[ { "id": 26, "name": "Marft", "slug": "marft", "former_names": [], "small_logo_thumb_url": "/company/thumb/missing.png", "website": "http://marft.com", "all_locations": "", "long_description": "Marft creates embeddable machine learning models for application developers. Users submit data by web/API, and receive optimized models implemented in a language of their choice.", "one_liner": "Marft creates embeddable machine learning models for application…", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1322045736, "tags": [ "Developer Tools", "Machine Learning" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2012", "status": "Inactive", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "Unspecified" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/marft", "api": "https://yc-oss.github.io/api/batches/winter-2012/marft.json" }, { "id": 90, "name": "AgileMD", "slug": "agilemd", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/809b12f827ff69a7f32abee89d407ac3eac9359d.png", "website": "https://agilemd.com", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "At AgileMD, we are building the most advanced real-time predictive analytics and clinical algorithms platform for hospitals. Our cloud-based engine helps thousands of doctors and nurses around the country make medical decisions, so that every patient receives the highest quality and value of care based on the latest medical knowledge and data.", "one_liner": "Predictive analytics and clinical pathways for hospitals ", "team_size": 19, "industry": "Healthcare", "subindustry": "Healthcare -> Healthcare IT", "launched_at": 1326789206, "tags": [ "Machine Learning", "Healthcare" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2011", "status": "Active", "industries": [ "Healthcare", "Healthcare IT" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/agilemd", "api": "https://yc-oss.github.io/api/batches/summer-2011/agilemd.json" }, { "id": 102, "name": "Sift", "slug": "sift", "former_names": [ "Sift Science", "Sift", "Sift Science" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4eb5f9ca677956a27183ce3ae798b02616a1e3e2.png", "website": "https://sift.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Sift is the leader in Digital Trust & Safety, empowering digital disruptors to Fortune 500 companies to unlock new revenue without risk. Sift dynamically prevents fraud and abuse through industry-leading technology and expertise, an unrivaled global data network of 70 billion events per month, and a commitment to long-term customer partnerships. Global brands such as DoorDash, Twitter, and Wayfair rely on Sift to gain a competitive advantage in their markets. \r\n", "one_liner": "The Leader in Digital Trust & Safety", "team_size": null, "industry": "B2B", "subindustry": "B2B -> Security", "launched_at": 1326789337, "tags": [ "Fintech", "Machine Learning", "SaaS", "B2B" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2011", "status": "Active", "industries": [ "B2B", "Security" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/sift", "api": "https://yc-oss.github.io/api/batches/summer-2011/sift.json" }, { "id": 245, "name": "Directed Edge", "slug": "directed-edge", "former_names": [], "small_logo_thumb_url": "/company/thumb/missing.png", "website": "http://directededge.com", "all_locations": "San Francisco, CA, USA", "long_description": "Directed Edge delivers Amazon-like \"People who bought this also bought...\" and \"We think you'd also like\"-style recommendations to other sites, using existing data being collected such as purchase or click histories. Recommendations are served in real-time via a REST API, with language bindings in several programming languages to make integration easy.", "one_liner": "Product recommendations.", "team_size": 2, "industry": "Consumer", "subindustry": "Consumer -> Home and Personal", "launched_at": 1326790627, "tags": [ "Artificial Intelligence", "Machine Learning", "Recommendation System" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2009", "status": "Active", "industries": [ "Consumer", "Home and Personal" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/directed-edge", "api": "https://yc-oss.github.io/api/batches/summer-2009/directed-edge.json" }, { "id": 590, "name": "Cruise", "slug": "cruise", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b9aae9ad065dcf8b7a07d47b45a0667c6953810b.png", "website": "http://getcruise.com", "all_locations": "San Francisco, CA, USA", "long_description": "Cruise is building the world’s most advanced, all-electric, self-driving car technology to safely connect people with the places, things, and experiences they care about. Self-driving cars will help save lives, reimagine cities, redefine time in transit, and restore freedom of movement for individuals who live in dense urban settings. Acquired by GM in 2016.", "one_liner": "Self-driving cars.", "team_size": 3000, "industry": "Industrials", "subindustry": "Industrials -> Automotive", "launched_at": 1384978717, "tags": [ "Autonomous Delivery", "Machine Learning", "Climate", "AI", "Self-Driving Vehicles" ], "tags_highlighted": [], "top_company": true, "isHiring": false, "nonprofit": false, "batch": "Winter 2014", "status": "Acquired", "industries": [ "Industrials", "Automotive" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/cruise", "api": "https://yc-oss.github.io/api/batches/winter-2014/cruise.json" }, { "id": 611, "name": "Theorem", "slug": "theorem", "former_names": [ "Algorithmic Lending", "Theorem LP" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a07fab3a68d06eb74f5105810d2d86f8ba404c4d.png", "website": "http://theoremlp.com", "all_locations": "San Francisco, CA, USA", "long_description": "Theorem conducts independent underwriting of consumer loans originated by banks, credit cards companies and other lenders. We utilize this information to manage institutional capital and securitize loans", "one_liner": "The mission of Theorem is to make credit safe and available. We use…", "team_size": 34, "industry": "Fintech", "subindustry": "Fintech -> Asset Management", "launched_at": 1384978922, "tags": [ "Fintech", "Machine Learning" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2014", "status": "Acquired", "industries": [ "Fintech", "Asset Management" ], "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": false, "url": "https://www.ycombinator.com/companies/theorem", "api": "https://yc-oss.github.io/api/batches/winter-2014/theorem.json" }, { "id": 612, "name": "Liftigniter", "slug": "liftigniter", "former_names": [ "Petametrics" ], "small_logo_thumb_url": "/company/thumb/missing.png", "website": "http://liftigniter.com/", "all_locations": "San Francisco, CA, USA", "long_description": "LiftIgniter uses cutting edge data science to help publishers and retailers optimize their websites and mobile apps in real-time. Machine learning personalization puts the perfect piece of \"content\"​ (video, article, item to buy) in front the user at the exact moment when they are most likely to engage or convert - no tags or manual work required. \n\nThe machine learns and updates itself so that's it's always perfectly in sync with your users and your \"content.\"​ We average 50% improvements in CTR, engagement and conversation - with only a day's work on your part. Imagine creating a truly dynamic, real-time digital property that enables the perfect experience for that user impression at that moment in time. That is LiftIgniter! \n\nOur team of PhDs has direct experience building state-of-the-art personalization systems at the petabyte scale for some of the largest companies on the planet. Unless you plan on hiring your own team with deep experience (not likely since very few people with that experience exist), you should contact us to talk about how we can supercharge your digital experiences.", "one_liner": "Machine Learning personalization for dynamic digital properties -…", "team_size": 11, "industry": "B2B", "subindustry": "B2B -> Marketing", "launched_at": 1384978926, "tags": [ "Machine Learning", "Personalization" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2014", "status": "Acquired", "industries": [ "B2B", "Marketing" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/liftigniter", "api": "https://yc-oss.github.io/api/batches/winter-2014/liftigniter.json" }, { "id": 688, "name": "MTailor", "slug": "mtailor", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ed1836376602c7f94a02b0049a5258986172b1ac.png", "website": "http://mtailor.com", "all_locations": "San Francisco, CA, USA", "long_description": "MTailor is an ipad or iphone service for men to capture their shirt size dimensions and have tailor made shirts made and delivered.", "one_liner": "Get measured by your phone in under 30 seconds for perfect fitting…", "team_size": 11, "industry": "Consumer", "subindustry": "Consumer -> Apparel and Cosmetics", "launched_at": 1398907868, "tags": [ "Machine Learning", "E-commerce", "Apparel" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2014", "status": "Active", "industries": [ "Consumer", "Apparel and Cosmetics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/mtailor", "api": "https://yc-oss.github.io/api/batches/summer-2014/mtailor.json" }, { "id": 695, "name": "PicnicAI", "slug": "picnicai", "former_names": [ "PicnicHealth" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/dbf45bc323953c8df6c8183d0e549e723e5e1a71.png", "website": "https://picnic.ai", "all_locations": "San Francisco, CA, USA", "long_description": "PicnicAI deploys AI into the real-world complexity of care delivery and clinical research. PicnicHealth helps patients navigate fragmented care with AI-powered tools backed by a clinical team, giving them a unified view of their health across all their doctors. PicnicResearch makes clinical research faster, cheaper, and more reliable, using AI agents and direct patient relationships to change the economics of drug development so that more treatments reach the patients who need them.", "one_liner": "Intelligence to accelerate human health.", "team_size": 100, "industry": "Healthcare", "subindustry": "Healthcare", "launched_at": 1398907926, "tags": [ "Machine Learning", "Health Tech", "Digital Health", "Healthcare", "NLP" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2014", "status": "Active", "industries": [ "Healthcare" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/picnicai", "api": "https://yc-oss.github.io/api/batches/summer-2014/picnicai.json" }, { "id": 707, "name": "SalesSift", "slug": "salessift", "former_names": [ "TaskPipes", "LeadFinch" ], "small_logo_thumb_url": "/company/thumb/missing.png", "website": "https://salessift.com", "all_locations": "London, England, United Kingdom", "long_description": "SalesSift (formerly known as LeadFinch) is an intelligent lead-sourcing platform.\n\nOur machine learning algorithm recommends the best new companies to target based upon the profile of your existing customers.", "one_liner": "Intelligent Lead Sourcing", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Sales", "launched_at": 1398908010, "tags": [ "Artificial Intelligence", "Machine Learning", "Sales", "Marketing", "CRM" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2014", "status": "Inactive", "industries": [ "B2B", "Sales" ], "regions": [ "United Kingdom", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/salessift", "api": "https://yc-oss.github.io/api/batches/summer-2014/salessift.json" }, { "id": 717, "name": "Tule", "slug": "tule", "former_names": [ "Tule Technologies" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/62c49ceac2dca396a7612ae66ae36ebcc4791a10.png", "website": "http://tuletechnologies.com", "all_locations": "Davis, CA, USA", "long_description": "Tule helps farmers make irrigation decisions.\r\n\r\nUsing UC Davis research-based technology, our hardware sensor provides growers with field-scale crop water use measurements (i.e., actual evapotranspiration), crop water stress measurements, applied irrigation measurements, and irrigation recommendations.\r\n\r\nUsing the latest AI technology and our unprecedented crop water stress dataset, our latest product, Tule Vision, provides growers with the water stress of their plants just by taking a picture with their mobile phone.", "one_liner": "Help farmers make irrigation decisions with sensors / computer vision ", "team_size": 8, "industry": "Industrials", "subindustry": "Industrials -> Agriculture", "launched_at": 1398908099, "tags": [ "Cellular Agriculture", "Machine Learning", "IoT" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2014", "status": "Acquired", "industries": [ "Industrials", "Agriculture" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/tule", "api": "https://yc-oss.github.io/api/batches/summer-2014/tule.json" }, { "id": 744, "name": "Pomello", "slug": "pomello", "former_names": [], "small_logo_thumb_url": "/company/thumb/missing.png", "website": "http://pomello.com", "all_locations": "San Francisco, CA, USA", "long_description": "Pomello maps your organizational culture on a team-by-team basis, and integrates with your existing recruiting process to allow you to find the candidates most likely to thrive within your organization. \r\n\r\nFounded at Stanford University, Pomello’s technology is based on 30 years of research in Organizational Behavior, which has been validated over time across multiple industries.", "one_liner": "Analytics software that helps companies measure organizational…", "team_size": 8, "industry": "B2B", "subindustry": "B2B -> Recruiting and Talent", "launched_at": 1415700310, "tags": [ "Machine Learning", "SaaS" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2015", "status": "Acquired", "industries": [ "B2B", "Recruiting and Talent" ], "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": false, "url": "https://www.ycombinator.com/companies/pomello", "api": "https://yc-oss.github.io/api/batches/winter-2015/pomello.json" }, { "id": 778, "name": "Pachyderm", "slug": "pachyderm", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/23351b36c00bacc651a4389386057c50f0690542.png", "website": "http://pachyderm.com", "all_locations": "San Francisco, CA, USA", "long_description": "Pachyderm is a tool for production data pipelines. If you need to chain together data scraping, ingestion, cleaning, munging, wrangling, processing, modeling, and analysis in a sane way, then Pachyderm is for you. If you have an existing set of scripts which do this in an ad-hoc fashion and you're looking for a way to \"productionize\" them, Pachyderm can make this easy for you.", "one_liner": "Data Versioning, Data Pipelines, and Data Lineage", "team_size": 60, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1416221071, "tags": [ "Developer Tools", "Machine Learning", "Data Science" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2015", "status": "Acquired", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/pachyderm", "api": "https://yc-oss.github.io/api/batches/winter-2015/pachyderm.json" }, { "id": 780, "name": "Paperspace", "slug": "paperspace", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/71d8fe724bf62445db1e2f76ff63e411c7f74f2c.png", "website": "https://www.paperspace.com", "all_locations": "Brooklyn, NY, USA", "long_description": "Paperspace is a cloud computing company creating simple and scalable accelerated computing applications. Our goal is to allow individuals and professional teams to seamlessly build and deploy computationally complex products and services.\r\n\r\nPaperspace is backed by leading investors including Y Combinator and Initialized Capital.\r\n\r\nMission:\r\nOur mission is to make cloud computing more accessible through radical simplicity, community-driven technical resources, and straightforward pricing.\r\n\r\n--\r\nTo learn more about Paperspace, please visit https://www.paperspace.com/ or follow us on Twitter at: @hellopaperspace.", "one_liner": "Paperspace is a cloud platform for building and scaling AI…", "team_size": 50, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1416221193, "tags": [ "Machine Learning", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2015", "status": "Acquired", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/paperspace", "api": "https://yc-oss.github.io/api/batches/winter-2015/paperspace.json" }, { "id": 789, "name": "Tempo", "slug": "tempo", "former_names": [ "SmartSpot" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/8d7bb4096474a73857a04dd3a797223c11e906d3.png", "website": "https://tempo.fit/", "all_locations": "San Francisco, CA, USA", "long_description": "SmartSpot is a post Series-A stealth startup backed by Founders Fund and Khosla Ventures that uses computer vision to deliver an unparalleled fitness training experience to your home. Our unique hardware solution gives amazing trainers the ability to see their class participants in real time and deliver detailed advice that was previously only possible in person.", "one_liner": "Live home fitness training powered by computer vision.", "team_size": 158, "industry": "Healthcare", "subindustry": "Healthcare -> Consumer Health and Wellness", "launched_at": 1416222026, "tags": [ "Machine Learning", "Consumer Health Services" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2015", "status": "Active", "industries": [ "Healthcare", "Consumer Health and Wellness" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": true, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/tempo", "api": "https://yc-oss.github.io/api/batches/winter-2015/tempo.json" }, { "id": 799, "name": "Yhat", "slug": "yhat", "former_names": [], "small_logo_thumb_url": "/company/thumb/missing.png", "website": "https://www.yhat.com", "all_locations": "Brooklyn, NY, USA; New York, NY, USA; Remote", "long_description": " Yhat (YC W15, pronounced y-hat) was an end-to-end data science platform. Acquired by Alteryx (NYSE:AYX)", "one_liner": "End-to-end data science lifecycle management platform. ", "team_size": 17, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1416222882, "tags": [ "Artificial Intelligence", "Machine Learning", "Enterprise", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2015", "status": "Acquired", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": true, "app_answers": true, "question_answers": false, "url": "https://www.ycombinator.com/companies/yhat", "api": "https://yc-oss.github.io/api/batches/winter-2015/yhat.json" }, { "id": 830, "name": "SigOpt", "slug": "sigopt", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/8587155629554384fccbdcf060b0568e458358d4.png", "website": "https://sigopt.com", "all_locations": "San Francisco, CA, USA", "long_description": "SigOpt is the optimization platform that amplifies your research. SigOpt takes any research pipeline and tunes it, right in place. Our cloud-based ensemble of optimization algorithms is proven and seamless to deploy, and is used by globally recognized leaders within the insurance, credit card, algorithmic trading and consumer packaged goods industries.", "one_liner": "SigOpt is an Optimization-as-a-Service platform that seamlessly tunes…", "team_size": 23, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1416310491, "tags": [ "Machine Learning", "SaaS", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2015", "status": "Acquired", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/sigopt", "api": "https://yc-oss.github.io/api/batches/winter-2015/sigopt.json" }, { "id": 832, "name": "Standard Cyborg", "slug": "standard-cyborg", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ea641cf296beace7a7288415d4808dc519f3a987.png", "website": "http://standardcyborg.com", "all_locations": "San Francisco, CA, USA", "long_description": "We are multiplying the potential of the real world by making computer vision accessible to all.\r\n\r\nWe create the cloud and edge tools that developers and non-developers require in order to build, deploy, and improve CV solutions quickly.\r\n\r\nstandardcyborg.com (YC W15)", "one_liner": "Buid, test and deploy perception applications", "team_size": 9, "industry": "Healthcare", "subindustry": "Healthcare -> Medical Devices", "launched_at": 1416310916, "tags": [ "Machine Learning", "Computer Vision", "Open Source" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2015", "status": "Inactive", "industries": [ "Healthcare", "Medical Devices" ], "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": false, "url": "https://www.ycombinator.com/companies/standard-cyborg", "api": "https://yc-oss.github.io/api/batches/winter-2015/standard-cyborg.json" }, { "id": 1019, "name": "Pulpix", "slug": "pulpix", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/8c132121b7d4ec5ea81300966ada8fd09448ac76.png", "website": "https://www.pulpix.com", "all_locations": "New York, NY, USA", "long_description": "Leveraging Artificial Intelligence to offer personalized video experience for online video platforms. ", "one_liner": "Binge-watching technology for video platforms. ", "team_size": 15, "industry": "B2B", "subindustry": "B2B -> Marketing", "launched_at": 1447312815, "tags": [ "Artificial Intelligence", "Machine Learning", "Video" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2016", "status": "Acquired", "industries": [ "B2B", "Marketing" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/pulpix", "api": "https://yc-oss.github.io/api/batches/winter-2016/pulpix.json" }, { "id": 1020, "name": "Revl", "slug": "revl", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/22c87d9ebe7f3211cc7fc4e6b1c3691c72354478.png", "website": "https://revl.com/", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Revl is an experience technology company and Y Combinator 2016 Winter Batch member launching the Revl Arc smart action camera. \r\n\r\nDesigned in coordination with frogVentures, Sony, Ambarella and leading engineers with backgrounds at NASA, HP and Sikorsky Aircraft, the Revl Arc is available for preorder and will begin shipping in December. \r\n\r\nRevl was founded in 2015 and is based in San Francisco. For more information, please visit www.revl.com", "one_liner": "AI edited video souvenirs as a service", "team_size": 22, "industry": "B2B", "subindustry": "B2B -> Marketing", "launched_at": 1447312815, "tags": [ "Machine Learning", "SaaS", "Sports Tech", "B2B", "Video" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2016", "status": "Active", "industries": [ "B2B", "Marketing" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/revl", "api": "https://yc-oss.github.io/api/batches/winter-2016/revl.json" }, { "id": 1080, "name": "Relativity Space", "slug": "relativity-space", "former_names": [ "Relativity Space", "Relativity" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/69fc3eaa7d024cb1636c3fb74c1b9ff45b63ca30.png", "website": "http://relativityspace.com", "all_locations": "Los Angeles, CA, USA", "long_description": "Relativity is building humanity’s multiplanetary future. We invented a new approach to design, build, and fly our own rockets, starting with Terran 1 – the world’s first entirely 3D printed rocket, and Terran R, our next generation medium-heavy lift reusable launch vehicle.\r\n \r\nAs a vertically integrated technology platform, Relativity is at the forefront of an inevitable shift toward software-defined manufacturing. By fusing 3D printing, artificial intelligence, and autonomous robotics, we are pioneering the factory of the future. Disrupting 60 years of aerospace, Relativity offers a radically simplified supply chain, building a rocket with fewer parts and faster iteration.\r\n \r\nWe believe in a future where interplanetary life fundamentally expands the possibilities for human experience. Our long-term vision is to upgrade humanity’s industrial base on Earth and on Mars.", "one_liner": "Building humanity’s multiplanetary future.", "team_size": 2500, "industry": "Industrials", "subindustry": "Industrials -> Aviation and Space", "launched_at": 1448133615, "tags": [ "Machine Learning", "Space Exploration", "Rocketry", "3D Printing", "Manufacturing" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2016", "status": "Active", "industries": [ "Industrials", "Aviation and Space" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Growth", "app_video_public": true, "demo_day_video_public": true, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/relativity-space", "api": "https://yc-oss.github.io/api/batches/winter-2016/relativity-space.json" }, { "id": 1247, "name": "NeoWize", "slug": "neowize", "former_names": [ "Shoptimally" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a44843d10a15e36161da09c06259a4bf0bc995f2.png", "website": "http://www.neowize.com", "all_locations": "Tel Aviv-Yafo, Tel Aviv District, Israel", "long_description": "NeoWize changes the way we look at machine learning and deep learning. \r\nCurrent deep learning algorithms focus on making the most out of the data available. \r\nNeoWize utilizes neural networks and adaptive input to create more data and better data, thus increasing our predictive power with small data-sets.\r\nWe use this technology to help e-commerce sites learn what each individual buyer is looking for and create a better user experience from the first visit.", "one_liner": "NeoWize created a new type of machine learning algorithm and uses it…", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1461643819, "tags": [ "Machine Learning", "E-Commerce", "Personalization" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2016", "status": "Acquired", "industries": [ "B2B", "Retail" ], "regions": [ "Israel", "Middle East and North Africa" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/neowize", "api": "https://yc-oss.github.io/api/batches/summer-2016/neowize.json" }, { "id": 1285, "name": "CrowdAI", "slug": "crowdai", "former_names": [ "StenoAI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/65641ddd8516f01cc3bf87dd2c876cd999d398f0.png", "website": "https://crowdai.com/", "all_locations": "San Francisco, CA, USA", "long_description": "CrowdAI equips enterprises of all sizes with the power of deep learning and the approachability and speed of no-code software. Our easy-to-master platform allows users of all technical abilities, from business operators to data scientists, to power real-time decisions from their visual world.\r\n\r\nRecognizing data as the new code, CrowdAI is the only vision AI platform to truly provide organizations with the infrastructure for the entire AI-lifecycle, empowering you to label data systematically, train models efficiently, scale models iteratively, and power decisions continuously.", "one_liner": "CrowdAI is the world's leading no-code platform for vision AI", "team_size": 32, "industry": "B2B", "subindustry": "B2B", "launched_at": 1461817213, "tags": [ "Machine Learning", "Computer Vision" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2016", "status": "Acquired", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/crowdai", "api": "https://yc-oss.github.io/api/batches/summer-2016/crowdai.json" }, { "id": 1294, "name": "Scale AI", "slug": "scale-ai", "former_names": [ "Ava", "Scale" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/8c45a78eb56f4a95e41a3a77960b00fdfb4cd918.png", "website": "http://scale.com", "all_locations": "San Francisco, CA, USA", "long_description": "Scale accelerates the development of AI within organizations of any size to deliver critical business insights and operational efficiency. Its data-centric infrastructure platform leverages RLHF (Reinforced Learning with Human Feedback) to help organizations build the strongest AI models that supercharge their business, with customers across industries including Meta, Microsoft, U.S. Army, DoD’s Defense Innovation Unit, Open AI, General Motors, Toyota Research Institute, Brex, Instacart and Flexport.", "one_liner": "Data-centric infrastructure to accelerate the development of AI ", "team_size": 500, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1461817215, "tags": [ "Artificial Intelligence", "Machine Learning" ], "tags_highlighted": [], "top_company": true, "isHiring": true, "nonprofit": false, "batch": "Summer 2016", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/scale-ai", "api": "https://yc-oss.github.io/api/batches/summer-2016/scale-ai.json" }, { "id": 1444, "name": "Bountiful", "slug": "bountiful", "former_names": [ "Vinsight" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/40bd701518c1492966677e92d610182861a00a02.png", "website": "https://bountiful.ag/", "all_locations": "San Francisco, CA, USA", "long_description": "We’re on a mission to optimize the agricultural industry.\r\n\r\nWhen we started Bountiful in 2015, the grape error rate for predicting production was 30 percent. Why? We found that many farmers in the specialty crops space were still using traditional pencil-and-paper techniques to predict yield. These low-fidelity forecasting methods weren’t giving them a clear enough understanding of their production until it was too late, leading to waste and inefficiency throughout the supply chain.\r\n\r\nWe saw a problem we wanted to solve.\r\n\r\nToday, Bountiful is using advanced data science to help farmers forecast more accurately, so they can make better decisions. In the last three years, we’ve combined the latest in machine learning with weather, satellite, geographic, and historical data. The result is a user-friendly platform that transforms volumes of complex agricultural information into simple, actionable insights farmers can use to run more economically and environmentally sustainable farms.\r\n\r\nMore recently, we’re working to open the dialogue between buyers and sellers, remove uncertainty, and provide clarity to the supply chain to meet global food demand.\r\n\r\nOur ultimate goal is to close the agricultural margin of error. Not only will this make individual farms more efficient, profitable, and sustainable, but it will help optimize the global food supply chain. That means healthier people and a healthier planet.", "one_liner": "An Operating System for agriculture.", "team_size": 4, "industry": "Industrials", "subindustry": "Industrials -> Agriculture", "launched_at": 1478053227, "tags": [ "Machine Learning", "Marketplace", "Analytics", "Agriculture" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2017", "status": "Active", "industries": [ "Industrials", "Agriculture" ], "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": false, "url": "https://www.ycombinator.com/companies/bountiful", "api": "https://yc-oss.github.io/api/batches/winter-2017/bountiful.json" }, { "id": 1445, "name": "Cowlar", "slug": "cowlar", "former_names": [], "small_logo_thumb_url": "/company/thumb/missing.png", "website": "http://www.cowlar.com", "all_locations": "Memphis, TN, USA", "long_description": "Cowlar, a fitbit for dairy cows provides data as a service to help dairy producers optimize operations and improve herd health.\n\nIt's simple. You strap it around a cow's neck. It measures temperature, activity and cow behavior. Cowlar makes sense of the data and sends the farmers actionable recommendations on how to:\n\n1. Boost reproduction rates\n2. Identify diseases instantly\n3. Improve milk yield \n4. We can even tell if someone is stealing your cow ! \n\nCowlar is simple, affordable and easy to use. It's rugged, water proof, comes with a 6 Month battery life so farmers dont have to worry about charging and farmers can be sent text messages in any language/ for those who cant read, we can send an automated phone call.", "one_liner": "Fitbit for dairy cows. Farms use cowlar's alerts & recommendations to…", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Agriculture", "launched_at": 1478053830, "tags": [ "Machine Learning", "IoT", "Agriculture" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2017", "status": "Inactive", "industries": [ "Industrials", "Agriculture" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/cowlar", "api": "https://yc-oss.github.io/api/batches/winter-2017/cowlar.json" }, { "id": 1483, "name": "Entry", "slug": "entry", "former_names": [ "XIX.ai" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/91f99c3342f7ef67fe23f91952d7102c8d49d799.png", "website": "http://getentry.com", "all_locations": "Los Angeles, CA, USA; San Francisco, CA, USA", "long_description": "Easily onboard, verify IDs, authenticate and continuously verify credentials and the identities of your users - in one place.", "one_liner": "Biometric sign in and identity verification platform", "team_size": 7, "industry": "B2B", "subindustry": "B2B -> Productivity", "launched_at": 1478224818, "tags": [ "Machine Learning", "Biometrics", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2017", "status": "Inactive", "industries": [ "B2B", "Productivity" ], "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": false, "url": "https://www.ycombinator.com/companies/entry", "api": "https://yc-oss.github.io/api/batches/winter-2017/entry.json" }, { "id": 1518, "name": "FloydHub", "slug": "floydhub", "former_names": [ "Floyd" ], "small_logo_thumb_url": "/company/thumb/missing.png", "website": "http://www.floydhub.com/", "all_locations": "San Francisco, CA, USA", "long_description": "FloydHub is a Platform-as-a-Service for training and deploying your DL models in the cloud. Start running your first project in < 30 sec! Floyd takes care of the grunt work so you can focus on the core of your problem.", "one_liner": "ML Platform for developing, training and deploying ML models", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1478662833, "tags": [ "AIOps", "Machine Learning", "SaaS" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2017", "status": "Inactive", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/floydhub", "api": "https://yc-oss.github.io/api/batches/winter-2017/floydhub.json" }, { "id": 1609, "name": "Nimble", "slug": "nimble", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b693002259f2dd2c99c3f0808e254c207525699a.png", "website": "http://www.hirenimble.com", "all_locations": "Remote", "long_description": "Nimble uses predictive analytics to give every K-12 student access to excellent teachers. Our smart applicant tracking system (ATS) leverages a predictive model to help school districts identify and hire the best educators for their classrooms.\r\n", "one_liner": "Data-driven teacher hiring", "team_size": 25, "industry": "Education", "subindustry": "Education", "launched_at": 1493265719, "tags": [ "Education", "Machine Learning", "SaaS" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2017", "status": "Active", "industries": [ "Education" ], "regions": [ "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/nimble", "api": "https://yc-oss.github.io/api/batches/summer-2017/nimble.json" }, { "id": 1610, "name": "Darmiyan", "slug": "darmiyan", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3be6f1febb81bc5a98e11a2a64bc294e0cee4eff.png", "website": "https://www.darmiyan.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Novel quantitative virtual microscopy for early detection of Alzheimer's disease from non-invasive MRI.", "one_liner": "Early detection of Alzheimer's disease", "team_size": 8, "industry": "Healthcare", "subindustry": "Healthcare -> Diagnostics", "launched_at": 1493265720, "tags": [ "Artificial Intelligence", "Machine Learning", "Health Tech", "Diagnostics" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2017", "status": "Active", "industries": [ "Healthcare", "Diagnostics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/darmiyan", "api": "https://yc-oss.github.io/api/batches/summer-2017/darmiyan.json" }, { "id": 1616, "name": "Flock Safety", "slug": "flock-safety", "former_names": [ "Flock" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ee69b5c905088288ff0fc007921dde14514a40a1.png", "website": "http://www.flocksafety.com", "all_locations": "Atlanta, GA, USA", "long_description": "Flock Safety provides the first public safety operating system that empowers private communities and law enforcement to work together to eliminate crime. We are committed to protecting human privacy and mitigating bias in policing with the development of best-in-class technology rooted in ethical design, which unites civilians and public servants in pursuit of a safer, more equitable society. \r\n\r\nOur Safety-as-a-Service approach includes affordable devices powered by LTE and solar that can be installed anywhere. Our technology detects and captures objective details, decodes evidence in real-time and delivers investigative leads into the hands of those who matter. \r\n\r\nWhile safety is a serious business, we are a supportive team that is optimizing the remote experience to create strong and fun relationships even when we are physically apart. Our flock of hard-working employees thrive in a positive and inclusive environment, where a bias towards action is rewarded. Flock Safety is headquartered in Atlanta and operates nationwide. We have raised $150M in our Series E led by Tiger Global at a $3.5B valuation.", "one_liner": "The first public safety operating system that eliminates crime.", "team_size": 1000, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1646149352, "tags": [ "Hardware", "Machine Learning", "SaaS" ], "tags_highlighted": [], "top_company": true, "isHiring": true, "nonprofit": false, "batch": "Summer 2017", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": true, "url": "https://www.ycombinator.com/companies/flock-safety", "api": "https://yc-oss.github.io/api/batches/summer-2017/flock-safety.json" }, { "id": 1638, "name": "Cairns Health", "slug": "cairns-health", "former_names": [ "Totemic Labs", "Totemic", "Koko" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f2571c59aad3d4224dae47b21fb2bc278e88e66c.png", "website": "https://www.cairns.ai", "all_locations": "Sunnyvale, CA, USA", "long_description": "Cairns Health is creating a fundamentally better healthcare experience for people with chronic health conditions and those who care for them. We make healthcare more accessible by simplifying complex care plans, connecting care teams and meeting patients where they live. Through our conversational AI, patients use their voice to interact with our digital care companion, who proactively gives medication reminders, symptom checks, behavioral nudges and even engages in friendly conversation to ease loneliness. Cairns uses a device that includes radar to put the patient in context and passively monitors their activities, including: heart rate, breathing rate and sleep stages, all without a wearable. The result is informed and timely intervention that drives improved clinical outcomes, reduced care delivery costs and a more satisfactory healthcare experience for all.", "one_liner": "Your voice. Your health. We care.", "team_size": 17, "industry": "Healthcare", "subindustry": "Healthcare -> Consumer Health and Wellness", "launched_at": 1493693427, "tags": [ "Hardware", "Machine Learning", "Consumer Health Services" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2017", "status": "Active", "industries": [ "Healthcare", "Consumer Health and Wellness" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/cairns-health", "api": "https://yc-oss.github.io/api/batches/summer-2017/cairns-health.json" }, { "id": 1671, "name": "Sourceress", "slug": "sourceress", "former_names": [ "Sourceress", "Generally Intelligent", "Imbue (formerly Generally Intelligent", "YC17)", "Imbue (formerly Generally Intelligent)" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cd298ab7cc0e50b44f16100129fb3d4a93dcabc0.png", "website": "http://sourceress.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Sourceress is an AI recruiter that is reinventing how people find jobs. With tailor-made machine learning models, we rigorously define what a company is looking for in a role, identify great candidates, and engage candidates with highly personalized introductions. Our process creates a stream of interested candidates that hiring managers are excited about more than 85% of the time.", "one_liner": "", "team_size": 35, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1493860914, "tags": [ "Artificial Intelligence", "Machine Learning", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2017", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/sourceress", "api": "https://yc-oss.github.io/api/batches/summer-2017/sourceress.json" }, { "id": 1678, "name": "Headstart", "slug": "headstart", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ac3d6ebaf0dfdd9434b6a3dd78182d498f7b6587.png", "website": "https://www.headstart.io", "all_locations": "London, England, United Kingdom", "long_description": "Headstart (YC S17) uses Machine Learning technology to help employers identify the best-suited talent in the shortest period of time. We provide leading organisations with a solution designed to help them transition away from experience/qualification based screening and towards a more inclusive and effective process which considers personality, behaviours, strengths and motivations. In doing so, Headstart helps companies hire people truly aligned to their values, culture and exact job requirements in a seamless, engaging way.\r\n\r\nThe Headstart process is simple and effective: companies save time and money by finding candidates who meet their exact job requirements at an earlier stage, and job seekers connect directly with businesses through an engaging, reusable 15 minute application form. We ensure a transparent process and initiate productive dialogue, making candidates feel valued and helping companies hire the right people.", "one_liner": "Headstart uses Machine Learning to help companies decide on who to…", "team_size": 44, "industry": "B2B", "subindustry": "B2B -> Recruiting and Talent", "launched_at": 1493881926, "tags": [ "Machine Learning", "Recruiting" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2017", "status": "Acquired", "industries": [ "B2B", "Recruiting and Talent" ], "regions": [ "United Kingdom", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/headstart", "api": "https://yc-oss.github.io/api/batches/summer-2017/headstart.json" }, { "id": 1723, "name": "Proven Group", "slug": "proven-group", "former_names": [ "Proven" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7c83aa289cd925acbb18fdef94c0f501396b2076.png", "website": "https://www.provenskincare.com", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Proven is a data powered skincare company that creates personalized skincare products based on more than 47 factors about an individual's skin, genetic background, lifestyle and environment. Our formulations are rooted in the largest beauty database in the world, the proprietary Skin Genome Project, built in-house by Proven's cofounder Amy Yuan, a computational physicist from Stanford. The database has won MIT's AI Technology of the Year award and encompasses more than 20Million consumer datapoints and thousands of scientific articles on skin. Our challenge now is to tell the story of Proven, and share our industry leading personalized skincare products with the world.", "one_liner": "PROVEN is using AI, data and personalization to disrupt CPG", "team_size": 40, "industry": "Consumer", "subindustry": "Consumer", "launched_at": 1508008727, "tags": [ "Artificial Intelligence", "Machine Learning", "Consumer", "E-commerce" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2018", "status": "Active", "industries": [ "Consumer" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/proven-group", "api": "https://yc-oss.github.io/api/batches/winter-2018/proven-group.json" }, { "id": 1739, "name": "Observant AI", "slug": "observant-ai", "former_names": [ "Buglife", "Observant" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2e800cad3bc0abdaeb2231fae95e02400fb25188.png", "website": "https://www.observantai.com", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Observant AI is an iPhone-based driver monitoring system for commercial fleets. It uses machine learning + iPhone's depth sensors to detect unsafe driver behavior, prevent accidents, and save lives.", "one_liner": "iPhone-based driver monitoring for commercial fleets.", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Operations", "launched_at": 1509562882, "tags": [ "Autonomous Trucking", "Hard Tech", "Machine Learning", "SaaS" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2018", "status": "Active", "industries": [ "B2B", "Operations" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/observant-ai", "api": "https://yc-oss.github.io/api/batches/winter-2018/observant-ai.json" }, { "id": 1775, "name": "Reverie Labs", "slug": "reverie-labs", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c167c3874ed6d5b52b8c339d61851123a4540f2c.png", "website": "http://www.reverielabs.com", "all_locations": "Cambridge, MA, USA", "long_description": "Reverie Labs is engineering next-generation, brain-penetrant cancer therapies.\r\n", "one_liner": " Engineering next-generation, brain-penetrant cancer therapies.", "team_size": 29, "industry": "Healthcare", "subindustry": "Healthcare -> Therapeutics", "launched_at": 1509678248, "tags": [ "AI-powered Drug Discovery", "Machine Learning", "Biotech" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2018", "status": "Inactive", "industries": [ "Healthcare", "Therapeutics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/reverie-labs", "api": "https://yc-oss.github.io/api/batches/winter-2018/reverie-labs.json" }, { "id": 1807, "name": "Edwin", "slug": "edwin", "former_names": [ "Edwin.ai" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/9acc840c27b5a4171f25ceb9a456d6444003093c.png", "website": "https://edwin.ai", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "It combines the latest adaptive learning and Natural Language Understanding technology with pedagogical content as well as on-demand human instructors to offer its students affordable, personalized, 1:1 learning. Based in San Francisco, the company was funded by General Catalyst, Y Combinator, Google Assistant Investments Program, and several other investors. Over 800 thousand students have improved their English with Edwin.\r\n\r\nIn early 2020 Edwin merged with MyBuddy.ai. The resulting company kept the name “Buddy.ai”. Headquartered in San Francisco, it focuses on building a virtual English conversation partner for over 500 million children around the globe who are trying to learn English, but can't reach fluency because they lack genuine practice speaking the language. The company doubled down on its mobile app Buddy, the voice-based English tutor for kids, organically combining solutions developed by Buddy.ai and Edwin.", "one_liner": "Edwin is virtual English tutor - an AI-powered service for learning…", "team_size": 14, "industry": "Education", "subindustry": "Education", "launched_at": 1510113785, "tags": [ "AI-Enhanced Learning", "Education", "Machine Learning", "Smart Home Assistants", "eLearning" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2018", "status": "Acquired", "industries": [ "Education" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/edwin", "api": "https://yc-oss.github.io/api/batches/winter-2018/edwin.json" }, { "id": 1823, "name": "Vathys", "slug": "vathys", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/14e804e717af07615be4e94540c5779418d30a78.png", "website": "http://vathys.ai", "all_locations": "Portland, OR, USA; Remote", "long_description": "Previously: Building machine learning hardware 10X faster than ASICs.\r\n\r\nAfter Pivot: Accelerating deep learning through software\r\n\r\nYC Winter 2018.", "one_liner": "Accelerating machine learning through software", "team_size": 6, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1510167825, "tags": [ "Artificial Intelligence", "Deep Learning", "Machine Learning" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2018", "status": "Inactive", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/vathys", "api": "https://yc-oss.github.io/api/batches/winter-2018/vathys.json" }, { "id": 1832, "name": "Tilt (f.k.a. Delphia)", "slug": "tilt-fka-delphia", "former_names": [ "Vox Pop Labs", "Delphia", "Delphia (d.b.a. Tilt)" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d97c7b6a062bbf024d979f3e67fe169d6f103b8b.png", "website": "http://tilt.io", "all_locations": "Toronto, ON, Canada; Remote", "long_description": "Tilt lets anyone build evidence-backed, point-in-time, and deterministic rules-based investment strategies... in minutes. All you need is a prompt — whether a theme, trend, or detailed thesis — we'll take care of the rest. Advisors also use Tilt to customize their client portfolios with tax considerations and investment preferences. \r\n\r\nIf you're thinking about working here, we're on a mission to price the world's information.", "one_liner": "Tilt lets anyone build an index out of any content on the web.", "team_size": 25, "industry": "Fintech", "subindustry": "Fintech -> Consumer Finance", "launched_at": 1510196648, "tags": [ "Fintech", "Machine Learning", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2018", "status": "Active", "industries": [ "Fintech", "Consumer Finance" ], "regions": [ "Canada", "America / Canada", "Remote", "Fully Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/tilt-fka-delphia", "api": "https://yc-oss.github.io/api/batches/winter-2018/tilt-fka-delphia.json" }, { "id": 1851, "name": "Voicery", "slug": "voicery", "former_names": [ "Tensorac" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d304f1473be86d423a2e762c1011d2016d56c04b.png", "website": "http://www.voicery.com", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Voicery synthesizes the most realistic human voices using deep neural networks. Prior to starting Voicery, Andrew, one of the founders, led the speech synthesis research team at Baidu Research. By synthesizing speech nearly indistinguishable from human, Voicery enable new media applications, such as auto-generated audiobooks, podcasts, television dubs, and voice overs.", "one_liner": "Automated voice acting and emotive speech synthesis with deep neural…", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1510977762, "tags": [ "Machine Learning", "SaaS", "B2B" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2018", "status": "Inactive", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/voicery", "api": "https://yc-oss.github.io/api/batches/winter-2018/voicery.json" }, { "id": 1858, "name": "Jido Maps", "slug": "jido-maps", "former_names": [ "MapSync" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/788dc05b2141606cea9f6805759306ec0ea99f5e.png", "website": "https://jidomaps.com/", "all_locations": "Berkeley, CA, USA; San Francisco, CA, USA; Remote", "long_description": "We help teams that may or may not have machine learning expertise quickly turn their data into deployed computer vision models. Example applications include security camera monitoring, automating data entry, interpreting web scraped images, validated user photo inputs, augmented reality and mobile product scanning. \r\n\r\nIf you have visual or scanned data that you wish your software could interpret at scale, we can turn around a first proof of concept in under a week. Reach out and see how computer vision can change your business.", "one_liner": "Turn your data into a deployed computer vision model", "team_size": 6, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1512529341, "tags": [ "Deep Learning", "Indoor Mapping", "Machine Learning", "Computer Vision" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2018", "status": "Acquired", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/jido-maps", "api": "https://yc-oss.github.io/api/batches/winter-2018/jido-maps.json" }, { "id": 1878, "name": "Swayable", "slug": "swayable", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a5d215c7313a052e41f5b021db99a546ebcecf7a.png", "website": "http://swayable.com", "all_locations": "New York, NY, USA", "long_description": "Swayable partners with the world's leading brands and advocacy groups to change minds, behaviors and attitudes.\r\n\r\nWe are hiring in data science, full stack engineering, data visualization, design, and operations. We welcome unsolicited CVs from anyone, and especially encourage women and people from under-represented groups to talk to us.", "one_liner": "Swayable predicts consumer opinion and the impact of content", "team_size": 30, "industry": "B2B", "subindustry": "B2B -> Marketing", "launched_at": 1515103348, "tags": [ "Machine Learning" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2018", "status": "Active", "industries": [ "B2B", "Marketing" ], "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": false, "url": "https://www.ycombinator.com/companies/swayable", "api": "https://yc-oss.github.io/api/batches/winter-2018/swayable.json" }, { "id": 1888, "name": "Phiar", "slug": "phiar", "former_names": [ "Phair" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/bb16323014c9e8250a467c58cc43f377d1919cf9.png", "website": "https://www.phiar.net", "all_locations": "Redwood City, CA, USA", "long_description": "At Phiar, we are building the first AI-powered AR navigation driving software solution that runs on a smartphone and in-vehicle displays, utilizing our ultra-lightweight road understanding AI that runs completely at-the-edge, in real-time, all on just a smartphone-level compute.\r\n\r\nOur mission is to enhance driving safety, facilitate more intuitive wayfinding, and connect drivers with their surrounding environments.", "one_liner": "We are developing a revolutionary AI-powered augmented reality…", "team_size": 12, "industry": "Industrials", "subindustry": "Industrials -> Automotive", "launched_at": 1524539151, "tags": [ "Artificial Intelligence", "Machine Learning", "Augmented Reality" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2018", "status": "Acquired", "industries": [ "Industrials", "Automotive" ], "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": false, "url": "https://www.ycombinator.com/companies/phiar", "api": "https://yc-oss.github.io/api/batches/summer-2018/phiar.json" }, { "id": 1898, "name": "Searchlight", "slug": "searchlight", "former_names": [ "AllyIQ", "Searchlight", "searchlight" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c614da05c9ea2efb343da05c4e5a237c56bad357.png", "website": "https://www.searchlight.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "Talent AI improving quality of hire", "team_size": 20, "industry": "B2B", "subindustry": "B2B -> Recruiting and Talent", "launched_at": 1524621947, "tags": [ "Machine Learning", "SaaS", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2019", "status": "Acquired", "industries": [ "B2B", "Recruiting and Talent" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/searchlight", "api": "https://yc-oss.github.io/api/batches/winter-2019/searchlight.json" }, { "id": 1939, "name": "64x Bio", "slug": "64x-bio", "former_names": [ "64-X", "64-x" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cfea1f5fda223a069c00cebbc1559d75a397a3f2.png", "website": "http://www.64xbio.com", "all_locations": "San Francisco, CA, USA", "long_description": "The future of medicine is taking shape, but scaling it remains a challenge. Some of the biggest breakthroughs in next generation therapies are being held back by manufacturing constraints. The science is moving fast, but the infrastructure is still catching up.\r\n\r\nOur VectorSelect platform is designed to unlock the scale these therapies need to survive. We combine massively parallelized screens with computational insights to engineer high yield cell lines and production technologies — accelerating the manufacturing of advanced therapies from the inside out. ", "one_liner": "Enabling next generation medicines. A comprehensive platform and…", "team_size": 25, "industry": "Healthcare", "subindustry": "Healthcare -> Industrial Bio", "launched_at": 1609711472, "tags": [ "Gene Therapy", "Machine Learning" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2018", "status": "Active", "industries": [ "Healthcare", "Industrial Bio" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/64x-bio", "api": "https://yc-oss.github.io/api/batches/summer-2018/64x-bio.json" }, { "id": 2001, "name": "Shelf Engine", "slug": "shelf-engine", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/30d8273cf77bf9ee7c72f1c08b3457034ba910b3.png", "website": "http://www.shelfengine.com", "all_locations": "Seattle, WA, USA", "long_description": "Shelf Engine helps businesses increase sales by accurately predicting the perfect amount of perishable goods to order, thus reducing food waste. ", "one_liner": "Transforms how grocery stores buy highly perishable foods.", "team_size": 40, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1525810118, "tags": [ "Machine Learning" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2018", "status": "Acquired", "industries": [ "B2B", "Retail" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": true, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/shelf-engine", "api": "https://yc-oss.github.io/api/batches/summer-2018/shelf-engine.json" }, { "id": 2023, "name": "SPATE", "slug": "spate", "former_names": [ "SPATE", "Spate" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7577742d36a89182bb27d25c3ad944da530cabbf.png", "website": "https://www.spate.nyc", "all_locations": "New York, NY, USA; Remote", "long_description": "Spate is your machine intelligence solution for finding the next big trend in Beauty and Food. For example, we spotted trends such as turmeric, face masks, and cold brew.", "one_liner": "Trends prediction for marketers", "team_size": 15, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1527062926, "tags": [ "Machine Learning", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2018", "status": "Active", "industries": [ "B2B", "Retail" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/spate", "api": "https://yc-oss.github.io/api/batches/summer-2018/spate.json" }, { "id": 11936, "name": "Pachama", "slug": "pachama", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2e55b15f7dfd0751a774fd43cb72476048b30df9.png", "website": "http://pachama.com", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Pachama is a leading climate-tech company harnessing cutting-edge technologies such as computer vision and satellites to drive funding to effective reforestation and conservation projects that sequester carbon, enhance biodiversity and enrich local communities around the world.\r\n\r\nThrough a tech-verified marketplace that counts as customer the likes of Amazon, Airbnb, Netflix and Nespresso, the company drives capital to forests in Brazil, Mexico, India, the USA and beyond. The company is backed by top investors such as Bill Gates' BEV, Chis Sacca's LowerCarbon, Amazon Climate Pledge among others. \r\n\r\nThe company is fully remote and driven by a strong sense of purpose.", "one_liner": "Restoring nature to solve climate change.", "team_size": 85, "industry": "Industrials", "subindustry": "Industrials -> Climate", "launched_at": 1541036076, "tags": [ "Carbon Capture and Removal", "Machine Learning", "Climate" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2019", "status": "Acquired", "industries": [ "Industrials", "Climate" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/pachama", "api": "https://yc-oss.github.io/api/batches/winter-2019/pachama.json" }, { "id": 11992, "name": "Basilica", "slug": "basilica", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f116850261b9a5e03cfc2d394c7f0b382eaabeb4.png", "website": "https://www.basilica.ai", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "Basilica is an API that embeds high-dimensional data like images and…", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1541192586, "tags": [ "Machine Learning", "API" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2019", "status": "Inactive", "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": false, "url": "https://www.ycombinator.com/companies/basilica", "api": "https://yc-oss.github.io/api/batches/winter-2019/basilica.json" }, { "id": 11994, "name": "Sapling.ai", "slug": "sapling-ai", "former_names": [ "Sapling Intelligence" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/5aa6fac6d2489885ce08d4c58cabcc5b5a131c29.png", "website": "https://sapling.ai", "all_locations": "Los Angeles, CA, USA", "long_description": "Sapling offers an API and SDK to help businesses integrate language models into their applications. Its messaging assistant sits on top of CRMs and messaging platforms to help users more efficiently compose responses.", "one_liner": "Language models for enterprise applications.", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Productivity", "launched_at": 1541266318, "tags": [ "Artificial Intelligence", "Deep Learning", "Generative AI", "Machine Learning", "B2B" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2019", "status": "Active", "industries": [ "B2B", "Productivity" ], "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": false, "url": "https://www.ycombinator.com/companies/sapling-ai", "api": "https://yc-oss.github.io/api/batches/winter-2019/sapling-ai.json" }, { "id": 12062, "name": "Autodial prev Qwest", "slug": "autodial-prev-qwest", "former_names": [ "Qwest", "qwest.", "Qwest Social Club", "qwest.", "In The Room", "In The Room, Inc.", "In The Room" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7b3eee35a4bfe7106117bae88bb555be906669dc.png", "website": "https://www.autodial.com", "all_locations": "Miami, FL, USA; Remote", "long_description": "Previous Qwest (W19) - skip busy club lines. Autodial (currently exiting) is a service for skipping busy phone lines for everyday people calling businesses. Our goal is to connect people directly to customer service via phone lines by reducing the wait time from 60 minutes to 5 minutes. We cover 10,000 phone lines ranging from financial institutions, telecom, home services, government, etc.\r\n\r\nThe Pivot\r\nClub and restaurant lines were non-existent during COVID. We reset the company and shifted focus using more technical skills in machine learning to build a service that millions of americans could use and leverage in the moment -- a service that called government phone lines and handled the call process.\r\n\r\nSucceeding we expanded quickly expanded and built a model to support people using the service for free. ", "one_liner": "Skip Busy Phone Lines", "team_size": 1, "industry": "Consumer", "subindustry": "Consumer", "launched_at": 1541644230, "tags": [ "Artificial Intelligence", "Machine Learning", "Telecommunications", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2019", "status": "Active", "industries": [ "Consumer" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": true, "demo_day_video_public": true, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/autodial-prev-qwest", "api": "https://yc-oss.github.io/api/batches/winter-2019/autodial-prev-qwest.json" }, { "id": 12260, "name": "AXDRAFT", "slug": "axdraft", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/95bd3baee270d1b082340a1d56709977638c161c.png", "website": "https://axdraft.com", "all_locations": "Kyiv, Ukraine; Frankfurt, HE, Germany; Lviv, Lviv Oblast, Ukraine", "long_description": "AXDRAFT analyzes patterns in your legal documents and transforms drafting process from erroneous and time consuming copy and paste to a mistake-free simple Q&A. The average time to draft a document with AXDRAFT is less than 4 minutes.\r\n\r\nOn top of this AXDRAFT allows to integrate data into the document from public registers and your internal databases, eliminating the need to double check every data input.\r\n\r\nData validation, e-signatures, access control, document id, visibility and personal accountability for drafted documents. All of this is possible with AXDRAFT.\r\n\r\n45 corporations using AXDRAFT reduce time spent on drafting legal documents by up to 90% and shorten their approval cycles by up to 4 days.\r\n\r\nBoth of these improvements mean more deals and better financial results for your company every quarter.\r\n\r\nAnd the best part is that from the moment we sign the contract AXDRAFT can be up and running in 2 weeks.\r\n\r\nFew case studies are available here: https://www.axdraft.com/customers", "one_liner": "AXDRAFT helps corporations draft, negotiate and approve documents 10x…", "team_size": 34, "industry": "B2B", "subindustry": "B2B -> Legal", "launched_at": 1543978964, "tags": [ "Machine Learning", "SaaS", "LegalTech" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2019", "status": "Acquired", "industries": [ "B2B", "Legal" ], "regions": [ "Ukraine", "Germany", "Europe", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/axdraft", "api": "https://yc-oss.github.io/api/batches/winter-2019/axdraft.json" }, { "id": 12415, "name": "Spiral Genetics", "slug": "spiral-genetics", "former_names": [ "Spiral Genetics", "Inc." ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/822d8282aa459c05cf652eefd3f059118ec38f90.png", "website": "http://www.spiralgenetics.com", "all_locations": "Seattle, WA, USA", "long_description": "Spiral Genetics (YC W19) makes genomic data mining software to compare large populations of whole human genomes. Our customers are genetics testing companies, governments of countries, and pharma companies. We train our machine learning algorithms to enable large scale comparison of genomes to power novel discoveries, enabling new diagnostics and drugable targets.  ", "one_liner": "Large Scale Genomic Data Mining Software", "team_size": 7, "industry": "Healthcare", "subindustry": "Healthcare -> Healthcare Services", "launched_at": 1548889511, "tags": [ "Machine Learning", "Genomics" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2019", "status": "Inactive", "industries": [ "Healthcare", "Healthcare Services" ], "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": false, "url": "https://www.ycombinator.com/companies/spiral-genetics", "api": "https://yc-oss.github.io/api/batches/winter-2019/spiral-genetics.json" }, { "id": 12531, "name": "Shiru", "slug": "shiru", "former_names": [ "Shiru Bio" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/96f8b3ffa1e973f19d7d140a20c5160d4529a01e.png", "website": "https://www.shiru.com/", "all_locations": "Emeryville, CA, USA", "long_description": "", "one_liner": "Shiru leverages ML to create proteins to feed the world sustainably. ", "team_size": 4, "industry": "Healthcare", "subindustry": "Healthcare -> Industrial Bio", "launched_at": 1555989874, "tags": [ "AI-powered Drug Discovery", "Cellular Agriculture", "Machine Learning" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2019", "status": "Active", "industries": [ "Healthcare", "Industrial Bio" ], "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": false, "url": "https://www.ycombinator.com/companies/shiru", "api": "https://yc-oss.github.io/api/batches/summer-2019/shiru.json" }, { "id": 12572, "name": "Short Story", "slug": "short-story", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/dac97eb3343bbee255adbecf7060b7b9ac299faf.png", "website": "https://shortstorybox.com", "all_locations": "San Francisco, CA, USA", "long_description": "Short Story is a style discovery platform to help petite women find clothes that fit. The average American woman is 5'4\" and petite, yet this remains an enormously underserved segment. We’re a team of curators passionate about finding style, quality, and fit for petite women. Our mission is to remove the “ugh” from the shopping equation and support petite women in telling their stories, stylishly and confidently. ", "one_liner": "Modern ecommerce for petite women", "team_size": 120, "industry": "Consumer", "subindustry": "Consumer -> Apparel and Cosmetics", "launched_at": 1556157792, "tags": [ "Machine Learning", "Marketplace", "E-commerce" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2019", "status": "Active", "industries": [ "Consumer", "Apparel and Cosmetics" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/short-story", "api": "https://yc-oss.github.io/api/batches/summer-2019/short-story.json" }, { "id": 12608, "name": "TRM Labs", "slug": "trm-labs", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/19aa5130e3a0a349d200e7510f0c2fe8439a646f.png", "website": "https://trmlabs.com/", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "TRM is on a mission to build a safer financial system for billions of people. We deliver a blockchain intelligence data platform to financial institutions, crypto companies, and governments to fight cryptocurrency fraud and financial crime. We consider our business — and our profit — as a way to move towards our mission sustainably and at scale. \r\n\r\nJoin our mission ➔ www.trmlabs.com/careers", "one_liner": "TRM is building a safer financial system for billions of people.", "team_size": 250, "industry": "B2B", "subindustry": "B2B -> Security", "launched_at": 1556572947, "tags": [ "Fintech", "Machine Learning", "Crypto / Web3", "Data Engineering" ], "tags_highlighted": [ "Crypto / Web3" ], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2019", "status": "Active", "industries": [ "B2B", "Security" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/trm-labs", "api": "https://yc-oss.github.io/api/batches/summer-2019/trm-labs.json" }, { "id": 12609, "name": "Soteris", "slug": "soteris", "former_names": [ "Soteris", "Inc." ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0e2f7076cd96bbe1cf2655f77eaf4ce963991da6.png", "website": "http://www.soteris.co", "all_locations": "San Francisco, CA, USA", "long_description": "Soteris is a YC-backed company with a four-person team and a great investor base building a first-of-its-kind data ML pricing system for insurance, starting with personal auto.", "one_liner": "We write ML software to more accurately select & price insurance risk.", "team_size": 4, "industry": "Fintech", "subindustry": "Fintech -> Insurance", "launched_at": 1611607083, "tags": [ "Fintech", "Machine Learning", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2019", "status": "Active", "industries": [ "Fintech", "Insurance" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/soteris", "api": "https://yc-oss.github.io/api/batches/summer-2019/soteris.json" }, { "id": 12613, "name": "Dashblock", "slug": "dashblock", "former_names": [ "Datap", "Dashblock (was Datap)" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/51f8695f18bceaae54b2384727e02f76debf98df.png", "website": "https://dashblock.com", "all_locations": "Paris, Île-de-France, France", "long_description": "Dashblock is the easiest way to access websites programmatically and collect structured data.", "one_liner": "Turn any website into an API", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1556596578, "tags": [ "Developer Tools", "Machine Learning", "Robotic Process Automation" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2019", "status": "Inactive", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "France", "Europe", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/dashblock", "api": "https://yc-oss.github.io/api/batches/summer-2019/dashblock.json" }, { "id": 12660, "name": "Rosebud AI", "slug": "rosebud-ai", "former_names": [ "Rosebud AI", "Rosebud AI : PixelVibe", "Rosebud AI Gamemaker" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0669f9afff20bf775d9b001b89480415cdb33109.png", "website": "http://rosebud.ai", "all_locations": "San Francisco, CA, USA", "long_description": "Rosebud lets anyone vibe code games. No coding skills required. \r\n", "one_liner": "Vibe code games. ", "team_size": 10, "industry": "Consumer", "subindustry": "Consumer", "launched_at": 1584125566, "tags": [ "Developer Tools", "Generative AI", "Machine Learning", "Gaming", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2019", "status": "Active", "industries": [ "Consumer" ], "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": false, "url": "https://www.ycombinator.com/companies/rosebud-ai", "api": "https://yc-oss.github.io/api/batches/summer-2019/rosebud-ai.json" }, { "id": 12724, "name": "Chaos Genius", "slug": "chaos-genius", "former_names": [ "GoodHealth" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c4d680463f8fee3408726becdad9bccd8e14c8a1.png", "website": "http://www.chaosgenius.io", "all_locations": "Bengaluru, KA, India; San Francisco, CA, USA; Remote", "long_description": "Chaos Genius is a DataOps Observability platform for Snowflake. Enable Snowflake Observability to reduce Snowflake costs and optimize query performance.", "one_liner": "DataOps Observability Platform for Snowflake", "team_size": 10, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1600455323, "tags": [ "Cloud Workload Protection", "Machine Learning", "Analytics", "Open Source", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2020", "status": "Acquired", "industries": [ "B2B", "Analytics" ], "regions": [ "India", "United States of America", "South Asia", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/chaos-genius", "api": "https://yc-oss.github.io/api/batches/winter-2020/chaos-genius.json" }, { "id": 12832, "name": "PredictLeads", "slug": "predictleads", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/1b1dfbe12c8d51212415378b6233142fd20817a2.png", "website": "https://predictleads.com", "all_locations": "Ljubljana, Ljubljana, Slovenia; Remote", "long_description": "PredictLeads provides structured data on companies. Using our data Sales teams can discover companies in their buy mode, Quant funds know when to perform trades and VCs can predict when a startup will be raising a new round. PredictLeads cuts down their market research time. Our goal is to structure the sea of public information on companies. ", "one_liner": "Best in class company intelligence data. ", "team_size": 37, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1559182380, "tags": [ "Machine Learning" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2019", "status": "Active", "industries": [ "B2B", "Analytics" ], "regions": [ "Slovenia", "Europe", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/predictleads", "api": "https://yc-oss.github.io/api/batches/summer-2019/predictleads.json" }, { "id": 12860, "name": "Deepnote", "slug": "deepnote", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/1d3472a27c98c1e565e5925980d8068da5917ef1.png", "website": "https://www.deepnote.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Data science is as much a scientific and creative process as it is an engineering one. It involves working together, failing, learning and going back to the drawing board. Data scientists are explorers. To make data projects successful, we need tools that are both powerful and easy to use. Tools that help us collaborate and share our work in an engaging way. Tools that make data science fun again.\r\n\r\nAt Deepnote, we’re building a new standard in data tooling — a notebook that brings teams together to explore, analyze and present data from start to finish.\r\n\r\nWe are building tools for explorers. Join us.", "one_liner": "A better data science notebook.", "team_size": 0, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1581020768, "tags": [ "Developer Tools", "Machine Learning" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2019", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/deepnote", "api": "https://yc-oss.github.io/api/batches/summer-2019/deepnote.json" }, { "id": 13081, "name": "Abalone Bio", "slug": "abalone-bio", "former_names": [ "Abalone Bio", "Inc" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e9f1d41bc9bfabd8ecaa9963112dc25b23472f0a.png", "website": "https://www.abalonebio.com", "all_locations": "San Francisco, CA, USA", "long_description": "Abalone Bio is tackling challenging undrugged targets underlying diseases affecting millions, focusing first cell-specific antibody drugs to treat obesity and metabolic disease without the GI side effects that cause 25% of GLP-1 drug patients to quit after 1 year. \r\n\r\n+ High throughput experimental measurement uniquely leverages AI/ML: We’ve engineered cells to measure antibodies for pharmacological activity, not just structure or binding like others, 100 million at a time, 100X+ the throughput of others. With our large, proprietary activity datasets, we uniquely leverage ML to both unlock the discovery of rare hits and generate optimized hits for challenging targets, starting with G-protein coupled receptors (GPCRs)\r\n\r\n+ Proven success: We have developed antibody agonists (activators) for 2 out of the 8 G-protein coupled receptors ever drugged by biotech.\r\n\r\n+ Pharma traction: We’ve secured 3 partnerships with $3M in revenue and $125M in downstream value. \r\n\r\n+ Externally validated science: We’ve been awarded $7M in non-dilutive grant funding for platform and program development.", "one_liner": "We create activating antibodies to treat diseases others can’t.", "team_size": 14, "industry": "Healthcare", "subindustry": "Healthcare -> Drug Discovery and Delivery", "launched_at": 1583908314, "tags": [ "Machine Learning", "Synthetic Biology", "Therapeutics", "Drug discovery" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2020", "status": "Active", "industries": [ "Healthcare", "Drug Discovery and Delivery" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/abalone-bio", "api": "https://yc-oss.github.io/api/batches/winter-2020/abalone-bio.json" }, { "id": 13098, "name": "MindsDB", "slug": "mindsdb", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2d1835a1b83e15542370853a52f30681b79212aa.png", "website": "https://www.mindsdb.com/", "all_locations": "San Francisco, CA, USA", "long_description": "MindsDB is a fast-growing AI startup headquartered in San Francisco, California. As a leading innovator bringing AI and Data together, our passion is empowering companies to easily build AI capabilities that can Think, Understand and Orchestrate: enabling teams to move from prototyping & experimentation to production in a fast & scalable way.\r\n\r\nMindsDB was founded in 2017 by Adam Carrigan and Jorge Torres, inspired by Ian M. Banks's Culture series, in which super AI systems called Minds collaborate with other forms of life to accomplish incredible goals. Starting as an Open-Source project, MindsDB has grown to be one of the most widely used AI-Data platforms in the world, with a growing community and more than 700 contributor developers from every corner of the globe.\r\n\r\nWe are backed with over $55M in funding from Mayfield, Benchmark, YCombinator, and nVidia. MindsDB is also recognized by Forbes as one of America's most promising AI companies (2021) and by Gartner as a Cool Vendor for Data and AI (2022).", "one_liner": "Connect, Unify, Respond to any data, anywhere with human-level…", "team_size": 41, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1584047879, "tags": [ "Developer Tools", "Machine Learning", "Open Source", "Enterprise Software", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2020", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/mindsdb", "api": "https://yc-oss.github.io/api/batches/winter-2020/mindsdb.json" }, { "id": 13112, "name": "Orbiter", "slug": "orbiter", "former_names": [ "In Good Company", "Orbiter (by In Good Company)" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/81f62b42761b3850734765fe84470eb84ad0de1b.png", "website": "http://www.getorbiter.com", "all_locations": "San Francisco, CA, USA", "long_description": "Orbiter’s ML models monitor business metrics automatically and send alerts when those metrics experience abnormal drops or spikes. Any company can onboard in less than five minutes with just their database credentials - no engineering required. ", "one_liner": "ML models automatically monitor business performance", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1584147330, "tags": [ "Machine Learning", "SaaS", "B2B" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2020", "status": "Inactive", "industries": [ "B2B", "Analytics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/orbiter", "api": "https://yc-oss.github.io/api/batches/winter-2020/orbiter.json" }, { "id": 13121, "name": "Handoff", "slug": "handoff", "former_names": [ "1build" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7c28f259776f3ae753c7e797a8482d385f032fef.png", "website": "https://www.handoff.ai/", "all_locations": "Austin, TX, USA", "long_description": "Handoff creates instant construction estimates and automates business operations for contractors with AI.\r\n\r\nUsing generative AI technology and access to localized construction costs, Handoff provides remodelers with a fast, accurate, and intuitive way to create construction cost estimates in minutes.", "one_liner": "AI estimator & agent for remodelers.", "team_size": 20, "industry": "Real Estate and Construction", "subindustry": "Real Estate and Construction -> Construction", "launched_at": 1578363908, "tags": [ "Machine Learning", "Construction", "B2B", "Proptech", "API" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2020", "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": false, "url": "https://www.ycombinator.com/companies/handoff", "api": "https://yc-oss.github.io/api/batches/winter-2020/handoff.json" }, { "id": 13147, "name": "Replicate", "slug": "replicate", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/256be79b4f9ac851425e3bf2a60af5ae33ca72ba.png", "website": "https://replicate.com", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "Run machine learning models in the cloud", "team_size": 36, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1647283616, "tags": [ "Developer Tools", "Machine Learning", "Community", "Open Source", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2020", "status": "Acquired", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/replicate", "api": "https://yc-oss.github.io/api/batches/winter-2020/replicate.json" }, { "id": 13161, "name": "Clayboard", "slug": "clayboard", "former_names": [ "Modulo", "Slingshow", "Clayboard", "Pathspace" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/95390ad4c8c9633ca7bffdf9af67b0ae984c5cd9.png", "website": "http://clayboard.com", "all_locations": "New York, NY, USA; Remote", "long_description": "", "one_liner": "Create active, collaborative learning experiences ", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Productivity", "launched_at": 1660775581, "tags": [ "Machine Learning", "SaaS", "B2B", "Productivity", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2020", "status": "Inactive", "industries": [ "B2B", "Productivity" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/clayboard", "api": "https://yc-oss.github.io/api/batches/winter-2020/clayboard.json" }, { "id": 13209, "name": "Scout", "slug": "scout", "former_names": [ "Probe", "Croft", "Scout", "CRONCH!", "Cronch", "Munchies" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d57f772c91256fa7714735af9ad73b3b7c3b1648.png", "website": "https://www.scout.ml/", "all_locations": "Berkeley, CA, USA", "long_description": "", "one_liner": "Dead simple CI/CD for ML teams", "team_size": 1, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1584176238, "tags": [ "Machine Learning", "DevOps" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2020", "status": "Inactive", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/scout", "api": "https://yc-oss.github.io/api/batches/winter-2020/scout.json" }, { "id": 13306, "name": "Trident Bioscience", "slug": "trident-bioscience", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/40f8f694b19393c459f2134d2ca7da347ce9ce08.png", "website": "https://trident.bio", "all_locations": "Mountain View, CA, USA; Remote", "long_description": "Trident Bioscience builds tools to expedite the discovery and optimization of useful proteins. Our technology first applies predictive models of protein structure and function to generate sets of potentially active protein sequences. We then apply our state-of-the-art sequence optimization algorithm to design gene libraries capable of testing these candidates extremely quickly and affordably. By combining these technologies, we're closing the design-build-test loop of protein optimization and cutting the total cycle time to help bring synthetic proteins to market faster than ever before.", "one_liner": "Accelerating protein engineering.", "team_size": 1, "industry": "Healthcare", "subindustry": "Healthcare -> Drug Discovery and Delivery", "launched_at": 1599762607, "tags": [ "Hard Tech", "Machine Learning" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2020", "status": "Inactive", "industries": [ "Healthcare", "Drug Discovery and Delivery" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/trident-bioscience", "api": "https://yc-oss.github.io/api/batches/summer-2020/trident-bioscience.json" }, { "id": 13332, "name": "PostEra", "slug": "postera", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6f01f8ef89abde929fff3e9924c177906b679828.png", "website": "https://postera.ai/", "all_locations": "Boston, MA, USA", "long_description": "PostEra is building a modern 21st century biopharma. We're using our advances in machine learning to accelerate Medicinal Chemistry and bring more cures to patients. PostEra advances small molecule programs through partnerships with biopharma while also advancing its own internal pipeline. We've raised $26M from top investors and closed $1Bn in AI partnerships, signing multi-year agreements with Amgen, Pfizer and the NIH. PostEra also launched and led the world's largest open-science drug discovery effort; COVID Moonshot.", "one_liner": "Medicinal Chemistry powered by Machine Learning", "team_size": 40, "industry": "Healthcare", "subindustry": "Healthcare -> Drug Discovery and Delivery", "launched_at": 1584128465, "tags": [ "AI-powered Drug Discovery", "Machine Learning", "COVID-19" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2020", "status": "Active", "industries": [ "Healthcare", "Drug Discovery and Delivery" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/postera", "api": "https://yc-oss.github.io/api/batches/winter-2020/postera.json" }, { "id": 13349, "name": "SprintAI", "slug": "sprintai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/88ed649d4ffefdc8e5652f12e5915dd242bed4ff.png", "website": "https://www.getsprint.ai/", "all_locations": "Bengaluru, KA, India", "long_description": "AI Platform that powers the brands & retailers of tomorrow. SprintAI helps the brands in better decision making & automating various processes in Inventory Management & Omnichannel Fulfilment.", "one_liner": "AI-led platform for inventory and fulfillment optimization", "team_size": 10, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1599935349, "tags": [ "Machine Learning", "SaaS", "Retail Tech" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2020", "status": "Inactive", "industries": [ "B2B", "Retail" ], "regions": [ "India", "South Asia" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/sprintai", "api": "https://yc-oss.github.io/api/batches/winter-2020/sprintai.json" }, { "id": 13405, "name": "Zumo Labs", "slug": "zumo-labs", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a53f5d4e5c3734ef65ff0417ad276ccdd20cafdd.png", "website": "https://zumolabs.ai/", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "At Zumo Labs, we generate synthetic training data for computer vision models.\r\n\r\nComputer vision is the essential technology that powers the products of the future: autonomous vehicles, smart retail, robotics, smart fitness, security and vision-based analytics. These algorithms require huge amounts of training data. This data is currently collected and labeled manually; a slow, imprecise, expensive process that is rife with bias and privacy issues. \r\n\r\nZumo Labs solves all of these problems (and more!) by creating feature rich synthetic training data in the cloud: cheaper, faster to generate and iterate on, covers all the edge cases, and has no bias or privacy issues. \r\n", "one_liner": "We generate synthetic data for computer vision models.", "team_size": 7, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1584126960, "tags": [ "Artificial Intelligence", "Machine Learning", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2020", "status": "Inactive", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/zumo-labs", "api": "https://yc-oss.github.io/api/batches/winter-2020/zumo-labs.json" }, { "id": 13413, "name": "adyn", "slug": "adyn", "former_names": [ "ADYN", "Adyn" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/01db92cbf9e971ce4967a2173b419590716a0fb8.png", "website": "https://adyn.com", "all_locations": "Seattle, WA, USA; Remote", "long_description": "", "one_liner": "The first test designed to prevent birth control side effects", "team_size": 7, "industry": "Healthcare", "subindustry": "Healthcare -> Consumer Health and Wellness", "launched_at": 1599762606, "tags": [ "Fertility Tech", "Machine Learning", "Consumer Health Services" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2020", "status": "Active", "industries": [ "Healthcare", "Consumer Health and Wellness" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/adyn", "api": "https://yc-oss.github.io/api/batches/summer-2020/adyn.json" }, { "id": 13472, "name": "Oda", "slug": "oda", "former_names": [ "Zappeal", "Oda", "Oda (was Zappeal)" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b282b3863a1e15b0e08e9b79cf5ac972840f5523.png", "website": "https://www.odastudio.ai/?ref=yc", "all_locations": "Los Angeles, CA, USA; Remote", "long_description": "Oda is an AI agent for home design. Homebuyers and renters alike can use Oda to discover their interior design preferences, apply those preferences to their new home, and then find the best furniture, décor, and appliances aggregated from many different online retailers. Oda distributes its product to homebuyers and renters through partnerships with real estate companies and platforms. Real estate partners add Oda AI iFrames to their websites to showcase listed homes with AI-generated designs. Each AI iFrame is directly linked to an Oda board, allowing consumers to transition from an iFrame to Oda to further personalize the designs and create their dream home.", "one_liner": "AI Agent for Home Design", "team_size": 9, "industry": "B2B", "subindustry": "B2B -> Marketing", "launched_at": 1584035955, "tags": [ "Machine Learning", "Computer Vision", "E-commerce", "AI Assistant" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2020", "status": "Active", "industries": [ "B2B", "Marketing" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/oda", "api": "https://yc-oss.github.io/api/batches/winter-2020/oda.json" }, { "id": 13522, "name": "Atmo", "slug": "atmo", "former_names": [ "Froglabs", "Atmo", "Atmo", "Inc.", "Atmo AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/081c3bd5a2080215bbdaaea1ede5e0d87e553390.png", "website": "http://atmo.ai", "all_locations": "San Francisco, CA, USA; Berkeley, CA, USA", "long_description": "Atmo is the leading company bringing artificial intelligence to meteorology for governments, militaries, and corporations. Atmo builds state-of-the-art AI weather forecasts that are up to 50% more accurate, 10x more detailed, and run 40,000x faster. Atmo has rapidly become the trusted AI meteorology partner for high-stakes users worldwide, such as the US Department of Defense, top aerospace companies, the Philippines, and the United Nations. Today, Atmo forecasting systems protect vital infrastructure and enhance economic activity for its partners, including disaster response, renewable energy, agriculture, transportation, and national security.", "one_liner": "Ultra-precise AI weather forecasting.", "team_size": 10, "industry": "Industrials", "subindustry": "Industrials", "launched_at": 1672960029, "tags": [ "Artificial Intelligence", "Machine Learning", "Weather", "Climate", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2020", "status": "Active", "industries": [ "Industrials" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/atmo", "api": "https://yc-oss.github.io/api/batches/winter-2020/atmo.json" }, { "id": 13525, "name": "PowerX", "slug": "powerx", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2eeb3dc369d1614059e4c225bfc4698c3ad41318.png", "website": "http://www.powerx.co", "all_locations": "New York, NY, USA", "long_description": "PowerX AI powered sensors create proprietary data to save corporations 30% or more in energy, water and emissions. ", "one_liner": "AI powered sensors that save energy, water and emissions", "team_size": 20, "industry": "Industrials", "subindustry": "Industrials -> Climate", "launched_at": 1650847602, "tags": [ "Machine Learning", "IoT", "Climate", "Energy" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2020", "status": "Acquired", "industries": [ "Industrials", "Climate" ], "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": false, "url": "https://www.ycombinator.com/companies/powerx", "api": "https://yc-oss.github.io/api/batches/winter-2020/powerx.json" }, { "id": 21769, "name": "Roboflow", "slug": "roboflow", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ba0036069bd338a4c6188cb137722d8f584d0016.png", "website": "https://roboflow.com", "all_locations": "San Francisco, CA, USA", "long_description": "Roboflow enables developers to make the world programmable.\r\n\r\nUse our tools to build better datasets (collect image, video / annotate), models (foundation and fine tuned small models), and deployments (self hosted, edge, APIs, SDKs) for computer vision. Over 250k developers, including those from over half the Fortune 100, build with our open source and hosted tools.\r\n\r\nBuild with us: https://app.roboflow.com\r\nHack with us: https://roboflow.slab.com/public/posts/roboflow-hackathons-external-u478m1iz\r\nWork with us: roboflow.com/careers\r\n", "one_liner": "🖼️ Give your software the sense of sight.", "team_size": 100, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1598130074, "tags": [ "Developer Tools", "Machine Learning", "Computer Vision", "Enterprise", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2020", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": true, "url": "https://www.ycombinator.com/companies/roboflow", "api": "https://yc-oss.github.io/api/batches/summer-2020/roboflow.json" }, { "id": 21771, "name": "Bandit ML", "slug": "bandit-ml", "former_names": [ "Bandit ML", "Iron Plans" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/efb807f0ae51b0f29f5d99ad5a5fa1d542f7a714.png", "website": "https://www.banditml.com/", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "", "one_liner": "Bandit ML builds machine learning tools for e-commerce companies.", "team_size": 4, "industry": "B2B", "subindustry": "B2B", "launched_at": 1599762607, "tags": [ "Machine Learning", "SaaS", "E-commerce" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2020", "status": "Acquired", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/bandit-ml", "api": "https://yc-oss.github.io/api/batches/summer-2020/bandit-ml.json" }, { "id": 21784, "name": "Blue Onion", "slug": "blue-onion", "former_names": [ "Finance Weaver", "Blue Onion Labs" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ade6715edaa57cf94e8649919bf33b3022c27458.png", "website": "https://www.blueonion.ai/", "all_locations": "New York, NY, USA", "long_description": "Blue Onion is the data backbone for tomorrow’s AI-powered finance teams — a subledger platform that transforms messy, scattered transactions into clean, reconciled, and automation-ready data. ", "one_liner": "Financial data layer for AI-powered finance and accounting", "team_size": 27, "industry": "B2B", "subindustry": "B2B -> Finance and Accounting", "launched_at": 1597935729, "tags": [ "Artificial Intelligence", "Machine Learning", "Finance" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2020", "status": "Active", "industries": [ "B2B", "Finance and Accounting" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/blue-onion", "api": "https://yc-oss.github.io/api/batches/summer-2020/blue-onion.json" }, { "id": 21857, "name": "Hypotenuse AI", "slug": "hypotenuse-ai", "former_names": [ "Hypotenuse" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2e709f345af0105b77cf1718bbd11559604606b2.png", "website": "https://hypotenuse.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Hypotenuse AI is an AI-native platform for managing, creating and optimizing your ecommerce product data and content. Fortune 500 ecommerce brands use us to enrich their product data, edit images, and create high-quality product copy at scale to make their teams 10x faster.", "one_liner": "AI-native Operating System for Enterprise Ecommerce Companies", "team_size": 15, "industry": "B2B", "subindustry": "B2B", "launched_at": 1597658049, "tags": [ "Generative AI", "Machine Learning", "E-commerce", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2020", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/hypotenuse-ai", "api": "https://yc-oss.github.io/api/batches/summer-2020/hypotenuse-ai.json" }, { "id": 21894, "name": "Humanloop", "slug": "humanloop", "former_names": [ "humanlupe" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/36780ef46af5eeec8e865ac191d6d27af56ff936.png", "website": "https://humanloop.com", "all_locations": "San Francisco, CA, USA", "long_description": "Humanloop is the LLM evals platform for enterprises. Teams at Gusto, Vanta and Duolingo use Humanloop to ship reliable AI products. We enable you to adopt best practices for prompt management, evaluation and observability.", "one_liner": "Humanloop is the LLM evals platform for enterprises. ", "team_size": 14, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1598299135, "tags": [ "Generative AI", "Machine Learning", "SaaS", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2020", "status": "Acquired", "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": false, "url": "https://www.ycombinator.com/companies/humanloop", "api": "https://yc-oss.github.io/api/batches/summer-2020/humanloop.json" }, { "id": 21902, "name": "Blissway", "slug": "blissway", "former_names": [ "Blissway", "BLISSWAY" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/41fb64af0fedc089c69c9af82b6619dfece6ffd3.png", "website": "https://www.blissway.com/", "all_locations": "Denver, CO, USA", "long_description": "", "one_liner": "The tolling industry’s prime tech infrastructure", "team_size": 22, "industry": "Government", "subindustry": "Government", "launched_at": 1597711066, "tags": [ "Hardware", "Machine Learning", "SaaS", "IoT", "Transportation" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2020", "status": "Active", "industries": [ "Government" ], "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": false, "url": "https://www.ycombinator.com/companies/blissway", "api": "https://yc-oss.github.io/api/batches/summer-2020/blissway.json" }, { "id": 22008, "name": "Aquarium Learning", "slug": "aquarium-learning", "former_names": [ "Aquarium" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a1aee7c2b8c6ada91b60405fb42ae026b6093676.png", "website": "https://www.aquariumlearning.com/", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "ML models are only as good as the datasets they're trained on, and that means that most improvement to model performance comes from improvement to the quality and diversity of their datasets.\r\n\r\nOur tooling makes it easy for ML teams to find anomalies + failure patterns in their datasets and fix these problems by editing / adding the right data. So the next time you retrain your model, it just gets better.", "one_liner": "We help ML teams improve their models by improving their datasets", "team_size": 12, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1597122957, "tags": [ "Deep Learning", "Developer Tools", "Generative AI", "Machine Learning", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2020", "status": "Acquired", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/aquarium-learning", "api": "https://yc-oss.github.io/api/batches/summer-2020/aquarium-learning.json" }, { "id": 22032, "name": "Intelligent", "slug": "intelligent", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b6ed23c59f075554e641d7d208bcb56abf6880d1.png", "website": "https://www.intelligent.services/", "all_locations": "San Francisco, CA, USA; Los Altos, CA, USA; Remote", "long_description": "We help businesses cut operational costs, while still exceeding customer expectations.\r\nMost businesses are consistently under- or over-staffed, which either damages customer experience or leaves money on the table (by unnecessarily increasing staffing costs). Granular, high-accuracy demand forecasting solves this issue by allowing businesses to align resources to exactly meet demand. \r\nOur demand forecasting as a service, brings simplicity & precision to this often complex and error-prone process, and quickly provides business users the right answers to run their operations. ", "one_liner": "Demand Forecasting as a Service ", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Sales", "launched_at": 1626231553, "tags": [ "Machine Learning", "SaaS", "B2B" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2020", "status": "Inactive", "industries": [ "B2B", "Sales" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/intelligent", "api": "https://yc-oss.github.io/api/batches/summer-2020/intelligent.json" }, { "id": 22124, "name": "Taktile", "slug": "taktile", "former_names": [ "Taktile", "Inc." ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fda6209e5ce1deac3dd962c779d7c375cd750a5a.png", "website": "http://www.taktile.com", "all_locations": "Berlin, Berlin, Germany", "long_description": "Taktile empowers financial institutions to quickly unlock AI-driven efficiencies across the customer lifecycle, reducing manual work while optimizing decisions and enabling seamless end-user experiences.\r\n\r\nBuilt for highly regulated environments, our agentic decision platform combines the speed of AI automation with the oversight of human judgement—so you can safely approve customers, catch more fraud, and stay compliant.\r\n\r\nWe power AI transformation from offices in NYC, London, Berlin, and Iasi, and have raised $80M in capital from top investors including Index Ventures, Tiger Global, Balderton Capital and Y Combinator.\r\n\r\nJoin over 200 leading financial institutions who rely on Taktile to enable faster, more intelligent decisions from onboarding to credit, AML, compliance, and fraud.", "one_liner": "Transform your decision-making with reliable AI agents in weeks, not…", "team_size": 150, "industry": "B2B", "subindustry": "B2B", "launched_at": 1638102391, "tags": [ "Artificial Intelligence", "Fintech", "Machine Learning", "Enterprise Software" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2020", "status": "Active", "industries": [ "B2B" ], "regions": [ "Germany", "Europe", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/taktile", "api": "https://yc-oss.github.io/api/batches/summer-2020/taktile.json" }, { "id": 22294, "name": "Clau", "slug": "clau", "former_names": [ "Flat" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/27f510d61e3fb71a7cb032342d796e9d330fa8a5.png", "website": "https://clau.com", "all_locations": "Mexico City, CDMX, Mexico", "long_description": "We are the real estate super app for Mexico combining a marketplace with over 20,000 properties, a crm for brokers, financial services including a mortgage brokerage, renovations and the leading data layer for residential real estate in the country.", "one_liner": "The real estate superapp for Mexico", "team_size": 90, "industry": "Real Estate and Construction", "subindustry": "Real Estate and Construction -> Housing and Real Estate", "launched_at": 1595778564, "tags": [ "Fintech", "Machine Learning", "Marketplace", "Proptech" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2020", "status": "Active", "industries": [ "Real Estate and Construction", "Housing and Real Estate" ], "regions": [ "Mexico", "Latin America", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/clau", "api": "https://yc-oss.github.io/api/batches/summer-2020/clau.json" }, { "id": 22301, "name": "Quell", "slug": "quell", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/133bcd99ce642360941054c47cfd64820d35818f.png", "website": "https://playquell.com", "all_locations": "London, England, United Kingdom", "long_description": "Quell is an immersive fitness game where players get fit fighting their way through a fantasy world. Our low-cost wearable uses smart resistance bands to guide you through an exciting, effective combat workout at home. We’re Peloton meets gaming at 1/10th of the price\r\n", "one_liner": "Get fit fighting your way through a fantasy world.", "team_size": 40, "industry": "Consumer", "subindustry": "Consumer -> Consumer Electronics", "launched_at": 1597757414, "tags": [ "Hardware", "Machine Learning", "Sports Tech", "Fitness", "Gaming" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2020", "status": "Inactive", "industries": [ "Consumer", "Consumer Electronics" ], "regions": [ "United Kingdom", "Europe", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/quell", "api": "https://yc-oss.github.io/api/batches/summer-2020/quell.json" }, { "id": 22664, "name": "SBX Robotics", "slug": "sbx-robotics", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/511a67e1066575bd8304628248a6a9307430e18f.png", "website": "https://www.sbxrobotics.com/", "all_locations": "Toronto, ON, Canada", "long_description": "SBX Robotics generates synthetic data that teaches robots to see. We use simulation software to create training data 10x faster and cheaper than annotation services or in-house teams. \r\n\r\nInstead of being blocked on data, our clients send 25 images from their robot’s camera, and receive 25,000 perfectly labeled synthetic training images. SBX data is ready to be used by deep learning computer vision models. ", "one_liner": "Synthetic data for better vision.", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1616603536, "tags": [ "Artificial Intelligence", "Machine Learning", "Robotics", "Computer Vision", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2021", "status": "Inactive", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "Canada", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/sbx-robotics", "api": "https://yc-oss.github.io/api/batches/winter-2021/sbx-robotics.json" }, { "id": 22744, "name": "Encord", "slug": "encord", "former_names": [ "Cord Technologies", "Cord" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fd8270caf52cdd1093c290cba2176776fc6c3460.png", "website": "https://encord.com", "all_locations": "London, England, United Kingdom", "long_description": "Encord is the data layer for physical AI. We're how the world's most ambitious AI teams turn messy, multimodal data into production systems - from humanoid robots to autonomous vehicles to smart infrastructure. 300+ teams including Toyota, Skydio, and Maxar rely on Encord to curate, manage, and align the data their models actually need. $110M raised. San Francisco, New York, and London.", "one_liner": "The data layer for physical AI", "team_size": 150, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1613768381, "tags": [ "Machine Learning", "Robotics", "Enterprise Software", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2021", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United Kingdom", "Europe" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/encord", "api": "https://yc-oss.github.io/api/batches/winter-2021/encord.json" }, { "id": 22778, "name": "HyperGlue", "slug": "hyperglue", "former_names": [ "Gemini AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a16e421a067f9b41e80bcc361abe747f87cfe040.png", "website": "https://www.hyperglue.com", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "There is more text generated than any one person or team can read. A single product team can not hope to sift through their thousands of feedback responses and determine the signal amongst the noise.\r\n\r\nHyperglue enables operators, product managers, and analysts to instantly access machine intelligence on large text datasets without the engineering or headcount overhead required to deploy natural language AI within their business.\r\n", "one_liner": "Business intelligence on text", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1651612188, "tags": [ "Machine Learning", "B2B", "NLP" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2021", "status": "Acquired", "industries": [ "B2B", "Analytics" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/hyperglue", "api": "https://yc-oss.github.io/api/batches/winter-2021/hyperglue.json" }, { "id": 22787, "name": "Expent Inc", "slug": "expent-inc", "former_names": [ "Expent" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a78fb173a701d08d55012208b7663e2dd99cb2be.png", "website": "https://www.expent.ai/", "all_locations": "Fremont, CA, USA; Remote", "long_description": "Expent is a marketplace that accelerates software procurement for teams, while giving organizations control over the entire purchasing process.", "one_liner": "Procure the right software 5x faster", "team_size": 10, "industry": "B2B", "subindustry": "B2B -> Operations", "launched_at": 1615171972, "tags": [ "Machine Learning", "SaaS", "B2B", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2021", "status": "Active", "industries": [ "B2B", "Operations" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/expent-inc", "api": "https://yc-oss.github.io/api/batches/winter-2021/expent-inc.json" }, { "id": 22827, "name": "Promoted.ai", "slug": "promoted", "former_names": [ "Promoted.ai", "Promoted", "Promoted.ai", "Promoted" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/bd28656a2bd5b2cc24a2d0577bedc594f2e0ffe7.png", "website": "http://www.promoted.ai", "all_locations": "Seattle, WA, USA", "long_description": "Promoted.ai unifies search, native ads, and feed ranking for online marketplaces and scaled e-commerce apps to dramatically improve relevance (and revenue) using AI. We are a team of ex-Google, Meta, and Pinterest ads engineers. Our customers are publicly traded and late-stage marketplace companies like Eventbrite, Upwork, and Outschool. Our mission is to connect every buyer and seller.", "one_liner": "Dramatically better search and ads for marketplaces", "team_size": 12, "industry": "B2B", "subindustry": "B2B", "launched_at": 1611343241, "tags": [ "Machine Learning", "Marketplace", "B2B", "E-commerce" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2021", "status": "Acquired", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/promoted", "api": "https://yc-oss.github.io/api/batches/winter-2021/promoted.json" }, { "id": 22944, "name": "Invoid", "slug": "invoid", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d2e3c9b022819f2037f731e715774474465db9c7.png", "website": "https://www.invoid.co/", "all_locations": "Gurugram, HR, India", "long_description": "Invoid currently processes more than 5 million KYC’s/ month and works with over 35 companies in India, including some of the leading banks, fintechs, investment platforms & shared economy companies. Using our solution, companies see onboarding speed increase by 5x and costs reduce by >80%.", "one_liner": "Create identity verification workflows the way you want", "team_size": 15, "industry": "B2B", "subindustry": "B2B", "launched_at": 1614668651, "tags": [ "Machine Learning", "SaaS", "B2B" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2021", "status": "Inactive", "industries": [ "B2B" ], "regions": [ "India", "South Asia", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/invoid", "api": "https://yc-oss.github.io/api/batches/winter-2021/invoid.json" }, { "id": 23050, "name": "Milk Video", "slug": "milk-video", "former_names": [ "Milk video", "Milk" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/61e5d39837f4f0d3298e7759e0d00633fe06a920.png", "website": "https://milkvideo.com", "all_locations": "New York, NY, USA", "long_description": "Milk Video is a video marketing platform that simplifies short-form video creation for marketers. \r\n\r\nAnyone can collect, clip, and ship video content such as customer testimonials, employee testimonials, and thought pieces in minutes.", "one_liner": "Create video testimonials with a link", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Marketing", "launched_at": 1614230111, "tags": [ "Machine Learning", "Design Tools", "Video" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2021", "status": "Inactive", "industries": [ "B2B", "Marketing" ], "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": false, "url": "https://www.ycombinator.com/companies/milk-video", "api": "https://yc-oss.github.io/api/batches/winter-2021/milk-video.json" }, { "id": 23056, "name": "Simplify", "slug": "simplify", "former_names": [ "Simplify Jobs" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/89afe9465849b0bb7b72a18155538d4f3125693e.png", "website": "https://simplify.jobs/", "all_locations": "San Francisco, CA, USA", "long_description": "Simplify is building the AI-enabled infrastructure to power the next generation of hiring – reimagining how people discover and secure their next career opportunity. We believe that everyone deserves an all-star talent agent helping them plan, manage, and accomplish their career goals, no matter their background, location, or education.\r\n\r\nThrough our flagship product, Copilot, we've helped over 1M+ job seekers discover and apply to over 100 million jobs - and we've done this with a tight-knit team of just 7 people. We're rapidly expanding on both the candidate and recruiter fronts, focused on our vision of building a common app and personal AI agent for your career.\r\n\r\nBacked by top-tier investors including Craft and YCombinator, we're a mission-driven team working to democratize the job search and disrupt the way hiring works today.", "one_liner": "Helping a billion people build their dream career", "team_size": 5, "industry": "Consumer", "subindustry": "Consumer -> Job and Career Services", "launched_at": 1616620834, "tags": [ "Generative AI", "Machine Learning", "Marketplace", "Recruiting" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2021", "status": "Active", "industries": [ "Consumer", "Job and Career Services" ], "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": false, "url": "https://www.ycombinator.com/companies/simplify", "api": "https://yc-oss.github.io/api/batches/winter-2021/simplify.json" }, { "id": 23430, "name": "Mystic", "slug": "mystic", "former_names": [ "Neuro AI", "Neuro", "Mystic", "Mystic AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f860b32ddb9b39b9b1ae8c22f0c17f140dc5e9d4.png", "website": "https://www.mystic.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Mystic’s platform allows companies to easily and reliably deploy ML models on our serverless cloud or on their own infrastructure without requiring a team of MLOps engineers. With our Python SDK, data-scientists immediately get an endpoint from their own model, or any open-source models.\r\nOnce uploaded, our platform handles routing, multi-cloud scaling, caching, GPU optimization and other features to provide the ultimate ML inference platform.", "one_liner": "Low latency API to run and deploy ML models", "team_size": 11, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1614265935, "tags": [ "AIOps", "Artificial Intelligence", "Developer Tools", "Machine Learning" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2021", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/mystic", "api": "https://yc-oss.github.io/api/batches/winter-2021/mystic.json" }, { "id": 23610, "name": "PipeBio", "slug": "pipebio", "former_names": [ "Pipe|bio" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b6fb87df991642ec6fcea487e6c1e54683c1319f.png", "website": "https://pipebio.com", "all_locations": "Aarhus, Denmark; Remote", "long_description": "Pipe|bio is the bioinformatics cloud for antibody / peptide screening & drug development.\r\n\r\nWe enable scientists to analyze and manage massive amounts of DNA sequencing data themselves without the need for bioinformaticians or programmers. The software is highly visual and enables you to overlay and filter information from different sources across your organization; be it assay data, sequence data or other process metadata. Insights from past results can be used to guide new experiments and they get better as you upload more and more data. Team leads get oversight and these capabilities combined empower organizations to find better drugs, faster.\r\n\r\nWe believe that science moves faster when scientists can curate and analyse their own data.", "one_liner": "PipeBio is a SaaS bioinformatics platform to develop antibody drugs.", "team_size": 10, "industry": "Healthcare", "subindustry": "Healthcare -> Therapeutics", "launched_at": 1614718514, "tags": [ "AI-powered Drug Discovery", "Machine Learning", "SaaS" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2021", "status": "Acquired", "industries": [ "Healthcare", "Therapeutics" ], "regions": [ "Denmark", "Europe", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/pipebio", "api": "https://yc-oss.github.io/api/batches/winter-2021/pipebio.json" }, { "id": 23781, "name": "Openlayer", "slug": "openlayer", "former_names": [ "Unbox", "OpenLayer" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/35b3b987d05aeeeea2e5ed41eb9bc474ea3d6529.png", "website": "https://openlayer.com", "all_locations": "San Francisco, CA, USA", "long_description": "Openlayer is the governance platform for AI applications.", "one_liner": "The fastest way to ship airtight AI", "team_size": 19, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1625008531, "tags": [ "AIOps", "Developer Tools", "Generative AI", "Machine Learning", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/openlayer", "api": "https://yc-oss.github.io/api/batches/summer-2021/openlayer.json" }, { "id": 23796, "name": "Slope", "slug": "slope", "former_names": [ "AirDesk" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/bb362ee6e3bfce450e6a8196b555db1534feef1b.png", "website": "http://www.slopepay.com", "all_locations": "San Francisco, CA, USA", "long_description": "Accept and reconcile B2B payments seamlessly.", "one_liner": "The B2B Payments Platform ", "team_size": 16, "industry": "Fintech", "subindustry": "Fintech -> Payments", "launched_at": 1625009192, "tags": [ "Artificial Intelligence", "Fintech", "Machine Learning", "Payments", "Fraud Detection" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "Fintech", "Payments" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/slope", "api": "https://yc-oss.github.io/api/batches/summer-2021/slope.json" }, { "id": 23951, "name": "Mindstate Design Labs", "slug": "mindstate-design-labs", "former_names": [ "Kykeon Biotechnologies Inc.", "Kykeon Biotechnologies" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f3509dac4b76d442f8f0aa79c2bda0b827e78798.png", "website": "http://mindstate.design", "all_locations": "San Francisco, CA, USA", "long_description": "We're making every therapeutically valuable emotion available on demand in pharmaceutical form.\r\n\r\nOur Osmanthus platform is an ensemble of AI models that synthesize the world’s largest datasets of psychoactive pharmacology and phenomenology, quantitatively pinpointing the combination of neurotransmitter receptor activity that underlies various emotional as well as cognitive and perceptual states.\r\n\r\nOur lead program MSD-001 is designed to be rapid-acting and produce heightened emotional and cognitive flexibility without hallucinations. MSD-001 is currently in human trials, and will be the base ingredient for multiple drug combination \"emotions in a bottle\" such as empathy, awe, clarity, or beauty.", "one_liner": "Clinical-stage AI neuroengineering platform", "team_size": 7, "industry": "Healthcare", "subindustry": "Healthcare -> Drug Discovery and Delivery", "launched_at": 1629815779, "tags": [ "Machine Learning", "Mental Health Tech", "Biotech", "Therapeutics", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "Healthcare", "Drug Discovery and Delivery" ], "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": false, "url": "https://www.ycombinator.com/companies/mindstate-design-labs", "api": "https://yc-oss.github.io/api/batches/summer-2021/mindstate-design-labs.json" }, { "id": 23971, "name": "Concord Materials", "slug": "concord-materials", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3184c6727a76207d43485049fdf4e2604c6b26d7.png", "website": "https://concordmaterials.com", "all_locations": "New York, NY, USA", "long_description": "SaaS automation tools, financing and marketplace for bulk construction materials", "one_liner": "Automating procurement and finance for construction companies", "team_size": 7, "industry": "Real Estate and Construction", "subindustry": "Real Estate and Construction -> Construction", "launched_at": 1629906919, "tags": [ "Fintech", "Machine Learning", "Marketplace", "Insurance", "Enterprise" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "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": false, "url": "https://www.ycombinator.com/companies/concord-materials", "api": "https://yc-oss.github.io/api/batches/summer-2021/concord-materials.json" }, { "id": 24135, "name": "Sleek", "slug": "sleek", "former_names": [ "Avery", "HeyAvery", "TBA" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d66df5c1e4eac0579c54f345375ef14714c7b02b.png", "website": "https://www.onsleek.com/", "all_locations": "Toronto, ON, Canada", "long_description": "Sleek builds AI agents that automate important eCommerce flows for online shoppers. We work with consumer businesses to power these experiences across mobile and desktop via the browser.", "one_liner": "Browser automation for businesses.", "team_size": 5, "industry": "B2B", "subindustry": "B2B", "launched_at": 1629234147, "tags": [ "Artificial Intelligence", "Machine Learning", "E-commerce" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Acquired", "industries": [ "B2B" ], "regions": [ "Canada", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/sleek", "api": "https://yc-oss.github.io/api/batches/summer-2021/sleek.json" }, { "id": 24156, "name": "Lariat Data", "slug": "lariat-data", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/48e2e81fa04d812d60bdd7e093944b8090c8742d.png", "website": "https://www.lariatdata.com", "all_locations": "New York, NY, USA", "long_description": "Lariat is a Continuous Data Quality monitoring platform to discover data bugs before your consumers do. Ensure data products don’t break even as business logic, input data and infrastructure change.\r\n\r\nUse Lariat to define and then automatically extract, store and visualize data quality metrics on raw event-level data through to delivered data products.\r\n", "one_liner": "Observability for Data Engineering Teams", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1626560864, "tags": [ "Machine Learning", "Big Data", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Inactive", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/lariat-data", "api": "https://yc-oss.github.io/api/batches/summer-2021/lariat-data.json" }, { "id": 24205, "name": "Jovian", "slug": "jovian", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d6f4074567727ce4d14de635e6debbbdc71b55f5.png", "website": "https://www.jovian.com", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Jovian is an online university for software development and data science. We offer practical and industry-focused programs that help professionals learn technical skills, build real-world projects, and advance their careers.\r\n\r\nStudents learn practical skills, build real-world portfolio projects, and undergo job readiness training. Our tutors offer 24x7 guidance & mentorship over Slack & Zoom. Students also get access to jobs with 200+ hiring partners.", "one_liner": "Online University for Tech Professionals", "team_size": null, "industry": "Education", "subindustry": "Education", "launched_at": 1625134988, "tags": [ "AI-Enhanced Learning", "Developer Tools", "Education", "Machine Learning" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "Education" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/jovian", "api": "https://yc-oss.github.io/api/batches/summer-2021/jovian.json" }, { "id": 24303, "name": "Cero", "slug": "cero", "former_names": [ "CERO.AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/28978000b8dcc240b064a1480e88b2e3fa90b056.png", "website": "https://cero.ai", "all_locations": "Santiago, Santiago Metropolitan Region, Chile; Remote", "long_description": "At Cero, we solve specific coordination tasks between hospitals and patients, such as appointment confirmations and last minute cancellations, by automatically communicating with patients over WhatsApp. For example, a patient can confirm and reschedule their appointment without needing to call anyone.\r\n\r\nAlmost half of the medical appointments in Latin America are missed because patients simply do not show up. This ranges from missing a regular dentist check to missing an expensive MRI scan. With increasing pressure to improve access to care in developing countries, optimizing communication and coordination with patients is a key task to achieve. This is a massive problem especially in places where most people don't know how to effectively use self-service mediums (or are too busy to use them).\r\n \r\nWe bootstrapped the company and we are profitable. As of August 2021 we have $97K in monthly revenue from 15 clients with a CMRG of 20% in the last year. We have 100% logo retention and we grow with our clients. We are currently coordinating over 600,000 medical appointments every month, just in Chile.\r\n\r\nThis problem represents a $3.5B market opportunity in Latin America only. Latin America has 650M people, each one having an average of 3 medical consultations per year. We charge for every time we effectively communicate with a patient. We plan to handle several coordination interactions with every patient for each consultation, which considers a roadmap of scheduling, confirming, booking, reimbursements, payments, among others.\r\n\r\nWe are a team mixing strong knowledge about the healthcare industry with deep technical skills. Felipe (CEO) is a former dentist that has led deep changes in healthcare payments in Chile. Mauricio (CTO) and Jorge (R&D), both PhD in Computer Science, led the creation of the most advanced Spanish Language Neural Network used daily by scientists and practitioners in LatAm (BETO: Spanish BERT).\r\n\r\nIn a weekend project, Mauricio and Jorge automated the communication with students attending a summer school obtaining impressive engagement. Felipe was struggling with contacting his patients to coordinate appointments, and saw a big opportunity in this technology. The three together have designed and run a solution that as of 2021 is coordinating over 600,000 patients per month in their home country, Chile.", "one_liner": "Automated communication between hospitals and patients in Latam", "team_size": 10, "industry": "B2B", "subindustry": "B2B", "launched_at": 1625106698, "tags": [ "Machine Learning", "Consumer Health Services", "B2B", "NLP" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "B2B" ], "regions": [ "Chile", "Latin America", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/cero", "api": "https://yc-oss.github.io/api/batches/summer-2021/cero.json" }, { "id": 24346, "name": "MindFi", "slug": "mindfi", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6b7be3c4ba661d5b0f410a12fded0d9add5f93d1.png", "website": "https://www.mindfi.co", "all_locations": "Singapore, Singapore", "long_description": "MindFi is an app that reduces burnout and improves mental health for employees. We sell to companies in Asia such as Deutsche Bank, KPMG, PatSnap, Visa. The team is headquartered in Singapore and consists of Bjorn, (ex-Zendesk product manager), psychologist Anita Sadasivan (UMich alum, ex-Raffles Hospital), Leon 2X startup founder with 2 exits and Gangeshwar, an award-winning AI engineer. ", "one_liner": "Transforming Mental Health for Corporate Asia", "team_size": 25, "industry": "B2B", "subindustry": "B2B -> Human Resources", "launched_at": 1628416801, "tags": [ "Machine Learning", "Mental Health Tech", "B2B", "HR Tech", "Health & Wellness" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "B2B", "Human Resources" ], "regions": [ "Singapore", "Southeast Asia", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/mindfi", "api": "https://yc-oss.github.io/api/batches/summer-2021/mindfi.json" }, { "id": 24444, "name": "Protex AI", "slug": "protex-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/500e8598ba6bacb62abd9828780893ab69ba3e5e.png", "website": "https://www.protex.ai", "all_locations": "Limerick, County Limerick, Ireland", "long_description": "Tl;dr: We’re building software that monitors existing cameras in the port, logistics, and manufacturing industries to ensure compliance and identify safety issues.\r\n\r\nAt Protex AI, we’re on a mission to protect the industrial workforce! We’re building a proactive computer vision tool for workplace safety - empowering industrial Health and Safety (HS) teams to identify risk and danger before it becomes a problem.\r\n\r\n🤕 The Problem:\r\nKeeping people safe at work is extremely hard. In the U.S. alone, there were over 5,000 deaths in the workplace in 2019, mainly in the heavy industry space.\r\n\r\nSerious workplace injuries cost U.S. businesses circa $62 Billion annually. Until now, safety has been reactive, someone has to get injured, and in some cases fatally before something is done about it.\r\n\r\n✅ Problem Solved:\r\nProtex AI’s platform uses privacy-preserving camera monitoring software to provide companies with an always-on guardian angel, protecting their workforce.\r\n\r\nThe platform plugs into existing CCTV infrastructure and enables HS teams to flexibly translate their document-based safety rules into the real world.\r\n\r\nProtex AI takes these rules and autonomously audits the customer’s facility to identify areas of high risk and non-compliance.\r\n\r\nHS teams can access this data via a reporting engine and use it in weekly safety meetings, external safety audits, insurance discussions, and legal claims.\r\n\r\nThe tool integrates seamlessly with existing safety workflows to augment data produced by any manual incident logging system in place.", "one_liner": "Computer vision that makes the industrial workplace, safer", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Supply Chain and Logistics", "launched_at": 1626335543, "tags": [ "Industrial Workplace Safety", "Machine Learning", "B2B" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "B2B", "Supply Chain and Logistics" ], "regions": [ "Ireland", "Europe", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/protex-ai", "api": "https://yc-oss.github.io/api/batches/summer-2021/protex-ai.json" }, { "id": 24484, "name": "Evidently AI", "slug": "evidently-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ff0b16931b863f29fd0bd341fe033523a5e16dd6.png", "website": "https://evidentlyai.com", "all_locations": "London, England, United Kingdom; San Francisco, CA, USA; Remote", "long_description": "We are building an open-source standard to monitor ML models in production. The tool is used by enterprise data science teams to operate their models reliably and detect and resolve issues.", "one_liner": "Open-source monitoring for machine learning models", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1625666125, "tags": [ "Developer Tools", "Machine Learning", "B2B", "Open Source" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "B2B", "Analytics" ], "regions": [ "United Kingdom", "United States of America", "Europe", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/evidently-ai", "api": "https://yc-oss.github.io/api/batches/summer-2021/evidently-ai.json" }, { "id": 24524, "name": "outloud.ai", "slug": "outloud-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a26f5f21689070c1c612757e20582c586c7d843e.png", "website": "https://www.outloud.ai/", "all_locations": "Miami, FL, USA; Remote", "long_description": "We record conversations that customers have when they are placing orders in drive-thru restaurants, automatically analyze them, and help operators to upsell better or alert them when they are out of stock.\r\n", "one_liner": "Building Gong.io for offline retail.", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1629292834, "tags": [ "Machine Learning", "SaaS", "B2B" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Inactive", "industries": [ "B2B", "Retail" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/outloud-ai", "api": "https://yc-oss.github.io/api/batches/summer-2021/outloud-ai.json" }, { "id": 24551, "name": "Mach9", "slug": "mach9", "former_names": [ "Mach9 Robotics" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/05390d32227edd1416d7dc545801c3fc59e2ac15.png", "website": "https://www.mach9.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Mach9 accelerates how teams model and understand the world with automated feature extraction technology. Founded in 2021 and headquartered in San Francisco, Mach9's flagship Digital Surveyor platform helps transportation agencies, utility companies, and engineering firms extract miles of road corridor projects in a fraction of traditional processing time. Built on decades of research from Carnegie Mellon University's Robotics Institute, Mach9 empowers the architecture, engineering, and construction industries to tackle large-scale infrastructure projects with unprecedented speed and accuracy. Leading survey and geospatial organizations, including Langan, Olsson, Woolpert, HDR, and major state DOTs trust Digital Surveyor to create engineering-grade maps for infrastructure design and operations.", "one_liner": "AI-native CAD software for civil engineering", "team_size": 25, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1628526474, "tags": [ "Artificial Intelligence", "Machine Learning", "Computer Vision", "Design Tools", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/mach9", "api": "https://yc-oss.github.io/api/batches/summer-2021/mach9.json" }, { "id": 24590, "name": "Waterplan", "slug": "waterplan", "former_names": [ "Water Plan" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/56794ad6ea12a6e16aa87fe26ec5e7109ba0e46d.png", "website": "http://waterplan.com", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Waterplan is the world’s leading climate platform to measure, respond, report, and monitor companies increasingly changing climate water risk. Customers include multinational companies like Coca-Cola, Diageo, Colgate & Ab InBev. The platform combines companies’ operational data with local water satellite imagery to provide a continuously updated financial assessment of water risk. Based on that, it offers tailored mitigation and adaptation opportunities, from conventional infrastructure to nature-based solutions. The company was founded by a team of tech and water 2nd-time entrepreneurs with two exits and almost ten years of experience working for Fortune 500 companies in water projects. Early investors include YCombinator, Giant Ventures, David Helgason, Leonardo DiCaprio, Richard Branson's family, Manu Ginobili, among others waterplan.com\r\n", "one_liner": "Water risk mitigation for industrial sites", "team_size": 20, "industry": "B2B", "subindustry": "B2B", "launched_at": 1627999929, "tags": [ "Machine Learning", "SaaS", "B2B", "Climate", "ClimateTech" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "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": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/waterplan", "api": "https://yc-oss.github.io/api/batches/summer-2021/waterplan.json" }, { "id": 24616, "name": "Vibe Kanban", "slug": "vibe-kanban", "former_names": [ "bloop" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/773b39b8261f5827258bdc470dd1356bfb4e9ee4.png", "website": "https://vibekanban.com", "all_locations": "London, England, United Kingdom", "long_description": "As AI agents become more capable at writing code, developers are spending more of their time planning and reviewing what those agents produce. Vibe Kanban helps them do exactly that, seamlessly integrating with leading coding agents like Anthropic’s Claude Code and OpenAI’s Codex.", "one_liner": "Plan and review AI generated code", "team_size": 10, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1629492105, "tags": [ "Artificial Intelligence", "Machine Learning", "Open Source" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "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": false, "url": "https://www.ycombinator.com/companies/vibe-kanban", "api": "https://yc-oss.github.io/api/batches/summer-2021/vibe-kanban.json" }, { "id": 24666, "name": "Baubap", "slug": "baubap", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/5b8f09f3d507f587a964edfec2e799e29ee3b8d5.png", "website": "https://www.baubap.com", "all_locations": "Mexico City, CDMX, Mexico; Remote", "long_description": "Baubap is LatinAmerica's firts AI-powered, credit-focused bank. Today we're the leading AI lending app in Mexico", "one_liner": "Smart micro financing for everyone", "team_size": 150, "industry": "Fintech", "subindustry": "Fintech -> Credit and Lending", "launched_at": 1625680094, "tags": [ "Machine Learning", "Lending" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "Fintech", "Credit and Lending" ], "regions": [ "Mexico", "Latin America", "Remote", "Fully Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/baubap", "api": "https://yc-oss.github.io/api/batches/summer-2021/baubap.json" }, { "id": 24737, "name": "CellChorus", "slug": "cellchorus", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b81eadcf3657043bd35cb166adc3ac4e9ad367e8.png", "website": "https://cellchorus.com", "all_locations": "Houston, TX, USA", "long_description": "At CellChorus, we apply artificial intelligence to evaluate thousands of microscopy videos in parallel to evaluate how immune cells move, interact and perform over time. This allows our customers to discover, develop, manufacture and deliver cell therapies, antibodies, vaccines and other novel therapies faster, at lower expense, and with higher rates of success.\r\n\r\nOur customers include top-25 biopharma companies and seed-stage biotechs that are developing cell therapies, antibody therapeutics and vaccines (including one of the few companies with an approved CAR T cell therapy).\r\n\r\nHear from the team at https://www.youtube.com/watch?v=IE9x_tm0XnI", "one_liner": "The dynamic single-cell analysis company", "team_size": 4, "industry": "Healthcare", "subindustry": "Healthcare -> Drug Discovery and Delivery", "launched_at": 1629064445, "tags": [ "AI-powered Drug Discovery", "Machine Learning" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "Healthcare", "Drug Discovery and Delivery" ], "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": false, "url": "https://www.ycombinator.com/companies/cellchorus", "api": "https://yc-oss.github.io/api/batches/summer-2021/cellchorus.json" }, { "id": 24816, "name": "Spoken", "slug": "spoken", "former_names": [ "Parakeet" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fb68ef89a464af9a6400e5fd08ed7a7f92342b66.png", "website": "http://www.spoken.io", "all_locations": "New York, NY, USA; Remote", "long_description": "Spoken is a website where users compare buying options for the exact same product across multiple stores. We help our users never overpay online.\r\n\r\nDane is a two-time technical YC founder; he sold his previous company, Parklet, to Greenhouse where he was VP of Platform for 4.5 years. Geoff is a Stanford MBA grad and sold his previous company Cabrio Taxi. ", "one_liner": "Never overpay online", "team_size": 7, "industry": "Consumer", "subindustry": "Consumer -> Home and Personal", "launched_at": 1647521413, "tags": [ "Artificial Intelligence", "Machine Learning", "Marketplace", "Consumer", "E-commerce" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Inactive", "industries": [ "Consumer", "Home and Personal" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/spoken", "api": "https://yc-oss.github.io/api/batches/summer-2021/spoken.json" }, { "id": 24820, "name": "Medium Biosciences", "slug": "medium-biosciences", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0f30f00dbe44cde67296a43e445c0bb0dc14f9b5.png", "website": "http://medium.bio", "all_locations": "San Francisco, CA, USA", "long_description": "We turn advances in AI and protein design into experimentally validated molecular tools, partnering with research teams and diagnostic developers to deliver high-performance affinity reagents in weeks, not months.\r\n", "one_liner": "AI-designed Affinity Reagents", "team_size": 6, "industry": "Healthcare", "subindustry": "Healthcare -> Diagnostics", "launched_at": 1630004252, "tags": [ "Artificial Intelligence", "Machine Learning", "Biotech" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "Healthcare", "Diagnostics" ], "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": false, "url": "https://www.ycombinator.com/companies/medium-biosciences", "api": "https://yc-oss.github.io/api/batches/summer-2021/medium-biosciences.json" }, { "id": 24879, "name": "Lightly", "slug": "lightly", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/5c14e2db32ad93491460c405faf7230c30575e54.png", "website": "https://lightly.ai/", "all_locations": "Zürich, ZH, Switzerland", "long_description": "When ML teams send their data to companies like Scale.ai for labeling, most can only afford to label 1% or less of their datasets. But today they don’t have a good way to pick which 1% to label. We help them pick the best 1% of their data to label. By labeling the most representative data, they significantly improve model accuracy at the same cost.\r\n", "one_liner": "Help ML teams label the right data", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1629386219, "tags": [ "Machine Learning", "Data Labeling" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "Switzerland", "Europe", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/lightly", "api": "https://yc-oss.github.io/api/batches/summer-2021/lightly.json" }, { "id": 24892, "name": "Safer Management", "slug": "safer-management", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/30ad58fe2e47b7bd28702a2603013a87e5e354bc.png", "website": "https://www.safermgmt.com/", "all_locations": "Dallas, TX, USA", "long_description": "Safer Management sells attendance software to public school districts and colleges. Public schools receive federal funding based on their average daily attendance, and our software ensures they get the money they need.\r\n\r\nWe started Safer Mgmt. 12 months ago after I dropped off my twin boys and experienced inefficiencies with the sign-in process. We are now in 75 public schools and two colleges with annual reoccurring revenue of $621,000. We have 82% margins and are profitable. At scale, we will charge $15 per student per year. \r\n\r\nThere are 70 million public school students in America which is a $1.4 billion dollar market opportunity.", "one_liner": "Student Attendance tracking for Public Schools", "team_size": 5, "industry": "B2B", "subindustry": "B2B", "launched_at": 1625084786, "tags": [ "Artificial Intelligence", "Education", "Machine Learning" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/safer-management", "api": "https://yc-oss.github.io/api/batches/summer-2021/safer-management.json" }, { "id": 25327, "name": "Starling", "slug": "starling", "former_names": [ "Starling Medical" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cdc25280245ff89ae883c07e3aa55cf751c7c285.png", "website": "https://starlingmedical.com/", "all_locations": "Houston, TX, USA", "long_description": "Starling is building a urine diagnostic remote patient monitoring platform that seamlessly integrates into anyone's bathroom routine. By detecting early changes in a patient's urine using our toilet indwelling mass spectroscopy device, our platform is aiming to prevent hospitalizations from numerous conditions like recurrent UTIs, BPH exacerbations, or diabetes. We do this while creating significant new annual revenues for our clinician partners from remote patient monitoring reimbursements without requiring any significant changes in a staff's day to day schedule. ", "one_liner": "AI enabling digital urine diagnostics in the home", "team_size": 5, "industry": "Healthcare", "subindustry": "Healthcare -> Diagnostics", "launched_at": 1644279781, "tags": [ "Machine Learning", "Medical Devices", "Digital Health" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "Healthcare", "Diagnostics" ], "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": false, "url": "https://www.ycombinator.com/companies/starling", "api": "https://yc-oss.github.io/api/batches/winter-2022/starling.json" }, { "id": 25328, "name": "Momento", "slug": "momento", "former_names": [ "momento" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/38d68fb5813f3fe9c931fd72dc47dbabdd81f6fb.png", "website": "https://www.tumomento.com/", "all_locations": "Mexico City, CDMX, Mexico", "long_description": "In Momento we are going through a challenging regulatory process to become a fully-licensed insurance carrier. By doing so, we will be able to underwrite risk, set prices and, ultimately, become owners of the product.\r\n\r\nOnce approved, around summer 22, we will be in a great position to size the $13bn untapped opportunity of +30 Mn uninsured vehicles – just in Mexico! As we will be able to attack the main pain points in the market: i) antiquated underwriting models and ii) payment conditions only adapted for the affluent.\r\n\r\nTo succeed, we have assembled an elite team with both innovative and experienced profiles. We are three cofounders, two ex-McKinsey and one ex-P&G, and we managed to attract two heavyweights of the Mexican insurance industry: the previous CUO of Zurich Mexico and the previous CFO and VP of Finance of ING and AXA Mexico. ", "one_liner": "Building a full-stack auto insurer for the underserved in LatAm", "team_size": 18, "industry": "Fintech", "subindustry": "Fintech -> Insurance", "launched_at": 1648222923, "tags": [ "Fintech", "Machine Learning", "Consumer", "Insurance" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "Fintech", "Insurance" ], "regions": [ "Mexico", "Latin America", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/momento", "api": "https://yc-oss.github.io/api/batches/winter-2022/momento.json" }, { "id": 25337, "name": "Cherry Recommends", "slug": "cherry-recommends", "former_names": [ "Four2" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ef13c682e0722d6aa718deef64884cf506fe9cce.png", "website": "https://cherry.ai/", "all_locations": "Singapore, Singapore; Melbourne, VIC, Australia; Remote", "long_description": "Cherry is the only AI promotion management platform. We help online stores boost revenue and increase their marketing ROI by delivering and tracking dynamic promotions. \r\n\r\nCherry uses AI to improve the targeting of promotions to new and existing customers in real-time\r\n\r\nCherry has helped its customers increase conversion rates by up to 51%. \r\n\r\nCherry is lead by an expert founding team. Isaac has a PhD in maths and delivered AI at McKinsey, Rian is an ex-Microsoft software engineer.\r\n\r\n", "one_liner": "Promotion management platform", "team_size": 6, "industry": "B2B", "subindustry": "B2B", "launched_at": 1644213172, "tags": [ "Machine Learning", "SaaS", "E-commerce" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Inactive", "industries": [ "B2B" ], "regions": [ "Singapore", "Australia", "Southeast Asia", "Oceania", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/cherry-recommends", "api": "https://yc-oss.github.io/api/batches/winter-2022/cherry-recommends.json" }, { "id": 25358, "name": "Nyckel", "slug": "nyckel", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/aee1b48f0824b44d72f028343c04530da1313ae1.png", "website": "https://www.nyckel.com", "all_locations": "CA, USA; Remote", "long_description": "Use Nyckel to train and integrate state of the art machine learning into your application. Our ML platform can be used by anyone and it only takes minutes to train your first model. Once trained, your functions is immediately deployed to production grade infrastructure.", "one_liner": "Classify Anything", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1642146841, "tags": [ "Machine Learning", "API", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/nyckel", "api": "https://yc-oss.github.io/api/batches/winter-2022/nyckel.json" }, { "id": 25396, "name": "HomeRoom", "slug": "homeroom", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/28c5f983626c200b08794eb57093e4b2320036df.png", "website": "https://livehomeroom.com/", "all_locations": "San Jose, CA, USA; Remote", "long_description": "Homeroom helps investors provide affordable housing while making a 22% ROI.\r\n\r\nWe do this by sourcing properties, arranging capital, managing construction, vetting tenants and collecting rent by the room. To date, Homeroom has brought on 85 property investors, growing 6X annually, are bringing in 420K in annualized net-revenue\r\n\r\nHow it works:\r\nWe help investors buy homes in cities that are attractive to young people, but lack affordable housing options. We then renovate and after about 20 days, the home is ready and we find qualified renters by the room.\r\n\r\nWe launched in 2018 in Kansas City with 1 home. We now have 105 homes in 31 cities. In 2021, we grew rental GMV to $1.8M (300% YoY growth). Our average rent across every property is $458, which is about 50% lower than market comps, and our investors see returns up to 50% higher.\r\n\r\nWe are HomeRoom. Johnny is the financial analyst/domain expert. Thomas is a cereal entrepreneur with a PHD in ML, and Mike hacked growth for Airbnb and Facebook.", "one_liner": "We Rent Your Property by the Room. You earn 50% more Rent.", "team_size": 25, "industry": "Real Estate and Construction", "subindustry": "Real Estate and Construction -> Housing and Real Estate", "launched_at": 1643818108, "tags": [ "Machine Learning", "Real Estate", "Proptech", "NLP", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Acquired", "industries": [ "Real Estate and Construction", "Housing and Real Estate" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/homeroom", "api": "https://yc-oss.github.io/api/batches/winter-2022/homeroom.json" }, { "id": 25398, "name": "Dynamo AI", "slug": "dynamo-ai", "former_names": [ "DynamoFL" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a0f71dda3502bef2323fa4a11bd6c434154ddec8.png", "website": "https://dynamo.ai", "all_locations": "San Francisco, CA, USA", "long_description": "End-to-end privacy, security, and compliance solutions to prepare your organization for emerging AI regulations.", "one_liner": "Compliant-Ready AI for the Enterprise", "team_size": 40, "industry": "B2B", "subindustry": "B2B", "launched_at": 1645652403, "tags": [ "Machine Learning", "Privacy", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/dynamo-ai", "api": "https://yc-oss.github.io/api/batches/winter-2022/dynamo-ai.json" }, { "id": 25399, "name": "Invert", "slug": "invert", "former_names": [ "Invert Bio" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/1e1a589d7f48cf8cc7fb3658ec8dea0855d526a0.png", "website": "http://www.invertbio.com/", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "We build software to manage, analyze, and optimize bioprocessing data. Our initial customers are bio-industrial companies, who produce various products in bioreactors.\r\n\r\n", "one_liner": "Data analytics software for biomanufacturing.", "team_size": 25, "industry": "Healthcare", "subindustry": "Healthcare -> Industrial Bio", "launched_at": 1648234072, "tags": [ "Cellular Agriculture", "Machine Learning", "Synthetic Biology", "Biotech" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "Healthcare", "Industrial Bio" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/invert", "api": "https://yc-oss.github.io/api/batches/winter-2022/invert.json" }, { "id": 25448, "name": "HypaHub", "slug": "hypahub", "former_names": [ "HypaHub, Inc." ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/5a364403fcd1dfaabe90af51ec8af68eac5364cf.png", "website": "https://www.hypahub.com", "all_locations": "Sunnyvale, CA, USA", "long_description": "HypaHub is a Cloud-Based Bioinformatics and AI Platform. It is the first HIPAA-compliant Bioinformatics SaaS that runs natively on users' clouds, providing both operation- and price-transparency. \r\n\r\nOur product is a one-stop shop to access complex technologies designed for scientists building data applications or performing data analytics to extract insights. It automates the creation and manages the operation of computing resources, eliminating the need for enterprises to set up and maintain a high-end R&D cloud infrastructure.", "one_liner": "A Cloud-Based Bioinformatics and AI Platform ", "team_size": 6, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1654727846, "tags": [ "Machine Learning", "Biotech", "Analytics" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Acquired", "industries": [ "B2B", "Analytics" ], "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": false, "url": "https://www.ycombinator.com/companies/hypahub", "api": "https://yc-oss.github.io/api/batches/winter-2022/hypahub.json" }, { "id": 25491, "name": "Bobidi", "slug": "bobidi", "former_names": [ "Bobidi, Inc." ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f84e00a73b712ac5b6de5e0cec130ff847c1a3e3.png", "website": "http://www.upswell.ai", "all_locations": "San Francisco, CA, USA", "long_description": "Bobidi runs Upswell, a platform that brings new guests to local restaurants and helps turn them into regulars.\r\n\r\nWe transform restaurants’ promotional videos on social media into engaging quiz campaigns based on the video content. Winners receive cash rewards that can be redeemed at the restaurants.", "one_liner": "Restaurant Loyalty Using Quiz", "team_size": 7, "industry": "B2B", "subindustry": "B2B -> Marketing", "launched_at": 1642208334, "tags": [ "Generative AI", "Machine Learning", "Human Resources", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "B2B", "Marketing" ], "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": false, "url": "https://www.ycombinator.com/companies/bobidi", "api": "https://yc-oss.github.io/api/batches/winter-2022/bobidi.json" }, { "id": 25532, "name": "Fintelite", "slug": "fintelite", "former_names": [ "Sribuu" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ab01da231dd5c6a43a0a49fe4617d17070096fd0.png", "website": "http://www.fintelite.ai", "all_locations": "Singapore, Singapore; Remote", "long_description": "Fintelite's AI streamlines loan approvals and fraud detection, ensuring swift, accurate decisions.\r\n\r\nRevolutionizing lending with AI-powered bank statement analysis and transaction data enrichment.\r\n\r\nFintelite empowers lenders with a next-generation approach to lending. Our AI platform utilizes:\r\n\r\nBank statement analysis: Gain deep insights into borrower financials through automated analysis.\r\nTransaction data enrichment: Extract valuable details from transactions for a holistic financial picture.\r\nThese capabilities enable lenders to:\r\n\r\nReduce fraud: Identify and prevent suspicious activity with superior accuracy.\r\nAccelerate approvals: Make faster, data-driven decisions with enriched information.\r\nOptimize risk management: Tailor risk assessments based on comprehensive borrower data.\r\nPassionate about building a future of responsible AI in financial services. I'm committed to helping lenders serve customers efficiently and securely.\r\n\r\n\r\nOur help to others includes:\r\n• BlubyBCA and ANZ increased efficiency by 15%\r\n• Qazwa and KoinWorks sped up loan processing 10x, cutting costs by 25%\r\n", "one_liner": "Intelligent Process Automation for Lending.", "team_size": 20, "industry": "Fintech", "subindustry": "Fintech", "launched_at": 1641201791, "tags": [ "Artificial Intelligence", "Fintech", "Machine Learning", "Lending" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "Fintech" ], "regions": [ "Singapore", "Southeast Asia", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/fintelite", "api": "https://yc-oss.github.io/api/batches/winter-2022/fintelite.json" }, { "id": 25537, "name": "Cerebrium", "slug": "cerebrium", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/730897d24e909ee905c210f74fec1b439d21c4a7.png", "website": "https://www.cerebrium.ai/", "all_locations": "New York, NY, USA", "long_description": "Cerebrium is a serverless infrastructure platform for AI applications. We make it easier for companies to build and deploy AI based applications. We offer Serverless GPU's with low cold start times, over 12 varieties of GPU chips, allow you to run large scale batch jobs, run realtime voice applications and much more. We are used by the teams at Tavus, CivitAI, Twilio and many more. \r\n\r\nCustomers typically experience 40% in cost savings when compared to using traditional cloud providers and can scale models to more than 10K requests per minute with minimal engineering overhead. ", "one_liner": "Serverless Infrastructure Platform for AI", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1641981854, "tags": [ "Machine Learning", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/cerebrium", "api": "https://yc-oss.github.io/api/batches/winter-2022/cerebrium.json" }, { "id": 25538, "name": "Lexter.ai", "slug": "lexter-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/13fb400d02f64e196fddff48bb201121acd1fa1d.png", "website": "https://www.lexter.ai", "all_locations": "São Paulo, SP, Brazil; Remote", "long_description": "Lexter is the first legal LLM company in Brazil, already working with 3 out of the top 5 law firms in the Country", "one_liner": "LLM for Legal in Brazil", "team_size": 18, "industry": "B2B", "subindustry": "B2B -> Legal", "launched_at": 1644264235, "tags": [ "Machine Learning", "LegalTech" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "B2B", "Legal" ], "regions": [ "Brazil", "Latin America", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/lexter-ai", "api": "https://yc-oss.github.io/api/batches/winter-2022/lexter-ai.json" }, { "id": 25561, "name": "LanceDB", "slug": "lancedb", "former_names": [ "ETO", "Eto" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7b3b44ab11047bbfddb4bfe44c9d2d3c87027258.png", "website": "https://lancedb.com", "all_locations": "San Francisco, CA, USA", "long_description": "LanceDB is a new open-source vector database that can support low-latency billion-scale vector search on a single node. Built around a new columnar data format, LanceDB makes it incredibly easy to build applications for generative AI, recsys, search engines, content moderation, and more.", "one_liner": "Open-source, serverless vectordb for production-scale generative AI", "team_size": 35, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1648263864, "tags": [ "AIOps", "Machine Learning", "Open Source", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/lancedb", "api": "https://yc-oss.github.io/api/batches/winter-2022/lancedb.json" }, { "id": 25585, "name": "Armilla AI", "slug": "armilla-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a0397658ae6c0ba5a9499d3b6844bdb898f09c38.png", "website": "http://www.armilla.ai", "all_locations": "Toronto, ON, Canada", "long_description": "Using industry-leading AI/LLM evaluation technology, Armilla AI provides third-party AI assessment and warranty solutions, backed by leading reinsurers Swiss Re, Greenlight Re and Chaucer. Vendors of AI-powered products leverage Armilla’s assessment to anticipate customer questions, respond to enterprise RFPs, meet regulatory requirements, build trust in the reliability of their solutions - and ultimately, to accelerate sales. \r\n\r\nArmilla’s clients include enterprises along with AI-first start ups & scale ups in Fintech, Insurtech, Healthtech, Legaltech, HRtech & more.", "one_liner": "AI/LLM Assessment & Warranty Solutions", "team_size": 14, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1642131883, "tags": [ "Artificial Intelligence", "Machine Learning" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "B2B", "Analytics" ], "regions": [ "Canada", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/armilla-ai", "api": "https://yc-oss.github.io/api/batches/winter-2022/armilla-ai.json" }, { "id": 25607, "name": "Axis", "slug": "axis", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f3e7a7c395e202f91209c183250f4e6d0835ea29.png", "website": "http://axis.xyz", "all_locations": "New York, NY, USA; Remote", "long_description": "Axis is a knowledge base of government regulations and officials that helps large companies do business in foreign markets. For example, if you want to operate in Saudi Arabia - our software tells you which laws you need to comply with and which officials you need approvals from. We currently cover major markets in Europe, Middle East, and Africa", "one_liner": "Knowledge base for corporate affairs teams", "team_size": 15, "industry": "B2B", "subindustry": "B2B -> Productivity", "launched_at": 1640038883, "tags": [ "Machine Learning", "B2B", "Subscriptions", "Regtech" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "B2B", "Productivity" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/axis", "api": "https://yc-oss.github.io/api/batches/winter-2022/axis.json" }, { "id": 25610, "name": "RedBrick AI", "slug": "redbrick-ai", "former_names": [ "RedBrick AI", "RedBrick AI (Zantula", "Inc.)" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/10e60623a6f9ead582ef32a7eb60d830f6544cbe.png", "website": "https://redbrickai.com", "all_locations": "Claymont, DE, USA; MH, India", "long_description": "RedBrick AI's mission is to accelerate the adoption of artificial intelligence in radiology by building world-class software infrastructure. Currently, we are focused on helping radiology AI teams prepare high-quality datasets to train their algorithms.\r\n\r\nRadiology data, such as CT and X-ray scans, is an incredibly important source of truth in healthcare delivery. In fact, over 90% of all healthcare data is medical imagery! However, the global radiology workforce is overburdened. In the UK, for example, only 2% of radiology departments are able to fulfill their reporting requirements, and this trend is reflected worldwide.\r\n\r\nThe acute state of radiology, coupled with the abundance of data, makes the use of AI in radiology a prime candidate. In 2022, $5.6 billion was invested in the development of AI in healthcare! However, a key hindrance to further adoption is the lack of sophisticated tools to build and deploy AI algorithms in clinical environments. This is the problem we’re focused on at RedBrick AI\r\n\r\nWe're a team based out of Bangalore India, and USA. We're backed by leading institutional investors like Y Combinator and Peak XV (formerly Sequoia Capital India). ", "one_liner": "Rapid medical data annotation", "team_size": 13, "industry": "B2B", "subindustry": "B2B", "launched_at": 1642587658, "tags": [ "AIOps", "Machine Learning", "Healthcare" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "India", "America / Canada", "South Asia", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/redbrick-ai", "api": "https://yc-oss.github.io/api/batches/winter-2022/redbrick-ai.json" }, { "id": 25674, "name": "Toko", "slug": "toko", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/27e4f86a5dfe2f9b052160388e2aeeacf844e019.png", "website": "https://tokotutor.com/", "all_locations": "New York, NY, USA", "long_description": "Toko helps English learners in East Asia achieve speaking fluency. Through our mobile app, learners engage in short, realistic conversations with an AI and receive feedback on their grammar.\r\n\r\nWith over 500 topics, learners can practice real-world scenarios ranging from small talk to workplace discussions. Toko offers a low-pressure environment to help learners build up their confidence.\r\n\r\nWe make language fluency accessible to everyone - not just those with the means to meet 1:1 with a tutor.\r\n\r\nIn Taiwan (our first market), Toko is ranked top 3 in the App Store for Education!", "one_liner": "Learn English by speaking with an AI", "team_size": 5, "industry": "Education", "subindustry": "Education", "launched_at": 1646685328, "tags": [ "AI-Enhanced Learning", "Education", "Generative AI", "Machine Learning", "Consumer" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "Education" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/toko", "api": "https://yc-oss.github.io/api/batches/winter-2022/toko.json" }, { "id": 25691, "name": "voize", "slug": "voize", "former_names": [ "voize GmbH" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/437f8a6e2847546f303d55acd48f2ca6050b4e54.png", "website": "https://voize.de/", "all_locations": "Berlin, Berlin, Germany", "long_description": "At voize, we believe the greatest gift to frontline workers is time - time to care, connect, and be present. Today, that time is lost to admin work that pulls nurses away from what matters most: people. \r\n\r\nWe’re changing that by building the AI companion that frees nurses from admin, giving them back up to 30% of time. We don’t replace humans - we support and amplify their impact. Today, 1,500+ care facilities trust voize, and over 100,000 nurses rely on our AI companion** to ease their daily workload.\r\n\r\nOur mission is backed with a $50M Series A funding led by Balderton Capital, with support from HV Capital, Y Combinator and other leading VCs.", "one_liner": "We build the AI companion for nurses, to create time for care.", "team_size": 140, "industry": "B2B", "subindustry": "B2B -> Productivity", "launched_at": 1648233375, "tags": [ "Machine Learning", "Speech Recognition", "Healthcare", "NLP" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "B2B", "Productivity" ], "regions": [ "Germany", "Europe", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": true, "url": "https://www.ycombinator.com/companies/voize", "api": "https://yc-oss.github.io/api/batches/winter-2022/voize.json" }, { "id": 25714, "name": "Strong Compute", "slug": "strong-compute", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b6d861374205c6a41091e3a76655da787098154b.png", "website": "https://strongcompute.com", "all_locations": "Sydney, NSW, Australia", "long_description": "Strong Compute is building the future of Cloud Computing, priced by performance not consumption. Our software and hardware optimizations speed up neural network development 10x-1000x, file transfer 1000x, instance start time 10x. We're starting with AI and are aimed at the $500B cloud market.", "one_liner": "10x-1000x faster compute for Neural Network training", "team_size": 8, "industry": "B2B", "subindustry": "B2B", "launched_at": 1646850573, "tags": [ "Artificial Intelligence", "Machine Learning", "Cloud Computing" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "B2B" ], "regions": [ "Australia", "Oceania", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/strong-compute", "api": "https://yc-oss.github.io/api/batches/winter-2022/strong-compute.json" }, { "id": 25817, "name": "Lifecast", "slug": "lifecast", "former_names": [ "Lifecast Incorporated" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/1a29e222d654365932751024c04701eec4344d05.png", "website": "http://www.lifecastvr.com", "all_locations": "Palo Alto, CA, USA; Remote", "long_description": "We make tools for state-of-the-art 3D VR video, which fix motion sickness for a more comfortable and immersive experience. Our team's experience includes building VR cameras at Facebook, and robot perception systems at Lyft and Google X.", "one_liner": "Software to create 3D video for VR, robotics and film.", "team_size": 2, "industry": "Consumer", "subindustry": "Consumer", "launched_at": 1645743234, "tags": [ "Machine Learning", "Robotics", "Virtual Reality" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Inactive", "industries": [ "Consumer" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/lifecast", "api": "https://yc-oss.github.io/api/batches/winter-2022/lifecast.json" }, { "id": 25891, "name": "PINA", "slug": "pina", "former_names": [ "PINA", "PT Pina Aplikasi Bersama" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a3371ff710a135af2d2ac975d4af1b4b7ff5df24.png", "website": "https://pina.id", "all_locations": "Jakarta, Jakarta, Indonesia", "long_description": "At PINA, we are designing and building the future of personal finance with a mission to help everyone achieve financial freedom by providing products and advice that make complicated financial decisions simple and relevant. \r\n\r\nWe seamlessly integrate money management and investing into one app to allow people to manage their finances holistically. Users can see their net worth, monthly cash flow and how their budget has changed over the past several months. All of this is automated and designed to help them achieve the savings goal which they have set .\r\n\r\nIn addition to money management, we focus on making investing easy with pre-built portfolios and automatic rebalancing. When you sign up for an account, it offers the option to pick an expertly built portfolio, or you can choose to build your own.", "one_liner": "WealthFront of Indonesia ", "team_size": 25, "industry": "Fintech", "subindustry": "Fintech", "launched_at": 1640802022, "tags": [ "Fintech", "Machine Learning" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "Fintech" ], "regions": [ "Indonesia", "Southeast Asia", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/pina", "api": "https://yc-oss.github.io/api/batches/winter-2022/pina.json" }, { "id": 25948, "name": "Spade", "slug": "spade", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/dc25342edef4b9f6942587780f3a5d96fae04f9c.png", "website": "https://www.spade.com", "all_locations": "New York, NY, USA", "long_description": "Spade is the next generation of fintech infrastructure. We’re building a financial data enrichment API purpose built to empower our customers to uncover the truth hidden within their transaction data. We use our vast, ground-truth merchant data set to decipher cryptic transactions, helping customers underwrite, detect fraud, build better banking infrastructure and get a unique understanding of their users’ spending habits.", "one_liner": "Enriched transaction data you can build on", "team_size": 25, "industry": "Fintech", "subindustry": "Fintech", "launched_at": 1641512856, "tags": [ "Fintech", "Machine Learning", "Payments", "Data Labeling", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "Fintech" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/spade", "api": "https://yc-oss.github.io/api/batches/winter-2022/spade.json" }, { "id": 25975, "name": "Ploomber", "slug": "ploomber", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b5abaea13a47b9e7cb04c8d183b6a2056824f626.png", "website": "https://ploomber.io/", "all_locations": "New York, NY, USA; Remote", "long_description": "We are building a cloud platform to help companies deploy and scale AI applications.", "one_liner": "Heroku for AI", "team_size": 7, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1643229196, "tags": [ "Developer Tools", "Machine Learning", "Analytics", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Inactive", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/ploomber", "api": "https://yc-oss.github.io/api/batches/winter-2022/ploomber.json" }, { "id": 25976, "name": "GoJom", "slug": "gojom", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6f6a49e808e5f793fd59cf2dacc4bd426cfbce9e.png", "website": "https://gojom.com", "all_locations": "Lima, Callao Region, Peru; Lima, Lima Province, Peru", "long_description": "GoJom is a One Stop Shop for Real Estate Solutions. It’s technology creates a faster and easier way to buy, sell and rent properties in LaTam. ", "one_liner": "One-stop-shop for Real Estate Solutions. ", "team_size": 140, "industry": "Real Estate and Construction", "subindustry": "Real Estate and Construction", "launched_at": 1639692064, "tags": [ "Fintech", "Machine Learning", "Proptech" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "Real Estate and Construction" ], "regions": [ "Peru", "Latin America", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/gojom", "api": "https://yc-oss.github.io/api/batches/winter-2022/gojom.json" }, { "id": 26238, "name": "Flike", "slug": "flike", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7958871792e5be922aaf99f654b521726b10126e.png", "website": "https://flike.app/", "all_locations": "San Francisco, CA, USA", "long_description": "Flike trains AI models on your product marketing knowledge, enabling your sales team to generate relevant&hyper-personalized emails that are aligned with your brand voice throughout the entire sales funnel (from cold outbound to upselling). And we're already partnering with some of the largest YC companies.", "one_liner": "Flike's AI crafts sales emails that convert", "team_size": 8, "industry": "B2B", "subindustry": "B2B", "launched_at": 1648043554, "tags": [ "Artificial Intelligence", "Machine Learning" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Inactive", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/flike", "api": "https://yc-oss.github.io/api/batches/winter-2022/flike.json" }, { "id": 26675, "name": "Birch Biosciences", "slug": "birch-biosciences", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6d5ede074951640a2e67e11927c78affb1e31b81.png", "website": "http://www.birchbiosciences.com", "all_locations": "Portland, OR, USA", "long_description": "Birch Biosciences engineers enzymes for plastic recycling using synthetic biology and machine learning. Our enzymes function as high performance “molecular scissors” that efficiently break down plastic polymers into chemical building blocks that can be used to manufacture high quality recycled plastic products. Today, plastic manufacturing is unsustainable and a major driver of climate change. Birch Biosciences is developing an economical end-to-end plastic recycling process that reduces carbon emissions by 70% and enables a circular plastic economy.\r\n", "one_liner": "We recycle plastic using engineered enzymes", "team_size": 10, "industry": "Industrials", "subindustry": "Industrials -> Climate", "launched_at": 1656393851, "tags": [ "Machine Learning", "Synthetic Biology", "Biotech", "Climate", "ClimateTech" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2022", "status": "Active", "industries": [ "Industrials", "Climate" ], "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": false, "url": "https://www.ycombinator.com/companies/birch-biosciences", "api": "https://yc-oss.github.io/api/batches/summer-2022/birch-biosciences.json" }, { "id": 26750, "name": "NuMind", "slug": "numind", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a271d83ee825be78f44453963c65aea56395a341.png", "website": "https://www.numind.ai", "all_locations": "Cambridge, MA, USA", "long_description": "NuMind is a tool for data scientists, data analysts, but also software engineers to create custom NLP models. For example, a recruiting company uses NuMind to find which job offers best match a given resume. Etienne (CEO) was head of Machine Learning at Wolfram Research, and Samuel (CTO) co-founded Make.org (8M users). NuMind originated from our own frustration when developing NLP models. Leveraging large language models similar to GPT-3, NuMind allows to complete NLP projects at least 10x faster than before. We launched a private beta August 2 and had 9 paying customers one month later.", "one_liner": "Create custom NLP models", "team_size": 6, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1656275044, "tags": [ "AIOps", "Artificial Intelligence", "Machine Learning", "NLP" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2022", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/numind", "api": "https://yc-oss.github.io/api/batches/summer-2022/numind.json" }, { "id": 26863, "name": "Provision", "slug": "provision", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/385a0231f7ab5d980e79ffdfbfa16bc2183b283d.png", "website": "https://provision.com", "all_locations": "Toronto, ON, Canada", "long_description": "Provision is building the AI Estimator for construction. We identify risks and obligations in contracts, specs, and drawings so contractors can reduce time spent reviewing documents and focus on winning and delivering projects profitably. Backed by Y Combinator (S22).", "one_liner": "Ironclad for construction", "team_size": 15, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1653315975, "tags": [ "Documents", "Machine Learning", "Construction", "Productivity", "NLP" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2022", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "Canada", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/provision", "api": "https://yc-oss.github.io/api/batches/summer-2022/provision.json" }, { "id": 27038, "name": "Fini", "slug": "fini", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b044a080c88a5aedab72016a60feff3dd053fc64.png", "website": "https://www.usefini.com", "all_locations": "Amsterdam, NH, Netherlands", "long_description": "Fini builds AI agents that autonomously resolve up to 80% of customer support tickets for enterprises specially in Fintech, E-commerce, Gaming and Fitness tech.\r\n\r\nOur agents understand complex workflows, take real actions (like refunds or KYC checks), and improve in real-time. Built on a proprietary knowledge engine, our agents deliver 98%+ accuracy and integrate deeply with tools like Zendesk, Salesforce, and internal APIs.\r\n\r\nEnterprises like Bitdefender and Training Peaks use Fini to slash support costs by 50% while boosting CSAT by 10%.", "one_liner": "Fini | Automate 80% of enterprise support with AI agents", "team_size": 14, "industry": "B2B", "subindustry": "B2B -> Operations", "launched_at": 1656434795, "tags": [ "Generative AI", "Machine Learning", "SaaS", "B2B", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2022", "status": "Active", "industries": [ "B2B", "Operations" ], "regions": [ "Netherlands", "Europe", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/fini", "api": "https://yc-oss.github.io/api/batches/summer-2022/fini.json" }, { "id": 27042, "name": "Artemis Search", "slug": "artemis-search", "former_names": [ "Artemis", "Artemis Labs", "Umbria (by Artemis Labs)" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/002e53ddce5bb4318d71a6b7c48c2417fb3ad159.png", "website": "https://search-artemis.com/", "all_locations": "San Francisco, CA, USA; Rochester, MN, USA; Remote", "long_description": "Artemis Search is a vector database search with a twist. We use special-purpose deep-learning models instead of using textual / semantic similarity to evaluate how good a search result is.\r\n\r\nThis enables us to actually reason how well search results match the intent of the search query, eliminating the problems that come from evaluating search results on how much they look like the search query.", "one_liner": "A search technology that actually finds what you’re looking for.", "team_size": 3, "industry": "B2B", "subindustry": "B2B", "launched_at": 1656613108, "tags": [ "Artificial Intelligence", "Machine Learning", "SaaS", "B2B", "Search" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2022", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/artemis-search", "api": "https://yc-oss.github.io/api/batches/summer-2022/artemis-search.json" }, { "id": 27092, "name": "Lamin", "slug": "lamin", "former_names": [ "Lamin Labs" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/65bf3f581eea5d1a5b7640c508e3fc0e7c8930f9.png", "website": "https://lamin.ai", "all_locations": "", "long_description": "Query, trace, and validate datasets and models at scale. Automate context for agents and humans.\r\n\r\nOne API: lakehouse, lineage, feature store, ontologies, bio-registries & formats.", "one_liner": "Open data lakehouse for biology", "team_size": 10, "industry": "Healthcare", "subindustry": "Healthcare -> Healthcare IT", "launched_at": 1655969538, "tags": [ "Developer Tools", "Machine Learning", "Biotech", "Open Source", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2022", "status": "Active", "industries": [ "Healthcare", "Healthcare IT" ], "regions": [ "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/lamin", "api": "https://yc-oss.github.io/api/batches/summer-2022/lamin.json" }, { "id": 27143, "name": "TypeLess", "slug": "typeless", "former_names": [ "Delight" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/9051729e9b529a474279cd2a8fa061cc7d5031fe.png", "website": "https://apps.apple.com/us/app/typeless-ai-messenger/id6478489620", "all_locations": "San Francisco, CA, USA", "long_description": "Typeless is an AI messaging API designed to facilitate communication for businesses and professionals. Our API generates smart, context-aware response suggestions to enhance messaging platforms in a variety of industries, from real estate to customer support.\r\n\r\nFor example, a real estate platform can use Typeless to automate responses for scheduling property viewings, answering client inquiries, and handling follow-ups. Similarly, a customer service platform can enable agents to respond faster with personalized, AI-driven suggestions for customer questions and issues.\r\n\r\nYou can download our demo messaging app built with the TypeLess API on the app store: https://apps.apple.com/us/app/typeless-ai-messenger/id6478489620", "one_liner": "AI messaging API for smarter, faster communication.", "team_size": 2, "industry": "B2B", "subindustry": "B2B", "launched_at": 1658105881, "tags": [ "Generative AI", "Machine Learning", "Messaging", "API", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 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": false, "url": "https://www.ycombinator.com/companies/typeless", "api": "https://yc-oss.github.io/api/batches/summer-2022/typeless.json" }, { "id": 27201, "name": "Lavo Life Sciences", "slug": "lavo-life-sciences", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/590ccfba5d4f0f97ed00fd962f2fdea307dbea2f.png", "website": "https://www.lavo.ai/", "all_locations": "", "long_description": "Lavo Life Sciences runs simulations of drug molecules on computers. Pharma companies use these simulations to guide their experiments and ultimately save time and money in the lab. This will de-risk and expedite clinical trials and FDA approval.", "one_liner": "AI for drug formulation", "team_size": 3, "industry": "Healthcare", "subindustry": "Healthcare -> Drug Discovery and Delivery", "launched_at": 1674082073, "tags": [ "AI-powered Drug Discovery", "Machine Learning", "Biotech", "Drug discovery" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2023", "status": "Inactive", "industries": [ "Healthcare", "Drug Discovery and Delivery" ], "regions": [ "Unspecified" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/lavo-life-sciences", "api": "https://yc-oss.github.io/api/batches/winter-2023/lavo-life-sciences.json" }, { "id": 27206, "name": "Delfino AI", "slug": "delfino-ai", "former_names": [ "Be Golden" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0ca7311a440acc157fc34997e9d9bbdd9f1873fd.png", "website": "https://www.delfino.ai/", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Delfino AI helps automate the repetitive phone calls that providers' offices make to payors", "one_liner": "Generative AI for administrative automation in healthcare ", "team_size": 2, "industry": "Healthcare", "subindustry": "Healthcare -> Healthcare IT", "launched_at": 1657044467, "tags": [ "Generative AI", "Machine Learning", "Health Tech", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2022", "status": "Active", "industries": [ "Healthcare", "Healthcare IT" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/delfino-ai", "api": "https://yc-oss.github.io/api/batches/summer-2022/delfino-ai.json" }, { "id": 27221, "name": "CAPSULE", "slug": "capsule", "former_names": [ "Dryftwell", "GLIMPSE" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/19f195e9a25d1cff1f914f65ceb3e7458c6d52b9.png", "website": "https://www.shopcapsule.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "CAPSULE is a mobile app that makes it easy to save and buy the things you find on any social media platform. Just snap a screenshot of anything you like, from any platform, and we search the entire internet to instantly give you shoppable links. \r\n\r\nInstead of searching hundreds of websites and sifting through thousands of products on your own, CAPSULE lets you find inspiration from anywhere and uses advanced machine learning to return results that feel like magic. ", "one_liner": "Buy anything you find on social media", "team_size": 4, "industry": "Consumer", "subindustry": "Consumer -> Apparel and Cosmetics", "launched_at": 1661989948, "tags": [ "Artificial Intelligence", "Generative AI", "Machine Learning", "Computer Vision", "E-commerce" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2022", "status": "Inactive", "industries": [ "Consumer", "Apparel and Cosmetics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/capsule", "api": "https://yc-oss.github.io/api/batches/summer-2022/capsule.json" }, { "id": 27260, "name": "Coverage Cat", "slug": "coverage-cat", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/9bd0bbec7d523edd1bef0a7fed1c32a4c5e91d07.png", "website": "https://www.coveragecat.com/", "all_locations": "New York, NY, USA; Remote", "long_description": "Coverage Cat, the AI-native insurance broker, fixes your coverage limits and finds cheaper premiums. \r\n\r\nWe provide both AI and human support so you can get fast answers on your policy and quickly get a response from a human agent so you can protect you assets or close on a new home. \r\n\r\nThe AI-first approach drives core search, support and shopping experiences to ensure you get the best prices with the correct coverage. ", "one_liner": "Consumer Optimized Insurance", "team_size": 4, "industry": "Fintech", "subindustry": "Fintech -> Insurance", "launched_at": 1659454514, "tags": [ "Fintech", "Machine Learning", "Insurance" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2022", "status": "Active", "industries": [ "Fintech", "Insurance" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/coverage-cat", "api": "https://yc-oss.github.io/api/batches/summer-2022/coverage-cat.json" }, { "id": 27361, "name": "Polymath Robotics", "slug": "polymath-robotics", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0d6f5a2035d19900b2a4411b03d2c1998b0aaa5e.png", "website": "http://www.polymathrobotics.com", "all_locations": "San Francisco, CA, USA", "long_description": "Polymath is building a general autonomy stack for cautious vehicles. Our software allows any industrial vehicle - whether it's a tractor in a field or a bulldozer in a mine, drive itself. We bundle together AI, ML, Controls, ROS, Safety and best-in-class deployment practices to enable our customers to tell automated vehicles to do via a REST API.\r\n\r\nWe're on more robots than we have engineers, are seeing our revenue (and robotic fleet) grow rapidly, and are looking for folks who want to help automate the world.", "one_liner": "General Autonomy for Industrial Vehicles", "team_size": 13, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1659110769, "tags": [ "Hard Tech", "Machine Learning", "Robotics", "Unmanned Vehicle", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2022", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": true, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/polymath-robotics", "api": "https://yc-oss.github.io/api/batches/summer-2022/polymath-robotics.json" }, { "id": 27821, "name": "PoplarML", "slug": "poplarml", "former_names": [ "Poplar" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e108e35156cecf90efeb1f504d510fca87ce7b44.png", "website": "http://poplarml.com", "all_locations": "San Francisco, CA, USA", "long_description": "PoplarML lets you deploy any machine learning model to a fleet of GPUs as a ready-to-use and scalable API endpoint with one command.", "one_liner": "Deploy Machine Learning Models with One Command", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1674681330, "tags": [ "AIOps", "Artificial Intelligence", "Machine Learning", "B2B", "API" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2023", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/poplarml", "api": "https://yc-oss.github.io/api/batches/winter-2023/poplarml.json" }, { "id": 27828, "name": "Scanbase", "slug": "scanbase", "former_names": [ "Scanbase", "Inc." ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c9177f461ffabba1796fab772ec9f376ad91bf4e.png", "website": "https://www.scanbase.com", "all_locations": "Los Angeles, CA, USA", "long_description": "Scanbase makes it easy for medical companies to convert photos of rapid diagnostic tests into results. We do this by providing a simple API that any medical company can access.\r\n", "one_liner": "The API for Diagnostic Test Analysis (COVID-19, FLU, RSV, STD,…", "team_size": 10, "industry": "Healthcare", "subindustry": "Healthcare -> Diagnostics", "launched_at": 1670991822, "tags": [ "Machine Learning", "Computer Vision", "Health Tech", "Telemedicine", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2023", "status": "Active", "industries": [ "Healthcare", "Diagnostics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/scanbase", "api": "https://yc-oss.github.io/api/batches/winter-2023/scanbase.json" }, { "id": 27839, "name": "Cosine", "slug": "cosine", "former_names": [ "Buildt" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4e00745e7a3c3ee63862572e35ef2d37f8197af5.png", "website": "http://www.cosine.sh", "all_locations": "London, England, United Kingdom", "long_description": "Cosine is a fully agentic SWE that allows you to instantly work on every single ticket at once, asynchronously. ", "one_liner": "Fully Agentic SWE", "team_size": 12, "industry": "B2B", "subindustry": "B2B", "launched_at": 1670878872, "tags": [ "Artificial Intelligence", "Developer Tools", "Generative AI", "Machine Learning", "NLP" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2023", "status": "Active", "industries": [ "B2B" ], "regions": [ "United Kingdom", "Europe", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": true, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/cosine", "api": "https://yc-oss.github.io/api/batches/winter-2023/cosine.json" }, { "id": 27867, "name": "DataSuite", "slug": "datasuite", "former_names": [ "Extensional AI", "Extensional", "Extensional AI", "Anarchy AI", "Anarchy", "Anarchy Labs", "TruthSuite" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/98dc541fc5fbbef1e6c9baee61264602e4e64531.png", "website": "https://truthsuite.com", "all_locations": "New York, NY, USA; Remote", "long_description": "DataSuite provides a way to manage and collect multi-terabyte multi-media datasets, and train generative models (diffusion, gan, interactive video) models based on them. \r\n\r\nWe make it trivial for non-technical builders to create their own networks by providing an instant way to collect with AI without worrying about data formats, unzipping power, caching, or data locality.", "one_liner": "Dataset Management for AI Trainers", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Legal", "launched_at": 1669080392, "tags": [ "Artificial Intelligence", "Developer Tools", "Generative AI", "Machine Learning", "DevOps" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2023", "status": "Active", "industries": [ "B2B", "Legal" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": true, "url": "https://www.ycombinator.com/companies/datasuite", "api": "https://yc-oss.github.io/api/batches/winter-2023/datasuite.json" }, { "id": 27906, "name": "1stCollab", "slug": "1stcollab", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/38bfe8c1abadf254cda7e353f68089f57109eaec.png", "website": "https://1stcollab.com/", "all_locations": "San Francisco, CA, USA", "long_description": "1stCollab is the first influencer platform that fully automates and optimizes every aspect of your influencer marketing program. We’ve helped hundreds of startups launch their first campaigns and enabled larger brands to scale to thousands of influencers, while saving them over $1M annually in influencer spend.\r\n\r\nWhat we offer:\r\n- Smart search & recommendations – Instantly connect with thousands of relevant influencers.\r\n- Full campaign automation – From outreach and negotiations to contracts, payments, and taxes, we handle it all.\r\n- Real-time performance tracking – Monitor conversions, revenue, and run A/B tests with detailed reporting.", "one_liner": "Performance-Optimized Influencer Marketing at Scale", "team_size": 11, "industry": "B2B", "subindustry": "B2B -> Marketing", "launched_at": 1671641116, "tags": [ "Artificial Intelligence", "Machine Learning", "Marketing", "Advertising", "Creator Economy" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2023", "status": "Active", "industries": [ "B2B", "Marketing" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": true, "url": "https://www.ycombinator.com/companies/1stcollab", "api": "https://yc-oss.github.io/api/batches/winter-2023/1stcollab.json" }, { "id": 27925, "name": "222", "slug": "222", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2e693471ebf0087cdb9edcdba2657ef0066b1a88.png", "website": "https://222.place", "all_locations": "New York, NY, USA", "long_description": "an IRL marketplace facilitating social experiences at local venues/events through AI recommendations.", "one_liner": "the AI social facilitator for offline human to human interactions", "team_size": 16, "industry": "Consumer", "subindustry": "Consumer", "launched_at": 1668648558, "tags": [ "Artificial Intelligence", "Machine Learning", "Marketplace", "Consumer", "Social" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2023", "status": "Active", "industries": [ "Consumer" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/222", "api": "https://yc-oss.github.io/api/batches/winter-2023/222.json" }, { "id": 27938, "name": "Boundary", "slug": "boundary", "former_names": [ "Gloo", "Gloo Chat", "Gloo" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7d66bb51ef2922c834b2fbb6de2b175e7a85b8f8.png", "website": "https://www.boundaryml.com", "all_locations": "Seattle, WA, USA", "long_description": "Boundary is building BAML -- a programming language to build AI agents.\r\n\r\nWe used to code in assembly, and moved on to C.\r\nFrom C, we moved on to higher level languages like Python.\r\nNow we are going from Python to natural language.\r\n\r\nWhat does the code look like when 50% of the business decisions is decided by an AI agent / prompts? How do you test these AI components? We made BAML to address these problems.\r\n\r\nBAML helps has built-in tools to test, observe, and work with structured LLM outputs / tool calling natively in the language 10x faster. With BAML you can also instantly parallelize LLM Calls, or react to certain events or changes in your pipelines, without having to write any boilerplate. It's like using 'React' for AI.\r\n\r\nBAML code can used from any other language -- providing a standardized way to organize and declare any LLM or AI code.", "one_liner": "The programming language for AI", "team_size": 10, "industry": "B2B", "subindustry": "B2B", "launched_at": 1678219068, "tags": [ "Artificial Intelligence", "Developer Tools", "Generative AI", "Machine Learning", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2023", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/boundary", "api": "https://yc-oss.github.io/api/batches/winter-2023/boundary.json" }, { "id": 27966, "name": "CombineHealth", "slug": "combinehealth", "former_names": [ "Oodles.ai", "upTrain AI", "UpTrain", "UpTrain AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3300df884c68b249e62977103a165c1536ec5e0e.png", "website": "https://www.combinehealth.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Preventing revenue leakage in health systems using AI", "one_liner": "Automating Healthcare Revenue Cycle Management with AI Workforce", "team_size": 15, "industry": "Healthcare", "subindustry": "Healthcare -> Healthcare IT", "launched_at": 1675744580, "tags": [ "Artificial Intelligence", "Machine Learning", "Healthcare" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 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": false, "url": "https://www.ycombinator.com/companies/combinehealth", "api": "https://yc-oss.github.io/api/batches/winter-2023/combinehealth.json" }, { "id": 28037, "name": "Diffuse Bio", "slug": "diffuse-bio", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/961a0aa4b25ffd0049a0526af8ad2406763125f4.png", "website": "http://diffuse.bio", "all_locations": "San Carlos, CA, USA", "long_description": "Diffuse is building generative AI for protein design. Our mission is to build AI systems that engineer new and useful proteins with unprecedented control and accuracy. Our team has been behind breakthroughs in AI protein design for the past 7 years, including the first experimental validation of AI-generated proteins and diffusion models for protein structure and sequence. ", "one_liner": "Generative AI for protein design", "team_size": 10, "industry": "Healthcare", "subindustry": "Healthcare -> Drug Discovery and Delivery", "launched_at": 1673220633, "tags": [ "AI-powered Drug Discovery", "Deep Learning", "Generative AI", "Machine Learning", "Biotech" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2023", "status": "Active", "industries": [ "Healthcare", "Drug Discovery and Delivery" ], "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": false, "url": "https://www.ycombinator.com/companies/diffuse-bio", "api": "https://yc-oss.github.io/api/batches/winter-2023/diffuse-bio.json" }, { "id": 28112, "name": "Persist AI", "slug": "persist-ai", "former_names": [ "Persist AI", "Persist AI Formulations Corp" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/eeb1e38a6ca6e6061c101deae73f22c28c142596.png", "website": "http://www.persist-ai.com", "all_locations": "Woodland, CA, USA", "long_description": "It takes 5 years for pharma to develop long lasting drug injections for chronic diseases like cancer and diabetes. Persist uses AI-driven automation to reduce formulation development time down to 2 years, a ~50% reduction.", "one_liner": "Developing long-lasting drug formulations 50% faster", "team_size": 6, "industry": "Healthcare", "subindustry": "Healthcare -> Drug Discovery and Delivery", "launched_at": 1671420729, "tags": [ "Machine Learning", "Robotics", "Microfluidics", "Nanotechnology", "Therapeutics" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2023", "status": "Active", "industries": [ "Healthcare", "Drug Discovery and Delivery" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": true, "demo_day_video_public": true, "app_answers": true, "question_answers": false, "url": "https://www.ycombinator.com/companies/persist-ai", "api": "https://yc-oss.github.io/api/batches/winter-2023/persist-ai.json" }, { "id": 28129, "name": "Luca", "slug": "luca", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c1a38009f747692e81bd13516e12a87a399aead1.png", "website": "https://www.askluca.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Pricing Strategy is one of the most powerful levers that retailers have at their disposal to create growth, yet it is underleveraged. Most retail pricing teams settle for making decisions in spreadsheets, shooting in the dark, and working backward from a cost-plus margin target, leaving a LOT of money on the table.\r\n\r\nOur founders experienced these problems at scale when they built pricing tech at Uber that made Uber a billion dollars in profit a year. They realized that retail was lacking the same quality and sophistication of price tooling. So, they built Luca.\r\n\r\nLuca is an AI-powered co-pilot for retail operators, which constantly identifies revenue and profit headroom, makes recommendations for price adjustments and saves countless work hours along the way. \r\n\r\nLuca is backed by Y Combinator, Menlo Ventures, and others.", "one_liner": "The Modern Pricing Engine for Retail", "team_size": 6, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1670277293, "tags": [ "Machine Learning", "SaaS", "Retail" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2023", "status": "Inactive", "industries": [ "B2B", "Retail" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/luca", "api": "https://yc-oss.github.io/api/batches/winter-2023/luca.json" }, { "id": 28808, "name": "PropRise", "slug": "proprise", "former_names": [ "River AI", "River", "Introscopic", "River AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/099267e4ee22818f2d0af078193f368735107d1e.png", "website": "https://www.proprise.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "PropRise is the AI platform for institutional CRE investment teams. We automate the tedious, Excel-heavy workflows that slow down dealmaking: from sourcing to underwriting to due diligence. Our two live products serve 50+ customers including Public Storage: Beacon automates site selection for developers, and Primer extracts financial data from deal packages into structured, model-ready formats, cutting hours of analyst work to minutes. We're expanding across asset classes to become the operating system for CRE dealmaking.", "one_liner": "The AI platform for CRE investment teams", "team_size": 3, "industry": "Real Estate and Construction", "subindustry": "Real Estate and Construction", "launched_at": 1690588132, "tags": [ "Machine Learning", "SaaS", "Real Estate", "B2B", "Analytics" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2023", "status": "Active", "industries": [ "Real Estate and Construction" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/proprise", "api": "https://yc-oss.github.io/api/batches/summer-2023/proprise.json" }, { "id": 28811, "name": "Casca", "slug": "casca", "former_names": [ "CORE Ai", "Cascading AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/db0a05cec73fa1efa5d096d33cfcc210c8930955.png", "website": "https://www.cascading.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Casca is building AGI for Banking.\r\n\r\nOur first product is an AI-native platform transforming small business lending by enabling banks and lenders to originate 10x more loans with 90% less manual effort. We’ve found product market fit already serving top 10 US banks and are scaling our team very quickly.\r\n\r\nSmall businesses are the heart of the American economy. Many banks shy away from providing funding because of the manual effort in pursuing those deals. With us, that changes. We unlock affordable, quick bank funding for the 30M+ small businesses in the US who would otherwise be subject to the high interest rates from predatory online lenders.\r\n\r\nWe are a world-class team of banking & AI experts from Stanford, MIT & Y Combinator. We like to win and we know that the only thing between us and the title is our own ability to improve every day.", "one_liner": "Make Banking Magical", "team_size": 40, "industry": "Fintech", "subindustry": "Fintech", "launched_at": 1691481257, "tags": [ "Artificial Intelligence", "Conversational Banking", "Fintech", "Machine Learning", "Finance" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2023", "status": "Active", "industries": [ "Fintech" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": true, "url": "https://www.ycombinator.com/companies/casca", "api": "https://yc-oss.github.io/api/batches/summer-2023/casca.json" }, { "id": 28837, "name": "Subsets", "slug": "subsets", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ef940e88fb60e59b177570256531952d8e4b1322.png", "website": "https://www.subsets.com", "all_locations": "Copenhagen, Denmark", "long_description": "Subsets is the leading lifecycle growth platform for consumer subscription teams.\r\n\r\nWe are building the AI decisioning layer that unifies and powers the existing growth stack, enabling teams to automate and scale lifecycle experimentation, orchestrate personalized user journeys, and measure impact across retention, engagement, and LTV without engineering support.\r\n\r\nTrusted by consumer subscription businesses like The Atlantic, NBCUniversal, Daily Mail, Matas Group, and Hearst.\r\n\r\nSubsets has raised $6.1m and launched out of Y Combinator’s Summer 2023 batch in San Francisco, and is now based in Copenhagen.", "one_liner": "AI-driven Retention Automation for subscription media businesses.", "team_size": 7, "industry": "B2B", "subindustry": "B2B", "launched_at": 1689562154, "tags": [ "Machine Learning", "B2B", "Enterprise Software", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2023", "status": "Active", "industries": [ "B2B" ], "regions": [ "Denmark", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/subsets", "api": "https://yc-oss.github.io/api/batches/summer-2023/subsets.json" }, { "id": 28838, "name": "GreenTally", "slug": "greentally", "former_names": [ "LogUnify", "DSensei", "Empower" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/673f3845b8ea0c788142227e93c082ac8e4ff91c.png", "website": "https://www.greentally.ai", "all_locations": "San Mateo, CA, USA", "long_description": "GreenTally is a carbon accounting platform built for all businesses that transforms environmental reporting from a complex, expensive ordeal into a streamlined, affordable process. Using LLM, we help companies measure their carbon footprint in hours instead of months.\r\n\r\nGreenTally automates emissions calculations and reporting, enabling businesses to meet regulatory requirements and track reduction targets without the overhead of consultants or dedicated sustainability teams. By making enterprise-grade carbon accounting accessible and practical, GreenTally empowers growing businesses to take control of their sustainability journey.", "one_liner": "Affordable carbon tracking solution for all businesses", "team_size": 2, "industry": "B2B", "subindustry": "B2B", "launched_at": 1690923306, "tags": [ "Artificial Intelligence", "Generative AI", "Machine Learning", "SaaS", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2023", "status": "Inactive", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/greentally", "api": "https://yc-oss.github.io/api/batches/summer-2023/greentally.json" }, { "id": 28891, "name": "Numen", "slug": "numen", "former_names": [ "Cleancard" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/801ff758c035f5849acfdcd35329ec161bd30cef.png", "website": "https://www.numen.com", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "Engineering a future without cancer deaths.", "team_size": 18, "industry": "Healthcare", "subindustry": "Healthcare -> Diagnostics", "launched_at": 1691571179, "tags": [ "Machine Learning", "Biotech", "Healthcare", "Diagnostics", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2023", "status": "Active", "industries": [ "Healthcare", "Diagnostics" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/numen", "api": "https://yc-oss.github.io/api/batches/summer-2023/numen.json" }, { "id": 28936, "name": "Empirical Health", "slug": "empirical-health", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/dd8134cbe5b8ea696157c320672eb55cc8649540.png", "website": "https://empirical.health", "all_locations": "New York, NY, USA", "long_description": "Don't die of heart disease. While heart disease is the #1 killer worldwide, 80% of heart disease is preventable.\r\n\r\nEmpirical's program starts with an advanced lab test with 100+ biomarkers, including ApoB, Lp(a), inflammation, and more. Then, we help you model your lifetime risk of heart disease and generate a plan to reduce your risk to an optimal level. Then we help you achieve that plan.\r\n\r\nEmpirical is licensed, registered, and insured to deliver real medical care in 30+ US states covering 200m+ people. We're growing >25% monthly.", "one_liner": "Don't die of heart disease. Empirical is the first AI-native heart…", "team_size": 4, "industry": "Healthcare", "subindustry": "Healthcare -> Consumer Health and Wellness", "launched_at": 1689658487, "tags": [ "Generative AI", "Machine Learning", "Consumer Health Services", "Healthcare", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2023", "status": "Active", "industries": [ "Healthcare", "Consumer Health and Wellness" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/empirical-health", "api": "https://yc-oss.github.io/api/batches/summer-2023/empirical-health.json" }, { "id": 28940, "name": "Guac", "slug": "guac", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3ffff2e450f7c22939b75b50d62a49acbce05716.png", "website": "https://www.guac.com/", "all_locations": "New York, NY, USA", "long_description": "Guac accurately forecasts grocery demand to help supermarkets order and produce the right amount of inventory — reducing food waste and increasing availability.", "one_liner": "AI-powered forecasting & replenishment for grocery", "team_size": 7, "industry": "B2B", "subindustry": "B2B -> Supply Chain and Logistics", "launched_at": 1688056061, "tags": [ "Grocery", "Machine Learning", "Climate", "Supply Chain" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2023", "status": "Active", "industries": [ "B2B", "Supply Chain and Logistics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/guac", "api": "https://yc-oss.github.io/api/batches/summer-2023/guac.json" }, { "id": 28958, "name": "Rimward", "slug": "rimward", "former_names": [ "Quack AI", "Sourcepulse" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/bd215af97ab581709a04ff6284c6091f29c2058e.png", "website": "https://rimward.ai/", "all_locations": "Paris, Île-de-France, France", "long_description": "Rimward helps operators of solar farms and other remote outdoor infrastructure detect intrusions from existing camera networks. We turn existing CCTV into operator-ready alerts with video verification, so security teams can reduce false alarms, respond faster, and avoid heavy hardware retrofits.\r\n\r\nWe are focused on sites where recurring theft, perimeter intrusion, and low staffing make traditional monitoring noisy and operationally weak. Our approach is software-heavy, field-oriented, and built to work with real site constraints.", "one_liner": "Low-false-positive intrusion detection for remote outdoor sites", "team_size": 1, "industry": "B2B", "subindustry": "B2B -> Security", "launched_at": 1691807496, "tags": [ "Machine Learning", "Computer Vision", "B2B", "Security", "Enterprise" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2023", "status": "Active", "industries": [ "B2B", "Security" ], "regions": [ "France", "Europe", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/rimward", "api": "https://yc-oss.github.io/api/batches/summer-2023/rimward.json" }, { "id": 28968, "name": "Trainy", "slug": "trainy", "former_names": [ "AB Labs" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/78fb6a9f034f5447cc3472b66f6c660fdf0cfa60.png", "website": "https://trainy.ai/", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Goodbye Slurm, Hello Konduktor.\r\n\r\nTrainy Konduktor is a software platform for AI teams to schedule workloads with priority, control resource allocation, and improve GPU reliability. With Konduktor, teams submit jobs to a healthy pool of GPUs, assign job priority with a simple user interface, and never worry about hardware faults again.", "one_liner": "Infrastructure for managing GPU clusters for training/serving.", "team_size": 3, "industry": "B2B", "subindustry": "B2B", "launched_at": 1687891811, "tags": [ "Developer Tools", "Machine Learning", "SaaS", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2023", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/trainy", "api": "https://yc-oss.github.io/api/batches/summer-2023/trainy.json" }, { "id": 29008, "name": "Andromeda Surgical", "slug": "andromeda-surgical", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ad29152e507992c17de56b3d0a62d1fd6769fd3b.png", "website": "http://www.andromedasurgical.com", "all_locations": "San Francisco, CA, USA", "long_description": "We're building autonomous robots to make surgery safe, easier and more efficient. Robots currently perform about 1/4 of surgeries but only help with the physical aspects. We use AI to make surgery cognitively easier. This has far greater potential to improve outcomes and reduce costs. Founded by 3x founders from medtech and autonomous vehicles, we're on track to be the fastest surgical robot to market of all time. First indication is prostate enucleation.", "one_liner": "Autonomous surgical robots", "team_size": 10, "industry": "Healthcare", "subindustry": "Healthcare -> Medical Devices", "launched_at": 1684515035, "tags": [ "Artificial Intelligence", "Hard Tech", "Machine Learning", "Medical Robotics", "Medical Devices" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2023", "status": "Active", "industries": [ "Healthcare", "Medical Devices" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/andromeda-surgical", "api": "https://yc-oss.github.io/api/batches/summer-2023/andromeda-surgical.json" }, { "id": 29154, "name": "Catamaran", "slug": "catamaran", "former_names": [ "Ultravity", "CatX" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b0af944f6ad96c6f8c2095e8c485de560a528833.png", "website": "https://www.trycatamaran.com", "all_locations": "London, England, United Kingdom", "long_description": "Catamaran uses AI to help people make clearer, faster decisions about risk. Our platform brings all internal and external risk data into one easy-to-understand workspace. By automating data gathering, checking, and scenario testing, we help insurers, reinsurers, brokers, and investors quickly understand and manage their risks. Catamaran also provides a regulated marketplace to easily buy, sell, and manage insurance coverage.", "one_liner": "The AI-powered risk decision platform ", "team_size": 5, "industry": "Fintech", "subindustry": "Fintech -> Insurance", "launched_at": 1687023200, "tags": [ "Machine Learning", "Finance", "Analytics", "Insurance", "Investing" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2023", "status": "Acquired", "industries": [ "Fintech", "Insurance" ], "regions": [ "United Kingdom", "Europe", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/catamaran", "api": "https://yc-oss.github.io/api/batches/summer-2023/catamaran.json" }, { "id": 29253, "name": "Andon Labs", "slug": "andon-labs", "former_names": [ "Vectorview" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7330cbaf802a2b7ccf2d046a09809940eb0d1050.png", "website": "https://andonlabs.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Safety from humans in the loop is a mirage. We evaluate, research, and apply AI control in our own real-world deployments of autonomous organizations.\r\n\r\nWe are building the Safe Autonomous Organization. We iteratively launch and scale autonomous organizations, while bridging AI control research with real-world testing.", "one_liner": "Autonomous organizations without humans in the loop", "team_size": 11, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1699380174, "tags": [ "Machine Learning", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2024", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/andon-labs", "api": "https://yc-oss.github.io/api/batches/winter-2024/andon-labs.json" }, { "id": 29296, "name": "Simplex", "slug": "simplex", "former_names": [ "Simplex", "Pansimulate" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/556d5a66ef0386d859db3ad9f500ceeadf756032.png", "website": "https://simplex.sh", "all_locations": "San Francisco, CA, USA", "long_description": "Simplex builds AI agents to handle provider enrollment end-to-end. We automate pulling provider data from CAQH, filling out enrollment forms + uploading licenses via payor portals/email/phone, updating applications when returned for corrections, and performing effective date follow-ups until a final determination is made, all autonomously.", "one_liner": "AI agents to enroll providers with payors", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1723709594, "tags": [ "Machine Learning", "Robotic Process Automation", "B2B", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/simplex", "api": "https://yc-oss.github.io/api/batches/summer-2024/simplex.json" }, { "id": 29365, "name": "Ellipsis", "slug": "ellipsis", "former_names": [ "BitBuilder", "Ellipsis", "ellipsis" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/825caa6d8502745ed1854595552f4f7f1091bb3e.png", "website": "https://ellipsis.dev", "all_locations": "New York City, NY, USA", "long_description": "Ellipsis will help your team merge code 13% faster.\r\n\r\nEllipsis is an AI developer tool that automatically reviews code and fixes bugs on pull requests. It uses LLM agents to catch logical errors, security issues, and can even enforce a team's style guide.\r\n\r\nThe coolest part is that after Ellipsis identifies an issue, developers can tag @ellipsis-dev to have Ellipsis implement the fix. Internally, Ellipsis actually executes the code it generates, just like a human does.\r\n\r\nAs a result, we allow developers to generate working, tested code directly from GitHub/GitLab. ", "one_liner": "AI code reviews & bug fixes", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1706288452, "tags": [ "Artificial Intelligence", "Developer Tools", "Machine Learning", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "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": false, "url": "https://www.ycombinator.com/companies/ellipsis", "api": "https://yc-oss.github.io/api/batches/winter-2024/ellipsis.json" }, { "id": 29375, "name": "Preloop", "slug": "preloop", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/62ebbbabf82f9c9badd0bbcb60f8749d391d5a78.png", "website": "https://www.preloop.com", "all_locations": "Seattle, WA, USA", "long_description": "Only 2 out of 10 ML models make it from experiment to production. Preloop helps automate the process of deployment, helping companies realize more value from their machine learning teams, while focusing teams' attention on science instead of engineering.", "one_liner": "Translate your experimental scripts into production ML services", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1702654646, "tags": [ "Artificial Intelligence", "Deep Learning", "Developer Tools", "Machine Learning", "Data Science" ], "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": false, "url": "https://www.ycombinator.com/companies/preloop", "api": "https://yc-oss.github.io/api/batches/winter-2024/preloop.json" }, { "id": 29442, "name": "Ocular AI", "slug": "ocular-ai", "former_names": [ "AutoflowAI (Zapier for AI Copilots)", "AutoflowAI", "Ocular" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c7d1b7d8fc2f64b1b430932a39db37a61d39131c.png", "website": "https://useocular.com", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "Applied AI Data Research Lab Encoding Human Expertise into Machines…", "team_size": 6, "industry": "B2B", "subindustry": "B2B", "launched_at": 1706216304, "tags": [ "Machine Learning", "Speech Recognition", "Data Engineering", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2024", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": true, "url": "https://www.ycombinator.com/companies/ocular-ai", "api": "https://yc-oss.github.io/api/batches/winter-2024/ocular-ai.json" }, { "id": 29460, "name": "Ryse", "slug": "ryse", "former_names": [ "RYSE" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b3127fdf5e5c4be37c6ea79ff2812b08ce513d40.png", "website": "https://www.rysemarket.com/", "all_locations": "New York, NY, USA", "long_description": "Ryse is the only marketplace where investors who want to buy leases can trade with real estate operators who want to sell leases.", "one_liner": "The secondary market for real estate leases", "team_size": 13, "industry": "B2B", "subindustry": "B2B", "launched_at": 1711502260, "tags": [ "Fintech", "Machine Learning", "Marketplace", "B2B", "Proptech" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2024", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/ryse", "api": "https://yc-oss.github.io/api/batches/winter-2024/ryse.json" }, { "id": 29523, "name": "K-Scale Labs", "slug": "k-scale-labs", "former_names": [ "dpsh" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/9a76d2d8803d634b3e622a584f55e531a3e72f45.png", "website": "https://kscale.dev/", "all_locations": "San Francisco, CA, USA", "long_description": "We're building humanoid robots to do most of what you find boring or tedious. We have an open-source design which we are releasing to the public, which is capable of walking, talking and manipulating objects.", "one_liner": "Open-source humanoid robots", "team_size": 10, "industry": "Consumer", "subindustry": "Consumer -> Consumer Electronics", "launched_at": 1711580332, "tags": [ "Machine Learning", "Robotics", "Consumer", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2024", "status": "Inactive", "industries": [ "Consumer", "Consumer Electronics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/k-scale-labs", "api": "https://yc-oss.github.io/api/batches/winter-2024/k-scale-labs.json" }, { "id": 29573, "name": "Undermind", "slug": "undermind", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2e44c4453098a5caed0988fdf2dff5b898cdcac4.png", "website": "https://www.undermind.ai", "all_locations": "San Francisco, CA, USA", "long_description": "At Undermind, we're building a search engine that can handle extremely complex questions. It’s geared at experts, like research scientists and doctors, who need to find very specific resources to solve high-stakes problems. \r\n\r\nWe’ve rebuilt search from the ground up to address this. Our new approach employs high-quality LLMs to adaptively explore a database, mimicking how a human researcher carefully discovers information. This approach dramatically outperforms (by 10-50x) traditional keyword search and other modern AI-based retrieval methods.\r\n\r\nOur first target users are the 50 million researchers searching for scientific literature on PubMed and Google Scholar every month. We’ve have paying users across fields like medicine, ML, biotech, finance, and more.", "one_liner": "An AI agent for scientific research", "team_size": null, "industry": "B2B", "subindustry": "B2B", "launched_at": 1718632251, "tags": [ "Machine Learning", "Biotech", "Search", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/undermind", "api": "https://yc-oss.github.io/api/batches/summer-2024/undermind.json" }, { "id": 29665, "name": "Cloudglue", "slug": "cloudglue", "former_names": [ "Aviary", "CloudGlue" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/83e6dd01545303c123ca60f1dcf8bdc7566497c5.png", "website": "https://cloudglue.dev", "all_locations": "San Francisco, CA, USA", "long_description": "Cloudglue is the video context layer for AI. We make it easy for your AI to understand video.\r\n- Tinycloud - your AI agent for video, now open for beta: https://tinycloud.cloudglue.dev\r\n- Developer API Platform: https://cloudglue.dev\r\n", "one_liner": "The video context layer for AI.", "team_size": 4, "industry": "B2B", "subindustry": "B2B", "launched_at": 1723146818, "tags": [ "Developer Tools", "Machine Learning", "Video", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/cloudglue", "api": "https://yc-oss.github.io/api/batches/summer-2024/cloudglue.json" }, { "id": 29673, "name": "Storia AI", "slug": "storia-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b303aec8b08b8ee5b7c074ef02f910506fd73654.png", "website": "https://storia.ai", "all_locations": "San Francisco, CA, USA", "long_description": "With AI increasingly automating away code generation, software engineers will spend more time reading, judging, and architecting code rather than writing it. Storia is building an open-source copilot that knows a company's codebase and its context.\r\n\r\nWe are starting with Sage, a Perplexity-like agent for helping developers understand, judge, and generate software. Given an existing codebase, developers can ask Sage questions such as:\r\n1) Given my project’s SLA and latency constraints, what is the appropriate underlying vector database to use? How would I incorporate it into my existing codebase?\r\n2) Why should I pick Redis over Milvus as my underlying vector store?\r\n3) Does this codebase in our organization still work and what steps are required for a complex integration with another library?\r\n\r\nSage’s answers are directly supported by documentation and external references like GitHub, Stack Overflow, technical design documents, and project management software, preventing hallucinations. Today, Sage has up-to-date knowledge about open-source repositories (indexed daily). Tomorrow it will have a deep understanding of every line of code on the Internet. For teams, Sage will know about your private codebase too.\r\n\r\nNo group has yet solved how to build an AI system that comprehends a codebase and its context and can empower every developer to architect better code, faster. This requires new research advances because vanilla RAG and out-of-the-box LLMs aren’t going to cut it. \r\n\r\nWe have 20+ years of software engineering and AI research experience. Julia worked on precursors of Gemini using contextual neural techniques before they were called “RAG” (and applied it to products like Google Keyboard and Pixel phones). Mihail built the earliest LLMs at Amazon Alexa and launched the first contextual deep learning conversational AI system in production at Alexa.\r\n", "one_liner": "Open source AI copilot that knows your company's code and its context", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1724629645, "tags": [ "Artificial Intelligence", "Developer Tools", "Machine Learning", "SaaS" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/storia-ai", "api": "https://yc-oss.github.io/api/batches/summer-2024/storia-ai.json" }, { "id": 29687, "name": "MinusX", "slug": "minusx", "former_names": [ "minusone.ai", "minusx.ai" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/92dbd9d186e22d922d985755f90407e21859378a.png", "website": "https://minusx.ai", "all_locations": "San Francisco, CA, USA", "long_description": "MinusX is a state-of-the-art data agent that can build the best dashboards for your data, and notify you when something's up. You can interrogate all your data on our open source BI platform via Slack or MCP. Connect your data, and put agents to work.", "one_liner": "Open source agentic BI for founders", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1722024736, "tags": [ "Artificial Intelligence", "Machine Learning", "Analytics", "Data Science", "AI Assistant" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "B2B", "Analytics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/minusx", "api": "https://yc-oss.github.io/api/batches/summer-2024/minusx.json" }, { "id": 29698, "name": "AutoPallet Robotics", "slug": "autopallet-robotics", "former_names": [ "Anteatr Robotics" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d2f0c4ca0e1ee62abec263fe32fc601c69e08139.png", "website": "https://autopallet.bot", "all_locations": "San Francisco, CA, USA", "long_description": "We’re building the next generation of warehouse robotics.\r\n\r\nIn the US today, retailers spend approximately $10B per year paying human laborers to pick up and move cardboard boxes in warehouses. Existing solutions for automating this are expensive and difficult to install, which is why manual operation is still so prevalent.\r\n\r\nOur solution is different. We make swarms of small mobile robots that install into existing warehouses to provide a low-cost and robust automation solution for case picking and mixed-SKU palletization. Our novel technology allows these robots to be installed and operate at significantly lower cost than existing solutions while being both flexible and robust.", "one_liner": "We make robots that move boxes in warehouses", "team_size": 6, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1723496700, "tags": [ "Hard Tech", "Machine Learning", "Warehouse Management Tech", "Swarm Robotics", "Automation" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": true, "url": "https://www.ycombinator.com/companies/autopallet-robotics", "api": "https://yc-oss.github.io/api/batches/summer-2024/autopallet-robotics.json" }, { "id": 29735, "name": "FINNY AI", "slug": "finny-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f2d0e659d5d03f52a35513c7fe53a3701c771832.png", "website": "https://www.finny.com/", "all_locations": "New York, NY, USA", "long_description": "FINNY is the AI-native organic growth engine for financial advisors, focused on helping them grow their practices\r\n \r\nOur goal is to empower financial advisors to reach the right potential clients at the right time, with the right message. We are building a world where anyone who wants financial advice can connect with the right advisor, while helping advisors ensure organic growth, the most existential problem advisors face. \r\n \r\nThe organic growth process has historically been highly inefficient and full of noise. Advisors often waste 60+ hours of business development to convert 1 new client. \r\n\r\nAt FINNY, we are certain we can do better with AI. With our tool, advisors can:\r\n- Identify prospects within their target niche, aggregating thousands of data points per lead\r\n- Prioritize prospects based on their predicted likelihood of converting using F-Score, a score unique to each advisor and prospect pair\r\n- Automate the outreach and meeting scheduling with their high priority prospects\r\n\r\nIn essence, FINNY does all the rote work for the advisors, letting them focus on what actually matters: the client relationship.", "one_liner": "The organic growth engine for financial advisors ", "team_size": 35, "industry": "Fintech", "subindustry": "Fintech -> Asset Management", "launched_at": 1716852989, "tags": [ "Fintech", "Machine Learning", "Finance", "Sales Enablement", "Automation" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "Fintech", "Asset Management" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/finny-ai", "api": "https://yc-oss.github.io/api/batches/summer-2024/finny-ai.json" }, { "id": 29754, "name": "Conductor Quantum", "slug": "conductor-quantum", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6f87b0dddb05a92646b51780f21648d12f3019bf.png", "website": "https://www.conductorquantum.com", "all_locations": "San Francisco, CA, USA", "long_description": "Conductor Quantum is building quantum superintelligence: AI that operates quantum computers to make scientific discoveries beyond human reach.\r\n\r\nQuantum computers let us understand the world at its most fundamental level, the path to new drugs, new materials, and discoveries no human can reach alone. \r\n\r\nA quantum computer is the perfect simulator of nature: it encodes the logic of reality into a programmable machine, atom by atom, electron by electron. Give AI that simulator and you open the door to discovery.\r\n\r\nThe bottleneck is operating the hardware. Today, engineers spend days or weeks by hand to bring a chip to operating conditions for just two qubits. A qubit is the information-carrying unit of a quantum computer, the equivalent of a bit in a classical one, and a useful machine needs billions. \r\n\r\nRemoving the human from that loop is only half the problem. Every command an AI sends to a quantum computer must be optimised for the specific hardware it runs on.\r\n\r\nWe build the AI that operates quantum computers and tunes every machine it runs on. That is the path to quantum superintelligence.", "one_liner": "AI that operates quantum computers for scientific discovery", "team_size": 4, "industry": "Industrials", "subindustry": "Industrials", "launched_at": 1718219316, "tags": [ "Artificial Intelligence", "Hard Tech", "Machine Learning", "Quantum Computing", "Semiconductors" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "Industrials" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": true, "url": "https://www.ycombinator.com/companies/conductor-quantum", "api": "https://yc-oss.github.io/api/batches/summer-2024/conductor-quantum.json" }, { "id": 29791, "name": "Cartage", "slug": "cartage", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3d0afccc0962e52bb6440d323cf8b43f42b8a268.png", "website": "https://cartage.ai", "all_locations": "San Francisco, CA, USA", "long_description": "Cartage is the future of freight coordination. Transparent, tech-driven and eliminating the need for human coordinators.", "one_liner": "Autonomous freight coordination", "team_size": 12, "industry": "B2B", "subindustry": "B2B -> Supply Chain and Logistics", "launched_at": 1716915052, "tags": [ "Machine Learning", "Workflow Automation", "Logistics", "Supply Chain", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "B2B", "Supply Chain and Logistics" ], "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": false, "url": "https://www.ycombinator.com/companies/cartage", "api": "https://yc-oss.github.io/api/batches/summer-2024/cartage.json" }, { "id": 29957, "name": "Anglera", "slug": "anglera", "former_names": [ "Angler" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a2dfb2adf611e11737fa14a1b9b4be581858cfc3.png", "website": "https://www.anglera.com/", "all_locations": "San Francisco, CA, USA", "long_description": "At Anglera, we're developing a suite of AI agents to help e-commerce companies run their operations more efficiently. Our flagship agent helps our customers onboard, enrich, and manage their product data, reducing time per product from 15 mins down to 5 seconds.\r\n\r\nWe previously developed ML to automatically enrich millions of products at Uber Eats, and we're now on a mission to automate the most common manual workflows for every e-commerce business.", "one_liner": "AI-Powered Product Data Enrichment", "team_size": 6, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1719875304, "tags": [ "Artificial Intelligence", "Machine Learning", "SaaS", "B2B", "E-commerce" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "B2B", "Retail" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/anglera", "api": "https://yc-oss.github.io/api/batches/summer-2024/anglera.json" }, { "id": 30016, "name": "Zeroframe", "slug": "zeroframe", "former_names": [ "Andoria AI", "Andoria" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3e936e66c47aaa18d5b9994edfdeb20a8146b9b4.png", "website": "https://zeroframe.ai", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "Pushing the boundaries of AI", "team_size": 2, "industry": "B2B", "subindustry": "B2B", "launched_at": 1730323819, "tags": [ "Artificial Intelligence", "Machine Learning" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2024", "status": "Inactive", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/zeroframe", "api": "https://yc-oss.github.io/api/batches/fall-2024/zeroframe.json" }, { "id": 30040, "name": "supercontrast", "slug": "supercontrast", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/790820337661ae1bc9c065bae89b47e0ad126432.png", "website": "https://supercontrast.com/", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "At Hive we worked on a product called Gencraft, an ai art generator we ramped from 0 to $1M ARR in 6 months. This inspired us to build supercontrast, an AI Copilot which empowers anyone to create and refine high quality designs and assets. ", "one_liner": "AI Co-Pilot for Design", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1727282803, "tags": [ "Machine Learning", "Design", "Design Tools" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2024", "status": "Inactive", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/supercontrast", "api": "https://yc-oss.github.io/api/batches/fall-2024/supercontrast.json" }, { "id": 30045, "name": "Archil", "slug": "archil", "former_names": [ "Neptune Storage", "Regatta Storage" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0695554aaa43f831a6d970c73486aad8f7a9101f.png", "website": "https://archil.com", "all_locations": "San Francisco, CA, USA", "long_description": "Archil transforms S3 buckets into a 30x faster, unlimited, local disk. Archil enables AI, analytics, and serverless applications to instantly access massive data sets without waiting for data transfer. Researchers use Archil for shareable, local storage of data set and model versions that never runs out of capacity.", "one_liner": "The high-performance file system that connects AI to data", "team_size": 11, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1727196277, "tags": [ "Developer Tools", "Machine Learning", "Big Data", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2024", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/archil", "api": "https://yc-oss.github.io/api/batches/fall-2024/archil.json" }, { "id": 30048, "name": "Matcha", "slug": "astrix-health", "former_names": [ "Astrix Health" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/03a2402a95d35a5f582628b40db3166e9aba2e26.png", "website": "https://www.matcha-health.com", "all_locations": "New York, NY, USA", "long_description": "We're building Matcha, the faster, smarter way to hire clinical talent—helping hospitals find active, qualified candidates at a fraction of the time and cost of job boards or headhunters.\r\n\r\nMatcha engages candidates at scale, matching them to your organization by qualifications and cultural fit. Recruiters save time, hospitals save money, and candidates get a better experience—a radically better hiring model for everyone involved.", "one_liner": "The best way to hire clinical talent.", "team_size": 2, "industry": "Healthcare", "subindustry": "Healthcare", "launched_at": 1728327995, "tags": [ "Machine Learning", "Marketplace", "Recruiting", "Healthcare", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2024", "status": "Active", "industries": [ "Healthcare" ], "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": false, "url": "https://www.ycombinator.com/companies/astrix-health", "api": "https://yc-oss.github.io/api/batches/fall-2024/astrix-health.json" }, { "id": 30079, "name": "Moonshine", "slug": "moonshine", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b168616a2e0ef551e8a1be5dfe50f9700bc903c0.png", "website": "https://usemoonshine.com", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "Extending AI to interact with the real world", "team_size": 2, "industry": "B2B", "subindustry": "B2B", "launched_at": 1729546253, "tags": [ "Artificial Intelligence", "Machine Learning" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2024", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/moonshine", "api": "https://yc-oss.github.io/api/batches/fall-2024/moonshine.json" }, { "id": 30103, "name": "Metreecs", "slug": "metreecs", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0896c8d6a3292048c3275f782ddd6f5a282d3e4a.png", "website": "https://www.metreecs.com", "all_locations": "", "long_description": "Metreecs helps retailers plan, buy, and allocate products using AI-demand forecasting. We prevent overstock and out-of-stock situations, allowing clients to eliminate waste, free up capital, and drive higher sales.", "one_liner": "AI-powered demand forecasting for retail", "team_size": 6, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1729012958, "tags": [ "Machine Learning", "Retail Tech", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2024", "status": "Active", "industries": [ "B2B", "Retail" ], "regions": [ "Unspecified" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/metreecs", "api": "https://yc-oss.github.io/api/batches/fall-2024/metreecs.json" }, { "id": 30240, "name": "Bezel", "slug": "bezel", "former_names": [ "Replenish" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6fff4fb87d06a4a76e786b38906a07e576147ff8.png", "website": "https://www.trybezel.com/", "all_locations": "New York, NY, USA", "long_description": "Bezel helps fashion brands create virtual photo/video shoots with AI. \r\n\r\nUpload images of clothes, select the human you want to model it, and Bezel generates pictures and videos that rival a full studio production. \r\n\r\nEvery detail of the clothing is rendered flawlessly. Try it for yourself.", "one_liner": "Digital AI humans that model clothes for e-commerce brands.", "team_size": 1, "industry": "B2B", "subindustry": "B2B", "launched_at": 1755619154, "tags": [ "Generative AI", "Machine Learning", "Marketing" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2025", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/bezel", "api": "https://yc-oss.github.io/api/batches/winter-2025/bezel.json" }, { "id": 30247, "name": "Osmosis", "slug": "osmosis", "former_names": [ "Gulp" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0e0e653e5da051b7c87a56070249ad76479b0594.png", "website": "https://osmosis.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Osmosis is a post-training platform that helps companies fine-tune language models using reinforcement learning. We work with fast-growing AI companies to train task/domain-specific models that beat foundation models on performance, cost, and latency. Our platform handles compute orchestration, reward modeling, and training run observability as a CLI-based product usable by developers and agents. ", "one_liner": "Reinforcement Learning (RL) for AI Agents", "team_size": 6, "industry": "B2B", "subindustry": "B2B", "launched_at": 1737656598, "tags": [ "Artificial Intelligence", "Machine Learning", "Reinforcement Learning", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2025", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/osmosis", "api": "https://yc-oss.github.io/api/batches/winter-2025/osmosis.json" }, { "id": 30251, "name": "Mecha Health", "slug": "mecha-health", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e851087b2c25e5bd175d39d8631791d74e04ebb1.png", "website": "https://www.mecha-health.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Mecha Health builds foundation models to automate x-ray analysis for radiologists. We take medical images and process them using proprietary models to produce accurate draft medical reports. Our first model was built in less than two months, and beat Microsoft, Google, and OpenAI on clinical accuracy metrics. On top of that, it’s two orders of magnitude smaller and trained with a quarter of the data.\r\n\r\nWe are partnering with the largest privately owned radiology practice in the US and a multinational tele-radiology company to provide them with their own foundation model, enabling their radiologists to go from reading 1 scan per hour to 1 scan every 5 minutes. By charging on a per scan basis, x-ray report generation represents a 40B+ market opportunity. ", "one_liner": "Foundation models to automate x-ray analysis for radiologists", "team_size": 4, "industry": "Healthcare", "subindustry": "Healthcare", "launched_at": 1737153298, "tags": [ "Artificial Intelligence", "Machine Learning", "Computer Vision", "Health Tech", "Healthcare" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2025", "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": false, "url": "https://www.ycombinator.com/companies/mecha-health", "api": "https://yc-oss.github.io/api/batches/winter-2025/mecha-health.json" }, { "id": 30271, "name": "Mundo AI", "slug": "mundo-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/31474af1f951c6780af0608ab7ed6a5b739d95bf.png", "website": "https://mundoai.world", "all_locations": "San Francisco, CA, USA", "long_description": "AI models are terrible in non-English languages because it's nearly impossible to find training data in other languages. So, we're building the world's largest and highest-quality multilingual data library.", "one_liner": "High Quality Multilingual Training Data for AI Models", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1739847539, "tags": [ "Artificial Intelligence", "Machine Learning", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2025", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/mundo-ai", "api": "https://yc-oss.github.io/api/batches/winter-2025/mundo-ai.json" }, { "id": 30286, "name": "Nitrode", "slug": "nitrode", "former_names": [ "Roach AI", "Inception Technologies" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/514545bed169ad1eb626571d7e0d77375b33f656.png", "website": "https://www.nitrode.com", "all_locations": "San Francisco, CA, USA", "long_description": "Nitrode builds high-quality game data to train and evaluate LLMs and agents on spatial and temporal reasoning. Today’s models are trained on static text and images, but struggle to understand how the world evolves over time. We create small, fully specified game environments that generate ground-truth data on state, transitions, and hidden dynamics. This enables AI systems to move beyond simple pattern matching, incorporating memory, causality, and multi-step reasoning to create more reliable agents in dynamic environments.", "one_liner": "Data for reasoning agents in dynamic environments", "team_size": 6, "industry": "B2B", "subindustry": "B2B", "launched_at": 1738144366, "tags": [ "Machine Learning", "B2B", "Data Engineering", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2025", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/nitrode", "api": "https://yc-oss.github.io/api/batches/winter-2025/nitrode.json" }, { "id": 30298, "name": "Artificial Societies", "slug": "artificial-societies", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3f1ebd1806463e3909d4a1f7b197b6c3788ebf4c.png", "website": "https://societies.io", "all_locations": "London, England, United Kingdom", "long_description": "Artificial Societies simulates how large groups of people respond to opinion surveys and react to information. We help global F100 enterprises anticipate how their most important stakeholders react to their most important decisions: from how investors and opinion-leaders react to comms messaging, to how high-value customers react to marketing strategies.\r\n\r\nWe are experts in human behaviour. James, our Founder and CEO, is a Cambridge psychologist and data scientist who led the seminal paper that studied how 33,000 AI chatbots interact. Patrick, our Founder and Chief Product Officer, is an Applied Behavioural Scientist with years of experience helping F500 enterprises conduct market research. They are joined by a team of behavioural scientists, social scientists, and political scientists, all with a passion for uniting technology and an understanding of humanity.\r\n\r\nWe know that every public-facing enterprise decision has million-dollar consequences. From how to position towards opinion-leaders, industry peers, and policymakers, to which marketing content to invest in, knowing how stakeholders would react matters. But traditional market research methods are too slow, too expensive, and often just fail to\r\nreach the stakeholders that truly matter.\r\n\r\nWe spend our lives solving this problem. Our offering is that we build bespoke AI\r\nsimulations of high-value audiences, for insights on questions no one else can answer. We’ve built up over 2.5 million AI personas that are all grounded in real human behaviour – not just what people say, but also what they do. \r\n\r\nBut our enterprise partners choose us not just because we have achieved 95% accuracy in simulating human opinions compared to human self-replication - more importantly, they choose us because of our ability to deliver impossible research projects. Such as having insights in under 24 hours, such as being able to test sensitive strategies on high-value audiences with 100% security, without human risk.\r\n\r\nAs a result, we’ve delivered over 18 million responses to global Fortune 100 enterprises, that helped shape over 100 million dollars’ worth of decisions ranging from global expansion strategies, product positioning, advertising, and strategic communications.\r\n\r\nOur vision of Artificial Societies is a Societal World Model that enables infinite experimentation, so that every organisation can have awareness of outcomes, before making a decision. No planes fly without a wind-tunnel; no medicines are approved without clinical trials; and yet, the biggest decision societies face today are taken as bets. We see Artificial Societies as a historically inevitable technology, and see it as our lives' mission to bring it to life.", "one_liner": "We build networks of AI personas that simulate stakeholder opinions", "team_size": 6, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1739843143, "tags": [ "Artificial Intelligence", "Machine Learning", "SaaS", "B2B", "Market Research" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2025", "status": "Active", "industries": [ "B2B", "Analytics" ], "regions": [ "United Kingdom", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/artificial-societies", "api": "https://yc-oss.github.io/api/batches/winter-2025/artificial-societies.json" }, { "id": 30400, "name": "Plexe", "slug": "plexe", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4911874a37ff01bfa27bb33e5f83f49e6970068e.png", "website": "https://plexe.ai", "all_locations": "London, England, United Kingdom", "long_description": "Plexe builds predictive ML models from a problem description. It connects to data sources, conducts experiments, evaluates and deploys the models to an API endpoint.", "one_liner": "Open-source agents to build predictive ML models from a prompt", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1745031118, "tags": [ "Machine Learning", "Data Science", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Spring 2025", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United Kingdom", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/plexe", "api": "https://yc-oss.github.io/api/batches/spring-2025/plexe.json" }, { "id": 30402, "name": "Kashikoi", "slug": "kashikoi", "former_names": [ "EigenAI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/bcf95c28a8d2140be9982bdbaf6aa05199441da7.png", "website": "https://www.getkashikoi.com", "all_locations": "San Francisco, CA, USA", "long_description": "Kashikoi is a simulation engine to benchmark AI agents. We generate CPU friendly world models that autonomously interview agents and generate deep behavioral assessments. We built a similar technology at Moveworks which was used to ship 250+ enterprise agents to customers daily.", "one_liner": "Simulation Engine for Benchmarking AI Products", "team_size": 2, "industry": "B2B", "subindustry": "B2B", "launched_at": 1748454120, "tags": [ "Developer Tools", "Generative AI", "Machine Learning", "AI" ], "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": false, "url": "https://www.ycombinator.com/companies/kashikoi", "api": "https://yc-oss.github.io/api/batches/spring-2025/kashikoi.json" }, { "id": 30433, "name": "The Robot Learning Company", "slug": "the-robot-learning-company", "former_names": [ "The Robot Learning Company (TRLC)" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fe9d24b61e68d5f71ffc72977fe38d21eece7328.png", "website": "https://www.robot-learning.co/", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "The infrastructure that robot intelligence is built and deployed on.", "team_size": 1, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1747554289, "tags": [ "Machine Learning", "Robotics" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/the-robot-learning-company", "api": "https://yc-oss.github.io/api/batches/spring-2025/the-robot-learning-company.json" }, { "id": 30465, "name": "Photonium", "slug": "photonium", "former_names": [ "PhotonIQ" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/1f9f89a3e11065395408b656b79f12f0fd9868a1.png", "website": "https://www.photoniumoptics.com/", "all_locations": "New York City, NY, USA", "long_description": "Photonium is building software to automate optical system design. We supercharge optics experts with intelligent tooling to reduce costs and deliver faster. We handle the full design stack — from optimization, verification, sourcing, to prototyping — for AR/VR, quantum, biotech, metrology/chip fab, LiDAR, and more. ", "one_liner": "AI-Powered Optical Consulting & Software", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1748388578, "tags": [ "Hard Tech", "Hardware", "Machine Learning", "B2B", "Manufacturing" ], "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": false, "url": "https://www.ycombinator.com/companies/photonium", "api": "https://yc-oss.github.io/api/batches/spring-2025/photonium.json" }, { "id": 30521, "name": "Kairos", "slug": "kairos", "former_names": [ "Janus" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3b44f7b050ecc3ee1451baeb4e0a733b19937955.png", "website": "https://www.withkairos.co/", "all_locations": "San Francisco, CA, USA", "long_description": "Kairos closes the last-mile reliability gap in AI deployments. \r\n\r\nWe bring frontier techniques to companies in critical industries, deploying specialized agents that encode operator expertise and reliably automate their most manual workflows.", "one_liner": "Specialized AI for Critical Industries", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1748466933, "tags": [ "AIOps", "Machine Learning", "Reinforcement Learning", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2025", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/kairos", "api": "https://yc-oss.github.io/api/batches/spring-2025/kairos.json" }, { "id": 30539, "name": "mlop", "slug": "mlop", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3af9294b241ac810c538d00aea0a921d1229099f.png", "website": "https://mlop.ai", "all_locations": "London, England, United Kingdom", "long_description": "A fully open-source, performant and actionable ML model training platform\r\n", "one_liner": "Experiment tracking for training ML models", "team_size": 2, "industry": "B2B", "subindustry": "B2B", "launched_at": 1746826132, "tags": [ "AIOps", "Developer Tools", "Machine Learning", "SaaS" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2025", "status": "Active", "industries": [ "B2B" ], "regions": [ "United Kingdom", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/mlop", "api": "https://yc-oss.github.io/api/batches/spring-2025/mlop.json" }, { "id": 30548, "name": "Theorem", "slug": "theorem-2", "former_names": [ "Aletheia" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4462cecf7e86ccbeaa67750a89b934e1dcf2fa9f.png", "website": "https://theorem.dev", "all_locations": "San Francisco, CA, USA", "long_description": "Theorem is training models that make program verification 10,000 times faster. Using verification as a feedback loop, developers have found zero-days in GPU accelerated code and cryptography implementations, and sped up code migration in legacy systems. If you have complicated code that needs to be correct and secure, sign up for our beta!", "one_liner": "Program verification so even your systems engineers can vibecode", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1747681841, "tags": [ "Machine Learning" ], "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": false, "url": "https://www.ycombinator.com/companies/theorem-2", "api": "https://yc-oss.github.io/api/batches/spring-2025/theorem-2.json" }, { "id": 30558, "name": "BitPatrol", "slug": "bitpatrol", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a49803acbbc34d447ce47d0129bde3f02dd6b0ec.png", "website": "https://www.bitpatrol.io/", "all_locations": "New York, NY, USA", "long_description": "Leverage cutting-edge AI to detect exposed credentials in real time and protect your organization from high-impact data breaches.", "one_liner": "AI-powered code security", "team_size": 1, "industry": "B2B", "subindustry": "B2B -> Security", "launched_at": 1747422859, "tags": [ "DevSecOps", "Machine Learning", "Cybersecurity" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2025", "status": "Acquired", "industries": [ "B2B", "Security" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/bitpatrol", "api": "https://yc-oss.github.io/api/batches/spring-2025/bitpatrol.json" }, { "id": 30649, "name": "Lilac", "slug": "lilac", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/18234851431f8da18d1f087abc867a57412f1a97.png", "website": "https://getlilac.com", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Lilac taps idle GPUs from cloud providers and enterprises, giving startups and researchers cheaper inference while letting companies monetize unused capacity. Fully automated with Kubernetes integration.", "one_liner": "We automatically monetize idle GPUs", "team_size": 4, "industry": "B2B", "subindustry": "B2B", "launched_at": 1754345371, "tags": [ "Artificial Intelligence", "Machine Learning", "Cloud Computing", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2025", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/lilac", "api": "https://yc-oss.github.io/api/batches/summer-2025/lilac.json" }, { "id": 30652, "name": "OnDeck AI", "slug": "ondeck-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/9fb6ad4cbd4cdfac49ff1b40404d7053d5789883.png", "website": "https://www.ondeckai.com", "all_locations": "Vancouver, BC, Canada", "long_description": "OnDeck is the infrastructure layer that makes Vision Language Models accessible and scalable for enterprise. We let organizations instantly find any object, behavior or event, in any footage, without needing to train a model or collect any training data.\r\n\r\nThe Pain: Creating vision models usually takes months: collecting training data, training, then deployment. Worse yet: \r\n+ it’s often impossible to get enough data for a specific task, and \r\n+ even the best cv models struggle to generalize across diverse camera setups, workflows and environments. \r\n\r\nTo overcome these blockers, we bet early on the power of VLMs and built a vision engine that can generalize across any task and doesn’t need any training data. We published a NeurIPS workshop paper showing our new methods with VLMs beat traditional CV even at niche tasks.\r\n\r\nOur current customers include:\r\n- National Defense Organizations\r\n- Robotics Research\r\n- Security cameras\r\n- Behaviour analysis for port monitoring\r\n- Off-shore oil & gas monitoring", "one_liner": "Analyze any footage, without training a model", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1755488960, "tags": [ "Machine Learning", "SaaS", "Computer Vision", "B2B", "Video" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2025", "status": "Active", "industries": [ "B2B", "Analytics" ], "regions": [ "Canada", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/ondeck-ai", "api": "https://yc-oss.github.io/api/batches/summer-2025/ondeck-ai.json" }, { "id": 30662, "name": "DeepAware AI", "slug": "deepaware-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c1f361055ad23340a67d324b48d58339307211fb.png", "website": "https://roboticscenter.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "DeepAware (Silicon Valley Robotics Center roboticscenter.ai) is the fastest way for enterprises and researchers to get robots and robotics parts in the US — 72-hour delivery or Bay Area pickup.\r\n\r\nBeyond hardware, we help teams collect teleoperation data, build reinforcement learning environments, and deploy robots into production. Customers include AI labs, industrial operations, research teams, and event producers.", "one_liner": "Robots, parts & RL environments - delivered in 72 hrs or pickup in SF.", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1753029704, "tags": [ "Artificial Intelligence", "Machine Learning", "Robotics", "Supply Chain", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/deepaware-ai", "api": "https://yc-oss.github.io/api/batches/summer-2025/deepaware-ai.json" }, { "id": 30791, "name": "Spotlight Realty", "slug": "spotlight-realty", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/677917fd980b1f33bfa85125a5b4023b60d9fa41.png", "website": "https://www.spotlight.realty", "all_locations": "San Francisco, CA, USA", "long_description": "We are a full-service sell-side residential brokerage that lists and markets your properties. We also screen and schedule tenants showings with our AI agent for a third of the normal commission. ", "one_liner": "AI powered brokerage reducing residential rental commissions in NYC…", "team_size": 4, "industry": "Real Estate and Construction", "subindustry": "Real Estate and Construction", "launched_at": 1755023391, "tags": [ "Machine Learning", "Real Estate" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2025", "status": "Active", "industries": [ "Real Estate and Construction" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/spotlight-realty", "api": "https://yc-oss.github.io/api/batches/summer-2025/spotlight-realty.json" }, { "id": 30835, "name": "Brickanta", "slug": "brickanta", "former_names": [ "Brickanta AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2f5fc73a5deec1c3a7c627cea71c8345b56ca431.png", "website": "https://www.brickanta.com", "all_locations": "Stockholm, Stockholm County, Sweden", "long_description": "Brickanta – agentic AI for society builders. Hundreds of construction-specific AI agents for project analysis, insights, tenders, procurement, and more. Combine the latest AI technology with your organization's project data, templates, and workflows to identify risks and opportunities early and produce better decision support. Brickanta has raised $8 million from leading AI, construction, and real estate investors behind companies like OpenAI/ChatGPT, Airbnb, Klarna, Spotify, and Plangrid-Autodesk, as well as star investors such as Mario Götze, Anton Osika, and Northzone (see movie and press). The founding team has been building and implementing AI in construction and industry since 2018 at companies such as ABB, Fabege, Husqvarna, IKEA and Konecranes.\r\n", "one_liner": "Agentic AI for Society Builders", "team_size": 11, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1759093006, "tags": [ "Machine Learning", "Construction", "AI", "AI Assistant" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Fall 2025", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "Sweden", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/brickanta", "api": "https://yc-oss.github.io/api/batches/fall-2025/brickanta.json" }, { "id": 30854, "name": "Hyperspell", "slug": "hyperspell", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4149c6afc651c9770fc182e08dde776e24f88554.png", "website": "https://hyperspell.com", "all_locations": "San Francisco, CA, USA", "long_description": "Hyperspell is your Company Brain. AI agents are brilliant and clueless. They ace any test and still have no idea how your company works. Hyperspell connects your tools and synthesizes documents and conversations into a live, permissioned context graph. Any agent can read from it and write back to it like a filesystem, with every fact traced to source.", "one_liner": "Your Company Brain", "team_size": 8, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1760534513, "tags": [ "Machine Learning", "SaaS", "Data Engineering", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Fall 2025", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/hyperspell", "api": "https://yc-oss.github.io/api/batches/fall-2025/hyperspell.json" }, { "id": 30876, "name": "Velum Labs", "slug": "velum-labs", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4539d70682bb12a4a56caa059c5bb83cd4745ad1.png", "website": "https://www.velum-labs.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Velum is the operating system for data quality. Velum automatically monitors and enforces data quality across a company's data stack, so bad data never reaches dashboards. We turn data quality from a manual task into infrastructure that runs itself.\r\n\r\nData trust you can prove. From the pipeline to the boardroom.", "one_liner": "The OS for data quality across any stack", "team_size": 2, "industry": "B2B", "subindustry": "B2B", "launched_at": 1762847882, "tags": [ "Machine Learning", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 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": false, "url": "https://www.ycombinator.com/companies/velum-labs", "api": "https://yc-oss.github.io/api/batches/winter-2026/velum-labs.json" }, { "id": 30895, "name": "Allus AI", "slug": "allus-ai", "former_names": [ "Allus AI Inc." ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e556d72ba8162e6d77731f52ccea802c98b54fa3.png", "website": "https://allus.ai", "all_locations": "Atlanta, GA, USA", "long_description": "Allus builds next-gen vision foundation models that bring real intelligence to manufacturing. Enabling factories to see, understand, and improve production in real time. ", "one_liner": "Transforming manufacturing with our next-gen Vision Foundation Model", "team_size": 3, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1761108820, "tags": [ "Artificial Intelligence", "Machine Learning", "SaaS", "Computer Vision", "Manufacturing" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Fall 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/allus-ai", "api": "https://yc-oss.github.io/api/batches/fall-2025/allus-ai.json" }, { "id": 30928, "name": "Thesis", "slug": "thesis", "former_names": [ "Thesis Labs" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/834b16b30c5de79bf9dbcd0a4819289bfa937936.png", "website": "https://thesislabs.ai", "all_locations": "San Francisco, CA, USA", "long_description": "We are automating AI research and development. Our aim is to help AI researchers uncover the next AlphaFold or build the next Transformer, faster, more systematically, and at scale. We treat discovery not as a matter of luck, but as a combinatorial search problem. Every major breakthrough in AI over the next decade will be made by Thesis.", "one_liner": "Autonomous AI research", "team_size": 3, "industry": "B2B", "subindustry": "B2B", "launched_at": 1762476616, "tags": [ "Hard Tech", "Machine Learning", "Automation", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Fall 2025", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": true, "url": "https://www.ycombinator.com/companies/thesis", "api": "https://yc-oss.github.io/api/batches/fall-2025/thesis.json" }, { "id": 30961, "name": "Arcten", "slug": "arcten", "former_names": [ "Cortex", "ArcTen", "Arc Ten", "ArcTen", "ArcTen, Inc.", "Arcten, Inc." ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b8b85a37c57824f6296369d2840bc02a481f8bf6.png", "website": "https://arcten.com", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "Lab working on long-horizon autonomous research and coding agents", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1761245566, "tags": [ "Deep Learning", "Generative AI", "Machine Learning", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2025", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/arcten", "api": "https://yc-oss.github.io/api/batches/fall-2025/arcten.json" }, { "id": 31010, "name": "Amika", "slug": "amika", "former_names": [ "Fixpoint" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c42840d914de4ea4ec78f647bf0db2e93434ca5d.png", "website": "https://www.amika.dev/", "all_locations": "New York, NY, USA", "long_description": "Amika is infra to build your software factory.\r\n\r\nWe give your team sandboxed AI coding agents in the cloud: the same infrastructure Ramp, Coinbase, and Stripe built in-house. Kick off work from a web UI, CLI, Slack, or API. Use your preferred coding agent (Claude Code, Codex, etc.). Each agent understands your codebase, runs autonomously, and ships real PRs with live previews of the apps it changed. Use it as your daily driver or plug it into your own code-gen pipeline via API.", "one_liner": "Infra to build your own software factory", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1759722442, "tags": [ "Artificial Intelligence", "Machine Learning", "B2B", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2025", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/amika", "api": "https://yc-oss.github.io/api/batches/fall-2025/amika.json" }, { "id": 31168, "name": "Instinct", "slug": "instinct-xyz", "former_names": [ "Assonant" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4f2c4947196f35e938655df560aee5ba21c58b51.png", "website": "https://instinct.xyz", "all_locations": "San Francisco, CA, USA", "long_description": "We believe in the next generation of finance where everyone around the world can access the global market and liquidity from the tip of their hands. \r\n\r\nWe are building the best mobile trading app that will enable this vision. \r\n\r\nHyperliquid is the house of all finance, Instinct is the app of all finance. \r\n\r\nHyperliquid.", "one_liner": "Trade your instinct", "team_size": 5, "industry": "Fintech", "subindustry": "Fintech", "launched_at": 1779953002, "tags": [ "Artificial Intelligence", "Machine Learning", "Trading", "Cryptocurrency" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2026", "status": "Active", "industries": [ "Fintech" ], "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": false, "url": "https://www.ycombinator.com/companies/instinct-xyz", "api": "https://yc-oss.github.io/api/batches/winter-2026/instinct-xyz.json" }, { "id": 31191, "name": "Traverse", "slug": "traverse", "former_names": [ "Clice AI", "Clice" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/35a08dba94f5c7c4efe9e2c566eb21cc8f85b0e1.png", "website": "https://www.traverse.so", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "Research lab solving non-verifiable work", "team_size": 1, "industry": "B2B", "subindustry": "B2B", "launched_at": 1767260558, "tags": [ "Machine Learning", "Reinforcement Learning", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 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": false, "url": "https://www.ycombinator.com/companies/traverse", "api": "https://yc-oss.github.io/api/batches/winter-2026/traverse.json" }, { "id": 32134, "name": "Parasma", "slug": "parasma", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/65a63b540239ee3a5538326d626bcceee19f52d9.png", "website": "https://parasma.com", "all_locations": "San Francisco, CA, USA", "long_description": "We write the algorithms to turn brain cells into compute.", "one_liner": "Training human brain cells for AI compute", "team_size": 1, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1782285260, "tags": [ "Machine Learning", "Neurotechnology", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/parasma", "api": "https://yc-oss.github.io/api/batches/summer-2026/parasma.json" }, { "id": 32650, "name": "Risklytics", "slug": "risklytics", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b0ad1653f775fb272b3481e8715c274f46c2c464.png", "website": "https://www.risklytics.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "We build AI-powered catastrophe risk models that help insurers, reinsurers, and financial institutions better understand and quantify natural disaster risk. Our platform combines continuously updated data, property-level analysis, and synthetic catastrophe simulations to deliver more accurate, transparent, and flexible risk assessments than traditional catastrophe models.", "one_liner": "AI-powered catastrophe risk modeling", "team_size": 2, "industry": "Fintech", "subindustry": "Fintech -> Insurance", "launched_at": 1783123197, "tags": [ "Machine Learning", "B2B", "Climate", "Insurance", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "Fintech", "Insurance" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/risklytics", "api": "https://yc-oss.github.io/api/batches/summer-2026/risklytics.json" } ]