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"skills": [] }, { "id": 95042, "title": "Revenue Associate", "url": "https://www.ycombinator.com/companies/encord/jobs/VvoCmAr-revenue-associate", "location": "London", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 95043, "title": "Human Data Operations Strategist", "url": "https://www.ycombinator.com/companies/encord/jobs/QoYBQMK-human-data-operations-strategist", "location": "London", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 96279, "title": "Senior Software Engineer, Full-Stack", "url": "https://www.ycombinator.com/companies/encord/jobs/HvlcMf7-senior-software-engineer-full-stack", "location": "London", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 96280, "title": "Software Engineer, Front-End Leaning", "url": "https://www.ycombinator.com/companies/encord/jobs/kETKeiR-software-engineer-front-end-leaning", "location": "London", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 96281, "title": "Software Engineer, Backend", "url": "https://www.ycombinator.com/companies/encord/jobs/J14Rblz-software-engineer-backend", "location": "London", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 96282, "title": "Deployment Strategist", "url": "https://www.ycombinator.com/companies/encord/jobs/O3v1WZP-deployment-strategist", "location": "New York", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 96283, "title": "Senior Software Engineer, Front-End Leaning", "url": "https://www.ycombinator.com/companies/encord/jobs/FXcMVmq-senior-software-engineer-front-end-leaning", "location": "London", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 96284, "title": "Product Engineer, Physical AI", "url": "https://www.ycombinator.com/companies/encord/jobs/gQlAVmO-product-engineer-physical-ai", "location": "London", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 96285, "title": "Product Engineer", "url": "https://www.ycombinator.com/companies/encord/jobs/E9vvz7Y-product-engineer", "location": "London", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 96286, "title": "Software Engineer, Full-Stack", "url": "https://www.ycombinator.com/companies/encord/jobs/elurIQG-software-engineer-full-stack", "location": "London", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 96287, "title": "Human Data Solutions Engineer", "url": "https://www.ycombinator.com/companies/encord/jobs/3ORQrcy-human-data-solutions-engineer", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 96288, "title": "Human Data Solutions Engineer", "url": "https://www.ycombinator.com/companies/encord/jobs/ochq0FK-human-data-solutions-engineer", "location": "London", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 96289, "title": "Commercial Associate, Physical AI", "url": "https://www.ycombinator.com/companies/encord/jobs/qsDc1PU-commercial-associate-physical-ai", "location": "New York", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 96290, "title": "Commercial Associate, Physical AI", "url": "https://www.ycombinator.com/companies/encord/jobs/FyzOIOY-commercial-associate-physical-ai", "location": "London", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 96291, "title": "GTM Special Projects, Physical AI", "url": "https://www.ycombinator.com/companies/encord/jobs/zbhrvUY-gtm-special-projects-physical-ai", "location": "New York", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 96292, "title": "Senior Product Manager", "url": "https://www.ycombinator.com/companies/encord/jobs/JDTYAXb-senior-product-manager", "location": "London", "type": "Full-time", "role": "Product", "role_type": null, "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 96294, "title": "Senior Growth Manager", "url": "https://www.ycombinator.com/companies/encord/jobs/Iqy1rqR-senior-growth-manager", "location": "London / New York / San Francisco", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 96295, "title": "Senior Software Engineer, Infrastructure ", "url": "https://www.ycombinator.com/companies/encord/jobs/CtonqI4-senior-software-engineer-infrastructure", "location": "London", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 96296, "title": "Software Engineer, Applied AI", "url": "https://www.ycombinator.com/companies/encord/jobs/ewUM3Z8-software-engineer-applied-ai", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 96297, "title": "Software Engineer, Full-Stack", "url": "https://www.ycombinator.com/companies/encord/jobs/AuJykwC-software-engineer-full-stack", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 96298, "title": "Senior Software Engineer, Full-Stack", "url": "https://www.ycombinator.com/companies/encord/jobs/AdAB4Zj-senior-software-engineer-full-stack", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 96299, "title": "Software Engineer, Physical AI", "url": "https://www.ycombinator.com/companies/encord/jobs/CuyvF2n-software-engineer-physical-ai", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 96300, "title": "General Manager, Human Data Operations", "url": "https://www.ycombinator.com/companies/encord/jobs/WE79ZUs-general-manager-human-data-operations", "location": "Bengaluru", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 100796, "title": "Finance Business Partner – GTM", "url": "https://www.ycombinator.com/companies/encord/jobs/A0pg6BM-finance-business-partner-gtm", "location": "London", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 113039, "title": "Principal Engineer - Backend", "url": "https://www.ycombinator.com/companies/encord/jobs/7uH7QHx-principal-engineer-backend", "location": "London, England, GB", "type": "Full-time", "role": "Engineering", "role_type": "Backend", "salary_range": "£150K - £200K GBP", "equity_range": "", "experience": "6+ years", "visa": "US citizenship/visa not required", "skills": [] } ], "news": [ { "title": "The Data Layer for the Robot Economy", "url": "https://www.youtube.com/watch?v=cSBdukYWWxQ", "date": "Apr 30, 2026" }, { "title": "Encord lands new cash to grow its data dev tools for AI | TechCrunch", "url": "https://techcrunch.com/2024/08/13/encord-lands-new-cash-to-grow-its-data-labeling-tools-for-ai/", "date": "Aug 13, 2024" }, { "title": "10 Most Advanced Medical Imaging Solution Providers 2022 July2022 - Insights Care", "url": "https://insightscare.com/10-most-advanced-medical-imaging-solution-providers-2022-july2022/", "date": "Jul 29, 2022" }, { "title": "Meet 23 Deeptech Startups Poised to Defy the Market Downturn, Per VCs", "url": "https://www.businessinsider.com/meet-23-deeptech-startups-poised-to-defy-market-downturn-vcs-2022-7", "date": "Jul 28, 2022" }, { "title": "Encord: Stringing a Powerful Cord of Futuristic Data-Centric Computer Vision", "url": "https://insightscare.com/encord-stringing-a-powerful-cord-of-futuristic-data-centric-computer-vision/", "date": "Jul 25, 2022" } ], "launches": [] }, { "id": 22880, "name": "True3D", "slug": "true3d", "former_names": [ "True3D", "Hyperplane", "Hackpack", "LeetDesign", "QuickVid.ai", "TutorAI.me", "QuickVid.ai", "QuickVid", "True3D", "True3D Labs", "Outpaint.com" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a242a0c2ce6b1ca1518d1744187f98a3bf8eade9.png", "website": "https://www.true3d.com/", "all_locations": "New York City, NY, USA", "long_description": "We're a research lab building foundation models and products for what comes after flat video.", "one_liner": "Building the next generation of visual media", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1614739771, "tags": [ "Video", "Media", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2021", "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/true3d", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2021/true3d.json", "year_founded": 2020, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/outpaint/", "x_url": "https://x.com/outpaintcom", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/a242a0c2ce6b1ca1518d1744187f98a3bf8eade9.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 579262, "full_name": "Daniel Habib", "title": "Founder", "founder_bio": "Ex-FB Engineer with expertise in live video, generative AI, virtual reality and scalable systems\n", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/daniel-habib-5b305767/", "x_url": "https://twitter.com/DannyHabibs", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/72749a3b280febc144aaf9f353d3bae566f8ae83.jpg" } ], "jobs": [], "news": [ { "title": "QuickVid uses AI to generate short-form videos, complete with voiceovers | TechCrunch", "url": "https://techcrunch.com/2022/12/30/quickvid-uses-ai-to-generate-short-form-videos-complete-with-voiceovers/?guccounter=1&guce_referrer=aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS8&guce_referrer_sig=AQAAALptn1iOjHaR-DkOiiKW3VgHFJ-8yzAmJ1_pepYTTcFBxvZJKXVin2yxpZCf2HBw33Li8h5NOgrtFoBvEdqgIdE8kk-zXlWVKjVowvMpcsS9UyL_g5AYdLjlZZLCo9jjb4G5IghZ0RTWBJk3YaQMsIwXXObXlFNZA7bx2udYDk1b", "date": "Dec 30, 2022" }, { "title": "ChatGPT Is on Fire, and a Cottage Industry of Bot Builders Is Exploding Alongside It — The Information", "url": "https://www.theinformation.com/articles/chatgpt-is-on-fire-and-a-cottage-industry-of-bot-builders-is-exploding-alongside-it", "date": "Dec 16, 2022" } ], "launches": [ { "id": 103954, "title": "Outpaint.com, Ad Reframe - convert winning UGC ads to CTV", "tagline": "Send us your UGC ad and get back a TV & Desktop ready version within days. ", "body": "Today on [Outpaint](https://outpaint.com/ad-reframe) we are launching **Ad Reframe**, the easiest way for advertisers to convert their winning UGC (9:16) for connected TV (16:9). \n\n![uploaded image](/media/?type=post&id=103954&key=user_uploads/579262/0d9469eb-a8fe-4035-82b5-8b8101014f76)\n\n**The problem**\n\nAdvertisers test endlessly to find a winning UGC video, then want to squeeze every bit of value from it, including running it on TV. But converting vertical to horizontal for the big screen today means black bars from pillarboxing or a smeared side blur.\n\n**The solution**\n\nInstead of adding black bars, we expand the content so it looks like it was shot natively for TV.\n\n![uploaded image](/media/?type=post&id=103954&key=user_uploads/579262/9c2c0fed-b0bb-4904-a4f4-55b28373782d)\n\nOutpainting wins on everything advertisers measure: engagement (skip rate falls to 17%, the lowest tested), quality (55% say it looks professionally produced vs. under 40% for the alternatives), and brand lift (consideration at 51%, favorability at 58%), because filling the screen with real content beats hiding the gap behind bars or blur. Report [link](https://outpaint.com/case-studies/ctv-format-test)\n\n![uploaded image](/media/?type=post&id=103954&key=user_uploads/579262/79d0f1d7-f541-4f01-9255-c811dde479f9)\n\n**How it works**\n\nThe conversion generates new content where the black bars used to be. We support any aspect ratio, resolutions up to 8K, any frame rate, and any color space.\n\n![uploaded image](/media/?type=post&id=103954&key=user_uploads/579262/b9f35bc8-49fc-4b12-ac11-e2cb85002956)\n\nHave an ad you want to convert? Grab 15 minutes on my calendar and we'll set you up. ", "url": "https://www.ycombinator.com/launches/R2g-outpaint-com-ad-reframe-convert-winning-ugc-ads-to-ctv", "votes": 18, "created_at": "2026-06-25T14:53:02.827Z" }, { "id": 102813, "title": "Outpaint.com - Expand any video to fit any screen", "tagline": "Cinema grade video outpainting models", "body": "I’m Daniel from [**Outpaint.com**](http://Outpaint.com) (W21) and we are putting an end to **black bars** around videos, from vertical ads to big theater screens.\n\n**Problem**\n\nPeople consume video on many different devices, but video can only be shot for a single screen at a time.\n\n**Solution**\n\nOur models expand any video to fit any screen by generating content to fill the extra space, while preserving every pixel of the original video.\n\n**Examples**\n\n9:16 →16:9 (Ads and Micro-dramas)\n\n![uploaded image](/media/?type=post&id=102813&key=user_uploads/579262/e014ce0f-23db-4ee6-a6ee-f2e4269bd9c5)\n\n16:9 → 1.43:1 (Premium big screens and IMAX full frame)\n\n![uploaded image](/media/?type=post&id=102813&key=user_uploads/579262/ab682ded-ee2d-4cb6-838b-b8f024ed41be)\n\n16:9 →180° Fisheye (Domes & VR)\n\n![uploaded image](/media/?type=post&id=102813&key=user_uploads/579262/4e182eb6-7782-4047-bc53-6ed83af33ca1)\n\n**How [_outpaint.com_](http://outpaint.com) works**\n\nSimply send us a video link and your target aspect ratio, and we'll send back the expanded version. Our models handle any duration, resolution, frame rate, and color space.\n\nWe've expanded everything from vertical ads for horizontal CTV spots to full films for immersive screens like IMAX and dome venues. We even got a [**shoutout on Rogan**](https://youtu.be/D_ZGWj_38uA?si=hY74cps5IN5THreL&t=8415) for some of our VR conversions.\n\n**Have a video you want to expand?**\n\nSend me an email at [**hello@outpaint.com**](mailto:daniel@outpaint.com) with a link to your video, and I'll follow up within 24 hours with a quote.", "url": "https://www.ycombinator.com/launches/QkH-outpaint-com-expand-any-video-to-fit-any-screen", "votes": 7, "created_at": "2026-06-09T16:17:02.245Z" }, { "id": 81306, "title": "🎥 QuickVid Autopilot - Post 1 viral clip per day to your socials", "tagline": "Autopilot curates, edits, and posts the best clips from your existing video content.", "body": "Hey everyone,\n\nI’m Dan, and I’m super excited to share that we are starting to roll out QuickVid [**Autopilot**](https://www.quickvid.ai/autopilot)!\n\n![uploaded image](/media/?type=post&id=81306&key=user_uploads/579262/891b19bb-7b43-492c-b234-ee213cd4a28b)\n\n### The Problem\n\nConsistently posting clips to your socials is just too time-consuming and expensive.\n\n🕗 Time Intensive: Curating and editing a 40-second clip from a 30-minute video can take up to 1-2 hours.\n\n💰 Expensive: A decent video editor can cost upwards of $200/clip\n\n🖥️ Difficult to get started: Editing requires specialized software like Adobe Premiere\n\n😰 You are too busy: Consistently posting to your socials is something that busy founders just don’t have time for!\n\n📊 Trends are always changing: What works on each social channel is always changing. We stay on top of trends, so you don’t have to.\n\n### The Solution\n\nConnect Autopilot to your long videos and desired posting locations, and you’re done! Autopilot will find the best clip from all your video sources and post it on your behalf every day.\n\n![uploaded image](/media/?type=post&id=81306&key=user_uploads/579262/a608e70e-d60d-4a25-98f6-97912f52d317)\n\n**Connect your video source**\n\nThese are the locations QuickVid will pull clips from. QuickVid checks for new content daily. (YouTube, Drive, Zoom, etc.)\n\n**Connect your video destinations**\n\nThis is where Autopilot will post your clips every day (YouTube, LinkedIn, Facebook, etc)\n\n**Choose your cadence**\n\nEither post once per day or let our AI decide the best time and cadence to post\n\n### About the Clips\n\nClips are:\n\n* Automatically cropped to a vertical 9:16 aspect ratio\n* Auto-Reframed to focus on the speaker\n* Baked with captions to help keep a viewer’s attention\n* Personalized with your branding\n\n![uploaded image](/media/?type=post&id=81306&key=user_uploads/579262/27645561-3a5a-4e38-af3a-0445c2ea712a)\n\n### Who is Autopilot for?\n\nIf you consistently create long **_talking_** videos (podcasts, interviews, zoom meetings, etc.) and are struggling to keep up with posting clips, sign up for Autopilot, and I will personally onboard you!\n\n[Sign Up Here](https://www.quickvid.ai/autopilot)", "url": "https://www.ycombinator.com/launches/L9O-quickvid-autopilot-post-1-viral-clip-per-day-to-your-socials", "votes": 9, "created_at": "2024-06-04T21:01:38.894Z" }, { "id": 77477, "title": "QuickVid 🎥 Cut up long videos into viral clips", "tagline": "A generative AI video tool that repurposes long videos into shorts in one click. ", "body": "**Tl;dr:** QuickVid makes growing your Youtube channel effortless by creating ready-to-post shorts out of _talking_ videos (Video Podcasts, Interviews, etc.). For anyone looking for a hands-off solution, checkout our autopilot add-on! \n\nHey everyone, I’m Daniel Habib.\n\nI just pivoted and am re-launching QuickVid (w21)\n\n![uploaded image](/media/?type=post&id=77477&key=user_uploads/579262/c54acda5-8765-4d5b-8272-36a515c77504)\n\n## **🧨The Problem**\n\nIf you’re looking to grow aggressively on LinkedIn, Youtube, or TikTok,  you should be posting **1-2 shorts per day**\n\nFor a busy founder, this can feel like an impossible task because:\n\n* Clipping shorts out of your videos takes too much time\n* Hiring a video editor is too expensive (sometimes over $300 per clip!)\n\n## **🎉The Solution**\n\nQuickVid is your automated video production studio. We take all of your source video content and repurpose it for different platforms at 1/1000th of the cost and time.\n\n![uploaded image](/media/?type=post&id=77477&key=user_uploads/579262/77ffd30d-f607-44e8-a4d5-6955d2233e1b)\n\nClips are:\n\n* Auto-reframed so the main subject is always in focus\n* Branded with subtitles and special effects\n* Spliced with B-Roll to keep engagement high – driving algorithm pickup\n* Supported in over 10 video languages\n* Editable, if you want to adjust a clip it’s easy to tweak\n* HD - 1080p supported\n* Graded with a Virality Score to help you find the best clips\n\n## **How it works**\n\nWe use our own proprietary models alongside multiple LLM and video processing chains to find and spice up the best clips.\n\nTo use, simply drop a link to your video and once processed, you’ll have dozens of clips ready for publishing.\n\n## **Full Autopilot (Beta)**\n\nFor those that are too busy to post their own shorts, we have an Autopilot add-on. Autopilot edits and posts one short a day on your behalf, it’s completely hands-off after initial setup. Every Friday you’ll get analytics on how your videos are performing.\n\n## **👋 Asks**\n\n* **Try out QuickVid!** (use promo code: _LAUNCHYC_ for a 20% discount for 2 years, only valid until next week)\n* **Share this post!** If you know any founders that regularly produce content I’d love to connect with them.\n* **Interested in Autopilot?** Shoot me an email with a link to your youtube channel: [daniel@quickvid.ai](mailto:daniel@quickvid.ai)", "url": "https://www.ycombinator.com/launches/K9d-quickvid-cut-up-long-videos-into-viral-clips", "votes": 34, "created_at": "2024-01-12T19:07:28.765Z" } ] }, { "id": 22953, "name": "Enode", "slug": "enode", "former_names": [ "Enode AS" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d173e80b5b8cf1006b5c3b5baa37e052acecc8c5.png", "website": "http://www.enode.com", "all_locations": "Oslo, Oslo, Norway; Remote", "long_description": "Device connectivity, home energy coordination, and grid orchestration in a single 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$250K", "equity_range": "", "experience": "3+ years", "visa": "Will sponsor", "skills": [] }, { "id": 92526, "title": "Forward Deployed Engineer", "url": "https://www.ycombinator.com/companies/tavus/jobs/IjHCBZB-forward-deployed-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$140 - $200", "equity_range": "", "experience": "3+ years", "visa": "Will sponsor", "skills": [] }, { "id": 92816, "title": "Customer Engineer", "url": "https://www.ycombinator.com/companies/tavus/jobs/IWCXiuC-customer-engineer", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "", "visa": "US citizen/visa only", "skills": [] }, { "id": 92819, "title": "Data Engineer ", "url": "https://www.ycombinator.com/companies/tavus/jobs/YxnA0Pd-data-engineer", "location": "Remote / Remote (US)", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "", "visa": "US citizen/visa only", "skills": [] }, { "id": 94046, "title": "Marketer (Brand, Product, Storytelling)", "url": "https://www.ycombinator.com/companies/tavus/jobs/jB6gyYb-marketer-brand-product-storytelling", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Marketing", "role_type": null, "salary_range": "$120K - $150K", "equity_range": "", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 106800, "title": "Brand & Product Designer", "url": "https://www.ycombinator.com/companies/tavus/jobs/kDDUkpB-brand-product-designer", "location": "San Francisco / Remote (US)", "type": "Full-time", "role": "Design", "role_type": "Web design", "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 106801, "title": "Enterprise Account Executive", "url": "https://www.ycombinator.com/companies/tavus/jobs/D3tKARq-enterprise-account-executive", "location": "San Francisco / Remote (US)", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 106802, "title": "Product Manager ", "url": "https://www.ycombinator.com/companies/tavus/jobs/pVtHurX-product-manager", "location": "San Francisco / Remote (US)", "type": "Full-time", "role": "Product", "role_type": null, "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 106803, "title": "Product Designer", "url": "https://www.ycombinator.com/companies/tavus/jobs/TuEEphx-product-designer", "location": "San Francisco / Remote (US)", "type": "Full-time", "role": "Design", "role_type": "Web design", "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 106804, "title": "Business Development Representative", "url": "https://www.ycombinator.com/companies/tavus/jobs/Q2J5Kgn-business-development-representative", "location": "San Francisco / Remote (US)", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 106805, "title": "Vibe Growth Marketer", "url": "https://www.ycombinator.com/companies/tavus/jobs/UDVRbcD-vibe-growth-marketer", "location": "San Francisco", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 106806, "title": "Senior Software Engineer (CVI)", "url": "https://www.ycombinator.com/companies/tavus/jobs/DzSZEjy-senior-software-engineer-cvi", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [ { "title": "Tavus: The AI Human Platform", "url": "https://www.youtube.com/watch?v=6yPs2nDpYZo", "date": "Nov 14, 2025" }, { "title": "Tavus raises $40M for more lifelike AI agents", "url": "https://www.axios.com/pro/enterprise-software-deals/2025/11/12/agentic-ai-tavus-human-40-milion-crv", "date": "Nov 12, 2025" }, { "title": "Tavus raises $18M to bring face and voice cloning to any app", "url": "https://techcrunch.com/2024/03/12/generative-ai-video-startup-tavus-raises-18m-to-bring-face-and-voice-cloning-to-any-app/", "date": "Mar 12, 2024" }, { "title": "Tavus taps generative AI to power personalized videos with voice and face cloning | TechCrunch", "url": "https://techcrunch.com/2023/03/20/tavus-taps-generative-ai-to-power-personalized-videos-with-voice-and-face-cloning/", "date": "Mar 20, 2023" } ], "launches": [ { "id": 83220, "title": "Conversational Replicas by Tavus", "tagline": "Build with real-time digital twins that speak, see, and hear", "body": "Hey everyone!\\\n\\\nWe're Quinn and Hassaan, co-founders of Tavus. At Tavus, we build AI models and APIs to empower development teams to build digital twin experiences with video generation and, now, real-time conversational video.\n\nWith the _Conversational Video Interface_, developers can build live video conversations with digital twins that speak, see, and hear. It's the world's only end-to-end conversational pipeline with less than a second of latency.\\\n\\\n**Live Demo**\n\n» Try talk to Carter, our demo Digital Twin, today at [www.tavus.io](http://www.tavus.io)\n\n![uploaded image](/media/?type=post&id=83220&key=user_uploads/731467/1e35574a-dbe4-425d-b9f3-f83d2d0e2752)\n\n**Challenge?** Consumers are feeling more isolated and detached than ever with the saturation of digital products and services, and they seek connectedness.\\\n\\\n**What are we launching?** Tavus is launching the Conversational Video Interface. It provides developers with all the tools they need to easily build innovative, immersive, and highly engaging conversational video experiences with digital twins that mimic real-life interactions.\n\nThis brings a human face, voice, emotion, and intelligence to daily digital interactions via life-like digital twins.\n\n![uploaded image](/media/?type=post&id=83220&key=user_uploads/731467/d6a855ad-878d-48c2-a98b-75e758c9fd38)\n\n**Use Cases**\n\nImagine getting live help from a human-like digital twin when buying something online, dealing with the DMV website, making a doctor's appointment, or booking travel.\n\nOr imagine speaking to an expert's digital twin, someone you otherwise couldn’t access.\n\nThese are the types of conversational video experiences you can build with the power of real-time digital twins and AI agents.\n\n**Try the LIVE DEMO!**\n\nSee the magic for yourself…\n\nChat with our demo digital twin, Carter. You can find him at [www.tavus.io.](http://www.tavus.io/)\n\n**Feedback welcome**\n\nWe’re excited to see what you build, and hear what you think!\n\n**Message us with feedback**\n\nDM on X:\\\n \\\n\\\n\\\nDiscord Community:\\\n\n\nAppreciate your support!\\\nQuinn & Hassaan", "url": "https://www.ycombinator.com/launches/LeG-conversational-replicas-by-tavus", "votes": 29, "created_at": "2024-08-20T14:57:47.178Z" } ] }, { "id": 24485, "name": "Cumbuca", "slug": "cumbuca", "former_names": [ "Comadre" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/77e60a49b6259a7c45a281590f221925fc32c563.png", "website": "https://www.cumbuca.com", "all_locations": "São Paulo, SP, Brazil", "long_description": "Cumbuca is an infratech bank for developers to build financial products with direct Central Bank connectivity. Instead of working around unreliable middleware, you get bare-metal access to Pix, payment initiation, and data APIs under our license, so you ship products faster and we handle the compliance. There's no vendor lock-in, and your service will never be disrupted by us. \r\n", "one_liner": "Bare-metal access to Brazil's Open Finance and Pix systems", "team_size": 5, "industry": "Fintech", "subindustry": "Fintech", "launched_at": 1630087087, "tags": [ "Fintech", "B2B", "API", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "Fintech" ], "regions": [ "Brazil", "Latin America", "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/cumbuca", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2021/cumbuca.json", "year_founded": 2021, "city": "São Paulo", "country": "BR", "linkedin_url": "https://www.linkedin.com/company/appcumbuca", "x_url": "https://twitter.com/appcumbuca", "fb_url": "https://www.facebook.com/appcumbuca", "cb_url": "https://www.crunchbase.com/organization/comadre", "github_url": "https://github.com/appcumbuca", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/77e60a49b6259a7c45a281590f221925fc32c563.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 358823, "full_name": "Daniel Ruhman", "title": "Founder", "founder_bio": "Self taught developer, released first iPhone app when 14y - currently 23y. Dropped out of Computer Engineering degree in Brazil after brief time doing Cog Sci @ UC Berkeley to become an entrepreneur focused on improving the lives of Brazil's lower income population, and have been working with low income households and gig economy workers for the past 2.5 years.\nI’m a huge enthusiast on all things human behavior, gig economy, fintech, and above all in ways to unlock LATAM full potential.", "is_active": true, "linkedin_url": "http://linkedin.com/in/daniel-ruhman-0b739353", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/fcc3abc1228d6b693f4a49ff8febab0358a86f11.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 95950, "title": "Cumbuca: The first proxy for the Brazilian regulated ecosystem", "tagline": "Develop your own payments infra in Brazil using our license.", "body": "Hey YC! 👋\n\nWe're Daniel, Bruno, and Pedro — founders of Cumbuca. We’re the first proxy for Brazil’s regulated ecosystem. After years of building fintechs in Brazil, we saw how painful it is to obtain a license or depend on PSPs and BaaS providers. Our previous B2C operation scaled to over a million accounts, and we suffered since a lot of our core product relied on partner infra, and it hurt us to not be able to solve the issues affecting our customers. We’ve been deeply involved with Open Finance since its earliest days — we were one of the first players in the ecosystem and became the **fourth ITP/PISP license ever issued in Brazil**, and after closing our B2C operation decided to pivot to B2B and build the financial infrastructure partner we always wished existed for ourselves.\n\nhttps://www.youtube.com/watch?v=F4_E2LYNBCQ\n\n## TL;DR\n\n**Cumbuca is the first regulatory proxy for Brazil's Open Finance and Pix ecosystem.** We give fintechs the same development freedom they'd have with their own license — direct API access, full operational control, custom infrastructure — while we handle compliance. No more choosing between years of licensing delays or surrendering control to third-party providers.\n\n**Ask:** Are you a global fintech looking to enter Brazil, or a payments company scaling beyond your current provider? Let's talk → [daniel@cumbuca.com](mailto:daniel@cumbuca.com)\n\n![uploaded image](/media/?type=post&id=95950&key=user_uploads/358823/0a8e01c7-dfb2-4489-aafa-c3e8f00a12bb)\n\n## ❌ The Problem\n\nBrazil is one of the most exciting fintech markets in the world — a forward-thinking Central Bank, Pix (the world's most successful instant payments system), and a mature Open Finance framework. Global fintechs want in.\n\nBut the path to market is brutal:\n\n**Option 1: Get your own license**\n\n* 12-24 months waiting for approval\n* Millions in regulatory capital\n* Constant compliance obligations\n* Need local expertise to navigate BACEN's evolving regulations\n\n**Option 2: Use a BaaS/OFaaS provider**\n\n* Fast time-to-market, but...\n* You're locked into their APIs and abstractions\n* Their maintenance windows = your downtime\n* Their support tickets = your customers waiting\n* Their roadmap = your product limitations\n* They use YOUR operational data for their own credit models\n\nFor companies serious about Brazil, neither option works. You either wait years or give up control of your destiny.\n\n---\n\n## 🛠 Our Solution: A Regulatory Proxy\n\nWe built something new: **a proxy that sits between your infrastructure and Brazil's regulated ecosystem.**\n\nHere's how it works:\n\n1. **You build your own infrastructure** using the exact same APIs that licensed institutions use\n2. **You send requests to our proxy**, which signs and forwards them under our license\n3. **You receive 1:1 responses** from the Central Bank ecosystem — no abstractions, no transformations\n\n**The key insight:** Instead of building \"Cumbuca APIs\" (which would impose our abstractions), we built a minimal regulatory layer. You develop against the official Open Finance and Pix specifications. When you're ready for your own license, you just swap our certificates for yours.\n\n**What you get:**\n\n* ⚡ **Immediate access** — start building today, not in 2 years\n* 🔧 **Full development freedom** — same API surface as licensed players\n* 🏗️ **Own your infrastructure** — build it yourself or use partner modules\n* 📊 **Own your data** — we don't use it for anything commercial\n* 🛡️ **Resolve issues directly** — no middlemen when problems arise\n* 🔄 **Future-proof** — migrate to your own license with minimal effort\n\n---\n\n## 👨‍💻 The Team\n\nWe didn't build Cumbuca from a whiteboard — we built it from scars.\n\n**Daniel Ruhman (CEO)** — Started coding as a kid after watching \"The Social Network.\" Dropped out of Computer Engineering to study at UC Berkeley. Built and pivoted through multiple startups: a gig economy platform, a Pix-native neobank for underserved Brazilians (Comadre), and a group expense app that grew to over 1 million accounts (Cumbuca B2C). Applied to YC 8 times before getting in.\n\n**Bruno Cury & Pedro Castilho (Co-founders)** — Together with Daniel, they became among the youngest statutory directors in Brazil's financial sector when they secured their first license in 2022. They've lived every pain point of building on Brazilian financial infrastructure.\n\nWe've assembled a dream team of Open Finance veterans:\n\n* **Gustavo Lino** (Head of Policy, Legal & Compliance) — Former President of INIT (Brazilian Association of Payment Initiators), board member of Open Finance Brazil\n* **Nic Marcondes** (Director of Open Finance) — Architect of the no-redirect payment flow (JSR), the technology behind Pix by Proximity. 5+ years building Open Finance before it officially existed.\n* **Ana Luisa Monteiro** (CFO) — Expert in Brazil's financial markets and regulated operations\n\n---\n\n## 🚀 Our Journey\n\n![uploaded image](/media/?type=post&id=95950&key=user_uploads/358823/7e9d0ec2-b17f-4efb-908c-9dd724d88dd1)\n\nThis is actually our **third pivot** — and it's working.\n\nWe were one of the first 5 companies to apply for a pure PISP license in Brazil. We co-founded INIT, the Payment Initiators Association. We operated over 1 million consumer accounts and learned firsthand how painful it is to depend on infrastructure you don't control.\n\nWhen our B2C monetization model failed (users only wanted Pix, not cards), we faced a choice: burn through our runway or leverage our real assets — our license and our team.\n\nWe chose to build the infrastructure partner we always wished existed.\n\n**The result:** Cumbuca has been profitable and cash-flow positive since August 2025 — just 3 months after pivoting to B2B.\n\n---\n\n## 🎯 Who We Work With\n\nCumbuca is **not a self-serve platform**. We work with:\n\n* **Global fintechs entering Brazil** — Series B+ companies that need more control than BaaS can offer\n* **Companies outgrowing their BaaS/OFaaS** — Ready to verticalize but don't want to wait for a license\n* **Companies in the licensing queue** — Start building and operating now, migrate when approved\n\nOur customers include credit companies using Open Finance data for underwriting, payment orchestrators, e-commerce giants, PFM apps, and investment aggregators.\n\n---\n\n## 🙏 Our Ask\n\n* **Entering Brazil?** Let's talk about how to launch without giving up control → [daniel@cumbuca.com](mailto:daniel@cumbuca.com)\n* **Know someone scaling in Brazilian payments?** Introduce us!\n* **Investor focused on LATAM fintech infra?** We'd love to connect.\n\n---\n\n## 🔗 Learn More\n\n* Website: [cumbuca.com](http://cumbuca.com)\n* Product Hunt: We're live — your upvote helps! 🚀\n\n---\n\nWe spent 7 years getting here. Now we're just getting started.\n\nDale. 🇧🇷\n\n— Daniel, Bruno, Pedro & the Cumbuca team", "url": "https://www.ycombinator.com/launches/Oxa-cumbuca-the-first-proxy-for-the-brazilian-regulated-ecosystem", "votes": 20, "created_at": "2025-12-03T17:07:13.744Z" } ] }, { "id": 24551, "name": "Mach9", "slug": "mach9", "former_names": [ "Mach9 Robotics" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/05390d32227edd1416d7dc545801c3fc59e2ac15.png", "website": "https://www.mach9.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Mach9 accelerates how teams model and understand the world with automated feature extraction technology. Founded in 2021 and headquartered in San Francisco, Mach9's flagship Digital Surveyor platform helps transportation agencies, utility companies, and engineering firms extract miles of road corridor projects in a fraction of traditional processing time. Built on decades of research from Carnegie Mellon University's Robotics Institute, Mach9 empowers the architecture, engineering, and construction industries to tackle large-scale infrastructure projects with unprecedented speed and accuracy. Leading survey and geospatial organizations, including Langan, Olsson, Woolpert, HDR, and major state DOTs trust Digital Surveyor to create engineering-grade maps for infrastructure design and operations.", "one_liner": "AI CAD Software for Civil Engineering", "team_size": 25, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1628526474, "tags": [ "Machine Learning", "Computer Vision", "Design Tools", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2021", "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/mach9", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2021/mach9.json", "year_founded": 2021, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/mach9geo/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": "https://github.com/mach9robotics", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/05390d32227edd1416d7dc545801c3fc59e2ac15.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": 311199, "full_name": "Alexander Baikovitz", "title": "Founder", "founder_bio": "Building software that actually understands the physical world to map, design, build, and operate infrastructure.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/alexbaikovitz/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1a4a4a7ee706d2b46a02c20f17ad12c3b880cfe1.jpg" }, { "user_id": 778495, "full_name": "Haowen Shi", "title": "Founder", "founder_bio": "Building software to efficiently create actionable 3D maps for critical infrastructure.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/haowensh/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b5f21444a01d1732352d40eec71971318478ace0.jpg" } ], "jobs": [ { "id": 95817, "title": "QA Survey Technician", "url": "https://www.ycombinator.com/companies/mach9/jobs/zZBxbuX-qa-survey-technician", "location": "San Francisco", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "$80K - $100K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 95818, "title": "Solutions Consultant", "url": "https://www.ycombinator.com/companies/mach9/jobs/osChnZ4-solutions-consultant", "location": "Remote / Remote (US)", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 95819, "title": "ML Engineer, Research", "url": "https://www.ycombinator.com/companies/mach9/jobs/gsr2Jt7-ml-engineer-research", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$180K - $300K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 95820, "title": "Head of ML", "url": "https://www.ycombinator.com/companies/mach9/jobs/6fEYLNX-head-of-ml", "location": "San Francisco / Remote (US)", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "$275K - $400K", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 109677, "title": "Founding Recruiting Lead", "url": "https://www.ycombinator.com/companies/mach9/jobs/aFHEXEy-founding-recruiting-lead", "location": "San Francisco", "type": "Full-time", "role": "Recruiting & HR", "role_type": "Recruiter", "salary_range": "$150K - $200K", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 109678, "title": "Solutions Engineer", "url": "https://www.ycombinator.com/companies/mach9/jobs/R3s4Kex-solutions-engineer", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$150K - $200K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 109679, "title": "Founding People Operations Lead", "url": "https://www.ycombinator.com/companies/mach9/jobs/WcSlS8P-founding-people-operations-lead", "location": "San Francisco", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "$130K - $180K", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 109680, "title": "Community Marketing Manager", "url": "https://www.ycombinator.com/companies/mach9/jobs/TrHOo1g-community-marketing-manager", "location": "San Francisco", "type": "Full-time", "role": "Support", "role_type": null, "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 109681, "title": "Head of Growth", "url": "https://www.ycombinator.com/companies/mach9/jobs/BWLMI1q-head-of-growth", "location": "San Francisco", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "$180K - $220K", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 109682, "title": "Software Engineer - Test Automation (SDET)", "url": "https://www.ycombinator.com/companies/mach9/jobs/RBOssgq-software-engineer-test-automation-sdet", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$130K - 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$400K", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 113501, "title": "ML Engineer, Product", "url": "https://www.ycombinator.com/companies/mach9/jobs/uUwtMzD-ml-engineer-product", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$180K - $300K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 114030, "title": "ML Infrastructure Engineer", "url": "https://www.ycombinator.com/companies/mach9/jobs/6vBDUBp-ml-infrastructure-engineer", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$160K - $250K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 115423, "title": "Perception Intern", "url": "https://www.ycombinator.com/companies/mach9/jobs/iaBeLx3-perception-intern", "location": "San Francisco", "type": "Internship", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": null, "visa": "US citizen/visa only", "skills": [] }, { "id": 116444, "title": "Business Development Representative", "url": "https://www.ycombinator.com/companies/mach9/jobs/15HcGWq-business-development-representative", "location": "San Francisco", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$105 - $120", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] } ], "news": [ { "title": "Mach9 Unveils Digital Surveyor 2 A New Standard For Lidar Feature Extraction", "url": "https://informedinfrastructure.com/post/mach9-unveils-digital-surveyor-2-a-new-standard-for-lidar-feature-extraction", "date": "Mar 20, 2026" }, { "title": "Between the Scanner and the Deliverable: How Mach9 is Building the Missing Layer in Geospatial Production", "url": "https://www.xyht.com/surveying/between-the-scanner-and-the-deliverable-how-mach9-is-building-the-missing-layer-in-geospatial-production/", "date": "Mar 19, 2026" }, { "title": "Mach9 Unveils an AI-Assisted Workflow Focused on Trust and Control at Scale", "url": "https://www.geoweeknews.com/sponsored/mach9-unveils-an-ai-assisted-workflow-focused-on-trust-and-control-at-scale", "date": "Feb 10, 2026" }, { "title": "Mach9 wants to create maps 30 times faster than previous standards | Geo Week News | Lidar, 3D, and more tools at the intersection of geospatial technology and the built world", "url": "https://www.geoweeknews.com/sponsored/mach9-digital-surveyor-lidar-data-feature-extraction-automation", "date": "Feb 06, 2024" }, { "title": "Mach9 launches new geospatial software platform aimed at infrastructure space", "url": "https://www.geoweeknews.com/news/tech-reality-capture-mach9-launches-new-geospatial-software-platform-aimed-at-infrastructure-space?utm_source=social&utm_medium=linkedin&utm_campaign=5msocial", "date": "Mar 16, 2023" } ], "launches": [ { "id": 99241, "title": "Mach9 - Make Maps Fast. AI-Powered CAD Software for Reality Capture", "tagline": "We help infrastructure survey and engineering teams turn raw point cloud data into engineering-ready CAD/GIS deliverables up to 100x faster.", "body": "Hi everyone! \n\nWe’re [Alex](https://www.linkedin.com/in/alexbaikovitz/), [Zach](https://www.linkedin.com/in/zachsussman/), [Haowen](https://www.linkedin.com/in/haowensh/), and [Michael ](https://www.linkedin.com/in/mmong/)- co-founders of [Mach9](https://mach9.ai/). \n\n**📍TLDR**: \n\nMach9's Digital Surveyor 2 is a geospatial platform that turns LiDAR point clouds into engineering-ready deliverables up to 100x faster. Its AI-powered extraction engine identifies and extracts linear features — including curbs, pavement edges, guardrails, and barriers — and learns from each user's edits to improve accuracy over time.\n\nSurvey and engineering teams at Langan, Olsson, HDR, Woolpert, Michael Baker International, and major utilities and state DOTs already use it in production.\n\nCheck out our Digital Surveyor 2 Launch Video:\n\n[**https://youtu.be/XoISK5nx87E?si=mzcrxg5uI3hynSm2**](https://youtu.be/XoISK5nx87E?si=mzcrxg5uI3hynSm2)\n\n**❌ The Problem**\n\nEvery road, bridge, fiber network, and utility corridor project starts with a survey. Increasingly, that survey is done with LiDAR scans encompassing millions of points.\n\n**But here's the thing**: Collecting data isn't the hard part anymore, turning it into engineering ready deliverables is. Today, that work is being done manually. Skilled technicians sit in front of a screen and trace features one by one across potentially thousands of features. Paint lines, curbs, poles, signs, guardrails. Mile after mile.\n\n**As a result**: Firms turn down work they could win, deadlines slip, and the most expensive bottleneck of the workflow is the part that hasn't changed in 20 years.\n\n**✅ Our Solution**\n\nDigital Surveyor 2 is a web-based CAD application where AI works alongside drafters to extract features from point cloud data dramatically faster — without sacrificing the precision their clients require.\n\nHere's what makes it different:\n\n🔹 **AI that drafts with you**. \n\nThe feature extraction engine in Digital Surveyor 2 suggests linear features, such as curbs, pavement edges, guardrails, and barriers directly from LiDAR point clouds — and adapts to the user’s drawing patterns. As users draw, the software picks up on their patterns and refines its suggestions in real time.\n\n![uploaded image](/media/?type=post&id=99241&key=user_uploads/311199/ca66f2e8-267b-4693-83ec-81b92eabb558)\n\n🔹 **Field-to-finish in one environment**. \n\nIngest point cloud data from any system such as RIEGL, Trimble, or Leica scanners. Extract features with AI-assisted workflows and precision tools. Easily QA everything in 3D. Export directly into AutoCAD, MicroStation, or ESRI. No switching between tools. No preprocessing pipeline.\n\n🔹 **Built for the people who do this work**. \n\nDS2 was designed so that a surveyor who knows where points go in the field can be productive on day one. Surveyors, field techs, and project managers can easily be working in it with minimal ramp time or CAD expertise.\n\n![uploaded image](/media/?type=post&id=99241&key=user_uploads/311199/e5e82676-f1fd-4bcd-bd86-fcca46636e29)\n\n🙏 **Our Ask**\n\n* **👉 Follow us** — Stay up to date with what we're building. Follow Mach9 on[ ](https://www.linkedin.com/company/mach9)[LinkedIn](https://www.linkedin.com/company/mach9geo).\n* **🔗 Intro us** — Know someone at a electric / telecom utility, data center owner, DOT, or survey/engineering firm that works with LiDAR or mobile mapping data? A warm intro goes a long way. We're especially looking to connect with survey and engineering leaders, mobile mapping teams, CAD/GIS technicians, and geospatial production leads.\n* **🚀 Try it yourself** — If your team is turning point clouds into deliverables today, we'd love to show you what DS2 can do. [Get started here](http://mach9.ai/get-started?utm_source=YC&utm_medium=article&utm_campaign=launch_post).\n* 💼 **We're hiring** — We're building engineering software to transform the $3 trillion global infrastructure industry. If you want to work on hard problems at the intersection of AI, geospatial, and computer graphics, we're scaling across GTM, engineering, and operations. Check out our open roles [here](https://jobs.ashbyhq.com/mach9).\n\n![uploaded image](/media/?type=post&id=99241&key=user_uploads/311199/d7592b72-f824-4cf8-9921-48b5b14674fc)\n\n", "url": "https://www.ycombinator.com/launches/Pof-mach9-make-maps-fast-ai-powered-cad-software-for-reality-capture", "votes": 29, "created_at": "2026-03-30T20:07:04.564Z" } ] }, { "id": 25320, "name": "Wingback", "slug": "wingback", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/de4dd6debd3ed51accf437ceb7b1b316e5fc5f36.png", "website": "https://www.wingback.com/", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Wingback provides tools and APIs for SaaS pricing and packaging. We are infrastructure that allows SaaS startups to deploy any set of features of their product using any pricing model. It enables non-technical teams to implement pricing and packaging changes and execute product-led growth campaigns without engineering involvement.", "one_liner": "Wingback provides tools and APIs for SaaS pricing and packaging.", "team_size": 12, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1639087626, "tags": [ "Fintech", "SaaS", "API", "Enterprise", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Inactive", "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/wingback", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2022/wingback.json", "year_founded": 2021, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/wingbackapp", "x_url": "https://twitter.com/wingbackapp", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/wingback", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/de4dd6debd3ed51accf437ceb7b1b316e5fc5f36.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Nicolas Dessaigne", "url": "https://www.ycombinator.com/people/nicolas-dessaigne" }, "founders": [ { "user_id": 614533, "full_name": "Torben Friehe", "title": "Founder", "founder_bio": "I've been fascinated by technology since early childhood, which led me to founding 1aim, an IoT startup. I ran 1aim together with my co-founder Yann for seven years before it was acquired. After that, I provided advice to some founder friends. In late 2020, I joined On Deck. After many conversations with On Deck fellows in SaaS, Yann and I started building Wingback. Besides startups, I'm interested in Formula 1, cars, and planes, but also in architecture, fashion, and history.", "is_active": false, "linkedin_url": "http://linkedin.com/in/tfriehe", "x_url": "https://twitter.com/tfriehe_", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f7a18b0d5f2540e3332864a2b99ec7e039a93bd8.jpg" } ], "jobs": [], "news": [ { "title": "Has Y Combinator’s new deal changed the early-stage investing game?", "url": "https://techcrunch.com/2022/01/13/has-y-combinators-new-deal-changed-the-early-stage-investing-game/", "date": "Jan 13, 2022" }, { "title": "How to hire without resumes from social media", "url": "https://www.fastcompany.com/90712236/we-skipped-resumes-and-sourced-candidates-directly-from-online-communities-like-discord", "date": "Jan 13, 2022" }, { "title": "Y Combinator-Backed Wingback Raised $1.9 Million Using This Pitch Deck", "url": "https://www.businessinsider.com/y-combinator-backed-wingback-19-million-using-this-pitch-deck-2021-11", "date": "Nov 09, 2021" } ], "launches": [] }, { "id": 25537, "name": "Cerebrium", "slug": "cerebrium", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/730897d24e909ee905c210f74fec1b439d21c4a7.png", "website": "https://www.cerebrium.ai/", "all_locations": "New York City, NY, USA", "long_description": "Cerebrium is a serverless infrastructure platform for AI applications. We make it easier for companies to build and deploy AI based applications. We offer Serverless GPU's with low cold start times, over 12 varieties of GPU chips, allow you to run large scale batch jobs, run realtime voice applications and much more. We are used by the teams at Tavus, CivitAI, Twilio and many more. \r\n\r\nCustomers typically experience 40% in cost savings when compared to using traditional cloud providers and can scale models to more than 10K requests per minute with minimal engineering overhead. ", "one_liner": "Serverless Infrastructure Platform for AI", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1641981854, "tags": [ "Machine Learning", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "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/cerebrium", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2022/cerebrium.json", "year_founded": 2021, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/cerebrium", "x_url": "https://twitter.com/cerebriumai", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/730897d24e909ee905c210f74fec1b439d21c4a7.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": 704363, "full_name": "Michael Louis", "title": "Founder", "founder_bio": "Michael is a South African entrepreneur that has founded multiple businesses across ML & A.I, Blockchain, Retail, and consumer marketplaces. Previously he was the CTO of OneCart which sold to Walmart/Massmart for an undisclosed sum. Currently, he is a co-founder at Cerebrium, a machine learning platform that makes it easier for businesses to train, deploy and monitor ML models in production.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/michael-louis-94104a113/", "x_url": "https://twitter.com/MichaelLouis_za", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/54b64443a0c4ba80ed7cb858105cd333c6837813.jpg" }, { "user_id": 831262, "full_name": "Jonathan Irwin", "title": "Founder", "founder_bio": "Co-founder & CTO of Cerebrium\n\n8+ years experience as a Javascript developer including a lot of time spent in a lead developer role.\n\nBComm undergrad and Finance Honours at the University of Cape Town. Data Science at Tilburg University.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jono-irwin/", "x_url": "https://twitter.com/jonoirwin", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5602f37dccfdb644c18dcdb0789f74f5a2740c09.jpg" } ], "jobs": [], "news": [ { "title": "Cerebrium blog | Cerebrium Raises $8.5M led by Gradient to Scale the Leading High-Performance Serverless AI Platform", "url": "https://www.cerebrium.ai/blog/cerebrium-raises-8-5m-led-by-gradient-to-scale-the-leading-high-performance-serverless-ai-platform", "date": "Jul 08, 2025" } ], "launches": [ { "id": 69873, "title": "Cerebrium: An AWS Sagemaker alternative", "tagline": "A framework that makes it easier to train, deploy and monitor ML models across serverless GPU's", "body": "# TL;DR\n\n[Cerebrium](https://www.cerebrium.ai/) is a machine learning framework that makes it easy to train, deploy and monitor ML models. You can:\n\n* [⚙️](https://emojipedia.org/gear/)**Train** LLM’s such as FlanT5, GPT-NEOx-20b etc with a few lines of code (beta)\n* [🚀](https://emojipedia.org/rocket/)**Deploy** LLM’s or even custom models using just one line of code to serverless CPU’s/GPU’s.\n* [📈](https://emojipedia.org/chart-increasing/)**Monitor** your ML models with our built in integrations with Arize and Censius.\n\nHi Everyone! We’re Michael and Jonathan and we are so excited to introduce you to Cerebrium!\n\n# [❌](https://emojiguide.com/symbols/cross-mark/) **The Problem**\n\nImplementing machine learning based applications in a business remains challenging. You have multiple infrastructure concerns, such as expensive GPU’s, scaling issues, fragmented tooling while additionally also struggle to find machine learning talent and keep up with the latest research and techniques. These barriers to entry prohibit smaller companies from implementing machine learning into their business sooner.\n\n# [🚀](https://emojipedia.org/rocket/) **The Solution**\n\nCerebrium helps teams easily train, deploy and monitor machine learning models in production. Using our framework, you can train and deploy models (custom built or LLM’s) to serverless CPU’s/GPU’s using one line of code. You are only charged for inference time and we automatically handle the scaling and the versioning of models.\n\nWhen it comes to training and/or inference, we use the latest research techniques to reduce training and inference times by 20-40%. You just focus on adding value to your use case and we will take care of the rest!\n\n# [⚙️](https://emojipedia.org/gear/) **How it works**\n\n1. Create a free account [here](https://dashboard.cerebrium.ai). You get $10 in free serverless GPU credits.\n2. Install our Python library: **_pip install cerebrium_**\n3. Write one line of code to deploy your custom model or deploy a pre-built template\n4. Get an endpoint that automatically scales based on traffic\n5. Check out our [documentation](https://docs.cerebrium.ai) to see a greater list of examples and features.\n\n![Demo](https://cerebrium-assets.s3.eu-west-1.amazonaws.com/Cerebrium-Demo-1-March-2023.webp)\n\n### [🤔](https://emojipedia.org/thinking-face/) **Why we Built Cerebrium**\n\nAt our previous business, machine learning made a huge impact across various teams but it took months of building, testing and experimenting to get it there. We wanted to make the same sort of impact accessible to companies who don’t have the resources or know-how - and of course make it available in a fraction of the time\n\n### [🙏](https://emojidictionary.emojifoundation.com/folded_hands) **Our Asks**\n\n* Try out our framework! It takes the average user less than 4 minutes to get a model up and running (yes even if its custom) and give us your feedback - its free.\n* Share our framework with people you know who are building ML based applications or are struggling to fine-tune/deploy their ML models.\n* Join our [Slack](https://join.slack.com/t/cerebriumworkspace/shared_invite/zt-1lvbha401-lPsnCWYnVlGymGKS2E5fvA) and [Discord](https://discord.gg/ATj6USmeE2) communities\n* Upvote and share this post!", "url": "https://www.ycombinator.com/launches/IAz-cerebrium-an-aws-sagemaker-alternative", "votes": 21, "created_at": "2023-03-02T17:32:30.939Z" } ] }, { "id": 25572, "name": "RDash", "slug": "rdash", "former_names": [ "Rolling Banners", "91Squarefeet", "Rdash" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/def911c8f3c9b81c8e514a4f1b29d88c06452d30.png", "website": "https://www.rdash.io", "all_locations": "Gurugram, HR, India", "long_description": "RDash is an AI powered construction management software that unifies site teams, procurement, design and finance - out of box; Without requiring customer to stitch anything. We are fastest to deploy and compatible with most accounting and ERP tools.", "one_liner": "AI Powered Construction Management Software", "team_size": 80, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1639295631, "tags": [ "SaaS", "Construction", "B2B", "Architecture", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "India", "South Asia" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/rdash", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2022/rdash.json", "year_founded": 2021, "city": "Gurugram", "country": "IN", "linkedin_url": "https://www.linkedin.com/company/r-dash", "x_url": "https://x.com/rdash_io", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/def911c8f3c9b81c8e514a4f1b29d88c06452d30.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": 597723, "full_name": "Amit Bansal", "title": "Founder", "founder_bio": "Co-founder and CEO at Rdash.\n\nI am a Civil Engineering graduate and worked as a structural designer at WSP. I have done postgraduate in supply chain management and had a short stint at Madura Fashion (The largest fashion retailer in India) before co-founding quifers.com. Quifers is a logistics SaaS platform for big enterprises that got acquired in May 2021. \n\n\n", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/amitbansal91/", "x_url": "https://twitter.com/abansal91", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e9a0c2681a3d886085e2e45a3da427123ecb2ed9.jpg" }, { "user_id": 839383, "full_name": "Puneet Bansal", "title": "Founder", "founder_bio": "Product Person\nI did my graduation in Civil engineering from IIT Delhi in 2012 and worked at WSP as a facilities designer-BIM professional for retail, mall, and engineering projects of UK and middle-east.\nI took to startup journey by joining Quifers ( a logistics a SAAS platform) as product manager in 2017. \nIn 2019, I co-founded 91Squarefeet.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/puneet-bansal-15656441/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1d329a927109337bfa03900b22af80914ade9649.jpg" } ], "jobs": [], "news": [ { "title": "91Squarefeet Raises $10 Mn To Help Companies Build Retail Stores", "url": "https://inc42.com/buzz/91squarefeet-raises-10-mn-to-help-companies-build-retail-stores/", "date": "Sep 13, 2022" }, { "title": "91 Squarefeet News: 91 Squarefeet capitalises on retail expansion, grows 20% month on month despite Covid - The Economic Times", "url": "https://economictimes.indiatimes.com/industry/services/retail/91-squarefeet-capitalises-on-retail-expansion-grows-20-month-on-month-despite-covid/articleshow/90438888.cms", "date": "Mar 25, 2022" }, { "title": "Retail platform 91Squarefeet raises pre-seed funding from Omphalos Ventures, others | VCCircle", "url": "https://www.vccircle.com/retail-platform-91squarefeet-raises-pre-seed-funding-from-omphalos-ventures-others", "date": "Jan 07, 2022" } ], "launches": [] }, { "id": 25725, "name": "Argo", "slug": "argo", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cbfb1f91a00cc67df3353e09e5e213ec32f77317.png", "website": "https://Argo.LA", "all_locations": "Los Angeles, CA, USA; Remote", "long_description": "A platform for brands and creator to monetize their video entertainment more efficiently, build an engaged community and reward their fans. \r\n", "one_liner": "A social streaming platform powered by creators and fans ", "team_size": 10, "industry": "Consumer", "subindustry": "Consumer -> Content", "launched_at": 1646632831, "tags": [ "Crypto / Web3", "Consumer", "Entertainment", "Social", "Infrastructure" ], "tags_highlighted": [ "Crypto / Web3" ], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "Consumer", "Content" ], "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/argo", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2022/argo.json", "year_founded": 2021, "city": "Los Angeles", "country": "US", "linkedin_url": "https://www.linkedin.com/company/43319673", "x_url": "https://twitter.com/Watch_Argo", "fb_url": "https://www.facebook.com/WatchArgo/", "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/cbfb1f91a00cc67df3353e09e5e213ec32f77317.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 395477, "full_name": "Arcadiy Golubovich", "title": "Founder", "founder_bio": "Graduate Moscow Economics School International Baccalaureate 2005. \nGraduate BA University of Arts London Central St Martins 2008. \nLiving in LA, working in film production and VC media tech. \nDeeply passionate about story telling, technology and psychology. \nStarted Argo in 2021 with a mission to empower independent filmmakers to tell stories that would otherwise never be told. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/arcadiy-golubovich-9a515125/", "x_url": "https://twitter.com/ArcadiyG", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/cc7460f697e0886cb3e05306bf5a52769bd6dfce.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 25777, "name": "BotCity", "slug": "botcity", "former_names": [], "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, "tags": [ "Developer Tools", "Open Source", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "Brazil", "Latin America", "Remote", "Fully Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/botcity", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2022/botcity.json", "year_founded": 2020, "city": "Campinas", "country": "BR", "linkedin_url": "https://www.linkedin.com/company/botcity/", "x_url": "https://twitter.com/BotcityDev", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/botcity-ce94", "github_url": "https://github.com/botcity-dev", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/7c9d51d01f280768899d76eff8f510583a2e1614.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Nicolas Dessaigne", "url": "https://www.ycombinator.com/people/nicolas-dessaigne" }, "founders": [ { "user_id": 831999, "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.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/lorhan/", "x_url": "https://twitter.com/lorhancaproni", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/bfc577683beeb0e52e9f1bd3d95153ad08198106.jpg" }, { "user_id": 860246, "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/", "x_url": "https://twitter.com/gabriel_archanj", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1a158c3dd00ed24edf0ef4a507aad99d4bdce9be.jpg" } ], "jobs": [], "news": [ { "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/", "date": "Feb 11, 2022" }, { "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" }, { "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" } ], "launches": [] }, { "id": 25871, "name": "Brainboard", "slug": "brainboard", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a1940cbdacec83b1df06f778aab51ef87295bad3.png", "website": "https://www.brainboard.co", "all_locations": "New York City, NY, USA; Paris, Île-de-France, France; Remote", "long_description": "Brainboard is a collaborative and end-to-end solution for engineers to visually design & manage their Cloud infrastructures.\r\nWe allow companies to lower the learning curve while moving to IaC, build a self serve model, have a service catalog to not reinvent the wheel.\r\n\r\nBoth technical profiles with 25+ years of combined expertise and after working together at a major French Cloud provider, Chafik and Jeremy launched Brainboard in 2020.", "one_liner": "Visually design and manage cloud infrastructures.", "team_size": 9, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1645991861, "tags": [ "Developer Tools", "DevOps", "Cloud Computing", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "France", "America / Canada", "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/brainboard", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2022/brainboard.json", "year_founded": 2020, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/brainboard-co", "x_url": "https://twitter.com/brainboard_co", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/brainboard", "github_url": "https://github.com/brainboard", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/a1940cbdacec83b1df06f778aab51ef87295bad3.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Nicolas Dessaigne", "url": "https://www.ycombinator.com/people/nicolas-dessaigne" }, "founders": [ { "user_id": 858189, "full_name": "Chafik Belhaoues", "title": "Founder", "founder_bio": "- Engineer with 17 years of experience on infrastructures (SRE, cloud architect, then software developer)\n- Former CTO of Scaleway (french cloud provider)\n- CEO at Brainboard.co", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/chafik-belhaoues-%E2%98%81-4145b320/", "x_url": "https://twitter.com/ChafikBelhaoues", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/da747ede5d673ae5a5f0d9fc0c7db1c435dd2634.jpg" }, { "user_id": 848539, "full_name": "Jeremy Albinet", "title": "Founder", "founder_bio": "- 10 years designing Cloud architectures and building infrastructures\n- co-founder of Brainboard\n- former SRE @Scaleway", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jeremy-albinet/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0c9f80e3928db234f29e441262a0149df1f3ca22.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 26144, "name": "MSPilot", "slug": "mspilot", "former_names": [ "Personabo", "EasyCode (Formerly Personabo)", "EasyCode", "OpenBuilder" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/af6da8314f45312f4d972daa5d200eefd67b2ec8.png", "website": "https://mspilot.io", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Make AI your next recurring revenue line.\r\n\r\nMSPilot helps Managed Service Providers deploy, govern, and monetize AI agents across their entire client base. Author an agent once, roll it out to your whole book, and bill for every token - with markup.", "one_liner": "Turn AI adoption into a recurring revenue line.", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1680284500, "tags": [ "Generative AI", "B2B", "No-code", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Fall 2025", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/mspilot", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/mspilot.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/mspilot", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/af6da8314f45312f4d972daa5d200eefd67b2ec8.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": 690363, "full_name": "Paul Li", "title": "Founder", "founder_bio": "Paul is a three time founder. CS @ UWaterloo.\nPreviously shipped coding extensions to 1.5M developers. \n", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/hey-paul/", "x_url": "https://x.com/PaulTheLi", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e0d7413beeb4dafe34f215ef59323ff88d60ac1f.jpg" }, { "user_id": 693712, "full_name": "James Jiang", "title": "Founder", "founder_bio": "Unlocking human potential with AI\nSerial Entrepreneur\nEx-Amazon Software Developer", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jamesdreamcrafters/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c8999cbcac17d038841a4908688b5d8be254bce6.jpg" } ], "jobs": [ { "id": 98296, "title": "Founding Engineer - AI Infra (Hybrid, Lviv)", "url": "https://www.ycombinator.com/companies/mspilot/jobs/CuNpIm2-founding-engineer-ai-infra-hybrid-lviv", "location": "Lviv, Lviv Oblast, UA / Remote (UA)", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$60K - $100K", "equity_range": "1.00% - 2.00%", "experience": "3+ years", "visa": "US citizenship/visa not required", "skills": [ "Amazon Web Services (AWS)", "Nginx", "PostgreSQL", "Python", "React", "TypeScript", "Vector Databases", "AI Agents" ] }, { "id": 98618, "title": "Founding GTM Specialist - Hybrid, Ukraine/Poland", "url": "https://www.ycombinator.com/companies/mspilot/jobs/jPKyaEN-founding-gtm-specialist-hybrid-ukraine-poland", "location": "Lviv, Lviv Oblast, UA / PL / Remote (UA; PL)", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$30K - $42K", "equity_range": "0.50% - 1.00%", "experience": "3+ years", "visa": "US citizenship/visa not required", "skills": [] } ], "news": [], "launches": [ { "id": 95336, "title": "OpenBuilder: Open source alternative to Lovable", "tagline": "Where vibe coders actually finish their projects. ", "body": "Hey YC, we are [Paul](https://www.linkedin.com/in/hey-paul/) and [James](https://www.linkedin.com/in/jamesdreamcrafters/), cofounders at [OpenBuilder](https://www.linkedin.com/company/openbuilder/). 👋\n\n### **TL;DR**\n\n**OpenBuilder is the open source alternative to Lovable — where non-technical builders actually finish their projects.**\n\nhttps://youtu.be/yVgGsf3nN44\n\n### 🔴 The Problem: vibe coding is a slot machine\n\n**Pay for credits, pull the lever, pray things work.**\n\nVibe coding has brought millions of non-technical users into building. But over 80% can't finish what they start. The magic fades as projects grow — bugs multiply, progress stalls, and builders get stuck\n\nThree core problems block non-technical builders:\n\n1. too expensive — costs spiral out of control\n2. too many bugs — issues pile up faster than they can fix\n3. getting help is nearly impossible — especially on closed platforms where backend/integration code is hidden\n\n![uploaded image](/media/?type=post&id=95336&key=user_uploads/690363/7a1df823-cdcf-4647-a6c4-6585daa3c4cf)\n\n### 🟢 The Solution:\n\n### At OpenBuilder, users build for free on a truly open platform, and pay to get unstuck from a real dev.\n\n**Vibe code without limits.**\n\nOpenBuilder uses optimized open-source models to match Claude Sonnet 4's performance—making building completely free.\n\n![uploaded image](/media/?type=post&id=95336&key=user_uploads/690363/cf0cf66d-a3da-4ef2-aa68-e1bf86fcd09b)\n\n**Pay to get unstuck.**\n\nOur interactive debugger helps you first. If that doesn't solve it, you can escalate to a real developer who already has your project context.\n\n![uploaded image](/media/?type=post&id=95336&key=user_uploads/690363/1be25b13-5159-4254-acd8-3ff15d2e8c9a)\n\n**Truly open platform, no lock-in.**\n\nOpenBuilder is truly open. It's built on VS Code, so you can swap in your own AI model, try different agents, or export your entire codebase anytime.\n\n### Team\n\nPaul & James have known each other for over 10 years. They met while studying CS at the University of Waterloo.\n\nBefore OpenBuilder, they built EasyCode — a popular context-aware coding assistant installed by over 1.5M developers between VS Code and JetBrains. Now they are applying similar technologies to help non-technical builders turn their ideas into reality.\n\n![uploaded image](/media/?type=post&id=95336&key=user_uploads/690363/c8743abd-9d52-49d6-bc36-2d17fe05fad7)\n\n### Ask\n\n**We're making building accessible to everyone. Non-technical founders shouldn't just start projects—they should finish and ship them.**\n\nHere is how you can help. 🙂\n\n* Follow us on [X](https://x.com/theopenbuilder) and [LinkedIn](https://www.linkedin.com/company/openbuilder/) and share the launch!\n* We're open sourcing our codebase soon. Want to contribute early? Email [paul@theopenbuilder.com](mailto:paul@theopenbuilder.com)\n\n![uploaded image](/media/?type=post&id=95336&key=user_uploads/690363/7c904f27-3027-481d-9d3f-aeee10be3e42)\n\n", "url": "https://www.ycombinator.com/launches/Ong-openbuilder-open-source-alternative-to-lovable", "votes": 60, "created_at": "2025-11-09T01:30:34.921Z" } ] }, { "id": 26657, "name": "HyperDX", "slug": "hyperdx", "former_names": [ "DeploySentinel" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d08fa4a9e984544038c06b9790dd7d376a594c35.png", "website": "https://hyperdx.io/", "all_locations": "San Francisco, CA, USA", "long_description": "HyperDX assists engineers in resolving production bugs more quickly with simple workflows that take you from alert to resolution. You can get set up in a matter of minutes and correlate debug telemetry all in one place, including logs, metrics, traces, and browser session replays, allowing you to resolve issues faster than ever before.\r\n\r\nHyperDX is open source and built on top of Clickhouse and S3, so customers can enjoy ten times the savings when compared to traditional vendors like Datadog.", "one_liner": "Open-source, dev-friendly observability.", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1657691194, "tags": [ "Developer Tools", "SaaS", "B2B", "Open Source", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2022", "status": "Acquired", "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/hyperdx", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2022/hyperdx.json", "year_founded": 2022, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/hyperdx", "x_url": "https://twitter.com/hyperdxio", "fb_url": null, "cb_url": null, "github_url": "https://github.com/hyperdxio", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/d08fa4a9e984544038c06b9790dd7d376a594c35.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/b0c290fbb11edd40600aa6cdae2cff9a43aa36f6.png" ], "primary_partner": { "name": "Nicolas Dessaigne", "url": "https://www.ycombinator.com/people/nicolas-dessaigne" }, "founders": [ { "user_id": 118499, "full_name": "Michael Shi", "title": "Founder", "founder_bio": "Currently building HyperDX (acq'd ClickHouse)", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/mikeshi42/", "x_url": "https://twitter.com/MikeShi42", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/250ff48efb35a783fcd5e27dea460b54a73c23b4.jpg" }, { "user_id": 346706, "full_name": "Warren Lee", "title": "Founder", "founder_bio": "Previously built a profitable company from 0 to millions ARR", "is_active": true, "linkedin_url": "https://linkedin.com/in/warren-jonhow-lee-7b91b3187", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/fbab8d65376adfa2ad3a03aef9debd96b86e8591.jpg" } ], "jobs": [], "news": [ { "title": "ClickHouse Acquires HyperDX to Accelerate the Future of Open-Source Observability - HyperDX Blog", "url": "https://www.hyperdx.io/blog/clickhouse-acquires-hyperdx-to-accelerate-the-future-of-open-source-observability", "date": "Mar 13, 2025" } ], "launches": [] }, { "id": 26663, "name": "Denormalized", "slug": "denormalized", "former_names": [ "Probably Nothing Labs" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b63e1460304048d366b7e3939ef213373a7766f2.png", "website": "https://www.denormalized.io/", "all_locations": "San Francisco, CA, USA", "long_description": "Denormalized is a serverless real-time data platform that allows users to query data quickly while eliminating the need to manage complex infrastructure. It enhances developer productivity by automating schema inference from sample data and simplifying data stream creation allowing engineers to go from idea to production fast. Denormalized supports SQL for data transformations without needing complex stream processing systems like Flink.", "one_liner": "serverless platform for real-time data", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1658936956, "tags": [ "Analytics", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2022", "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/denormalized", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2022/denormalized.json", "year_founded": 2022, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/probably-nothing-labs", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/b63e1460304048d366b7e3939ef213373a7766f2.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 698248, "full_name": "Amey Chaugule", "title": "Founder", "founder_bio": "Spent 10+ years working at the intersection of ML & Data Infra.\n\nWorking on Uber's Marketplace Dynamics 2016-2020 was an honour of a lifetime. I can nerd out about pricing algorithms and marketplace optimizations till kingdom come.", "is_active": false, "linkedin_url": "https://www.linkedin.com/in/ameychaugule/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/54b9fb4c7224819d06fcba138730d3e1a8c7da88.jpg" }, { "user_id": 9674, "full_name": "Matt Green", "title": "Founder", "founder_bio": "Data things.", "is_active": false, "linkedin_url": "https://www.linkedin.com/in/mgreen9", "x_url": "https://twitter.com/IAmMattGreen", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/fa894df0a424af40b0b1ffd5873da1acccb76b08.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 64973, "title": "Probably Nothing Labs - Databricks for Web3", "tagline": "Real-time Indexer-as-a-Service to help Web3 teams power data backends for their apps in days", "body": "**🤔 The Problem**\n\nIndexing public blockchains is a major pain!\n\nEngineers need to build resilient poll loops around chain specific validators that request, parse, and track raw blocks, transactions and event logs as they arrive. This work requires in-depth knowledge of specific protocols, smart contract ABIs, and stateful stream processing (not to mention handling chain re-org or tracking the mempool). All of this work just to build a backend for your Uniswap position tracking dashboard or that Instagram for NFTs app.\n\nNevermind having to build systems to monitor individual positions for collateral drops in DeFi lending protocols. \n\n**🤌 Our Solution**\n\nWe built **Gigabrain**, a best-in-class blockchain indexer with support for Ethereum and Solana. Using advanced stateful streaming techniques, Gigabrain is able to parse, index, and store transactions within seconds of blocks being confirmed. In addition, we’ve created a versioned registry of all smart contracts on Ethereum as well its L2s.\n\nWith Gigabrain you can —\n\n* Run **complex stateful aggregations** for **on-chain events** as soon as - or before - they show up on the blockchain.\n* Never have to worry about keeping track of contract specific ABIs with our **Smart Contract Registry**.\n* **Run live SQL** against the **Ethereum mempool** (we use a globally distributed set of nodes that we manage ourselves).\n* Run **large scale analytics** against our datalake as well as **power robust data backends** for your own Web3 apps.\n\n[🎬](https://emojipedia.org/clapper-board/) **The Demo**\n\nCheck out our [short demo on Loom](https://www.loom.com/share/d4784d7e2a9f4503bd2beab5e070e840).\n\n**📞 Our Ask**\n\nIf you or anyone else in your network -\n\n* Need to work with on-chain data at scale or in real-time\n* Parse a wide array of smart contract specific on-chain events\n* Have the need to build sophisticated on-chain monitoring solutions for DeFi protocols or NFT Marketplaces\n\nPlease get in touch with us!\n\n**Amey**: [amey@probablynothinglabs.xyz](mailto:amey@probablynothinglabs.xyz) , **Telegram**: @ambrood, **Discord**: ambrood#9366\n\n**Matt**: [matt@probablynothinglabs.xyz](mailto:matt@probablynothinglabs.xyz), **Telegram**: @mgreenn, **Discord**: mattt#2076", "url": "https://www.ycombinator.com/launches/Gtx-probably-nothing-labs-databricks-for-web3", "votes": 18, "created_at": "2022-07-28T14:40:55.685Z" } ] }, { "id": 26837, "name": "Unify", "slug": "unify", "former_names": [ "Deep Ivy Inc.", "Ivy", "Unify", "Ivy" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/90e213981ccee521dac2989633ba8959528e318e.png", "website": "https://unify.ai", "all_locations": "London, England, United Kingdom; Remote", "long_description": "Building the next frontier of models that continually learn from a stream of experience.", "one_liner": "Models that keep learning", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Productivity", "launched_at": 1657390616, "tags": [ "Reinforcement Learning", "Open Source", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2023", "status": "Active", "industries": [ "B2B", "Productivity" ], "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/unify", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/unify.json", "year_founded": 2023, "city": "London", "country": "GB", "linkedin_url": "https://www.linkedin.com/company/unifyai", "x_url": "https://twitter.com/letsunifyai", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/unify-ai", "github_url": "https://github.com/unifyai", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/90e213981ccee521dac2989633ba8959528e318e.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": 949841, "full_name": "Daniel Lenton", "title": "Founder", "founder_bio": "Love to dive deep into engineering rabbit holes 🕳️🐇", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/daniellenton", "x_url": "https://twitter.com/DanielLenton1", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7f9d4085e00b2a0b42cbb6845e6ad5a9a6d40bb8.jpg" } ], "jobs": [], "news": [ { "title": "In 2024, it really is better to run a startup in San Francisco, according to data and founders who’ve relocated | TechCrunch", "url": "https://techcrunch.com/2024/08/25/in-2024-it-really-is-better-to-run-a-startup-in-san-francisco-according-to-data-and-founders-whove-relocated/", "date": "Aug 25, 2024" }, { "title": "Unify helps developers find the best LLM for the job | TechCrunch", "url": "https://techcrunch.com/2024/05/22/unify-helps-developers-find-the-best-llm-for-the-job/", "date": "May 22, 2024" } ], "launches": [ { "id": 81027, "title": "Unify - The best LLM on every prompt ✨", "tagline": "Dynamically route each prompt to the best LLM, so you can balance quality, speed and cost with ease", "body": "**TL;DR** Unify dynamically routes each prompt to the best LLM and provider so you can balance quality, speed, and cost with ease ✨\n\n🔀 [Try out our router in the browser](https://unify.ai/chat?default=true)\n\n💸 [Sign up now and get $50 free credits!](https://console.unify.ai/)\n\n🧑‍💻 [Get a Demo](https://calendly.com/unify-chat/general)\n\n**💥Problem** \\\nThere is a new LLM emerging almost every week, and all LLM applications have unique requirements for output quality, cost, and speed. It’s also unclear which models provide the highest quality on your task. This results in lots of manual signups, testing different models, bespoke benchmarking, etc. It’s overwhelming, and the final solution is almost always sub-optimal.\n\n![](https://t9015538723.p.clickup-attachments.com/t9015538723/65677e25-4ec6-4c1a-b235-56ff1fee6552/splash3.png)\n\nMany people give up and just use the largest models for everything. However, you really don't need GPT4 to summarize simple documents. Llama 8B is more than capable and is **15 times faster** and **100 times cheaper**. LLM apps are currently _much_ slower and more expensive than needed 💵🔥⏱️, and also often underperform in output quality because of poorly selected models 📉 (Claude Opus vs. GPT4 vs. Gemni etc.) for your specific prompts.\n\n**🤩 Not Anymore**\n\nUnify automatically routes each prompt to the most suitable model based on your preferences for quality, speed, and cost. Simply tune these three dials and let Unify do all the hard work.\n\n![uploaded image](/media/?type=post&id=81027&key=user_uploads/949841/fa900ddd-6849-408f-9a6c-1ad5dcfb0872)\n\nYour \"easy\" prompts will go to the fastest and cheapest models, and only the \"hard\" prompts will go to the most appropriate heavy lifters, like GPT-4o, Opus, and Gemini. You focus on building your LLM app, and we'll focus on providing the best models, with the fastest providers, at the lowest cost ⚡\n\n![uploaded image](/media/?type=post&id=81027&key=user_uploads/949841/b59ee67a-6566-4728-b146-57b102cf3151)\n\nWatch our [explainer video](https://youtu.be/15wgxK1Cw0E?si=5G04-7tGRKPyxiNa) to learn more about the solution at a high level.\n\n**What Unify Offers ✨**\n\n* **⚙️ Control**: Choose which models and providers to route to and adjust three sliders: quality, cost, and latency.\n* 📈 **Self Improvement**: Unify automatically improves your LLM application over time as new models and providers emerge.\n* 📊 **Observability**: [Compare all models and providers](https://console.unify.ai/dashboard) and see which are best for your needs.\n* ⚖️ **Impartiality**: Unify treats all models and providers equally, ensuring unbiased quality, cost, and speed [benchmarks](https://console.unify.ai/dashboard).\n* 🔑 **Convenience**: With a single API key, [access all models and providers](https://unify.ai/docs/api/first_request.html) behind a single endpoint, queryable individually or via the router.\n* 🧑‍💻 **Focus**: Don't stress about updating models and providers; Unify handles it for you so you can focus on building great LLM products.\n\n**Getting Started 🛠️**\n\n[Sign up](https://console.unify.ai/), select your [router](https://unify.ai/chat?default=true), then `pip install unifyai` and you're ready to go!\n\n```\nfrom unify import Unify\nunify = Unify(\n api_key=\"UNIFY_KEY\",\n endpoint=\"router@q:1\",\n)\nresponse = unify.generate(user_prompt=\"Hello there\")\n```\n\n🙏 **Our Ask**\n\nGive Unify a try, and let us know what you think! [Sign up](https://console.unify.ai/), `pip install unifyai`, take our [router](https://unify.ai/chat?default=true) for a spin, and check out our [product walkthrough](https://youtu.be/ZpY6SIkBosE). If you're excited about Unify, tell a friend about it 😊 If you don’t think it’s useful, please tell us. We’d love to know!", "url": "https://www.ycombinator.com/launches/L4t-unify-the-best-llm-on-every-prompt", "votes": 48, "created_at": "2024-05-22T15:22:53.596Z" } ] }, { "id": 27137, "name": "PrimeVault", "slug": "primevault", "former_names": [ "Exchecker", "Excheqr" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c063ef6501ec4e09baa9f49d2abc635ba2fa65b8.png", "website": "https://www.primevault.com", "all_locations": "Bengaluru, KA, India; Remote", "long_description": "PrimeVault is the all-in-one digital asset and stablecoin platform for enterprises and financial institutions. Built for modern finance, PrimeVault combines secure wallets, programmable treasury, compliance, and market access in one seamless solution. \r\n\r\nWith robust security and modular infrastructure, PrimeVault empowers institutions to issue, manage, and move digital assets at scale.\r\n\r\nDiscover how we makes digital asset finance simple at primevault.com.", "one_liner": "Infrastructure powering stablecoin and digital finance", "team_size": 11, "industry": "Fintech", "subindustry": "Fintech -> Asset Management", "launched_at": 1659127326, "tags": [ "Fintech", "Crypto / Web3", "Payments", "B2B", "Infrastructure" ], "tags_highlighted": [ "Crypto / Web3" ], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2022", "status": "Active", "industries": [ "Fintech", "Asset Management" ], "regions": [ "India", "South Asia", "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/primevault", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2022/primevault.json", "year_founded": 2022, "city": "Bengaluru", "country": "IN", "linkedin_url": "https://www.linkedin.com/company/primevault", "x_url": "https://twitter.com/primevaultHQ", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/excheqr", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/c063ef6501ec4e09baa9f49d2abc635ba2fa65b8.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": 982839, "full_name": "Prashant Upadhyay", "title": "Founder", "founder_bio": "Co-founder @ PrimeVault - turnkey technology platform for enterprises and financial institutions to launch and scale their digital assets use case: stablecoin-powered payments and issuance, RWA tokenization, crypto trading / brokerage and more. Formerly, first PM @ Rippling (YC W17) building and scaling payroll, payments, compliance, risk and accounting products. Math, payments and travel nerd.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/prashant-upadhyay/", "x_url": "https://twitter.com/prashantupd", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/17bbdd3ebf93ec39702cd94d4953478a00f5aa0c.jpg" }, { "user_id": 587423, "full_name": "Vivek Kumar", "title": "Founder", "founder_bio": "Co-founder @ PrimeVault,\nFormer Tech lead at Rippling", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/vivek-kumar-578013119/", "x_url": "https://twitter.com/vivek_kumar_15", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/201e6eab4b6bcbcb45124b879c90179fe3e3a9b3.jpg" } ], "jobs": [ { "id": 65428, "title": "Full-time Backend Engineer", "url": "https://www.ycombinator.com/companies/primevault/jobs/zH4amoV-full-time-backend-engineer", "location": "IN / Remote (IN)", "type": "Full-time", "role": "Engineering", "role_type": "Backend", "salary_range": "$40K - $45K", "equity_range": "", "experience": "3+ years", "visa": "US citizenship/visa not required", "skills": [] }, { "id": 79609, "title": "Marketing & Growth Lead ", "url": "https://www.ycombinator.com/companies/primevault/jobs/3FXwQzR-marketing-growth-lead", "location": "Bengaluru, KA, IN / Bengaluru, Karnataka, IN / Dubai, Dubai, AE", "type": "Full-time", "role": "Marketing", "role_type": null, "salary_range": "$20K - $34K", "equity_range": "", "experience": "3+ years", "visa": "US citizenship/visa not required", "skills": [] } ], "news": [ { "title": "YC-backed PrimeVault Builds the Future of Institutional DeFi - Decrypt", "url": "https://decrypt.co/154919/yc-backed-primevault-builds-the-future-of-institutional-defi", "date": "Sep 04, 2023" }, { "title": "Enterprise insights from YC S22 Demo Day | Wing Venture Capital", "url": "https://www.wing.vc/content/enterprise-insights-from-yc-s22-demo-day", "date": "Sep 15, 2022" }, { "title": "Crypto and web3 stands out in the YC Summer 2022 batch", "url": "https://techcrunch.com/2022/09/07/y-combinator-crypto-investment-summer-2022/", "date": "Sep 07, 2022" } ], "launches": [] }, { "id": 27673, "name": "Reflex", "slug": "reflex", "former_names": [ "Pynecone" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/677513c7f80f22199de3136c5024581799a126f2.png", "website": "https://reflex.dev", "all_locations": "San Francisco, CA, USA", "long_description": "Reflex is the operating system for building mission-critical enterprise applications.\r\n\r\nToday’s enterprise stack is fragmented. Shipping an app requires stitching together multiple tools and coordinating across multiple roles. Reflex replaces that complexity with a single, unified platform to build, deploy, and manage production applications end-to-end.\r\n\r\nWe empower teams to own the entire lifecycle of their apps — from idea to production — without needing specialized infrastructure, DevOps, or platform teams. We do this by providing solid, reusable abstractions at both the framework and infrastructure layers. Because we own the underlying open-source framework and the platform it runs on, we can manage the full lifecycle of the application seamlessly.\r\n\r\nWith Reflex, teams securely connect to company data, use AI to build standardized applications on top of our open-source framework, and deploy with a single click to share across their organization.\r\n\r\nWe’re replacing the fragmented enterprise stack — and the organizational bottlenecks that come with it.\r\n\r\nFounded by Alek Petuskey and Nikhil Rao, Reflex has powered over 1 million applications, earned 28,000+ GitHub stars, and is used by 30% of Fortune 500 companies for internal tools and data-driven applications.", "one_liner": "The operating system for building mission-critical enterprise apps.", "team_size": 10, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1674447011, "tags": [ "Developer Tools", "Open Source", "Web Development", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2023", "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/reflex", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/reflex.json", "year_founded": 2023, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/reflex-dev", "x_url": "https://twitter.com/getreflex", "fb_url": null, "cb_url": null, "github_url": "https://github.com/reflex-dev", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/677513c7f80f22199de3136c5024581799a126f2.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": 1164088, "full_name": "Nikhil Rao", "title": "Founder", "founder_bio": "Building Reflex - a way to make web apps in pure Python.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/nrao95/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/6d6d6d80493910dc4730348750093fa77d20924d.jpg" }, { "user_id": 676253, "full_name": "Alek Petuskey", "title": "Founder", "founder_bio": "Cofounder @ Reflex", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/aleksanderpetuskey/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/53b72097f7f472d9ad35ff5a98a3d26ff81d5539.jpg" } ], "jobs": [ { "id": 95191, "title": "Growth Lead", "url": "https://www.ycombinator.com/companies/reflex/jobs/KpOaIpx-growth-lead", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$150K - $200K", "equity_range": "0.35%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "Python", "SQL", "LLMs" ] }, { "id": 103944, "title": "Growth Engineer", "url": "https://www.ycombinator.com/companies/reflex/jobs/71x5GFb-growth-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Marketing", "role_type": null, "salary_range": "$130K - $200K", "equity_range": "0.10% - 0.40%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [ "Python" ] }, { "id": 108783, "title": "Founding Sales Development Representative (SDR)", "url": "https://www.ycombinator.com/companies/reflex/jobs/0BmuKm6-founding-sales-development-representative-sdr", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$175 - $210K", "equity_range": "0.10%", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [], "launches": [ { "id": 94833, "title": "Reflex: AI app builder for creating production-grade web apps entirely in Python", "tagline": "Just connect your data and enter a prompt. Reflex generates production-ready apps that integrate any data source, API, or Python package.", "body": "[**Reflex**](https://www.linkedin.com/company/reflex-dev/) is an AI app builder for creating production-grade web apps entirely in Python, powered by its own open-source framework.\\\n\\\nPython is one of the most popular programming languages in the world, and web development is one of the most popular applications of programming. So why can’t we make full-stack web apps using just Python?\\\n\\\nWith Reflex, you just connect your data and enter a prompt. It generates production-ready apps that integrate any data source, API, or Python package.\\\n\\\nFounded by [**Nikhil Rao**](https://www.linkedin.com/in/nrao95/) and [**Alek Petuskey**](https://www.linkedin.com/in/aleksanderpetuskey/), Reflex has over 1 million apps created, 27k GitHub stars, and has been used by 30% of Fortune 500 companies for internal tools and data-driven applications.\\\n\\\nTry it at [**https://build.reflex.dev**](https://build.reflex.dev).\\\n\\\nhttps://www.youtube.com/watch?v=Hy3uhBVRdtk&feature=youtu.be", "url": "https://www.ycombinator.com/launches/OfZ-reflex-ai-app-builder-for-creating-production-grade-web-apps-entirely-in-python", "votes": 10, "created_at": "2025-10-22T18:11:26.021Z" }, { "id": 68556, "title": "Pynecone: Web apps in pure Python 🐍", "tagline": "Build web apps in minutes. Deploy with a single command.", "body": "Hello! We’re Alek and Nikhil and we’re excited to launch [Pynecone](https://pynecone.io)!\n\n## **TL;DR:**\n\n**Pynecone is an open-source framework to build web apps in pure Python and deploy with a single command. This can be anything from a small data science/internal app to a large multi page web app.**\n\n![uploaded image](/media/?type=post&id=68556&key=user_uploads/1164088/65dd0f6c-0edd-4c0c-9f18-e4b78b06a443)\n\n[Here is an example](https://dalle.pynecone.app/) of a Dalle Pynecone App created in \\~50 lines of Python.\n\nYou can see how to install Pynecone and start building in minutes [here](https://pynecone.io/docs/getting-started/introduction).\n\n### **The Problem**\n\nPython is one of the most popular programming languages in the world. Webdev is one of the most popular applications of programming. So why can’t we make full-stack web apps using just Python?\n\nWe found that even skilled engineers who wanted to make a web app but didn’t know traditional frontend tools like Javascript / React found it too overwhelming and time consuming. And even after they made their app, deploying it was a nightmare. We wanted to provide them with a framework where they can leverage their existing Python skills to create and deploy apps, without compromising on flexibility or customization.\n\nRecent no code and low code alternatives have issues. No code solutions that save time in the development process lack the flexibility and robustness of traditional web development. Low code frameworks are often confusing and only solve part of the problem forcing you to use multiple tools to get the job done.\n\n# **Solution**\n\n## **1️⃣ Language For Your Web App**\n\nWith Pynecone we wanted to enable software engineers to build performant customizable web apps without the overhead of learning traditional webdev. You can make anything from a small data science project to a full-scale, multi page web app in Pynecone. We have over 60+ built-in components and are adding more.\n\n## **🔋Batteries-Included Hosting**\n\nOnce you have your app built, the next big challenge is deploying it. Learning to host on a cloud service can be confusing and time-consuming. On top of hosting your frontend/backend you need to learn how to configure and maintain SSL, CDNs, and monitoring/analytics.\n\nSince we specialize in hosting a single type of app, we can provide all of this out of the box with zero configuration. With a single `pc deploy` command we will automatically set up your infrastructure so you can get your ideas out faster. You can also host with your own cloud provider.\n\n## **🥞Empower Your Team**\n\nNow instead of having separate dedicated engineers for frontend, backend, and infra, every engineer can understand and work across the whole stack. This reduces communication overhead and lets your team go from idea to working product as efficiently as possible.\n\n## **💬 We’d love to talk to you:**\n\n* Do you or your team use Python and have any internal tools/customer facing web apps. We would love to chat to see if Pynecone can simplify your tech stack and provide value.\n* ⭐️ us on [GitHub](https://github.com/pynecone-io/pynecone) to keep up with releases and news.\n* Join [our Discord](https://discord.gg/T5WSbC2YtQ)!\n\n(A short video of a user reviewing Pynecone)\n\n", "url": "https://www.ycombinator.com/launches/Hpk-pynecone-web-apps-in-pure-python", "votes": 75, "created_at": "2023-01-19T21:01:27.254Z" } ] }, { "id": 27697, "name": "Lume", "slug": "lume-2", "former_names": [ "Abyssinia" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/053379bcb6d2f8ca33ff9eb81f1d899a06a6872a.png", "website": "https://www.lume.ai", "all_locations": "", "long_description": "Lume speeds up customer implementation with AI. Lume helps teams analyze, map, and ingest customer data up to 87% faster, accelerating time-to-revenue.", "one_liner": "Speed up customer implementation with AI", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1675974530, "tags": [ "SaaS", "B2B", "Data Engineering", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2023", "status": "Acquired", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "Unspecified" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/lume-2", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/lume-2.json", "year_founded": 2022, "city": null, "country": null, "linkedin_url": "https://www.linkedin.com/company/lume-ai/", "x_url": "https://twitter.com/TryLume", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/lume-ee1a", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/053379bcb6d2f8ca33ff9eb81f1d899a06a6872a.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/a4a09c0df0505d292ec360324b588ebb509217e1.png" ], "primary_partner": { "name": "Brad Flora", "url": "https://www.ycombinator.com/people/brad-flora" }, "founders": [ { "user_id": 1157038, "full_name": "Robert Ross", "title": "Founder", "founder_bio": "Co-Founder of Lume (W23) || Stanford CS ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/robertross04", "x_url": "https://twitter.com/imrobertross", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5e7508e23027231f8a8a622784d767f645ba2af1.jpg" }, { "user_id": 1159508, "full_name": "Nicolas Machado", "title": "Founder", "founder_bio": "Co-Founder of Lume (W23), Stanford AI, Brazilian.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/machado-nicolas", "x_url": "https://twitter.com/machado___nic", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b9c71f39931d9c5a32bd9eafa8eb0f2fbf504d6f.jpg" }, { "user_id": 1141304, "full_name": "Nebyou Zewde", "title": "Founder", "founder_bio": "Co-Founder of Lume, Stanford CS AI, Ethiopian ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/nebyou-zewde-b6ba02157/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ea4b965b24c80d662cb2560764c500023276586c.jpg" } ], "jobs": [], "news": [ { "title": "General Catalyst and Khosla Ventures back data mapping startup Lume | TechCrunch", "url": "https://techcrunch.com/2024/11/12/general-catalyst-and-khosla-ventures-back-data-mapping-startup-lume/", "date": "Nov 12, 2024" } ], "launches": [ { "id": 81770, "title": "Lume: Automate data mappings using AI", "tagline": "Ingest client data, normalize data from different sources, and build data pipelines, automatically.", "body": "**TL;DR**\n\nLume helps teams map data between systems with AI. If your team spends time mapping data for customer data onboarding, data normalization between systems, or mapping for data integrations, we can help! Please go to our [website and sign up](https://www.lume.ai/?utm_source=ycombinator&utm_medium=social&utm_campaign=launch_yc_5_24) for a free trial.\n\n—-\n\nHi everyone! We are Nicolas, Nebyou, and Robert, the founders of Lume. We are on a mission to automate the painstakingly manual process of data mapping, after experiencing this frustration as engineers ourselves. We have onboarded several customers who are growing and are excited to help more teams use AI in their data mapping workflows.\n\n![uploaded image](/media/?type=post&id=81770&key=user_uploads/1159508/77b12bac-08ae-40df-9984-f0cbc0f10c1d)\n\n**🧨 Problem**\n\nThe usual mapping process involves a labor-intensive cycle: analyzing data to determine what's relevant, selecting the appropriate properties, developing the mapping logic, and constantly updating mappers to accommodate schema changes in source or target systems. This process, we learned, takes days, weeks, or even months for most teams, and automating it has traditionally been borderline impossible due to unique differences in data.\n\n**✨ Solution**\n\nLume uses AI to automatically map data between any start and end schema, whether it is customer data, external sources, or anything else. Lume provides this via an API and a no-code platform where you can generate mapping logic, review and edit it, and manage multiple data pipelines. Whether you want to onboard customer data, normalize data from multiple sources, or create auto-mapping UIs over Lume, Lume delivers. With automated transformations and data delivery, error and type checking, auto-maintenance with schema inference, and execution via an API or a no-code App for different use cases, teams can spend more time delivering their core value to customers instead of wrangling and manually mapping data.\n\n**🚀 Key Features**\n\n* ✨ Generate mapping logic in seconds: via our API or the Lume app, simply pass in a sample of your source data and a target format, and Lume will generate the mappings.\n* 🛠️ Edit mapping logic: review and edit the mapping logic and mapped data as needed to ensure you have the desired outcome. Leverage tools ranging from natural language all the way to full code edits to edit the mappers quickly and easily.\n* ✅ Deploy mappers: Use the mappers deterministically in your code via our API or the app, allowing you to reliably move data between schemas as you scale your data pipelines.\n* 🤖 Auto-maintain mappers: Lume detects changes in your schemas, notifying you and allowing you to use AI to update the mapping logic, effectively automating your maintenance.\n* 📊 Manage and organize mappers: use Lume’s dashboard to have visibility over all of your mappers and live data pipelines.\n* 📑 Handle any format: Lume supports JSON, CSV, XLS, PDF, and other formats! You can move data through the API or the app.\n* 🔮 Upcoming: adding custom logic with lambda functions, custom validation rules, python SDK, transferring your existing mappings when migrating to Lume, and more.\n\n**⚙️ How it works**\n\n* To create mappers: specify your target structure and provide a sample of source data. This can be done via the Lume API or the Lume Platform.\n\n![uploaded image](/media/?type=post&id=81770&key=user_uploads/1159508/d27fd09d-3943-4748-817a-cb16a4b5952a)\n\n* ✨ Lume’s AI system creates the mappings between any two schemas, ranging from simple 1-1 mappings, time-series aggregations, complex calculations, and ontology classifications.\n* Use the generated mappings and mapping logic: Use the Lume API or the Lume Platform to upload new incoming data and retrieve the corresponding output mapped data and mapping logic. Your data has just been automatically mapped with AI!\n\n ![uploaded image](/media/?type=post&id=81770&key=user_uploads/1159508/c25b7d28-9b19-49b5-b103-ad8a69ef21e7)\n\n* For creating robust data pipelines, review and edit the generated mapping logic before running production data. Once saved, you can confidently use these mappers as deterministic pipelines. This is helpful for your data integrations between systems.\n\n![uploaded image](/media/?type=post&id=81770&key=user_uploads/1159508/c9f8696c-e294-4c01-b602-aa16f3635f21)\n\n![uploaded image](/media/?type=post&id=81770&key=user_uploads/1159508/b2766b97-2eda-4dca-baf5-9f87ffb22d8d)\n\n* Alternatively, build on top of the Lume API to deploy your own auto-mapper UI to allow customers to self-onboard.\n\n**💡 Use Cases**\n\nLume handles three core use cases:\n\n* Onboarding Client Data\n* Normalizing Data from Multiple Sources\n* One to Many Integrations\n\nHere are three customer success stories:\n\n* For a growth-stage battery analytics company, mapping each customer’s sensor data went from 2 weeks to 1.5 hours with Lume.\n* For a large HR analytics platform, Lume mapping accuracy reached 95% for their most recent batch of integrations, saving them weeks of onboarding time for mapping and classifying data from incoming systems.\n* For an early-stage financial product startup, Lume is handling \\~500 live data pipelines that are externally facing, constantly mapping and adapting to new incoming data.\n\nAll of these have the common theme of having to map data between unique schemas, where even discrepancies as minor as column name variations make this process time-consuming and near-impossible to automate. This gets even worse at scale. Clients previously were allocating engineers, customer success teams, or offshore labor to analyze incoming data, map the data, and route it to their new systems. This process used to take up to multiple months for some teams, costing significant time and money.\n\nWe serve multiple industries ranging from ecommerce, insurance, manufacturing, and financial products.\n\n**👨‍💻Meet the Team**\n\n![uploaded image](/media/?type=post&id=81770&key=user_uploads/1159508/fe023d78-6ef6-49c3-b202-d264bc80270e)\n\nMy co-founders Nebyou Zewde (right), Robert Ross (middle), and I (left) all met during our first year at Stanford. As engineers ourselves, we’ve spent plenty of time grudgingly going over the manual task of mapping data. We quickly learned that we were not the only ones who faced this problem - most companies spend too much time on this. As AI grads, and with a fire for this problem, we built Lume AI. We are part of the Y Combinator W23 batch, and we’re excited to be launching here.\n\n**🙏 Our ask**\n\n* Sign up for a free trial to get started by [visiting our website](https://www.lume.ai/?utm_source=ycombinator&utm_medium=social&utm_campaign=launch_yc_5_24) or [booking a call here](https://cal.com/team/lume/intro). We’ll get you on a Slack and onboarded quickly.\n* Share this with anyone who works on data mapping for customer onboarding, data normalization, or moving data between any two systems. We support a variety of use cases.\n* Upvote and share this post!\n\n**💥 The Deal**\n\nMention you saw Lume via Launch YC, and we will give you a 50% discount for your first 6 months. We also offer a free pilot.", "url": "https://www.ycombinator.com/launches/LGs-lume-automate-data-mappings-using-ai", "votes": 40, "created_at": "2024-06-26T17:31:22.598Z" }, { "id": 70009, "title": "Lume - No-code tool to create and maintain custom data integrations", "tagline": "Lume uses AI to automatically transform data between any start and end schema.", "body": "**TL;DR**\n\nLume helps engineering teams build and maintain custom data integrations with no code. If you spend countless hours manually transforming data for custom integrations, we can help! Please go to our [website](https://www.lume.ai/?utm_source=ycombinator&utm_medium=social&utm_campaign=launch_yc_5_23) and sign up for our private beta.\n\n—-\n\n---\n\nHi everyone! We are Nicolas, Nebyou, and Robert, the founders of Lume. We are on a mission to empower companies to focus on delivering their core value proposition rather than spending time on data integrations and transformations. \n\n![uploaded image](/media/?type=post&id=70009&key=user_uploads/1157038/0a606e9a-7357-4f36-bd06-be63bddcd635)\n\n**🧨 Problem** \n\nEngineers spend countless hours manually transforming data for custom integrations or pay large amounts to consulting firms to do the same. Dynamic schemas from different clients or apps require engineers to build and maintain custom integration pipelines one by one, and companies spend days, weeks, and even months building integrations. Lume is tackling this problem head-on. \n\n**✨ Solution**\n\nLume uses AI to automatically transform data between _any_ start and end schema and pipes the data directly to your desired destination. Lume provides this through a no-code platform where you can build and maintain your custom data integrations. Whether you want to map multiple sources to your internal unified schema or connect to your third-party apps without manual mapping, Lume delivers. With automated transformations and data delivery, backtesting and data quality checks, and version control, engineers can spend more time delivering their core value to customers instead of wrangling and manually mapping data. \n\n**⚙️ How it works**\n\n* You connect your custom schemas and authenticate into your desired apps.\n* Lume’s AI system creates the transformations between any two schemas, ranging from internal schemas to structured third-party apps.\n* Once you validate the transformed data, Lume will pipe the correct data to your specified destination.\n\nWe can connect to your data warehouse and leverage its compute to keep your data in-house.\n\n**Common Use Cases:**\n\n* Internal: Transforming separate data sources into one unified internal ontology\n * Ex: a unified schema between Salesforce, Hubspot, Quickbooks, and Pipedrive.\n* External: Custom syncs between your SaaS apps\n * Ex: Enrich CRM data from multiple sources before sending it to your BI tool\n* Onboarding: Mapping prospective client data to fit your product’s input schema\n * Ex: Consulting firms mapping each new clients’ unique ERP schemas to their internal ontology on Snowflake.\n* Migration: Creating custom integration pipelines between competitor products to yours \n * Ex: New productivity tool startup creates an “Import from Notion/Evernote” for newly converted users.\n\n**👨‍💻Meet the Team**\n\n![uploaded image](/media/?type=post&id=70009&key=user_uploads/1157038/86b2a6a9-5fb4-4300-be17-30125bdb80fa)\n\nMy co-founders Nicolas Machado (right), Nebyou Zewde (middle), and I (left) all met during our first year at Stanford, where we received our undergraduate and Master's degrees in computer science with a focus on Artificial Intelligence. With experience working at both unicorn startups and big tech companies, our team has knowledge and experience building and deploying applied machine learning systems.\n\n**🙏 Our ask**\n\n* Sign-up for our [private beta](https://www.lume.ai/?utm_source=ycombinator&utm_medium=social&utm_campaign=launch_yc_5_23) if you want to try Lume and see a demo.\n* Share this with anyone that works on custom data integrations.\n* Upvote and share this post!\n\n**💥 The Deal**\n\n**Sign-up before demo day for a 50% discount for the first year!**", "url": "https://www.ycombinator.com/launches/IDB-lume-no-code-tool-to-create-and-maintain-custom-data-integrations", "votes": 251, "created_at": "2023-03-07T18:12:57.774Z" } ] }, { "id": 27810, "name": "Cakework", "slug": "cakework", "former_names": [ "Sahale" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c4dbd8d6bcbc396c907943226c3f01d2cbcd5809.png", "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. ", "one_liner": "API that adds cloud hosting to any developer platform", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1673854005, "tags": [ "Developer Tools", "B2B", "Cloud Computing", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2023", "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/cakework", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/cakework.json", "year_founded": 2022, "city": "Seattle", "country": "US", "linkedin_url": "https://www.linkedin.com/company/usecakework", "x_url": "https://twitter.com/usecakework", "fb_url": null, "cb_url": null, "github_url": "https://github.com/usecakework", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/c4dbd8d6bcbc396c907943226c3f01d2cbcd5809.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": 461027, "full_name": "Eric Chen", "title": "Founder", "founder_bio": "working on www.cakework.com!", "is_active": false, "linkedin_url": "https://www.linkedin.com/in/ericchen90/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ab6f8addc07bcec89848ca31970e5441e18517e4.jpg" }, { "user_id": 1098594, "full_name": "Jessie Young", "title": "Founder", "founder_bio": "CEO of Cakework", "is_active": false, "linkedin_url": "https://www.linkedin.com/in/jyoung73/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/bacd8dfbf932dba178be48e147deb56a5188e65c.jpg" } ], "jobs": [], "news": [], "launches": [ { "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" } ] }, { "id": 27813, "name": "Omnistrate", "slug": "omnistrate", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/428feb2a5e495458be88abd1793ebca289d4798b.png", "website": "http://www.omnistrate.com", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Omnistrate helps software companies to build their own private-label control plane to deliver your product as vendor-hosted SaaS, inside customer cloud accounts/VPCs/Kubernetes clusters, on-premises, in air-gapped environments, and through cloud marketplaces.", "one_liner": "Build your control plane to deploy your product in your customer VPC…", "team_size": 25, "industry": "B2B", "subindustry": "B2B", "launched_at": 1677779443, "tags": [ "Developer Tools", "B2B", "Cloud Computing", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2023", "status": "Active", "industries": [ "B2B" ], "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/omnistrate", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/omnistrate.json", "year_founded": 2023, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/omnistrate/", "x_url": "https://twitter.com/omnistrate", "fb_url": "https://www.facebook.com/omnistrate", "cb_url": "https://www.crunchbase.com/organization/omnistrate", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/428feb2a5e495458be88abd1793ebca289d4798b.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": 1159729, "full_name": "Kamal Gupta", "title": "Founder", "founder_bio": "Kamal is a Co-Founder & CEO of Omnistrate. He is a repeat founder with an entrepreneurial spirit. Kamal led the engineering for Kafka at Confluent across all channels. During his time, Kafka Cloud revenue grew by 20x. Before that, he led the database engineering for AWS Aurora MySQL, a BB+ dollar business managing MM+ of database nodes. During his period at AWS (2007-2020), he built more than half-a-dozen cloud services at AWS across different domains & providers\n", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/kkgupta2/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2bdbc295d004c505d91a3663ec8ab3dc6870254d.jpg" }, { "user_id": 1157545, "full_name": "Alok Nikhil", "title": "Founder", "founder_bio": "Alok comes with deep technical expertise in Serverless, Networking, Performance on the Cloud. He was the original technical author of Aurora Serverless, which revolutionized the data systems space. Within the first year of its introduction, ~50% of hundreds of thousands of Aurora DBs created were on Aurora Serverless. He also scaled networking (packets-per-second) on AWS by 10-15x during his tenure at Cisco, scaled Confluent Cloud by 5x from 4GBps to 20GBps, and Kafka Cloud latencies by 10x.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/nikhilalok/", "x_url": "https://twitter.com/aloknnikhil", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/933eb8ed887865783271f7d6a4ceef25eccf1973.jpg" } ], "jobs": [ { "id": 79259, "title": "Platform Engineer [US]", "url": "https://www.ycombinator.com/companies/omnistrate/jobs/L0WAiFF-platform-engineer-us", "location": "US / Remote (US)", "type": "Full-time", "role": "Engineering", "role_type": "Backend", "salary_range": "$100K - $140K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [ "Go", "Kubernetes", "Distributed Systems" ] }, { "id": 97793, "title": "Founding AE Role", "url": "https://www.ycombinator.com/companies/omnistrate/jobs/yeQMikj-founding-ae-role", "location": "US / Remote (US)", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$120K - $160K", "equity_range": "", "experience": "6+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 97794, "title": "SDR role [India only]", "url": "https://www.ycombinator.com/companies/omnistrate/jobs/T2nsaRb-sdr-role-india-only", "location": "Remote", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$1", "equity_range": "", "experience": "3+ years", "visa": "US citizenship/visa not required", "skills": [] } ], "news": [], "launches": [ { "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: \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: \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: \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: \n\nIf you would like to interested to learn more about Agent deployments, check out: ", "url": "https://www.ycombinator.com/launches/VpF-deploy-your-product-in-your-customer-vpc-or-single-tenant-saas-or-airgapped", "votes": 6, "created_at": "2026-10-15T15:50:12.811Z" }, { "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 <[support@omnistrate.com](mailto:support@omnistrate.com)>\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" }, { "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: \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", "votes": 560, "created_at": "2023-03-10T14:58:53.557Z" } ] }, { "id": 27893, "name": "BuildJet", "slug": "buildjet", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6581ded9fa54308e7ffa3c61c36bd6ef62e369cd.png", "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, "tags": [ "Developer Tools", "SaaS", "B2B", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2023", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "Germany", "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/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/", "x_url": "https://twitter.com/buildjet", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/6581ded9fa54308e7ffa3c61c36bd6ef62e369cd.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": 730963, "full_name": "Adam Shiervani", "title": "Founder", "founder_bio": "Adam Shiervani is a co-founder of BuildJet, with over a decade of experience working in startups, Adam began as a frontend developer and progressed over the years to become the Chief Product Officer at Germany's largest market research company, Civey. At Civey, Adam, together with Lian, who served as CTO, scaled the company and discovered the significant impact that consumer CPUs have on CI speed.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/adamshiervani/", "x_url": "https://twitter.com/adamshiervani", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2b5ed35a7ba7b36ed7d13454395d29b3eb433b90.jpg" }, { "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.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/chemhack/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3e9b5890a69d9bbc29d3d3300ac0b5798e215fc4.jpg" } ], "jobs": [], "news": [], "launches": [ { "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 , 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" } ] }, { "id": 28087, "name": "Rivet", "slug": "rivet", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/78acdf0f2271926c4c6856385a0b7846a8135bd7.png", "website": "https://rivet.dev", "all_locations": "San Francisco, CA, USA", "long_description": "Rivet Actors are the primitive for stateful workloads.\r\n\r\nBuilt for AI agents, collaborative apps, and durable execution.\r\n\r\nOpen-source.", "one_liner": "Rivet Actors are the primitive for stateful workloads", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1675129787, "tags": [ "B2B", "Open Source", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 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/rivet", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/rivet.json", "year_founded": 2022, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/rivet-gg", "x_url": "https://twitter.com/rivet_dev", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/rivet-d09f", "github_url": "https://github.com/rivet-dev", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/78acdf0f2271926c4c6856385a0b7846a8135bd7.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/6da34c70835663d011938535108f4fa9de12f48b.png", "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/faa2f29d16c356659d7e9503af2f7d8450fdcdc4.png" ], "primary_partner": { "name": "Diana Hu", "url": "https://www.ycombinator.com/people/diana-hu" }, "founders": [ { "user_id": 1202740, "full_name": "Nicholas Kissel", "title": "Founder", "founder_bio": "Building open-source Cloudflare Workers & Durable Objects. Previously at Paradox.ai & Addicting Games. University of Arizona.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/nicholaskissel/", "x_url": "https://twitter.com/nicholaskissel", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/05071905f0a181ad8de5ebecf50a79deacc08675.jpg" }, { "user_id": 1203698, "full_name": "Nathaniel Flurry", "title": "Founder", "founder_bio": "The actor guy", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/nathanflurry/", "x_url": "https://twitter.com/NathanFlurry", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a9522beab1d7c1477b8094827a080f37f42dc11a.jpg" } ], "jobs": [ { "id": 104561, "title": "Software Engineer", "url": "https://www.ycombinator.com/companies/rivet/jobs/08lOGd6-software-engineer", "location": "Remote", "type": "Full-time", "role": "Engineering", "role_type": "Backend", "salary_range": "$80K - $150K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizenship/visa not required", "skills": [ "C++", "Go", "PostgreSQL", "Rust", "SQLite", "Distributed Systems" ] } ], "news": [ { "title": "Our favorite startups from YC's Winter 2023 Demo Day — Part 1 | TechCrunch", "url": "https://techcrunch.com/2023/04/05/y-combinator-demo-day-favorites-part-one/", "date": "Apr 05, 2023" } ], "launches": [ { "id": 70240, "title": "👾 Rivet - Heroku for multiplayer games", "tagline": "Run multiplayer games with managed game servers, matchmaking, and DDoS mitigation.", "body": "**TL;DR:** [_Rivet_](https://rivet.gg) makes it easy to run multiplayer games with managed game servers, matchmaking, and DDoS mitigation. Contact us at [_yc@rivet.gg_](mailto:yc@rivet.gg) to get access to the closed beta!\n\n![uploaded image](/media/?type=post&id=70240&key=user_uploads/1203698/e8281ea7-b796-4b7d-83e1-91367747b058)\n\n[**Rivet**](https://rivet.gg) **is trusted by publicly traded companies to indie studios to serve millions of monthly players on our infrastructure.**\n\n**The Team**\n\nIn high school, we procrastinated our homework by building and launching multiplayer games together for fun. We always wanted to make building multiplayer games more accessible, so we started Rivet to do exactly that.\n\n![uploaded image](/media/?type=post&id=70240&key=user_uploads/1203698/b4463d5c-b8d6-4fe2-9e89-268db904ebfa)\n\n**Together, we built a small game studio and launched 4 games with one acquisition.**\n\n[Nathan](https://www.linkedin.com/in/nathanflurry/) (right) independently built infrastructure serving over 15M MAU & 20k concurrent players while still in high school on games like [Krunker.io](http://Krunker.io) (acquired by FRVR). He was an Apple WWDC scholar from 2016-2018 and was featured in TechCrunch for his visual programming language.\n\n[Nicholas](https://www.linkedin.com/in/nicholaskissel/) (left) was a PM at the [Paradox.ai](http://Paradox.ai) R&D department to help built AI HR solutions for companies like McDonalds. He continued to work at Addicting Games as a PM on multiple multiplayer games and helped launch [Apes.io](http://Apes.io), a cutting-edge browser-based battle royale.\n\n**The Problem**\n\nModern games need game servers to support large lobbies, anti-cheat, low latency, and mobile platforms. **The need for game servers is growing, but** **studios have to build their own game server infrastructure from scratch.**\n\nTherefore, **studios spend more time building in-house game server infrastructure than adding content** when trying to launch games with game servers. This makes it unreasonably difficult for small to medium-sized studios to launch and maintain these types of games.\n\n**Our Solution**\n\n![uploaded image](/media/?type=post&id=70240&key=user_uploads/1203698/5918c6af-05a5-404b-943a-66c4ccc9c276)\n\n**We make it easy for game developers to run their game servers on **[**Rivet**](https://rivet.gg)**.** We take care of auto-scaling servers, matchmaking, and DDoS mitigation so the developer can focus on adding content. Rivet works with all major game engines and custom server code.\n\n**Integrating Rivet into a game takes 4 lines of code in any language.** We provide no-downtime deploys with easy rollbacks.\n\n![uploaded image](/media/?type=post&id=70240&key=user_uploads/1203698/49c025ec-b2b3-4148-8f08-55625dca99a6)\n\nOnce a game is up and running, Rivet provides a sleek dashboard for operating the game and streamlining DevOps. Developers can manage their lobbies, view analytics, rollback versions, diagnose crashes, and manage namespaces.\n\n![uploaded image](/media/?type=post&id=70240&key=user_uploads/1203698/3fe4f55a-dc32-42b0-a444-4de15f618120)\n\nWant to see Rivet in action? Watch our [3-minute crash course](https://www.youtube.com/watch?v=pBE7s-PK0j0)!\n\n**Our Ask**\n\nIf you or a friend is building a multiplayer game – even if it’s a hobby project – we’d love to chat! Contact us at [yc@rivet.gg](mailto:yc@rivet.gg).", "url": "https://www.ycombinator.com/launches/IGu-rivet-heroku-for-multiplayer-games", "votes": 57, "created_at": "2023-03-13T20:31:18.735Z" } ] }, { "id": 28743, "name": "Leafpress", "slug": "leafpress", "former_names": [ "Leafpress" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/8b397defdcecf4c281122216507cb5239f88b392.png", "website": "https://www.trycardinal.ai/", "all_locations": "", "long_description": "AI-Native Utility Management", "one_liner": "AI Energy Management", "team_size": 2, "industry": "B2B", "subindustry": "B2B", "launched_at": 1689209330, "tags": [ "Enterprise", "Enterprise Software", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2023", "status": "Inactive", "industries": [ "B2B" ], "regions": [ "Unspecified" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/leafpress", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/leafpress.json", "year_founded": 2025, "city": null, "country": null, "linkedin_url": "", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/8b397defdcecf4c281122216507cb5239f88b392.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/aca1516addb270f93f3487c24e60b659fd5bb217.png" ], "primary_partner": { "name": "Gustaf Alstromer", "url": "https://www.ycombinator.com/people/gustaf-alstromer" }, "founders": [ { "user_id": 1244892, "full_name": "Devi Jha", "title": "Founder", "founder_bio": "Devi dropped out from Harvard with(out) a degree in Computer Science. YC S23 with an energy software company, sold it to Johnson Controls (NYSE: JCI).", "is_active": false, "linkedin_url": "https://linkedin.com/in/devishijha", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e5feb78146a61be2f7a5e8872004e378e7be83d8.jpg" }, { "user_id": 663394, "full_name": "Jianna Liu", "title": "Founder", "founder_bio": "Jianna graduated from MIT with a degree in computer science. She has worked on the software teams at Meta, DoorDash, Nvidia. Previously YC S23, energy software company. Acquired by Johnson Controls (NYSE: JCI)", "is_active": false, "linkedin_url": "https://linkedin.com/in/jianna-liu-90747413b", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/27d211f97bb944135f4095da5b25aeeba4d23af2.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 28812, "name": "Cedana", "slug": "cedana", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/765d8a1a78a1c5939f354a26be87d3c1c1696290.png", "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", "launched_at": 1689189501, "tags": [ "Deep Learning", "Developer Tools", "Cloud Computing", "Infrastructure", "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", "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/cedana", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/cedana.json", "year_founded": 2023, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/cedanacorp/", "x_url": "https://twitter.com/cedana_ai", "fb_url": null, "cb_url": null, "github_url": "https://github.com/cedana", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/765d8a1a78a1c5939f354a26be87d3c1c1696290.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": 77597, "full_name": "Neel Master", "title": "Founder", "founder_bio": "CEO of Cedana. Previously CEO/co-founder of Engooden, AI-powered chronic disease management proven to improves outcomes and lower costs for patients (Series B). VP of Corp Development for Petra Systems (predictive smart grid/solar company) scaled from $0-$70M ARR. At TL Ventures ($1.6B VC fund) investing across semi, software and systems. Built a system for large-scale, automated ML and computer vision at MIT CSAIL. Patents and publications in AI, computer vision.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/neelmaster1", "x_url": "https://twitter.com/neelmaster", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d563c8b75caf8e9bc463baf0be90836b8802c73f.jpg" }, { "user_id": 297703, "full_name": "Niranjan Ravichandra", "title": "Founder", "founder_bio": "Co-founder/CTO at Cedana. Previously Robotics at Shopify. Previously previously Mech/Aero, published in control systems, neuromorphic computing and satellite formation flight. ", "is_active": true, "linkedin_url": "https://linkedin.com/in/niranjanravichandra", "x_url": "https://x.com/0xnravic", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/537093808141633a595f61b05e15face61dc9b9c.jpg" } ], "jobs": [ { "id": 95527, "title": "Forward Deployed Engineer: AI + HPC", "url": "https://www.ycombinator.com/companies/cedana/jobs/d1vYocG-forward-deployed-engineer-ai-hpc", "location": "US / Remote (US)", "type": "Full-time", "role": "Engineering", "role_type": "Backend", "salary_range": "$140K - $180K", "equity_range": "0.10% - 0.25%", "experience": "6+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 95761, "title": "Systems Engineer: Linux Kernel Test and Validation", "url": "https://www.ycombinator.com/companies/cedana/jobs/BntWOIg-systems-engineer-linux-kernel-test-and-validation", "location": "US / Remote (US)", "type": "Full-time", "role": "Engineering", "role_type": "Backend", "salary_range": "$140K - $180K", "equity_range": "0.10% - 0.30%", "experience": "6+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [], "launches": [ { "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", "url": "https://www.ycombinator.com/launches/JAP-cedana-real-time-save-move-and-resume-for-compute", "votes": 26, "created_at": "2023-08-01T22:03:04.520Z" } ] }, { "id": 28843, "name": "SID", "slug": "sid", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cac6ad037170806bce925f0d0ed9373eec18f576.png", "website": "https://www.sid.ai", "all_locations": "San Francisco, CA, USA", "long_description": "SID is an AI research center based in San Francisco. We train models that can retrieve and reason over any data source.", "one_liner": "AI research center for retrieval", "team_size": 7, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1689093789, "tags": [ "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2023", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/sid", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/sid.json", "year_founded": 2023, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/sidai/", "x_url": "https://twitter.com/SID_AI", "fb_url": null, "cb_url": null, "github_url": "https://github.com/sidhq", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/cac6ad037170806bce925f0d0ed9373eec18f576.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 1134710, "full_name": "Maximilian-David Rumpf", "title": "Founder", "founder_bio": "Max is the CEO of SID.ai. Previously, he was a researcher at ETH Zürich, where he worked on AI accelerator design with the professor who developed Google's TPU architecture. Max was awarded a German national excellence scholarship, awarded to 0.5% of German students.", "is_active": true, "linkedin_url": "https://linkedin.com/in/maximiliandavid", "x_url": "https://twitter.com/maxrumpf", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/36a366b6e36d8e32f443ea45b69fca6fd4df26c8.jpg" }, { "user_id": 746723, "full_name": "Lotte Seifert", "title": "Founder", "founder_bio": "Lotte is determined to let people use their data for their own good. She holds a degree in CS from ETH Zürich and a degree in Economics from the University of St. Gallen. ", "is_active": true, "linkedin_url": "https://linkedin.com/in/lotte-seifert", "x_url": "https://twitter.com/lotteellen", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9381e5b5b03dfe8c71b03c574051aab9ede94457.jpg" } ], "jobs": [ { "id": 81528, "title": "Research Intern (Summer 2026)", "url": "https://www.ycombinator.com/companies/sid/jobs/SmhVhTs-research-intern-summer-2026", "location": "San Francisco, CA, US", "type": "Internship", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$5K - $10K / monthly", "equity_range": "", "experience": null, "visa": "US citizen/visa only", "skills": [ "Torch/PyTorch", "Reinforcement learning (RL)" ] }, { "id": 94626, "title": "Research Engineer", "url": "https://www.ycombinator.com/companies/sid/jobs/3izpJe0-research-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [ "Torch/PyTorch", "Reinforcement learning (RL)", "CUDA", "Search", "LLMs", "Vector Embeddings", "AI Agents", "MLOps" ] } ], "news": [ { "title": "Is A.I. Startup Funding a Rerun of the Dot-Com Bubble? | Chicago Booth Review", "url": "https://www.chicagobooth.edu/review/is-ai-startup-funding-rerun-dotcom-bubble", "date": "Jul 14, 2023" } ], "launches": [ { "id": 72952, "title": "SID.ai – AI research lab for retrieval", "tagline": "AI research lab for retrieval", "body": "**Intelligence needs Context**\n\nAI is giving humanity a new computer: one that can learn, reason, and act. But intelligence and skills are inconsequential without context. _Context imposes the upper bound._ At SID, we're training models to provide this context. _To connect intelligence to the world._\n\n**Context needs Retrieval**\n\nTo provide the right context, you need to find it first: Humanity has known how to do search on the internet for a while. But great search over everything else has been elusive so far. We think _we have an angle to solve it once and for all_. [SID-1](https://www.sid.ai/research/sid-1), our first agentic retrieval model, doubles embedding-only accuracy and outperforms frontier models on the most complex retrieval tasks.\n\n![uploaded image](/media/?type=post&id=72952&key=user_uploads/1134710/cd8dc357-3db7-4db0-9476-265e176bb6bb)\n\n**SID-1**\n\n_SID-1 is our first model for agentic retrieval: 1.8x more likely to surface the right results than embedding-only search across general knowledge, finance, science, legal, and email. It is more accurate than agentic retrieval based on Gemini 3 Pro, Sonnet 4.5, and GPT-5.1 at its highest compute setting, while being 24x faster (144 vs 5.7 seconds)._\n\nTraditional retrieval pipelines pre-program each step: query rewriting, searching, reranking. SID-1 retrieves like a human would: it searches, reads results, and refines its queries, taking as many steps as needed. We trained SID-1 on questions that take human researchers over an hour to solve.\n\nSID-1 is drop-in compatible with existing retrieval systems. It is designed to work as a subagent with larger LLMs like GPT-5 or Sonnet. Teams running embedding-only retrieval or RAG can typically integrate it in an afternoon.\n\nStep-change improvements in retrieval create new winners. Claude Code was better at finding the right file, unlocking larger code bases and driving massive adoption for Anthropic. Open Evidence made retrieving over medical research easier and took doctors by storm. Looking back further, relational was better than hierarchical for databases, creating Oracle. Better web search created Google. [_We're working closely with a small group of companies who want that edge now for their domains._](https://tally.so/r/gDDVMd)\n\nGiven we're compute-limited, we're rolling SID-1 out slowly. We're offering SID-1 through our API, AWS Bedrock, and as a self-hosted model. _If you're interested in SID-1, please sign up to our [waitlist](https://tally.so/r/gDDVMd), follow us on [X](https://x.com/SID_AI), or read the [technical report](https://www.sid.ai/research/sid-1-technical-report) for more details._", "url": "https://www.ycombinator.com/launches/Iye-sid-ai-ai-research-lab-for-retrieval", "votes": 135, "created_at": "2023-07-11T18:57:41.923Z" } ] }, { "id": 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": [ "Developer Tools", "B2B", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2023", "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, "question_answers": null, "url": "https://www.ycombinator.com/companies/hiro", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/hiro.json", "year_founded": 2023, "city": "New York City", "country": "US", "linkedin_url": "", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/d1d128fbe59c627f74405a0637c6a9692cc736f0.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 877309, "full_name": "Ethan Blackburn", "title": "Founder", "founder_bio": "Excited about developer tools/infrastructure and AI. Always down for a hike :)", "is_active": true, "linkedin_url": "https://linkedin.com/in/ethanblackburn", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d8883a267597442937c262b19c84eac21b547f26.jpg" }, { "user_id": 945403, "full_name": "Daniel Schofield", "title": "Founder", "founder_bio": " ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/daniel-sss/", "x_url": "https://twitter.com/thedschofie", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/22c8818c4887068601bc4d22ac33f5ab5d462f09.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 28900, "name": "Epsilla", "slug": "epsilla", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a2a1e40bf12e61df1ea8d4d6a4f8b7691ac3982f.png", "website": "https://www.epsilla.com/", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Epsilla is an all-in-one platform for building AI agents powered by your private data and knowledge. Easy to use for domain professionals, deeply customizable for AI experts, and fully equipped for enterprise customers with security, scalability, and integration.", "one_liner": "All-in-one platform to create AI agents with your private knowledge", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1687398753, "tags": [ "SaaS", "Infrastructure", "AI", "Databases" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2023", "status": "Active", "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/epsilla", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/epsilla.json", "year_founded": 2023, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/epsilla/", "x_url": "https://twitter.com/epsilla_inc", "fb_url": "https://www.facebook.com/Epsilla-101648343029200", "cb_url": null, "github_url": "https://github.com/epsilla-cloud/", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/a2a1e40bf12e61df1ea8d4d6a4f8b7691ac3982f.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/f684a445e68e17098c7b485b86f0971629d143cc.png", "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/ef792393c19d6a025f86bdc862636cd3d194ab3e.png" ], "primary_partner": { "name": "Diana Hu", "url": "https://www.ycombinator.com/people/diana-hu" }, "founders": [ { "user_id": 14642, "full_name": "Richard Song", "title": "Founder", "founder_bio": "Richard Song is the Co-Founder and CEO of Epsilla. Before Epsilla, Richard was the Senior Director of Cloud Engineering at TigerGraph, led the team to build the DBaaS offering of TigerGraph's graph analytics platform. In addition to this, Richard led the team to build a suite of tools designed to empower developers, data scientists, and DevOps teams, enabling them to extract value from TigerGraph.", "is_active": true, "linkedin_url": "https://linkedin.com/in/renchu-song-a4099247", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/efd8878b92658ca4f156698b03dbc7fa22580f5c.jpg" }, { "user_id": 1378779, "full_name": "Ricki Qin", "title": "Founder", "founder_bio": "Ricki Qin is the Co-Founder of Epsilla. Before Epsilla, Ricki was the Engineering Manager in Cloud team at TigerGraph, led the team to build the Cloud Portal. Ricki has 5 years experience in the database industry, helped to build a suite of tools designed to empower developers, data scientists, and DevOps teams.", "is_active": true, "linkedin_url": "https://linkedin.com/in/jing-qin-48a4baa4", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/bf236ad8ca1ac9aefa6cdfd915d5f8b586d59301.jpg" }, { "user_id": 1378751, "full_name": "Eric Yang", "title": "Founder", "founder_bio": "Eric is the Co-Founder of Epsilla. Before Epsilla, Eric was the Architect of Tigergraph Cloud. Eric has 10+ years experience in Cloud Infrastructure with deep insight of System Relability and Scalability.", "is_active": true, "linkedin_url": "https://linkedin.com/in/eric-yang-a4a743271", "x_url": "https://x.com/eric_epsilla", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2cb278dd724352b939feb5cb82048fdaa03927e6.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 122233, "title": "UHP: Unified Harness Protocol by HarnessRouter", "tagline": "An open standard for running complete agent harnesses as your product's backend, now officially adopted by Qoder by Alibaba", "body": "**TL;DR:** We're launching the Unified Harness Protocol (UHP), an open standard (Apache 2.0) for running complete agent harnesses as your agent product's backend. Qoder by Alibaba now officially supports UHP. Integrate once, and Qoder, Codex, Claude Code, Hermes and 20+ agent harnesses become your product's backend through one contract. No harness engineering required.\n\n\\*\\*Stop building the agent backend. Focus on your product.\\*\\*\\\nYou don't need LangChain, an agent SDK, or a managed agent platform to build your agent's backend. Instead of building your own agent loop, tool execution, sandbox, orchestration, and tracing, plug in a pre-built, configurable harness like Qoder, Codex or Claude Code as your backend. Every task runs in an isolated sandbox, is orchestrated across harnesses, and is fully traced. Tailor your tools, plugins and skills, and focus on your product.\n\n![uploaded image](/media/?type=post&id=122233&key=user_uploads/14642/185decdc-9d10-47be-965c-5f24336a39bf)\n\n**The problem:** A harness is a complete agent runtime that plans, calls tools, edits files and reports back. Every harness already knows how to do the work. What none of them agree on is how a product should drive one: how to start a task, follow its progress, continue it, cancel it, get the files it produced, and understand why it failed.\n\nThat's an N×M problem: N products times M harnesses, each pair wired up by hand. So most teams end up building their own harness instead, and spend months on harness engineering before shipping a single feature.\n\n**What UHP is**\n\n* An HTTP contract. You send a task and get back a running agent, results and files. The unit is a job, not a completion.\n* Shaped like the OpenAI Responses API, so existing SDKs, streaming parsers and UI code work with no changes.\n* Versioned spec, OpenAPI schema, and a conformance suite with 95 runnable checks that defines what \"conformant\" means.\n* No hosted service required: a conformant server can run entirely on your own machine with your own keys.\n\n**Qoder by Alibaba adopts UHP:** Qoder now officially supports UHP, so you can use it as a pre-built, configurable agent harness for your product. Instead of building your own agent loop, tool execution, sandbox, orchestration, and tracing, you get a complete backend: Qoder reads files, runs commands, and delivers finished work, from generated files to completed actions. Every task runs in an isolated sandbox, is orchestrated through HarnessRouter, and is fully traced. Build your frontend and let Qoder handle your users' tasks.\n\n![uploaded image](/media/?type=post&id=122233&key=user_uploads/14642/7be585c9-451d-4618-bd89-1bbf42951eb2)\n\n\n**Run it:** HarnessRouter is the open-source UHP server, and HarnessRouter Cloud runs it for you. You build the frontend; the harness is your backend.\n\n**Links**\n\n* Spec: [unifiedharnessprotocol.org](http://unifiedharnessprotocol.org)\n* Repo: [github.com/HarnessRouter/harnessrouter](http://github.com/HarnessRouter/harnessrouter)\n* Cloud: [harnessrouter.ai](http://harnessrouter.ai)\n\n**Our ask:** If you build agent harnesses, implement UHP and run the conformance suite. If you're building an agent product, skip the harness engineering: use Qoder as your backend through HarnessRouter and tell us which harness you want next.", "url": "https://www.ycombinator.com/launches/VnV-uhp-unified-harness-protocol-by-harnessrouter", "votes": 4, "created_at": "2026-10-14T22:11:14.980Z" }, { "id": 111172, "title": "HarnessRouter: Open-Sourcing the World’s First Unified Interface for Agent Harnesses and the Unified Harness Protocol", "tagline": "Plug Codex, Claude Code, and Hermes into your backend on your own infrastructure. Introducing the Unified Harness Protocol (UHP), an open standard for connecting applications to different agent harnesses.", "body": "Hey everyone 👋 Three weeks ago, we[ launched HarnessRouter here on YC](https://www.ycombinator.com/launches/RpL-harnessrouter-bring-the-world-s-best-ai-agents-into-your-app-with-one-api) with one promise:\n\nBring the world’s best AI agents into your app, with one API.\n\nToday, we’re opening the layer underneath that promise.\n\nWe’re releasing HarnessRouter Community Edition and the Unified Harness Protocol (UHP). You can now run Codex, Claude Code, and Hermes as your product’s backend on infrastructure you control, using the same API contract as HarnessRouter Cloud.\n\n**TL;DR：**\n\nHarnessRouter is the world’s first unified interface for agent harnesses.\n\nYour product sends a task through one agent API. HarnessRouter runs the supported harness you choose and returns completed work, including files, artifacts, progress, and results.\n\nSessions, streaming, cancellation, and failure handling follow the same contract across Codex, Claude Code, and Hermes. You can add or switch a supported harness without rebuilding your product integration.\n\n🎥[ Watch the launch video](https://www.youtube.com/watch?v=iqrfCBrb6zY)\n\n### **Why agent harnesses aren't infrastructure yet**\n\nAn agent harness is the runtime layer around a model. It executes tasks, uses tools, manages sessions and files, streams progress, and returns completed work.\n\nHistorically, product teams built this layer themselves: task execution, session management, streaming, file and artifact handling, and error recovery, then maintained everything as models and tools evolved.\n\nNow frontier labs and open-source communities are building increasingly capable harnesses. Codex, Claude Code, Hermes, and DeepSeek Harness are examples. But they're still seen as coding tools rather than reusable infrastructure, so teams keep rebuilding this layer in-house. Just as product teams don't build their own databases, they shouldn't have to build their own harness layer either.\n\nEven teams that do adopt an existing harness hit the next obstacle: every harness works differently, so each new product-harness pair needs its own integration. We call this the N×M harness problem. In practice, it becomes harness lock-in: teams stick with the first harness they integrated, even when better or cheaper options exist.\n\nWe asked a simple question: what if agent harnesses became plug-and-play infrastructure that any product can build on?\n\nPlug-and-play means you integrate once, run any supported harness, and switch anytime a better or cheaper one ships.\n\nThat is what HarnessRouter makes possible.\n\n### **What we’re open-sourcing**\n\nWe’re releasing two core components under the Apache License 2.0:\n\n* **Unified Harness Protocol (UHP):** UHP is an open standard that gives different agent harnesses a shared execution contract. This release includes a versioned specification, schemas, and a conformance suite covering harness configuration, task execution, progress, sessions, files, cancellation, errors, and results.\n* **HarnessRouter Community Edition:** The self-hosted implementation of UHP. Gateway, Runner, and Console ship in a single Docker container. It runs Codex, Claude Code, Hermes, and more through one API and passes the full UHP conformance suite.\n\n![uploaded image](/media/?type=post&id=111172&key=user_uploads/14642/2bea0a11-8aba-49c5-9a85-112001854d96)\n\nYour model-provider credentials, application state, and files remain under your control. Model calls still go to the providers you configure.\n\nMCP connects agents to tools. UHP covers a different boundary: how an application drives a complete agent harness and receives its full execution lifecycle.\n\n### **Start self-hosted. Scale with Cloud when you’re ready.**\n\nHarnessRouter Community Edition and HarnessRouter Cloud implement the same UHP contract, so one integration works for both. Start self-hosted on infrastructure you control, or scale into Cloud when you're ready.\n\nHarnessRouter Cloud provides agent harness as a service (HaaS): fully managed harnesses with serverless execution in isolated sandboxes, so teams can scale concurrent runs without operating sandbox capacity themselves.\n\n### **Agent harnesses can do more than write code: runnable examples**\n\nWe also released a **Starter Kit** with runnable applications that show an end-to-end Community Edition integration.\n\nOne example puts a harness behind an Excel column so each row can trigger agent work. Other examples cover presentations, dashboards, and video generation.\n\n![uploaded image](/media/?type=post&id=111172&key=user_uploads/14642/914297fb-2588-4d8a-9a3b-37d39d82bae7)\n\nAgent harnesses can do much more than write code. We want the Starter Kit to show what becomes possible when you put them inside products.\n\n![uploaded image](/media/?type=post&id=111172&key=user_uploads/14642/f4cff64a-7539-41b3-804e-fa5ee53d77bd)\n\nStarter Kit components are available under their applicable licenses.\n\n### **Choose harnesses in production with evidence**\n\nWe benchmarked eight Harness × Model configurations on the same task and input. Cost varied by 475× and latency by 3.2×. Even with the model fixed, changing the harness moved cost by 1.5–2.1× and latency by up to 1.95×.\n\nHarness selection is a task-level production decision, not a one-time choice. HarnessRouter helps teams compare configurations on their own workloads. This was one controlled test, not a universal ranking; we published the methodology, results, and limitations.\n\n### **What teams are already building**\n\nTeams are using HarnessRouter in very different settings:\n\n* 🏥 Stanford Medicine is connecting its operational data through a shared agent layer, an “academic brain” for the organization.\n* ✅ Readily.ai encodes domain expertise into agent skills and can move a new agent from problem and plan to production within 24 hours.\n* 🎬 Spira.ai drives its generation pipeline through HarnessRouter.\n* 🪄 hibo.ai uses HarnessRouter to execute and evaluate agent skills.\n\n### **Why we built it**\n\nWe’re Kuanze Ma and Richard Song, the co-founders of HarnessRouter.\n\nKuanze is a four-time founder focused on human-AI systems. Richard has spent more than a decade building large-scale systems, including at TigerGraph and Meta.\n\nWe both worked on agent systems before HarnessRouter. We kept seeing product teams rebuild the same application-to-harness layer, so we decided to turn that layer into shared infrastructure.\n\n### **What we want from you**\n\n* If you build an agent harness or already maintain your own runtime, read UHP and tell us where it is wrong. Which parts should be standardized, and which should remain harness-specific? That comparison is worth more to us than a signup.\n* Try the Community Edition Quickstart on a clean machine. Tell us where it breaks or where the execution lifecycle is incomplete.\n* If your compliance requirements prevent you from using a hosted agent runtime, try Community Edition on infrastructure you control.\n* If you want to contribute, we use a proposal-before-code process. Describe the problem, your proposed change, and its expected impact. You do not need to arrive with a finished implementation.\n* Intros are welcome to teams shipping agent-powered features that do not want to own another backend.\n\n### **Run it yourself**\n\n* [Open-source repository](https://github.com/HarnessRouter/harnessrouter)\n* [Unified Harness Protocol](https://unifiedharnessprotocol.org)\n* [Starter Kit](https://github.com/HarnessRouter/starter-kit)\n* [Benchmark and methodology](https://harnessrouter.ai/benchmarks)\n* [Docs and HarnessRouter Cloud](https://harnessrouter.ai)\n\nReach us at [contact@harnessrouter.ai](mailto:contact@harnessrouter.ai).", "url": "https://www.ycombinator.com/launches/Sv6-harnessrouter-open-sourcing-the-world-s-first-unified-interface-for-agent-harnesses-and-the-unified-harness-protocol", "votes": 6, "created_at": "2026-08-17T22:23:24.250Z" }, { "id": 106971, "title": "HarnessRouter: Bring the World's Best AI Agents Into Your App, With One API", "tagline": "One API that puts Codex, Claude Code, Hermes, and more behind your product, so your users get real output: videos, games, code, documents.", "body": "Hey everyone 👋 Today we're introducing HarnessRouter.\n\n**TL;DR:** HarnessRouter lets builders bring Codex, Claude Code, Hermes, and other agents into your products through one API. Each task runs in an isolated sandbox with step-by-step tracing and configurable cost caps. It's designed to scale from consumer apps to large-scale model evaluations, orchestrating thousands of isolated sandbox runs in parallel. Start with our [AGENTS.md](https://harnessrouter.ai/agents.md), drop it into your coding agent, describe want you want to build, add an API key, and ship without rebuilding agent runtime infrastructure.\n\n**Try it now:** [harnessrouter.ai](http://harnessrouter.ai?utm=yc)\n\n\n\n## **The Problem**\n\nThere's a gap between what AI agents can do and what your product can offer.\n\nAgents like Codex and Claude Code can genuinely finish work now, but they're built for developers, not for your users. Bringing that capability to your users inside your own product means building the infrastructure yourself: isolated execution environments, agent runtime, tool orchestration, file handling, streaming, retries, permissions, cost controls. Every team building an AI feature rebuilds this same stack from scratch, and it takes months. After launch, the upgrades and maintenance never stop.\n\nAs a result, most teams ship a chat interface instead, when what users actually need is finished output.\n\n## **The Solution**\n\nHarnessRouter runs the entire agent stack as a service. Your product sends a task through one API; We run it on the agent you choose and return the result in structured, renderable form: reviewable diffs, generated files, images, video, confirmed tool actions.\n\nTeams are already running production workloads on it:\n\n* 🏥 A top medical research institution is connecting its operational data into a unified agent layer, an \"academic brain\" for the organization.\n* ✅ A leading healthcare compliance company encodes domain expertise into agent skills, saving their clients hundreds of hours of manual work per audit.\n* 🎬 An AI video marketing startup drives its content generation pipeline through HarnessRouter, producing viral-grade video at human quality.\n\nIntegration takes three steps: drop our [AGENTS.md](https://harnessrouter.ai/agent.md) into your coding agent, describe the feature you want and add your API key. Switching agents is a one-line configuration change, and the same setup scales from a single task to thousands of concurrent runs.\n\n## **Who We Are**\n\n**Kuanze Ma, Co-founder**\\\nKuanze is a four-time founder focused on human–AI systems, with experience in systems design, product management, algorithms, recruiting, marketing, and engineering. He holds a BSc in Mathematics, a diploma in Software Engineering, and an MSL from Northwestern University.\n\n**Richard Song, Co-founder**\\\nRichard has over a decade of experience building large-scale systems, including vertical AI agents powered by private data and domain knowledge. Previously, he was a Senior Director at TigerGraph and a Senior Software Engineer at Meta. He holds an MS in Computer Science from Cornell University and a BS in Computer Science.\n\n## **Our Ask**\n\n* **If you're building an AI feature**, start with the free 7-day trial. We'll help you integrate.\n* **If you need to run thousands of agents in parallel**, for model evaluations, batch generation, or large-scale pipelines, that's what the sandbox orchestration layer was built for. Talk to us.\n* **If you've built your own agent infrastructure**, we'd value the comparison. Tell us what we're missing.\n* **Intros welcome** to any team that wants to ship agent-powered features without building the backend.\n\nReach us at [contact@harnessrouter.ai](mailto:contact@harnessrouter.ai)", "url": "https://www.ycombinator.com/launches/RpL-harnessrouter-bring-the-world-s-best-ai-agents-into-your-app-with-one-api", "votes": 29, "created_at": "2026-07-23T13:44:28.619Z" }, { "id": 99723, "title": "ClawTrace — Make Your OpenClaw Agent Better, Cheaper, and Faster", "tagline": "The observability platform for OpenClaw agents: execution traces, cost analysis, and Tracy, your OpenClaw's doctor agent.", "body": "## 🚀 TL;DR\n\n[ClawTrace](https://clawtrace.ai?utm=yc) is the observability platform for OpenClaw agents. It captures every trajectory your OpenClaw agent runs — every LLM call, tool use, and sub-agent delegation — and gives you three views to understand it: an execution path, a call graph, and a timeline. When you need answers fast, ask Tracy, your built-in AI analyst, in plain English. Watch our demo [here](https://youtu.be/-moG7vCkawQ?si=ivl7Utv3h7ynv5rb):\n\n—\n\nHello, world! I'm Richard, and today I'm excited to introduce **ClawTrace** — the observability platform for OpenClaw agents.\n\nAI agents are going to production. But right now, when something goes wrong, you're flying blind.\n\n## ❌ The Problem\n\nDeploying an OpenClaw agent is easy. Understanding what it actually did is not.\n\nWhen a run costs $104.70 instead of the usual $1.5, you have no idea why. When an agent fails silently, you don't know which step broke or what input caused it. When a trajectory takes 3 minutes instead of 30 seconds, you can't tell where the time went. You end up reading raw JSON logs, manually counting token estimates, and guessing at execution paths. This doesn't scale.\n\nExisting options make this worse, not better:\n\n* **General distributed tracing tools** (Jaeger, Zipkin, Datadog) weren't built for LLM concepts — they have no understanding of token counts, model costs, prompt/completion pairs, or sub-agent hierarchies.\n* **Framework-specific tools** like LangSmith only work within their own ecosystem. If you're on OpenClaw, you're on your own.\n* **Point solutions** cover one slice of the problem — just logs, just cost tracking, just evals — and leave you to stitch everything together yourself.\n* **Every tool** dumps data into a dashboard and expects you to interpret it. There's no analyst. You still have to do all the thinking.\n\n## ⭐️ Our Solution\n\nWe built ClawTrace to give you complete visibility into every OpenClaw agent run — automatically, with zero code changes to your agent.\n\nOne plugin. Three commands. Every trajectory captured.\n\n```bash\nopenclaw plugins install @epsilla/clawtrace\nopenclaw clawtrace setup\nopenclaw gateway restart\n```\n\nThat's it. From that point on, every agent run streams to ClawTrace automatically.\n\n**With ClawTrace, you get:**\n\n* **Execution Path** — a collapsible tree of every step your agent took: LLM calls, tool executions, sub-agent delegations, with full input and output payloads at every node. Metadata badges show model name, duration, token counts, and estimated cost inline.\n\n ![uploaded image](/media/?type=post&id=99723&key=user_uploads/14642/d592e3b7-c8d3-4f7c-b71d-a27037551bba)\n\n* **Call Graph** — an interactive force-directed diagram showing the relationships between every agent, model, and tool in a run. Understand the shape of a complex multi-agent workflow at a glance.\n\n ![uploaded image](/media/?type=post&id=99723&key=user_uploads/14642/e81258a7-05d0-4c5d-be9a-0ef944b72329)\n\n* **Timeline** — a Gantt chart of every span in the trajectory, positioned by start time and sized by duration. Bottlenecks, parallelism, and idle gaps become immediately visible.\n\n ![uploaded image](/media/?type=post&id=99723&key=user_uploads/14642/bf94f46d-90e6-4ea4-8b1e-2971ad79af85)\n\n* **Tracy, your OpenClaw’s Doctor** — every other observability tool gives you data and expects you to figure it out yourself. Tracy is different. Ask her a question in plain English — _\"where is the bottleneck in this trace?\"_ — and she queries your trajectory graph live, generates a visualization, and delivers specific recommendations: which step to fix, why, and how. Tracy is powered by a Claude managed agent and has real-time Cypher access to your full trajectory graph via PuppyGraph graph lake-house architecture.\n\n ![uploaded image](/media/?type=post&id=99723&key=user_uploads/14642/7cb3bad9-86b3-4795-b761-75b7a390ce62)\n\n* **Cost Estimation** — per-span cost calculation covering 80+ models across OpenAI, Anthropic, Google, DeepSeek, Mistral, Alibaba Qwen, Zhipu GLM, Moonshot, and more. Cache-aware pricing (fresh input vs. cached input vs. output tokens) for accurate estimates.\n* **Consumption-based billing** — pay for what you use with credits. No seat fees, no per-user pricing. Start with 100 free credits.\n\n## 🔦 The Ask\n\nAI agents are moving from demos to production. ClawTrace is the observability layer that makes that transition safe, debuggable, and cost-efficient.\n\n* 🚀 **Sign up for free** at [clawtrace.ai](http://clawtrace.ai) — 100 credits included, your first trajectory shows up in minutes.\n* ⭐ **Star us on GitHub** — ClawTrace is fully open source under Apache 2.0: [github.com/epsilla-cloud/clawtrace](https://github.com/epsilla-cloud/clawtrace)\n* 💬 **Tell us what you're building** — we'd love to hear about your OpenClaw setup and what observability problems matter most to you. [Schedule a call with me](https://epsilla-ai.sg.larksuite.com/scheduler/dc6a62e558c3a1cc).", "url": "https://www.ycombinator.com/launches/PwR-clawtrace-make-your-openclaw-agent-better-cheaper-and-faster", "votes": 12, "created_at": "2026-04-14T15:34:37.032Z" }, { "id": 84075, "title": "Epsilla — Ship production-ready AI agents on day 1", "tagline": "All-in-one platform to create AI agents with your private data and knowledge.", "body": "### **🚀 TL;DR**\n\n[Epsilla](https://www.epsilla.com/) is an all-in-one platform for building AI agents powered by your private data and knowledge. Easy to use for domain professionals, deeply customizable for AI experts, and fully equipped for enterprise customers with security, scalability, and integration. Watch our demo [here:](https://www.youtube.com/watch?v=ZhBPsxr2AL0)\n\n---\n\n—\n\nHello, world! We are Richard, Eric, and Ricki. Today, we are super excited to introduce Epsilla, the all-in-one platform for creating AI agents with your private data and knowledge.\n\n### **❌ The Problem**\n\nBuilding a prototype AI agent is easy, but creating production-level AI agents with private knowledge can be overwhelming. It involves managing LLMs, prompt engineering, tool usage, memory management, vector databases, RAG (Retrieval-Augmented Generation), evaluation, and more.\n\nExisting AI agent-building products in the market are:\n\n* Either developer-facing tools that require a significant amount of engineering work;\n* Or lacking depth in customization and flexibility, limiting the final agent's performance and quality;\n* Or just focus on only one small aspect of the problem—such as prompt engineering, workflow, retrieval, evaluation, or hosting—leaving builders to handle the heavy lifting of integrating these components into a cohesive system.\n\n### **⭐️ Our Solution**\n\n![uploaded image](/media/?type=post&id=84075&key=user_uploads/14642/83e9fd99-cf4a-473a-b1ac-57f4935ff4dc)\n\nWe have reimagined the AI agent platform from the ground up and developed an all-in-one solution for creating, iterating, and operating AI agents—without writing a single line of code.\n\nWith Epsilla, you can:\n\n* Build high-quality knowledge bases from diverse data sources, including uploaded files, websites, Google Drive, Notion, cloud storage, and more.\n* Deeply customize AI agents with options for appearance, prompt tuning, workflow customization, and advanced, modular, agentic, and graph-based RAG.\n* Evaluate agent performance, monitor user engagement, and manage user feedback.\n* In addition to providing an out-of-the-box ChatGPT or Perplexity-like UI, we also allow developers to use the agents as their application backend via REST API.\n* Epsilla seamlessly integrates with a growing set of Large Language Model providers, allowing you to choose the best model at any stage of the knowledge base and agent workflow to balance quality, latency, and cost.\n\n### **🔦 The Ask**\n\nThousands of GenAI builders, along with dozens of enterprises and SMBs across various industries, are already building their AI agents on Epsilla. We hope to see you join them soon!\n\n* Sign up for FREE at to build your first AI agent within 10 minutes!\n* Let’s talk about your use case! Schedule a meeting with us [here](https://epsilla-ai.larksuite.com/scheduler/4aca8159d1224454).\n* Join our community with us on [Discord](https://discord.gg/cDaY2CxZc5) and share what you built on Epsilla!", "url": "https://www.ycombinator.com/launches/Ls3-epsilla-ship-production-ready-ai-agents-on-day-1", "votes": 35, "created_at": "2024-09-17T16:47:45.508Z" }, { "id": 73587, "title": "Epsilla - A 10x faster open source vector database", "tagline": "The information retrieval foundation for the next generation of AI applications", "body": "### **🚀 TL;DR**\n\nEpsilla is an open-source vector database. Epsilla offers low-latency searches across billions of vectors, consumption-based database-as-a-service, comprehensive APIs, and multi-language bindings. Our team has 7 years of experience building the high-performance graph database, and our advanced ANN index leverages parallel graph traversal technology, making the vector search 10x faster.\n\n![uploaded image](/media/?type=post&id=73587&key=user_uploads/14642/801e5229-0b56-4eb5-a3fb-e5ff7d2686ec)\n\n### **❌ The Problem**\n\nWith the surge of LLMs and the evolution of AI agents for task planning and decomposition for complex tasks, a **high-performance vector database** for information retrieval and enhancing context in prompts is a **MUST**! Most vector databases utilize HNSW, and its performance significantly degrades when aiming for high search precision.\n\n### **⭐️ Our Solution**\n\nWe’ve reimagined vector search from the ground up for scalability, performance, and cost-effectiveness. We implemented the state-of-art ANN index algorithm from the academia that leverages intra-query parallel graph traversal, which outperforms HNSW by **5x** on high precision query latency on medium size (1M) vector space and outperforms HNSW by **50 times** on large-scale vector search.\n\n![uploaded image](/media/?type=post&id=73587&key=user_uploads/14642/7f276b64-0500-4286-b589-e23d339abe6d)\n\n### **🔦 The Ask**\n\n* Try us at \n* Follow our repo at \n* Connect with us on [Discord](https://discord.gg/cDaY2CxZc5)\n* Let’s talk at !", "url": "https://www.ycombinator.com/launches/J8t-epsilla-a-10x-faster-open-source-vector-database", "votes": 41, "created_at": "2023-07-31T01:45:04.471Z" } ] }, { "id": 28968, "name": "Trainy", "slug": "trainy", "former_names": [ "AB Labs" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/78fb6a9f034f5447cc3472b66f6c660fdf0cfa60.png", "website": "https://trainy.ai/", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Goodbye Slurm, Hello Konduktor.\r\n\r\nTrainy Konduktor is a software platform for AI teams to schedule workloads with priority, control resource allocation, and improve GPU reliability. With Konduktor, teams submit jobs to a healthy pool of GPUs, assign job priority with a simple user interface, and never worry about hardware faults again.", "one_liner": "Infrastructure for managing GPU clusters for training/serving.", "team_size": 3, "industry": "B2B", "subindustry": "B2B", "launched_at": 1687891811, "tags": [ "Developer Tools", "Machine Learning", "SaaS", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2023", "status": "Active", "industries": [ "B2B" ], "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/trainy", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/trainy.json", "year_founded": 2023, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/trainy-ai/about/", "x_url": "https://twitter.com/TrainyAI", "fb_url": null, "cb_url": null, "github_url": "https://github.com/Trainy-ai/", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/78fb6a9f034f5447cc3472b66f6c660fdf0cfa60.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": 509361, "full_name": "Roanak Baviskar", "title": "Founder", "founder_bio": "Studied CS & Mathematics at UC Santa Cruz. Led Audio team at Hive AI, where we trained and deployed 500M parameter-scale models to production.", "is_active": true, "linkedin_url": "https://linkedin.com/in/roanakb", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5b4b5bdb3a6c92540c471e0ac581790dcb5bba8a.jpg" }, { "user_id": 1404133, "full_name": "Andrew Aikawa", "title": "Founder", "founder_bio": "Co-founder and CTO at Trainy building a training platform to make deep learning go faster. Previously a lead Machine Learning Engineer for Hive AI's object detection products. I completed my Physics Ph.D. UC Berkeley '22 where my thesis focused on applying computer vision and deep learning on nanoscience. Physics & Computer Science B.A. UC Berkeley '17.", "is_active": true, "linkedin_url": "https://linkedin.com/in/asai", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/870dd300be109c4ae6d065c20bc6114a5a646b21.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 97424, "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. \n\nAlso join our community if you want to stay up to date with the development of our tools. ", "url": "https://www.ycombinator.com/launches/Isl-trainy-identify-bottlenecks-boost-training", "votes": 21, "created_at": "2023-06-27T19:06:48.265Z" } ] }, { "id": 28983, "name": "Converge", "slug": "converge", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6ddaa5bebf2aae550b90599e16a46dc1f877c755.png", "website": "http://www.runconverge.com", "all_locations": "New York City, NY, USA", "long_description": "We're building the unified marketing measurement stack for online stores. We make it easy for marketeers to understand where their customers come from, cut unprofitable channels, and scale when things are working.\r\n\r\nWe are vertically integrating the modern data stack for marketing teams of online stores by consolidating customer data collection, consent management, identity resolution, transformations, attribution, data forwarding, and analytics into a single platform.", "one_liner": "All-in-one marketing measurement for B2C", "team_size": 11, "industry": "B2B", "subindustry": "B2B", "launched_at": 1687127368, "tags": [ "SaaS", "Analytics", "E-commerce", "Marketing", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 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, "question_answers": null, "url": "https://www.ycombinator.com/companies/converge", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/converge.json", "year_founded": 2022, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/81685997/", "x_url": "https://twitter.com/runconverge", "fb_url": null, "cb_url": null, "github_url": "https://github.com/run-converge", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/6ddaa5bebf2aae550b90599e16a46dc1f877c755.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Nicolas Dessaigne", "url": "https://www.ycombinator.com/people/nicolas-dessaigne" }, "founders": [ { "user_id": 559019, "full_name": "Jan-Henrik Lambrechts", "title": "Founder", "founder_bio": "co-founder and ceo @Converge -- worked on ml vision models @TsinghuaU before that", "is_active": true, "linkedin_url": "https://linkedin.com/in/janhenrik-lambrechts", "x_url": "https://twitter.com/janhenriklamb", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ef7a2e2909a4692230ff50a73fb74c4526156c45.jpg" }, { "user_id": 772323, "full_name": "Jerome Billiet", "title": "Founder", "founder_bio": "Co-founder at Converge - studied finance at London Business School before.", "is_active": true, "linkedin_url": "https://linkedin.com/in/j%C3%A9r%C3%B4mebilliet", "x_url": "https://twitter.com/BillietJerome", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5e225291757e7b22b72f9ae5b8c186eb23fe0d4c.jpg" }, { "user_id": 772314, "full_name": "Thomas Holvoet", "title": "Founder", "founder_bio": "Studied CS in Ghent (Belgium), went on to drop out of the data science masters at Columbia to start Converge", "is_active": true, "linkedin_url": "https://linkedin.com/in/thomas-holvoet", "x_url": "https://twitter.com/thomas_holvoet", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/414b694acb50a5deca033ab387a6e0d2868c48a0.jpg" } ], "jobs": [ { "id": 79269, "title": "Account Executive", "url": "https://www.ycombinator.com/companies/converge/jobs/lQamnCz-account-executive", "location": "New York, NY, US", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$160K - $200K", "equity_range": "0.15% - 0.35%", "experience": "1+ years", "visa": "Will sponsor", "skills": [] }, { "id": 89633, "title": "Product Engineer", "url": "https://www.ycombinator.com/companies/converge/jobs/rCwUC9I-product-engineer", "location": "New York, NY, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$180K - $240K", "equity_range": "0.50% - 0.85%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [ { "title": "MarTech startup Converge raises $5.6M", "url": "https://www.axios.com/pro/media-deals/2025/02/06/exclusive-martech-startup-converge-raises-56m", "date": "Feb 06, 2025" } ], "launches": [ { "id": 72382, "title": "Converge - Segment for ecommerce", "tagline": "We help online stores improve ad performance and attribution accuracy through better tracking.", "body": "**TL;DR:** [**Converge**](https://www.runconverge.com?utm_source=yc&utm_medium=organic&utm_campaign=launch-yc) auto-tracks and forwards ecommerce customer events like Add To Cart and Purchase to analytics and ad platforms for accurate attribution and better ad performance.\n\n### **Problem: Tracking for ecommerce is broken**\n\nCorrect attribution and conversion tracking is at the core of every ecommerce business.\n\nHowever, tracking setups suffer from..\n\n* **Missing** **data**: Stores miss on avg. \\~10-30% of conversions due to limitations of browser tracking (e.g. ad-blockers) resulting in _broken attribution data and wasted ad budget._\n* **Poor observability:** Popular tools like Google Tag Manager provide no way to check whether tracking is still working, resulting in _costly bugs that remain undiscovered._\n* **Cluttered configurations:** Operators often loose grip on their tracking setup after years of uncoordinated updates, resulting in a clutter of pixels, tags, and first-party integrations across multiple platforms.\n* **Lack of developers:** Many ecommerce teams don't have in-house devs, making it infeasible for them to integrate with existing CDP tools such as Segment.\n\n## **Solution: Accurate auto-tracking**\n\nConverge tracks all important events automatically – across the browser, store backend and subscription platforms. No technical expertise required.\n\nBecause conversions are being tracked on the store backend rather than the browser, Converge can track 100% of conversions and forward these to relevant ad platforms and analytics tools.\n\nUnlike Segment or other CDPs, Converge allows non-technical ecommerce operators to set this tracking up in minutes.\n\n![uploaded image](/media/?type=post&id=72382&key=user_uploads/772323/7f38e933-f6ce-489f-abf6-cd11149e83d1)\n\nOnce tracking is set up, Converge aggregates data from all sources and provides a single overview of ecommerce KPIs.\n\n![uploaded image](/media/?type=post&id=72382&key=user_uploads/772323/5eb15873-3ea8-4e32-8e96-2efa057df4d7)\n\nUsers can also break down attribution metrics across channels, campaigns, adsets, and even ads, showing what is driving growth on a granular level.\n\n![uploaded image](/media/?type=post&id=72382&key=user_uploads/772323/eb78601f-2d1a-4a75-a35b-f5e7db168d3f)\n\n## **Our ask**\n\n* Sign up for [**Converge**](https://www.runconverge.com?utm_source=yc&utm_medium=organic&utm_campaign=launch-yc) today and test it for free!\n* If you know any **ecommerce brands or agencies**, we would love to chat!", "url": "https://www.ycombinator.com/launches/IpS-converge-segment-for-ecommerce", "votes": 24, "created_at": "2023-06-20T14:03:45.650Z" } ] }, { "id": 28998, "name": "Automorphic", "slug": "automorphic", "former_names": [ "Sibyl" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6632890863ba8f97b3c98f84ce71158a24887e9a.png", "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, "tags": [ "AIOps", "Deep Learning", "Developer Tools", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 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, "question_answers": null, "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", "x_url": "https://twitter.com/AutomorphicAI", "fb_url": null, "cb_url": null, "github_url": "https://github.com/automorphic-ai", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/6632890863ba8f97b3c98f84ce71158a24887e9a.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": 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", "x_url": "https://twitter.com/sandkoan", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2f073adeb6c9ba6591e097d17f81f051d0ae71ff.jpg" }, { "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", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/38c64b0f499364e92826147408ed30c847ad9260.jpg" }, { "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.", "is_active": true, "linkedin_url": "https://linkedin.com/in/mahesh-natamai-b17683188", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c7ac55ddb274bbc274308cc40cf70b18aa906241.jpg" } ], "jobs": [], "news": [ { "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" } ], "launches": [ { "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" } ] }, { "id": 29073, "name": "Terracotta AI", "slug": "terracotta-ai", "former_names": [ "Monitaur", "Monitaur (Pivoted)", "Monitaur", "OpsBerry AI (formally Monitaur)", "OpsBerry AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7901d3a776bcd60d2813e642a8814ea750bb84ef.png", "website": "https://tryterracotta.com", "all_locations": "Las Vegas, NV, USA", "long_description": "Terracotta AI is an AI-powered Infrastructure as Code PR reviewer for Terraform, OpenTofu, and CDK-TF code, making Infrastructure as Code changes more transparent, less risky, and faster.\r\n\r\nTerracotta stops your Infrastructure as Code deployments from becoming ticking time bombs every time you modify your environment with AI-driven, contextual feedback delivered directly to your pull requests.", "one_liner": "AI-powered Infrastructure as Code PR reviews", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1686680826, "tags": [ "Developer Tools", "DevOps", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "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/terracotta-ai", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/terracotta-ai.json", "year_founded": 2023, "city": "Las Vegas", "country": "US", "linkedin_url": "https://www.linkedin.com/company/tryterracotta", "x_url": "https://x.com/tryterracotta", "fb_url": null, "cb_url": null, "github_url": "https://github.com/enfraxyz", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/7901d3a776bcd60d2813e642a8814ea750bb84ef.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/eabe482f39bc0afc6cc8d9d7d476984b577f043f.png" ], "primary_partner": { "name": "Garry Tan", "url": "https://www.ycombinator.com/people/garry-tan" }, "founders": [ { "user_id": 925045, "full_name": "Carlos Feliciano", "title": "Founder", "founder_bio": "Co-founder and CEO of Terracotta AI. Over a decade of experience in Infrastructure, monitoring, and operations at YC-backed startups and large enterprises. AWS Solutions Architect. Love PC gaming, fitness, the beach, and just good vibes!", "is_active": true, "linkedin_url": "https://linkedin.com/in/carlosfelicianoii", "x_url": "https://twitter.com/gtlpanda", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/eeaf8878cafd92cf0af4729b52597c4c0f51b0a8.jpg" } ], "jobs": [], "news": [], "launches": [ { "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", "votes": 16, "created_at": "2025-06-16T22:20:23.169Z" }, { "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": 29086, "name": "Eden Care", "slug": "eden-care", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7fa49eb2930eeded02c619636a22909358301f3b.png", "website": "https://www.edencaremedical.com/", "all_locations": "Nairobi, Nairobi County, Kenya", "long_description": "Eden Care is building the claims infrastructure for African health insurance ", "one_liner": "Claims infrastructure for African health insurance", "team_size": 28, "industry": "Fintech", "subindustry": "Fintech -> Insurance", "launched_at": 1687277447, "tags": [ "Fintech", "Health Insurance", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2023", "status": "Active", "industries": [ "Fintech", "Insurance" ], "regions": [ "Kenya", "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/eden-care", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/eden-care.json", "year_founded": 2022, "city": "Nairobi", "country": "KE", "linkedin_url": "https://www.linkedin.com/company/edencaremedical/?viewAsMember=true", "x_url": "https://twitter.com/edencaremedical", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/7fa49eb2930eeded02c619636a22909358301f3b.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/32d8553d147f9813494bc88a74f31afc506e6b7a.png" ], "primary_partner": { "name": "Tom Blomfield", "url": "https://www.ycombinator.com/people/tom-blomfield" }, "founders": [ { "user_id": 584359, "full_name": "Moses Mukundi", "title": "Founder", "founder_bio": "I founded my first startup, an agritech startup, at 23 that scaled to profitability and was acquired in 2017. I spent 6 years in the insurance and healthcare verticals in Africa before pursuing my MBA at Wharton Business School. ", "is_active": true, "linkedin_url": "https://linkedin.com/in/mosesmukundi", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/92dbf4e853015c0ebd369988003ecaa2eb7b42c0.jpg" } ], "jobs": [], "news": [ { "title": "Eden Care: Y Combinator's latest health insurance bet in Africa", "url": "https://techcabal.com/2023/08/26/eden-care-medical-y-combinators-latest-health-insurance-bet-in-africa/", "date": "Aug 26, 2023" }, { "title": "Eden Care becomes first Rwandan company to join Y Combinator", "url": "https://www.benjamindada.com/eden-care-y-combinator-first-rwandan/", "date": "Jul 04, 2023" } ], "launches": [ { "id": 72392, "title": "Eden Care - Digital health insurance for employers in Africa", "tagline": "Saving employers time and money with better, cheaper health insurance", "body": "**Tl;dr:** Eden Care offers digital health insurance to employers in Africa. We are making health insurance cheaper by building a new tech stack that reduces the cost of insurance operations by 43%. In 6 months since launch, we have $2.1M in gross premiums and growing 100% month-on-month. Check out [Eden Care](https://www.edencaremedical.com/) today.\\\n—\n\nHello, I am Moses Mukundi, and my team and I are building [Eden Care](https://www.edencaremedical.com/). We are on a mission to provide access to affordable quality health insurance to the 90 million uninsured African employees. See some of our team below:\n\n![uploaded image](/media/?type=post&id=72392&key=user_uploads/584359/6d025c95-c4e5-41e1-9052-b7f58978a690)\n\n**Problem: Underserved**\n\nAfrican insurance cost of operation (claims, distribution, and fraud cost) is 2.2x the global average resulting in expensive insurance. No wonder, health insurance penetration in Africa is 0.2%, 15x lower than emerging market peers. \n\nThis $11 billion industry hasn’t modernized (manual, limited customer insights, and high fraud waste and abuse) and has largely focussed on large companies and high network individuals, leaving out the majority of Africans. There’s a need for a new solution for Africans to increase health insurance uptake.\n\n**Our Solution: Digital infrastructure that automates the entire value chain**\n\nEden Care is a full-stack licensed health insurer. We are building a new tech that reduces our cost operation by 43% resulting in cheaper cover. \n\nWe have deployed tech infrastructure across 3 main users - HR& admin teams, employees, and healthcare facilities. This enables us to automate the majority of our processes reducing cost but also improving customer experience. \n\n**For HR teams**, we provide them with a portal to easily manage the health benefits of their team.\n\n![uploaded image](/media/?type=post&id=72392&key=user_uploads/584359/17e2bd51-fcc1-4ad0-8dff-946759a190b3)\n\n**For employees and their dependents**, we provide them with an app that helps them access and navigate healthcare, participate in Eden Care’s wellness and prevention program, and earn/redeem rewards.\n\n![uploaded image](/media/?type=post&id=72392&key=user_uploads/584359/3aa361ff-2a28-440f-b060-660a4cc70ebd)\n\n**For service providers**, we have provided an end-to-end digital tool that enables them to quickly serve our members and digitally complete all their processes on our system — eliminating the majority of manual processes and paper, automating the majority of the tasks, and saving time and money.\n\n![uploaded image](/media/?type=post&id=72392&key=user_uploads/584359/6a47735f-0923-4997-8c72-081a79109571)\n\nWith this data-rich view, we can:\n\n1. automate >90% of all back-end insurance processes enabling us to deliver real-time decision-making and personalized health nudges\n2. intervene at the point of service to prevent fraud, waste, and abuse \n3. deliver better underwriting and products more relevant to user needs.\n4. Develop AI tools to improve stakeholder experience while lowering ops cost even further\n\n**The opportunity: Right time to build Eden Care**\n\n1. 22 Africans will transition to middle-income status by 2030. This transition is associated with a 7x growth in health insurance spend.\n2. SMEs are formalising at a faster rate and buying insurance for their teams for the first time. This is the largest insurance opportunity in Africa and is where Eden Care is positioning itself to be the segment leader. \n3. Rapid digitisation of healthcare facilities and end users is for the first time enabling the deployment of end-to-end digital health infrastructure. \n4. 310 million Africans will be middle class by 2030. The majority are young digital native families buying insurance for the first time. Eden Care is becoming the default insurer for this group.\n\n**Ask: How you can help us**\n\n1. Share this post! Please help spread the word, as you never know who it may help.", "url": "https://www.ycombinator.com/launches/Ipc-eden-care-digital-health-insurance-for-employers-in-africa", "votes": 19, "created_at": "2023-06-20T18:45:31.877Z" } ] }, { "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": 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": 29231, "name": "Ubicloud", "slug": "ubicloud", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/621ac44e76ec8f002f47c567b4533df1d318abcc.png", "website": "https://www.ubicloud.com", "all_locations": "San Francisco, CA, USA", "long_description": "Ubicloud is an open source cloud that can run anywhere.\r\n\r\nOur cloud services include elastic compute, block storage, virtual networking, managed Postgres, K8s, AI inference, and powerful IAM. Ubicloud provides these services on bare metal providers, such as Hetzner, Leaseweb, or AWS Bare Metal.\r\n\r\nYou can self-host our software or use our managed service to reduce your cloud costs by 3-10x.", "one_liner": "Open source alternative to AWS", "team_size": 15, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1700481295, "tags": [ "Cloud Computing", "Infrastructure", "AI", "Databases" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2024", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "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/ubicloud", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/ubicloud.json", "year_founded": 2023, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/ubicloud", "x_url": "https://twitter.com/UbicloudHQ", "fb_url": null, "cb_url": null, "github_url": "https://github.com/ubicloud/ubicloud", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/621ac44e76ec8f002f47c567b4533df1d318abcc.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": 26240, "full_name": "Umur Cubukcu", "title": "Founder", "founder_bio": "Previously visiting partner at YC for W23 and S23; now co-founder at Ubicloud. Co-founder and CEO of Citus Data (S11), the creators of the distributed PostgreSQL database Citus. Led the PostgreSQL product team at Azure, after Citus Data was acquired in 2019 by Microsoft.", "is_active": true, "linkedin_url": "https://linkedin.com/in/umurc", "x_url": "https://twitter.com/umurc", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/811b92be504c42ee56cf6aad47e9f0f260d0fc7c.jpg" }, { "user_id": 26241, "full_name": "Ozgun Erdogan", "title": "Founder", "founder_bio": "I’m the cofounder of Ubicloud (YC W24), an open source alternative to AWS. We're on a mission to rebuild the cloud market with different values.\n\nPreviously, I was a partner at Microsoft, leading PostgreSQL engineering teams. I came to Microsoft through its acquisition of Citus Data (S11). I was the cofounder and CTO at Citus, and I learned a lot about doing startups there. Before all this, I built distributed systems at Amazon.", "is_active": true, "linkedin_url": "https://linkedin.com/in/ozgune", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d633f56431a747505416d1e826a81fb1377926ee.jpg" }, { "user_id": 49554, "full_name": "Daniel Farina", "title": "Founder/CTO", "founder_bio": "I am one of the founders of Ubicloud.\n\nI've contributed to a number of control planes from an early phase, starting at Heroku, in what would become Heroku Postgres. Since then, I've serially created new control planes and infrastructure cloud products with some close colleagues, at Citus Cloud and Crunchy Bridge. Ubicloud is the fourth such system.\n", "is_active": true, "linkedin_url": "https://linkedin.com/in/danfarina", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/18aa66df55ba80101caba48b73dd18d85d324c17.jpg" } ], "jobs": [ { "id": 89544, "title": "Software Engineer", "url": "https://www.ycombinator.com/companies/ubicloud/jobs/j4bntEJ-software-engineer", "location": "CA, US / Remote (NL; TR)", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$95K - $250K", "equity_range": "0.15% - 0.50%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [ { "title": "Ubicloud wants to build an open source alternative to AWS | TechCrunch", "url": "https://techcrunch.com/2024/03/05/ubicloud-wants-to-build-an-open-source-alternative-to-aws/", "date": "Mar 05, 2024" } ], "launches": [ { "id": 79315, "title": "Ubicloud - Open source alternative to AWS", "tagline": "Ubicloud is an open source cloud that can run anywhere.", "body": "**TL;DR**: Ubicloud provides IaaS cloud features on bare metal providers, such as Hetzner, Leaseweb, or AWS Bare Metal. You can self-host our software or use our managed service to reduce your cloud costs by 3-10x.\n\nHey everyone 👋 We’re Umur, Daniel, and Ozgun from [Ubicloud](https://www.ubicloud.com). We’re on a mission to rebuild the cloud market with different values. More on us below.\n\n## The Problem\n\n![uploaded image](/media/?type=post&id=79315&key=user_uploads/26241/10a339e1-dafe-421e-99f4-9484960966a7)\n\nAWS, Azure, and Google Cloud make life easier for start-ups and enterprises. But they are closed source, have you rent computers at a huge premium, and lock you in. It gets worse after your credits expire.\n\nAlthough the cloud came in with savings in its early years, the market evolved into a few players that overcharge for non-differentiated services, with increasingly complex products for standard, essential services. Each vendor optimizing for their walled gardens leaves customers stuck maintaining their apps and infra across incompatible clouds.\n\nThe cloud is here to stay. We believe a simpler, secure, and open source version of it will have a lasting impact.\n\n## The Solution\n\nUbicloud offers an open source alternative, reduces your costs, and returns control of your infrastructure back to you — all without sacrificing the cloud’s benefits. We’re starting with elastic compute, virtual networking, block storage (non-replicated), managed PostgreSQL, and powerful IAM.\n\nOur managed cloud runs on cost-effective bare metal providers, such as Hetzner. As a result, you can reduce your costs by 3-10x. Example use-cases:\n\n1. GitHub Actions: Change 1-line in your workflow file. Reduce costs by 10x\n2. Compute for batch processing: Run data pipelines for AI, scientific computing, and video processing - on-demand and encrypted. Reduce costs by 3x (vs AWS VMs)\n3. Managed PostgreSQL: Open source and portable. Uses local NVMes for higher performance, ideal for analytics. Reduce costs by 3x (vs AWS RDS)\n\n## The Team\n\n![uploaded image](/media/?type=post&id=79315&key=user_uploads/89898/3ce2495a-3697-4f8e-a61e-a6aa4a64bde7)\n\n_“Never tell me the odds.” — Han Solo_\n\nWe think the cloud galaxy deserves a solution that stands for open source values. We’re building to those values as part of the Rebel Alliance (yes, an alliance is needed to outmatch the empire :). From left to right:\n\n[Umur](https://www.linkedin.com/in/umurc/) - 5 years at startups. Then co-founded and led Citus Data (S11) to Microsoft acquisition. Led product teams within Azure. YC Visiting Partner for the previous two batches\n\n[Ozgun](https://www.linkedin.com/in/ozgune/) - 4 years at Amazon. Then co-founded and led Citus Data (S11) to Microsoft acquisition. Led engineering teams within Azure.\n\n[Daniel](https://www.linkedin.com/in/danfarina/) - Instrumental in building Heroku PostgreSQL. Amazed everyone with his skills in building managed cloud services at Citus Data, Azure, and Crunchy Bridge.\n\n## Our Ask\n\n1. Help us build the Rebel Alliance. [**Follow us (@UbicloudHQ)**](https://twitter.com/UbicloudHQ) on Twitter and tweet [**this post**](https://twitter.com/UbicloudHQ/status/1767594825023721858)!\n2. Start using Ubicloud for [GitHub Actions](https://www.ubicloud.com/use-cases/github-actions), [secure virtual machines](https://www.ubicloud.com/use-cases/ubicloud-compute), or [managed PostgreSQL](https://www.ubicloud.com/use-cases/postgresql). We reduce costs by 3-10x and we are open source!\n\n## The Deal\n\nTweeting and following us on Twitter gets 5,000 free compute minutes (standard-2). Using Ubicloud for one of the above use cases before demo day gets 10,000 compute minutes. Claim those minutes by sending us an email at [founders@ubicloud.com](mailto:founders@ubicloud.com)", "url": "https://www.ycombinator.com/launches/KdH-ubicloud-open-source-alternative-to-aws", "votes": 121, "created_at": "2024-03-12T16:11:25.761Z" } ] }, { "id": 29300, "name": "Trellis AI", "slug": "trellis-ai", "former_names": [ "Trellis" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f9cc80521b4e48dc602aef29ce4fb7d4c0f5dda1.png", "website": "https://runtrellis.com/", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "Accelerate Medication Access with AI", "team_size": 34, "industry": "B2B", "subindustry": "B2B", "launched_at": 1709255809, "tags": [ "B2B", "Data Engineering", "Infrastructure", "AI", "Databases" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2024", "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/trellis-ai", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/trellis-ai.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/runtrellis", "x_url": "https://twitter.com/runtrellis", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/f9cc80521b4e48dc602aef29ce4fb7d4c0f5dda1.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": 365595, "full_name": "Mac Klinkachorn", "title": "Founder/CEO", "founder_bio": "Mac is the co-founder and CEO of Trellis. Previously, he worked at the Stanford AI lab on large multimodal models for Stanford Health and built ML infrastructure at Cresta, Moveworks, and Amazon. ", "is_active": true, "linkedin_url": "https://linkedin.com/in/sirapop-klinkachorn-stanford", "x_url": "https://twitter.com/MKlinkachorn", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3b1519f0bcfd993a8dbb236c3c3623c4e3ef1818.jpg" }, { "user_id": 1470616, "full_name": "Jacky Lin", "title": "Founder/CPO", "founder_bio": "Jacky is a co-founder of Trellis and has taught hundreds of Stanford graduate students how to build, train, and deploy AI models in the Stanford School of Engineering & Graduate School of Business. Previously, he worked at Meta, the World Bank, and Wayfair. ", "is_active": true, "linkedin_url": "https://linkedin.com/in/jhslin", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/839a64adac97b949f442d82bf502f77a5cc97e42.jpg" } ], "jobs": [ { "id": 90948, "title": "AI Deployment Strategist", "url": "https://www.ycombinator.com/companies/trellis-ai/jobs/qCGwSCc-ai-deployment-strategist", "location": "San Francisco, CA, US / Remote (US)", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "$120K - $220K", "equity_range": "", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 92422, "title": "Member of Technical Staff (full-time)", "url": "https://www.ycombinator.com/companies/trellis-ai/jobs/cg2Sy6U-member-of-technical-staff-full-time", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$150K - $275K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 96753, "title": "Windows Systems Engineer ", "url": "https://www.ycombinator.com/companies/trellis-ai/jobs/g0VlgB5-windows-systems-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Devops", "salary_range": "$100K - $175K", "equity_range": "0.10% - 0.30%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "PowerShell", "Windows" ] }, { "id": 111456, "title": "RCM Operations Specialist, Infusion (AI Platform)", "url": "https://www.ycombinator.com/companies/trellis-ai/jobs/Dtj2yEH-rcm-operations-specialist-infusion-ai-platform", "location": "San Francisco, CA, US / Remote (US)", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "$70K - $120K", "equity_range": "", "experience": "3+ years", "visa": "Will sponsor", "skills": [] }, { "id": 116076, "title": "Forward Deployed Engineers (October 2026)", "url": "https://www.ycombinator.com/companies/trellis-ai/jobs/GU8CEhE-forward-deployed-engineers-october-2026", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$120K - $225K", "equity_range": "", "experience": "1+ years", "visa": "Will sponsor", "skills": [] }, { "id": 116768, "title": "Account Executive", "url": "https://www.ycombinator.com/companies/trellis-ai/jobs/J5OtVzK-account-executive", "location": "San Francisco, CA, US / Remote (US)", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$250K - $350K", "equity_range": "", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 117422, "title": "GTM Engineer", "url": "https://www.ycombinator.com/companies/trellis-ai/jobs/TGrLp7J-gtm-engineer", "location": "San Francisco, CA, US / Remote (US)", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$100K - $175K", "equity_range": "", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [], "launches": [ { "id": 78943, "title": "🌊 Trellis AI: Automate your Pre-sevice workflow⚡️", "tagline": "Reduce time-to-treatment, improve reimbursement rates, and ", "body": "### **TL;DR**\n\nTrellis helps healthcare providers treat more patients faster—while eliminating pre-service paperwork. We automate document intake, prior authorizations, and appeals at scale to streamline operations and accelerate care.\n\n❌ **Problem — Administrative costs are delaying care and draining revenue**\n\nOver 20% of U.S. healthcare spending goes toward administrative costs, delaying care, reducing revenue, and driving staff burnout—while leaving providers with less visibility into patient care than ever before.\n\nPrior authorizations, appeals, and pre-service documentation are some of the biggest bottlenecks to timely treatment. Manual processing is slow, error-prone, and costly—leading to delayed treatments, increased denial rates, and frustrated patients.\n\n🎉 **Solution**\n\nOur AI agent is trained on millions of clinical data points and converts messy, unstructured documents into clean, structured data directly in your EHR—at scale.\n\nWe handle the heavy lifting:\n\n* **Automating document intake** from faxes, PDFs, and scanned forms\n* **Processing prior authorizations and appeals** with high accuracy\n* **Integrating directly into EHR workflows** so staff can focus on care, not paperwork\n\nTrellis in action: Processing hundreds of pages per patient case to identify missing information, complete submissions, and accelerate treatment approvals.\n\n🏃🏽‍♂️ **Leading healthcare organizations use Trellis to:**\n\n* **Reduce time to treatment by over 90%**—ensuring patients start therapy faster\n* **Improve prior authorization approval and reimbursement rates**—reducing revenue leakage\n* **Leverage structured data for better clinical decision-making**—enhancing drug program performance and patient outcomes\n\n**About Us:**\n\nMac & Jacky are friends from the Stanford AI Lab, where we spent too much time indoors building language models and hoping they’d talk back 🧠💻\n\nPreviously, Mac built LLM infra at Cresta and Moveworks where our ML pipelines processed terabytes of chat logs and voice calls. Jacky taught AI classes at Stanford and worked at Meta on real-time machine learning systems handling complex model deployment challenges.\n\nTrellis is a spinout from Stanford AI Lab and is backed by leading investors including YC, General Catalyst, Telesoft Partners, and executives at Google and Salesforce.", "url": "https://www.ycombinator.com/launches/KXH-trellis-ai-automate-your-pre-sevice-workflow", "votes": 69, "created_at": "2024-03-01T14:13:48.722Z" } ] }, { "id": 29320, "name": "Celest", "slug": "celest", "former_names": [ "Teo" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/708de5f70d1c62cfdbd2dc173bb1fb905166fb19.png", "website": "https://celest.dev", "all_locations": "San Francisco, CA, USA", "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.", "one_liner": "The Vercel of Flutter", "team_size": 1, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1701978273, "tags": [ "Developer Tools", "SaaS", "B2B", "Cloud Computing", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2024", "status": "Inactive", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": true, "demo_day_video_public": true, "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": "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." }, { "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." } ], "url": "https://www.ycombinator.com/companies/celest", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/celest.json", "year_founded": 2023, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/celest-dev/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": "https://github.com/celest-dev", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/708de5f70d1c62cfdbd2dc173bb1fb905166fb19.png", "app_video_url": "https://bookface-images.s3.us-west-2.amazonaws.com/bf-public_profile/29377/app_video.mp4?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAQC4NIECAOTKCHR7A%2F20261020%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20261020T022717Z&X-Amz-Expires=60&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEHEaCXVzLXdlc3QtMiJHMEUCIQDeV7cQCYWa%2ByyakJaw7aH8e0HNWEyd2tO1Fn9KHjIpkgIgJPUveNomWrSf4Oq5DPuVDY7LKeaNJPvi5F2sbSx87Hoq5QMIOhAAGgwwMDYyMDE4MTEwNzIiDJ7%2FkqUU8p5mIeDC5CrCA7F4UggTYlVYiff4mYkoYiIpXa9r%2FKkUhcKwMNwtYpcuNTEBtH5xi9Hzkl3B%2FOYmUn%2FIacrdemsB9KrtOuRo%2FccaY%2Bs%2FSuIzime%2BcYuI7%2B%2Fg2nldjcm7YPCf32sIR8EflXc2916%2FDRMbztsRKDiQDL1ZKbK6YPHJppiQyVyRrrcCFD0X7tEf0D7QgK2DIpKnu8zGLzN4oAHn6xfHIgQnynrupcJbc9cga5AURtsRl7TfSM6XaGTtp1fNogyhUKX9f%2FYIL2pg03nlhLpRpDuqHpJ9qbbVsf%2FvboDHQ4IRRkiCaWH6GZwuTm%2FaXzTPIrAlVKH5%2F0RNaaExh%2Byw4VhHEEsSkHSs4mw%2BmNAKnW2FnWuldPRw5kn3j05dqhv5fkQxdp74JTYQe5wex1YN5PCok147bSKEuieYlIgH%2FiP9NY3Ym0ZRUWuo0zL40XWv9X3L1tLg%2BYWY0fCdhDKHGgTuesmbVajzEhu%2Bg9iWLptoK63cZ4UfO8oOd6sOc09XF6lBy%2BmD%2BSVmOfDWUOzz5ELD16slDTUwml0MZsttBoLDzldUc0olkl5nCAl23UqraiUXeaeW3yLOvJn%2BAD%2B%2FM6PvmZF0VzDn%2FdrWBjqlAVRsuTd0UsfPEqyKlBgBcSJTbWkHvSj10wzTCIqvOoZ3bz1TWza43iHLTCs7u%2FHmvoKE0qG5FTOsMYhLZb5XFdRretuo%2F1BjdoZt%2Fr0dHWGT4LLkmfYrkFclUq7u0pvMr6%2FR4I41ZYdCD3cWpGAcOrCQxKJukkkU%2Fx4O0IOnvZKvXzK4OISHe4XPgWQrnAJcSBOFX%2BXRwhpFbVXOOC%2BtEw%2BR3JTElw%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=6c9daee9dc28547ac9c1761f1afbd62cee3509f94303bb4b06f2cfc1b04f591d", "dday_video_url": "https://bookface-images.s3.us-west-2.amazonaws.com/video_event/64/1712209683673-mzvyg9rvzo-7ada906fac2a0efe1f8414a056622231/dfa71f0f63a12f07ea44272bb82eba3d.mp4?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAQC4NIECABPQ2AHNW%2F20261020%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20261020T022717Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&X-Amz-Signature=41ac71f90cfc5d15fd2523982ec2bf3b092c1fe1d4c36be2b3427c3d40ca383f", "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/f80a060d049f45f71278dd2f6dcd4779479d3afc.png" ], "primary_partner": null, "founders": [ { "user_id": 251048, "full_name": "Dillon Nys", "title": "Founder", "founder_bio": "Founder & CEO at Celest. Previously, I wrote the Amplify Flutter framework at AWS.", "is_active": false, "linkedin_url": "https://linkedin.com/in/dillon-nys", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/115197e5419648fa054955244579810145dab9d8.jpg" } ], "jobs": [], "news": [], "launches": [ { "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" } ] }, { "id": 29425, "name": "Zep AI", "slug": "zep-ai", "former_names": [ "Zep Software", "Inc." ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/834036f2803ad1fb4cf8305e1be757592a8588a1.png", "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, "tags": [ "Developer Tools", "Infrastructure", "AI", "Conversational AI", "AI Assistant" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 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/zep-ai", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/zep-ai.json", "year_founded": 2023, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/zep-ai/", "x_url": "https://twitter.com/zep_ai", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/zep-ai", "github_url": "https://github.com/getzep", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/834036f2803ad1fb4cf8305e1be757592a8588a1.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": 808515, "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.", "is_active": true, "linkedin_url": "https://linkedin.com/in/danielchalef", "x_url": "https://twitter.com/danielchalef", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9dd4658ad4e97387766ac3f0a1ee51f1c59c048d.jpg" } ], "jobs": [ { "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", "Machine Learning", "LLMs", "AI Agents" ] } ], "news": [], "launches": [ { "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\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: \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\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" }, { "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\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\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" } ] }, { "id": 29433, "name": "Hatchet", "slug": "hatchet-run", "former_names": [ "Hatchet Technologies", "Inc." ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/5e540520fafc66c31f803395b8f5603e6765d484.png", "website": "https://hatchet.run", "all_locations": "New York City, NY, USA", "long_description": "Hatchet is an orchestration platform for managing and observing AI agents, background tasks, and mission-critical workflows. Our mission is to provide developers with a simple, powerful, and reliable orchestration layer, enabling them to focus on building great applications.", "one_liner": "The orchestration platform for teams who ship.", "team_size": 7, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1709312849, "tags": [ "Developer Tools", "Open Source", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 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/hatchet-run", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/hatchet-run.json", "year_founded": 2023, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/hatchet-run", "x_url": "https://twitter.com/hatchet_dev", "fb_url": null, "cb_url": null, "github_url": "https://github.com/hatchet-dev", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/5e540520fafc66c31f803395b8f5603e6765d484.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "David Lieb", "url": "https://www.ycombinator.com/people/david-lieb" }, "founders": [ { "user_id": 363082, "full_name": "Alexander Belanger", "title": "Founder/CEO", "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! ", "is_active": true, "linkedin_url": "https://linkedin.com/in/alexander-belanger-aa3974135", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/dcd99d9baed3140b5158d3e00172acbd3c38202a.jpg" }, { "user_id": 491474, "full_name": "Gabe Ruttner", "title": "Founder", "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", "is_active": true, "linkedin_url": "https://linkedin.com/in/gruttner", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9d541cd209f295191f2aab598e156d38bd01d8bf.jpg" } ], "jobs": [], "news": [], "launches": [ { "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\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", "votes": 57, "created_at": "2024-03-11T14:21:38.752Z" } ] }, { "id": 29508, "name": "CrowdVolt", "slug": "crowdvolt", "former_names": [ "Mirage Match" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/49d2b2fe60b70ec0fe7e8a8f8b9fc420d26c4098.png", "website": "https://crowdvolt.com/", "all_locations": "New York City, NY, USA", "long_description": "CrowdVolt is rebuilding the infrastructure for live events, starting with an automated marketplace for raves and electronic dance music.", "one_liner": "The integration layer for live events infrastructure ", "team_size": 12, "industry": "Consumer", "subindustry": "Consumer", "launched_at": 1708402036, "tags": [ "Marketplace", "Entertainment", "Social Network", "Music", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2024", "status": "Active", "industries": [ "Consumer" ], "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/crowdvolt", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/crowdvolt.json", "year_founded": 2024, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/crowdvolt/", "x_url": "https://twitter.com/CrowdVolt", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/49d2b2fe60b70ec0fe7e8a8f8b9fc420d26c4098.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/925b83be77ddf7d77eda8bf61b56eff8a4b877d9.png" ], "primary_partner": { "name": "Jared Friedman", "url": "https://www.ycombinator.com/people/jared-friedman" }, "founders": [ { "user_id": 1410116, "full_name": "Max Hammer", "title": "Founder/CEO", "founder_bio": "Co-Founder and CEO of CrowdVolt (W24)", "is_active": true, "linkedin_url": "https://linkedin.com/in/max-hammer-2360571b2", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a9b1a595fa8a67948701694f466eb8cd8538ce44.jpg" }, { "user_id": 1153773, "full_name": "Josh Karol", "title": "Founder/CTO", "founder_bio": "I'm originally from Connecticut and am a Co-Founder and the CTO at CrowdVolt. I previously was a Software Engineer at Millennium. In my free time I like to go skiing and fishing.", "is_active": true, "linkedin_url": "https://linkedin.com/in/josh-karol-4b1a97143", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1145713ea731701d221159a4a8320d99498f901f.jpg" }, { "user_id": 1167277, "full_name": "Aria Mohseni", "title": "Founder/COO", "founder_bio": "Co-Founder at CrowdVolt", "is_active": true, "linkedin_url": "https://linkedin.com/in/ariamohseni", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4a57541bb3ff2e253f7efd142f7a24b7e7be8c02.jpg" } ], "jobs": [], "news": [ { "title": "YC-backed CrowdVolt shakes up the secondary ticket market with its bid-ask model | TechCrunch", "url": "https://techcrunch.com/2024/07/16/yc-backed-secondary-ticketing-startup-crowdvolt/", "date": "Jul 16, 2024" } ], "launches": [ { "id": 78886, "title": "⚡️ CrowdVolt - StockX for live event tickets", "tagline": "Exchange tickets to see your favorite DJs, electronic music shows and festivals!", "body": "**Tl;dr** [CrowdVolt](https://crowdvolt.com/) ⚡️ lets fans resell tickets to events, starting with raves & EDM concerts. We are a social, bid/ask style marketplace with counterparty security and favorable financing terms.\n\n❌ **The problem**\n\nThe secondary ticketing marketplace is fundamentally broken. Fees have skyrocketed, while the user experience has deteriorated. As giants such as Ticketmaster and SeatGeek have moved towards lucrative primary sales in partnership with large venues, they have disenfranchised a whole class of live event attendees.\n\nMany have naturally aggregated themselves on grey markets on legacy social media platforms (think Facebook marketplace and Reddit) to avoid institutional barriers and attempt to find better pricing/execution. These social platforms are not designed to house this type of exchange.\n\n![uploaded image](/media/?type=post&id=78886&key=user_uploads/1410116/aaead000-ef6c-4e10-ac85-0cc03a7a3b9c)\n\n🔥  **Our solution – the StockX of tickets** (StockX uses a bid/ask style model for collectible sneakers and streetwear)\n\n![uploaded image](/media/?type=post&id=78886&key=user_uploads/1410116/8ae6c463-3456-4f1c-83c5-4c63c4626f4d)\n\n* A two-sided marketplace for tickets: buyers can opt to “buy now” or bid, while sellers can opt to “sell now” or ask for a higher price, all with a publicly viewable transaction book\n* Counterparty security: CrowdVolt intermediates transactions with secure payment processing, avoiding fraudulent activity and scams; third-party issued tickets are automatically transferred between counterparties\n* Social: gone are the days of buying or selling from an anonymous blue dot on Ticketmaster; concerts are communal events meant to be experienced with others, so we’ve made buying and selling a social experience with social media integration and messaging\n* Financing: sellers do not wait until event occurrence to receive payouts, but rather receive payment within days, alleviating the cash flow burden\n\nCheck out our promo [here](https://youtu.be/WszI6Jfi650)!\n\n**🌃 Background**\n\n[Josh](https://www.linkedin.com/in/josh-karol-4b1a97143/) and [Max](https://linkedin.com/in/max-hammer-2360571b2) grew up down the street from each other, while [Aria](https://linkedin.com/in/ariamohseni) and Josh met in college. We have diverse professional backgrounds across tech, finance, and consulting, but a common love for EDM (Aria is also a DJ, having played at iconic New York venues including the Williamsburg Hotel and Virgo Night Club in front of crowds numbering 2k+). We are avid attendees of this genre of events (80+ in 2023), and know the secondary marketplace experience through the existing mediums is poor, so have opted to rebuild it ourselves.\n\n_A few years ago…_\n\n![uploaded image](/media/?type=post&id=78886&key=user_uploads/1410116/adf1e869-6351-48ec-b912-d88b7b01efa3)\n\n_Now!_\n\n![uploaded image](/media/?type=post&id=78886&key=user_uploads/1410116/a49dd802-e56f-44fa-8d9c-64d0af809737)\n\n**Our ask 🙏**\n\nWe’ve started in our hometown, New York, with our favorite genre of music, and will look to expand to other geographies and primary point of sale in the future.\n\n* If you know anyone working in the live events space – ranging from artists to event managers to promoters – let us know! We’d love to connect.\n* If you’re a fan of dance music, festivals, or raves (or have friends who are!) – hit us up at [founders@crowdvolt.com](mailto:founders@crowdvolt.com)!\n* Sign up now at [https://www.crowdvolt.com](https://www.crowdvolt.com/) if you’re in New York, or join the waitlist for your city at !", "url": "https://www.ycombinator.com/launches/KWM-crowdvolt-stockx-for-live-event-tickets", "votes": 93, "created_at": "2024-02-29T04:04:02.829Z" } ] }, { "id": 29575, "name": "Doublezero", "slug": "doublezero", "former_names": [ "SuperFilter", "Superfilter", "Ceejay" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ea427a37dc1568cb8c8a1e8aa0b5bda3a77baac1.png", "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" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "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": null, "url": "https://www.ycombinator.com/companies/doublezero", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/doublezero.json", "year_founded": 2025, "city": null, "country": null, "linkedin_url": "https://www.linkedin.com/company/doublezero-tech", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/ea427a37dc1568cb8c8a1e8aa0b5bda3a77baac1.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": 213326, "full_name": "Scott Moss", "title": "Founder", "founder_bio": "Co-founder at Doublezero S24, Tipe W18. Prev eng @Netflix, former VC.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/willscottmoss/", "x_url": "http://twitter.com/scotups", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/abf9fb1542d85846cc03d3a57c891f06fdef57cd.jpg" }, { "user_id": 668684, "full_name": "Travis Ueki", "title": "Founder/CTO", "founder_bio": "Co-Founder of Ceejay, Previously Tipe (W18), Coinbase (S12)\n\nObsessed with building product. Born and raised on Oahu, Hawaii, my journey’s been anything but conventional.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/travis-ueki/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1e2ee2a9940449a727dc0f2040ca7873e9e5b143.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 85084, "title": "Ceejay - Give Your Inbox and Calendar a Brain", "tagline": "Ceejay uses AI to lighten the mental load of managing your inbox and calendar.", "body": "**TLDR;** We’re launching Ceejay – an all-knowing assistant connected to your inbox and calendar. [Download it here](https://tryceejay.com) (if you have Gmail and an iPhone!).\n\n### **The Problem**\n\nOur inboxes are too noisy to manage and too important to ignore. 70% of people who have a full-time executive assistant start by having them manage their email and calendar. \n\nWhy? It’s an easy way to save time (say, an hour a day) and both platforms have enough context that an assistant can ramp up fairly quickly. We’ve proven LLMs can do this for you, for a fraction of the cost of a human.\n\nWe previously built [Superfilter](https://superfilter.ai) to tackle a similar problem, but we made a _ton_ of mistakes. Thankfully those mistakes led us to a product people find very valuable.\n\n### **Enter Ceejay**\n\nUsing Ceejay is similar to the experience of chatting with a human assistant.\n\nWatch this 60-second video to understand what [Ceejay can do for you.](https://www.youtube.com/watch?v=ybeCMdFXqhc)\n\nCeejay has a growing list of things it can do for you including:\n\n**Searching your inbox:** Why search your inbox for that receipt from July when you can ask Ceejay?\n\n**Managing your schedule:** Why send a calendar link or book an event when you can ask Ceejay (who handles conflicts!)?\n\n**Highlight messages that matter:** Why separate your important messages from the unimportant when Ceejay can do it for you?\n\n**Learning about you:** Ceejay is also the only inbox that deliberately remembers facts about you to reference later. I told Ceejay that my coworkers are Scott and Travis.\n\nJust ask, and you shall receive. There’s no additional inbox to manage. No new interface to learn. Just a clean chat with a ton of features you can use to manage your schedule and (important) email-based conversations efficiently.\n\n### **Who are we?**\n\nWe’re Scott, Travis, and Albrey. We participated in the S24 batch, building Superfilter. During our time building Superfilter, we learned from over 1,000 people about the pain they feel having to manage their inboxes. Our mission is to bring the experience of having a personal assistant to every knowledge worker at 1/100th of the cost. \n\n![uploaded image](/media/?type=post&id=85084&key=user_uploads/1856435/b5abf171-7e63-4c0e-835b-624ec0244d66)\n\n### **How can you help us?**\n\nIf you’re an iPhone and Gmail user, download the product at [tryceejay.com.](http://tryceejay.com)", "url": "https://www.ycombinator.com/launches/M8K-ceejay-give-your-inbox-and-calendar-a-brain", "votes": 18, "created_at": "2024-10-28T16:33:46.810Z" }, { "id": 83227, "title": "Superfilter - An executive assistant in your pocket", "tagline": "Let us manage your inbox so you don't have to.", "body": "**TLDR;** We built a companion that manages your inbox with the intelligence of an executive assistant. It never misses an important email, suggests follow up actions, and handles things like meeting coordination and quick replies in one click. [**Sign up here to get access.**](https://bit.ly/superfilter-beta)\n\n### **Who we are?**\n\nHey everyone, we’re [Scott](https://www.linkedin.com/in/willscottmoss/), [Travis](https://www.linkedin.com/in/travis-ueki/), and [Albrey](https://www.linkedin.com/in/albreybrown/). We’re serial entrepreneurs who’ve worked together for almost a decade. Over various roles, we discovered the worst part of work is managing our email inbox. So we built an [assistant](https://bit.ly/superfilter-beta) that handles it for us and are now offering it to you.\n\n![uploaded image](/media/?type=post&id=83227&key=user_uploads/1856435/7eed6456-08d3-4d5f-a796-7b251a1dcc52)\n\n# **The Problem**\n\nIn [_A World Without Email,_](https://www.amazon.com/World-Without-Email-Reimagining-Communication/dp/0525536558) Cal Newport explains that the average knowledge worker spends 30% of their workday managing their inboxes rather than engaging in meaningful work. Cutting this time in half could unlock hundreds of hours of productivity.\n\nWe interviewed founders and executives to understand how they deal with this. We typically heard one of three strategies:\n\n👀 Ignoring email altogether. Super efficient, but results missed opportunities and annoyed customers and friends.\n\n🤝🏿 Hiring an executive assistant. Saves a lot of time, but is very expensive.\n\n✉️ Clients like Superhuman. Affordable, but marginally more efficient than traditional email clients.\n\nWe couldn’t find a solution that was as reliable as an executive assistant and as affordable as a suped-up email client, so we set out to build it.\n\n# **Enter Superfilter**\n\nSuperfilter doesn’t replace your email client. Rather — it connects to your inbox and manages it like your executive assistant. While you’ll use email for strategic work, Superfilter keeps you on top of the tactical stuff.\n\nHere are some of its capabilities users love so far:\n\n**Overviews make sure you never miss an important email**\n\n![uploaded image](/media/?type=post&id=83227&key=user_uploads/1856435/3fc62c41-26dd-4448-83e9-c794bbca2c50)\n\n**Feeds keep track of your to-do’s and FYI’s**\n\n![uploaded image](/media/?type=post&id=83227&key=user_uploads/1856435/aaa241d9-d8ff-416b-99bd-6fdb8798a9a0)\n\n**Tasks let you delegate repetitive work to Superfilter**\n\n![uploaded image](/media/?type=post&id=83227&key=user_uploads/1856435/4cb8b15f-2185-4a51-bde6-24580ca1c2a4)\n\nSuperfilter’s purpose is to give you back time and peace of mind. It’s always working, improves as it learns from you, and will only leave to work for another person if you cancel your subscription.\n\n# **The Ask**\n\nUse the product and give us feedback. We only support iPhone and Gmail (Superhuman and Hey included).\n\n* [**Sign up on our waitlist for early access**](https://bit.ly/superfilter-beta)\n* **Follow us:** Give us a follow on [Twitter &](https://x.com/superfilter_ai) [LinkedIn](https://www.linkedin.com/company/superfilter-ai/)", "url": "https://www.ycombinator.com/launches/LeN-superfilter-an-executive-assistant-in-your-pocket", "votes": 60, "created_at": "2024-08-20T16:53:25.765Z" } ] }, { "id": 29585, "name": "Mem0", "slug": "mem0", "former_names": [ "Embedchain Inc", "Embedchain" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7d1e9679b389145f8635f2a0ae631bb24eba7cf8.png", "website": "https://mem0.ai", "all_locations": "San Francisco, CA, USA", "long_description": "Mem0 enhances AI assistants and agents with an intelligent memory layer, enabling personalized AI interactions. It remembers user preferences, adapts to individual needs, and continuously learns over time - ideal for customer support chatbots, AI assistants, and autonomous systems.", "one_liner": "The Memory layer for AI Agents", "team_size": 10, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1716511817, "tags": [ "Developer Tools", "Generative AI", "Open Source", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "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/mem0", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/mem0.json", "year_founded": 2023, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/mem0", "x_url": "https://twitter.com/mem0ai/", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/mem0", "github_url": "https://github.com/mem0ai/", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/7d1e9679b389145f8635f2a0ae631bb24eba7cf8.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Nicolas Dessaigne", "url": "https://www.ycombinator.com/people/nicolas-dessaigne" }, "founders": [ { "user_id": 661173, "full_name": "Taranjeet Singh", "title": "Founder/CEO", "founder_bio": "Taranjeet Singh is the co-founder & CEO of Mem0. He joined Khatabook (YC S18) as first growth engineer & quickly transitioned to Senior PM. He began his software engineering career at Paytm (India's Paypal) & witnessed its meteoric rise to become a household name. He built an AI-powered tutoring app that was featured at Google I/O. He co-created EvalAI, an open source Kaggle alternative with Deshraj & grew it to 1.6K GitHub stars. He also created the first GPT app store, scaling it to 1M+ users.", "is_active": true, "linkedin_url": "https://linkedin.com/in/taranjeet7114", "x_url": "https://twitter.com/taranjeetio", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d4e46598a908b054b56c5810940d4738fad1f89d.jpg" }, { "user_id": 299508, "full_name": "Deshraj Yadav", "title": "Founder/CTO", "founder_bio": "Deshraj Yadav is the co-founder and CTO of Mem0. He is broadly interested in the field of Artificial Intelligence and Machine Learning Infrastructure. He led the AI Platform at Tesla Autopilot, which enabled large-scale training, model evaluation, monitoring, and observability for Tesla's full self-driving development. Prior to that, Deshraj created EvalAI, an open source ML platform, as his master's thesis at Georgia Tech. He has published papers at top AI conferences like CVPR, ECCV, AAAI etc.", "is_active": true, "linkedin_url": "https://linkedin.com/in/deshrajdry", "x_url": "https://twitter.com/deshrajdry", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5c22c1ea2c1c9b13972a9eb2b1b511ad2cc4890f.jpg" } ], "jobs": [ { "id": 97144, "title": "Full Stack Engineer", "url": "https://www.ycombinator.com/companies/mem0/jobs/i1LyerD-full-stack-engineer", "location": "San Francisco Bay Area", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$150K - $250K", "equity_range": "0.10% - 0.50%", "experience": "3+ years", "visa": "Will sponsor", "skills": [] }, { "id": 99945, "title": "Research Engineer - Agent Memory", "url": "https://www.ycombinator.com/companies/mem0/jobs/fuNIwmP-research-engineer-agent-memory", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$175K - $250K", "equity_range": "", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 99947, "title": "Developer Relations ", "url": "https://www.ycombinator.com/companies/mem0/jobs/mpmlfnN-developer-relations", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$140K - $180K", "equity_range": "", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 99951, "title": "Forward Deployed Engineer", "url": "https://www.ycombinator.com/companies/mem0/jobs/85yRXxn-forward-deployed-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$150K - $190K", "equity_range": "", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [ { "title": "This Startup Is Trying To Solve The AI Memory Problem", "url": "https://www.youtube.com/watch?v=Sr1STQP0cds", "date": "Jan 23, 2026" }, { "title": "Mem0 raises $24M from YC, Peak XV and Basis Set to build the memory layer for AI apps | TechCrunch", "url": "https://techcrunch.com/2025/10/28/mem0-raises-24m-from-yc-peak-xv-and-basis-set-to-build-the-memory-layer-for-ai-apps/", "date": "Oct 28, 2025" }, { "title": "Mem0's scalable memory promises more reliable AI agents that remembers context across lengthy conversations | VentureBeat", "url": "https://venturebeat.com/ai/mem0s-scalable-memory-promises-more-reliable-ai-agents-that-remembers-context-across-lengthy-conversations/", "date": "May 08, 2025" } ], "launches": [ { "id": 83896, "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: \n * GitHub: ", "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" } ] }, { "id": 29623, "name": "Entangl", "slug": "entangl", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/5593913bae70a1285b652709232688417e1071ac.png", "website": "https://www.entangl.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Entangl uses AI to detect and automatically resolve issues in data center engineering and operations, ensuring efficiency and uptime. ", "one_liner": "Find & resolve issues in data center engineering & operations using AI", "team_size": 22, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1716219164, "tags": [ "Enterprise Software", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/entangl", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/entangl.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/entangl", "x_url": "https://twitter.com/Entangl_AI", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/entangl", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/5593913bae70a1285b652709232688417e1071ac.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Tom Blomfield", "url": "https://www.ycombinator.com/people/tom-blomfield" }, "founders": [ { "user_id": 533860, "full_name": "Shapol M", "title": "Founder/CEO", "founder_bio": "Co-founder & CEO at Entangl. ", "is_active": true, "linkedin_url": "https://linkedin.com/in/shapol", "x_url": "https://twitter.com/Shapol_m", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7d51f52ae31d3904f1480fb565c673d80836be24.jpg" } ], "jobs": [ { "id": 93501, "title": "Jony Ive", "url": "https://www.ycombinator.com/companies/entangl/jobs/Mmxt1jv-jony-ive", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Design", "role_type": "Web design", "salary_range": "$120K - $180K", "equity_range": "1.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "JavaScript", "Figma", "Svelte" ] }, { "id": 93502, "title": "Jony Ive", "url": "https://www.ycombinator.com/companies/entangl/jobs/snSaa27-jony-ive", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Frontend", "salary_range": "$120K - $180K", "equity_range": "1.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "TypeScript", "Figma", "Svelte" ] }, { "id": 97599, "title": "Bill McDermott (Account Executive)", "url": "https://www.ycombinator.com/companies/entangl/jobs/7WIZ9Gt-bill-mcdermott-account-executive", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$150K - $300K", "equity_range": "0.10% - 1.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 97630, "title": "Greg Brockman", "url": "https://www.ycombinator.com/companies/entangl/jobs/s6zm6uT-greg-brockman", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$150K - $200K", "equity_range": "0.10% - 1.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 98981, "title": "Account Executive", "url": "https://www.ycombinator.com/companies/entangl/jobs/JwshcnN-account-executive", "location": "San Francisco, CA, US / Remote (US)", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$130K - $350K", "equity_range": "0.10% - 1.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 98982, "title": "Sales Development Rep (SDR)", "url": "https://www.ycombinator.com/companies/entangl/jobs/ffkLbxN-sales-development-rep-sdr", "location": "San Francisco, CA, US / Remote (US)", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$70K - $100K", "equity_range": "0.10% - 1.00%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 110929, "title": "Full Stack Engineer", "url": "https://www.ycombinator.com/companies/entangl/jobs/CJBPxvX-full-stack-engineer", "location": "San Francisco, CA, US / SG / Remote (US; SG)", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$120K - $180K", "equity_range": "0.10% - 1.00%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 111026, "title": "Full Stack Engineer", "url": "https://www.ycombinator.com/companies/entangl/jobs/nu9J4uA-full-stack-engineer", "location": "New York, NY, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$120K - $180K", "equity_range": "0.10% - 1.00%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 111027, "title": "Full Stack Engineer", "url": "https://www.ycombinator.com/companies/entangl/jobs/Jn36xh5-full-stack-engineer", "location": "Boston, MA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$120K - $180K", "equity_range": "0.10% - 1.00%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 111028, "title": "Full Stack Engineer", "url": "https://www.ycombinator.com/companies/entangl/jobs/kLor7KK-full-stack-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$120K - $180K", "equity_range": "0.10% - 1.00%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 111290, "title": "Executive Assistant", "url": "https://www.ycombinator.com/companies/entangl/jobs/gzwUmD9-executive-assistant", "location": "San Francisco, CA, US / Remote (US)", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "$90K - $140K", "equity_range": "", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [], "launches": [] }, { "id": 29633, "name": "Unsloth AI", "slug": "unsloth-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/821f8850dee6e9f14ef87d19a86abcd55976c80c.png", "website": "https://unsloth.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Unsloth helps builders create custom models better & faster using RL and custom kernels. We're developing the all in one solution to help you create highly-accurate custom models 30x faster with 90% less memory use.\r\n\r\nWith over 10 million monthly model downloads and 40K GitHub stars, our mission is to make training and open-source the best it can be!", "one_liner": "Open-Source Reinforcement Learning (RL) & Fine-tuning for LLMs.", "team_size": 12, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1725425996, "tags": [ "Developer Tools", "Generative AI", "Open Source", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/unsloth-ai", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/unsloth-ai.json", "year_founded": 2023, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/unsloth/", "x_url": "https://twitter.com/UnslothAI", "fb_url": null, "cb_url": "https://crunchbase.com/organization/unsloth-ai", "github_url": "https://github.com/unslothai/unsloth", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/821f8850dee6e9f14ef87d19a86abcd55976c80c.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Nicolas Dessaigne", "url": "https://www.ycombinator.com/people/nicolas-dessaigne" }, "founders": [ { "user_id": 866879, "full_name": "Daniel Han", "title": "Founder", "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.", "is_active": true, "linkedin_url": "https://linkedin.com/in/danielhanchen", "x_url": "https://twitter.com/danielhanchen", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2474ade2e08b30c118c37a2941e293f1404098a7.jpg" }, { "user_id": 883803, "full_name": "Michael Han", "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!", "is_active": true, "linkedin_url": "https://linkedin.com/in/michaelhan3", "x_url": "https://twitter.com/UnslothAI", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f72dd529b73107324d916ccf651786697e2d027d.jpg" } ], "jobs": [ { "id": 73175, "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", "skills": [ "Amazon Web Services (AWS)", "Microsoft Azure", "Google Cloud", "Mathematica", "Torch/PyTorch", "Machine Learning", "Deep Learning", "Reinforcement learning (RL)" ] } ], "news": [ { "title": "How to Fine-Tune LLMs on RTX GPUs With Unsloth | NVIDIA Blog", "url": "https://blogs.nvidia.com/blog/rtx-ai-garage-fine-tuning-unsloth-dgx-spark/", "date": "Dec 15, 2025" }, { "title": "Train an LLM on NVIDIA Blackwell with Unsloth—and Scale for Production | NVIDIA Technical Blog", "url": "https://developer.nvidia.com/blog/train-an-llm-on-an-nvidia-blackwell-desktop-with-unsloth-and-scale-it/", "date": "Oct 23, 2025" } ], "launches": [] }, { "id": 29649, "name": "Wordware", "slug": "wordware", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ff410def03c8c58c3adc7db9615becc8164804e3.png", "website": "https://wordware.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Every tool you use was built as an island, so you became the glue between them. You carry a name from Gmail into the CRM, a time from the CRM into Calendly, a note from Calendly into a doc. AI showed up and mostly became an eleventh window to paste into. \r\n\r\nSauna is a hybrid of AI and software standing on one shared brain. It holds your context and hands you real software built on top of it. You talk to it like a chatbot and use what it builds like an app: software for the path you repeat, AI for the edge that never repeats. Keep it to yourself, or share the brain with your team. \r\n\r\nThe clearest way to see it is a tool doing what its whole category cannot. An ordinary Calendly shows a stranger your free slots. Your Calendly writes the invite email itself, because it knows how the two of you know each other, and it offers a board member the slot over your gym block, because it knows which of your busy hours bend and for whom. \r\n\r\nWordware is the team behind it, 15 people backed by Spark Capital, Felicis, and Y Combinator with a $30M seed, the largest in YC's history. 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Previously I cofounded and exited KRISTALIC, which tried to augment the human memory. Before that, I studied Deep Learning at Cambridge. \n\nThe most interesting fact about me outside of work is that I travelled to 103 countries and was part of multiple high-altitude mountaineering expeditions and rescue operations in Kyrgyzstan and Nepal. I also do sailing, paragliding, kitesurfing and boxing.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/rafaell0pez/", "x_url": "https://twitter.com/kozerafilip", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/97f0e2d2b3e5ed0937b9bcde43b6fc1d4d8b1177.jpg" }, { "user_id": 1377439, "full_name": "Robert Chandler", "title": "Founder/CTO", "founder_bio": "Robert Chandler is a founder & CTO at Wordware. \n\nHe started his career as an early engineer at a self-driving car startup, Five AI, which was acquired by Bosch. Here he lead the Offline Perception team which accelerated the dev-test cycle through automated ground truthing and was awarded 5+ patents in the process.\n\nHe has been in the AI space for over a decade since studying Information Engineering at the University of Cambridge. ", "is_active": true, "linkedin_url": "https://linkedin.com/in/robertjhchandler", "x_url": "https://twitter.com/bertie_ai", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a1a5c68c003591a1edfc51c175f2295bc1c399a6.jpg" } ], "jobs": [ { "id": 100381, "title": "Ex-YC Founder", "url": "https://www.ycombinator.com/companies/wordware/jobs/0Uw5LLO-ex-yc-founder", "location": "San Francisco", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 100382, "title": "Past Founder with Track Record and Experience", "url": "https://www.ycombinator.com/companies/wordware/jobs/KnEnNLv-past-founder-with-track-record-and-experience", "location": "San Francisco", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 100386, "title": "Senior Full Stack Engineer (Back-End)", "url": "https://www.ycombinator.com/companies/wordware/jobs/q25ojiS-senior-full-stack-engineer-back-end", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$180K - $240K", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 100409, "title": "Head of Growth", "url": "https://www.ycombinator.com/companies/wordware/jobs/3zXoo6V-head-of-growth", "location": "San Francisco", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "$200K - $280K", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 107156, "title": "Founding Growth Marketer", "url": "https://www.ycombinator.com/companies/wordware/jobs/E2cby3G-founding-growth-marketer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Marketing", "role_type": null, "salary_range": "$150K - $250K", "equity_range": "", "experience": "1+ years", "visa": "Will sponsor", "skills": [] }, { "id": 107959, "title": "Senior Applied AI Engineer", "url": "https://www.ycombinator.com/companies/wordware/jobs/ngciYZN-senior-applied-ai-engineer", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$180 - $240", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 107960, "title": "Content Producer", "url": "https://www.ycombinator.com/companies/wordware/jobs/O2FEogq-content-producer", "location": "San Francisco / Remote (US)", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 109286, "title": "Growth Engineer", "url": "https://www.ycombinator.com/companies/wordware/jobs/tWwK61i-growth-engineer", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$150K - $250K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 110533, "title": "Senior Product Engineer", "url": "https://www.ycombinator.com/companies/wordware/jobs/NbKjip9-senior-product-engineer", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$180K - $240K", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 110567, "title": "Staff Engineer", "url": "https://www.ycombinator.com/companies/wordware/jobs/r5nar82-staff-engineer", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$280K - $400K", "equity_range": "", "experience": "8+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 115019, "title": "Senior Platform Engineer", "url": "https://www.ycombinator.com/companies/wordware/jobs/Obb6hO2-senior-platform-engineer", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [ { "title": "Wordware raises $30 million to make AI development as easy as writing a document | VentureBeat", "url": "https://venturebeat.com/ai/how-wordware-30m-seed-round-could-disrupt-the-entire-ai-development-industry/", "date": "Nov 21, 2024" } ], "launches": [ { "id": 82674, "title": "Wordware — Build your AI stack 20x faster", "tagline": "First toolkit for building AI Agents with Natural Language Programming", "body": "Wordware is an IDE that enables anyone to build complex AI Agents and applications. Domain experts and engineers can now iterate 20x faster with prebuilt tools, API deployment, tracing, and more.\n\nCurrently, prompting is mostly done by engineers inside the code base. This is just a coincidence, and it yields poor quality and a long iteration cycle due to communication overhead with domain experts.\n\nWordware is the go-to tool for these cross-functional teams. Our clients range from AI tinkerers developing their ideas to large companies using Wordware as their whole LLM backend.\n\nIt’s a tool (an IDE) that enables you to quickly build custom AI agents for specific use cases, like legal contract generation, marketing content automation, invoice analysis, candidate screening, generating PRDs, and many more. We call applications built on Wordware ‘WordApps’ because you can create them using natural language—in other words, using words (pun intended).\n\n![uploaded image](/media/?type=post&id=82674&key=user_uploads/89898/b9693831-0217-438e-a787-e99a4d9d7031)\n\nOur core belief is that the domain expert—not the engineer—knows what good LLM output looks like. For example, lawyers building legal SaaS need to be deeply involved in the process, and working directly in the codebase or going back and forth with engineers isn’t the way to go. Most of our clients are cross-functional teams, including less technical members, who need to collaborate with engineers on LLM applications, such as assessing prompt outputs, and care about the speed of iterations.\n\nWe are in production with 7 YC Companies and looking to give other early-stage companies with their AI Stack on fire unreasonable amounts of attention. Start for free or book a demo at [www.wordware.ai.](https://www.wordware.ai/)\n\nI met Robert (my CTO) at the University of Cambridge. We have both worked with LLMs since BERT and created well-performing stacks before AI Ops was a term. We both have exits in the field.\n\n![uploaded image](/media/?type=post&id=82674&key=user_uploads/286908/9e4aec68-a8db-44af-884c-71d8201cecb9)\n\n", "url": "https://www.ycombinator.com/launches/LVS-wordware-build-your-ai-stack-20x-faster", "votes": 18, "created_at": "2024-08-02T14:15:10.409Z" } ] }, { "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": [ "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/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, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/29c89a57406f27700f9b8b7efac971895519ec3f.png" ], "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": 29721, "name": "Panora", "slug": "panora", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/10b041265670ef03fc794bc6300cf8eef692d02a.png", "website": "https://getpanora.com", "all_locations": "San Francisco, CA, USA", "long_description": "Panora automates PO entry for distributors, manufacturers and wholesalers. Stop wrong shipments, block duplicates, reclaim ~80% of your order-entry time.", "one_liner": "Turning messy inboxes into ERP-Ready Data", "team_size": 1, "industry": "B2B", "subindustry": "B2B", "launched_at": 1715907913, "tags": [ "API", "Supply Chain", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "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/panora", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/panora.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/usepanora/", "x_url": "https://twitter.com/getpanora", "fb_url": null, "cb_url": null, "github_url": "https://github.com/panoratech", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/10b041265670ef03fc794bc6300cf8eef692d02a.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 1617348, "full_name": "Rachid Flih", "title": "Founder/CEO", "founder_bio": "Helping wholesalers & distributors automate their PO workflows", "is_active": true, "linkedin_url": "https://linkedin.com/in/rflih", "x_url": "https://twitter.com/rflih_", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0b91c7fef8b5c4c610a999020102903fc002ed10.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 29728, "name": "expand.ai", "slug": "expand-ai", "former_names": [ "ExpandAI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cbb3378711a3516d3cc0bdd3c41a57f151832b9b.png", "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" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2024", "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": [ { "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." } ], "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", "fb_url": null, "cb_url": null, "github_url": "https://github.com/expandai", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/cbb3378711a3516d3cc0bdd3c41a57f151832b9b.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/3d23be7a597aa6e4551e86d055ffdc34068fa564.png" ], "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" } ], "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\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 \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" } ] }, { "id": 29767, "name": "Thunder Compute", "slug": "thunder-compute", "former_names": [ "Thunder" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2623539c5a9dddb54681db96f38cf2be0f9428d9.png", "website": "https://www.thundercompute.com", "all_locations": "San Francisco, CA, USA", "long_description": "Thunder Compute is a systems research lab with commercial focus. We productionize GPU virtualization research to provide step-change improvements in utilization to our cloud offering and partner GPU fleets.", "one_liner": "GPUs for Agents", "team_size": 10, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1723245936, "tags": [ "Developer Tools", "Data Science", "Cloud Computing", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 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": [ { "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": "Carl Peterson and Brian Model met as freshmen at Georgia Tech and became close friends. The idea for Thunder Compute sparked from Brian's experience in his Systems for AI lab, where researchers made GPU reservations weeks in advance via Google Sheets, severely hindering research progress. This inefficiency inspired us to explore ways to improve GPU access." } ], "url": "https://www.ycombinator.com/companies/thunder-compute", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/thunder-compute.json", "year_founded": 2022, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/thundercompute/", "x_url": "https://x.com/ThunderCompute", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/thunder-9b4c", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/2623539c5a9dddb54681db96f38cf2be0f9428d9.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/d3fd827d18b35d35d4f3861cffb2a960801078b5.png" ], "primary_partner": { "name": "Aaron Epstein", "url": "https://www.ycombinator.com/people/aaron-epstein" }, "founders": [ { "user_id": 1276433, "full_name": "Carl Peterson", "title": "Founder/CEO", "founder_bio": "CEO of Thunder Compute, formerly Management Consultant at Bain", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/cpeterson42", "x_url": "https://twitter.com/carl_petey", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/64f0d31897538a58874ce79d46b9d3390a4e51f9.jpg" }, { "user_id": 1989859, "full_name": "Brian Model", "title": "Founder/CTO", "founder_bio": "CTO of Thunder Compute, formerly Quantitative Developer at Citadel Securities", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/brian-model/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c3c91379c7fd849da36c768aedd80a5f6151a624.jpg" } ], "jobs": [ { "id": 79986, "title": "Cloud Infrastructure Engineer", "url": "https://www.ycombinator.com/companies/thunder-compute/jobs/dtlQhtw-cloud-infrastructure-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$1", "equity_range": "", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [ "Go", "Kubernetes", "Python", "Linux" ] }, { "id": 82422, "title": "Systems Software Engineer (C++)", "url": "https://www.ycombinator.com/companies/thunder-compute/jobs/SZq8TQx-systems-software-engineer-c", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Backend", "salary_range": "$1", "equity_range": "", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [ "C++", "TCP/IP", "Linux", "Distributed Systems" ] } ], "news": [ { "title": "Thunder Compute raises $13M to squeeze more work out of idle GPUs - SiliconANGLE", "url": "https://siliconangle.com/2026/08/19/thunder-compute-raises-13m-squeeze-work-idle-gpus/", "date": "Aug 19, 2026" }, { "title": "Thunder Compute Raises $500K to Advance GPU Access for AI Developers | citybiz", "url": "https://www.citybiz.co/article/575672/thunder-compute-raises-500k-to-advance-gpu-access-for-ai-developers/", "date": "Jul 10, 2024" } ], "launches": [ { "id": 82910, "title": "Thunder Compute: Launch GPU instances in one click for 80% less", "tagline": "Self-serve GPUs in VS Code with persistent storage, snapshots, and hot-swappable hardware, for 80% less than AWS", "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/)", "url": "https://www.ycombinator.com/launches/LZG-thunder-compute-launch-gpu-instances-in-one-click-for-80-less", "votes": 50, "created_at": "2024-08-11T14:49:40.486Z" } ] }, { "id": 29777, "name": "Zettascale Computing", "slug": "zettascale-computing", "former_names": [ "Exa Labs", "Exa Laboratories", "Zettascale" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/dc824cdcd1866f181c1cae19f0dfc1371a717e51.png", "website": "https://zscc.ai", "all_locations": "San Francisco, CA, USA", "long_description": "AI silicon for the era of recursive self-improvement and superintelligence", "one_liner": "Chips for frontier AI", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials", "launched_at": 1722631140, "tags": [ "Hard Tech", "Semiconductors", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "Industrials" ], "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/zettascale-computing", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/zettascale-computing.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/zettascale-computing-corp", "x_url": "https://x.com/zettascale", "fb_url": null, "cb_url": null, "github_url": "https://github.com/thezettascale", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/dc824cdcd1866f181c1cae19f0dfc1371a717e51.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": 779644, "full_name": "Elias Almqvist", "title": "Founder/CEO", "founder_bio": "Founder/CEO of Zettascale Computing, autodidact dropout", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/almqv", "x_url": "https://x.com/fcvprzhfgsybj", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a6432e5966767866a5568fae25b979f0f8da9f7d.jpg" } ], "jobs": [ { "id": 109821, "title": "Founding Silicon Engineer", "url": "https://www.ycombinator.com/companies/zettascale-computing/jobs/E3xe53H-founding-silicon-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Hardware", "salary_range": "$200K - $300K", "equity_range": "1.00% - 2.00%", "experience": "1+ years", "visa": "Will sponsor", "skills": [ "Tcl", "Verilog", "FPGAs" ] } ], "news": [ { "title": "9 startups that stood out on YC Demo Day 2 | TechCrunch", "url": "https://techcrunch.com/2024/09/26/9-startups-that-stood-out-on-yc-demo-day-2/", "date": "Sep 26, 2024" } ], "launches": [ { "id": 120562, "title": "XPU Grasshopper: An AI chip designed for the era of recursive self-improvement", "tagline": "AI chip co-designed with AI for the era of recursive self-improvement", "body": "![uploaded image](/media/?type=post&id=120562&key=user_uploads/779644/45160b6c-c87e-4ed1-ad59-7ded469a382d)\n\nToday we’re announcing XPU Grasshopper, our AI architecture co-designed with AI!\n\nIt went from its first tokens to 816x faster in 13 weeks on FPGA.\n\nWith a very small team and autonomous AI agents, we were able to design the hardware and software together. The agents rewrote kernels, reworked the hardware overlay, and ran and tested their own FPGA builds.\n\nRunning gemma-3-1b-it (yes, it runs other models too, but that’s for the next launch :)) at more than 51 tok/s and over 90% utilization at batch 1, on four tiles on an FPGA, measured end to end, to prove out our micro-architecture and software stack before silicon.\n\nWe wrote up the full story, including the day-by-day optimizations the agents found, the Mutation Tile Unit architecture, and the benchmarks: \n\n100 numbered FPGA devkits are open for pre-order, with early cluster API and SSH access: \n\nRead more: ", "url": "https://www.ycombinator.com/launches/VMY-xpu-grasshopper-an-ai-chip-designed-for-the-era-of-recursive-self-improvement", "votes": 7, "created_at": "2026-10-07T16:33:31.723Z" }, { "id": 83472, "title": "Exa Laboratories - 27.6x more efficient chips for AI 🔥🚀", "tagline": "Reconfigurable chips for AI that are 27.6x more energy efficient.", "body": "### TL;DR:\n\nWe're building reconfigurable chips for AI that are up to 27.6x more efficient and powerful than the H100 GPUs. This could save data centers hundreds of millions to billions in annual energy costs.\n\n### Meet the Team\n\nHello! We're [Elias](https://www.linkedin.com/in/almqv/) and [Prithvi](https://www.linkedin.com/in/prithvi-raj-eng/) from [Exa](https://exalaboratories.com/). We're developing **reconfigurable chips for AI** that are up to around **27\\.6x\\* more efficient and performant** than the modern H100 GPUs.\n\n\\*: [_Read our litepaper!_](https://exalaboratories.com/litepaper)\n\n![uploaded image](/media/?type=post&id=83472&key=user_uploads/779644/fe720272-a21f-4761-a766-9b90dc6401a9)\n\n[**CEO, Elias Almqvist**](https://www.linkedin.com/in/almqv/) (right): Self-taught engineer who also studied computer science and computer engineering (dropped out and founded Exa, btw) at Chalmers University of Technology. Previously worked in the embedded software space but also worked on various aerospace projects at university.\n\n[**CTO, Prithvi Raj**](https://www.linkedin.com/in/prithvi-raj-eng/) (left): Holds an MEng from the world-leading Computational Stats & ML Lab at Cambridge. During his time there, he fell in love with scientific machine learning, a field that demands bespoke neural network architectures and extreme hardware efficiency, and also interned at Microsoft as a software engineer.\n\n### The problems!\n\nThe AI industry faces critical challenges threatening its sustainable growth:\n\n1. **Unsustainable Energy Consumption**: Modern GPUs consume 600-1000 W per unit, creating massive scaling issues for data centers. Large data centers face energy costs in the hundreds of millions to potentially billions each year. **GPU power draw seems to be increasing with each new release**, while **compute per area has remained the same** for the past 5 years.\n2. **Exponential Compute Demand**: With AI advancements, computational power demand is rapidly increasing. Unchecked, this trend could lead to an energy crisis, impeding AI progress and costing data centers billions of dollars.\n3. **Hardware Limitations**: **Current fixed architectures constrain AI innovation**. They lack the versatility to efficiently support diverse AI architectures and custom neural network designs crucial for solving real-world problems.\n\n### The solution.\n\nExa's polymorphic computing technology addresses these challenges:\n\n* **Reconfigures for each AI model architecture**, maximizing efficiency and versatility\n* Supports diverse approaches, from **transformers** and **GPTs** to novel AI architectures (e.g., the new [**Kolmogorv-Arnold Networks (KAN)**](https://arxiv.org/abs/2404.19756))\n* Early simulations indicate potential efficiency gains of up to **27\\.6x** over the H100 GPUs\n\n**This technology could save data centers hundreds of millions to billions in annual energy costs**, significantly reducing operational expenses and environmental impact.\n\n![uploaded image](/media/?type=post&id=83472&key=user_uploads/779644/12f4a895-8885-4089-a331-920fb65b683c)\n\nFor a somewhat deeper technical dive, refer to our [litepaper](https://exalaboratories.com/litepaper)!\n\n### Asks :)\n\n* Read our [litepaper](https://exalaboratories.com/litepaper)! All feedback welcome!\n* Introduce us to anyone in the scientific machine learning space and/or someone conducting research in AI, **particularly those who have very “_cursed model architectures.”_**\n* Get us in contact with any data center, AI research organization, or GPU cloud provider (i.e., AWS, OpenAI, Anthropic, DeepMind, Lambda).\n* Give us intros to semiconductor industry professionals, particularly those interested in **bringing back chip manufacturing to the US**!\n\nFeel free to reach us at [founders@exalaboratories.com](mailto:founders@exalaboratories.com), **we would love to hear your feedback and answer your questions!**", "url": "https://www.ycombinator.com/launches/LiK-exa-laboratories-27-6x-more-efficient-chips-for-ai", "votes": 35, "created_at": "2024-08-27T19:36:23.464Z" } ] }, { "id": 29844, "name": "Oway", "slug": "oway", "former_names": [ "Oway Inc." ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a3e196a71b4a93ad7200cf278186954bda68e7e3.png", "website": "https://www.oway.io", "all_locations": "San Francisco, CA, USA", "long_description": "The physical economy still operates without a common language. Enterprise systems, factories, trucks, and robots generate enormous amounts of data, but most remains fragmented across legacy software and incompatible formats. Without a shared understanding of what is happening, even the most advanced AI cannot reliably coordinate how goods are made, moved, and delivered.\r\n\r\nOway is building that common language. Our protocol, IOI, connects enterprise systems and physical hardware, cleaning messy legacy data and live telemetry into a standardized schema that AI can understand and act on. Through a shared API, businesses can query their operations, identify inefficiencies, and automate actions across systems without replacing their existing software.\r\n\r\nOur first model, Juno, applies this intelligence to unused truck capacity. It tracks empty space on trucks and sells it at a 50% discount to businesses shipping in the same direction. By moving freight directly on trucks already making the trip, Oway reduces shipping costs, damage, and transit times while generating additional revenue for carriers.\r\n\r\nEvery connected system and shipment expands our understanding of capacity, pricing, routes, facilities, and industrial operations. As this network grows, Oway is building toward a future where enterprise software, automated factories, self-driving vehicles, and robots can communicate and coordinate through one shared layer, making the physical economy programmable.", "one_liner": "Building the open operating system for the automated physical economy.", "team_size": 16, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1717601253, "tags": [ "B2B", "API", "Infrastructure", "AI", "Industrial" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2024", "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/oway", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/oway.json", "year_founded": 2023, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/oway/", "x_url": "https://twitter.com/owayinc", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/oway-a533", "github_url": "https://github.com/Oway-Inc", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/a3e196a71b4a93ad7200cf278186954bda68e7e3.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": 993914, "full_name": "Phillip Nadjafov", "title": "Founder/CEO", "founder_bio": "Founder of Oway, building the Internet of Industrials (IOI), a common protocol that connects industrial systems and gives AI the context to coordinate the physical economy.\n\nPreviously co-founded Isotrex, a multinational defense manufacturer, at 16. Built its supply chain and production end to end, became CEO in 2019, and scaled it to roughly $100M in annual revenue and 4,000+ vehicles built.\n\nSystems engineer and designer focused on American industrial automation.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/phillipnadjafov/", "x_url": "https://x.com/phillipnadjafov", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c489f534c0991a4bbb449634a505008d7338e3e9.jpg" } ], "jobs": [ { "id": 115283, "title": "Staff Engineer, IOI (Internet of Industrials)", "url": "https://www.ycombinator.com/companies/oway/jobs/My3AkWy-staff-engineer-ioi-internet-of-industrials", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$220K - $300K", "equity_range": "0.30% - 1.00%", "experience": "6+ years", "visa": "US citizen/visa only", "skills": [ "Java", "TypeScript", "Reinforcement learning (RL)", "Machine learning", "AI Agents" ] }, { "id": 115284, "title": "Senior Full-Stack Engineer, IOI Applications", "url": "https://www.ycombinator.com/companies/oway/jobs/kigce04-senior-full-stack-engineer-ioi-applications", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$185K - $250K", "equity_range": "0.30% - 1.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "MongoDB", "TypeScript", "AI Agents" ] }, { "id": 115285, "title": "Forward Deployed Engineer, Enterprise", "url": "https://www.ycombinator.com/companies/oway/jobs/AqsthKE-forward-deployed-engineer-enterprise", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$185K - $220K", "equity_range": "0.30% - 1.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "TypeScript", "Data Warehousing", "Data Modeling", "AI Agents" ] }, { "id": 115286, "title": "Strategic Partnerships Lead, Enterprise", "url": "https://www.ycombinator.com/companies/oway/jobs/bGqgrpO-strategic-partnerships-lead-enterprise", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$150K - $250K", "equity_range": "0.20% - 1.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 115287, "title": "Enterprise Sales Manager, Pod Lead", "url": "https://www.ycombinator.com/companies/oway/jobs/dRnkn65-enterprise-sales-manager-pod-lead", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$150K - $220K", "equity_range": "0.30% - 1.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 115288, "title": "Fleet Partnerships Director, IOI (Internet of Industrials)", "url": "https://www.ycombinator.com/companies/oway/jobs/EEzVXlb-fleet-partnerships-director-ioi-internet-of-industrials", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$150K - $220K", "equity_range": "0.20% - 1.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 115290, "title": "Quantitative Researcher, IOI Index", "url": "https://www.ycombinator.com/companies/oway/jobs/LHEjh2d-quantitative-researcher-ioi-index", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Data science", "salary_range": "$220K - $320K", "equity_range": "0.30% - 1.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "Go", "TypeScript", "Machine Learning", "Reinforcement learning (RL)" ] } ], "news": [ { "title": "5 Founders Building the Future of Logistics, AI, and Industrial Technology - The San Francisco Tribune", "url": "https://thesanfranciscotribune.com/5-founders-building-the-future-of-logistics-ai-and-industrial-technology/", "date": "Oct 15, 2026" }, { "title": "How Oway uses AI to fill empty trucks and cut shipping costs - FreightWaves", "url": "https://www.freightwaves.com/news/how-oway-uses-ai-to-fill-empty-trucks-and-cut-shipping-costs", "date": "Sep 30, 2025" }, { "title": "YC-backed Oway raises $4M to build a decentralized ‘Uber for freight’ | TechCrunch", "url": "https://techcrunch.com/2025/08/22/yc-backed-oway-raises-4m-to-build-a-decentralized-uber-for-freight/", "date": "Aug 22, 2025" }, { "title": "9 startups that stood out on YC Demo Day 2 | TechCrunch", "url": "https://techcrunch.com/2024/09/26/9-startups-that-stood-out-on-yc-demo-day-2/", "date": "Sep 26, 2024" } ], "launches": [ { "id": 122375, "title": "Oway: Building the Internet of Industrials", "tagline": "Oway connects industrial systems through a common protocol, giving AI the context to coordinate the physical economy.", "body": "**TL;DR:** We’re building the Internet of Industrials (IOI), a shared context layer connecting industrial systems and giving AI a common basis of structured data across companies. IOI already powers Oway, where our first model, Juno, uses it to coordinate shipments through unused truck capacity. We’re opening that same foundation to robotics, automated factories and other industrial systems to accelerate US industrial automation.\n\n![](/media/?type=post&id=122375&key=user_uploads/993914/9346b6ba-f710-49c9-9ecb-72882cc13bca)\n\n**An example:** A factory asks its AI for eight units of mild steel by tomorrow morning. Through IOI, the AI coordinates production with a connected certified supplier and books a connected truck for delivery. All three systems share the context needed to execute and track the order.\n\n### The problem\n\nAmerica is building new factories, deploying automation, and developing autonomous vehicles. But the systems connecting industrial operations still speak different languages.\n\nInventory, capacity, equipment, orders, and operating constraints are scattered across ERP systems, TMSs, warehouses, carriers, sensors, and closed systems. That fragmentation extends across the companies that need to work together. AI cannot reliably coordinate physical work without understanding what exists, what is available, and what each system can do.\n\nProductive capacity goes unused while businesses pay more to make, store, and move goods.\n\n### Introducing IOI\n\nWe built IOI as the backend that runs Oway. It already connects every Oway customer and carrier. We’re now making it available to other businesses as a common structured context layer.\n\nOur thesis is that logistics provides the foundational language for an industrial network. Nearly every physical business can be described through a common set of primitives: **what exists, where it is, where it needs to go, available capacity, time, cost, constraints, storage, and transformation.**\n\nIOI translates those states into structured data that enterprise software, physical hardware and AI agents can share across company boundaries. Businesses can build nodes alongside their existing systems instead of replacing them. \n\nSetting up an IOI node is extremely simple, our default setup allows you to simply plug Oway in as a “carrier” into your stack that monitors and optimizes your supply chain quotes and orders - automatically gaining the context to build a full IOI data lake for you that already has action capabilities and can infer your inventory levels and SKU-level performance. Data can then automatically be fed back to SAP, Oracle Netsuite, or any data system / AI agent you’d like.\n\n![uploaded image](/media/?type=post&id=122375&key=user_uploads/993914/c9f841f6-3976-429b-9f25-81e63bc0c113)\n\nIOI will be open source soon, with Oway maintaining the standard so developers can build compatible systems. It is designed around widely adopted enterprise security practices, with each business controlling its data, access permissions and authorized actions. Nodes can run in enterprise clouds or at the edge.\n\n**Below: Ask IOI anything -** Each Oway enterprise customer also gets search functionality out of the box. \n\n![](/media/?type=post&id=122375&key=user_uploads/993914/07bea764-9c83-47a6-8c71-97f5130d28b5)\n\n### Our first model: Juno\n\nJuno is our first AI model. It reasons over IOI to price, coordinate and execute pooled shipments on trucks already traveling the route.\n\nBy ridesharing shipments into capacity already moving, we lower costs, shorten transit times and reduce damage from handling. Carriers earn from their existing capacity, with legal paperwork, insurance and DOT compliance all automatically monitored and handled.\n\n**Below: Juno in Oway OS.** A full API, MCP and EDI-compatible suite that enables businesses to leverage Juno’s rideshare capabilities however they’d like for freight shipping.\n\n![](/media/?type=post&id=122375&key=user_uploads/993914/f2a8e9b3-a635-4c69-b9a8-4c5d3f8eb1f7)\n\nWe estimate this is a **$200B+ annual optimization opportunity within America’s roughly $1T trucking industry**.\n\nWith Oway Rideshare, we deliver average savings of 30% per transaction, while also reducing damage rates, and transit times as well for cross-country shipments.\n\nFreight gives IOI an operating environment where its primitives have to produce real physical outcomes.\n\n### Where we’re going\n\nEvery connected system and shipment adds context about capacity, pricing, routes, facilities, and industrial operations.\n\nThat shared context gives robotics companies, automated factories and self-driving trucks a way to communicate and coordinate across companies. Every company on Oway, and even Oway’s model - are already running on IOI. We believe that providing these capabilities at a national level will lead to significant improvements to the GDP and global competitiveness of US-made products.\n\nOway + IOI already serves Fortune 500 companies, connects over 10,000 vehicles nationwide, and indexes hundreds of millions of dollars in annualized shipping demand.\n\nIf you’re working at a company that makes, stores, or moves physical goods, [we’d love to show you what we’re building](https://www.shipoway.com).", "url": "https://www.ycombinator.com/launches/Vpn-oway-building-the-internet-of-industrials", "votes": 23, "created_at": "2026-10-15T15:50:53.501Z" } ] }, { "id": 29950, "name": "Pipeshift", "slug": "pipeshift", "former_names": [ "Xylem AI", "Pipeshift AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6dc8136429eadec250bda86f1102143f81a24beb.png", "website": "https://pipeshift.com", "all_locations": "San Francisco, CA, USA", "long_description": "Pipeshift offers ultra-low latency infrastructure for engineering teams to run real-time inference in production. We offer latency-optimized runtimes for voice, chat, and physical AI, paired with distributed orchestration that routes and auto-scales across clusters and regions — typically 3 to 5X lower time-to-first-audio, so teams serve 2x the users on the same hardware.", "one_liner": "Inference for real-time voice and chat", "team_size": 10, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1717199794, "tags": [ "AIOps", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2024", "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/pipeshift", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/pipeshift.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://linkedin.com/company/pipeshift", "x_url": "https://x.com/pipeshiftai", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/pipeshift", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/6dc8136429eadec250bda86f1102143f81a24beb.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/7bbe0c7a8e3c5d237daced05c9c6ccf3e3d2c253.png" ], "primary_partner": { "name": "Tyler Bosmeny", "url": "https://www.ycombinator.com/people/tyler-bosmeny" }, "founders": [ { "user_id": 951072, "full_name": "Arko C", "title": "Founder/CEO", "founder_bio": "CEO @ Pipeshift.\nBuilding inference for real-time voice and chat.", "is_active": true, "linkedin_url": "https://linkedin.com/in/arkoc", "x_url": "https://x.com/arkobuilds", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/39136e6e723e1f76e5a1bdc560206943aee81027.jpg" }, { "user_id": 960185, "full_name": "Enrique Ferrao", "title": "Founder/CTO", "founder_bio": "CTO @ Pipeshift. Focused on squeezing out max LLM performance from GPUs", "is_active": true, "linkedin_url": "https://linkedin.com/in/enrique-ferrao", "x_url": "https://x.com/FerraoEnrique", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a33343830babab394b79c61cdb3cffd378b0f8f5.jpg" }, { "user_id": 960170, "full_name": "Pranav Reddy", "title": "Founder/CIO", "founder_bio": "CIO @ Pipeshift. Making LLMs go brrrr at Pipeshift", "is_active": true, "linkedin_url": "https://linkedin.com/in/pranavreddyg", "x_url": "https://x.com/pranavreddyg", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b8b0ad79f3f331999efdd9b6b917e168ce8ed31e.jpg" } ], "jobs": [], "news": [ { "title": "Democratising Access To Open-Source GenAI With Pipeshift", "url": "https://www.forbes.com/sites/davidprosser/2025/01/23/democratising-access-to-open-source-genai-with-pipeshift/", "date": "Jan 23, 2025" } ], "launches": [ { "id": 83260, "title": "Pipeshift AI - Fine-tuning and inference for open-source LLMs", "tagline": "Replace GPT/Claude in production with specialized LLMs that are fine-tuned on your context, offering higher accuracy, lower latencies and model ownership.", "body": "**_TL;DR:_** Pipeshift is the cloud platform for finetuning and inferencing open-source LLMs, helping teams get to production with their LLMs faster than ever. With Pipeshift, companies making >1000 calls/day on frontier LLMs can use their data and logs to replace GPT/Claude with specialized LLMs that offer higher accuracy, lower latencies, and model ownership. [_Connect with us._](https://cal.com/arkoc/pipeshift)\n\n![uploaded image](/media/?type=post&id=83260&key=user_uploads/951072/55b3d2ab-6279-4002-9bc7-2e7527c8578b)\n\n# **🧨 The Problem: Building with Open-source LLMs is hard!**\n\nThe open-source AI stack is missing, forcing most teams to experiment by **duct-taping things like TGI/vLLM but having nothing ready for production.** As you scale, it requires expensive ML talent, long build cycles, and constant optimizations.\n\nThe **gap between open-source and closed-source models is shrinking** (Meta's Llama 3.1 405B is a testament to that)! And open-source LLMs offer multiple benefits over their closed-source counterparts:\n\n🔏 Model ownership and IP control\\\n🎯 Verticalization and customizability\\\n🏎️ Improved inference speeds and latency\\\n💰 Reduction of API costs at scale\n\n# **🎉 The Solution: Heroku/Vercel for Open-source LLMs**\n\nPipeshift is the **cloud platform for fine-tuning and inferencing open-source LLMs**, helping developers get to production with their LLMs faster than ever.\n\n**🎯 Fine-tune Specialized LLMs**\\\nRun multiple LoRA-based fine-tuning jobs to build specialized LLMs.\n\n**⚡️ Serverless APIs of Base and Fine-tuned LLMs**\\\nRun inference for your fine-tuned LLMs and pay as per your token usage.\n\n**🏎️ Dedicated Instances for High Speed and Low Latency**\\\nUse our optimised inference stack to get max throughputs and utilisation on GPUs.\n\n[Product Demo: https://youtu.be/z8z5ILyXxCI](https://youtu.be/z8z5ILyXxCI)\n\n_Our inference stack is one of the best globally, hitting **150+ tokens/sec on 70B parameter LLMs** without any model quantization. And, since our private beta access was opened (<2 weeks back), we have already seen **25+ LLMs being fine-tuned with over 1.8B tokens in training data** across 15+ companies._\n\n![uploaded image](/media/?type=post&id=83260&key=user_uploads/951072/b91ba4bb-dca1-4567-8a0c-cf637e03b561)\n\n# **👋 Ask: How you can help**\n\nIf you’re building an AI co-pilot/agent/SaaS product and **are looking to move to open-source LLMs** or know someone who’s looking to do that same, then [book a call](https://cal.com/arkoc/pipeshift) or mail us at [_founders@pipeshift.ai_](mailto:founders@pipeshift.ai) - whichever you’d like!", "url": "https://www.ycombinator.com/launches/Leu-pipeshift-ai-fine-tuning-and-inference-for-open-source-llms", "votes": 703, "created_at": "2024-08-21T01:29:39.204Z" } ] }, { "id": 29966, "name": "Mica AI", "slug": "mica-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0e4f97e07f6e1a169c14a54417c11eec5688e0c6.png", "website": "https://usemica.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Today, as employees teach AI how to perform valuable company work, the resulting capabilities often remain trapped on individual laptops or scattered across chats and repositories. \r\n\r\nMica gives each company a managed, agent-native internal marketplace where employees can publish capabilities, discover them by describing the task they need help with, and install them through the AI tools they already use. Mica tracks ownership, requirements, permissions, and team customizations while letting employees contribute improvements back to the shared version for evaluation and approval.\r\n\r\nThe result: employees stop rebuilding workflows their coworkers have already solved, useful improvements spread across the organization without overwriting team-specific customizations, and security gains visibility without blocking bottom-up innovation. Mica turns scattered AI work into institutional knowledge that compounds.", "one_liner": "Turn employees' AI skills into shared company infrastructure", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1720831958, "tags": [ "Marketplace", "B2B", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 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/mica-ai", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/mica-ai.json", "year_founded": 2023, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/mica-ai", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/0e4f97e07f6e1a169c14a54417c11eec5688e0c6.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": 281665, "full_name": "Achyuta Iyengar", "title": "Founder/CEO", "founder_bio": "Achyuta is the co-founder and CEO of Mica AI.\n\nPrior to Mica, Achyuta worked as a Product Manager at Lob (YC S13) where he led the New Product Development, Address Verification, and Developer Experience teams. He has a BS in Business Administration from the Haas School of Business at UC Berkeley. \n", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/achyuta-iyengar/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a5f83813035e3085879bf3a9c23416cf0181ee03.jpg" }, { "user_id": 1626603, "full_name": "Bharadwaj Swaminathan", "title": "Founder/CTO", "founder_bio": "Bharadwaj is the founder and Head of Engineering at Mica AI. Previously, he worked as a Data Scientist at Hewlett Packard Enterprise, working on creating machine learning products in the networking space. He has a Bachelor's in Data Science and Economics from UC Berkeley.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/bharadwajswaminathan", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c683cdfe84236872d02756b37c82e756443872ad.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 82748, "title": "Mica AI - AI Agents that Automate B2B Sales", "tagline": "Helping SaaS sales teams close more deals.", "body": "Hi everyone, we’re Achyuta, Jai, and Bharadwaj!\n\n**TLDR:**\n\n[**Mica**](https://usemica.com/) helps B2B sales teams close more deals by automating their entire sales follow-up process. Our AI agents analyze sales calls, generate tailored collateral, and follow up with prospects until the deal is closed.\n\n**The Problem:**\n\nThe best sales reps aren’t just great at selling—they are elite content creators. They crafted tailored collateral like decks, 1-pagers, and product demos to help champions advocate internally. However, creating this content often takes over 30 minutes per call, and with multiple calls a day, even the best reps can only prioritize a few clients, leaving others with subpar follow-ups and millions in lost deals.\n\n**Our Solution:**\n\nMica automates the sales follow-up process by generating deal-closing collateral in less than a minute. Our AI analyzes sales calls, extracts key insights, builds tailored collateral, and sends this to prospects in a centralized deal summary page.\n\n![uploaded image](/media/?type=post&id=82748&key=user_uploads/281665/a654eebe-5ef9-48ee-ab9d-ca41efc83bc4)\n\n**Key Benefits**\n\n1. **Quicker Follow-up Time:** Mica creates personalized follow ups in under 1 minute. This lets top performers do A+ work on every deal and helps the rest of the team sell like a top performer.\n2. **Faster Sales Cycles:** The point of contact can easily review important information from the call, share it internally, and make decisions faster.\n\n**How it Works**\n\n1. **Upload:** Mica automatically pulls in your sales call from existing recording or notetaking tools.\n2. **Extract Key Insights:** Mica identifies the key points the prospect was most interested in.\n3. **Generate Tailored Collateral:** Mica creates tailored decks, product demos, and 1-pagers for each key topic.\n4. **Share:** Mica generates a shareable link containing all the collateral, which can be sent directly to the prospect in follow-up emails that Mica also creates.\n\nHere’s a demo of Mica that we created from an actual Mica sales call:\n\n\n\n**Our Ask:** We’re looking to onboard customers who want to automate and improve their sales follow-ups.\n\nWe’re looking for:\n\n* Sales reps and heads of sales at B2B SaaS companies.\n* Founders who are doing founder-led sales.\n\nAnyone who is interested can book a demo [**here**](https://calendly.com/achyutaiyengar/mica-15-minute-demo).\n\n![uploaded image](/media/?type=post&id=82748&key=user_uploads/281665/307627c1-b261-47d7-b07a-b78ac54926be)\n\n", "url": "https://www.ycombinator.com/launches/LWe-mica-ai-ai-agents-that-automate-b2b-sales", "votes": 16, "created_at": "2024-08-05T20:19:18.712Z" } ] }, { "id": 30041, "name": "Revyl", "slug": "revyl", "former_names": [], "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, "dday_video_url": null, "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" } ], "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\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": 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", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/0695554aaa43f831a6d970c73486aad8f7a9101f.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Nicolas Dessaigne", "url": "https://www.ycombinator.com/people/nicolas-dessaigne" }, "founders": [ { "user_id": 2542, "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.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/hleath/", "x_url": "https://x.com/jhleath", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/211cb23fe3bd004ef4434c9069d5d0694c5b647e.jpg" } ], "jobs": [], "news": [ { "title": "Archil - All of your data, on every instance, instantly", "url": "https://archil.com/post/archil-file-system-to-data-company", "date": "Jun 02, 2025" }, { "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" } ], "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)", "url": "https://www.ycombinator.com/launches/M8T-archil-transform-s3-into-an-infinite-local-file-system", "votes": 65, "created_at": "2024-10-28T17:59:23.946Z" } ] }, { "id": 30060, "name": "Lingo.dev", "slug": "lingodotdev", "former_names": [ "Replexica" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/8a284047c475d06365013890a991877b3bdad21e.png", "website": "https://lingo.dev", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Lingo.dev is the localization engineering platform: the best way to translate with LLMs, measure translation quality, and proofread with native speakers.\r\n\r\nLingo.dev is built for teams accountable for quality in languages they can't read. Teams configure localization engines, stateful translation APIs that hold the glossary, brand voice, and per-locale model preferences, and every request retrieves that context at inference time through retrieval augmented localization. Every translation is scored before it goes live, scores and corrections tune the engine, and the localization team runs the localization infrastructure. Integrate through the API, CLI, CI/CD, or native integrations with the code repository and the CMS. \r\n\r\nLingo.dev is the standard localization infrastructure for modern enterprise teams scaling into new markets – including Mistral, Solana, SoSafe, and Cal.com. Over 300M words processed, SOC 2 Type II compliant.", "one_liner": "The Localization Engineering Platform", "team_size": 7, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1728389519, "tags": [ "B2B", "International", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2024", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "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": "Veronica and Max met eight years ago at work and have been building together since. Veronica came from data science, then AI. Max came from engineering, having led a DORA-elite frontend team at Typeform.\r\n\r\nBetween them they had shipped software at startups and enterprises and bootstrapped a SaaS with customers in over 100 countries. Localization broke the same way every time: the people accountable for the result could not read most of the languages they were accountable for. They approved work they could not check, and they found out it was wrong from a customer.\r\n\r\nEvery product on the market treated that as a workflow problem, so it sold coordination. It is a measurement problem. Lingo.dev was built around the instrument first, and the pipeline around the instrument." }, { "question": "How did you decide to apply to Y Combinator? What was your experience applying, going through the batch, and fundraising at demo day?", "answer": "Our first serious customers arrived, Cal.com among them, and the question stopped being whether this works and became how far it goes. Localization is a global problem by definition. Every company that grows past one language has it, in every market it enters, permanently. A problem that shape deserves a lasting, durable company behind it rather than a good couple of years.\r\n\r\nSo we shot for the stars and applied to the best accelerators in the world. We ended up in conversations with several, and we chose Y Combinator.\r\n\r\nNo other program has a record like it. Stripe, Airbnb, DoorDash, and Coinbase all started there, and each one became the default infrastructure of an entire category, operating in nearly every market on earth. YC backs companies at the point where the idea still looks small and the market does not exist yet, and it does that more often, and more correctly, than anyone else. That is the standard it sets, and that is the company we wanted to keep.\r\n\r\nThe batch did what it is known for: sharper questions, faster iteration, and a peer group that tells you the truth early rather than politely later. We raised $4.2M from Y Combinator, Initialized Capital, and the founders of Supabase and Dependabot to scale the platform and meet the growing demand from international teams." }, { "question": "How have you kept in touch with the YC community and continued to use YC resources & programs since the batch ended?", "answer": "We attend YC events and stay close to the private network between them.\r\n\r\nWe try to be genuinely useful. Founders ask about localization, going multilingual, and expanding internationally, and we take those conversations whenever there is a chance to help. The network works because founders treat it as something to contribute to, so that is how we use it." }, { "question": "What's the history of your company from getting started until the present day? What were the big inflection points?", "answer": "Founded in December 2023, after winning an AI product competition at Cornell Tech in New York. Full-time from February 2024.\r\n\r\nThe first product translated software with AI on every commit. It worked, and it showed how small that problem is. The commit loop is roughly one percent of localization work, and it was already close to solved.\r\n\r\nThe inflection was the buyer. Localization managers and localization engineers carry accountability for quality in languages they cannot read, and the market treats that seat as an afterthought. The company was rebuilt around that seat, and the tool became a platform: localization engines, quality scoring, native integrations, and proofreading with native speakers.\r\n\r\nToday over 300M words have been processed on the platform, for teams including Mistral, Solana, SoSafe, and Cal.com. Lingo.dev is SOC 2 Type II compliant and has raised $4.2M from Y Combinator, Initialized Capital, and the founders of Supabase and Dependabot to scale the platform and meet the growing demand from international teams." }, { "question": "What is the core problem you are solving? Why is this a big problem? What made you decide to work on it?", "answer": "A company releases into thirty languages. The person accountable for those languages reads two.\r\n\r\nTranslation stopped being the constraint, it comes back in seconds, from an agency or straight from a model, and it gets cheaper every quarter. What nobody hands the accountable team is the number: which languages are good, which drifted, and what to fix first. Without it the team either trusts output it cannot read, or pays a person to read every string.\r\n\r\nLingo.dev is where that number comes from. Teams pick from the industry-standard metrics or define quality criteria in plain words, and every translation is scored before it goes live. Every low score carries its reason, traced to the model, the translation rule, or the missing glossary term. Corrections from native speakers tune the localization engine, so the edit rate falls over time.\r\n\r\nIt is a big problem because the accountability does not move. Software goes out in more languages every year, the people who answer for those languages still cannot read them, and the volume of text nobody has checked grows with every release." }, { "question": "What is your long-term vision? If you truly succeed, what will be different about the world?", "answer": "Translation quality becomes a measured quantity.\r\n\r\nToday it is an opinion. Vendors assert it, buyers cannot check it, and nearly every quality number published in this industry arrives without a method behind it. When Lingo.dev succeeds, a team states what its Japanese was worth this quarter, what changed since last quarter, and what caused the change, the same way it states its uptime.\r\n\r\nDownstream of that, a product goes live in every language it has customers in on the day it goes live in English, and the team that owns those languages proves the result instead of defending it." } ], "url": "https://www.ycombinator.com/companies/lingodotdev", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/lingodotdev.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/lingodotdev/", "x_url": "https://x.com/lingodotdev", "fb_url": null, "cb_url": null, "github_url": "https://github.com/lingodotdev", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/8a284047c475d06365013890a991877b3bdad21e.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/333cb48eb636ff7b5d665261d9c36759c9766fa3.png" ], "primary_partner": { "name": "Pete Koomen", "url": "https://www.ycombinator.com/people/pete-koomen" }, "founders": [ { "user_id": 1992394, "full_name": "Max Prilutskiy", "title": "Founder/CEO", "founder_bio": "Max is a co-founder and CEO of Lingo.dev.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/maxprilutskiy", "x_url": "https://twitter.com/maxprilutskiy", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b2bf4dde1a3ffd83d232fe5a388e7b3ff6283e46.jpg" }, { "user_id": 1989733, "full_name": "Veronica Prilutskaya", "title": "Founder/CPO", "founder_bio": "CPO and co-founder of Lingo.dev.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/vrcprl/", "x_url": "https://twitter.com/vrcprl", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/cdaba224c6470b15da00112c10285c1520724cd1.jpg" } ], "jobs": [], "news": [ { "title": "Lingo.dev is an app localization engine for developers | TechCrunch", "url": "https://techcrunch.com/2025/02/18/lingo-dev-is-an-app-localization-engine-for-developers/", "date": "Feb 18, 2025" } ], "launches": [ { "id": 84681, "title": "Lingo.dev – The Localization Engineering Platform", "tagline": "Lingo.dev is the localization engineering platform: the best way to measure translation quality, translate with LLMs, and proofread with native speakers.", "body": "![uploaded image](/media/?type=post&id=84681&key=user_uploads/1992394/c62aca07-353c-49ad-a49e-b403d1b784e0)\n\n**TL;DR**\n\n[Lingo.dev](https://lingo.dev) is the localization engineering platform: the best way to translate with LLMs, measure translation quality, and proofread with native speakers.\n\nIt's built for teams accountable for quality in languages they can't read: a localization team, or the product, engineering, or marketing team that inherited localization without one. Every translation is scored before it goes live, and scores and corrections tune the localization engine.\n\n**Speed stopped being the problem**\n\nA release goes out in thirty languages, and the person accountable for it reads two.\n\nTranslation comes back fast now, from an agency or straight from a model, and it gets cheaper every quarter. The number nobody hands you is the quality one: which languages are good, which drifted, and what to fix first. Without it you are accountable for quality you can neither read nor repair.\n\n**What Lingo.dev does**\n\n* **Build your own localization engine.** A localization engine is a stateful translation API that holds your glossary, brand voice, and per-locale model preferences. Retrieval augmented localization sends that context to the LLM at inference time. Assign the highest-scoring model per language pair, with a fallback order, on your own LLM provider API key or through Lingo.dev without markup.\n* **Measure translation quality in languages you can't read.** Pick from the industry-standard metrics, define your own quality criteria in plain words, bring the quality scorecard you have, or start from a template built for your content type. The criteria you define score translations from LLMs and from native speakers, and every low score comes with the reason, traced to the model, the translation rule, or the missing glossary term.\n* **Integrate localization into the tools you already use.** Connect the code repository, the CMS, the help center, and the email provider through native integrations, and reach the same localization engine from the API, the CLI, and CI/CD. The localization team runs the localization infrastructure.\n* **Proofread with native speakers.** Decide what waits for a person, by content type, by locale, or by a score threshold you set. Every correction tunes the localization engine, so the native speakers' edit rate falls over time.\n\n**Who runs on it**\n\nLingo.dev is the standard localization infrastructure for modern enterprise teams scaling into new markets, including Mistral, Solana, SoSafe, and Cal.com. Teams have processed over 300M words on the platform, for their customers all over the world. Lingo.dev is SOC 2 Type II compliant, and has raised $4.2M from Y Combinator, Initialized Capital, and the founders of Supabase and Dependabot to scale the platform and meet the growing demand from international teams.\n\n**Ask**\n\nIf you release into languages nobody on your team reads, we will score what goes live today, per language, on your own content.\n\nSet up Lingo.dev: \n\nBook a demo: \n\nAnd send this to the localization professional you know. Scoring quality in languages nobody on the team reads is their job, and this is where that work happens.\n\n**Team**\n\n[Veronica](https://www.linkedin.com/in/vrcprl/) and [Max](https://www.linkedin.com/in/maxprilutskiy/), [Lingo.dev](https://lingo.dev)'s founders, met eight years ago at work. Veronica has a data science and AI background. Max has an engineering background, having led a DORA-elite frontend team at Typeform, one of Europe's best-known SaaS products.\n\nBoth experienced localization problems firsthand while working at startups and enterprise companies and while bootstrapping a SaaS with customers from over 100 countries. This shared experience led them to create Lingo.dev, so the professionals accountable for translation quality can measure it in every language, including the ones nobody on the team reads.\n\n![uploaded image](/media/?type=post&id=84681&key=user_uploads/1989733/dfd03586-1d6f-4747-b6fc-e0d84f5022a5)\n\n", "url": "https://www.ycombinator.com/launches/M1p-lingo-dev-the-localization-engineering-platform", "votes": 60, "created_at": "2024-10-10T18:18:35.695Z" } ] }, { "id": 30107, "name": "Surge", "slug": "surge", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/1f4a489f75647f08676e6de181d0f4d27016b18f.png", "website": "https://surge.app", "all_locations": "Lehi, UT, USA", "long_description": "Surge is Stripe for telephony. Our team has experience building telephony software at billion dollar scale. Because of increased regulation, Twilio and other SMS APIs take weeks to onboard new customers, but we can get startups onboarded same day. Surge wins by enabling easy carrier registration, better support, and higher level APIs and no code UI components to make implementation easier for startups and developers.", "one_liner": "Stripe for telephony", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1731622401, "tags": [ "Developer Tools", "SaaS", "API", "Telecommunications", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2024", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/surge", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/surge.json", "year_founded": 2024, "city": "Lehi", "country": "US", "linkedin_url": "https://www.linkedin.com/company/surgeapi", "x_url": "https://x.com/surgeapi", "fb_url": null, "cb_url": null, "github_url": "https://github.com/surgeapi", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/1f4a489f75647f08676e6de181d0f4d27016b18f.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 97400, "full_name": "Dennis Beatty", "title": "Founder/CEO", "founder_bio": "Founder/CEO at Surge (F24), the easiest way for developers to send text messages. Formerly principal engineer over payments at Entrata and early engineer at Podium (W16) where I was a tech lead and senior engineer over the messaging platform and led engineering for the SMS payments product that reached a $2B run rate in year 2.", "is_active": true, "linkedin_url": "https://linkedin.com/in/dnsbty", "x_url": "https://x.com/dnsbty", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/79d9d9b29325e34b22eeab9a512d25f0be13b325.jpg" }, { "user_id": 2247072, "full_name": "Brett Beatty", "title": "Founder", "founder_bio": "Co-Founder/CTO at Surge (F24), the easiest way to add text messaging to software. Prior to Surge, I spent six years at Podium (W16) where I was a senior engineer on the Phones team and the account structure team, building the APIs upon which the rest of Podium's products were built. I was very focused on providing five nines of uptime and sub-millisecond response times.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/brett-t-beatty", "x_url": "https://twitter.com/brett_beatty", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1b00399d92ce6592796cbb14df7658c9dbe4b954.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 85595, "title": "Surge ⚡ The easiest SMS API for developers", "tagline": "Get registered and sending text messages faster than ever before.", "body": "[Surge is the easiest way for developers to send and receive text messages.](https://youtu.be/3cTyfiw5jtE)\n\n# **The Problem**\n\nIt used to be easy to start texting with Twilio and other APIs, but after recent carrier compliance changes, you have to jump through hoops and piece together fragmented documentation to get registered. Then you still have to wait 2-3 weeks for approval before you can actually send messages.\n\n![uploaded image](/media/?type=post&id=85595&key=user_uploads/97400/2bd7755f-cbb7-4d0d-ad1f-bfd7f8804db9)\n\nThe big SMS APIs are all now focused on big companies paying them millions of dollars per year. Startups are left with a terrible user experience, unresponsive email support, and a feeling of helplessness when trying to add SMS functionality to our applications.\n\n# **Our Solution**\n\n![uploaded image](/media/?type=post&id=85595&key=user_uploads/97400/17af9950-2bdc-46d5-b7ae-83f4194fbd42)\n\nBy incorporating the new compliance standards into our product from the beginning, Surge lets developers send texts without having to become experts on the registration process first. We provide white glove onboarding to get you through carrier registration or toll-free verification, and we can do it in 1-2 business days (sometimes even same day) instead of the typical 2-3 weeks. And we can get you up and running with a trial in minutes.\n\nOur intuitive REST API and webhooks are designed at a higher level of abstraction than other providers, which helps you simplify your application logic. And if you’d rather write as little code as possible, we even have embeddable low-code UI components that make two-way texting a breeze to set up. On top of that, we offer responsive support to help you figure out any issues you have, no matter your size.\n\n# **Our Team**\n\n[Dennis](https://linkedin.com/in/dnsbty) and [Brett](https://www.linkedin.com/in/brett-t-beatty) are brothers who spent a combined 11 years at Podium (W16) where they worked on communications infrastructure for small businesses. Brett was a senior engineer on the Phones product, and Dennis was a tech lead and senior engineer on the Messenger platform. We’re excited to be building together, and to be taking on a problem that has caused so much frustration for developers like us.\n\n![uploaded image](/media/?type=post&id=85595&key=user_uploads/97400/b94153ab-d83e-404b-a1d8-be5068d37906)\n\nIf you’re currently using Twilio or another SMS API, please reach out! Even if you have no interest in switching providers, we would love to hear about your experience. [Book time on my calendar](https://cal.com/team/surge/sms-chat-from-yc-launch), or reach out to [ycdirectory@surgemsg.com.](mailto:ycdirectory@surgemsg.com)", "url": "https://www.ycombinator.com/launches/MGZ-surge-the-easiest-sms-api-for-developers", "votes": 42, "created_at": "2024-11-15T18:20:36.034Z" } ] }, { "id": 30114, "name": "Ryvn", "slug": "ryvn", "former_names": [ "Armada" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/38a4a570871fba4b9702b51fa8da50142159b1a8.png", "website": "https://ryvn.ai", "all_locations": "New York City, NY, USA", "long_description": "Ryvn provides the devtools and infrastructure to easily deploy any workload, on any cloud, and on-prem. Run apps in your own cloud and offer Bring Your Own Cloud (BYOC) to your customers in minutes, with built-in observability designed for sensitive industries.", "one_liner": "Easy and secure customer cloud deployments", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1730680026, "tags": [ "Developer Tools", "SaaS", "DevOps", "Infrastructure" ], "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/ryvn", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/ryvn.json", "year_founded": 2024, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/ryvn/", "x_url": "https://x.com/ryvnai", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/38a4a570871fba4b9702b51fa8da50142159b1a8.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": 1690248, "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", "x_url": "https://x.com/albert_", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f61743a26b1715c1db12a6ea5c68fe199e4866fc.jpg" }, { "user_id": 682648, "full_name": "Shardool Patel", "title": "Founder/CTO", "founder_bio": "Building deployment infrastructure to help companies deploy to multi-cloud. Previously led an engineering team at Palantir and helped scale the internal deployment platform to a $20M ARR product.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/sp97/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f49826d81086cce33d2c2d395e7c170ea460ca3e.jpg" } ], "jobs": [ { "id": 84793, "title": "Founding Software Engineer", "url": "https://www.ycombinator.com/companies/ryvn/jobs/qg0OM1Q-founding-software-engineer", "location": "New York City", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$160K - $220K", "equity_range": "0.50% - 2.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "Amazon Web Services (AWS)", "Microsoft Azure", "Go", "Google Cloud", "React", "TypeScript" ] } ], "news": [], "launches": [ { "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 \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 \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 \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 \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 \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", "url": "https://www.ycombinator.com/launches/MD5-ryvn-deploy-applications-to-customer-clouds-on-prem", "votes": 84, "created_at": "2024-11-08T14:33:26.181Z" } ] }, { "id": 30198, "name": ".Wave", "slug": "dotwave", "former_names": [ "Dollyglot" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e16adbb8c4442e6124b56566c82ed680beaba21a.png", "website": "https://dotwave.ai/", "all_locations": "Paris, Île-de-France, France", "long_description": ".Wave builds a continuous inference engine for streaming AI models, including full-duplex voice and streaming speech recognition. \r\n\r\nCustomers bring their models; we integrate and run them, managing execution, session state, and scheduling to reduce end-to-end latency and serving cost per live session. \r\n\r\nWe use cadenced inference to support more concurrent sessions per GPU while keeping latency low and consistent.", "one_liner": "Continuous inference for streaming AI models", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1741300119, "tags": [ "Generative AI", "B2B", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2025", "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/dotwave", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/dotwave.json", "year_founded": 2024, "city": "Paris", "country": "FR", "linkedin_url": "https://www.linkedin.com/company/dotwaveai/about/?viewAsMember=true", "x_url": "https://x.com/dotwaveai", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/e16adbb8c4442e6124b56566c82ed680beaba21a.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": 1458005, "full_name": "Thomas Minassian", "title": "Founder/CEO", "founder_bio": "CEO .Wave. Our team built Parler-TTS Mini Multilingual, the world’s first fully multilingual open-source text-to-speech model, with 300,000 monthly downloads, and Dollyglot, the first model to turn a photo into a real-time video avatar.", "is_active": true, "linkedin_url": "https://linkedin.com/in/thomas-minassian-b25626102", "x_url": "https://x.com/thminassian", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3b4cb586d951f5c9e9e241d2265b52891a44a07b.jpg" }, { "user_id": 1646678, "full_name": "Paul-Henri Biojout", "title": "Founder/CTO", "founder_bio": "CTO .Wave. Our team built Parler-TTS Mini Multilingual, the world’s first fully multilingual open-source text-to-speech model, with 300,000 monthly downloads, and Dollyglot, the first model to turn a photo into a real-time video avatar.", "is_active": true, "linkedin_url": "https://linkedin.com/in/phbiojout", "x_url": "https://x.com/PH_BJT", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/55f57ae0118a71774fb96b1871b9a9eaf10dc3b9.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 88334, "title": "Dollyglot: Befriend Anybody", "tagline": "Dollyglot is like Character.ai but with real-time video avatars.", "body": "[Dollyglot](https://www.dollyglot.com/) is like Character.ai but with real-time video avatars.\n\nTurn a photo and a voice into a real friend. Speak with Harry Potter about Hogwarts, or brainstorm ideas with The Rock!\n\n[**Our Product Video**](https://youtu.be/GhuqAMSq6HY)\n\n**Our Team:** **We’ve lived and worked together for two years**\n\n**Thomas**: Ex-quant at Société Générale. Master’s in Applied Mathematics and Business (HEC Paris, University of Paris 7).\n\n**Paul-Henri**: Built the Yumi Dialogue Engine, an AI for creator “clones” that scaled to 1 000 paying users. Dropped out of CentraleSupélec (Computer Science) to launch Dollyglot.\n\n**Together, we built Parler-TTS Mini Multilingual**, the world’s first and only fully open-source multilingual text-to-speech model. In the last month alone, it has garnered over 5,000 downloads and inspired many fine-tuning projects.\n\n![uploaded image](/media/?type=post&id=88334&key=user_uploads/89898/49894db9-ac0d-45da-bb91-4944831f8a38)\n\n**Our Vision**\\\nWithin five years, every Gen Alpha will have an AI best friend. By nature, AI is empathetic and nonjudgmental, creating a safe space where everyone can truly be themselves.\n\n**What We’ve Built**\n\nDollyglot developed the world’s first and only photo-to-real-time video avatar model. Paired with reasoning models like DeepSeek R1 or Grok, we bring your AI friends to life and make 'non-lobotomized' characters.\n\n **What’s Next**\n\nJoin our waitlist to try Dollyglot in the coming weeks.\n\nQuestions? Contact Thomas (CEO) at [thomas.minassian@dollyglot.com](mailto:thomas.minassian@dollyglot.com) or Paul-Henri (CTO) at [paul-henri.biojout@dollyglot.com](mailto:paul-henri.biojout@dollyglot.com).", "url": "https://www.ycombinator.com/launches/Myk-dollyglot-befriend-anybody", "votes": 18, "created_at": "2025-03-07T01:37:29.930Z" } ] }, { "id": 30213, "name": "Dexto", "slug": "dexto", "former_names": [ "Truffle AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/151976ce07fb22bf59209dda8531a283a9eeda58.png", "website": "https://www.dexto.ai/", "all_locations": "San Francisco, CA, USA", "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.", "one_liner": "AWS for AI Agents", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1740509470, "tags": [ "Developer Tools", "Generative AI", "Infrastructure", "AI", "AI Assistant" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2025", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "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/dexto", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/dexto.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/dexto", "x_url": "https://x.com/dexto_ai", "fb_url": null, "cb_url": null, "github_url": "https://github.com/truffle-ai/", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/151976ce07fb22bf59209dda8531a283a9eeda58.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": 1684384, "full_name": "Shaunak Srivastava", "title": "Founder/CEO", "founder_bio": "Co-founder. \nPrev. GenAI & 3D Research@CMU | Published at NeurIPS 2022, WACV '23 (in collaboration with Meta).\nBuilt AI products for face recognition and health estimation at Hyperverge. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/shaunak-srivastava-244567163/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/258124ca26936b290fdca6cc846cfacb79c9ed9e.jpg" }, { "user_id": 2369842, "full_name": "Rahul Karajgikar", "title": "Founder/CTO", "founder_bio": "Co-founder and CTO at Truffle AI - building developer tools for AI agents\nFormer engineer at AWS OpenSearch. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/rahul-karajgikar", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/77e603d364e1917893bf77902db6eb2fe62e6c07.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 88053, "title": "Truffle AI - AI Agents that work in any Software Application", "tagline": "Integrate AI Agents with simple APIs, seamlessly", "body": "Hey YC!\n\nWe’re Shaunak and Rahul and we are making it easy for developers to **integrate AI Agents into any software application**. We do this by making agents available as simple APIs that can be called from anywhere. Developers have used Truffle to add customer support agents into WhatsApp and integrate analytics agents into Slack. Check out our demo below 👇\n\n\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" } ] }, { "id": 30216, "name": "Sublingual", "slug": "sublingual", "former_names": [ "Khipu" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c536945e04bdc8b405d2bb35c81631f9b7c3c738.png", "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, "tags": [ "Developer Tools", "Open Source", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2025", "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/sublingual", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/sublingual.json", "year_founded": null, "city": "San Francisco", "country": "US", "linkedin_url": "", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/c536945e04bdc8b405d2bb35c81631f9b7c3c738.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": 2378452, "full_name": "Matthew Tang", "title": "Founder/CEO", "founder_bio": "recommendation systems, computer vision, deep learning theory", "is_active": false, "linkedin_url": "https://www.linkedin.com/in/mhtang2/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a8999b6b3036091766eabf43e32d32bab7872005.jpg" }, { "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/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/779188a524ab36421995729be2db856fc8c916c1.jpg" } ], "jobs": [], "news": [], "launches": [ { "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\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:**  \n\n🔗 **Website:** \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", "url": "https://www.ycombinator.com/launches/Muu-sublingual-llm-evals-for-lazy-devs", "votes": 44, "created_at": "2025-02-27T01:56:08.363Z" } ] }, { "id": 30247, "name": "Osmosis", "slug": "osmosis", "former_names": [ "Gulp" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0e0e653e5da051b7c87a56070249ad76479b0594.png", "website": "https://osmosis.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Osmosis is a post-training platform that helps companies fine-tune language models using reinforcement learning. We work with fast-growing AI companies to train task/domain-specific models that beat foundation models on performance, cost, and latency. Our platform handles compute orchestration, reward modeling, and training run observability as a CLI-based product usable by developers and agents. ", "one_liner": "Reinforcement Learning (RL) for AI Agents", "team_size": 6, "industry": "B2B", "subindustry": "B2B", "launched_at": 1737656598, "tags": [ "Machine Learning", "Reinforcement Learning", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2025", "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/osmosis", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/osmosis.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/osmosis-ai/", "x_url": "https://x.com/osmosis_ai", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/gulp-ai", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/0e0e653e5da051b7c87a56070249ad76479b0594.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": 695591, "full_name": "Kasey Zhang", "title": "Founder/CEO", "founder_bio": "Currently: osmosis.ai \n\nPreviously: gaming founder, VC", "is_active": true, "linkedin_url": "https://linkedin.com/in/kasey-zhang", "x_url": "https://x.com/_WEEXIAO", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/89bfeaa626b0c7c6444e4634610ad1c228392c9f.jpg" }, { "user_id": 1479747, "full_name": "Andy Lyu", "title": "Founder/CTO", "founder_bio": "Defining how real time systems should be built. Previously worked on data architecture and ecosystem at TikTok recommendations as the 5th and youngest US hire", "is_active": true, "linkedin_url": "https://linkedin.com/in/baiqingl", "x_url": "https://x.com/viewerisland", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4acaad1754ca9e5bf80ca3d25cdc86b8226565d6.jpg" } ], "jobs": [ { "id": 88480, "title": "Machine Learning Engineer ", "url": "https://www.ycombinator.com/companies/osmosis/jobs/N17l8oV-machine-learning-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$180K - $250K", "equity_range": "", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [ "Reinforcement learning (RL)" ] } ], "news": [], "launches": [ { "id": 87475, "title": "Osmosis: Unlocking Real-Time Learning for AI Agents", "tagline": "Osmosis gives AI agents the ability to learn like DeepSeek R1, all in real-time ", "body": "What if AI agents could immediately learn from their mistakes?\n\n## TL;DR\n\nWhile AI agent capabilities continue to improve, the agentic workflows remain brittle since agents aren’t able to learn from tasks in real-time. Osmosis is a framework that helps your AI agents learn in real-time (similar to DeepSeek R1’s post-training loop) in order to make them better, faster, and more responsive.\n\nOn the first run, we scored 21.5% accuracy, which is 60% better than base 4o performance (16X more expensive!). **This means that even on a first run, we're 25X+ more cost effective than base 4o - and that would be significantly better on a second run.** We also averaged 7.5 steps per task while OpenAI Operator averaged 67 steps per task (faster and cheaper!).\n\nIf you’re building AI agents and want to make them better, faster, and more responsive, we’d love to chat! Email [kasey@gulp.ai](mailto:kasey@gulp.ai) or book time [here](https://calendly.com/kasey-gulp/).\n\n## The Problem\n\nAI agents still struggle with novel and complex (multi-step) tasks. Even OpenAI Operator (current state-of-the-art) just scores 58% accuracy on the WebArena benchmark. The worst part is that agents make the same mistakes again and again!\n\nAnd even when agents can solve a task, there’s generally a lack of optimization in their process. This ends up negatively affecting performance while also driving up inefficient inference costs for users.\n\n## The Solution\n\nOsmosis builds and maintains a ‘library’ of an agent’s previous interactions. It’s a super simple two line addition in a developer’s agent infrastructure that:\n\n* Ingests and understand a user’s prompt\n* Queries a vector database to search for similar past scenarios\n* Recommends a relevant plan of action for the task\n* Quantifies an agent’s performance when it finishes, and embeds the assessment\n\nJust like that, we have a flow that enables agents to learn in real-time with each successive task!\n\nHere’s a head-to-head (Operator versus Claude 3.5 Sonnet + Osmosis):\n\n\n\n**Osmosis was 3X faster and 6X more efficient in the number of steps taken!**\n\n## Our Ask\n\nIf you (or anyone you know) are building AI agents and struggling with accuracy, speed, or cost, we’d love to chat and see how we can help! Please reach out at [kasey@gulp.ai](mailto:kasey@gulp.ai), or book some time directly [here](https://calendly.com/kasey-gulp/).\n\n## The Team\n\nWe’ve (Kasey and Andy) known each other for over a decade!\n\n[Kasey](https://www.linkedin.com/in/kasey-zhang/) (CEO) previously co-founded and ran a gaming startup for two years before it was acquired. From there, he worked at various VC firms focusing on AI and data investments before deciding to jump back into building.\n\n[Andy](https://www.linkedin.com/in/baiqingl/) (CTO) previously worked at TikTok, where he joined as an early member of the data infrastructure team and eventually became a tech lead, running data infrastructure for recommendations across the core TikTok app, Shop, Live, and more.\n\n![uploaded image](/media/?type=post&id=87475&key=user_uploads/695591/d662049a-cf42-4d21-bc5f-08643fd3be5e)\n\n", "url": "https://www.ycombinator.com/launches/Mkt-osmosis-unlocking-real-time-learning-for-ai-agents", "votes": 155, "created_at": "2025-02-06T19:22:40.649Z" } ] }, { "id": 30269, "name": "Liquid Compute", "slug": "liquid-compute", "former_names": [ "PowerPlay", "Strike", "Pluto" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ddb1c0f50037d9c24b823a5a568655e0a2d1980d.png", "website": "https://www.liquidcompute.com", "all_locations": "New York City, NY, USA", "long_description": "", "one_liner": "Pending CFTC regulation to be the first cash and physically settled…", "team_size": 5, "industry": "Fintech", "subindustry": "Fintech -> Banking and Exchange", "launched_at": 1740523068, "tags": [ "FinOps", "Fintech", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2025", "status": "Active", "industries": [ "Fintech", "Banking and Exchange" ], "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/liquid-compute", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/liquid-compute.json", "year_founded": 2024, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/liquid-compute", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/ddb1c0f50037d9c24b823a5a568655e0a2d1980d.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": 1526382, "full_name": "Ronit Jain", "title": "Founder/CEO", "founder_bio": "CEO @ Liquid Compute", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/ronitjain5", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3a8f6d92dc2c46bb92d40c7a409eb6741ae8befb.jpg" }, { "user_id": 2378932, "full_name": "Aarav Patel", "title": "Founder/CTO", "founder_bio": "Working on derivatives exchange", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/aaravpatel04", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/8be0b2f5460b3c6e32f744ecf647b4b5c7e1540e.jpg" } ], "jobs": [ { "id": 97134, "title": "Head of GTM", "url": "https://www.ycombinator.com/companies/liquid-compute/jobs/FjZBn9g-head-of-gtm", "location": "New York, NY, US", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$150K - $200K", "equity_range": "0.10% - 0.30%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [], "launches": [ { "id": 98145, "title": "Liquid Compute", "tagline": "Building a Regulated Venue that Commoditizes Intelligence", "body": "Today, Liquid Compute emerges from stealth with a $15 million seed round co-led by Chemistry and Firstmark. They are joined by K8 Capital, Night Capital, TrueBridge, Brainchild Holdings, UFO Holdings, Y Combinator and angel investors such as Dmitry Balyasny. Alongside the launch, the company is announcing pending applications before the CFTC for Designated Contract Market (DCM) and Derivatives Clearing Organization (DCO) status to build the first regulated exchange to trade both cash and physically settled contracts on AI infrastructure, starting with compute.\n\n## The Strategic Rationale for Regulation\n\nBuilding a true financial layer for compute requires the same institutional-grade framework that governs traditional commodities. While pursuing a regulated path is long and arduous, and liquidity is difficult to bootstrap, startup entrants such as ICE in energy, CBOE in volatility, and Kalshi in event contracts prevailed and actually accrued most of the financial value in the commoditization of their multi-trillion-dollar asset classes precisely because they secured regulatory status while focusing deeply on the unique physical and structural nuances of their specific markets.\n\nFor compute, there are unique physical dynamics that are particularly challenging to overcome. Oil can be stored in a barrel. Compute cannot. If a GPU sits idle this afternoon, that capacity evaporates forever. Its value depends entirely on location, availability, configuration, and the specific workloads it can run. The heterogeneity of compute is actually far more analogous to the power markets, but instead of acting as a proxy of generating electricity, compute acts as a direct proxy for access to intelligence, making it a critical pillar of both economic and national power. The United States recognizes this reality and is pouring unprecedented capital into chips, data centers, and energy grid expansion to secure its geopolitical edge. However, building supply is only half the equation. To truly secure compute as a strategic asset, America needs robust, regulated market infrastructure to price it, allocate it efficiently, finance its rapid growth, and allow dependent companies to manage their risk.\n\n## Enabling the Compute Trader\n\nBecause intelligence is rapidly developing a measurable cost curve, massive businesses will need to manage their exposure to it. Enterprises running heavy inference will need to hedge against rising AI costs. Neoclouds will need to lock in future utilization revenues, and lenders financing data centers will need forward prices to underwrite cash flows.\n\nThis reality is driving a massive structural shift where the buyer of compute is no longer always the end user. A new class of participant is emerging, including neoclouds, brokers, and dedicated trading firms looking to buy capacity, warehouse it, resell it, arbitrage price differences, or simply take a speculative view.\n\nToday, these participants trade on fundamentally bilateral, cumbersome infrastructure. Every resale requires a new contract, a fresh credit decision, another payment setup, and a separate SLA. As capacity changes hands, the chain of liability becomes hopelessly tangled.\n\nLiquid Compute exists to abstract away that complexity. Before a meaningful futures market can launch, the industry must standardize exactly what is being delivered, which requires verifiable infrastructure, defined performance metrics, and credible physical reference prices. By building an Exchange for Physical (EFP) market and clearing transactions through a common framework, any participant with a balance sheet will be able to take a position on compute without needing to become a cloud operator, credit underwriter, or AI company.\n\nThis is precisely why the company has partnered with institutional market participants like Susquehanna, BGC, and Wintermute. Liquid Compute is building the infrastructure that empowers market makers, lenders, and entirely new classes of participants to trade compute as a liquid asset. More participants taking risk means a more liquid physical market, which in turn creates robust reference prices for the financial market above it. Our overall thesis is that intelligence becomes a utility supplied by many vendors, that its cost becomes a variable buyers have to actively manage, and that managing it well requires a trusted reference price, standardized contracts, and a market to trade them in.\n\nLiquid Compute is a Y Combinator W25 company based in New York.", "url": "https://www.ycombinator.com/launches/PWz-liquid-compute", "votes": 142, "created_at": "2026-02-24T18:07:42.893Z" } ] }, { "id": 30277, "name": "ReJot", "slug": "rejot", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f75ba97279846098d21850986cc1298a5b21d9a0.png", "website": "https://rejot.dev", "all_locations": "Amsterdam, NH, Netherlands", "long_description": "ReJot is building Fragno to let API companies go from simply exposing an API to offering drop-in integrations that work out of the box.\r\n\r\nFragno is an open‑source framework for packaging backend endpoints, data storage patterns, and frontend utilities into reusable building blocks. API providers ship full integrations, not just low‑level SDKs and docs.\r\n\r\nCustomers configure rather than write code, so integrations are both much faster to launch and far more consistent across customers.", "one_liner": "We turn complex API integrations into drop‑in full‑stack libraries ", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1737760830, "tags": [ "Developer Tools", "API", "Infrastructure", "Databases" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2025", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "Netherlands", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/rejot", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/rejot.json", "year_founded": 2024, "city": "Amsterdam", "country": "NL", "linkedin_url": "https://www.linkedin.com/company/rejot/", "x_url": "https://x.com/ReJotSync", "fb_url": null, "cb_url": null, "github_url": "https://github.com/rejot-dev/", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/f75ba97279846098d21850986cc1298a5b21d9a0.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/68e338dd900d2b3b7d20081a394ee01f7ab156fd.png" ], "primary_partner": { "name": "Harj Taggar", "url": "https://www.ycombinator.com/people/harj-taggar" }, "founders": [ { "user_id": 2356635, "full_name": "Wilco Kruijer", "title": "Founder/CEO", "founder_bio": "CEO & Co-founder at ReJot, previously worked on a distributed financial platform at Adyen. Interested in the relation between distributed data and software maintainability.", "is_active": true, "linkedin_url": "https://linkedin.com/in/wilcokruijer/", "x_url": "https://twitter.com/WilcoKr", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c559d7b970c16e5775029a16c951070b472d676c.jpg" }, { "user_id": 2377112, "full_name": "Jan Schutte", "title": "Founder/CTO", "founder_bio": "CTO & Co-founder at ReJot, former Data Platform Engineer at Adyen, interested in distributed systems and database technologies. Current product is https://fragno.dev/", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jan-schutte-183145135/", "x_url": "https://x.com/Jan_Schutte", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5b79dd57e3e607f50dbdb4bce0ff2926a9e3da01.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 88081, "title": "ReJot - Enterprise Synchronization Engine", "tagline": "Sync engine to share data across engineering teams in enterprises", "body": "Hey everyone, we're Wilco & Jan, co-founders of ReJot! We're building a sync engine that helps big companies share data across engineering teams. We increase developer velocity and, most of all, ensure companies are not forced onto Kafka when they don't actually need event streaming.\n\n\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: \n\n![uploaded image](/media/?type=post&id=88081&key=user_uploads/2356635/98e4ff65-8266-448c-a2c9-637da1065625)\n\n", "url": "https://www.ycombinator.com/launches/Muf-rejot-enterprise-synchronization-engine", "votes": 84, "created_at": "2025-02-26T21:55:32.444Z" } ] }, { "id": 30284, "name": "Exla", "slug": "exla", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/94cd00784e37842fc455ee2fd7b22d487b0693cf.png", "website": "https://exla.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Exla is your 24/7 AI SRE agent. It reads your production logs, traces, and deploys, and holds full context on your codebase. It establishes a live baseline of normal behavior, so when something silently regresses, it catches the deviation immediately, pins it to the exact commit that caused it, and opens a fix PR. No paging a human at 3am, no digging through dashboards to find what changed.\r\n\r\nhttps://cal.com/exla-ai/schedule", "one_liner": "Building agents that reads logs and fixes issues on your behalf.", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1740012412, "tags": [ "Infrastructure", "AI" ], "tags_highlighted": [], "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/exla", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/exla.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/exla-corp", "x_url": "https://x.com/exla_ai", "fb_url": null, "cb_url": null, "github_url": "https://github.com/exla-ai", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/94cd00784e37842fc455ee2fd7b22d487b0693cf.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": 956313, "full_name": "Viraat Das", "title": "Founder/CEO", "founder_bio": "CEO @ Exla. Previously machine learning engineer @ Amazon.", "is_active": true, "linkedin_url": "https://linkedin.com/in/viraatdas", "x_url": "https://x.com/therealviraat", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9056f9785492560382fac9defa19f98d3b453cc6.jpg" }, { "user_id": 2212412, "full_name": "Pranav Nair", "title": "Founder/CTO", "founder_bio": "CTO at Exla. Previously an OS engineer at Apple leading sleep/hibernation for all Apple devices.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/pranavnair311/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/45b540ae3ca67482fd629d374168e25e3e74bb7a.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 88090, "title": "Exla – Run datacenter models on edge devices", "tagline": "Optimize models to run on edge devices (e.g. Jetsons) with 3-20x faster inference and 80% less memory requirements", "body": "Hey YC! We’re Viraat and Pranav – cofounders of Exla.\n\n![uploaded image](/media/?type=post&id=88090&key=user_uploads/2212412/6f2a4f23-207a-4ba8-84dd-1be1039c46f7)\n\n# **TL;DR**\n\nThe Exla SDK optimizes models for edge devices (e.g. NVIDIA Jetsons), **cutting memory usage by up to 80%, with 3-20x faster inference**. We’re focusing on optimizing and deploying **LLMs, VLMs, VLAs, and other CV models** on the edge.\\\n[Here’s Viraat showcasing our SDK](https://www.loom.com/share/d8fbb4faef87493c9806610fff6ff86c?sid=10b54831-159b-4157-95b7-8b9f7a5c8d8e)\n\n# **‼️ The Problem**\n\n**Frontier models are unlocking new applications on constrained edge devices** – Vision-Language Models in manufacturing defect detection, Vision-Language-Action Models to control robots via natural language, and LLMs to power in-car assistants are a few examples.\n\n**But these** **models are now shy of a _trillion_ parameters**, and with the emergence of inference-time scaling, **they are more computationally demanding than ever**. This limits their adoption to edge devices with beefy GPUs and sufficiently large VRAM, and even then, a Jetson Orin Nano Super is completely saturated attempting to run a 13B model, leaving little room for other tasks.\n\n# **🏎️ The Solution: The Exla SDK**\n\n**We’re building mixed-precision low-bit quantization software** to dramatically cut the compute footprint of these models, leading to **80% less memory usage, 3-20x faster inference**, and reduced energy consumption.\n\n**Today we’re starting with the Exla SDK** which applies our optimizations to a catalog of transformer-based and CV models, with growing support for your custom models. We’re primarily targeting deployment on NVIDIA Jetsons, followed by CPU-based platforms like Raspberry Pis and other embedded platforms.\n\n![uploaded image](/media/?type=post&id=88090&key=user_uploads/2212412/68c46641-ffb9-4dc9-a0a0-8facdba4e132)\n\nOur roadmap includes building custom silicon that takes advantage of the quirks of low bit compute – which we expect to bring in another order of magnitude in compute savings. _We’re bringing frontier models everywhere._\n\n# **🥷 The Team**\n\nWe met each other on the first day of college under questionable circumstances and have built several projects together since. Exla is the latest in that series!\n\n[Viraat](https://www.linkedin.com/in/viraatdas/) graduated in 2.5 years and joined Amazon as machine learning engineer, where he worked on building personalized search and infrastructure to optimize models. In a previous life, he used to marathon around the world. Now he marathons at home, coding.\n\n[Pranav](https://www.linkedin.com/in/pranavnair311/) previously worked at Apple as an OS engineer, hacking the iOS/macOS kernel to improve the sleep/wake experience for over a billion devices. In his non-existent free time, he tends to his 5 year old baby – an operating system he’s built from scratch.\n\n# **🙏 Our Ask!**\n\nPlease reach out to [**founders@exla.ai**](mailto:founders@exla.ai) if you’re facing issues optimizing your models on Jetsons, other edge devices, or on-prem deployments! We’re happy to onboard you to our private beta.\n\nWe’re particularly looking to solve model optimization at companies working on robotics, manufacturing & industrial automation, and camera-based systems – your help would make a world of difference <3", "url": "https://www.ycombinator.com/launches/Muo-exla-run-datacenter-models-on-edge-devices", "votes": 27, "created_at": "2025-02-27T01:55:49.203Z" } ] }, { "id": 30352, "name": "Monte", "slug": "monte", "former_names": [ "Fluidize" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/213b59f051867cd51ae0008db2962b11e76fd9f3.png", "website": "https://trymonte.ai", "all_locations": "San Francisco, CA, USA", "long_description": "Monte is an applied research lab building products for continual learning and recursive self-improvement for AI agents.", "one_liner": "Continual Learning for Agents", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1753994250, "tags": [ "Reinforcement Learning", "B2B", "Infrastructure", "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/monte", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/monte.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/monte-ai", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/213b59f051867cd51ae0008db2962b11e76fd9f3.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": 1442725, "full_name": "Henry Bae", "title": "Founder/CEO", "founder_bio": "Co-Founder @ Monte. He has an AB/SB/SM in Physics, CS, and Applied Math at Harvard.", "is_active": true, "linkedin_url": "https://linkedin.com/in/henrybae", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3a08df12c5c2e00192e906f21e47b8490974d058.jpg" }, { "user_id": 1874285, "full_name": "Alex Fleury", "title": "Founder/COO", "founder_bio": "Co-founder @ Monte | CS, statistics, AI research @ Harvard | 4 minute miler", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/victoralexfleury/", "x_url": "https://x.com/alexfleury160", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b8135fb60a6325f6bf506ca77edef9aaab45f366.jpg" }, { "user_id": 1599108, "full_name": "Jamin Liu", "title": "Founder", "founder_bio": "Co-founder @ Monte | CS & MCB @ Harvard", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jamin-liu-255277163", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/6a757051e43e5cee1744f246cd8ad8ca651d2b13.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "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.", "one_liner": "Agent identity and communication infrastructure", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1736800806, "tags": [ "Developer Tools", "B2B", "Email", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2025", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United Kingdom", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/artil", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/artil.json", "year_founded": 2025, "city": "London", "country": "GB", "linkedin_url": "", "x_url": "", "fb_url": null, "cb_url": null, "github_url": "https://github.com/artilai/", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/e50d8dfa254f692b3d51a22620ca8519141e9ed2.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Gustaf Alstromer", "url": "https://www.ycombinator.com/people/gustaf-alstromer" }, "founders": [ { "user_id": 626328, "full_name": "Alex Tkachenko", "title": "Founder/CEO", "founder_bio": "CEO at Artil. Previously founded Hashscan, blockchain analytics startup. Created Hodler, crypto portfolio tracker app (sold in 2022).", "is_active": true, "linkedin_url": "https://linkedin.com/in/alextcn", "x_url": "https://twitter.com/jackqack", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5a8afd23b084a0bd4885df51efd9f1c676d29ac4.jpg" } ], "jobs": [], "news": [], "launches": [ { "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 - .\n\n\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" }, { "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\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: \n\nLinkedIn: ", "url": "https://www.ycombinator.com/launches/Mu8-fira-agentic-ai-analyst", "votes": 35, "created_at": "2025-02-26T01:51:02.509Z" } ] }, { "id": 30366, "name": "Blaxel", "slug": "blaxel", "former_names": [ "Beamlit" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/daedc1e66e212180bb678c683cd4595f1c7cd149.png", "website": "https://blaxel.ai", "all_locations": "San Francisco, CA, USA", "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.", "one_liner": "The infrastructure for autonomous agents", "team_size": 12, "industry": "B2B", "subindustry": "B2B", "launched_at": 1745276338, "tags": [ "Developer Tools", "Cloud Computing", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2025", "status": "Acquired", "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/blaxel", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/blaxel.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/blaxel-ai", "x_url": "https://x.com/blaxelAI", "fb_url": null, "cb_url": null, "github_url": "https://github.com/blaxel-ai", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/daedc1e66e212180bb678c683cd4595f1c7cd149.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Nicolas Dessaigne", "url": "https://www.ycombinator.com/people/nicolas-dessaigne" }, "founders": [ { "user_id": 2156675, "full_name": "Paul Sinaï", "title": "Founder/CEO", "founder_bio": "Co-founder & CEO @ Blaxel - I'm a repeat entrepreneur; I founded two startups and sold the last one to the largest European cloud provider to become their analytics products suite. Currently, I'm working on an exciting project at Blaxel, where my team and I are focused on building the next generation of cloud for AI Agents. From the Infrastructure to the UX, we are redesigning the entire stack for the Agentic world.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/paul-sinai", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c42fc1b535157da171db617f8def74e699966dd2.jpg" }, { "user_id": 2458126, "full_name": "Charles Drappier", "title": "Founder", "founder_bio": "I'm a Co-founder & Developer at Blaxel, the AWS for AI Agents.\nI have 15 years of experience building cloud infrastructure products with a successful exit.\nAt Blaxel, we provide AI builders with the infrastructure they need to develop and scale intelligent agents efficiently.\nI'm focused on creating the essential technology backbone for the next generation of AI applications.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/charles-drappier-48017962/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/dcb8f7bffdf5d4ddfc22287d07f8e56740bae7a4.jpg" }, { "user_id": 2458128, "full_name": "Mathis Joffre", "title": "Founder", "founder_bio": "I’m the co-founder and engineering lead at Blaxel, where I’m building the infrastructure layer for AI agents. My background spans cloud systems, microVMs, and distributed compute — from designing next-gen architectures at OVHcloud and developing tooling across large-scale network environments. I’m focused on creating an AI-native platform that makes deploying and scaling agentic applications simple, reliable, and accessible to every developer.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/mathis-joffre-30992712a/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a994928802dcdb5bf5e7448208abba1a2fd22f19.jpg" }, { "user_id": 2264960, "full_name": "Nicolas Lecomte", "title": "Founder", "founder_bio": "Building Blaxel, the cloud for your AI agents.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/nicolas-lecomte-080317153/?locale=en_US", "x_url": "https://x.com/NicolasLec91112", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9d694e23f02fde3fc03c7bf36a07a04b5e434e7e.jpg" }, { "user_id": 2264607, "full_name": "Christophe Ploujoux", "title": "Founder/CTO", "founder_bio": "Addict software developper, with 8 years of experience at ForePaaS, where I contributed to launch a PaaS for Data and AI projects, I developed a deep understanding of building scalable platforms that empower innovation. \nThis experience inspired me to create Blaxel, an end-to-end platform for AI agents, aimed at simplifying the development, deployment and management of AI solutions for businesses. My passion lies in bridging complex technology with real-world applications, making advanced AI", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/christophe-ploujoux/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2fe3f4c8556189c150ab20e02a118d320c492d1a.jpg" } ], "jobs": [], "news": [ { "title": "Blaxel raises $7.3M seed round to build 'AWS for AI agents' after processing billions of agent requests | VentureBeat", "url": "https://venturebeat.com/ai/blaxel-raises-7-3m-seed-round-to-build-aws-for-ai-agents-after-processing-billions-of-agent-requests/", "date": "Jul 17, 2025" } ], "launches": [ { "id": 90942, "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 <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" } ] }, { "id": 30407, "name": "Golf", "slug": "golf", "former_names": [ "authed", "Authed", "authed", "Authed" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cb627188af8a389c044d02fc9024aae3ea05cdd3.png", "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.", "one_liner": "Agentic AI Security and Governance", "team_size": 1, "industry": "B2B", "subindustry": "B2B -> Security", "launched_at": 1745255607, "tags": [ "Developer Tools", "Security", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "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, "question_answers": null, "url": "https://www.ycombinator.com/companies/golf", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/golf.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/106327716", "x_url": "", "fb_url": null, "cb_url": null, "github_url": "https://github.com/golf-mcp", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/cb627188af8a389c044d02fc9024aae3ea05cdd3.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "David Lieb", "url": "https://www.ycombinator.com/people/david-lieb" }, "founders": [ { "user_id": 1366358, "full_name": "Wojciech Błaszak", "title": "Founder/CEO", "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.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/wojciech-błaszak11/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9a5daa1c44dcd87e2763d40b6840f93abec96904.jpg" }, { "user_id": 1313739, "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.", "is_active": true, "linkedin_url": "https://linkedin.com/in/antoni-gmitruk-80a268211", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2e0b52ea49b6bc7e7ceceb4127f248f43085852e.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 90569, "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" } ] }, { "id": 30432, "name": "HelixDB", "slug": "helixdb", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/64b0b8869e482d2c399a6856e5127933c31381bd.png", "website": "https://helix-db.com", "all_locations": "London, England, United Kingdom", "long_description": "As AI agents replace traditional software, they need a way to store, recall, and reason over contextual data. HelixDB gives them all of that in one system. We’re building the knowledge infrastructure every AI agent will depend on.", "one_liner": "The fastest & most scalable graph-vector database on the market", "team_size": 6, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1747978820, "tags": [ "Developer Tools", "Open Source", "Infrastructure", "AI", "Databases" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2025", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United Kingdom", "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/helixdb", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/helixdb.json", "year_founded": 2025, "city": "London", "country": "GB", "linkedin_url": "https://www.linkedin.com/company/helixdb/", "x_url": "https://x.com/helixdb", "fb_url": null, "cb_url": null, "github_url": "https://github.com/HelixDB/helix-db", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/64b0b8869e482d2c399a6856e5127933c31381bd.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 1342245, "full_name": "George Curtis", "title": "Founder/CEO", "founder_bio": "CEO & Co-Founder of HelixDB, a graph-vector database for building RAG.", "is_active": true, "linkedin_url": "https://linkedin.com/in/george-curtis-12b232a5", "x_url": "https://x.com/georgecurtiss", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/798e68bcfd436f7772a4c61133638d2dde6c0de4.jpg" }, { "user_id": 1335533, "full_name": "Xavier Cochran", "title": "Founder", "founder_bio": "The \"rust guy\". Building HelixDB.", "is_active": true, "linkedin_url": "https://linkedin.com/in/xaviercochran", "x_url": "https://x.com/xav_db", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3f8da8079cb678cdbf47207673bb3c7c705639db.jpg" } ], "jobs": [], "news": [ { "title": "Fondo | HelixDB Launches: The Database for RAG & AI", "url": "https://www.tryfondo.com/blog/helixdb-launches?utm_term=launchblogs-helix&utm_campaign=Launch%20Blogs&utm_content=334218246&utm_medium=social&utm_source=twitter&hss_channel=tw-1250676001727639553", "date": "May 29, 2025" }, { "title": "Build MCP AI Agents with NoCode PLUS: Native graph-vector database, Use MCP servers with Claude on web", "url": "https://www.theunwindai.com/p/build-mcp-ai-agents-with-nocode", "date": "Apr 14, 2025" } ], "launches": [ { "id": 90705, "title": "HelixDB - The database for RAG & AI", "tagline": "HelixDB is a graph-vector database that brings structure to your un-structured data for RAG and AI applications. ", "body": "Hi everyone 👋\n\nWe’re [George](https://www.linkedin.com/in/george-curtis-12b232a5/) and [Xav](https://www.linkedin.com/in/xaviercochran/) – co-founders of [HelixDB](https://www.helix-db.com)\n\n# TL;DR\n\n**HelixDB is an open-source graph-vector database that brings structure to your un-structured data for RAG and AI applications.**\n\n**_ASK:_** Can you introduce us to people/companies that are working on Graph/Hybrid RAG that could benefit from better performance or less overhead in their development cycles? Contact me at [george@helix-db.com](https://mailto:george@helix-db.com)\n\nhttps://youtu.be/V5viTRj2h68\n\n# ❌ The Problem\n\nAI is changing at a rapid rate which is fundamentally changing technology. This new tech **_needs_** new infrastructure.\n\nEveryone is trying to build AI applications, which often involve dedicated data retrieval for their specific use case. Building these retrieval systems is hard. Previously, we’ve relied solely on vector databases to retrieve semantic matches on tiny snippets of text data. But, this technology is shifting and is relying more heavily on connected data, which comes with better context.\n\nBut building these retrieval systems often involve:\n\n1. **Vector databases**\n2. **Graph databases**\n3. Bespoke **middleman/syncing** software\n\nThese setups are complicated, take a lot of time, engineering expertise, and create huge amounts of overhead which makes maintaining them very time consuming and expensive.\n\n# ✅ Our Solution\n\nHelixDB integrates semantic meaning (through its vector types) with relationships to other data (graph types), a similar model to how we structure information in our brains.\n\n![uploaded image](/media/?type=post&id=90705&key=user_uploads/1342245/468263b3-fb06-4efe-9352-4c30923c6d10)\n\nThis makes it the best solution for making AI retrieval engines for agents and LLMs.\n\nHow we currently do this:\n\n1. Seamlessly integrate **vector types** into your **knowledge graph**\n2. **Type-safe query language** that guides developers and agents to write correct queries before they are executed\n3. **Extreme speeds** outperforming industry leaders by 1-3 orders of magnitude\n\nHow we’re going to make it better:\n\n1. **MCP tools** that allow agents to walk the graph themselves, deciding at each step how to traverse the graph based on the schema and available data.\n2. Built-in **ingestion pipelines** for multi-modal data.\n3. Built-in **embedding-models** bringing immediate structure to your knowledge graph.\n\nTo get setup, follow the guide in our README:\\\n[HelixDB Github](https://github.com/helixdb/helix-db)\n\n# 🙏🏻 Our Ask\n\n* Can you introduce us to people/companies that are working on Graph/Hybrid RAG that could benefit from better performance or less overhead in their development cycles? Get them to [book a call](https://cal.com/georgec/30min) or email [george@helix-db.com](https://mailto:george@helix-db.com)\n* If you have a Github account, then [give us a star 🌟](https://github.com/HelixDB/helix-db)\n\nYour help and support makes a huge difference for this project. **Thank you!**", "url": "https://www.ycombinator.com/launches/Naz-helixdb-the-database-for-rag-ai", "votes": 160, "created_at": "2025-05-24T19:55:54.908Z" } ] }, { "id": 30449, "name": "Attune", "slug": "attune", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/8df0ce49cc11e96b09c8980da86ed900b39fe9dc.png", "website": "https://attunehq.com", "all_locations": "San Francisco, CA, USA", "long_description": "Attune makes blazingly fast build tools that require zero migration effort.\r\n\r\nAs AI enables developers to write code faster than ever, slow builds are increasingly becoming the bottleneck in development velocity. Developers regularly lose hours of productivity every day waiting for their builds. Imagine being able to write code in 1 minute, but needing to wait 30 minutes to compile, deploy, and test it.\r\n\r\nExisting solutions either require painful migrations to new tools (e.g. Bazel) or rely on just using bigger servers to run your builds. Instead, we do native, first-class integrations into compilers and build systems.\r\n\r\nWith Attune, you don't need to integrate a new tool. Just make a one-line change from `cargo build` to `hurry cargo build` for 20x faster builds.\r\n\r\nEliza (ex-Google) and Xin worked together for 3 years at FOSSA, where Eliza was Head of Engineering and Xin was Head of Product. Eliza brings a decade of programming languages and build systems expertise, while Xin brings a decade of experience building developer tools products, most recently as VP of Product at Teleport (S15). Having experienced the pain of slow builds firsthand across hundreds of production codebases, we're building the solution we've always wanted.", "one_liner": "Faster builds, zero effort.", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1747089464, "tags": [ "Developer Tools", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Spring 2025", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/attune", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/attune.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/attunehq", "x_url": "https://x.com/attunehq", "fb_url": null, "cb_url": null, "github_url": "https://github.com/attunehq", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/8df0ce49cc11e96b09c8980da86ed900b39fe9dc.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": 429685, "full_name": "Xin Ding", "title": "Founder/CEO", "founder_bio": "Xin is the cofounder and CEO of Attune.\n\nBefore Attune, Xin was the VP of Product at Teleport (S15), where he built the product and design teams. He helped scale the company to unicorn status and its new SaaS offering from 0 to 8-figures in ARR. Prior to that, he joined FOSSA at seed stage and scaled it from 0 to 8-figures in ARR. Xin has a proven track record of leading early-stage developer tools startups through hypergrowth phases by building products developers actually want to use.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/xinding3/", "x_url": "https://x.com/xinding33", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/27d43ba54caa28758ab512279cab9d31b56897e1.jpg" } ], "jobs": [ { "id": 78125, "title": "Founding Software Engineer", "url": "https://www.ycombinator.com/companies/attune/jobs/ZWLdtj8-founding-software-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Backend", "salary_range": "$150K - $200K", "equity_range": "0.50% - 1.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "Rust" ] } ], "news": [], "launches": [ { "id": 90363, "title": "Attune - Faster Builds, Zero Effort", "tagline": "Attune makes blazingly fast build tools that require zero migration effort.", "body": "Hey everyone, we’re Eliza and Xin, cofounders of Attune.\n\n# ⚡️ TL;DR\n\nAttune makes blazingly fast build tools that require zero migration effort. Built by developers with a decade of experience in build systems and developer tools.\n\nIf you or someone you know is suffering from slow builds, we’d love to help! \n\nContact us at [founders@attunehq.com](mailto:founders@attunehq.com).\n\n![uploaded image](/media/?type=post&id=90363&key=user_uploads/429685/31b348ca-dc4a-4649-8886-fc28ed78e37a)\n\n# ❌ The Problem\n\nAs AI enables developers to write code faster than ever, slow builds are increasingly becoming the bottleneck in development velocity. Developers regularly lose hours of productivity every day waiting for their builds. Imagine being able to write code in 1 minute, but needing to wait 30 minutes to compile, deploy, and test it.\n\nExisting solutions either require painful migrations to new tools (e.g. Bazel) or rely on just using bigger servers to run your builds.\n\n# ✅ Our Solution\n\nWe’re building drop-in replacements for existing build tools that dramatically speed up build times with zero migration effort. Simply prefix your existing build commands with hurry and get faster builds through incremental builds, remote execution, distributed caching, and a whole suite of other language-native and compiler-native optimizations.\n\nhttps://www.youtube.com/watch?v=DxM5Dj6ikVc\n\nFor example, instead of running cargo build, now you can run hurry cargo build for up to 20x faster builds.\n\nThat's it. No migration headaches, no complex configuration, and no learning a new tool and rewriting your build files.\n\nNow available for Rust, with Docker and additional language support launching soon.\n\n# 👷‍♀️👷‍♂️Our Team\n\nEliza (ex-Google) and Xin worked together for 3 years at FOSSA helping customers analyze and secure their build systems. Eliza was Head of Engineering and Xin was Head of Product. Eliza brings a decade of programming languages and build systems expertise, while Xin brings a decade of experience building developer tools products, most recently as VP of Product at Teleport (S15). We’ve seen the pain of slow builds firsthand across hundreds of production codebases, we're building the solution we've always wanted.\n\n# 🙏 Our Ask\n\nTired of waiting on builds? We'd love to show you how much time Attune can save your team.\n\nReach out to us at [founders@attunehq.com](mailto:founders@attunehq.com).", "url": "https://www.ycombinator.com/launches/NVT-attune-faster-builds-zero-effort", "votes": 49, "created_at": "2025-05-13T17:46:08.929Z" } ] }, { "id": 30464, "name": "Sixtyfour", "slug": "sixtyfour", "former_names": [ "Sixtyfour", "Sixtyfour AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7a94c5b6ca35db4a8ecda083bd02671f8be5393f.png", "website": "https://www.sixtyfour.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Sixtyfour deploys AI agents that investigate people and companies across the open and dark web, official records, proprietary databases, and unstructured sources. We resolve identities, map entity relationships, and surface risk signals for teams where data quality is essential.", "one_liner": "Intelligence Infrastructure on People and Entities", "team_size": 12, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1747432267, "tags": [ "B2B", "Enterprise Software", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Spring 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/sixtyfour", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/sixtyfour.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/sixtyfourai", "x_url": "https://x.com/sixtyfourai", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/7a94c5b6ca35db4a8ecda083bd02671f8be5393f.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "David Lieb", "url": "https://www.ycombinator.com/people/david-lieb" }, "founders": [ { "user_id": 804300, "full_name": "Saarth Shah", "title": "Founder/CEO", "founder_bio": "CEO @ Sixtyfour. Previously, engineering @ Whatnot (W20) and Deepgram AI (W16). UC Berkeley alum. Ex-Data Science Researcher @ Stanford Snyder & San Diego Supercomputer Center.", "is_active": true, "linkedin_url": "https://linkedin.com/in/saarthshah", "x_url": "https://x.com/saarth_", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ae314900a25755eb76714796bd4247b017213d5b.jpg" }, { "user_id": 937584, "full_name": "Christopher Price", "title": "Founder/COO", "founder_bio": "Cornell CS, AI CalHacks Winner, Prev @ Onyx (YC W24), Currently Building AI Agents for GTM", "is_active": true, "linkedin_url": "https://linkedin.com/in/christopher-price-59a24b178", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/bdefc2881870b21c12576e33f1c4f91751a59ee6.jpg" } ], "jobs": [ { "id": 105487, "title": "Growth Intern - Fall 2026", "url": "https://www.ycombinator.com/companies/sixtyfour/jobs/lPEgSOT-growth-intern-fall-2026", "location": "San Francisco, CA, US", "type": "Internship", "role": "Marketing", "role_type": null, "salary_range": "$30 - $50 / hourly", "equity_range": "", "experience": null, "visa": "US citizen/visa only", "skills": [] }, { "id": 112379, "title": "Product Marketing Lead", "url": "https://www.ycombinator.com/companies/sixtyfour/jobs/WR7Fp66-product-marketing-lead", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Marketing", "role_type": null, "salary_range": "$100K - $200K", "equity_range": "0.05% - 0.30%", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [], "launches": [ { "id": 102050, "title": "Sixtyfour - People Intelligence Infrastructure", "tagline": "Deploy thousands of AI agents to research any person or company.", "body": "👋 Hi, we're Saarth and Chris, co-founders of Sixtyfour (YC X25). \n\n\n\n**The problem**\n\nIn 2025-2026 alone, Texas, Nevada, Indiana, and New Jersey all sued Discord for failing to identify predators on the platform.\n\nAnonymous accounts on Polymarket made $2.4M with a 98% win rate on Iran war bets.\n\nOnur Aksoy ran 19 shell companies and 25 Amazon storefronts, selling $100M in counterfeit Cisco gear that ended up on US military aircraft.\n\nToday, teams that need to follow it (Trust & Safety, KYB, threat intel, due diligence) throw analyst teams at it. Still not trusting the answer after days or weeks of research. Not to mention it doesn't scale.\n\nBad actors slip through. People get harmed.\n\n**What we built** \n\nThe child predator's username. The scammer's banned accounts. The fraudster's shell company. \n\nAll of them leave a trail.\n\nImpossible to connect, but the trail was always there.\n\nOur agents have now made it possible to follow it.\n\nGive us one identifier (a name, email, phone number, username, or company name), and we deploy agents to recursively search the open web, dark web, social platforms, court records, and regulatory filings. Every signal is cross-referenced across thousands of sources. Every data point cited.\n\nCompanies using us today:\n\n* Cloaked uses us to uncover highly sensitive, hidden data about people, identifying attack vectors against their users.\n* TRM Labs uses us to attribute bad actors to real-world identities.\n* Airwallex uses us to screen counterparties for shell companies and AML risk.\n* Whatnot uses us to find qualified marketplace sellers that no platform can surface.\n* Surge, Turing, and Datacurve use us to source niche domain experts for AI training data.\n\nTo name a few.\n\n**Two ways to use it**\n\n1. App at [app.sixtyfour.ai](http://app.sixtyfour.ai)\n2. [API](https://docs.sixtyfour.ai/introduction) + [MCP](https://docs.sixtyfour.ai/developer-tools/mcp-setup) server to plug into Claude, Codex, Cursor, or your own stack\n\n\\\n**The numbers**\n\nIn the next couple of weeks, we’ll publicly release our benchmark results with independent validation from one of the world’s leading data labs.\n\nOur new deep people research system sets a new state-of-the-art, outperforming Gemini 3.1 Pro, Grok 4.20, GPT 5.4, Exa Deep Reasoning, and Parallel Ultra while running 3x faster than the closest competitor.\n\n![uploaded image](/media/?type=post&id=102050&key=user_uploads/804300/9d779b0d-a669-4606-991d-d7a595ab098e)\n\n\\\n**Our ask**\n\nWould really love Intros :) \n\n* Heads of Trust & Safety, \n* Fraud, AML, or KYB at marketplaces, banks, and fintechs \n* Heads of Risk and Threat Intel at cybersecurity teams \n* Heads of Talent and Recruiting at hypergrowth companies\n* Companies needing people and company data enrichment solutions\n\n\\\nReach out at [saarth@sixtyfour.ai](mailto:saarth@sixtyfour.ai)\n\nHiding just got harder. Try it now at [app.sixtyfour.ai](http://app.sixtyfour.ai).\n\nSaarth, Chris & the Sixtyfour team\n\n![uploaded image](/media/?type=post&id=102050&key=user_uploads/804300/b56fa1e1-efb9-4695-9e4f-d1af45d331dd)\n\n", "url": "https://www.ycombinator.com/launches/QXy-sixtyfour-people-intelligence-infrastructure", "votes": 21, "created_at": "2026-05-27T19:22:20.361Z" }, { "id": 90535, "title": "Sixtyfour - Bloomberg Terminal for sales", "tagline": "We help hypergrowth companies deploy custom research agents that map their TAM and surface real-time, tailored market signals.", "body": "Enterprise sales teams spend 50% of their time on research that misses the mark. Here's why — and how we're fixing it.\n\nHey everyone! We’re Saarth & Christopher – the founders of Sixtyfour. 👋\n\n**TL;DR**\n\nSixtyfour AI is the Bloomberg Terminal for sales. We work with hypergrowth companies to deploy custom research agents that map their Total Addressable Market and deliver real-time market signals, fully tailored to what matters most.\n\nCustomers like **Mercor**, **Traba**, **Hockeystack**, and **Conduit** use Sixtyfour to stay ahead of the curve.\n\n\n\n**🧠** **The Enterprise GTM Problem**\n\nIf you’re selling into a niche or regulated market ( health systems, manufacturing, fintech, govtech, and so on), you already know: generic data platforms don’t work.\n\nHere’s why:\n\n**💡 “Intent signals” are too broad**\n\nMost tools will tell you someone visited a pricing page. That’s not useful when you’re selling a $250K solution into a regional hospital network or a logistics hub in the Midwest.\n\n**🧱 The nuance is everything**\n\nEnterprise sellers ask real questions:\n\nDid that manufacturing facility just expand its fleet?\n\nDoes it have two or three parking bays?\n\nDid that nursing home file a new Medicare cost report?\n\nIs the new VP of Ops a better entry point than the outgoing admin director?\n\nThese are the signals that drive pipeline and predict fit, and no off-the-shelf platform can give you that.\n\n**🔍 Static filters can’t model your ICP**\n\nTry finding “companies that just adopted Drift, expanded their marketing team by 30%, and hired a new CRO in the past 90 days” in traditional tools. Impossible. Our agents live in that world\n\n**✨ The Sixtyfour Advantage**\n\nWe don’t sell contact lists. We build intelligence infrastructure for your GTM engine.\n\n**📍 Custom TAMs, always current**\n\nWe work with your team to define and continuously update your market using real-world, dynamic data — regulatory filings, facility attributes, staff movements, and even track infrastructure like parking lot size.\n\n**📡 Proprietary real-time signals**\n\nFrom Medicare cost report changes to decision-maker exits to new vendor adoption — we detect what matters to your team, as it happens.\n\n**🧠 Deployable custom ML models**\n\nHave internal data on close rates, deal velocity, or expansion triggers? We plug it in.\n\nWe can train and deploy custom ML models to estimate buyer readiness, ICP fit, churn risk, and more, directly tailored to your pipeline data.\n\n**🤖 Agents that think like your best rep**\n\nOur AI agents mirror your go-to-market motion, tracking, qualifying, and notifying you at the exact right time.\n\n**👥The Team**\n\nWe’re both repeat founders who have built and sold into complex markets.\n\nSaarth is a UC Berkeley Data Science grad and ex-Whatnot (YC W20), Deepgram (YC W16), and Stanford researcher. He built one of the earliest conversational AI agents (Dart) and has been shipping products since he was 10.\n\nChristopher, a Cornell dropout, led GTM at Onyx (YC W24) and built sales AI tools at Symbl. He’s a CalHacks AI winner and ex-analyst at Cornell Atkinson, with deep experience across AI, ops, and consumer tech.\n\nWe’ve lived the pain of building GTM systems by hand, and we’re building the platform we always wished existed.\n\n**👋 Our Ask**\n\n🏢 Know a GTM, RevOps, or sales leader at an enterprise or hypergrowth vertical SaaS company? Send them to [sixtyfour.ai](http://sixtyfour.ai) — we’d love to chat.\n\n💬 Frustrated with generic signals and shallow filters? Let’s build something that works for your team.\n\nEvery intro, share, and shoutout means the world. Thank you — we’re just getting started.\n\n![uploaded image](/media/?type=post&id=90535&key=user_uploads/804300/0c80ad45-4d97-43f6-8fed-9a5782416b19)\n\n", "url": "https://www.ycombinator.com/launches/NYF-sixtyfour-bloomberg-terminal-for-sales", "votes": 156, "created_at": "2025-05-19T22:27:28.413Z" } ] }, { "id": 30492, "name": "Prism", "slug": "prism", "former_names": [ "Prism AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/12dc6e609224f33b9c452f9656b3020116496003.png", "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": [ "Developer Tools", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2025", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/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", "x_url": "https://x.com/teamprismai", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/12dc6e609224f33b9c452f9656b3020116496003.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "David Lieb", "url": "https://www.ycombinator.com/people/david-lieb" }, "founders": [ { "user_id": 551584, "full_name": "Rajit Khanna", "title": "Founder/CEO", "founder_bio": "Founder @ Prism. Prev @ Greptile (YC W24), Skydio, Stripe (YC S09), and Blissway (YC S20).", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/rajitkhanna", "x_url": "https://x.com/rajitwrites", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/fa583ac735194f7bc43967d9a949e34ba9f55e8f.jpg" }, { "user_id": 557217, "full_name": "Alex Liu", "title": "Founder/CTO", "founder_bio": "CTO @ Prism. Prev engineering @ Palantir, AWS. Georgia Tech Alum", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/alexyliuswe", "x_url": "https://x.com/spicy_liu", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c8ecd63989b26ca5e6967aece51948172d712f42.jpg" } ], "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" } ], "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\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&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" } ] }, { "id": 30507, "name": "ParaQuery", "slug": "paraquery", "former_names": [ "Hypermorphic" ], "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": [ "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/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, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/023b1fec88d11ac0cc00d33e137188a1088f80f1.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": 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" } ], "jobs": [], "news": [], "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:  \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" } ] }, { "id": 30509, "name": "Boost Robotics", "slug": "boost-robotics", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4ab11f23c518bbbd560df743f85f60218829e65f.png", "website": "https://www.boostrobotics.ai", "all_locations": "Boston, MA, USA", "long_description": "Boost Robotics is building autonomous mobile manipulation robots to remotely perform manual tasks in data centers. \r\n\r\nThe surge in AI applications is pushing data centers to scale faster than they can manage, leading to suboptimal operations and staffing shortages amid rising power and compute demands.\r\n\r\nWe save data centers millions in insurance premiums and SLA violations by increasing the frequency of inspection and maintenance while reducing the time it takes to triage and address failures.", "one_liner": "Robots for the inspection and maintenance of data centers", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1748984174, "tags": [ "Hard Tech", "Hardware", "Robotics", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": [ { "question": "How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)", "answer": "We met as engineering school freshmen at Carnegie Mellon University in 2015, when we both joined the same competitive Bhangra dance team. Over the next 10 years, we have lived together, performed and won awards at Bhangra competitions, worked together in school projects, and both received separate robotics Master’s degrees from CMU’s Robotics Institute. In every context we have worked together, we have found ways to grow, overcome challenges, and succeed. We’re excited to take the next step with this venture." } ], "url": "https://www.ycombinator.com/companies/boost-robotics", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/boost-robotics.json", "year_founded": 2025, "city": "Boston", "country": "US", "linkedin_url": "https://linkedin.com/company/boost-robotics", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/4ab11f23c518bbbd560df743f85f60218829e65f.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/3e373405fcdb24fc612d085c8d27845b37501b94.png" ], "primary_partner": { "name": "Diana Hu", "url": "https://www.ycombinator.com/people/diana-hu" }, "founders": [ { "user_id": 973181, "full_name": "Hardik Singh", "title": "Founder/CEO", "founder_bio": "Co-Founder @ Boost Robotics.\n\nMS in Robotic Systems Development @ CMU Robotics Institute. Commencement speaker at CMU SCS Masters Ceremony.\n\nI've worked on nearly every robot you can think of: autonomous drones, rovers, tractors, hexapods, quadrupeds, and robot arms - both cobot and industrial.\n\nRobots are hard. Building a talented team greater than the sum of its parts is the only way to do it.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/hardiksingh", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a81e9e30f870f18ad982d9ab996528d35300c310.jpg" }, { "user_id": 2564407, "full_name": "Hans Kumar", "title": "Founder/CTO", "founder_bio": "Co-Founder at Boost Robotics. Previously at Boston Dynamics and Carnegie Mellon Robotics Institute. Eagles fan and Taco Bell fan.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/kumarhans/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/085ccf5a8fc02e387262789439bdd65ac582ed38.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 91007, "title": "Boost Robotics - Robots for the inspection and maintenance of data centers", "tagline": "Physical Agents for Digital Infrastructure", "body": "Hello!\n\nWe are [Hans](https://www.linkedin.com/in/kumarhans) and [Hardik](https://www.linkedin.com/in/hardiksingh) - longtime friends and co-founders of Boost Robotics.\n\n**TL;DR**\n\nBoost Robotics builds autonomous mobile manipulation robots that can inspect and physically interact with data center infrastructure.\n\nInstead of dispatching technicians for every cable check, reboot, or hardware swap, data centers can now triage and resolve issues through “robot remote hands”. When not performing interventions, the robots continuously provide 24/7 security monitoring and operational analytics.\n\nhttps://www.youtube.com/watch?v=SVqbUd1crU0\n\n🚨 **The Problem**\n\nAs AI infrastructure continues to scale up, data center physical operations are becoming increasingly difficult:\n\n* **Growth bottleneck:** AI demand is scaling faster than the operational capacity to support it.\n* **Increasingly Remote Locations:** Data centers are being built near cheaper power sources in sparsely populated areas—often with limited access to skilled labor.\n* **Competition:** Hyperscalers are looking for every possible edge. Downtime means SLA violations and lost revenue.\n* **Hazardous Environments:** Maintenance involves high-voltage power and toxic liquid coolants.\n\nNow more than ever, robots are gaining the dexterity and generality to solve these critical problems.\n\n🤖 **The Solution**\n\nWe are building a general purpose robot to handle a variety of use cases in data centers. \n\n* Predict, find, and solve issues faster, even when you’re not physically on-site. \n* Enable one skilled technician to debug multiple issues across multiple sites through context-aware teleoperation, and eventually autonomy.\n* Provide 24/7 security monitoring and inventory management, simplifying compliance and financial audits while collecting data for your data center digital twin models.\n\n**Early Renderings of our Robot**\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXfjbzl61UaeLu1lIocEDGGwIyFhxHWCF9OIaKZb85nQ4MS-muTqxZDodGZE1IyiKbf8Ryo1f5n_tcic5oV284i0IvnG_4D1V3X2lxolzUC32Nrc4yeRF1uAHrxs71tU3NEnXoT-2g?key=m-hLuOQB66mOy66_Sg1ptQ)\n\n**Bi-Manual Teleoperation of the Manipulation Subsystem**\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXdqZfjtJGw48PJmg0KUnARoJVCpa29xC7wyK_3JTD7SuCact7vXgAA9csNhLUSKxNknFKbE9xTIsr6Uk5qwVUXSLJdd2QuRUt8EiSbtaFKRofi4p9PJVw8_jp8WkYIMcyr5GwXk?key=m-hLuOQB66mOy66_Sg1ptQ)\n\n# **👥 The Team**\n\nWe met as engineering school freshmen at Carnegie Mellon University in 2015, when we both joined the same competitive Bhangra dance team. Over the next 10 years, we lived together, worked together in school projects, and both received Master’s degrees from CMU’s Robotics Institute. We always knew we would start a company together.\n\n![uploaded image](/media/?type=post&id=91007&key=user_uploads/2564407/f3defc57-762e-47f4-9bfa-4a346913346b)\n\nHardik was previously robotics team lead at an agtech startup where he pivoted the team to a new product and made sales within 1 month. He was selected as commencement speaker for the CMU School of Computer Science Masters ceremony by his professors in recognition of his leadership.\n\nHans was previously a Staff Software Engineer at Boston Dynamics, where he worked on productizing computer vision algorithms for the Spot inspection robot. Before that, he built GPS-denied drone autonomy at a startup and conducted legged robotics research at CMU’s Robotics Institute.\n\n**Our Ask**\n\nWe're actively seeking forward-thinking data centers to pilot our autonomous robotics platform at their facilities. \n\nReach out to us at [**founders@boostrobotics.ai**](mailto:founders@boostrobotics.ai) — let’s shape the future of data center operations together.\n\n![uploaded image](/media/?type=post&id=91007&key=user_uploads/2564407/6f2eb4dc-5340-46dc-a264-fdf00f57c8ce)\n\n", "url": "https://www.ycombinator.com/launches/Nfr-boost-robotics-robots-for-the-inspection-and-maintenance-of-data-centers", "votes": 73, "created_at": "2025-06-04T02:59:25.110Z" } ] }, { "id": 30522, "name": "Naïve", "slug": "naive", "former_names": [ "Relixir.ai", "Relixir", "Naive", "Naïve", "naïve" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4a69089a2a0c9f75ef6115c3f5aebf4d621f71e8.png", "website": "https://usenaive.ai", "all_locations": "San Francisco, CA, USA", "long_description": "Naïve is an AI research lab building autonomous companies.\r\n\r\nWe develop the systems, environments, and agent infrastructure required for AI to operate real businesses end-to-end, then release increasingly capable autonomous companies into the world.", "one_liner": "Autonomous Company Infrastructure", "team_size": 8, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1747424808, "tags": [ "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Spring 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/naive", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/naive.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/usenaive", "x_url": "https://x.com/usenaive", "fb_url": null, "cb_url": null, "github_url": "https://github.com/usenaive", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/4a69089a2a0c9f75ef6115c3f5aebf4d621f71e8.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Andrew Miklas", "url": "https://www.ycombinator.com/people/andrew-miklas" }, "founders": [ { "user_id": 1529804, "full_name": "Sean Dorje", "title": "Founder/CEO", "founder_bio": "CEO & Co-founder @ Naïve", "is_active": true, "linkedin_url": "https://linkedin.com/in/seandorje", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e22bccfe197969399138294cea78e04d8fe4bae2.jpg" }, { "user_id": 994977, "full_name": "Dennis Zax", "title": "Founder/CTO", "founder_bio": "Co-Founder & CTO of Naïve", "is_active": true, "linkedin_url": "https://linkedin.com/in/dennis-zax-704165201", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/bf845ab98fee993395800b81815d4a89bb4e4ae5.jpg" } ], "jobs": [ { "id": 110960, "title": "Founding Growth Engineer", "url": "https://www.ycombinator.com/companies/naive/jobs/rpnVz7a-founding-growth-engineer", "location": "Mountain View, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$130K - $180K", "equity_range": "2.00% - 4.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 110961, "title": "Founding Product Engineer", "url": "https://www.ycombinator.com/companies/naive/jobs/CGCujyp-founding-product-engineer", "location": "Mountain View, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$150K - $200K", "equity_range": "2.00% - 4.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "Python", "TypeScript", "Next.js" ] }, { "id": 110962, "title": "Founding Member of Technical Staff — RL", "url": "https://www.ycombinator.com/companies/naive/jobs/OTnFKjw-founding-member-of-technical-staff-rl", "location": "Mountain View, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$190K - $225K", "equity_range": "2.00% - 4.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "Python", "LLMs", "AI Agents" ] }, { "id": 110963, "title": "Founding Member of Techincal Staff - Agents", "url": "https://www.ycombinator.com/companies/naive/jobs/qOwzkq2-founding-member-of-techincal-staff-agents", "location": "Mountain View, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$190K - $225K", "equity_range": "2.00% - 4.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "AI Agents" ] }, { "id": 112022, "title": "Growth Engineer Intern", "url": "https://www.ycombinator.com/companies/naive/jobs/cDWbl15-growth-engineer-intern", "location": "Mountain View, CA, US / Remote (US)", "type": "Internship", "role": "Engineering", "role_type": "Full stack", "salary_range": "$6K - $10K / monthly", "equity_range": "", "experience": null, "visa": "US citizen/visa only", "skills": [] }, { "id": 115481, "title": "In-House Video Editor", "url": "https://www.ycombinator.com/companies/naive/jobs/MZLbwFK-in-house-video-editor", "location": "Remote (US)", "type": "Contract", "role": "Marketing", "role_type": null, "salary_range": "$5K - $10K / monthly", "equity_range": "0.50%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [ { "title": "Naïve raises $28.5M to automate the grunt work of setting up and running a company | TechCrunch", "url": "https://techcrunch.com/2026/08/06/naive-raises-28-5m-to-automate-the-grunt-work-of-setting-up-and-running-a-company/", "date": "Aug 06, 2026" } ], "launches": [ { "id": 98930, "title": "Naive - Hire Autonomous Employees that actually run your company.", "tagline": "Describe your business. Naive runs it. ", "body": "\\\n\\\nNaïve is an autonomous company runtime. \\\n\\\nYou describe your business — or connect your existing one — and Naïve deploys AI employees that actually execute.\n\n1. Our employees have their own identity. Own bank account, own email, own credentials, own compute. \n2. They sign up for tools, pay for services, deploy apps, and file documents as themselves. No human in the loop.\n3. They learn recursively. Every output, every result gets stored. They extract patterns about YOUR business and compound performance week over week.\n\n**New companies** — describe what you want, Naïve builds and runs it. \\\n\\\n**Existing companies** — one-click connect your stack (CRM, codebase, Shopify, Notion, whatever), Naïve employees plug in day one.\\\n\\\n**Get Started for FREE + YC Deal**\\\n\\\nFree to get started, pay as you go.\\\nWe also have a YC deal! \n\n[usenaive.ai](http://usenaive.ai)\\\n$100 Off for YC Alum: ", "url": "https://www.ycombinator.com/launches/Pje-naive-hire-autonomous-employees-that-actually-run-your-company", "votes": 7, "created_at": "2026-03-19T20:33:57.095Z" } ] }, { "id": 30605, "name": "Dedalus Labs", "slug": "dedalus-labs", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7090c5a2d73a4c3057030995d02dc87abae964a5.png", "website": "https://www.dedaluslabs.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Dedalus Labs builds persistent compute for AI agents. Our flagship product, Dedalus Machines, gives agents isolated computers where they can run software, keep files and state, and do useful work over time.\r\n\r\nWe build across virtualization, distributed storage, networking, scheduling, and orchestration. Our goal is to make persistent compute dependable and straightforward to use through APIs and developer tools, so developers can build agents that work with real software and maintain a working environment across sessions.", "one_liner": "Persistent computers for AI agents", "team_size": 8, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1756399069, "tags": [ "Developer Tools", "DevOps", "Cloud Computing", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 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/dedalus-labs", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/dedalus-labs.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/dedalus-labs", "x_url": "https://x.com/dedaluslabs", "fb_url": "https://www.facebook.com/dedaluslabs", "cb_url": "https://www.crunchbase.com/organization/dedalus-labs", "github_url": "https://github.com/dedalus-labs", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/7090c5a2d73a4c3057030995d02dc87abae964a5.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/54c7bc34d7f644f26f4d2fb8aea33cfc23d4684b.png", "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/16c9af42d9adfb160dd3a15005b124edb50fd1fc.png" ], "primary_partner": { "name": "Jared Friedman", "url": "https://www.ycombinator.com/people/jared-friedman" }, "founders": [ { "user_id": 2684979, "full_name": "Cathy Di", "title": "Founder/CEO", "founder_bio": "Let us build the wings\n so your agents can fly 🪽", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/cathydi", "x_url": "https://x.com/itsCathyDi", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e6105f830d0c2b1243019fb14c0f57b4130c8298.jpg" }, { "user_id": 1126811, "full_name": "Windsor Nguyen", "title": "Founder/CTO", "founder_bio": "Moving electrons really fast.", "is_active": true, "linkedin_url": "https://linkedin.com/in/windsornguyen", "x_url": "https://x.com/WindsorNguyen", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5dc47e2245af96f7a157a8480c9a6f536a01ab2e.jpg" } ], "jobs": [ { "id": 107466, "title": "Systems Engineer", "url": "https://www.ycombinator.com/companies/dedalus-labs/jobs/694An25-systems-engineer", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$120K - $250K", "equity_range": "0.50% - 1.00%", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [] }, { "id": 107469, "title": "Infrastructure Engineer Intern", "url": "https://www.ycombinator.com/companies/dedalus-labs/jobs/012beI1-infrastructure-engineer-intern", "location": "San Francisco", "type": "Internship", "role": "Engineering", "role_type": "Full stack", "salary_range": "$7.8K - $8.67K / monthly", "equity_range": "", "experience": null, "visa": "US citizen/visa only", "skills": [] }, { "id": 107661, "title": "Systems Engineer Intern", "url": "https://www.ycombinator.com/companies/dedalus-labs/jobs/EQcMolJ-systems-engineer-intern", "location": "San Francisco", "type": "Internship", "role": "Engineering", "role_type": "Full stack", "salary_range": "$7.8K - $8.67K / monthly", "equity_range": "", "experience": null, "visa": "US citizen/visa only", "skills": [] }, { "id": 112907, "title": "Software Engineer, Infrastructure & Performance", "url": "https://www.ycombinator.com/companies/dedalus-labs/jobs/KSsPCqY-software-engineer-infrastructure-performance", "location": "San Francisco", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$120K - $250K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [] } ], "news": [ { "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" }, { "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/", "date": "Sep 15, 2025" }, { "title": "The 9 most sought-after startups from YC Demo Day | TechCrunch", "url": "https://techcrunch.com/2025/09/15/the-9-most-sought-after-startups-from-yc-demo-day/", "date": "Sep 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", "date": "Aug 28, 2025" } ], "launches": [ { "id": 94675, "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. 🪽", "url": "https://www.ycombinator.com/launches/Od1-dedalus-labs-build-deploy-complex-agents-in-5-lines-of-code", "votes": 23, "created_at": "2025-10-15T18:10:39.053Z" } ] }, { "id": 30610, "name": "TraceRoot.AI", "slug": "traceroot-ai", "former_names": [ "TraceRoot.ai" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fc86727a443ac448343eba0a5ce27b88d63b2f8f.png", "website": "https://traceroot.ai", "all_locations": "San Francisco, CA, USA", "long_description": "TraceRoot is the open-source AI agent improvement platform. Turn production traces into actionable feedback and evals, closing the improvement loop with your coding agent.", "one_liner": "Open Source AI Agent Improvement Platform", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1753318246, "tags": [ "Developer Tools", "Open Source", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2025", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "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/traceroot-ai", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/traceroot-ai.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/traceroot-ai", "x_url": "https://x.com/TracerootAI", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/traceroot", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/fc86727a443ac448343eba0a5ce27b88d63b2f8f.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": 2543076, "full_name": "Xinwei He", "title": "Founder/CEO", "founder_bio": "Founder and CEO at TraceRoot.AI.\nPrev. Research Scientist at Meta & Founding Engineer at Kumo.AI (Forbes 50 AI).\nStanford CS, published in top conferences including ICLR, NeurIPS, KDD.\nOSS Core Contributor: PyTorch Geometric.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/xinwei-he-586512134/", "x_url": "https://x.com/xinwei_97", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1eae779e9c1f7189e53a1571f16176084a99ea06.jpg" } ], "jobs": [ { "id": 84777, "title": "Founding Engineer", "url": "https://www.ycombinator.com/companies/traceroot-ai/jobs/xLdkDw5-founding-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$120K - $220K", "equity_range": "0.50% - 2.00%", "experience": "3+ years", "visa": "Will sponsor", "skills": [ "Node.js", "Python", "React", "TypeScript" ] }, { "id": 86084, "title": "Software Engineering Intern", "url": "https://www.ycombinator.com/companies/traceroot-ai/jobs/RCbNRRq-software-engineering-intern", "location": "San Francisco, CA, US / Remote", "type": "Internship", "role": "Engineering", "role_type": "Full stack", "salary_range": "$4K - $8K / monthly", "equity_range": "", "experience": null, "visa": "Will sponsor", "skills": [ "Node.js", "Python", "React", "TypeScript" ] }, { "id": 103799, "title": "Founding GTM", "url": "https://www.ycombinator.com/companies/traceroot-ai/jobs/9JpJdnw-founding-gtm", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$100K - $140K", "equity_range": "0.25% - 1.00%", "experience": "1+ years", "visa": "Will sponsor", "skills": [ "Python", "SQL", "Data Analytics", "Growth design", "Marketing design" ] }, { "id": 105076, "title": "Developer Marketing Intern", "url": "https://www.ycombinator.com/companies/traceroot-ai/jobs/dk1ep2K-developer-marketing-intern", "location": "San Francisco, CA, US / Remote (US; CA)", "type": "Internship", "role": "Marketing", "role_type": null, "salary_range": "$4K - $6K / monthly", "equity_range": "", "experience": null, "visa": "Will sponsor", "skills": [ "Python", "SQL", "Data Analytics", "Growth design", "Marketing design" ] } ], "news": [], "launches": [ { "id": 92809, "title": "TraceRoot - Open source AI agents that automatically fix your production bugs", "tagline": "We help engineering teams fix production bugs faster using AI agents.", "body": "# TL;DR\n\nTraceRoot is an open-source debugging platform that helps engineers fix production issues faster by using AI agents that intelligently leverage structured context - including traces, logs, metrics, source code, GitHub PRs, issues, and Slack threads to analyze and resolve bugs efficiently.\n\nOur SDK just crossed 10,000 downloads and engineering teams are using our product to monitor, debug, and improve visibility for their production systems.\n\nhttps://www.youtube.com/watch?v=I9fjV_9dM-4\n\n# Our Story\n\nWe’re Stanford-trained engineers and ex-builders from [Kumo.AI](http://Kumo.AI) (Forbes AI 50), Meta Platforms, and AWS, where we fixed 300+ production bugs and experienced firsthand how painful debugging can be in distributed systems. It was so painful that we quit our jobs to solve this problem and [open-sourced](https://github.com/traceroot-ai/traceroot) it!\n\n# The Problem\n\nDebugging production issues today is a mess. Here's what happens:\n\n* You spot an error during release or in production. You open Grafana, check logs, jump to GitHub, scroll Slack, and try to piece things together.\n* Sharing findings? It’s a chain of screenshots, links, and DMs - super painful.\n* It takes engineers hours even days to fix a production bug.\n* Meanwhile, you're drowning in 10+ P0 bugs across multiple releases, and customers won’t stop pinging you on Slack.\n\n# Our Solution\n\nWe built TraceRoot, an agentic debugging platform that ties all your context together and helps your team get to the root cause.\n\n* AI agents automatically summarize the issue and trace logs, spans, and GitHub context into a single execution tree. Ask the agent any question you want to debug.\n* Once the issue is understood, generate GitHub issues or draft PRs directly from the platform.\n* Visual trace explorer that lets you zoom into log clusters, suspicious spans, and trace paths. You can guide the agent by selecting spans or contexts to focus on.\n\n![uploaded image](/media/?type=post&id=92809&key=user_uploads/2543076/7af84b17-1836-4743-9590-dcdd3e862b8e)\n\n# The Ask\n\nIf you're stuck vide-coding through bugs or if your team spends a significant amount of engineering time fixing production issues. We’d love to help!\n\nGive our product a try! Schedule a meeting at https://cal.com/traceroot/30min or email us at [founders@traceroot.ai](mailto:founders@traceroot.ai)\n\n![uploaded image](/media/?type=post&id=92809&key=user_uploads/2543076/5670184a-7bc0-4f39-994e-1e9a297106c7)\n\n", "url": "https://www.ycombinator.com/launches/O8v-traceroot-open-source-ai-agents-that-automatically-fix-your-production-bugs", "votes": 27, "created_at": "2025-08-07T06:27:04.705Z" } ] }, { "id": 30620, "name": "Bidflow", "slug": "bidflow", "former_names": [ "Playdo.ai", "Ghostship" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fb5bdff2af780675e7950b4a0fb5dcad2dfdc802.png", "website": "https://usebidflow.com", "all_locations": "New York City, NY, USA", "long_description": "We use AI to help electricians speed up the time it takes to submit a competitive bid to a job. We do this by scanning complex CAD drawings and 10X-ing the time it takes to estimate a job. This involves using vision models to read and count complex symbols in large PDFs, which typically take hours (sometimes days) to do precisely. Every missed symbol can cost thousands, and our AI can count to 99% accuracy.", "one_liner": "AI Takeoffs for Electrical", "team_size": 2, "industry": "Real Estate and Construction", "subindustry": "Real Estate and Construction -> Construction", "launched_at": 1754285936, "tags": [ "SaaS", "Computer Vision", "Construction", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2026", "status": "Active", "industries": [ "Real Estate and Construction", "Construction" ], "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/bidflow", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/bidflow.json", "year_founded": 2025, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/110460044", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/fb5bdff2af780675e7950b4a0fb5dcad2dfdc802.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/2ccef533b872120f2c409dfa7281f478dc5d02ff.png" ], "primary_partner": { "name": "Ankit Gupta", "url": "https://www.ycombinator.com/people/ankit-gupta" }, "founders": [ { "user_id": 1512811, "full_name": "Jesse Choe", "title": "Founder/CEO", "founder_bio": "College dropout. Building AI software for electrical contractors.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jc10/", "x_url": "https://x.com/jesse_choe10", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/df7d3df3631ef86be1acce92e6aa46ae90ba4344.jpg" }, { "user_id": 2694876, "full_name": "Gautham Ramachandran", "title": "Founder/CTO", "founder_bio": "taking care of change orders", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/gautham-ramachandran-74b5712a4/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7f61fd9ece592bdfecd3b2104c37e873db832e7d.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 96918, "title": "Bidflow - AI Copilot for Electrical Estimating", "tagline": "We use AI to help electricians compete for 4x more contracts", "body": "Hi!\n\nWe’re [Jesse](https://www.linkedin.com/in/jc10/) and [Gautham](https://www.linkedin.com/in/gautham-ramachandran-74b5712a4/), and we’re building [Bidflow](https://usebidflow.com/) to help electricians bid on more jobs. Bidflow is an AI copilot that helps electrician companies sift through tedious documents and automate the repetitive work that goes into quoting a job.\n\nAsk: Do you know any electrical contractors? If so, introduce us at [founders@tryghostship.dev](mailto:founders@tryghostship.dev) or [book a demo with us](https://calendly.com/jessechoe10/demo-with-bidflow).\n\n# The Problem\n\nElectrical estimating - the process of figuring out how much an electrical construction project will cost is super tedious and can take anywhere from a few hours to months. Imagine reading through 500-page PDFs, counting hundreds of small symbols per page on 50 pages of complicated circuits, and manually entering thousands of numbers on slow, legacy software.\n\nElectrical estimators do this process everyday but manually, and most of the time, they lose the job by a small margin. Estimating is the only way electrical contractors make revenue, and they do it manually because one mistake can cost thousands of dollars and they need to be careful!\n\n# Our Solution\n\nBecause estimating is such a careful process, electrical contractors still do everything manually, especially because AI is hard to trust. That’s why we built Bidflow - an AI copilot for electrical estimating that serves as an assistant not a replacement.\n\nBidflow is designed with context to think like an electrician and most importantly, show the estimator “proof of work”, turning the estimators job more into reviewing the AI’s mistakes. We’re able to process all of your project documents and save you time in reading through hundreds of pages of fine print.\n\nBidflow also has the same features as the legacy softwares these estimators use, but it combines everything together, making it an all-in-one platform that also saves estimators time switching between the softwares.\n\n\n\n### Our Team\n\nWe decided to target electrical contractors because we both have family in the industry who’ve complained about how slow work has been. We then decided to go door-to-door in the Bay Area and got our first design partner.\n\nJesse (CEO, right) - **Top 1%** competitive coder in the US; **Jane Street** extern. Gautham (CTO, left) - Bootstrapped to **$120K** at **16**.\n\n![uploaded image](/media/?type=post&id=96918&key=user_uploads/1512811/3c223688-5b55-49b7-b1bf-e08439b4b1e4)\n\n### Why Now?\n\nConstruction is picking up in the United States, and the demand for electrical work is going up due to the data center boom. New data centers are being built left and right, meaning there’s a lot of electrical construction projects in the market. A huge boost in estimating efficiency would give the faster electrical contractors a huge advantage in winning jobs, and with AI agents getting better now more than ever, now is the time to bring AI into the electrical estimating workforce.", "url": "https://www.ycombinator.com/launches/PDC-bidflow-ai-copilot-for-electrical-estimating", "votes": 16, "created_at": "2026-01-19T04:48:20.442Z" }, { "id": 92813, "title": "Ghostship - QA agents to find bugs in your product", "tagline": "Ghostship helps you 10x your UX by catching bugs before production.", "body": "Hey guys! \n\nWe're [Jesse](https://x.com/jesse_choe10) and [Gautham](https://x.com/TheGauthamRam), and we're building [Ghostship](https://tryghostship.dev/?utm_source=yc&utm_medium=launch&utm_campaign=yc_s25) to help you never ship a bug again. Ghostship spins up AI agents to find bugs in your product by crawling through your interface and simulating users.\n\nAsk: Do you care about shipping a good user experience? You definitely should and if so, email us at [founders@tryghostship.dev](mailto:founders@tryghostship.dev) or [book a demo with us](https://calendly.com/jessechoe10/demo-with-ghostship-yc-s25).\n\n# The Problem\n\nTo grow quickly, you probably rush shipping new features, which often introduces bugs and causes customer churn. Current solutions like manual testing is expensive and slow and automated testing is flaky.\n\n# Our Solution\n\nImagine a QA team of 5,000 testers available 24/7 on every new feature you ship. That's Ghostship, but we use AI agents. \n\nOur agents will crawl through your product and interact with it like users would to find the bugs (especially edge cases) that lead to churn—all at a fraction of the cost.\n\nHere’s a demo video of our product:\n\nhttps://youtu.be/THa43hQMDEU\n\nOur Team\n\n**TL;DR: We are competitive programmers that never finished college, so we're all in on Ghostship.**\n\nJesse (CEO, right) - Jesse was a **top 1%** competitive coder in the US and was the **first high schooler** to write competitive coding questions. He was a **Jane Street** intern at **18** before dropping out.\n\nGautham (CTO, left) - Gautham was a **top 5%** competitive coder in the US. He also has 3 preprints related to **reinforcement learning** in the **ICML** conference and bootstrapped his way to **$120K** at **16**.\n\n![uploaded image](/media/?type=post&id=92813&key=user_uploads/1512811/b271ce7f-ac3f-465c-95b6-0fe28b05a408)\n\nBoth of us have been developers for more than half our lives, and we've experienced the pain of shipping bugs throughout our lives. We want to solve this problem once and for all, and make developers' lives way easier.\n\n# Our Ask\n\n\\- Follow us on [LinkedIn](https://www.linkedin.com/company/ghostship), [X](https://x.com/ghostship_ai), and [book a demo](https://calendly.com/jessechoe10/demo-with-ghostship-yc-s25) with us.\n\n\\- **Share this post!** - If you know any startup founders who are having trouble with growth due to technical debt or product people (PMs, QAs, etc.) at larger companies who care about shipping quality, please share this post with them.\n\n\\- Visit [our website](https://tryghostship.dev/) for more info.", "url": "https://www.ycombinator.com/launches/O8z-ghostship-qa-agents-to-find-bugs-in-your-product", "votes": 132, "created_at": "2025-08-07T19:28:30.592Z" } ] }, { "id": 30623, "name": "Playgent", "slug": "playgent", "former_names": [ "Pharmie AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/5ad8d62052816b9ab3349fc92ba2137b2b1edb02.png", "website": "https://useplaygent.com", "all_locations": "San Francisco, CA, USA", "long_description": "When enterprise agents fail in production, the conditions that caused the failure are critical: user state, data, tool calls, and context. Without a way to recreate these conditions, teams can't fix what broke.\r\n\r\nPlaygent provides infrastructure to create high-fidelity sandbox environments for AI agents. Our environments come packaged as a single MCP url where tool calls are mocked, authentication is abstracted away, and test data can be initialized via natural language or JSON specifications.\r\n\r\nTeams can use Playgent to reproduce production failures in safe, scoped environments that accurately reconstruct state. Finally, export runs as OTel traces from Playgent's environment to plug directly into your observability tools or RL pipelines.", "one_liner": "Sandboxes for AI agents", "team_size": 2, "industry": "Healthcare", "subindustry": "Healthcare -> Healthcare IT", "launched_at": 1754457298, "tags": [ "SaaS", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2025", "status": "Active", "industries": [ "Healthcare", "Healthcare IT" ], "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/playgent", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/playgent.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/useplaygent", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/5ad8d62052816b9ab3349fc92ba2137b2b1edb02.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Tyler Bosmeny", "url": "https://www.ycombinator.com/people/tyler-bosmeny" }, "founders": [ { "user_id": 2671843, "full_name": "Neer Jain", "title": "Founder/CEO", "founder_bio": "Hey I'm Neer, cofounder of Playgent. We're building an Sandboxes for Agents!\n\nIn college, I studied Math, Business, and CS at UT Austin and worked in product and engineering roles at multiple early stage AI startups. At Visa, I launched features used by thousands of banks and built internal tools.\n\nFeel free to reach out -- neer@useplaygent.com", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/neer-jain/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/27de95e4ccb8ea8f4a00c5acf84b72064dbd0cdd.jpg" }, { "user_id": 969465, "full_name": "Aniruddh Sriram", "title": "Founder/CTO", "founder_bio": "Hi! I’m Aniruddh - co-founder of Playgent! We are building sandboxes for AI agents. I did 4 years of NLP research with publications in EMNLP/ACL and was on-route to pursue a PhD when I decided to join YC.\n\nIn my free time, I like writing articles on Medium, playing basketball, and doing acrylic art.\n\nYou can reach me at aniruddh@useplaygent.com!", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/aniruddh-sriram/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f137d83046edc10cc83d2700771d9c031fb2cbfa.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 92806, "title": "Pharmie AI - Your AI Pharmacy Technician", "tagline": "AI voice/text agents that handle pharmacy admin so staff don’t have to", "body": "We’re excited to share Pharmie, an AI assistant for pharmacists. Check out our [launch video](https://youtu.be/pFKd8YJ6vsQ) and [website](https://www.pharmie.app/)!\n\n**The Problem**\n\nPharmacies are overwhelmed with phone calls about refills, insurance questions, chasing doctors, and handling appointment logistics. This nonstop volume creates constant interruptions, forcing pharmacists and technicians to multitask and context-switch throughout the day. As a result, staff burn out quickly, turnover is high, and time is lost retraining replacements.\n\n**What’s Pharmie?**\n\n**Pharmie is your always-on AI pharmacy assistant.** It never gets tired, works autonomously, and plugs directly into your pharmacy management system to streamline communication and boost efficiency.\n\nPharmie can:\n\n* **Answer inbound calls 24/7:** no more missed calls or hold times\n* **Process refills, transfers, and appointments:** fully automated, no staff intervention needed\n* **Verify insurance and handle patient questions:** from copays to medication availability\n* **Upsell pharmacy services:** intelligently offers vaccines, delivery, or sync programs based on the conversation and patient history\n\n**How It Works**\n\nPharmie seamlessly integrates with your existing pharmacy management system (PMS) to automate phone calls, refills, and patient communication.\n\nDuring onboarding, we work closely with you to:\n\n* Connect to your PMS or set up secure workflows if a direct integration isn’t available\n* Give Pharmie pharmacy-specific information like store hours, address, staff names, services offered, and policies\n* Train Pharmie on your workflows (e.g. how you handle refills, transfers, insurance, and voicemails)\n* Customize messaging for promotions, vaccine reminders, and targeted outreach campaigns\n* Set up call routing and escalation rules to transfer to your team when needed\n\nWe’re already in production at 4 locations, cutting phone volume by 70% and helping teams focus on patient care instead of call chaos.\n\n**The Team**\n\nAniruddh and Neer met freshman year of high school and instantly bonded over their love for math and science. Since then, they’ve worked on all types of projects together from personal gadgets to sophisticated sports betting models that generated 6-figure profit.\n\n![uploaded image](/media/?type=post&id=92806&key=user_uploads/2671843/472d3c8e-7a05-494f-8149-e7fdd21b5942)\n\nIf you know a pharmacist or work with pharmacies, shoot us a message at [**founders@pharmie.app**](mailto:founders@pharmie.app)", "url": "https://www.ycombinator.com/launches/O8s-pharmie-ai-your-ai-pharmacy-technician", "votes": 43, "created_at": "2025-08-07T00:47:21.168Z" } ] }, { "id": 30625, "name": "LLM Stats", "slug": "llm-stats", "former_names": [ "ZeroEval", "CallingBox" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3a26ef8cd21c96b9e05cbe02e5462bd2096d53b7.png", "website": "https://llm-stats.com", "all_locations": "New York City, NY, USA", "long_description": "We build independent and contamination-proof benchmarks that measure real world performance.\r\n\r\nLLM Stats is the most complete LLM leaderboard. We have the most complete archive of LLM benchmark results and also run independent evaluations that are not the classical ones that are already in the training data of most models.\r\n\r\nOur mission: become the biggest community dedicated to AI transparency.", "one_liner": "Independent AI evaluations lab", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1755052091, "tags": [ "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 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/llm-stats", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/llm-stats.json", "year_founded": 2025, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/llm-stats", "x_url": "https://x.com/LlmStats", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/3a26ef8cd21c96b9e05cbe02e5462bd2096d53b7.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": 562577, "full_name": "Jonathan Chávez", "title": "Founder", "founder_bio": "Co-Founder at LLM-Stats.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jonathanchatab", "x_url": "https://x.com/pirchavez", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e4684ed9c5fa4e105c6ccc348b3ef03cb5df5094.jpg" }, { "user_id": 208921, "full_name": "Sebastian Crossa", "title": "Founder", "founder_bio": "Co-Founder @ LLM Stats. Previous founding engineer at Micro building the future of email (backed by a16z), as well as founding engineer at Atrato Pago (W21). Formerly built and scaled Minecraft servers during my spare time during highschool.", "is_active": true, "linkedin_url": "https://linkedin.com/in/sebastiancrossa", "x_url": "https://x.com/sebcrossa", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/080f94f0e789bd63c6a6cfd8d91688ce079670d2.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 93136, "title": "ZeroEval - Build self-improving agents", "tagline": "A tool to evaluate and optimize AI agents using human feedback.", "body": "![uploaded image](/media/?type=post&id=93136&key=user_uploads/208921/328fd273-24d5-4307-9322-075a26467fe9)\n\nHey everyone, we're Sebastian and Jonathan - founders of ZeroEval.\n\n### **TL;DR**\n\nZeroEval is a tool that helps you build reliable AI agents through evaluations that learn from their mistakes and get better over time.\n\nhttps://www.youtube.com/watch?v=hSkpdHE7mCs\n\n### **The problem**\n\nEvaluating complex AI systems is hard and time consuming. The more complex your agents get, the harder this issue becomes. This is especially the case when building:\n\n1. Long-running, multi-turn agents with dozens of intermediate tool calls \n2. Agents where you want to measure the quality of images, video, generated UI, audio, personality, taste, etc\n\n**Current offline eval methods are high-friction**, a lot of work is needed to continuously curate labeled data and write experiments and evaluators. \n\nOn the other hand, **current LLM judges are static and often have terrible performance**, they lack context on how they fail and the nuances of the task at hand. \n\nYour AI agents are as good as your evals. Without them, surpassing the quality threshold your product needs will feel like a never-ending task.\n\n### **What we’re building**\n\nA way to create **calibrated LLM judges** that get better over time the more production data they see and the more incorrect samples are labeled. The more you teach it on where it's failing, the more reliable it becomes.\n\nOnce you have a judge that matches the human preference baseline, you can continue using it on production data or in offline experiments.\n\n![uploaded image](/media/?type=post&id=93136&key=user_uploads/208921/f815b7cf-a84e-4285-974d-1ffc943889ad)\n\nWe’re also introducing **Autotune**, a way to do automatic evaluation on dozens of models and prompt optimization based on a few human samples.\n\n![uploaded image](/media/?type=post&id=93136&key=user_uploads/208921/954461b0-5b4a-42b9-b464-0a698c3f6fd0)\n\nWe envision a future where AI software improves based on human feedback, where developers define the evaluation criteria as a starting point and errors back propagate to find the optimal implementation.\n\n### **The team**\n\nWe met during their first year of college in Mexico over 7 years ago. During that time they worked on side projects together, joined a leading fintech startup as first engineers and most recently built [llm-stats.com](http://llm-stats.com), a leading LLM leaderboard website that reached 60k MAU and  ⅓  million unique users since its launch a few months ago.\n\n* **Sebastian** was founding engineer at Micro building the future of email (backed by a16z), as well as founding engineer at Atrato (YC W21).\n* **Jonathan** was an early employee on the LLM observability team at Datadog. He did undergrad research on vision transformers for particle physics and RL for robotics.\n\nFoundational models have transformed the world. We’re building the second line of offense to fill their capability gaps and create AI products that actually work. We are determined to build the engine behind self-improving software for the following decades. \n\n![uploaded image](/media/?type=post&id=93136&key=user_uploads/208921/b912b213-762c-42ba-8fe5-dd39de8dd748)\n\n### **Our ask**\n\nIf you have AI agents in production and are struggling to measure their quality and/or achieve the reliability needed for your product's success, we’d love to chat!\n\nWe don't just deliver a tool, but will sit with you to understand your pain points and help you build high quality evals.\n\nFeel free to reach out at [founders@zeroeval.com](mailto:founders@zeroeval.com) or [book a demo](https://cal.com/team/zeroeval/demo).", "url": "https://www.ycombinator.com/launches/OEC-zeroeval-build-self-improving-agents", "votes": 35, "created_at": "2025-08-19T15:36:48.670Z" } ] }, { "id": 30649, "name": "Lilac", "slug": "lilac", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/18234851431f8da18d1f087abc867a57412f1a97.png", "website": "https://getlilac.com", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Lilac sells flexible GPU contracts and runs the software layer on top: monitoring, bare-metal provisioning, and managed Kubernetes and Slurm. We also run this layer for GPU cloud providers as their named operations and support partner.", "one_liner": "We sell GPUs.", "team_size": 4, "industry": "B2B", "subindustry": "B2B", "launched_at": 1754345371, "tags": [ "Machine Learning", "Cloud Computing", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2025", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": true, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/lilac", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/lilac.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/get-lilac", "x_url": "https://x.com/LilacML", "fb_url": null, "cb_url": null, "github_url": "https://github.com/getlilac", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/18234851431f8da18d1f087abc867a57412f1a97.png", "app_video_url": null, "dday_video_url": "https://bookface-images.s3.us-west-2.amazonaws.com/video_event/73/1757438550-c9621df37029cc122bc2415a49351917/9eadda8ada622d88427020d698f25df7.mp4?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAQC4NIECABPQ2AHNW%2F20261020%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20261020T022728Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&X-Amz-Signature=9aaaa0453d588f17ec05b77f091b5d1a5603a8b5cf39b20595f6f0bb5ada7d38", "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/e53628ce1b948c6a0fdc6aa376c679c34368c258.png" ], "primary_partner": { "name": "Tyler Bosmeny", "url": "https://www.ycombinator.com/people/tyler-bosmeny" }, "founders": [ { "user_id": 2382454, "full_name": "Lucas Ewing", "title": "Founder/CEO", "founder_bio": "I'm Lucas, born and raised in Stockholm Sweden, and moved to the US for High School and College (Harvey Mudd '23!)\n\nWorking on democratizing GPUs!", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/lucasboewing/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4052bd2e866b8460ca058a8fff43ad5c446f355c.jpg" }, { "user_id": 2356063, "full_name": "Ryan Ewing", "title": "Founder", "founder_bio": "I'm Ryan, a software engineer with a background in building cloud and networking services at AWS.\n\nCurrently working on Lilac, a spot GPU marketplace that leverages idle GPUs in data centers and on-prem clusters.\n\nwww.getlilac.com", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/rjewing/", "x_url": null, "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/bb13aa0cdc322cde8ee75db007c6ad439670d73c.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 92724, "title": "Lilac - We find you GPUs!", "tagline": "Lilac! The open-source tool that ensures your data scientists always have GPUs", "body": "💬 **TL;DR Lilac is an open-source tool that ensures your data scientists always have enough GPUs for their work. We seamlessly connect compute from any source, on-prem or cloud. [Check out our GitHub!](https://github.com/getlilac/lilac)**\n\n![uploaded image](/media/?type=post&id=92724&key=user_uploads/2382454/b1a41fba-535e-4392-9526-f97e72771387)\n\n❗**The Problem: The GPU Scramble is Slowing Down AI Innovation**\n\nAsk any data scientist and they will likely tell you their biggest frustration is finding GPUs. One team we talked to is spending $7 million dollars a year with a service provider to guarantee GPUs, yet they were still running out. This forces data science and infrastructure teams into a difficult position:\n\n* **Wasted Time:** Data scientists waste hours hunting for available GPUs across different clouds and on-premise servers, distracting them from building models.\n* **Spiraling Costs & Security Risks:** Infrastructure teams lose visibility as desperate data scientists use personal keys on unmanaged instances, leading to security gaps and unpredictable cloud bills.\n* **Slowed Innovation:** The result is a direct trade-off between innovation speed and engineering best practices. Companies either accept a slow model development lifecycle or pay millions for dedicated GPU contracts in a single cloud, losing flexibility.\n\n🏆 **The Solution: Unify Your Compute, Unleash Your Data Scientists**\n\nLilac is an open-source platform that transforms your scattered, multi-cloud, and on-premise GPU resources into a single, unified compute fabric.\n\nInstead of hunting for servers, your data scientists simply submit their training jobs to Lilac. Our intelligent scheduler handles the rest—finding the first available GPU that meets the job's requirements, allocating it, and running the job.\n\n**The Result:**\n\n* **For Data Scientists:** Maximum productivity. They can focus on building models, not managing infrastructure.\n* **For Infrastructure Teams:** Centralized control. Gain full visibility, enforce security policies, and manage costs across your entire fleet of compute resources.\n\nLilac bridges the gap between R&D and infrastructure, turning GPU scarcity into a streamlined, efficient workflow.\n\nHere’s an introduction and example of how it works:\n\n[**https://www.youtube.com/watch?v=n8Ye-8YS0I4&ab_channel=Lilac**](https://www.youtube.com/watch?v=n8Ye-8YS0I4&ab_channel=Lilac)\\\n\\\n🥇 **About Us**\n\nWe're a team of two brothers, [**@Ryan Ewing**](https://bookface.ycombinator.com/user/2356063) and [**@Lucas Ewing**](https://bookface.ycombinator.com/user/2382454), who have spent our careers building the infrastructure that powers the modern web. With experience scaling enterprise infrastructure at **AWS** and building end-to-end data platforms at **Webflow**, we've seen firsthand how critical, and how broken, the tooling for AI development is. We believe the rapid acceleration of AI requires a fundamental rethinking of the infrastructure stack, and we built Lilac to be the foundation of that new ecosystem.\\\n\\\n⭐ **Our Ask**\n\nWe are thrilled to announce that Lilac is now open-source with the release of **v0.1.0**!\n\n* **Check out our GitHub:** [**github.com/getlilac/lilac**](https://github.com/getlilac/lilac)\n* **Try it out:** Star the repo, try the quick start, and give us your feedback. We welcome all contributions, from bug reports to feature requests.\n* **Get in touch:** If the problem we're solving resonates with your company, we'd love to connect. Reach out at [**contact@getlilac.com**](mailto:contact@getlilac.com), [**schedule a 15-minute chat**](https://calendly.com/lucas-getlilac/15-minute-meeting) with us, or checkout our [**website**](https://getlilac.com/).", "url": "https://www.ycombinator.com/launches/O7Y-lilac-we-find-you-gpus", "votes": 23, "created_at": "2025-08-04T22:34:11.492Z" } ] }, { "id": 30660, "name": "Magnitude", "slug": "magnitude", "former_names": [ "Magnitude", "Sidekick", "Sagekit" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/9292b62c58dc81055b437ce647dc7c3ea10ffc5c.png", "website": "https://magnitude.dev", "all_locations": "San Francisco, CA, USA", "long_description": "Magnitude is an open source inference engine that tunes its kernels on your hardware to find the fastest way to run each model. It's over 2x faster than Ollama and works on Apple Silicon, NVIDIA, AMD, or just a CPU. One click connects it to the agent you already use (Pi, OpenCode, Hermes, Codex, and more)", "one_liner": "Run open models as fast as your hardware allows", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1751905744, "tags": [ "Developer Tools", "Open Source", "Infrastructure", "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/magnitude", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/magnitude.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/usemagnitude", "x_url": "https://x.com/usemagnitude", "fb_url": null, "cb_url": null, "github_url": "https://github.com/magnitudedev", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/9292b62c58dc81055b437ce647dc7c3ea10ffc5c.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Andrew Miklas", "url": "https://www.ycombinator.com/people/andrew-miklas" }, "founders": [ { "user_id": 2033744, "full_name": "Tom Greenwald", "title": "Founder/CEO", "founder_bio": "CEO at Magnitude. Studied CS at Northeastern. Ran special projects as a PM at SimpliSafe", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/t-greenwald/", "x_url": "https://x.com/tomgreenwald", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/aa83f88685c3b82270a3c00320fa6bbfeb0ae528.jpg" }, { "user_id": 1458582, "full_name": "Anders Lie", "title": "Founder/CTO", "founder_bio": "CTO at Sagekit. Studied CS and Math at Iowa State. Ex SWE at AWS working on no-code automation platforms", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/anders-lie/", "x_url": "https://x.com/ndrsrkl", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/69cb7c9f7eb6d1d3f325516f56e92c24e44eb478.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 30671, "name": "Panoptive", "slug": "panoptive", "former_names": [ "AgentHub" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e968a9edc53bbf932ccbe0585917fe2029077b90.png", "website": "https://www.panoptive.com", "all_locations": "San Francisco, CA, USA", "long_description": "We turn unstructured monitoring data - monitoring visit reports, EDC data - into structured deviation, safety, and quality findings for human review. Panoptive generates an audit-ready oversight trail as a natural byproduct. \r\n\r\nThe platform aggregates findings and identifies systemic patterns across sites and subjects before they compound, and tracks every finding through decision, follow-up, and resolution.", "one_liner": "The continuous oversight engine for clinical trials", "team_size": 2, "industry": "B2B", "subindustry": "B2B", "launched_at": 1753389326, "tags": [ "B2B", "Biotech", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2025", "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/panoptive", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/panoptive.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/panoptive-health", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/e968a9edc53bbf932ccbe0585917fe2029077b90.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": 715142, "full_name": "Youssef Kallel", "title": "Founder/CEO", "founder_bio": "Building the oversight engine for clinical trials @Panoptive. CS @ CMU, previously a tech lead on the Foundation Model Evaluation team at Apple.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/youssefkallel/", "x_url": "https://x.com/ymkallel", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9682bb7b67349e3ed4282ddad6d49a76ec9a964e.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 92664, "title": "💻 AgentHub 📈 - The Staging Environment for your AI Agents", "tagline": "Simulate, trace, and evaluate agent behavior in real-world environments", "body": "### **TL;DR**\n\nAgentHub is an implementation-agnostic platform for evaluating AI agents in realistic simulation environment sandboxes. Use cases that we support include computer-use, browser, conversational, and tool-use agents. We help teams test, trace, track, and improve agent behavior at scale before deployment, closing the gap between vibe checks and real-world performance.\n\n👉 Check us out [AgentHubLabs.com](http://AgentHubLabs.com)\n\n💬 If you’re building agents, training models, or can connect us to someone who is, we’d love to [chat](https://calendar.google.com/calendar/appointments/schedules/AcZssZ1FO0fw7yHEhAAHWoiyCOS2umxQTuat9bIUwOOzomfV4D8bxhKakigP0nglXPAQh-4qvrYwukiM)!\n\n---\n\nhttps://www.youtube.com/watch?v=1gPVYcphmmY\n\n### **🧩 The Problem**\n\nLLM-based agents often **pass simple evals at a small scale and in specific cases** but **fail in deployment**. They hallucinate tool use, misuse APIs, or follow an inefficient (or incorrect) reasoning trajectory that isn’t captured in standard benchmarks. There’s no standard way to evaluate agents beyond prompt-based tests - especially across **tool use**, **UI interactions**, and **multi-step reasoning**.\n\n---\n\n![uploaded image](/media/?type=post&id=92664&key=user_uploads/1435098/77c2d173-7349-41e4-90a2-e2b69712ede5)\n\n### **✅ The Solution: AgentHub**\n\nAgentHub lets you **simulate real-world environments** and **evaluate agents end-to-end** using structured tasks, traces, and grading:\n\n* 🧪 **Multi-domain, customizable environments for**: e-commerce, CRM, filesystem, browser agents, dashboards, and more\n* 🕵️ **Full tracing** in standardized OpenTelemetry format: capture every LLM/tool call, decision point, and UI step\n* 📊 Evaluation that’s easy to plug and play: LLM, human-in-the-loop, and rule-based grading + custom metrics at the task, step, or tool level\n* 🛠️ **Debug and iterate fast**: See exactly where agents fail, and improve reasoning or control loops\n* 🧠 **Automated Insights**: Get automatic insights into failure modes and auto-generate suggested fixes\n\nWhether you’re testing autonomous workflows, tool-using copilots, or browser agents, we give you a **sandboxed, realistic playground** to evaluate in before you ship.\n\n---\n\n![uploaded image](/media/?type=post&id=92664&key=user_uploads/1435098/a2b71d28-7310-4423-ac4d-1c717f244af4)\n\n### **🕵️ Who We Are**\n\nYoussef was previously a tech lead on the Foundation Model Evaluation team at Apple and studied CS at CMU.\n\nSandra has been an engineer at multiple startups, Google, and Meta, and studied CS and design at MIT.\n\nWe’ve been friends since a few years ago through a summer spent in Seattle and are obsessed with building the missing critical infrastructure to help teams **evaluate, debug, and trust** their agents.\n\n---\n\n### **🙌 How to Help / Get Involved**\n\n* Learn more and book a demo: [AgentHubLabs.com](http://AgentHubLabs.com)\n* We’re looking for teams and labs working on agents in:\n * tool-use\n * browser automation\n * conversational chat\n * and computer-use\n* Have an eval challenge? We’ll help you simulate it.\n* Use agents in prod? It’d be bananas to not test them on AgentHub first 🍌\n\n![uploaded image](/media/?type=post&id=92664&key=user_uploads/89898/9cf2b39b-039e-45a4-b4a6-969310c4378e)\n\n", "url": "https://www.ycombinator.com/launches/O6a-agenthub-the-staging-environment-for-your-ai-agents", "votes": 29, "created_at": "2025-08-02T13:40:37.564Z" } ] }, { "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\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 \\\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: \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": 30762, "name": "KERNEL", "slug": "kernel", "former_names": [ "Kernel" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0b651ae4215e55c6eec3b366c18c9dcdd7838a97.png", "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": [ "B2B", "Infrastructure" ], "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/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", "x_url": "https://x.com/usekernel", "fb_url": null, "cb_url": null, "github_url": "https://github.com/onkernel", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/0b651ae4215e55c6eec3b366c18c9dcdd7838a97.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Tyler Bosmeny", "url": "https://www.ycombinator.com/people/tyler-bosmeny" }, "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/", "x_url": "https://twitter.com/rfgarcia", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/70c4b460440085cf060e26d5a87677498f80b80b.jpg" } ], "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" } ] }, { "id": 30777, "name": "Modelence", "slug": "modelence", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/caf676672b230c36291913a0a2ddce1bd212e7b0.png", "website": "https://modelence.com", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "You built your product in a weekend and deployed to Vercel, Supabase, Railway or AWS. Now you need to figure out how to pick the right region, scale to multiple instances, add monitoring and alerts, and who to ping when something breaks… and you don't have a cloud engineer.\r\n\r\nWe spent a decade at our previous startup (CodeSignal), building a $500M platform while scaling to millions of users and customers like Meta & Netflix. Now we're standardizing how web applications are operated in production, so developers can build reliable production apps without becoming cloud infrastructure experts.\r\n\r\nModelence is a production cloud that's designed for enterprise-grade apps, abstracting away the infrastructure layer:\r\n- Deployments & hosting\r\n- Background jobs and persistence\r\n- File storage, real-time data and networking\r\n- Monitoring and alerts\r\n\r\nPlatforms like Vercel and Supabase are easy to start with, but most companies that start getting real customers eventually need a persistent backend where processes can run beyond just a few minutes at a time, unlike pure serverless. And low-level cloud platforms like AWS are meant to be operated by cloud engineers and are too complicated for engineers who want to focus on product rather than infra. Modelence is your managed backend infrastructure, built on decades of our experience operating web apps in the cloud.", "one_liner": "Production infrastructure on autopilot", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1752778004, "tags": [ "Developer Tools", "Open Source", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2025", "status": "Active", "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/modelence", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/modelence.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/modelence", "x_url": "https://x.com/modelencecom", "fb_url": "https://www.facebook.com/modelence", "cb_url": "https://www.crunchbase.com/organization/modelence", "github_url": "https://github.com/modelence", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/caf676672b230c36291913a0a2ddce1bd212e7b0.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Tyler Bosmeny", "url": "https://www.ycombinator.com/people/tyler-bosmeny" }, "founders": [ { "user_id": 2485356, "full_name": "Aram Shatakhtsyan", "title": "Founder/CEO", "founder_bio": "Before Modelence, I co-founded CodeSignal (valued $500M) and spent a decade on building and scaling one of the largest skill assessment platforms, used by millions of users and companies like Uber, Zoom & Netflix.\n\n- ex-Principal Eng @ Intuit\n- ex-Co-Founder & CTO @ CodeSignal\n- Forbes 30u30 US & Canada, Enterprise Technology\n- Silver medalist of IOI 2007 / former competitive programmer", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/artahian/", "x_url": "https://x.com/artahian", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d60b0336e85dcf23221d37984f59e6c1dd63374f.jpg" }, { "user_id": 2538231, "full_name": "Eduard Piliposyan", "title": "Founder/CTO", "founder_bio": "Co-Founder & CTO @ Modelence\n\nAn engineer and engineering manager with 18 years of experience. Was the founding engineer and Director of Engineering at CodeSignal.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/eduard-piliposyan", "x_url": "https://x.com/ed_piliposyan", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/76f86fd3828b608f6c73c2bf5f1124ef485f7244.jpg" } ], "jobs": [], "news": [], "launches": [ { "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" } ] }, { "id": 30853, "name": "Bolna AI", "slug": "bolna-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0b089abe00badc05c8bba9c5210bd4a34f636170.png", "website": "https://bolna.ai", "all_locations": "Bengaluru, KA, India", "long_description": "Bolna handles the complexity of voice infra, so enterprises can automate calls faster, better, and cheaper, at scale\r\n\r\nBolna is a Voice AI Orchestration platform purpose-built for Indian enterprises.\r\nBusinesses in India run tens of thousands of calls every day - across sales, support, collections, recruitment, and more. Bolna gives them the power to build and deploy Voice AI Agents directly from their transcripts and FAQs, so they can start automating calls immediately.\r\n\r\nWith Bolna, enterprises get:\r\n\r\n1. Full control over agent intelligence, tone, and workflows\r\n2. Cost efficiency at scale with smart routing across providers and price points\r\n3. Enterprise-grade performance on latency, interruptions, multi-language, and multi-accent understanding\r\n\r\n", "one_liner": "Voice AI to enable India's next billion", "team_size": 21, "industry": "B2B", "subindustry": "B2B", "launched_at": 1758900227, "tags": [ "B2B", "Infrastructure", "AI", "Conversational AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Fall 2025", "status": "Active", "industries": [ "B2B" ], "regions": [ "India", "South Asia", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/bolna-ai", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/bolna-ai.json", "year_founded": null, "city": "Bengaluru", "country": "IN", "linkedin_url": "https://www.linkedin.com/company/bolna-ai/", "x_url": "https://x.com/bolna_dev", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/whismurwave-inc", "github_url": "https://github.com/bolna-ai/bolna", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/0b089abe00badc05c8bba9c5210bd4a34f636170.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/f1ccd6a8c9fc96f2cb6904ab26e0b38dfaa5ea8a.png" ], "primary_partner": { "name": "Tom Blomfield", "url": "https://www.ycombinator.com/people/tom-blomfield" }, "founders": [ { "user_id": 1427127, "full_name": "Maitreya Wagh", "title": "Founder/CEO", "founder_bio": "Engineer turned Consultant turned AI Founder. Building the Total Voice AI Ochestration for India. Love sports and travel", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/maitreya-wagh/", "x_url": "https://x.com/maitreya_wagh", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/fd57dd6d87585a243317dbf8e55d05df3a61701c.jpg" }, { "user_id": 340680, "full_name": "Prateek Sachan", "title": "Founder/CTO", "founder_bio": "Building the Voice API infrastructure platform for India.\n\nPreviously built and scaled Zomato, Tata 1MG, BrowserStack & Atlassian.", "is_active": true, "linkedin_url": "https://linkedin.com/in/prateek-sachan", "x_url": "https://x.com/xan_ps", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5b79cc81789e524489e929c7c68ca77473fa839a.jpg" } ], "jobs": [], "news": [ { "title": "Bolna nabs $6.3M from General Catalyst for its India-focused voice orchestration platform", "url": "https://techcrunch.com/2026/01/20/bolna-nabs-6-3-million-from-general-catalyst-for-its-india-focused-voice-orchestration-platform/", "date": "Jan 20, 2026" }, { "title": "Bolna AI’s Bold Bet: Becoming the Distribution Layer for Every Voice Model", "url": "https://analyticsindiamag.com/ai-startups/bolna-ais-bold-bet-becoming-the-distribution-layer-for-every-voice-model/", "date": "Sep 09, 2025" } ], "launches": [ { "id": 94216, "title": "Bolna - Voice AI for India", "tagline": "We enable Indian businesses to automate calls with multilingual, realistic Voice AI agents", "body": "Call our AI Agents at [+18722412481](tel:+18722412481) or [+912269539260](tel:+912269539260) to know everything about Bolna!\n\nhttps://www.youtube.com/watch?v=Lq9ouROmRHA\n\n**The Problem**\n\nIn India, phone calls remain the backbone of how businesses operate - from banks chasing loan repayments, to edtech companies qualifying leads, to e-commerce brands confirming deliveries. Millions of such calls happen every day. But the system is broken:\n\n* **20+ Languages, 200+ Accents/Dialects**: Building a team that can handle all is impossible. Calls often switch mid-conversation (Hindi → Hinglish → Gujarati), and only a natural, adaptive AI can follow along and give a personalised experience to each caller.\n* **Context-Dependent Requirements**: A delivery driver in Bangalore needs a low-latency, Kannada-capable model with high noise cancellation. A recruitment call to an engineer requires a slower but higher-quality reasoning model. There is no “one model to rule them all,” and integrating and managing 100s of models at scale is an unwanted hassle for businesses.\n* **Cost Efficiency at Scale**: In India, every rupee matters. Voice AI must be engineered for efficiency - pre-recorded messages for common utterances, smaller vertical-focused models, and intelligent routing to minimize token usage.\n\n![uploaded image](/media/?type=post&id=94216&key=user_uploads/1427127/bb2d0f37-0050-4606-8271-c8664a3d541b)\n\n**The Solution**\n\nBolna is a **Voice AI Platform** purpose-built for India’s scale, linguistic complexity, and cost sensitivity. We enable enterprises to go live with thousands of concurrent calls in days, not months.\n\n* **Enterprise-grade performance**: Sub-500ms latency, interruption handling, multi-language (10+) and accent (50+) adaptation, fluent in natural multi-language conversations (Hinglish, English + Tamil etc.)\n* **India-specific routing**: Bolna automatically picks the optimal model blend for the context, regardless of language, region, or use case.\n* **Cost-efficiency engine**: Calls are optimized with pre-recorded inserts, cheaper small models where possible, and routing logic that prioritizes ROI without sacrificing experience.\n* **Complete control**: Enterprises define workflows, tone, and intelligence. Bolna handles everything behind the scenes.\n\nToday, Bolna powers **500K+ minutes of calls every month** across BFSI, e-commerce, and recruitment. Customers achieve **higher pickup rates, lower costs, and faster deployments** than with any alternative.\n\nFor Indian enterprises, Bolna is not just automation, it is the fastest path to scaling voice operations profitably.\n\n![uploaded image](/media/?type=post&id=94216&key=user_uploads/1427127/b5dd1f69-0a2d-4256-97d8-fc281cbccd14)\n\n", "url": "https://www.ycombinator.com/launches/OVc-bolna-voice-ai-for-india", "votes": 38, "created_at": "2025-09-30T05:29:03.741Z" } ] }, { "id": 30894, "name": "Unsiloed AI", "slug": "unsiloed-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f9f85fd135a735334483a66e34f7d25f1c8f535c.png", "website": "https://www.unsiloed.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "AI teams spend 6+ months building document workflows, yet fewer than 10% ever reach production. Generic LLM parsers and OCR collapse on multimodal documents with text, tables, images, and charts. Poor parsing and suboptimal chunking cripple RAG pipelines and downstream automation. Unsiloed AI has built state-of-the-art vision models which serves as the infrastructure layer for turning unstructured data into structured, queryable, and LLM-ready assets.\r\n\r\nOur APIs are already parsing hundreds of thousands of documents for startups and NASDAQ-listed enterprises, powering vertical AI solutions across industries. On public benchmarks, Unsiloed AI consistently outperforms solutions from LlamaIndex, Gemini, Mistral, and Unstructured.io among others.", "one_liner": "API for parsing multimodal unstructured data", "team_size": 2, "industry": "B2B", "subindustry": "B2B", "launched_at": 1759119503, "tags": [ "B2B", "Infrastructure", "AI", "APIs" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Fall 2025", "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/unsiloed-ai", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/unsiloed-ai.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/unsiloed-ai", "x_url": "https://x.com/UnsiloedHQ", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/unsiloed-ai", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/f9f85fd135a735334483a66e34f7d25f1c8f535c.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/078b943a7238682920862bf5368e98a5b340997d.png" ], "primary_partner": { "name": "Nicolas Dessaigne", "url": "https://www.ycombinator.com/people/nicolas-dessaigne" }, "founders": [ { "user_id": 879419, "full_name": "Aman Mishra", "title": "Founder/CEO", "founder_bio": "Co-founder at Unsiloed AI • IIT Kharagpur\n\nPreviously built an ultra low-latency trading system moving billions at a hedge fund. Founding Engineer (#1) at an SF-based startup building AI copilots for firms like Goldman Sachs and Charles Schwab. Launched a P2P rental platform from my dorm room, scaling it to thousands of orders within 2 months of operation.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/aman005/", "x_url": "https://x.com/__Aman_Mishra", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a4bb76f1ec54978aaf3cce9053ad7e1808c01338.jpg" }, { "user_id": 2381336, "full_name": "Adnan Abbas", "title": "Founder/CTO", "founder_bio": "Co-founder & CTO at Unsiloed AI • MIT • IIT Kharagpur\n\nBuilt multi-modal models deployed at a Fortune 10 company. Was building autonomous navigation systems at Mercedes Benz. Launched India’s first Web 3.0 audio app while in college, scaling it to thousands of users within a month.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/adnan-abbas-903b711a2", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a5d0a35df645a59a83211a7fc63a99585bff4b90.jpg" } ], "jobs": [ { "id": 87605, "title": "Founding Software Engineer - Backend and Infrastructure", "url": "https://www.ycombinator.com/companies/unsiloed-ai/jobs/cmlq27S-founding-software-engineer-backend-and-infrastructure", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Backend", "salary_range": "$150K - $300K", "equity_range": "0.10% - 1.00%", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [] }, { "id": 87808, "title": "Founding ML Researcher", "url": "https://www.ycombinator.com/companies/unsiloed-ai/jobs/SJCT4d4-founding-ml-researcher", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$200K - $300K", "equity_range": "0.10% - 1.00%", "experience": "3+ years", "visa": "Will sponsor", "skills": [ "Python", "Torch/PyTorch", "CUDA", "Computer Vision", "Data Analytics" ] }, { "id": 95433, "title": "Founding GTM Lead", "url": "https://www.ycombinator.com/companies/unsiloed-ai/jobs/ePft6Ux-founding-gtm-lead", "location": "San Francisco, United States", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$120K - $200K", "equity_range": "0.10% - 1.00%", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [], "launches": [ { "id": 95076, "title": "Unsiloed AI: Make Unstructured Data LLM-Ready", "tagline": "We build APIs to parse multimodal unstructured data and convert it into LLM-ready formats. Our vision is to make documents as computable and queryable for AI Agents as your data sitting in an RDS.", "body": "Hey YC, we are [Aman Mishra](https://www.linkedin.com/in/aman005/) and [Adnan Abbas](https://www.linkedin.com/in/adnan-abbas-903b711a2) from [Unsiloed AI](https://www.unsiloed.ai/).\n\n**TL;DR:** _Unsiloed AI is building the most accurate APIs for ingesting multimodal unstructured data like PDFs, PPT, DOCX, tables, charts, and images, and converting it into structured Markdown and JSON for downstream LLMs and AI Agents._\n\nWe are already processing millions of pages of complex documents each week for Fortune 150 banks, NASDAQ‑listed companies, as well as early‑stage startups in accuracy-sensitive domains like finance, legal, and healthcare.\n\nhttps://youtu.be/ULDK5dgfgzM\n\n**The Problem**\n\nMore than **80% of enterprise data is multimodal and unstructured**. AI teams spend **6+ months** building accurate document‑ingestion pipelines that keep breaking.\n\n* From the tons of open‑source solutions out there, it’s still tough to achieve superior accuracy on even mildly complex cases.\n* Traditional OCRs are static and break with changing layouts.\n* LLMs, although good at comprehension, suffer at **deterministic extraction**, making them unreliable for accuracy‑sensitive domains like finance and healthcare.\n* Early‑stage vertical AI teams end up becoming **document AI companies**, reinventing the wheel, as evident from **300+ conversations** we’ve had with AI teams of all sizes.\n\n**Solution (What we built)**\n\nWe combine **vision models** with **OCR‑based models** to accurately extract information from complex documents.\n\n**1) Pre‑processing & Segmentation**\n\n* We segment data into **texts, tables, images, and plots** using specialized models for each task.\n* We use a **heatmap‑based chunking** technique that first generates **pivot elements** from the document. Pivot elements are the elements of importance, e.g., **numbers and merged cells in tables**.\n* This chunking strategy ensures all related pieces of information are preserved in the **same chunk** (e.g., a table spanning multiple pages, rows split across pages), while unrelated information is split across chunks. The result: retrieval feeds **only accurate, complete‑context chunks** to LLMs.\n\n**2) Dual‑Stream Representation**\n\nPost pre‑processing, we pass the segmented chunks through **two parallel streams**:\n\n* **Data Stream:** preserves the **extracted content**.\n* **Layout Stream:** preserves the **actual layout & hierarchy** (indentation, alignment, clause/sub‑clause structure).\n\nThis matters because the data is not just text and numbers the **structure carries meaning** (e.g., a right‑aligned cell in a financial table or the way clauses/sub‑clauses are arranged). The dual stream captures both **semantic content** and **structural cues**.\n\n**3) Domain‑Specific Decoder**\n\n* A decoder consumes both the streams and structures the outputs as per the required **JSON schema** or **Markdown**.\n* We incorporate **domain‑specific ontologies** (finance, healthcare, legal).\n* An in-built **RL pipeline** to train the decoder when outputs involve internal terminology that is hard to capture using a general LLM.\n* We generate **confidence scores** for each extracted item; **low‑score items** are collected over time to run **fine‑tuning jobs**\n\nWe can run all of this under fully air-gapped on-premise environments as well for privacy-sensitive verticals.\\\n\\\n**Here are some sample outputs generated by our Vision Models:**\n\n![uploaded image](/media/?type=post&id=95076&key=user_uploads/879419/fdfed5e7-994a-47d3-9357-b20b1d2a3b67)\n\nPIE Chart formatted markdown\n\n![uploaded image](/media/?type=post&id=95076&key=user_uploads/879419/7e78481c-6898-4bfe-a6d8-c49ada7cef52)\n\nJSON output from handwritten, scanned docs, along with confidence scoring and citations.\\\n\\\n**Our Progress:**\n\nWe are already processing millions of pages for Fortune 150 banks, NASDAQ‑listed companies, as well as early‑stage startups (including 10+ YC startups) across finance, legal, and healthcare. On public benchmarks, we consistently outperform solutions from LlamaIndex, Gemini, Mistral, and [**Unstructured.io**](http://Unstructured.io)**,** among others.\n\nHere is a representation of the volume of pages we have processed, stacked on top of each other.\n\n![uploaded image](/media/?type=post&id=95076&key=user_uploads/879419/849f06b2-5d8d-4c77-8b73-40f6661a3f92)\n\n**Our Ask:**\n\nParsing **PDFs, images, PPTs,** or **Excel files** for your **Vertical AI** use case or **RAG** pipeline? Give [**Unsiloed AI**](https://www.unsiloed.ai/) a try. We turn months of ingestion work into one API call for every document type.\\\n\\\nSign up on [**unsiloed.ai**](http://unsiloed.ai) to give it a try (no credit card needed)\\\n\\\n**For any queries or feedback**:\\\n\\\nShoot us an email at [**founders@unsiloed.ai**](mailto:founders@unsiloed.ai) \\\nPing on WhatsApp/iMessage at +1 415 996 5878 (Aman)\\\nWebsite: [**https://www.unsiloed.ai/**](https://www.unsiloed.ai/)", "url": "https://www.ycombinator.com/launches/OjU-unsiloed-ai-make-unstructured-data-llm-ready", "votes": 52, "created_at": "2025-10-31T20:18:08.350Z" } ] }, { "id": 30903, "name": "Kestrel AI", "slug": "kestrel-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a17c93b508bc423bb59667db4befdfd07cfd6f68.png", "website": "https://usekestrel.ai/", "all_locations": "San Francisco, CA, USA", "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.", "one_liner": "AI Agents for Platform Engineering", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Security", "launched_at": 1761187283, "tags": [ "AIOps", "Developer Tools", "DevOps", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 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, "question_answers": null, "url": "https://www.ycombinator.com/companies/kestrel-ai", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/kestrel-ai.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/kestrel-ai-security/", "x_url": "https://x.com/kestrel__ai", "fb_url": null, "cb_url": null, "github_url": "https://github.com/KestrelAI/Kestrel-Operator", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/a17c93b508bc423bb59667db4befdfd07cfd6f68.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/1567ed15193a6530e6a8ca6468ddada7553e0aa0.png" ], "primary_partner": { "name": "Pete Koomen", "url": "https://www.ycombinator.com/people/pete-koomen" }, "founders": [ { "user_id": 2950276, "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, "linkedin_url": "https://www.linkedin.com/in/ramanvarma/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b2b5f7e9806eb261a5342845ec47b959b65e467e.jpg" } ], "jobs": [], "news": [], "launches": [ { "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 <5 mins with $1,000 in usage credits at [usekestrel.ai](http://usekestrel.ai).\n\n\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: \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: \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: \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" } ] }, { "id": 30913, "name": "Captain", "slug": "captain", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0c5e5da360891b80b4a1d6d511de963d613bbf08.png", "website": "https://captain.dev", "all_locations": "San Francisco, CA, USA", "long_description": "Captain makes product catalogs and complex, multimodal files searchable for customers and AI agents. It syncs files from sources like S3, SharePoint, and Google Drive and tunes search to your data and workloads.\r\n\r\nInstead of stitching together parsers, embeddings, vector databases, rerankers, and retrieval infrastructure, developers use Captain to power product search and file retrieval through managed APIs.\r\n\r\nOn evaluated file-search benchmarks, Captain’s tuning improved retrieval accuracy from roughly 78% with standard RAG to over 97%.\r\n\r\nBuilt for complex catalogs and demanding file-search workloads, including regulated and high-stakes applications.", "one_liner": "Self-tuning search for products and files", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1762492786, "tags": [ "B2B", "API", "Data Engineering", "Search", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "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, "question_answers": null, "url": "https://www.ycombinator.com/companies/captain", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/captain.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/runcaptain/", "x_url": "https://x.com/captaindotdev", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/captain-technologies", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/0c5e5da360891b80b4a1d6d511de963d613bbf08.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/8c35ef0b175d1d2ac7f51910ee2cfa78036029ea.png" ], "primary_partner": { "name": "Garry Tan", "url": "https://www.ycombinator.com/people/garry-tan" }, "founders": [ { "user_id": 2044865, "full_name": "Lewis Lien Polansky", "title": "Founder/CEO", "founder_bio": "CEO @ Captain, building self-tuning search for products & files. Engineer, designer, founder of a cybersecurity CTF org, recipient of U.S. Congressional recognition for community software, and randomly co-invented the soy-based milk carton.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/lewispolansky/", "x_url": "https://x.com/lienpolansky", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ecd86ae152b80dc12d55579cb0913bf93c33451f.jpg" }, { "user_id": 2578789, "full_name": "Edgar Babajanyan", "title": "Founder/CTO", "founder_bio": "CTO @ Captain | Published AI NLP Researcher | Built OCR engines @ Boar's Head | Scaled high-performance RAG pipelines for the past 4 years | Built a Cross Region L2 Datacenter", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/edgar-babajanyan-a28230217/", "x_url": "https://x.com/BabajanyanEdgar", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a4db53926ab205e15c802b0761d911b65a0e7321.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 95291, "title": "Captain - The Reliable Alternative to RAG", "tagline": "Search files with much higher accuracy than RAG (Avg improves 78% → 95%)", "body": "**TL; DR**: Captain delivers **the most accurate** general-purpose **knowledge search** engine **ever built.** \n\nIf you need to search through large text or multimodal files, and:\n\n* Don’t have time for **a tedious RAG sprint** -or-\n* Your current search pipeline lacks accuracy\n\nWe should talk. → [runcaptain.com/sales](https://runcaptain.com/sales?utm_source=ycombinator&utm_medium=launchyc&utm_campaign=launchyc&utm_content=weshouldtalk1) or [founders@runcaptain.com](mailto:founders@runcaptain.com)\n\nhttps://www.youtube.com/shorts/RxMPHqou94o\n\nIn a world where **90% of enterprise knowledge** cannot be stored in traditional databases, this ‘unstructured data’ is an **untapped goldmine** for decision-making. \n\nThe issue is that current RAG solutions have poor retrieval quality overall and are only performant on pre-optimized question types. \n\n![uploaded image](/media/?type=post&id=95291&key=user_uploads/2044865/425e4da0-2c47-43ea-a2c5-5dc32b2168fd)\n\n**Captain** unlocks **better responses** thanks to an effectively **Infinite Context window**. We distribute it across many LLMs in parallel + some embeddings sprinkled in, and then ‘Map-Reducing’ responses down to a single output.\n\n![uploaded image](/media/?type=post&id=95291&key=user_uploads/2044865/4be36851-322b-4836-be35-8e447cea51cd)\n\nWithout context limits, we have great freedom to optimize our retrieval engine for maximal accuracy. We can now play with a truly dynamic top-k or just run the LLM exhaustively (if a full knowledge audit is needed).\n\n![uploaded image](/media/?type=post&id=95291&key=user_uploads/2044865/e373def8-4aec-4add-b2a6-7d5fd9a02cb3)\n\n**We’re two lifelong builders** obsessed with data! \n\n* Lewis (right) solved hallucinations for code generation through his previous startup. \n* Edgar (left) researched NLP+AI and has built production RAG pipelines for the past 3 years.\n\nWe’ve seen the pains and limits of these systems from the start, and **the industry is primed for a more accurate alternative.** \n\nThis past summer, we met with every engineer we could at **Snowflake** and **Databricks**, and we kept hearing the same thing again and again: \n\n> There’s **no good** scalable **unstructured** data **search**.\n\nUntil **today**.\n\n**Captain abstracts the engineering of retrieval entirely.** Connecting files is all that’s needed, and we’ll beat your RAG's accuracy. Guaranteed. \n\n**Our Ask**\n\nIf you know a **CTO** or **Head of AI** at a mid-market or enterprise **AI-native** (or are building one yourself), we would love an introduction!\n\nCheck us out at [RunCaptain.com](https://runcaptain.com?utm_source=ycombinator&utm_medium=launchyc&utm_campaign=launchyc&utm_content=website)\\\nor reach us directly through [founders@runcaptain.com](mailto:founders@runcaptain.com)\\\n\\\nHappy Shipping! 🚢", "url": "https://www.ycombinator.com/launches/Omx-captain-the-reliable-alternative-to-rag", "votes": 115, "created_at": "2025-11-07T19:59:17.455Z" } ] }, { "id": 30935, "name": "s2.dev", "slug": "s2-dev", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/db49ec4c66c85d205171bbf2f1700ea1146f627c.png", "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, "tags": [ "Developer Tools", "Open Source", "API", "Infrastructure", "Databases" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2025", "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/s2-dev", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/s2-dev.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/streamstore/", "x_url": "https://x.com/s2_streamstore", "fb_url": null, "cb_url": null, "github_url": "https://github.com/s2-streamstore", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/db49ec4c66c85d205171bbf2f1700ea1146f627c.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/f0557b757a7ba472cfd3e29dc99f717e31930607.png" ], "primary_partner": { "name": "Nicolas Dessaigne", "url": "https://www.ycombinator.com/people/nicolas-dessaigne" }, "founders": [ { "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", "x_url": "https://x.com/shikhrr", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/57590395516b13e3ef14efeeefecfc7409c09e62.jpg" }, { "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/", "x_url": "https://x.com/sgbalogh0", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/23704db7d2ff94bf5b6f5b2309970e60225a41b3.jpg" } ], "jobs": [], "news": [], "launches": [ { "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, "created_at": "2025-11-08T06:30:48.434Z" } ] }, { "id": 30969, "name": "Lemma", "slug": "uselemma", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/335dca5772b36d447d2e1c9b0f730539813d1846.png", "website": "https://www.uselemma.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Lemma is production monitoring for AI agents. We catch the silent failures your observability tools and evals miss (think bad tool calls, lost context, and infinite loops) before your users find them.", "one_liner": "Production Monitoring for AI agents", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1761703288, "tags": [ "Developer Tools", "Analytics", "Infrastructure", "Monitoring", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Fall 2025", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/uselemma", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/uselemma.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/uselemma", "x_url": "https://x.com/uselemma_ai", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/335dca5772b36d447d2e1c9b0f730539813d1846.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Nicolas Dessaigne", "url": "https://www.ycombinator.com/people/nicolas-dessaigne" }, "founders": [ { "user_id": 1798805, "full_name": "Jerry Zhang", "title": "Founder/CEO", "founder_bio": "Co-founder @ Lemma (YC F25) | Reliability platform for AI agents", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jerry-n-zhang/", "x_url": "https://x.com/zjearbear", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5ea73d82ad13ecb85985095e699c5a6b06cff636.jpg" }, { "user_id": 1374781, "full_name": "Cole Gawin", "title": "Founder/CTO", "founder_bio": "developing the next generation of intelligent systems @ lemma (f25) | ex-USC", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/colegawin", "x_url": "https://x.com/colegawin_", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/deca21906919edc6e42060d0665ec4c3ae3d597a.jpg" } ], "jobs": [ { "id": 104341, "title": "Product Engineer", "url": "https://www.ycombinator.com/companies/uselemma/jobs/wrFU6bU-product-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$120K - $200K", "equity_range": "0.50% - 2.00%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 113900, "title": "AI/ML Engineer", "url": "https://www.ycombinator.com/companies/uselemma/jobs/vyHNWKs-ai-ml-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "AI engineer", "salary_range": "$120K - $200K", "equity_range": "0.50% - 2.00%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] } ], "news": [], "launches": [ { "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", "votes": 204, "created_at": "2025-11-05T19:58:08.940Z" } ] }, { "id": 31010, "name": "Amika", "slug": "amika", "former_names": [ "Fixpoint" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c42840d914de4ea4ec78f647bf0db2e93434ca5d.png", "website": "https://www.amika.dev/", "all_locations": "New York City, NY, USA", "long_description": "Amika is infra to build your software factory.\r\n\r\nWe give your team sandboxed AI coding agents in the cloud: the same infrastructure Ramp, Coinbase, and Stripe built in-house. Kick off work from a web UI, CLI, Slack, or API. Use your preferred coding agent (Claude Code, Codex, etc.). Each agent understands your codebase, runs autonomously, and ships real PRs with live previews of the apps it changed. Use it as your daily driver or plug it into your own code-gen pipeline via API.", "one_liner": "Infra to build your own software factory", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1759722442, "tags": [ "Machine Learning", "B2B", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 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/amika", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/amika.json", "year_founded": 2023, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/amikadev/", "x_url": "https://x.com/amikadev", "fb_url": null, "cb_url": null, "github_url": "https://github.com/gofixpoint/amika", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/c42840d914de4ea4ec78f647bf0db2e93434ca5d.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": 101903, "full_name": "Dylan Mikus", "title": "Founder/CEO", "founder_bio": "Making infra for software factories. Helping people spin up sandboxed coding agents, and then control the interactively or programmatically so they can automate their entire SDLC.\n\nCMU grad in comp sci and ML\n2x YC founder", "is_active": true, "linkedin_url": "https://linkedin.com/in/dbmikus", "x_url": "https://twitter.com/dbmikus", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/10786d1817ed7d689f6f3313f3b2c73f38c9f9a5.jpg" }, { "user_id": 1013839, "full_name": "Jakub Cichon", "title": "Founder/CTO", "founder_bio": "co-founder / CTO at Amika. Building infra for software factories. \n\n2x YC founder.", "is_active": true, "linkedin_url": "https://linkedin.com/in/jakub-cichon-14016a3b", "x_url": "https://x.com/jdcamika", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/095af1aef16261010001d5599b3059bc222330e3.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 103929, "title": "Amika - the operating system for AI agents to write and verify code", "tagline": "Run fleets of human-in-the-loop or background coding agents inside cloud computers. Let them automate coding and verify it's correct.", "body": "Software isn't a craft anymore, it's a manufacturing problem.\n\nAt Amika, we're building **the open source operating system for coding agents to automate their work**, like how the factory automated manufacturing.\n\n**Amika gives each agent a cloud computer, and lets you build automated or human-in-the-loop workflows for agents to write code and prove that the code is correct.**\n\nA couple of examples:\n\n\\- Have Amika monitor production and auto-fix errors, testing the fix against your real app\n\n\\- Add Amika to shared customer Slack channels. Auto-implement customer requests and share a live preview the updated app with them\n\nCheck out some more examples in our video 👇\n\n\n\n# The problem\n\nAI coding agents made code generation cheap. Producing correct code at scale, with real quality controls, is still unsolved. You're left with a tradeoff: pore over every change and go slow, or vibe-code and ship slop.\n\nCoding agents are useful, but the surrounding system is missing.\n\n\\- They lack the right **dev environment to verify their work**\n\n\\- They lack the right **context to understand the full problem**\n\n\\- They lack **deterministic guardrails controlling what they can change**\n\n\\- They produce 10x more code, but teams lack **a system for 10x more review**\n\n# How Amika solves this\n\nAmika composes 5 primitives into its agent operating system:\n\n1\\. **Sandboxed environments**: isolated cloud computers with the repos, tech stack, MCP servers, skills, and context an agent needs.\n\n2\\. **Workflows**: programs as code or markdown files that define when an agent runs and what job it does.\n\n3\\. **Deterministic guardrails**: rules enforced on every code change, like \"do not cross this module boundary\" or \"every database query must include a customer ID filter.\"\n\n4\\. **Automated verification**: test, review, fix, and merge loops that check the work against your real tech stack before it ships.\n\n5\\. **Audit trails**: the agent chat session, code changes, which checks passed, and what the run cost.\n\n![uploaded image](/media/?type=post&id=103929&key=user_uploads/101903/a1246cf3-1ed1-435d-94fb-2cb7437b4995)\n\nAmika works with your existing coding agent subscriptions (Claude Code, Codex, etc.) so **you're not locked into one vendor**. Start agents from the web, Slack, GitHub, the CLI, or the API. At any point, a human can take over the sandbox and inspect the running apps, or drive from their own code editor.\n\nBecause each sandbox runs your full stack, you review the agent's work in a live preview of your real app, plus the verification artifacts it produced, like screen captures or API test requests, instead of poring over the diff line by line.\n\nWith Amika's workflows and environments, you can spend time building higher level loops for your agent to write and verify code, speeding up your product development.\n\n![uploaded image](/media/?type=post&id=103929&key=user_uploads/101903/60e16093-3dcf-4285-b73b-998c74507145)\n\n![uploaded image](/media/?type=post&id=103929&key=user_uploads/101903/3b84372e-0a00-46a3-afd1-d711547c256b)\n\n# Who we are\n\nWe're [Jakub](https://www.linkedin.com/in/jakub-c-14016a3b/) and [Dylan](https://www.linkedin.com/in/dbmikus/), two time YC cofounders.\n\n![uploaded image](/media/?type=post&id=103929&key=user_uploads/101903/497da8a5-bfa8-407e-98f6-b613d9389b50)\n\nWe pivoted our YC company to bet on this, and we already use Amika for the majority of our PRs. We're building it in the open: each primitive ships as open source, and our cloud platform packages the whole operating system into a software factory for teams.\n\n# Our ask\n\n\\- Sign up for a **free two-week trial at [amika.dev](https://www.amika.dev/)**\n\n\\- Dig into the **open source repo** on GitHub: \n\n\\- If you want **help setting up your software factory**, book at demo at \n\n![uploaded image](/media/?type=post&id=103929&key=user_uploads/101903/3e200f7d-2b3f-4e3e-99f3-d0249987c72c)\n\n", "url": "https://www.ycombinator.com/launches/R2H-amika-the-operating-system-for-ai-agents-to-write-and-verify-code", "votes": 18, "created_at": "2026-06-24T17:06:48.500Z" }, { "id": 94868, "title": "Fixpoint - Uber for AI trainers and human-in-the-loop supervisors", "tagline": "Fixpoint helps AI data companies automate sourcing, vetting, and all HR for your expert annotator teams", "body": "Hello, world! We’re [Jakub](https://www.linkedin.com/in/jakub-c-14016a3b/) and [Dylan](https://www.linkedin.com/in/dbmikus/), the co-founders of [Fixpoint](https://fixpoint.co/).\n\n**Fixpoint helps AI training data companies hire the expert humans that create AI training data**.\n\nAI needs human experts to teach it new skills and benchmark its performance: PhDs for science, lawyers for contract review, etc. But finding and vetting these experts is time-consuming, and without properly vetting experts, you’re paying for bad data!\n\nFixpoint automates this process, connecting companies with verified experts at the push of a button, so you can focus on creating quality AI training data instead of recruiting.\n\n[Launch Video](https://youtu.be/9TCgpe0tT3w)\n\n**We have two products:**\n\n1. **Worker Vetting API** - Plug Fixpoint’s API into your onboarding workflow and vet the credentials and backgrounds of workers. **Catch 10x the worker fraud!**\n2. **White-Glove Expert Staffing** - When you need annotators fast, Fixpoint can source and hire a team of qualified experts. **Staff a team of 100s in just a couple weeks.**\n\n**Our track record:**\n\n* We’ve caught 10x the fraudulent applicants for top AI data companies\n* We’re partnered with data companies to staff teams for the top AI labs\n* We are GDPR ready and SOC 2 certification is underway\n\nUltimately, we're building the platform for \"human data ops\". Just as chip designers use TSMC for chip manufacturing, AI companies can use Fixpoint for the human expertise and tools needed to create specialized training data and evals.\n\n# Our ask\n\nSend us an email at [**founders@fixpoint.co**](mailto:founders@fixpoint.co) or [**grab a demo**](https://cal.com/fixpoint/demo) if:\n\n* You’re an AI data company or RL company and need a team of expert annotators\n* You’re an enterprise that needs to eval or benchmark your AI agents in a specialized domain (healthcare, legal, etc.)\n* You’re on the “human data” team at a model lab and have trouble managing experts or their data\n* You don’t fit in the above, but you or someone you know could use our services!\n\n# About us\n\nWe’re [Jakub](https://www.linkedin.com/in/jakub-c-14016a3b/) and [Dylan](https://www.linkedin.com/in/dbmikus/). We’re second time YC founders who’ve worked together since we met at Oscar Health in 2018. We’ve built everything from search systems, to chatbots, to data infrastructure, to AI web research agents.\n\n![uploaded image](/media/?type=post&id=94868&key=user_uploads/101903/ad8316ad-d855-46de-9ffc-67bb1fd62847)\n\n", "url": "https://www.ycombinator.com/launches/Og8-fixpoint-uber-for-ai-trainers-and-human-in-the-loop-supervisors", "votes": 25, "created_at": "2025-10-23T21:41:36.522Z" } ] }, { "id": 31074, "name": "OneTriangle", "slug": "onetriangle", "former_names": [ "EvalAI", "TrustAI Labs", "TrustAI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/75197a50573558e4b8c16932b7db7c7c11f235a4.png", "website": "https://onetriangle.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Inference has surpassed training as AI’s largest compute cost, accelerated by increasing demand for AI and agents. By using proprietary KV cache transfer tech, OneTriangle has cut inference costs by 20% and time by 40% compared to present standards.", "one_liner": "The cheapest, fastest inference cloud", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1783378352, "tags": [ "Open Source", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 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, "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": "Hi, we’re Hannah and Medha! Three years ago, we met at MIT, and now are co-founding OneTriangle. Hannah loves scaling companies and Medha loves making ideas become real products. Together, we built OneTriangle to push the limits on latency, cost, and quality. " }, { "question": "What is your long-term vision? If you truly succeed, what will be different about the world?", "answer": "We believe the future of AI will be defined by intelligence and trust. AI agents will reliably carry out human intent while recognizing and refusing actions that are unsafe, unlawful, or harmful. With the rate of advancing ML systems, we will bridge this ever-increasing gap. We provide a compliance standard for all agents to follow, ensuring that humans and agents are perfectly aligned in their intentions." } ], "url": "https://www.ycombinator.com/companies/onetriangle", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/onetriangle.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/trustaiinference/", "x_url": "https://x.com/OneTriangleAI", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/75197a50573558e4b8c16932b7db7c7c11f235a4.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/f775cf723e5a0f2258a41df7227d4243e4b2b3b5.png", "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/d28c1c890fcf41f1e457a449b678b33930d05cb5.png" ], "primary_partner": { "name": "Ankit Gupta", "url": "https://www.ycombinator.com/people/ankit-gupta" }, "founders": [ { "user_id": 2573695, "full_name": "Hannah Chung", "title": "Founder/CEO", "founder_bio": "MIT CS & Econ → @Virtu Financial → Fastest, Cheapest Lightweight Inference @OneTriangle\n", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/hannahchung1/", "x_url": "https://x.com/hannah_chuu", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a97b9b67d35f8f68aeebc4b930d52ab56e6b4e49.jpg" }, { "user_id": 2043461, "full_name": "Medha Venkatapathy", "title": "Founder/CTO", "founder_bio": "Hi! I studied physics + cs at mit, and we're building the cheapest/fastest inference with KV cache transferability. In my free time, I like to bike and get lost.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/medhav/", "x_url": "https://x.com/medha_rv", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/543ebe65ad3407ffb95c2dd2e5183140b298be3f.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 111487, "title": "OneTriangle - The fastest, cheapest inference, powered by KV cache transfer", "tagline": "Lightweight novel inference ", "body": "**TL;DR:** OneTriangle is building the cheapest, fastest inference. We cut inference prefill costs by 20% and time-to-first-token by 40%, letting you get large-model quality at small-model cost.\n\nVideo: \n\n**Team**\n\nWe’re Hannah (CEO) and Medha (CTO), MIT CSAIL grads building with a team of 4 MIT engineers spanning ex-DeepMind and Jane Street, Physics and Astronomy Olympiad medalists, and NeurIPS/ICML authors. \n\n**The Problem**\n\nInference is expensive. \n\n• You’re forced into a bad tradeoff. You need the decoding power of large models, but you have the budget for small ones.\n\n• Prefill is the hidden tax. For long-context and agentic workloads, prefill dominates cost and latency, and everyone just eats it.\n\n**Our Solution**\n\nOneTriangle transfers the KV cache between models, something that has never been done in production. We prefill on a small model, strip the positional encoding, map the cache into the large model’s space, and restore relative importances. The result:\n\n• 20% lower prefill costs\n\n• 40% faster TTFT\n\n• Large-model quality at small-model cost\n\nWe beat out NVIDIA’s KV cache transfer paper by getting a lower KL divergence score in 2 weeks.\n\n![uploaded image](/media/?type=post&id=111487&key=user_uploads/2573695/e64727d6-a7b1-404a-bfbb-22ad2b941142)\n\n\\\nNo API changes, no quality cliff, and we’re upstreaming it into vLLM so the fastest path to cheap inference is the infrastructure you already run.\n\n**Why Now**\n\nInference has surpassed training as AI’s largest compute cost, and it’s accelerating with demand for agents that generate 10x the tokens a chat session does. Inference already eats up to 90% of total compute cost, over $600 billion is going into AI data centers this year alone. Every team pushing the frontier is bottlenecked by the same thing: serving costs.\n\n\\\n**The Future**\n\nOur bet is that model-mixing becomes the default serving pattern: small models handle prefill and routine tokens, large models handle the hard ones, and the cache moves freely between them. Whoever owns the transfer layer owns the economics of inference. We are the future of lightweight, fast inference.", "url": "https://www.ycombinator.com/launches/T0B-onetriangle-the-fastest-cheapest-inference-powered-by-kv-cache-transfer", "votes": 10, "created_at": "2026-08-21T02:30:02.532Z" } ] }, { "id": 31088, "name": "RunAnywhere", "slug": "runanywhere", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/361f4cc73d27e788a8d1f92355ba04c3d71218ee.png", "website": "https://www.runanywhere.ai/", "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, "tags": [ "Developer Tools", "Open Source", "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, "question_answers": null, "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/", "x_url": "https://x.com/RunAnywhereAI", "fb_url": null, "cb_url": null, "github_url": "https://github.com/RunanywhereAI", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/361f4cc73d27e788a8d1f92355ba04c3d71218ee.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/d2a59b0835e877f9f60b9b43278eb61b82f23221.png" ], "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/", "x_url": "https://x.com/sanchitmonga22", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4df4145bbb5414a5759e0cd88d32ebaf4190a401.jpg" }, { "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/", "x_url": "https://x.com/ShubhamMal72313", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/36de7fe20c276b5c28fa88ab307242c6cda7a811.jpg" } ], "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", "equity_range": "", "experience": null, "visa": "US citizenship/visa not required", "skills": [ "Android", "LLMs" ] } ], "news": [ { "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\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\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\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" } ] }, { "id": 31114, "name": "Piris Labs", "slug": "pirislabs", "former_names": [ "Piris Inc.", "Pirislabs" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cfbd3640d376f89f668901f7449636b7f882fdb6.png", "website": "https://pirislabs.io/", "all_locations": "San Francisco, CA, USA", "long_description": "Up to 80% of the most advance AI compute chips sits idle because of slow networking. Piris Labs builds photonic based networking solutions to enable fast, scalable, and low cost AI workload execution infrastructure.", "one_liner": "The Networking Layer of AI", "team_size": 8, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1770857008, "tags": [ "Hard Tech", "Hardware", "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, "question_answers": null, "url": "https://www.ycombinator.com/companies/pirislabs", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/pirislabs.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/110912035", "x_url": "https://x.com/PirisLabs", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/piris-labs", "github_url": "https://github.com/PirisLabs", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/cfbd3640d376f89f668901f7449636b7f882fdb6.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Ankit Gupta", "url": "https://www.ycombinator.com/people/ankit-gupta" }, "founders": [ { "user_id": 2792621, "full_name": "Ali Khalatpour", "title": "Founder/CEO", "founder_bio": "Founder (YC W26), reimagining AI compute architectures | PhD EE (MIT → NASA → Stanford)", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/alikhalatpour", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/42b5a5f623f8120937aa26e3d674989a58a1f3f4.jpg" }, { "user_id": 3157622, "full_name": "Keyvan Moghadam", "title": "Founder/President", "founder_bio": "I am an AI technologist with a decade of experience scaling AI/ML products. At Meta and X, I specialized in leading tiger teams to launch high-stakes 0-to-1 initiatives.\n\nNow, I am the Co-Founder of Piris Labs. We are building high-speed photonic interconnects to solve the energy and latency constraints for AI data inference. My current focus is to iterate on our inference service and onboard customers into our platform.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/keyvanrm/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b998bdac71f94c01737efbb8c8777cfb76a14d3a.jpg" } ], "jobs": [ { "id": 93808, "title": "Founding Engineer -- AI Inference Stack ", "url": "https://www.ycombinator.com/companies/pirislabs/jobs/r6mskwZ-founding-engineer-ai-inference-stack", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Backend", "salary_range": "$100K - $200K", "equity_range": "0.10% - 1.00%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [ "Rust", "TCP/IP", "Design systems", "Transformers" ] } ], "news": [], "launches": [ { "id": 104954, "title": "Piris Labs: We Set the Fastest Reported GLM-5.2 Inference Speed", "tagline": "Fast, scalable AI workload execution infrastructure.", "body": "Piris Labs just achieved the fastest reported inference speed for the new GLM-5.2, outperforming pioneers and veterans in the space.\n\nWe finished the YC batch just a few months ago and believed it was important to maintain that same pace of execution while keeping our technical bar high. So yes, the YC advice is right: keep building.\n\nA lean, highly passionate team with strong execution and the right long-term vision can accomplish in a short period of time what often takes much larger organizations with billions in funding and hundreds of people years to achieve.\n\nWe're well on track to build fast, scalable, and low-cost AI workload execution infrastructure with a deep focus on the data movement layer, where many of the biggest bottlenecks in performance and unit economics exist.\n\nRead the full details here:\n\n\n\nWe welcome independent third-party benchmarking. Feel free to DM us or reach out by email.\n\n#AIInference #MachineLearning #GLM52 #GenAI #AIInfrastructure #TechInnovation\n\n![uploaded image](/media/?type=post&id=104954&key=user_uploads/2792621/98b898a8-99fa-482a-ab7a-d65badc2b3e4)\n\n", "url": "https://www.ycombinator.com/launches/RIo-piris-labs-we-set-the-fastest-reported-glm-5-2-inference-speed", "votes": 5, "created_at": "2026-07-07T22:22:52.996Z" }, { "id": 97751, "title": "Piris Labs: Inference at Light Speed", "tagline": "We deliver low-latency, low-cost AI inference by eliminating the memory wall using full-stack optical interconnects and a purpose-built software stack.", "body": "**The Problem: The Memory Wall Is Breaking the Economics of AI Compute**\n\nAI’s promise is unprecedented, but its economics are broken. Copper-based interconnects cannot keep up with modern models, limiting data movement between and within compute and memory. The result is high latency, inefficient hardware utilization, and unsustainable inference costs—creating a hard ceiling on AI margins.\n\n---\n\n**The Solution: Grow-Style Optimization for the Interconnect**\n\nToday’s data-center compute and networking were not designed for inference. Slow, power-hungry **copper** interconnects, along with costly signal processing and memory overhead, drive high latency and high cost.\n\nHigh-performance inference requires purpose-built hardware and a vertically optimized software stack. Piris Labs builds this optimized stack by combining proprietary **optical** interconnects with software designed to maximize hardware utilization. We vertically optimize the interconnect layer—just as the compute layer was vertically optimized by **Groq** (acquired by **NVIDIA** for $20 B).\n\nPiris Labs combines proprietary optical interconnects with a purpose-built software stack designed to maximize hardware utilization, delivering **5x** lower latency, **10x** lower power per bit, and **2x** lower cost per token\\\n\\\n**Our Launch Video**\\\n\n\n**The Team**\n\nWe are a team of specialists at the intersection of hardware and AI:\n\n* Ali Khalatpour: MIT-trained engineer and Harvard–Stanford–trained optical scientist; developed the first room-temperature terahertz semiconductor laser; led the development of GUSTO’s optical engine for NASA\n* Keyvan Rezaei Moghadam: AI scientist and engineering leader with experience building 0-to-1 AI infrastructure at Meta and Twitter.\n\n### **Our Ask**\n\n**AI Products**: If you want to scale your inference workloads while slashing costs, reach out to us at [**contact@pirislabs.io**](mailto:contact@pirislabs.io).\\\n\\\n**Chip Makers & ODM Partners**: We are also looking for a couple of additional partners who get the chance of trying our optical solution first hand. Shoot us an email at [**founders@pirislabs.io**](mailto:founders@pirislabs.io).", "url": "https://www.ycombinator.com/launches/PQd-piris-labs-inference-at-light-speed", "votes": 21, "created_at": "2026-02-12T17:58:23.293Z" } ] }, { "id": 31147, "name": "Salus", "slug": "salus", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ab475a73fae950cedb2c238eb5a23d6a709d5cb2.png", "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, "question_answers": null, "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/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/ab475a73fae950cedb2c238eb5a23d6a709d5cb2.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Ankit Gupta", "url": "https://www.ycombinator.com/people/ankit-gupta" }, "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", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/bb85a6b93f54bf5dfe9bf73ff7696fb9b3b03f51.jpg" } ], "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", "skills": [] }, { "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)", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$250K - $500K", "equity_range": "0.50% - 2.00%", "experience": "1+ years", "visa": "Will sponsor", "skills": [ "Python", "TypeScript", "LLMs", "AI Agents" ] } ], "news": [], "launches": [ { "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\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" } ] }, { "id": 31152, "name": "Fern", "slug": "fern-bot", "former_names": [ "ProactiveAI", "Ishiki Labs", "Fern (Formerly Ishiki Labs)" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/937df36cb9a1992b6e2ab4f4415451f1ad6f7174.png", "website": "https://fern.bot", "all_locations": "", "long_description": "Fern provides RL environments for robotics companies powered by a foundational world model. Companies can plug and play their robot policies completely in software with varying starting scenes of their production environment, and we'll produce RL heads on top of your existing policies to improve speed and success rate. Our customers get a continual learning flywheel where their production robots improve every week.", "one_liner": "RL environments for robotics companies", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1768297786, "tags": [ "Robotics", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2026", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "Unspecified" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/fern-bot", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/fern-bot.json", "year_founded": 2025, "city": null, "country": null, "linkedin_url": "https://www.linkedin.com/company/fernbot", "x_url": "https://x.com/ishikilabs", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/ishiki-labs ", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/937df36cb9a1992b6e2ab4f4415451f1ad6f7174.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/9aa481a01c92aff3ef9ad6396f367ccbff24cd03.png" ], "primary_partner": { "name": "Gustaf Alstromer", "url": "https://www.ycombinator.com/people/gustaf-alstromer" }, "founders": [ { "user_id": 2972207, "full_name": "Amit Yadav", "title": "Founder/CEO", "founder_bio": "Cofounder and CEO at Ishiki Labs (W26). Previously: Research Scientist, first in LlaMA team training multimodal LLMs and then in Reality Labs at Meta training video assistant for smart glasses. PhD from Purdue University with 20+ publications at top conferences like CVPR, NeurIPS, and ICASSP", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/amit-kumar-singh-yadav", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5df16b6162b4b3786dc3815473d7c24badaeff21.jpg" }, { "user_id": 3201791, "full_name": "Robert Xu", "title": "Founder", "founder_bio": "Co-founder & CTO of Ishiki Labs (W26). Previously worked on multi-modal AI and Orion AR glasses at Meta and research infra at Citadel Securities.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/robert-xu/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0946e3006e82ae99c29383b458713393504b6926.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 97949, "title": "Fern – Realtime Socially Aware AI for Meetings", "tagline": "Fern joins every meeting as–either invisible copilot or active participant–so every conversation runs like a top 1% professional", "body": "**TL;DR**\\\n[Fern](https://www.ishikilabs.ai/download) is a realtime AI that joins your meetings as either an invisible copilot or an active participant– your choice! It realtime proactively coaches you through every conversation so you always show up like a top 1% professional.\n\nHey everyone, we're Amit and Robert, cofounders of Ishiki Labs.\n\n**The Problem**\n\n_“AI meeting assistant” has become synonymous with a note-taker waiting to summarize at the end. That's not a meeting assistant. That's a fancier transcript._ \n\nBuilding a realtime AI meeting copilot is hard in two distinct ways.\n\nThe invisible assistant must understand the live meeting context at blazing speed and surface the right thing at the right moment – questions to ask, things you're missing, who you're talking to. Timing is everything. Current AI is purely reactive. Making AI an active participant in discussion is even harder. AI has no social awareness – every pause becomes a prompt, every gap an invitation to speak.\n\nAI that is socially aware and proactive is an unsolved problem. That's what we're building.\n\nThe cost of this gap is real. Cofounders, AEs, recruiters, investors – in discovery calls, sales meetings, investor conversations. The moments that matter most, and AI is absent from all of them.\n\n**How Fern Solves it**\n\n[Fern](https://www.ishikilabs.ai/download) joins your meetings as a true participant or an invisible copilot – your choice. It has two modes:\n\n**Full Presence**: Fern joins visibly, listens, and speaks up when invited. It offers realtime opinions, deep research, and can complete tasks like filing notes or sending emails on the spot. Built for internal product, engineering, and strategy meetings. Watch the demo- \n\n**Shadow Mode**: Silent and invisible to everyone else. You get a private realtime feed: live summaries, questions to ask, things you're missing, context on who you're talking to. A sharp colleague whispering in your ear – with fully customizable insights. Built for client calls, investor meetings, and any conversation where you want invisible support.\n\nBoth modes include a post-meeting summary, transcript, and full insights.\n\n**Team**\n\nWe're both ex-Meta. Amit is an AI Scientist from LLaMA (now Meta Super Intelligence Lab) and Reality Labs – PhD in AI, 20+ publications at NeurIPS/CVPR, trained multimodal assistants for smart glasses. Robert was systems and infra lead in Reality Labs, with four years building low-latency multimodal systems at Meta and Citadel Securities. \n\nOur mission: make AI socially timed and contextually aware – so every conversation you have runs like a top 1% professional.\n\n**Our Ask**\n\nDownload [Fern](https://www.ishikilabs.ai/download) and if you're a founder or AE who lives in high-stakes conversations and don’t want to settle for AI note-takers, reach out: [team@ishikilabs.ai](mailto:team@ishikilabs.ai)", "url": "https://www.ycombinator.com/launches/PTp-fern-realtime-socially-aware-ai-for-meetings", "votes": 26, "created_at": "2026-02-19T15:09:16.569Z" } ] }, { "id": 31192, "name": "Approxima", "slug": "approxima", "former_names": [ "Sidekit", "SideKit" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e6e6d183a6369dfc8a86aad778e45ad07d16406f.png", "website": "https://approxima.ai", "all_locations": "Toronto, ON, Canada", "long_description": "Human-assisted development should be for novel ideation, not routine maintenance, bug fixes or incremental updates. Approxima is bringing you that future with agents that can scope work, code, validate their fixes end-to-end in sandbox environments and merge to production. Book a demo: https://calendly.com/ashish-selvaraj/approxima", "one_liner": "Your software should build itself.", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1767593677, "tags": [ "Enterprise Software", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2026", "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/approxima", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/approxima.json", "year_founded": 2025, "city": "Toronto", "country": "CA", "linkedin_url": "https://www.linkedin.com/company/approximai/", "x_url": "https://x.com/approximai", "fb_url": null, "cb_url": null, "github_url": "https://github.com/appsidekit/", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/e6e6d183a6369dfc8a86aad778e45ad07d16406f.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": 3229135, "full_name": "Ethan Pronev", "title": "Founder", "founder_bio": "Co-founder at Approxima, building the trust layer to help software development scale with AI. Previously worked on trading systems at Jane Street and Citadel Securities. Computer Science graduate from the University of Waterloo, class of 2025.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/ethan-pronev/", "x_url": "https://x.com/ethanpronev", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/bc2e0a901422a1951b677c9ae1edbf7f9d8b954a.jpg" }, { "user_id": 2960509, "full_name": "Ashish Selvaraj", "title": "Founder", "founder_bio": "Co-founder at Approxima, building the trust layer to help software development scale with AI. Previously worked on delta live tables at Databricks, an infra testing engine at Microsoft and graduated with a double degree in Computer Science and Business from Waterloo in 2025.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/ashish-selvaraj/", "x_url": "https://x.com/asheeeeeshh", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b55ae2511335d9eef1ee99bbf880a8b7585339e1.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 31216, "name": "Archal", "slug": "archal", "former_names": [ "Archal Labs" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d5457b412312bd26ecc72ccead99d16248cd087a.png", "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", "launched_at": 1776709029, "tags": [ "Developer Tools", "API", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 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, "question_answers": null, "url": "https://www.ycombinator.com/companies/archal", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/archal.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/archal-labs", "x_url": "https://x.com/archal_labs", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/d5457b412312bd26ecc72ccead99d16248cd087a.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Ankit Gupta", "url": "https://www.ycombinator.com/people/ankit-gupta" }, "founders": [ { "user_id": 2037605, "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/", "x_url": "https://x.com/AidanTiruvan", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/6d8e1a01ea012584fc41d1ef014c296c0bbdbd00.jpg" } ], "jobs": [], "news": [], "launches": [ { "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" } ] }, { "id": 31300, "name": "Shofo", "slug": "shofo", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cdc8fbfe28cb5c8e4405b92f33ce7b6536b88c17.png", "website": "https://shofo.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "We are building the world’s largest video library. We've aggregated billions of videos into a searchable index and use agents to find and label the exact datasets a lab needs on demand.\r\n\r\nIf a lab needs 100K hours of cooking videos where someone is holding a pan, with reasoning annotations on top, our agents search the index, extract the matching subset, route it through our labeling pipeline, and deliver a custom dataset in days, not months.", "one_liner": "The World's Largest Video Library", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1768432806, "tags": [ "Data Labeling", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "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, "question_answers": null, "url": "https://www.ycombinator.com/companies/shofo", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/shofo.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/shofoai/", "x_url": "https://x.com/shofoai", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/cdc8fbfe28cb5c8e4405b92f33ce7b6536b88c17.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": 2555175, "full_name": "Braiden Dishman", "title": "Founder/CEO", "founder_bio": "Co-Founder & CEO @ Shofo | UCSB Econ | Prev. AWS", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/braiden-dishman/", "x_url": "https://x.com/BraidenDishman", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3e18cf46ac55fb35ab744fe0d1918aee373a3d85.jpg" }, { "user_id": 2980379, "full_name": "Andre Braga", "title": "Founder & Head of AI", "founder_bio": "Co-Founder & Head of AI @ Shofo | UCSB BS Statistics & Data Science | Prev. MIT", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/andre-braga-nlp", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/fd2a63604446d02437087711d56e433ed4cc9760.jpg" }, { "user_id": 3192733, "full_name": "Alexzendor Misra", "title": "Founder/CTO", "founder_bio": "Co-Founder & CTO @ Shofo | UCSB Dropout | Prev. CEO @ Correkt (43k users)", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/alexzendor-misra-15907a23b/", "x_url": "https://x.com/AlexzendorMisra", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/00c1c60b83a6b26bb5e20e358aefe74084124197.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 97200, "title": "Shofo - The World's Largest Video Library", "tagline": "Shofo is building the largest index of videos", "body": "### **TL;DR**\n\nShofo is building the largest index of videos.\n\n\n\n### **❌ The Problem**\n\nAI labs require massive, high-quality video data to train multimodal models, but clean, custom video datasets cost millions and take months to collect.\n\n### **✅ Our Solution**\n\nWe're building the world's largest library of videos by combining public videos collected from the open web and private videos aggregated from thousands of different sources. Both feed into a single, continuously updating index of billions of videos that we clean, search, and label to build custom datasets for AI teams.\n\nFor example, if a lab needs 100K hours of cooking videos featuring hand-object interactions with no scene changes, we query our index, extract the matching subset, and deliver a clean, structured dataset in days.\n\n### **🙏 Our Ask**\n\nIf you or anyone you know is working with computer vision, we'd love to chat. Reach out at [founders@shofo.ai](mailto:founders@shofo.ai) or fill out this form [here](https://www.shofo.ai/contact).\n\n### 📖 **Our Story**\n\nOur team met while building a previous startup called Correkt. Correkt was an AI search engine focused on multimodal content and reached over 40k users before pivoting to become Shofo.\n\n![uploaded image](/media/?type=post&id=97200&key=user_uploads/2355557/635c1bd9-0c05-4fcb-be47-39f092eec605)\n\n_From left to right: Braiden (COO), Alex (CTO), Bryan (CEO), and Andre (Head of AI)_\n\n### **😼 Appendix**\n\nWebsite: [https://www.shofo.ai](https://www.shofo.ai/)\n\nHugging Face: \n\nLinkedin: \n\nX: ", "url": "https://www.ycombinator.com/launches/PHk-shofo-the-world-s-largest-video-library", "votes": 45, "created_at": "2026-01-27T01:15:35.213Z" } ] }, { "id": 31301, "name": "OpenVector", "slug": "openvector", "former_names": [ "TeleOps", "BotZero", "Foveal" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/54df715903ce304e2b9e3b2fe1f375caf7811ea6.png", "website": "https://openvector.com", "all_locations": "San Francisco, CA, USA", "long_description": "OpenVector transforms any existing camera into an automated 24/7 workforce without requiring new hardware. We've built the world's fastest vision-language model inference engine that allows users to simply describe a task in plain English and automatically build a custom AI vision model to monitor their feed. When it detects an important physical event—like a stalled production cycle, a safety violation, or a waiting customer—it operates a computer just like a human to take immediate action. It integrates with legacy systems, makes calls, sends emails, updates a POS/CRM, or triggers webhooks in real time. OpenVector enables any camera to do real work.", "one_liner": "AI that turns any camera to an autonomous worker with real-time vision", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1785369468, "tags": [ "Robotics", "Computer Vision", "Infrastructure", "Industrial" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 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, "question_answers": null, "url": "https://www.ycombinator.com/companies/openvector", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/openvector.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://linked.com/in/openvectorlabs", "x_url": "https://x.com/openvectorlabs", "fb_url": "https://www.facebook.com/profile.php?id=61591381283372", "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/54df715903ce304e2b9e3b2fe1f375caf7811ea6.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": 633157, "full_name": "Andrey Gizdov", "title": "Founder/CEO", "founder_bio": "Dropped out of PhD. Computer Vision @ Harvard.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/andreygizdov/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/994295941ffb048fecb964921a35db1494d051b3.jpg" }, { "user_id": 2384953, "full_name": "Vishal Urlam", "title": "Founder", "founder_bio": "CMU'23, ECE'20 | MIT GrandHack '25 | Kellogg Design Challenge '23", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/vishal-urlam/", "x_url": "https://x.com/vishalurlam", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/398802b070ebc9a50a9873e3441541de12ccedfb.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 108360, "title": "OpenVector - Self-improving AI that turns any camera into an autonomous worker.", "tagline": "Most cameras just record. We give them the ability to do real work.", "body": "**TLDR;** OpenVector turns existing cameras into an automated 24/7 workforce. Describe a task in plain English, and it auto-builds a custom vision model that takes real-time actions on a computer when it spots an event.\n\n**Ask;** If you or someone you know runs physical operations (manufacturing, logistics, retail, security) and wants to automate visual tasks without buying new hardware, we’d love to connect!\n\n**Our Launch Video:**\n\n\n\n**Our Team:**\n\nOpenVector was founded by a team of builders and engineers obsessed with bringing self-improving visual intelligence to the physical world.\n\n* [Andrey Gizdov](https://www.linkedin.com/in/andreygizdov/), CEO, dropped a fully-funded **PhD** scholarship from Fulbright, worth **$170,000**, with invitations at **Harvard and MIT**, where he worked on real-time vision models.\n* [Vishal Urlam](https://www.linkedin.com/in/vishal-urlam/), CTO, previously automated camera systems and network protocols for Tata, the **second-largest network infrastructure in the world**. CMU embedded systems engineer.\n\n**Problem**:\n\nMany important business moments happen in the physical world: Someone tailgates. A production cycle stalls. A worker skips a step in the manufacturing process. A customer arrives, and no one responds. There are over 1 billion cameras worldwide, but they only record it for later. For physical operations, the best technology available to catch these events in real-time has been a human staring at a monitor.\n\n**Solution:**\n\nOpenVector is an AI that brings action to any camera.\n\n* **Plain English to AI Model:** No coding or expensive setup. Simply describe your task in plain English, and OpenVector automatically builds the best AI vision model for it, and watches your camera feeds 24/7. It’s an app that takes 2 minutes to download and set up, and works with any camera.\n* **Acts Like a Human:** OpenVector operates a computer just like a human based on what it sees.\n* **Legacy Integration:** It automatically integrates with your existing systems to make a call, send an email, update your POS or CRM, or trigger a webhook the second an event happens.\n* **Zero New Hardware:** Works entirely with the cameras you already have installed (custom end-to-end solutions also available).\n\n**We’ve Already Started:**\n\nOpenVector is already live and seeing use cases across security, retail, manufacturing, and logistics. We are tracking production cycle efficiency directly from existing CCTV, ensuring good-manufacturing-practices, and catching physical design errors.\n\n**Now Onboarding:**\n\nOpenVector is ready to deploy on your camera feeds today. Contact us if you’re tired of cameras that only watch and want them to actually do work for you. [founders@openvector.com](mailto:founders@openvector.com)\n\n![uploaded image](/media/?type=post&id=108360&key=user_uploads/633157/46faabca-90e0-4c69-a364-138588d733d5)\n\n", "url": "https://www.ycombinator.com/launches/SBk-openvector-self-improving-ai-that-turns-any-camera-into-an-autonomous-worker", "votes": 16, "created_at": "2026-07-31T18:00:43.590Z" } ] }, { "id": 31318, "name": "Databuddy", "slug": "databuddy", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/41cf5cb7088967b39be98f97d7bb5d8f97df5aac.png", "website": "https://www.databuddy.cc", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Databuddy gives you your very own data analyst, always watching over your data, combining all your context to investigate and paint a full picture on every product issue that emerges in real-time; conversion drops, user frustration and churn.\r\n\r\nIt makes your product better without needing to have you look at a dashboard and spend hours figuring out the why. one click to install or switch from any dated analytics provider.", "one_liner": "AI Data Analyst for fast-growing teams", "team_size": 1, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1791412796, "tags": [ "B2B", "Analytics", "Data Engineering", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2026", "status": "Active", "industries": [ "B2B", "Analytics" ], "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/databuddy", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/databuddy.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/trydatabuddy", "x_url": "https://www.twitter.com/trydatabuddy", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/databuddy", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/41cf5cb7088967b39be98f97d7bb5d8f97df5aac.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Pete Koomen", "url": "https://www.ycombinator.com/people/pete-koomen" }, "founders": [ { "user_id": 2755916, "full_name": "Issa Nassar", "title": "Founder", "founder_bio": "Building the coolest analytics platform that handles your analytics for you.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/issanassar", "x_url": "https://x.com/izadoesdev", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/91c0735889e9859c7981c36fd71679fb069d9050.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 31375, "name": "Hub", "slug": "hub", "former_names": [ "Hub", "Hub.xyz" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4807c17f08dbbfbdd8f51297746a838ba6db58c1.png", "website": "https://hub.xyz", "all_locations": "San Francisco, CA, USA", "long_description": "Hub is a multimodal lab providing real world data to frontier labs and robotic companies.", "one_liner": "Real-world training data for frontier AI labs and robotics.", "team_size": 40, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1773429014, "tags": [ "Robotics", "Crowdsourcing", "Big Data", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Spring 2026", "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/hub", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2026/hub.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/hub-xyz", "x_url": "https://x.com/hubdotxyz", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/4807c17f08dbbfbdd8f51297746a838ba6db58c1.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": 3369916, "full_name": "Armin Kiani", "title": "Founder/CEO", "founder_bio": "CS & robotics. \nMicrosoft Innovation Award, 2020. \nWorked at Freedelity, Belgium's largest consumer-data platform.\nspeeding embodied agi with hub.xyz", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/armin-k-3439033ab/", "x_url": "https://x.com/xarmin", "avatar_thumb_url": 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required", "skills": [] }, { "id": 114525, "title": "Machine Learning Engineer", "url": "https://www.ycombinator.com/companies/hub/jobs/ghznA3v-machine-learning-engineer", "location": "Paris, IDF, FR / Paris, Île-de-France, FR", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$90K - $120K", "equity_range": "0.02% - 0.20%", "experience": "3+ years", "visa": "US citizenship/visa not required", "skills": [] } ], "news": [], "launches": [ { "id": 103084, "title": "Hub: real-world training data for frontier AI labs and robotics", "tagline": "Leveraging a global human network to collect data that don’t exist yet.", "body": "Hub provides real-world training data to frontier AI labs and robotics companies. We went to 7-figure revenue agreement on data delivery during the last weeks, working with some of the biggest names in AI and robotics.\\\n\\\n**Why now**\n\nThe gap between frontier models is closing, and internet-scale data is largely exhausted. The only edge left is real-world data that humans have to produce. Every lab now wins or loses on its edge cases, and edge cases need specific data captured by specific people: data that doesn't exist anywhere online. Whoever can go collect the right data first ships the better model first. Human labor is half of global GDP, and almost none of it has been recorded yet.\n\n**What Hub does**\n\nWe capture this data through a global network of humans, across all continents. We route and activate the exact people who fit a lab's brief and deliver in days, not the months it takes to source a generic dataset off the shelf. Because we collect the data ourselves, we can attest its provenance, which you can't do for data you didn't capture. Our ML and QA pipelines then verify and enrich it, so we meet the hardest dataset requirements labs throw at us. The moat isn't the data, it's how fast we can go get it.\n\n**Traction**\n\nFrom 5-figure to 7-figure in revenue agreement on successful data delivery. We now work with some of the biggest frontier AI labs and robotics companies in the world.\n\n**The ask**\n\nTwo asks: —> You're building frontier models or robots and data is your constraint. \\\n—> You're a top robotics engineer, a PhD whose research touches robotics or egocentric data, or someone with deep experience at a leading robotics lab, we're hiring. \\\n\\\nReach out here: [founders@hub.xyz](mailto:founders@hub.xyz).", "url": "https://www.ycombinator.com/launches/Qoe-hub-real-world-training-data-for-frontier-ai-labs-and-robotics", "votes": 1, "created_at": "2026-06-15T14:57:21.570Z" } ] }, { "id": 31516, "name": "Expanse", "slug": "expanse", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/af6cfe1f95da6fb2bfc1789fb605ed70b77da3b4.png", "website": "https://expanse.sh", "all_locations": "London, England, United Kingdom", "long_description": "Expanse unlocks wasted GPU capacity. We recover idle compute through three capabilities: resource prediction (right-sizing job submissions before they reach the scheduler), optimisation suggestions (code and config changes researchers can apply themselves), and failure prediction (catching jobs that will fail before they consume hours of GPU time).\r\n\r\nWe’re four engineers. We ran HPC and GPU training workloads at the largest quant funds and national supercomputing centres. We faced this problem first hand and the only fix was to over-provision and burn millions. Ismaeel built the first multimodal HPC resource predictor as research at EPCC (Edinburgh’s Parallel Computing Centre), which beat every published baseline. This is the tool we wish we had.", "one_liner": "Unlock wasted GPU capacity.", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1777849866, "tags": [ "Deep Learning", "B2B", "Infrastructure", "ML" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2026", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United Kingdom", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/expanse", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2026/expanse.json", "year_founded": 2025, "city": "London", "country": "GB", "linkedin_url": "https://www.linkedin.com/company/expanse-compute", "x_url": "https://x.com/ExpanseCompute", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/expanse", "github_url": "https://github.com/expanse-labs", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/af6cfe1f95da6fb2bfc1789fb605ed70b77da3b4.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/1a2d766656b058e3ae5a7333ccf58b05bb9d8689.png" ], "primary_partner": { "name": "David Lieb", "url": "https://www.ycombinator.com/people/david-lieb" }, "founders": [ { "user_id": 3381342, "full_name": "Ismaeel Bashir", "title": "Founder/CEO", "founder_bio": "Ismaeel is co-founder and CEO of Expanse. Built the first multimodal HPC resource predictor at EPCC (Edinburgh’s Parallel Computing Centre), beating every published baseline. Previously: ran large scale ML models at one of the world’s largest quantitative funds (QRT). Studied Computer Science at the University of Edinburgh.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/ismaeel-bashir/", "x_url": "https://x.com/ismaeel_bashir_", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3c4fa6230901fda37ce33a006271ece271e5e9e8.jpg" }, { "user_id": 3409042, "full_name": "Nikodem Bieniek", "title": "Founder", "founder_bio": "Nikodem is co-founder and CTO of Expanse. Trained and optimised speech recognition models on GPU clusters. Previously: managed the platforms researchers and engineers depended on at one of the world’s largest hedge funds (Millennium). Studied Computer Science at the University of Edinburgh.", "is_active": true, "linkedin_url": "https://linkedin.com/in/nikodemb/", "x_url": "https://x.com/nkdem_b", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c2d55059ebf4b59335ad292b3cc38a1e9d667650.jpg" }, { "user_id": 3409418, "full_name": "Yafet Melake", "title": "Founder", "founder_bio": "Yafet is co-founder and COO of Expanse. Built the first GNN-based cluster graph network for predicting SLURM queue wait times at EPCC (Edinburgh’s Parallel Computing Centre). Previously: tooling and infrastructure for researchers at one of the world’s largest quantitative funds (G-Research). Studied Computer Science at the University of Edinburgh.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/yafet-melake", "x_url": "https://x.com/yafet_melake", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/db8ab1acbb09fe838ce4d380889c7d1c27bf0975.jpg" }, { "user_id": 2274795, "full_name": "Eren Mendi", "title": "Founder", "founder_bio": "Eren is co-founder and CPO of Expanse. Built state-of-the-art decentralised foundation model training systems and performance models. Previously: prototyped emerging technologies in quantitative finance (G-Research). Studied Computer Science at the University of Edinburgh and Imperial College London.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/eren-mendi-929b55138", "x_url": "https://x.com/erenzmendi03", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/af898412d2d555432b879560ffcdfde4fbb3e53a.jpg" } ], "jobs": [], "news": [ { "title": "Why we started Expanse, and our $5.3M seed · Expanse Blog", "url": "https://expanse.sh/blog/expanse-raises-5-3m-seed", "date": "Sep 16, 2026" }, { "title": "What Y Combinator's Latest Batch Reveals About The Future", "url": "https://www.forbes.com/sites/dariashunina/2026/06/04/what-y-combinators-latest-batch-reveals-about-the-future/", "date": "Jun 08, 2026" } ], "launches": [ { "id": 100703, "title": "Expanse - Unlock wasted GPU capacity", "tagline": "Unlock wasted GPU capacity.", "body": "**TL;DR**\n\nExpanse unlocks wasted GPU capacity. We’re the intelligence layer for compute infrastructure. Submit jobs with the right resources. Optimise them to run faster. Debug failures in seconds, not days. Works on cloud and on-prem HPC.\n\nWant to know how much more you can get out of your hardware? Schedule a call: \n\n**Problem**\n\nRunning compute on a cluster means guessing memory, time, and GPUs before you submit. Get it wrong and your job fails mid-run. Over-guess and you pay for compute you never use. 30% of cloud spend is lost to over-allocation \\[1\\]. Microsoft Research found their own deep learning jobs hit 50% GPU utilisation or lower \\[2\\].\n\nSizing jobs takes decades of experience. Memory patterns, batching, GPU threading, CPU vectorisation. AI agents don’t have enough information to fix it either. SLURM and Kubernetes don’t expose enough structured data. Even strong platform teams are forced to choose: spend time debugging and optimising every job, or accept the waste. AI infrastructure spending will hit $2.52 trillion in 2026 \\[3\\]. The waste grows with every new cluster. This problem isn’t going away.\n\n**Solution**\n\nExpanse learns your cluster. We analyse your code and hardware telemetry, then track them over time. Our deep learning models build a picture of what your workloads actually need. Predictions get sharper with every job.\n\nOur models are deployed on your cluster. All analysis runs on your network. Your code and telemetry never leave your infrastructure. We can’t see your data, and you maintain full data sovereignty.\n\nOne command installs Expanse on your cluster. You get two tools.\n\n`expanse analyse` - for every job:\n\n* **Suggests the right resource configuration**\n* **Predicts failures from historical code and telemetry patterns**\n* **Surfaces code-level optimisations that increase efficiency**\n\n`expanse diagnose` - for every failure:\n\n* **Finds the root cause**\n* **Returns solution-oriented logs with the exact code and config changes to fix it**\n\nDays of debugging and optimising become seconds. Platform teams get what they need to do this in minutes instead of weeks.\n\n**Founders**\n\nWe're four engineers from the University of Edinburgh, all coming from top quant funds and national supercomputing centres. Ismaeel built the first multimodal HPC resource predictor at EPCC (Edinburgh's Parallel Computing Centre), beating every published baseline. Yafet built the first GNN cluster graph network for predicting SLURM queue wait times. Eren built decentralised foundation model training systems at Edinburgh. Niko trained large-scale speech ML models on GPU clusters and architected cloud and Kubernetes infrastructure at one of the largest hedge funds in the world. We left our jobs to fix this ourselves.\n\n**CTA / Ask**\n\nRunning compute and not getting enough out of what you’re paying for? Failing jobs, unclear errors, bills too high? We’d love to chat.\n\nKnow anyone in AI infrastructure (managing cloud and/or on-premise data centres), quant finance, drug discovery, or AI research labs? An intro would mean a lot :)\n\n**YC Deal**\n\nAll YC companies running serious ML training can contact us for a discounted pilot. We’ll find inefficiencies and wastage on your compute setup. Then we deploy Expanse, no changes to your workflows. You get more out of the hardware you’re paying for.\n\nReach out: [founders@expanse.sh](mailto:founders@expanse.sh) or \n\nReferences\n\n\\[1\\] \n\n\\[2\\] \n\n\\[3\\] ", "url": "https://www.ycombinator.com/launches/QCF-expanse-unlock-wasted-gpu-capacity", "votes": 53, "created_at": "2026-05-04T04:30:18.506Z" } ] }, { "id": 31526, "name": "Uno Wallet", "slug": "uno-wallet", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c2393bf402ae2e425fc41cb7f78facb4b67fa9d5.png", "website": "https://myunowallet.com/", "all_locations": "San Francisco, CA, USA", "long_description": "We are changing the way that people pay...\r\nFounded by:\r\nSaket Joshi: www.linkedin.com/in/saket-dattatray-joshi/\r\nMordi Shadpour: www.linkedin.com/in/mordi-shadpour/", "one_liner": "The AI mobile wallet that replaces Apple Pay", "team_size": 2, "industry": "Fintech", "subindustry": "Fintech -> Payments", "launched_at": 1779834493, "tags": [ "Fintech", "Payments", "Consumer", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Spring 2026", "status": "Active", "industries": [ "Fintech", "Payments" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": [ { "question": "How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)", "answer": "The founders met at a Harvard startup mixer in 2023 and immediately bonded over fintech. They stayed in touch as friends and idea sparring partners, and later realized that advances in AI and new platform unlocks made Uno Wallet a massive opportunity to build together in the infrastructure and fintech space." } ], "url": "https://www.ycombinator.com/companies/uno-wallet", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2026/uno-wallet.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/uno-wallet", "x_url": "https://x.com/MyUnoWallet", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/c2393bf402ae2e425fc41cb7f78facb4b67fa9d5.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/1fecca5d8dafd39142796c306a3102c067cff398.png" ], "primary_partner": { "name": "Andrew Miklas", "url": "https://www.ycombinator.com/people/andrew-miklas" }, "founders": [ { "user_id": 1631278, "full_name": "Mordi Shadpour", "title": "Founder/CEO", "founder_bio": "Co-founder & CEO of Uno Wallet | MBA @ Harvard\nBuilding the AI that automates your financial life, starting with the decision everyone gets wrong 50 times a month: which card to tap.\n\nBloomberg Terminal. California native, based in the Bay Area.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/mordi-shadpour", "x_url": "https://x.com/MordiShadpour", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/845444df2aded4c1492d125d61ff8d68a63131cd.jpg" } ], "jobs": [ { "id": 103221, "title": "Founding Engineer - Product & Infrastructure", "url": "https://www.ycombinator.com/companies/uno-wallet/jobs/UsckBfY-founding-engineer-product-infrastructure", "location": "San Francisco, CA, US / Palo Alto, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$120K - $205K", "equity_range": "0.50% - 2.00%", "experience": "1+ years", "visa": "Will sponsor", "skills": [] }, { "id": 113112, "title": "Founding Head of Product", "url": "https://www.ycombinator.com/companies/uno-wallet/jobs/VzmlenM-founding-head-of-product", "location": "South San Francisco, CA, US / Palo Alto, CA, US", "type": "Full-time", "role": "Product", "role_type": null, "salary_range": "$125K - $200K", "equity_range": "0.50% - 2.50%", "experience": "3+ years", "visa": "Will sponsor", "skills": [] } ], "news": [], "launches": [] }, { "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, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/de52713fe1552551dbe8aa2a5e60202c09bfc0d7.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "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\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", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1783408799, "tags": [ "Developer Tools", "SaaS", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": true, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/rindler", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/rindler.json", "year_founded": 2025, "city": "Boston", "country": "US", "linkedin_url": "https://www.linkedin.com/company/rindler", "x_url": "https://x.com/RindlerAI", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/ba85eb3919f954ce9bf661f9b9ee195327c93ceb.png", "app_video_url": "https://bookface-images.s3.us-west-2.amazonaws.com/bf-public_profile/31628/app_video.mp4?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAQC4NIECANGNRRAJW%2F20261020%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20261020T022738Z&X-Amz-Expires=60&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEHEaCXVzLXdlc3QtMiJHMEUCIQC3G81IFSUZtThVVLqv%2FNP8JAonBeKueJ3nqFDE3FxXUwIgKp6ifAPW9xtNk4cHGnVzE9T5oK7HksFpS9B%2BDm%2FLIOQq5QMIOhAAGgwwMDYyMDE4MTEwNzIiDMiErSqdA9fZ5I2ahyrCAyhI4VxFZU5tGwj2zBKwzP3YopALEsVr%2F%2BZE%2BqKG5ExbN%2FLTC2qWrBSqlDY2M5sbNAwfqQqFkcx31kz1vOn4FSuJMRYW%2BkzTF0sHdYK6D3qvReS29sXOai4xEgytMpWv0HHodzBVtqmM6lhZul7EdriU1r3NMgn6kwrys472GaamCoy9cButcMuxdA6JAW7AePBgk0hcnFGzaY5aao9TXEqqqLDlP1z95aeQK0rFfjBuVVTlW6dspQwwAJwsuJjoI9t1YkL4Lit4gUGj1QI7PUIH70gMRgnlfqNLB7jJcwv%2BI4Rfgnv%2FfKmc5%2BoYexcBkjZu9myZq6QOA6uBoHrB0oTKfDnTUxCfp3Zyd%2BYXd%2BRBrzgSL0LnII%2Fr1P71gX8BqFIaJIcILi5J6qUg2doC6qXH8L6zz0Tim2049E5pbQ072LSzepYlZMqQ983uJSL3eUXk86ehR9Lyldz67yIvyCRilZUgb11jcjrMydu%2Fj2RI4J5upBB3IYDl1jhGlV%2FvgsHTaVujKGAhe3lEnUZs9YdCRwpmLb5XcbpM70m15Z8MQhDcr6si85gNENVvPMk4eUw4FkmyLz2%2FrGX%2BhkiQHEAiUzDJ%2FdrWBjqlAa1FguiGB0WcOcaP9Dwwt66PPG2naOQP7x5F5wwTg7gWx2PYYqZ05ZF%2F2dhdA4HJKOntgl0neDqra19sFySGeXNdHt7tNNndMpVniacUOziehXVxpr49zgL%2FhWtvSxfqv2mUAjPVCs%2FBJs6SqN3WzVfiA2RUodOJqzLA7KluY8D8t3zxMbqsQdARPCP3FgqSkJ8A8HTGWYo9w0rLlT%2Fugv6qZCfQcg%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=75c8f2ef5b675327c07a14b514bbf81a3d4208eb77c04dbd585c94ad46792ecf", "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Ankit Gupta", "url": "https://www.ycombinator.com/people/ankit-gupta" }, "founders": [ { "user_id": 3137449, "full_name": "Michael Serrano", "title": "Founder/CEO", "founder_bio": "CEO of Rindler. MIT SB + MEng in Physics and Computer Science.\n\nPrev: ML engineer at Roblox, LLM research at MIT CSAIL.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/michael-y-serrano", "x_url": "https://x.com/m_y_serrano", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f3cd87258b68e1b56889ab4cd3dfe82eb0c9fcdd.jpg" }, { "user_id": 3443947, "full_name": "Arthur De Los Santos", "title": "Founder/CTO", "founder_bio": "MIT '26 in CS/AI/ML\nWe're building Rindler, the infrastructure layer that allows AI agents to buy, book, and browse on any website.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/arthurdelossantos", "x_url": "https://x.com/_arthurdls_", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c56d4f5147e18b73ad91bb87d13c4f42271e652f.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 104865, "title": "Rindler - Turn Any Website Into An API For AI Agents", "tagline": "Reliable web actions for AI agents, without integrations or scripts", "body": "**TL;DR:** Rindler turns websites into deterministic APIs for AI agents. We map a site once into screens, actions, and structured outputs, so agents can read data and take actions quickly and reliably.\n\n**Ask:** If you’re building an agent that needs to browse the web, compare products, fill forms, search listings, use authenticated portals, or act on third-party websites without an API, we’d love to help.\n\n\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", "url": "https://www.ycombinator.com/launches/RHN-rindler-turn-any-website-into-an-api-for-ai-agents", "votes": 17, "created_at": "2026-07-09T11:07:42.901Z" } ] }, { "id": 31591, "name": "RightNow", "slug": "rightnow", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/59b2e02a314037738d9f32192f83e8bd442be246.png", "website": "https://runinfra.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "RightNow AI is a research lab for GPU kernel optimization. Our platform RunInfra serves top open-source models optimized for AI agents at a fraction of the cost of closed-source APIs\r\n\r\nRightNow AI lab: https://rightnowai.co\r\nRunInfra platform: https://runinfra.ai.", "one_liner": "Co-designing the fastest intelligence", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1779474756, "tags": [ "Developer Tools", "Generative AI", "Machine Learning", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 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, "question_answers": null, "url": "https://www.ycombinator.com/companies/rightnow", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/rightnow.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/rightnowai/", "x_url": "https://x.com/rightnowai_co", "fb_url": null, "cb_url": null, "github_url": "https://github.com/RightNow-AI", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/59b2e02a314037738d9f32192f83e8bd442be246.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Nicolas Dessaigne", "url": "https://www.ycombinator.com/people/nicolas-dessaigne" }, "founders": [ { "user_id": 1615104, "full_name": "Jaber Jaber", "title": "Founder", "founder_bio": "Technical Co-founder at RightNow (YC F26)", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jaber-jaber-b65246234", "x_url": "https://x.com/Akashi203", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d84f84e8e758be1fe000c134de47a36196f14705.jpg" }, { "user_id": 3147259, "full_name": "Osama Jaber", "title": "Founder/CMO", "founder_bio": "Commercial Co-founder at RightNow (YC F26)\n", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/osama-jaber-osama2001/", "x_url": "https://x.com/OsamaKakashi", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f6bf68d49afc56cca1afb65f6882a4b4cf721300.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 32131, "name": "Shielded", "slug": "shielded", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/eec883dcf84a87963c1d7874cef470c16c9dad19.png", "website": "https://www.shieldedglobal.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Shielded connects companies’ internal and external data to map market shifts, tariffs, and disruptions directly to suppliers, products, and margins. We turn those impacts into real-time decisions that grow and protect the business. ", "one_liner": "We help Fortune 500 companies hedge their supply chain risk", "team_size": 0, "industry": "B2B", "subindustry": "B2B -> Finance and Accounting", "launched_at": 1784606823, "tags": [ "Fintech", "Supply Chain", "Agriculture", "Energy", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "B2B", "Finance and Accounting" ], "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/shielded", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/shielded.json", "year_founded": null, "city": "San Francisco", "country": "US", "linkedin_url": "https://linkedin.com/company/shieldedglobal", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/eec883dcf84a87963c1d7874cef470c16c9dad19.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": [], "jobs": [], "news": [], "launches": [ { "id": 109233, "title": "Shielded: The company brain for supply chain risk", "tagline": "Shielded helps manufacturers understand and act on supply chain risk in real time.", "body": "Shielded helps manufacturers understand and act on supply chain risk in real time.\n\nAs the world has become more volatile, businesses need a tool to monitor events and rapidly take action. Founder James Simon saw this problem first hand in commodities trading, in fact his whole job was to take advantage of other firms reacting too slowly as the world changed. \n\nThat’s what inspired him to build Shielded, as an intelligence layer that integrates quickly, deeply understands your specific business, and turns volatility into clear, proactive decisions.\n\nShielded supports critical part and supplier management for leading defense companies, ingredient price audits for multinational CPG firms, and tariff impact analysis for global manufacturers.\n\nWith API, MCP, BOM, and spreadsheet integrations, every customer deployment to date has taken less than 72 hours.\n\nInstead of simply receiving an alert when something happens, Shielded gives procurement, finance, and supply chain teams company-specific guidance on the impacts of external events, market shifts, and regulation changes, and recommends the right operational or hedging responses.\n\nShielded is your supply chain’s command center that never sleeps.\n\n", "url": "https://www.ycombinator.com/launches/SPp-shielded-the-company-brain-for-supply-chain-risk", "votes": 5, "created_at": "2026-08-06T18:00:00.390Z" } ] }, { "id": 32198, "name": "Riften", "slug": "riften", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d3c58cea1afce06f81a0352c8f3ecc8554d707c7.png", "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, "tags": [ "Developer Tools", "Reinforcement Learning", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 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, "question_answers": null, "url": "https://www.ycombinator.com/companies/riften", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/riften.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/riftenai/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/d3c58cea1afce06f81a0352c8f3ecc8554d707c7.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Harshita Arora", "url": "https://www.ycombinator.com/people/harshita-arora" }, "founders": [ { "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/", "x_url": "https://x.com/carlstauffer_", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0a3a2f44ecdd315423ad0b8510ef3bffafaf4843.jpg" } ], "jobs": [], "news": [], "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" } ] }, { "id": 32225, "name": "Stoa", "slug": "stoa", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cf71f2bfca9f3f554d22c43f0dfd7b1a38171535.png", "website": "https://www.stoaexchange.com", "all_locations": "San Francisco, CA, USA", "long_description": "Stoa provides pricing and trading infrastructure for AI hardware, live with an RFQ marketplace where companies buy and sell GPUs through vetted dealers real-time.", "one_liner": "The market behind AI hardware.", "team_size": 3, "industry": "Fintech", "subindustry": "Fintech", "launched_at": 1785367811, "tags": [ "Fintech", "Hardware", "Marketplace", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "Fintech" ], "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/stoa", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/stoa.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/stoamarkets/", "x_url": "https://x.com/stoaexchange", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/stoa-d396", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/cf71f2bfca9f3f554d22c43f0dfd7b1a38171535.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": 1961995, "full_name": "Berat Celik", "title": "Founder/CEO", "founder_bio": "CEO of Stoa. Repeat founder who walked away from xAI to build Stoa. UBC, computer science and economics; Cornell M.Eng., computer science.", "is_active": true, "linkedin_url": "https://linkedin.com/in/beratcelik1", "x_url": "https://x.com/beratcelik0", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3db0925f484f9622bdabb784771b1618d0408f66.jpg" }, { "user_id": 1960190, "full_name": "Eren Berke Saglam", "title": "Founder/CFO", "founder_bio": "CFO of Stoa. Traded interest rates derivatives at Citi. Dartmouth salutatorian, computer science and economics.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/eren-berke-saglam", "x_url": "https://x.com/erenberke0", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/8fa08c8d9b7dd4e7053173162485cba755b2b252.jpg" }, { "user_id": 3415052, "full_name": "Kaan Yigit", "title": "Founder/CTO", "founder_bio": "CTO of Stoa. Worked as a quantitative developer at Uniper, building the trading systems behind financial oil and gas books. UIUC, computer science.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/kaan-yigit/", "x_url": "https://x.com/kaan_yigit0", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/94061540990806801bdde87e10a5a8fad1228468.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 108473, "title": "Stoa: The market behind AI hardware", "tagline": "GPU marketplace where vetted dealers bid blind with firm quotes. $300M+ in RFQs in our first month.", "body": "**TL;DR:** AI hardware trades over phone calls and forwarded spreadsheets. No venue, no price to mark against: lenders mark billions in GPU collateral off appraisals. We're building Stoa, an RFQ marketplace where buyers and sellers get firm quotes within 48 hours, and settled trades build the prices the market can mark, finance, and hedge against.\n\n\n\nGPU deals close in group chats. We know because we've been in them.\n\nA price arrives as a voice note. Someone forwards an inventory list, then it gets forwarded again, and soon three brokers are offering the same machines. Nobody knows who actually owns what or whether any quote is firm.\n\nThe market behind those chats is worth hundreds of billions of dollars a year. Lenders mark billions in GPU collateral off appraisals, not trades.\n\nWe're Berat, Eren, and Kaan. We're building Stoa.\n\nAI hardware is becoming an asset class, but its market is missing the basics: a venue where hardware can trade, prices that buyers, sellers, and lenders can mark against, and eventually financing and hedging built on those prices. We're starting with the venue: an RFQ marketplace for GPUs. It gets buyers and sellers firm quotes, and every bid and settlement builds the history the rest needs.\n\n**Here's how it works**\n\nPost what you want to buy or sell: B300s, H200s, H100s, a bare card or a full cluster, new or secondary.\n\nVetted dealers bid blind with firm quotes. Instead of spending weeks calling around, you get through the RFQ in 48 hours.\n\nWe handle the unglamorous parts too: KYB and counterparty checks, contracts, shipping, and settlement.\n\nIn our first month, $300M+ in RFQs ran through the book.\n\n**Why the marketplace comes first**\n\nAsk what an H100 is worth and everyone you call gives you a different answer.\n\nOn Stoa, dealers quote against the same RFQ without seeing each other's bids. Because every RFQ, firm quote, award, and settlement runs through us, we see what the hardware actually trades for.\n\nA quote is an opinion. A settled trade is a receipt.\n\nThat transaction history becomes prices buyers, sellers, and lenders can mark against. Once marks are grounded in settled trades, financing and hedging can follow.\n\nPlatts started printing oil prices in a magazine. Kelley Blue Book began as one dealer's published list of what he'd pay for cars. GPU inventory is still being passed around in forwarded spreadsheets, and Blackwell upgrades are now pushing H100 fleets into the secondary market.\n\nSomeone is going to be the price.\n\n**The team**\n\nWe've known each other for more than ten years. We have founded companies, traded interest rate derivatives, and built trading and pricing infrastructure for oil and gas. Now we're building it for AI hardware.\n\n**Buying or selling?**\n\nIf you're buying GPUs or compute, or you're sitting on hardware, sign up at [stoaexchange.com](http://stoaexchange.com).\n\n**Schedule a call: [https://stoa.cal.com/stoa/intro](https://stoa.cal.com/stoa/intro)**\n\n**Email us: [founders@stoaexchange.com](mailto:founders@stoaexchange.com)**\n\n**Text or call us:** +1 510 605 3844\n\nAnd if you know infrastructure heads at neoclouds or data centers, hyperscaler capex teams, dealers, ITADs, or credit desks lending against GPUs, please send this their way.\n\nBerat, Eren & Kaan", "url": "https://www.ycombinator.com/launches/SDZ-stoa-the-market-behind-ai-hardware", "votes": 779, "created_at": "2026-07-31T12:13:42.502Z" } ] }, { "id": 32253, "name": "Touchmark", "slug": "touchmark", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fac4fb7e32c7424e6eea88690415f386be2f5832.png", "website": "https://touchmark.ai", "all_locations": "San Francisco, CA, USA", "long_description": "Buy tokens over a time window from the provider of your choice at a price fixed today - 10-30% off the on-demand price. If your plans change - resell your reserved capacity to another buyer.", "one_liner": "Market for future inference capacity", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1781312801, "tags": [ "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 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, "question_answers": null, "url": "https://www.ycombinator.com/companies/touchmark", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/touchmark.json", "year_founded": null, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/touchmark-ai", "x_url": "https://x.com/TouchmarkAI", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/fac4fb7e32c7424e6eea88690415f386be2f5832.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": 1998938, "full_name": "Ilia Bolgov", "title": "Founder/CEO", "founder_bio": "Co-founder of Touchmark. Product @ Revolut, Maths @ Imperial College London.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/ilia-bolgov-8683b0254", "x_url": "https://x.com/iliabolgov", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3922ff830a5e34f8d4d4a2a31ed11113a28e954e.jpg" }, { "user_id": 3532865, "full_name": "Roman Yanushevskyi", "title": "Founder/CTO", "founder_bio": "Co-Founder at Touchmark. Previously 2x Quantitative Research intern at Citadel Securities, AI Engineering intern at Lovable. Math and CS graduate from the National University of Singapore. IOI gold medalist.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/roman-yanushevskyi/", "x_url": "https://x.com/ryanushevskyi", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c1c4b14a1f4d9113b9badc24e14f63df1cde9840.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 110492, "title": "Touchmark: Market for future inference capacity", "tagline": "Buy tokens in advance with flexibility to resell unused capacity up to 30%+ off - or more for larger orders via direct quotes", "body": "**TL;DR:** We are building a market for future inference capacity. You buy tokens for a model over a time window from the provider of your choice at a price fixed today (up to 30% off - or more for larger orders via direct quotes). If your plans change, you will be able to resell your reserved capacity to another buyer.\n\n\n\n**Problem**\n\nToken spend is growing and it’s growing fast. Out of 100+ companies we spoke to, most are trying to cut their inference costs.\n\nReserved capacity guarantee deals provide discounts + certainty, but are negotiated bilaterally, take time, and are **hard to switch from** - as a buyer you commit by prepayment, which you lose if you switch to a different provider, or in some cases even a different model.\n\nWhat if a buyer could:\n\n1. See all possible discounted capacity deals in one place\n2. Buy with a click of a button\n3. Have an option to resell to another buyer with another click of a button\n\n**But why would model providers (sellers) want this?**\n\nIn short:\n\n1. Model providers’ goal is to maximise GPU utilization - the more information they have about future demand, the better they can allocate capacity.\n2. Selling future capacity is an excellent way to finance GPU compute - dilution-free and interest-free\n3. Extra distribution channel for enterprise buyers\n\n**What if a new model comes out but I already bought capacity for the older one?**\n\nContracts for “Best model in class” allow you to buy frontier model capacity in advance. And even if you're holding a contract on an older model when a new generation ships - far from every application needs the frontier, so you can list your capacity for resale.\n\n**What if I am a _very large_ buyer and these discounts are not enough?**\n\nWe are launching Requests for Quotes (RFQs) - as a buyer you can create a request for capacity you need and let providers bid to offer you the best price.\n\n**Team**\n\nIlia: Maths & Finance @ Imperial, Product (Wealth & Trading) @ Revolut\n\nRoman: CS + Math @ NUS, IOI gold, 2x Quant Research @ Citadel Securities, AI engineer @ Lovable\n\n**If you're a company buying tokens or a model provider, email us at [contact@touchmark.ai](mailto:contact@touchmark.ai) or sign up at[ https://app.touchmark.ai/signup](https://app.touchmark.ai/signup)**\n\n_Capacity transactions on Touchmark are limited to commercial producers and commercial end users in the wholesale capacity market. Sellers offer capacity to Buyers that purchase it to consume or use in connection with the Buyers' commercial operations. Some contracts are available only in the primary markets._", "url": "https://www.ycombinator.com/launches/Sk8-touchmark-market-for-future-inference-capacity", "votes": 26, "created_at": "2026-08-14T13:43:29.567Z" } ] }, { "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" ], "tags_highlighted": [], "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", "x_url": "https://x.com/agencytoolco", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/244ddf9b0965c4c601170d71dd660ad1a89f8792.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "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" } ], "jobs": [], "news": [], "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\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": 32618, "name": "Click", "slug": "click", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3eb675c91f3464d134cd3d9c18712ad08bea23bb.png", "website": "https://www.useclick.ai", "all_locations": "San Francisco, CA, USA", "long_description": "Click serves agents over an API. Bring your model keys, tools, and context - Click runs the agent and streams back events.\r\nAsk your coding agent about useclick.ai/reference!", "one_liner": "Managed Agents API", "team_size": 1, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1785963586, "tags": [ "API", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 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/click", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/click.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/use-click", "x_url": "https://x.com/useclick_ai", "fb_url": null, "cb_url": null, "github_url": "https://github.com/use-click/", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/3eb675c91f3464d134cd3d9c18712ad08bea23bb.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/29bbb33ca2f50ca76c9e6e410f2b4252a484c4e9.png" ], "primary_partner": { "name": "Harshita Arora", "url": "https://www.ycombinator.com/people/harshita-arora" }, "founders": [ { "user_id": 1995988, "full_name": "Aditya Asgaonkar", "title": "Founder/CEO", "founder_bio": "Founder at Click. Previously helped build Ethereum's distributed system (proof-of-stake) as an open-source contributor at the Ethereum Foundation.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/aditya-asgaonkar/", "x_url": "https://x.com/adiasg", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1d21221f7711a082e5615e10bb6d4053d1be4205.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 110141, "title": "Click - Research services inside Codex & Claude", "tagline": "Live external context from professional & social platforms, marketplaces, financials, and more.", "body": "**TLDR:** Click is an MCP that provides extensive research connectors to give external context that the built-in web search misses.\n\n![uploaded image](/media/?type=post&id=110141&key=user_uploads/1995988/91aff538-41b1-4c8b-96eb-c1bf84bd5e47)\n\n**Video:** \n\n**Problem:**\n\nClick is largely motivated by a change in my own behavior:\n\nCodex & Claude are amazing products. I live inside their surface now - using it more than my browser. It feels like home, to the point that I’m annoyed to have to leave. Most often, I’m stepping outside to do external-facing tasks, like researching my leads on LinkedIn or comparing flight options. I want my agents to do these tasks as well.\n\nCurrently, those can’t be completed because their gateway to the world (in-built web search) has limited access. Often the agent also asks to use the browser with a logged-in session, which I’m uncomfortable with.\n\nSo, I built the connector layer that I wish existed.\n\n**Solution:**\n\nClick’s MCP is a single installation that provides your agent with an ever-growing bundle of the best data connectors. The current set of connectors enable new use cases inside the chat, like:\n\n* Lead research & enrichment\n* Researching ad campaigns from competitors\n* Analyzing sentiment around a topic across social media\n* Planning travel with live fares & availability\n\n**Team:**\n\nI’m Aditya, the founder of Click. Previously, I helped build Ethereum, with a vision to create a platform that enables new kinds of applications. \n\nNow, I’m focusing on the next application platform - the AI chat surface. Click builds useful services that meet users right inside the conversation. I’m building one trusted service at a time, and research is the first one.", "url": "https://www.ycombinator.com/launches/SeT-click-research-services-inside-codex-claude", "votes": 10, "created_at": "2026-08-12T19:00:01.957Z" } ] }, { "id": 32848, "name": "Luca IQ", "slug": "luca-iq", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/05718bc482e46fde4208c29e7eef28f2f4b686e7.png", "website": "https://lucaiq.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Luca IQ is an API for deterministic tax calculation and an IRS Authorized e-filing engine - the foundation for accounting firms and fintechs building on tax.", "one_liner": "API-first tax engine for CPA firms and developers", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Finance and Accounting", "launched_at": 1785364349, "tags": [ "B2B", "API", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "B2B", "Finance and Accounting" ], "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/luca-iq", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/luca-iq.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/lucaiq", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/05718bc482e46fde4208c29e7eef28f2f4b686e7.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/b7319b807eb27608540596ccef27337c2998ea22.png" ], "primary_partner": { "name": "Jared Friedman", "url": "https://www.ycombinator.com/people/jared-friedman" }, "founders": [ { "user_id": 2754880, "full_name": "Angelo Policicchio", "title": "Founder/CEO", "founder_bio": "Founder at Luca IQ. CPA. Previously Equity Research Associate at Credit Suisse, Forensic Accounting at the FBI, Public Accountant at EY. MBA from Harvard Business School.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/angelo-policicchio", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/56e0986c5f092107d5de09990091ea3d9a92d763.jpg" }, { "user_id": 3101824, "full_name": "Akash Sadashivapeth", "title": "Founder/CTO", "founder_bio": "Founder at Luca IQ. Previously Head of Data Science at Welligence Energy Analytics.\n\nStudied Data Science at Penn and an MBA from Harvard Business School.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/akash-sadashivapeth/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/19e9446ccd10b06ab85431a7e79b07c759587087.jpg" } ], "jobs": [ { "id": 108815, "title": "Founding Tax Lead (CPA or EA Required)", "url": "https://www.ycombinator.com/companies/luca-iq/jobs/VQUCBls-founding-tax-lead-cpa-or-ea-required", "location": "Chicago, IL, US / Remote (US)", "type": "Full-time", "role": "Product", "role_type": null, "salary_range": "$100K - $200K", "equity_range": "0.25% - 1.50%", "experience": "6+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 110614, "title": "AI Engineer", "url": "https://www.ycombinator.com/companies/luca-iq/jobs/U8IX0ke-ai-engineer", "location": "Chicago, IL, US", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$150K - $200K", "equity_range": "", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "Python", "Machine learning", "LLMs", "Fine-tuning", "Evals", "AI Agents" ] } ], "news": [ { "title": "Luca IQ receives IRS approval for federal 1040 e-filing", "url": "https://cfotech.news/story/luca-iq-receives-irs-approval-for-federal-1040-e-filing", "date": "Aug 03, 2026" }, { "title": "Tech news: Luca IQ launches with e-file approved tax engine for CPA firms | Accounting Today", "url": "https://www.accountingtoday.com/list/tech-news-luca-iq-launches-with-e-file-approved-tax-engine-for-cpa-firms", "date": "Jul 31, 2026" } ], "launches": [ { "id": 108364, "title": "Luca IQ - An API for U.S. tax calculation and e-filing", "tagline": "An open API, IRS-authorized e-file tax engine for CPA firms and Fintechs", "body": "# \\*\\*\\*\\*\n\n**TL;DR: We're building a modern tax engine for accountants and fintechs building on tax: a deterministic tax calculation and e-filing core behind a single API, built on the IRS's official e-file infrastructure (MeF).**\n\n## A tax return is math. It should be a function call.\n\nWe're Angelo and Akash, and we built Luca IQ, a new tax engine for accounting firms. One set of inputs in, a completed, filed return out in minutes. Not bolted onto decades out desktop software.\n\nFor CPA firms, that means more returns per preparer, less spend on labor, and a clean path off 30-year-old desktop software. For the PE groups acquiring and scaling firms, it means real operating leverage on the single most labor-intensive part of the business.\n\n\n\n**The problem.** \\~95% of US firms file their returns through just four companies, and all of them were built decades ago, for the desktop, and are closed. Firms are stuck running tax season on software that can't scale with them. Every modern AI tax tool just pushes data into that same closed software it can't control. Everyone rebuilt the interface.\n\n**What we built.** A new one, and we're opening it. A key principle: AI never does the tax math. AI and human judgment set the inputs, and a deterministic engine computes the return, with a full audit trail on every number. It's either 100% correct or it's wrong, and only a deterministic engine can promise the former. For firms, that means throughput without giving up accuracy or defensibility.\n\nOur core leverage: we're an **IRS-authorized e-file provider as a Software Developer, Transmitter, and Intermediate Service Provider**, so Luca IQ doesn't just compute the return, it e-files straight to the IRS. That full path, calculation through filing, is what firms can't get from a closed engine today.\n\n**Why now.** The profession is running out of people. 300,000+ accountants have left since 2019, and \\~70% of CPAs are near retirement. At the same time, private equity is rolling up firms and pushing hard on margin. The work isn't going away. The people are, and the pressure to do more with fewer preparers has never been higher.\n\n**Who we are.** Angelo (CEO) is a CPA who worked in forensic accounting with the FBI, Wall Street, EY and spent years working at tax firms using the legacy softwares we are now replacing. Akash (CTO) was employee #1 at a fintech data-infrastructure startup and leads engineering.\n\n**What we need:**\n\n* **CPA firms who dread tax season**, We'd love 20 minutes to show you what Luca IQ does for throughput and margin. This is who we build for.\n* **PE firms rolling up accounting practices.** If tax prep labor is your biggest cost line, let's talk.\n* **Developers and fintechs** who need 1040 calculations or e-filing. The engine is one API call, and you can build on it early.\n\nReach us at [founders@lucaiq.com](mailto:founders@lucaiq.com).", "url": "https://www.ycombinator.com/launches/SBo-luca-iq-an-api-for-u-s-tax-calculation-and-e-filing", "votes": 4, "created_at": "2026-07-31T14:01:23.291Z" } ] }, { "id": 33013, "name": "Operon", "slug": "operon", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/aaeb7f2ff7aa5b0b7e64888230be2a7e46342f66.png", "website": "https://operonsolutions.com/en", "all_locations": "San Francisco, CA, USA", "long_description": "Operon is the data intelligence layer for heavy industry. We ingest the messy documents a plant runs on (P&IDs, schematics, datasheets, scans) and turn them into one structured, queryable model of the facility.\r\n\r\nOn top of it, engineers query their plant in natural language and build agentic workflows for safety, compliance, and design. \r\n\r\n", "one_liner": "Agentic data layer for manufacturing & process industries. ", "team_size": 0, "industry": "Industrials", "subindustry": "Industrials", "launched_at": 1782593141, "tags": [ "Computer Vision", "Manufacturing", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "Industrials" ], "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/operon", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/operon.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/operonsolutions/?viewAsMember=true", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/aaeb7f2ff7aa5b0b7e64888230be2a7e46342f66.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": 2155140, "full_name": "Anderson Chen", "title": "Founder/CEO", "founder_bio": "Founde/CEO @ Operon Solutions.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/anderson-chen-2b6941216/", "x_url": null, "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/289ff08d5218c7b14ea8d2d173dfb9330c17e927.jpg" } ], "jobs": [ { "id": 96232, "title": "Founding FDE", "url": "https://www.ycombinator.com/companies/operon/jobs/w7qf3HJ-founding-fde", "location": "San Francisco, CA, US / Remote (US)", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$100K - $150K", "equity_range": "0.20% - 1.00%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] } ], "news": [], "launches": [] }, { "id": 33014, "name": "Inkbox", "slug": "inkbox", "former_names": [ "Inkbox (Vectorly Inc)" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/59d6214df81a05c739db52287017ae33c8c45f0d.png", "website": "https://inkbox.ai", "all_locations": "San Francisco, CA, USA", "long_description": "For your AI agents to behave like teammates, we give them persistent identities with their own email, phone, and iMessage. We also provide them an agent-to-agent channel, so they can communicate for task delegation.", "one_liner": "The identity and communication layer for AI agents", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1782881612, "tags": [ "Developer Tools", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 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, "question_answers": null, "url": "https://www.ycombinator.com/companies/inkbox", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/inkbox.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/inkbox-ai", "x_url": "https://x.com/inkbox_ai", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/59d6214df81a05c739db52287017ae33c8c45f0d.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Tyler Bosmeny", "url": "https://www.ycombinator.com/people/tyler-bosmeny" }, "founders": [ { "user_id": 778892, "full_name": "Ray Liao", "title": "Founder/CEO", "founder_bio": "PhD in Computer Science from MIT. Previously cofounder/CTO at Empallo, an AI-powered virtual clinic for cardiovascular care.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/ruizhi-liao/", "x_url": "https://x.com/rayruizhiliao", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/af788a5cd4056a418504ce1f6575ee97d05e4f22.jpg" }, { "user_id": 2770188, "full_name": "Dima Vremenko", "title": "Founder", "founder_bio": "Co-founder at Inkbox. Previously Research Associate at Harvard Medical School, where he built ML pipelines for clinical prediction models using gigapixel pathology images and EHRs, co-authored 6 publications, and contributed to an R01 NIH Grant. BS in Biochemistry and Computer Science from Northeastern.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/dimavrem/", "x_url": "https://x.com/DVremenko", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/03bf2d678fb1434af863ffe50748028f1b1ddf01.jpg" }, { "user_id": 2773563, "full_name": "Alex Wilcox", "title": "Founder/CTO", "founder_bio": "Cofounder at Inkbox. Previously ML engineering and computer networking research. MS in CS and dual BS in Math and Econ from Northeastern University.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/alxwlcx", "x_url": "https://x.com/alxwlcx", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/aed3f2339877d7f84f73c49b3b73598cee41245b.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 104960, "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" } ] }, { "id": 33047, "name": "Decawork", "slug": "decawork", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/44fee5cae005d704af84e7ed5ed7418d4ca0580c.png", "website": "https://decawork.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "An agent’s access should depend on the task it is doing. The same action can be appropriate for one task and wrong for another. Access decisions need to adapt in real time as the agent works, but companies can’t turn every business judgment into a fixed rules or have people manually approve every step.\r\n\r\nWe train small, company-specific models that approve AI actions in real time. They consider the company’s policies and interests, the agent’s current task, and its past actions to decide whether each proposed action should be allowed. Access is specific to the task at hand and reassessed as the agent works.\r\n\r\nCompanies will rent intelligence from AI labs or run open-source models to power their agents. They’ll own the models that keep their entire AI workforce acting in their interests. Decawork is building those models.", "one_liner": "Training company-specific models that approve AI actions.", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1785265630, "tags": [ "B2B", "Security", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 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, "question_answers": null, "url": "https://www.ycombinator.com/companies/decawork", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/decawork.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/decawork-ai/", "x_url": "https://twitter.com/decawork", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/44fee5cae005d704af84e7ed5ed7418d4ca0580c.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/bea64bca8f89d0506e06952dbd00022b772363d1.png" ], "primary_partner": { "name": "Brad Flora", "url": "https://www.ycombinator.com/people/brad-flora" }, "founders": [ { "user_id": 1632535, "full_name": "Aman Raj", "title": "Founder/CEO", "founder_bio": "- Built AI compliance platform at Barclays used by internal teams globally\n- Founded a fintech and scaled it to 52K families and $1.5M AUM\n- Led product at a consumer AI startup, scaled to 100K+ MAU (Google Play Best App 2024)\n- IIT Kharagpur", "is_active": true, "linkedin_url": "https://linkedin.com/in/aman-raj-84636a158", "x_url": "https://x.com/arxneo14", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2ae56b87789485359a28cd015856039060019efe.jpg" }, { "user_id": 1049492, "full_name": "Sarthak Aggarwal", "title": "Founder/CTO", "founder_bio": "- AI systems at NVIDIA (deployed at OpenAI, Meta)\n- Enterprise AI at Ema (used by Microsoft, Hitachi)\n- Led Conquest, Asia's largest student-run accelerator\n- Google Code-In Global Winner + Open source since the age of 12\n- BITS Pilani", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/sarthak-agg/", "x_url": "https://x.com/_sarthak4", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f93e2ff857332071c545c3c16f569835408cf579.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 109883, "title": "Decawork - Training company-specific models that approve every AI action", "tagline": "Our small AI models decide agent access in real time, task by task, based on your company’s interests.", "body": "Hi everyone 👋 - we're Aman and Sarthak, founders of Decawork.\\\n\\\n**TL;DR:** AI agents shouldn’t have permanent access to company systems. The same action can be appropriate for one task and wrong for another, but companies can’t turn every business judgment into fixed rules or manually approve every step. Decawork trains small, company-specific AI models that approve every agent action in real time, based on company policies and interests, the agent’s task, and its past actions. Access is granted for the task at hand and revoked when it’s done.\\\n\\\nLaunch video: [Watch it here](https://www.youtube.com/watch?v=SanpHIyFcV4)\\\n\\\n🚧 **The Problem & Why now?**\\\nCompanies are putting long-running, more autonomous agents to work on broader tasks and goals. These agents need access to critical company systems, but their actions can be unpredictable and may not serve the company’s interests.\n\nOpenAI’s agents have already hacked Hugging Face during testing with reduced safeguards. Replit’s agent deleted data from a live application’s database.\n\nAn agent’s access should depend on the task it is doing. The same action can be appropriate for one task and wrong for another. Permanent access lets an agent keep using permissions even when they are no longer appropriate for its task.\n\nAs agents take on more work independently, access decisions need to happen in real time. But companies can’t turn every business judgment into a fixed rule or have people manually approve every step.\\\n\\\n✅ **How we solve this?**\\\nDecawork gives AI agents access for the task at hand and revokes it when the task is done.\n\n* Connect your agents. Route API requests and MCP tool calls through Decawork to see activity and manage access in one place.\n* Set company policies. Write policies in plain English, specify when human approval is required, and connect your existing identity and IT service management systems.\n* Deploy a company-specific policy model. We deploy small models that approve actions in real time using your company’s policies and priorities, task context, and past actions. Your agents do the work. Decawork evaluates each proposed action and enforces the access decision before it runs.\n\n🚀 **Team**\\\nSarthak built AI systems at NVIDIA that were deployed at OpenAI and Meta, and worked on enterprise AI agents at Ema.\n\nAman built the AI compliance platform at Barclays used by internal teams globally, then led product at a consumer AI startup serving 100K+ monthly users, hand-wiring credentials for the agents he shipped.\n\nEvery one of those deployments came down to the same questions: what can it access, who approved it, and what did it do? We kept solving agent access by hand - so we quit to build the system we wished we’d had.\n\n![uploaded image](/media/?type=post&id=109883&key=user_uploads/1632535/0ef2784e-ab45-422f-91b9-960473f11dd5)\n\n🙏 **Our Ask**\n\n* If you’re on an IT team or know someone who’s worried about AI agents accessing or misusing company systems, talk to us: or [founders@decawork.ai](mailto:founders@decawork.ai)", "url": "https://www.ycombinator.com/launches/SaJ-decawork-training-company-specific-models-that-approve-every-ai-action", "votes": 152, "created_at": "2026-08-12T16:30:00.369Z" } ] }, { "id": 33313, "name": "SubVysion", "slug": "subvysion", "former_names": [ "SubVysion, Inc." ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0df819d609df4c8e15ebdc21bbc1f518d56e52d8.png", "website": "https://subvysion.com", "all_locations": "San Francisco, CA, USA", "long_description": "We build centimeter-accurate 3D maps of underground utilities to help construction contractors dig safer and faster. With underground intelligence, contractors can avoid dangerous utility strikes and costly project delays.", "one_liner": "Autonomous rovers to make the ‘Google Maps’ of underground utilities", "team_size": 2, "industry": "Real Estate and Construction", "subindustry": "Real Estate and Construction -> Construction", "launched_at": 1783960374, "tags": [ "Hard Tech", "Computer Vision", "Real Estate", "Construction", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "Real Estate and Construction", "Construction" ], "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/subvysion", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/subvysion.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/subvysion/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/0df819d609df4c8e15ebdc21bbc1f518d56e52d8.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Gustaf Alstromer", "url": "https://www.ycombinator.com/people/gustaf-alstromer" }, "founders": [ { "user_id": 1363066, "full_name": "Maxwell Stone", "title": "Founder/CEO", "founder_bio": "Founder at SubVysion. Previously Machine Learning Engineer at Roboflow, where he built on-device inference SDKs deployed in 10,000+ pharmacies for a Fortune 100 healthcare company and developed ML solutions for enterprise customers including railyard mapping and defect detection. MSE and BSE candidate in Computer Science from UPenn.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/maxwell-stone-2b5b6b1a0?utm_source=share&utm_campaign=share_via&utm_content=profile&utm_medium=ios_app", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/534fdc481c3e4f0ac1b1ba8eb1dbfcf6b3c19b39.jpg" }, { "user_id": 3411443, "full_name": "Wenson Tang", "title": "Founder/COO", "founder_bio": "Co-founder and COO at SubVysion, Inc. Computer Science and Consumer Psychology from UPenn. Previously Software Developer at CentralSquare Technologies, working cross-jurisdiction emergency dispatch allowing first responders to reach emergencies three minutes faster.\n", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/wenson-tang", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/6138c520a0b71cd0f533baf3b0cd765d9ffc1ddd.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 111406, "title": "SubVysion: Preventing $150B is wasted construction spending", "tagline": "Autonomous rovers building the 'Google Maps' of subsurface infrastructure", "body": "\n\nConstruction has a mapping problem. Of the $2.2T in annual US construction spending, $150B is wasted due to a lack of subsurface knowledge. All construction starts from the ground up, and more often than not, unexpected assets underneath the surface will hold a construction project back. Whether it's an unknown utility line, unexpected rock layer, or old foundation that wasn’t on any design map, the costs of delays from underground conflicts quickly add up. \n\nTake utility strikes, when an excavator hits an active utility line. For every dollar spent on the explicit repair cost of that utility line itself, the contractor loses an additional $30 per repair-dollar in project delays, insurance claims, idle work crews, and increased insurance premiums. For a hyperscale project such as data center construction, a single day of delay can cost the cloud-provider up to $14 million dollars for that single day.\n\nIn metropolitan areas, maps are incomplete at best and none create a unified picture of critical infrastructure, making excavation especially dangerous when natural gas or electric lines are broken.\n\nEnter SubVysion. We’ve built a fleet of autonomous rovers carrying ground-penetrating radar and other sensors that create a centimeter-accurate map of subsurface infrastructure. Our hardware is the first and the best to map the entirety of US infrastructure. Using our rovers, we comprehensively map construction sites, city streets, and even larger indoor buildings, at 100x better granularity and 10x the speed (with a single rover) compared to our competitors. We process vast amounts of data using machine learning and agents, and output that data into an easy-to-understand 3D scene. \n\nWho are we? Maxwell Stone was an early ML engineer at Roboflow (YC S20), and Wenson Tang built the world’s smallest and cheapest LiDAR-capable drone for adverse environments. We both studied computer science at the University of Pennsylvania. Together, we’re building SubVysion to map the entirety of America’s subsurface infrastructure.\n\nWe’re currently on job sites in Philadelphia and Texas, helping our first market of utility contractors save hundreds of thousands of dollars every year. We’re soon to expand our mapping services to municipalities and energy providers as we scale up our rover fleet and capacity!\n\nIf you’re in the energy, infrastructure, or hyperscale construction world, we’d love to hear from you at [founders@subvysion.com](mailto:founders@subvysion.com)!", "url": "https://www.ycombinator.com/launches/Sys-subvysion-preventing-150b-is-wasted-construction-spending", "votes": 7, "created_at": "2026-08-19T23:30:02.157Z" } ] }, { "id": 33348, "name": "Autoresearch, Inc.", "slug": "autoresearch-inc", "former_names": [ "hiloop" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/5b91efea37962386a163af58e2f2920b1e9d0aa7.png", "website": "https://autoresearch.inc", "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.", "one_liner": "Autoresearch as a service: we solve your hardest measurable problems", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1785348094, "tags": [ "Developer Tools", "Machine Learning", "Reinforcement Learning", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 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, "question_answers": null, "url": "https://www.ycombinator.com/companies/autoresearch-inc", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/autoresearch-inc.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/autoresearchinc/", "x_url": "https://x.com/hiloopai", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/5b91efea37962386a163af58e2f2920b1e9d0aa7.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Ankit Gupta", "url": "https://www.ycombinator.com/people/ankit-gupta" }, "founders": [ { "user_id": 1714115, "full_name": "Karan Brar", "title": "Founder/CEO", "founder_bio": "Founder at Autoresearch, Inc. Previously ML at Reducto, Head of ML Infra at DynamoAI.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/brarkaran", "x_url": "https://x.com/deepmatmul", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e596ed985a539262821de87d80ea418725ab7a90.jpg" }, { "user_id": 1597736, "full_name": "Thomas Boser", "title": "Founder/CTO", "founder_bio": "Founder at Autoresearch, Inc. Previously engineer at Reducto, founding engineer at Crosswise, senior ML engineer at Discord, ML at Sentropy & SoFi.", "is_active": true, "linkedin_url": "https://linkedin.com/in/tboser", "x_url": "https://x.com/thomasboser", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7c1d2d3062a34b6d55d2d4e7aef55e887853400b.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 108337, "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!", "url": "https://www.ycombinator.com/launches/SBN-hiloop-we-run-thousands-of-experiments-to-improve-your-models", "votes": 8, "created_at": "2026-07-29T19:50:09.250Z" } ] }, { "id": 33673, "name": "Caution", "slug": "caution", "former_names": [ "Caution SEZC" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a0571039e7dc6cc20c7a181c0b7ffa967bc5c6d3.png", "website": "https://caution.co", "all_locations": "George Town, George Town, Cayman Islands", "long_description": "Caution is a hosting platform for software you can't afford to get hacked. It simplifies and extends confidential compute, and lets developers deploy workloads to secure enclaves in minutes and give customers, auditors, and counterparties cryptographic proof that production is running the exact reviewed source code, build, configuration, and runtime - not an opaque binary controlled by a cloud operator or internal admin.\r\n\r\nConfidential computing hardware exists, but the tooling is too fragmented and incomplete for most teams to use well. Today, attestation often proves only that a binary has a certain hash; it does not prove what source code produced that binary. Building the missing deployment, reproducibility, and verification layer requires specialized security engineering and often locks teams into one cloud or hardware stack. Caution turns that into a simple git-based workflow that builds reproducible enclave images, provisions infrastructure, and lets anyone independently verify what is running.\r\n\r\nWe built Caution after years securing high-risk systems through Distrust, where we worked with hedge funds, custodians, blockchain teams, cloud platforms, and critical grid operators on systems responsible for more than $600B in assets. Again and again, the same problem showed up: teams running mission-critical infrastructure could not reliably prove what was executing in production.\r\n\r\nAs AI, fintech, healthcare, and regulated data collaboration move into the cloud, \"trust us\" is no longer enough. Caution is a general-purpose platform: if it runs on a server, it can run verifiably on Caution. We're starting where trust failures cost the most, but we believe verifiable compute will become the default way software runs, the same way HTTPS became the default way it's served. Infrastructure you can verify, not trust.", "one_liner": "Hosting platform for software you can't afford to have hacked", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1785719703, "tags": [ "Cybersecurity", "Cloud Computing", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "Cayman Islands", "Latin America", "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/caution", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/caution.json", "year_founded": 2025, "city": "George Town", "country": "KY", "linkedin_url": "https://www.linkedin.com/company/cautionco", "x_url": "https://x.com/CautionHosting", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/a0571039e7dc6cc20c7a181c0b7ffa967bc5c6d3.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": 3655130, "full_name": "Anton Livaja", "title": "Founder/CEO", "founder_bio": "Co-founder/CEO of Caution (YC S26). We give teams a hosting platform to run sensitive workloads in secure enclaves and cryptographically prove what code is running in prod. Previously co-founded Distrust, securing systems for hedge funds, custodians, and critical infra responsible for $600B+ in assets. Deep in confidential computing, supply chain security, and applied cryptography. Mission: improve the freedom, security, and privacy of as many people as possible.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/alivaja/", "x_url": "https://x.com/antonlivaja", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f6dddfa8391b5f9fce21fa7496e2368d59ef6987.jpg" }, { "user_id": 3654857, "full_name": "Ksenia Lesko", "title": "Founder", "founder_bio": "Co-founder at Caution, where we help teams run sensitive workloads in secure enclaves and cryptographically prove what code is running in production. I lead the business and product side; previously ran strategy and ops at Distrust (distrust.co) and led customer education and activation at Ada (ada.cx).", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/ksenialesko/", "x_url": "https://x.com/xenush", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4ecf3715be1ffcf30eedb062148902b9a1458237.jpg" }, { "user_id": 52788, "full_name": "Lance Vick", "title": "Founder/CTO", "founder_bio": "Technology sovereignty maximalist. Lead security architect at Caution. Former security lead at Turnkey, BitGo, Unit 410, Pebble. Founded Stagex Linux distribution, and #! decentralized hackerspace. Experienced in Linux hardening, privacy, software engineering, security auditing, cryptographic key management, tamper evidence, HSMs, and supply chain security. Frequently internet infamous for exposing security negligence. Prolific mechanical puzzle collector, lockpicker, and hardware hacker.", "is_active": true, "linkedin_url": "https://lance.dev", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/45728fc907c9915858fe6304bbdb25700f05d67b.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 108800, "title": "Caution: Hosting platform for software you can't afford to have hacked", "tagline": "Deploy to secure enclaves in minutes, isolate sensitive workloads, cryptographically prove what code is running.", "body": "Hey everyone! We're [Anton Livaja](https://www.linkedin.com/in/alivaja/), [Lance Vick](https://lance.dev), and [Ksenia Lesko](https://www.linkedin.com/in/ksenialesko/) from [Caution](https://caution.co).\n\n**TL;DR:** Caution is a hosting platform for software you can't afford to have hacked. Your software and data Istay protected even if your CI/CD pipeline, host infrastructure, or a developer laptop gets compromised. You go from source to a verifiable deployment in three commands. \n\n**Built for:** payment processors, PHI processors, AI agents, policy and fraud engines, secrets management, and other sensitive workloads.\n\n[https://drive.google.com/file/d/1u-l2TSBQO2t5dbhBsatCkZf5earCTyDD](https://drive.google.com/file/d/1u-l2TSBQO2t5dbhBsatCkZf5earCTyDD/view?usp=sharing)\n\n### **Why we built this**\n\nOn February 21, 2025, attackers stole **$1.5 billion** worth of Ethereum from Bybit, the largest digital heist in history. They never breached Bybit's own infrastructure: North Korea's Lazarus Group compromised a single developer machine at Safe{Wallet}, Bybit's multisig provider, and injected malicious JavaScript into the signing interface. Bybit's team approved what looked like a routine transfer and handed over a cold wallet to the attackers. The code everyone trusted was not the code that was running.\n\nThis keeps happening because nearly all software runs on blind trust:\n\n* trust in the cloud host\n* trust in production admins\n* trust in CI/CD\n* trust that the code you reviewed is the code actually running\n\nIf any part of that chain is compromised, an attacker can read your secrets, tamper with your business logic, or quietly run code your team never reviewed. It's the same failure behind SolarWinds and Codecov: tampered code arriving through a trusted channel, passing every check. Caution exists to shrink that attack surface and make the most sensitive systems verifiable.\n\n### **Caution proves exactly what's running on your server**\n\nCryptographically, and in real time. Deploying into secure enclaves normally takes a specialist team and months of integration. Caution automates the entire flow: source to verifiable deployment in minutes, with three commands:\n\n![uploaded image](/media/?type=post&id=108800&key=user_uploads/3654857/f3161435-2a97-4207-915a-96375a72be82)\n\n**🎥** [Watch Anton walk through the platform](https://caution.co/platform-tour.html)\n\nUnder the hood, **Caution is a verifiable confidential compute platform:** hardware-backed cryptography isolates your workloads, preserves data privacy, and proves what software is running on a server in real time. The entire platform is open source, so verification never requires trusting us. In practice, this eliminates entire classes of attacks out of the box:\n\n* **Build & CI/CD tampering**: reproducible, multi-party signed builds mean injected code can't pass as a legitimate release.\n* **Infrastructure & insider compromise**: a compromised cloud account, admin, or laptop can't silently swap what's running.\n* **Runtime data theft**: data is processed in hardware-isolated enclaves, unreadable even to the host, the cloud provider, or us.\n\nCaution guards against everything but first- or third-party code bugs: if the release you approve has a flaw, that's what runs. Nothing can be added, no fix can be stripped out, and every patch is provably live.\n\n### **Why now**\n\nWith advances in AI, attacks that used to require rare, expensive expertise are now cheap and scalable, and the gap between a vulnerability existing and being exploited is collapsing toward zero. Reactive patching was already losing. It can't win a race against automated attackers.\n\nIn the post-Mythos world, the security model has to flip. Infrastructure can no longer assume it won't be compromised. It has to be built to stay secure even when the host, the pipeline, or individuals with privileged access are compromised, and to prove, cryptographically, that it has. That's what Caution does.\n\nCaution is a general-purpose platform: if it runs on CPU or GPU, it can run verifiably on Caution. We're starting where trust failures cost the most, but we believe verifiable compute will become the default way software runs, the same way HTTPS became the default way it's served.\n\n### **Why us**\n\n[Anton](https://www.linkedin.com/in/alivaja/) and [Lance](https://lance.dev) have spent their careers securing some of the most security-critical systems in the world: BitGo, Ledn, Turnkey, OpenZeppelin, and Unit 410 (later acquired by Coinbase). Across hundreds of engagements, from hedge funds to critical grid operators, the systems we've helped secure hold more than **$600B** in digital assets. [Ksenia](https://www.linkedin.com/in/ksenialesko/) spent years helping enterprises adopt new technology, and now leads go-to-market, customer education, and operations at Caution, turning deep security engineering into a product companies can understand, buy, and use.\n\nWe've been the people companies call in when this class of attack hits. Teams needed stronger guarantees against supply chain and runtime attacks, but existing solutions were too hard, too bespoke, or too expensive. So we built the platform we kept wishing existed.\n\n### **Traction**\n\nCaution is in production and onboarding customers spanning crypto infrastructure, blockchain labs, digital asset lending, consumer hardware, post-quantum security, and private AI inference.\n\nWe support AWS Nitro Enclaves today. Intel TDX, AMD SEV-SNP, TPM 2.0, NVIDIA Confidential Computing, and broader cloud support is in active development and coming soon.\n\n### **Our ask**\n\nIf you're running software where sensitive data must stay private or business logic can't be tampered with, we'd love to help you level up your security. [Book 20 minutes with us](https://caution.co/contact.html) or email us at [founders@caution.co](mailto:founders@caution.co).\n\nWe'd especially love to hear from you if you're a:\n\n* security team that wants proof, not promises, from your infrastructure\n* fintech running payments, policy, or fraud engines\n* crypto custodian, exchange, or wallet team that can't afford another Bybit\n* healthcare or AI company processing PHI or other regulated data\n* team giving AI agents production credentials and losing sleep over it\n* company using AI inference with sensitive data\n\nYou can also learn more on our [blog](https://caution.co/blog.html), and follow us on [LinkedIn](https://www.linkedin.com/company/cautionco/) and [X](https://x.com/CautionHosting) for updates.", "url": "https://www.ycombinator.com/launches/SIq-caution-hosting-platform-for-software-you-can-t-afford-to-have-hacked", "votes": 59, "created_at": "2026-08-04T17:02:42.242Z" } ] }, { "id": 33806, "name": "Experiential Labs", "slug": "experiential-labs", "former_names": [ "Resolute Labs" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/716e828c9efd6efe6da64574ff67dd5bfa0c2a25.png", "website": "https://experientiallabs.ai", "all_locations": "San Francisco, CA, USA", "long_description": "We are building an open source gateway for AI budget holders to control model access and turn their traffic into better models that they own. We're a team that has earned an ML PhD at Georgia Tech, scaled AutoGPT to 160k GitHub stars, and led a self-driving simulation team at Waabi.", "one_liner": "Open source AI gateway that turns your traffic into better models", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1782607347, "tags": [ "Reinforcement Learning", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 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, "question_answers": null, "url": "https://www.ycombinator.com/companies/experiential-labs", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/experiential-labs.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/experiential-labs/", "x_url": "https://x.com/explabsai", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/716e828c9efd6efe6da64574ff67dd5bfa0c2a25.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": 3149739, "full_name": "Kion Fallah", "title": "Founder/CEO", "founder_bio": "Co-founder and CEO of Experiential Labs. Previously Staff Research Scientist at Waabi leading the mixed reality simulation team. PhD in Machine Learning from Georgia Tech focused on synthetic data.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/kfallah", "x_url": "https://x.com/okfallah", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/eb099f2fb8bbfee19779eae1dae81307ea85d07d.jpg" }, { "user_id": 411375, "full_name": "Silen Naihin", "title": "Founder/CTO", "founder_bio": "Built and grew AutoGPT to 160k stars. Did AI for science at the DOE. Previously cofounded Stackwise (was in W24) and various founding AI eng roles. Did continual learning, interp, and evals research.", "is_active": true, "linkedin_url": "https://linkedin.com/in/silen-naihin", "x_url": "https://twitter.com/silennai", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b68b10165c34092f3bb0c78caccfa5794a625212.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 109456, "title": "Experiential Labs - Turn your AI spend into a cheaper + better model you own", "tagline": "Train a model your company owns, guaranteed to match or beat frontier quality at 50% lower cost.", "body": "**TL;DR: Companies are spending more on AI every month, but almost none of that spending becomes an asset they own. We train a small language model for your company's use cases. You fully own it, and we guarantee the same or better quality as the frontier models you use today at 50% lower cost.**\n\n\n\nCompanies are spending more on AI every month, but almost none of that spending becomes an asset they own.\n\nThe prompts, traces, and use cases are yours, _but the model stays rented._\n\nSo you keep paying frontier prices for repetitive work a smaller, specialized model could do faster, cheaper, and often better\n\nWe built Experiential Labs to change that.\n\n**Here's how it works**\n\nKeep using GPT, Claude, or whatever models are already in your stack.\n\nExperiential Labs uses your traffic to build a simulation of the tasks, failures, and edge cases your agent encounters. You can also upload existing traces to bootstrap the process.\n\nThe platform trains you a model against that simulation, so it gets better at your specific use cases over time.\n\nAs your model improves, it earns more traffic. Hard requests can still go to the frontier. Everything else moves to your faster, cheaper model.\n\nYou own the weights, can run them wherever you want, and keep the profits they create. When a stronger base model comes out, we transfer what your model has learned instead of making you start over.\n\nOn some tasks we've seen up to 97% lower cost and +50% higher quality. Across a full deployment, we guarantee at least 50% lower cost at the same or better quality, backed by an SLA.\n\n**The team**\n\nWe are both AI researchers. Kion built simulation systems for autonomous vehicles at Waabi after earning his ML PhD at Georgia Tech. Silen built and grew AutoGPT to 160,000 GitHub stars and has worked across continual learning, evaluations, interpretability, and AI for science.\n\n## Our ask\n\nIf your company sends significant traffic to GPT, Claude, or other frontier models, we would love to help.\n\nIntros to founders and AI leaders with growing inference bills are also greatly appreciated.\n\n**Email:** [founders@xplabs.ai](mailto:founders@xplabs.ai) \n\n**Schedule a call:** \n\n**Website:** [xplabs.ai](http://xplabs.ai) ", "url": "https://www.ycombinator.com/launches/STQ-experiential-labs-turn-your-ai-spend-into-a-cheaper-better-model-you-own", "votes": 18, "created_at": "2026-08-06T22:00:00.114Z" } ] }, { "id": 34365, "name": "Runtime.si", "slug": "runtimesi", "former_names": [ "Lambda Robotics", "Runtime" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/461a9d05728add7a3449b82167ac418e94d301eb.png", "website": "https://runtime.si/", "all_locations": "San Francisco, CA, USA", "long_description": "Runtime is building the evaluation layer for physical intelligence. We push robot policies to their limits across thousands of simulated worlds, before they face the real one.", "one_liner": "Evaluation Infrastructure for Robotics (YC F26)", "team_size": 5, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1785385611, "tags": [ "Robotics", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Fall 2026", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "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/runtimesi", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/runtimesi.json", "year_founded": null, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/runtime-yc-f26", "x_url": "https://x.com/runtimesi", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/461a9d05728add7a3449b82167ac418e94d301eb.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": 3900443, "full_name": "Chen Peng", "title": "Founder/CEO", "founder_bio": "Co-founder, CEO at Runtime.si. Researcher at UPenn's GRASP and Penn Engineering; Previously investment analyst at BlackRock. BA in Physics from UPenn.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/chen-peng-6737681bb", "x_url": "https://x.com/chennpeng", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f13d7e62eab252812a41d0f0434752acd19c176f.jpg" }, { "user_id": 3900687, "full_name": "Yim Ying", "title": "Founder", "founder_bio": "Co-founder at Runtime.si. Full-stack robotics engineer focused on robotics productization, manipulation, and manufacturing.MechE @ Penn.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/qingyun-ying-46558235b?utm_source=share_via&utm_content=profile&utm_medium=member_ios", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3abf1241b0a3a88b9721dba23ce1cce5e431f5ea.jpg" }, { "user_id": 3133784, "full_name": "Liam Zhong", "title": "Founder/CTO", "founder_bio": "Co-founder & CTO at Runtime.si. Researcher at UPenn GRASP, CV, Control, and RL. 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", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/pvarshh", "x_url": "https://x.com/pvarshh", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a0ba07e21403033e8b96bfd650c021bf227174ee.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 35265, "name": "Hopper", "slug": "hopper", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6640b732eb4efe17f2fb11ff75f6f6bc14184872.png", "website": "https://withhopper.com", "all_locations": "San Francisco, CA, USA", "long_description": "Train, inference, and continuously improve any model.\r\n\r\nHopper post-trains STT, TTS, and LLMs on your production traces, then serves and improves them against your live traffic.", "one_liner": "Inference and post-training for realtime agents", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1788561875, "tags": [ "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 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, "question_answers": null, "url": "https://www.ycombinator.com/companies/hopper", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/hopper.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/143037522", "x_url": "https://x.com/hopper_research", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/6640b732eb4efe17f2fb11ff75f6f6bc14184872.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Charlie Warren", "url": null }, "founders": [ { "user_id": 612777, "full_name": "Pavan Katta", "title": "Founder/CEO", "founder_bio": "CEO at Hopper (YC F26). 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Electrical Engineering from IIT Madras", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jashwanth12/", "x_url": "https://x.com/jashwanth_p", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/68915ff570196397487cc4d5d9f4b60d93624720.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 35355, "name": "Invertix", "slug": "invertix", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c2332aa776f979c1ef83d3026fd24932b6576eea.png", "website": "https://www.invertix.ai", "all_locations": "Munich, BY, Germany", "long_description": "The next constraint is not intelligence, it is the energy and operational cost of running it.\r\nWe deploy custom AI models inside critical infrastructure companies that ingest SCADA data, work orders, human interventions, operational data no public model has seen, grounded in physics-informed neural networks and differentiable simulators. \r\nThis creates a flywheel: more operator data → better process understanding → more efficient operations → cheaper energy → cheaper AI → more deployment → more data. \r\n\r\nhttps://www.youtube.com/watch?v=0uDH6pMn5OE\r\n\r\nAI compute doubles every 2.2 years. Data center demand grows from 415 to 945 TWh by 2030. Without near-zero energy cost, AI remains limited by human infrastructure. We are the layer that runs AI at zero energy cost.\r\nEnergy is a $10 trillion market. The infrastructure layer doesn't exist yet. \r\nWe are building it.", "one_liner": "Energy Superintelligence, AI that operates critical infrastructure", "team_size": 8, "industry": "Industrials", "subindustry": "Industrials -> Energy", "launched_at": 1789740763, "tags": [ "Solar Power", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2026", "status": "Active", "industries": [ "Industrials", "Energy" ], "regions": [ "Germany", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/invertix", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/invertix.json", "year_founded": 2026, "city": "Munich", "country": "DE", "linkedin_url": "", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/c2332aa776f979c1ef83d3026fd24932b6576eea.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/e09c46b000c5ff25f7042e775e76c8f61773eba1.png" ], "primary_partner": { "name": "David Lieb", "url": "https://www.ycombinator.com/people/david-lieb" }, "founders": [ { "user_id": 2057026, "full_name": "Joseph Perrotta", "title": "Founder/CEO", "founder_bio": "CEO at Invertix. Ex pro volleyball player, at 18 sold more than $17M of houses.\nPreviously at Cubbit, where they raised $25M. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/joseph-perrottaa", "x_url": "https://x.com/josephperrotta_?s=11", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4c94847dab0f5d6b7a96ecfa63944ac1372b58ca.jpg" }, { "user_id": 2234234, "full_name": "Kaan Durmaz", "title": "Founder/CTO", "founder_bio": "Co-founder & CTO at Invertix. Previously worked in computer vision, differential privacy and ai for chemistry. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/kdurmaz/", "x_url": "https://x.com/kdurmazx", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c13c2bd6f00b49f60836de5dce5ee88f099e7656.jpg" } ], "jobs": [], "news": [ { "title": "Invertix Labs launch", "url": "https://www.youtube.com/watch?v=0uDH6pMn5OE", "date": "Sep 18, 2026" } ], "launches": [ { "id": 116072, "title": "Invertix: Energy Superintelligence", "tagline": "Building AI agents to operate the world's energy infrastructure and data centers", "body": "Hey YC, we’re Joseph and Kaan.\n\nWe’re building **Energy Superintelligence: swarms of coordinated AI agents to operate energy infrastructure and data centers, carrying out work across entire organizations.**\n\nEnergy is one of the bottlenecks to scaling intelligence. Our vision is agents coordinating humans and other agents to operate, maintain, and build energy infrastructure worldwide, with applications extending to data centers.\n\n\n\n**How we got here**\n\nWe reached out to roughly 5,000 people in energy and had over 400 conversations. The same problem kept appearing: people were manually connecting fragmented data, investigating faults, and coordinating work across departments.\n\n**What we’re building**\n\nOur engineers work inside energy companies to map their data, workflows, responsibilities, and operating procedures. We combine that knowledge with an energy-specific ontology, giving specialized agents a shared understanding of the business and procedures they can follow. We see the same opportunity in data center operations: connecting equipment, maintenance procedures, suppliers, and on-site teams so agents can coordinate real work.\n\nThe system we’re building connects four things:\n\n1. **Onology:** equipment, telemetry, documents, contracts, and people in one connected model.\n\n ![uploaded image](/media/?type=post&id=116072&key=user_uploads/2057026/a14398e1-34a7-4399-a75f-c2ce6eb631c3)\n\n2. **AI Employees:** agents use different tools, correlate evidence across assets, and review each other’s findings. \n\n ![uploaded image](/media/?type=post&id=116072&key=user_uploads/2057026/70610c1d-cc3e-4c13-a96e-38a1acc6777f)\n\n3. **Physical execution:** agents coordinate interventions with humans, incorporate field observations, and verify production recovery.\n\n ![uploaded image](/media/?type=post&id=116072&key=user_uploads/2057026/7c425af9-22cb-44ec-9da9-dd79ce445a54)\n\n4. **Sofware builder:** We allow technical and non technical builders to build on top of the platform. creating visualizations, agents, ML models, all using the data of the platform and centered intelligence.\n\n ![uploaded image](/media/?type=post&id=116072&key=user_uploads/2057026/8abcc1a0-1a6d-44cf-8da9-74dbef23944d)\n\n\nOur ambition is coordinated agents at every critical infrastructure company in the world, helping produce more energy and accelerate intelligence.\n\nWe believe **Energy Superintelligence is a necessary step toward ASI.**\n\n**The founding team**\n\n_17th of December 2026 - YC Mountain View_\n\n![uploaded image](/media/?type=post&id=116072&key=user_uploads/2057026/a7dc00e4-7377-4136-8b3e-a57e081e523b)\n\n* **Nicole:** our first hire; black-hole physics, Max Planck research with Nobel laureates, and surgical robotics at Harvard Med.\n* **Menelaos:** led TUM ai E-Lab; Siemens and TUM ML research.\n* **Nicolas:** previously built and raised for his deeptech startup; leads GTM with Joseph.\n* **Simon:** EX JetBrains, leads product and agent systems.\n* **Pietro:** Leads FDE, Early hire at a startup that raised $30M.\n* **Vishisht:** Cambridge & UPenn Research; first hire at an a16z-backed startup.\n\nWe’re deployed Autonomously across **\\~2 GW**, signing two of the largest utilities in the world, with interest from **30+ energy companies**. And are woking with partners that have over **50 GW**\n\n**Our ask:** introductions to operations leaders at utilities, energy asset owners, O&M companies, and data center operators, especially in the US.", "url": "https://www.ycombinator.com/launches/UC8-invertix-energy-superintelligence", "votes": 8, "created_at": "2026-09-28T07:00:00.116Z" } ] }, { "id": 35395, "name": "Workers IO", "slug": "workers-io", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/12ec3720a247bad2e5a39d162b68e217ed6b74bd.png", "website": "https://workers.io", "all_locations": "San Francisco, CA, USA", "long_description": "Workers IO is building simulation environments to catch failures in mission-critical software before they reach production. We run your entire system through millions of simulated production scenarios to verify its correctness and performance properties.\r\n\r\nCoding agents can now generate code faster than teams can review it. Meanwhile, software and the infrastructure it runs on keep getting more complex. Tests check a small set of cases in isolation, in environments that are different from production. Some of the most expensive failures only surface when customers encounter them.\r\n\r\nWe run your entire system unmodified and simulate network faults, disk failures, crashes, and clock drift. We build the fault models for you and check your system’s requirements across millions of scenarios. Every failure we find can be perfectly reproduced.", "one_liner": "Simulation environments for verifying mission-critical software", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1787942068, "tags": [ "Developer Tools", "B2B", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Fall 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/workers-io", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/workers-io.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/workersio", "x_url": "https://x.com/workersio", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/12ec3720a247bad2e5a39d162b68e217ed6b74bd.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": 3410079, "full_name": "Chaitanya Choudhary", "title": "Founder/CEO", "founder_bio": "Founder & CEO at Workers IO, helping teams build and verify mission-critical systems.\n\nBuilt and sold first company, The Timelinears, at 19 after growing it to 3 million monthly active viewers.\n\nFounding engineer at Grit (Acquired), OnDeck, CW (Acquired) and Research Assistant at Harvard Law School. Advised ICICI Bank and Times on building a reward model for their fintech products.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/chaitanyya", "x_url": "https://x.com/chaaai", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/29ed0f9255cfb914fff0a4ce79f6f8c0c1224267.jpg" } ], "jobs": [ { "id": 109294, "title": "Systems Engineer, Hypervisor and Kernel", "url": "https://www.ycombinator.com/companies/workers-io/jobs/UV8iE3b-systems-engineer-hypervisor-and-kernel", "location": "San Francisco, CA, US / Remote (US)", "type": "Full-time", "role": "Engineering", "role_type": "Backend", "salary_range": "$80K - $250K", "equity_range": "0.50% - 4.00%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [ "Amazon Web Services (AWS)", "C", "Rust", "Linux", "Software Architecture" ] } ], "news": [], "launches": [] }, { "id": 35850, "name": "Dreamscale Labs", "slug": "dreamscale-labs", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/5a0eb88901e7f46ec71cc8739e8069f4815b0a52.png", "website": "https://dreamscalelabs.com", "all_locations": "San Francisco, CA, USA", "long_description": "Dreamscale Labs is building the fastest cloud inference platform for robotics. As complex physical AI models become difficult to fit on expensive on-robot GPUs, we let users offload inference to the cloud and serve them with real-time latency. So far, we've hit 40-50% lower latency than existing neoclouds.\r\n", "one_liner": "Real-time cloud inference for robotics.", "team_size": 4, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1788577910, "tags": [ "Robotics", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2026", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "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/dreamscale-labs", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/dreamscale-labs.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/dreamscalelabs", "x_url": "https://x.com/dreamscalelabs", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/5a0eb88901e7f46ec71cc8739e8069f4815b0a52.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "David Lieb", "url": "https://www.ycombinator.com/people/david-lieb" }, "founders": [ { "user_id": 3499827, "full_name": "Eric Ren", "title": "Founder/CEO", "founder_bio": "Co-founder @ Dreamscale Labs : realtime cloud inference for robotics.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/e-ren", "x_url": "https://x.com/eternaI_entropy", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c5f556cfa846dddb7160f7706bb48cde404f1d53.jpg" }, { "user_id": 3612640, "full_name": "Kevin Lin", "title": "Founder/Chief Scientist", "founder_bio": "Co-founder & Chief Scientist at Dreamscale Labs (YC F26). 2x IChO silvers. Former quant turned roboticist.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/kevin-lin-760945225", "x_url": "https://x.com/KDog112358", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3cb1cdd011a18c5f4a990d27be41f778083f05fe.jpg" }, { "user_id": 1446496, "full_name": "Antoine Nguyen", "title": "Founder/CTO", "founder_bio": "Co-founder & CTO at Dreamscale Labs (YC F26). Previously VLA quantization researcher at UTS.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/antoine-n-633b84200", "x_url": "https://x.com/AntoineNeedGPUs", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/65178e94b80417e23e068039b7c0d6457cd4bca5.jpg" }, { "user_id": 2226354, "full_name": "Chris Yoo", "title": "Founder/CPO", "founder_bio": "Co-founder & CPO at Dreamscale Labs (YC F26). 15x hackathon winner. Youngest CCNA at 13yo.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/chris-yoo", "x_url": "https://x.com/pentestduck", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b1bd23643f138ca967c39ecdfe173e5347a12513.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 115448, "title": "Dreamscale Labs: Running robot brains in the cloud", "tagline": "The fastest cloud inference platform for robotics.", "body": "**TL;DR: We're 40-50% faster than existing cloud providers in serving frontier robot AI models, e.g. DreamZero, MolmoAct2.**\n\n\n\n\\[1x speed, autonomous\\]\n\nDSL is building the fastest cloud inference platform for robotics. We let you deploy physical AI without needing expensive local GPUs.\n\nRobot foundation models are growing more and more computationally expensive. The latest frontier of robotics no longer fits feasibly on local GPUs. Compute costs keep soaring amidst a global LPDDR shortage; NVIDIA just doubled the prices of Jetsons in July.\n\n**We're taking a contrarian bet that the future is moving inference _off the robot_ and _into the cloud._**\n\n![uploaded image](/media/?type=post&id=115448&key=user_uploads/3499827/4ca20fc9-00a8-4043-bc43-d51b8b5d0cbf)\n\nHow do we do this? We work across the full stack of robot inference to push latency down:\n\n* Model-level architectural adjustments for faster inference\n* Kernel-level optimizations to maximally leverage server-grade GPUs\n* Network-level optimizations for fast and reliable transport over the cloud\n* Region-specific compute allocation to ensure the shortest physical distance between the servers and our customers' robots\n\nThese optimizations enable us to be **8% faster** than NVIDIA's implementation **at half the GPU count** (320ms vs 350ms, for DreamZero 14B).\n\n![uploaded image](/media/?type=post&id=115448&key=user_uploads/3499827/69393040-ca17-41cd-a1fb-cd5d70176921)\n\nFurthermore, something we noticed for robotics companies with fast R&D cycles was that their GPUs had long idle periods with concentrated bursts of inference traffic. We're one of the first companies in the world to offer on-demand pricing for physical AI inference, giving users more flexibility with the cost.\n\nWe're already working closely with a range of early partners across deployment, research and evaluation. In full FDE spirit, we collaborate with our customers to custom-fit inference stacks that address their unique deployment challenges. We help you get your robot AI to deployment faster.\n\nOur mission is to democratize access to frontier physical intelligence, and we believe cloud is the way forward. You can read our thesis here:\n\n•⁠ ⁠\n\n\\\n**Our ask:** Reach out at [founders@dreamscalelabs.com](mailto:founders@dreamscalelabs.com) !", "url": "https://www.ycombinator.com/launches/U24-dreamscale-labs-running-robot-brains-in-the-cloud", "votes": 52, "created_at": "2026-09-17T23:00:00.159Z" } ] }, { "id": 36777, "name": "Sona8", "slug": "sona8", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/68fe01dae2c3bf0906f880c9a0f3fca2b2a16863.png", "website": "https://sona8.com", "all_locations": "San Francisco, CA, USA", "long_description": "Sona8 uses AI voice agents to interview employees about how work gets done. Consulting, transformation and corporate development teams use it to hear from more people and follow up after changes.\r\n\r\nEmployees open a link and speak in their own language. The agent asks follow-up questions, and teams compare problems across sites and departments. We’ve completed 10,000+ employee interviews and signed one of the world’s top three consulting firms.\r\n\r\nWe’re building the context layer and operating system for strategy teams: combining employee knowledge with company data to understand operations, improve processes and put decisions into action. The same context will guide AI agents as they take over work, so the company keeps what it learns.", "one_liner": "Context layer from employee voices to improve & automate workflows", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Operations", "launched_at": 1788994017, "tags": [ "HR Tech", "Infrastructure", "AI", "Conversational AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2026", "status": "Active", "industries": [ "B2B", "Operations" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": [ { "question": "How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)", "answer": "Thilo and I worked together at BCG, interviewing employees and repeatedly going back to them during implementation. On our evening runs, we started asking whether AI could make those conversations possible across an entire company.\r\n\r\nWe started building after BCG, while I was at MIT and Thilo was researching conversational AI at TUM. As pilots gained traction, we both left our programs. Madeleine brought her experience as a self-taught engineer, repeat founder and former principal engineer at McKinsey QuantumBlack." }, { "question": "What is your long-term vision? If you truly succeed, what will be different about the world?", "answer": "Every major decision depends on context. Much of it sits with employees who know how work happens and why things fail, but that knowledge rarely reaches the people deciding what to change.\r\n\r\nWe’re building Sona8 into the operating system for strategy and transformation teams. We will combine what our voice agents learn from employees with company data to build a live model of the organization. Teams will use it to compare alternatives and understand what a decision would require across sites and departments.\r\n\r\nThe same model will be the context layer for AI automation. Sona8 will use it to deploy agents and coordinate execution, then learn from the results. Small teams will be able to steer company-wide change, with the organization keeping what it learns as people and agents move on." } ], "url": "https://www.ycombinator.com/companies/sona8", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/sona8.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/sona8/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/68fe01dae2c3bf0906f880c9a0f3fca2b2a16863.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Nicolas Dessaigne", "url": "https://www.ycombinator.com/people/nicolas-dessaigne" }, "founders": [ { "user_id": 3105161, "full_name": "Anton Hantel", "title": "Founder/CEO", "founder_bio": "Founder at Sona8. Previously consultant at BCG. Left my MBA at MIT to pursue Sona8. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/anton-hantel/", "x_url": "https://x.com/anton_hantel", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c14efb12829902c98a22acefb4498ba903d68b9a.jpg" }, { "user_id": 3678831, "full_name": "Madeleine Malmsten", "title": "Founder/CTO", "founder_bio": "Founder at Sona8, leading tech. Previously principal engineer at McKinsey & Company / QuantumBlack.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/mmalmsten", "x_url": "https://x.com/madde", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f607e063e70742117b7da2519cdb306640b41c09.jpg" }, { "user_id": 3201024, "full_name": "Thilo Tamme", "title": "Founder/CPO", "founder_bio": "Founder of Sona8. Previously, Project Lead at BCG X and AI Researcher at TUM for conversational agentic-AI. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/ttamme/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a8ba204166c8494164fcfd905127a89f60550e3e.jpg" } ], "jobs": [], "news": [ { "title": "Y Combinator Launches of the Week", "url": "https://www.menlotimes.com/post/y-combinator-launches-of-the-week-181", "date": "Oct 13, 2026" }, { "title": "What Employees Tell AI Voice Agents About Workplace AI", "url": "https://techyorker.com/employee-ai-use-and-voice-agents-what-a-small-field-study-found/", "date": "Oct 11, 2026" }, { "title": "Sona8 entra en Y Combinator: las startups de IA que automatizan las entrevistas de trabajo", "url": "https://www.merca2.es/2026/10/05/sona8-y-combinator-startups-ia-2468011/", "date": "Oct 05, 2026" }, { "title": "Sona8: Former Consultants Get Into Y Combinator With A.I. Interviews | Trending Topics", "url": "https://www.trendingtopics.eu/sona8-y-combinator-ai-interviews/", "date": "Oct 05, 2026" }, { "title": "Sona8: Unternehmen nutzen Interviews mit KI", "url": "https://startupvalley.news/de/sona8-unternehmen-interviews-ki/", "date": "Sep 30, 2026" } ], "launches": [ { "id": 120585, "title": "Sona8: AI voice agents surveying employees about their work", "tagline": "The context layer for AI automation, starting with what employees say", "body": "**TL;DR:** [Sona8](https://sona8.com/) is building the context layer for AI automation tools, starting with AI voice surveys of employees. Corporate development, transformation and consulting teams use Sona8 to find out how to improve or automate processes.\n\n\n\nWe're [Thilo](https://www.linkedin.com/in/ttamme/), [Madeleine](https://www.linkedin.com/in/mmalmsten/) and [Anton](https://www.linkedin.com/in/anton-hantel/). We're building Sona8.\\\nAt BCG and McKinsey we often interviewed a few dozen people, hired interpreters and came back with a deck. The processes that were written down were never the lived processes and a few dozen interviews never gave us the full picture.\\\n\\\n**How it works**\n\n* **Choose what you want to improve or automate.** Pick a question and the people to survey. This could be about sales quoting or mapping processes before implementing AI.\n* **Survey employees with AI voice agents.** Employees talk to our voice agent about their work, in their own language. The agent asks follow-up questions to understand the problems they describe.\n* **Use the findings and check progress.** See themes across interviews by department, get process maps, and ask again later to see what changed.\n\n\\\n**Already live**\\\nWe’ve completed more than 10,000 employee interviews and signed one of the top three consulting firms.\\\n\\\n**Where this is going** \\\nCompanies will try a lot of AI agents and automation tools in the next few years. Each one needs to know how the work is done before it changes anything, and most of that isn't written down. Sona8 creates infrastructure for AI automation tools. Over time we are building a live context graph of workflows by reading the systems a company already uses and connecting them to what employees say. \\\n\\\n**Who it’s for**\\\nSona8 is for corporate development and transformation teams in enterprises, and the consulting firms supporting them. Reach out if you want to understand and improve how work gets done, roll out AI, or build AI tools that understand real-world workflows.\\\n**👉 [Book a demo](https://sona8.com/book-demo) / [anton@sona8.com](mailto:anton@sona8.com)**\n\n\\\n**Team**\n\n* [Anton Hantel (CEO):](https://www.linkedin.com/in/anton-hantel/) ex BCG, MIT MBA (dropped out)\n* [Thilo Tamme (CPO): ](https://www.linkedin.com/in/ttamme/)ex BCG X, TUM Conversational AI PhD (dropped out)\n* [Madeleine Malmsten (CTO):](https://www.linkedin.com/in/mmalmsten/) ex McKinsey QuantumBlack\n* [Jakob Schepers (Founding Engineer):](https://www.linkedin.com/in/jakob-schepers/) TUM CS Master's\n* [Niklas Schneider (Founding Account Executive): ](https://www.linkedin.com/in/nikschneider/) ITONICS, Maastricht SBE", "url": "https://www.ycombinator.com/launches/VMv-sona8-ai-voice-agents-surveying-employees-about-their-work", "votes": 52, "created_at": "2026-10-09T14:30:04.447Z" } ] }, { "id": 36906, "name": "Memorable", "slug": "memorable", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/044e23bebf5afa8daf2de443d127002bbc57895a.png", "website": "https://www.memorable.sh/", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "", "one_liner": "reducing agent reasoning into a graph search problem", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1789543087, "tags": [ "Developer Tools", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2027", "status": "Active", "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": [ { "question": "What is your long-term vision? If you truly succeed, what will be different about the world?", "answer": "Our long-term vision is that AI agents accumulate experience instead of resetting after every session.\r\n\r\nIf Memorable succeeds, every completed task will make every future agent in an organization more capable. An agent facing a new goal will compose previously verified procedures, reason only about what is genuinely unfamiliar, and improve those procedures through use. Work that once required thousands of independent model decisions will become reliable execution over an evolving graph of operational knowledge.\r\n\r\nThe immediate implication is that we change what companies own. Today they rent intelligence from model providers while the experience generated by their agents disappears into logs. In the future, companies will own a durable memory of how their work gets done.\\\r\n\\\r\nThe greater vision however is a world where agents can pursue goals across weeks, months, and years; Memorable will be the runtime layer of abstraction for agents to do less menial work and more time thinking, planning, and orchestrating. **Long horizon tasks will be trivial.** Drift will be reduced 10x. \\\r\n\\\r\nAnd if everything goes perfectly, this **shared network** of **raw procedural intelligence** will get us one step closer to AGI." } ], "url": "https://www.ycombinator.com/companies/memorable", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2027/memorable.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/memorable-sh/about/?viewAsMember=true", "x_url": "https://x.com/memorablesh", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/044e23bebf5afa8daf2de443d127002bbc57895a.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/57e2408110cd21effc657ee481fca3ba7ce6ce7a.png" ], "primary_partner": { "name": "Kulveer Taggar", "url": null }, "founders": [ { "user_id": 2164442, "full_name": "Nikhil Krishnaswamy", "title": "Founder/CEO", "founder_bio": "CS @ Stanford\nBuilding navigation for agents @ Memorable\nnikhil@memorable.sh", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/nikhil-krishnaswamy/", "x_url": "https://x.com/nikhilk8754", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ebb2609ed670c13f4da2e10851ae8caceca35a18.jpg" }, { "user_id": 3250603, "full_name": "Advaiyt Sane", "title": "Founder/CTO", "founder_bio": "CS @ CMU '29\nCreating Memorable, turning agent reasoning into graph search. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/advaiyt-sane-7a960a215/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/945086f34ce3b411a9ca8661006f418a4bab2718.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 115489, "title": "Memorable: graph procedural memory for AI agents. Stop re-teaching your agents!", "tagline": "Memorable gives AI agents procedural memory so they stop re-deriving the same workflow every time — cutting tool calls 60% and latency 40%.", "body": "# **_| TL;DR:_** Memorable records the tool calls an agent made to run a task, reuses that workflow on similar tasks instead of re-deriving through reasoning from scratch. –60% tool calls, –40% latency.\n\n\n\n**Memorable turns agent reasoning into a graph search problem.**\n\n1. We **capture your agents' traces** and store them as a lightweight graph.\n2. When a similar prompt arrives, we **extrapolate a workflow with a graph search.**\n3. We **inject a short pointer** (50 to 100 tokens) into the prompt.\n\n![uploaded image](/media/?type=post&id=115489&key=user_uploads/2164442/8a549d1f-423e-4011-90b8-d8e0145a1323)\n\n# **So the agent runs deterministically instead of re-deriving a plan every. single. time.**\n\n### **_Forget tokenmaxxing._**\n\n**We're graph-first and anti-text so you SAVE time, tokens, and money.**\n\n* **–60% tool calls** and **–40% latency** on [**QM's**](https://github.com/yc-software/qm) benchmarks\n* **–20% turns** in [**Gbrain**](https://github.com/garrytan/gbrain) bench, ran [**GStack’s**](https://github.com/garrytan/gstack) /investigate skill with **–98% tokens**\n\n**Do your agents need procedural memory?**\n\n* Memorable is for anyone running agents that do the same work more than once.\n* We've built for **coding, support, ops, research, company brain, and browser/computer-use agents.**\n* If you find yourself repeatedly having to correct or guide your agents, they need procedural memory!\n\n### **Imagine a world where your agents don’t reason.**\n\n* Most agent memory layers store facts using text: preferences, docs, past chats, while Memorable stores procedures: the steps an agent takes to achieve an outcome.\n* We are able to encode this graphically using nodes and edges, making it incredibly agent-friendly and token-efficient, allowing most agents to skip the preliminary planning step altogether.\n\n**Try Memorable, your agent will onboard you!**\n\n```\nnpx memorable-cli\ncurl -fsSL https://memorable.sh/install.sh | sh\n```\n\n* Compatible with **Claude Code, Codex, Cursor, and Claude Cowork**\n* You can try it out live in [**QM**](https://github.com/yc-software/qm) and [**Gbrain**](https://github.com/garrytan/gbrain) (thanks [**@Joshua France**](https://bookface.ycombinator.com/user/211454) &\n\n [**@Garry Tan**](https://bookface.ycombinator.com/user/678)!)\n* Procedures live encrypted in your own cloud, or run entirely local.\n\n![uploaded image](/media/?type=post&id=115489&key=user_uploads/2164442/59c2f411-3d34-482a-ba18-a03e14ecc4e2)\n\n**Memorable Team**\n\n* [**Nikhil Krishnaswamy**](https://bookface.ycombinator.com/user/2164442) \\[Stanford CS\\]: created an iOS MCP interning at AGI Inc, research published in COLM and IEEE\n* [**Advaiyt Sane**](https://bookface.ycombinator.com/user/3250603) \\[Carnegie Mellon CS\\]: built dev tools at Nvidia that create 50k AV tests a month\n\n**We are looking for design partners!**\n\n* Would love to chat with teams **deploying agents at volume** (high tool-call or token spend, repeated workflows) willing to **pilot as design partners.**\n* Open to **custom harness and framework integrations** for your interesting use cases\n\nEmail [info@memorable.sh](mailto:info@memorable.sh) and we'll spend a day solving your memory problems with you, plus:\n\n* LIFETIME of Memorable Pro FREE\n* Reach out to us about anything agent memory-related, whether or not you use Memorable :)\n\nand grab a slot: [**cal.com/team/memorable/30**](http://cal.com/team/memorable/30)\n\n[website](https://memorable.sh) | [docs](https://memorable.sh/docs) | [try memorable](https://memorable.sh)\n\nLet's build something Memorable!", "url": "https://www.ycombinator.com/launches/U2j-memorable-graph-procedural-memory-for-ai-agents-stop-re-teaching-your-agents", "votes": 15, "created_at": "2026-09-17T19:00:00.406Z" } ] }, { "id": 37038, "name": "Caveman", "slug": "caveman", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/255bbf73f87bb02fde740dd7da4814d8d2b5f4e1.png", "website": "https://caveman.so", "all_locations": "Amsterdam, NH, Netherlands", "long_description": "Caveman is the optimization stack for AI agents. It observes real agent workloads, finds cost and performance inefficiencies, tests improvements, and safely deploys the ones that work.", "one_liner": "Caveman cuts what AI agents cost without making them dumber.", "team_size": 1, "industry": "B2B", "subindustry": "B2B", "launched_at": 1791916413, "tags": [ "Developer Tools", "Open Source", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2026", "status": "Active", "industries": [ "B2B" ], "regions": [ "Netherlands", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/caveman", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/caveman.json", "year_founded": 2026, "city": "Amsterdam", "country": "NL", "linkedin_url": "https://www.linkedin.com/company/caveman-so/", "x_url": "", "fb_url": null, "cb_url": null, 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", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/olism/", "x_url": "https://x.com/oliviersm199", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d54e4534691360fc80d558e0622c9457684b7278.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 37435, "name": "GrayPass", "slug": "graypass", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/824e97773961053f47e92f9a1a6fd805d2328d0b.png", "website": "https://www.graypass.org", "all_locations": "Toronto, ON, Canada", "long_description": "Login tells you who signed in. GrayPass helps apps check who’s behind sensitive actions and whether they’re authorized before those actions go through.\r\n\r\nIt combines identity, device and session context with behavioral signals like typing rhythm, cursor movement and scrolling. 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Allowed actions receive short-lived, signed proof tied to the exact action and your app.\r\n\r\nYour existing login and authentication stack stays in place.", "one_liner": "Verify the expected person is still in control before sensitive…", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1789869580, "tags": [ "Biometrics", "Identity", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2026", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "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/graypass", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/graypass.json", "year_founded": 2025, "city": "Toronto", "country": "CA", "linkedin_url": "https://www.linkedin.com/company/graypass", "x_url": "https://x.com/graypassinc", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/824e97773961053f47e92f9a1a6fd805d2328d0b.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/48514b7baa4f379e077c2d2d12a82ebd8ae031f4.png" ], "primary_partner": { "name": "Max Kolysh", "url": null }, "founders": [ { "user_id": 1531836, "full_name": "Arav Mathur", "title": "Founder/CEO", "founder_bio": "Founder/CEO at GrayPass (YC F26). University of Waterloo CS. Founded my first startup at 15 and raised $30K. Launched a fashion app that reached 3K users in 3 weeks and generated 1M+ views on social media. Served as the sole growth engineer at Stan ($40M ARR). At 16, developed dubbing and translation tools for creators including Logan Paul, Yes Theory and GothamChess. Now building GrayPass to help apps verify who's behind sensitive actions and whether they're authorized, even after login.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/aravmathur/", "x_url": "https://x.com/aravmathur23", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d0532c0b2de20032b2205d049f1f59bf9049dd28.jpg" }, { "user_id": 3483494, "full_name": "Aditya Ranjan", "title": "Founder/COO", "founder_bio": "Founder/COO @ GrayPass (YC F26) | Making human agency legible. Previously studied Neuroscience @ McGill. Conducted neurosurgical research at SickKids, with work published in Springer Nature. Granted a fellowship @ UBC to develop longitudinal transformer models predicting epilepsy outcomes from MRI scans. Founded an organization developing seizure-detection technology for epilepsy applications. Created brain tumour segmentation algorithms for UPenn BraTS challenges alongside EPFL researchers. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/ad1tyaranjan", "x_url": "https://x.com/ad1tyaranjan", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/fdf5b6e06af9375cb8bc6e94648303ce942a314f.jpg" } ], "jobs": [], "news": [ { "title": "Small Business Security Now Depends On What Happens After Login", "url": "https://www.forbes.com/sites/terdawn-deboe/2026/09/23/small-business-security-now-depends-on-what-happens-after-login/", "date": "Sep 23, 2026" } ], "launches": [] }, { "id": 38061, "name": "Maritime", "slug": "maritime", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d8ff801ef7e9094077a292c8bed3e86ce7e01f00.png", "website": "https://maritime.sh/", "all_locations": "San Francisco, CA, USA", "long_description": "Maritime is a fully managed cloud platform for startups selling AI agents. 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", "is_active": true, "linkedin_url": "https://linkedin.com/in/aryshriv", "x_url": "https://x.com/AryShriv", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1fd69dca86a8ca1c88e42dea655277268f3e64e4.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 120824, "title": "Maritime: Fully managed cloud for running AI agents at scale", "tagline": "Run millions of agents, each on its own isolated, persistent VM.", "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\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" } ] } ]