[ { "id": 289, "name": "JustSpotted", "slug": "justspotted", "former_names": [], "small_logo_thumb_url": "/company/thumb/missing.png", "website": "http://justspotted.com", "all_locations": "San Francisco, CA, USA; Copenhagen, Denmark", "long_description": "The artist-formerly-known-as Scoopler is a real-time search engine. It aggregates and organizes content being shared on the Internet as it happens, like eye-witness reports of breaking news, photos and videos from big events, and links to the hottest memes of the day. It does this by constantly indexing live updates from services including Twitter, Flickr, Digg, Delicious and more. When users search for a topic on Scoopler, they get the most relevant results, updated in real-time.\n\nScoopler has now become JustSpotted, a celebrity-tracking tool, meant to give fans an idea of what their favorite celebrities are up to at any given moment. JustSpotted, like Scoopler, is a data-aggregator, yet JustSpotted collects from Twitter, Facebook, and Foursquare -- alongside their own data they’ll be collecting from users who actual spot celebrities in the wild. All the information we aggregate is publicly available and you can even do a search on Twitter yourself and find sightings of celebrities. We're just the first people to organize it on a map and in such a way that it's easy to consume and ENJOY.”\n\nJustSpotted is about connecting with celebs. All the sightings on our website are naturally occurring events where an everyday person bumps into a celebrity as a chance occurrence. Back in the day, when you saw a celebrity while you were out and about the first thing you would have done was phone or text a friend. In the new age of social media, the first thing you do is share it on Facebook or Twitter. This phenomena is already happening.\n\nThe service, which launches the week of October 11, 2010, is the latest creation by AJ Asver, Dilan Jarawardane and Benjamin Tauber.", "one_liner": "Acquired by Google in 2011", "team_size": 2, "industry": "Consumer", "subindustry": "Consumer -> Content", "launched_at": 1326791006, "tags": [ "AI", "ML" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2008", "status": "Acquired", "industries": [ "Consumer", "Content" ], "regions": [ "United States of America", "Denmark", "America / Canada", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/justspotted", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2008/justspotted.json", "year_founded": null, "city": "San Francisco", "country": "US", "linkedin_url": null, "x_url": null, "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/justspotted", "github_url": null, "logo_url": null, "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [], "jobs": [], "news": [], "launches": [] }, { "id": 1583, "name": "Skyways", "slug": "skyways", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6732fcb5c7c414475034015c2f1a9fa75a9f12a7.png", "website": "http://skyways.com", "all_locations": "Austin, TX, USA", "long_description": "", "one_liner": "Creating a new form of air transportation to advance our civilization", "team_size": 33, "industry": "Industrials", "subindustry": "Industrials -> Drones", "launched_at": 1493063490, "tags": [ "Air Taxis", "Robotics", "Computer Vision", "AI", "ML" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2017", "status": "Active", "industries": [ "Industrials", "Drones" ], "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/skyways", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2017/skyways.json", "year_founded": 2017, "city": "Austin", "country": "US", "linkedin_url": "https://www.linkedin.com/company/skyways-air-transportation-inc/", "x_url": "", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/skyways", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/6732fcb5c7c414475034015c2f1a9fa75a9f12a7.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": 74039, "full_name": "Charles Acknin", "title": "Founder", "founder_bio": "Software Engineer turned Chief Email Officer", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/charlesacknin", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4d6b88b66f3363f857e0d2909a3aca9b839d7710.jpg" } ], "jobs": [ { "id": 15757, "title": "Senior Software Engineer", "url": "https://www.ycombinator.com/companies/skyways/jobs/YAwmo8Xu5-senior-software-engineer", "location": "Austin, TX / Remote", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "3+ years", "visa": "US citizenship/visa not required", "skills": [ "C++", "JavaScript", "Python" ] }, { "id": 31256, "title": "Senior ML/AI/CV Software Engineer", "url": "https://www.ycombinator.com/companies/skyways/jobs/8eze2rSvj-senior-ml-ai-cv-software-engineer", "location": "Austin, TX / Remote", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "", "equity_range": "", "experience": "3+ years", "visa": "US citizenship/visa not required", "skills": [ "C++", "Python" ] } ], "news": [], "launches": [] }, { "id": 12091, "name": "Superb AI", "slug": "superb-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/557ab62b86d1ab472dd3665292fc28d7191fb8b9.png", "website": "https://www.superb-ai.com", "all_locations": "Seoul, Seoul, South Korea", "long_description": "Superb AI is a leading computer vision platform and professional services provider that provides enterprise-grade, end-to-end MLOps and DataOps workflows to accelerate the adoption and development of data-centric AI. Through the practical application of AI-based automation, Superb AI helps teams manage the entire ML lifecycle more efficiently, from data annotation to curation, model training, and deployment, while ensuring optimal data accuracy and consistency.", "one_liner": "Superb AI provides end-to-end computer vision MLOps platform", "team_size": 80, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1541714572, "tags": [ "AIOps", "SaaS", "B2B", "AI", "ML" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2019", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "South Korea", "East Asia", "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/superb-ai", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2019/superb-ai.json", "year_founded": 2018, "city": "Seoul", "country": "KR", "linkedin_url": "https://www.linkedin.com/company/superb-ai", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/557ab62b86d1ab472dd3665292fc28d7191fb8b9.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 283696, "full_name": "Hyun Kim", "title": "Founder", "founder_bio": "- Co-founder, CEO @ Superb AI ('18-now)\n- AI Engineer @ SK Telecom ('16-'18)\n- Duke University, B.S / Ph.D. dropout", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/hyunsoo-kim-a60557b2/", "x_url": "https://twitter.com/_hyunkim_", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4fa2d826959ab8d087998c92b24f202bcbc4fc8e.jpg" }, { "user_id": 291225, "full_name": "Moonsu Cha", "title": "Founder", "founder_bio": null, "is_active": true, "linkedin_url": "https://www.linkedin.com/in/moonsucha/", "x_url": null, "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7168e703887857dbabe80127b8a5318492f00f23.jpg" }, { "user_id": 291636, "full_name": "Jonghyuk Lee", "title": "Founder", "founder_bio": null, "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jonghyuk-lee-5612a312a", "x_url": null, "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/50818bc4ac0183178b7789a819e4514fcc8f7b06.jpg" }, { "user_id": 291639, "full_name": "Jungkwon Lee", "title": "Founder", "founder_bio": null, "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jung-kwon-lee-67a36a152/", "x_url": null, "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d5cd3c5ce5668e2006e0012e5b0f1803004cf199.jpg" } ], "jobs": [], "news": [ { "title": "YC-Backed AI Startup Raises Series C From Korea’s Doosan And Hyundai", "url": "https://www.forbes.com/sites/johnkang/2024/10/24/yc-backed-ai-startup-raises-series-c-from-koreas-doosan-and-hyundai/", "date": "Oct 24, 2024" } ], "launches": [] }, { "id": 24291, "name": "DigiBuild", "slug": "digibuild", "former_names": [ "DigiBuild Software Inc.", "DigiBuild Software" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/619bfcc11ede71a157f8463466ae0bd8ddd6cc7e.png", "website": "https://digibuild.com", "all_locations": "Miami, FL, USA", "long_description": "Our platform fixes construction's broken supply chain. 70% of construction projects finish late or over budget; procuring and managing building materials is the number 1 reason why. \r\n\r\nWe use LLMs to buy and manage building materials for large construction companies.\r\nWith DigiBuild, construction contractors can find, order, track and manage their materials from the supplier to the job site. We help customers save money, staff time, and improve construction project schedules.\r\n\r\nWe work with the top real estate developers, general contractors, and subcontractors in the US. We manage billions in building material volume annually in the 2nd largest market in the world.", "one_liner": "We buy & track building materials for construction companies.", "team_size": 15, "industry": "Real Estate and Construction", "subindustry": "Real Estate and Construction -> Construction", "launched_at": 1626214444, "tags": [ "SaaS", "Supply Chain", "AI", "ML" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "Real Estate and Construction", "Construction" ], "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/digibuild", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2021/digibuild.json", "year_founded": 2018, "city": "Miami", "country": "US", "linkedin_url": "https://www.linkedin.com/company/digibuild-software/", "x_url": "https://twitter.com/DigiBuildInc", "fb_url": "https://www.facebook.com/DigiBuildSoftware", "cb_url": null, "github_url": "https://github.com/DigiBuildOfficial", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/619bfcc11ede71a157f8463466ae0bd8ddd6cc7e.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 499292, "full_name": "Robert Salvador", "title": "Founder", "founder_bio": "- Cofounder & CEO of PoliTech.AI: Digital sales robots that sell for startups.\n- Fmr Founder & CEO DigiBuild: AI optimizes buying building materials.\n- Fmr Founder & President of SLP, a Commercial Construction company.\n- 750M+ in sales prospected and closed since 2015.\n- Bitcoin & Crypto since 2016.\n- Seen on Fox Business, NBC, CNBC, Newsnation.\n- Influencer on Linkedin, X.\n-Prev backed by: YC, Draper Associates, Valhalla Ventures, Picus Cap, Bluefield Capital, Cathexis Ventures, Harvard.\n", "is_active": false, "linkedin_url": "https://www.linkedin.com/in/robertjsalvador/", "x_url": "https://twitter.com/robertjsalvador", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/fda657636b07cd862a9a20ed722eb1e0347bc61e.jpg" }, { "user_id": 406774, "full_name": "Ivan Franco", "title": "Founder", "founder_bio": "VP of Eng @DigiBuild", "is_active": false, "linkedin_url": "https://www.linkedin.com/in/theivanfranco/", "x_url": "https://twitter.com/theivanfranco", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d80c8f2a876cb49ac1189b1028db247c634fa24c.jpg" } ], "jobs": [ { "id": 87922, "title": "Sales Lead | The “Promota\" Gauntlet", "url": "https://www.ycombinator.com/companies/digibuild/jobs/zdGrE47-sales-lead-the-promota-gauntlet", "location": "Chicago, IL, US / San Francisco, CA, US / Remote (US)", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$50K - $250K", "equity_range": "1.00% - 5.00%", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [ { "title": "DigiBuild raises $1.3M seed extension, inks partnerships with major builders.", "url": "https://www.linkedin.com/feed/update/urn:li:activity:7063919781657116673/", "date": "May 15, 2023" }, { "title": "DigiBuild on Fox Business.", "url": "https://www.foxbusiness.com/video/6326568901112", "date": "May 01, 2023" }, { "title": "Tech expert Robert Salvador: We don't want 'mass layoffs' because of disruptive technology | Fox Business Video", "url": "https://www.foxbusiness.com/video/6326568901112", "date": "May 01, 2023" }, { "title": "AI set to transform construction industry", "url": "https://www.foxbusiness.com/technology/ai-disrupt-construction-industry", "date": "Apr 26, 2023" }, { "title": "DigiBuild Raises $4M Seed Round to Fix Construction Supply Chains", "url": "https://www.ibtimes.com/digibuild-raises-4m-seed-round-fix-construction-supply-chains-3586919", "date": "Jul 26, 2022" } ], "launches": [] }, { "id": 24573, "name": "Telmai", "slug": "telmai", "former_names": [ "Telm.ai" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/263d4d84c92376ed8c755e0f7348f5c855dc3ec8.png", "website": "https://www.telm.ai/", "all_locations": "San Francisco, CA, USA; Foster City, CA, USA; Remote", "long_description": "Telmai is a Data observability and Data Quality platform designed for Open architecture. It monitors data stored/managed in any data system, such as a data lake or data warehouse, in its raw format at scale without sampling", "one_liner": "Automated data observability and quality for Data Lake", "team_size": 12, "industry": "B2B", "subindustry": "B2B", "launched_at": 1629822671, "tags": [ "Analytics", "AI", "ML" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2021", "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": [ { "question": "Describe what your company does in 50 characters or less.", "answer": " Intelligent data observability platform" }, { "question": "How long have each of you been working on this? How much of that has been full-time? Please explain.", "answer": "The co-founders, Mona Rakibe (CEO) and Max Lukichev (CTO) have been working on Telm.ai full-time since November 2020. Both Mona and Max each bring 15+ years of experience in Data management and enterprise products." }, { "question": "What is your company going to make? Please describe your product and what it does or will do.", "answer": "Telm.ai is a real-time data anomaly detection, and investigation platform that is built for data engineers and data architects to ensure high data quality pipelines. \r\nOur product (API), can monitor every data value ingested at the record level to detect and understand the problems in the data much before they get into your analytical and AI systems, hence reducing Mean Time To Detect (MTTD) and Mean Time to Resolve (MTTR) data issues." } ], "question_answers": null, "url": "https://www.ycombinator.com/companies/telmai", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2021/telmai.json", "year_founded": 2020, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/telmai", "x_url": "https://twitter.com/telmai1", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/263d4d84c92376ed8c755e0f7348f5c855dc3ec8.png", "app_video_url": null, "dday_video_url": "https://bookface-images.s3.us-west-2.amazonaws.com/video_event/54/1630627379366-l5l21gysoyp-a404e30bb0c93d6e5d845386bd6769e9/05b6982bca20053d76222a437c532823.mp4?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAQC4NIECABPQ2AHNW%2F20261020%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20261020T022659Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&X-Amz-Signature=806c274fa476ea99051ba47964ef938ec2003f607e2c8d0e3eebd5f239d872d8", "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 716028, "full_name": "Mona Rakibe", "title": "Founder", "founder_bio": "Started Telmai in November 2020 with a vision to improve data quality.\nPrior to Telmai spend 5 years at a Data management start-up as director of product management. \n\n", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/monarakibe/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ad63abd07d293c44039137cf6304c32cf25318bd.jpg" }, { "user_id": 730028, "full_name": "Maxim Lukichev", "title": "Founder", "founder_bio": "Data Science and Engineering Leader with over 15 years of experience in various environments including startups and Fortune 500 companies", "is_active": true, "linkedin_url": "http://linkedin.com/in/maximlukichev", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/8a9fccf97ea63769b3a9b57d0ea5c3eb7b58e9a2.jpg" } ], "jobs": [ { "id": 88608, "title": "Forward-Deployed Customer Engineer (Enterprise)", "url": "https://www.ycombinator.com/companies/telmai/jobs/ScUH8cF-forward-deployed-customer-engineer-enterprise", "location": "US / Remote (US)", "type": "Contract", "role": "Sales", "role_type": null, "salary_range": "$140 - $160", "equity_range": "0.10% - 1.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "Data Modeling" ] }, { "id": 91092, "title": "Technical Sales Engineering", "url": "https://www.ycombinator.com/companies/telmai/jobs/1AJFiA4-technical-sales-engineering", "location": "US / CA / Remote (US; CA)", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$120K - $160K", "equity_range": "0.20% - 0.80%", "experience": "6+ years", "visa": "US citizen/visa only", "skills": [ "Data Modeling", "Data Analytics" ] } ], "news": [ { "title": "Data observability startup Telmai raises $5.5M in oversubscribed seed round - SiliconANGLE", "url": "https://siliconangle.com/2023/06/15/data-observability-startup-telmai-raises-5-5m-oversubscribed-seed-round/", "date": "Jun 15, 2023" }, { "title": "Telmai Announces $2.8 Million Seed From .406 Partners, Zetta Venture Partners, Y Combinator & others", "url": "https://www.telm.ai/post/telmai-announces-2-8-million-seed-from-406-partners-zetta-venture-partners-y-combinator-others", "date": "Oct 26, 2021" } ], "launches": [] }, { "id": 25590, "name": "Emobi", "slug": "emobi", "former_names": [ "Laegacy Inc.", "AeonCharge" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d33f8249b3bdf459257e46d019d4e6687e56a9c0.png", "website": "https://www.emobi.ai", "all_locations": "San Francisco, CA, USA", "long_description": "Emobi is a unified legal, financial, and technical infrastructure that delivers seamless, secure, and reliable EV charging across networks—powering apps, fleets, and automakers while maximizing charger utilization. Our secure, fully automated charging technology, JustPlug, works instantly with no special hardware, software, or setup, making EV charging effortless.\r\n\r\nWith 122,000+ EV chargers integrated across the U.S. and Canada, Emobi is recognized as the largest EV charging ecosystem in North America. Backed by two provisional patents and 15+ enterprise customers, Emobi's technology is also trusted by the Department of Energy (DoE) and the Department of Transportation (DoT). To learn more, visit www.emobi.ai.", "one_liner": "A single point integration for secure and automated EV charging.", "team_size": 9, "industry": "B2B", "subindustry": "B2B", "launched_at": 1642021051, "tags": [ "API", "Energy", "Electric Vehicles", "AI", "ML" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "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/emobi", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2022/emobi.json", "year_founded": 2020, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/emobi-ai/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/d33f8249b3bdf459257e46d019d4e6687e56a9c0.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": 580972, "full_name": "Lin Sun Fa", "title": "Founder/CEO", "founder_bio": "Lin Sun Fa, CEO at Emobi, is an EV enthusiast with a deep knowledge in cybersecurity. Lin plays a leading role in the climate tech and energy space, garnered trust from organizations and leaders in the industry. He earned his Cybersecurity degree at Purdue University and was previously the global director of operations at Solar Chapter, a World-bank affiliated non-profit. In his free time, he is an avid traveler and a loving corgi-dad. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/lsunfa/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/6ba0c2349d48cfd7e95b952ce10bdc621645caed.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 26704, "name": "Two Dots", "slug": "two-dots", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/06c738449ceac7bc3068c3a0510a285b6078503d.png", "website": "https://www.twodots.com", "all_locations": "San Francisco, CA, USA", "long_description": "We're building an AI consumer underwriting automation agent. ", "one_liner": "AI fraud prevention and underwriting agent", "team_size": 28, "industry": "Fintech", "subindustry": "Fintech -> Consumer Finance", "launched_at": 1652906962, "tags": [ "Fintech", "Real Estate", "B2B", "AI", "ML" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2022", "status": "Active", "industries": [ "Fintech", "Consumer Finance" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Growth", "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": "Max and I have known each other since we were best friends at a middle school for gifted children in the Bay Area.After a four-year stint in the Foreign Exchange trading group covering Hedge Funds at Goldman, I spent two years as the fourth employee selling software to property managers. That experience taught me that every property manager’s biggest problem in their business was leasing, and no one had solved it. I called my old friend Max, who was working on the search team at Google, and asked him for advice on solving income verification for rentals. He responded that he had spent years working on this problem in the Mortgage space for Blend (now public), and that the transformers AI revolution finally made an end-to-end solution possible.Max resigned from Google a few months later, and we were working on Two Dots. Still hard to believe the serendipity sometimes." } ], "url": "https://www.ycombinator.com/companies/two-dots", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2022/two-dots.json", "year_founded": 2022, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/two-dots-financial", "x_url": "https://twitter.com/TwoDotsFinance", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/06c738449ceac7bc3068c3a0510a285b6078503d.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 965090, "full_name": "Henson Orser", "title": "Founder", "founder_bio": "Building Two Dots - AI fraud prevention and underwriting agent. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/henson-orser/", "x_url": "https://twitter.com/HensonOrser1", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/8ad18bb808ecb7004e70e21894f7eb49867be519.jpg" } ], "jobs": [ { "id": 76935, "title": "Product Engineer", "url": "https://www.ycombinator.com/companies/two-dots/jobs/ntVRsMt-product-engineer", "location": "San Francisco HQ", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$175K - $225K", "equity_range": "0.10% - 0.50%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "Google Cloud", "Node.js", "PostgreSQL", "Python", "React", "TypeScript" ] }, { "id": 76936, "title": "Sales Development Representative", "url": "https://www.ycombinator.com/companies/two-dots/jobs/GxUeTh3-sales-development-representative", "location": "San Francisco HQ", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$85K - $125K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 76937, "title": "Member of the Technical Staff - Machine Learning", "url": "https://www.ycombinator.com/companies/two-dots/jobs/ohLqqLG-member-of-the-technical-staff-machine-learning", "location": "San Francisco HQ", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$350K - $400K", "equity_range": "0.10% - 1.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "Torch/PyTorch", "Deep Learning", "Natural Language Processing", "Computer Vision", "LLMs" ] }, { "id": 95426, "title": "Chatbot Engineer", "url": "https://www.ycombinator.com/companies/two-dots/jobs/13hZxc3-chatbot-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$175K - $275K", "equity_range": "0.10% - 1.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "Chatbots", "Prompt Engineering", "LLMs", "AI Agents" ] }, { "id": 95427, "title": "Backend Engineer - Document Processing and Workflows", "url": "https://www.ycombinator.com/companies/two-dots/jobs/upEi8yp-backend-engineer-document-processing-and-workflows", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Backend", "salary_range": "$175K - $250K", "equity_range": "0.10% - 0.50%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "Google Cloud", "Kubernetes", "PostgreSQL", "Python", "Distributed Systems", "Machine Learning", "Data Analytics" ] }, { "id": 104067, "title": "Account Executive", "url": "https://www.ycombinator.com/companies/two-dots/jobs/NYVYkLL-account-executive", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$275K - $300K", "equity_range": "0.10% - 0.20%", "experience": "6+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [], "launches": [ { "id": 64985, "title": "Two Dots - Income & Employment Verification for Lenders", "tagline": "Two Dots is making it easy for underwriters, starting with large apartment managers, to make sure applicants make enough money to afford their products (like apartment rentals)", "body": "### **The Problem**\n\nTraditionally when a consumer wants to borrow money, take out a mortgage, or rent an apartment, they need to provide the underwriter with a bunch of financial documents to prove they can afford the product.  This is a time consuming & fraud ridden process!\n\n### **Our Solution**\n\nTo solve this problem we’re first automating the process of verifying income and employment data for large property managers. Over time we plan to integrate with many data sources so payroll data can be seamlessly used to make better & faster underwriting decisions by any financial institution.\n\n### **Who We Are**\n\nI started my career working at Goldman for 4 years, before making the jump to startup-land as the 4th employee at a proptech startup, where we processed online rental applications.  Seeing up close how broken the income verification process is, and how broken the overall way underwriters decide who gets access to housing (credit scores), lead us to realize there’s a better way.\n\nMax started his career as one of the first engineers on the income verification team at Blend, spending years working on this problem before making the jump to work on search at Google.  After experiencing both the excitement of being early at a rapidly scaling startup (Blend is now public), and the mega-scale of search at Google, Max and I decided we were the team to tackle the broken consumer underwriting system.\n\n### **How You Can Help**\n\nOur biggest focus today is getting more customers, **so if you know anyone managing thousands of rental properties we would love an intro!** ", "url": "https://www.ycombinator.com/launches/Gu9-two-dots-income-employment-verification-for-lenders", "votes": 18, "created_at": "2022-07-28T21:42:54.049Z" } ] }, { "id": 29046, "name": "Elythea", "slug": "elythea", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/bd032cddcdb63dd5b12b5be82827d23e79135094.png", "website": "https://elythea.org/", "all_locations": "San Diego, CA, USA", "long_description": "Over 80% of maternal mortalities were preventable with earlier intervention. Currently, doctors miss >50% of moms who have life-threatening complications and wait until labor to start doing manual risk assessments, at which point it's too late.\r\n\r\nElythea's proprietary ML models catch life-threatening obstetric complications (like postpartum hemorrhage, preeclampsia/eclampsia, emergency c-section, preterm labor, and more) as soon as the first visit. We automatically analyze relevant demographic and clinical risk factors, flag high-risk patients, and provide evidence-based interventions, giving doctors months in advance to intervene and prevent complications from ever happening.\r\n\r\nOur global clinical studies have shown that we can catch 3x more complications than clinical judgment 10x sooner. ", "one_liner": "ML to predict and prevent pregnancy complications ", "team_size": 2, "industry": "Healthcare", "subindustry": "Healthcare", "launched_at": 1691977453, "tags": [ "Health Tech", "Digital Health", "Women's Health", "AI", "ML" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2023", "status": "Active", "industries": [ "Healthcare" ], "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/elythea", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/elythea.json", "year_founded": 2023, "city": "San Diego", "country": "US", "linkedin_url": "https://www.linkedin.com/company/elythea/", "x_url": "", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/elythea", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/bd032cddcdb63dd5b12b5be82827d23e79135094.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/4083a31fd1a4daa7be3cc76af34a7d013be86f8d.png" ], "primary_partner": null, "founders": [ { "user_id": 483063, "full_name": "Reetam Ganguli", "title": "Founder", "founder_bio": "Got into Med school at Brown at 17, was studying to be an OBGYN, and dropped out to do Elythea. 1st authored 20+ publications, including multiple Nature journals. Previously founded and scaled a medical education organization across 30+ countries.", "is_active": true, "linkedin_url": "https://linkedin.com/in/reetamganguli", "x_url": "https://twitter.com/ReetamGanguli", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d4d58e1c64c1467a1d228bf705923115214b09e4.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 74096, "title": "Elythea: Preventing maternal mortality with ML", "tagline": "80%+ of pregnancy deaths are preventable. We use ML to catch and prevent life-threatening complications starting from the 1st visit.", "body": "# **🏆 TL;DR:**\n\nDoctors miss >50% of the life-threatening complications of pregnancy. We are an ML platform that integrates into the EHR to flag high-risk patients as early as their 1st visit, so doctors can intervene months before delivery.\n\n### **❌ The Problem**\n\nOver 80% of cases of maternal mortality are preventable with earlier intervention (CDC). Risk assessments in the status quo have low high-risk detection rates, which hurt a doctor’s ability to administer preventative care and ensure safe, healthy deliveries. \n\n**Doctors currently miss more than 50% of patients who have life-threatening complications and wait until labor to start doing manual risk assessments, at which point it's too late.**\n\nEach of these complications cost providers between $3K-15K per case and can cost payors up to $75k per case. \n\n**These major pregnancy complications cost insurers >$55B annually**!\n\n**📚Quick Quiz**: Hemorrhage (excessive bleeding) is the #1 killer of moms during labor. What percent of all moms that hemorrhage do you think doctors currently identify as high risk?\n\n**✔️Answer**: 22%. Yep, in 2023, doctors have to manually tabulate a risk assessment when patients are on the delivery bed and still fail to classify >75% of hemorrhage cases as high risk. Elythea catches 2x-3x more hemorrhaging patients as early as the first visit, evolving over the course of a pregnancy with patient visits.\n\n### **🌟 Our Solution**\n\n![uploaded image](/media/?type=post&id=74096&key=user_uploads/483063/6201ae97-898f-4d97-a435-839e7178f7a1)\n\nEarlier intervention and improved clinical preparation have been shown to **prevent nearly two-thirds of severe maternal complications**. Elythea's ML models flag high-risk patients as soon as the first visit and evolve over the course of a pregnancy.\n\n**We automatically analyze relevant demographic and clinical risk factors, flag high-risk patients, and provide evidence-based interventions, giving doctors weeks to months in advance to intervene and prevent complications from ever happening**.\n\nWe predict risk for conditions like postpartum hemorrhage, preeclampsia/eclampsia, emergency C-section, preterm labor, and more.\n\nWe have completed prospective international clinical studies across USA, Cameroon, and Nigeria demonstrating that our models have better performance than current gold-standard clinical tools. **Our global clinical studies have shown that we can catch 2-3x more moms with complications than current clinical risk assessments >10x sooner.**\n\n### **📖 The Backstory**\n\nReetam was on the medical school track to be a high-risk obstetrician and read all the standard OBGYN medical textbooks. He came across this problem after interviewing 80+ obstetric providers, where the vast majority pointed him toward the direction of postpartum hemorrhage and hypertensive complications. \n\n**Reetam** previously founded Junior Medical Academy, a global medical education nonprofit accessible to students across 30+ countries, and Survivor Central, a national platform matching survivors of sexual assault/domestic violence with medical/legal/financial resources. He has 1st authored >15 accepted medical publications, including in multiple Nature Journals. He studied cancer engineering at Brown and left medical school to work on Elythea full-time. \n\n### **🙏 Asks**\n\n* **Share this post!** We want to help as many high-risk moms as possible, any intro helps!\n* Connect us with **Providers** (obstetricians and MFM doctors, obstetric private practices, and hospital C-suite executives) \n* Connect us with **Health Plans**\n* Connect us with innovative maternity care startups that can benefit from our AI models!\\\n \\\n _\\* quick blurb to copy & paste:_ \\\n I came across Elythea, a YC S23 startup that uses ML to predict and prevent pregnancy complications as soon as the 1st visit! They integrate into EHR systems and flag complications like hemorrhage, preeclampsia, preterm labor, and emergency C-sections, helping to prevent them from happening. Check them out at or contact them at [info@elythea.org](mailto:info@elythea.org) to learn more!", "url": "https://www.ycombinator.com/launches/JH6-elythea-preventing-maternal-mortality-with-ml", "votes": 140, "created_at": "2023-08-15T01:22:26.863Z" } ] }, { "id": 29088, "name": "Cair Health", "slug": "cair-health", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/174cf352bddd34701bef4a958ce1e21e7d49de3d.png", "website": "https://www.cairhealth.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Cair Health empowers billing companies, care management platforms, EHRs, offshore BPOs, provider groups, and specialty pharmacies with AI-driven RCM solutions. Our suite of AI Agents helps RCM teams streamline operations, reduce manual costs, and improve consistency—while maintaining full control over core workflows. Cair is trusted by 100+ practices across the country — including iconic VC-backed digital health startups, leading specialty EHRs, and some of the largest billing companies and BPOs\r\n\r\nBacked by Y Combinator, Foundation Capital, Soma Capital, Translink Capital & many others.. ", "one_liner": "AI Agents for Healthcare RCM", "team_size": 6, "industry": "Healthcare", "subindustry": "Healthcare -> Healthcare IT", "launched_at": 1690913334, "tags": [ "Health Tech", "Healthcare", "Health Insurance", "AI", "ML" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2023", "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/cair-health", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/cair-health.json", "year_founded": 2023, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/cair-health/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/174cf352bddd34701bef4a958ce1e21e7d49de3d.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 1370983, "full_name": "Shehbaz Virk", "title": "Founder", "founder_bio": "Co-Founder @ Cair Health,\nPublic Health & Biochemistry @ UC Berkeley", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/shehbazvirk/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/71748884bfbe1b858958bd71a621295ef2b29331.jpg" }, { "user_id": 1371723, "full_name": "Ishan Balakrishnan", "title": "Founder", "founder_bio": "Co-Founder @ Cair Health,\nComp Sci & Business @ UC Berkeley", "is_active": true, "linkedin_url": "https://linkedin.com/in/ishanbalakrishnan", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7d50db33e360227615622d12c07eba5a88bdbb7c.jpg" } ], "jobs": [ { "id": 97972, "title": "Founding Customer Success Engineer", "url": "https://www.ycombinator.com/companies/cair-health/jobs/XuQEfj7-founding-customer-success-engineer", "location": "Remote (US)", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$110K - $130K", "equity_range": "0.10% - 0.20%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "Amazon Web Services (AWS)", "Git", "MySQL", "PostgreSQL", "Python", "React", "Docker", "AI Agents" ] }, { "id": 98751, "title": "Founding Forward Deployed Engineer ", "url": "https://www.ycombinator.com/companies/cair-health/jobs/Ye8X3VN-founding-forward-deployed-engineer", "location": "Remote (US)", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$110K - $130K", "equity_range": "0.10% - 0.30%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 98752, "title": "Software Engineer (SWE)", "url": "https://www.ycombinator.com/companies/cair-health/jobs/3oPirfm-software-engineer-swe", "location": "Remote (US)", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$120K - $150K", "equity_range": "0.10% - 0.40%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [], "launches": [] }, { "id": 29125, "name": "truemetrics", "slug": "truemetrics", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a6cd7b0f7663e8989ac828e2eeebe6e1968813d3.png", "website": "https://www.truemetrics.io/", "all_locations": "Berlin, Berlin, Germany", "long_description": "truemetrics helps logistics companies to find their customer's faster. By detecting and mapping entrances, we help GLS, a key logistics company in Europe, save 32.7 seconds on each delivery.\r\n\r\nThe way couriers navigate is broken.\r\n\r\n“You Have Arrived At Your Destination!” — or so Google Maps thinks. In reality, the way couriers navigate is broken: No parking, hard-to-find entrances, and labyrinth-like apartment and office complexes can turn the last meters of delivery into a time-consuming puzzle.\r\n\r\ntruemetrics provides parking positions and entrance locations to enable faster drop-offs. Our data is generated by analyzing sensor data from drivers' smartphones, allowing truemetrics to identify precise parking and entrance locations, thereby simplifying the last meters of delivery.\r\n", "one_liner": "We show couriers where to park and enter a building.", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Supply Chain and Logistics", "launched_at": 1688493255, "tags": [ "Delivery", "Logistics", "AI", "ML" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2023", "status": "Active", "industries": [ "B2B", "Supply Chain and Logistics" ], "regions": [ "Germany", "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/truemetrics", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/truemetrics.json", "year_founded": 2021, "city": "Berlin", "country": "DE", "linkedin_url": "https://www.linkedin.com/company/truemetricsio", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/a6cd7b0f7663e8989ac828e2eeebe6e1968813d3.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 1019217, "full_name": "Ingo Boegemann", "title": "Founder", "founder_bio": "Studied mechanical engineering at the technical university of Hamburg and at UC Berkeley\nWorked in tech consulting for almost 10 years with a focus on supporting classical European tech companies (automotive, aerospace, etc. ) \nFounded my own consulting company which I exited to a competitor in 2020\nStarted working on sensor fusion technologies which are part of truemetrics core tech stack in 2020\nIn my free time I love to the outdoors, especially camping and surfing", "is_active": true, "linkedin_url": "https://linkedin.com/in/ingo-boegemann-a78800bb", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/73cf0926ae6f86b6c2e562ab1072b7e7f023cb2f.jpg" }, { "user_id": 1372422, "full_name": "Jan Bischof", "title": "Founder", "founder_bio": "Jan Bischof is a highly skilled and accomplished software engineer with a strong background in artificial intelligence research. With a passion for developing innovative solutions, Jan has a proven track record of designing and implementing cutting-edge algorithms and software systems. He possesses excellent problem-solving abilities and a deep understanding of machine learning techniques, making him a valuable asset in the field of AI and software development. ", "is_active": true, "linkedin_url": "https://linkedin.com/in/jan-bischof", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7f49658ac12d4a60e2bdb8e5ce62ded4c8e0d66a.jpg" } ], "jobs": [ { "id": 113238, "title": "GTM Founder's Associate", "url": "https://www.ycombinator.com/companies/truemetrics/jobs/THLEzXI-gtm-founder-s-associate", "location": "Berlin, BE, DE / Berlin, Berlin, DE", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "€50K - €60K EUR", "equity_range": "0.10% - 0.50%", "experience": "1+ years", "visa": "US citizenship/visa not required", "skills": [] } ], "news": [], "launches": [ { "id": 74016, "title": "truemetrics - helping logistics companies deliver to their customer’s doorstep", "tagline": "truemetrics provides logistics companies with precise delivery coordinates to guide couriers to their customer's doorstep.", "body": "### **_TL;DR_**\n\ntruemetrics provides logistics companies with precise delivery coordinates to guide couriers to their customer's doorstep. Our tech enables GLS, one of Europe’s biggest logistics companies, to speed up their deliveries by 2-10 minutes.\\\n\\\nHi! We are Ingo, Jan, and David and we believe that **the way how couriers navigate is broken.**\n\n![uploaded image](/media/?type=post&id=74016&key=user_uploads/1295475/c9886fc5-f687-4973-b936-d2a54ddae884)\n\n“You Have Arrived At Your Destination!” — or so Google Maps thinks. In reality, the way couriers navigate is broken: No parking, hard-to-find entrances, and labyrinth-like apartment and office complexes can turn the last meters of delivery into a time-consuming puzzle.\n\n### **Solution**\n\n![uploaded image](/media/?type=post&id=74016&key=user_uploads/1295475/58631705-41f1-4a39-8f74-075582b6bdcb)\n\n\n[truemetrics](https://truemetrics-26059762.hs-sites-eu1.com/en/product-presentation) provides parking positions and entrance locations to enable faster deliveries. Our data is generated by analyzing sensor data from drivers' smartphones, allowing truemetrics to identify precise parking and entrance locations, thereby simplifying the last meters of delivery.\n\n### **Team**\n\nDuring his management of Wolt's operations in three of Germany's four regions, David often faced challenges with inefficiencies in the last 50 meters of delivery. Together with Jan and Ingo, he started truemetrics to overcome these problems. Ingo contributes 10 years of engineering and entrepreneurial experience, along with a successful exit. Jan Bischof holds a PhD in Control Theory and has developed software and AI solutions for nearly a decade.\n\n### **Ask: How you can help**\n\n* [Please connect us with COOs and CTOs from your network!](https://mailto:david@truemetrics.io)\n* We would be happy to hear your feedback! [Discover the biggest address fuck-ups](https://www.demonstrator.truemetrics.cloud/map) and share with us [your favourite navigation mishaps](https://forms.gle/ugDzhR6YTWfMdWaM9).", "url": "https://www.ycombinator.com/launches/JFo-truemetrics-helping-logistics-companies-deliver-to-their-customer-s-doorstep", "votes": 27, "created_at": "2023-08-10T21:49:21.358Z" } ] }, { "id": 29503, "name": "Dragoneye", "slug": "dragoneye", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/354a00433e0332ff17869b4c08d6ee8d10b8a232.png", "website": "https://dragoneye.ai/", "all_locations": "New York City, NY, USA", "long_description": "Dragoneye helps devs build their custom video detection models in less than 5 minutes. These models can then be used to power apps and features that use images and videos. No more arduous process of annotating any training data or doing any machine learning work themselves.\r\n\r\nTry out our demo today at https://playground.dragoneye.ai/ !", "one_liner": "Custom video detection models in less than 5 minutes", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1705986923, "tags": [ "Developer Tools", "Computer Vision", "AI", "ML" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2024", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/dragoneye", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/dragoneye.json", "year_founded": 2023, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/dragoneyeai", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/354a00433e0332ff17869b4c08d6ee8d10b8a232.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": 818332, "full_name": "Alex Liao", "title": "Founder/CEO", "founder_bio": "Building computer vision so every app can see the world. \n\nex-Jane Street, ex-Facebook, UPenn Physics and CS\n\n", "is_active": true, "linkedin_url": "https://linkedin.com/in/alexliaoo", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ed58640fb40fa1b4d8e3bf915680b1f8045c7799.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 95768, "title": "Dragoneye: Production video detection models in <5 minutes", "tagline": "Build zero-shot video models quickly with 0 training data", "body": "![uploaded image](/media/?type=post&id=95768&key=user_uploads/818332/27d779bf-8574-4d51-adbe-d69a806e6d0b)\n\nHey YC! I’m Alex, founder of Dragoneye. \n\n**I want to share with y’all the launch of our new interactive Playground, which allows you to build your own custom video detection models in under 5 minutes.**  \n\n![uploaded image](/media/?type=post&id=95768&key=user_uploads/818332/51fa21e6-bc13-41ad-8f9e-03947fd50b7a)\n\n# **The Problem:**\n\nVideo detection models are incredibly useful. Analyzing security camera footage, ensuring PPE compliance, monitoring production lines. \n\nBut it’s always been hard to build video detection models. Thousands of hours of videos that need to be annotated. You train the model only to find that it doesn’t perform as well as you need it. Really cool ideas that never get to prototype, never mind released in production. Crucial features that take tens of thousands of $$ to trial and months to implement. \n\n# **Our Solution:**\n\nOur new Playground allows you to build and deploy production-ready video detection models in less than 5 minutes, enabled by our powerful zero-shot models.\n\nTo get started:\n\n1. Upload a video\n2. Describe the categories of items you want to detect in your video\n3. The model streams the predictions and you can preview it on your video\n4. Iterate on your categories till you’re set. \n\nOnce you’re happy with your model, you can save it out and it’s live! To make it easier to integrate with your apps, we have libraries for Python and Node.js, with more languages to come.\n\nCheck out the Playground at https://playground.dragoneye.ai/ to get started. You can follow our step by step guide below as well!\n\nhttps://youtu.be/2rhKBO4N7B0\n\nWe can’t wait to see what you build! 🙂 ", "url": "https://www.ycombinator.com/launches/Oue-dragoneye-production-video-detection-models-in-5-minutes", "votes": 11, "created_at": "2025-11-25T16:18:04.833Z" }, { "id": 85450, "title": "Dragoneye - More detailed object detection than Google and Amazon!", "tagline": "We offer vision object detection for 13k+ classes right out of the box.", "body": "Hey YC! I’m Alex, founder of Dragoneye. \n\n**I want to share with y’all the launch of our object detection platform, which can recognize 40x more classes than Amazon Rekognition and 20x more than Google Vision across a wide range of categories.** \n\n![uploaded image](/media/?type=post&id=85450&key=user_uploads/818332/45a1bd0a-16f7-4061-9c0e-ebd5a586450f)\n\n# **The Problem:**\n\nYou’re building a new feature that relies on the ability to recognize things in camera or photos. But all of the off-the-shelf APIs today don’t get the detail you need. You don’t just need to know it’s a dress, but that it’s a checkered short-shift dress! \n\nYou look into how to train your own computer vision model, but you soon realize what a daunting task it is. There are thousands to millions of photos to collect, and it takes weeks of time. What can you do?\n\n# **Our Solution:**\n\nWe want to have the best visual recognition API out there, and enable devs to build powerful vision-driven features in a pinch.\n\n**What we’re focused on:**\n\n* **Latency** - our fastest models can detect objects in 12ms\n* **Detail** - 13,000 different classes over 25 categories now, and we aim to get to 100,000+ by the end of 2024\n* **Implementation ease** - under 10 lines in Python & JS and a simple REST API\n\nSeeing is believing - pun intended - so here is our side-by-side comparison with Google’s Vision API and Amazon’s Rekognition\n\n![](https://bookface.ycombinator.com/media/?type=post&id=85450&key=user_uploads/818332/aa480801-a466-48a9-89a4-1e0bbb8fc9e7)\n\n![](https://bookface.ycombinator.com/media/?type=post&id=85450&key=user_uploads/818332/f6058fa7-c804-4c68-a282-9faab8873005)\n\n![](https://bookface.ycombinator.com/media/?type=post&id=85450&key=user_uploads/818332/4c0c954f-c1c0-4382-8d3d-9998404b461d)\n\n# **Our Ask**\n\n1. Try out our instant demo at . We know we have some bugs to squash, so please let us know what works great and what doesn’t. \n2. [Book a meeting with us](https://calendly.com/dragoneye-cal/intro-call) if you have computer vision/object detection needs - coffee is on us!", "url": "https://www.ycombinator.com/launches/MEE-dragoneye-more-detailed-object-detection-than-google-and-amazon", "votes": 13, "created_at": "2024-11-11T18:54:56.008Z" }, { "id": 79474, "title": "Dragoneye - Computer vision for every developer", "tagline": "We automate the entire process for building computer vision, allowing developers to get custom vision recognition models from just a model spec.", "body": "![uploaded image](/media/?type=post&id=79474&key=user_uploads/818332/3b1dd109-a001-41f9-a1a8-39e46badb5a5)\n\n**TLDR:** [**Dragoneye**](https://dragoneye.ai/) helps developers use computer vision without needing to bring any of their own training data or do any CV/ML work themselves.\n\n## Demo\n\n\n\n## ❓The problem\n\nGetting data from images today is hard. LMMs allow you to get started quickly but have capability limitations and are slow. On the other hand, building your own vision recognition models requires a ton of time and a ton of expertise.\n\nI learned this firsthand when I tried to build my own fashion outfit**\\-**matching app a few years ago. What started as coding a fun consumer app was quickly taken over by the challenges of building custom image models - annotating data, model evaluation, training, deployment, etc. Before long, I realized that I was basically building a computer vision startup - literally!\n\n## ✨ Our solution\n\nDragoneye enables developers to build and use cutting-edge CV models simply by specifying the model spec.\n\n**Specification → Working Model Automagically:** After specifying the model, Dragoneye’s systems scurries away to find the best implementation strategy and then builds it for you!\n\n**Continuous Improvement:** In the background, Dragoneye constantly keeps the models and tech at the cutting edge so you keep getting the best performance without any work on your end at all.\n\n**Grows with your need:** As your needs grow, we grow with you. Simply update your model specification, and Dragoneye will figure out how to make it work best.\n\n## 🙏 Ask\n\nWe just opened up our self-service feature. [Sign up on our site](https://dragoneye.ai/) for access!\n\nAlso, we’d love to hear what you want to build with Dragoneye - please email me at [alex@dragoneye.ai](mailto:alex@dragoneye.ai)!\n\n![uploaded image](/media/?type=post&id=79474&key=user_uploads/818332/dc0fc2db-02eb-44be-99dc-c79bdc7721cd)\n\n", "url": "https://www.ycombinator.com/launches/Kfq-dragoneye-computer-vision-for-every-developer", "votes": 49, "created_at": "2024-03-18T18:59:47.892Z" } ] }, { "id": 29682, "name": "RunLocal AI", "slug": "runlocal-ai", "former_names": [ "Neuralize", "RunLocal" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0c096a99a018da47706cb093bff201df7e6cbd6d.png", "website": "https://runlocal.ai", "all_locations": "London, England, United Kingdom", "long_description": "RunLocal is an environment that specializes AI agents to optimize model for onboard compute platforms like NVIDIA Orin/Thor and Qualcomm → www.runlocal.ai\r\n\r\nRunLocal is built for Physical AI engineering teams across autonomous vehicles, robotics, smart cameras and more.\r\n\r\nIt tracks every experiment and continuously refines experimentation data into an understanding of what drives performance on your target hardware.\r\n\r\nThis environment means that a generic coding agent (e.g. Codex or Claude Code) can experiment and iterate better, faster and cheaper. \r\n\r\nWith RunLocal, you hit performance targets faster and ship more optimized models – without hiring inference optimization specialists. \r\n\r\nWe’re working with leaders in autonomous vehicles and robotics. We're backed by investors like Y Combinator and 468 Capital.", "one_liner": "AI agent that optimizes inference for embedded compute like Jetson", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1722617907, "tags": [ "Developer Tools", "Computer Vision", "AI", "ML" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United Kingdom", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/runlocal-ai", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/runlocal-ai.json", "year_founded": 2024, "city": "London", "country": "GB", "linkedin_url": "https://www.linkedin.com/company/runlocalai", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/0c096a99a018da47706cb093bff201df7e6cbd6d.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": 766869, "full_name": "Ismail Salim", "title": "Founder/CEO", "founder_bio": "Co-Founder & CEO of RunLocal AI\n\nRunLocal is an environment that specializes AI agents to optimize model for onboard compute platforms like NVIDIA Orin/Thor and Qualcomm → www.runlocal.ai\n\nRunLocal is built for Physical AI engineering teams across autonomous vehicles, robotics, smart cameras and more.\n\nPreviously worked on the first edge AI video codec at Deep Render and AR/VR apps at Meta.", "is_active": true, "linkedin_url": "https://linkedin.com/in/ismail-salim-cv", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9c2f30f10d201502b7c1ac8cbb6a5eec3ba09ef6.jpg" }, { "user_id": 1972003, "full_name": "Ivan Chan", "title": "Founder/CTO", "founder_bio": "CTO of Neuralize. Previously a software engineer at Marshall Wace (Europe's largest hedge fund) building an internal AI platform for developers and optimizing low latency streaming systems.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/ivan-chan-959610b7/", "x_url": "https://x.com/ivanchanavinah", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/400731efd4eb96439ed56efd47c95302c3db188a.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 30431, "name": "Feyn", "slug": "feyn", "former_names": [ "Chonkie" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7711f83eeb988737aadd19d8943c753d2e4085f4.png", "website": "https://www.usefeyn.com", "all_locations": "San Francisco, CA, USA", "long_description": "Feyn is an end-to-end service for building custom models from your data. Our models learn how your product actually works, handle the rare cases that are costly to get wrong, and grow sharper the longer they run.\r\n\r\nOur engineers start by reviewing your current setup and agreeing on what quality means for your workflow. Then we train a model on your data. Once it ships, new cases feed back into training so the model keeps improving. \r\n\r\nThe result is a model that runs faster, improves with use, and is yours to own.", "one_liner": "Custom models trained on your data", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1741421145, "tags": [ "Developer Tools", "AI", "ML" ], "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/feyn", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/feyn.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/feynai", "x_url": "https://x.com/FeynAI", "fb_url": null, "cb_url": null, "github_url": "https://github.com/feyninc", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/7711f83eeb988737aadd19d8943c753d2e4085f4.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": 1849274, "full_name": "Shreyash Nigam", "title": "Founder/CEO", "founder_bio": "Building custom models at Feyn. Previously on-device AI, Ads personalization, and VM memory at Google.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/shreyashnigam/", "x_url": "https://x.com/shreyash_nm", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e86317090d196e007433ab568f64e87ab6fd26a9.jpg" }, { "user_id": 2021313, "full_name": "Bhavnick Minhas", "title": "Founder/CTO", "founder_bio": "Building document AI support (and more) @ Chonkie 🦛✨ ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/bhavnicksm/", "x_url": "https://x.com/BhavnickMinhas", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/10236992930ff8cf9988d127b3775ddf30bf997c.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 90330, "title": "Chonkie 🦛 Open Source Data Ingestion for AI", "tagline": "Feed your models better. Chonkie cleans, chunks, and makes your data AI ready", "body": "![uploaded image](/media/?type=post&id=90330&key=user_uploads/1849274/669a375f-f24a-4d4b-9cca-c668ce5d3da4)\n\n## 🚀 TL;DR\n\nModels are now a commodity. The real differentiator for AI applications is _how effectively they use their data_. However, building robust data systems can be both complex and time-consuming.\n\nChonkie fixes this. We make it easy to bring high-quality data ingestion and context-building to your AI projects, ensuring your application is accurate, fast, and cost-efficient.\n\nWe’re open source on GitHub! ([Python](https://github.com/chonkie-inc/chonkie), [TypeScript](https://github.com/chonkie-inc/chonkie-ts)). Leave us a ⭐!\n\n# 🎬 Launch Video\n\nhttps://www.youtube.com/watch?v=eBvCCEgbNDw\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n## 👀 Are you…\n\n👷 **A Builder**\n\n* Install with [pip install chonkie ](https://pypi.org/project/chonkie/)or [npm i chonkie](https://www.npmjs.com/package/chonkie)\n* Use it for free in your projects\n* Join our [Discord](https://discord.gg/6V5pqvqsCY) for direct support from the founders!\n\n🏢 **Business Looking To Go AI Native**\n\n* Want a managed ingestion pipeline? [Contact us](https://cal.com/shreyashn/chonkie-demo)\n* Enjoy a white-glove onboarding experience\n* Use our hosted solution or deploy on-prem!\n\n## ✨ Why Chonkie?\n\nMost AI products today don’t fail because of the model. They fail because they’re fed disorganized, bloated, or incomplete data. The results in wrong answers, slow performance, and expensive bills. There are some existing tools that try to address this, however they are either:\n\n* 🔻 Too slow or bloated\n* 🧱 Too barebones — feels like reinventing the wheel every time\n\nSo we built **Chonkie** — fast, lightweight, and comprehensive.\n\n**Chonkie + Your Amazing AI Application =**\n\n* 🎯 More accurate result\n* ⚡ Faster response times\n* 💸 Lower token usage\n\n## 🔧 What Can Chonkie Do?\n\nChonkie handles the full data ingestion pipeline for AI projects:\n\n* 📄**Bring Any Document**: All formats welcome\n* 🍳**Clean It with Our Chefs**: Normalize and prep your data\n* 🧩**Chunk It**: Break documents into meaningful pieces\n* 🛠️**Refine Your Chunks:** Add context, metadata, or convert to embeddings\n* 🔌**Connect Anywhere**: Integrate with any database and fetch your chunks with ease\n\n## 🎥 See It in Action\n\nSee how Chonkie splits your data, reduces token costs by over **75%**, and generates citations automatically!\n\n![uploaded image](/media/?type=post&id=90330&key=user_uploads/1849274/5ec9dbe7-37c8-428d-b589-8d71c6195191)\n\n## ✅ Try Chonkie Today\n\n* 📬Looking for a managed enterprise solution? [Contact us](https://cal.com/shreyashn/chonkie-demo)\n* 💻 Install our open source offering with  pip install chonkie or npm i chonkie\n* 💬Join our [Discord](https://discord.gg/6V5pqvqsCY) for support and community\n\n\\~Happy Chonking! 🦛✨", "url": "https://www.ycombinator.com/launches/NUw-chonkie-open-source-data-ingestion-for-ai", "votes": 80, "created_at": "2025-05-13T13:34:25.524Z" } ] }, { "id": 30501, "name": "Cartpole", "slug": "cartpole", "former_names": [ "Prophet", "Jazzberry" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/154693ac9eca92a2d8f93ead7153a0858c38d2b3.png", "website": "https://cartpole.com", "all_locations": "San Francisco, CA, USA", "long_description": "We're creating reinforcement learning environments for training frontier models.", "one_liner": "Building reinforcement learning environments", "team_size": 2, "industry": "B2B", "subindustry": "B2B", "launched_at": 1744600545, "tags": [ "Reinforcement Learning", "Data Labeling", "AI", "ML" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 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/cartpole", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/cartpole.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/cartpole", "x_url": "https://x.com/cartpoleai", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/154693ac9eca92a2d8f93ead7153a0858c38d2b3.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": 2557020, "full_name": "Mateo Perez", "title": "Founder/CEO", "founder_bio": "Building Cartpole. PhD @ CU Boulder.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/mateo-perez/", "x_url": "https://x.com/m_perez_", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/bc4e196cc3b6bc16eb7775444008cd50ad1ddd64.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 90047, "title": "Jazzberry - AI bug finding with real code execution", "tagline": "We're creating the best AI agent for bug finding", "body": "Hello everyone, \n\nWe’re Mateo and Marco, and we're excited to introduce Jazzberry, an AI agent for finding bugs. Jazzberry is powered by running your code in a secure sandbox and integrates directly into your pull request workflow on GitHub.\n\n**Try it here →** \n\n\n\n**Why we built Jazzberry**\n\nAI code generation has dramatically increased the amount of code that is written without the tools for bug finding keeping up, leading to a world with more buggy code that is hindering developers. To improve bug finding, we’ve created an AI agent with the ability to run snippets of your code. We're not just flagging potential issues based on code patterns; we're observing the real behavior of your software. Here’s how it works.\n\n1. When you create a pull request, Jazzberry gets to work.\n2. Your repository is cloned into a microVM.\n3. Our agent examines the contents of the pull request to guide its search. It can write and execute code in the microVM as it looks for bugs.\n4. Jazzberry returns a clear markdown table directly as a comment.\n\n![uploaded image](/media/?type=post&id=90047&key=user_uploads/2557020/31d75b00-abc3-4a60-8ef5-b3a685edfcd5)\n\n**Real Bugs, Real Impact**\n\nWe've already seen Jazzberry make a tangible difference for our early users. So far, Jazzberry has…\n\n* successfully identified a SQL injection vulnerability\n* discovered a critical logical error in API key validation\n* [found an incorrect page navigation](https://blog.openint.dev/how-we-scale-prs/) (see below, we are formerly known as Prophet)\n\n![uploaded image](/media/?type=post&id=90047&key=user_uploads/2557020/864328cf-c4b9-4b9a-b267-e9059a158f32)\n\n**Who we are**\n\nWe have been friends for over a decade, and are coming together to create Jazzberry. Marco completed his MS at the University of Stellenbosch specializing in LLMs for automated test suite generation. Mateo completed his PhD at the University of Colorado Boulder with a research focus on reinforcement learning and formal methods.\n\n**Our Ask**\n\n* **Try it out** – Jazzberry is available now with a free trial at .\n* **Contact us** – We’d love to hear your feedback and what bugs Jazzberry helps you catch. Reach us at [founders@jazzberry.ai](mailto:founders@jazzberry.ai).", "url": "https://www.ycombinator.com/launches/NQN-jazzberry-ai-bug-finding-with-real-code-execution", "votes": 42, "created_at": "2025-05-05T22:37:45.137Z" } ] }, { "id": 30559, "name": "Godela", "slug": "godela", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fe1589548b774d33ca4f20c5020467a9627f9c13.png", "website": "http://godela.ai", "all_locations": "San Francisco, CA, USA", "long_description": "What if every experiment you wanted to run could be modeled using AI? \r\nGodela is an AI-powered physics engine that gives engineers faster, cheaper replacement to simulations and physical prototypes.\r\nNo set up, no wait. Just ask—and get simulation quality result.\r\n", "one_liner": "AI Physics Engine to replace simulations and prototypes", "team_size": 10, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1747413596, "tags": [ "Hard Tech", "Hardware", "Aerospace", "AI", "ML" ], "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": [ { "question": "What is the core problem you are solving? Why is this a big problem? What made you decide to work on it?", "answer": "Engineers and scientists rely on simulations and physical testing to understand how the world works. Today, those tools are slow, expensive, and fragmented. \r\n\r\nRunning a single simulation can take hours to days. Building physical prototypes takes weeks to months. Every domain—from fluid dynamics to thermal modeling—requires different solvers, different experts, and perfect setups. This creates massive bottlenecks in innovation. We’re building AI that turns engineering questions into instant, physics-based models. No solvers. No bottlenecks." }, { "question": "What is your long-term vision? If you truly succeed, what will be different about the world?", "answer": "The next wave of breakthroughs will come from AI that deeply understands physics, not just text.\r\n\r\nWe’re building Godela to give humanity the power to instantly model, explore, and invent across the physical world. Imagine being able to instantly test any idea, uncover hidden relationships, and accelerate discovery at the speed of thought." } ], "url": "https://www.ycombinator.com/companies/godela", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/godela.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/godela-ai", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/fe1589548b774d33ca4f20c5020467a9627f9c13.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": 1725296, "full_name": "Cinnamon Sipper", "title": "Founder/CEO", "founder_bio": "Built laptops and iPads at Apple. Built AI products for Google. Now building Godela—AI that models the physical world, for engineers and scientists everywhere.\n", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/cinnamonsipper", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/570e39102fe604a6a07c24ff01576933926b0869.jpg" }, { "user_id": 2549090, "full_name": "Abhijit Pranav Pamarty", "title": "Founder/CTO", "founder_bio": "Researched physics-driven optimization at Harvard and generative models for fluid mechanics at Stanford. Built surrogate models for semiconductor manufacturing at Intel. Now building Godela - giving engineers and scientists their own AI model for physics.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/abhijit-pranav-pamarty-6b2453152/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5d4db953f29142244b996d150241a0b4753b00b9.jpg" } ], "jobs": [ { "id": 82147, "title": "Founding Engineer (ML Systems) – Godela", "url": "https://www.ycombinator.com/companies/godela/jobs/6MlUqiS-founding-engineer-ml-systems-godela", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$120K - $180K", "equity_range": "0.10% - 1.50%", "experience": "3+ years", "visa": "Will sponsor", "skills": [ "Amazon Web Services (AWS)", "ML", "Python", "CUDA" ] }, { "id": 82354, "title": "Founding Simulation Engineer – Godela", "url": "https://www.ycombinator.com/companies/godela/jobs/vWajfU5-founding-simulation-engineer-godela", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Mechanical", "salary_range": "$120K - $180K", "equity_range": "0.08% - 1.50%", "experience": "3+ years", "visa": "Will sponsor", "skills": [] }, { "id": 82749, "title": "Founding Engineer (SWE) – Godela", "url": "https://www.ycombinator.com/companies/godela/jobs/rKMZtYt-founding-engineer-swe-godela", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$120K - $180K", "equity_range": "0.10% - 1.50%", "experience": "3+ years", "visa": "Will sponsor", "skills": [ "ML" ] } ], "news": [ { "title": "Three Big Projects That Win The AI Prize In Silicon Valley", "url": "https://www.forbes.com/sites/johnwerner/2025/09/19/three-big-projects-that-win-the-ai-prize-in-silicon-valley/", "date": "Sep 25, 2025" } ], "launches": [ { "id": 90799, "title": "Godela: AI Powered Physics Engine for Engineers", "tagline": "Bringing AI powered intelligence to the physical world", "body": "**AI powered physics is the next frontier**\n\n**TL;DR:** Godela is an AI-powered physics engine that gives engineers faster, cheaper, simulation-quality answers to even the most complicated engineering problems.\n\nHi YC—we’re @Cinnamon Sipper and @Abhijit Pamarty, former engineers at Apple, Google, and Intel, now turning our Stanford research into the future of engineering.\n\nhttps://youtu.be/I5E1Zi9cpM4\n\n**The Problem: Engineering Discovery is Too Slow.** Every groundbreaking innovation—from fusion reactors to life-saving drugs—hinges on understanding how the physical world works. Yet, engineers spend agonizing weeks, even months, wrestling with complex simulations, preprocessing data, and manually tuning parameters just to answer _one_ question. Many critical questions go unasked because the effort is too great.\n\n![uploaded image](/media/?type=post&id=90799&key=user_uploads/1725296/03894dba-703c-4a25-a00b-b1ba24b27392)\n\n**Our Vision: Ask About the Physical World as Easily as You Use Language.** Imagine a world where understanding the implications of a new design, material, or physical scenario is as instant as a search query. That’s the future Godela is building.\n\n![uploaded image](/media/?type=post&id=90799&key=user_uploads/1725296/b7ae00e6-d8ea-4354-a110-233a65568e0f)\n\n**Introducing Godela: Your AI Copilot for Engineering.** Godela is an AI-native platform that transforms your engineering questions into computable, physics-informed models—instantly.\n\n* **Ask Anything:** Pose complex questions in natural language or with your existing data.\n* **Upload Your World:** Integrate CAD files, experimental results, or existing simulation data.\n* **Get Instant Insights:** Receive actionable, simulation-quality models you can explore, refine, and iterate on immediately.\n\nInstead of replacing simulations, Godela becomes their intelligent, adaptive home—blending diverse data sources with AI to provide insights that were previously out of reach or would take weeks to uncover.\n\n**Why We’re Building This:** As engineers who’ve designed everything from chips and laptops to particle accelerators, we’ve lived the frustration of slow design-simulation loops. Inspired by how AI revolutionized access to information (like ChatGPT for language), we believe it’s time for the same leap in understanding the physical world.\n\n![uploaded image](/media/?type=post&id=90799&key=user_uploads/1725296/308937e8-b076-46b9-a432-39585f6ea464)\n\n**Partner with Us:** We're looking for forward-thinking engineering teams eager to break free from traditional simulation constraints. If you know engineers battling simulation bottlenecks, send them our way!\n\nIf you want to accelerate your design cycles and unlock new levels of understanding:\n\n🌐 Visit: [www.godela.ai](http://www.godela.ai) \n\n✉️ Email us: [founders@godela.ai](mailto:founders@godela.ai) \n\n🗣️ Talk to us: https://calendly.com/cinnamon-sipper", "url": "https://www.ycombinator.com/launches/NcV-godela-ai-powered-physics-engine-for-engineers", "votes": 129, "created_at": "2025-05-28T13:50:39.357Z" } ] }, { "id": 31019, "name": "Ndea", "slug": "ndea-com", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/51a1310dd1344aa031a62430dad084db50b7229d.png", "website": "https://ndea.com", "all_locations": "Remote", "long_description": "Ndea is building frontier AI systems that blend intuitive pattern recognition and formal reasoning into a unified architecture.\r\n\r\n# AI for Scientific Advancement\r\n\r\nUnlike all life before us, humanity's ascent is a story of ingenuity, not just biological evolution. Our progress has been driven by the curiosity to acquire knowledge, the ability to pass it on, and an intrinsic drive to innovate. We build technology which gives us leverage beyond our biology.\r\n\r\nWe stand at the top of a knowledge and technology colossus that we collectively created over the past ten thousand generations. Scientific progress has helped us overcome burdens that long defined human life — famines, plagues, and widespread illiteracy. Science will continue to redefine the boundaries of the human condition.\r\n\r\nToday, the acceleration of scientific progress hinges on one factor: AI capable of independent invention and discovery. This capacity is the gateway to advancements beyond our wildest imagination.\r\n\r\n# A New Research Lab\r\n\r\nWe're starting Ndea — an AI research and science lab. The name - like 'idea' with an 'n' - is inspired by the Greek concepts ennoia (intuitive understanding) and dianoia (logical reasoning), capturing our first goal to merge deep learning with program synthesis.\r\n\r\nNdea is entirely focused on developing and operationalizing AGI to realize unprecedented scientific progress in our lifetime for the benefit of all current and future generations.\r\n\r\nBuilding AGI alone is a monumental undertaking, but our mission is even bigger. We're creating a factory for rapid scientific advancement — a factory capable of inventing and commercializing N ideas.\r\n\r\nFrom our vantage point today, we see many 'known' frontiers like self-driving vehicles, drug discovery, sustainable energy, robotics, and space exploration. While AGI will benefit all of these, the most exciting adventure lies in the 'unknown'. AGI promises discoveries and progress we cannot imagine today.", "one_liner": "Building AGI that can innovate.", "team_size": 15, "industry": "Industrials", "subindustry": "Industrials", "launched_at": 1772669917, "tags": [ "Deep Learning", "Hard Tech", "Remote Work", "AI", "ML" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2026", "status": "Active", "industries": [ "Industrials" ], "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/ndea-com", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/ndea-com.json", "year_founded": 2024, "city": null, "country": null, "linkedin_url": "https://www.linkedin.com/company/ndea/", "x_url": "https://x.com/ndea", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/51a1310dd1344aa031a62430dad084db50b7229d.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": 2858111, "full_name": "Francois Chollet", "title": "Founder", "founder_bio": "https://fchollet.com/", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/fchollet/", "x_url": "https://x.com/fchollet", "avatar_thumb_url": "/avatars/thumb/missing.png" }, { "user_id": 898, "full_name": "Mike Knoop", "title": "Founder", "founder_bio": "https://mikeknoop.com", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/mikeknoop", "x_url": "https://twitter.com/mikeknoop", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/45810451d10680414c72b6b9db3769a697c4bc6d.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "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": 32167, "name": "Orchestra", "slug": "orchestra", "former_names": [ "Understudy Labs" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/900e0fabf138d248123ff3ddf28833736fbfb71d.png", "website": "https://orchestra.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Orchestra is an inference cloud. We capture your AI work traces, train smaller models, and automatically deploy them (only when they outperform the expensive model you are currently paying for).\r\n\r\nInstead of renting the same frontier model forever, your AI infrastructure gets faster, smarter, and cheaper every time it runs.\r\n\r\nSuppose your product uses Claude for a repetitive legal workflow.\r\n\r\nOrchestra observes successful production runs, learns the specific tools and judgment required for that workflow, and trains a specialized open-weight model.\r\n\r\nOnce that model matches or beats Claude on a held-out evaluation, Orchestra starts routing production traffic to it.\r\n\r\nAs more work is completed, the model keeps improving.\r\n\r\nWe started Orchestra because we believe every company using AI should be accumulating intelligence, not accumulating API bills.", "one_liner": "Self-optimizing neocloud that cuts LLM costs by 100x", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1783740567, "tags": [ "Open Source", "AI", "ML" ], "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": true, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/orchestra", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/orchestra.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/understudy-labs", "x_url": "https://x.com/understudylabs", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/900e0fabf138d248123ff3ddf28833736fbfb71d.png", "app_video_url": "https://bookface-images.s3.us-west-2.amazonaws.com/bf-public_profile/32225/app_video.mp4?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAQC4NIECAOYE2QNZ5%2F20261020%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20261020T022739Z&X-Amz-Expires=60&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEHEaCXVzLXdlc3QtMiJIMEYCIQDZr7mht6VpZroejzIM4ovdqqWjmh9u8AZ4wJ%2BcxZeHaQIhAN0TyP1C5dfPpTpdf3vcwz%2B044IBUbnJ55rbsOHYRWQWKuUDCDoQABoMMDA2MjAxODExMDcyIgxycpAO09Mq3A1cvyQqwgN39qg2Ox70YWArW8Z19bx1LbIV2O3f8r7xSc%2BDpl3XtmT02s9DHm%2FdyEMimOoBk5McFrR%2FThfgO9h1Zcmt1NqN1y6d1lWIsDAdluAWIqXM089dX1KVjFmsSwg8hWS2%2F4ysZFTLuD5VBUHeANJPyfmRKN9Kb4JepbPSE01eipdz4aqPxRqz%2FVUJEYLUTh5YJM6jJKNzl5l2mnWSSFiFdUfT5OS16LHDCYH4PGt9WRY2iseRxMu7FZcICWM0P8aN14WLxKsu1H0yVxk8LS%2BNbXezGhQnkMsa3bf7aMNU7x4TSs7KyM01QgiCZxC01YV43U4O8vFENPThr%2FHtKaAvtZ0%2BXSTwUE691O8mG15thNVkorInjIhilxdazy%2BzEYcGsAMNZtfx0Bd5Xn43Xf7b%2Fie4vv0d0RCHqbCGLmxRHj5VG3Pdta5Kju3%2Fpb8n%2FKmRjY%2FtuIfi9oTYAjc4PVyikHTm8UXURiHmaM0tqXZjxyh0iIponEKehSmtjmjudiXLWICFBoPhEXeaUeyK2AT6btvH4fclsQa0qRmkxdgguiWvrYxLKhNNfPLTc5QA0jlPSRoDJ%2F%2BxNHLFrGusOX7IwU6hfRMw6P3a1gY6pAETos2BWzWJY973oh8s1gy0zFzSYQP7N%2B39nIjIA7I0ymOVnRNJktoZRF6GV9DH3ymBPT2fnMgKvEaFAqVR%2F0WVwXz3ixgSwFGrvlwPr39cuFnKBEcdnivQJOXkexjqUxi9alVn76GV8ONTXD1ZupAQeLYI09gLaaAmJlyJPRAUCybD64XlECdPqS2TV2e%2FZlA5duJD1GekpDGthoc0y8PIc1ahwA%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=993a52d820dba9b6623af23273922c1e1980795db53cc2f2ee2ad22f445bb5e7", "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Tyler Bosmeny", "url": "https://www.ycombinator.com/people/tyler-bosmeny" }, "founders": [ { "user_id": 3647059, "full_name": "Luis Manrique", "title": "Founder/CEO", "founder_bio": "Founder at Orchestra (YC S26). Previously founding Member of Technical Staff (and founding sales guy) at Gumloop, closing ~$2M in first year. Led Ads ML and also consumer AI as first PM at Instacart's Carrot AI. Prior co-founder/CEO at Ones and Zeros (text-to-SQL using transformers). Early at Wildfire (acquired by Google), then 5 years across Google's ads ML and programmatic platforms. SVP Solutions at VideoAmp building TV measurement infrastructure.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/luismanrique", "x_url": "https://x.com/lluismanrique", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/704197b652568953035fd4d4a70a73910a60a37c.jpg" }, { "user_id": 73303, "full_name": "Aamir Poonawalla", "title": "Founder/CTO", "founder_bio": "Founder at Orchestra (YC S26). 10 years at Instacart. Built the ads serving and ML infrastructure, auction platform, and experimentation framework. 2nd time YC Founder. MS in Computer Science from Georgia Tech.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/aamir-p-a3575318/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4c9a96d07312de424f0f4d4023f16b6a3238ce54.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 114099, "title": "Orchestra: Self-optimizing inference cloud to cut your AI costs by 100x", "tagline": "Your AI inference gets smarter and cheaper the more you use it. ", "body": "We’re Aamir & Luis and we’re excited to launch our company’s new brand ahead of demo day this week: Orchestra ([orchestra.ai](http://orchestra.ai)) \\\n\\\nCompanies move their frontier inference spend to Orchestra, with a single URL swap. We relay their traffic through to the frontier labs, while building evals in the background automatically. These evals allows us to post-train specialist models that replace the frontier, at a fraction of the cost. When our model beats the frontier at your product’s work, we promote it and your bills go down. Then we repeat the loop continuously, forever; your AI inference gets smarter and cheaper the more you use it. \\\n\\\nWe’re going straight after the $104B inference market; Anthropic grew 14x YoY but we’ve seen time and time again that start-ups and enterprises are willing to move spend if you can prove the performance. That it. We don’t have FDEs. We don’t pre-train models. Most of the application layer lives in a CLI that coding agents use. \\\n\\\nWe just do one thing really well: building and routing your work to the most efficient model. We found the easiest way to build a fast growing business is to _sell_ your product to people who have pain and who are already spending money with someone else. The more we focused on the fastest growing segments of our business, the faster our product got better at solving a simple, but incredibly painful problem: “You don’t need a PhD to work in the mailroom”. \n\n**It’s the “Age of the Unc”** \n\nI shared my experiences doing YC as a 38-year old () but for any founders out there thinking about coming back to YC: do it. We worked 60-hour weeks, not 100-hour weeks. We had a network of angels, customers and advisors. We ran the marathon, instead of sprinting it. At 38, I’m old enough to understand that pedagogy is the point of YC. Learning how to work on your company is the point. You’ll get **so much more** out of YC when you’re doing it again with the hindsight of all your past successes and failures. Having done it before is a huge advantage, but having a long career in which I’ve encountered a lot of situations and had to make a lot of decisions and a few mistakes, and see others do the same, allows me to understand how YC’s advice impacts the real world. You will manage your agents better. You will close customers faster. You’ll build a better company. \n\n**Why Orchestra?** \n\nBranding is everything, especially outside of silicon valley. We launched as the ‘alternative’, the ‘backup’; but as time went on, we realized how open companies are to moving **all** their spend to a single place and making it work efficiently. Inference is the fastest growing market in the history of capitalism and we needed a brand that reflected our ambitions. Orchestra is going to win a huge chunk of that market; not the back-up, but the entire show. \n\nSay hello to Orchestra. And if your bills are too damn high, send us a note. We’d love to help.\n\n![uploaded image](/media/?type=post&id=114099&key=user_uploads/3647059/d32c3f74-5cd4-4026-ad40-1c7bd729a08a)\n\n", "url": "https://www.ycombinator.com/launches/TgJ-orchestra-self-optimizing-inference-cloud-to-cut-your-ai-costs-by-100x", "votes": 5, "created_at": "2026-09-07T14:00:00.839Z" }, { "id": 109219, "title": "Understudy: The self-optimizing inference cloud", "tagline": "We distill your production usage into cheaper, specialized models your company owns", "body": "Hey YC! We’re Luis and Aamir, founders of Understudy.\n\n### TL;DR\n\nWe help you cut your company’s Anthropic bill by 80% with no loss of performance.\n\nUnderstudy is an inference cloud. We capture your employee’s AI work traces, train smaller models, and automatically deploy them (only when they outperform the expensive model you are currently paying for).\n\nInstead of renting the same frontier model forever, your AI infrastructure gets cheaper and better every time it runs.\n\nSee more: \n\n### The problem\n\nLast week, we met with a company spending $40M/year on Anthropic. And it’s only going in one direction.\n\nTo them, it feels totally out of control.\n\nThey’re not alone - every company we meet is spending record amounts on models from frontier labs.\n\nBut almost none of that spending compounds.\n\nI.e. You send a prompt, pay for the answer, and throw away the experience. Six months later, you are still renting the same general-purpose model at roughly the same price.\n\nMeanwhile, training custom models requires an entire ML team to collect and clean traces, build evals, choose training data, fine-tune and reinforce models, test serving configurations, compare cost, latency, and quality, safely deploy or roll back the winner.\n\nFor most companies, it’s just too much to bother with.\n\n### What Understudy does\n\nPoint Understudy at an AI workload.\n\nWe capture how your existing agent performs, turn those traces into evals, and start training smaller models that can do the same job better.\n\nUnderstudy handles the entire loop:\n\n**Observe → evaluate → train → test → deploy → repeat**\n\nA new model is promoted only when it beats the incumbent on the metrics you care about, such as:\n\n* task success\n* inference cost\n* latency\n* privacy\n* deployment size\n\nYour customized models are owned by you, and can run in our cloud, your cloud, or on-premise.\n\n### An example\n\nSuppose your product uses Claude for a repetitive legal workflow.\n\nUnderstudy observes successful production runs, learns the specific tools and judgment required for that workflow, and trains a specialized open-weight model.\n\nOnce that model matches or beats Claude on a held-out evaluation, Understudy starts routing production traffic to it.\n\nAs more work is completed, the model keeps improving.\n\n### Why us\n\nAamir and I met building Instacart’s optimization and experimentation systems, growing multiple business lines to more than $1B in annual revenue.\n\nWe started Understudy because we believe every company using AI should be accumulating intelligence, not accumulating API bills.\n\n### Our ask\n\nSpending too much on repetitive model workloads? Ready to own your own models? We want to meet you - come to [understudylabs.com](http://understudylabs.com) today.", "url": "https://www.ycombinator.com/launches/SPb-understudy-the-self-optimizing-inference-cloud", "votes": 16, "created_at": "2026-08-05T02:21:26.322Z" } ] }, { "id": 37566, "name": "The Agentic Data Co.", "slug": "the-agentic-data-co", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/72ebbcacfd48c52bf6fc298c17ddf035a00bbc08.png", "website": "https://theagenticdatacompany.com", "all_locations": "San Francisco, CA, USA", "long_description": "We design and collect audio datasets for training speech models.", "one_liner": "Training Data For Speech Models.", "team_size": 2, "industry": "B2B", "subindustry": "B2B", "launched_at": 1788964517, "tags": [ "AI", "Conversational AI", "ML" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2026", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/the-agentic-data-co", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/the-agentic-data-co.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/theagenticdataco/", "x_url": "https://x.com/agenticdataco", "fb_url": null, "cb_url": null, "github_url": "https://github.com/The-Agentic-Data-Co", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/72ebbcacfd48c52bf6fc298c17ddf035a00bbc08.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Christopher Golda", "url": "https://www.ycombinator.com/people/christopher-golda" }, "founders": [ { "user_id": 736135, "full_name": "Christian Vestergaard", "title": "Co-Founder", "founder_bio": "Co-founder of The Agentic Data Company.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/chrisvestergaard/", "x_url": "https://x.com/CVestergaard_", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9b7c98c539ead059320476be40f4613119e293e8.jpg" }, { "user_id": 3402778, "full_name": "Matias Voldby Drejer", "title": "Co-founder", "founder_bio": "Co-Founder at The Agentic Data Company. Prev. Head of Growth & Ops at Female Invest (S21).", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/matiasdrejer/", "x_url": "https://x.com/matiasdrejer", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ae175fc5bc0b93d49ea06bf770fb6a53f4fbc2eb.jpg" } ], "jobs": [], "news": [], "launches": [] } ]