from $85/month to $4.94/month on equivalent hardware.\n\nETEC+ builds agents for Australian support, sales and ops teams. Chris's brief going in: \"Ideally I just want to sell, and not do any backend.\" Six days after picking up our starter kit, they had a branded product where clients sign up, pay, and get an always-on agent, and they moved their 30+ existing clients onto it.\n\n**Our ask**\n\nIf you've built an agent that works and you want to sell it to more than one customer, try us at [agent37.com](http://agent37.com). You get $2,500 in sandbox credits, worth over $50,000 of uptime on most other sandbox providers. And if you know someone who could use this, please send them our way.\n\n**About us:** Our goal is to make running agents affordable for everyone in the world. ",
        "url": "https://www.ycombinator.com/launches/UTg-agent37-host-any-agent-harness",
        "votes": 7,
        "created_at": "2026-09-29T17:00:00.120Z"
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    "id": 34928,
    "name": "Boat",
    "slug": "boat",
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    "website": "https://boat.dev",
    "all_locations": "Paris, Île-de-France, France; Remote",
    "long_description": "**Problem**\r\n\r\nHumans used to need laptops to do their work. Now they prompt agents instead, and those agents need computers too: always-on, in large quantities, and with unlimited capabilities. \r\n\r\nBuilding and maintaining that yourself is far from trivial.\r\n\r\n**Solution**\r\n\r\nBoat provides powerful, simple, permissive Ubuntu VMs in the cloud. In a sandbox, an agent can work for long periods on code or on knowledge work like legal, research, reporting, and auditing.\r\n\r\n**Why Boat and not any other cloud VM?**\r\n\r\n1. It is ready out of the box: every sandbox ships with a desktop, chrome, languages, docker, snapshots, and templates, plus a CLI, SDK, API, and control pane for your fleet.\r\n2. It is permissive and paradigm agnostic: any number of agents can use any number of sandboxes. Agents can run inside or use sandboxes as an external tool.\r\n3. It is expertly crafted: we manage everything from the individual CPU to the orchestration software, which makes sandboxes stable, persistent, scalable, and secure.\r\n4. It is the best performance and price in town: our CPUs rank first on HPC benchmarks, and sandboxes are typically 9x to 18x cheaper than other leading sandboxes.\r\n\r\n**Further notes**\r\n\r\nSandboxes are hosted in Europe, which keeps prices low, and more regions are coming. Unless compliance requires it, agents don't notice the region they run in.",
    "one_liner": "The best cloud VMs for billions of agents",
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    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
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    "year_founded": 2024,
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    "country": "FR",
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        "user_id": 918787,
        "full_name": "Anicet Nougaret",
        "title": "Founder/CEO",
        "founder_bio": "Founder at Ascii",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/anicet-nougaret-b7846b174",
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        "full_name": "Kirill",
        "title": "Founder/CTO",
        "founder_bio": "co-founder @ ascii.dev",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/luaroncrew/",
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    "id": 35126,
    "name": "Armorer Labs",
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    "website": "https://armorerlabs.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Armorer helps companies in regulated industries ship their own AI agents faster and keep them secure in production.\n\nMost security tools flag an issue and file a ticket. Armorer assesses your agent and simulates attacks to find the real issues. Then it creates a verified fix that stops the attack without breaking the business, ready for your approval in about 4 hours.\n\nIn production, Armorer checks every agent action in milliseconds, with no GPU needed. It detects malicious behavior such as prompt injection, goal hijacking and data leaks, then allows, holds or denies the action.\n\nArmorer's detection models beat every other detector we tested on six public benchmarks. Armorer is 22% more accurate than JEV while being 88x faster, so users won't feel the delay.\n\nWe spent years building and evaluating AI security systems together at AWS, including its first customer-facing AI security agent, which scaled to 100k+ customers. Armorer is backed by Paul Vixie, Internet Hall of Fame inductee and former AWS Deputy CISO.",
    "one_liner": "Continuous security verification for AI agents in regulated industries",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Security",
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    "year_founded": 2026,
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    "country": "US",
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        "full_name": "Daniel Begimher",
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        "full_name": "Cristian Leo",
        "title": "Founder/CTO",
        "founder_bio": "Co-Founder of Armorer Labs (YC F26). Led AI security science at AWS, building and evaluating AI systems for security.\n\nHe is the creator of ThreatForest, the first open source automated threat modeling agent, and a co-author of SIR-Bench, a benchmark for evaluating AI security investigations. He is a Black Hat and re:Invent speaker.",
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        "linkedin_url": "https://www.linkedin.com/in/cristian-leo",
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    "id": 35258,
    "name": "Mirrors",
    "slug": "mirrors",
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    "website": "https://www.mirrors.dev",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Production agents handle many different customer workflows. Currently, when one handles a situation badly, an engineer reads the trace and patches the prompt. The next situation needs another exception. Soon, improving the agent becomes a recurring engineering job, and the prompt keeps growing.\r\n\r\nMirrors finds patterns in past runs. Engineers review guidance for a specific situation and preview where it would apply. Mirrors then delivers that guidance while the agent works, inside the team’s existing setup. The team can check whether the change improved the outcome.\r\n\r\nWe’re building Mirrors for engineering teams running customer-facing agents across varied workflows, so they can improve behavior without hardcoding every lesson in the global prompt.",
    "one_liner": "Give AI agents the right context at the right moment",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1789011304,
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    "stage": "Early",
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    "year_founded": 2026,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/runmirrors/",
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      "url": "https://www.ycombinator.com/people/andrew-miklas"
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        "full_name": "Aryan Singhal",
        "title": "Founder/CEO",
        "founder_bio": "Co-Founder & CEO @ Mirrors (YC F26). Published four AI/ML research papers in high school at top AI conferences such as NeurIPS and EMNLP. Prev. ML research at UT Austin and UCSB.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/aryan-singhal-ai",
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    "id": 35289,
    "name": "ByteAsk",
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    "website": "https://byteask.ai/",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "ByteAsk is an AI coding agent built for C and C++, the code that runs trading systems, cars, chips, and operating systems. It does not stop at a diff that looks right. ByteAsk builds, debugs, and tests every change with the real toolchain until the change holds. If the compiler, the debugger, or the tests can catch it, then ByteAsk catches it too. It runs from the terminal or inside VS Code, Neovim, and Emacs, and is available fully on-prem.",
    "one_liner": "The AI coding agent for C and C++",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1788984366,
    "tags": [
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      "Enterprise Software",
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    ],
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    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/byteask/",
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        "full_name": "Anirudha Kulkarni",
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        "founder_bio": "Debugged low-latency C++ at Optiver and Quantbox; now building the agent that does it.\n- At Quantbox, built a Python-to-C++ transpiler for trading strategies: 1.5 s to 150 ns, beating hand-optimized C++.\n- Spoke at CppCon 2026 on C++ in the age of AI.\n- Co-founded LawSutra AI (CEO); acquired within months by Manupatra, India's largest legal-tech firm. Its search now serves 100k+ lawyers.\n- IIT Delhi CS (B.Tech + M.Tech)\n- 3rd in India, Jane Street Electronic Trading Challenge",
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        "full_name": "Pratyush Saini",
        "title": "Founder/CTO",
        "founder_bio": "Pratyush is the co-founder and CTO of ByteAsk, an AI coding tool for C and C++. He studied Computer Science at IIT Delhi. He was a core engineer on NeuralDB and BOLT, ThirdAI's CPU-only search and deep learning engines, then a founding engineer at Simbian, where he co-built the AI security agent that handles over a million incidents a year. He co-founded LawSutraAI as CTO and sold it to Manupatra, India's largest legal tech firm, where his legal research agent serves over 100,000 lawyers.",
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        "linkedin_url": "https://www.linkedin.com/in/pratyush-saini-96108a1a7/",
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        "title": "Two IIT Delhi Grads Built & Sold an AI Startup in 4 Months. Now They Are Building for C++",
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        "date": "Sep 24, 2026"
      },
      {
        "title": "AI coding startup ByteAsk raises $1 million from YC, Entrepreneur First - The Economic Times",
        "url": "https://economictimes.indiatimes.com/tech/startups/ai-coding-startup-byteask-raises-1-million-from-yc-entrepreneur-first/articleshow/134443548.cms?from=mdr",
        "date": "Sep 24, 2026"
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    "id": 35292,
    "name": "Agent Relay",
    "slug": "agent-relay",
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    "website": "https://agentrelay.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Agent Relay lets software teams' AI coding agents message each other directly, so people stop copy/pasting between Claude Code, Codex, Cursor, and their teammates' agents. A frontend agent can ask the backend agent what an API returns, two agents can sort out a merge conflict between themselves, and your agent can answer a colleague's agent while you sleep.\r\n \r\nAgents connect wherever they run: terminals, desktop apps, phones, laptops, cloud boxes, or a Mac mini across the world. Every session goes into shared, searchable history, so decisions don't get stuck in one person's chat. You can even let a customer's agent debug with yours. Setup takes about 5 minutes: give your agent the link and it installs itself. Use our hosted version free, or self-host the open-source version",
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    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1789747031,
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        "user_id": 50118,
        "full_name": "Will Washburn",
        "title": "Founder/CEO",
        "founder_bio": "Previously built Tailwind, where I spent 14 years scaling a marketing SaaS for small businesses to eight-figure ARR, 50K+ paying customers, 1M+ users, 60+ people, and a Series A. Now building Agent Relay so teams' coding agents can coordinate directly. We run 50+ agents in parallel ourselves.",
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        "linkedin_url": "https://www.linkedin.com/in/willwashburn/",
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        "user_id": 50117,
        "full_name": "Khaliq Gant",
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        "body": "Hey everyone! 👋 \\\n\\\nWe're Macy, Faiz and Niyaz - co-founders of[ Papaya](https://papaya.fyi) \n\n**TL;DR**\n\nPapaya is the optimization engine for AI agents. Connect your production agent and Papaya watches every action, finds what's hurting quality, cost, and latency, and gives you the fix. Once a fix is in place, Papaya makes sure your agent doesn't regress. Teams running Papaya are seeing 20%+ improvements to quality, latency, and cost.\n\n**Ask:** If you run an agent in production, connect it to Papaya. [Grab a time to get started here](https://cal.com/macy-mody/macy-papaya).\n\n<https://youtu.be/cG9iIVB5Psk>\n\n**The Problem**\n\nWe’ve been building agentic systems for years (6 years to be exact…before it was cool), including really large ones that helped run major workflows inside Amazon. We know firsthand that the hard part isn’t getting an agent to work, it’s keeping it working at a high quality bar. We consistently saw that every model update and every prompt change shifted behavior in ways nobody caught until something downstream looked wrong. The only way to find out what changed was to pull traces and read them by hand.\n\nMost companies shipping agents today are focused on the next feature for customers and they don't have time to fully maintain what's already been released. When we built our own agent as a three-person team, we hit the same wall. We needed to make sure our agent had high quality answers, was fast for our customers, and as low cost as possible, but we had to look at everything by hand. Every hour we spent examining traces was an hour we couldn’t spend on new product development. That's why we built Papaya.\n\n**How Papaya works 🔧** \n\nAt Papaya, our goal is to do the hard AI engineering work for you, staying up to date on the latest and greatest research so you can take advantage of this knowledge through optimizations. Simply stream your production traces through a lightweight SDK. From there, Papaya:\n\n* **Finds your use cases**: groups every run by the job the agent is doing, so you're looking at \"refund requests,\" not \"run 4812.\"\n* **Runs 200+ analyses**: checks every use case against 200+ research-backed failure patterns across quality, cost, and latency.\n* **Ranks the fixes by impact**: every recommendation comes with an estimated effect on quality, latency, and cost. Approve the ones you want directly in Papaya and Papaya opens the PR.\n* **Watches for regression**: once a fix ships, Papaya keeps checking that the improvement holds.\n\n![uploaded image](/media/?type=post&id=115486&key=user_uploads/2135001/0a49f356-ac11-44d5-bcc1-69caf4ba64d9)\n\n**Our Ask 🙏**\n\n* Run an agent in production? Connect it to Papaya. [Grab a time with us here](https://cal.com/macy-mody/macy-papaya).\n* Know any companies spending tons of time maintaining and fixing their agents? Intro us at [macy@papaya.fyi](mailto:macy@papaya.fyi).\n* Building agents and want a second set of eyes? Ping us. We are happy to help however we can!\n\n**The Team**\n\nWe've spent over 10 years building large scale agentic systems at Amazon, and we've scaled other YC startups from $0 to $10M ARR through acquisition. We started out building an analytics agent. The harness we built to optimize our own agent became the center of every prospect conversation, so we pivoted to it. Meet our team below :) \n\n![uploaded image](/media/?type=post&id=115486&key=user_uploads/2135001/ba5c9344-fb83-47ed-8c8c-deef533840ce)\n\n",
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        "title": "Maritime: Fully managed cloud for running AI agents at scale",
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        "body": "Hi everyone, we’re Maria and Ary, founders of [Maritime](https://bookface.ycombinator.com/company/38061) (YC F26).\n\n**TL;DR:** Maritime is a fully managed cloud platform for running millions of AI agents, each on its own isolated, persistent VM.\n\n<https://www.youtube.com/watch?v=TnGXH9H0cTw>\n\n**Why we built Maritime** \n\nWe believe we’re heading toward a world with billions of AI agents. Everyone will have agents working for them, and businesses will run entire teams of AI employees. A new generation of startups will build and sell these agents, giving every customer one of their own.\n\nWe started working on Maritime when OpenClaw was released. Now, with dots, Instinct, Grok Bot, and Muse, that future is taking shape. We saw the infrastructure challenge firsthand while hosting hundreds of agents during our research at MIT. Even at that scale, our time went into getting environments running, maintaining them, and debugging individual agents.\n\nRunning billions of agents will require infrastructure that lets developers give each one a persistent computer and manage entire fleets with ease. We’re building Maritime to make that possible, so any startup can launch an agent product, give every customer their own agent, and scale it to millions in no time.\n\n![uploaded image](/media/?type=post&id=120824&key=user_uploads/3118952/6772cfd5-737c-4278-8a02-ec3793cb070b)\n\n**What Maritime does**\n\nMaritime gives every agent a persistent computer and manages the infrastructure around it:\n\n* **An isolated VM for each agent.** Run code, install software, and use a browser.\n* **Pricing built for scale.** Hosting starts at $1 per agent per month, making it practical to give every customer their own persistent computer and grow your fleet as your product grows.\n* **Persistence between tasks.** Keep files, memory, installed software, and logins so agents can pick up where they left off.\n* **Tools to manage individual agents.** Inspect, debug, and fix each customer’s agent directly.\n* **Different environments for different workflows.** Choose Linux computers, Windows desktops, or virtual Android phones based on the software and apps your agents need.\n\nYou can run your agent code inside a Maritime VM, or keep your agent on your existing backend and use MCP to let it control a Maritime computer.\n\n![uploaded image](/media/?type=post&id=120824&key=user_uploads/3118952/db071ab8-94f8-4245-9de8-f574cc2aba1d)\n\n**Who it’s for**\n\nTeams building and selling AI employees, personal assistants, and other products where every customer has an agent of their own.\n\nWe want founders to focus on building and growing their products, with Maritime managing the infrastructure to run them.\n\n**Our ask**\n\n* **Try Maritime:** Host three agents for free at [maritime.sh](http://maritime.sh). Hosting starts at $1 per agent per month.\n* **Introduce us:** If you know teams building and selling agents, especially those deploying a separate agent or computer for every customer, please comment or connect us.",
        "url": "https://www.ycombinator.com/launches/VQm-maritime-fully-managed-cloud-for-running-ai-agents-at-scale",
        "votes": 23,
        "created_at": "2026-10-09T19:00:00.166Z"
      }
    ]
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    "all_locations": "San Francisco, CA, USA",
    "long_description": "Port your development environment to the cloud. Give every coding agent on its own cloud computer, bring your Codex or Claude subscription, start agents from Slack and Linear, and manage them from your desktop, phone, or terminal.",
    "one_liner": "Cloud development environments for AI coding",
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    "top_company": false,
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    "nonprofit": false,
    "batch": "Fall 2026",
    "status": "Active",
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    "regions": [
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      "America / Canada"
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    "stage": "Early",
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    "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/boxesdev.json",
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    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/boxes-dev",
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    "company_photos": [],
    "primary_partner": {
      "name": "Andrew Miklas",
      "url": "https://www.ycombinator.com/people/andrew-miklas"
    },
    "founders": [
      {
        "user_id": 195662,
        "full_name": "Nick Bushak",
        "title": "Founder",
        "founder_bio": "Co-founder @ Boxes.dev. Before Boxes.dev, Nick founded Gem, a recruiting CRM used by most high growth tech companies, and led engineering teams at Facebook.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/nbushak",
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        "full_name": "Drew Regitsky",
        "title": "Founder",
        "founder_bio": "Co-founder @ Boxes.dev. Previously first engineer/employee at Gem (YC S17). MIT '10.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/drewregitsky",
        "x_url": "https://x.com/drewregitsky",
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    "news": [],
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]