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I'm a UPenn Alum where I studied computer science and management. I'm building low-code data science software for the next 1M data analysts with my best friend and twin brother. \n\nExcited to learn from & with other YC founders. Say hi!", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/aaron-diamond-reivich/", "x_url": "https://twitter.com/_aaronDR", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ce8b60b12bd61610e1a60375cb480eae613c7b16.jpg" }, { "user_id": 409220, "full_name": "Jake Diamond-Reivich", "title": "Founder", "founder_bio": "Jake graduated with a BS in Finance @ Wharton. Before founding Mito, he helped launch a global personalization analytics tool at SAP. He's our head of growth, and manages our open source community as well as our sales pipeline.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jacob-diamond-reivich-03ab62145/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/21e7aaf673fff445854cea35f7f0a9210496de82.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "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": null, "url": "https://www.ycombinator.com/companies/patterns", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2021/patterns.json", "year_founded": 2021, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/atoma-ai/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/55e8a16f61ac33cced5393c8d68ea9f0899f1e49.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 52795, "full_name": "Ken Van Haren", "title": "Founder", "founder_bio": "Founder @ Patterns. Previously Square, Google, stats PhD @ Duke.", "is_active": false, "linkedin_url": "http://linkedin.com/in/kenvanharen", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/55451e2f3a29d444202af141e90902291148139d.jpg" }, { "user_id": 43909, "full_name": "Chris Stanley", "title": "Founder", "founder_bio": "", "is_active": false, "linkedin_url": "https://www.linkedin.com/in/chris-stanley", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/339f8dca62b76beeedc6c36bbf4dd04f64ded934.jpg" } ], "jobs": [], "news": [ { "title": "Y Combinator–backed Patterns is building a platform to abstract away data science busywork | TechCrunch", "url": "https://techcrunch.com/2023/03/09/y-combinator-backed-patterns-is-building-a-platform-to-abstract-away-data-science-busywork/", "date": "Mar 09, 2023" } ], "launches": [] }, { "id": 26094, "name": "Cellbyte", "slug": "cellbyte", "former_names": [ "Glocally" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cdcdb88b3fbed507fd0624712ba4d55c173500ac.png", "website": "https://www.cellbyte.com/", "all_locations": "Munich, BY, Germany", "long_description": "Cellbyte's AI agents help pharma companies launch new drugs worldwide. Market-leading firms are using Cellbyte to answer questions like “What price can we achieve for our new drug in the U.S. versus Germany?“.\r\n\r\nThe three co-founders have known and worked with each other for many years: Daniel brings 5+ years of industry experience from his previous job at leading global Life Sciences consultancy Simon-Kucher. Felix has sold $3m+ ACV deals to customers like H&M for his previous YC startup. Samuel holds an MSc in Information Systems from TUM, and has built enterprise AI applications from scratch as ML Engineer at Celonis.", "one_liner": "AI Agents for Pharma Drug Launches", "team_size": 3, "industry": "Healthcare", "subindustry": "Healthcare -> Healthcare IT", "launched_at": 1643107083, "tags": [ "Data Science", "Healthcare IT", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "Healthcare", "Healthcare IT" ], "regions": [ "Germany", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/cellbyte", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2022/cellbyte.json", "year_founded": 2024, "city": "Munich", "country": "DE", "linkedin_url": "https://www.linkedin.com/company/cellbyte-com", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/cdcdb88b3fbed507fd0624712ba4d55c173500ac.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 820521, "full_name": "Felix Steinbrenner", "title": "Founder/CEO", "founder_bio": "Co-founder & CEO of Cellbyte. We are building AI agents to accelerate the launch and commercialization of pharmaceutical drugs.\n\nPivoted from Last Mile Logistics in 2023: previously co-founded and led Operations at Glocally (W22), where we offered a same-day parcel delivery service to e-commerce brands like H&M. Utilizing electric vehicles only, we surpassed 150K parcels with excellent reviews, and raised >$2M from top-tier Angels and VCs (YC, Trucks,...).", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/felix-steinbrenner-9b3765184", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0f1f21459ff9bccedcef61e3ea9888c733e37843.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 83038, "title": "Cellbyte - AI Agents for Pharma Drug Launches", "tagline": " Cellbyte's AI agents help pharma companies launch new drugs worldwide. Market-leading firms are using Cellbyte to answer questions like “What price can we achieve for our new drug in the U.S. versus Germany?“.", "body": "Hi everyone! We are Daniel, Felix, and Samuel, and we are building Cellbyte.\n\n**TL;DR:** [Cellbyte](https://cellbyte.com)’s AI agents help pharma companies launch new drugs worldwide. Market-leading firms are using Cellbyte to answer questions like “What price can we achieve for our new drug in the U.S. versus Germany?“.\n\n![uploaded image](/media/?type=post&id=83038&key=user_uploads/820521/da2f6118-b254-4f9c-bc07-97db95767dc6)\n\n\n# **Problem:**\n\nMost medicines being launched are missing their revenue potential by a large margin due to messy pharma data causing expensive inefficiencies. When preparing a drug launch, pharmaceutical manufacturers have to choose between three options:\n\n* **Manual research:** time-consuming, human errors, language barriers\n* **Databases:** $300k / year, poor data quality, limited scope\n* **Consulting:** $300k / project, answers in weeks, data snapshots\n\n# **Solution:**\n\n* Cellbyte consists of 3 main layers:\n * **High-quality data:** comprehensive, globally interconnected, up-to-date\n * **Analytics:** instant due to integrated databases, personalized to each user\n * **Workflows:** built on deep user understanding, human-in-the-loop-interactions, consulting-level outputs\n* Cellbyte’s AI workforce replaces Legacy Providers\n* We’re live in **12 key markets,** adding new ones every week\n\n# **Who we are:**\n\nThe three co-founders have known and worked with each other for many years: Daniel brings 5+ years of industry experience from his previous job at leading global Life Sciences consultancy Simon-Kucher. Felix has sold $3m+ ACV enterprise deals to customers like H&M for his previous YC startup. Samuel holds an MSc in Information Systems from TUM, and has built enterprise AI applications from scratch as ML Engineer at Celonis.\n\n![uploaded image](/media/?type=post&id=83038&key=user_uploads/820521/9cc5b7f4-b6f4-4f9a-8d67-28bf52a576cb)\n\n\n# **Asks:**\n\n* **June 2025 - We are fundraising!** Get in touch with Felix (felix.steinbrenner@cellbyte.com) if you are an investor or happen to know someone who might be a good fit.", "url": "https://www.ycombinator.com/launches/LbK-cellbyte-ai-agents-for-pharma-drug-launches", "votes": 8, "created_at": "2024-08-14T19:24:13.690Z" } ] }, { "id": 27831, "name": "Neptyne", "slug": "neptyne", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4bba48abf01450796ed84c6bb6dcb5adc2044c9a.png", "website": "https://neptyne.com", "all_locations": "New York City, NY, USA", "long_description": "Neptyne is the first natively programmable spreadsheet, with a full Python environment, just like a Jupyter notebook. And we built in AI to make it easy to use, even if you’re not a Python expert. Neptyne turns anyone who can use Excel into a programmer.\r\n\r\nAt Google, Douwe launched products to millions in Search, Mobile and workplace. He founded multiple startups, and published a book on deep learning. 4 years ago Douwe rejoined Google, where he met his cofounder Jack and the rest of the team.\r\n\r\nNeptyne launched on Hacker News in February 2023, and since then users have made thousands of spreadsheets. People have built everything from option trading systems to machine learning classifiers using Neptyne.", "one_liner": "The programmable spreadsheet.", "team_size": 4, "industry": "B2B", "subindustry": "B2B", "launched_at": 1675313769, "tags": [ "Generative AI", "Data Science", "Data Visualization" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2023", "status": "Inactive", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/neptyne", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/neptyne.json", "year_founded": 2022, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/neptyne/", "x_url": "https://twitter.com/neptynehq", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/neptyne", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/4bba48abf01450796ed84c6bb6dcb5adc2044c9a.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Jared Friedman", "url": "https://www.ycombinator.com/people/jared-friedman" }, "founders": [ { "user_id": 178715, "full_name": "Douwe Osinga", "title": "Founder", "founder_bio": "\"Solving hard problems using software that lead to real products used by lots of people\" Founder of 4 companies, ex-Google. Like travel and living in different countries.", "is_active": false, "linkedin_url": "https://www.linkedin.com/in/douweosinga", "x_url": "https://twitter.com/dosinga", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0943ece6f991641579b53b475690849ec09b5304.jpg" }, { "user_id": 1156805, "full_name": "Jack Amadeo", "title": "Founder", "founder_bio": "Jack is cofounder and CTO of Neptyne (W23), the programmable spreadsheet. Prior to Neptyne, Jack worked at Sidewalk Labs building generative design for cities, at Compass building the real estate platform for the 21st century, and at Bloomberg building communication systems.\n\nJack is a New England native who now lives in Brooklyn with his wife and son, and likes to sometimes run marathons.", "is_active": false, "linkedin_url": "https://www.linkedin.com/in/jackamadeo/", "x_url": "https://twitter.com/jackamadeo", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/678b06fb3d4a690640113ec636d29969334e416c.jpg" } ], "jobs": [], "news": [ { "title": "Python Comes to Google Sheets - The New Stack", "url": "https://thenewstack.io/python-comes-to-google-sheets/", "date": "Oct 19, 2023" }, { "title": "Neptyne is building a Python-powered spreadsheet for data scientists | TechCrunch", "url": "https://techcrunch.com/2023/03/27/y-combinator-backed-neptyne-is-building-a-python-powered-spreadsheet-for-data-scientists/", "date": "Mar 27, 2023" } ], "launches": [ { "id": 70264, "title": "Neptyne - The spreadsheet reimagined for the AI era", "tagline": "Our Python-based spreadsheet is built from the ground-up for both human and AI collaboration, to go from raw data to useful insights and visualizations at lightning speed.", "body": "Hello everyone, we are Douwe and Jack, and we're the founders of [Neptyne](https://neptyne.com/). We’re on a mission to create the world's most productive data platform. We really like spreadsheets and love programming and our product combines the two in quite a literal sense.\n\nNeptyne provides a new approach to working with data that combines the ease of use of spreadsheets with the power of data science tools such as Pandas and notebooks. By leveraging AI, Neptyne makes this unified approach accessible to everyone, eliminating the limitations of spreadsheets and reducing the complexity of using advanced data tools.\n\n![uploaded image](/media/?type=post&id=70264&key=user_uploads/178715/71682cab-9b0c-47d9-a074-706623f8b2cd)\n\n**So how does this work?** Of course, you can ask the AI for simple things, like ‘add a profit column’ or ‘create a map showing where the customers are’. But it really shines when you ask the AI to change existing code. If you have a complicated calculator predicting revenue that takes into account four factors, ask it to add a fifth or change the weighting.\n\nOr let’s say you have a powerful, pandas-based pivot table that summarizes the data by product and region. With Neptyne, you can ask the AI to modify the pivot table calculation to include or exclude specific products or change the grouping criteria, such as by product category instead of an individual product. The calculations are updated in real-time, allowing you to quickly explore different options and gain new insights from the data.\n\nIt's like having a co-worker next to you who knows Python well and can help you write new code, change existing code or even explain what’s going on.\n\nIn order to learn about the appetite for a Python-based spreadsheet environment, we launched a version of Neptyne on Hacker News a few weeks ago without the AI-based features. Thousands tried the product, and from that audience, an enthusiastic group of power users emerged. They're using Neptyne to build financial trading applications, personal fitness tracking, and Twitter bot automation.\n\nCheck out [our launch post on Hacker News](https://news.ycombinator.com/item?id=34818706) for more discussion on Neptyne \n\n**Our ask:**\n\nTake 3 minutes to go through our tutorial and get inspired to build your next thing.", "url": "https://www.ycombinator.com/launches/IHI-neptyne-the-spreadsheet-reimagined-for-the-ai-era", "votes": 37, "created_at": "2023-03-14T14:49:06.460Z" } ] }, { "id": 28802, "name": "Sohar Health", "slug": "sohar-health", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/9e3f7c771362aee962754af2fd00c6281c92c7b2.png", "website": "https://www.soharhealth.com", "all_locations": "New York City, NY, USA; Remote", "long_description": "Sohar Health is an AI-driven front-end RCM solution that transforms insurance verification processes for healthcare providers, enabling faster patient conversions and reducing administrative workloads. With a 95% automation rate, our API-first platform seamlessly integrates into existing workflows to provide real-time claim accuracy and eligibility checks. \r\nKey performance metrics showcase the power of our technology: Median latency of just 6 seconds, ensuring real-time eligibility; over 90% of checks returned within 30 seconds for increased patient conversion; 96% accuracy in identifying and verifying benefits details; Industry-leading 99% accuracy for eligibility determination; >90% carve-out detection rate, mitigating surprise billing risks; a 60% success rate with our Insurance Discovery API, helping identify coverage for self-pay patients.\r\n\r\nOur customers include outpatient clinics, specialty practices, and digital health platforms looking to streamline front-end claim management. By reducing errors and maximizing clean claim submissions, Sohar Health empowers healthcare organizations to convert and retain more patients, reduce operating costs, and increase their top-line revenue.", "one_liner": "AI-powered insurance verification to boost patient conversion.", "team_size": 8, "industry": "Healthcare", "subindustry": "Healthcare -> Healthcare IT", "launched_at": 1688557144, "tags": [ "Health Tech", "Digital Health", "API", "Data Science", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2023", "status": "Acquired", "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": [ { "question": "How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)", "answer": "MEET THE BRAIN & THE HEART OF SOHAR HEALTHSohar Health is the marriage of an engineer’s problem-solving brain and a physician’s healing heart, connecting healthcare providers & payers in a more integrated and centralized way.LUCAS GORDONEx-CTO & CISO of Quit Genius (YC W18)Most recently CTO of Quit Genius, the world’s leading digital clinic for substance addictions, Lucas is uniquely positioned to solve benefits integration problems using all he’s learned along his career journey. He’s one of a handful of people in this market who’s experienced firsthand the pain caused by this problem, and the value of solving it. Lucas holds an MSc in Computer Science from the University of London. He’s designed and built systems to integrate with 100+ employers, including integrations with Evernorth and a Fortune 10 customer. At Quit Genius, he also assumed the role of Chief Information Security Officer, leading the company through SOC-2 compliance audits, achieving HITRUST certification, and attended the Y Combinator program in 2018–helping secure over $80M investment funding from seed to Series-B. It was there he met his co-founder, and their aligned passion for healthcare and technology, combined with their deep knowledge of inherent pain points, sparked the idea that became Sohar Health.DR. ASHISH (ASH) MANDAVIAMedical Doctor & Digital Health InnovatorA former National Healthcare System doctor in the UK, Ash was inspired to jump into the world of startups seven years ago, initially as a product manager, using his clinical knowledge to support a team of engineers to create and build a piece of triage software for ERs in the UK. He moved on to a medical education technology company as employee one and helped scale the organization as product and services director. There, he found a love for the commercial side and moved into business development.This led Ash to taking on the role as EMEA Commercial Director of Quit Genius (YC W18), where he led a team to deliver commercial B2B sales, client success, and partnerships with large employers, private healthcare insurers, and public health systems. It was there he discovered inherent pain points related to integrating with these types of payers, slowing access for people getting the help they need.Most recently, Ash was a strategic consultant  at Simon Kucher and Partners, focusing on market access and reimbursement for Digital Health solutions across the UK, Europe, and the US." }, { "question": "How did you decide to apply to Y Combinator? What was your experience applying, going through the batch, and fundraising at demo day?", "answer": "The ethos and ambition towards growth and becoming a $1b+ company at Quit Genius was a strong motivator to take Sohar Health through the YC accelerator program. The company has accelerated by 12 months in a 10 week period and this is mainly due to the strong guidance from our group partners and accountability that we have shown to our peers and colleagues. We have developed significant traction among customers and our product is loved by our customers. YC has pushed us to become the most accurate eligibility verification tool in the behavioral health market and we now run upwards of 60,000 eligibility checks per month. The fundraising process has moved faster than our initial expectations and we feel that the feedback and support given prior to the raise has allowed us to enter those conversations with more confidence and purpose. " }, { "question": "How have you kept in touch with the YC community and continued to use YC resources & programs since the batch ended?", "answer": "From in-person events across the bay area to the founder matching program, we have managed to embed ourselves in the YC community and learn from this amazing network of founders. As we complete our Seed round, we hope to follow the guidance laid out in the post-batch manual and Series A fundraising guide to continue our growth trajectory and our journey towards becoming a unicorn in the health tech space." }, { "question": "What's the history of your company from getting started until the present day? What were the big inflection points?", "answer": "Lucas and I caught up at the start of 2023 when he had exited Quit Genius (YC W18) and I was on paternity leave from my strategy consulting role. We had discussed this burning platform issue on several occasion and recognized that we were in a unique position to solve it. We initially focused on employer eligibility verification for digital health companies, but quickly became aware, through customer discovery, of an even greater challenge to tackle in Real Time Eligibility (RTE) and Coverage of Benefits (COB) determination in the behavioral health space. This was an inflection point and gave us the confidence to pursue a pre-seed round, led by Concept Ventures and allowed us to build our eligibility verification tool and automated AI coding feature. We gained further proof points of the value of our product with strong initial customer traction, booking $118K ARR in the past two months." }, { "question": "What is the core problem you are solving? Why is this a big problem? What made you decide to work on it?", "answer": "One of the biggest reasons behavioral health companies can’t grow faster is that 11% of every patient get denied for insurance reimbursement which directly hits revenue, employee cost and marketing cost. A large proportion of these claims denials are related to eligibility inaccuracies. With our 99% accurate eligibility checker, we reduce these denials to 2%.To determine a patient’s eligibility for a behavioral health service, you could use an existing electronic checker or amass a manual administrative team. Standard automated eligibility checks in the market can only achieve a 50 - 60% accuracy level for mental and behavioral health. The reason these vendors don’t work is that they do not take account of payer carve outs - when insurance companies carve out behavioral health coverage to third party insurers.With our deep understanding of the complex integrations within the payer ecosystem, we can get our automated accuracy check up to 99% and essentially significantly reduce the chance that a patient’s claim will be denied by their insurer." }, { "question": "What is your long-term vision? If you truly succeed, what will be different about the world?", "answer": "We believe in patients accessing healthcare without limits.What if providers were free from the barriers & burdens that waste money and time, and instead could focus on the things that help patients regain and maintain their health? What if signing up for appointments with service providers were easier to manage and integrate? What if there was an easy, cost-effective way to simplify providers’ operations? What if providers had more time to deliver excellent care and weren’t focusing on how to work with insurers? Sohar Health is the marriage of an engineer’s problem-solving brain and a physician’s healing heart, connecting healthcare providers & payers in a more integrated and centralized way.\\We’ve felt the devastating effects of ineffective healthcare on a very personal level, and we have a focused vision of getting better care to more people, quickly and seamlessly. What if clinical services, delivered in bricks and mortar practices or remotely, were able to be the lifeline of hope they were intended to be for millions of patients across the US? Smoother integration.Fewer barriers.Less waste.Improved health.Greater productivity.Effortless connection between payers & providers.What if?It’s time to fully connect and integrate via Sohar’s clearing house for the modern healthcare system" } ], "url": "https://www.ycombinator.com/companies/sohar-health", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/sohar-health.json", "year_founded": 2023, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/sohar-health/", "x_url": "https://twitter.com/soharhealth", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/sohar-health", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/9e3f7c771362aee962754af2fd00c6281c92c7b2.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/7c448092ce5ceb82048219f074b738af8df8f2dc.png" ], "primary_partner": { "name": "Gustaf Alstromer", "url": "https://www.ycombinator.com/people/gustaf-alstromer" }, "founders": [ { "user_id": 1376962, "full_name": "Dr Ashish Mandavia MD", "title": "Founder", "founder_bio": "I am a health-tech entrepreneur, with a clinical background, and the CEO at Sohar Health, automating insurance eligibility verifications. With 8+ years of combined experience in health-related startups, strategy consulting, and clinical practice, I have a unique perspective and skill set to drive innovation and growth in the digital health and technology space across EMEA and the US.", "is_active": true, "linkedin_url": "https://linkedin.com/in/ashishmandavia", "x_url": "https://twitter.com/ash_soharhealth", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/638f520c1d51225e78cedb02ddb093362d08c0eb.jpg" }, { "user_id": 682456, "full_name": "Lucas Gordon", "title": "Founder", "founder_bio": "CTO and cofounder of Sohar Health (S23)", "is_active": true, "linkedin_url": "https://linkedin.com/in/lucas-gordon-48ba6439", "x_url": "https://twitter.com/lucasjgordon", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/95a13107cd71fae4f1999fb40052e32082acee12.jpg" } ], "jobs": [], "news": [ { "title": "Zocdoc acquires health tech company Sohar Health for automated benefits eligibility checks", "url": "https://www.fiercehealthcare.com/ai-and-machine-learning/zodoc-acquires-health-tech-company-sohar-health-automated-benefits", "date": "Oct 14, 2026" } ], "launches": [ { "id": 72772, "title": "🧠 Sohar Health: AI-powered eligibility checks, VoBs and insurance discovery for behavioral health", "tagline": "Unleash your behavioral health company's potential with targeted eligibility verification, and AI-powered Verification of Benefits (VoB) to drive revenue from health payers.", "body": "### \n\n![uploaded image](/media/?type=post&id=72772&key=user_uploads/1376962/82bc99d7-9218-4ecd-b405-2aad0c12fbd7)\n\n### ⚡**TL;DR**\n\nBehavioral health providers are investing significant resources into expensive manual operations teams to determine if patients are eligible for care, in-network, based on their payer contracts, and determine the patient’s responsibility towards their healthcare reimbursement. Enter Sohar Health. Our API-based platform streamlines insurance eligibility verification and offers AI-powered Verification of Benefits (VoB) and insurance discovery, automating manual workflows, increasing patient intake, and generating more revenue. Experience the power of seamless integration and unleash the full potential of your behavioral health company with Sohar Health.\n\n### **🤯 The problem**\n\nImproving front end RCM (revenue cycle management) accuracy is crucial as 85% of related-denied claims (worth $40 billion) are preventable. However, determining the eligibility, network status, and pricing transparency for patients is a challenge due to complex relationships between payers and the limited data exchange standards in healthcare IT ecosystem. These exchanges are costly, time-consuming, and divert engineering resources, hindering product development. Delaying or skipping integrations leads to revenue loss and increased manual efforts for RCM operations teams, creating a significant barrier for behavioral health companies in a rapidly growing industry, valued at $280 billion in 2020.\n\n![uploaded image](/media/?type=post&id=72772&key=user_uploads/1376962/008d7770-25e8-44a6-9f88-883c5470b9c1)\n\n### **🧠 The Solution**\n\nSimilar to Stripe (YC09) and Plaid, Sohar Health empowers developers by providing direct integrations to payers. Our API-based platform offers three key features: targeted insurance eligibility determination, accurate network status, and AI-powered Verification of Benefits (VoB). By leveraging our services, behavioral health providers can:\n\n1. Unlock up to 25% additional revenue through improved front end RCM accuracy\n2. Find more eligible patient and minimize churn or attrition \n3. Halve the time spent on manual operations by intake or RCM teams\n\n### **👋 Our Backstory**\n\nAt Pelago (formerly, Quit Genius W18), the leading digital clinic for substance addictions, Ash and Lucas joined forces. Ash is an MD, with a background in digital health, hospital administration, and Health IT strategy consulting. As CTO and employee one at Pelago, Lucas possesses unparalleled expertise in resolving behavioral health integration challenges. With a track record of successfully integrating with 100+ employers, including major players like Evernorth and a Fortune 10 customer, Lucas's firsthand experience and Y Combinator background have been instrumental in securing over $80M in investment funding from seed to Series-B.\n\n**Our ask**\n\nIntroduce us to **behavioral health providers** (digital or hybrid) in your network. [Click here](mailto:hello@soharhealth.com?subject=Connecting%20to%20Ash%20and%20Lucas%20at%20Sohar%20Health)\n\nConnect us to your health plan or payers (e.g. Humana, Cigna, Aetna) that you’re working with. [Click here](mailto:hello@soharhealth.com?subject=Connecting%20to%20Ash%20and%20Lucas%20at%20Sohar%20Health)\n\n**Interested in hearing more?** Feel free to book a meeting [here](https://calendly.com/d/z7j-8n2-w2v/30mins-meeting-with-sohar-health)\n\n![uploaded image](/media/?type=post&id=72772&key=user_uploads/1376962/95f7f9e8-53b0-4bd6-9bd1-750d07fb0561)\n\n", "url": "https://www.ycombinator.com/launches/Ivk-sohar-health-ai-powered-eligibility-checks-vobs-and-insurance-discovery-for-behavioral-health", "votes": 20, "created_at": "2023-07-05T14:57:13.166Z" } ] }, { "id": 28868, "name": "Briefer", "slug": "briefer", "former_names": [ "Ergomake" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/1e589854f66150c916444527d7f4aa314d3961ed.png", "website": "https://briefer.cloud", "all_locations": "São Paulo, SP, Brazil; Remote", "long_description": "Briefer helps data scientists and analysts build interactive visualizations and data apps using a Notion-like interface.\r\n\r\nConnect to your data sources, write SQL or Python, collaborate through comments and multiplayer editing, and run code in whichever compute environments you need.", "one_liner": "The collaborative data platform.", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1687307247, "tags": [ "Developer Tools", "B2B", "Data Science", "Data Engineering", "Data Visualization" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2023", "status": "Inactive", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "Brazil", "Latin America", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/briefer", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/briefer.json", "year_founded": 2022, "city": "São Paulo", "country": "BR", "linkedin_url": "https://www.linkedin.com/company/briefercloud/", "x_url": "https://twitter.com/briefercloud", "fb_url": null, "cb_url": null, "github_url": "https://github.com/briefercloud", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/1e589854f66150c916444527d7f4aa314d3961ed.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Aaron Epstein", "url": "https://www.ycombinator.com/people/aaron-epstein" }, "founders": [ { "user_id": 578593, "full_name": "Lucas da Costa", "title": "Founder", "founder_bio": "I'm the founder and CEO at Briefer. Previously, I worked as a senior software engineer at Elastic and led software engineering teams at an early-stage startup in London.\n\nI used to maintain large OSS projects like Chai.js and Sinon.js and contributed to many others, including Jest.\n\nAs an author, I wrote \"Testing JavaScript Applications,\" published by Manning. I've also spoken in more than ten countries, and my content has been voluntarily translated into more than seven languages.", "is_active": false, "linkedin_url": "https://linkedin.com/in/lucasfdacosta", "x_url": "https://twitter.com/thewizardlucas", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3c67c3654b38517081d8943217dd52f520daa16d.jpg" }, { "user_id": 1372900, "full_name": "Lucas Vieira", "title": "Founder", "founder_bio": "Lucas, is a software engineer and open-source enthusiast with a decade of experience, actively contributes to numerous open source projects. He used to maintain Chai.js, a popular JavaScript testing framework with 7.8k+ GitHub stars. As the former Head of Technology at Joga, he built a product from scratch, used by thousands in dozens of countries. Now, Lucas is the CTO of Ergomake, developing a product for developers to deploy preview environments for any stack.", "is_active": false, "linkedin_url": "https://linkedin.com/in/lucas-vieira-1ba001a4", "x_url": "https://twitter.com/commadangle", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4b304961c58125ab235255d85217abb378470ab1.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 88718, "title": "❇️ Briefer Agent: your AI data analyst, built into a powerful data workspace", "tagline": "Briefer's agent helps anyone on your team turn data into clear and instant insights.", "body": "Hey YC! I'm Lucas, founder of Briefer: a data workspace for notebooks and dashboards.\n\n**✨ Today, we're launching the Briefer Agent: an AI analyst that helps anyone on your team turn data into clear and instant insights ✨**\n\n\n\nFor the past year, we've been building a powerful data workspace to help thousands of technical users uncover deep insights they wouldn't otherwise have. Many of these people use Briefer every day and get a lot of value out of it thanks to features like Python support, point-and-click visualizations, scheduling, and turning query results into data frames automatically.\n\n**Now, we're bringing Briefer's magic to _everyone_.** Whenever _anyone_ on your team has a question, they can ask our AI analyst, and it'll use Briefer to get them an answer.\n\n‎\n\n---\n\n# **⭐ It's not just another text-to-SQL chatbot**\n\n**Our AI analyst is _not_ just another “text-to-SQL” chatbot that spits out random graphs.** Instead, it's an intelligent agent that operates Briefer's powerful data workspace to generate answers that are precise and reviewable.\n\nOur agent can do anything a human analyst does in Briefer: write SQL, plot graphs, and even run Python for data manipulation and advanced analyses.\n\n‎\n\n---\n\n# **🤝 Especial things the Briefer Agent can do**\n\n* **🏦 Handle business-specific context.** If you have business-specific context you'd like to explain to the agent, you can easily add it to help the agent better understand your data and goals.\n* ☁️ **Connect to all the most popular data sources.** Briefer connects to all the most popular data sources, including Postgres, BigQuery, Redshift, Athena, Snowflake, MySQL, and others. The agent can use those data sources too.\n* **📄 Analyze CSV, XLS, and Parquet files.** If you have a CSV or Excel file, you can also upload it and ask for the Briefer agent to analyze it for you. That'll be easy because the agent knows how to use Briefer's DuckDB integration to query that file too.\n* 🎈**Run on your own infrastructure.** You can fully self-host Briefer's enterprise version and use your own Bedrock or Vertex services to power the agent. Therefore, all your data remains on your cloud, _always_.\n\n‎\n\n---\n\n# **➡️ How can I try the agent?**\n\nTo try out Briefer's agent, [book a call using this link](https://calendly.com/lucasfcosta/briefer-intro) and we'll help you get started ASAP.\n\nIf you have questions, feel free to email us, the founders, directly at [founders@briefer.cloud](mailto:founders@briefer.cloud).", "url": "https://www.ycombinator.com/launches/N4w-briefer-agent-your-ai-data-analyst-built-into-a-powerful-data-workspace", "votes": 27, "created_at": "2025-03-17T19:16:57.634Z" }, { "id": 83864, "title": "❇️ Briefer: Python notebooks and dashboards in one place (now open-source)", "tagline": "Create Python notebooks that look like Notion, and publish them as reports or dashboards.", "body": "⭐ Today, we're launching [Briefer's open-source offering](https://github.com/briefercloud/briefer).\n\n**Briefer is like Notion for code notebooks and dashboards. It gives technical users all the flexibility they need to publish dashboards, analyze data, create reports, and build data apps. At the same time, Briefer makes it easy for non-technical users to view and interact with data.**\n\n![](https://i.imgur.com/EYLk7xK.gif)\n\nIn Briefer, you can:\n\n* 📚📊 **Create notebooks and dashboards** using Markdown, Python, SQL, and native visualizations.\n* 🤳 **Build interactive data apps** using inputs, dropdowns, and date pickers.\n* 🤖 **Generate code and queries** using an AI that understands your database schema and your notebook's context.\n* 🕰️ **Schedule notebooks and dashboards** to run and update periodically.\n* ⚙️ **Create and test ad-hoc pipelines** using writebacks.\n\nIn addition to all that, Briefer is also multiplayer, meaning two or more people can work on the same notebook or dashboard simultaneously and see each other's changes in real time.\n\nFrom today, you can use Briefer for free on your machine or deploy it to your own infrastructure so that your whole team can use it and eliminate your data silos.\n\n \n\n### **🍱 What's included in the open-source offering?**\n\n![uploaded image](/media/?type=post&id=83864&key=user_uploads/578593/fdaa030e-0bad-43d6-a35f-e96332f951a6)\n\nBriefer's open-source offering includes everything you need to build notebooks and dashboards, including Markdown, SQL, Python, point-and-click visualizations, scheduled runs, writebacks, and more.\n\nAlso, given you'll be running Briefer on your own machines, there's no limit on how many users you can invite, how much memory and compute you can give to your notebooks, and how many pages you can schedule.\n\nThe only things that are _not_ in Briefer's open-source offering are PDF exports, granular permissions, and email and Slack integrations. These are available in the paid version of Briefer, for which you can sign up [here](https://briefer.cloud).\n\n \n\n### **🤔 Why open-source?**\n\nWe want people to have zero barriers to using Briefer, and we believe that making it open-source is the best way to achieve that.\n\nBy making Briefer open-source, we're giving you the freedom to run it on your own infrastructure, customize it to your needs, and contribute to its development.\n\nFurthermore, given Briefer will be running on your own machines, you don't have to worry about your data being stored in a third-party service. You have full control over your data.\n\nIf you want an in-depth explanation of our open-source strategy, [you can read it here](https://briefer.cloud/blog/posts/open-source-strategy).\n\n \n\n### **✨ How do I get started?**\n\n**➡️ You can get started by following the instructions in our **[**GitHub repository**](https://github.com/briefercloud/briefer)**. While you're there, please don't forget to give us a star ⭐.**\n\nIf you have any questions, please send me an email at [lucas.costa@briefer.cloud](mailto:lucas.costa@briefer.cloud). I respond to every email I receive from users.\n\nIn case you need help deploying Briefer or just want to talk directly to me, please [book a time here](https://calendly.com/lucasfcosta/briefer-intro-call).", "url": "https://www.ycombinator.com/launches/Loe-briefer-python-notebooks-and-dashboards-in-one-place-now-open-source", "votes": 28, "created_at": "2024-09-09T17:05:36.669Z" }, { "id": 80177, "title": "❇️ Briefer: Jupyter Notebooks and data apps in the cloud - and it looks like Notion!", "tagline": "Create and share beautiful analyses, visualizations, and data apps", "body": "\\*\\*TL;DR: If you're using Jupyter Notebooks or have ad-hoc scripts and data apps, you should consider switching to [**Briefer**](https://briefer.cloud) ❇️. Briefer works like Jupyter Notebooks, but it runs in the cloud and is as pretty and intuitive as Notion. It allows you to create beautiful and in-depth analyses, visualizations, and data apps.\\*\\*\\\n—\n\nHi, we're Lucas da Costa and Lucas Vieira (the Lucas²), founders of Briefer.\n\nWe've built Briefer to help data scientists create analyses, visualizations, and data apps and share their work with others — including non-technical people!\n\n![uploaded image](/media/?type=post&id=80177&key=user_uploads/578593/d4956051-0462-4492-b4f7-512a2652739a)\n\n[**🎬 Here's a demo 📹**](https://www.loom.com/share/f5658419cd154958862de41f1ea328c8?sid=685856a5-d188-4c53-baf3-51084ef3d141)\n\nYou can use Briefer instead of writing messy notebooks, building unmanageable ad-hoc scripts, wrangling with SQL in limited BI tools, or going through the hassle of setting up the infrastructure for a data app.\n\n# \n\n# **⭐ Briefer is better than Jupyter or ad-hoc solutions because:**\n\n* 💅 It looks way better and is 1000x easier to use — non-technical stakeholders will love it too.\n* 🤗 It's easy to share — just copy a link, no need to install dependencies or pull a git repo.\n* 💾 You can run SQL and Python in the same place — All SQL queries can be used as Pandas data-frames straightaway. No need to write custom wrapper libraries.\n* 🖥️ It's interactive — you can use text fields or dropdowns for viewers to provide input to your pages.\n* ⚡No Memory or GPUs? No problem — we can get you more powerful machines if you need them.\n* 👯 Real-time collaboration — you can see what others are doing if you're editing the same document, just like Google Drive.\n\n# **⭐ Get started now ✨**\n\n[**➡️ Click here to book an intro call if you want to get started with Briefer ⭐**](https://calendly.com/lucasfcosta/briefer-intro-call)\n\nWe move fast and we prioritize making customers happy over everything else - and we can help you build your first analyses and data apps. So, as a small team, there's a limited number of people we can onboard at a time - **make sure to book a call as soon as possible to ensure we'll get you a spot.**\n\nIf you have any other questions or comments, please email us at [founders@briefer.cloud](mailto:founders@briefer.cloud).", "url": "https://www.ycombinator.com/launches/KrB-briefer-jupyter-notebooks-and-data-apps-in-the-cloud-and-it-looks-like-notion", "votes": 73, "created_at": "2024-04-15T17:39:24.496Z" }, { "id": 73177, "title": "🧚 Ergomake - Deploy a staging environment for every pull request", "tagline": "Whenever engineers push changes, we deploy their entire application and send them a link.", "body": "**TL;DR Ergomake creates a staging environment for each pull request. Every time an engineer pushes changes, we deploy their entire application and send them a link to see it. Our customers use Ergomake for QA, product, and design reviews before any code gets merged.**\n\nHey everyone! We're Lucas and Lucas (yes, Lucas²), the founders of [Ergomake](https://ergomake.dev).\n\n![uploaded image](/media/?type=post&id=73177&key=user_uploads/578593/67fb36be-2271-4b94-8403-f3f1c9bf4612)\n\n**Ergomake creates a new staging environment every time engineers push changes**, making reviews much quicker and easier and helping teams avoid shipping broken changes.\n\n## ❌ The problem: staging is a bottleneck.\n\nEngineers must ship code to a staging environment whenever they need feedback from QAs, designers, and product managers.\n\nThe problem with this approach is that **teams usually have only one staging environment**. Therefore, **engineers scramble to see who will use staging or end up merging changes before anyone else sees them**.\n\n![uploaded image](/media/?type=post&id=73177&key=user_uploads/578593/0d929f46-4a46-425d-86e8-458fc4843816)\n\n**Consequently, teams slow down, applications break, or undesirable code gets shipped**.\n\nWhen that happens, engineers rush to fix the broken code already merged. For that, they must go through the whole review process again, which is a massive waste of time and money.\n\n## 💡 The solution: everyone gets their own staging.\n\nWith Ergomake, every change gets deployed to a new staging environment.\n\n![uploaded image](/media/?type=post&id=73177&key=user_uploads/578593/dc0ff32d-60c5-46d1-a759-b875aaaaea15)\n\nThat way, engineers can get input from the rest of their team without queueing to use staging.\n\nAdditionally, by getting reviews _before_ deploying code, teams avoid merging all sorts of undesirable changes. Consequently, they avoid bugs and reduce rework by keeping `main` always working.\n\nWith Ergomake, teams can merge straight into `main` because they do all their manual testing and validations within their pull requests. Therefore, these teams avoid complicated branching strategies and painful integration cycles.\n\n![uploaded image](/media/?type=post&id=73177&key=user_uploads/578593/9b319d08-4e0e-4239-9786-f5cc9373d979)\n\n## ⚙️ How does it work?\n\nErgomake integrates with GitHub and gets notified whenever someone opens a pull request.\n\nWhen that happens, Ergomake uses the `docker-compose.yaml` file within the repository to deploy your application on our infrastructure.\n\nOnce Ergomake has spun everything up, it adds a comment to the pull request containing the link to test your application.\n\nOur previews can include databases, and they support all types of projects, including those spread across multiple repos.\n\n## ➡️ The ask: sign-up now (there's a free tier)\n\n**You can sign-up for Ergomake at **[**app.ergomake.dev**](https://app.ergomake.dev)**.** There, you'll be able to configure previews for any repositories you want for free.\n\n**If you prefer, we're happy to do all the integration for you or hop on a call and guide you through the process**. If you think that could be helpful, [book an intro call here](https://calendly.com/lucasfcosta/ergomake-15-minutes).\n\nFor anything else, [we're also on Discord](https://discord.gg/daGzchUGDt).", "url": "https://www.ycombinator.com/launches/J2H-ergomake-deploy-a-staging-environment-for-every-pull-request", "votes": 85, "created_at": "2023-07-18T15:59:24.172Z" } ] }, { "id": 28931, "name": "Vizly", "slug": "vizly", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ba0d44f6e33397a7932f4616c99d34e64aaaa42c.png", "website": "https://vizly.fyi", "all_locations": "San Francisco, CA, USA", "long_description": "Vizly helps you get the most out of your data by turning it into actionable insights in seconds. Whether you're a researcher, professor, data analyst, or business leader, Vizly's AI capabilities enable you to visualize, analyze, and interpret your data effortlessly.\r\n\r\nFor example, Vizly can automatically generate interactive visualizations, perform detailed statistical analyses, and offer predictive insights, making your data analysis workflow seamless.\r\n\r\nBefore Vizly, Ali built out people-based AI recommendations at Apple and Sami built mission-critical data visualization systems at NASA's Jet Propulsion Laboratory.", "one_liner": "Data to insights in seconds", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1690922920, "tags": [ "Privacy", "Data Science", "Data Visualization", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2023", "status": "Inactive", "industries": [ "B2B", "Analytics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/vizly", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/vizly.json", "year_founded": 2023, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/squaredtechnologiesinc/", "x_url": "https://twitter.com/vizlyhq", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/vizly", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/ba0d44f6e33397a7932f4616c99d34e64aaaa42c.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 634427, "full_name": "Ali Shobeiri", "title": "Founder", "founder_bio": "I was previously a Machine Learning Engineer at Apple owning people based recommendations across devices. Before that, I was a ML Research Intern at Unity and a Software Engineer at Microsoft. ", "is_active": false, "linkedin_url": "https://linkedin.com/in/ali-shobeiri", "x_url": "https://twitter.com/Ali_Shobeiri", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f3b1d98183acd018ae32e0841391237a80219434.jpg" }, { "user_id": 635591, "full_name": "Sami Sahnoune", "title": "Founder", "founder_bio": "Before Vizly, Sami built mission-critical data systems at NASA's Jet Propulsion Laboratory, architected widely-used data visualization libraries at Splunk, and worked at Plotly, a leading data visualization company with over 500 million open-source downloads. His work has consistently pushed the boundaries of data visualization and analysis, benefiting thousands of users worldwide.", "is_active": false, "linkedin_url": "https://linkedin.com/in/samisahnoune", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2bb513e0ff0b55132c5db0962ac5fcd9ccac7e6c.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 74490, "title": "Vizly – Chat with your data", "tagline": "Query your data using natural language", "body": "### TL;DR - Explore your Data by Asking Questions, No External APIs Required\n\nBuilt by Apple and NASA engineers, [Vizly](https://www.vizly.fyi/) is an on-premises, AI-powered data analysis tool that allows users to perform data tasks using plain English. Instead of learning complicated BI tools, customers and enterprises can use Vizly to get AI-powered data analysis, without exposing any of their sensitive data to unsecure external APIs.\n\n### **The Problem**\n\nBI tools are complicated and have a steep learning curve to use. Despite enterprises shifting to data-centric cultures, the adoption rate of BI tools in enterprise has remained at **only 15%** \\[1\\]. With more people wanting to access data, existing BI tools have not kept up. This has left data teams to pick up the slack with analysts often spending large portions of their day fighting a barrage of data questions.\n\n### **Our Solution**\n\nWith [Vizly](https://www.vizly.fyi/), we are building a dead simple BI tool that runs fully on-premises and allows anyone to perform their data tasks using plain English. Instead of needing expensive hardware to run, a Vizly instance is both powerful enough and small enough to run even on a single MacBook.\n\nA single employee can set up Vizly on their machine by simply selecting the data sources and sharing a link with their non-technical colleagues. With just a link, anyone in the enterprise can explore the shared data sources using plain English. It operates securely behind the firewall, ensuring no data ever leaves the enterprise network.\n\n# Vizly\n\nTry it out [here](https://www.vizly.fyi/).\n\n![uploaded image](/media/?type=post&id=74490&key=user_uploads/634427/7bafc4a8-fe78-4f8d-9449-78279f199001)\n\nVizly makes data analysis as easy as asking a question.\n\n# **The Team**\n\nSami and I met at McGill University and have been friends for almost a decade. We previously built and sold [YouTube Party](https://chrome.google.com/webstore/detail/youtube-party/ngmncgebkdchkdokiecifpmodajbaopj) together, a project that gained over 300K weekly active users.\n\nNow we are using our expertise from NASA and Apple to build the next generation of enterprise BI tools.\n\nPlotly HQ in Montreal, 2019:\n\n![uploaded image](/media/?type=post&id=74490&key=user_uploads/634427/824a70b3-f7ba-49b2-9684-ed49da20e004)\n\nSan Francisco, 2023:\n\n![uploaded image](/media/?type=post&id=74490&key=user_uploads/634427/590d583a-6941-44f3-bb50-d27ea6171095)\n\nHere’s a little about the team (from left to right):\n\n[Sami](https://www.linkedin.com/in/samisahnoune/): Implemented data visualization libraries at Splunk and previously built critical data visualization systems at NASA Jet Propulsion Laboratory, enabling the Mars Perseverance Rover in its mission of drilling samples from Martian terrain. Previous experience at Plotly, building one of the most widely downloaded low-code data tools.\n\n[Ali](https://www.linkedin.com/in/ali-shobeiri/): Machine learning engineer at Apple, building out people-based recommendations. If you’ve ever shared a photo on your iPhone, or done autocomplete searches, you used a model Ali deployed. Previous experience at Plotly, Microsoft, and Unity Research.\n\n# **Our Ask**\n\n* Give Vizly a try at [vizly.fyi](https://www.vizly.fyi/)\n* Get in touch to tell us about your data needs at [ali@vizlylabs.com](mailto:ali@vizlylabs.com)\n* [Schedule a time to chat](https://cal.com/vizly/30min)\n\nLet us know what you think! Feel free to reach out to [founders@vizlylabs.com](mailto:founders@vizlylabs.com) anytime!\n\n\\[1\\] - ", "url": "https://www.ycombinator.com/launches/JNS-vizly-chat-with-your-data", "votes": 39, "created_at": "2023-08-29T21:41:30.414Z" } ] }, { "id": 28967, "name": "MantleBio", "slug": "mantlebio", "former_names": [ "DryBox Bio" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/15716b62f7c6d475631f039d985c650683ee0837.png", "website": "https://www.mantlebio.com", "all_locations": "", "long_description": "Mantle brings modern data engineering to the lab to help scientists turn insights into world-changing breakthroughs.", "one_liner": "Transform scientific data into discoveries", "team_size": 7, "industry": "B2B", "subindustry": "B2B", "launched_at": 1689053097, "tags": [ "SaaS", "Biotech", "Data Science" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2023", "status": "Inactive", "industries": [ "B2B" ], "regions": [ "Unspecified" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/mantlebio", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/mantlebio.json", "year_founded": 2023, "city": null, "country": null, "linkedin_url": "https://www.linkedin.com/company/mantlebio/", "x_url": "https://twitter.com/mantlebio", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/15716b62f7c6d475631f039d985c650683ee0837.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 876391, "full_name": "Emily Damato", "title": "Founder", "founder_bio": "CEO and Co-Founder of MantleBio, modern data engineering for biotech. Previously developed software at GRAIL, Arsenal Bio, and The Broad Institute. MIT Computer Science and Biology. 10+ years at the intersection of computer science and life science.", "is_active": false, "linkedin_url": "https://linkedin.com/in/emily-damato-36932523", "x_url": "https://twitter.com/damato_emily", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/78b9808f1e62aa083dd6d0e1a05e6d7d56f2169d.jpg" }, { "user_id": 1435929, "full_name": "Madeline Schade", "title": "Founder", "founder_bio": "CTO and Co-Founder of MantleBio. Previously worked as a software engineer at Google, Arsenal Bio and GRAIL.", "is_active": false, "linkedin_url": "https://linkedin.com/in/madeline-schade", "x_url": "https://twitter.com/SchadeMadeline", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e8c503fd7daf298aa41440bb472880783bf8898c.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 82415, "title": "MantleBio - Helping scientists transform data into discoveries", "tagline": "Modern data engineering, now available free for the scientific community", "body": "TL;DR: [Mantle](https://mantlebio.com/) makes data engineering easy (and sometimes fun) for scientists.\n\n**Today, we are excited to announce the launch of Mantle’s free plan, now available to the scientific community. Get started **[**here**](https://mantlebio.com/get-started/)**!**\n\n# 💻  Why does biology need better data engineering?\n\nBiotech generates very big, very complex data. A single DNA sequencing experiment can create 7 TB of data, and generating high-throughput multi-modal data is becoming the norm. Recent breakthroughs in computer science and ML have incredible potential to accelerate life science research. \n\nElectronic lab notebooks (ELNs), like Benchling, help organize research in the wet lab. However, biotech lacks tools to organize and analyze data from instruments, CROs, and public databases.\n\n**Does this sound familiar?**\n\n* Storing experimental metadata in file paths\n * Writing regex scripts to parse metadata out of those file paths\n * Regex scripts break when the file path format changes\n* Running bioinformatics scripts locally on a laptop\n * Not being able to process data when the computational scientist is on vacation\n * Losing analyses when the computational scientist loses their laptop on vacation\n* Analyzing datasets one by one in a desktop application\n * Not being able to compare data between teams because each person made the graph slightly differently\n * Spending a weekend regenerating all of the graphs consistently, and finding several copy-and-paste errors made on the data that was submitted to the grant application last week\n\nAt Mantle, we think science deserves better.\n\n# 🔬 What can you do with Mantle?\n\n**Instant Insights**\n\nMake decisions quickly and confidently. See everything in one place, in real time.\n\n![uploaded image](/media/?type=post&id=82415&key=user_uploads/876391/0e8966ed-9477-45c2-ba61-408feb3884e8)\n\n**Modern Data Management**\n\nDon’t let unscalable spreadsheets and inflexible databases slow down your research. Scientific research requires rapid iteration and experimentation, and Mantle’s data lake can keep up.\n\n![uploaded image](/media/?type=post&id=82415&key=user_uploads/876391/7aeaa967-f989-4112-9a74-e6b343c4f57a)\n\n**Bring Your Code**\n\nEffectively leveraging computation, data science, and ML separates the next generation of biotech companies from the last. Mantle hosts the infrastructure to help connect no-code users and great-code writers.\n\n![uploaded image](/media/?type=post&id=82415&key=user_uploads/876391/6f1860f2-4570-4fa1-8a14-b4fea6961f0c)\n\n# 🌎 How does it work?\n\nMantle is a data infrastructure layer (the “mantle” 🙂 🌎) for biological data analysis.\n\n![uploaded image](/media/?type=post&id=82415&key=user_uploads/876391/45cbb641-63e7-4475-8f46-35af154abca9)\n\n* **Import** data from ELNs (e.g. Benchling), instruments (e.g. Illumina), CROs, and more\n* **Process** data reproducibly with bioinformatics pipelines and Jupyter Notebooks\n* In a private **data lake**, find, organize, and analyze data of any type and scale\n* **Insights** are accessible to no-code users through real-time visualizations\n* **Data Science & ML** results can be easily shared and traced back to raw data\n\n**Why doesn’t biology use “normal” data engineering tools?**\n\n* **The data is different.** General-purpose tools are designed for consistently structured tabular data. Biology generates data with frequently changing metadata in biology-specific formats. _Mantle’s data lake stores data of any scale, format, or type in a single place._\n* **The ecosystem is different.** Tools that are not designed for biology don’t prioritize integrations with other tools in the science ecosystem. _Mantle has off-the-shelf integrations with standard life science tools._\n* **The processing is different.** Tabular data can typically be processed with simple transformations. Preprocessing genomics data can take dozens of hours and careful parameter tuning. _Custom and off-the-shelf bioinformatics pipelines can be run reproducibly through Mantle, with or without code._\n\n# 👋 Help us close the gap between data and discovery\n\n![uploaded image](/media/?type=post&id=82415&key=user_uploads/876391/e731a73f-ecf6-4bc2-b601-ed42ee8fb6a9)\n\nWe love data engineering, and we love helping scientists. If you’d like to, here are some ways you can help us:\n\n* **Give Mantle a try!**\n * Get started [here](https://mantlebio.com/get-started/) for free.\n* **Let us know what you think!**\n * If you want to chat or see a demo, please reach out to me here: [emily@mantlebio.com](mailto:emily@mantlebio.com)\n * If you would like help debugging a weird AWS error, please reach out to my co-founder here: [madeline@mantlebio.com](mailto:madeline@mantlebio.com) \n * We are celebrating this launch with a Computation & Biology happy hour at our SF office on August 13. Space is limited; please RSVP [here](https://lu.ma/jraavbdm).\n* **Learn with us!**\n * Check out our blogs on [bioinformatics engineering](https://blog.mantlebio.com/p/intro-to-bioinformatics-engineering), [ELNs](https://blog.mantlebio.com/p/eln-breakdown-scale-scope-and-science), and [more](https://blog.mantlebio.com/).\n * Check out our upcoming [workshops and events](https://lu.ma/mantlebio).\n* **Share this post!**\n * If you enjoyed reading this, your friends might too 😀\n\nThank you!", "url": "https://www.ycombinator.com/launches/LRH-mantlebio-helping-scientists-transform-data-into-discoveries", "votes": 13, "created_at": "2024-07-25T14:07:49.934Z" }, { "id": 72941, "title": "🔬 MantleBio: Scaling data driven discovery for biotech", "tagline": "Our data platform helps scientists and computational biologists manage and analyze high-throughput experiments", "body": "Hi everyone, we’re [Emily](https://www.linkedin.com/in/emily-damato-36932523/) and [Madeline](https://www.linkedin.com/in/madeline-schade/) from [MantleBio](http://mantlebio.com)!\n\nMantleBio is a modern data engineering platform for life science research and computational biology. While software like Benchling helps organize research in the wet lab, MantleBio powers research in the dry lab. Our platform helps biotech companies leverage advances in computational science and machine learning with tools built for biotech.\n\nIf you’re a computational biologist or work with biological data we would love to chat. Contact us at [mantlebio.com](http://mantlebio.com) or [info@mantlebio.com](mailto:info@mantlebio.com).\n\n### The Problem\n\nBiotech generates a tremendous amount of data. High-throughput sequencing and screening have become the norm, R&D groups can generate terabytes of data per day, and biotech is estimated to have the largest volume of data of any industry by [2025](https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002195).\n\nRecent breakthroughs in computer science and machine learning have the opportunity to profoundly impact scientific research. However, the majority of biotech companies lack the tools or software team necessary to fully utilize these advances and the data they have.\n\nWithout implementing the best data practices, biotech companies are often unable to find past results, reproduce analyses, or integrate multiomic datasets. This can be a bottleneck for future experiments and jeopardize regulatory filings. Meanwhile, generic data management software fails to address the complexities specific to life science. MantleBio bridges this gap, accelerating data driven discovery with tools built for biotech.\n\n![uploaded image](/media/?type=post&id=72941&key=user_uploads/1435929/28c97902-c13b-461a-917e-17858a41d971)\n\n### Our Solution\n\n* Simplify multiomics with centralized data management.\n * Other systems require scientists to design their own schemas. We collaborate with experts to create domain-aware data models available off the shelf.\n * Our API, CLI, and UI make datasets easily accessible to no-code users and computational scientists.\n* Automate the analysis of routine workflows. Start a DNA sequencing run, grab coffee, and receive the results in your inbox.\n * We connect to Benchling, Notion, BaseSpace and other systems to read experimental data from the source. Our API and data transformation pipelines allow custom integrations with even the most difficult laboratory instruments.\n* Create bioinformatics pipelines in minutes, not days.\n * Computational biologists can create production pipelines directly in MantleBio without managing cloud infrastructure or writing Docker files.\n* Prepare for the next IND filing or FDA audit with reproducible datasets and analyses.\n * MantleBio automatically records a version history for all datasets. The platform captures inputs, processing, and outputs of all analyses, creating a connected and auditable graph of everything in the computational lab.\n\n![uploaded image](/media/?type=post&id=72941&key=user_uploads/1435929/c5949154-a9ed-49a9-9fa5-37c572dc06ad)\n\n## About Us\n\nMadeline is a software engineer with experience as a full-stack engineer at multiple biotech companies and at Google working on large data pipelines. At GRAIL she developed an EDC that supported one of the largest clinical trials ever performed (over 200k patients), and at Google worked on a system supporting 10 billion queries per day. She studied computer science and computer engineering at UC Santa Cruz, where she did research in large distributed systems.\n\nEmily is a “full-stack computational biologist”. Her software experience includes back-end, full-stack, and machine learning. She has done biology research at MIT in both the wet lab and dry lab, and in industry has worked in drug discovery, cell therapy, diagnostics, molecular dynamics simulations, and patient health records.\n\nEmily and Madeline met while working as software engineers at GRAIL, a cancer diagnostic company. From there they both went to Arsenal Bio, a cell therapy company. They realized these biotech companies had common data management needs, but there was no common tool available. They started MantleBio to make the best data engineering practices accessible to all life science research.\n\n### Want to learn more?\n\nContact us at [mantlebio.com](http://mantlebio.com) or [info@mantlebio.com](mailto:info@mantlebio.com).\n\nWe love helping scientists. If you have questions about your current data practices (e.g.“will this scale?”) we also do free data infrastructure reviews.", "url": "https://www.ycombinator.com/launches/IyT-mantlebio-scaling-data-driven-discovery-for-biotech", "votes": 45, "created_at": "2023-07-11T17:43:56.253Z" } ] }, { "id": 29134, "name": "Cognitio Labs", "slug": "cognitio-labs", "former_names": [ "Flair Technology Services Inc.", "Flair", "Flair Health", "Flair Technologies" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ef89599f5919a67db2c626d5aa12b8e6f38bf8da.png", "website": "https://cognitioiq.com", "all_locations": "Los Angeles, CA, USA", "long_description": "CoAsync by Cognitio Labs is the AI back office for product quality compliance teams.\r\n\r\nWe help mission-critical food manufacturers automate repetitive, document-intensive workflows.\r\n\r\nWe started with Certificates of Analysis (COAs), one of the many workflows quality teams manage before products can ship. Today, this work is still performed manually across PDFs, emails, spreadsheets, and disconnected ERP systems. \r\n\r\nOther documents we help quality teams respond to 24x7 include supplier audit questionnaires, production schedules, lab reports & changes in product specifications and quality records.\r\n\r\nCoAsync automates the workflow by:\r\n\r\nReading supplier documents\r\nExtracting laboratory data\r\nValidating product specifications\r\nApplying compliance requirements\r\nDrafting compliant COAs\r\nOrganizing audit-ready documentation\r\n\r\nResults from one of our initial deployments with a mid-market food processor:\r\n\r\n85% less QA administrative work\r\n4× more COAs processed per shift\r\n1-2 hours saved per document\r\nNew product onboarding in under one day\r\n\r\nCOAs are just the beginning. Our vision is to build the AI back office for product quality and compliance across regulated industries by automating the many document-intensive workflows manufacturers manage every day.\r\n\r\nBacked by Y Combinator and leading investors. Founder Diva Avaya Sharma has presented example AI workflows for product quality and compliance through the World Economic Forum Centre for Advanced Manufacturing and Supply Chains' SmartStart initiative and at the International Telecommunication Union's AI for Good Global Summit, organized in partnership with the United Nations.\r\n\r\nKnow a company shipping food & product urgently? Help them get started with their own document workflows at https://cognitioiq.com", "one_liner": "AI back office for food product quality teams", "team_size": 3, "industry": "Industrials", "subindustry": "Industrials", "launched_at": 1690407835, "tags": [ "AIOps", "B2B", "Data Science", "AI", "AI Assistant" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 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": null, "url": "https://www.ycombinator.com/companies/cognitio-labs", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2023/cognitio-labs.json", "year_founded": 2025, "city": "Los Angeles", "country": "US", "linkedin_url": "https://www.linkedin.com/company/cognitio-labs/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/ef89599f5919a67db2c626d5aa12b8e6f38bf8da.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 339188, "full_name": "Diva Avaya Sharma", "title": "Founder", "founder_bio": "Diva is the founder of Cognitio Labs (former Flair telehealth) and inventor of a patented remote patient monitoring device. Previous companies & projects at Ancestry.com, Facebook, Johnson & Johnson, and the Stanford School of Medicine. Alum: Stanford University (Bachelors)", "is_active": true, "linkedin_url": "https://linkedin.com/in/diva-sharma", "x_url": "https://twitter.com/adivawhocodes", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/66eb801562304c65890ec479268fc5fa4cacc625.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 109669, "title": "Cognitio Labs - the AI Back Office for Product Quality Teams", "tagline": "CoAsync by Cognitio Labs, the AI back office for product quality teams.", "body": "CoAsync by Cognitio Labs, the AI back office for product quality teams.\n\n\n\nCertificates of Analysis are one of the sources of documentation clogging food and consumer product shipments today. Every day, millions of dollars of product sit waiting to ship because paperwork isn't ready to certify it is safe.\n\nBefore food can leave a facility, quality teams review supplier documents, lab reports, product specs, and regulatory requirements to produce a COA, the document certifying a product is safe, meets quality standards, and complies with destination-country rules. That still happens across PDFs, emails, spreadsheets, and disconnected ERPs, and a single COA can take hours.\n\nCoAsync ingests supplier documents, extracts lab data, validates specifications, applies country-specific compliance requirements, and drafts audit-ready COAs, keeping quality teams in control at every step.\n\n![uploaded image](/media/?type=post&id=109669&key=user_uploads/339188/d089cbb5-ccba-49ee-a89b-29f4ad88253f)\n\n\nResults: A Fresno-based dry fruit manufacturer cut COA processing from 8 hrs/week to under 1 hr in a six-week deployment, an 85% drop in QA admin work. A California fig grower now processes 4x more COAs per shift, saving 1 to 2 hours per document, and onboarded in under a day.\n\n![uploaded image](/media/?type=post&id=109669&key=user_uploads/339188/c9de609b-22b8-4634-a6d0-47768cd58e52)\n\n\nWe're starting with food, one of the most document-intensive, regulated supply chains in the world, building toward an AI operating system for safety and quality across consumer products adoption.\n\nOur founder @[Diva Avaya Sharma](https://www.linkedin.com/in/diva-sharma/) presented on critical supply chains adopting artificial intelligence tools at the World Economic Forum's SmartStart Manufacturing Initiative Initiative and the AI for Good Global Summit (International Telecommunications x United Nations).\n\nIf you know a food, consumer products, or ingredients manufacturer buried in paperwork overload, we welcome an introduction: .\n\n![uploaded image](/media/?type=post&id=109669&key=user_uploads/339188/7e9b5cea-da52-47c8-b61a-c419b89e02bf)\n\n\n#YCLaunch #FoodTech #SupplyChain #AI #FoodSafety", "url": "https://www.ycombinator.com/launches/SWr-cognitio-labs-the-ai-back-office-for-product-quality-teams", "votes": 2, "created_at": "2026-08-07T17:12:02.313Z" }, { "id": 104819, "title": "Cognitio Labs: The AI back office for Food & Product Quality", "tagline": "The AI back office for Food & Product Quality", "body": "[Cognitio Labs ](https://cognitioiq.com/)is building CoAsync, the AI back office for product quality teams. We started with one of food's most document-intensive workflows: the Certificate of Analysis.\n\n85% less QA admin time. 4× more COAs per shift. New products onboarded in under a day.\n\nEvery day, millions of dollars of food sit waiting to ship because the paperwork isn't ready.\n\nBefore food can leave a facility, quality teams manually review supplier documents, lab reports, product specifications, and regulatory requirements to produce a Certificate of Analysis (COA). It's just one of dozens of document-heavy workflows quality teams manage every day.\n\nToday, that work still happens across PDFs, emails, spreadsheets, and disconnected ERP systems. A single COA can take hours.\n\nOver a six-week deployment, the manufacturer reduced COA processing time from 8 hours per week to under 1 hour, centralized supplier documentation, and dramatically improved audit readiness. The result was an 85% reduction in QA administrative work.\n\nCoAsync ingests supplier documents, extracts lab data, validates specifications, applies country-specific compliance requirements, drafts compliant COAs, and prepares audit-ready documentation while keeping quality teams in control at every step.\n\nWe're starting with food because it's one of the most document-intensive, highly regulated supply chains in the world. Our vision is to build the AI back office for product quality and compliance across every regulated industry.\n\nThis summer, our founder [Diva Avaya Sharma](https://linkedin.com/in/diva-sharma) is presenting example AI workflows for product quality and compliance through the World Economic Forum Centre for Advanced Manufacturing and Supply Chains’ SmartStart initiative and at the AI for Good Global Summit, organized by the International Telecommunication Union (ITU) in partnership with the United Nations. These examples explore how AI can reduce repetitive documentation, strengthen compliance, and support the next generation of quality, manufacturing, and supply chain professionals.\n\nAre you a food quality manufacturer or processor ready to see CoAsync on your own products? Upload a supplier document, a sample lab report, and a historical COA, and watch your quality workflow automate in minutes on ", "url": "https://www.ycombinator.com/launches/RGd-cognitio-labs-the-ai-back-office-for-food-product-quality", "votes": 3, "created_at": "2026-07-06T15:52:02.427Z" }, { "id": 99119, "title": "Cognitio Labs – Real-time food traceability for safety and compliance", "tagline": "Automating real-time food traceability for FDA compliance", "body": "[Cognitio Labs](https://cognitioiq.com) is an applied AI research lab building real-time compliance infrastructure for regulated supply chains, serving as the first line of defense against recalls and regulatory failure.\n\nView our launch video at: [**https://youtu.be/iFD6vxaS0eY**](https://youtu.be/iFD6vxaS0eY)\n\nWhen a food contamination event happens, time is everything. If traceability takes days instead of hours, entire product categories get destroyed, brands lose trust, and recalls cost $10M to $100M+.\n\nYet today, most operators still rely on spreadsheets, PDFs, and manual logs. Traceability data is fragmented across facilities, systems, and partners, and critical events like temperature, handling, and lot transformations are not automatically captured or standardized. As a result, generating accurate, regulator-ready records is slow, manual, and error-prone.\n\n**Why now:** The FDA’s [FSMA 204 rule](https://www.fda.gov/food/food-safety-modernization-act-fsma/fsma-final-rule-requirements-additional-traceability-records-certain-foods) requires companies to produce standardized, lot-level digital traceability records within 24 hours by 2028, impacting over 60,000 U.S. food facilities. The regulatory bar is rising, but the infrastructure to meet it requires improvement.\n\nWe are building that infrastructure.\n\nOur system uses sensors and AI to automatically capture key events such as temperature, humidity, handling, and lot-level movements across production, storage, and transit. We convert fragmented operational data into standardized, FSMA 204-compliant traceability records and generate regulator-ready reports in real time.\n\nCompliance is generated as operations happen, not after.\n\nThis becomes the first line of defense by enabling faster recalls, reducing spoilage, eliminating manual compliance work, and protecting contracts, insurance coverage, and brand equity. Avoiding even one major recall can save $10 million to over $100 million.\n\nCognitio Labs was founded by [Diva Avaya Sharma](https://www.linkedin.com/in/diva-sharma/), a Stanford-trained technologist who previously built a patented remote patient monitoring system integrating sensors and machine learning in regulated healthcare environments, recognized by global development institutions and national innovation programs.\n\nWe are starting with food and expanding into other regulated, high-risk supply chains.\n\nLearn more at [**cognitioiq.com**](http://cognitioiq.com).\n\nFollow our Linkedin Page [**here**](https://www.linkedin.com/company/110755112/)**.**", "url": "https://www.ycombinator.com/launches/Pmh-cognitio-labs-real-time-food-traceability-for-safety-and-compliance", "votes": 11, "created_at": "2026-03-26T19:07:46.555Z" } ] }, { "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": [ "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": null, "url": "https://www.ycombinator.com/companies/quary", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/quary.json", "year_founded": 2023, "city": "London", "country": "GB", "linkedin_url": "https://www.linkedin.com/company/quarylabs", "x_url": "https://twitter.com/quarylabs", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/quary", "github_url": "https://github.com/quarylabs/", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/e54d14cc55231dd1bd8f1cfd85b8f8366f88fae7.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Brad Flora", "url": "https://www.ycombinator.com/people/brad-flora" }, "founders": [ { "user_id": 1400304, "full_name": "Benjamin King", "title": "Founder", "founder_bio": "American and British Luxembourger. Failed physicist. Cofounder and ex-CTO of Tumelo. Now working on Quary.", "is_active": false, "linkedin_url": "https://linkedin.com/in/benfking", "x_url": "https://twitter.com/BenFKing", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/57e5a152908e6b47ecc0300e14b991407d92bc63.jpg" }, { "user_id": 528679, "full_name": "Louis Jordan", "title": "Founder", "founder_bio": "Ex-Amazon (Data/Fintech)", "is_active": false, "linkedin_url": "https://linkedin.com/in/louis-j-52841a105", "x_url": "https://twitter.com/louisjoejordan", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/90d150f0764608d33f53599e65c132f972ce4e1f.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 78152, "title": "🆀 Quary - Transform data together 🤝", "tagline": "Stop depending on your data team and bring everyone into the data action!", "body": "**tl;dr: Quary connects to your data warehouse and lets your team transform raw data into valuable insights in seconds, right from your browser! Try our free trial:** [www.quary.dev](http://www.quary.dev)\n\n\\\nHey 👋. [Ben](https://linkedin.com/in/benfking) and [Louis](https://www.linkedin.com/in/louisjor/) here, we’re excited to share what we’ve been up to! [Quary](https://www.quary.dev/) is a browser-based **SQL transformation tool** that turns your raw data— whether in Snowflake, BigQuery, or DuckDB— into organized, well-documented & tested transformations.\n\n![uploaded image](/media/?type=post&id=78152&key=user_uploads/528679/2e025d53-262b-4795-823a-57dba3ba798e)\n\n**❌ The problem**\n\nData engineers make up **5%** of businesses. They dig for insights for the other **95%** with predictable outcomes: siloed & overworked data teams, unshared knowledge, and delayed answers to critical business questions.\n\n**✅ The solution**\n\nQuary makes data engineering collaborative, sharing the responsibility across the organization. With Quary, **5%** becomes **50%**. Anyone who writes SQL can build production-grade pipelines in minutes.\n\n**The team**\n\n**Ben** and **Louis** here, we’re originally from Luxembourg 🇱🇺. Ben founded [Tumelo](https://www.tumelo.com) and led engineering there through its Series A. Louis survived a 4-year stint as a Software Engineer in Finance at Amazon.\n\n**Try out our free trial:** ", "url": "https://www.ycombinator.com/launches/KKW-quary-transform-data-together", "votes": 138, "created_at": "2024-02-05T15:57:48.178Z" } ] }, { "id": 29366, "name": "Metofico", "slug": "metofico", "former_names": [ "Metofico ltd" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/9fad9edec40c2dac0c3cfb3743f5450804f2ada1.png", "website": "https://metofico.com/", "all_locations": "London, England, United Kingdom; Remote", "long_description": "Metofico provides a no-code data analysis tool tailored for the life sciences. Our platform enables life scientists to analyse complex/massive datasets and extract necessary insights without needing advanced programming skills. This accessibility helps both researchers new to data science and experts save months of work.\r\n\r\nMetofico aims to be the leading centralized platform for data analysis in life science research, covering a wide range of applications from brain activity analysis (like photometry and EEG) to AI-powered detection and tracking of research animals. Our vision is to accelerate research processes and enhance the quality of research outputs across the board. By streamlining complex data analysis and making it more accessible, we’re committed to driving forward scientific discoveries and innovation.\r\n", "one_liner": "No Code Data Analysis for Life Science Research", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1710801203, "tags": [ "SaaS", "Data Science", "No-code", "Data Visualization" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2024", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United Kingdom", "Europe", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/metofico", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/metofico.json", "year_founded": 2021, "city": "London", "country": "GB", "linkedin_url": "https://www.linkedin.com/company/31390857/admin/inbox/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/9fad9edec40c2dac0c3cfb3743f5450804f2ada1.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Tom Blomfield", "url": "https://www.ycombinator.com/people/tom-blomfield" }, "founders": [ { "user_id": 1579715, "full_name": "Mehdi Boudjadja", "title": "Founder/CEO", "founder_bio": "Neuroscientist and CEO of Metofico", "is_active": true, "linkedin_url": "https://linkedin.com/in/mehdi-boutagouga-boudjadja-ph-d-553003138", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/35447ebe58a029b7c9c308575029eb5afc769a65.jpg" }, { "user_id": 1634457, "full_name": "Salah Boudjadja", "title": "Founder/CTO", "founder_bio": "Co-founder and CTO of Metofico ltd.\nI really enjoy creating solutions for data science and analysis since I obtained my Master's degree in programming, computer vision and signal processing at the University of Paris Est.\nMy passion for digital art also allows me to create Metofico's graphic designs.", "is_active": true, "linkedin_url": "https://fr.linkedin.com/in/salah-boudjadja-42a05a19b", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/55e10aa93f3c0834a7d0de95eebbbbe631f7f315.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 79483, "title": "Metofico - No-code data analysis for life science research", "tagline": "We make it easy for life scientists to process large and complex data within minutes instead of weeks or months", "body": "Hello everyone, we are Mehdi and Salah, the co-founders of [Metofico](https://www.metofico.com/), and we are on a mission to simplify the analysis of complex and large data sets produced by life science research and save researchers months of work.\n\n![uploaded image](/media/?type=post&id=79483&key=user_uploads/1579715/fd599206-68e4-44cb-82b3-7478fb7d4627)\n\n_From left to right:_\n\n[Salah:](https://www.linkedin.com/in/salah-boudjadja-42a05a19b/) MSc in Data Science, Image Processing, and AI; Salah is passionate about making no-code and intuitive tools for science to extract as many insights as possible in the least amount of time.\n\n[Mehdi:](https://www.linkedin.com/in/mehdi-boutagouga-boudjadja-ph-d-553003138/) PhD in Circuit Neuroscience; Mehdi has seen many researchers struggle to analyse Gigabytes of data in Excel and missing opportunities for scientific breakthroughs. He has developed tools to make these analyses simple, and these tools are now Metofico.\n\n**The Problem: Data analysis complexity hampers life scientists, slowing down research.**\n\nThe volume and complexity of data generated by modern life science research are overwhelming. Traditional tools like Excel, once the go-to for researchers, now fall short when faced with gigabytes or terabytes of data. Moreover, most life scientists cannot program or do advanced data science, so they are stuck.\n\n**Our Solution: A no-code, intuitive SaaS platform designed specifically for life science research**\n\nOur platform transforms the way life scientists handle and analyse data, making processes that used to take weeks or months achievable in just minutes. Whether it's video tracking of rodents, fiber photometry, or any other data-intensive research, Metofico makes it simple and fast, with no programming knowledge required.\n\n![uploaded image](/media/?type=post&id=79483&key=user_uploads/1579715/b1b25a9c-9115-4d58-96fc-b2945d58647c)\n\nExample of automated segmentation of rodents using our AI\n\n**Demo:**\n\n\n\nExample of brain activity analysis using our fiber photometry analyzer\n\n**Our Ask:**\n\nWe're seeking forward-thinking life science researchers and institutions interested in streamlining their data analysis processes. If you're ready to cut down months of work to just minutes, we'd love to get in touch. Whether it's for feedback, potential partnerships, or just to say hello, your insights are invaluable to us as we strive to make Metofico even better.\n\nContact us at [info@metofico.com](https://mailto:info@metofico.com)", "url": "https://www.ycombinator.com/launches/Kfz-metofico-no-code-data-analysis-for-life-science-research", "votes": 15, "created_at": "2024-03-18T22:34:05.805Z" } ] }, { "id": 29375, "name": "Preloop", "slug": "preloop", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/62ebbbabf82f9c9badd0bbcb60f8749d391d5a78.png", "website": "https://www.preloop.com", "all_locations": "Seattle, WA, USA", "long_description": "Only 2 out of 10 ML models make it from experiment to production. Preloop helps automate the process of deployment, helping companies realize more value from their machine learning teams, while focusing teams' attention on science instead of engineering.", "one_liner": "Translate your experimental scripts into production ML services", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1702654646, "tags": [ "Deep Learning", "Developer Tools", "Machine Learning", "Data Science", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2024", "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": null, "url": "https://www.ycombinator.com/companies/preloop", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/preloop.json", "year_founded": 2023, "city": "Seattle", "country": "US", "linkedin_url": "https://www.linkedin.com/company/preloop/", "x_url": "https://twitter.com/preloop", "fb_url": "https://facebook.com/preloop", "cb_url": "https://www.crunchbase.com/organization/preloop", "github_url": "https://github.com/preloop", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/62ebbbabf82f9c9badd0bbcb60f8749d391d5a78.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Diana Hu", "url": "https://www.ycombinator.com/people/diana-hu" }, "founders": [ { "user_id": 1310033, "full_name": "Tejas Hosangadi", "title": "Founder/CEO", "founder_bio": "Tejas is the co-founder and CEO of Preloop, a product that automatically translates ML experimental scripts into production services. Before Preloop, he worked at Amazon where he scaled a data science team from 0-1, delivering 4 projects in the first year and leading the expansion of the team. He also worked as a senior MLE at EvolutionIQ, where he made significant improvements to a predictive model in his first month, helping them land a long term contract with Prudential.", "is_active": false, "linkedin_url": "https://linkedin.com/in/tejashosangadi", "x_url": "https://www.twitter.com/tejastmh", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/02c87a1b7a20ffb5d7fdff8f05417310d0a049b5.jpg" }, { "user_id": 1660688, "full_name": "Nikith Hosangadi", "title": "Founder", "founder_bio": "Technical founder experienced in working with distributed systems and machine learning. Before Preloop, he worked as a software engineer at AWS, writing code in C and Java for the VPC team.", "is_active": false, "linkedin_url": "https://linkedin.com/in/nikithhosangadi", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9d2b3aed1c122e5c4788fc71373bfc4dd8e5ad4d.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 78894, "title": "➿ Preloop - Deploy your ML models in hours instead of weeks", "tagline": "Preloop automatically translates your experimental scripts into production ML workflows", "body": "**Tl;dr:** [Preloop](https://www.preloop.com/) automatically translates your ML training scripts into production services, handling the creation of the training pipeline and REST endpoints. This means that science teams can focus on developing new models while cutting deployment times from weeks to just a few hours (or less). We’re building Vercel for model deployments.\n\n—\n\nHey everyone, we’re [Tejas](https://linkedin.com/in/tejashosangadi) and [Nikith](https://linkedin.com/in/nikithhosangadi) and we’re building Preloop. Tejas previously worked as a data scientist and software engineer at several companies, including Amazon and most recently EvolutionIQ, often leading 0-1 projects on newly established teams. Nikith has experience as a software engineer building multi-tenant distributed systems, most recently working at AWS on the networking team.\n\n![uploaded image](/media/?type=post&id=78894&key=user_uploads/1310033/6f2948a3-73ad-43eb-829c-0b23006cd26b)\n\nOur goal is to unshackle scientists from the repetitive tasks that accompany their model deployments and empower science teams to move faster. \n\n## **😫 The problem**\n\nData scientists hate the work associated with deploying their models. Science teams spend anywhere from a couple of weeks to over two months deploying their models. Assuming that a team deploys 10 models a year and each model takes 2 weeks on average to deploy, this is 20 weeks of science time spent just on deployments. \n\nThe biggest bottlenecks to quick deployment are a lack of easy-to-use tools and delays caused by handing off deployments to a separate team.\n\n## **🪄 Our solution**\n\nPreloop automates the tedious and repetitive tasks associated with deploying and using your ML models, including creating the training pipeline and inference endpoints, autoscaling based on demand and retraining. We provide an easy-to-use CLI in addition to a dashboard to monitor and track your models. It works with major ML packages like xgboost, torch, and scikit-learn, with broader support on the roadmap.\n\n![uploaded image](/media/?type=post&id=78894&key=user_uploads/1310033/3a401fe4-e051-45c2-a3b9-98bd8b492abd)\n\n## **🔍 How it works**\n\nWe scan through your existing script, identifying key information about the data, transformations, and the model being trained. This is used to construct both the training and data pipelines, as well as the inference endpoints that serve your model. \n\n![uploaded image](/media/?type=post&id=78894&key=user_uploads/1310033/976dd0ad-2492-43a4-a674-eb3618536144)\n\nWe also handle auto-scaling, observability, and versioning, so that you can train and deploy, but just as easily roll back unintended model changes. We have support for on-prem deployments for teams that have stronger security requirements.\n\n## **🤔 Why are we building this?**\n\nAs a data scientist, Tejas noticed that scientists (including himself) loved experimenting and building models but hated deploying them. More importantly, he witnessed that it often took multiple weeks before they were in production. There was a lack of a more automated solution to handle the deployment process, and even tools like Sagemaker require tons of boilerplate to work.\n\nWe want to make it easier to deploy models, so that teams can move quicker, and scientists can focus more on science. \n\n## **🙏 Our ask**\n\n* Intros to data science and ML managers at mid to large-size startups as well as large enterprises. \n* If your science team struggles with lengthy deployment times, please reach out to us by emailing [founders@preloop.com](mailto:founders@preloop.com), or by booking a meeting [here](https://outlook.office.com/bookwithme/user/27ea63c6cc9c4d398ba6525a9c0e6b25@preloop.com/meetingtype/ZKpbyV0QyU2cya_WNaNuJw2?anonymous&ep=mlink).", "url": "https://www.ycombinator.com/launches/KWU-preloop-deploy-your-ml-models-in-hours-instead-of-weeks", "votes": 209, "created_at": "2024-02-29T16:10:32.259Z" } ] }, { "id": 29439, "name": "camelAI", "slug": "camelai", "former_names": [ "qaml (pronounced camel)", "qaml", "camelQA" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/db5295154418cf383d1fd6006f379854b772ebda.png", "website": "https://camelai.com/", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "Unlimited inference at $5 per stream", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1701468865, "tags": [ "SaaS", "Data Science", "Data Visualization", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2024", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": true, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/camelai", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/camelai.json", "year_founded": 2023, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/usecamelAI", "x_url": "https://twitter.com/usecamelAI", "fb_url": null, "cb_url": null, "github_url": "https://github.com/qaml-ai", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/db5295154418cf383d1fd6006f379854b772ebda.png", "app_video_url": "https://bookface-images.s3.us-west-2.amazonaws.com/bf-public_profile/29497/app_video.mp4?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAQC4NIECAOMAGS7ZB%2F20261020%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20261020T022719Z&X-Amz-Expires=60&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEHEaCXVzLXdlc3QtMiJHMEUCIG5%2FEuPdHreXKRdGLYlyC2AjaYHPccvwucNqtFtDJEpNAiEAs4s5lSDOcogMQrwGhSKvVJXgimMvlIc1KK%2Fa7hojYD4q5QMIOhAAGgwwMDYyMDE4MTEwNzIiDMPa%2BQzgV8CSsX3XwyrCA9yWuwhv7VPDGJqPM%2BDoevlHz47k5lLRdgsGITLyqtSgmLV07z1Y86XDlb4dZMfcWmY5u5FLutDaUy2PMJ92q6vIq41n2jI5tC6SNSed8Qx%2Frdr9Wotko6WcUJWENt0Rs1K4pKZ8ZHCjH22BoWJkWLaTQ8fDKsmgWu0C8NMhnc8i44rKtbZLOvQwKZIlI546tkfyyliSiXPWdZ4XhGxEegateXp4TnM4yWfebpv22hrRHRotmFYX8ANU3B8yiEQL9yrU1y10N8c42JlHR%2FXHZNxaFQqX6eENp2aa2yewya2kPgdiQ3efnk5d0LiuPYxk7ZBa6uOug4fCBPHurDSGZqOlYX9D4h6PAMyUN2kZw2IcUR9QWKM2BmEsGorqokH5Oe34gs0DmnOGrGbhANOh9LKlKDu%2B6Pc4U%2F8L3%2Bmxug0q%2B3JBUGE7Wf6ySj%2B%2BbW8eOteynPrtIEUsD0pcfnSFNzQepsmnoTP5xc7qG%2FEn4MNWO3TviPmcIdg9qyW7bwOWKSyly4BuerWbZWVxIVolnUdqKu2PxDrgnb41QrRtObgKLlbhdehgPlqhIVqZ1cWH9s2uGHoiWlN5FRY8vYYodKzLGjDn%2FdrWBjqlAdXY8WsF5AC2X79ObZ%2FmZD1gjSCNFddCxk1e7RhQVznesCZJDMryJDWqJGSqI7lLEk62aPqOUbquB9Ghba%2BJXI%2FUV%2BHgkJZAPy7wzbnv8vLB8WccujudilaH29xgpqopxweKHuQzlcRMMeq0SZHCo3PizMnbhtLrqB%2BiK9IdfwMp8c15fBnQEe2RAGCsOWYNCrhsPiR6yT5V9698E5KnRPYRfOeFQw%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=961f85a73b60d52d2fbc6bf10064f19df5e6db1411e465e5649a2f707faecf27", "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Tom Blomfield", "url": "https://www.ycombinator.com/people/tom-blomfield" }, "founders": [ { "user_id": 1925221, "full_name": "Illiana Reed", "title": "Founder/CEO", "founder_bio": "CEO @ camelAI - building unlimited DeepSeek Flash at $5/stream/month", "is_active": true, "linkedin_url": "https://linkedin.com/in/illiana-reed", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c2ba4e9c1a7448d1241ecc5940b94d40ccd796c1.jpg" }, { "user_id": 1925222, "full_name": "Isabella Reed", "title": "Founder/CRO", "founder_bio": "I'm the COO & Co-Founder of CamelAI.", "is_active": true, "linkedin_url": "https://linkedin.com/in/isabellareed", "x_url": "https://twitter.com/isabella_patane", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a5b99cfd60854ffffb4071d64bf2931bf1122b64.jpg" }, { "user_id": 321757, "full_name": "Miguel Salinas", "title": "Founder/CTO", "founder_bio": "Cofounder & CTO at CamelAI, the AI Business Intelligence and Data Analysis Agent", "is_active": true, "linkedin_url": "https://linkedin.com/in/miguel-salinas-b2781426", "x_url": "https://twitter.com/Vercantez", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/39eb6f4ee20f85cea33fa737cad71d9c78c7cb5b.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 94363, "title": "CamelAI API: Ship \"Chat With Your Data\" in 5 Minutes", "tagline": "Give your users an AI-powered data analytics chat without building it yourself. We handle the complex stuff so you ship faster.", "body": "**The Problem**\n\nYour users want to chat with their data. Building this yourself means:\n\n* 3+ months of engineering time\n* Wrestling with SQL generation, context windows, and hallucinations\n* Maintaining AI infrastructure that isn't your core product\n* Constant updates as models evolve\n\nMeanwhile, your competitors are shipping AI features today.\n\n**Our Solution: CamelAI API**\n\nConnect your database. Embed our iframe. Ship in 5 minutes.\n\n```\nresponse = requests.post( 'https://api.camelai.com/api/v1/iframe/create', headers={'Authorization': 'Bearer token', 'Content-Type': 'application/json'})\n```\n\n_Your users get:_\n\n* Natural language to SQL that actually works\n* Interactive Plotly visualizations\n* Context that learns their business terminology\n* Easy-to-make dashboards\n\n![uploaded image](/media/?type=post&id=94363&key=user_uploads/1925222/4ab6ceae-6239-4deb-b592-7cc8beda11ff)\n\n![uploaded image](/media/?type=post&id=94363&key=user_uploads/1925222/cc044d1a-3a97-42d4-9bfe-299dbfe4b17b)\n\n_You get:_\n\n* Zero maintenance AI infrastructure\n* A beautiful chat embed\n* Full customization to match your brand\n* Works with Postgres, MySQL, Snowflake, BigQuery, ClickHouse, and more\n* Built in row-level security for multi-tenant architecture\n\n![uploaded image](/media/?type=post&id=94363&key=user_uploads/1925222/3255be73-e070-41be-b598-9283a3623374)\n\nWe process over 40,000 queries every month. On average, integrating camelAI’s embeddable API takes just 5 minutes. Since our Product Hunt launch in July 2025, camelAI is already live in production with 2 Fortune 500 companies and dozens of startups.\n\n**Who's Using This**\n\n* Vertical SaaS platforms tired of building custom dashboards for every customer\n* Data companies that need to offer self-serve analytics, but don’t want to invest a team of engineers\n* Enterprise teams replacing ticket queues with instant insights\n\n_Example:_ A transaction cleansing platform embedded CamelAI so their banking clients could explore their own data without filing support tickets. Integration took one afternoon.\n\n**Pricing**\n\nPro: $200/month + usage (includes $10 credits)\n\nEnterprise: Custom pricing, VPC deployment, dedicated support\n\n**Start Now**\n\nNo sales calls. No demos required. Try free today.\n\n1. Visit [camelai.com/api](https://camelai.com/api)\n2. Grab your API key\n3. Ship your AI feature today\n\nQuestions? Shoot us an email at: [founders@camelai.com](mailto:founders@camelai.com)", "url": "https://www.ycombinator.com/launches/OXz-camelai-api-ship-chat-with-your-data-in-5-minutes", "votes": 7, "created_at": "2025-10-07T14:05:09.594Z" }, { "id": 76776, "title": "camelAI — The First Deep Research Agent for Your Structured Data", "tagline": "Ask questions, get insights from your data.", "body": "Hi YC! We're [Illiana](https://www.linkedin.com/in/illiana-reed/), [Miguel](https://www.linkedin.com/in/miguel-salinas-b2781426/), and [Isabella](https://www.linkedin.com/in/isabellareed/), the team behind camelAI.\n\n# What We're Building\n\ncamelAI is the last BI tool you'll ever need. What AI has done for coding, camelAI is doing for analytics. We connect an LLM directly to your database, turning natural language questions into in depth reports complete with beautiful visualizations in seconds. No modeling, no drag-and-drop limitations, no tickets to the data team.\n\n\n\n# The Problem: Text-to-SQL Has Failed\n\nLet's be honest: Text-to-SQL has been around for years. It's been done to death and it still leaves users frustrated. Instead of giving clear answers, Text-to-SQL makes users fight for insights:\n\n* Setup takes forever\n* Queries only work well for narrow, predictable questions\n* Results come as raw data tables, not analysis\n* Business users struggle to get actionable insights\n\nBusiness users don't want raw tables of data—they need clear insights. But text-to-SQL forces them to piece together answers manually, leaving them frustrated and no closer to a decision.\n\nThe real problem: Getting valuable insights out of your own data is still too hard and too time consuming.\n\nFor executives, founders, and product managers, this means:\n\n* Waiting days for simple data requests\n* Making decisions without complete information\n* Spending hours building and maintaining dashboards\n* Wasting precious engineering time for a \"quick data pull\"\n\nFor technical teams, it means:\n\n* Constant context-switching to answer basic data questions\n* Building one-off dashboards that are rarely used\n* Explaining the same metrics repeatedly\n\n## Our Solution: camelAI\n\nAsk camelAI anything - from basic KPIs to complex business metrics your team hasn't even thought to track:\n\n**Deep Research Agent:** Watch as our Agent writes SQL queries in real time, explores your data, and generates interactive visualizations that deliver immediate insights. Complete transparency at every step.\n\n**Learns Your Company:** camelAI learns your company's language through use. It remembers past queries and improves through your feedback, creating consistent company-specific analysis.\n\n**Instant Visualizations:** camelAI doesn't just dump query results; it automatically creates interactive Plotly visualizations with written analysis of what the data actually means.\n\n**One-Click Dashboards:** Any visualization can be saved to a dashboard that refreshes automatically. Create comprehensive dashboards in minutes, not hours.\n\n**Enterprise-Ready:** We support on-prem and VPC deployments across multiple databases.\n\n# The New Reality\n\nWithout camelAI:\n\n1. Adding tickets to sprints for basic data questions\n2. Waiting days for simple insights\n3. Engineers constantly pulled away from building products\n\nWith camelAI:\n\n1. Business teams get answers immediately\n2. Engineers focus on building products\n3. Founders make better decisions faster\n\n## Who Needs This Yesterday\n\n* **Founders** who can't afford to wait for data\n* **Product Teams** tracking metrics without a dedicated analyst\n* **CTOs** tired of being the bottleneck for data requests\n* **Junior Analysts** who want to focus on insights, not queries\n\n# Setup Takes 60 Seconds\n\n1. Connect your data source — pick from 10+ connections or upload a CSV\n2. Ask your first question\n3. Start making better decisions\n\n# 🐪 How We Got Here\n\n![uploaded image](/media/?type=post&id=76776&key=user_uploads/1925221/b319f130-c38f-4080-8e5c-8edf8d77e91d)\n\nWe've been shipping products together for three years. We're not data analysts, and that was the problem.\n\nOur organized data was right there, but we couldn't get to it without SQL expertise or wrestling with clunky BI tools that never quite answered our actual questions. So we built the tool we needed.\n\nOur insight was simple: stop writing SQL queries by hand. Let AI do what it's good at. Let humans ask natural questions and get answers they can use right away.\n\n## Try camelAI Today\n\nOur free tier gives you 10 messages per week: \n\nQuestions? We read every email: [illiana@camelai.com](mailto:illiana@camelai.com)\n\nLooking for: Teams tired of SQL bottlenecks who want to transform how they use data.", "url": "https://www.ycombinator.com/launches/JyK-camelai-the-first-deep-research-agent-for-your-structured-data", "votes": 92, "created_at": "2025-04-21T20:16:07.000Z" } ] }, { "id": 29687, "name": "MinusX", "slug": "minusx", "former_names": [ "minusone.ai", "minusx.ai" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/92dbd9d186e22d922d985755f90407e21859378a.png", "website": "https://minusx.ai", "all_locations": "San Francisco, CA, USA", "long_description": "MinusX is a state-of-the-art data agent that can build the best dashboards for your data, and notify you when something's up. You can interrogate all your data on our open source BI platform via Slack or MCP. Connect your data, and put agents to work.", "one_liner": "Open source agentic BI for founders", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1722024736, "tags": [ "Machine Learning", "Analytics", "Data Science", "AI", "AI Assistant" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "B2B", "Analytics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/minusx", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/minusx.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/minusx-ai", "x_url": "https://twitter.com/minusxai", "fb_url": null, "cb_url": null, "github_url": "https://github.com/minusxai", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/92dbd9d186e22d922d985755f90407e21859378a.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Gustaf Alstromer", "url": "https://www.ycombinator.com/people/gustaf-alstromer" }, "founders": [ { "user_id": 164724, "full_name": "Vivek Aithal", "title": "Founder/CEO", "founder_bio": "Co-founder & CEO of MinusX. Spent the last 3 years as a research engineer building the world's best open-source autonomous driving agent at comma.ai. Currently building a data science agent that can sit in your browser and use all your data tools. UC Berkeley and IIT Kharagpur grad. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/vivek-aithal-575b207b/", "x_url": "https://twitter.com/nuwandavek", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/430c252ee108b6b83096cba330f4b1b46f7c26ab.jpg" }, { "user_id": 1798297, "full_name": "Sreejith Puthanpurayil", "title": "Founder", "founder_bio": "Co-Founder & CTO of MinusX. Previous stints include Ads Delivery & Ranking at Meta, Ride-hailing backend & infra at Gojek, & full stack at Elanic, a social c2c marketplace (acquired by Share Chat)", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/ppsreejith", "x_url": "https://twitter.com/ppsreejith_", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/51ad324025788a0b7a4961ab7b419a0b20b734ff.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 82787, "title": "MinusX: AI Data Scientist for Jupyter and Metabase", "tagline": "An AI data scientist that is a scientist, not yet-another-new-analytics-platform.", "body": "# **TL;DR**\n\nMinusX is a Chrome Extension that adds a side chat to Jupyter and Metabase. Given an instruction, our agent operates the apps— via clicking and typing— to analyze data and answer queries. We strongly believe that you already have all the tools you need; you just need someone like MinusX to use them! Checkout [**minusx.ai**](http://minusx.ai) for more info.\n\n\n\n# **Asks**\n\n1. Install our [**Chrome extension**](https://minusx.ai/chrome-extension).\n2. Take MinusX for a spin in our [**playground**](https://minusx.ai/playground)!\n3. We’re working on supporting more tools. Want us to hurry up, or don't see your favorite tool in our list? Here’s a [**google form**](https://minusx.ai/tool-request) you can fill out so that we can notify you when we support your tool!\n\n# **Features**\n\n### 1\\. Generate Hypotheses and Explore data\n\n![uploaded image](/media/?type=post&id=82787&key=user_uploads/164724/53f4faaf-4dae-4226-9037-4142ffea5462)\n\n### 2\\. Interop with MinusX to modify existing Jupyter notebooks or Metabase Questions\n\n![uploaded image](/media/?type=post&id=82787&key=user_uploads/164724/259d0be2-0f20-4440-90af-84cae7297264)\n\n### 3\\. Select a region and ask questions, or ask for modifications\n\n![uploaded image](/media/?type=post&id=82787&key=user_uploads/164724/40ed2aeb-29c3-42c8-9e9b-3b1d96b866ae)\n\n# **Pain**\n\n* Lack of data analyst/data scientist bandwidth is a certified pain.\n* If you’re a programmer, you just want answers. If you’re a product manager, you just want answers. If you’re an analyst/scientist, you want 10 clones of yourself.\n* Any new fancy “talk-to-data” platform is a whole thing. You have to migrate your data, and you have to convince your whole team to move— just to start using it.\n* Working in ChatGPT / Claude requires constant copy-pasting. Also, you want to inter-operate with AI, make corrections when it messes up, and guide it rather than just admonish it in chat.\n* More importantly, they’re still just chat! No AI system today can really use analytics software - click and type - to get you that data you needed 5 minutes ago.\n\n# **Our Approach**\n\n> ### **_An AI Data Scientist is a Scientist, not yet-another-new-analytics-platform_**\n\n* Advanced agents should just work with tools you already use and get out of the way.\n* MinusX integrates seamlessly into workflows. You can invoke it only when you need it to do something.\n* Whether you’re a data analyst, programmer, or product manager, you can use MinusX to speed up your workflows instantly.\n* We believe the path to advanced agents runs through specialized, useful intermediaries.\n\n# **Team**\n\n![uploaded image](/media/?type=post&id=82787&key=user_uploads/164724/8f305720-54ba-4af7-9303-8125b9f02f2a)\n\nWe love to build stuff. We met about a decade ago in the drowsy hinterlands of IIT Kharagpur and have been building things together at work, on side projects, and at hackathons ever since. ​​[**Vivek**](https://x.com/nuwandavek) was most recently a Research Engineer working on self-driving cars at [**comma.ai**](http://comma.ai/), [**Sreejith**](https://x.com/ppsreejith_) was a Senior Engineer in the Meta shops ads ranking team optimizing Facebook Shops Ads delivery & core infrastructure, and [**Arpit**](https://x.com/arpit_tarang) was building a warehouse robot fleet as a Product Engineer at Udaan. We have extensive experience in machine learning, data infrastructure, and systems engineering needed to build the best, most delightful class of Data Science agents you'll ever use.\n\n# **Ask(ing again!)**\n\n1. Install our [**Chrome extension**](https://minusx.ai/chrome-extension).\n2. Take MinusX for a spin in our [**playground**](https://minusx.ai/playground)!\n3. We’re working on supporting more tools. Want us to hurry up, or don't see your favorite tool in our list? Here’s a [**google form**](https://minusx.ai/tool-request) you can fill out so we can notify you when we support your tool!\n\nIf you have any questions or comments, you can join our [**discord**](https://minusx.ai/discord) or ping me anytime at [**vivek@minusx.ai**](mailto:vivek@minusx.ai). Hope you enjoy using MinusX as much as we enjoy building it!\n\n### ❤️\n\n![uploaded image](/media/?type=post&id=82787&key=user_uploads/164724/a35b579f-ea8a-4bf4-a0d8-ad65bd607b47)\n\n", "url": "https://www.ycombinator.com/launches/LXH-minusx-ai-data-scientist-for-jupyter-and-metabase", "votes": 57, "created_at": "2024-08-06T20:14:50.518Z" } ] }, { "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": [ "LegalTech", "Data Science", "Data Engineering", "AI", "Conversational AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "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": null, "url": "https://www.ycombinator.com/companies/overstand-labs", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/overstand-labs.json", "year_founded": 2024, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/overstand-labs/", "x_url": "https://x.com/OverstandLabs", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/061e173be11210d3cca9f1b51ba89c7c5255750b.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Tyler Bosmeny", "url": "https://www.ycombinator.com/people/tyler-bosmeny" }, "founders": [ { "user_id": 1993194, "full_name": "Mihir Patil", "title": "Founder/CTO", "founder_bio": "Co-founder of Overstand Labs. California Native. Ex-Palantir. Faculty @ NYU. Go Bears!", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/mihirnpatil/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f426ba6fe9ee49a3ffe6f50a7fa7bdaf607d2a5e.jpg" }, { "user_id": 282405, "full_name": "Derrick Cheng", "title": "Founder", "founder_bio": "Co-Founder of Overstand Labs | Ex-Meta | AI @ Berkeley", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/chengderrick", "x_url": "http://twitter.com/dowithderrick", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/eb972f35799a490a0e323593b2ea731f4a7db12c.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 98764, "title": "Overstand: A personal data team for Execs", "tagline": "Business leaders have ideas all the time. Overstand lets them validate and act upon them in just a few minutes.", "body": "**TL;DR**: [Overstand](https://overstandlabs.com/) is a personal data lab for Execs. We allow business leaders validate their intuitions against their company’s data — with their just their voice, you can go from a raw idea to an evidence-backed answer. They can even see a reproducible step-by-step process and underlying data behind it — all in a few in minutes. Have a look at our [launch video](https://www.youtube.com/watch?v=KrOwutgKsEA).\\\n\\\nAfter working with a bunch of larger companies, we learned something important: some of the most valuable questions are not the ones people plan dashboards for. They're the spontaneous ones, the realizations that you have mid-conversation... the \"wait a minute…\" moments.\n\nHere’s an example that many of us have encountered at some point: let's say you're talking to a customer, and they say \"_you know we've really struggled to figure out how to solve X at our company. Is that something you can help us with?_\" They might explain why X is hard, and you'd go back and forth a little.\n\nThen you wonder, at some point — is this just them, or have others said the same thing? Has anyone else on your 200-person GTM team heard of _X_ before? The signal is buried across massive email threads, Gong transcripts, Slack threads, and CRM notes — there’s no way to know quickly.\n\nSo this intuition fades. Perhaps you’re able to help that customer in a one-off way, but you don’t see the broader pattern.\n\nWe built Overstand to solve for this exact gap — the crevices where data collection has traditionally failed to help you. The spurious thought that you might’ve had.\n\nYou articulate your intuition in plain language — \"_show me all instances of a customer indicating they're struggling with X._\" Overstand builds an entire data pipeline on top of your company's comms + hard data and surfaces the underlying examples that answer your questions — in just a few minutes. From there you can drill down: ask follow-ups to hone in on specific instances, chart the results over time or pull everything into a single context to discuss what was found. You can even action each result individually — sending contextually-crafted emails to each customer who mentioned _X_.\n\nAll of this, with just your computer or phone (and you can even do it with your voice — we call it _speech-to-data-pipeline_).\n\nMost enterprise tools are built around questions you already know to ask. Overstand is built around the ones you didn't plan for.\n\nIf you're running GTM, CS, or product at a company with real customer volume and this problem sounds familiar — we'd love to talk.\n\n![uploaded image](/media/?type=post&id=98764&key=user_uploads/1993194/7ad71368-31a7-4dca-aa7c-9139d83f452a)\n\n", "url": "https://www.ycombinator.com/launches/Pgy-overstand-a-personal-data-team-for-execs", "votes": 8, "created_at": "2026-03-19T20:31:17.415Z" }, { "id": 87277, "title": "Overstand – Unlock Founder Mode with Real-Time Customer Insights", "tagline": "Know where your company needs you most", "body": "[Overstand](https://www.overstandlabs.com/) is a single platform and API that helps business leaders unlock \"founder mode\" by providing real-time insights from all customer communications—Slack, email, WhatsApp, call recordings, and more.\\\n\\\n**The problem:** As companies grow, it becomes harder for leaders to stay deeply connected to their customers. Critical trends, opportunities, and issues often go unnoticed, leading to slower decision-making, missed opportunities, and unresolved problems. Scaling without visibility into what’s happening at the “edges” of the business—customer interactions—creates blind spots that hinder growth.\n\n![uploaded image](/media/?type=post&id=87277&key=user_uploads/1993194/f829b629-7042-4789-b7ee-6cc44d8ed063)\n\n**How we solve it:** Overstand aggregates customer communications into one unified platform and delivers actionable insights.\n\n* **Know Where You’re Needed Most:** Focus on areas where your involvement can drive the biggest impact.\n* **Find Opportunities Everywhere:** Discover new prospects or expand existing relationships.\n* **Spot Trends Instantly:** Identify issues and opportunities in real time.\n* **Integrate Seamlessly:** Use Overstand’s API to bring insights directly into workflows, dashboards, or other tools.\n\nWith Overstand, business leaders regain clarity, focus, and the ability to scale while staying deeply in tune with their customers. [See a demo of Overstand here.](https://www.youtube.com/watch?v=-8tqKeXW2Cw)\\\n\\\n**Our ask:** If you or someone you know is struggling to maintain visibility into their company's customer interactions and opportunities, we’d love to help. Reach out to [founders@overstandlabs.com](mailto:founders@overstandlabs.com) or visit [overstandlabs.com](http://overstandlabs.com) to learn more or schedule a demo.", "url": "https://www.ycombinator.com/launches/Mhh-overstand-unlock-founder-mode-with-real-time-customer-insights", "votes": 57, "created_at": "2025-01-29T18:28:19.132Z" }, { "id": 83338, "title": "Overstand - The platform for upselling your enterprise accounts", "tagline": "Meet Overstand, the cross-selling engine for enterprise software companies.", "body": "**TLDR**: [Overstand](https://overstandlabs.com/) helps enterprise software teams maximize revenue by reading all customer communication channels (chat, email, call recordings, support tickets) to uncover opportunities for contract expansion.\n\n**The problem:**\n\nBig tech companies know that one of the best ways to increase revenue is to bring more value to existing customers. But customer account management involves not just sales, but also support, customer success, implementation teams, and so on. Customers might voice problems that are not conveyed in a timely manner (or at all!) to those responsible for expanding the account.\n\nEnterprise software companies are leaving a lot of potential revenue on the table— some offer a whole menu of products, with each enterprise customer only taking advantage of one or a few of the offerings.\n\n**The solution:**\n\nOverstand is designed to read all customer communications and flag opportunities for expansion of customer accounts. It identifies hidden expansion opportunities that are buried in customer communications by analyzing every single message and comparing it to product docs and even existing use cases at other enterprise accounts.\n\n![uploaded image](/media/?type=post&id=83338&key=user_uploads/1996894/9b65d2c3-9f8d-48e5-a07a-a6f6b37196f1)\n\n![uploaded image](/media/?type=post&id=83338&key=user_uploads/1996894/1295ceae-f91f-4bcf-9b1f-4cb244c655cf)\n\n**The team:**\n\n![uploaded image](/media/?type=post&id=83338&key=user_uploads/1996894/108201eb-a1e6-43f0-8397-4436134a5589)\n\nWe met at Palantir several years ago and both recognized the importance of empowering customer-facing teams to fully understand and sell highly technical and complex products. [Mihir](https://www.linkedin.com/in/mihirnpatil/) was a PM and engineering lead at Palantir and often felt that many existing customers could have further benefited from using his products. [Senta](https://www.linkedin.com/in/senta/) managed customer accounts valued in the double-digit millions and often observed challenges associated with upselling into existing accounts.\n\n**Asks:**\n\nIf you’re interested in cross-selling and upselling as a strategy for growing your enterprise account revenue, we’d love to chat! Email us at [founders@overstandlabs.com](mailto:founders@overstandlabs.com).\n\nFollow us [on LinkedIn](https://www.linkedin.com/company/overstand-labs/)!", "url": "https://www.ycombinator.com/launches/LgA-overstand-the-platform-for-upselling-your-enterprise-accounts", "votes": 52, "created_at": "2024-08-23T01:13:45.957Z" } ] }, { "id": 29731, "name": "Zoa Research", "slug": "zoa-research", "former_names": [ "Pastel Health", "Olive Legal", "Paradome" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0a603d093e3e3a39d0f3743b7f24486743b3bd06.png", "website": "https://zoaresearch.com", "all_locations": "New York City, NY, USA", "long_description": "Historically, quantitative models are domain specific. Brilliant people spend their best years testing features, tuning hyperparameters, and iterating architectures within a narrow domain. But scale is the panacea: large models will find patterns people, and specialized models, could not. \r\n\r\nForecasting generalizes. Zoa trains cross-domain event forecasting engines. \r\n\r\n*Automating Iteration*\r\n\r\nLLMs—embedded in multi-agent optimization loops and evaluated against fixed policies—can automate the build-test-improve modeling cycle. Think AlphaEvolve for forecasting problems.\r\n\r\n*Sample-Efficient General Models*\r\n\r\nToday’s forecasting models are narrowly crafted with deep human priors. But larger models will outperform state-of-the-art specialized models.\r\n\r\nUnlike existing event models, our models leverage data from across contexts and rely less on human intuition. And compared to LLMs, our models are built with more inductive priors and rely more heavily on inference-time compute—improving sample efficiency.\r\n\r\n*Why It Matters*\r\n\r\nIn the real economy, our models could be useful for forecasting supply chain volatility, energy supply and demand, even earthquake risk.\r\n\r\nScience is, Ian Hacking writes, the taming of chance. It is the process of iteratively updating priors (something like: identify uncertainty, conceive experiment to reduce uncertainty, execute, update). If science is uncertainty-reduction, forecasting is a critical measure of progress. \r\n\r\nBetter forecasting improves our ability to select interesting experiments (roughly those with greatest expected uncertainty reduction) and update priors. Our models will be used by labs and academics in data-heavy domains. \r\n\r\nSam's ex-girlfriend introduced him to Greg back at Carnegie Mellon in 2017, and while that relationship didn't last, their friendship has. After college, Greg went to Harvard Law School, while Sam worked for three years at Jane Street on their Options desk, building & leading a satellite dev team.", "one_liner": "Powerful quantitative forecasting models", "team_size": 5, "industry": "B2B", "subindustry": "B2B", "launched_at": 1724859181, "tags": [ "Data Science", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/zoa-research", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/zoa-research.json", "year_founded": 2024, "city": "New York City", "country": "US", "linkedin_url": "", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/0a603d093e3e3a39d0f3743b7f24486743b3bd06.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Harj Taggar", "url": "https://www.ycombinator.com/people/harj-taggar" }, "founders": [ { "user_id": 1969072, "full_name": "Greg Volynsky", "title": "Founder/CEO", "founder_bio": "Co-founder and CEO of Zoa\n\ninterested in 20th century political history, neural / artificial intelligence, Soviet bard music & climbing", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/greg-volynsky-3b863177/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e6f5299121363cbd031545fda460653af8f78526.jpg" }, { "user_id": 1969077, "full_name": "Sam Damashek", "title": "Founder/CTO", "founder_bio": "Sam is the co-founder and CTO of Paradome.\n\nHe worked for three years at Jane Street on the options trading desk writing algorithmic strategies using applied ML, for two years in NYC and then one year in Hong Kong, where he built out a satellite dev team for the Asia options markets.\n\nHe graduated with a BS in Computer Science from CMU, where for some reason he led a fledging constitutional law debate team, never to victory though frequently to Ohio.\n", "is_active": true, "linkedin_url": "https://linkedin.com/in/sdamashek", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/91779aa03f9275534277ca4d79aa92d2f6f8fc0f.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 29767, "name": "Thunder Compute", "slug": "thunder-compute", "former_names": [ "Thunder" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2623539c5a9dddb54681db96f38cf2be0f9428d9.png", "website": "https://www.thundercompute.com", "all_locations": "San Francisco, CA, USA", "long_description": "Thunder Compute is a systems research lab with commercial focus. We productionize GPU virtualization research to provide step-change improvements in utilization to our cloud offering and partner GPU fleets.", "one_liner": "GPUs for Agents", "team_size": 10, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1723245936, "tags": [ "Developer Tools", "Data Science", "Cloud Computing", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": [ { "question": "How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)", "answer": "Carl Peterson and Brian Model met as freshmen at Georgia Tech and became close friends. The idea for Thunder Compute sparked from Brian's experience in his Systems for AI lab, where researchers made GPU reservations weeks in advance via Google Sheets, severely hindering research progress. This inefficiency inspired us to explore ways to improve GPU access." } ], "url": "https://www.ycombinator.com/companies/thunder-compute", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/thunder-compute.json", "year_founded": 2022, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/thundercompute/", "x_url": "https://x.com/ThunderCompute", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/thunder-9b4c", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/2623539c5a9dddb54681db96f38cf2be0f9428d9.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/d3fd827d18b35d35d4f3861cffb2a960801078b5.png" ], "primary_partner": { "name": "Aaron Epstein", "url": "https://www.ycombinator.com/people/aaron-epstein" }, "founders": [ { "user_id": 1276433, "full_name": "Carl Peterson", "title": "Founder/CEO", "founder_bio": "CEO of Thunder Compute, formerly Management Consultant at Bain", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/cpeterson42", "x_url": "https://twitter.com/carl_petey", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/64f0d31897538a58874ce79d46b9d3390a4e51f9.jpg" }, { "user_id": 1989859, "full_name": "Brian Model", "title": "Founder/CTO", "founder_bio": "CTO of Thunder Compute, formerly Quantitative Developer at Citadel Securities", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/brian-model/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c3c91379c7fd849da36c768aedd80a5f6151a624.jpg" } ], "jobs": [ { "id": 79986, "title": "Cloud Infrastructure Engineer", "url": "https://www.ycombinator.com/companies/thunder-compute/jobs/dtlQhtw-cloud-infrastructure-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$1", "equity_range": "", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [ "Go", "Kubernetes", "Python", "Linux" ] }, { "id": 82422, "title": "Systems Software Engineer (C++)", "url": "https://www.ycombinator.com/companies/thunder-compute/jobs/SZq8TQx-systems-software-engineer-c", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Backend", "salary_range": "$1", "equity_range": "", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [ "C++", "TCP/IP", "Linux", "Distributed Systems" ] } ], "news": [ { "title": "Thunder Compute raises $13M to squeeze more work out of idle GPUs - SiliconANGLE", "url": "https://siliconangle.com/2026/08/19/thunder-compute-raises-13m-squeeze-work-idle-gpus/", "date": "Aug 19, 2026" }, { "title": "Thunder Compute Raises $500K to Advance GPU Access for AI Developers | citybiz", "url": "https://www.citybiz.co/article/575672/thunder-compute-raises-500k-to-advance-gpu-access-for-ai-developers/", "date": "Jul 10, 2024" } ], "launches": [ { "id": 82910, "title": "Thunder Compute: Launch GPU instances in one click for 80% less", "tagline": "Self-serve GPUs in VS Code with persistent storage, snapshots, and hot-swappable hardware, for 80% less than AWS", "body": "![uploaded image](/media/?type=post&id=82910&key=user_uploads/1276433/30b5b896-6109-4aa6-8a05-fb9a138f61a8)\n\n### **The backstory**\n\nHi everyone, we’re Carl and Brian, aka the team behind [Thunder Compute.](https://thundercompute.com)\n\n![uploaded image](/media/?type=post&id=82910&key=user_uploads/1276433/07db7c92-f1f2-4356-80f8-9dabf9c2fbcd)\n\nBefore Thunder Compute, [Carl](https://www.linkedin.com/in/cpeterson42) was a Management Consultant at Bain & Company, and [Brian](https://www.linkedin.com/in/brian-model/) was a Quantitative Developer at Citadel Securities. Carl and Brian met at Georgia Tech and have been close friends for over 6 years.\n\n### **Problem**\n\nGPU access sucks. Today’s options are expensive and hard to use. Developers are crowded out of the market by large corporations and can’t get the GPUs they need for reasonable prices. Even if you can afford GPUs, they are scarce and hard to use.\n\n### **Solution**\n\nThunder Compute sells cloud GPUs for the lowest rates on the market and provides a simple interface to access them.\n\nYou can connect in one click through VSCode, without SSH. We have “prototyping” mode, with prices 50% lower than anywhere else, and “production” mode, with higher uptime and multi-GPU nodes.\n\n### **Our offer**\n\nSimple: low-cost, easy GPUs. \\\n\\\nIf you’re looking for a better GPU cloud, join Thunder Compute’s public beta today at [www.thundercompute.com](https://www.thundercompute.com).\\\n\\\nIf you have questions, need technical support, or want to rant about the current state of GPUs, join our discord at [**https://discord.gg/nwuETS9jJK**](https://discord.gg/nwuETS9jJK) or contact us at [**founders@thundercompute.com.**](https://mailto:founders@thundercompute.com/)", "url": "https://www.ycombinator.com/launches/LZG-thunder-compute-launch-gpu-instances-in-one-click-for-80-less", "votes": 50, "created_at": "2024-08-11T14:49:40.486Z" } ] }, { "id": 30400, "name": "Plexe", "slug": "plexe", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4911874a37ff01bfa27bb33e5f83f49e6970068e.png", "website": "https://plexe.ai", "all_locations": "London, England, United Kingdom", "long_description": "Plexe builds predictive ML models from a problem description. It connects to data sources, conducts experiments, evaluates and deploys the models to an API endpoint.", "one_liner": "Open-source agents to build predictive ML models from a prompt", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1745031118, "tags": [ "Machine Learning", "Data Science", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Spring 2025", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United Kingdom", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/plexe", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/plexe.json", "year_founded": 2025, "city": "London", "country": "GB", "linkedin_url": "https://www.linkedin.com/company/plexe-ai/", "x_url": "https://x.com/PlexeAI", "fb_url": null, "cb_url": null, "github_url": "https://github.com/plexe-ai/", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/4911874a37ff01bfa27bb33e5f83f49e6970068e.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Nicolas Dessaigne", "url": "https://www.ycombinator.com/people/nicolas-dessaigne" }, "founders": [ { "user_id": 2260416, "full_name": "Vaibhav Dubey", "title": "Founder/CEO", "founder_bio": "I make AI create AI.", "is_active": true, "linkedin_url": null, "x_url": "https://x.com/VaibhavMDubey", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3ef2a9cbf97215a02c0cd71bfe9793e95f7182c3.jpg" } ], "jobs": [ { "id": 78821, "title": "Forward Deployed Engineer", "url": "https://www.ycombinator.com/companies/plexe/jobs/eocGfXv-forward-deployed-engineer", "location": "IN / Remote (IN)", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "₹1.5M - ₹3M INR", "equity_range": "0.01% - 0.03%", "experience": "3+ years", "visa": "US citizenship/visa not required", "skills": [] } ], "news": [ { "title": "10 Most Exciting AI Agent Startups at YC Demo Day Spring Cohort 2025 - Business Insider", "url": "https://www.businessinsider.com/y-combinator-yc-demo-day-spring-ai-agent-startups-2025-6", "date": "Jun 11, 2025" } ], "launches": [ { "id": 90589, "title": "Plexe - Build ML models from a prompt", "tagline": "Plexe is an open-source agent that turns natural language task descriptions into trained machine learning models.", "body": "We’re Vaibhav and Marcello. We’re building Plexe, an open-source agent that turns natural language task descriptions into trained ML models.\n\nhttps://youtu.be/CwNX0aU9MsE\n\n## **🤔 1. Problem**\n\nLots of great use cases for ML models in businesses never materialize because ML projects are messy and convoluted. You spend months finding the data, cleaning it, experimenting with models and deploying them to production, only to find out that the project has been binned due to taking so long. At a previous employer, we witnessed a team of 10 ML engineers spend 2 years and $3M building models for a project that never saw the light of day. \n\nThere are several tools for “automating” ML, but it still takes teams of ML experts to actually productionize something of value. And we can’t keep throwing LLMs at every ML problem. Why use a generic 10B parameter language model, if a logistic regression trained on your data could do the job better?\n\n## **✅ 2. Solution**\n\nStep 1: Connect your data sources\\\nStep 2: Describe your problem statement\\\nStep 3: Use the deployed model via API\n\nhttps://youtu.be/zByvH0wTSuE\n\n## **🚀 3. How does it work?**\n\nPlexe uses a self-correcting team of ML engineering agents to research, experiment, evaluate, refine, and deploy the best performing model over an API endpoint. It connects to data sources, discovering relevant fields, and autonomously building the model. Think of it like your own ML helper helping you go from idea to deployed models 10x faster.\n\nhttps://youtu.be/bUwCSglhcXY\n\n## **👋 4. Team**\n\n[Vaibhav Dubey](https://bookface.ycombinator.com/user/2260416) (ex-Proofpoint, Expedia, Imperial College London) and [Marcello De Bernardi](https://bookface.ycombinator.com/user/2337737) (ex-AWS, Expedia, Oxford) met 6 years ago while building a chatbot that served 9+ million customers of a large bank. Since then, they’ve built enterprise-scale ML solutions that serve billions of predictions per day for millions of users worldwide.\n\n![uploaded image](/media/?type=post&id=90589&key=user_uploads/2260416/4e5a0513-e013-4adc-9520-ebde07c44981)\n\n## **🙏 5. Our ask**\n\n* We’d love to get in touch with any companies that have a lot of data but have not been able to build ML features on top of them!\n* If you’re an individual who believes that the future of ML development is autonomous and open source, check out our agent: https://github.com/plexe-ai/plexe\n\nGet in touch with us: [founders@plexe.ai](mailto:founders@plexe.ai) ", "url": "https://www.ycombinator.com/launches/NZ7-plexe-build-ml-models-from-a-prompt", "votes": 67, "created_at": "2025-05-21T01:44:48.117Z" } ] }, { "id": 30444, "name": "Percival", "slug": "percival", "former_names": [ "Percival Technologies" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cdf1ebc7dc7ea895611a77f39a7009d41c1f8342.png", "website": "https://percy.tech", "all_locations": "San Francisco, CA, USA; Remote", "long_description": "Building an AI copilot for researchers to analyze and transform real-world data.", "one_liner": "Accelerating data analysis for research", "team_size": 3, "industry": "B2B", "subindustry": "B2B", "launched_at": 1745969288, "tags": [ "Developer Tools", "Data Science", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2025", "status": "Inactive", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/percival", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/percival.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/percivaltech", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/cdf1ebc7dc7ea895611a77f39a7009d41c1f8342.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "David Lieb", "url": "https://www.ycombinator.com/people/david-lieb" }, "founders": [ { "user_id": 2463323, "full_name": "Kevin Bi", "title": "Founder", "founder_bio": "Building Tinker at Thinking Machines Lab. Please reach out if you're interested in fine tuning LLMs!\n\nFormerly founder of Percival (P25).", "is_active": false, "linkedin_url": "https://www.linkedin.com/in/kevin-bi-006426148/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/865c4f69e3d0c731c263487b2fa6380e9b8f3445.jpg" }, { "user_id": 2432982, "full_name": "David Zhu", "title": "Founder", "founder_bio": "Building Percival: AI-powered data entry for wholesalers and distributors", "is_active": false, "linkedin_url": "https://www.linkedin.com/in/davidzhu10/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/287bea5a97329e4f992a54f5b6a5d5c8a4b46c7e.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 30638, "name": "Lotas", "slug": "lotas", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b64e79cf442071bbe251c8f19acacccc3dbf1fea.png", "website": "https://www.lotas.ai", "all_locations": "San Francisco, CA, USA", "long_description": "Quantitative trading", "one_liner": "AI for quantitative trading", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1754374450, "tags": [ "Developer Tools", "Data Science", "Data Visualization", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 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": null, "url": "https://www.ycombinator.com/companies/lotas", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/lotas.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/lotas/", "x_url": "https://x.com/lotas_ai", "fb_url": null, "cb_url": null, "github_url": "https://github.com/lotas-ai", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/b64e79cf442071bbe251c8f19acacccc3dbf1fea.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/674a3c65b711a03e0a53e55c2f405314328629c9.png" ], "primary_partner": { "name": "Ankit Gupta", "url": "https://www.ycombinator.com/people/ankit-gupta" }, "founders": [ { "user_id": 1845082, "full_name": "Jorge Guerra", "title": "Founder/CEO", "founder_bio": "Founder/CEO Lotas — quantitative trading with AI\nHarvard '24", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jorge-o-guerra", "x_url": "https://x.com/jorgeguerrajr", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c9188857caef45433587c3241d504b930d7b6921.jpg" }, { "user_id": 1846075, "full_name": "William Nickols", "title": "Founder/CTO", "founder_bio": "Founder/CTO Lotas — quantitative trading with AI\nHarvard '24", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/willnickols/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4224a64ec156b9f0c6f404911435d3f531a7524c.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 92746, "title": "Lotas — Cursor for Data Science", "tagline": "Building a secure, AI-native IDE for data scientists", "body": "Hey everyone! We’re Jorge and Will from Lotas. We’re building a secure, AI-native IDE for data science—and as a first step, we’ve built an AI coding assistant into RStudio (think Cursor for RStudio). We’re looking for RStudio users, data scientists, and students who want to code way faster and are excited to see AI integrated into data science workflows.\n\nhttps://www.youtube.com/watch?v=c47Ch1kB0eU\n\n❌ Problem\n\nRStudio is used by about 5 million data scientists and academics, but they currently lack a coding assistant within their IDE. Developers in other environments benefit from tools like Cursor and Windsurf, but R users don’t have an equivalent tool that’s truly integrated into their day-to-day workflow. And more broadly, data science teams need an AI-native environment that understands notebooks, dataframes, plots, and multi-language workflows—without forcing work into the cloud or tools they don’t use.\n\n✅ Solution\n\nWe’re building a secure, AI-native IDE for data science that is context-aware (files, variables, terminals), can read and write code, run analyses, and interpret textual or visual output across R and Python to start. While we build this IDE, we’ve shipped Rao: a fork of RStudio with an embedded AI assistant that is aware of the user’s local context (both files and variable environment), can read and write files, can run code or commands, and can interpret textual or visual output. It works with the file formats RStudio users already rely on (R, notebooks including RMDs and QMDs, Python, Stan, etc.), so you can iteratively perform entire data analyses inside your preferred IDE today—and help us design the next one.\n\n👨‍🎓 Who we are\n\nBoth of us were PhD students at Harvard. Jorge was in the biophysics program and Will was in the biostatistics program where most people used RStudio every day. We saw how integrated coding assistants were taking off in other IDEs, but RStudio integrations lagged behind. Many R users were copying and pasting code from ChatGPT to build their workflows, which was slow and fragile. Other AI data science tools are either (1) built on the web or in environments people don’t already use, (2) completely focused on Python notebooks, or (3) weak package-based assistants with limited functionality. We’re closing these gaps—first with Rao, and next with a purpose-built IDE for data science.\n\n🚀 Try Rao & get early access\n\nYou can download Rao, watch our demo, and work through example use cases. If you’re interested in a secure, AI-native IDE for data science, contact us for an early preview!\\\n\\\n✉️ **Contact**\\\nYou can reach us at [founders@lotas.ai](mailto:founders@lotas.ai) and follow us on [LinkedIn](https://www.linkedin.com/company/lotas/) and [X](https://x.com/lotas_ai).\n\n![uploaded image](/media/?type=post&id=92746&key=user_uploads/1845082/a6d066f2-358c-46b1-959e-6e2618b44df4)\n\n", "url": "https://www.ycombinator.com/launches/O7u-lotas-cursor-for-data-science", "votes": 14, "created_at": "2025-08-05T16:49:32.810Z" } ] }, { "id": 30775, "name": "Fleetline", "slug": "fleetline", "former_names": [ "Axel AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/8008d7d50f1ead47eae177bcede0c9d614312ad4.png", "website": "https://fleetline.ai", "all_locations": "New York City, NY, USA", "long_description": "Fleetline is building the first complete-context algorithmic load planner for mid to large-sized trucking fleets. Today’s dispatchers face an overwhelming task: balancing regulations, customer demands, live fleet data, and individual driver needs, all while coordinating across siloed tools and teams. Mistakes run rampant, and each mistake is thousands of dollars. Even the select fleets using algorithms that have fleet-wide context struggle: the outputs are rigid, hard to interpret, and are blind to real-world nuances like driver preferences and schedule exceptions. Fleetline solves this by combining advanced optimization with LLMs that can easily adapt algorithms to each fleet’s needs and capture driver-specific information. The result is smarter planning truly optimized for every fleet and its drivers.", "one_liner": "Optimizing fleet planning with data driven algorithms", "team_size": 11, "industry": "B2B", "subindustry": "B2B -> Supply Chain and Logistics", "launched_at": 1754335865, "tags": [ "Logistics", "Supply Chain", "Data Science", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2025", "status": "Active", "industries": [ "B2B", "Supply Chain and Logistics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/fleetline", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/fleetline.json", "year_founded": 2025, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/fleetlineai", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/8008d7d50f1ead47eae177bcede0c9d614312ad4.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Jared Friedman", "url": "https://www.ycombinator.com/people/jared-friedman" }, "founders": [ { "user_id": 757578, "full_name": "Saurav Kumar", "title": "Founder/CEO", "founder_bio": "Optimizing and automating dispatch ops @ Fleetline", "is_active": true, "linkedin_url": "https://linkedin.com/in/sauravml", "x_url": "https://twitter.com/sauravml", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/39edd7839bf52e30dab32c05a547013c48aff70d.jpg" }, { "user_id": 2828390, "full_name": "Veer Juneja", "title": "Founder/COO", "founder_bio": "Combining LLMs with traditional advanced optimization techniques to automate trucking dispatch operations. I studied philosophy @ USC. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/veer-juneja-67255417a/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/fdc7a7c95b217654e469b590c4c9bbc9f06ba6a4.jpg" } ], "jobs": [ { "id": 85256, "title": "Founding Engineer", "url": "https://www.ycombinator.com/companies/fleetline/jobs/dVipAK8-founding-engineer", "location": "New York, NY, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$140K - $190K", "equity_range": "0.50% - 1.00%", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [] }, { "id": 91065, "title": "Founding Algorithm Developer", "url": "https://www.ycombinator.com/companies/fleetline/jobs/az5DIjt-founding-algorithm-developer", "location": "New York, NY, US", "type": "Full-time", "role": "Engineering", "role_type": "Data science", "salary_range": "$130 - $180", "equity_range": "0.40% - 1.00%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] } ], "news": [], "launches": [ { "id": 92822, "title": "Fleetline 🚛 Optimizing Fleet Planning with Data Driven Algorithms", "tagline": "Combining LLMs with advanced optimization to unlock algorithmic load planning for all fleets, in all situations ", "body": "# TLDR:\n\nToday’s fleets are **stuck between two failing approaches to load planning**: human dispatchers drowning in complexity (driver preferences, regulatory constraints, shifting schedules, and more) or inflexible algorithms blind to tribal knowledge and driver nuance. We solve this by combining advanced optimization with LLMs that can adapt algorithms to deliver intelligent planning for real-world operations. \\\nhttps://youtu.be/9LHYILVw6ks\n\n# **💥 The problem:**\n\nPlanning just one week of routes for a 50-truck fleet involves **more possible combinations than there are grains of sand on Earth**. For humans, consistently piecing together reasonable combinations is difficult. Making optimal ones is impossible. Dispatchers juggle:\n\n* Regulatory constraints, like drivers’ hours of service\n* Complex forecasts, like considering the likelihood of receiving a load from a flaky customer\n* And human preferences, like a driver’s disdain for a specific commodity\n\nThis complexity forces fleets to effectively **silo their operations**—assigning each dispatcher a subset of trucks to manage. **Instead of coordinating as a cohesive operation, fleets become mini-operations, resulting in load mismatches and under-utilized capacity.** For a low-margin industry like trucking, those inefficiencies are the difference between making or missing payroll. \n\nIn response, some fleets have adopted expensive load planning algorithms. While these traditional solutions are a marginal improvement over manual work, they fail to meaningfully solve the problem. \n\nRigid algorithms operate like complete black boxes, often leaving dispatchers with a lack of confidence in their decisions. Deterministic algorithms cannot be responsive to the soft preferences of either the fleet or the driver. For example, dispatchers may have to reshuffle their planning board because an algorithm cannot optimize for a driver needing to be home early one day for his daughter’s recital. \n\nThat means the algorithm's recommendations are largely not followed or, if they are, drivers are left unhappy. With an active driver shortage, fleets can’t tolerate the latter. \n\nTrucking is a trillion-dollar industry, yet its biggest players have no good option for load planning. \n\n# **✅ The solution:**\n\n**Fleets no longer have to choose between two existentially threatening options with Fleetline.** By combining traditional advanced optimizations with LLMs, we created a solution that allows fleets to optimize their schedules while being adaptive to soft preferences and surprises. All users need to do is prompt our AI agent with any changes / added constraints to include in the optimization algorithm, and the load planning is re-done. \n\nFor example, if a driver at a fleet needs to make it back home by 2 PM on a given Tuesday to see his daughter’s recital, instead of manually scrambling the planning board, our AI agent can re-optimize around the new constraint. \n\nWe’re already working with large fleets in California and talking to others across the country.\n\n# **🏋️‍♂️ The team:**\n\nSaurav and Veer are lifelong friends who have been working on projects together since they were 14. Saurav graduated from UIUC and has worked at Icon, Meta, and Nvidia, and is a previous founder (Blast AI). Veer was pursuing his master’s at USC, was a nationally ranked high school and college debater, and is an exited founder. \n\nWe’re excited about building revolutionary tech for a trillion-dollar industry that is functionally the backbone of the country. \n\n# **📈 Vision:**\n\nA dynamic algorithm unlocked by LLMs will allow fleets of any size to find value in our optimization software. \n\n### **Our ask:**\n\nPlease let us know if you have any connections at all in the trucking or logistics space 🙂\\\nWould also love to talk to anyone who has built RL environments or dynamic programming algorithms at scale!\n\n\\\nContact us at [founders@fleetline.ai](mailto:founder@fleetline.ai) ", "url": "https://www.ycombinator.com/launches/O98-fleetline-optimizing-fleet-planning-with-data-driven-algorithms", "votes": 30, "created_at": "2025-08-07T21:08:34.390Z" } ] }, { "id": 32191, "name": "Lyon", "slug": "lyon", "former_names": [ "Lyon (Branding TBD)" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/27ce3fff3af03da64bc8cfefeb3efef7b6d080b7.png", "website": "https://lyon.so", "all_locations": "San Francisco, CA, USA", "long_description": "Lyon builds private foundation models for banks, insurance companies, and fintechs. Each model learns from the company’s proprietary transactions, payments, clicks, and customer interactions to predict credit, fraud, collections, income, churn, and lifetime value; and runs inside the company’s cloud, so its data and intelligence remain under its control. Lyon is already working with a major insurer and trained a model on 28B transactions for a fintech serving tens of millions of active users, identifying premium-card converters 4x more precisely than its existing rules; the model is now being deployed for credit.", "one_liner": "Foundation models on enterprise transaction data.", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1786694987, "tags": [ "Machine Learning", "Finance", "Data Science", "Big Data" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2026", "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": null, "url": "https://www.ycombinator.com/companies/lyon", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/lyon.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/lyon-ai/", "x_url": "https://x.com/gabrielnoya7", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/27ce3fff3af03da64bc8cfefeb3efef7b6d080b7.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Gustaf Alstromer", "url": "https://www.ycombinator.com/people/gustaf-alstromer" }, "founders": [ { "user_id": 1690305, "full_name": "Gabriel Noya", "title": "Founder/CEO", "founder_bio": "Stanford EE and CS 26'", "is_active": true, "linkedin_url": "https://linkedin.com/in/gabriel-noya", "x_url": "https://x.com/gabrielnoya7", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4af339e08470b73536f535219d74828f249a98b7.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 32262, "name": "Alkera AI", "slug": "alkera-ai", "former_names": [ "Alkera AI, Inc.", "Alkera AI", "Alkera AI, Inc." ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/eecc1a49c35b3a26973c35ce53d1c3f862a058cb.png", "website": "https://alkera.ai", "all_locations": "San Francisco, CA, USA", "long_description": "Alkera is a data engineering/analysis/science agent that works in your IDE or CLI. If you’re tired of agents that produce false, or even dangerous, reports about your data, then Alkera is for you. Our agent is equipped with your data’s history and lineage, your team’s knowledge, and tailored plugins for data apps such as Snowflake and dbt. Simply install and connect your services to begin doing trusted agentic data work. We also offer VPC & on-prem deployment options for when data can't leave your boundary.", "one_liner": "Reliable and safe data engineering and data science agents", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1783697969, "tags": [ "Developer Tools", "Data Science", "Data Engineering", "Enterprise Software", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/alkera-ai", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/alkera-ai.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/alkera-ai", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/eecc1a49c35b3a26973c35ce53d1c3f862a058cb.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Ankit Gupta", "url": "https://www.ycombinator.com/people/ankit-gupta" }, "founders": [ { "user_id": 3652826, "full_name": "Rick Gao", "title": "Founder/CEO", "founder_bio": "Founder at Alkera AI, Inc. Previously at Verition Fund Management where he built financial models and optimizations for treasury financing. Previous computational biology research at Yale's Gerstein Laboratory. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/rgao09", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/515662055ce684fc796921959375d09b477afbfa.jpg" }, { "user_id": 3406186, "full_name": "Tony Li", "title": "Founder/COO", "founder_bio": "Founder at Alkera AI, Inc. Previously Agentic Software Engineer at ByteDance, where he built a Python framework for multi-agent AI workflows and deployed production bots used across company teams. Former Quantitative Developer at Carthage Capital. BS in Computer Science and Mathematics from Yale.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/tonyli4722", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9e00bcde4966ff8eb6ea44e6847dce0d34f0c0b5.jpg" }, { "user_id": 3673412, "full_name": "Andrew Tran", "title": "Founder/CTO", "founder_bio": "Cofounder at Alkera AI. Prev SWE intern at Ramp and HRT, working closely with data teams. CS B.S/M.S from Yale. Prev ML research at Yale's Gerstein Lab developing biology reasoning models.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/andrewtran-cs/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/fbb518656ab4ebfa5220bc5c8406b2716cf75c60.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 106204, "title": "Alkera - The data agent that you can trust", "tagline": "Alkera is an agent that replaces your coding agent to reliably and safely perform real data engineering/analysis/science work.", "body": "**TL;DR:** Data teams adopting AI agents want speed, but one wrong step can quietly ripple through your dbt models, dashboards, and business decisions before anyone notices. [Alkera](https://alkera.ai) **is an AI data agent for data engineers/analysts/scientists or anyone who wants to gather data insights that actually understands your data stack** (column-level lineage, graph-based planning, and a living knowledge base), so it ships data work you can trust. It's **#1 on UC Berkeley's [DataAgentBench](https://ucbepic.github.io/DataAgentBench/),** which tests complex, data-oriented tasks.\n\n\n\nCoding agents can write data code that runs. **For data engineering, knowing it's correct is the hard part.** This is knowing that a transformation didn't quietly redefine a column three models downstream and corrupt the revenue dashboard that the exec team checks every Monday. **For data analysis and data science, beyond data access and lineage problems, coding agents struggle with highly parallel work spread across multiple machines.** When interacting with remote computing nodes, they do so only via fragile chains of SSH commands. Long processing and training runs have you more as a babysitter than a scientist.\n\n**Alkera is a data agent that works natively across your entire data stack, with the context and guardrails coding agents lack.** Every change it makes to a query, transformation, model, or notebook is backed by a real understanding of your pipeline.\n\nIt's **#1 on UC Berkeley's DataAgentBench,** which tests complex, data-oriented tasks. You reach it through an IDE extension (VSCode, Cursor), a CLI, or the browser — wherever you already work.\n\nWhat makes it different:\n\n* **Column-level lineage across your data stack.** Trace a single row from Snowflake, through your dbt models, to your Hex dashboard. Before the agent changes anything, it maps the _blast radius_ — every downstream table and dashboard the change would touch.\n* **Graph-based planning with flexible computation.** Plan complex data tasks with parallel agents from a quick analysis to days-long modeling experiments to run across your machine and remote CPU/GPU nodes.\n* **A living knowledge base.** Alkera learns your schema docs, trusted queries, and the tribal conventions that never make it into documentation — written by both agents and humans, with humans verifying what the agent adds.\n* **Production protection.** Fine-grained permissions over every tool, including bash and SQL. Block a seemingly innocent SQL query with a dangerous UPDATE hidden away in a subexpression. Enforce OAuth to connect your warehouses to maintain existing data permissions.\n\n# **Try it**\n\nDownload Alkera at or read the docs at . For data engineering, point it at your stack and **watch it trace a change through your pipeline**, lighting up everything downstream. For data analysis and data science, have it **spin up parallel research agents** to explore your data. Reach out to [contact@alkera.ai](mailto:contact@alkera.ai) to see how we can tailor Alkera to your specific data apps/tools and computing environment.\n\n# **Our team**\n\n* Andrew Tran studied CS at Yale. At Yale, he trained LLMs to reason over multi-modal biological data. At Ramp and Hudson River Trading, he worked closely with data teams to build out ergonomic tooling for data engineers and researchers.\n* Rick Gao studied CS at Yale. He was previously at Verition Fund Management, where he worked with internal data teams and counterparties to develop ingestion pipelines and internal financial models.\n* Tony Li studied CS and Math at Yale. During his time at Carthage Capital and ByteDance, he worked with data engineering teams to build data pipelines, data analysis, and agentic tooling.\n\n# **Our ask**\n\nIf you:\n\n* perform data engineering work on production pipelines with tools like dbt and Apache Airflow\n* perform data analysis/data science work in Python/R and with tools like Jupyter notebooks\n* manage a data team – engineers, analysts, or scientists\n* want to enable non-data experts to create data insights\n\nCheck out and reach out at [contact@alkera.ai](mailto:contact@alkera.ai). We’d love to showcase a demo, learn more about your data teams’ pain points, and share more about how Alkera can help supercharge them.", "url": "https://www.ycombinator.com/launches/Rcy-alkera-the-data-agent-that-you-can-trust", "votes": 12, "created_at": "2026-07-17T18:50:58.787Z" } ] }, { "id": 33279, "name": "Hebbian Robotics", "slug": "hebbian-robotics", "former_names": [ "Vanda Labs" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4e7272f21860060f8aa33bb297af6d18fab5ffdc.png", "website": "https://hebbianrobotics.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Hebbian Robotics builds open source foundational infrastructure for Physical AI to develop robots that extend what humanity can do, for the benefit of the communities they serve.", "one_liner": "Foundational infrastructure for Physical AI", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1786123276, "tags": [ "Robotics", "Data Science", "Data Engineering", "AI", "Databases" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/hebbian-robotics", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/hebbian-robotics.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/hebbian-robotics/", "x_url": "https://x.com/hbr_pbc", "fb_url": null, "cb_url": null, "github_url": "https://github.com/Hebbian-Robotics", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/4e7272f21860060f8aa33bb297af6d18fab5ffdc.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/18513ded63751a708b6d42e2a84d2517cb404aaf.png" ], "primary_partner": { "name": "Diana Hu", "url": "https://www.ycombinator.com/people/diana-hu" }, "founders": [ { "user_id": 388120, "full_name": "Brandon Ong", "title": "Co-Founder", "founder_bio": "Brandon is the co-founder of Hebbian Robotics, which builds APIs that help robotics data teams verify data quality for model training. He previously built Gigit AI, a Sequoia-backed AI customer experience startup. His research on AI for low-resource languages topped SEA-HELM, an LLM benchmark co-developed with Percy Liang's research group at Stanford. He briefly pursued a PhD in Robotics at Columbia and NTU before starting Hebbian.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/ongjjbrandon", "x_url": "https://x.com/brandon1", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5b65343ad1d0b482401872b3124da731618a3058.jpg" }, { "user_id": 968709, "full_name": "Kingston Kuan", "title": "Co-founder", "founder_bio": "Kingston spent the last few years at Jane Street building systems that scaled to millions of messages per second. He graduated valedictorian from the National University of Singapore (NUS) in Computer Engineering.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/kingston-kuan/", "x_url": "https://x.com/kstonekuan", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b674a8b80df5cd21ef03f13e6470d6126bc4c333.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 109711, "title": "Hebbian Robotics - APIs for searching and analyzing Physical AI data at scale", "tagline": "We enable evaluation of data quality without training a robotics model", "body": "# \\*\\*\\*\\*\n\n**TLDR;**\n\n* **Hebbian Robotics builds APIs for searching and analyzing Physical AI data at scale**\n* Our APIs enable data providers to get **on-demand signals and metrics** on the quality of their data, without managing infrastructure\n* We help our customers evaluate data quality without training a robotics model\n\n\n\n**Our Ask**\n\n* Buyers want data they can trust. If you're selling egocentric or robot data, **Let’s Chat ([https://calendly.com/brandon-hebbianrobotics/30min](https://calendly.com/brandon-hebbianrobotics/30min)**) and we'll show you how quality signals and metrics help you sell more at higher prices\n* **Check out Pareto ([https://pareto.hebbianrobotics.com/](https://pareto.hebbianrobotics.com/)),** an example of how our APIs can be used\n\n### **Who We Are**\n\n* We’re Brandon and Kingston, we've trained AI models for industrial cleaning robots and built production systems for camera fleets across the globe\n* [**Brandon Ong**](https://bookface.ycombinator.com/user/388120)'s previous AI startup was backed by Sequoia. He did research on AI for low resource languages that topped Stanford’s LLM benchmark, SEA-HELM, and dropped out of his joint PhD in Robotics at Columbia and NTU\n* [**Kingston Kuan**](https://bookface.ycombinator.com/user/968709) spent years at Jane Street building systems that scaled to millions of messages per second. At Verkada, he worked on their core video surveillance platform that processed large scale multimodal data\n\n### **The Problem**\n\n* **High quality data is the bottleneck for unlocking the next frontier of intelligence in robotics**\n* Buyers want **data they can trust** \n* Data providers don’t have the bandwidth to provide signals and metrics about the quality of their data when they are **focused on** **operational excellence** \n* This means that **model developers are forgoing model improvements due to a lack of high quality data**, impeding progress in robotics\n\n### **Our Solution**\n\n* APIs for searching and analyzing Physical AI data at scale that enables providers to get **on-demand signals and metrics on data quality**\n* Buyers demanding per-collector hour limits? **Prove compliance while we stay ahead of the workarounds**\n* Changed standard operating procedures for collection? **Monitor for quality drift and regression**\n* Suspect duplicate samples? **Verify quickly with a single API call**\n* Our APIs enable **evaluation of data quality without training a robotics model, fast iteration cycles for** high quality data collection, and unlock **model improvements** \n\n### **How to reach us**\n\n* We want to support data providers who believe in collecting high quality data in an ethical way\n* To get started, email [**brandon.ong@hebbianrobotics.com**](mailto:brandon.ong@hebbianrobotics.com)", "url": "https://www.ycombinator.com/launches/SXX-hebbian-robotics-apis-for-searching-and-analyzing-physical-ai-data-at-scale", "votes": 81, "created_at": "2026-08-09T03:00:00.116Z" } ] }, { "id": 35266, "name": "TrueMile", "slug": "truemile", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/94408cc02a79b94fd281d47aabc0056465683df6.png", "website": "https://TrueMile.AI/", "all_locations": "San Francisco, CA, USA", "long_description": "TrueMile is building a fully autonomous logistics company, starting with trucking. Delayed pickups, empty miles and poor planning eat into a carrier’s profits. Our agents coordinate loads, routes, driver schedules and fuel stops to earn more from each truck and lower the cost of moving goods.\r\n\r\nWe’re starting with our own fleet so we control execution, learn from every delivery and keep the gains. Human drivers come first. As autonomous trucks become available on our routes, we’ll have the customers, freight and infrastructure ready for them.\r\n\r\nAs we drive toward AGI, people will still need groceries, clothes and materials to build their homes. Someone has to move all of it. We want every leap in AI to show up in what people pay for everyday goods.", "one_liner": "An AI-operated logistics company.", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Supply Chain and Logistics", "launched_at": 1790031761, "tags": [ "AIOps", "Machine Learning", "Logistics", "Data Science" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2026", "status": "Active", "industries": [ "B2B", "Supply Chain and Logistics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/truemile", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/truemile.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/truemile/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/94408cc02a79b94fd281d47aabc0056465683df6.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/a12b26e20f33313f399874daf66fede460128c50.png" ], "primary_partner": { "name": "Andrew Miklas", "url": "https://www.ycombinator.com/people/andrew-miklas" }, "founders": [ { "user_id": 3107234, "full_name": "Harpreet Dhaliwal", "title": "Founder/CEO", "founder_bio": "Harpreet has generated over $7M+ in trucking revenue, running his family's fleet since 19 and building the operation agents that became TrueMile. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/harpreet-dhaliwal/", "x_url": "https://x.com/harpreetd14", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c44eac0421520202a48251098ea059ed7d9a460b.jpg" } ], "jobs": [], "news": [], "launches": [] } ]