[ { "id": 155, "name": "Insight Data Science", "slug": "insight-data-science", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e2887e0f0ad9804a54eb3d6ed6cb6b819dfed068.png", "website": "http://insightdatascience.com", "all_locations": "Palo Alto, CA, USA", "long_description": "The Insight Data Science Fellows Program is an intensive seven week post-doctoral training fellowship bridging the gap to new careers in Data Science, Data Engineering, Health Data, and AI in Silicon Valley, New York City, Boston, Seattle and across the US with our Remote program. Insight is a Palo Alto based education startup, funded by Y Combinator and SV Angel, with 1000 alumni at hundreds of companies including Facebook, Netflix, LinkedIn, Twitter, The New York Times, Apple, Airbnb, Microsoft, Capital One, NBC, Memorial Sloan Kettering, and many others.", "one_liner": "Turning PhDs & engineers into data scientists & data engineers", "team_size": 11, "industry": "Education", "subindustry": "Education", "launched_at": 1326789868, "tags": [ "Data Science", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2011", "status": "Inactive", "industries": [ "Education" ], "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/insight-data-science", "api": "https://yc-oss.github.io/api/batches/winter-2011/insight-data-science.json" }, { "id": 291, "name": "BackType", "slug": "backtype", "former_names": [ "Backtype" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0ec00079f2609a11308b0e89a7e2ed64081516db.png", "website": "http://backtype.com", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "BackType was an analytics company acquired by Twitter in 2011", "team_size": 0, "industry": "B2B", "subindustry": "B2B -> Marketing", "launched_at": 1326791016, "tags": [ "SaaS", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2008", "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/backtype", "api": "https://yc-oss.github.io/api/batches/summer-2008/backtype.json" }, { "id": 473, "name": "Scuba", "slug": "interana", "former_names": [ "Interana" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/75095731e25d34e505b54386e1fbac0016ef69ea.png", "website": "https://www.scuba.io", "all_locations": "", "long_description": "Scuba is the fast and scalable event-based analytics solution to answer critical business questions about how customers behave and products are used. Interana allows users to analyze and explore the key business metrics that matter most in a data-driven world – such as growth, retention, conversion and engagement – in seconds, rather than the hours or days it often takes with existing solutions. Interana allows customers to discover and investigate these key insights easily through its visual and interactive interface, which makes data analysis a natural extension of everyone’s workflow.", "one_liner": "Analytics for impatient people.", "team_size": 51, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1354492621, "tags": [ "Analytics", "Big Data", "Data Engineering", "Data Visualization" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2013", "status": "Acquired", "industries": [ "B2B", "Analytics" ], "regions": [ "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": true, "question_answers": false, "url": "https://www.ycombinator.com/companies/interana", "api": "https://yc-oss.github.io/api/batches/winter-2013/interana.json" }, { "id": 482, "name": "Fivetran", "slug": "fivetran", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d6b5710a13038fe1daa1421a986e1f4a7839a65a.png", "website": "http://fivetran.com", "all_locations": "Oakland, CA, USA", "long_description": "Fivetran automates data movement out of, into and across cloud data platforms. We automate the most time-consuming parts of the ELT process from extracts to schema drift handling to transformations, so data engineers can focus on higher-impact projects with total pipeline peace of mind. With 99.9% uptime and self-healing pipelines, Fivetran enables hundreds of leading brands across the globe, including Autodesk, Conagra Brands, JetBlue, Lionsgate, Morgan Stanley, and Ziff Davis, to accelerate data-driven decisions and drive business growth. Fivetran is headquartered in Oakland, California, with offices around the world. ", "one_liner": "The leader in automated data movement", "team_size": 1200, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1354492705, "tags": [ "SaaS", "B2B", "Analytics", "Data Engineering" ], "tags_highlighted": [], "top_company": true, "isHiring": false, "nonprofit": false, "batch": "Winter 2013", "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/fivetran", "api": "https://yc-oss.github.io/api/batches/winter-2013/fivetran.json" }, { "id": 488, "name": "Etleap", "slug": "etleap", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/07c9b19241da3d7897596f5f34b6c9baa7c7518e.png", "website": "https://etleap.com", "all_locations": "San Francisco, CA, USA", "long_description": "Etleap is an ETL solution for creating perfect data pipelines from day one. Unlike other enterprise solutions, Etleap doesn’t require extensive engineering work to set up, maintain, and scale. It automates most ETL setup and maintenance work, and simplifies the rest into 10-minute tasks that analysts can own.", "one_liner": "Etleap is an ETL solution for creating perfect data pipelines. ", "team_size": 11, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1354492752, "tags": [ "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2013", "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/etleap", "api": "https://yc-oss.github.io/api/batches/winter-2013/etleap.json" }, { "id": 749, "name": "Mezmo", "slug": "mezmo", "former_names": [ "PushMarket", "LogDNA" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f3a71ea034c7bfc9aef393b47b27829a3413f0b3.png", "website": "https://www.mezmo.com/", "all_locations": "San Jose, CA, USA; Mountain View, CA, USA; Remote", "long_description": "Mezmo, formerly LogDNA, is an observability platform to manage and take action on your data. It ingests, processes, and routes log data to fuel enterprise-level application development and delivery, security, and compliance use cases.\r\n\r\nMezmo was brought to life by three-time co-founders Chris Nguyen and Lee Liu and included in the Winter 2015 batch of Y Combinator. In 2018 the company partnered with tech giant, IBM, to become the sole logging provider for IBM Cloud.\r\n\r\nMezmo is on a mission to empower people who build solutions that shape the world. We’re doing this by delivering a platform that enables enterprises to get more value from their observability data in real time, regardless of source, destination, use case, or scale. We’re not the only ones working on this problem but we have a few things the others don’t.\r\n\r\nWe’re cloud-native and know how to make the most of modern technology like Kubernetes.\r\nWe have scaled a solution from zero to petabyte scale in a short amount of time, while supporting thousands of active users across multiple environments.\r\nWe are hungry for change and are surrounded by enterprises telling us they’re hungry, too.\r\nWe have a kick-ass group of people who are thinking about the problem analytically and are excited to change the observability world for the better.\r\nMezmo has helped some of the world’s most innovative companies transform how they manage their systems and applications. Still, we know that we can help them get more value from their observability data by providing more flexibility and control over how they use it. This will enable teams to spend less time switching between data silos so they can focus on shipping better, more resilient, and secure products.\r\n\r\nWe have momentum on our side. Last year we saw triple digit revenue growth and added 800 new customers to our roster. Recent accolades include being named to YC’s Top Companies, CRN’s 10 Hottest DevOps Startups, and EMA’s Top 3 Observability Platforms.\r\n", "one_liner": "Observability platform to control all of your log data", "team_size": 172, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1416218667, "tags": [ "Developer Tools", "DevSecOps", "SaaS", "Kubernetes", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2015", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "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/mezmo", "api": "https://yc-oss.github.io/api/batches/winter-2015/mezmo.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": 952, "name": "TetraScience", "slug": "tetrascience", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ddb32b2efdb22265a0c610b84a66c92b4e545b61.png", "website": "https://www.tetrascience.com", "all_locations": "Boston, MA, USA; Remote", "long_description": "TetraScience provides the world’s first and only R&D Data Cloud, with a mission to transform life sciences R&D, accelerate discovery, and improve human life. Scientists at global pharma and biotech organizations rely on our innovative Tetra Data Platform for easy access to centralized, harmonized, and actionable scientific data to accelerate their digital lab transformation. With best-in-class SaaS performance, a team of industry innovators, and excellent product/market fit, Tetra is positioned to become an iconic life sciences software company.", "one_liner": "The only R&D data cloud for life sciences", "team_size": 100, "industry": "Healthcare", "subindustry": "Healthcare -> Healthcare IT", "launched_at": 1430204716, "tags": [ "SaaS", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2015", "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/tetrascience", "api": "https://yc-oss.github.io/api/batches/summer-2015/tetrascience.json" }, { "id": 1051, "name": "Gecko Robotics", "slug": "gecko-robotics", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/eb7bd253bc194c1e1245a6c643b86e65d530a53f.png", "website": "https://www.geckorobotics.com", "all_locations": "Pittsburgh, PA, USA; Austin, TX, USA", "long_description": "Gecko Robotics is the pioneer of AI + Robotics [AIR technology], transforming how the world builds, operates, and maintains its most critical infrastructure for a more reliable and sustainable future. Using fixed sensors and robots that climb, crawl, swim, and fly, we combine first-order data layers with the predictive power of AI into a single source of truth for the physical world. Cantilever™ is our operating platform, powered by AIR technology, that empowers teams to achieve operational excellence through actionable data for immediate and long-term planning.", "one_liner": "AI + Robotics for the Built World", "team_size": 230, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1447653915, "tags": [ "Artificial Intelligence", "Robotics", "Energy", "Big Data", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2016", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "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/gecko-robotics", "api": "https://yc-oss.github.io/api/batches/winter-2016/gecko-robotics.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": 1945, "name": "LabelFlow", "slug": "labelflow", "former_names": [ "Sterblue" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/799423cdb14bc1fbe4eb1d647eedf74d0a22e8c7.png", "website": "https://labelflow.ai/", "all_locations": "Nantes, Pays de la Loire, France; Remote", "long_description": "At LabelFlow, we build GitHub for visual data. Our mission is to facilitate and accelerate the development of AI at scale thanks to top-notch labeling tools and a dataset marketplace.", "one_liner": "GitHub for visual data", "team_size": 6, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1525147499, "tags": [ "Computer Vision", "Data Engineering", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2018", "status": "Inactive", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "France", "Europe", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/labelflow", "api": "https://yc-oss.github.io/api/batches/summer-2018/labelflow.json" }, { "id": 11955, "name": "DevFlight", "slug": "devflight", "former_names": [], "small_logo_thumb_url": "/company/thumb/missing.png", "website": "https://devflight.com", "all_locations": "Somerville, MA, USA; Remote", "long_description": "", "one_liner": "Managed equipment data pipelines for manufacturers", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1541122481, "tags": [ "Data Engineering" ], "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", "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/devflight", "api": "https://yc-oss.github.io/api/batches/winter-2019/devflight.json" }, { "id": 12258, "name": "Datamode", "slug": "datamode", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/028000b4921cd21235c9b7b837cd86a36f92a101.png", "website": "http://www.datamode.com", "all_locations": "Seattle, WA, USA", "long_description": "We're building a tool to help data engineers diagnose problems in their data pipelines. Datamode integrates with the technologies you use to provide a single place to start investigating problems and reduce the mean time to diagnosis. This means higher data quality and improved reliability for the business.", "one_liner": "Datamode (datamode.com) is a tool for engineers to instantly diagnose…", "team_size": 1, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1543978906, "tags": [ "Analytics", "Data Engineering" ], "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/datamode", "api": "https://yc-oss.github.io/api/batches/winter-2019/datamode.json" }, { "id": 12549, "name": "Symplex", "slug": "symplex", "former_names": [ "Symplex", "Demigod", "Violet", "communion", "violet", "demigod", "symplex", "demigod" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/33294c2e2a853eb8b88c2102faadf92348a869e3.png", "website": "", "all_locations": "New York, NY, USA", "long_description": "• Acquired by Scale AI\r\n\r\n\r\n", "one_liner": "Applied Reinforcement Learning Research Laboratory", "team_size": 8, "industry": "B2B", "subindustry": "B2B", "launched_at": 1556077735, "tags": [ "Artificial Intelligence", "Data Engineering", "AI Assistant" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2019", "status": "Acquired", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": true, "demo_day_video_public": true, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/symplex", "api": "https://yc-oss.github.io/api/batches/summer-2019/symplex.json" }, { "id": 12598, "name": "Narrator", "slug": "narrator", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/18139ce5e1ad199f99ea66921af1fd68a63f6e95.png", "website": "https://www.narratordata.com/", "all_locations": "New York, NY, USA; Remote", "long_description": "Narrator is an end-to-end platform built on top of the data standard, the Activity Schema and starting at $500/mo. Data analyst are able to build their definitions of their user journey, and use that journey to answer any question that comes up. From there, data can be visualized in a dashboard, used to build a story like analysis, exported and more. \r\n\r\nThe biggest values of Narrator is Speed and Cost reduction. Small teams are able to move fast and answer questions in minutes allowing them to preform the work of very large data teams. All while Narrator is optimized to minimize compute cost of the warehouse.", "one_liner": "The only platform that can prep data to answer EVERY question you…", "team_size": 8, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1556223953, "tags": [ "Analytics", "Big Data", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2019", "status": "Inactive", "industries": [ "B2B", "Infrastructure" ], "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/narrator", "api": "https://yc-oss.github.io/api/batches/summer-2019/narrator.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": 12618, "name": "Embrace", "slug": "embrace", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6c5df7e755694ec01e6b16cfc307e0ddf5712e43.png", "website": "https://embrace.io", "all_locations": "Los Angeles, CA, USA; Remote", "long_description": "*S19 and YCG F21*\r\nEngineering teams shouldn’t be in the dark when it comes to the performance of their web and mobile apps and user experiences. With our industry-leading observability technology, Embrace aims to give SRE and DevOps teams better insight into what matters most – their users – by tying performance data to backend observability insights.\r\n\r\nAs the only user-focused, use-focused observability solution built on OpenTelemetry, Embrace delivers crucial insights across both DevOps and frontend teams to illuminate real customer impact – not just server impact – to deliver the best app experiences. Customers like The New York Times, Marriott, Warby Parker, Masterclass, Home Depot, and Cameo love Embrace’s observability platform because it makes extremely complicated and voluminous data actionable.", "one_liner": "Modern user-focused observability built on OpenTelemetry", "team_size": 62, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1556659657, "tags": [ "Artificial Intelligence", "SaaS", "Open Source", "Data Engineering" ], "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", "Fully Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": true, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/embrace", "api": "https://yc-oss.github.io/api/batches/summer-2019/embrace.json" }, { "id": 12669, "name": "Data Mechanics", "slug": "data-mechanics", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/041cd41aaf413fd601a958566433246e70084357.png", "website": "https://www.datamechanics.co", "all_locations": "Paris, Île-de-France, France", "long_description": "Data Mechanics was acquired by NetApp in 2021 and integrated in the Spot.io product portfolio. Our managed Spark-on-Kubernetes platform is live and running under the name Ocean for Apache Spark: https://spot.io/products/ocean-apache-spark/", "one_liner": "Spark-on-Kubernetes Data Engineering Platform", "team_size": 25, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1556782113, "tags": [ "SaaS", "B2B", "Open Source", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2019", "status": "Acquired", "industries": [ "B2B", "Infrastructure" ], "regions": [ "France", "Europe", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/data-mechanics", "api": "https://yc-oss.github.io/api/batches/summer-2019/data-mechanics.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, 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": 13088, "name": "Polytomic", "slug": "polytomic", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4767968ca9a72ca160b394cd0fb3eba2f5602eb7.png", "website": "https://www.polytomic.com", "all_locations": "San Francisco, CA, USA", "long_description": "Polytomic is a no-code web app to sync data between your internal databases, business systems (e.g. Stripe, Salesforce, etc), data warehouses, spreadsheets, and even HTTP APIs. ", "one_liner": "No-code data syncing between your systems", "team_size": 7, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1612396813, "tags": [ "SaaS", "B2B", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2020", "status": "Active", "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/polytomic", "api": "https://yc-oss.github.io/api/batches/winter-2020/polytomic.json" }, { "id": 13185, "name": "Operator.io", "slug": "operatorio", "former_names": [ "Atana", "Atana Health", "Trimwire", "Operator", "Operator Labs", "Operator" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ddad5e732e1515ab69da4100f7fa6d3a5d491e82.png", "website": "http://operator.io", "all_locations": "New York, NY, USA", "long_description": "Operator.io is the easiest way to set up an OpenClaw agent and connect it to 1000+ different applications like Gmail, Notion, Stripe, and more. Onboard an AI executive assistant that tackles the tasks you know need to be done that you don't have bandwidth for.", "one_liner": "Operator.io is OpenClaw that just works ", "team_size": 6, "industry": "B2B", "subindustry": "B2B", "launched_at": 1583870881, "tags": [ "Generative AI", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 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/operatorio", "api": "https://yc-oss.github.io/api/batches/winter-2020/operatorio.json" }, { "id": 13205, "name": "Logarithm Labs", "slug": "logarithm-labs", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/71c1fab536511f29e3d68a7aa3cadd96e12f41f2.png", "website": "http://www.logarithmlabs.com", "all_locations": "Foster City, CA, USA", "long_description": "Easy button to use data for your daily operations. Power your business workflows with quality data.\r\n\r\nLogarithm Labs helps you turn manual data wrangling and ad-hoc scripts into repeatable pipelines for your operational workflows. Power your workflows with quality data.\r\n\r\nOur product and team of experts do the heavy lifting so that can focus on the business logic that drives your organization.\r\n\r\nTo learn more, contact us at hello@logarithmlabs.com.", "one_liner": "Easy button to use data for your daily operations", "team_size": 2, "industry": "B2B", "subindustry": "B2B", "launched_at": 1584126560, "tags": [ "Developer Tools", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2020", "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/logarithm-labs", "api": "https://yc-oss.github.io/api/batches/winter-2020/logarithm-labs.json" }, { "id": 13211, "name": "Metaplane", "slug": "metaplane", "former_names": [ "Quantifai" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/aa2c854ed688cf4ff0f5cf7f48786c533f00b943.png", "website": "https://metaplane.dev", "all_locations": "New York City, NY, USA", "long_description": "Metaplane ensures everyone trusts the data that powers your business. Data teams at Bose, Ramp, and Klaviyo use our data observability platform to prevent and detect data issues — before the CEO pings them about weird revenue numbers.\r\n\r\nWe do this with ML-based anomaly detection, end-to-end column-level lineage, and tools to help prevent incidents before they occur. You can monitor your entire data stack within 30 minutes.\r\n\r\nThe company is backed by Khosla Ventures, Y Combinator, and the founders of Okta, HubSpot, and Vercel.", "one_liner": "Data observability for modern data teams", "team_size": 32, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1614011784, "tags": [ "Developer Tools", "SaaS", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2020", "status": "Acquired", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/metaplane", "api": "https://yc-oss.github.io/api/batches/winter-2020/metaplane.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": 13549, "name": "Airbyte", "slug": "airbyte", "former_names": [ "Daxtarity", "Dataline" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fc4c9a8bb7a853c14be4dac967fb9717f36fca1c.png", "website": "https://airbyte.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Airbyte Agents is the context layer your AI agents query before they act. Features the Context Store, which unifies entities across Salesforce, Stripe, Zendesk and more. Use it from the UI, your LLM via MCP, or our SDK. 40% fewer tool calls, up to 80% fewer tokens.\r\n\r\nAirbyte Data Replication is the leading open data movement platform that empowers data teams in the AI era by transforming raw data into actionable intelligence. \r\n\r\nhttps://github.com/airbytehq/", "one_liner": "Context layer for production-grade AI agents", "team_size": 90, "industry": "B2B", "subindustry": "B2B", "launched_at": 1584288236, "tags": [ "Artificial Intelligence", "Developer Tools", "Open Source", "Data Engineering", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2020", "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/airbyte", "api": "https://yc-oss.github.io/api/batches/winter-2020/airbyte.json" }, { "id": 19932, "name": "Jitsu", "slug": "jitsu", "former_names": [ "kSense" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d2a6bc92874bce104c70f6971a040465116e2321.png", "website": "https://jitsu.com", "all_locations": "New York City, NY, USA; Remote", "long_description": "Jitsu is the fastest, most durable way to collect event data from every source - web, app, email, chatbot, CRM - into your data warehouse. 100% open-source. Purpose built, secure and ready in minutes.", "one_liner": "Open-Source CDP (acquired by Helium Ventures)", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1597695723, "tags": [ "SaaS", "B2B", "Open Source", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2020", "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/jitsu", "api": "https://yc-oss.github.io/api/batches/summer-2020/jitsu.json" }, { "id": 21781, "name": "Datafold", "slug": "datafold", "former_names": [ "Datafold", "datafold" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/196898f11a9311436ed24d99e2972511f8433f5d.png", "website": "https://datafold.com", "all_locations": "New York, NY, USA; Remote", "long_description": "Datafold automates manual work in data engineering. \r\n\r\nWe leverage agentic AI to automate both day-to-day tasks, such as testing and code reviews, and massive one-off projects, such as data platform code migrations. Companies from Perplexity to Disney use Datafold to unlock more value from their data by freeing up their data teams from manual work, accelerating developer velocity, and ensuring data quality.", "one_liner": "Automating manual and repetitive data engineering tasks with AI", "team_size": 30, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1599762606, "tags": [ "SaaS", "Analytics", "Data Engineering", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2020", "status": "Active", "industries": [ "B2B", "Analytics" ], "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/datafold", "api": "https://yc-oss.github.io/api/batches/summer-2020/datafold.json" }, { "id": 21858, "name": "Monosi", "slug": "monosi", "former_names": [ "Vocable", "Kosmos", "qz" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a79a7e737458c49c901b1062ceb420254ed8ac77.png", "website": "https://monosi.dev", "all_locations": "San Francisco, CA, USA", "long_description": "Monosi is an extensible data observability platform that ensures teams achieve data reliability.", "one_liner": "Open Source Data Observability", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1598983823, "tags": [ "Developer Tools", "B2B", "Open Source", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2020", "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/monosi", "api": "https://yc-oss.github.io/api/batches/summer-2020/monosi.json" }, { "id": 21985, "name": "Streamdal", "slug": "streamdal", "former_names": [ "Batch" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/905df51a88d30785af526f036fcac3fcad730bb2.png", "website": "https://streamdal.com", "all_locations": "Portland, OR, USA; Remote", "long_description": "SaaS data platform for observing, repairing and replaying data in streaming systems.", "one_liner": "Data Quality & Playback Platform", "team_size": 9, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1598191564, "tags": [ "Developer Tools", "Data Engineering", "DevOps" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2020", "status": "Inactive", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/streamdal", "api": "https://yc-oss.github.io/api/batches/summer-2020/streamdal.json" }, { "id": 22076, "name": "Dataland", "slug": "dataland", "former_names": [ "Realism Labs", "Sidekick", "Realism Labs", "Sidekick" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/9c1084ef28edc951f15115194ba8b7bc7c1889eb.png", "website": "https://dataland.io", "all_locations": "New York, NY, USA", "long_description": "Dataland is the applied AI lab for complex operations and customer support. In 8 months, we've grown to multi-million dollar ARR as just two founders and are highly profitable. We’re partnering with some of the fastest growing startups and public companies in the world.", "one_liner": "AI agents for customer support.", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Operations", "launched_at": 1594828571, "tags": [ "B2B", "Data Engineering", "Data Visualization", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2020", "status": "Active", "industries": [ "B2B", "Operations" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/dataland", "api": "https://yc-oss.github.io/api/batches/summer-2020/dataland.json" }, { "id": 22091, "name": "Supabase", "slug": "supabase", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/9e8c106f46123a6f28b7a7da41f0ee695da48786.png", "website": "https://supabase.com", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Supabase is the easiest way to get started with Postgres. \r\n\r\nEach project within Supabase is an isolated Postgres cluster, allowing customers to scale independently, while still providing the features that you need to build: instant database setup, auth, row level security, realtime data streams, auto-generating APIs, and a simple to use web interface.\r\n\r\nWe are 100% remote.\r\n\r\n", "one_liner": "Build in a weekend. Scale to millions.", "team_size": 120, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1596180346, "tags": [ "Developer Tools", "Open Source", "Big Data", "Data Engineering", "Databases" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2020", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "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/supabase", "api": "https://yc-oss.github.io/api/batches/summer-2020/supabase.json" }, { "id": 22248, "name": "Mozart Data", "slug": "mozart-data", "former_names": [ "MarioData" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/26b12777ded0ad248c87b09da978d09a244dcff3.png", "website": "http://www.mozartdata.com", "all_locations": "San Francisco, CA, USA", "long_description": "Mozart Data provides an out-of-the-box modern data stack that empowers anyone to easily consolidate, organize, and prepare their data for analysis. Spin up a data stack that’s built on a best-in-class data warehouse and ETL tool in hours, without any engineering. You can finally spend more time on generating insights and less time wrangling your data.", "one_liner": "The easiest way to set up a modern data stack", "team_size": 24, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1598228399, "tags": [ "SaaS", "B2B", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 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/mozart-data", "api": "https://yc-oss.github.io/api/batches/summer-2020/mozart-data.json" }, { "id": 22632, "name": "authzed", "slug": "authzed", "former_names": [ "Petricorp", "Inc." ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ee578b781cb190a51362b9fda6dc57b36d74972d.png", "website": "https://authzed.com", "all_locations": "New York, NY, USA; Remote", "long_description": "We build the tools companies need to provide performant and scalable authorization for their applications.\r\n\r\nWe’re founded by 3 successful entrepreneurs with expertise in enterprise software, most recently as leaders at Red Hat. Jake and Joey met on the APIs team at Google in 2010. They went on to found Quay, where Jimmy joined as their first hire. Over the past decade, they’ve changed the landscape for building and deploying software.", "one_liner": "Authorization Infrastructure securing AI at OpenAI, Zoom, & more", "team_size": 31, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1624982412, "tags": [ "Artificial Intelligence", "Developer Tools", "Security", "Open Source", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2021", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/authzed", "api": "https://yc-oss.github.io/api/batches/winter-2021/authzed.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": 22771, "name": "Avenue", "slug": "avenue", "former_names": [ "Avenue Technologies" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e5f67e2ce27f5eb8afbeff838eb65ceab7f77903.png", "website": "https://avenue.app/", "all_locations": "New York, NY, USA", "long_description": "Avenue is a simple way for business teams to set up alerts from their database or data warehouse. Think Datadog / PagerDuty for operations teams.\r\n\r\nOperations teams create set-and-forget alerts on all their data, so they can be more proactive with their time (and monitor on more nuanced triggers than just what fits on their dashboard page).\r\n\r\nAvenue can improve response times to critical problems from several days to real-time by alerting directly on the data sources that customers already use.", "one_liner": "Observability platform for operations teams", "team_size": 8, "industry": "B2B", "subindustry": "B2B -> Operations", "launched_at": 1614620141, "tags": [ "Developer Tools", "SaaS", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2021", "status": "Acquired", "industries": [ "B2B", "Operations" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/avenue", "api": "https://yc-oss.github.io/api/batches/winter-2021/avenue.json" }, { "id": 22772, "name": "Prequel", "slug": "prequel", "former_names": [ "Vigo" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/adf6a0c470e58a697fb3d5dfb5dbbe734d9aa0fd.png", "website": "https://prequel.co", "all_locations": "New York, NY, USA", "long_description": "Prequel makes it easy for companies to share data with their customers. It helps you export data directly to your customer's Snowflake, Redshift, BigQuery, Databricks, or other data warehouse on an ongoing basis.", "one_liner": "Helping B2B co's sync data to their customers", "team_size": 9, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1614619481, "tags": [ "SaaS", "Analytics", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2021", "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/prequel", "api": "https://yc-oss.github.io/api/batches/winter-2021/prequel.json" }, { "id": 23041, "name": "Platypus", "slug": "platypus", "former_names": [ "ProcessLabs" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fa8d744e8f842398dd0f47dc4ec6415a9bdaa423.png", "website": "https://www.getplatypus.com", "all_locations": "San Francisco, CA, USA", "long_description": "For Business Operators: Connect & automate processes on top of any data, crazy fast.\r\n\r\nFor Engineering Teams: Connect any data, across any stack, in any format, crazy fast.", "one_liner": "The Distributed Data Operating System", "team_size": 3, "industry": "B2B", "subindustry": "B2B", "launched_at": 1615308252, "tags": [ "B2B", "Workflow Automation", "Data Engineering", "AI Assistant" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2021", "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/platypus", "api": "https://yc-oss.github.io/api/batches/winter-2021/platypus.json" }, { "id": 23550, "name": "Clear", "slug": "clear", "former_names": [ "Quill", "haut" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/04169b13bb38d8ba7da4e38bb6ab9eafa9c93938.png", "website": "https://getclearapp.com/", "all_locations": "London, England, United Kingdom; Remote", "long_description": "On the surface, Clear is a free mobile app where consumers track routines, products and selfies, get brand-agnostic recommendations, and learn from others in the community. Underneath, we’re building a vertically focused AI/data platform that helps consumers, clinicians, and brands understand what actually works, for whom, and why.\r\n\r\nThe skincare industry is worth over $200B globally, yet it still runs largely on guesswork: consumers waste money on trial-and-error, brands lack real-world evidence, and dermatologists have limited visibility into day-to-day product use and outcomes.\r\n\r\nClear is brand-agnostic, data-rich, and community-driven. Every routine log, product review, and progress update helps create a unique longitudinal dataset across skin concerns, routines, and outcomes - powering better decisions for users and better innovation for the wider industry.\r\n\r\nWe were the 2022 L’Oréal Beauty Tech for Good winners, have been recognised by Beiersdorf, and have been featured multiple times by Apple, including App of the Day and Best New Apps.", "one_liner": "The unbiased AI and data layer for skin health.", "team_size": 2, "industry": "Consumer", "subindustry": "Consumer -> Social", "launched_at": 1624200731, "tags": [ "Marketplace", "Consumer", "Digital Health", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2021", "status": "Active", "industries": [ "Consumer", "Social" ], "regions": [ "United Kingdom", "Europe", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": true, "app_answers": null, "question_answers": true, "url": "https://www.ycombinator.com/companies/clear", "api": "https://yc-oss.github.io/api/batches/winter-2021/clear.json" }, { "id": 23950, "name": "Pipekit", "slug": "pipekit", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/04ac699768ee01bea09ec4c32c01f02b31efebd7.png", "website": "https://pipekit.io", "all_locations": "Remote", "long_description": "Our app manages Argo Workflows for data teams, enabling complex data &\r\n CI pipelines in half the time while saving companies hundreds of thousands of dollars annually. We maintain Argo Workflows, an open-source pipeline framework for Kubernetes that’s used in production by Bloomberg, Intuit, Adobe, New Relic, NVIDIA, and many other open-source early adopters. ", "one_liner": "Pipekit scales data & CI pipelines for enterprises", "team_size": 9, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1630089531, "tags": [ "Developer Tools", "Open Source", "Data Engineering", "DevOps" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "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/pipekit", "api": "https://yc-oss.github.io/api/batches/summer-2021/pipekit.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": 24159, "name": "Patterns", "slug": "patterns", "former_names": [ "Snapdata", "Basis", "Patterns", "Atoma" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/55e8a16f61ac33cced5393c8d68ea9f0899f1e49.png", "website": "https://patterns.app/", "all_locations": "San Francisco, CA, USA", "long_description": "Patterns revolutionizes financial analysis by making it easy and accessible through natural language. We are seeking passionate individuals excited about simplifying financial analytics and transforming business intelligence. If you're interested in joining an innovative team in the finance space, explore our job openings and become part of our mission.\r\n\r\nOur advanced AI transforms financial data workflows and reporting, surpassing traditional spreadsheets and inflexible SaaS solutions. By integrating state-of-the-art LLMs with autonomous querying and financial reasoning, Patterns empowers practitioners to perform complex analyses effortlessly via a natural language interface.", "one_liner": "Next-Gen Financial Analysis and Reporting with AI Agents", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1627403220, "tags": [ "Analytics", "Data Science", "Data Engineering", "Data Visualization" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Inactive", "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/patterns", "api": "https://yc-oss.github.io/api/batches/summer-2021/patterns.json" }, { "id": 24191, "name": "Secoda", "slug": "secoda", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4b049a52be34bb701fef7828f1cea14c3624e5f6.png", "website": "https://secoda.co", "all_locations": "Toronto, ON, Canada", "long_description": "We believe that finding the right data shouldn’t require a technical background or hours of digging. That’s why Secoda applies AI to transform messy, siloed analytics into a searchable, intuitive knowledge layer—so every question gets a fast, useful answer.\r\n\r\nOur vision is to become the AI search engine for your company’s analytics, making data discovery as seamless as finding a website on Google. To do that, Secoda gets data AI-ready by unifying governance, cataloging, observability, and lineage into one trusted, easy-to-use platform—empowering every team to move faster, stay compliant, and make smarter decisions.", "one_liner": "Secoda is the AI layer for your Analytics", "team_size": 27, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1626792128, "tags": [ "Artificial Intelligence", "SaaS", "B2B", "Analytics", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "B2B", "Analytics" ], "regions": [ "Canada", "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/secoda", "api": "https://yc-oss.github.io/api/batches/summer-2021/secoda.json" }, { "id": 24195, "name": "Tarsal", "slug": "tarsal", "former_names": [ "V-diff", "vdiff" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/75747b61e59eadbd8831c406fbe1beed2fd4957b.png", "website": "https://www.tarsal.co/", "all_locations": "New York, NY, USA; San Francisco, CA, USA; Remote", "long_description": "Tarsal is a data pipeline custom built for security teams. As security data grows 25% year over year, security teams desperately need access to best-in-class data infrastructure. Tarsal bridges the gap between the modern data stack and security teams, pioneering the modern security data stack. \r\n", "one_liner": "Data pipeline for your security data lake.", "team_size": 10, "industry": "B2B", "subindustry": "B2B -> Security", "launched_at": 1680491615, "tags": [ "B2B", "Cybersecurity", "Big Data", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Acquired", "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/tarsal", "api": "https://yc-oss.github.io/api/batches/summer-2021/tarsal.json" }, { "id": 24384, "name": "Whalesync", "slug": "whalesync", "former_names": [ "Whaleform Inc. (product is Whalesync)" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/859ce6355b2e4ff52655c420f97fbe51b3849528.png", "website": "https://www.whalesync.com", "all_locations": "Miami, FL, USA; Remote", "long_description": "Whalesync makes data syncing easy. Our automation platform syncs data between key business tools like Webflow/Wix/WordPress and Airtable/Notion/Google Sheets. We give marketing teams two-way, real-time sync, so they can manage their website from their favorite collaboration tools.\r\n\r\nWhalesync launched during Y Combinator’s S21 cohort. Since then we’ve raised from some of the world’s top investors. We’re now trusted by hundreds of companies like [Ramp](https://ramp.com/), [Webflow](https://webflow.com/), and [Alchemy](https://www.alchemy.com/), and process millions of transactions every day. Many of our customers enjoy the product so much they [tell all their friends](https://whalesync.com/customers).", "one_liner": "Manage your website from your favorite tools like Airtable and Notion", "team_size": 8, "industry": "B2B", "subindustry": "B2B -> Marketing", "launched_at": 1626201713, "tags": [ "SaaS", "Remote Work", "No-code", "Data Engineering", "Web Development" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "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/whalesync", "api": "https://yc-oss.github.io/api/batches/summer-2021/whalesync.json" }, { "id": 24481, "name": "Whaly", "slug": "whaly", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0a1af514f9cd7a1856ce3c31281c3e222087d748.png", "website": "https://whaly.io", "all_locations": "Paris, Île-de-France, France", "long_description": "Whaly helps data teams save time on maintenance and analysis building while making business users more autonomous on the analysis they want to improve their decision making.\r\n\r\nWe do this by providing a self service data platform where both data and business teams can work together.\r\n\r\nWe understood that most data teams were ending up being a bottleneck for the rest of the company and needed to give more autonomy to business teams to back their decisions with data.\r\n\r\nEmilien, Florian and Pierre were the minds behind the Data advertising platforms of the major media and e-commerce companies in France in their earlier position as Product Manager and head of Customer Success, giving them an edge on how to execute successfully a data project.", "one_liner": "Whaly is building a self-service analytics platform", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1627307992, "tags": [ "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "B2B", "Analytics" ], "regions": [ "France", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/whaly", "api": "https://yc-oss.github.io/api/batches/summer-2021/whaly.json" }, { "id": 24827, "name": "Evidence", "slug": "evidence", "former_names": [ "Evidence.dev" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4d8b363264f6bac1f6d0ca15696cb97172806885.png", "website": "https://www.evidence.dev", "all_locations": "Toronto, ON, Canada; Remote", "long_description": "Evidence is an open source, code-based alternative to drag-and-drop BI tools. Build polished data products with just SQL and markdown.", "one_liner": "Business intelligence as code", "team_size": 6, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1628028455, "tags": [ "Developer Tools", "B2B", "Analytics", "Data Engineering", "Data Visualization" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "status": "Active", "industries": [ "B2B", "Analytics" ], "regions": [ "Canada", "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/evidence", "api": "https://yc-oss.github.io/api/batches/summer-2021/evidence.json" }, { "id": 24866, "name": "Satsuma", "slug": "satsuma", "former_names": [ "Riser" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/534b4a727c846e2797022922053e8d79d2f196d2.png", "website": "https://www.satsuma.xyz/", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Satsuma is a developer tool for building applications on top of real-time blockchain data. Our product lets developers take decoded data from multiple chains, customize it for their use cases, and access it through API endpoints.\r\n\r\nBlockchains serve as distributed databases for these products, holding their most important data. However, it’s difficult to access and query that data. We believe this friction is an enormous blocker for web3 developers and that better tooling will enable mass adoption for web3.\r\n\r\nWe’re a founding team of engineers, having built data infrastructure and product as early employees at Airtable, Heap, and Y Combinator.", "one_liner": "Reliable blockchain indexing & querying for web3 engineering teams.", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1652717569, "tags": [ "Developer Tools", "SaaS", "Crypto / Web3", "Data Engineering" ], "tags_highlighted": [ "Crypto / Web3" ], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2021", "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/satsuma", "api": "https://yc-oss.github.io/api/batches/summer-2021/satsuma.json" }, { "id": 25307, "name": "Sieve", "slug": "sieve", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b247c36fd7cd016d5bb505d32429cd07b9acfcbb.png", "website": "https://sievedata.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Sieve is the only AI research lab exclusively focused on video data.\r\n\r\nVideo already makes up 80% of internet traffic and has become the dominant medium driving creativity, communication, gaming, AR/VR, and robotics. Unlocking the ability to truly model video is the key to breakthroughs across all of these domains but progress has been bottlenecked by one thing: high-quality training data. That’s where Sieve comes in.\r\n\r\nWe bring together exabyte-scale video infrastructure, novel video understanding techniques, and dozens of diverse data sources to create datasets that push the frontier of video modeling. This unique combination allows us to deliver data with unmatched precision, quality, and speed which has earned the trust of frontier AI labs, Fortune 100 companies, and fast-growing generative AI startups.", "one_liner": "Video datasets for frontier AI", "team_size": 18, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1643510053, "tags": [ "Developer Tools", "Video", "Data Labeling", "Data Engineering", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2022", "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/sieve", "api": "https://yc-oss.github.io/api/batches/winter-2022/sieve.json" }, { "id": 25334, "name": "FlowDeploy", "slug": "flowdeploy", "former_names": [ "Toolchest" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2d5821bc4ff8ad8ac82401a9ffd37cd8adb868bc.png", "website": "https://flowdeploy.com", "all_locations": "Mountain View, CA, USA; Remote", "long_description": "FlowDeploy helps bioinformaticians manage their data analysis pipelines. We provide everything they need to try, run, develop, and share their pipelines. That includes integrations with AWS, Snakemake, Nextflow, GitHub, Slack, SSO, and more, as well as a clean API and web app for launching and monitoring pipelines and managing their data.\r\n\r\nFlowDeploy is built for bioinformaticians: it doesn't restrict how pipelines are built and managed, as long as a bioinformatics workflow manager like Nextflow or Snakemake is used. But it does eliminate several footguns like idle spend and accidental data egress, and it reduces the potential for users accidentally sharing credentials.\r\n\r\nFlowDeploy runs the pipelines in either our managed cloud or the customer's cloud – eliminating the need to transfer data externally.\r\n\r\nNon-computational biologists can use FlowDeploy, too: features like pipelines templates decrease the complexity to launch a new pipeline, which reduces user error and decreases the need for advanced cloud training for non-computational users.", "one_liner": "Bioinformatics pipelines in the cloud", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1643247528, "tags": [ "Developer Tools", "Drug discovery", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Inactive", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/flowdeploy", "api": "https://yc-oss.github.io/api/batches/winter-2022/flowdeploy.json" }, { "id": 25353, "name": "Sarus", "slug": "sarus", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/eeaf8f8226d85960b7834ae51a48adfa24515b3b.png", "website": "https://www.sarus.tech", "all_locations": "Paris, Île-de-France, France", "long_description": "Sarus solves the problem of accessing or sharing personal data for analytics or machine learning. \r\nThe solution deploys natively in data infrastructures and lets practitioners work on data they cannot see. Every interaction with the sensitive data is protected with the highest privacy standard: differential privacy\r\nSarus makes traditional anonymization methods irrelevant, saving months in compliance and data engineering while preserving all of the value of data.", "one_liner": "Use personal data for analytics and ML, safely and seamlessly", "team_size": 16, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1642494204, "tags": [ "Analytics", "Compliance", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Acquired", "industries": [ "B2B", "Analytics" ], "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/sarus", "api": "https://yc-oss.github.io/api/batches/winter-2022/sarus.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": 25541, "name": "Versable", "slug": "versable", "former_names": [ "Vista" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/27cef04a2b2af454d42923ab9d77113e9f198884.png", "website": "https://www.versableai.com/", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Auto parts retailers get product data from hundreds of manufacturers that is inaccurate and inconsistent, often with big gaps in key values. They currently have a team of \"catalog managers\" who are required to process and enhance this data line by line, resulting in a week to months long lag between receiving product data and actually being able to start generating revenue from those products. \r\n\r\nVersable leverages AI to scan the web for tens of millions of auto parts listings, and uses a fine-tuned LLM with RAG to instantly process, enhance, and transform data. With just a part number, Versable is able to generate market-ready titles, product descriptions, and specs, in any format that's needed. ", "one_liner": "AI powered product description enhancement for the auto parts industry", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1642519106, "tags": [ "Manufacturing", "Data Engineering", "AI", "Automotive" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2022", "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/versable", "api": "https://yc-oss.github.io/api/batches/winter-2022/versable.json" }, { "id": 25542, "name": "Elementary", "slug": "elementary", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/45aadc83c7554b356da35bb6d48a350f575804b2.png", "website": "http://elementary-data.com/", "all_locations": "Tel Aviv-Yafo, Tel Aviv District, Israel", "long_description": "Elementary enables data teams to detect problems in their data before their users do. An open-source solution that any data engineer can deploy in minutes without sharing sensitive data.", "one_liner": "Open-source data observability for data teams", "team_size": 12, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1647515701, "tags": [ "Developer Tools", "Analytics", "Open Source", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "B2B", "Analytics" ], "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/elementary", "api": "https://yc-oss.github.io/api/batches/winter-2022/elementary.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": 25616, "name": "Stackshine", "slug": "stackshine", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2f75e99dea11ca83cb5f3e5de76cf447b57d842e.png", "website": "https://www.stackshine.com", "all_locations": "Portland, OR, USA; Providence, RI, USA; Remote", "long_description": "Stackshine is creating mission control for enterprise IT teams. We discover all the software being used across their organization and then automate workflows related to onboarding/offboarding, cost savings, and security. ", "one_liner": "Automating all IT operations", "team_size": 7, "industry": "B2B", "subindustry": "B2B -> Operations", "launched_at": 1646144116, "tags": [ "Robotic Process Automation", "Productivity", "Analytics", "Enterprise", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Acquired", "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/stackshine", "api": "https://yc-oss.github.io/api/batches/winter-2022/stackshine.json" }, { "id": 25738, "name": "Hydra", "slug": "hydra", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/87c0954c151aa7067e034d8de33b3174d43f5ff0.png", "website": "https://hydra.so", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Hydra is a real-time analytics database management system for Postgres. We seperate compute from storage to offer software engineers serverless analytics with autoscale, write isolation, automatic caching, and more.\r\n\r\nShipping scalable projects on time series and event data has never been easier. Hydra is available for local development, cloud, and bare metal deployment.", "one_liner": "Serverless Analytics on Postgres", "team_size": 6, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1642199733, "tags": [ "Developer Tools", "Analytics", "Open Source", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "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/hydra", "api": "https://yc-oss.github.io/api/batches/winter-2022/hydra.json" }, { "id": 25743, "name": "Trackingplan", "slug": "trackingplan", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7b1ef39c22b700cf5d44570c7f6569b245f3ee28.png", "website": "https://trackingplan.com", "all_locations": "Barcelona, CT, Spain; CT, Spain; Remote", "long_description": "Trackingplan automatically discovers and monitors all the information your applications and websites are collecting, ensuring that you can trust your BI, analytics, marketing, and sales tools. \r\n\r\nYou can think of us as Segment Protocols but totally transparent, where developers can keep using Google Analytics, Amplitude, Hubspot, Intercom, Braze, etc. as they are used to. \r\n\r\nInstalled in minutes in using your Tag Manager or adding just one line of code to your web or apps, we model all the data being sent to third parties. Since Trackingplan understands what each piece of data means, it identifies patterns, detects anomalies, and automatically connects the dots to create value from data that was hidden in plain sight:\r\n\r\n- An always up-to-date single source of truth and data governance tool. To discover, understand and document your data and improve communication across teams.\r\n- Automated notifications when something breaks or changes. To make sure that integrations are always well implemented: Schema errors, traffic anomalies, rogue events... \r\n- Easy to understand, customizable, cross-service alerts. To detect trends, insights, and problems without using complex, engineer-oriented solutions.", "one_liner": "Automated QA for your Digital Analytics", "team_size": 17, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1641391102, "tags": [ "SaaS", "Analytics", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "B2B", "Analytics" ], "regions": [ "Spain", "Europe", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": true, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/trackingplan", "api": "https://yc-oss.github.io/api/batches/winter-2022/trackingplan.json" }, { "id": 25905, "name": "Bracket", "slug": "bracket", "former_names": [ "Palette Financial", "Inc.", "Palette" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/743850446c402a0284c29ccc61272697d62fc139.png", "website": "https://www.usebracket.com/", "all_locations": "New York, NY, USA; Los Angeles, CA, USA", "long_description": "Bracket is the two-way data pipeline between popular business tools and backend databases. When ops teams update data in Salesforce or Airtable, and engineers update data in the database, Bracket connects the two sources to reflect the same information. ", "one_liner": "Two-way syncs between business tools and your database", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1641941124, "tags": [ "SaaS", "B2B", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Acquired", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "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/bracket", "api": "https://yc-oss.github.io/api/batches/winter-2022/bracket.json" }, { "id": 26726, "name": "ilumadata", "slug": "ilumadata", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/66d4cb68e2a9b002d6e82fe002cef40a30254971.png", "website": "https://www.ilumadata.io/", "all_locations": "London, England, United Kingdom; Sydney, NSW, Australia; Remote", "long_description": "We’re retool for data pipelines. We allow less-technical people to edit data pipelines, with easy to use tools.", "one_liner": "Confidently ship analytics code faster with fewer errors", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1657474709, "tags": [ "Developer Tools", "B2B", "Analytics", "Enterprise", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2022", "status": "Inactive", "industries": [ "B2B", "Analytics" ], "regions": [ "United Kingdom", "Australia", "Europe", "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/ilumadata", "api": "https://yc-oss.github.io/api/batches/summer-2022/ilumadata.json" }, { "id": 26756, "name": "Midplane", "slug": "midplane", "former_names": [ "Deekard", "IvyCheck", "WithIda" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/5fda9dc0196ef666a5a460e8ffbc29dddfc27396.png", "website": "https://midplane.ai/", "all_locations": "Berlin, Berlin, Germany; Remote", "long_description": "Companies are connecting AI coding agents like Cursor and Claude directly to their databases — where one wrong command can delete data or leak customer records. Midplane sits in between and controls what each agent is allowed to do: it blocks dangerous queries, hides sensitive data, and keeps a record of everything the agent touches. It’s open source, and runs either as a hosted service or on your own servers.", "one_liner": "The safety layer between AI agents and your database", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1658837091, "tags": [ "Artificial Intelligence", "Generative AI", "B2B", "Productivity", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2022", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "Germany", "Europe", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/midplane", "api": "https://yc-oss.github.io/api/batches/summer-2022/midplane.json" }, { "id": 27040, "name": "Grai", "slug": "grai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/217dbf57c9649c7822bbee101a62b2d34a750a85.png", "website": "https://www.grai.io", "all_locations": "San Francisco, CA, USA; London, England, United Kingdom; St. Louis, MO, USA", "long_description": "Grai is open source version control for metadata. We can determine how database changes will affect deployed machine learning models, apis, and dashboards because we understand how data relates across systems which don’t otherwise talk to each other.", "one_liner": "Open source version control for metadata", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1660014966, "tags": [ "Developer Tools", "SaaS", "Analytics", "Open Source", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2022", "status": "Inactive", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "United Kingdom", "America / Canada", "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/grai", "api": "https://yc-oss.github.io/api/batches/summer-2022/grai.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": 27097, "name": "Findly", "slug": "findly", "former_names": [ "Conversion Pattern" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fb66cc9915337d3770b18b75f9fd9abe54a3e901.png", "website": "https://www.findly.ai/join", "all_locations": "London, England, United Kingdom", "long_description": "Findly.ai is the co-pilot for Business Intelligence that revolutionizes how businesses understand and interact with their data. By creating an engaging chat environment, it empowers decision-makers to gain insights, request reports, and generate visualizations based on their company's metrics. This seamless interaction is made possible by integrating a metric layer that comprehends all your company's metrics. The chat-based exploration simplifies complex data analysis, allowing users to generate comprehensive summaries with a single click, which can be exported to various formats. Furthermore, with the introduction of scheduled chats and action-triggered automations, Findly.ai enhances the autonomy and efficiency of decision-makers. It's more than a tool; it's a decision-making operational system aiming to facilitate decision-makers in achieving their KPIs while spending less time waiting for data.", "one_liner": "Co-pilot for Business Intelligence", "team_size": 11, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1660122078, "tags": [ "Artificial Intelligence", "Generative AI", "B2B", "Chatbot", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2022", "status": "Active", "industries": [ "B2B", "Analytics" ], "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/findly", "api": "https://yc-oss.github.io/api/batches/summer-2022/findly.json" }, { "id": 27108, "name": "Sanifu", "slug": "sanifu", "former_names": [ "Patika Technology Limited", "Patika" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/dc10943e14517d77a119ecad164eb2d76d6db52b.png", "website": "https://sanifu.ai", "all_locations": "Nairobi, Nairobi County, Kenya; Remote", "long_description": "Sanifu automates the repetitive work spreadsheets are used for. Teams across finance, marketing, operations, and revenue simply describe their repetitive work like cleaning and validating data, matching records, preparing reports and moving data from emails, PDFs and Excel exports into dashboards and other systems. Sanifu captures the steps, rules and outputs so the work is repeated reliably every time\r\n\r\nSome of these work never needed spreadsheets to begin with; the likes of data cleanup, bank reconciliations, report consolidation, payment allocations, channel attributions. Spreadsheets have become the standard workbench for handling these tasks and in the process, teams lose valuable time doing manual data entry, filling templates, formatting data, applying formulas, deleting rows or columns.\r\n\r\nSanifu is replacing the spreadsheet while maintaining the logic and processes behind the work, getting you from inputs to your desired outputs in seconds. This significantly reduces time spent on copy-paste work, spreadsheet cleanup, and manual entries and checking, while improving accuracy, consistency, and operational visibility. Sanifu helps teams scale critical back-office processes without relying on brittle spreadsheets, scripts, or general AI tools that reinvent the logic every run.\r\n\r\nSanifu is a full operational platform with 5k+ app integrations, 1k+ native functions, forms, scheduler, data stores, dashboards, approvals, reviews, AI-powered entity matching among many other features that make it an end-to-end data app management platform", "one_liner": "Automate the repetitive work spreadsheets are used for", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Operations", "launched_at": 1655225496, "tags": [ "SaaS", "B2B", "Analytics", "Data Engineering", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2022", "status": "Active", "industries": [ "B2B", "Operations" ], "regions": [ "Kenya", "Africa", "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/sanifu", "api": "https://yc-oss.github.io/api/batches/summer-2022/sanifu.json" }, { "id": 27146, "name": "Sunpia", "slug": "sunpia", "former_names": [ "Cloudless", "Sunpia", "Cloudless" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0a8f293ade5299bdff930dd4920f116a323117fe.png", "website": "http://sunpia.io", "all_locations": "San Jose, CA, USA; Remote", "long_description": "Sunpia lets developers easily experience the cost and speed benefits of serverless infrastructure, without having to rewrite their code. Developers annotate their code and Sunpia automatically designs a microservice version of it they can deploy on their own cloud.", "one_liner": "Deploy serverless without rewriting code", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1662145175, "tags": [ "Developer Tools", "Kubernetes", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2022", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/sunpia", "api": "https://yc-oss.github.io/api/batches/summer-2022/sunpia.json" }, { "id": 27177, "name": "MovingLake", "slug": "movinglake", "former_names": [ "Moving Lake" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ca7dff480b4b49f376fc3b90d1adc3c17872277f.png", "website": "https://movinglake.com", "all_locations": "Mexico City, CDMX, Mexico; Remote", "long_description": "MovingLake is Fivetran for event-driven architectures. Companies such as Casai use our product to obtain orders and price changes in real time.", "one_liner": "Realtime Data Connectors", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1657821965, "tags": [ "SaaS", "B2B", "Analytics", "API", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2022", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "Mexico", "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/movinglake", "api": "https://yc-oss.github.io/api/batches/summer-2022/movinglake.json" }, { "id": 27683, "name": "Versori", "slug": "versori", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/72ebeb10f18857a66bed8b775cde8113255925d4.png", "website": "https://www.versori.com/", "all_locations": "Manchester, England, United Kingdom", "long_description": "Orchestrate custom integrations, workflows & agents in hours, not months. Take control of your integration strategy and breathe easy with maintenance on AI Autopilot.\r\n\r\nFor Product Teams: Build better integration libraries. Build a feature-rich integration library, for your users to enjoy. Offer out-of-the-box integrations that work for you and your customers. Embedded IPaaS typically locks you into connector or endpoint limitations. Versori gives you to tools for limitless customisation. Proactive, self healing agents, scan your connected apps for endpoint or schema changes. You get alerted, Versori AI fixes the change. Embed Versori built integrations into your app with the Versori SDK. Flexible to your development approach with advanced user management.\r\n\r\nFor Operations Teams: Get your internal systems speaking the same language. Deliver integrations for new software in days, not months—so you can start unlocking value immediately. Versori’s speed to value reduces typical deployment fees by half—or more. Low code for speed. Full code for control. No more limits from inflexible integration platforms.\r\n\r\nFor GTM & Sales Teams: Say yes to any prospect's integration request. Stop bouncing between teams to get integrations built. With Versori, Sales can go straight to yes. No more escalations or delays. Versori offer fully managed custom-builds, so your customers get exactly what they need, without compromise.", "one_liner": "Agentic integrations & automations for enterprise", "team_size": 16, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1666106474, "tags": [ "SaaS", "B2B", "API", "No-code", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2023", "status": "Acquired", "industries": [ "B2B", "Infrastructure" ], "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/versori", "api": "https://yc-oss.github.io/api/batches/winter-2023/versori.json" }, { "id": 27697, "name": "Lume", "slug": "lume-2", "former_names": [ "Abyssinia" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/053379bcb6d2f8ca33ff9eb81f1d899a06a6872a.png", "website": "https://www.lume.ai", "all_locations": "", "long_description": "Lume speeds up customer implementation with AI. Lume helps teams analyze, map, and ingest customer data up to 87% faster, accelerating time-to-revenue.", "one_liner": "Speed up customer implementation with AI", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1675974530, "tags": [ "SaaS", "B2B", "Data Engineering", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2023", "status": "Acquired", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "Unspecified" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/lume-2", "api": "https://yc-oss.github.io/api/batches/winter-2023/lume-2.json" }, { "id": 27762, "name": "Ohm", "slug": "ohm-2", "former_names": [ "Byterat" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6b3e2558be3a398339579a5be68b4d4a636ca905.png", "website": "https://www.ohm.ai", "all_locations": "San Francisco, CA, USA", "long_description": "Ohm is transforming how physical products are developed, using AI. We support major tech enterprises across batteries, automotive and consumer electronics to reimagine how they develop, test and validate their products. Ohm is used by leading engineering teams to launch new hardware products faster, optimize engineer productivity and reduce the cost of engineering test programs.", "one_liner": "Ohm helps engineering labs develop better products faster, with AI.", "team_size": 6, "industry": "Industrials", "subindustry": "Industrials", "launched_at": 1676603508, "tags": [ "Artificial Intelligence", "Data Engineering", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2023", "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": false, "url": "https://www.ycombinator.com/companies/ohm-2", "api": "https://yc-oss.github.io/api/batches/winter-2023/ohm-2.json" }, { "id": 27868, "name": "Outerbase", "slug": "outerbase", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e7ffc83c79c7fc5268f3ebcb40e602151effc32b.png", "website": "https://www.outerbase.com", "all_locations": "Pittsburgh, PA, USA; San Francisco, CA, USA; Remote", "long_description": "Outerbase is the interface for your database. Companies use Outerbase to view, edit, and modify their data and even generate beautiful visual dashboards without having to write a single line of SQL.", "one_liner": "The interface for your database", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1673832882, "tags": [ "Developer Tools", "Generative AI", "Analytics", "Data Engineering", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2023", "status": "Acquired", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/outerbase", "api": "https://yc-oss.github.io/api/batches/winter-2023/outerbase.json" }, { "id": 27897, "name": "TableFlow", "slug": "tableflow", "former_names": [ "Inquery" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fad6d127e5843dda3d9f06585de22ad73a6df795.png", "website": "https://tableflow.com", "all_locations": "San Francisco, CA, USA", "long_description": "TableFlow builds AI teammates for data tasks, helping operations and data teams automate the messy, manual tasks buried in PDFs, spreadsheets, images, and emails.", "one_liner": "AI Teammates for Data Tasks", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Operations", "launched_at": 1676487521, "tags": [ "Documents", "SaaS", "Data Engineering", "Automation", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2023", "status": "Active", "industries": [ "B2B", "Operations" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/tableflow", "api": "https://yc-oss.github.io/api/batches/winter-2023/tableflow.json" }, { "id": 27951, "name": "Honeydew", "slug": "honeydew", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/628b819928f75f1e921c92594fbcd9a7e63a91b4.png", "website": "https://honeydew.ai", "all_locations": "Tel Aviv-Yafo, Tel Aviv District, Israel", "long_description": "The way people use data is constantly changing. Data teams must support every new context without breaking the shared truth. Honeydew’s semantic layer does it automatically. We validate each change and update every data flow.\r\n\r\nUsing Honeydew, data teams can support 10x more data users - without more engineers or compromising integrity. ", "one_liner": "The home for shared data logic", "team_size": 6, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1670747027, "tags": [ "SaaS", "B2B", "Analytics", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2023", "status": "Active", "industries": [ "B2B", "Analytics" ], "regions": [ "Israel", "Middle East and North Africa", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/honeydew", "api": "https://yc-oss.github.io/api/batches/winter-2023/honeydew.json" }, { "id": 28650, "name": "Artie", "slug": "artie", "former_names": [ "Artie Technologies" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/973d2f0c6c4d07505113e974a08d18864eb95d54.png", "website": "https://www.artie.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Artie is software that streams data from databases to data warehouses in real-time. Today, most companies run their ETL process every few hours or overnight, so their data warehouse is always out of date; with Artie, the warehouse always has live production data.", "one_liner": "Software that streams data from databases to warehouses in real-time", "team_size": 16, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1684375922, "tags": [ "Developer Tools", "SaaS", "Data Engineering", "Enterprise Software" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2023", "status": "Active", "industries": [ "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/artie", "api": "https://yc-oss.github.io/api/batches/summer-2023/artie.json" }, { "id": 28659, "name": "PeerDB", "slug": "peerdb", "former_names": [ "PeerDB Inc" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4a83477f0ae90481f26400baea36bd4c2fed890a.png", "website": "https://peerdb.io/", "all_locations": "", "long_description": "At PeerDB, we are building a fast, simple and the most cost effective way to stream data from Postgres to Data Warehouses, Queues and Storage engines. If you are running Postgres at the heart of your data-stack and move data at scale from Postgres to any of the above targets, PeerDB can provide value.\r\n\r\n\r\nWe support different modes of streaming - log based (CDC), cursor based (timestamp or integer) and XMIN based. Performance wise, we are 10x faster than existing tools. Features wise, we support native Postgres features such as comprehensive set of data-types incl. jsonb/arrays/postgis, efficiently streaming toast columns, schema changes and so on.", "one_liner": "Fast, native ETL for Postgres 🐘 🚀", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1686776037, "tags": [ "Developer Tools", "Open Source", "Data Engineering", "Enterprise Software", "Databases" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2023", "status": "Acquired", "industries": [ "B2B", "Analytics" ], "regions": [ "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": true, "url": "https://www.ycombinator.com/companies/peerdb", "api": "https://yc-oss.github.io/api/batches/summer-2023/peerdb.json" }, { "id": 28829, "name": "DataShare", "slug": "datashare", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a781f87fe1bbe72d69bfd79f2391a43f15cb2f9b.png", "website": "http://datashare.co/", "all_locations": "Austin, TX, USA; Remote", "long_description": "DataShare is a data-as-a-service platform that lets you embed charts, dashboards and exports directly into your product. For example, if you run an accounting startup, DataShare would enable you to embed a full profit and loss dashboard, with downloadable statements. DataShare is backed by an enterprise-grade data warehouse, and can be implemented in fewer than 20 lines of code. \r\n", "one_liner": "Embed charts, dashboards and exports in your app", "team_size": 1, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1693343113, "tags": [ "Analytics", "Data Engineering", "Databases" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2023", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "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/datashare", "api": "https://yc-oss.github.io/api/batches/summer-2023/datashare.json" }, { "id": 28868, "name": "Briefer", "slug": "briefer", "former_names": [ "Ergomake" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/1e589854f66150c916444527d7f4aa314d3961ed.png", "website": "https://briefer.cloud", "all_locations": "São Paulo, SP, Brazil; Remote", "long_description": "Briefer helps data scientists and analysts build interactive visualizations and data apps using a Notion-like interface.\r\n\r\nConnect to your data sources, write SQL or Python, collaborate through comments and multiplayer editing, and run code in whichever compute environments you need.", "one_liner": "The collaborative data platform.", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1687307247, "tags": [ "Developer Tools", "B2B", "Data Science", "Data Engineering", "Data Visualization" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2023", "status": "Inactive", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "Brazil", "Latin America", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/briefer", "api": "https://yc-oss.github.io/api/batches/summer-2023/briefer.json" }, { "id": 29071, "name": "Cedalio", "slug": "cedalio", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/253ca8c2833042159f28652e47d94970cc10b5cc.png", "website": "https://cedalio.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Cedalio is the AI agent platform for the Office of the CFO. We automate procurement, AP, and the data flows behind them — from invoice intake to 3-way match to payment — so finance teams stop doing the work and start governing it.", "one_liner": "AI agents that automate AP, procurement, and finance", "team_size": 6, "industry": "B2B", "subindustry": "B2B", "launched_at": 1685752888, "tags": [ "Fintech", "Finance", "Data Engineering", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2023", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/cedalio", "api": "https://yc-oss.github.io/api/batches/summer-2023/cedalio.json" }, { "id": 29254, "name": "Reducto", "slug": "reducto", "former_names": [ "Remembrall" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/9794d4fb523375d125992ce9fa5e9e9db45daf9a.png", "website": "https://reducto.ai", "all_locations": "San Francisco, CA, USA", "long_description": "Reducto is the agentic document platform for leading AI teams building systems to automate document workflows at enterprise scale.\r\n\r\nOur platform provides a comprehensive toolkit for working with documents the way a human would, combining custom in-house and leading frontier models to power efficient and accurate document workflows. Reducto is trusted by leading AI teams at companies like Harvey, Scale AI, and Vanta.\r\n\r\nWe are built for enterprise workloads with flexible deployment options from the cloud to fully air-gapped environments, SOC II and HIPAA compliance, and zero data retention.\r\n\r\nLearn more: https://reducto.ai/\r\nFind our YC deal: https://reducto.ai/yc", "one_liner": "The complete agentic document platform", "team_size": 30, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1704664395, "tags": [ "Documents", "Data Engineering", "Enterprise Software", "Search", "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": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/reducto", "api": "https://yc-oss.github.io/api/batches/winter-2024/reducto.json" }, { "id": 29260, "name": "Quary", "slug": "quary", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e54d14cc55231dd1bd8f1cfd85b8f8366f88fae7.png", "website": "https://www.quary.dev", "all_locations": "London, England, United Kingdom", "long_description": "Quary is the first analytics engineering platform that brings the entire model-test-deploy workflow into the browser. \r\n\r\nAt our first customer, a fast-growing fintech company, Quary empowers analysts in the growth team to self-serve, contribute, and reduce reliance on the data engineering team, letting teams ship metrics faster & executives get answers sooner", "one_liner": "The first in-browser analytics engineering platform", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1707148568, "tags": [ "Artificial Intelligence", "Analytics", "Data Science", "Data Engineering", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2024", "status": "Inactive", "industries": [ "B2B", "Analytics" ], "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/quary", "api": "https://yc-oss.github.io/api/batches/winter-2024/quary.json" }, { "id": 29300, "name": "Trellis AI", "slug": "trellis-ai", "former_names": [ "Trellis" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f9cc80521b4e48dc602aef29ce4fb7d4c0f5dda1.png", "website": "https://runtrellis.com/", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "Accelerate Medication Access with AI", "team_size": 34, "industry": "B2B", "subindustry": "B2B", "launched_at": 1709255809, "tags": [ "B2B", "Data Engineering", "Infrastructure", "AI", "Databases" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2024", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/trellis-ai", "api": "https://yc-oss.github.io/api/batches/winter-2024/trellis-ai.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": 29507, "name": "kater.ai", "slug": "kater-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/8e4c3ef97e004d2c1c5507c262401d7ad2a716ab.png", "website": "https://www.kater.ai", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "1. You explain your problem.\r\n2. Kater identifies the most important data questions to ask.\r\n3. Kater writes the code.\r\n4. You get insights in seconds rather than weeks.\r\n\r\nKater.ai flips the script on enterprise analytics by making every user an expert analyst. It uses a continuous classification engine to turn a single business question into a contextualized package of questions that is specific to your needs.\r\n\r\nKater puts the power of data into the hands of business experts while ensuring they use trusted data that is specific to their persona. No more waiting for data analysts. No more wasted time on analysis misfires and rework.\r\n\r\nYvonne was a data engineer and analyst who built the entire data stack at CREXi. Robin led engineering in Microsoft. \r\n\r\n\r\nData is the new oil. Companies are data-rich, insight-poor. We're helping companies become insight-rich. This is the future of data. ", "one_liner": "Deliver complete data analysis from a single question", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1706308353, "tags": [ "Artificial Intelligence", "Analytics", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2024", "status": "Active", "industries": [ "B2B", "Analytics" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/kater-ai", "api": "https://yc-oss.github.io/api/batches/winter-2024/kater-ai.json" }, { "id": 29727, "name": "Overstand Labs", "slug": "overstand-labs", "former_names": [ "Overstand Labs", "Overstand Labs Inc." ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/061e173be11210d3cca9f1b51ba89c7c5255750b.png", "website": "https://overstandlabs.com", "all_locations": "New York City, NY, USA", "long_description": "Overstand is a data lab that allows our customers to navigate any set of data in just a few minutes.\r\n\r\n*Enterprise*: For enterprises, we we unify Slack, email, calls, and operational data, then surface the signals that matter — customer needs, risks, and revenue opportunities hidden in everyday conversations.\r\n\r\n*Legal Firms*: For legal firms, we help them really quickly understand their entire discovery corpus (either before, or after document review), and quickly build out an initial case assessment and facts.\r\n\r\nInstead of waiting on reports or manual analysis, teams get immediate, evidence-backed answers from the data they already have. Overstand delivers clarity and leverage as your business scales.", "one_liner": "Navigate any set of data - no matter how large - in minutes.", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1724369845, "tags": [ "Artificial Intelligence", "LegalTech", "Data Science", "Data Engineering", "Conversational AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2025", "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/overstand-labs", "api": "https://yc-oss.github.io/api/batches/winter-2025/overstand-labs.json" }, { "id": 29745, "name": "Sharpe", "slug": "sharpe", "former_names": [ "January", "Lumenary", "Lumenary, Inc.", "Lumenary" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ed377f5e3e709abc9139475076cec71316b01c06.png", "website": "https://sharpe.sh", "all_locations": "San Francisco, CA, USA", "long_description": "Sharpe helps traders go from idea to profit in minutes with AI, bundling petabytes of market data with high-performance infrastructure. Sharpe helped a top 5 quant firm find $10m+ of profit within a few hours of deployment.", "one_liner": "Agents for quantitative research and financial data science.", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1722638950, "tags": [ "Artificial Intelligence", "Finance", "Analytics", "Big Data", "Data Engineering" ], "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/sharpe", "api": "https://yc-oss.github.io/api/batches/summer-2024/sharpe.json" }, { "id": 29784, "name": "Sensei", "slug": "sensei", "former_names": [ "OBO" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0e3e1067b2d9b0492706fd6cec1ccf4d50ee5c59.png", "website": "https://senseirobotics.com", "all_locations": "San Francisco, CA, USA", "long_description": "Sensei helps robotics companies scale and outsource their training data collection. Our hardware platform enables the collection of human-demonstration data at a tenth of the cost and twice the speed of current teleop approaches. Our software platform acts like Scale AI for robotics data: a large network of paid human operators use our low-cost collection platform to fulfill data-generation requests. ", "one_liner": "Robotic Training Data at Scale", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1724658554, "tags": [ "Artificial Intelligence", "Hard Tech", "Marketplace", "Robotics", "Data Engineering" ], "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": false, "url": "https://www.ycombinator.com/companies/sensei", "api": "https://yc-oss.github.io/api/batches/summer-2024/sensei.json" }, { "id": 29966, "name": "Mica AI", "slug": "mica-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0e4f97e07f6e1a169c14a54417c11eec5688e0c6.png", "website": "https://usemica.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Mica's AI agents replace the data ops teams fixing bad data.\r\n\r\nWhen bad or missing data breaks the pipeline, and orchestration, retries, and monitoring fail, painful manual review work kicks in, pulling humans in to investigate and patch data issues across systems. Mica does what those humans do: gathering the right information from internal docs and external systems, reasoning across context, and resolving errors autonomously to get the pipeline moving again.\r\n\r\nThe result: dramatically reduce time, cost, and operational drag as your data pipelines scale without scaling ops headcount. Mica turns judgment-heavy data fixes from a manual bottleneck into an automated background process with full auditability.\r\n", "one_liner": "Replace the humans fixing bad data", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Operations", "launched_at": 1720831958, "tags": [ "Data Science", "Data Engineering", "Enterprise Software" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "B2B", "Operations" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/mica-ai", "api": "https://yc-oss.github.io/api/batches/summer-2024/mica-ai.json" }, { "id": 30101, "name": "Kilvin", "slug": "kilvin", "former_names": [ "Chorrie", "BrowserBook" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/32467b13d36c9fed6c944cbb62eed3f24594bf45.png", "website": "https://www.kilvin.ai", "all_locations": "New York, NY, USA", "long_description": "Kilvin is an AI-native agency that builds custom software solutions for non-technical teams.\r\n\r\nWith AI, the future of software is democratized. Every team deserves tools built exactly for them, not off-the-shelf SaaS products they need to adapt to. Kilvin makes it a reality, delivering a private, secure workspace of custom applications, built around your workflows and ready in days, not months.\r\n\r\nNo engineers needed on your side. Just software that fits exactly how you work.", "one_liner": "Custom software for non-technical teams.", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1731609344, "tags": [ "Developer Tools", "Productivity", "Data Engineering", "Automation", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Fall 2024", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/kilvin", "api": "https://yc-oss.github.io/api/batches/fall-2024/kilvin.json" }, { "id": 30113, "name": "Melder", "slug": "melder", "former_names": [ "Echo" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/78670a3e0cef588e19eb8b9dd11bc151ceac64fa.png", "website": "https://melder.io", "all_locations": "New York, NY, USA", "long_description": "Melder is an Excel add-in that brings AI functions and document support into your spreadsheets. Upload files directly into cells, use smart formulas like =GEN, and build automations—all without leaving Excel.\r\n\r\nCore features:\r\n- File-to-Sheet: Drop PDFs directly into cells, then reference them in formulas.\r\n- AI-Powered Functions: Write formulas like =GEN() or =EXTRACT() to summarize, classify, and analyze content.\r\n- Chat Assistant: Use our AI assistant to help build your sheets or answer questions from your data, live in the workbook.\r\n\r\nBusiness users use Melder to:\r\n- Accelerate diligence by extracting insights from data rooms\r\n- Review contracts by identifying key terms and clauses instantly\r\n- Run market research by pulling information from competitor websites\r\n- Synthesize transcripts by generating summaries from interviews and calls\r\n\r\nMelder brings the power of structured spreadsheet logic to the messy, unstructured data world—no coding needed.", "one_liner": "AI formulas and document support for Microsoft Excel", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Productivity", "launched_at": 1731437113, "tags": [ "Artificial Intelligence", "Generative AI", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2024", "status": "Active", "industries": [ "B2B", "Productivity" ], "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/melder", "api": "https://yc-oss.github.io/api/batches/fall-2024/melder.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": 30542, "name": "Vision Lab", "slug": "vision-lab", "former_names": [ "Comply Genie", "Vision Nexus", "LineWise" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f9c8aab3bb47bc9402833acb64276f52de063681.png", "website": "https://thevisionlab.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "We capture and structure real factory workflows at scale by combining first-person industrial video with SOP-level process knowledge.\r\n\r\nThis enables robotics and AI labs to train on real production data, not just controlled lab environments.", "one_liner": "Industrial data layer for robotics training", "team_size": 11, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1743036496, "tags": [ "Robotics", "Manufacturing", "Data Engineering", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/vision-lab", "api": "https://yc-oss.github.io/api/batches/spring-2025/vision-lab.json" }, { "id": 30552, "name": "sieve", "slug": "sieveai", "former_names": [ "Sieve" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/459d63741f9af0815baebb98ab6c243158d589c2.png", "website": "https://usesieve.com/", "all_locations": "New York, NY, USA", "long_description": "sieve solves data cleaning for hedge funds and investment firms by letting them get clean data in four lines of code. Currently, their data pipelines have conditions that raise for human review, which literally send an email to engineers with data that needs to be reviewed. We provide an API that integrates directly into their existing pipeline - instead of raising for human review, they can send all the same information to our API and get clean, high-quality data back.\r\n\r\nBy using our AI agents built specifically for financial data collection, along with expert-in-the-loop review, we provide our clients with clean, validated data at a scale and level of quality that wasn't achievable before.", "one_liner": "AI + human review to solve data cleaning - accessible via API or Excel", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Finance and Accounting", "launched_at": 1747624073, "tags": [ "Investing", "Data Engineering", "APIs" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2025", "status": "Active", "industries": [ "B2B", "Finance and Accounting" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/sieveai", "api": "https://yc-oss.github.io/api/batches/spring-2025/sieveai.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": 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": 30913, "name": "Captain", "slug": "captain", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0c5e5da360891b80b4a1d6d511de963d613bbf08.png", "website": "https://runcaptain.com", "all_locations": "San Francisco, CA, USA", "long_description": "Captain delivers the most accurate file search engine built for AI agents. We’ll index data from the sources folks already use like S3, SharePoint, and Google Drive, and easily scale multimodal, petabyte-level content search. We’re the Snowflake for Unstructured Data.\r\n\r\nCaptain tops the Open-RAG-Benchmark with over 20% higher accuracy than standard RAG pipelines. We achieve this through robust data processing techniques like embedding normalization across modalities, ensuring that representations cluster by semantic content rather than data type.", "one_liner": "Give AI agents accurate knowledge search that scales", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1762492786, "tags": [ "B2B", "API", "Data Engineering", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2026", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/captain", "api": "https://yc-oss.github.io/api/batches/winter-2026/captain.json" }, { "id": 30995, "name": "Velvet", "slug": "velvet", "former_names": [ "Inline", "Lenscape" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3c02ad81894db8e1b1d0e71c379c7cae04211613.png", "website": "https://velvetlab.ai", "all_locations": "San Francisco, CA, USA", "long_description": "The multimodal data lab.", "one_liner": "The multimodal data lab.", "team_size": 4, "industry": "B2B", "subindustry": "B2B", "launched_at": 1761236237, "tags": [ "Artificial Intelligence", "Generative AI", "Data Engineering", "Conversational 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": false, "url": "https://www.ycombinator.com/companies/velvet", "api": "https://yc-oss.github.io/api/batches/fall-2025/velvet.json" }, { "id": 31030, "name": "Haladir", "slug": "haladir", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6b1a47bf16f93d71a3d1f3af6d10a6c736e170b2.png", "website": "https://www.haladir.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Haladir is the decisional AI layer for logistics. We sit on top of your WMS, TMS, OMS, etc., unify their data into one operational graph, and embed solver-grade optimization, ML models, and process intelligence into the decisions that power supply chains. Today's AI brought intelligence. The next frontier is judgement.", "one_liner": "Operational Superintelligence for Global Logistics", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Operations", "launched_at": 1766374394, "tags": [ "Logistics", "Supply Chain", "Data Engineering", "Operations", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2026", "status": "Active", "industries": [ "B2B", "Operations" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/haladir", "api": "https://yc-oss.github.io/api/batches/winter-2026/haladir.json" }, { "id": 31051, "name": "Corvera", "slug": "corvera", "former_names": [ "Sarah.AI", "Sarah AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/9ba3bd8042a63e5e4cc8707533d8561d2aa5bf74.png", "website": "https://www.corvera.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Corvera (YC W26) is the context layer for AI-native CPG brands. We help brands unlock the full potential of AI by making their unified data legible to any AI tool via MCP. \r\n\r\nAs of mid-March 2026, we scaled from $0 to $33k in MRR in 4 weeks, are serving 12 brands, and are growing 130% week-on-week.\r\n\r\nWith Corvera in place, brands can enable anyone in their organization to:\r\n- Rapidly deploy AI agents via tools such as Claude and ChatGPT,\r\n- Build dashboards and apps using Cursor and Lovable, and\r\n- Automate workflows across the entire business, from category management to supply chain.\r\n\r\nAll in a secure, audit-logged, and access-controlled environment, without the need for a team of data engineers or AI specialists, in a simple plug-and-play solution.\r\n\r\nWe're founded by Chris (2x Founder; ex-CEO at Better Nature; Forbes 30U30), Dirk (ex-Google Data & AI Lead), and Matthew (ex-Head of Product at Rosemark; Princeton MEng in CS).\r\n\r\nTo-date, we’ve raised $6.2M and are backed by YC, firstminute capital, 6 Degrees Capital, 20VC, Rebel Fund, Duke Capital Partners, and more. Our ICP are omnichannel retail-focused CPG brands at the $100M+ revenue inflection point.\r\n\r\nOur mission is bold: to enable the next generation of unicorn CPG brands to be run by teams of less than 10 people. \r\n\r\nOur vision is even bolder: to be the system of intelligence for the $5.4T global CPG industry.\r\n\r\nVisit www.corvera.ai to learn more!", "one_liner": "The context layer for AI-native CPG brands", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Operations", "launched_at": 1763141207, "tags": [ "Artificial Intelligence", "SaaS", "Consumer", "B2B", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2026", "status": "Active", "industries": [ "B2B", "Operations" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/corvera", "api": "https://yc-oss.github.io/api/batches/winter-2026/corvera.json" }, { "id": 32988, "name": "Markov", "slug": "markov", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/455a1b80a115b180bc211a79ff00bc48bf9cb451.png", "website": "https://www.markovstudios.com/", "all_locations": "San Francisco, CA, USA", "long_description": "We source high quality tasks and data to train the next generation of computer use AI models.", "one_liner": "Data for computer-use ai", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1782277833, "tags": [ "Reinforcement Learning", "Data Labeling", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/markov", "api": "https://yc-oss.github.io/api/batches/summer-2026/markov.json" }, { "id": 33310, "name": "Petrarch", "slug": "petrarch", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7b5debb8ea62766300bda39dac40230ec792801c.png", "website": "https://petrarch.co/", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "Market maker for specialized data assets", "team_size": 3, "industry": "B2B", "subindustry": "B2B", "launched_at": 1782965522, "tags": [ "Marketplace", "B2B", "Data Engineering" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/petrarch", "api": "https://yc-oss.github.io/api/batches/summer-2026/petrarch.json" } ]