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Using fixed sensors and robots that climb, crawl, swim, and fly, we combine first-order data layers with the predictive power of AI into a single source of truth for the physical world. 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How did you decide to be a founder?)", "answer": "Troy and Jake met in at Grove City College outside of Pittsburgh. They lived in the same dorm, played sports together and enjoyed frequent conversations about the world. After initially bootstrapping Gecko, Jake and Troy reconnected and saw the same vision of building a robotics company to solve real challenges in the built world." }, { "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": "Jake was unfamiliar with YC before they applied. In the fall of 2016, Troy learned that Kevin Hale was scheduled to be in Pittsburgh promoting the next cohort. Jake and Troy met him and talked through the vision for how Gecko could scale. At the time Gecko was making money but wasn’t yet focused on raising money or the traction it would take to turn the company into a scalable business. Kevin, Jake and Troy talked through that path and Jake and Troy turned in their application almost immediately afterwards. Going through the batch was formative for helping Jake and Troy chart Gecko’s path forward. As the batch was starting they were weighing an acquisition offer but, thanks in large part to the advice they were getting at YC, they decided to reject the offer and build the company together." }, { "question": "How have you kept in touch with the YC community and continued to use YC resources & programs since the batch ended?", "answer": "Yes. Mostly through interactions with Kevin Hale, Jared Friedman, Sam Altman and Jon Levy. " }, { "question": "What's the history of your company from getting started until the present day? What were the big inflection points?", "answer": "Jake built the world’s first wall-climbing ultrasonic testing robot in 2012. Soon after we were making money but weren’t sure on the path to scale. Going though YC was a key inflection point that lead us to our model for scaling Gecko. The decision to turn down early acquisition attempts and investments in favor of building the company we wanted build to was another key inflection point. Gecko turned down offers right before demo day from investors in favor of walking. Fast forward to today and Gecko is closing deals with some of the biggest energy providers on the planet as well as global institutions like the U.S. Air Force and U.S. Navy." }, { "question": "What is the core problem you are solving? Why is this a big problem? What made you decide to work on it?", "answer": "Jake visited a power plant while in college. The owner talked about how assets at the plant just fail and the plant shuts down regularly and that was seen as just the cost of doing business. That seemed wrong to Jake. It made him think about the importance of the built world and how much we rely on physical assets to provide power, water, safety and other critical services. Yet at the same time they are aging and starting to breakdown - Jake thought he had found a problem hiding in plain sight. Jake and Troy talked a lot about that in the early days of Gecko and committed the company on a path to deploy advanced robotics to solve this critical problem that no one else seemed to be working on." }, { "question": "What is your long-term vision? If you truly succeed, what will be different about the world?", "answer": "The long-term vision for Gecko Robotics is to transform the world’s most important industries that have been left behind in the digitalization movement. Gecko aims to be one of the first truly impactful robotics companies and prove that the best way to build incredible hardware and software is around solving real world problems and creating impactful outcomes for customers. 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", "one_liner": "Unlocking the utility of genomics for the world.", "team_size": 50, "industry": "Healthcare", "subindustry": "Healthcare -> Industrial Bio", "launched_at": 1607278601, "tags": [ "Hard Tech", "Hardware", "Robotics", "Genomics", "Biotechnology" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2019", "status": "Active", "industries": [ "Healthcare", "Industrial Bio" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": [ { "question": "Describe what your company does in 50 characters or less.\n", "answer": "We build Integrated circuits for biology workflows" }, { "question": "What is your company going to make? Please describe your product and what it does or will do.\n", "answer": "A high throughput automation system for Next-Generation Sequencing (NGS) sample preparation using digital microfluidic chip technology." } ], "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": "In 2018, Volta Labs was born in the halls of MIT with a clear mission: to unlock the utility of genomics for the world.\\\\Previously nestled in the vibrant hub of Kendall Square, known as \"the most innovative square mile on the planet,\" we quickly became immersed in the dynamic biotech culture. After numerous conversations with other scientists and hours of research, we discovered that trailblazing biologists were being held back by the constraints of existing automation tools, particularly in the realm of DNA sequencing. While DNA readout technologies surged ahead, the upstream steps of sample preparation (sample prep) lagged behind.\\\\During Founder Udayan Umapathi’s graduate stint at the MIT Media Lab, what began as a humble printed circuit board to manipulate colorful droplets soon evolved into a solutionfor the notorious \"sample prep bottleneck.\" Propelled into action, we secured funding from top-tier VCs and got to work." }, { "question": "What's the history of your company from getting started until the present day? What were the big inflection points?", "answer": "Since the company was funded coming our YC in Winter 2019, our focus has been laser-sharp in the lab, where we've been busy inventing and constructing groundbreaking fluidic and sample manipulation technologies. We embrace an anti-disciplinary approach, tackling the toughest challenges by seamlessly integrating instrumentation, fluidics, software, biology, and chemistry. While we're currently channelling our energies into sequencing sample prep, our grand vision extends beyond – envisioning a future where a single universal machine automates the lion's share of biological workflows in genomics, proteomics, and synthetic biology.\\\\At Volta, we're not just shaping the future of genomics; we're engineering it. Join us in harnessing the power of biology and technology to change the world." }, { "question": "What is the core problem you are solving? Why is this a big problem? What made you decide to work on it?", "answer": "We are in the midst of a genomic revolution. From 1999 to 2000, the Human Genome Project generated the first “draft” human genome, which cost \\~$300 million across 20 labs worldwide. It took another three years, and hundreds of millions of dollars, to produce a human genome that was \\~90% complete, as complete as the technologies for sequencing DNA allowed at the time. In 2023, a scientist can sequence a genome at a bench for hundreds of dollars in a day. The adoption of sequencing technologies across new applications only continues to accelerate as it becomes easier, faster, and cheaper. \\\\Despite these advancements, preparing samples for sequencing remains a significant bottleneck. We believe that disruptive innovations are needed in sample prep to unlock the true utility of genomics. With the new reality of the $200 genome (sequencing cost alone), sample prep is becoming a more significant burden on labs than ever before. " } ], "url": "https://www.ycombinator.com/companies/volta-labs-inc", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2019/volta-labs-inc.json", "year_founded": 2018, "city": "Boston", "country": "US", "linkedin_url": "https://www.linkedin.com/company/volta-labs-inc", "x_url": "https://twitter.com/voltalabsinc", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/volta-labs-a9c8", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/373e91d473569c304899f7cec638ddc0b46d10d6.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/b174dc71f1ac1b5b04ae4d55f5100d5bef2f19b8.png", "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/7bb2e9324a7753b95d0c687a8a5d98b14165bf0a.png" ], "primary_partner": null, "founders": [ { "user_id": 11802, "full_name": "Udayan Umapathi", "title": "Founder", "founder_bio": "As the founder and CEO of Volta Labs, Inc., I have over five years of experience in creating and scaling a company that is transforming the field of sequencing sample prep. With a background in entrepreneurship, engineering, design and biology, I have a unique perspective and skill set that enables me to bridge the gap between different disciplines and domains.\n\nAt Volta Labs, we are building a disruptive product that streamlines the entire process of preparing samples for any sequencing technol", "is_active": true, "linkedin_url": "http://linkedin.com/in/udayanu/", "x_url": "https://twitter.com/uday1489", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e36948027c0c8b60f053b0afec83af2bc19a7b3f.jpg" } ], "jobs": [], "news": [ { "title": "Volta Labs Launches Electrowetting-Based Automated NGS Sample Prep Platform | GenomeWeb", "url": "https://www.genomeweb.com/sequencing/volta-labs-launches-electrowetting-based-automated-ngs-sample-prep-platform", "date": "Feb 07, 2024" }, { "title": "Volta Labs and Integrated DNA Technologies Partner to Advance Target Enrichment Workflows", "url": "https://www.prnewswire.com/news-releases/volta-labs-and-integrated-dna-technologies-partner-to-advance-target-enrichment-workflows-302052365.html?tc=eml_cleartime", "date": "Feb 06, 2024" }, { "title": "Volta Labs and Watchmaker Genomics Partner to Simplify and Optimize NGS Library Prep", "url": "https://www.prnewswire.com/news-releases/volta-labs-and-watchmaker-genomics-partner-to-simplify-and-optimize-ngs-library-prep-302052367.html?tc=eml_cleartime", "date": "Feb 05, 2024" }, { "title": "Volta Labs Launches Callisto to Revolutionize Genomics and Sample Prep", "url": "https://www.prnewswire.com/news-releases/volta-labs-launches-callisto-to-revolutionize-genomics-and-sample-prep-302049915.html", "date": "Feb 01, 2024" }, { "title": "Volta Labs grabs $20 million to address a growing genomics bottleneck – TechCrunch", "url": "https://techcrunch.com/2022/03/18/volta-labs-grabs-20-million-to-address-a-growing-genomics-bottleneck/", "date": "Mar 18, 2022" } ], "launches": [ { "id": 78341, "title": "Volta Labs - A genomics applications company revolutionizing sample prep", "tagline": "Unlocking the utility of genomics for the world", "body": "**_tl;dr_** - Volta Labs introduces Callisto, a groundbreaking genomics sample preparation system. With its push-button simplicity, Callisto transforms sample prep unlike anything else in the past 15 years, offering a revolutionary and hands-free experience. Checkout the [**_product here._**](https://www.voltalabs.com/product)\n\n[Volta Labs](https://www.voltalabs.com/product) is a group of antidisciplinary scientists and builders working at the intersection of engineering and biology. With the release of Callisto, we brought to life a sequencer agnostic platform that spans from the raw biological sample to sequenceable molecules. We have done this by reinventing the full stack — hardware, software, chemistry, and biology. At Volta, we’re not just shaping the future of genomics, we are engineering it.\n\n![uploaded image](/media/?type=post&id=78341&key=user_uploads/11802/3c27fa33-e647-497c-997f-4c09284f47b6)\n\n\\\n[🤔](https://emojipedia.org/thinking-face) **The Problem** \n\nGenomic sequencing has made remarkable strides since its inception in 1990, with continuous advancements in both sequencing and data analysis over the past three decades. However, the process of preparing samples for sequencing has seen limited innovation during this time. Despite the tremendous progress in sequencing technologies, the sample preparation phase remains a bottleneck, often taking multiple days and requiring skilled lab technicians and expensive instruments.\n\n**✅ The Solution - The CallistoTM Sample Prep System**\n\nAt Volta, we aim to reduce time and complexity with the introduction of our flagship product, Callisto – a benchtop instrument with many pre-optimized applications that reduces operational requirements and costs in the laboratory and clinic that were previously cost-prohibitive. This innovation addresses the longstanding challenges that have hindered efficiency and accessibility in genomics, making it a game-changer for the industry.\n\n![uploaded image](/media/?type=post&id=78341&key=user_uploads/11802/ae8be7a4-5028-465f-a3f4-ea4d05dabc30)\n\n![uploaded image](/media/?type=post&id=78341&key=user_uploads/11802/da90f1f1-fd22-49a5-b025-5814ed501736)\n\n![uploaded image](/media/?type=post&id=78341&key=user_uploads/11802/c2fd28d3-6988-410b-a677-d20a6f0c1eae)\n\n**✨ Benefits**\n\nCallisto is set to revolutionize laboratories, seamlessly combining efficient nucleic acid extraction with push-button library creation. Explore some of the many advantages that Callisto introduces to the field of genomics sequencing:\n\n* Can be operated without specialized training and takes minutes to set up\n* Sequencer agnostic\n* All-in-one, benchtop solution that allows users to press start and walk away\n* Speeds up and simplifies both short- and long-read sequencing preparations\n* Out of the box, pre-optimized applications\n\n\n\n🤝 **Our Ask**\n\n* **Connect us with companies and individuals in life sciences and beyond.** Feel free to connect on [LinkedIn](https://www.linkedin.com/in/udayanu) or [send me an email directly](mailto:hello@voltalabs.co)\n* Volta is growing fast and looking for talented engineers as we ramp up production - software, mechanical and electrical. **Our immediate need is for a Software Engineering Lead, Electrical Lead and a Head of Manufacturing.**  [Apply here](https://www.voltalabs.com/careers) or [send me an email](https://hello@voltalabs.co) directly if you want to refer a friend.", "url": "https://www.ycombinator.com/launches/KNZ-volta-labs-a-genomics-applications-company-revolutionizing-sample-prep", "votes": 4, "created_at": "2024-02-12T03:20:46.409Z" } ] }, { "id": 12267, "name": "Mars Auto", "slug": "mars-auto", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f5295faf44c40fbb90c24090479454a928300bbd.png", "website": "https://marsauto.com", "all_locations": "Seoul, Seoul, South Korea", "long_description": "Mars Auto is building autonomous trucks to fully automate long-haul freight shipping.", "one_liner": "Autonomous trucks to fully automate long-haul freight shipping", "team_size": 15, "industry": "Industrials", "subindustry": "Industrials -> Automotive", "launched_at": 1544040063, "tags": [ "Autonomous Trucking", "Robotics", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2019", "status": "Active", "industries": [ "Industrials", "Automotive" ], "regions": [ "South Korea", "East Asia" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/mars-auto", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2019/mars-auto.json", "year_founded": 2017, "city": "Seoul", "country": "KR", "linkedin_url": "https://www.linkedin.com/company/marsauto", "x_url": "", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/mars-auto", "github_url": "https://github.com/marsauto", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/f5295faf44c40fbb90c24090479454a928300bbd.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 11057, "full_name": "Ilsu Park", "title": "Founder", "founder_bio": "", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/daftshady/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/86e0561fc0e3e29f2aa0db0280140a46d7566b54.jpg" } ], "jobs": [], "news": [ { "title": "Self-driving truck startup Mars Auto eyes 'middle-mile' market in U.S. | Yonhap News Agency", "url": "https://en.yna.co.kr/view/AEN20231215005700320", "date": "Dec 14, 2023" } ], "launches": [] }, { "id": 12553, "name": "Well Principled", "slug": "well-principled", "former_names": [ "Well Principled", "BODYSIM by Well Principled" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6c59ac5aca8c4a74c69ab15c408544b91f24e98e.png", "website": "https://wellprincipled.com", "all_locations": "St. Louis, MO, USA", "long_description": "We aren’t building AI to replace \"knowledge work” that requires neither, but to bolster the working human intellect which has never failed to discover new paths to prosperity.\r\n\r\nFor all their success, mainstream approaches to AI have fundamental limitations preventing them from solving critical classes of problems. We are building a new AI architecture from first principles to break from these limitations.\r\n\r\nThe status quo has ossified around the supervised, brute-force pretraining paradigm. These systems do not, and cannot, handle the essential skills of continual learning, goal discovery, novel planning, and the creation of new knowledge.\r\n\r\nThese limitations are not trivial. Our national prosperity depends directly on overcoming these limitations, because the essential skills underlie the skilled trades. From electricians to machinists to nurses, apprentice tradespeople in all of these fields learn “skilled improvisation” where every solution is novel, and even the goal must be discovered. Prosperity demands the precise capabilities where status quo AI is structurally weak.\r\n\r\nWorse, these limitations will not be overcome with more compute or training data. They are inescapable consequences of the underlying technologies of supervised learning, neural networks, transformers, backprop, and gradient descent. Progress requires independence from them.\r\n\r\nWe are building a new AI architecture by reverse-engineering the system that got us this far: the human brain. By triangulating between neuroscience, cognitive science, and the evolutionary elaboration of brains, we have identified the brain’s algorithms to (a) continually learn a causal world model (b) select goals to both achieve and learn to achieve more (c) plan to reach novel goals, and (d) creatively produce new knowledge.\r\n\r\n\r\nJoin us in building intelligence with ingenuity to bolster the skilled trades.\r\n\r\n", "one_liner": "The neural engine for autonomous robots", "team_size": 3, "industry": "B2B", "subindustry": "B2B", "launched_at": 1556081533, "tags": [ "Hard Tech", "Neurotechnology", "Robotics", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2019", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": true, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/well-principled", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2019/well-principled.json", "year_founded": 2018, "city": "St. Louis", "country": "US", "linkedin_url": "https://www.linkedin.com/company/well-principled", "x_url": "https://twitter.com/WellPrincipled", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/well-principled", "github_url": "https://github.com/wellprincipled", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/6c59ac5aca8c4a74c69ab15c408544b91f24e98e.png", "app_video_url": null, "dday_video_url": "https://bookface-images.s3.us-west-2.amazonaws.com/video_event/45/1566241198616-71hnc3yy20s-e44047fd543930de13cd42793c010be6/9c5803bb1c409138256027580ef7c991.mp4?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAQC4NIECABPQ2AHNW%2F20261020%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20261020T022643Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&X-Amz-Signature=dbc2c54bb5f28caeb41240d2b9c97286f72aeafa80af24a39d2b5728d1cf412d", "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/f3e9f53254f6f411d6c324fc428104be8af65d13.png" ], "primary_partner": null, "founders": [ { "user_id": 337500, "full_name": "Ryan Richt", "title": "Founder", "founder_bio": "Ryan has galvanized teams with bold vision and disruptive, patented innovations since 2003. Ryan transformed distributed analytics across an academic lab, his first bootstrap startup and computational biology and cloud teams at Monsanto. He grew VC-backed CiBO from 7 to 70 engineers and data scientists. Ryan holds an MBA and BA prob/stats from Olin and WashU.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/ryan-richt/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e251b1296e81516f1167cf3a6363f07ff33fedc3.jpg" }, { "user_id": 338275, "full_name": "Christopher Shafer", "title": "Founder", "founder_bio": "Chronically the first customer-facing engineer, Chris has delighted customers with deep-data applications from corn germplasm catalogs to global satellite data and environment simulations. Marshalling his broad expertise from cloud architecture to data visualization, Chris delivers outcomes customers love and leads solutions teams to productize them.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/chris-shafer/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7c828b926156cb2ee1bccbd77869529553cbf3f0.jpg" }, { "user_id": 338266, "full_name": "Joseph Wingbermuehle", "title": "Founder", "founder_bio": "Joe has spent 15 years building foundational platforms, from middleware at AT&T, to startups across FPGA-accelerated high-frequency trading, accelerated ETL, machine learning based network security (acquired by Cisco) and hybrid AI/physical models of global-scale crop simulation. Joe holds a BS in Applied Math and a PhD in Computer Science from WashU.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/joewing", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/bc10e36863ae342f0586145c2ce2fcc5c7fcd6e0.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 83050, "title": "BODYSIM: Gain muscle and shed fat with a digital twin of your body", "tagline": "Your body's app-based simulation that recommends nutrition and exercise to meet your goals.", "body": "![uploaded image](/media/?type=post&id=83050&key=user_uploads/337500/1b2cc420-a97a-4df4-9066-c1974aff8915)\n\nWe're excited to announce a complete overhaul of BODYSIM from a tracking and modeling tool for your metabolism into an end-to-end fitness forecasting system. After launching our initial beta last fall, we discovered something crucial: our users didn't just need another tracking tool with cool graphs, they needed a complete solution that bridges the gap between goals and real results.\n\n# The Challenge of Getting Results is Still Valid\n\nIf you've ever tried to build muscle and lose fat, you know the frustration:\n\n* Conflicting advice from countless \"experts\" and unreliable information\n* Scattered data across different apps and devices, each telling a different story\n* The exhausting task of turning abstract targets into actual meals and workouts\n\n# The (new) BODYSIM Solution: Building Your Digital Twin\n\nAt BODYSIM's core is our advanced \"digital twin\" technology, combining sensor fusion with the science of metabolism and physiology to help you understand your true potential, using:\n\n* DEXA scans\n* BIA weigh-ins\n* 3D body scans\n* Fitness tracker data\n* Resistance training\n* Macro-tracking\n* Blood panel biomarkers\n\nThis comprehensive data integration unlocks hidden insights about your metabolism, including your Basal Metabolic Rate (BMR), Total Daily Energy Expenditure (TDEE), hormone balance, and body composition changes.\n\n# What's New: Tools are Not Enough - Get Our Users Outcomes\n\n### 1. Prescriptive Meal Plans: Chef-Created Meal Plans & Virtual Meal Kits\n\n* Library of high-protein, low-fat recipes with step-by-step instructions to make eating for transformation easy\n* Customizable weekly meal plans based on your preferences and goals\n* Direct integration with Walmart and Amazon delivery: order your entire meal plan with a few clicks\n* Simplified food logging with grouping, automated recipe creation, and easy to repeat meals\n\n![uploaded image](/media/?type=post&id=83050&key=user_uploads/337500/2ce2e1ea-b35c-40b9-9cf4-26d0cf6b18cb)\n\n### 2. Prescriptive Workouts: Comprehensive Workout System\n\n* 2,200+ exercises with detailed videos and instructions\n* Intelligent weekly split recommendations\n* Progressive overload tracking to optimize muscle gain\n* 3D scan integration to track individual muscle group progress\n\n![uploaded image](/media/?type=post&id=83050&key=user_uploads/337500/68860789-4915-47c8-a893-f0df1991b813)\n\n### 3. Fitness Forecasting: Advanced Integration Features\n\n* Scenario planning to understand how to achieve goals faster\n* Muscle group modeling that maps exercises to specific body measurements\n* Blood marker sub-models that connect nutrition choices to health outcomes with quantitative recommendations to make a change\n* Overtraining Syndrome (OTS) risk monitoring\n\n![uploaded image](/media/?type=post&id=83050&key=user_uploads/337500/5c951bcb-3162-4b27-9bba-e1d9521fed0b)\n\n---\n\n---\n\n# Why Trust Us\n\nThis is what we do; our core tech distills messy academic literature into simulations. We've deployed science-based models of consumer behavior and battery electrochemistry to enterprise. We built BODYSIM to guide our own fitness journeys. It worked. I put on 45 lbs of muscle, and my co-founder put on 25 lbs of muscle while losing 50 lbs of fat.\n\nAnd it worked in our alpha test (ages 29-69, 50% female). 8 alpha testers lost an average of 12.6 pounds in 3 months, and 4 alpha testers with a maintain goal changed <1.4 pounds in 3 months.\n\nWe then had some beta amazing beta tester results: one lost 40 lbs, another gained 12 lbs of muscle, a female user gained 8 lbs muscle, a co-founder gained 10 lbs of muscle, and more.\n\n![uploaded image](/media/?type=post&id=83050&key=user_uploads/337500/04e38715-bc9f-4c3d-ab07-adacd8f1ee9f)\n\n![uploaded image](/media/?type=post&id=83050&key=user_uploads/337500/cc37c2ce-b3d5-40b2-a5ac-455b0dc85f93)\n\n# The Complete Package\n\nYour BODYSIM subscription includes:\n\n* Quarterly DEXA scans\n* Withings Body Scan scale\n* Monthly at-home blood tests\n* Escali food scale for precise tracking\n* Daily body composition updates\n* Live signals like Resistance Training Intensity to adaptively steer to your goals\n* Personalized exercise and nutrition recommendations\n\n# Join Us\n\nJoin us in revolutionizing how people transform their bodies. With BODYSIM, you're not just getting another fitness app - you're getting a science-based, personalized system that guides you from where you are to where you want to be.\n\nReady to transform your body with confidence? Visit [bodysim.com](http://bodysim.com) today.", "url": "https://www.ycombinator.com/launches/LbW-bodysim-gain-muscle-and-shed-fat-with-a-digital-twin-of-your-body", "votes": 24, "created_at": "2024-08-14T20:27:45.090Z" } ] }, { "id": 12597, "name": "Lucid Bots", "slug": "lucid-bots", "former_names": [ "Lucid Drone Technologies", "Lucid Drone Tech" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3ef3c01732ca1adf6e17c2105c507271f7b86744.png", "website": "https://lucidbots.com/", "all_locations": "Charlotte, NC, USA", "long_description": "At Lucid, we are a B2B robotics provider for dull, dirty, and dangerous jobs, starting with the cleaning industry, which has a 200% annual turnover rate. \r\n\r\nOur primary product is a drone that can clean anything from windows to roofs to stadium domes to industrial tanks. Our drones can clean up to 8x faster. Due to customer demand, we also launched a ground-based pressure-washing robot to complement our cleaning drone.\r\n\r\nWe support customers around the country who use our robots every day to clean properties with great safety and efficiency. We engineer, manufacture, and support our technology from a 20,000 sqft headquarters in Charlotte, NC.", "one_liner": "We build robots for dull, dirty, and dangerous jobs.", "team_size": 26, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1556215532, "tags": [ "Robotics", "Drones", "Manufacturing", "Aerospace", "Self-Driving Vehicles" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2019", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/lucid-bots", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2019/lucid-bots.json", "year_founded": 2018, "city": "Charlotte", "country": "US", "linkedin_url": "https://www.linkedin.com/company/lucid-bots", "x_url": "https://twitter.com/lucid_bots", "fb_url": "https://www.facebook.com/lucidbots/", "cb_url": "https://www.crunchbase.com/organization/lucid-drone-technologies", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/3ef3c01732ca1adf6e17c2105c507271f7b86744.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 324936, "full_name": "Andrew Ashur", "title": "Founder", "founder_bio": "Andrew manages the overall operations of Lucid, including product development, strategic partnerships, and investor relations. He is a prolific learner with a demonstrated track record for extreme productivity. Andrew graduated with a double major from Davidson College in just three years, while playing a Division I sport, working three jobs, and founding Lucid. ", "is_active": true, "linkedin_url": "https://linkedin.com/in/andrewashur", "x_url": "https://twitter.com/andrew__ashur", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7dab073afb6738934109b1ebf3cf32a194453587.jpg" } ], "jobs": [], "news": [ { "title": "Lucid Bots secures $9M for drones to clean more than your windows | TechCrunch", "url": "https://techcrunch.com/2024/05/08/lucid-bots-9m-drones-clean-windows/", "date": "May 08, 2024" }, { "title": "Charlotte company turns to drones for window washing | Charlotte Observer", "url": "https://www.charlotteobserver.com/news/business/article263258723.html", "date": "Jul 12, 2022" } ], "launches": [] }, { "id": 12622, "name": "Yummy Future", "slug": "yummy-future", "former_names": [ "Yummy Future", "Yummy Future Inc." ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b16e65239377a055987a5fda8f301c3a3cd7876f.png", "website": "https://yummy-future.com", "all_locations": "Champaign, IL, USA", "long_description": "We amplify worker produtivity by10X. Restaurants and food retail businesses require high volume and consistency, yet many business owners struggle to achieve this. Employees also dislike working in repetitive and labor-intensive environments, where even a slight mistake can lead to customer complaints. 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Our technology reduces the burden on human workers, allowing them to focus on building closer connections with customers.\n\n![uploaded image](/media/?type=post&id=86631&key=user_uploads/310507/94f263ae-be8f-49a6-b20a-3d3a8fc988b9)\n\n## **The Problem: Restaurant Price Inflation**\n\nAccording to Finance Buzz, restaurant prices increased by an average of 60% between 2014 and 2024—nearly double the national inflation rate. To make matters worse, service quality has declined. CNBC reports that 25.9% of Starbucks customers experienced longer wait times, reflecting a broader trend of labor shortages in the industry.\n\n![uploaded image](/media/?type=post&id=86631&key=user_uploads/310507/7b2798ce-cc88-4789-98cf-124637dd96cc)\n\nWhy is the labor shortage happening?\n\nMany workers view server or barista roles as unsustainable long-term careers, especially on minimum wage, leading to **high turnover rates**, such as **130.7%** in 2020. This forces businesses to incur additional expenses for hiring, training, and maintaining staff while overburdening existing employees to stay profitable.\n\n# **Our solution**\n\nWe're here to change the game—making businesses profitable while ensuring workers find satisfaction and sustainability in their roles.\n\n[YC launch Video](https://youtu.be/3cQhbJTUL10)\n\n![uploaded image](/media/?type=post&id=86631&key=user_uploads/310507/ec24464e-a9a9-4eda-b0ce-52e69a6884d4)\n\nOur system is a high-throughput, modular, and reconfigurable solution, designed to serve as a flexible multi-category food and beverage assembly line. By automating routine and production-heavy tasks, it reduces the burden on human workers, allowing them to focus on building closer connections with customers—answering questions, addressing their needs, and fostering meaningful interactions.\n\n![uploaded image](/media/?type=post&id=86631&key=user_uploads/310507/10db4630-8784-4114-a96f-85cf52a555f3)\n\n# **Our ask**\n\nWe’d love to hear from you:\n\n* **Support Our Crowdfunding Campaign:** \n* **Franchising Interests:** Let’s explore how we can grow together.\n* **Partnership Opportunities:** If you have an existing brand and want to integrate our solution, let’s collaborate!\n* **Join the Waitlist for Coffee Shop in a Box:** Email us at [business@yummy-future.com](mailto:business@yummy-future.com)\n\nWe look forward to connecting and working together!\n\n![uploaded image](/media/?type=post&id=86631&key=user_uploads/310507/a9c1edd9-fbb1-46d2-9f04-5d274611c758)\n\n", "url": "https://www.ycombinator.com/launches/MXH-yummy-future-robot-workforce-for-the-food-beverage-industry", "votes": 10, "created_at": "2025-01-07T01:36:29.570Z" } ] }, { "id": 13085, "name": "Teleo", "slug": "teleo", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/27eb2aa5b06962471ae4c326b326810f092de134.png", "website": "http://www.teleo.ai", "all_locations": "San Francisco, CA, USA; Palo Alto, CA, USA", "long_description": "Teleo converts heavy equipment, like dozers, trucks, and loaders, into supervised autonomous robots. This enables a single operator to remotely operate multiple machines while sitting at a remote control center, unlocking productivity gains for the General Contractor.", "one_liner": "Supervised Autonomous Heavy Equipment", "team_size": 30, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1583906560, "tags": [ "Autonomous Trucking", "Hard Tech", "Robotics" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2020", "status": "Acquired", "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/teleo", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2020/teleo.json", "year_founded": 2019, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/teleo-ai", "x_url": "https://www.twitter.com/teleoai", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/teleo", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/27eb2aa5b06962471ae4c326b326810f092de134.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 417365, "full_name": "Rom Clément", "title": "Founder/CTO", "founder_bio": "Co-founder and CTO of Teleo, Inc\nEx-Lyft L5 (self-driving), Ex-Google (Street View)\n0 to 60 across the board (tech sales, hardware, software, supply chain, deployment and customer success)", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/romclement/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/35f8eb3137921ebcc2d279db388495164cbf6a4c.jpg" }, { "user_id": 302603, "full_name": "Vinay Shet", "title": "Founder", "founder_bio": "Vinay is the co-founder and CEO of Teleo. Prior to Teleo, he was the Director of Product Management at Lyft working on building Lyft's self-driving cars. Prior to Lyft, Vinay led Product Management at Google Street View, Google Maps, and Google reCAPTCHA launching several consumer products used by millions of users worldwide. Vinay has a Ph.D. in Computer Science, focusing on Computer Vision from the University of Maryland, College Park", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/vinayshet/", "x_url": "https://twitter.com/vinay_shet", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0b9037152ce8a6d6d6b5c31985c828cf00554573.jpg" } ], "jobs": [], "news": [ { "title": "Teleo transform Construction and Mining | Silicon Valley Business Journal", "url": "https://bizj.us/1qgf58", "date": "Jan 09, 2023" }, { "title": "Announcing Teleo’s Series A | Teleo", "url": "https://www.teleo.ai/blog/announcing-teleos-series-a/", "date": "Jun 07, 2022" } ], "launches": [] }, { "id": 13087, "name": "RoboTire", "slug": "robotire", "former_names": [ "RoboTire", "Inc" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/07e8ffa81c10eb2269c2c3a93e56b98e17f2aef9.png", "website": "http://www.robotire.com", "all_locations": "Plymouth, MI, USA", "long_description": "In a fleet-centric world where everything is delivered to your doorstep, cost-per-mile and uptime are all that matter. Vehicles will be driving more miles and the decreased complexity of electric motors will fundamentally change the automotive service industry. ROBOTIRE will bring manufacturing-level automation to vehicle servicing. \r\n\r\nTires are the perfect vertical to tackle first because they are future-proof (tires are going nowhere) and scale from luxury personal automobiles to freight-centric big-rigs. The current tire changing industry is entrenched with an aging workforce but maintains strong margins. We will build and deploy a robotic tire changing container that can change tires in 10 minutes. \r\n\r\nOur fully-integrated ROBOTIRE containers can be placed inside existing shops, Walmart parking lots or in the middle of a fleet service area hundreds of miles away from a major city. In the medium term, we will expand to brakes, oil, batteries, etc. becoming an uptime assembly line that keeps fleets on the road 24/7 at a fraction of the maintenance cost per mile we see today. In a fleet-centric world, cost-per-mile and uptime are all that matter. ROBOTIRE tackles both.\r\n", "one_liner": "Robotire is automating vehicle maintenance for today and future…", "team_size": 20, "industry": "Industrials", "subindustry": "Industrials -> Automotive", "launched_at": 1582738118, "tags": [ "Hardware", "Robotics", "Automation" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2020", "status": "Inactive", "industries": [ "Industrials", "Automotive" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/robotire", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2020/robotire.json", "year_founded": null, "city": "Plymouth", "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/07e8ffa81c10eb2269c2c3a93e56b98e17f2aef9.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 324637, "full_name": "Victor Darolfi", "title": "Founder", "founder_bio": "Victor Darolfi is a seasoned entrepreneur (1 exit) and passionate roboticist with 11 years of experience designing, fabricating, and building robotics and automation equipment. 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", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/michael-carter-2684b575/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a533272decc1ee91b6f09eb177c3e938a9439ccd.jpg" } ], "jobs": [], "news": [ { "title": "Fleetzero begins its search for the first giant ship to convert to battery power – TechCrunch", "url": "https://techcrunch.com/2022/06/30/fleetzero-begins-its-search-for-the-first-giant-ship-to-convert-to-battery-power/", "date": "Jun 30, 2022" }, { "title": "This electric cargo ship could soon replace fuel-burning freight", "url": "https://www.fastcompany.com/90738126/this-startup-designed-an-electric-cargo-ship-to-cross-the-ocean", "date": "Apr 06, 2022" }, { "title": "Fleetzero wins Harvard Business School New Venture Competition", "url": "https://www.hbs.edu/news/releases/Pages/new-venture-competition-25-years.aspx", "date": "Apr 01, 2022" }, { "title": "Why the next electric battery boom may be in cargo ships", "url": "https://www.cnbc.com/2021/10/26/why-the-next-electric-battery-boom-may-be-in-cargo-ships.html", "date": "Mar 19, 2022" }, { "title": "New Orleans Startup Seeks to Develop Swappable-Battery Electric Ships", "url": "https://www.maritime-executive.com/editorials/new-orleans-startup-seeks-to-develop-swappable-battery-electric-ships", "date": "Mar 19, 2022" } ], "launches": [] }, { "id": 25400, "name": "Industrial Next", "slug": "industrial-next", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f77b3fae4e9032c53ab1dabf92d2dde1c13be9a0.png", "website": "https://www.industrialnext.ai", "all_locations": "San Francisco, CA, USA", "long_description": "We're building the brain for the factory floor, developing AI-driven robotic systems powered by a proprietary foundation model for the difficult, contact-rich manufacturing tasks where conventional automation falls short.\r\n\r\nFounded by veterans of Tesla, Waymo, Ford, and GM who built the systems that brought modern autonomy into manufacturing, IndustrialNext is bringing that same intelligence to the factory floor: autonomous factories that are cost-competitive at any scale, anywhere.\r\n\r\nBacked by Y Combinator, Khosla Ventures, Lenovo, AlphaX Partners, and Plug and Play.", "one_liner": "IndustrialNext builds the AI brain for manufacturing –…", "team_size": 9, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1648273643, "tags": [ "Hard Tech", "Robotics", "Manufacturing", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/industrial-next", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2022/industrial-next.json", "year_founded": 2021, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/industrial-next/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/f77b3fae4e9032c53ab1dabf92d2dde1c13be9a0.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": 823297, "full_name": "Lukas Pankau", "title": "Founder", "founder_bio": "Lukas was the lead electrical architect behind Ford’s Global Fusion and Edge platforms, and Tesla’s Model X, 3, and Y. In his five years at Tesla he transitioned to lead next-generation Autopilot hardware architecture and special projects in the Fremont factory focusing on autonomous manufacturing. After Tesla Lukas spend three years defining Waymo’s next-generation sensor and communications architecture. In his spare time he enjoys cooking and reading terrible fiction novels.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/lukaspankau/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/38479b451f73743db55a473805b3ee83f21261e3.jpg" }, { "user_id": 848063, "full_name": "Allen Pan", "title": "Founder", "founder_bio": "Telsa autonomous factory lead, GM advanced autonomous control engineer, Neolix chief architect. \nAn Industry veteran in industrial automation, flexible manufacturing, and autonomous driving expert, with more than 10 years of experiances", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/allen-pan/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/27a9040ee1454c91558f35f55e71cd37dc0a3098.jpg" } ], "jobs": [], "news": [ { "title": "Industrial Next wants factory robots to switch tasks in minutes, not weeks", "url": "https://techcrunch.com/2026/10/13/industrial-next-wants-factory-robots-to-switch-tasks-in-minutes-not-weeks/", "date": "Oct 13, 2026" }, { "title": "Tesla veterans’ Industrial Next picks up $12M to automate EV production – TechCrunch", "url": "https://techcrunch.com/2022/06/28/tesla-veterans-industrial-next-raises-from-to-ev-auto-factories/", "date": "Jun 28, 2022" } ], "launches": [] }, { "id": 25817, "name": "Lifecast", "slug": "lifecast", "former_names": [ "Lifecast Incorporated" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/1a29e222d654365932751024c04701eec4344d05.png", "website": "http://www.lifecastvr.com", "all_locations": "San Francisco, CA, USA; Palo Alto, CA, USA; Remote", "long_description": "We make tools for state-of-the-art 3D VR video, which fix motion sickness for a more comfortable and immersive experience. Our team's experience includes building VR cameras at Facebook, and robot perception systems at Lyft and Google X.", "one_liner": "Software to create 3D video for VR, robotics and film.", "team_size": 2, "industry": "Consumer", "subindustry": "Consumer", "launched_at": 1645743234, "tags": [ "Machine Learning", "Robotics", "Virtual Reality" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Inactive", "industries": [ "Consumer" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/lifecast", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2022/lifecast.json", "year_founded": 2021, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/lifecast", "x_url": "https://twitter.com/LifecastI", "fb_url": "https://www.facebook.com/groups/1075792393218140", "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/1a29e222d654365932751024c04701eec4344d05.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": 810885, "full_name": "Forrest Briggs", "title": "Founder", "founder_bio": "Forrest (CEO at Lifecast) has a Ph.D. in machine learning and over 20 patents in VR video and AI perception systems. He previously developed computer-vision based VR video rendering software at Facebook, and was a tech lead at Lyft and Google X working on perception systems for self-driving cars and robots.", "is_active": false, "linkedin_url": "https://www.linkedin.com/in/forrest-briggs-45b233b7/", "x_url": "https://twitter.com/LifecastI", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9547b9116f9b19edb7cbdbae2b7c39475c8f52ee.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 26072, "name": "Impossible Metals", "slug": "impossible-metals", "former_names": [ "Impossible Mining" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ea0fdeea1c74c026930139320ca3eca24d80b7f3.png", "website": "https://impossiblemetals.com", "all_locations": "Los Angeles, CA, USA", "long_description": "Impossible mining is building underwater robotics vehicles which collect battery metals from the seabed without harming the environment. We have $500M+ in off-take LoI’s and have signed a partnership with a global offshore logistics company which holds a seabed mining exploration permit. We have also built the 1st PoC underwater robotic arm.\r\n\r\nPolymetallic nodules are rocks which are rich in critical battery metals. Specially nickel, cobalt, manganese and copper. These metals are the the most expensive part of EVs.", "one_liner": "Underwater robotic vehicles that collect battery metals responsibly", "team_size": 20, "industry": "Industrials", "subindustry": "Industrials -> Climate", "launched_at": 1643398430, "tags": [ "Hard Tech", "Robotics", "Mining", "ClimateTech", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2022", "status": "Active", "industries": [ "Industrials", "Climate" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/impossible-metals", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2022/impossible-metals.json", "year_founded": 2020, "city": "Los Angeles", "country": "US", "linkedin_url": "https://www.linkedin.com/company/74093268/admin/", "x_url": "https://twitter.com/ImpossMetals", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/impossible-mining", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/ea0fdeea1c74c026930139320ca3eca24d80b7f3.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": 805125, "full_name": "Oliver Gunasekara", "title": "Founder/CEO", "founder_bio": "Early employee at Arm. Grew Arm's market share from 0% to 95%. VP, Global Head of Corporate Development. Sponsored and executing the 2006 acquisition of Falanx (Mali GPU) by Arm. Founder of the non-profit MIPI Alliance. Founded and ran NGCodec as its CEO for 7 years till its successful 5x exit to Xilinx in 2019. Founded Impossible Mining and recruited co-founders.\n\nCEO/Co-founder, Entrepreneur, Investor & Advisor in DeepTech/ClimateTech\n30+ years experience.\n", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/gunasekara/", "x_url": "https://twitter.com/OlyG", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/af46a7c94f96181d4e87cbd7254c2addd2c5b110.jpg" }, { "user_id": 812029, "full_name": "Jason Gillham", "title": "Founder", "founder_bio": "Jason is an achievement driven entrepreneur, driven by seeing positive impact to society. \n\nHis passion is solving customer problems through unique business models, technology and go to market strategies. With a passion for subsea technology, his first company, 2G Robotics (Voyis), developed an underwater laser scanner and imaging product for monitoring in the offshore energy, military and civil infrastructure markets. He led the company to a successful acquisition in January 2020.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jason-gillham-31b23824/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f0b067c16d517c5d29c62ffc31217576d05d2014.jpg" }, { "user_id": 855438, "full_name": "Renee Grogan", "title": "Founder", "founder_bio": "Renee is a sustainability expert with 16 years' experience in due diligence, pre-feasibility and feasibility, permitting, strategy, risk and community and stakeholder engagement. Her experience includes working in Australasia, the Pacific, the United States, Africa and parts of Europe. Renee has worked predominantly in the extractive resources industry, including consulting to financial institutions, resources companies, government and intergovernmental agencies, NGOs and research institutions.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/renee-grogan-a3646361/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/525e301f4d60cfe064097b877a87d73e28d5b0ce.jpg" } ], "jobs": [], "news": [ { "title": "This massive robot is designed to harvest EV metals from the ocean | FastCompany", "url": "https://www.fastcompany.com/90822101/massive-robot-ev-metals-ocean-sustainably", "date": "Dec 13, 2022" }, { "title": "Impossible Metals demonstrates its super-careful seabed mining robot", "url": "https://newatlas.com/marine/seabed-mining-robot-impossible-metals/", "date": "Dec 08, 2022" }, { "title": "Roundtable Discussion Plants Flag to Support Responsible Technology for DSM — Impossible Mining", "url": "https://impossiblemining.com/news/5u8j2o1gj2vwtzqpm3kvzzvpb4u08a", "date": "Jul 20, 2022" }, { "title": "Impossible Mining is combing the seafloor for battery metals – TechCrunch", "url": "https://techcrunch.com/2022/06/21/impossible-mining-is-combing-the-seafloor-for-battery-metals/", "date": "Jun 21, 2022" }, { "title": "Impossible Mining announces its plans to develop the world's first sustainable and responsible deep-sea mining technology — Impossible Mining", "url": "https://impossiblemining.com/news/2021/11/03/impossible-mining-announces-its-plans-to-develop-the-worlds-first-sustainable-and-responsible-deep-sea-mining-technology", "date": "Mar 28, 2022" } ], "launches": [] }, { "id": 26784, "name": "Seaflight Technologies", "slug": "seaflight-technologies", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/8a03c035eb081cba9d31fbf5316b214d8d910584.png", "website": "https://www.seaflight.tech", "all_locations": "Sydney, NSW, Australia; Torrance, CA, USA", "long_description": "Seaflight Technologies has developed a new form of Aerodynamic Flow Control for electrified aircraft that increases range and payload by 30%. That's the same performance improvement you'd get from hopping in a DeLorean to 2035 and coming back with batteries from the future. But it's available today - our tech has been derisked by testing supported by the National Science Foundation, the US Air Force, and the Australian Government. \r\n\r\nOur first product is a simple fixed-wing large cargo drone that is efficient enough to remove the \"green penalty\" currently associated with electric aviation. That's a step change from today's conventional platforms. \r\n\r\nFirst generation electric aircraft are heavy, expensive, complicated, and limited in terms of range and payload. In the entire history of aviation, that's never been a winning formula. When everyone already has access to the same batteries, materials, and motors, what really makes the difference? The answer is revolutionary aerodynamics, but in a form factor that suits today's operations and manufacturing. \r\n\r\nBeyond our own drone product line, we have partners across Aerospace helping incorporate our tech into their products. In the future, if you want to have the most efficient and cost-effective flying machine of any description, you'll need Seaflight's Flow Control inside. \r\n\r\n", "one_liner": "We make the world's most efficient aircraft", "team_size": 4, "industry": "Industrials", "subindustry": "Industrials -> Aviation and Space", "launched_at": 1659334578, "tags": [ "Robotics", "Airplanes", "Logistics", "Climate", "Transportation" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2022", "status": "Active", "industries": [ "Industrials", "Aviation and Space" ], "regions": [ "Australia", "United States of America", "Oceania", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": [ { "question": "How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)", "answer": "Graham \"Myself and Will Sutton built the first prototypes in our garages, this was before we even got into YC. Some bits of plane are still in there. We were obsessed with the idea that if you could make an electric plane just dramatically more efficient using aerodynamics, then you'd start to get the range that'll make it viable so much sooner than anyone expects. Then it'll take on that air of inevitability that happened with cars as soon as the Model S arrived\"    " }, { "question": "What's the history of your company from getting started until the present day? What were the big inflection points?", "answer": "Seaflight originally started out by developing “wingships”, ultra-low altitude craft that fly just a few ft above the waves for extra efficiency. After 6 prototypes and a series of record-breaking flights in Australia, the performance and market data wasn’t adding up, **so the company undertook a pivot.** With backing from the National Science Foundation and the US Air Force we developed our Aerodynamic Flow Control and immediately felt stronger pull from customers for our ultra-efficient cargo drone - one that can operate from any short airfield, anywhere. The Australian Government has funded our $2m project to develop a full flight demonstrator of our cargo drone by 2026, which will also serve as our first saleable product to early adopters in Defense and commercial operators. " }, { "question": "What is your long-term vision? If you truly succeed, what will be different about the world?", "answer": "Imagine a world where literally all short distance flight is electrified, quiet, direct, and low cost. Taking advantage of cutting-edge high lift technologies that we have government funding to develop, a much broader range of applications is on the horizon as we aim to be a global leader in large capacity drones as well as a high-value developer of key tech that can be used by every company pursuing electrified flight. We aim to show it’s possible \\*now\\* to cut costs, cut emissions, cut time, and cut worries globally with electric flight that is focused on extreme efficiency, not crazy complexity." } ], "url": "https://www.ycombinator.com/companies/seaflight-technologies", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2022/seaflight-technologies.json", "year_founded": 2022, "city": "Sydney", "country": "AU", "linkedin_url": "https://www.linkedin.com/company/seaflight-technologies", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/8a03c035eb081cba9d31fbf5316b214d8d910584.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/636ce8f3dca71a667390405d8a8afd5754714e0e.png" ], "primary_partner": { "name": "Jared Friedman", "url": "https://www.ycombinator.com/people/jared-friedman" }, "founders": [ { "user_id": 881099, "full_name": "Graham Doig", "title": "Founder", "founder_bio": "Graham Doig, founder/CEO of Seaflight Technologies, has >18 years experience across aerospace and automotive, and in academia with over 90 technical papers to his name as a Lockheed Martin-endowed professor. After his PhD on the aerodynamics of low altitude flight, he led the aero/range team at EV startup Canoo from early through SPAC, and conducted funded research programs with NASA, Tesla, and Joby Aviation. He designed 2 solar-electric vehicles which set international land speed records. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/graham-doig/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a31c91732204ac6b1751cdf7365ad61022f47494.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 65921, "title": "Seaflight ✈️ We make the world's most efficient airplanes", "tagline": "We use aerodynamic magic to make electric aircraft good enough to take over aviation", "body": "Hi everyone, Graham here, founder at Seaflight Technologies. We developed an aerodynamic technology for any fixed-wing aircraft that makes it possible to carry more payload, over longer distances - perfect for electric aviation to overcome the limitations of today’s batteries. Our first product is a large cargo drone called AURAE. \n\n![uploaded image](/media/?type=post&id=65921&key=user_uploads/881099/5f0e8973-d450-4958-aff1-e4820d36eae7)\n\n\n### **BATTERIES ARE NOT VERY GOOD**\n\nAviation is incredibly hard to decarbonize, and first generation electric aircraft are proving to be heavy, expensive, complicated, and limited in range. That formula has never been successful in the history of aviation. Could we just wait for better batteries? Not great - emissions keep rising, and progress is incremental - a few % improvement each year means a few % more range... What about better motors, or lighter structures? There’s a few % still on the table there too, sure.\n\nBut if you could _double_ the aerodynamic efficiency, you could double the range that’s possible with today’s batteries. \n\nSeaflight uses Aerodynamic Flow Control. It’s tech that suits today’s operations, manufacturing approaches, and form factors, and we’ve de-risked it to the point where it’s ready to fly. \n\n### **CONTROL THE AIR**\n\n**Thanks to over $2m in backing from the National Science Foundation, the US Air Force, and the Australian Government**, we’ve been able to develop and test our Aerodynamic Flow Control - an active system that pulls more air over the wing when we need it (takeoff and landing), but otherwise adds almost no mass or drag to the aircraft (unlike adding extra propulsion). \n\nBecause we triple the lift only when we need it, we can have smaller wings. Smaller wings mean less drag in cruise, which means much less energy used. \n\n**This is key enabling technology to make electric flight viable.** \n\nOur upcoming large scale flight demonstrator will take to the skies over Australia in early 2026, with a production version to follow. \n\nBest of all, this is universal technology. Every plane has wings… Seaflight’s tech can go on every plane. \n\n![uploaded image](/media/?type=post&id=65921&key=user_uploads/881099/4b0649c0-2cb1-47d2-900d-a8b8791842cf)\n\n\n### **HOW DID WE GET HERE**\n\nWill Sutton and Graham Doig founded Seaflight Technologies heading into the S22 batch. We originally worked on ultra-low-altitude “ground effect” flight. After 6 prototypes and a series of world-first flight achievements, we realized the numbers didn’t add up to viable economics. After pivoting to aerodynamic flow control and developing the new IP, including a test campaign at Caltech, it’s time to make the AURAE flight demonstrator a reality and break some world records for electric flight. \n\n### **About the founder :**\n\nGraham Doig has a PhD in aerodynamics and has worked on electric mobility for 19 years, including 2 world land speed records. He led the aero/range team at EV startup Canoo, and was a Lockheed Martin-endowed professor of engineering in a past life, working on projects with the likes of Tesla and NASA. \n\n### **Lastly, Asks 🙏**\n\nDo you know anyone involved in **logistics** that has already been looking at or using drone technology?\n\nDo you know any **wizards in electric or autonomous mobility** who are looking for a bonkers new professional challenge?", "url": "https://www.ycombinator.com/launches/H9F-seaflight-we-make-the-world-s-most-efficient-airplanes", "votes": 39, "created_at": "2022-09-08T07:48:51.950Z" } ] }, { "id": 26883, "name": "Hedgehog", "slug": "hedgehog-2", "former_names": [ "Hedgehog Agriculture" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cefd49e2f001817fd856853325f328d68d72bfa7.png", "website": "http://hedgehogfoods.com", "all_locations": "San Francisco, CA, USA", "long_description": "Hedgehog builds robotic mushroom farms. Our robots eliminate labor and our AI optimizes grow conditions to increase yield. We’ll soon grow mushrooms and fungi for <1/3rd the cost of leading growers. \r\n\r\nFungi may address our food system’s biggest problems: they transform agricultural waste into protein-rich foods with near-zero environmental impact. Hedgehog’s technology is unleashing fungi as our next major food source.", "one_liner": "Building robotic mushroom farms", "team_size": 50, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1659119457, "tags": [ "Robotics", "Climate", "Food Tech", "Agriculture", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2022", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/hedgehog-2", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2022/hedgehog-2.json", "year_founded": 2022, "city": "San Francisco", "country": "US", "linkedin_url": "", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/cefd49e2f001817fd856853325f328d68d72bfa7.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": 995535, "full_name": "Jamie Balsillie", "title": "Founder", "founder_bio": "Jamie is a co-founder of Hedgehog, building robotic mushroom farms. He previously founded Indigo Carbon, the largest agriculture carbon credit platform. He joined Indigo Agriculture pre-revenue and helped scale sales to >$250m as GM of two new business units. Before Indigo, he worked in software and food at McKinsey & Co. In June 2022, Jamie graduated from Stanford's MBA.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jamie-balsillie/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5aa2163395da235b872c74cafa583fc7ef5b1e0b.jpg" }, { "user_id": 953786, "full_name": "Wilson Ruotolo", "title": "Founder", "founder_bio": "Wilson Ruotolo is a co-founder of Hedgehog, where he designs robotics for mushroom production. He received his PhD from Stanford, studying the design of robotic hands. He collaborated with NASA on end-effectors for martian exploration and his prototypes have been used to retrieve artifacts off the Mediterranean seafloor. He has first author publications in multiple journals, including Science Robotics, and his work is featured in TechCrunch, Popular Science, and Spotify’s Soft Robotics podcast.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/wilson-ruotolo-679a6697/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/57aabf53f1d51058462c50a0b5e4664dc4cd9ebe.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 65014, "title": "🍄 Hedgehog - Robotic mushroom farms", "tagline": "Growing mushrooms & fungi for 1/3rd cost.", "body": "**tl;dr** Hedgehog builds robotic farms that grow mushrooms and fungi for 1/3rd the cost. Fungi produce protein-rich foods with near-zero environmental impact. Our tech is unleashing them as our next major food source.\n\nHey everyone! We’re Jamie & Wilson, co-founders of Hedgehog.\n\n**Opportunity: Fungi - our next major food source?**\n\n![uploaded image](/media/?type=post&id=65014&key=user_uploads/995535/6274e56c-e42e-41de-97aa-a0e6bc59c109)\n\nFungi are unique crops. They transform agricultural waste (corn husks, wheat straw, etc.) into protein-rich, meaty-tasting food. And they do it without arable land, irrigation, or energy intensive lighting. With 30% of global greenhouse gas emissions coming from food, this is an opportunity we must seize. Fungi are our chance to produce quality food at scale with near-zero environmental impact.\n\n**Problem: They’re labor intensive** \\\nUnfortunately, producing mushrooms and fungi is labor intensive, limiting their scale and affordability. For even the most sophisticated mushroom and fungi farms, labor is the vast majority of cost. They require delicate handling and careful monitoring – difficult jobs to automate.\n\n**Solution: Robots** \\\nOh yeah. Robots. We’re building robotics and AI to automate each step of production. Autonomous dexterous manipulation harvests, breaks down, and packages the mushrooms. Computer vision and low-cost sensors power decisions like when to harvest. AI optimizes >60 dimensions to increase yield. Eliminating labor and increasing yield will reduce costs by 70%+.\n\n \n\n\\*\\*How you can help:\\*\\*\\\nWe aim to unleash fungi as our next major food source, making these healthy, sustainable foods affordable for anyone. If you’re interested in helping out, we’d love to meet:\n\n* A+ talent in robotics and ML\n* Mushroom growers\n\nReach out at [hello@hedgehogfoods.com](mailto:hello@hedgehogfoods.com)\n\nJamie & Wilson\\\n🦔", "url": "https://www.ycombinator.com/launches/Guc-hedgehog-robotic-mushroom-farms", "votes": 272, "created_at": "2022-07-29T22:20:01.173Z" } ] }, { "id": 27361, "name": "Polymath Robotics", "slug": "polymath-robotics", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0d6f5a2035d19900b2a4411b03d2c1998b0aaa5e.png", "website": "http://www.polymathrobotics.com", "all_locations": "San Francisco, CA, USA", "long_description": "Polymath is building a general autonomy stack for cautious vehicles. Our software allows any industrial vehicle - whether it's a tractor in a field or a bulldozer in a mine, drive itself. 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The Robot Report", "url": "https://www.therobotreport.com/polymath-robotics-to-share-lessons-learned-at-a-saas-based-startup-at-robobusiness/", "date": "Aug 14, 2024" } ], "launches": [ { "id": 65002, "title": "📍 Polymath Robotics: plug & play autonomy for industrial vehicles", "tagline": "Polymath lets you easily add autonomy to any industrial vehicle, and build your own applications via Rest API.", "body": "Hey, we’re Stefan & Ilia, founders of Polymath Robotics.\n\n**Polymath makes autonomy software for industrial vehicles.**\n\nToday we’re excited to introduce **Caladan**: a set of simulated vehicles & environments you can use to build autonomous industrial vehicle applications via Rest API.\n\n### **The problem**\n\nBuilding an autonomous industrial vehicle is a multiyear, multimillion-dollar project. Just getting a vehicle to drive itself reliably takes 6 months of engineering effort at a minimum. Even then, the autonomy itself is often buggy and unreliable, and impossible to transfer across different vehicle types.\n\nAs a result, many autonomy companies run out of steam before they even have a reliably-working product … let alone product-market fit.\n\n### **Our solution: general autonomy software**\n\nPolymath software handles generalized basic autonomy — in other words, **driving around and not hitting stuff** — for any industrial vehicle in a controlled environment. That means autonomous industrial vehicle companies can have an autonomous vehicle on day 1.\n\nSince we’re _just_ working on autonomy, we can focus on making the system **stable and reliable.** No more battling with weird controls issues or buggy obstacle detection.\n\n### Caladan: build on Polymath autonomy in simulation\n\nCaladan makes it easy to build autonomous vehicle behaviors in sim. The tool is a set of simulated vehicles & environments you can use to interact with Polymath autonomy via Rest API.\n\nThat means you can program custom autonomous vehicle behaviors and applications using Python, not ROS. And when you’re ready, whatever you’ve built in Caladan can seamlessly transition to a physical vehicle.\n\n### Product demo / example application\n\nHere’s an example application you could build with Caladan (you can download the example code [here](https://github.com/polymathrobotics/caladan_examples)).\n\n\n\nThe free version of Caladan comes with a simulated farm environment or simulated port environment. You can also reach out to us about a custom environment & vehicle in Caladan.\n\n### **Does Polymath autonomy work for my vehicle/use case?**\n\nPolymath autonomy is limited to industrial vehicles in closed environments, since the system will stop immediately if there’s trouble, and fall back on teleoperation in hazardous situations.\n\n**Use case examples:** ⛏ Mining trucks • 🚜 Agricultural vehicles • 🌲 Logging trucks • ✈️ Ground support equipment at airports • 🚢 Yard trucks\n\n### **Can I try it?**\n\nHeck yeah. You can try Caladan for free by signing up [here](http://polymathrobotics.com/product).", "url": "https://www.ycombinator.com/launches/GuQ-polymath-robotics-plug-play-autonomy-for-industrial-vehicles", "votes": 67, "created_at": "2022-07-29T15:56:38.207Z" } ] }, { "id": 28112, "name": "Persist AI", "slug": "persist-ai", "former_names": [ "Persist AI", "Persist AI Formulations Corp" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/eeb1e38a6ca6e6061c101deae73f22c28c142596.png", "website": "http://www.persist-ai.com", "all_locations": "Sacramento, CA, USA", "long_description": "It takes 5 years for pharma to develop long lasting drug injections for chronic diseases like cancer and diabetes. Persist uses AI-driven automation to reduce formulation development time down to 2 years, a ~50% reduction.", "one_liner": "Developing long-lasting drug formulations 50% faster", "team_size": 6, "industry": "Healthcare", "subindustry": "Healthcare -> Drug Discovery and Delivery", "launched_at": 1671420729, "tags": [ "Machine Learning", "Robotics", "Microfluidics", "Nanotechnology", "Therapeutics" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2023", "status": "Active", "industries": [ "Healthcare", "Drug Discovery and Delivery" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": true, "demo_day_video_public": true, "app_answers": [ { "question": "Describe what your company does in 50 characters or less.\n", "answer": "Help pharma develop slow release drugs faster" }, { "question": "What is your company going to make? Please describe your product and what it does or will do.\n", "answer": "For a pharma company to develop a sustained-release (slow release) drug formulation takes about 3-5 years and $10M or more. This is because there are a lot of variables and scientists' intuition (aka guesswork) needed to arrive at the final formulation solution.\r\n\r\nWe will provide a service to pharma companies to develop their formulations for them 50% faster and cheaper than current methods. To do this we will screen formulations in high throughput using automation and train ML which can make better predictions based on data (rather than guesses).\r\n\r\nThis will enable pharma companies to get drugs to market faster and earn revenue sooner." } ], "question_answers": null, "url": "https://www.ycombinator.com/companies/persist-ai", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2023/persist-ai.json", "year_founded": 2022, "city": "Sacramento", "country": "US", "linkedin_url": "https://www.linkedin.com/company/persist-ai/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/eeb1e38a6ca6e6061c101deae73f22c28c142596.png", "app_video_url": "https://bookface-images.s3.us-west-2.amazonaws.com/bf-public_profile/28167/app_video.mp4?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAQC4NIECAOMAGS7ZB%2F20261020%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20261020T022712Z&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=c66d7d91c1532ade147f60b6506c8084f0b87596e1d90190def0886579506001", "dday_video_url": "https://bookface-images.s3.us-west-2.amazonaws.com/video_event/60/1680881229067-tn5frveent9-fbed84ada9379d7720a00b6d13e1f184/ba402ea2758b4d68f29d058ba99cd408.mp4?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAQC4NIECABPQ2AHNW%2F20261020%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20261020T022712Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&X-Amz-Signature=69e456b3a0e858aa28c02639034baef60514627411b140d9fa05f425a7d41c39", "company_photos": [], "primary_partner": { "name": "Jared Friedman", "url": "https://www.ycombinator.com/people/jared-friedman" }, "founders": [ { "user_id": 1094851, "full_name": "Karthik Raman", "title": "Founder", "founder_bio": "When mom got brain cancer, I used to take her for her \"infusions\". \n\nFor 4 hours, we would sit there while drug was being infused into her veins and she had horrible nausea and hair loss.\n\nI built Persist to eradicate this horrible experience for future patients. \n\nWe package drugs so that patients take 1 injection per month or year, without an infusion. This lowers the overall dose the patient receives (reducing side-effects), improves compliance, and quality of life. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/karthik-raman-scientist/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ecc2a524e445309696a536435506c40bc98010ac.jpg" }, { "user_id": 1114143, "full_name": "Christopher Shelner", "title": "Founder", "founder_bio": "Career program manager, first time founder. Focus has been in electronics, automation, and manufacturing. Super excited to be part of the YC batch! ", "is_active": true, "linkedin_url": "http://www.linkedin.com/in/christophershelner/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/25ae4aac51df1a910d1efc90c169f83830fc6913.jpg" } ], "jobs": [], "news": [ { "title": "Beyond the $12M: Revolutionizing Drug Formulation Development at Persist AI", "url": "https://www.persist-ai.com/post/beyond-the-12m-revolutionizing-drug-formulation-development-at-persist-ai", "date": "May 19, 2025" }, { "title": "Persist AI Raises $4M in Seed Financing to Revolutionize Drug Formulation ", "url": "https://www.persist-ai.com/post/persist-ai-raises-4m-in-seed-financing-to-revolutionize-drug-formulation", "date": "Aug 04, 2023" } ], "launches": [ { "id": 69239, "title": "Persist - We build long-lasting drugs 50% faster 💊", "tagline": "Drug formulations made by robotics and designed by AI", "body": "### **TLDR**\n\nPersist helps pharma make drug injections that last up to 1 year. \n\nUsing robotics & AI, we reduce a 5-year drug formulation process to \\~2 years.\n\n**Contact Us (**[**founders@persist-ai.com**](mailto:founders@persist-ai.com)**) for a case-study formulation**\n\nTo make injections we encapsulate drugs inside injectable microspheres made with FDA-approved materials.\n\n![uploaded image](/media/?type=post&id=69239&key=user_uploads/1094851/19542a20-d5f0-4ccd-9450-d6b8427a6b94)\n\n**_Left:_** _Image of a \\~37 um microsphere made by our robotics_\n\n**_Right:_** _A Schematic showing how encapsulated drugs are released over 1 year so patients don’t take as many injections._\n\n### 🤔**THE PROBLEM**\n\nFor chronic diseases, most patients prefer 1 injection/yr rather than multiple injections per week.\n\nHowever, making a long-lasting injection takes a lot of trial and error and the time between iterations is long.\n\nKey challenges include:\n\n* **Using manual work & intuition is slow**: Typical teams manually mix and match chemicals to optimize the amount of drug that’s loaded into the spheres and the rate of release of drug\n* **Trial and error is cumbersome:** Because changing one variable may have multiple effects \n* **Scale-up is unpredictable:** Even if something works at a small scale, batch-to-batch consistency during scale-up is uncertain because production is done in large reactors\n\n### 💡**OUR SOLUTION**\n\nWe utilize custom robotics and AI to solve the problems with building microspheres. \n\n* **We automatically mix & optimize formulations:** We use a closed-loop robotics + AI approach so there’s minimal manual work\n* **We reduce trial & error with AI predictions:** We generate 50x more data than most formulation teams and use that data to train AI. This unique data enables us to make better predictions than others.\n* **We build small batches, faster:** So we can QC batches more frequently and scale up predictably\n\n### ❤️**OUR ASKS**\n\nIntroduce us to friends who work in Pharma. Email [founders@persist-ai.com](mailto:founders@persist-ai.com) \n\n“Follow” us [on LinkedIn](https://www.linkedin.com/company/persist-ai/)", "url": "https://www.ycombinator.com/launches/I0l-persist-we-build-long-lasting-drugs-50-faster", "votes": 36, "created_at": "2023-02-13T16:43:58.890Z" } ] }, { "id": 29185, "name": "Relari", "slug": "relari", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d8724ca6da40d81a8aadbd3cf9cf5fbaa58ac997.png", "website": "https://www.relari.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Relari is a robotics research company developing new ways for robots to learn dexterous manipulation from humans. We combine video with rich, scalable biomechanical data—including electromyography (EMG), motion, force, and touch—to train robotics foundation models for more capable, human-like manipulation.", "one_liner": "Building dexterous robots that learn from human biomechanics", "team_size": 4, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1709879960, "tags": [ "Robotics" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2024", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/relari", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/relari.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/relari", "x_url": "https://x.com/relariai", "fb_url": null, "cb_url": null, "github_url": "https://github.com/relari-ai/", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/d8724ca6da40d81a8aadbd3cf9cf5fbaa58ac997.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/23fd0aa60eb175a501ea1228afb056d31d6dc5bf.png" ], "primary_partner": null, "founders": [ { "user_id": 983988, "full_name": "Yi Zhang", "title": "Founder", "founder_bio": "Co-Founder & CEO of Relari. Previously building autonomous cars & trucks at Pony.ai and warehouse robots at Dexterity.ai. Harvard MBA.", "is_active": true, "linkedin_url": "https://linkedin.com/in/yizhang0123", "x_url": "https://twitter.com/Yiszzzz", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d055e5f1485a40abcce6e3419a1108537fecd4a4.jpg" }, { "user_id": 1884040, "full_name": "Pasquale Antonante", "title": "Founder", "founder_bio": "Co-Founder & CTO of Relari. I have a PhD from MIT focusing on the reliability of complex AI systems such as autonomous cars. Previously at NVIDIA and Raytheon Technologies (previously United Technologies).", "is_active": true, "linkedin_url": "https://linkedin.com/in/pasquale-antonante-5306524a", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/45803c3461bd6b70f33bfa7b9c35a577b4825f7d.jpg" } ], "jobs": [ { "id": 106785, "title": "Research Engineer, Robot Learning", "url": "https://www.ycombinator.com/companies/relari/jobs/vZgIE15-research-engineer-robot-learning", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$125K - $175K", "equity_range": "0.25% - 2.00%", "experience": "3+ years", "visa": "Will sponsor", "skills": [] }, { "id": 106811, "title": "Research Engineer, Human Biomechanics", "url": "https://www.ycombinator.com/companies/relari/jobs/xoRkCNW-research-engineer-human-biomechanics", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Science", "role_type": "Research", "salary_range": "$125K - $175K", "equity_range": "0.25% - 2.00%", "experience": "3+ years", "visa": "Will sponsor", "skills": [] }, { "id": 106812, "title": "Hardware Engineer", "url": "https://www.ycombinator.com/companies/relari/jobs/CLokIVv-hardware-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Hardware", "salary_range": "$125K - $175K", "equity_range": "0.25% - 2.00%", "experience": "3+ years", "visa": "Will sponsor", "skills": [] }, { "id": 106813, "title": "Software Engineering Intern", "url": "https://www.ycombinator.com/companies/relari/jobs/WfW1xjj-software-engineering-intern", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$40 - $60 / hourly", "equity_range": "", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [] }, { "id": 106814, "title": "Data Operations Lead", "url": "https://www.ycombinator.com/companies/relari/jobs/pjJ1WLP-data-operations-lead", "location": "San Francisco, CA, US / Remote", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "$100K - $150K", "equity_range": "0.25% - 1.00%", "experience": "3+ years", "visa": "Will sponsor", "skills": [] } ], "news": [], "launches": [ { "id": 91726, "title": "Nuvi – The AI Agent Builder for Software 3.0", "tagline": "Write specs in natural language. Get working agents. It’s that simple.", "body": "![uploaded image](/media/?type=post&id=91726&key=user_uploads/983988/7e12281e-7f3b-4f82-b803-dd815931d5c8)\n\n### **TL;DR**\n\nEveryone wants to build AI agents. But doing it right is still way too hard.\n\nYou can build a website with natural language in tools like Lovable. But if you want to build AI agents, you're stuck dragging blocks or writing code.\n\n[**Nuvi**](https://www.nuvi.dev) is the AI agent builder for Software 3.0: Write specs in plain English. Get testable, verifiable behavior — out of the box.\n\n---\n\n## **❌ The Problem**\n\nBuilding AI agents still means building behavior manually — whether you’re writing code, dragging blocks, or tweaking prompts.\n\n* **Tools like n8n** let you create agents without code, but you’re still wiring up logic step by step.\n* **Tools like Cursor** help you code faster, but you still need to know what code to write.\n\nAt the same time, **tools like Lovable have shown what’s possible with natural language** — you can build and launch a polished UI in minutes.\n\nKarpathy called it years ago: _“English is the hottest new programming language.”_ But while we’ve embraced it for websites and weekend projects, there’s still no reliable Lovable for building AI agents.\n\n**Intelligent software still lacks a way to go from natural language to tested, trusted behavior.**\n\nWe need a system where intent becomes implementation — with structure, simulation, and shared understanding built in.\n\n---\n\n## **🎯 The Solution: Nuvi**\n\nNuvi lets anyone define, build, and deploy intelligent agents using natural language — with the **structure and guarantees** of real software development.\n\nWhat makes us different:\n\n🧠 **All in Natural Language**\n\nIf you can explain what you want, Nuvi helps you build it. No coding, no frameworks, no LLM know-how required.\n\n![uploaded image](/media/?type=post&id=91726&key=user_uploads/983988/e8536123-efac-4c99-8924-a3798a077a15)\n\n**🤝 Built for Collaboration**\n\nSpecifications are readable, editable, and versioned — so people across different teams stay aligned.\n\n![uploaded image](/media/?type=post&id=91726&key=user_uploads/983988/2b0f6f88-9d1d-473b-8e76-6e8c3ad190eb)\n\n🧪 **Fully Tested by Default**\n\nUser stories become behavioral tests. You can simulate how your agent behaves _before_ launch — and continuously validate after. Using only language.\n\n![uploaded image](/media/?type=post&id=91726&key=user_uploads/983988/d18df70f-0181-4ec0-83f0-208bab3379aa)\n\n⚙️ **One-Click Deployment**\n\nClick to deploy. Built-in access control and integrations mean you go from idea to agent in minutes.\n\n![uploaded image](/media/?type=post&id=91726&key=user_uploads/983988/7c089cfe-87e5-44c6-9472-e81963a1431f)\n\n---\n\n## **✅ Nuvi Agents at Work**\n\nAgents built with Nuvi are already transforming how real work gets done — here are a few examples:\n\n* A legal SaaS company built a custom BDR agent that scans hundreds of court filings daily, flags high-complexity cases, and drafts tailored outreach directly in HubSpot.\n* A mortgage brokerage built a fulfillment agent that processes messy loan documents, checks them against underwriting rules, and saves hours of manual review on every application.\n* An international nonprofit built an AI coach that interviews underserved small business owners, generates detailed financial forecasts, and dramatically scales personalized support.\n\n---\n\n## **💡Our Secret sauce: Specification-as-Source**\n\nIn his recent AI Startup School keynote, Andrej Karpathy revamped the idea of **Software 3.0** — where we write software using English instead of code.\n\nBut English alone isn’t a programming language. If it were, we wouldn’t have invented C or Python. For English to work as code, it needs structure (but we can now relax how much structure we need). That’s what Nuvi provides.\n\n**🧠 1. AI Specification Assistant**\n\nDescribe the agent in plain English. Nuvi helps you clarify goals, cover edge cases, and remove ambiguity — like a linter for intent.\n\n**🧾 2. Specification-as-Source**\n\nThe spec _is_ the agent’s source code. It’s structured, complete, and readable by both humans and machines.\n\n**⚙️ 3. One-Click Agent Compilation**\n\nWe compile your spec into a live agent. Just like devs once implemented PRDs — but this time, the AI does it.\n\n**🧪 4. Simulation & Continuous Testing**\n\nUser stories become test cases. You can simulate the agent’s behavior before launch — and verify it keeps working after.\n\nNuvi is the behavioral compiler for Software 3.0. Not another prompt wrapper. Not another no-code toy. Real behavior. From real specs. Written in plain English.\n\n---\n\n## **🙌 Our Ask**\n\n* Try Nuvi and build your first agent — all in plain English.\n* Want to join the mission, collaborate, or write about us? Reach out at [nuvi.dev](https://www.nuvi.dev/)", "url": "https://www.ycombinator.com/launches/NrS-nuvi-the-ai-agent-builder-for-software-3-0", "votes": 17, "created_at": "2025-06-30T16:10:38.865Z" }, { "id": 79322, "title": "Relari - Testing and simulation stack for GenAI systems", "tagline": "Relari helps AI teams simulate, test, and validate complex GenAI applications throughout the development lifecycle.", "body": "# **TL;DR**\n\n[Relari](https://www.relari.ai/) is an open-source platform to simulate, test, and validate complex Generative AI (GenAI) applications. With 30+ open-source metrics, synthetic test-set generators, and online monitoring tools, we help AI app developers achieve a high degree of reliability in mission-critical use cases such as compliance copilot, enterprise search, financial assistance, etc.\n\n# **⭐ Meet the Relari Team**\n\nHi everyone, [Yi](https://www.linkedin.com/in/yizhang0123/) and [Pasquale](https://www.linkedin.com/in/pasquale-antonante-5306524a/) from [Relari](https://www.relari.ai/) here. We both spent years building safety-critical AI applications, particularly in autonomous driving and robotics. Pasquale has a PhD from MIT where he researched fault detection in complex AI systems. Yi has an MBA from Harvard and led multiple AI products from concept to production including robo-taxis, self-driving trucks, and warehouse robots.\n\n![uploaded image](/media/?type=post&id=79322&key=user_uploads/983988/a8982b08-9cda-4741-bc17-eb3df31679e1)\n\n# **💡 Our Inspiration: Autonomous Vehicles**\n\nJust like autonomous vehicles promise to change how we move, GenAI applications promise to revolutionize the way we work. However, ensuring these systems are safe and reliable requires a shift in the development process. Autonomous vehicles need to drive billions of miles to ensure that they are safer than human drivers. This would take decades, so the industry relies on simulation and synthetic data to efficiently test and validate each iteration of the self-driving software stack.\n\nWe see a strong parallel in the world of GenAI. At [Relari.ai](https://www.relari.ai/), we are building towards a future where a similar infrastructure will enable complex and powerful applications based on large language models (LLMs).\n\n# **🔴 Problem: GenAI Apps are Unreliable**\n\nLLM-based applications can be inconsistent and unreliable. This blocks GenAI’s adoption in mission-critical workflows and hurts user confidence and retention once deployed to production. Good testing infrastructure is paramount to achieving the quality users demand, but GenAI app developers across startups and enterprises struggle to define the right set of tests and quality-control standards for deployment.\n\nThe main challenges the AI teams face are:\n\n* **Complex Pipelines:** GenAI pipelines are getting increasingly more complex and it is often difficult to pinpoint where problems originate.\n* **Gap from Evaluation to Reality:** There is a huge gap between the metrics used in offline evaluation and user feedback, leading to distrust in offline evaluation results.\n* **Lack of Relevant Datasets:** Public datasets are overfitted by models and often not relevant to specific applications. However, manual curation of custom datasets is extremely time-consuming and costly.\n\n# **🚀 Solution: Harden AI Systems with Simulation**\n\nRelari offers a complete testing and simulation stack for GenAI pipelines designed to directly address the problems above. Relari allows you to:\n\n* **Pinpoint problem root causes with modular evaluation:** Define your pipeline and flexibly orchestrate modular tests to quickly analyze performance issues. Our open source framework offers 30+ metrics covering text generation, code generation, retrieval, agents, and classification with more coming soon.\n\n ![uploaded image](/media/?type=post&id=79322&key=user_uploads/983988/04a313af-1bb9-4469-a9d3-4f89c5132aa5)\n\n* **Simulate user behavior with close-to-human evaluators:** Leverage user feedback to train custom evaluators that are 90%+ aligned with human evaluators (backed by our research). Introduce a feedback loop connecting your production system and the development process.\n\n ![uploaded image](/media/?type=post&id=79322&key=user_uploads/983988/908218e2-4462-43d5-a23d-7c005c927a29)\n\n* **Accelerate development with synthetic data:** Generate large-scale synthetic datasets tailored to your use case and stress test your AI pipeline. Ensure coverage of all the corner cases before shipping to users.\n\n ![uploaded image](/media/?type=post&id=79322&key=user_uploads/983988/d78bb49e-ec9d-4519-909b-b46532751380)\n\n\n# **❤️ Our Ask**\n\n* ⭐ Star us on Github ([link](https://github.com/relari-ai/continuous-eval))\n* 📅 Book a demo with us ([link](https://cal.com/pasquale/relari-demo))\n* 👉 Introduce us to AI / ML / Data Science teams building mission-critical GenAI applications ([founders@relari.ai)](mailto:founders@relari.ai)", "url": "https://www.ycombinator.com/launches/KdO-relari-testing-and-simulation-stack-for-genai-systems", "votes": 75, "created_at": "2024-03-12T17:42:49.322Z" } ] }, { "id": 29241, "name": "Tekton Dynamics", "slug": "tekton-dynamics", "former_names": [ "MAIHEM", "Maihem" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c88f8c82a6ce22ef99621a0f594acb23ef6aa48f.png", "website": "https://www.tekton-dynamics.com", "all_locations": "London, England, United Kingdom", "long_description": "Our mission is to empower every manufacturer, no matter their scale, to invent and build anything using intelligent robots.\r\n\r\nToday’s industrial robots are fast but \"blind\". They struggle with any task that isn't perfectly repetitive. We are building the eyes and brain (a proprietary vision system and AI model) that allow industrial robots to see, reason, and perform complex work with sub-millimeter accuracy and the adaptability of a human expert.\r\n\r\nWe are witnessing the start of a new industrial revolution: an era of advanced manufacturing powered by AI and robotics. We aim to lead this shift by putting these tools into the hands of every manufacturer, ensuring the power to invent and build at scale isn’t a privilege of the few.", "one_liner": "AI control layer for welding robots", "team_size": 3, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1706234384, "tags": [ "Robotics", "Manufacturing", "AI", "Industrial" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2024", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "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/tekton-dynamics", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/tekton-dynamics.json", "year_founded": 2023, "city": "London", "country": "GB", "linkedin_url": "https://www.linkedin.com/company/maihem/", "x_url": "https://x.com/maihem_ai", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/maihem", "github_url": "https://github.com/maihemlabs/", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/c88f8c82a6ce22ef99621a0f594acb23ef6aa48f.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": 1616651, "full_name": "Max Ahrens", "title": "Founder/CEO", "founder_bio": "Max is the Founder & CEO of Tekton Dynamics. He did his PhD and Postdoc in Machine Learning at the University of Oxford. During his Postdoc, he was also the Project Leader of a +$500,000 research grant which he was awarded by the Alan Turing Institute and the British Ministry of Defence. Previously, he worked as a consultant with McKinsey.", "is_active": true, "linkedin_url": "https://linkedin.com/in/maximilianahrens", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/80bef22695b3397da58980f1c3ebd03912d55d75.jpg" } ], "jobs": [ { "id": 96215, "title": "General Application", "url": "https://www.ycombinator.com/companies/tekton-dynamics/jobs/wfu5lO9-general-application", "location": "London", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "£75K - £180K GBP", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 96216, "title": "Founding Engineer", "url": "https://www.ycombinator.com/companies/tekton-dynamics/jobs/knCVBh5-founding-engineer", "location": "London", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "£100K - £150K GBP", "equity_range": "0.50% - 2.00%", "experience": "3+ years", "visa": "US citizenship/visa not required", "skills": [ "Python", "Machine Learning", "Deep Learning", "Computer Vision", "CAD Design" ] } ], "news": [], "launches": [] }, { "id": 29257, "name": "Tuesday Labs", "slug": "tuesday-labs", "former_names": [ "Adagy Robotics", "Tuesday Lab" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/bb7c6f660a8e21354833989c609687d7125a07b0.png", "website": "https://www.tuesdaylabs.com", "all_locations": "New York City, NY, USA", "long_description": "Tuesday makes delightful robots that tidy your home for you", "one_liner": "Delightful robots", "team_size": 7, "industry": "Consumer", "subindustry": "Consumer -> Consumer Electronics", "launched_at": 1706678921, "tags": [ "Robotics", "Consumer", "Gaming", "Electronics", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2024", "status": "Active", "industries": [ "Consumer", "Consumer Electronics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/tuesday-labs", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/tuesday-labs.json", "year_founded": 2023, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/tuesdaylabs/", "x_url": "https://x.com/roboticscorp", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/bb7c6f660a8e21354833989c609687d7125a07b0.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": 1151107, "full_name": "Rosalind Shinkle", "title": "Founder/CEO", "founder_bio": "Ros is the founder and CEO of Tuesday Labs. Before starting Tuesday, Ros was a Staff Robotics Engineer at Boston Dynamics, where she worked on the Spot Manipulation team. At Boston Dynamics, Ros engineered the algorithms that tell the Spot arm how to interact with the world, e.g. how to inspect manufacturing lines and place sensitive objects. Ros has a BSE in Mechanical Engineering and Applied Mechanics and a Master’s in Robotics from UPenn.", "is_active": true, "linkedin_url": "https://linkedin.com/in/rosalind-shinkle", "x_url": "https://twitter.com/ros_shinkle", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/480b24eb70dc949df4b776fbee39a4773c66c476.jpg" } ], "jobs": [ { "id": 77209, "title": "Open Call for Candidates", "url": "https://www.ycombinator.com/companies/tuesday-labs/jobs/PWQE14e-open-call-for-candidates", "location": "New York City", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "", "visa": "US citizen/visa only", "skills": [] } ], "news": [], "launches": [] }, { "id": 29273, "name": "Pivot Robotics", "slug": "pivot-robotics", "former_names": [ "Pivot AI", "Pivot Robots" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ee0d44cf8688258862f3d2457491a3a79d07f53c.png", "website": "https://pivotrobotics.com", "all_locations": "San Francisco, CA, USA", "long_description": "Pivot Robotics makes AI software for robotic arms that helps manufacturers automate their most labor intensive tasks. We are starting out with the dangerous task of metal grinding and are currently deploying our software on 10+ robots in a cast-iron foundry. ", "one_liner": "AI for Robot Arms in Factories", "team_size": 8, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1709584102, "tags": [ "Robotics", "AI", "Industrial" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2024", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/pivot-robotics", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/pivot-robotics.json", "year_founded": 2023, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/pivot-robots/", "x_url": "https://twitter.com/pivotrobots", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/ee0d44cf8688258862f3d2457491a3a79d07f53c.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": 1333819, "full_name": "Siddharth Girdhar", "title": "Founder/CEO", "founder_bio": "AI, Robots, Soccer.", "is_active": true, "linkedin_url": "https://linkedin.com/in/siddharthgir", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/dd54777195d0ae4314e22e6d32d4a65a6dc013f1.jpg" }, { "user_id": 509746, "full_name": "Vignesh Rajmohan", "title": "Founder/CTO", "founder_bio": "Co-Founder of Pivot Robotics", "is_active": true, "linkedin_url": "https://linkedin.com/in/vignesh-rajmohan", "x_url": "https://twitter.com/vrajmo", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d7e3e1feba2670721b48a43c0bac55297d9433ef.jpg" } ], "jobs": [ { "id": 73893, "title": "Robotics Software Engineer", "url": "https://www.ycombinator.com/companies/pivot-robotics/jobs/0sRNlmU-robotics-software-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$120K - $160K", "equity_range": "", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [ "Amazon Web Services (AWS)", "Python", "Machine Learning", "Computer Vision" ] }, { "id": 88453, "title": "Software Engineer", "url": "https://www.ycombinator.com/companies/pivot-robotics/jobs/IDlqU83-software-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$120K - $160K", "equity_range": "", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [ "Amazon Web Services (AWS)", "Python", "Machine Learning", "Computer Vision" ] } ], "news": [ { "title": "YC-backed AI startup Pivot Robots raises funding from NuVentures", "url": "https://www.business-standard.com/companies/start-ups/yc-backed-ai-startup-pivot-robots-raises-funding-from-nuventures-124070100581_1.html", "date": "Jul 01, 2024" } ], "launches": [ { "id": 79034, "title": "Pivot Robotics - Automating high-mix manufacturing with AI", "tagline": "Pivot Robotics builds software to tackle the next frontier of manufacturing automation.", "body": "**TL;DR** We’re building this -\n\n![uploaded image](/media/?type=post&id=79034&key=user_uploads/509746/b2c4bca3-62a5-4591-9743-29683d930076)\n\nAnd we are Ex-Google and Meta robotics engineers that are using foundation vision models to solve the riddle of high-mix to redefine American manufacturing.\n\n—\n\n### **🚨 The Problem:**\n\nU.S. manufacturing is making a comeback for the first time since the 1970s, but there is a problem: **Nobody is filling these jobs**. Decades of decline and entire generations shying away from manufacturing jobs have left the industry facing an expected 2.4 million jobs going unfulfilled by 2030. \n\nThe obvious solution is to use robots, but **75% of all U.S. manufacturers are effectively unable to use traditional robotic automation** due to their high-mix production: they produce a wide array of products in small quantities. Traditional automation is rigid and needs new fixturing and re-programming for each part, and doesn’t provide ROI for high-mix manufacturers since so little of each part is produced. \n\nIf America is unable to capitalize on the current manufacturing and AI boom, we lose out on **$1 trillion per year in opportunity cost** and the chance to strengthen our weakened industrial base. High-mix manufacturers are a crucial component for this and they urgently need adaptable automation solutions that can cheaply handle their large variety of parts. \n\n### **🦾 Our Solution:**\n\nPivot Robotics combines off-the-shelf robots and vision sensors with our pioneering AI vision control software to give industrial robots the ability to adapt. Our first product, Proteus, addresses the dangerous and unpopular task of grinding metal parts, offering zero-shot adaptation to new parts with the same precision, and efficiency. **We do this by leveraging the latest advances in foundational vision models**, allowing us to avoid the large data requirements that prior attempts of adding vision to industrial robots faced. We are currently engaged in a **pilot to deploy 10+ Proteus systems** at a large cast iron foundry that produces over 200 different parts a year.\n\n### **🤝 Who We Are:**\n\n![uploaded image](/media/?type=post&id=79034&key=user_uploads/509746/dca22c09-4fc2-4c3c-aa64-5482d6880583)\n\nWe both met on the first day of college at Carnegie Mellon University, living 2 doors across from each other. \n\n[Siddharth](https://bookface.ycombinator.com/user/1333819/linkedin_redirect?key=74798b374abfa1117de67acaa6e2c7591293097d) has worked on self-driving cars at Uber ATG, AI at Meta, and most recently was designing multi-agent algorithms for warehouse robots at Nimble Robotics.\n\n[Vignesh](https://bookface.ycombinator.com/user/509746/linkedin_redirect?key=102ec6e610057e9a5088e60101031188a7145ab9) optimized motion planning for general-purpose robots at Google X, researched LLM applications for robotics in the Atkeson Lab, and worked on manipulation at ABB.\n\nBoth of us are inspired to use our robotics experience to solve real-world labor problems after watching our respective parents’ careers in these industries (agriculture and manufacturing).\n\n### 🔮**The Future:**\n\nExpanding our vision technology to develop hand-eye coordination for robot arms, enabling the automation of tasks beyond grinding, like materials handling and assembly for high-mix manufacturers.\n\n### **🙏Our Ask:**\n\nWe’re looking for introductions to manufacturing partners eager to embrace AI-driven automation and investors who share our vision for the future of manufacturing.\n\n### **✉️ Contact Us:**\n\nReach out at [founders@pivotrobotics.com](mailto:founders@pivotrobots.com) and follow us on [Twitter](https://twitter.com/pivotrobots)/[Linkedin](https://www.linkedin.com/company/pivot-robots/) for updates and cool demos.", "url": "https://www.ycombinator.com/launches/KYk-pivot-robotics-automating-high-mix-manufacturing-with-ai", "votes": 136, "created_at": "2024-03-04T20:30:42.743Z" } ] }, { "id": 29402, "name": "Yondu", "slug": "yondu", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0b7969c1cf6999d5b5333e8a0fd7ca63e13f079f.png", "website": "https://yondu.ai/", "all_locations": "Los Angeles, CA, USA", "long_description": "Yondu is creating the robotic workforce of the future starting with logistics automation. We're deploying humanoid robots in the first flexible, drop-in picking automation solution designed for 3PLs.", "one_liner": "Robots to Automate Fulfillment", "team_size": 7, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1709280983, "tags": [ "Hard Tech", "Robotics", "Logistics", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2024", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/yondu", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/yondu.json", "year_founded": 2024, "city": "Los Angeles", "country": "US", "linkedin_url": "https://www.linkedin.com/company/yonduai/", "x_url": "https://twitter.com/yonduai", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/0b7969c1cf6999d5b5333e8a0fd7ca63e13f079f.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/a96f5a9a53d9ee9d1ca8ef51cb6f294eab9b6ad6.png" ], "primary_partner": { "name": "Diana Hu", "url": "https://www.ycombinator.com/people/diana-hu" }, "founders": [ { "user_id": 782277, "full_name": "Michael Chen", "title": "Founder/CEO", "founder_bio": "Michael Chen is at a unique crossroads with a background in intelligent machines from MIT and research experience at the forefront of robotics and AI. He helped build an open source bipedal robot at MIT CSAIL. Michael is an avid entrepreneur who has always loved business (even owning a sauce brand). For fun, he builds all sorts of cool machines ranging from FPV drones to train track cleaning robots to gasoline powered snowboards. ", "is_active": true, "linkedin_url": "https://linkedin.com/in/michael-chen-17464a1b1", "x_url": "https://twitter.com/chenouttaten", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/16760bb043b9bd6619773df1464be0a224e3f300.jpg" }, { "user_id": 1547615, "full_name": "Tahmid Jamal", "title": "Founder/CTO", "founder_bio": "Tahmid graduated from MIT with degrees in AI and AeroAstro. There he's worked on projects ranging from language model compression and quantization to astrodynamics simulations for a solar research proposal to NASA. He was doing his master's researching uncertainty estimation methods in deep learning before dropping out to participate in YC. In his free time, he enjoys movies, board games, and climbing the occasional tree.", "is_active": true, "linkedin_url": "https://linkedin.com/in/74hm1d", "x_url": "https://twitter.com/74hm1d", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/dc90be30b2779e01b76edb62c535d5bb13944890.jpg" } ], "jobs": [ { "id": 71111, "title": "Active Interest for Engineers", "url": "https://www.ycombinator.com/companies/yondu/jobs/DEor4se-active-interest-for-engineers", "location": "Gardena, CA, US / Los Angeles, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$120K - $200K", "equity_range": "0.50% - 1.60%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [ "Bash/Shell", "C++", "Torch/PyTorch", "Linux", "Deep Learning", "Reinforcement learning (RL)", "Docker", "Computer Vision", "Microcontrollers", "CAD Design", "PCB design", "Sensor integration" ] }, { "id": 74730, "title": "Robotics Researcher", "url": "https://www.ycombinator.com/companies/yondu/jobs/QAKnidR-robotics-researcher", "location": "Gardena, CA, US / Los Angeles, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$120K - $200K", "equity_range": "0.50% - 1.60%", "experience": "3+ years", "visa": "Will sponsor", "skills": [] }, { "id": 87004, "title": "Senior Robotics Engineer", "url": "https://www.ycombinator.com/companies/yondu/jobs/l6z04IP-senior-robotics-engineer", "location": "Gardena, CA, US / Los Angeles, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$120K - $200K", "equity_range": "0.50% - 1.60%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "Bash/Shell", "C++", "Python", "Linux", "Docker", "Sensor integration" ] }, { "id": 107166, "title": "Robot SWE", "url": "https://www.ycombinator.com/companies/yondu/jobs/fOsMYvM-robot-swe", "location": "Gardena, CA, US / Los Angeles, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$100K - $200K", "equity_range": "0.20% - 1.20%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [ "Bash/Shell", "C++", "Python", "Linux", "Docker" ] }, { "id": 113732, "title": "Robotics Hardware Engineer ", "url": "https://www.ycombinator.com/companies/yondu/jobs/Y0Ek2e8-robotics-hardware-engineer", "location": "Los Angeles, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Hardware", "salary_range": "$100K - $200K", "equity_range": "0.10% - 1.00%", "experience": "1+ years", "visa": "Will sponsor", "skills": [] }, { "id": 114065, "title": "Physical AI Infrastructure Engineer", "url": "https://www.ycombinator.com/companies/yondu/jobs/dLJNfs8-physical-ai-infrastructure-engineer", "location": "Los Angeles, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$100K - $200K", "equity_range": "0.10% - 1.00%", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [ "C++", "Python", "Linux", "Microcontrollers" ] }, { "id": 116145, "title": "Chief of Staff", "url": "https://www.ycombinator.com/companies/yondu/jobs/AwihGGR-chief-of-staff", "location": "Gardena, CA, US", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "$100K - $200K", "equity_range": "0.10% - 0.50%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 116147, "title": "Forward Deployed Engineer", "url": "https://www.ycombinator.com/companies/yondu/jobs/EYpToWD-forward-deployed-engineer", "location": "Gardena, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$80K - $120K", "equity_range": "0.01% - 0.10%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 116149, "title": "Robot Technician", "url": "https://www.ycombinator.com/companies/yondu/jobs/Af1rQ7C-robot-technician", "location": "Gardena, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$60K - $80K", "equity_range": "", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 116150, "title": "Software Engineering Intern (Spring/Summer)", "url": "https://www.ycombinator.com/companies/yondu/jobs/0Cu1yIr-software-engineering-intern-spring-summer", "location": "Gardena, CA, US", "type": "Internship", "role": "Engineering", "role_type": "Robotics", "salary_range": "$4K - $10K / monthly", "equity_range": "", "experience": null, "visa": "US citizen/visa only", "skills": [] }, { "id": 116151, "title": "Mechatronics Intern (Spring/Summer)", "url": "https://www.ycombinator.com/companies/yondu/jobs/glxSqKV-mechatronics-intern-spring-summer", "location": "Gardena, CA, US", "type": "Internship", "role": "Engineering", "role_type": "Mechanical", "salary_range": "$4K - $6K / monthly", "equity_range": "", "experience": null, "visa": "US citizen/visa only", "skills": [] } ], "news": [], "launches": [ { "id": 95475, "title": "Yondu AI ➡️ Enabling the robot workforce of the future", "tagline": "Yondu is the platform for robot labor starting with drop-in order fulfillment automation", "body": "### **We are a platform-to-application company that puts robots in warehouses and makes them useful on day one. Our state-of-the-art remote teleoperation gives immediate efficiency gains, with our robot behavior models gradually taking over to reach full automation and drive costs down further. We’re starting with mobile order fulfillment, where a huge chunk of warehouse labor spend sits.**\n\n![uploaded image](/media/?type=post&id=95475&key=user_uploads/1547615/e8add669-ff4f-4eaa-9579-da70973fc77b)\n\n[https://www.youtube.com/watch?v=GzglTuRloCo](https://www.youtube.com/watch?v=GzglTuRloCo&t=1s)\n\n### ——————————————————————————————\n\n# **The timing**\n\nGeneral purpose robot **hardware has gotten 10x cheaper** in the past decade. And advancements in robot learning are helping automate **long-form, complex tasks**. **BUT** it’s still hard to achieve the **perfect human level success rates necessary** for deployment! The **opportunity lies in automating the shorter-form, easier-to-master tasks** that still have a level of complexity that made them impossible to automate in the past. The logistics field is full of these types of problems…\n\n![uploaded image](/media/?type=post&id=95475&key=user_uploads/1547615/8a3ea638-c361-46bd-8276-97be15ccf669)\n\n_A simple, fully autonomous pick at 1× speed_\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n### ——————————————————————————————\n\n# **The problem in mind**\n\nOrder picking labor can account for up to **50%** of warehouse manual operating costs. Pickers often walk **miles** per shift! Warehouses still rely on people for repetitive, physically demanding tasks with high turnover. Existing order fulfillment automation falls into two buckets:\n\n\\- **ASRS (Automated Storage and Retrieval Systems)**: Basically turns a warehouse into a giant 3D robot grid system. It gets high throughput but costs tens of millions and requires an overhaul of warehouse space. 😢 **_HIGH COST_**_, 😊 **HIGH AUTOMATION**_\n\n\\- **AMR (Autonomous Mobile Robots)**: These robots carry shelves and goods around which reduces walking time. But they still require human picking. 😊 **_LOW COST_**_, 😢 **LOW AUTOMATION**_\n\n### ——————————————————————————————\n\n# **OUR SOLUTION**\n\n**We’ve created a 3 part embodied-AI platform that automates bin picking using off the shelf robots in brownfield deployments. 😊 _LOW COST, 😊 HIGH AUTOMATION_**\n\nhttps://youtu.be/UVmMSui2_FQ\n\nWith **ULTRON** (user-friendly low-latency **remote teleoperation** system) we **deploy first**, putting robots to use immediately in our customers’ operations and spinning up our data flywheel.\n\n![uploaded image](/media/?type=post&id=95475&key=user_uploads/1547615/6ddec526-7b14-48db-a5b1-387ea371943e)\n\nOur **WMS** (warehouse management software) **integration and** **orchestration** software routes orders from a warehouse’s WMS to our platform, instructing robots where to go and operators what to pick.\n\n![uploaded image](/media/?type=post&id=95475&key=user_uploads/1547615/583a510d-09f3-46e7-8b54-c44e0edc3e9b)\n\nOur autonomy stack **YGM** (Yondu General Manipulation) pushes the system to fully autonomous as we **gain more in-the-wild** experience. Over time the manipulation policy takes over more work and the operator is required less. YGM is responsible for:\n\n* Steering our robot policy to pick and place from the correct bins\n* Identifying how good a job it is doing and whether it is struggling so an operator can take over\n* Learning from new experiences and adapting to succeed in situations that it previously struggled in\n\n![uploaded image](/media/?type=post&id=95475&key=user_uploads/1547615/663a0f0b-53ce-40b5-ad46-95980e70197b)\n\n_Operations in our partner warehouse_\n\n### ——————————————————————————————\n\n# Our Vision\n\nOur platform is **not limited to only helping us conquer bin picking**. Logistics warehouses still have many more repetitive-yet-slightly-complex tasks such as decanting, replenishing, and packing. And as **robot learning capabilities continue to grow**, our pipeline of _deploy→collect→refine→automate_ only increases in value. There will be **more brownfield robotics automation providers** for specific industries and increasingly complex tasks. They will need to integrate with their customers and spin up their own data flywheels. And the Yondu platform will be available for them so they can automate **any task** with **any robot**.\n\n### ——————————————————————————————\n\n# **Team**\n\nWe’ve gathered quite the team. Here are just a few of our talented members\n\n\\- **Michael Chen (CEO)** Ex-MIT Controls and Robotics\n\n\\- **Tahmid Jamal (CTO)** MIT AI & Aerospace\n\n\\- **Lianhao Yin (Head of Research)** MIT CSAIL Postdoc in Robotic Systems\n\n\\- **Jairo Maldonado (Teleop Lead)** Georgia Tech PhD in Robotic Prosthesis\n\n\\- **Mehul Kumar (Founding Researcher)** Industry veteran in VR, humanoids, simulations, and teleop\n\n![uploaded image](/media/?type=post&id=95475&key=user_uploads/1547615/b5914757-4088-48a7-b88b-0252656f6300)\n\n### ——————————————————————————————\n\n# Ask\n\n\\- **3PLs**: If you are in charge of warehouse operations and think you’re spending more resources on a job than you _should_ be, **complain to us**!\n\n\\- **Robotics partner**: If you’re also in the robotics automation space and would like to use our platform, **let’s partner up**\n\n**Reach out to [founders@yonduai.com](mailto:hello@yonduai.com)**\n\n### ——————————————————————————————", "url": "https://www.ycombinator.com/launches/Opv-yondu-ai-enabling-the-robot-workforce-of-the-future", "votes": 58, "created_at": "2025-11-14T18:30:57.452Z" } ] }, { "id": 29523, "name": "K-Scale Labs", "slug": "k-scale-labs", "former_names": [ "dpsh" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/9a76d2d8803d634b3e622a584f55e531a3e72f45.png", "website": "https://kscale.dev/", "all_locations": "San Francisco, CA, USA", "long_description": "We're building humanoid robots to do most of what you find boring or tedious. We have an open-source design which we are releasing to the public, which is capable of walking, talking and manipulating objects.", "one_liner": "Open-source humanoid robots", "team_size": 10, "industry": "Consumer", "subindustry": "Consumer -> Consumer Electronics", "launched_at": 1711580332, "tags": [ "Machine Learning", "Robotics", "Consumer", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2024", "status": "Inactive", "industries": [ "Consumer", "Consumer Electronics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/k-scale-labs", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2024/k-scale-labs.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/kscale/", "x_url": "https://twitter.com/kscalelabs", "fb_url": null, "cb_url": null, "github_url": "https://github.com/kscalelabs", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/9a76d2d8803d634b3e622a584f55e531a3e72f45.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": 216598, "full_name": "Benjamin Bolte", "title": "Founder", "founder_bio": "AI researcher @ OpenAI, fmr. Tesla, Meta, Google and Amazon", "is_active": false, "linkedin_url": "https://linkedin.com/in/benjaminbolte", "x_url": "https://twitter.com/benjamin_bolte", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/8a2681a62183e56fe3557cdbbbf57fc2e3eed5b8.jpg" }, { "user_id": 1963405, "full_name": "Matthew Freed", "title": "Founder", "founder_bio": "MechE + AI", "is_active": false, "linkedin_url": "", "x_url": "https://twitter.com/mattfreed", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/bf71707e2370d20249f9a01a3806c01a878ce0fc.jpg" } ], "jobs": [], "news": [ { "title": "The Open-Source Robotics Startup That Caught OpenAI’s Eye — The Information", "url": "https://www.theinformation.com/articles/open-source-robotics-startup-caught-openais-eye", "date": "May 16, 2025" }, { "title": "X", "url": "https://twitter.com/Scobleizer/status/1766365088129368113", "date": "Mar 08, 2024" } ], "launches": [ { "id": 79758, "title": "K-Scale Labs 🤖 Open-source humanoid robots for everyone", "tagline": "Meet Stompy, the world's first open-source general-purpose humanoid robot", "body": "At [K-Scale Labs](https://kscale.dev/), we are building the world’s first open-source general-purpose humanoid robot.\n\n### The Problem\n\nIn recent years, domains like NLP and computer vision have benefited enormously from the [bitter lesson](http://www.incompleteideas.net/IncIdeas/BitterLesson.html) that general methods that are able to leverage computation are ultimately the most effective. The ability to scrape the internet for large, in-the-wild datasets has brought these fields from working well on academic benchmarks to becoming useful real-world products.\n\nHowever, although [there is evidence](https://robotics-transformer-x.github.io/) that the same scaling laws likely apply to robotics as well, the field is stymied by lack of access to the same large, in-the-wild datasets that work well in other domains, resulting in foundation models with poor cross-embodiment and out-of-distribution generalization. While there has been a [surge of investment](https://agilityrobotics.com/news/2023/opening-robofab-worlds-first-factory-for-humanoid-robotsnbsp-xxna2-g9mhr-rnk52) in trying to grow these datasets, we view the [capital-intensive](https://www.therobotreport.com/figure-raises-70m-to-commercialize-humanoids/), [factory-first](https://www.prnewswire.com/news-releases/figure-announces-commercial-agreement-with-bmw-manufacturing-to-bring-general-purpose-robots-into-automotive-production-302036263.html) approach as unlikely to generate the scale and diversity of data required to make these robotics foundation models match the state-of-the-art seen in other fields.\n\n### Our Solution\n\nWe designed and built a fully-featured humanoid robot that anyone with a 3D printer and some time can build on their own. We are releasing it for anyone to build themself, along with an operating system that will enable the robot to perform basic task and learn from experience.\n\n![uploaded image](/media/?type=post&id=79758&key=user_uploads/216598/4ba0e510-77a0-4703-8df4-4d04593c537a)\n\nOur robot, Stompy, is a 4-foot humanoid robot featuring the claw gripper from the recent [Universal Manipulation Interface](https://umi-gripper.github.io/) paper, designed so that each part fits on a 256 × 256 3D printer bed, with a total bill of materials costing less than $10,000. We’re using carbon fiber PAHT, but in principle, any reasonably strong plastic could be used instead. Our actuators are quasi-direct drives with between 6:1 and 8:1 reduction ratios, meaning that all the joints on our robot are low-inertia and back-drivable, with nominal torque values from 3-12 Nm. Each robot features a hot-swappable 48V 15Ah battery pack, which can power it for over an hour.\n\nWe started designing Stompy from scratch shortly after the start of the YC batch. In the last three months, we built five different iterations of the hardware as we’ve ironed out issues with assembly, part reliability, motor torque, and gripper design. Having worked with a number of robots in my professional career, including the Stretch from Hello Robot, the Spot from Boston Dynamics, and the early prototypes of the Optimus from Tesla, I feel confident saying that we have the best general-purpose hardware design for our BOM cost - and we are going to give it away for free.\n\n![Image](https://pbs.twimg.com/media/GILolqbaEAAzDUv?format=jpg&name=large)\n\nAdditionally, we have built the software tooling to train policies in simulation, using simulators like Isaac from Nvidia, and translate those policies to the robot. This enables anyone to get started developing models for simple tasks for free. We will also release the VLM we’ve trained in-house as a foundation model for the robot perception stack, enabling developers to learn task-specific policies in a data-efficient manner.\n\n![uploaded image](/media/?type=post&id=79758&key=user_uploads/216598/2379dd19-b364-4990-958c-007b258bc1d7)\n\n### About Us\n\nOur CEO ([Ben](https://bookface.ycombinator.com/user/216598/linkedin_redirect?key=f2e912c331dc16e3f6c704008aeced6a0055e4ec)) is a robotics researcher and engineer who has worked on robotics foundation models at Tesla and Meta AI. At Tesla, he wrote the CUDA kernel behind the voxel occupancy network, which served as the first perception foundation model to run in the Optimus. At Meta, his papers on speech and robotics representation learning have been cited over 2000 times.\n\n### Our Ask\n\nIf you are interested in either building, buying, or developing a humanoid robot, please send an email to [ben@kscale.dev](mailto:ben@kscale.dev) with your request. We’re working towards a future where anyone with a few 3D printers and some scrappiness can start a robot factory, and anyone who wants a humanoid robot will be able to get one.", "url": "https://www.ycombinator.com/launches/KkQ-k-scale-labs-open-source-humanoid-robots-for-everyone", "votes": 82, "created_at": "2024-03-27T23:01:52.242Z" } ] }, { "id": 29557, "name": "Ultra", "slug": "ultra", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4e0a45197c7d56b15f0976e431a519c2b35929c0.png", "website": "https://ultra.tech", "all_locations": "New York City, NY, USA", "long_description": "Ultra builds practical, general-purpose robots that are deploying—and producing ROI—today.\r\n\r\nUnlike traditional industrial automation that’s rigid and complex, our robots are zero integration (able to be installed in hours, not weeks) and are highly flexible, capable of quickly learning new tasks and delivering immediate value to customers.\r\n\r\nFounded by a team of three-time entrepreneurs with a decade of collaboration, Ultra moves fast. We already have robots in the field generating revenue and data, with plans to rapidly scale deployments this year.", "one_liner": "Practical, general-purpose robots for repetitive industrial tasks", "team_size": 4, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1723759198, "tags": [ "Robotics", "Logistics", "AI", "Industrial" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/ultra", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/ultra.json", "year_founded": 2024, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/ultraroboticsco", "x_url": "https://x.com/Ultraroboticsco", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/4e0a45197c7d56b15f0976e431a519c2b35929c0.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": 36827, "full_name": "Jon Miller Schwartz", "title": "Founder/CEO", "founder_bio": "Robotmaxxing at Ultra. Prev Arena AI, Voodoo Manufacturing (YC W17), Body Labs, and Layer By Layer (YC S13).\n", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jmschwartz11", "x_url": "https://twitter.com/JMSchwartz11", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4175a41b7ddfb0a9f80aaa87d7b4354f003a0842.jpg" }, { "user_id": 36828, "full_name": "Max Friefeld", "title": "Founder", "founder_bio": "Max is the co-founder and COO of Ultra. \n\nHe studied Computer and Electrical Engineering at Harvey Mudd College ('13), and founded two YC-backed companies, Layer By Layer (S13) and Voodoo Manufacturing (W17).\n\nImmediately prior to starting Ultra, Max led teams at Boston Consulting Group optimizing operations for the largest logistics networks in the world and developing go-to-market strategy for private equity backed robotics companies.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/mfriefeld", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d8216f62957dfd9a799bdefaf861c60b0774a844.jpg" }, { "user_id": 36829, "full_name": "Oliver Ortlieb", "title": "Founder/CTO", "founder_bio": "Oliver is the co-founder and CTO of Ultra.\n\nBefore co-founding Ultra, Oliver Ortlieb was the Co-founder & CTO at Voodoo Manufacturing where he built the software and systems to support one of the largest 3D printing factories in the world. Prior to that, he co-founded Layer By Layer, a secure marketplace for 3D-printable products. He holds multiple patents in the field of 3D printing, and received his BS in Computer Science from Harvey Mudd College.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/oliverortlieb", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c3fc0be0545afe2d8211c303677994e8a2952daa.jpg" }, { "user_id": 1831182, "full_name": "Chetan Parthiban", "title": "Founder", "founder_bio": "Chetan is a Co-Founder and Chief Scientist of Ultra. \n\nHe studied Mathematics and Robotics at the University of Pennsylvania, where he received both his BA and MSE. Chetan has deep experience in applied AI as he was one of the first machine learning scientists at Arena, where he focused on applying machine learning to solve high frequency decision making problems. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/chetan-parthiban", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/749af06a053a239e175d1652781dd89476c0a8c5.jpg" } ], "jobs": [ { "id": 74646, "title": "Robotics Software Engineer", "url": "https://www.ycombinator.com/companies/ultra/jobs/Dureryz-robotics-software-engineer", "location": "New York, NY, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$150K - $250K", "equity_range": "0.10% - 1.00%", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [ "Python" ] }, { "id": 74651, "title": "Machine Learning Scientist", "url": "https://www.ycombinator.com/companies/ultra/jobs/4eHDieo-machine-learning-scientist", "location": "New York, NY, US", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$150K - $275K", "equity_range": "0.10% - 1.25%", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [ "Python", "Machine learning" ] }, { "id": 86406, "title": "Senior Machine Learning Engineer", "url": "https://www.ycombinator.com/companies/ultra/jobs/rrGm2vq-senior-machine-learning-engineer", "location": "NY, US", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$175K - $275K", "equity_range": "0.25% - 0.75%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 102723, "title": "Senior Mechatronics Engineer - R&D", "url": "https://www.ycombinator.com/companies/ultra/jobs/2TWk03F-senior-mechatronics-engineer-r-d", "location": "New York, United States", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 102725, "title": "Deployment Engineer", "url": "https://www.ycombinator.com/companies/ultra/jobs/ypeplP4-deployment-engineer", "location": "New York, United States", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 102726, "title": "Field Support Technician", "url": "https://www.ycombinator.com/companies/ultra/jobs/pq8Nnee-field-support-technician", "location": "New York, United States", "type": "Full-time", "role": "Support", "role_type": null, "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 102727, "title": "Senior Electrical Engineer", "url": "https://www.ycombinator.com/companies/ultra/jobs/67kIKjJ-senior-electrical-engineer", "location": "New York, United States", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 102728, "title": "Supply Chain and Procurement Lead", "url": "https://www.ycombinator.com/companies/ultra/jobs/bwhTqw4-supply-chain-and-procurement-lead", "location": "New York, United States", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 102729, "title": "Robot Manufacturing Technician", "url": "https://www.ycombinator.com/companies/ultra/jobs/GmHGHC0-robot-manufacturing-technician", "location": "New York, United States", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 102733, "title": "Research Scientist", "url": "https://www.ycombinator.com/companies/ultra/jobs/JUvjsB0-research-scientist", "location": "New York, United States", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "$250K - $350K", "equity_range": "", "experience": "6+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 102734, "title": "Technical Program Manager, Data & Autonomy", "url": "https://www.ycombinator.com/companies/ultra/jobs/yOuxbEY-technical-program-manager-data-autonomy", "location": "New York, United States", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "$150K - $250K", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 102738, "title": "Founding Product", "url": "https://www.ycombinator.com/companies/ultra/jobs/FBkPnMN-founding-product", "location": "New York, United States", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 102739, "title": "Head of People", "url": "https://www.ycombinator.com/companies/ultra/jobs/SVLN1F9-head-of-people", "location": "New York, United States", "type": "Full-time", "role": "Recruiting & HR", "role_type": "Recruiter", "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 103176, "title": "Head of Marketing", "url": "https://www.ycombinator.com/companies/ultra/jobs/Vafn155-head-of-marketing", "location": "New York, United States", "type": "Full-time", "role": "Marketing", "role_type": null, "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 105451, "title": "Product Engineer ", "url": "https://www.ycombinator.com/companies/ultra/jobs/nHZ29Tq-product-engineer", "location": "New York, United States", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 107001, "title": "Senior Software Infrastructure Engineer ", "url": "https://www.ycombinator.com/companies/ultra/jobs/hyzmpbG-senior-software-infrastructure-engineer", "location": "New York, United States", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 113502, "title": "Data Operations Associate", "url": "https://www.ycombinator.com/companies/ultra/jobs/9jPJKd3-data-operations-associate", "location": "New York, United States", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 115421, "title": "Head of Hardware", "url": "https://www.ycombinator.com/companies/ultra/jobs/fCC9bhS-head-of-hardware", "location": "New York, United States", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 117036, "title": "Facilities & Office Manager", "url": "https://www.ycombinator.com/companies/ultra/jobs/IYhbTmv-facilities-office-manager", "location": "New York, United States", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 117231, "title": "Head of Pilot Operations", "url": "https://www.ycombinator.com/companies/ultra/jobs/nXjHf7e-head-of-pilot-operations", "location": "New York, United States", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": "5+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [ { "title": "Ultra raises $62 million for fast-growing ‘robots as a service’ business, announces tie-up with AI research firm Physical Intelligence | Fortune", "url": "https://fortune.com/2026/10/09/ultra-raises-62-million-fast-growing-robots-service-tie-up-ai-research-firm-physical-intelligence/", "date": "Oct 09, 2026" } ], "launches": [ { "id": 83218, "title": "🇺🇸🤖 Ultra - Building the next million robots to automate American warehouses", "tagline": "Warehouses are filled with dull, repetitive tasks still done by people. Ultra makes robots to change that.", "body": "**_TL;DR_**: Ultra robots automate e-commerce order packaging and returns in fulfillment centers. Traditional automation isn't working for warehouses because it's costly, rigid, and often underutilized. Our robots are different: they’re easy to deploy, resilient to changing environments, and powered by AI that’s trained with examples.\n\n![uploaded image](/media/?type=post&id=83218&key=user_uploads/36827/b95e65a5-16bd-4a49-9790-0cf80c5b5c27)\n\nHi everyone - we’re [Oliver](https://www.linkedin.com/in/oliverortlieb/), [Chetan,](https://www.linkedin.com/in/chetan-parthiban/) [Jon](https://www.linkedin.com/in/jmschwartz11/), and [Max](https://www.linkedin.com/in/mfriefeld/). After years of building and scaling manufacturing and robotics companies (_Layer By Layer, S13, and Voodoo Manufacturing, W17_), we’re now focused on bringing automation to the industries that need it most.\n\n![uploaded image](/media/?type=post&id=83218&key=user_uploads/36827/8b8174a9-9ca6-46cc-b6f6-f7b1e854c160)\n\nWe believe we’re at a moment in history when robots can be made accessible and capable enough for mass adoption - and we need it more than ever.\n\n**Labor is harder to come by than it’s been in decades**.\n\nImagine running a warehouse: you hire 20 temp workers to come in one day, but only 15 show up in the morning, and just 5 return after lunch. That’s the reality one of our partners told us they face.\n\nIn 2018, the U.S. entered its first labor shortage in over 60 years. Today, we are short over 1.3 million workers, causing companies to go understaffed or rely on high-churn temp labor.\n\nAnd yet, **traditional warehouse automation isn’t being adopted fast enough**.\n\n![uploaded image](/media/?type=post&id=83218&key=user_uploads/36827/04cde5a1-5136-4f3b-b880-24464506183b)\n\n# **🤖 Ultrabots**\n\nUltra is building robots that can be dropped in at existing workstations and quickly trained to do repetitive tasks. They are more cost-effective than human labor and can operate around the clock, giving your team [✨](https://emojipedia.org/sparkles)superpowers[✨.](https://emojipedia.org/sparkles)\n\nWe use reliable off-the-shelf hardware so we can focus on rapid deployment. The key to unlocking the next million robots is data scale, and the fastest way to get there is to put robots in real-world environments doing useful tasks.\n\n# **⏰ Why Now?**\n\nRecent AI breakthroughs mean we can control robots with neural nets trained with examples, rather than with explicitly programmed routines.\n\n![uploaded image](/media/?type=post&id=83218&key=user_uploads/36827/ebd67a19-babf-4f49-81f4-7994950ed7f7)\n\n_Above is an example of a fully autonomous picking policy we trained on \\~2hrs of data from teleoperating our research arms. The two RGB camera feeds are the input to the model, which outputs the joint+gripper positions at 10Hz._\n\n![uploaded image](/media/?type=post&id=83218&key=user_uploads/36827/13ced136-d5de-4a57-ade8-cb53e074a4a7)\n\n_Examples of emergent behavior learned from the training data, but not explicitly programmed like what would be required in traditional automation._\n\n# **🙏 Asks**\n\nWe’d love to connect to e-commerce 3PLs and large brands that handle their own fulfillment. You can reach us at [founders@ultra.tech](mailto:founders@ultra.tech). Thanks!", "url": "https://www.ycombinator.com/launches/LeE-ultra-building-the-next-million-robots-to-automate-american-warehouses", "votes": 66, "created_at": "2024-08-20T14:59:15.048Z" }, { "id": 66553, "title": "YC Deals - Access to software deals for employees at YC companies", "tagline": "Employees at YC companies have access to more than 100 discounts and exclusive offers on industry leading tools.", "body": "Hello, [Oliver](https://www.linkedin.com/in/oliverortlieb/) and [Zach](https://www.linkedin.com/in/zach-kamran/) here, software engineers at Y Combinator. We are thrilled to announce YC Deals. \n\nEmployees at YC companies can now leverage one of the major benefits previously only available to YC founders – [YC Deals](https://deals.ycombinator.com/). Through YC Deals, employees have access to more than 100 discounts and exclusive offers on industry leading tools. There are already $500,000 worth of free credits and discounts available, and new deals are constantly being added.\n\n**❌ The Problem**\n\nWe built YC Deals for our companies with a growing team. The founders still want to take advantage of the wide variety of discounts and free credits that YC companies receive, but their employees don’t have access to Bookface (our internal platform for YC founders), where these exclusive deals are listed. \n\n**✨ Our Solution**\n\nNow any employee of a YC company can redeem these deals and help their company save money. Building something new? There are dozens of dev tools like PostHog, Fivetran, and OneSignal.  First HR or ops hire? Get Deel and Stable up and running at a discount. In charge of security? Check out Vanta.  Also find deals on startup staples, like Gusto, GitHub, Algolia, and Amplitude. Help build and grow your company using world-class tools on a startup budget. \n\n![](https://lh5.googleusercontent.com/OVsQc12ujUnJFjcR_OxLDPXrIqj4mEsltXolYe2QhAQEnu2RuZ3Fxv57z2kkc_q2P9rfXhkFKPmJzqM2pJ-th57ArroztYuQQ43o04-PI_6lwk6qWZxnAWciWP6K7x5i8ZTQiBabH2s5ax5vH2n5nh7UUjf1Y4_F3-hK7cxIzjMPxTTyqYIzK0pp)\n\n**👉 Next steps**\n\nEmployees at YC companies can access YC Deals by completing a simple email verification flow using their company email address [here](https://deals.ycombinator.com/).\n\nIf you’d like to offer a deal to the YC community and their employees, you can submit one [here](https://bookface.ycombinator.com/deals/new). \n\nAny additional questions about YC Deals? Visit our FAQs [here](https://deals.ycombinator.com/faq).", "url": "https://www.ycombinator.com/launches/HJR-yc-deals-access-to-software-deals-for-employees-at-yc-companies", "votes": 20, "created_at": "2022-10-06T16:03:12.293Z" } ] }, { "id": 29569, "name": "Miru", "slug": "miru-ml", "former_names": [ "Continuous AI", "Miru ML", "Miru", "Miru ML" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/5f8c54103232ce6ad4a91f33685eeaecbcd4d224.png", "website": "https://www.mirurobotics.com", "all_locations": "San Francisco, CA, USA", "long_description": "Miru makes it easy for robotics teams to manage, version, and deploy robot configurations. Developers use our well-documented APIs and UI components to automate configuration updates for both engineers and operators.\r\n\r\nIn the long term, we're building software infrastructure to accelerate the automation of the physical world.", "one_liner": "Config Management for Robotics", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1722117145, "tags": [ "Developer Tools", "Robotics", "DevOps" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/miru-ml", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/miru-ml.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/miruml", "x_url": "https://x.com/mirurobotics", "fb_url": null, "cb_url": null, "github_url": "https://github.com/miruml", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/5f8c54103232ce6ad4a91f33685eeaecbcd4d224.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": 620575, "full_name": "Armel Talla", "title": "Founder/CEO", "founder_bio": "Armel is the Co-Founder and CEO of Miru.\n\nHe graduated from UT Austin with a B.S. in Computer Science and Mathematics. He previously founded Clips AI, an AI video dev tool that automatically repurposes long videos into clips. During college, Armel interned at Google and YouTube, focusing on building internal tools.", "is_active": true, "linkedin_url": "https://linkedin.com/in/armeltalla", "x_url": "https://twitter.com/armelwtalla", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/40ee8e8adf3b9d90905f829608ed5f600d2b079b.jpg" }, { "user_id": 1035647, "full_name": "Vedant Nair", "title": "Founder", "founder_bio": "Vedant is the Co-Founder and COO of Miru.\n\nHe graduated from UT Austin, where he studied Business and Computer Science. He previously founded Clips AI, an AI video developer tool that automatically repurposed long videos into clips. During college, he interned at Bain & Co. and EY-Parthenon, doing GTM consulting for software companies.", "is_active": true, "linkedin_url": "https://linkedin.com/in/vedantnair", "x_url": "https://x.com/vedantnair__", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2bf4c979b9371b48d25473b333207ae536ec3e6b.jpg" }, { "user_id": 1521401, "full_name": "Benjamin Smidt", "title": "Founder/CTO", "founder_bio": "Ben is the Co-Founder and CTO of Miru. \n\nHe holds a B.S. in Electrical and Computer Engineering from UT Austin, where he initially spent two years studying Mechanical Engineering, igniting his passion for hardware and robotics. Prior to Miru, Ben founded Clips AI, where he developed production-ready AI models and video processing servers using Kubernetes.", "is_active": true, "linkedin_url": "https://linkedin.com/in/benjamin-smidt", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/dd7148f07187d171dea5d0364ead07b775dc74f5.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 82564, "title": "Miru - Deployment infrastructure for Robotics and IoT 🦾", "tagline": "Deploy software updates over the air to fleets of devices", "body": "**tl;dr:** Miru helps robotics and IoT teams painlessly deploy software over the air, provision devices, and manage versioning for their fleets.\n\nFor engineers using Miru, _updating software on thousands of devices is as easy as pushing a change to GitHub._\n\n**Our Ask:** Engineers in robotics and IoT, [get started with Miru today!](https://www.miruml.com/)\n\n![uploaded image](/media/?type=post&id=82564&key=user_uploads/1035647/c64f81c9-695b-472e-bab9-5687c4eef19f)\n\n**❌ The Problem**\n\nRobotics and IoT companies don’t have robust, off-the-shelf DevOps tools.\n\nAs a result, to deploy their software, they’re forced to manually SSH/SCP into their devices or build a hacky solution internally.\n\n**But building this infrastructure is costly.** These companies often need to dedicate more than half of their software team to build and maintain their custom internal tools. This balloons engineering costs and decreases product velocity.\n\nIt’s one of the reasons **why many of these companies die.**\n\n**🦾 Miru**\n\nMiru helps engineers build and maintain their deployment pipelines, saving them months of work.\n\nWith Miru, you can:\n\n1. Push changes to GitHub, and let Miru handle building, staging, and deploying your software to your devices across the world\n2. Manage devices and track software versioning on a centralized dashboard\n3. Enjoy obsessive, fast, 24/7 customer support 🫡\n\n**Installation is easy.** If your device already uses Ubuntu, the Miru installation is just one command **🪄**\n\nMiru users have an unfair advantage. They enjoy reliable, scalable, and secure deployments _without all the pain of building it themselves_.\\\n\\\n\n\n🧍🏼🧍🏿🧍🏾 **About Us**\n\nHi 👋🏾 - we’re [Vedant](https://linkedin.com/in/vedantnair), [Armel](https://linkedin.com/in/armeltalla), and [Ben](https://linkedin.com/in/benjamin-smidt)!\n\n![uploaded image](/media/?type=post&id=82564&key=user_uploads/1035647/a48e7554-cf3c-493b-b5c7-d8aa5a03eb84)\n\nAfter meeting at our freshman dorm at UT Austin, we instantly clicked and became best friends. Whether we were playing intramural basketball or scaling our previous startup, [Clips AI](https://www.clipsai.com/), to 7000 MAUs in just three months, we've proven we make an exceptional team.\n\nOutside of Clips AI, Armel worked as a software engineer at Google and YouTube, focusing on building internal tools and infrastructure. Vedant brings experience in software GTM consulting from Bain & Co. and EY-Parthenon. Ben, our hardware fanatic, has a background in mechanical and electrical engineering, and he’s built production-ready AI and video processing infrastructure using Kubernetes.\n\nWe’re passionate about a future where robots can free humans from doing the dull, dirty, and dangerous tasks that dominate billions of people’s lives. We founded Miru to provide the infrastructure to accelerate this transition.\n\nWe’re obsessed with solving this problem. If you’re a software engineer in robotics or IoT who is struggling with deployment, we’d LOVE to make your life easier.\n\nJust reach out at \\[vedant\\] @ miruml \\[dot\\] com, or better yet, [start using Miru today](https://www.miruml.com/)", "url": "https://www.ycombinator.com/launches/LTg-miru-deployment-infrastructure-for-robotics-and-iot", "votes": 235, "created_at": "2024-07-30T16:20:31.446Z" } ] }, { "id": 29588, "name": "Saphira AI", "slug": "saphira-ai", "former_names": [ "Saphira AI", "Saphira" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/50fee2cba3e02a1824e08a39a9224adb0d2098b5.png", "website": "https://saphira.ai", "all_locations": "San Francisco, CA, USA", "long_description": "Saphira is the easiest way for hardware products to get safety certified and reach market faster, such as industrial robots and heavy machinery.", "one_liner": "The Enablement Layer for Physical AI", "team_size": 7, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1717266827, "tags": [ "Hardware", "Robotics", "Compliance", "Enterprise", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": true, "demo_day_video_public": true, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/saphira-ai", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/saphira-ai.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://linkedin.com/company/saphira-ai", "x_url": "https://twitter.com/saphira_ai", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/50fee2cba3e02a1824e08a39a9224adb0d2098b5.png", "app_video_url": "https://bookface-images.s3.us-west-2.amazonaws.com/bf-public_profile/29647/app_video.mp4?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAQC4NIECAOTKCHR7A%2F20261020%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20261020T022720Z&X-Amz-Expires=60&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEHEaCXVzLXdlc3QtMiJHMEUCIQDeV7cQCYWa%2ByyakJaw7aH8e0HNWEyd2tO1Fn9KHjIpkgIgJPUveNomWrSf4Oq5DPuVDY7LKeaNJPvi5F2sbSx87Hoq5QMIOhAAGgwwMDYyMDE4MTEwNzIiDJ7%2FkqUU8p5mIeDC5CrCA7F4UggTYlVYiff4mYkoYiIpXa9r%2FKkUhcKwMNwtYpcuNTEBtH5xi9Hzkl3B%2FOYmUn%2FIacrdemsB9KrtOuRo%2FccaY%2Bs%2FSuIzime%2BcYuI7%2B%2Fg2nldjcm7YPCf32sIR8EflXc2916%2FDRMbztsRKDiQDL1ZKbK6YPHJppiQyVyRrrcCFD0X7tEf0D7QgK2DIpKnu8zGLzN4oAHn6xfHIgQnynrupcJbc9cga5AURtsRl7TfSM6XaGTtp1fNogyhUKX9f%2FYIL2pg03nlhLpRpDuqHpJ9qbbVsf%2FvboDHQ4IRRkiCaWH6GZwuTm%2FaXzTPIrAlVKH5%2F0RNaaExh%2Byw4VhHEEsSkHSs4mw%2BmNAKnW2FnWuldPRw5kn3j05dqhv5fkQxdp74JTYQe5wex1YN5PCok147bSKEuieYlIgH%2FiP9NY3Ym0ZRUWuo0zL40XWv9X3L1tLg%2BYWY0fCdhDKHGgTuesmbVajzEhu%2Bg9iWLptoK63cZ4UfO8oOd6sOc09XF6lBy%2BmD%2BSVmOfDWUOzz5ELD16slDTUwml0MZsttBoLDzldUc0olkl5nCAl23UqraiUXeaeW3yLOvJn%2BAD%2B%2FM6PvmZF0VzDn%2FdrWBjqlAVRsuTd0UsfPEqyKlBgBcSJTbWkHvSj10wzTCIqvOoZ3bz1TWza43iHLTCs7u%2FHmvoKE0qG5FTOsMYhLZb5XFdRretuo%2F1BjdoZt%2Fr0dHWGT4LLkmfYrkFclUq7u0pvMr6%2FR4I41ZYdCD3cWpGAcOrCQxKJukkkU%2Fx4O0IOnvZKvXzK4OISHe4XPgWQrnAJcSBOFX%2BXRwhpFbVXOOC%2BtEw%2BR3JTElw%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=76984abbd23aca3a771e67f5fffe47e1f1d9b2e14954c793a0ac2afe6b1829ab", "dday_video_url": "https://bookface-images.s3.us-west-2.amazonaws.com/video_event/65/1727459788-98ebaafc9e6edb74a44fb5c9ec779514/12927dbe517675b42c6befea3a26afaa.mp4?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAQC4NIECABPQ2AHNW%2F20261020%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20261020T022720Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&X-Amz-Signature=70d26199307862ba54e557629caf9cf94fbd10edf05281e911cc37dc2f89606d", "company_photos": [], "primary_partner": { "name": "Jared Friedman", "url": "https://www.ycombinator.com/people/jared-friedman" }, "founders": [ { "user_id": 1549881, "full_name": "Akshay Chalana", "title": "Founder/CEO", "founder_bio": "Co-Founder, CEO - Saphira AI\n - \nAutomating Safety+Systems Engineering: ex-Citadel (real-time trading workflow configuration), Apple (pb-scale dataset management for Siri and Vision Pro), Tesla (made sure batteries didn't explode in the heat of the sun), Meta (PyTorch/ONNX), Hyperloop (blew up and crashed pods)", "is_active": true, "linkedin_url": "https://linkedin.com/in/akshaychalana", "x_url": "https://twitter.com/ac2zoom", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/04ff32552fea0828ae6a9941bab65428a909eddc.jpg" }, { "user_id": 386679, "full_name": "Oscar Avatare", "title": "Founder/CTO", "founder_bio": "Saphira AI (S24)\n\nFormerly at Amazon and Twitter. \n\nPassionate about helping the next generation of innovative hardware companies build safe and compliant products faster. \n\nPer aspera ad astra. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/oavatare", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9090e195ceea72a74d097cd17d7e29e029b90341.jpg" } ], "jobs": [ { "id": 72982, "title": "Founding Full-Stack Engineer", "url": "https://www.ycombinator.com/companies/saphira-ai/jobs/coBVUDL-founding-full-stack-engineer", "location": "San Francisco, CA, US / Remote (US)", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$100K - $150K", "equity_range": "0.50% - 2.00%", "experience": "6+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 72983, "title": "Founding Applied AI Engineer", "url": "https://www.ycombinator.com/companies/saphira-ai/jobs/xzdpKAm-founding-applied-ai-engineer", "location": "San Francisco, CA, US / Remote (US)", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$100K - $150K", "equity_range": "0.50% - 2.00%", "experience": "6+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 79326, "title": "Senior Industrial Functional Safety Engineer", "url": "https://www.ycombinator.com/companies/saphira-ai/jobs/kpoYQnd-senior-industrial-functional-safety-engineer", "location": "San Francisco, CA, US / Remote (US; DE)", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$100K - $200K", "equity_range": "0.10% - 2.00%", "experience": "3+ years", "visa": "US citizenship/visa not required", "skills": [] }, { "id": 81814, "title": "Founding Account Executive - Enterprise Safety & Compliance (Hardware + AI)", "url": "https://www.ycombinator.com/companies/saphira-ai/jobs/dPGz0d4-founding-account-executive-enterprise-safety-compliance-hardware-ai", "location": "San Francisco, CA, US / Remote", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$100K - $150K", "equity_range": "0.50% - 1.00%", "experience": "6+ years", "visa": "US citizenship/visa not required", "skills": [] } ], "news": [], "launches": [ { "id": 82619, "title": "Saphira: Vanta for hardware", "tagline": "The easiest way to get safety certified.", "body": "**tl;dr: Hardware companies** use [Saphira](https://saphira.ai/) to easily **generate safety reports** and **get certified to sell** their product.\n\nWe’re [Oscar](https://www.linkedin.com/in/oavatare/) and [Akshay](https://www.linkedin.com/in/akshaychalana/), and we’ve built software for hardware and compliance at Twitter, Tesla, Amazon, and Hyperloop. \n\nWe’re making it really easy to get **UL, CE, ISO, and TÜV** certifications like **ISO 10218** and **ISO 26262** for hardware products.\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXfgRUpv-5EuNnEHb2YIIuVzkGDYVFRp2ZwD4LryC9TKyufX-m6IO4V8qlC90YErv5esvNgJjWF-CXaxHa1OwaBKHuRCZarwEg_h8aBjzqPVt9kxFd-aQB_m8D_SL7nwOyiLf1k0h07SsyflNQUdd_184BAh?key=Migms48Dt65ISx6x08AVig)\n\n# What are safety certifications, and who needs them?\n\nBuilding **industrial machinery** that can hurt someone, like robot arms and autonomous trucks?  Your **customers will mandate** TÜV safety certification per particular ISO and IEC standards!  \n\nBuilding **small appliances** that plug into the grid?  Many **retailers won’t sell your product,** and **commercial buildings won’t install** it unless you’re UL or CE certified!  \n\nBuilding a **satellite or communication system**?  The **FCC won’t allow** it to operate without certification!\n\nBuilding **defense equipment** for the government?  **They won’t buy** it unless it’s compliant with the relevant MIL-STDs!\n\n# Why did we start Saphira?\n\nHardware products can’t get to market because teams **don’t know how to navigate the certification process**. Unlike SaaS, there are no tools like Vanta that tell you exactly what you need to test, change, and re-evaluate in your designs to pass audits. This sucks because every hardware company we talk to gets stuck in **rework cycles** with their consultants and auditors that they call **“horrendous and intimidating”** (real customer quote).\n\nWe've seen this at Amazon and Tesla, where engineers don't know when a change breaks certification. Each iteration requires them to work with consultants to understand what broke, lengthening the time to launch.\n\nWe created Saphira to empower these innovators to **rapidly** build complex products **that actually work**, all while achieving and maintaining compliance with the **evolving regulatory landscape**.\n\n# What does Saphira do?\n\nSaphira tells you exactly what you need to account for in your **design and testing** to **achieve and maintain** hardware safety certification and compliance. We’re a centralized data source for the **requirements, tests, and standards** that are relevant to your product, making it straightforward to **identify and triage safety and compliance risks** without wasting months of time and thousands of dollars on **slow safety consultants**.\n\nSaphira automates **traceability**: regulatory reports by engineers that prove that requirements like “the robot arm won’t shock an attendant if touched while in motion” were implemented and validated. These reports are **painful and tedious** to produce. By maintaining references to all necessary source information, Saphira can automatically generate these reports, and even automatically identify which additional standard clauses are relevant to each requirement or design value.\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXfaxD8bMvNCW5gDewAe4uowrZviZqV3i00DsW2NM-2eVsuZCkRj_4t0oGKIJljGp0GTnS_AFmLlm1qLNUF4teYn5VTi6ZDyM1HtM1Vl56x3t0O4AKTWSq6FtmddRQWAtpes92noQLkImJgftBhWOqOKmWf0?key=Migms48Dt65ISx6x08AVig)\n\n# Who is Saphira for?\n\nSaphira is for engineers at hardware organizations of any scale and size:\n\n* The **safety engineering team** at an industrial robotics company can use Saphira’s **compliance report generator** (i.e. ISO-12100 and ISO-10218) to **achieve certification** to operate in the US.\n* An **engineering leader** at a hardware startup that needs UL certs to sell to more customers can use Saphira to speed up their process by months by avoiding hiring a slow safety consultant. \n* A **systems engineer** at an aerospace/defense company can use Saphira’s **AI tooling** to understand **how various military and government standards** (such as MIL-STD-810 or ISO-26262) are relevant to each facet of their specs and models.\n\n# Ask\n\n* We are experts in certifications for hardware companies.  If you think you might need this but aren't sure how to approach it, we are happy to help for free — [just reach out](mailto:akshay@saphira.ai).\n* If you know other engineering leaders seeking to improve their certification processes, [connect us](mailto:akshay@saphira.ai)! We are most interested in talking to leaders in industrial robotics, energy systems, autos, aeros, and defense. \n* If you worked at a larger hardware company before and saw any of these issues, we would love to talk just to learn from your experience\n* We would love product feedback: [book a demo](https://calendly.com/ac2zoom/30min)!", "url": "https://www.ycombinator.com/launches/LUZ-saphira-vanta-for-hardware", "votes": 81, "created_at": "2024-07-31T18:47:18.084Z" }, { "id": 81405, "title": "Saphira AI - Orchestrating safe hardware engineering", "tagline": "Intelligent engineering design management for safety-critical products", "body": "**tl;dr:** We capture **requirements and design** in a central platform so that safety for complex physical products can be continuously evaluated: a simple and easy-to-use alternative to Jama or IBM DOORS.\n\nWe’re [Oscar](https://www.linkedin.com/in/oavatare/) and [Akshay](https://www.linkedin.com/in/akshaychalana/), and we’ve built hardware controls and virtualization for Tesla, Amazon, and Hyperloop. We’ve blown up prototypes and fried lasers by not applying effective system design and are building tools to make it easier to prevent such failures.\n\n![uploaded image](/media/?type=post&id=81405&key=user_uploads/1549881/efe6234d-8f86-4d19-b499-4fc3380514eb)\n\n# Why did we start Saphira?\n\nWhile building Hyperloop pods, we struggled with unusual and novel constraints: we had to take the propulsion, braking, and electronics of a sophisticated train and make them work perfectly in a vacuum chamber. Basic things that work in the normal world just didn’t there: network activity was severely throttled so remote control and telemetry were difficult, and electronics would arc more easily, requiring additional protections. This mandated that we put together clear **product requirements** that we needed to integrate and validate across the entire implementation stack, which turned out to be so hard that we struggled to get our pods working in time and faced weeks of all-nighters just to fail review and be barred from the race!  \n\nSince then, we’ve been searching for how large organizations we’ve been part of, like Tesla and Amazon, have made this easier: in truth, they haven’t! The most mature, most established industries, such as aerospace, account for this with **process**: intensive modeling, documentation, and data entry that **innovators don’t have time for**. When regulation and certification standards are put in place, **products are taken off the market or endure years-long delays**. \n\nWe created Saphira to empower these innovators to rapidly build complex products **that actually work**, all while achieving and maintaining compliance with the **evolving regulatory landscape**.\n\n![](https://lh7-us.googleusercontent.com/docsz/AD_4nXc5i1avhrYfKOrHWzQzEyt6C88KBCZnFtCGL4YRw6nTaPipxU2-cXEpcxY4d9qHtMD0sO84I2xragUNrmUAdAju9BAD-HWgoS54BIUZX2U-bNV4n_cv0WnQwgnTq-zsSdo5Vf-6L6h8SJ0dKuJoPWOEygG3?key=Ebyb5ZyTMv3M7lBQpS9B7Q)\n\n# What does Saphira do?\n\nSaphira is a **single source of truth** where requirements, architecture, and tests can all be entered, parsed from existing documents, and tied together so that safety risks are identified and triaged quickly.\n\nSaphira is the easiest way to demonstrate **traceability**: regulatory reports by engineers that prove that requirements like “the Hyperloop pod must not catch fire in a vacuum chamber” were implemented and validated. These reports are painful and tedious to produce: by maintaining references to all the source information for them, Saphira can automatically generate them! Most importantly, Saphira removes systems engineers as a bottleneck to updating foundational engineering data, enabling any engineer to model and report on safety and compliance, making traceability easy for any fast-moving team.\n\n![](https://lh7-us.googleusercontent.com/docsz/AD_4nXe_cgZGZGZLN8qYxQsHQhSKZbvtyL0vH1UGAAEu8uQr02TBKvptPzordelrm_y0Ltrns4l7GOCUsEjQYy1F8l1igdLtVx85IywthG9bRGS6CsAQI9zTzAVYbLV6aIdKlFwj64DEsu2_hGe-PMGeew_SbAl2?key=Ebyb5ZyTMv3M7lBQpS9B7Q)\n\nUltimately, we see traceability as not just a regulatory requirement but an enabler for automated engineering: as engineers define the relationships we use to sync data between, say, their codebase and task management system, this can be used to automatically propagate changes across an entire system! For example, one could change the requirement for a motor to produce 200 Nm of torque to 300 Nm: since they had linked this through a formula in Saphira to the current draw requirement from the battery, we would automatically update that in the power distribution PCB schematics, short-circuiting hours of work per change!\n\n# Who is Saphira for?\n\nSaphira is for engineers at innovative companies designing and building safety-critical hardware and software systems at organizations of any size:\n\n* The **safety engineering team** at an industrial robotics company can use Saphira’s **compliance report generator** (i.e. ISO-12100 and ISO-10218) to **achieve certification** to operate in the US a year faster than it otherwise would be able to.\n* A **systems engineer** at an AV startup can use Saphira’s test management framework to perform **release safety reviews** 50% faster and double their pace of software iteration.\n* The **head of hardware** responsible for **writing product requirements** at an energy startup that makes residential batteries can use Saphira’s **AI tooling** to parse design documents and generate supplier specifications in half the time to get faster quotes from prospective manufacturers and ship to customers sooner.\n\n# Ask\n\n* If you are seeking an engineering/application lifecycle management, requirements management, or systems engineering tool for your hardware company, [let’s talk](mailto:akshay@saphira.ai)!\n* If you know other engineering leaders seeking to improve their processes, [connect us](mailto:akshay@saphira.ai)! We are most interested in talking to leaders in industrial robotics, energy systems, autos, aeros, and defense. \n* If you worked at a larger hardware company before and saw any of these issues, we would love to talk just to learn from your experience\n* We would love product feedback: [book a demo](https://calendly.com/ac2zoom/30min)!", "url": "https://www.ycombinator.com/launches/LAz-saphira-ai-orchestrating-safe-hardware-engineering", "votes": 113, "created_at": "2024-06-10T15:48:04.873Z" } ] }, { "id": 29589, "name": "Theseus", "slug": "theseus", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/05b004a38c0a5df5a4e151b258151cd9a38f08c8.png", "website": "https://theseus.us", "all_locations": "San Francisco, CA, USA", "long_description": "Theseus builds visual navigation software for GPS-denied drone operations. Using onboard cameras, inertial sensors, and satellite reference imagery, our system computes position fixes entirely passively. The system is entirely self contained, can't be jammed and has no RF signature.", "one_liner": "GPS Denied Navigation for Drones", "team_size": 7, "industry": "Industrials", "subindustry": "Industrials -> Drones", "launched_at": 1725406335, "tags": [ "Robotics", "Drones", "Defense" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "Industrials", "Drones" ], "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/theseus", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/theseus.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/theseustech/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/05b004a38c0a5df5a4e151b258151cd9a38f08c8.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": 1290514, "full_name": "Ian Laffey", "title": "Founder", "founder_bio": "GPS-denied nav for drones", "is_active": true, "linkedin_url": "https://linkedin.com/in/ian-laffey-943200247", "x_url": "https://twitter.com/ilaffey2", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0dea34f6fa9fe3e815c86e9a875ee467ffc01ab0.jpg" }, { "user_id": 917795, "full_name": "Sacha Lévy", "title": "Founder", "founder_bio": "Sacha Lévy is Co-Founder and Chief Technology Officer of Theseus Technology Corporation, where he develops visual navigation systems that enable drones to operate autonomously without GPS.\n\nBefore founding Theseus, he was a PhD student in Computer Science at Yale University, where his research applied large language models to biological data and was published in top machine learning conferences. He holds a B.Eng. in Computer Engineering from McGill University.", "is_active": true, "linkedin_url": "https://linkedin.com/in/sacha-levy", "x_url": "https://x.com/sachalevy3", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d81061c1de4f0c0f74d5e91ca8625a9b5c3d1446.jpg" } ], "jobs": [ { "id": 92386, "title": "Lead Robotics Software Engineer, Localization", "url": "https://www.ycombinator.com/companies/theseus/jobs/yUlD33Z-lead-robotics-software-engineer-localization", "location": "San Francisco, CA, US / Remote (US)", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$200K - $300K", "equity_range": "0.10% - 0.50%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [ "C++", "Python", "Linux" ] }, { "id": 92621, "title": "Forward Deployed Software Engineer", "url": "https://www.ycombinator.com/companies/theseus/jobs/NYFHBhe-forward-deployed-software-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$80K - $120K", "equity_range": "0.10% - 0.50%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [ "C++", "Python" ] } ], "news": [ { "title": "Defense tech Theseus landed Y Combinator, the US Special Forces, and $4.3M from a tweet | TechCrunch", "url": "https://techcrunch.com/2025/04/17/defense-tech-theseus-landed-y-combinator-the-us-special-forces-and-4-3m-from-a-tweet/", "date": "Apr 17, 2025" } ], "launches": [ { "id": 83768, "title": "Theseus: GPS Denied Navigation for Drones", "tagline": "Our Visual Navigation System is a replacement for GPS that works with any drone.", "body": "![uploaded image](/media/?type=post&id=83768&key=user_uploads/1290514/a1856391-04dc-473d-92dd-9ad6c8a8cb95)\n\nSix months ago we did a hackathon, this month we sold to SOCOM. Our Visual Navigation System (VNS) uses cameras, an inertial measurement unit, and pre-loaded satellite imagery to determine it’s position and send a fake GPS signal to any drone. Integrations typically take <30min.\n\n### How It Started\n\n![uploaded image](/media/?type=post&id=83768&key=user_uploads/1290514/3f680d0f-91e3-4f9e-bf5f-212a076df8fa)\n\nIn February, [Carl](https://www.linkedin.com/in/carlscho) was a Senior at Stanford, [Sacha](https://linkedin.com/in/sacha-levy) was a PhD student at Yale, and [Ian](https://linkedin.com/in/ian-laffey-943200247) was working with a British celebrity. After our post went viral, we spent weeks talking with troops on the ground, drone manufacturers, and DoD.\n\nWe learned that:\n\n\\- The front lines of Ukraine are 100% GPS-denied\n\n\\- Cheap, DIY drones are extremely effective but typically rely on GPS\n\n\\- Existing GPS alternatives are extremely heavy and extremely expensive\n\nWe set out to create a low-cost, low-weight replacement for GPS that works with any drone.\n\n### How It’s Going\n\n![uploaded image](/media/?type=post&id=83768&key=user_uploads/1290514/edd612ed-a0d4-421d-afe4-36931183b93f)\n\nOur first customer in the Special Forces has enabled us to push our VNS to its limits, and the results have been impressive. Here are a few excerpts from a memorandum written by the Captain we work with:\n\n_“Having tested the Theseus’ VizNav system for a week, I am convinced that their technology presents the best solution for a current, and ever-expanding urgent operational need.”_\n\n![uploaded image](/media/?type=post&id=83768&key=user_uploads/1290514/edd4eb3e-a568-4519-84a8-de2020556437)\n\n_“As a company, Theseus has shown a willingness to seek the ground truth from the operator and make improvements based on these recommendations immediately. The progress they have made with limited funding gives me incredible confidence that they act quicker and more efficiently than any other vendors we have worked with.”_\n\n![uploaded image](/media/?type=post&id=83768&key=user_uploads/1290514/7fe82322-4001-49c7-b9ab-255c2a9174d6)\n\nDue to the sensitive nature of our product, technical details and customer-specific information in this post will be limited. We are happy to discuss results in more detail privately.\n\n### Going Forward\n\n![uploaded image](/media/?type=post&id=83768&key=user_uploads/1290514/5acb4bc0-1658-47f2-83ef-38d0dd6d3601)\n\nAmerica is way behind. The current demand for drones in Ukraine is 1-2 million yearly. Every country in the world sees this and is in the process of building out its arsenal. Our product affordably enables an entirely new capability set for every one of these platforms.\n\nWe have sold units to multiple customers, have six-figure LOIs from large drone manufacturers, integrations scheduled, and eight figures in funding for our VNS requested by the DoD for FY25.\n\nThe West needs to build millions of drones, and all of those drones need Theseus.\n\n![uploaded image](/media/?type=post&id=83768&key=user_uploads/1290514/3f997243-9cf5-4868-9a58-fda72313a613)\n\n", "url": "https://www.ycombinator.com/launches/Ln6-theseus-gps-denied-navigation-for-drones", "votes": 57, "created_at": "2024-09-04T22:35:57.651Z" } ] }, { "id": 29597, "name": "Spaceium Inc", "slug": "spaceium-inc", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0afea0e3a81a3c4895401d9a1e4f5620a04a076b.png", "website": "https://spaceium.com", "all_locations": "Ottawa, ON, Canada", "long_description": "Spaceium builds fully automated space stations to refuel and repair spacecraft. We have secured $86.1 million in binding commercial contracts and have an additional $230 million in the pipeline. Additionally, we have 1 billion dollars in letters of intent. We have successfully tested our hardware, which will launch to space next year. \r\n\r\nOur fully automated space stations will efficiently store and transfer both cryogenic (extremely cold) and non-cryogenic fuels with zero loss during storage and transfer. And they can transfer fuel seamlessly to any spacecraft design using our proprietary modular robotic arm.\r\n\r\nOur customers include launch vehicles, orbital transfer vehicles, moon landers, and spacecraft that benefit from increased payload capacity and extended travel capabilities. Our long-term vision is to build service hubs along the space superhighway to connect Earth to Moon and Mars and help humanity to become multi multi-planetary species\r\n", "one_liner": "In-Space Refueling", "team_size": null, "industry": "Industrials", "subindustry": "Industrials -> Aviation and Space", "launched_at": 1715783569, "tags": [ "Hard Tech", "Robotics", "Space Exploration", "Aerospace" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "Industrials", "Aviation and Space" ], "regions": [ "Canada", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/spaceium-inc", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/spaceium-inc.json", "year_founded": 2023, "city": "Ottawa", "country": "CA", "linkedin_url": "https://www.linkedin.com/company/spaceium-inc", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/0afea0e3a81a3c4895401d9a1e4f5620a04a076b.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": 985204, "full_name": "Ashi Dissanayake", "title": "Founder/CEO", "founder_bio": "Co-Founder & CEO @ Spaceium (S24) \nI love space and grew up wanting to be an astronaut one day. I co-founded Spaceium to build space infrastructure for a better new space economy. 
\nI specialize in orbital mechanics and rocket propulsion systems. Previously, I worked on Aerodynamic models for NASA, built models for interplanetary transfers for an unmanned return mission to an asteroid in real time, and built rocket engines, payload structures, and recovery systems. ", "is_active": true, "linkedin_url": "https://linkedin.com/in/ashi-dissanayake", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e89b228c2cf8c0d080711c619dd0f4632d64e346.jpg" }, { "user_id": 1009478, "full_name": "Reza Fetanat", "title": "Founder/CTO", "founder_bio": "Co-founder & CTO @ Spaceium (S24).\nBelieve in developing in-space infrastructure to sustainably explore space and find a better place to call home, like the first caveman stepping out of their cave. Help humanity become a multiplanetary species.\nI led a rocket program at university. We successfully launched 3 rockets and became fastest growing team. \nFully developed 4 rocket engines and built a propulsion stability model. \nBuilt many robots including rocket tracker for recovery.", "is_active": true, "linkedin_url": "https://linkedin.com/in/rezafetanat", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e7e9c6e7386b210ae285efac855201ec036fdbcf.jpg" } ], "jobs": [ { "id": 92025, "title": "Embedded Software Engineer – Canada", "url": "https://www.ycombinator.com/companies/spaceium-inc/jobs/kq3uAHj-embedded-software-engineer-canada", "location": "Ottawa, ON, CA / Ottawa, Ontario, CA", "type": "Full-time", "role": "Engineering", "role_type": "Embedded systems", "salary_range": "$75K - $110K CAD", "equity_range": "0.10% - 0.50%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [ "C", "C++" ] } ], "news": [ { "title": "Y Combinator grad Spaceium raises oversubscribed $6.3M for space re-fueling | TechCrunch", "url": "https://techcrunch.com/2025/01/23/space-re-fueling-startup-spacium-raises-6-3-million/", "date": "Jan 23, 2025" }, { "title": "Spaceium Partners Space Machines for Space Cryogenic Refuelling", "url": "https://spacewatch.global/2024/01/spaceium-partners-space-machines-for-space-cryogenic-refuelling/", "date": "Jan 16, 2024" }, { "title": "Spaceium and The Exploration Company Partner for In-Space Servicing", "url": "https://www.google.com/search?client=safari&rls=en&q=spaceium+and+exploration+company&ie=UTF-8&oe=UTF-8", "date": "Sep 13, 2023" } ], "launches": [ { "id": 81561, "title": "🚀 Spaceium: Automated space stations that refuel and repair spacecraft in orbit", "tagline": "Enabling deep space exploration through unmanned service stations.", "body": "**TL;DR:** **Spaceium is building unmanned servicing stations in space to improve mission efficiency. Our stations will offer proprietary cryogenic fuel storage and transfer technology, enabling in-space refueling and providing robotic repair solutions, a capability that sets us apart. We aim to launch servicing stations in Low Earth Orbit in 2025 and expand to Geostationary Orbit, the Moon, and Mars by 2030.**\n\n\"Helping space explorers go \"where no man has gone before\" - Captain James T. Kirk :)\n\n**_ _** \n\nHi, everyone. We are [Ashi Dissanayake](https://linkedin.com/in/ashi-dissanayake) and [Reza Fetanat](https://linkedin.com/in/rezafetanat), the team behind [Spaceium](https://spaceium.com/).\n\n![uploaded image](/media/?type=post&id=81561&key=user_uploads/985204/76cbc58c-243e-410f-99ca-5eaa12bdeb79)\n\n**Here's a brief introduction:**\n\n**Ashi** is an Aerospace Engineer specializing in **Orbital Mechanics and rocket propulsion.** Ashi has worked on real-time simulation models for uncrewed return missions to asteroids and on **NASA-related aerodynamics projects**.\n\n**Reza** is also a space enthusiast and a Mechanical Engineer specializing in **Robotics, structures, and Cryogenics**. Reza has worked on revitalizing the **LR-101 engine, which was used on Atlas, Thor, and Delta launch vehicles.**\n\nWe first met while leading the University of Ottawa's rocketry team, where we built high-powered rockets to send scientific payloads to different altitudes. In our spare time, we enjoyed working together to build rockets in the backyard, sometimes leading to interesting experiences with backyard fires. 🔥\n\nThroughout our careers, we've noticed the constraints on space missions due to the lack of ability to refuel or repair spacecraft in orbit. The current solutions are costly, and a centralized location where spacecraft can refuel and repair is a massive necessity. We are on a mission to build the missing piece of space infrastructure that connects the space superhighway, Just like how service stations were built on Earth back in the day!\n\n# **The problem**\n\nAll spacecraft and space missions face a standard set of challenges. Fuel is a limited and difficult resource to transport. In the event of a significant issue, spacecraft cannot be repaired in space. These challenges have significantly hindered efficiency in current space missions and have been a substantial obstacle in humanity's quest to explore space further. \n\nUnlike a road trip where refueling is common and convenient, spacecraft face a unique challenge. Spacecraft cannot refuel along the way. Instead, they must carry all the fuel required for the mission from Earth. **An overwhelming 85% - 95% of the launch weight is fuel on a typical launch vehicle, with 80-90% burned off to reach orbit.** 🚀\n\nAs a result, spacecraft that transport loads in space (space tugs) can only perform, **on average, 25% as many missions as they're technically capable of due to the absence of refueling in space.** 🛰️\n\nFurthermore, even if a spacecraft wanted to carry additional fuel, it is not easy. Current spacecraft require cryogenic fuels such as liquid oxygen, methane, and liquid hydrogen, which must be stored and transferred at extremely low temperatures of -285°F. 🥶 Environmental factors in space, such as heat and radiation, increase the temperature of these fuels, causing them to boil off (vaporize).\n\nIn addition, **there is no current solution for spacecraft repair**. This means that today's spacecraft must operate flawlessly to maximize efficiency, which is only sometimes the case. For instance, Eutelsat Communications' satellites experienced power loss mid-mission with no option for repair, resulting in a **$30 million** revenue loss. **With Spaceium's multifunction robotic arm, the communication satellite could have been fixed.** 🛠️\n\n# **Solution**\n\n_Automated servicing stations in space 🌎🚀🛰️_\n\nOur primary solution aims to improve space missions' efficiency by addressing refueling challenges. **The developed cryogenic fuel storage and transfer technology is designed to store fuel without any boil-off for multiple years in space.** As a result, spacecraft can now refuel in space, carry more payload, and travel longer distances.\n\nTwo fundamental principles guide our proprietary Zero Boil Off (ZBO) technology. \n\n* Firstly, we prevent heat from entering the system through a unique tank design, insulation, and coating system. \n* Secondly, our innovative multistage closed-loop cooling system evenly removes the heat from the cryogenic fuel and transfers it to radiators, ensuring zero boil-off.\n\n \n\nOur cryogenic storage system is not only efficient but also highly scalable. Our current cooling system is **65% more efficient** than any other cooling system, and our scalable storage system can store up to 30 metric tons of fuel, making it adaptable to a wide range of space missions and requirements.\n\nAfter successfully addressing the challenge of transporting large amounts of space fuel, we turned our attention to developing technology for delivering this fuel to spacecraft in space. This is achieved through the use of a **multifunction robotic arm**. This advanced arm can securely dock with incoming spacecraft and initiate the fuel transfer. **The fluid system built within the arm allows the transfer of different fuel types through the robotic arm**. The built-in thermal system ensures that fuel is transferred to the customer's spacecraft at the correct temperature without any boil-off issues associated with cryogenic fuels in space.\n\nAdditionally, the same robotic arm is versatile enough to handle non-cryogenic fuels as well, providing a comprehensive solution for refueling spacecraft in space.\n\nIn addition to safe and efficient fuel transfer, the robotic arm is equipped with an interchangeable end effector designed for in-space repairs. In-space repairs are achieved through a fully automated robotic arm that can retrieve tools from a stored \"toolbox\" within the system. This innovative feature ensures that even in the event of a significant issue, spacecraft can be repaired in space, minimizing the risk of mission failure and maximizing mission efficiency.\n\nOur vision is to transform the space industry. Starting in Low Earth Orbit (LEO), our servicing infrastructure will progressively expand to encompass Geostationary Earth Orbit (GEO), the moon, and eventually Mars. We are on a mission to empower space missions to go further, explore more, and achieve what was once deemed impossible.\n\n**Who can benefit from our service stations in space** \n\n* **Launch vehicles** \n* **Orbital transfer vehicles** \n* **Space tugs** \n* **Moon landers** \n* **Satellites**\n\n# **Ask**\n\n* **Feedback, comments, or questions.** Reach out to us to learn how we can help with your missions.\n* **Warm Intros.** If you know or work with any launch providers, space companies, or satellite providers who could benefit from our service, please introduce us to them. 🛰 \n* **Follow.** Follow us on [LinkedIn](https://www.linkedin.com/company/spaceium-inc), [X](https://x.com/SpaceiumInc). Cool news coming soon\n* **Share.** Please share this post with your network so we can reach more space companies looking for refueling, repairs, and other services for their future missions. 👾\n\n# Email us [HERE](mailto:founders@spaceium.com).\n\nThank you!", "url": "https://www.ycombinator.com/launches/LDV-spaceium-automated-space-stations-that-refuel-and-repair-spacecraft-in-orbit", "votes": 30, "created_at": "2024-06-17T15:53:21.197Z" } ] }, { "id": 29753, "name": "Autumn Labs", "slug": "autumn-labs", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/5df469af020f91ac0b4d19796abb3d31c3518288.png", "website": "https://www.autumnlabs.io/", "all_locations": "San Francisco, CA, USA", "long_description": "Autumn Labs delivers a developer-friendly platform for monitoring and managing modern manufacturing lines. Seamlessly integrating with robotic stations—automated test stations, robotic assembly cells, and industrial arms—it ensures full traceability, live data monitoring, and secure data transport. We prioritize streamlining factory operations, boosting production quality, and preventing supply chain disruptions, all while offering an effortless onboarding experience for engineers and manufacturers.", "one_liner": "Datadog for industrial robots", "team_size": 3, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1724817075, "tags": [ "Hardware", "Robotic Process Automation", "SaaS", "Robotics", "Manufacturing" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada", "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/autumn-labs", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/autumn-labs.json", "year_founded": 2023, "city": "San Francisco", "country": "US", "linkedin_url": "", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/5df469af020f91ac0b4d19796abb3d31c3518288.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": 991674, "full_name": "Prathik Muppidi", "title": "Founder/CEO", "founder_bio": "University of Waterloo Mechatronics Engineering, ex-Google Engineer", "is_active": true, "linkedin_url": "https://linkedin.com/in/prathikmuppidi", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ae728870bbb8d337d10dc9aecf09f3058982fe3b.jpg" }, { "user_id": 1250574, "full_name": "Harsh Bhatt", "title": "Founder/CTO", "founder_bio": "Ex. Apple | Mechatronics Engineering @ University of Waterloo", "is_active": true, "linkedin_url": "https://linkedin.com/in/harshmbhatt", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f9cfe0f35ded2657954fedd4b377c34d61c80e6c.jpg" }, { "user_id": 309960, "full_name": "Sam Monga", "title": "Founder/CTO", "founder_bio": "Hardware software engineer", "is_active": true, "linkedin_url": "https://linkedin.com/in/sammonga", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ba15caa4ff5b343488e5acfc1fd1063b92da206c.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 83709, "title": "Autumn Labs - Monitoring platform for industrial robots and manufacturing", "tagline": "Detect machine downtime, process quality, and factory issues — in real time. ", "body": "**tl;dr:** [Autumn Labs](https://www.autumnlabs.io/) delivers a unified platform to monitor and manage modern factories. Our SDK seamlessly integrates with manufacturing systems (test stations, assembly robots, industrial arms, and manual stations) to provide real-time monitoring, control, and production data management. The result? Lower operation costs, higher product quality, and a smoother production line.\n\n🍁 = 🤖 + 🏭 + 📊\n\n### **Problem - Advanced Machines, Outdated Infrastructure**\n\nThe adoption of robots in manufacturing is exploding, especially to keep up with producing increasingly more complex products and shortages in skilled labor. However, the infrastructure in which these robots would be deployed is still years behind.\n\nWithout effective systems, manufacturing physical products might seem like an insurmountable black box, especially when they are made in factories on another continent where critical information is only reported via spreadsheets every other week.\n\nThe past: [_src_](https://www.youtube.com/watch?app=desktop&v=xqPfY8S5HJ4)\n\n![uploaded image](/media/?type=post&id=83709&key=user_uploads/991674/84c0d0be-c84c-4872-84f8-20aa591d28a6)\n\nToday: [_src_](https://www.youtube.com/watch?app=desktop&v=luFGI13Mv8o)\n\n![uploaded image](/media/?type=post&id=83709&key=user_uploads/991674/2da6a941-47af-48e3-aaf4-4ddee5351437)\n\nBut the manufacturing data is always lagging and still looks like this:\n\n![uploaded image](/media/?type=post&id=83709&key=user_uploads/991674/5472966f-362b-483b-9117-37b4730a3676)\n\n### **Solution - Seamless Integration, Real-time insights**\n\nAutumn Labs provides an SDK that’s easy to integrate into any robotic architecture, enabling seamless monitoring and management of machines and, ultimately, the factory in which they reside. This way, robotic integrators and developers have a standard platform where they pull and push critical data that’s specific to their machine’s tasks. Both factory operations and engineering teams are able to get actionable data they need to improve production utilizations and process quality.\n\n_A Unified Platform for Hybrid Factories:_\n\nOur platform is built for hybrid factory lines, too, allowing for seamless integration of manual human assembly stations. Factory personnel can now get a holistic view of your factory's performance—robotic or not.\n\n![uploaded image](/media/?type=post&id=83709&key=user_uploads/991674/8d55d085-5141-4c8e-a11f-d4751a050099)\n\nWith Autumn Labs, you can track, triage, and push fixes for:\n\n1. Robotic assembly stations/cells\n2. Automated test stations\n3. Palletizing robots\n4. Manual assembly stations\n\n### **Traction - Real Results, Real Impact:**\n\nAutumn Labs is already monitoring and managing 50+ automated factory stations in 4 different consumer electronics factory lines across multiple companies and contract manufacturers. There’s a good chance that a product you use today has gone through our platform.\n\nWhy our customers love us:\n\n1. Clear insights into Manufacturing Value Added (MVA) costs\n2. Increased machine utilization\n3. Rapid improvements in production quality\n4. Enhanced product development cycles\n\n### **Meet the Founders**\n\nWe’re [Sam](https://www.linkedin.com/in/sammonga/), [Harsh](https://www.linkedin.com/in/harshmbhatt/), and [Pra](https://www.linkedin.com/in/prathikmuppidi/)[thik](https://www.linkedin.com/in/harshmbhatt/) — Mechatronics engineers from the University of Waterloo with decades of combined experience at Apple (iPhone), Google (Nest), and Meta (Oculus). After countless sleepless nights fixing robotic assembly lines and test stations, we decided it was time to create the ultimate tool for manufacturing. We’re building the solution we wish we had back then.\n\n![uploaded image](/media/?type=post&id=83709&key=user_uploads/991674/4ecd6fa2-6352-46ae-a602-f69219f0fe93)\n\n### **Our Ask - Let's Transform Manufacturing Together**\n\nKnow someone struggling to get real-time data from robots, test stations, or factories? Let’s talk. Reach us at [founders@autumnlabs.io](mailto:founders@autumnlabs.io)", "url": "https://www.ycombinator.com/launches/Lm9-autumn-labs-monitoring-platform-for-industrial-robots-and-manufacturing", "votes": 35, "created_at": "2024-09-03T16:30:31.314Z" } ] }, { "id": 29763, "name": "Piggy Robotics", "slug": "piggy-robotics", "former_names": [ "RigManic" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/bb8bcc76da3e91c1a436eea5e5eec4075f3deb89.png", "website": "https://piggyrobotics.com", "all_locations": "London, England, United Kingdom", "long_description": "We build humanoid robots that do your chores at iPhone prices. Just like the millions of cars generating data for self-driving, we need millions of humanoids generating real-world data for general-purpose robotics. Humanoid companies today can only manufacture hundreds a year because motors are expensive and slow to assemble. We use artificial muscles. Each muscle is just a tube wrapped in braided fibre, and the whole robot is powered by a single pump — which means we can mass-produce humanoids by the millions. Our design is built for that scale from day one and is cheap enough to enter billions of homes.", "one_liner": "Humanoid robots that do your chores for the price of an iPhone!", "team_size": 5, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1756389316, "tags": [ "Smart Home Assistants", "Robotics", "AI", "Home Automation" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "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/piggy-robotics", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/piggy-robotics.json", "year_founded": 2024, "city": "London", "country": "GB", "linkedin_url": "https://www.linkedin.com/company/piggy-robotics/", "x_url": "https://x.com/PiggyRobotics", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/bb8bcc76da3e91c1a436eea5e5eec4075f3deb89.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": 1476712, "full_name": "Richard Gong", "title": "Founder/CEO", "founder_bio": "Dropped out of medicine at Oxford to build humanoid robots for the home.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/richard-g-15852b22b/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/81c7dc84e57f6a45dd2d098072df6cdf5c873de1.jpg" }, { "user_id": 3244838, "full_name": "Chenny (Qianyi) Deng", "title": "Founder", "founder_bio": "Founder @ Piggy Robotics (YC F25) ｜ PhD Candidate in Computer Science @ the University of Oxford ｜ Ex-Tencent AI researcher ｜ Founded the largest laser-tag arena in my city at age 13", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/qianyi-deng/", "x_url": "https://x.com/Chenny_Deng33", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e7b598f4ae3dd0f4dd4988e9c3e4e0bdb0fc577f.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 95684, "title": "Piggy Robotics - Humanoid robots", "tagline": "We built a mass-producible humanoid robot for less than $1000 in 2 months.", "body": "Hello! We’re [Richard ](https://www.linkedin.com/in/richard-g-15852b22b)and [Chenny](https://www.linkedin.com/in/qianyi-deng/), founders of Piggy Robotics. We build mass-producible humanoid robots that do your chores at iPhone prices.\n\nBelow is why our architecture is uniquely positioned to win the humanoid race:\n\n1\\. We built a **full-size**, **mass-producible** humanoid robot in **2 months**, complete with custom muscles, valves, and pumps for **less than $1000**. For comparison, other humanoid companies with hundreds of millions in cash spent years developing their actuators before touching a full prototype. We’re the most capital-efficient humanoid company, and we’re on track to catch up with incumbents that have far more capital within one year.\n\n[Piggy Robotics F25 Launch](https://www.youtube.com/shorts/ty0fOJORnoc)\n\n2\\. **Mass production** must happen before **autonomy**. Tesla collects hundreds of thousands of hours of driving data per day from cars with basically 2 DoF. A humanoid has >50 DoF. To collect the same amount of data, you need >100K humanoid robots deployed. Existing humanoid companies can only produce a few hundred units per year. Our artificial muscles are far cheaper and simpler, meaning we can manufacture millions of humanoids and reach autonomy far sooner.\n\n️3. Only our humanoid at **iPhone prices** can **enter every home**. A household robot cannot be a 70kg, $20k metal beast. At that price point, adoption follows car-level economics. New cars mostly cost over $20k, and the entire world buys only around 75 million per year. But at $2k, adoption shifts into phone-level territory, where the world buys over a billion smartphones every year. Only an architecture built around cheap, simple-to-produce artificial muscles can reach phone-scale manufacturing quickly and make that future possible.\n\n**Team**\n\n[Richard ](https://www.linkedin.com/in/richard-g-15852b22b)studied **Medicine** at **Oxford University**, built AI systems for personalized cancer vaccines, and has a deep understanding of human anatomy and biomechanicsx—knowledge that is directly relevant to designing artificial muscles and full-body actuation.\n\n[Chenny ](https://www.linkedin.com/in/qianyi-deng/)trained AI models to read human motion—the foundational step for teleoperation and future autonomy—while doing her **PhD in Computer Science** at **Oxford University**. She previously worked on AI at Tencent. Fun fact: at age 13, Chenny built the largest laser-tag centre in her city.\n\nTogether, we spent a year inside factories deploying humanoid robots in real production environments.\n\nEven though Piggy Robotics is only a few months old, we’ve already assembled a **16-engineer elite hardware & software team** from **Oxford University** and **top global robotics competitions**. This combination of deep biomechanics, AI motion understanding, and hands-on factory deployment uniquely positions us to build the **first truly mass-producible humanoid robot**.\n\n![uploaded image](/media/?type=post&id=95684&key=user_uploads/89898/901840c8-864a-4d85-b82b-7ecf78a9b6b0)\n\n**Our Ask**\n\nIf our mission resonates and you want to ship humanoids with us, we’d love to connect: [founders@piggyrobotics.com](mailto:founders@piggyrobotics.com)", "url": "https://www.ycombinator.com/launches/OtI-piggy-robotics-humanoid-robots", "votes": 753, "created_at": "2025-11-21T17:31:10.408Z" }, { "id": 94076, "title": "Piggy Robotics: Humanoid robots that do your chores at iPhone prices.", "tagline": "Tesla promise robots for the price of a car. We will sell ours for the price of an iPhone. ", "body": "In **two months**, we built a **full humanoid** prototype with 22-degree-of-freedom **dexterous hands**, powered by our own custom **artificial muscles** for **less than $1000**!\n\n[Piggy Robotics F25 Launch](https://www.youtube.com/shorts/ty0fOJORnoc)\n\nCompared to electric-motor driven humanoids, ours are **softer**, **safer**, and delivers **higher strength-to-weight**. It will be **20x cheaper** enabling real-world AI training at scale.\n\n[Richard](https://www.linkedin.com/in/richard-g-15852b22b) trained AI to optimize cancer vaccines while studying **Medicine at Oxford University**. As a teen he scored **top 3 nationally** in the UK Intermediate Maths Olympiad.\n\n[Chenny](https://www.linkedin.com/in/qianyi-deng/) trained AI to read human motion while doing her **PhD in Computer Science at Oxford University**. At the **age of 13** she built the largest laser tag centre in her city!\n\n![uploaded image](/media/?type=post&id=94076&key=user_uploads/89898/2182c0f0-e665-410d-b83e-574bba525662)\n\n### Chat with us at: [founders@rigmanic.com](mailto:founders@rigmanic.com)", "url": "https://www.ycombinator.com/launches/OTM-piggy-robotics-humanoid-robots-that-do-your-chores-at-iphone-prices", "votes": 291, "created_at": "2025-09-23T22:11:41.061Z" } ] }, { "id": 29768, "name": "Ember Robotics", "slug": "ember-robotics", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d7501c381ec6654b0249e7c8d1881f708e27ce6e.png", "website": "https://www.emberrobotics.com", "all_locations": "San Francisco, CA, USA", "long_description": "Ember builds hardware and system observability tools for robots and IoT devices. Founded by former Tesla Autopilot engineers, we help hardware teams catch failures early, reduce downtime, and iterate with confidence from prototype to scale.", "one_liner": "Datadog for robots", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1722583865, "tags": [ "Developer Tools", "Robotics", "B2B", "Analytics", "Data Visualization" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/ember-robotics", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/ember-robotics.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/ember-robotics", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/d7501c381ec6654b0249e7c8d1881f708e27ce6e.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/6c2229c2c42289396d01eae7f571cb9a5c3d6351.png" ], "primary_partner": { "name": "Diana Hu", "url": "https://www.ycombinator.com/people/diana-hu" }, "founders": [ { "user_id": 1932951, "full_name": "Shivani Mouleeswaran", "title": "Founder/CEO", "founder_bio": "Co-founder and CEO @ Ember Robotics. Previously at Tesla Autopilot / Simbe Robotics. I love robots, basketball, and playing the sitar!", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/shivanicm", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ca21e267ed252271b8234a225ca024e791db442e.jpg" }, { "user_id": 1946129, "full_name": "Ritika Shrivastava", "title": "Founder/CTO", "founder_bio": "Ritika is a roboticist who loves helping robots see 🕶! She is a proud UC Berkeley alumna (B.S. EECS '21 & M.S. EECS '22) 🐻, where she researched and taught about computer vision and robotics. Formerly a computer vision engineer at Tesla Autopilot, Ritika is excited to build tools that help roboticists!\n\nIn her free time, she enjoys playing tennis 🎾, building gizmos, and reading 📖!", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/ritikashrivastava/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/62f2b8c1226f588a683c681ac6ac1c7ceb5d341c.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 87515, "title": "Ember Robotics: Datadog for Robots", "tagline": "From prototype to scale, we keep robots running", "body": "# **tldr; Fast-track your robotics development**\n\nAt [**Ember**](https://www.emberrobotics.com/), we make it easy for robotics teams to catch and fix issues fast. Our edge-first robot diagnostics platform helps you stay on top of system performance—whether you're prototyping, scaling, or deploying in the field. \\\n\\\nWith instant insights and built-in reliability, we help you move faster, build smarter, and launch with confidence. Ready to try it out? Book a demo [**here**](https://www.emberrobotics.com/) or reach out to us at [**founders@emberrobotics.com**](mailto:founders@emberrobotics.com)!\n\n# **The problem**\n\n1. **No Visibility in Low-Network Zones** – When robots lose connectivity, **cloud-based diagnostics fail**, making it hard to track performance or troubleshoot failures in real time.\n2. **Slow, Costly Root-Cause Analysis** – Debugging is painful, with teams sifting through **dense logs and complex graphs** instead of getting clear, actionable insights.\n3. **Inefficient DIY Monitoring Stacks** – Robotics teams **waste months building custom diagnostics** because existing tools don’t work for their needs.\n4. **Reactive Debugging Leads to System Failures** – Without **proactive monitoring**, small issues snowball into major downtime and expensive repairs.\n\n# **Our solution**\n\n### **🌐 Works Offline**\n\n* **Edge-first diagnostics** to store and analyze data even when the network is down.\n* **Smart caching & prioritized sync** ensure no critical insights are lost.\n\n### **🔍 Faster, Clearer Troubleshooting**\n\n* **Instant anomaly detection** surfaces failures before they escalate.\n* **Real-time sensor & system health analytics** (cameras, IMU, LiDAR, CPU, memory).\n* No more digging through logs—just **straightforward insights** when you need them.\n\n### **⚡ Seamless Integrations**\n\n* **Built-in Sensor Plugins & Robotics Middleware Support** – Off-the-shelf support for **Intel® RealSense™, Luxonis®, Orbbec®**, and more. Easy integrations for **ROS and e-Cal** —no extra setup required.\n* **Deploy in minutes with standard Linux packages**—skip the custom integrations.\n* **API-first design** lets you access diagnostics effortlessly and extend with your own **custom metrics plugins**.\n\n### **📈 Scale up to Fleet-Wide Monitoring**\n\n* Grow reliably from 1 to 10,000 robots with **consistent, structured data collection**.\n* Identify **trends & patterns across groups of sensors and devices**.\n* Works in **low-bandwidth environments**, ensuring continuous insights.\n\n# **Check it out**\n\n![uploaded image](/media/?type=post&id=87515&key=user_uploads/1932951/8cd43030-d313-4ade-af0d-f7fe7197ac0d)\n\n[**\\[dashboard demo\\]**](https://www.tella.tv/video/ember-robotics-dashboard-gvog)\n\n[**\\[real-time diagnostics demo\\]**](https://www.tella.tv/video/ember-real-time-diagnostics-walk-through-dcdf)\n\n### **Meet the team**\n\nWe built software at Simbe Robotics and Tesla Autopilot to optimize robot reliability—covering real-time diagnostics, sensor calibration, field service alerts, and low-latency data pipelines. From early R&D to fleet-scale deployment, we ensure robots stay operational, efficient, and ready for any environment.\n\n![uploaded image](/media/?type=post&id=87515&key=user_uploads/1932951/b82857af-566f-465a-8212-74965d060e03)\n\n# \n\n# **Our ask**\n\nStruggling with blind spots in your fleet? Drowning in logs while root-causing issues? **Ember streamlines troubleshooting and ensures reliable performance—no matter the network conditions.**\n\n🔹 **Book a demo** → [**here**](https://www.emberrobotics.com/)\n\n🔹 **Know someone working with robots, drones, or multi-camera systems?** Send them our way!\n\n🔹 **Just love talking robots?** Same—let’s chat!\\\n\\\nLet’s make **robot monitoring effortless.** Hit us up at [**founders@emberrobotics.com**](mailto:founders@emberrobotics.com)! 🚀", "url": "https://www.ycombinator.com/launches/MlX-ember-robotics-datadog-for-robots", "votes": 25, "created_at": "2025-02-07T22:07:48.510Z" }, { "id": 82673, "title": "Ember Robotics: Camera diagnostics for robots", "tagline": "Reducing vision failures from the source", "body": "# **tldr; Got camera problems? We’ve got solutions.**\n\n[Ember](https://www.emberrobotics.com/) builds software to monitor and resolve robot camera issues - so you can reduce vision failures from the source.\n\nIs robot camera reliability or degraded vision driving you nuts? Book a demo [here](https://www.emberrobotics.com/) or reach out to us at [founders@emberrobotics.com](mailto:founders@emberrobotics.com)!\n\n### **The problem**\n\nWe’ve spent years working on vision systems for autonomous robots and found similar issues everywhere:\n\n![uploaded image](/media/?type=post&id=82673&key=user_uploads/1932951/335dd4a4-e0b6-4c6b-bb64-a4c9c0c60f7f)\n\n☐ Robotics companies work on lean teams that have to do lots of things super fast - **hardware reliability is often secondary to core product features**\n\n☐ **Camera failures cause large fires** because they float up the stack to critically damage perception, controls, and safety\n\n☐ **Digging through layers of software / hardware to figure out what went wrong is painful** (ex. sometimes you spend hours goose-chasing a “perception issue” just to find a loose cable)\n\n### **Our solution**\n\n![uploaded image](/media/?type=post&id=82673&key=user_uploads/1932951/9c181ef2-e04a-498d-a839-35bfa75fd1dc)\n\n**A camera diagnostics framework that ties in real-time data, logs, and reports to contextualize your robot’s vision health.** Support the full life-cycle of your robot with features like:\n\n✅ Out-of-the-box tracking for common issues (disconnection, frame drops, time sync)\n\n💬 Automated suggestions for error resolution\n\n⏱️ Real-time alerts\n\n🖌️ Image quality analysis tools to optimize computer vision\n\n📈 Historical data analysis for predictive maintenance\n\n### **Try it out: Plug-and-play camera testing**\n\nBench-test cameras or diagnose issues in the field with one easy tool. **Fill a config file, launch our service, and get fast metrics on camera health.**\\\n[demo](https://www.youtube.com/watch?v=OnoCmdVEzzM)\n\nCurrently we support Intel® RealSense™ D400 cameras and ROS - more cameras and pub-sub models coming soon!\n\n### **Meet the team**\n\n![uploaded image](/media/?type=post&id=82673&key=user_uploads/1932951/cc554985-1fa2-4bd8-9d16-96609bb82645)\n\nHi, we are [Shivani](http://linkedin.com/in/shivanicm) & [Ritika](https://www.linkedin.com/in/ritikashrivastava/)! We built software at Tesla Autopilot to optimize camera performance for autonomy. We’ve covered the camera stack end-to-end (low-latency image capture, real-time camera monitoring, online camera calibration, multi-trip reconstruction, and SLAM) - we’re passionate about helping robots see!\n\n### **Our ask**\n\nIs robot camera reliability or degraded vision driving you nuts? Book a demo [here](https://www.emberrobotics.com/) or reach out to us at [founders@emberrobotics.com](mailto:founders@emberrobotics.com)!\n\nIf you know anyone working on robots, drones, or other multi-camera systems (surveillance, manufacturing, etc.) we would love a warm intro.\n\nAnd for those who are just generally robot-curious - always happy to chat!", "url": "https://www.ycombinator.com/launches/LVR-ember-robotics-camera-diagnostics-for-robots", "votes": 101, "created_at": "2024-08-02T13:50:39.909Z" } ] }, { "id": 29784, "name": "Sensei", "slug": "sensei", "former_names": [ "OBO" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0e3e1067b2d9b0492706fd6cec1ccf4d50ee5c59.png", "website": "https://senseirobotics.com", "all_locations": "Boston, MA, USA", "long_description": "Sensei helps robotics companies scale and outsource their training data collection. Our hardware platform enables the collection of human-demonstration data at a tenth of the cost and twice the speed of current teleop approaches. Our software platform acts like Scale AI for robotics data: a large network of paid human operators use our low-cost collection platform to fulfill data-generation requests. ", "one_liner": "Robotic Training Data at Scale", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1724658554, "tags": [ "Hard Tech", "Marketplace", "Robotics", "Data Engineering", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/sensei", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/sensei.json", "year_founded": 2024, "city": "Boston", "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/0e3e1067b2d9b0492706fd6cec1ccf4d50ee5c59.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": 842573, "full_name": "Anubhav Guha", "title": "Founder/CEO", "founder_bio": "CEO at Sensei - building the marketplace for robotic training data. Previously MIT Robotics PhD (dropped out) and Chief Engineer & Program Manager of Aurora Flight Science/Boeing's DARPA AlphaDogfight team. I've spent my whole career in robotics, and my goal is to help make AI robotics a reality.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/anubhav-guha-886445129/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9580bcefaa36422ee6b7c4f52ebab522fc7e6491.jpg" }, { "user_id": 2033335, "full_name": "John Piotti", "title": "Founder/CTO", "founder_bio": "CTO at Sensei - scaling robotic training data collection to be 2x faster and 10x cheaper. Previously MIT '19, Robotics Engineer at Aurora Flight Science/Boeing, and full stack web development at UtilityAPI. Also building a house in my free time. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/john-piotti-51a67412a/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/16f9d0a34775f335bac9e0e7ac869194c2b0cd63.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 83555, "title": "🦾 Sensei: Robotics training data, at scale.", "tagline": "We produce high quantities of high-quality training data for robotics companies.", "body": "**tl;dr:** [Sensei](https://senseirobotics.com/) is the Scale AI for robotics training data. Our platform collects human demonstration data at a tenth of the cost and twice the speed of current approaches.\n\n# **Our Team**\n\nWe are MIT engineers who have been friends since undergrad. We worked together at Aurora Flight Sciences, where we ran a DARPA-funded program to develop AI algorithms for autonomous fighter jet combat. [John](https://www.linkedin.com/in/john-piotti-51a67412a/) went on to spearhead the reinforcement learning efforts at Aurora, while [Anubhav](https://www.linkedin.com/in/anubhav-guha-886445129/) returned to MIT for a PhD focused on robotics, control theory, and machine learning (but dropped out to found Sensei!).\n\nWe have spent our careers working at the frontiers of robotics and AI. With Sensei, we plan to empower the expansion of those frontiers. \n\n![uploaded image](/media/?type=post&id=83555&key=user_uploads/842573/7653e304-26fe-4239-b434-58c524f60b31)\n\n# **The Problem**\n\n**Data scarcity is one of the biggest challenges in developing robotic artificial intelligence.** \n\nInnovators in the space are looking to apply the learnings from the Foundation Model Era: that large models trained on huge datasets are incredibly powerful. As researchers, engineers, and a rapidly growing number of commercial efforts race to develop large models for robotic intelligence, it’s become increasingly clear that the availability of sufficient quantities of quality data is the most significant bottleneck. \n\nCurrent solutions are slow, expensive, and fundamentally not scalable. Human demonstrations are the gold standard for training data. Robotics companies currently employ fleets of 5-20 data-collectors. These in-person contractors teleoperate a robot to perform hundreds of demonstrations a day - with tasks ranging from clothes folding, to bin sorting, to dishwasher loading. **This is not the right long-term solution:** \n\n* Large-scale collection is prohibitively expensive: a teleop setup requires a physical robot, often with a cost of $40,000+ per operational platform.\n* Low-quality data: restriction to labs/office spaces makes it hard to collect varied and realistic demonstrations\n* Slow data collection rates: non-intuitive interfaces, cumbersome equipment, and faulty hardware lead to slow demonstrations on platforms that break often.\n\n \n\nThese drawbacks make it impossible to scale quality training data collection to the quantities needed for robotics.\n\n# **Our Solution**\n\nWe design and manufacture low-cost and easy-to-use devices for collecting human demonstration data. Our platform costs less than $300 and can be used by anyone to collect high-quality training data. As seen in a clothes folding task that demonstrates our research prototype, the operator is equipped with a sensorized exoskeleton arm that closely matches the natural human range of motion. The intuitive design, coupled with a suite of angle, vision, and inertial sensors, enables the rapid collection of highly accurate visuo-spatial state information. \n\n![uploaded image](/media/?type=post&id=83555&key=user_uploads/842573/a58f4a6e-504c-4dd7-a1e1-8afd1d02cb30)\n\nOur main advantage is that an operator can easily set up and equip the platform, leading to an unprecedented ability to generate quality data at scale. Demonstrations can be performed for a broad range of common tasks, in a nearly infinite number of diverse settings, in as many different ways as human behavior is varied. \n\nIn order to maximally utilize a fleet of our data-collect platforms, we are building out and operating a network of Senseis— contractors that have been trained to collect high-quality training data using our devices. Our Senseis receive task descriptions from robotics researchers and engineers, and are then paid to collect demonstrations that fulfill the request. \n\n**Our combined hardware + software stack represents the first truly scalable solution to generating training data for AI robotics.**\n\n# **Our Goal**\n\nWithin the next five years, we envision tens of thousands of operators, equipped with increasingly sophisticated, portable, and effective data-collection arms, exoskeletons, headwear, and tools. These Senseis will be located all over the world, come from and live in a variety of environments, and all have different takes on what it means to perform tasks “like a human.” This is the best way to power data collection for improved robots, and it is the future we’re building.\n\n# **Ask**\n\nIf you’re interested in solving the data scarcity problem in robotics - either for yourself, your company, or your customers - we’d love to hear from you. You can reach us at [founders@senseirobotics.com](mailto:founders@senseirobotics.com)", "url": "https://www.ycombinator.com/launches/Ljf-sensei-robotics-training-data-at-scale", "votes": 112, "created_at": "2024-08-28T20:27:10.260Z" } ] }, { "id": 29847, "name": "Bucket Robotics", "slug": "bucket-robotics", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/55cc697d9f14eca5a5d45772ac14d97a83df16ae.png", "website": "https://bucket.bot", "all_locations": "San Francisco, CA, USA", "long_description": "Bucket Robotics builds deployable computer vision systems for manufacturing — without labeling, long pilots, or fragile rules.\r\nWe turn CAD and sample data into production-ready vision models that run on existing cameras and edge hardware. No manual labeling. No cold-start problem. Models deploy in minutes and adapt as parts, defects, and lines change.\r\n\r\nOur roots are in self-driving cars (Argo AI, Uber ATG, Stack AV), where we learned how to ship perception systems that operators trust in messy, real-world environments. We’re applying that playbook to factories: robust sensing, fast iteration, and tooling engineers actually enjoy using.\r\n\r\nManufacturers struggle with inspection because parts are too variable for rules-based vision and too expensive to inspect by hand. Legacy systems are rigid, hardware-locked, and slow to customize. We take the opposite approach: software-first vision that fits into existing automation and scales across SKUs, facilities, and workflows.\r\n\r\nAmerican Manufacturing is in the middle of a $700B automation push — but quality is still a trust problem. Bucket Robotics is building the vision infrastructure that lets factories automate inspection with confidence.", "one_liner": "Defect detection for manufacturing built from CAD and synthetic data.", "team_size": 8, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1719001491, "tags": [ "Robotic Process Automation", "Robotics", "Computer Vision", "Manufacturing" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": [ { "question": "What is your long-term vision? If you truly succeed, what will be different about the world?", "answer": "If we succeed, quality inspection stops being a human bottleneck. Manufacturing quality becomes software—deployed from CAD, scaled instantly across factories, and verified automatically. The world builds complex physical products faster, with less waste, and with machine-verifiable trust." } ], "url": "https://www.ycombinator.com/companies/bucket-robotics", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2024/bucket-robotics.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/bucketrobotics/", "x_url": "https://x.com/BucketRobotics", "fb_url": "https://www.facebook.com/profile.php?id=61578008815737", "cb_url": null, "github_url": "https://github.com/bucket-robotics", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/55cc697d9f14eca5a5d45772ac14d97a83df16ae.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/72627bb1c990f52131cd9089f7589fc3dc47457f.png" ], "primary_partner": { "name": "Diana Hu", "url": "https://www.ycombinator.com/people/diana-hu" }, "founders": [ { "user_id": 1918803, "full_name": "Matt Puchalski", "title": "Founder/CEO", "founder_bio": "Matt is the co-founder and CEO of Bucket Robotics, building CAD-driven computer vision for manufacturing inspection and assembly verification. Previously, he worked on autonomous vehicle integration and deployment at Argo AI, Latitude AI, and Stack AV, helping bring self-driving vehicles onto public roads in the United States and Germany.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/matt-puchalski", "x_url": "https://x.com/lasermatts", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/96e15f894eb00281539dee8a84cf516b581aac67.jpg" } ], "jobs": [ { "id": 73634, "title": "ML Engineer", "url": "https://www.ycombinator.com/companies/bucket-robotics/jobs/wamcLUR-ml-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$120K - $165K", "equity_range": "0.70% - 2.80%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "ML", "Python", "Machine Learning", "CUDA" ] }, { "id": 95125, "title": "Senior Full Stack Engineer", "url": "https://www.ycombinator.com/companies/bucket-robotics/jobs/6pT0gS3-senior-full-stack-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$160K - $220K", "equity_range": "1.00% - 3.00%", "experience": "6+ years", "visa": "US citizen/visa only", "skills": [ "Data Modeling" ] }, { "id": 95797, "title": "Forward Deploy Engineer", "url": "https://www.ycombinator.com/companies/bucket-robotics/jobs/va6hXZz-forward-deploy-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$100K - $120K", "equity_range": "0.25% - 1.20%", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [ "Python" ] } ], "news": [ { "title": "Synthetic Data Comes of Age: How Bucket Robotics is Changing the Economics of Machine Vision - MVPro Media", "url": "https://mvpromedia.com/synthetic-data-comes-of-age-how-bucket-robotics-is-changing-the-economics-of-machine-vision/", "date": "Jul 21, 2026" }, { "title": "How YC-backed Bucket Robotics survived its first CES | TechCrunch", "url": "https://techcrunch.com/2026/01/18/how-yc-backed-bucket-robotics-survived-its-first-ces/", "date": "Jan 18, 2026" } ], "launches": [ { "id": 82809, "title": "Bucket Robotics 🤖 Vision for Manufacturing", "tagline": "Go from CAD model to defect detection system in the blink of an eye.", "body": "# ☕ **_TL;DR_**\n\n[_Bucket Robotics_](https://bucket.bot) makes defect detection models way faster and easier to deploy. CAD goes in — detection model comes out.\n\n![uploaded image](/media/?type=post&id=82809&key=user_uploads/1918803/d49ec265-a7cd-4a9c-ad32-62b45df8c825)\n\n# **👥** **The Team**\n\n### Hi everyone, we’re [Matt](https://www.linkedin.com/in/matt-puchalski/) and [Steph](https://www.linkedin.com/in/stephan-wolski/), and we’re Bucket Robotics!\n\n![uploaded image](/media/?type=post&id=82809&key=user_uploads/1918803/a2825a9a-9dd1-4c95-8aa4-46ba2826efae)\n\n# **📉 The Problem**\n\nDefects are a universal challenge in manufacturing, particularly with methods like injection molding, die casting, and 3D printing. Factories using these methods frequently retool their lines for different products making it difficult and costly to gather enough data to train defect detection models.\n\nManufacturers strive to ensure that only the highest quality products reach their customers. Avoiding the shipment of defective products not only protects their reputation but also safeguards expensive machinery from damage, maximizes yield by leveraging advanced analytics, and prevents the progression of faulty parts through the production line, which can lead to compounded waste and increased costs.\n\nA 2017 study estimates that [yield losses account for 44% of sheet metal used](https://www.sciencedirect.com/science/article/abs/pii/S092401361730211X) in the production of passenger vehicles — and we want to bring that number down, saving money and the environment.\n\nTraditionally, defect detection comes in two flavors:\n\n1. Pay a person to watch your line.\n2. Train a vision model the old-fashioned way — wait for defective parts to come out and add your sample to the dataset.\n\nPaying people to check parts is inefficient and a miserable job. Collecting enough labeled data samples to train a model is impractical for rapidly retooled outputs, and the labeling is expensive. This often leaves manufacturers with a critical gap in quality assurance, leading to increased scrap, downtime, and potentially unhappy customers with defective parts.\n\n## **📈 The Solution**\n\nWe help eliminate the need for inefficient human monitoring and outdated defect detection by providing a system where we generate defect detection models using CAD files—something every part designed for modern manufacturing has. Our models can run on an edge computing device as small as a Jetson Orin Nano and be continually refined with real-world data.\n\n### **_Here’s why this is a game-changer:_**\n\n* **Early Deployment:** Your defect detector can arrive at your manufacturing line before you’ve manufactured any parts. This means you can catch defects right from the get-go.\n* **Continuous Improvement:** As defects start to appear, we can automatically refine and improve the model, ensuring your system remains top-notch.\n* **Classification**: The system tells you how the part is defective, allowing you to dial in your tooling configuration and maintenance cycle—e.g. when it's time to create a new mold.\n\nCheck out a video on our process here: [Bucket Robotics | Defect Detection](https://youtu.be/U_bJxaH_U9U)\n\n# **🙏How You Can Help**\n\nWe are seeking connections and collaborations to drive our mission forward. If you or anyone in your network is interested in learning more or helping out, we want to hear from you! We’re specifically looking to connect with:\n\n* Quality Assurance and Factory Automation leaders\n* Companies and brands in high-volume and precision manufacturing\n* Experts in the manufacturing and defect detection industries\n\nIf that’s you or someone you know, [please get in touch!](https://bucket.bot)", "url": "https://www.ycombinator.com/launches/LXd-bucket-robotics-vision-for-manufacturing", "votes": 77, "created_at": "2024-08-07T05:00:27.470Z" } ] }, { "id": 30097, "name": "Innate", "slug": "innate", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/374e6b2cd282f5fe31c64fcc82aaebb3105153c9.png", "website": "https://innate.bot", "all_locations": "San Francisco, CA, USA", "long_description": "We make personal AI robots - general-purpose physical machines that anyone can teach with code, language and demonstrations.\r\n\r\nWe believe building open platforms like the first PCs this is the only way to bring the robotics future that we all want, where everyone can participate in the robotics revolution.", "one_liner": "Personal AI Robots", "team_size": 7, "industry": "Consumer", "subindustry": "Consumer -> Consumer Electronics", "launched_at": 1730365227, "tags": [ "Developer Tools", "Hard Tech", "Robotics", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Fall 2024", "status": "Active", "industries": [ "Consumer", "Consumer Electronics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/innate", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2024/innate.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/innate-bot", "x_url": "https://x.com/innate_bot", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/374e6b2cd282f5fe31c64fcc82aaebb3105153c9.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": 938249, "full_name": "Axel Peytavin", "title": "Founder/CEO", "founder_bio": "CEO @Innate. Former researcher at Stanford HCI, The Ocean Cleanup", "is_active": true, "linkedin_url": "https://linkedin.com/in/axel-peytavin", "x_url": "https://x.com/ax_pey", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f87ffaf60cfa73031c4d08001d38c77d4b23ac75.jpg" }, { "user_id": 1831970, "full_name": "Vignesh Anand", "title": "Founder/CTO", "founder_bio": "Former Stanford robotics graduate student. Former flight sciences intern at Archer. Also built high-powered rockets and underwater robots. Currently building the future of embodied AI with Innate", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/vignesh-anand-iitb/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7adac2bc127fc7a93bf960286b96991e5463f4df.jpg" } ], "jobs": [ { "id": 100521, "title": "Content & Marketing Intern", "url": "https://www.ycombinator.com/companies/innate/jobs/PZV8HFZ-content-marketing-intern", "location": "Palo Alto, CA, US", "type": "Full-time", "role": "Marketing", "role_type": null, "salary_range": "$4.33K - $5.2K / monthly", "equity_range": "", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [] }, { "id": 114969, "title": "Open Application", "url": "https://www.ycombinator.com/companies/innate/jobs/XCZlld4-open-application", "location": "Palo Alto, CA, US", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "$38.9K - $300K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [] }, { "id": 114970, "title": "Mechatronics Engineer", "url": "https://www.ycombinator.com/companies/innate/jobs/AoTR6iU-mechatronics-engineer", "location": "Palo Alto, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Hardware", "salary_range": "$150K - $180K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [] } ], "news": [], "launches": [ { "id": 85667, "title": "Innate 🤖 Teach your own general-purpose robots", "tagline": "Shipping assembled AI robots for builders of Silicon Valley!", "body": "Innate builds **AI brains for general-purpose robots**, and **affordable embodiments** for consumers to experience the first AI robots.\n\nOur first product, **Maurice**, is a mobile robot with a trainable arm, designed for Silicon Valley builders to play with, customize and build on. It runs our AI brain that can navigate, perform physical tasks, interact with people, and reason.\n\n\n\nThe brain is **completely teachable**: You can prompt it, chat with it, and teach it physical tasks.\n\nIt takes **only 5 minutes** for you to write another prompt for Maurice to behave very differently, for example, performing security at home:\n\n\n\n# ⚙️ Under the hood\n\nIn the past 3 months, we created **our brain, an AI orchestrator** leveraging several of the most recent research publications in AI for manipulation, navigation, reasoning and planning.\n\nIt combines **9 different models** to create something that feels innately intelligent - like GPT, Gemini, Claude and Llama (Groq) got a body and learned to move. Maurice **constantly understands its environment**, makes decisions, remembers what is sees and where, and learns from you.\n\n![uploaded image](/media/?type=post&id=85667&key=user_uploads/938249/cc03013d-d569-4272-93d8-e7a3c7f0a6b8)\n\n**This system comprises:**\n\n🧠 A **multi-agent** orchestrator running specialized models locally and in cloud 🤖 **Real-time manipulation** models controlled by our own transformers\n\n🦾 A **full data pipeline** to collect arm data, train in the cloud, run inference on the platform\n\n💬 **A 100% interactive platform**, that can be steered vocally or through its prompts\n\n📈 An **eval pipeline** for our brain’s decision making, to progressively make it better\n\nMaurice learns your space, remembers context, and makes autonomous decisions about where, what to do next.\n\n**It’s also ready to build on:**\n\n* **All the compute required** is onboard (uses a Jetson Orin Nano)\n* Shipped with a **teleop arm** to train it quickly\n* **SDK to access the agent**, steer it, give it new functions to call\n\n ![uploaded image](/media/?type=post&id=85667&key=user_uploads/938249/1459c238-8aff-4226-acec-5c3c3770f57c)\n\n\nAnd as a user, you can customize it, collect data quickly to train it, and even change the hardware.\n\n![uploaded image](/media/?type=post&id=85667&key=user_uploads/938249/1039d908-0523-43d5-a70e-8d6d00971063)\n\nThis allows Maurice (and future robots) to learn several kinds of physical tasks.\n\n![uploaded image](/media/?type=post&id=85667&key=user_uploads/938249/ed3e71f0-37cb-498d-8448-57f2ebb47178)\n\nFinally, Maurice is already reliable enough for us to do live, autonomous demos!\n\nWe're also developing a larger robot that can reach countertops. Our interoperable software ensures quick capability matching across all future embodiments using the Innate brain.\n\n# Our Ask: Join us into the **future**\n\nWe're making teachable robots accessible to builders now, because we believe it is the right way to tailor robots people want, for a reasonable price. Furthermore, the data we collect along the way, teaching our robots, will be useful for all future robots.\n\nOur first platform is for Silicon Valley builders who want to shape what teachable robots can do. Sign up for our waitlist [on our website.](https://innate.bot)\n\n1. **Join the community:** Builders, if you want to know more, join our Discord and / or get one, send us a DM at [@ax_pey](https://x.com/ax_pey) on X or at [axel@innate.bot](mailto:axel@innate.bot)\n2. **Intro us:** Our AI brain could be useful to an individual or company you know making robots? We’d love to chat!\n3. **I just want to chat! :** Great! Happy to! The best way is still through [X](https://x.com/ax_pey), [LinkedIn](https://www.linkedin.com/in/axel-peytavin/) or [email](https://mailto:axel@innate.bot)!\n\n# Who we are\n\nWe are Vignesh and Axel, two former Stanford grad students and researchers in AI for robotics and AI for HCI. We met almost a year ago working on a previous idea, and through several iterations of this project, we have come to trust our shared abilities to face the hard problems ahead to make general-purpose robotics accessible to everyone.\n\nThis company embodies our vision of bringing a technology that will be a major game-changer for humanity, in the hands of everyone. So that robots are made for humans, taught by humans.\n\n![uploaded image](/media/?type=post&id=85667&key=user_uploads/938249/8d097e3a-cf0a-4ef9-ac06-4b6397935231)\n\n_Us, 10mn before a successful live demo of our robot in front of 40 people, fixing an unexpected bug_\n\nThe future of robotics is teachable. It’s time to build it!", "url": "https://www.ycombinator.com/launches/MHj-innate-teach-your-own-general-purpose-robots", "votes": 44, "created_at": "2024-11-18T19:25:14.391Z" } ] }, { "id": 30201, "name": "Dartboard", "slug": "dartboard", "former_names": [ "Dartboard Energy" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e6b5a6279db8d201fef41a88a35c1d4c0828744e.png", "website": "https://dartboard.ai", "all_locations": "San Francisco, CA, USA", "long_description": "Dartboard is the modern remote operations center for hardware fleets. We pair expert operators with AI agents to identify, diagnose, and fix issues faster.", "one_liner": "AI-native remote operations center for hardware fleets", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials", "launched_at": 1739492408, "tags": [ "Hardware", "Robotics", "Energy", "AI", "Industrial" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2025", "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/dartboard", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/dartboard.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/dartboard-ai/", "x_url": "https://x.com/dartboard_ai", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/e6b5a6279db8d201fef41a88a35c1d4c0828744e.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": 44103, "full_name": "Rohun Ati", "title": "Founder/CEO", "founder_bio": "CEO at Dartboard. 10th employee and data scientist at Second Measure (YC S15), stayed through its acquisition by Bloomberg. Built the data pipelines for a first-to-market credit card transaction dataset, now powering the Bloomberg Terminal. Later worked at AutoGrid forecasting battery revenues across U.S. power markets. Built ERCOT benchmarking software used by utility-scale battery operators including Spearmint Energy and UBS.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/rohunati", "x_url": "https://twitter.com/rohunati", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1797a7c71f5ed6498665c5cf7dde48d71e005ff5.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 87687, "title": "Dartboard Energy: AI Analyst for Electricity Markets", "tagline": "Uncover missed revenue for grid-connected battery owners while staying compliant", "body": "We’re building an AI Analyst for Electricity Markets, starting with the owners of grid-connected battery projects.\\\n\\\n\n\n**Context**\n\nBattery owners earn revenue by charging (buying) and discharging (selling) power in electricity markets.\n\nThe goal is to maximize revenue within constraints – some of which are physical, like battery capacity, duration, and efficiency, while others are regulatory. This is challenging because (1) markets are volatile and (2) complex and frequent regulatory updates make it difficult to assess both the revenue impact of rule changes and compliance risks.\n\n**Problem**\n\nTo make money on the grid, battery owners must analyze market data and keep up with thousands of constantly changing regulatory documents. Electricity markets work like auctions -- every 5 minutes, battery owners decide how much power to buy or sell and at what price. Even the most data-savvy teams can’t keep up, leaving owners with little visibility into how others are making money. And rule changes aren’t just small tweaks – they can completely upend the market. To avoid financial penalties, battery owners spend millions on lawyers and consultants just to stay compliant.\n\n**Solution**\n\nDartboard is an AI Analyst that uncovers missed revenue for owners of grid connected batteries while ensuring compliance. We provide value in two key ways:\n\n* **Market Intelligence:** We ingest historical market data so that owners can evaluate optimization strategies and uncover money they might be leaving on the table.\n* **Regulatory Guidance:** Our AI Analyst, trained on the latest rule changes, translates complex regulations into clear, actionable insights — helping owners navigate compliance without the need for expensive consultants.\n\n**Asks**\n\nIf you know any developer/owner/operators of grid-scale battery projects, energy traders, or energy-focused private equity investors, we’d love to meet them. Please reach out at [**rohun@dartboardenergy.com**](mailto:rohun@dartboardenergy.com).\n\n![uploaded image](/media/?type=post&id=87687&key=user_uploads/44103/4c267efd-7f8c-4bec-b718-7d5b6a16c3b4)\n\n", "url": "https://www.ycombinator.com/launches/MoJ-dartboard-energy-ai-analyst-for-electricity-markets", "votes": 23, "created_at": "2025-02-14T01:49:36.560Z" } ] }, { "id": 30276, "name": "General Trajectory", "slug": "general-trajectory", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4c79fb57c52ab75fc14e93779100504407b5e064.png", "website": "https://www.generaltrajectory.com/", "all_locations": "Los Angeles, CA, USA", "long_description": "General Trajectory is using AI to solve the world's most important problems, from autonomous defense to scientific R&D.", "one_liner": "AI for the physical world", "team_size": 1, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1738545890, "tags": [ "Robotics", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/general-trajectory", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/general-trajectory.json", "year_founded": 2024, "city": "Los Angeles", "country": "US", "linkedin_url": "https://linkedin.com/company/generaltrajectory", "x_url": "https://x.com/gentrajectory", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/4c79fb57c52ab75fc14e93779100504407b5e064.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/4a09fcc4294bb183b611351cfbd5c9e4d1bb97cb.png", "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/203af2059eae51bdf6c7d474ffde4132486c0709.png" ], "primary_partner": { "name": "Harj Taggar", "url": "https://www.ycombinator.com/people/harj-taggar" }, "founders": [ { "user_id": 1366241, "full_name": "Joshua Belofsky", "title": "Founder/CEO", "founder_bio": "Recent graduate focusing on AI for the physical world. Background is in academic ML research.", "is_active": true, "linkedin_url": "https://linkedin.com/in/joshua-belofsky-25328523b", "x_url": "https://x.com/joshuabelofsky", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4f608bc7f9da030e188bbc67691c92726b24e872.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 96524, "title": "🤖 General Trajectory - A Foundation Model for Humanoid Robots", "tagline": "Reward-guided imitation learning for dexterous manipulation", "body": "\n\n## What is it?\n\nA foundation model that helps humanoid robots pick up unseen objects and perform real-world work. It generalizes to novel objects and scenes, including cases where prior SoTA models achieve 0% success.\n\n![uploaded image](/media/?type=post&id=96524&key=user_uploads/1366241/6cbcabb4-44fe-4d86-8b20-4b5220709f58)\n\n## The problem\n\nHumanoid robots can do backflips and kung fu, but still struggle with economically useful work. Dexterous manipulation is the main bottleneck to useful physical labor.\n\n## Our approach\n\nWe collect an efficient set of human demonstrations and train a reward model to improve the base model's grasps.\n\n![uploaded image](/media/?type=post&id=96524&key=user_uploads/1366241/86269800-22b9-4a15-bf3c-7d63285ea25d)\n\nThe result is strong generalization: up to 63% gains on difficult objects where the best baselines achieve 0%, while maintaining near-perfect performance on standard objects. Full details are available in our [technical post](https://www.generaltrajectory.com/technical-update).\n\nThe physical world is 80% of global GDP. We believe this research represents progress toward a future in which AI systems are not limited to computer work.\n\n## Open-source\n\nWe open-sourced our teleop stack!\n\n\n\nIt uses vision + wrist trackers instead of data gloves → about **$500** in hardware vs. **\\~$5,000**.\n\n![uploaded image](/media/?type=post&id=96524&key=user_uploads/1366241/aeeb02d9-821a-44b5-bef0-f491af1fa15a)\n\n## Call to action\n\nIf you are interested in AI for the physical world (scientific R&D, defense, etc.), please reach out!\n\n* Website: \n* X: ", "url": "https://www.ycombinator.com/launches/P6q-general-trajectory-a-foundation-model-for-humanoid-robots", "votes": 15, "created_at": "2026-01-05T15:51:54.579Z" }, { "id": 88311, "title": "General Trajectory – Reasoning Models for Robotics", "tagline": "Bringing AI into the physical world", "body": "# **TL;DR**\n\nWe’re training models that can reason through physical tasks using chain-of-thought to automate traditionally difficult work in industrial environments like warehouses and manufacturing facilities.\n\n![uploaded image](/media/?type=post&id=88311&key=user_uploads/1366241/ed2288b5-baa9-4959-896d-cd75e4074858)\n\n# How it works\n\nWe fine-tune vision-language models to output low-level robotic controls across primary tasks in logistics: mixed-sku palletization, item picking, sorting, and packing.\n\nBefore predicting the next action, our model is explicitly trained to `` about its next step. This allows it to reason through long-horizon tasks.\n\n\n\n# RL from Verifiable Rewards\n\nOur fine-tuned model is then rolled out in Nvidia’s Isaac Sim where it generates reasoning + action traces that get scored using simple verifiers. This continues to improve the model using photorealistic data without any human in the loop.\n\n![uploaded image](/media/?type=post&id=88311&key=user_uploads/1366241/db7af549-6c06-433d-a8da-16d6dffd5737)\n\n# Our ask\n\nWe see logistics as an entry point to even greater automation across industries. Soon you will be able to tell AI to do any physical tasks in the same way current systems can handle the cognitive ones.\n\nIf you have any tasks you’d like to automate or know of anyone interested in working on embodied AI, please reach out: [joshua@generaltrajectory.com](mailto:joshua@generaltrajectory.com)\n\n# The Team\n\n![uploaded image](/media/?type=post&id=88311&key=user_uploads/1366241/ed970f7d-fd66-473d-9c72-17cc18dedb5d)\n\nJoshua studied CS & neuroscience at the University of Chicago but spent most of his time outside of class doing ML research. He first joined NASA Ames Research Center and later worked at Caltech. His [research](https://scholar.google.com/citations?user=RoD9hE8AAAAJ&hl=en) focused on generally capable AI agents and reasoning.", "url": "https://www.ycombinator.com/launches/MyN-general-trajectory-reasoning-models-for-robotics", "votes": 15, "created_at": "2025-03-06T15:48:57.648Z" } ] }, { "id": 30305, "name": "Forge Automation", "slug": "forge-automation", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/83675e4cb8108f5003548d5dd5c6e5ee56ede4aa.png", "website": "https://www.forgeautomation.ca", "all_locations": "Toronto, ON, Canada", "long_description": "Forge Automation runs software enabled factories that deliver custom metal parts in four days or less. Instead of mechanical engineers having to wait two to three weeks for their low volume CNC parts, they can simply upload a CAD model on our platform and we will ship it out in four days or less. We aim to give mechanical engineers the \"Amazon experience\" for custom metal parts.", "one_liner": "Software Enabled CNC Parts Supplier", "team_size": 21, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1736647566, "tags": [ "Hard Tech", "Hardware", "Robotics", "Manufacturing", "Industrial" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "Canada", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/forge-automation", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/forge-automation.json", "year_founded": 2022, "city": "Toronto", "country": "CA", "linkedin_url": "https://www.linkedin.com/company/forge-automation", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/83675e4cb8108f5003548d5dd5c6e5ee56ede4aa.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": 1502123, "full_name": "Timothy Seto", "title": "Founder/CEO", "founder_bio": "Co-founder + CEO @ Forge Automation | I make metal parts. Send me CAD, I will make it in the real world.\n\nI went to the University of Waterloo Engineering, and interned at Apple, Formlabs and iRobot. I have been machining for over 10 years and I love building robots and machines. I graduated in the summer of 2022 and co-founded Forge Automation right after.", "is_active": true, "linkedin_url": "https://linkedin.com/in/timmy-seto", "x_url": "https://x.com/TimmySeto", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e323b40b6256f205c7b5e8cf0bc59216b4541428.jpg" }, { "user_id": 1631233, "full_name": "Walter Raftus", "title": "Founder/CTO", "founder_bio": "Co-Founder + CTO @ Forge Automation | I love computers, math, and big specialized machines controlled with software!\n\nI went to the University of Waterloo for AI + Mechatronics Engineering, and interned at Nvidia, Trexo Robotics (W19), and Intel PSG working on a bunch of different software ranging from system software, deep learning, and embedded control. I graduated in the summer of 2022 and co-founded Forge Automation right after!", "is_active": true, "linkedin_url": "https://linkedin.com/in/walterraftus", "x_url": "https://x.com/walter_raftus", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0d7ab215db8f29667413c93869cec9b8fdba5150.jpg" } ], "jobs": [ { "id": 103180, "title": "Manufacturing Software Engineer", "url": "https://www.ycombinator.com/companies/forge-automation/jobs/GAgHVzO-manufacturing-software-engineer", "location": "Toronto, ON, CA / Toronto, Ontario, CA", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$100 - $160 CAD", "equity_range": "0.10% - 0.30%", "experience": "3+ years", "visa": "US citizenship/visa not required", "skills": [] } ], "news": [], "launches": [ { "id": 87618, "title": "Forge Automation - CNC parts in 4 days or less", "tagline": "Forge Automation runs software enabled factories that deliver quickturn on-demand CNC parts.", "body": "**TLDR**\n\nForge Automation runs software enabled factories that deliver quickturn on-demand CNC parts.  For customers who prioritize consistent and fast lead times, Forge offers the option to reserve dedicated CNC machines on their floor, giving you a guaranteed SLA on production time. Alternatively, customers can order parts on-demand at a higher price. We’ve shipped thousands of parts to engineers all over North America ranging from Fortune 10 companies to start-ups.\n\n**For an instant quote, upload a CAD file at** [**www.forgejobshop.com**](http://www.forgejobshop.com)!\\\n\\\n[**Check out our Factory!**](https://www.youtube.com/watch?v=KSKWPaM_Yno) \n\n**Problem:**\n\nHardware development is hard because it takes 2-3 weeks to receive prototype parts after placing an order with a supplier. For those in the software world, imagine having to wait 2 weeks to compile your code - you would hate your life and nothing would get done! Engineers just want a CNC service that is quick, affordable, and reliable! \n\n**Introducing Forge Automation:**\n\nWe are a North American based machine shop that makes custom, low volume CNC parts. Over the past two years, we’ve shipped thousands of parts to engineers all over North America ranging from Fortune 10 companies to brand new start-ups.\n\nAlong with the high quality and fast lead times, customers love our service because it’s the easiest way to order parts online. **Engineers can ditch the drawing and add manufacturing intent directly onto their CAD model within our platform.** Here's a quick demo showing how easy it is to submit an order.\n\n[**Quoting Demo:**](https://www.youtube.com/watch?v=bkJ73dUJ1gs)\n\nWe are excited to launch a new product – **Forge Reserve Machines**. Customers can get dedicated access to their own CNC machine on Forge's shop floor. Forge handles everything - purchasing and maintaining a 3 axis mill, plus providing one of their skilled machinist to make your parts. Forge Reserved Machines represent an SLA guaranteeing you 4 day production times so your parts are never late!\n\n**Our Ask - If you need parts made:**\n\nIt's easy to get started! Upload a CAD model to [**www.forgejobshop.com**](http://www.forgejobshop.com), receive an instant quote, checkout online, and have a part in your hand lightning fast!\n\nIf you want fast, reliable, and guaranteed service on your CNC parts, check out our [**Reserved Machine**](https://www.forgejobshop.com/docs/reserve) option.\n\n![uploaded image](/media/?type=post&id=87618&key=user_uploads/1502123/01702dfd-885e-4894-a3e6-420115ecedc5)\n\n", "url": "https://www.ycombinator.com/launches/MnC-forge-automation-cnc-parts-in-4-days-or-less", "votes": 37, "created_at": "2025-02-12T19:12:07.695Z" } ] }, { "id": 30320, "name": "Proception Inc", "slug": "proception-inc", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/9bbd5c88222cf5eb971b76232ac40284413785f0.png", "website": "https://proception.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "Making humanoids dexterous enough to thread a needle", "team_size": 10, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1739402915, "tags": [ "Robotics", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/proception-inc", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/proception-inc.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/proceptionai/?viewAsMember=true", "x_url": "https://x.com/proceptionAI", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/9bbd5c88222cf5eb971b76232ac40284413785f0.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": 2177365, "full_name": "Jay Li", "title": "Founder/CEO", "founder_bio": "Working on humanoid. Stanford alumni", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jaylicareer/", "x_url": "https://x.com/jaylistanford", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e1e14b438d6bcc0a1dde6f23547a7be16e34e1f3.jpg" }, { "user_id": 2602106, "full_name": "Jack Xu", "title": "Founder", "founder_bio": "UWaterloo Alumni, Ex-Tesla Engineer, Ex-Trexo [YC 19]", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jack-xu-jxinbox/", "x_url": "https://x.com/_jaku_xu?s=21", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/697b46f581ed12f84f2c38b91fa0a4bcace94d71.jpg" } ], "jobs": [ { "id": 84326, "title": "Robotics Technician (Assembly & Testing)", "url": "https://www.ycombinator.com/companies/proception-inc/jobs/YQt8sOz-robotics-technician-assembly-testing", "location": "Palo Alto, CA, US", "type": "Contract", "role": "Operations", "role_type": null, "salary_range": "$25 - $35 / hourly", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] } ], "news": [ { "title": "Robot hand company settles Tesla trade secret suit and announces $11M raise | TechCrunch", "url": "https://techcrunch.com/2026/06/29/robot-hand-company-settles-tesla-trade-secret-suit-and-announces-11m-raise/", "date": "Jun 29, 2026" } ], "launches": [ { "id": 104230, "title": "Proception - The dexterous robot hand we wish existed", "tagline": "The hand that enables robots. The glove that teaches them.", "body": "# **Shipping ProHand: The Human-Like Robotic Hand Built for Dexterous Manipulation**\n\nMost robots still cannot use their hands.\n\nThat sounds strange, because robots have gotten dramatically better over the past decade. They can navigate warehouses, run, jump, perceive their surroundings, and reason over visual scenes. But when it comes to actually touching the world, most robots still rely on simple grippers.\n\n![uploaded image](/media/?type=post&id=104230&key=user_uploads/2602106/4c624b0d-144a-4af0-8144-a88769012c9d)\n\nThat works if the object is rigid, predictable, and placed exactly where the robot expects it to be. It breaks down quickly when the task requires the kind of manipulation humans do every day: adjusting grip, feeling contact, using multiple fingers, handling soft objects, or recovering when something slips.\n\nWe started Proception because we kept running into the same bottleneck: humanoid robots will not become truly useful until they can manipulate the world with something much closer to a human hand.\n\nToday we are introducing ProHand 1.0, a high-dexterity robotic hand built for researchers and robotics companies working on contact-rich manipulation.\\\n\\\n\n\n## Why We Built a Human-Like Hand\n\nThe human hand is not just a gripper. It has more than twenty degrees of freedom, dense tactile feedback, tendon-driven actuation, and an incredible ability to adapt through contact.\n\nThat is what makes simple tasks deceptively hard for robots. Tying shoelaces, opening packaging, handling tools, plugging in cables, folding clothes, or repairing electronics are not just vision problems. They are contact problems.\n\nTo build ProHand, we worked closely with hand surgeons and designed the system around the structure of the human hand.\n\n![uploaded image](/media/?type=post&id=104230&key=user_uploads/2602106/7dacec7a-3a65-412f-8513-cef8caf8b27f)\n\nProHand includes:\n\n* **Twenty-two degrees of freedom**, with multiple joints per finger, enabling a wide range of human-like motions.\n* **Tendon-driven actuation**, where motors pull cables to move the fingers while keeping the hand lightweight and compact.\n* **A compact and robust mechanical design**, built to be impact tolerant, serviceable, and practical for real robotics research.\n* **Integrated skin-like sensors**, which detect contact and support grip control during manipulation.\n\nThe goal was not to build a hand that looks human for aesthetics. The goal was to build hardware that can interact with the world in the same manipulation regime as human hands.\n\n## The Bigger Problem Is Data\n\nDexterous manipulation is not only a hardware problem. It is also a data problem.\n\nAI has made enormous progress in vision and language because those fields had access to large-scale datasets. Robotics does not have the same advantage. Manipulation data is expensive, slow, and usually collected in labs through teleoperation.\n\nTeleoperation is useful, and ProHand supports standard teleoperation workflows out of the box. But it has two big limitations.\n\nFirst, it does not scale easily. Data collection is limited by how many robots you have and how much time operators can spend controlling them.\n\nSecond, it loses important human interaction signals. When someone teleoperates a robot, they are not directly touching the object. The robot sees motion commands, but it often misses the subtle pressure, contact, and adjustment strategies humans naturally use when manipulating objects.\n\nBecause ProHand is designed around human hand kinematics and skin-like sensing, we can also collect data directly from human hands.\n\nThat is why we built **ProGlove**.\n\n![uploaded image](/media/?type=post&id=104230&key=user_uploads/2602106/1ee06ef7-e3b4-422a-b38c-2987494df668)\n\nProGlove turns the same sensor skin used on ProHand into a wearable data collection system. A person can wear the glove, interact with real objects, and capture human manipulation data without needing a robot in the loop. Combined with a headset for visual context, researchers can collect real human hand interaction data and transfer those movements and skills to ProHand.\n\nOur bet is simple: the fastest path to dexterous robots is to build hardware close enough to the human hand that we can learn from human hands directly.\n\n## Shipping This Week\n\nProception has raised **$11 million in seed funding** led by **First Round Capital**, with participation from **Y Combinator** and **BoxGroup**. This allows us to expand the team, scale production, and keep building the hardware and data infrastructure needed for dexterous manipulation.\n\nOur team has designed consumer electronics at Apple that reached millions of users, built robotic systems at Tesla and early-stage startups, and spent years working on the messy details of real hardware: actuation, sensing, reliability, calibration, control, and data collection.\n\nWe are building ProHand in Mountain View, and the first batch of units is shipping this week to researchers and robotics companies.\n\nIf you are building dexterous manipulation systems, humanoid robots, teleoperation workflows, or robot learning pipelines, you can order ProHand on [our website](https://www.proception.ai/product/pro-hand/gen1).\n\nIf you want to help build the hands that make humanoid robots useful, we are hiring .\n\n## ", "url": "https://www.ycombinator.com/launches/R78-proception-the-dexterous-robot-hand-we-wish-existed", "votes": 7, "created_at": "2026-06-29T15:46:59.992Z" }, { "id": 88112, "title": "🦾 Proception.ai - World's most dexterous humanoid", "tagline": "We make humanoids dexterous enough to thread a needle", "body": "Our mission is to revolutionize humanoid robotics by developing robots capable of performing complex tasks, transforming how we interact with technology in industries like healthcare, manufacturing, and beyond.\n\n### **What We Do**\n\nAt Proception, we are developing advanced humanoid robotic hands and robots, starting with a high-precision hand for research. We’ve successfully built our first functional prototype in just 4 months—an incredible milestone that sets us on the path to shipping to researchers soon. Our unique approach to **data collection**—where we collect data through human interaction rather than teleoperating robots—has significantly increased the efficiency of our data gathering. This enables us to train more effective AI models for manipulation and task execution.\n\n\n\n### **The Journey Ahead**\n\nOur robotic hands are just the beginning. In the next few years, we’ll expand from hands to fully autonomous humanoid robots capable of performing a wide range of tasks across industries. From healthcare and elder care to manufacturing and logistics, Proception’s robots will drive automation and unlock new efficiencies.\n\n### **Why We’re Different**\n\n![uploaded image](/media/?type=post&id=88112&key=user_uploads/2177365/6b25ce59-4945-4d41-8c32-2bd1379203d9)\n\n1. **Efficient Data Collection**: Unlike traditional teleoperation methods, we gather data through human-driven interactions, dramatically improving the efficiency of data collection and speeding up the training of AI models.\n2. **Execution**: In just 4 months since founding Proception, we’ve built a functional prototype of our humanoid hand, and we’re now preparing to ship it to research institutions in the near future.\n3. **Scalability**: Our robot is highly versatile and adaptable across a wide range of tasks, with a clear roadmap to scale from research applications to both industrial and household markets.\n\n![uploaded image](/media/?type=post&id=88112&key=user_uploads/2177365/c4f61f1e-d25c-4da2-b887-f72dd29bda8f)\n\n### **What’s Next**\n\nIn the coming 9 months, we will continue refining our robotic hand and prepare for the first shipments to research customers. We’ll also focus on further developing our AI software and preparing for the next phase: scaling to humanoid robots capable of performing real-world tasks. By years 2–3, we plan to deploy humanoid robots into industries that can benefit from automation and complex task execution.\n\n### **Backstory**\n\nMy journey into humanoid robotics began during my two years at Tesla, where I worked on the Tesla Optimus project. I developed a deep emotional connection to the potential of humanoid robots, which inspired me to pursue a path where I could bring that vision to life. Before Tesla, I worked at two startups, both of which successfully IPO’d. Those experiences taught me that the most challenging problems, especially in robotics, can only be solved through the agility and innovation of startups. That’s why I founded Proception—to take on these hard problems and push the boundaries of what’s possible with humanoid robots.\n\n### **Join Us on This Journey**\n\nJoin us in shaping the future of humanoid robotics. If you’re interested in learning more about our progress or exploring ways we can work together, let’s connect! Reach us at [**contact@proception.ai**](mailto:contact@proception.ai) or sign up at [proception.ai](https://proception.ai)\n\nTogether, we’re building the future—one robot at a time.", "url": "https://www.ycombinator.com/launches/MvA-proception-ai-world-s-most-dexterous-humanoid", "votes": 27, "created_at": "2025-02-27T18:50:09.198Z" } ] }, { "id": 30353, "name": "Axal", "slug": "axal", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/82e9354c307a1bd5e3bca2ede62b3b0bdfbdba15.png", "website": "https://www.axal.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Axal is a quick-turn PCB assembly shop in San Francisco. Samai and Nand build every board themselves, and both are IPC certified. For quantities under 10, we assemble boards in under 48 hours. Order online in 2 minutes at axal.ai.\r\n\r\nSend us your board files and we handle the parts, bare boards, assembly, inspection, and delivery. ", "one_liner": "We assemble PCBs in under 48 hours for quantities under 10", "team_size": 3, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1736891737, "tags": [ "Hardware", "Robotics", "Manufacturing", "Electronics" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/axal", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/axal.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/axalai/?viewAsMember=true", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/82e9354c307a1bd5e3bca2ede62b3b0bdfbdba15.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": 1097575, "full_name": "Samai Patel", "title": "Founder", "founder_bio": "I like making electronics. Made projects being used by Lockheed Martin and Amazon Kuiper. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/samaipatel", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e5a05bba8f4675bd20d06a33f7fa30448bfcc345.jpg" }, { "user_id": 570999, "full_name": "Nand Vinchhi", "title": "Founder", "founder_bio": "Co-founder and CTO of Axal - https://axal.ai", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/nandvinchhi", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e03b530f45ad3e0b17ec21eb09353b338338a5de.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 108343, "title": "Axal: Designing and Getting PCB's in China is Dead", "tagline": "We help companies design and assemble their board in days", "body": "We are launching Axal, a services company that designs, assembles, and tests custom PCBs for hardware startups in days. American manufacturing is back. 🇺🇸\n\nAxal enables hardware teams to get custom PCBs designed and built in the U.S. without needing electrical engineers on staff.\n\nWe’ve helped teams go from no PCB design to a working board delivered in as little as two weeks.\n\nIt’s ridiculous that American hardware startups have to go overseas just to get a PCB designed and built affordably. Together, we can change that and build more hardware in America.", "url": "https://www.ycombinator.com/launches/SBT-axal-designing-and-getting-pcb-s-in-china-is-dead", "votes": 2, "created_at": "2026-07-30T06:10:46.886Z" }, { "id": 91586, "title": "Axal: Legacy Code, Understood in Hours. Seriously.", "tagline": "We help startups who want to integrate their tech into enterprise legacy systems by expediting the process of discovery + rewrite by months.", "body": "Hi, we’re Samai and Nand — Co-Founders of Axal 👋\n\nIf you're selling to a sticky product to enterprises, you've probably run into this:\n\n“We’d love to use your product, but our stack is too old...”\n\nThat’s where we come in.\n\nAxal reverse engineers legacy codebases (Java, C#) to generate **functional requirements and user stories in hours** — essentially helping your clients expedite the discovery process of their modernization. A beta version of our tool then figures out what needs to be rewritten and makes an outline for your team so you can easily rewrite their code and integrate your product. \n\nMongoDB already does this to land enterprise deals — they rewrite the client’s legacy system _just enough_ to make it so they can integrate their product and switch up the DB. Then they are sticky forever.\n\nGet setup in less than 1 hour guaranteed. \n\nAxal Demo - Creating Functional Requirement Document and User story of 30k line Java codebase \n\nhttps://www.youtube.com/watch?v=yXWTFxfw2vE\n\nWe make that process instant and repeatable so if you have a sticky product you can integrate with enterprise codebases easily.\n\n**Why it matters to you (YC founder):**\n\nYou’re not just selling software. You’re selling _change_.\n\nIf legacy tech is blocking your deal, let us unblock it — so you can close faster and look like a hero.\n\nTo get started, email me - [samai@joinaxal.com](mailto:samai@joinaxal.com)\n\nJoin the waitlist rewrite tool: ", "url": "https://www.ycombinator.com/launches/NpC-axal-legacy-code-understood-in-hours-seriously", "votes": 9, "created_at": "2025-06-24T14:50:34.452Z" }, { "id": 86865, "title": "Axal - Automate identifying and fixing architectural tech debt", "tagline": "Break down monoliths, identify tech debt, and fix it with AI at scale!", "body": "Hey everyone, I’m Nand - Founder at Axal👋\\\n\\\nWe built a tool that uses deterministic methods to **automate the hardest parts of application modernization**— identifying architectural bottlenecks and prioritizing those issues based on business value. Once the issues are broken down by Axal, AI can autonomously collaborate with your team to resolve them.\n\n# **The Problem**\n\nEveryone knows that software teams cut corners in development over time, resulting in accumulation of debt tech overtime that slows them down and raises costs. Until now, to address this problem there needed to be long modernization efforts, where stakeholders spent months finding possible solutions to the problem, if you could even find and train the team members needed to do the work. \n\n# **Our Solution: One platform for Application Modernization**\n\nAxal uses deterministic methods to provide teams with clear observability into architectural technical debt.\n\n![uploaded image](/media/?type=post&id=86865&key=user_uploads/570999/5453ac1a-0928-4ba2-91f1-665ad2c142fd)\n\nWe show tech debt scores tailored to your goals. For example, if maintainability is your focus, we display the maintainability index, aligning business impact with priorities to guide effective action.\n\nTechnical teams can leverage our graphs to gain clear insights into class-level and domain-level codebase relationships.\n\n![uploaded image](/media/?type=post&id=86865&key=user_uploads/570999/ceaeb77c-b33c-4ef2-8540-3e5fc5f564d2)\n\nArchitectural issues - domain exclusivity, circular dependencies, dead code, etc. - are automatically detected based on the goals that an organization makes, and engineers can work with Axal to assign their priority.\n\n![uploaded image](/media/?type=post&id=86865&key=user_uploads/570999/f63d172c-c479-4a22-92b6-ab40ffdd2ef7)\n\nOnce prioritized, **Axal leverages AI to autonomously address issues**, while ensuring none of the existing code breaks.\n\n![uploaded image](/media/?type=post&id=86865&key=user_uploads/570999/01d79606-ac19-4fd4-a503-aff34a23a9c8)\n\n**Demo Video** (\\* excludes technical debt scores and AI code fix demonstration)\n\n\n\n# **Our Ask**\n\nPlease reach out:\n\n\\- If you want to see your team's architectural technical debt \n\n\\- If you have a Java, C#, or Go monolithic application you want to modernize, contact us (min. 100k lines of code)\n\nPlease let us know if you have any previous connections to large to medium-sized companies undergoing application modernization\n\nLearn more at [axal.ai](http://axal.ai)", "url": "https://www.ycombinator.com/launches/Mb3-axal-automate-identifying-and-fixing-architectural-tech-debt", "votes": 117, "created_at": "2025-01-15T17:17:50.625Z" } ] }, { "id": 30430, "name": "Almond", "slug": "almond-2", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/37312e12dc6f12e2470a531052ec0e30ee697a75.png", "website": "https://almond.bot/", "all_locations": "San Francisco, CA, USA", "long_description": "We build robots for physical AI. Meet Axol - A dual-arm robot designed for real-world tasks using AI.", "one_liner": "A dual-arm robot built for physical AI.", "team_size": 6, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1745432874, "tags": [ "Hardware", "Robotics", "Manufacturing", "Automation", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Spring 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/almond-2", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/almond-2.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/almond-inc", "x_url": "https://x.com/almond_robotics", "fb_url": null, "cb_url": null, "github_url": "github.com/orgs/almond-bot/repositories", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/37312e12dc6f12e2470a531052ec0e30ee697a75.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": 33058, "full_name": "Saba Khalilnaji", "title": "Founder/CEO", "founder_bio": "ex-DoorDash logistics engineer & ex-CTO Conduit (W23)", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/saba-khalilnaji-853631241/", "x_url": "https://twitter.com/saba_khalilnaji", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/06726c32d6bbe24037817517e07713cd6f57f7ee.jpg" }, { "user_id": 1049100, "full_name": "Shawn Patel", "title": "Founder/CTO", "founder_bio": "🤖", "is_active": true, "linkedin_url": "https://linkedin.com/in/shawnpatel", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c9b2f7b4ac6a5d23217331e11b703fcb1d08bcb1.jpg" } ], "jobs": [ { "id": 86930, "title": "Founding Robotics Software Engineer", "url": "https://www.ycombinator.com/companies/almond-2/jobs/RXD2GSW-founding-robotics-software-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$130K - $200K", "equity_range": "0.50% - 3.00%", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [ "Python", "Rust", "Torch/PyTorch", "WebVR" ] }, { "id": 86932, "title": "Founding Mechanical Engineer", "url": "https://www.ycombinator.com/companies/almond-2/jobs/5NPlb6V-founding-mechanical-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Mechanical", "salary_range": "$100K - $200K", "equity_range": "0.25% - 5.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "CAD Design" ] }, { "id": 95984, "title": "Assembly & Production Technician", "url": "https://www.ycombinator.com/companies/almond-2/jobs/pBOdInA-assembly-production-technician", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "$25 - $40 / hourly", "equity_range": "", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 102952, "title": "Founding Software Engineer", "url": "https://www.ycombinator.com/companies/almond-2/jobs/HiQT2fV-founding-software-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$130K - $200K", "equity_range": "0.50% - 3.00%", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [ "Python" ] } ], "news": [], "launches": [ { "id": 102875, "title": "Axol - A dual-arm robot built for AI.", "tagline": "Axol is the robot for the teams turning physical AI into reality. ", "body": "Today, we’re launching **Axol**, a dual-arm robot built for real-world tasks.\n\n\n\nWe spent the last year deploying robots in factories and grocery stores.\n\nAnd they kept breaking.\n\nData collection was just too difficult. Reach and payload were limited. Singularities reduced our workspace. Cables failed but support was slow.\n\nThe robots we tried were built for demos, not real tasks.\n\nSo we built our own.\n\n![uploaded image](/media/?type=post&id=102875&key=user_uploads/33058/8029ac83-f0a9-4809-8bf9-f13c97c24bc6)\n\nAxol is for builders who believe robots should work, in the real world, not just staged environments.\n\nAxol’s Specs:\n\n* Extra-long 860mm reach & 4kg sustained payload\n* Joints exceeding human range of motion with fewer singularities\n* Protected cabling and robust hardware\n* Open-source SDK + data collection that works out of the box\n\nOur factory is in San Francisco so we can support teams directly and be there when it matters.\n\n**Available now.**\n\n* Axol — standalone robot\n* Axol Kit — robot + cameras + compute (start training day 0)\n\nFirst orders deliver this week.\n\nIf you're working on manipulation or physical AI, Axol is for you.", "url": "https://www.ycombinator.com/launches/QlH-axol-a-dual-arm-robot-built-for-ai", "votes": 20, "created_at": "2026-06-10T16:30:47.683Z" } ] }, { "id": 30433, "name": "The Robot Learning Company", "slug": "the-robot-learning-company", "former_names": [ "The Robot Learning Company (TRLC)" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fe9d24b61e68d5f71ffc72977fe38d21eece7328.png", "website": "https://www.robot-learning.co/", "all_locations": "BY, Germany", "long_description": "", "one_liner": "Tools for the next era of physical automation.", "team_size": 1, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1747554289, "tags": [ "Machine Learning", "Robotics" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "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/the-robot-learning-company", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/the-robot-learning-company.json", "year_founded": 2025, "city": null, "country": "DE", "linkedin_url": "https://www.linkedin.com/company/the-robot-learning-company/", "x_url": "https://x.com/RobotLearningCo", "fb_url": null, "cb_url": null, "github_url": "https://github.com/robot-learning-co", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/fe9d24b61e68d5f71ffc72977fe38d21eece7328.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/382e706b6ee5904a0c147f93557e4b51c58f4a40.png" ], "primary_partner": null, "founders": [ { "user_id": 2427273, "full_name": "Jannik Grothusen", "title": "Founder/CEO", "founder_bio": "Jannik holds a degree in Mechatronics and spent the past two years conducting robot learning research at UC Berkeley and TU Munich. He is actively contributing to open-source software for robot learning.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jannik-grothusen/", "x_url": "https://x.com/JannikGrothusen", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f13baadd68541cb03243f553e8c8050d2014021c.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 91187, "title": "TRLC - Affordable robotic workers", "tagline": "AI-powered robot platform that makes automation accessible to businesses.", "body": "Hi 👋 this is [Jannik](https://www.linkedin.com/in/jannik-grothusen/) - Founder of The Robot Learning Company.\n\n**TL;DR:** We make automation accessible to businesses with an affordable, general-purpose robot platform designed to automate repetitive, stationary tasks.\n\n![uploaded image](/media/?type=post&id=91187&key=user_uploads/2427273/0797ea73-9264-46d4-b089-731c1ec76f89)\n\n# The Problem\n\n**Traditional automation is broken** for tasks outside of factories. It’s expensive, rigid, and slow to deploy. Each new use-case demands a custom $100,000+ integration, months of setup, and only works in tightly controlled environments.\n\n**General-purpose robots promise to change that**. The dream: drop-in systems that replace expensive human labor with cheap, flexible robotic labor. But in reality, most general robotic systems don’t justify their cost. The math doesn’t work:\n\n**_Value = Human labor saved – Robot cost_**\n\nToday, robots lose this equation in two key areas:\n\n* Low productivity: they don’t save enough labor\n* Hardware, setup, and training costs are too high\n\nThe future doesn’t need more traditional robotic arms - it needs smarter, cheaper ones that can adapt quickly.\n\n# Our Solution\n\nWe’re building affordable and easy-to-deploy general-purpose robotic workers.\n\n\n\nWe combine:\n\n* **Low-cost hardware**: a pair of stationary robotic arms for under $10,000\n* **Self-learning control software**: we use imitation learning and offline reinforcement learning to adapt the robot to new tasks and environments from just a handful of demonstrations\n\nThis makes robotic automation accessible to a far broader set of businesses - even ones that previously couldn’t justify the investment.\n\n# About Us\n\nI’m [Jannik](https://www.linkedin.com/in/jannik-grothusen/), a former robot learning researcher at UC Berkeley and TU Munich, with a degree in Mechatronics. I’ve contributed to frontier open-source projects in robotic manipulation, and my work in the space has been [featured by TechCrunch](https://techcrunch.com/2024/11/04/built-in-four-days-this-120-robot-arm-cleans-a-spill-with-help-from-gpt-4o/).\n\n# Our Ask\n\nWe’re looking for pilot partners who want to automate repetitive manual tasks in their operations - and help us build the future of low-cost robotic labor.\n\n![uploaded image](/media/?type=post&id=91187&key=user_uploads/2427273/06432ad1-2691-4aac-b7ec-61325aa2c246)\n\n", "url": "https://www.ycombinator.com/launches/Nil-trlc-affordable-robotic-workers", "votes": 21, "created_at": "2025-06-10T19:52:00.513Z" } ] }, { "id": 30434, "name": "Zeon Systems", "slug": "zeon-systems", "former_names": [ "Zeon Technologies" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/95786f7359527c0b6051a250e5f3cb00d43b578b.png", "website": "https://www.zeonsystems.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "We’re building AI-powered systems that automate manual work in scientific labs using robotics.\r\n\r\nScientists simply type their experiment in plain English. Zeon translates it into code and runs it on robotic arms (no coding required).\r\n\r\nBy controlling robots with natural language, we’re enabling automation for every lab, every scientist, and every experiment.\r\n\r\nZeon is lab-aware. It detects equipment, adapts to protocols, and moves autonomously between instruments to execute full workflows.\r\n\r\nWe’re already working with labs at Stanford and UCSF to accelerate discovery - from running overnight nanoparticle fluorescence measurements to safely disposing of hundreds of bacterial samples. \r\n\r\nZeon reclaims time for what matters most: the science.", "one_liner": "AI-powered robotics for scientific lab automation.", "team_size": 5, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1745428848, "tags": [ "Robotic Process Automation", "Robotics", "Automation", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/zeon-systems", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/zeon-systems.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/zeon-systems/", "x_url": "https://x.com/zeonsystems", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/95786f7359527c0b6051a250e5f3cb00d43b578b.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": 379901, "full_name": "Brontë Kolar", "title": "Founder/CEO", "founder_bio": "cofounder & CEO @ Zeon Systems (YC X25)\n-\naccelerating science with robotics + AI.\n-\nbuilt electronic systems for electric aircraft and high-density batteries before pivoting to computational biology research at UCSF and UPenn. early engineer at LatchBio.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/bronte-kolar", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ef08976f1f1aa308a330e07e05531de19928bf84.jpg" }, { "user_id": 2502032, "full_name": "Tahir D'Mello", "title": "Founder/CTO", "founder_bio": "cofounder & CTO @ Zeon Systems (YC X25)\naccelerating science with robotics and AI.\n\n----------------\n\nbeen building software and ML for science labs basically all my adult life, doing computational research at IIT, Yale and working in biotech and pharma across India and the US.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/tahirdme/", "x_url": "https://x.com/TahirMello", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/437000c0ac09fa8258a3cafc8d88e43d147e15be.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 89951, "title": "Zeon Systems: AI-powered robotics for lab automation 🧪", "tagline": "We turn natural language into real-time lab automation.", "body": "Hey everyone 👋\n\nWe’re [Brontë](https://www.linkedin.com/in/bronte-kolar/) and [Tahir](https://www.linkedin.com/in/tahirdme/) – co-founders of [Zeon Systems](https://www.zeonsystems.ai/). We’re on a mission to make science move at the speed of thought.\n\n# **TL;DR**\n\n**We turn natural language into lab automation.** Scientists type their experiment in English. Our software programs robots to execute it.\\\n\n\n# **Problem**\n\nThe biggest scientific breakthroughs -- _think Selman Waksman mining microbes for antibiotics or Akira Yoshino testing early lithium-ion batteries_ _at Sony_ -- started in labs through painful, manual work. **Decades later, discovery still relies on pipetting, weighing, and prepping by hand.**\n\nIt’s inefficient, exhausting, and slows down discovery. Automation solutions exist, but are often **$$$** or built for **specific use cases**. \n\nWe want to change that.\n\n# **Our Take**\n\nWhat if you could run an experiment by just typing it out? \n\nThat’s what we’re building for: **automation that’s usable by everyday scientists.**\n\n# **The Zeon System 🦾**\n\nWe sell a hardware + software system that runs lab experiments using off-the-shelf robotics. **Labs receive a ready-to-run automation setup** that includes:\n\n* Our AI-powered software\n* 2 off-the-shelf robotics arms with mounted depth cameras\n\n_How it works:_\n\n* Scientists describe protocols in plain English\n* Zeon interprets them, detects lab tools using computer vision, and plans the execution\n* The system generates and executes robotic code in real-time, adapting to the specific lab environment\n\n![uploaded image](/media/?type=post&id=89951&key=user_uploads/379901/f18d8421-74dc-4213-8f17-a91419504529)\n\n# **What’s Possible**\n\nWe are already piloting with labs at UCSF and Stanford to:\n\n* Run fluorescence screens for nanoparticles overnight\n* Automate multichannel pipetting for clinical assays\n* Dispose of biohazardous waste while researchers sleep\n\n# **Big Picture**\n\nEventually, we want to **enable labs that run themselves**. Think self-driving labs on Mars or in the middle of the ocean doing science while humans dream. 🪐 🧪🧬\n\n# **The Team**\n\n[Brontë](https://www.linkedin.com/in/bronte-kolar/) built electronic systems for electric aircraft and high-density battery packs before pivoting to computational biology research at UCSF, UC Berkeley, and Erasmus Medical Center. \n\n[Tahir](https://www.linkedin.com/in/tahirdme/) has been building software and ML for science labs basically all his adult life, doing computational research at IIT, Yale and working in biotech and pharma across India and the US.\n\n# \n\n# **Our Ask**\n\nWe are looking for **pilot partners** interested in deploying our system in their labs! \n\n* **Know a scientific lab or company that should work with us?** → Email us at [founders@zeonsystems.ai](mailto:founders@zeonsystems.ai) \n* **Resonate with our message?** → Share this post (or our [promo video](https://www.youtube.com/watch?v=x-jid99QPFA))\n\n—\n\n[_Let’s make science move faster._](https://www.zeonsystems.ai/)\n\n\\-Brontë + Tahir\n\n![uploaded image](/media/?type=post&id=89951&key=user_uploads/379901/3896ab4e-84de-4bfd-ad2e-7fd6f0462be3)\n\n", "url": "https://www.ycombinator.com/launches/NOp-zeon-systems-ai-powered-robotics-for-lab-automation", "votes": 65, "created_at": "2025-04-29T23:00:50.835Z" } ] }, { "id": 30445, "name": "Mbodi AI", "slug": "mbodi-ai", "former_names": [ "mbodi AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ff64e6d141801dbac20dba751384bbd49f916a4a.png", "website": "https://www.mbodi.ai/", "all_locations": "New York City, NY, USA", "long_description": "Teach robots new skills through natural language and run reliably in production in minutes.\r\n\r\nMbodi combines generative AI and agent orchestration, turning everyday language and quick demos into precise, reliable robot actions for industrial automation.", "one_liner": "Industrial Robots that Learn and Operate Like Humans", "team_size": 6, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1747670628, "tags": [ "Robotics", "Automation", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Spring 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/mbodi-ai", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/mbodi-ai.json", "year_founded": 2024, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/mbodiai", "x_url": "https://x.com/mbodiai", "fb_url": null, "cb_url": null, "github_url": "https://github.com/mbodiai", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/ff64e6d141801dbac20dba751384bbd49f916a4a.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Pete Koomen", "url": "https://www.ycombinator.com/people/pete-koomen" }, "founders": [ { "user_id": 1639266, "full_name": "Sebastian Peralta", "title": "Founder/CEO", "founder_bio": "Interested in making humans lazier.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/sebjperalta", "x_url": "https://x.com/sebjperalta", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/53dc9bdb64b25f4747b238dc99fe2c79d0b2cc31.jpg" }, { "user_id": 1111983, "full_name": "Xavier (Tianhao) Chi", "title": "Founder", "founder_bio": "Building the future of AI x Robotics\nEx-Google TL, 8.8.8.8, Guardian of the Internet.\nECE @ UIUC", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/xavierchi/", "x_url": "https://x.com/chitianhao", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/983ab0d4bb8ac297b97811c83724ded2b8c13dbe.jpg" } ], "jobs": [ { "id": 104525, "title": "Founding Research Engineer", "url": "https://www.ycombinator.com/companies/mbodi-ai/jobs/NJF6jNS-founding-research-engineer", "location": "New York, NY, US", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$150K - $250K", "equity_range": "0.50% - 2.00%", "experience": "1+ years", "visa": "Will sponsor", "skills": [ "ML", "Python", "AI Agents" ] }, { "id": 104526, "title": "Senior Robotics Engineer", "url": "https://www.ycombinator.com/companies/mbodi-ai/jobs/KHiy8Yk-senior-robotics-engineer", "location": "New York, NY, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$150K - $250K", "equity_range": "0.50% - 2.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [ { "title": "How Mbodi is solving robotics’ scaling problem, with Xavier Chi | TechCrunch", "url": "https://techcrunch.com/podcast/how-mbodi-is-solving-robotics-scaling-problem-with-xavier-chi/", "date": "Sep 09, 2026" }, { "title": "Meet Mbodi, Automate’s 2026 Startup Challenge winner | Association for Advancing Automation", "url": "https://www.automate.org/ai/industry-insights/meet-mbodi-automates-2026-startup-challenge-winner", "date": "Jul 06, 2026" }, { "title": "Mbodi will show how it can train a robot using AI agents at TechCrunch Disrupt 2025 | TechCrunch", "url": "https://techcrunch.com/2025/10/27/mbodi-will-show-how-it-can-train-a-robot-using-ai-agents-at-techcrunch-disrupt-2025/", "date": "Oct 26, 2025" }, { "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 10, 2025" }, { "title": "Mbodi AI launches on Y Combinator, developing embodied AI for industrial robots", "url": "https://www.therobotreport.com/mbodi-ai-launches-y-combinator-developing-embodied-ai-industrial-robots/", "date": "May 22, 2025" } ], "launches": [ { "id": 90633, "title": "Mbodi AI- Embodied AI for Industrial Robotics", "tagline": "Teach robots new skills through natural language and run reliably in production, in minutes.", "body": "Hey friends [👋](https://emojipedia.org/waving-hand)\n\nThis is [Xavier](https://www.linkedin.com/in/xavierchi/) and [Sebastian](https://www.linkedin.com/in/sebbyjp/) - Co-Founders of Mbodi AI, and we are making robots learn like humans.\n\n# **TL;DR**\n\n**We’re building an embodied AI platform that lets anyone teach robots new skills — just by talking to them.** No code. No engineers. No week-long reprogram. Mbodi turns natural language and quick demos into precise, reliable robot actions that run in production in minutes, and adapt as often as you need.\n\nWe are now rolling out real-world deployments to customers with a joint commercialization partner, [ABB](https://new.abb.com/products/robotics), the world’s leading robot manufacturer.\n\nhttps://youtu.be/CwRxP3_F9MA\n\n# 🚨 **The Problem**\n\nManufacturing is facing a critical inflection point.\n\n**Labor crisis:** Labor accounts for nearly half of global GDP ($40+ trillion), but over 70% of factories face severe labor shortages.\n\n**Flexibility gap:** Traditional robots require week-long reprogramming by engineers or specialists every time things change.\n\n**Untapped automation potential:** Hundreds of billions of dollars in manufacturing tasks, especially those with high variation, remain out of reach for automation because robots can’t adapt fast enough.\n\nThis mismatch, between inflexible robots and ever-shifting production needs, leaves a massive automation gap across global manufacturing. We simply need robots to be more **versatile**. It wasn’t quite possible — **until now**.\n\n# **🧠 How Mbodi AI Helps**\n\nMbodi is an embodied AI platform that makes robots learn like humans, with natural language. So anyone can teach robots new skills by talking to them and execute the learned skills reliably in production, in minutes.\n\n![uploaded image](/media/?type=post&id=90633&key=user_uploads/1111983/cd7897e7-4fc9-4137-8c3d-2b6fe0b487bb)\n\nWe’ve built a cloud-to-edge system that takes your instructions, understands the environment, makes a plan, and turns it into precise, safe robot actions. All within a second. Our universal agent framework can run across any robotic hardware, coordinating perception, reasoning, planning, and control in real time.\n\n* 🕐 No week-long reprograms\n* 👷‍♂️ No on-site engineers\n* 🗣️ Just say what you want done\n* 🏭 Run reliably in production\n\nWhen one robot learns something, the entire fleet does. Individual skills can be reused, repurposed, and adapted instantly — across machines, factories, and tasks.\n\n# 🚀 **What’s Happening**\n\nWe’re moving toward real-world deployments after entering a joint commercialization agreement with ABB Robotics, one of the world’s leading robot manufacturers, following our win in their global AI Startup Challenge from among hundreds. This represents a first-of-its-kind system in industrial automation.\n\nWe’re building toward a world where robots are as easy to teach and adapt as software — turning them into true consumer commodities and making automation accessible to every factory and beyond.\n\n# 📣 **Our Ask**\n\nIf you're a **manufacturer**, **system integrator**, or **robot maker** exploring more flexible and intelligent automation, we’d love to connect and solve automation challenges that were previously out of reach.\n\nReach us at: [**founders@mbodi.ai**](mailto:founders@mbodi.ai)\n\nWe’re also strong advocates of the open-source community. We open-sourced one of our libraries, [embodied-agents](https://github.com/mbodiai/embodied-agents), to enable seamless integration of transformer models into robotics stacks, with more open-source projects coming in the future.\n\n# 👥 **The Team**\n\n[Sebastian Peralta](https://www.linkedin.com/in/sebbyjp/) is a physicist, roboticist, and deep learning researcher. Before Mbodi, he was a core engineer at Google Public DNS (8.8.8.8), and earned a triple major (EE, CS, Physics) from UPenn, where he also conducted graduate research at the GRASP Robotics Lab.\n\n[Xavier (Tianhao) Chi](https://www.linkedin.com/in/xavierchi/) is a former tech lead of Google Public DNS (8.8.8.8), one of the world’s most critical internet services, with work featured in[ The Register](https://www.theregister.com/2023/01/19/google_dns_queries/) and topping[ Hacker News](https://news.ycombinator.com/item?id=39960125). He holds bachelor's and master's degrees in ECE from UIUC.\n\n![uploaded image](/media/?type=post&id=90633&key=user_uploads/1111983/87381bac-5704-43f6-9fa3-1796b4af0f53)\n\nWe started Mbodi after seeing robots fall short of their potential — stuck in brittle code and long deployment cycles. With breakthroughs in generative AI and agentic systems, we’re building a future where robots can truly learn, adapt, and scale.\n\n![uploaded image](/media/?type=post&id=90633&key=user_uploads/1111983/447ef918-87d3-4a90-a120-04274434878f)\n\n", "url": "https://www.ycombinator.com/launches/NZp-mbodi-ai-embodied-ai-for-industrial-robotics", "votes": 98, "created_at": "2025-05-22T14:25:21.451Z" } ] }, { "id": 30469, "name": "HABIT", "slug": "habit", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/346513b86ce82dc04f53e62543ed7ec57a508425.png", "website": "https://habit.inc", "all_locations": "San Francisco, CA, USA", "long_description": "We build autonomous research agents that accelerate frontier world models.", "one_liner": "Accelerating world models.", "team_size": null, "industry": "B2B", "subindustry": "B2B", "launched_at": 1747768090, "tags": [ "Generative AI", "Robotics", "B2B", "API", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2025", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/habit", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/habit.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/habitinc", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/346513b86ce82dc04f53e62543ed7ec57a508425.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": 872167, "full_name": "Michael Trehan", "title": "Founder/CEO", "founder_bio": "Building HABIT. Prev: SWE @ Radiant Nuclear; Investment Banking @ JP Morgan. Berkeley M.E.T. alum.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/michaeltrehan", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/473afbd7753b7e048826def35476749260c6fb85.jpg" }, { "user_id": 315180, "full_name": "Harish Palani", "title": "Founder/CTO", "founder_bio": "Building HABIT. Prev: AI/ML Research Scientist @ Amazon; led deep learning projects at Twitch. Berkeley M.E.T. alum.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/harishkpalani", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b7709d4851ba41b48004b5910bd0a34dd73af38a.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 30509, "name": "Boost Robotics", "slug": "boost-robotics", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4ab11f23c518bbbd560df743f85f60218829e65f.png", "website": "https://www.boostrobotics.ai", "all_locations": "Boston, MA, USA", "long_description": "Boost Robotics is building autonomous mobile manipulation robots to remotely perform manual tasks in data centers. \r\n\r\nThe surge in AI applications is pushing data centers to scale faster than they can manage, leading to suboptimal operations and staffing shortages amid rising power and compute demands.\r\n\r\nWe save data centers millions in insurance premiums and SLA violations by increasing the frequency of inspection and maintenance while reducing the time it takes to triage and address failures.", "one_liner": "Robots for the inspection and maintenance of data centers", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1748984174, "tags": [ "Hard Tech", "Hardware", "Robotics", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": [ { "question": "How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)", "answer": "We met as engineering school freshmen at Carnegie Mellon University in 2015, when we both joined the same competitive Bhangra dance team. Over the next 10 years, we have lived together, performed and won awards at Bhangra competitions, worked together in school projects, and both received separate robotics Master’s degrees from CMU’s Robotics Institute. In every context we have worked together, we have found ways to grow, overcome challenges, and succeed. We’re excited to take the next step with this venture." } ], "url": "https://www.ycombinator.com/companies/boost-robotics", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/boost-robotics.json", "year_founded": 2025, "city": "Boston", "country": "US", "linkedin_url": "https://linkedin.com/company/boost-robotics", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/4ab11f23c518bbbd560df743f85f60218829e65f.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/3e373405fcdb24fc612d085c8d27845b37501b94.png" ], "primary_partner": { "name": "Diana Hu", "url": "https://www.ycombinator.com/people/diana-hu" }, "founders": [ { "user_id": 973181, "full_name": "Hardik Singh", "title": "Founder/CEO", "founder_bio": "Co-Founder @ Boost Robotics.\n\nMS in Robotic Systems Development @ CMU Robotics Institute. Commencement speaker at CMU SCS Masters Ceremony.\n\nI've worked on nearly every robot you can think of: autonomous drones, rovers, tractors, hexapods, quadrupeds, and robot arms - both cobot and industrial.\n\nRobots are hard. Building a talented team greater than the sum of its parts is the only way to do it.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/hardiksingh", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a81e9e30f870f18ad982d9ab996528d35300c310.jpg" }, { "user_id": 2564407, "full_name": "Hans Kumar", "title": "Founder/CTO", "founder_bio": "Co-Founder at Boost Robotics. Previously at Boston Dynamics and Carnegie Mellon Robotics Institute. Eagles fan and Taco Bell fan.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/kumarhans/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/085ccf5a8fc02e387262789439bdd65ac582ed38.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 91007, "title": "Boost Robotics - Robots for the inspection and maintenance of data centers", "tagline": "Physical Agents for Digital Infrastructure", "body": "Hello!\n\nWe are [Hans](https://www.linkedin.com/in/kumarhans) and [Hardik](https://www.linkedin.com/in/hardiksingh) - longtime friends and co-founders of Boost Robotics.\n\n**TL;DR**\n\nBoost Robotics builds autonomous mobile manipulation robots that can inspect and physically interact with data center infrastructure.\n\nInstead of dispatching technicians for every cable check, reboot, or hardware swap, data centers can now triage and resolve issues through “robot remote hands”. When not performing interventions, the robots continuously provide 24/7 security monitoring and operational analytics.\n\nhttps://www.youtube.com/watch?v=SVqbUd1crU0\n\n🚨 **The Problem**\n\nAs AI infrastructure continues to scale up, data center physical operations are becoming increasingly difficult:\n\n* **Growth bottleneck:** AI demand is scaling faster than the operational capacity to support it.\n* **Increasingly Remote Locations:** Data centers are being built near cheaper power sources in sparsely populated areas—often with limited access to skilled labor.\n* **Competition:** Hyperscalers are looking for every possible edge. Downtime means SLA violations and lost revenue.\n* **Hazardous Environments:** Maintenance involves high-voltage power and toxic liquid coolants.\n\nNow more than ever, robots are gaining the dexterity and generality to solve these critical problems.\n\n🤖 **The Solution**\n\nWe are building a general purpose robot to handle a variety of use cases in data centers. \n\n* Predict, find, and solve issues faster, even when you’re not physically on-site. \n* Enable one skilled technician to debug multiple issues across multiple sites through context-aware teleoperation, and eventually autonomy.\n* Provide 24/7 security monitoring and inventory management, simplifying compliance and financial audits while collecting data for your data center digital twin models.\n\n**Early Renderings of our Robot**\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXfjbzl61UaeLu1lIocEDGGwIyFhxHWCF9OIaKZb85nQ4MS-muTqxZDodGZE1IyiKbf8Ryo1f5n_tcic5oV284i0IvnG_4D1V3X2lxolzUC32Nrc4yeRF1uAHrxs71tU3NEnXoT-2g?key=m-hLuOQB66mOy66_Sg1ptQ)\n\n**Bi-Manual Teleoperation of the Manipulation Subsystem**\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXdqZfjtJGw48PJmg0KUnARoJVCpa29xC7wyK_3JTD7SuCact7vXgAA9csNhLUSKxNknFKbE9xTIsr6Uk5qwVUXSLJdd2QuRUt8EiSbtaFKRofi4p9PJVw8_jp8WkYIMcyr5GwXk?key=m-hLuOQB66mOy66_Sg1ptQ)\n\n# **👥 The Team**\n\nWe met as engineering school freshmen at Carnegie Mellon University in 2015, when we both joined the same competitive Bhangra dance team. Over the next 10 years, we lived together, worked together in school projects, and both received Master’s degrees from CMU’s Robotics Institute. We always knew we would start a company together.\n\n![uploaded image](/media/?type=post&id=91007&key=user_uploads/2564407/f3defc57-762e-47f4-9bfa-4a346913346b)\n\nHardik was previously robotics team lead at an agtech startup where he pivoted the team to a new product and made sales within 1 month. He was selected as commencement speaker for the CMU School of Computer Science Masters ceremony by his professors in recognition of his leadership.\n\nHans was previously a Staff Software Engineer at Boston Dynamics, where he worked on productizing computer vision algorithms for the Spot inspection robot. Before that, he built GPS-denied drone autonomy at a startup and conducted legged robotics research at CMU’s Robotics Institute.\n\n**Our Ask**\n\nWe're actively seeking forward-thinking data centers to pilot our autonomous robotics platform at their facilities. \n\nReach out to us at [**founders@boostrobotics.ai**](mailto:founders@boostrobotics.ai) — let’s shape the future of data center operations together.\n\n![uploaded image](/media/?type=post&id=91007&key=user_uploads/2564407/6f2eb4dc-5340-46dc-a264-fdf00f57c8ce)\n\n", "url": "https://www.ycombinator.com/launches/Nfr-boost-robotics-robots-for-the-inspection-and-maintenance-of-data-centers", "votes": 73, "created_at": "2025-06-04T02:59:25.110Z" } ] }, { "id": 30512, "name": "MorphoAI", "slug": "morphoai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b6d184a7985bf94fb06fe3645712c7af87070512.png", "website": "https://morpho.ai/", "all_locations": "New York City, NY, USA", "long_description": "We're building an AI powered platform for engineers that are building new robots and machines. \r\n\r\nWe allow users to invent and modify machine designs in a matter of minutes, not years. Ayna and Andy, the co-founders, met during their time at Harvard and started this in 2024 as their programs were wrapping up. We're commercializing 10+ years research done by our team at Harvard and MIT on this space. Our team wrote the very first papers on applying GenAI and optimization algorithms to compose robots from parts and applying computational design to fine tune machine designs. We're bringing in our deep knowledge of modifying equipment and integrating it into factories keenly understanding what makes hardware hard. \r\n\r\nWe take in parts under consideration, constraints and tasks at hand and our algorithm formulates and fine tunes from 100s of possible design options. All in a few clicks, so engineers can push hardware to market faster and companies can benefit from the inventions being done by their R&D teams. We already have two paying customers in the OEM and system integrator spaces. \r\n\r\nWe are venture backed and supported by a GBP 2.5MM grant by ARIA, the UK Government's invention agency. ", "one_liner": "Software tool for designing robots and machines ", "team_size": 7, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1746718035, "tags": [ "Robotics", "Manufacturing", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Spring 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/morphoai", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/morphoai.json", "year_founded": 2024, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/morphoai/?viewAsMember=true", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/b6d184a7985bf94fb06fe3645712c7af87070512.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": null, "founders": [ { "user_id": 2358627, "full_name": "Ayna Arora", "title": "Founder/CEO", "founder_bio": "Building an AI Powered CAD platform for robotics and machine engineers. Backed with a grant from the UK government. Founded 2 businesses in manufacturing tech previously, setting up factories each time (one of them is now series B). Former VC (software, manufacturing, and CPG focus). Harvard MBA / Industrials + Manufacturing undergrad. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/aynaarora/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/fbb25788fb7817f3b1da61f3e473e82d22cc0557.jpg" }, { "user_id": 2225896, "full_name": "Andrew Spielberg", "title": "Founder/CTO", "founder_bio": "\n\nCTO of MorphoAI - interested in simulation methods, design algorithms, and digital manufacturing processes.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/andrew-spielberg-82073926a/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9ce7186cd93e4275f6a302f4199728c7a03d3d3a.jpg" } ], "jobs": [ { "id": 76272, "title": "Founding Engineer", "url": "https://www.ycombinator.com/companies/morphoai/jobs/aTiZdB8-founding-engineer", "location": "London, England, GB", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "£40K - £110K GBP", "equity_range": "", "experience": "1+ years", "visa": "US citizenship/visa not required", "skills": [ "C#", "Python", "Torch/PyTorch", "Reinforcement learning (RL)", "Unity", "GPU Programming", "Software Architecture", "CAD Design" ] }, { "id": 97107, "title": "Chief of Staff", "url": "https://www.ycombinator.com/companies/morphoai/jobs/VvPeGQK-chief-of-staff", "location": "London, England, GB", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "£30K - £45K GBP", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] } ], "news": [], "launches": [ { "id": 90214, "title": "MorphoAI - AI‑powered computer‑aided invention for robotics and machine engineering", "tagline": "Turn parts and task requirements into working machine designs in minutes, not years.", "body": "We’re Ayna and Andrew, and we’re building [MorphoAI](https://morpho.ai/). We’re a team of manufacturing tech experts and MIT PhDs who have written 30+ papers on foundational research of AI design methods for robotics engineering. We met at Harvard last year and decided to help people develop hardware at the speed of software. \n\nIn our research, we demonstrated capabilities that allowed engineers to generate 100s of verified optimal designs from parts and task requirements in minutes, and now we’re translating those findings to a product for robotics & automation. We’re cutting R&D cycles by 50 %+ and letting teams ship better hardware, faster!\n\nhttps://www.youtube.com/watch?v=iGmXIsoUc2Y&feature=youtu.be\n\n### **Problem**\n\nDesigning a new robot, machine, or work‑cell still feels like 1985: weeks of manual CAD drawing, long prototype‑and‑test loops, and “does it even work?” uncertainty. A single product can take 40‑100 iterations and burn through months of engineering time. This all amounts to $240B spent on mechanical design each year. https://www.morpho.ai/ \n\n### **Our Take**\n\nWhat if you could take requirements and ideas into _validated machine designs_ automatically? We’re building that for hardware—so engineers can explore more, better-performing designs, fine-tune the ones likely to work, and land on an optimal design before the first part is cut. Engineers input and tasks and constraints (_what the robot must do)_ and their favorite parts to build with, and MorphoAI’s software auto‑generates, verifies, and fine tunes manufacturable designs in minutes—cutting R&D cycles by 50 %+ and letting teams ship new hardware faster. \n\n### **The MorphoAI Platform**\n\n1. **Generate** hundreds of verified design candidates from parts and task requirements in minutes, and select the concepts to fine-tune.\n2. **Simulate** full‑dynamical behavior with optimal, verified controllers.\n3. **Optimize** for cost, performance, weight, manufacturability, and more.\n\nThe result is a ready‑to‑manufacture machine design, programmable motions, and BOM—delivered in minutes, not months.\n\n### **Team**\n\n* **Ayna Arora** (CEO, Co-founder) – Harvard Business School; Former VC, 2x founder in manufacturing tech setting up factories across the world.\n* **Andy Spielberg, PhD** (CTO, Co-founder) – MIT CSAIL; Harvard PostDoc (digital manufacturing). 30+ papers on Optimization algorithms in robotics design.\n* Founding team: Allan Zhao (MIT PhD on GenAI for robot design), Amira Abdel-Rahman (Havard + MIT PhD on design for hardware) Han Wang (simulation expert in research+industry).\n\nWe’re also backed by ARIA (UK Government’s Invention Agency) with a 2.5MM GBP Grant.\n\n### **What’s Possible Today**\n\nOur early users are:\n\n* Resizing robot geometry and motors to maximize reach and payloads.\n* Redesigning workcells to minimize costs, design time, and improve margins.\n* Auto-generating new end-of-arm tooling designs from parts in hours, not weeks\n\n### **Big Picture**\n\nMorphoAI is the “compiler” for the physical world. As we expand our capabilities, any company will be able to invent machines that were previously infeasible— shrinking $MM R&D budgets and accelerating everything from factory automation to medical innovation to planetary exploration.\n\n### **Let’s Talk**\n\nBuilding a new robot or a new cutting-edge machine? We’d love to talk. Drop us a note at [**hello@morpho.ai**](mailto:hello@morpho.ai) .", "url": "https://www.ycombinator.com/launches/NT4-morphoai-ai-powered-computer-aided-invention-for-robotics-and-machine-engineering", "votes": 24, "created_at": "2025-05-08T17:40:20.776Z" } ] }, { "id": 30542, "name": "Linewise", "slug": "linewise", "former_names": [ "Comply Genie", "Vision Nexus", "LineWise", "Vision Lab" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2b6523fd3e82e786169b750e69bb81160c422bc6.png", "website": "https://linewise.io/", "all_locations": "San Francisco, CA, USA", "long_description": "We capture how physical things are made, from the first design to the final assembly, and turn it into training data for frontier AI and robotics models.", "one_liner": "Industrial data layer for physical RSI", "team_size": 25, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1743036496, "tags": [ "Robotics", "Manufacturing", "Data Engineering", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/linewise", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2025/linewise.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/linewise-ai/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/2b6523fd3e82e786169b750e69bb81160c422bc6.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/27f8fa04b65e99bdb2ebabb86e73fd71f35f9bb5.png", "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/35658d6d055e51d7f572f0d0813d8eb3a9b7bf76.png" ], "primary_partner": { "name": "Tom Blomfield", "url": "https://www.ycombinator.com/people/tom-blomfield" }, "founders": [ { "user_id": 2371704, "full_name": "Tanachart (James) Kujareevanich", "title": "Founder/CEO", "founder_bio": "James is the co-founder and CEO at Vision Lab. MBA from MIT. Former McKinsey Ops consultant.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/tanachartkujareevanich/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a51605bd53380345564966573f52709d42356d3c.jpg" }, { "user_id": 2373140, "full_name": "Zhichu Ren", "title": "Founder/CTO", "founder_bio": "Zhichu is the co-founder and CTO at Linewise. MIT PhD. Built robotics automation for materials research.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/zhichu-ren/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/98ef468f54a1e6b309dcae7ccfd3531eacb003e8.jpg" }, { "user_id": 2547908, "full_name": "Will Wenbo Zhang", "title": "Founder/CPO", "founder_bio": "Will is the co-founder and CPO at Linewise. MSE in AI & Robotics at UPenn GRASP Lab. Former founding engineer at Greyscale AI and Bestmow.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/wenbo-zhang6", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/dae0fb87a14c53d5de2764acef1e34263c5c100a.jpg" } ], "jobs": [], "news": [ { "title": "Vision lab raises $6m to bring real-world factory data to robotics foundation models · vision lab", "url": "https://thevisionlab.ai/articles/seed-2026", "date": "Jun 15, 2026" }, { "title": "Race Capital - Our Investment in Vision Lab: The Industrial Data Layer for Physical AI", "url": "https://race.capital/blog/our-investment-in-vision-lab-the-industrial-data-layer-for-physical-ai", "date": "Jun 15, 2026" } ], "launches": [ { "id": 99007, "title": "Vision Lab: The Industrial Data Layer for Robotics", "tagline": "Aggregating the Largest Manufacturing Process Data for Robotics Training", "body": "## **TL;DR**\n\nWe capture and structure real factory workflows at scale, pairing first-person industrial video with SOP-level process knowledge, so robotics and AI labs can train models on the data that actually exists inside production environments, not just lab demos. We are already working with 2 frontier AI labs.\n\n🎥 **Our 60-second Product Launch**:\\\n\n\n## **THE PROBLEM**\n\nThe robotics industry is being trained mostly on lab demos, even though robots will ultimately need to operate in messy, high-variance real factories. The industry has **less than 0.3% of the data it needs**, and almost none of it comes from real factory environments.\n\nWhy?\n\n**Industrial data does not exist at scale**\\\nIt cannot be scraped or passively collected. It has to be captured inside real factories, on real production lines, during real operations.\n\n**Raw footage is not enough**\\\nUnstructured industrial video is noise. Models need process context: what step is happening, in what order, with what tools, and whether it was done correctly.\n\n**Crowdsourcing cannot solve it**\\\nUnderstanding industrial actions requires factory expertise. Anyone can label an object; far fewer can distinguish whether a torque check, weld, inspection, or setup sequence was performed correctly.\n\n---\n\n## **THE SOLUTION**\n\nVision Lab solves the industrial data problem by building:\n\n**The most diverse industrial dataset**\\\nSOP-structured production data spanning cutting-edge environments like biotech, EV manufacturing, semiconductors, and medical devices, as well as large-scale manufacturing.\n\n**Industrial access at scale**\\\nA network of **2,000+ factories across 50+ industries in 27 countries**, with operators and factory owners embedded in the capture process so every sequence, tool, and technique is recorded correctly at the source.\n\n**A proprietary VLM for industrial settings**\\\nA temporal VLM trained on SOP-paired industrial footage to understand not just what is happening, but the **order, timing, and correctness** of real industrial processes. Our state-of-the-art VLM outperforms Gemini by **2.5x on temporal understanding in industrial settings**.\n\n---\n\n## **PARTNER WITH US**\n\nIf you believe the next decade of robotics and world models will depend on **real-world industrial data, not just compute**, we’d love to talk.\n\nVision Lab partners with robotics labs, frontier AI teams, and manufacturers to build the default industrial data layer for robotics.\n\n**Contact:** [founders@thevisionlab.ai](mailto:founders@thevisionlab.ai)\\\n**More info**: [www.thevisionlab.ai](http://www.thevisionlab.ai)\n\n![uploaded image](/media/?type=post&id=99007&key=user_uploads/2371704/81b524d4-30fd-40cf-9b55-6cacc2bcaffb)\n\n", "url": "https://www.ycombinator.com/launches/Pkt-vision-lab-the-industrial-data-layer-for-robotics", "votes": 18, "created_at": "2026-03-23T17:15:21.041Z" }, { "id": 90196, "title": "LineWise - AI Copilot for Manufacturers", "tagline": "AI that troubleshoots your production line", "body": "### **TL;DR**\n\nLineWise is building an AI assistant for manufacturing teams to get their production lines back up and running - fast.\n\nWe connect siloed factory data (PLCs, maintenance logs, manuals) to triage faults, guide technicians to fixes, and capture every resolution for smarter troubleshooting in the future.\n\n🎥 **Our 60-second Product Launch:\\\n[https://youtu.be/DfnmQ4k8q-k](https://youtu.be/DfnmQ4k8q-k)**\n\n### **THE PROBLEM**\n\nWhen a line goes down, it can take **hours** to identify the problem. Engineers and technicians chase PLC logs, flip through outdated manuals, and rely on the one person who “just knows.” While production stalls, tribal knowledge disappears, and the same issues repeat.\n\n### **THE SOLUTION**\n\nLineWise centralizes critical knowledge by integrating siloed data from IoT sensors, maintenance records, and machine manuals. It ranks the most likely causes and guides the team to a fix in just **minutes**. But the best part? It remembers every issue for next time and advocates for preventative actions.\n\n---\n\n### **How LineWise Works**\n\n🔧 Upload an error code image or describe the issue in a message.\n\n🤖 The AI provides a refocused problem statement for confirmation.\n\n📊 The AI dynamically ranks possible hypotheses of causes by probability.\n\n🧠 A human validates each hypothesis to identify the true cause.\n\n🛠️ Resolve the issue by following a step-by-step guide.\n\n🔍 Conduct further investigation to uncover the root cause.\n\n📚 Enrich the knowledge base with insights from the issue and resolution.\n\n---\n\n### **Join Us to Revolutionize Manufacturing**\n\nLineWise partners with forward-thinking manufacturers to minimize unplanned downtime, empower frontline teams, and unlock the value of siloed data within a company. \n\nIf that sounds like you, we’d love to talk.\n\n🔧 **Want to see LineWise in action?** Contact: [info@linewise.io](mailto:info@linewise.io)\n\n![uploaded image](/media/?type=post&id=90196&key=user_uploads/2371704/9ed0ed2e-2221-436f-8407-534f1abd18a2)\n\n", "url": "https://www.ycombinator.com/launches/NSm-linewise-ai-copilot-for-manufacturers", "votes": 37, "created_at": "2025-05-07T23:13:06.095Z" } ] }, { "id": 30629, "name": "Topological", "slug": "topological", "former_names": [ "TipTop", "TipTop AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/2b9c845239fb1f16317889a4a843409e109b24f6.png", "website": "https://www.topological.com", "all_locations": "San Francisco, CA, USA", "long_description": "Topological is developing physics-based foundation models for CAD optimization. We help hardware teams iterate at the same speed that software teams do. Our technology is accelerating the engineering workflow with AI and scales design and optimization to identify the ideal designs for complex problems given their physical constraints with enhanced speed and performance. \r\n\r\nOur first model, UToP-v1, is a SOTA topology optimization model that understands physics, geometry, and manufacturability. It can generate the most efficient design given a problem’s physical requirements. It has <5% compliance error and is 1930x faster than current methods. We're reimagining mechanical engineering and computational design with precision spatial AI.", "one_liner": "Physics-based foundation models for CAD optimization.", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1755729176, "tags": [ "Reinforcement Learning", "Robotics", "Design Tools", "3D Printing", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2025", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/topological", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/topological.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/topologicalai", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/2b9c845239fb1f16317889a4a843409e109b24f6.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": 2395628, "full_name": "Nicole Ma", "title": "Founder/CEO", "founder_bio": "Building Topological (YC S25). Prev. CS/MechE @ Stanford, physics simulations @ NASA", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/ma06nicole/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a27a3d8667b1bb56b79f33bd09bed9589db509ef.jpg" }, { "user_id": 2391326, "full_name": "Zeyneb Kaya", "title": "Founder/CTO", "founder_bio": "Building Topological (YC S25). Prev CS/Physics/Math @ Stanford; research in RL, pretraining, efficient algorithms, synthetic data, physics. 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Conducted research in the nanofabrication lab, and worked in industry on automating vision to action pipelines for agriculture robotics. Also deployed neural networks on edge including a patented system for child heat protection in vehicles. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/krisluo", "x_url": "https://x.com/theKrisLuo", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d15a85b53b352a41a9b96f6c123f78754ef02ca6.jpg" }, { "user_id": 1959092, "full_name": "Niel Ok", "title": "Founder/CTO", "founder_bio": "Co-founder and CTO at Null Labs. Previously led infrastructure at a DeepMind spinout working on automating AI research and studied EE and did neuroscience theory research at Stanford. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/niel-ok/", "x_url": "https://x.com/nielok20", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/a9410ed47494d188fbca6cc705e1d684e8dd53f7.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 30662, "name": "DeepAware AI (Robotics Center of Silicon Valley)", "slug": "deepaware-ai-robotics-center-of-silicon-valley", "former_names": [ "DeepAware AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b55e7c4492211c3d35247562da291230d55e6cdb.png", "website": "https://roboticscenter.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "DeepAware (Robotics Center of Silicon Valley, https://roboticscenter.ai/) is the fastest way for enterprises and researchers to get robots and robotics parts in the US — 72-hour delivery or Bay Area pickup.\r\n\r\nBeyond hardware, we help teams collect teleoperation data, build reinforcement learning environments, and deploy robots into production. Customers include AI labs, industrial operations, research teams, and event producers.", "one_liner": "Robots, parts & RL envs & evals - delivered in 48 hrs / pickup in SF.", "team_size": 4, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1753029704, "tags": [ "Machine Learning", "Robotics", "Supply Chain", "Data Engineering", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/deepaware-ai-robotics-center-of-silicon-valley", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/deepaware-ai-robotics-center-of-silicon-valley.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/roboticscenter/", "x_url": "https://x.com/RoboticsCtr", "fb_url": "https://www.facebook.com/roboticscenterai", "cb_url": "https://www.crunchbase.com/organization/deepaware-ai", "github_url": "https://github.com/roboticscenter", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/b55e7c4492211c3d35247562da291230d55e6cdb.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": 2760576, "full_name": "Jerry Huang", "title": "Founder/CEO", "founder_bio": "Building Robotics Center of Silicon Valley https://roboticscenter.ai/", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jerryh01/", "x_url": "https://x.com/jerryhuang01", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1a1c665b9491d7b3b0b21fc7085627a6859b1b85.jpg" }, { "user_id": 2786524, "full_name": "Stela Tong", "title": "Founder/CTO", "founder_bio": "Building DeepAware AI", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/stela-tong-a2583110b/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/eec06f27921ccffb2a5407cb05d034193102259a.jpg" } ], "jobs": [ { "id": 79914, "title": "Business Development Associate ", "url": "https://www.ycombinator.com/companies/deepaware-ai-robotics-center-of-silicon-valley/jobs/Oz49Id3-business-development-associate", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$50K - $100K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [] }, { "id": 79915, "title": "Robotics Engineer", "url": "https://www.ycombinator.com/companies/deepaware-ai-robotics-center-of-silicon-valley/jobs/2PyKMig-robotics-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$80K - $180K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [] }, { "id": 99767, "title": "Operations Associate", "url": "https://www.ycombinator.com/companies/deepaware-ai-robotics-center-of-silicon-valley/jobs/iyyRVWT-operations-associate", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "$50K - $100K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [] }, { "id": 100904, "title": "Business Development Intern", "url": "https://www.ycombinator.com/companies/deepaware-ai-robotics-center-of-silicon-valley/jobs/a9Gr7BR-business-development-intern", "location": "San Francisco, CA, US", "type": "Internship", "role": "Sales", "role_type": null, "salary_range": "", "equity_range": "", "experience": null, "visa": "Will sponsor", "skills": [] }, { "id": 100905, "title": "Robotics Engineer Intern", "url": "https://www.ycombinator.com/companies/deepaware-ai-robotics-center-of-silicon-valley/jobs/extm5EN-robotics-engineer-intern", "location": "San Francisco, CA, US", "type": "Internship", "role": "Engineering", "role_type": "Robotics", "salary_range": "", "equity_range": "", "experience": null, "visa": "Will sponsor", "skills": [] }, { "id": 100906, "title": "Operations Intern", "url": "https://www.ycombinator.com/companies/deepaware-ai-robotics-center-of-silicon-valley/jobs/o5YcLop-operations-intern", "location": "San Francisco, CA, US", "type": "Internship", "role": "Operations", "role_type": null, "salary_range": "", "equity_range": "", "experience": null, "visa": "Will sponsor", "skills": [] }, { "id": 102117, "title": "Marketing Intern", "url": "https://www.ycombinator.com/companies/deepaware-ai-robotics-center-of-silicon-valley/jobs/PHQdrZy-marketing-intern", "location": "San Francisco, CA, US", "type": "Internship", "role": "Marketing", "role_type": null, "salary_range": "", "equity_range": "", "experience": null, "visa": "Will sponsor", "skills": [] } ], "news": [], "launches": [ { "id": 92985, "title": "DeepAware - Automation for next-gen AI data centers", "tagline": "AI-driven automation that makes any data center as secure, efficient, and adaptive as Google’s or Amazon’s.", "body": "## **DeepAware - Automation for next-gen AI data centers**\n\n👋 Hello world! Are you ready to embrace a much more efficient AI infrastructure? Check out [DeepAware](http://deepawareai.com/) / [LinkedIn](https://www.linkedin.com/company/deepaware/):\n\nhttps://youtu.be/mywozPhOAnA\n\nTL;DR\n\n1. DeepAware AI brings Google- and Amazon-level technology to any data center, making them more secure, efficient, and autonomous.\n2. Our reinforcement learning scheduler, real-time market integration, and robotics cut energy waste by up to 30% while ensuring 24/7 uptime.\n\n![uploaded image](/media/?type=post&id=92985&key=user_uploads/2760576/4188b3ad-71bd-4af7-a52d-eac733f67211)\n\n**Problem**\n\n1. With AI workloads surging, the data center industry is booming—global capacity is expanding rapidly, and the market is projected to hit **$1 trillion by 2030**\n2. Data centers waste 20–30% of energy due to siloed tooling and manual controls.\n3. Hyperscalers like Google and Amazon solve this with custom AI, but mid-market operators lack access to those technologies.\n\n![uploaded image](/media/?type=post&id=92985&key=user_uploads/2760576/c08c6a9b-22d9-4ffa-830a-c828ce7597a5)\n\n**Solution**\\\nDeepAware brings Google- and Amazon-grade AI controls to any data center:\n\n1. **RL Scheduler** optimizes GPU workload placement for power, performance, and cost.\n2. **Real-Time Market Integration** shifts workloads to low-price windows and supports demand-response programs.\n3. **Unified Dashboard** for one-click policy tuning, automated alerts, and “what-if” scenario testing.\n4. **Autonomous Robotics (coming soon)** for remote “robot hand” inspections, cable swaps, and maintenance—enabling 24/7 physical operations with minimal on-site staff.\n\n![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeWFdq7APkR0uqewAgWtXeKANKr7EDV1KIz0diikWoGKDlTmA6bqIP_-8vNP0V4Fp9d0il-oEnk8u4uCkO_usPJd4xVHtCOifCEAgMO4muD-Dh7s_sFDGyNnR8YeClKD71vLBoOeA?key=Ok6o8HSu--upaY5wBSe41Q)\n\n**Our Team:** \n\n1. We are both second-time founders. We spent 3 years together building our first company providing second-level energy optimization for dozens of factory.\n\n**Traction:**\n\n1. **6-digit agreement** with a major 30 MW+ data center operator to use our system.\n2. **Simulation results** show 15% energy savings.\n3. **Industry validated** through Green AI Summits at Harvard with industry leaders from Oracle and Meta AI.\n\n**Ask:\\\nWe’re looking for:**\n\n1. **Data center operators** (and people in the AI infra sector) interested in piloting AI-driven optimization.\n2. **AI/ML researchers** tackling real-world control problems.\n\nGot feedback or want to pilot? Reach out: 👉 [jerry@deepawareai.com](mailto:jerry@deepawareai.com) or [LinkedIn](https://www.linkedin.com/in/jerryh01/) visit http://deepawareai.com/.\n\n![uploaded image](/media/?type=post&id=92985&key=user_uploads/2760576/03fe5788-d736-48c7-83f3-98bf11b31fca)\n\n", "url": "https://www.ycombinator.com/launches/OBl-deepaware-automation-for-next-gen-ai-data-centers", "votes": 15, "created_at": "2025-08-14T01:42:09.062Z" } ] }, { "id": 30689, "name": "b12 Labs", "slug": "b12-labs", "former_names": [ "B12", "b-12" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/64c9b960693fdd85d6fb6be6fefc443ca4ab80af.png", "website": "https://b12-labs.com/", "all_locations": "San Francisco, CA, USA", "long_description": "b12 makes high-value molecules that are otherwise hard to make. We help pharma companies plan and make new drugs, accelerating early-stage drug discovery from years to months.\r\n\r\nAndres built the first AI agent that can autonomously think and make molecules in a robotic lab, published in Nature Machine Intelligence (1000+ citations), and won the best paper award at the NeurIPS AI for Science conference.\r\nZlatko is a 3x National Chemistry Olympiad champion, competed at IChO level, and medicinal chemist who has worked at Roche and leading lab robotics companies. \r\n\r\nCombined, we have an extensive network of hundreds of chemists, automation scientists, and AI 4 Science researchers.\r\n\r\nWe run paid pilots with big pharma companies, demonstrating that our platform planned a set of experiments that achieved full conversion in a single attempt, eliminating the iteration cycle.", "one_liner": "Making hard molecules for Pharma and Biotech", "team_size": 3, "industry": "Healthcare", "subindustry": "Healthcare -> Drug Discovery and Delivery", "launched_at": 1753004647, "tags": [ "AI-powered Drug Discovery", "Robotics" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2025", "status": "Active", "industries": [ "Healthcare", "Drug Discovery and Delivery" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": [ { "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": "Andres and Zlatko met at EPFL, while working in the Lab of Artificial Chemical Intelligence. Zlatko was doing his postdoc and Andres was doing his PhD." }, { "question": "How did you decide to apply to Y Combinator? What was your experience applying, going through the batch, and fundraising at demo day?", "answer": "We decided to apply after we had a YC partners visit our campus at EPFL. Experience was very intense, a lot of work and great advice on how to build a startup. " } ], "url": "https://www.ycombinator.com/companies/b12-labs", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/b12-labs.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/108178057/admin/dashboard/", "x_url": "https://x.com/b12Labs", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/64c9b960693fdd85d6fb6be6fefc443ca4ab80af.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/2086595d1ba11517239f8da752e3e320cd135a61.png" ], "primary_partner": { "name": "Diana Hu", "url": "https://www.ycombinator.com/people/diana-hu" }, "founders": [ { "user_id": 2507050, "full_name": "Zlatko Jončev", "title": "Founder/CEO", "founder_bio": "at b-12 we are developing AI agents for automated workflows in chemistry and pharma R&D, as a way of manifestating chemical super intelligence in physical world.\n\nour long-term goal is to create autonomous labs that can perform complex, multistep syntheses with minimal human intervention.\n", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/zlatkojoncev/", "x_url": "https://x.com/ZJoncev", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3dbd05f37d1de0578d9ceb0b4ef177c4ad19375c.jpg" }, { "user_id": 2507280, "full_name": "Andres Bran", "title": "Founder/CTO", "founder_bio": "Before b-12, Andres built the first AI agent to plan and make molecules in a robotic lab (750+ cites in Nature Machine Intelligence, and Best Paper at NeurIPS AI for Science), along with several other works in agents and LLMs for chemistry (1100+ citations).\nHe was an Intern at Max Planck (Math in Science), and PhD at EPFL (AI+Chemistry).\n\nAutomation is the future of chemistry, but integration and human operability is the hidden demon nobody talks about. We're fixing that at b-12.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/andrescmb", "x_url": "https://x.com/drecmb", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/88d3dfc21250265c0b0b6f6f758fa7494e23fbfa.jpg" } ], "jobs": [ { "id": 105109, "title": "Founding Product Engineer (Full Stack)", "url": "https://www.ycombinator.com/companies/b12-labs/jobs/IEX0tV9-founding-product-engineer-full-stack", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$120K - $160K", "equity_range": "0.50% - 2.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [], "launches": [ { "id": 120586, "title": "b12 Foundry - We Make the Molecules AI Designs", "tagline": "AI Chemistry Foundry - from a molecule on a screen to a compound in a vial", "body": "![uploaded image](/media/?type=post&id=120586&key=user_uploads/2507050/a1d7d999-eef2-4350-86a4-f299ef904756)\n\n\\\n**TL;DR:**\n\nAI can design a molecule in seconds, but making it can still take a chemist weeks. b12 Foundry turns a molecule on a screen into a compound in a vial, in a fraction of the time it would take a chemist. A combination of state-of-the-art AI agents plans the route, designs the experiments and runs them on robots in our partner lab, so you get your molecules, and clean data including failed reactions, without needing a lab of your own. **Last year we launched here as a chemistry copilot. Today we work with several large companies, across pharma, flavor and fragrance, energy and biotech industries and universities, and the Foundry is actively making molecules for clients.**\n\n#### ❌ **The problem:**\n\n**AI designs molecules faster than anyone can make them:**\n\n* AI models can now design a molecule in seconds, but making it can still take a chemist weeks.\n* The most interesting designs sit outside the catalogues vendors build from simple, reliable reactions, so someone has to make each one by hand.\n* In practice, teams end up testing an easier cousin of the molecule their model wanted, or nothing at all.\n\n**Good chemistry data is hard to find:**\n\n* Published data mostly shows the reactions that worked, so the failures that models need to learn from rarely get recorded.\n* Running clean, consistent experiments at scale takes a lab, robots and people that most AI teams don't have.\n\nIf you're building AI for drug discovery or materials, synthesis is quickly becoming your bottleneck.\n\n## ✅ **Our Solution:**\n\n\n\n**b12 Foundry** combines state-of-the-art AI agents with robots in our partner lab, so we can **plan** and **run** complex chemistry for you, end to end.\n\n**How it works:**\n\n* **Send us a molecule or a workflow:** Share a structure your model designed, or an experiment you want run.\n* **Our agents plan the chemistry:** They work out how to make the molecule and design the experiments for the hardest steps.\n* **Robots run it in our partner lab:** The agents run every experiment on the robots, including chemistry that is hard to do by hand.\n* **You get compounds and data back:** You receive the molecules plus every result, failed reactions included, and everything we run for you belongs to you.\n\n## **👥 Our Team:**\n\nWe are Zlatko and Andres, and in the past, we have:\n\n1. Worked with big pharma (Roche), Chemical Robotics ([**Chemspeed**](https://chemspeed.com/)), and big chemical data ([**MaxPlanck**](https://www.mis.mpg.de/));\n2. Pioneered [**AI agents**](https://www.nature.com/articles/s42256-024-00832-8) for chemistry and [**retrosynthesis**](https://arxiv.org/abs/2503.08537) (at EPFL);\n3. Invented [**new chemistry**](https://onlinelibrary.wiley.com/doi/10.1002/anie.202211168).\n\nWhen we launched here last year, we promised a full stack from planning to robotic execution. Since then, our customer base has grown well beyond pharma. Alongside three large pharma companies, including a top-3 global pharma that came back as a repeat customer, we now work with a flavor and fragrance leader, energy companies, biotech companies, and universities around the world. An AI drug discovery platform has also built our synthesis agent into its own pipeline, and this summer we opened the Foundry, which is actively making molecules for clients.\n\nThe team has grown with it. **Adriana Faraone**, our Research Scientist, runs the experiments in the Foundry, and **Victor Sabanza Gil** joins us from his PhD at EPFL, where he worked on [**Bayesian optimization**](https://arxiv.org/abs/2410.00544) for molecules and materials, the kind of AI that decides which experiment to run next. Together, we give anyone with a molecule on a screen extra **brainpower** and an **additional pair of hands**.\n\n## 🙏 Our Ask:\n\nDo you know a biotech or AI-for-science team whose molecules are hard to make, or who needs experimental chemistry data? We would love a warm intro!\n\nIf you've set up a wet lab in the Bay Area, we'd love 20 minutes of your advice, because our own lab here is next.\n\nSend us an email at: [founders@b12-labs.com](mailto:founders@b12-labs.com) or send them to our website: [b12-labs.com](http://b12-labs.com)\n\n#### ", "url": "https://www.ycombinator.com/launches/VMw-b12-foundry-we-make-the-molecules-ai-designs", "votes": 6, "created_at": "2026-10-08T13:52:26.985Z" }, { "id": 92473, "title": "b-12 - Chemistry Copilot for Pharma & Biotech", "tagline": "Full Stack Chemistry Platform - from planning to robotic execution of experiments", "body": "**TL;DR:**\n\nDrug discovery is slow, and it costs billions of dollars. The bottleneck in early discovery is chemical synthesis. b-12 is building a full stack of AI agents to deliver planning and robotic executions of experiments, in minutes, not months. **Our team has developed custom robots for chemistry (Chemspeed), orchestrated AI agents for lab control (EPFL & IBM), and is translating this into a powerful and easy-to-use product.**\n\n**Ask:** Are you running chemistry experiments or chemical robots? Do you know someone who is? Email us at [founders@b12-labs.com](mailto:founders@b12-labs.com) to be added to our pilot program. See below for details.\n\nhttps://www.youtube.com/watch?v=qmf7q-Sie2o\n\n# ❌ **The problem:**\n\n**Drug Discovery is slow:**\n\n* It takes 10+ years and over $2 billion to discover a new drug.\n* 2 in 10000 compounds make it.\n* Chemistry execution is very slow.\n\nExperiments take time! Designing good experiments and trial and error in the lab are big factors.\n\n![uploaded image](/media/?type=post&id=92473&key=user_uploads/2507050/0cd3f202-e48b-48da-a6e5-3ae1572cddab)\n\n**Software for chemists is fragmented:**\n\n* There are many solutions for many different parts of the pipeline.\n* Tools are outdated, and integration is largely missing.\n\n**Lab robots are underused:**\n\n* Most lab robots are _not accessible to scientists_ because they are hard to use.\n* Drag and drop software for multimillion-dollar robotic labs.\n* Lab automation engineers are hard to find.\n\n**Current State:**\n\n![uploaded image](/media/?type=post&id=92473&key=user_uploads/2507050/2a3d91a0-8e78-44d9-a89c-f1dcc7b45f67)\n\n**b-12:**\n\n![uploaded image](/media/?type=post&id=92473&key=user_uploads/2507050/893d0cd2-d071-43be-b08e-ddf29b8aaddc)\n\n# ✅ **Our** **Solution:**\n\nWe are integrating a full stack of Agents to **design experiments** and **write code for the robot** that runs these experiments, with the tools and context needed to predict chemically meaningful results, and close the experimental loop.\\\n\\\n**Key capabilities of our Agents:**\n\n* **Streamline Experiment Planning**: Our tools accelerate creation of experimental details based on literature and expert tools, and tailor the output to the user’s specific needs.\n* **Unified platform:** Our platform integrates several agents that are in tight communication and can go from natural language input to robotic execution in minutes.\n* **No coding required - use natural language:** With arbitrary input flexibility, we can control the robot the same way you would talk to your lab-mates, including inputs from previous runs, and uploading relevant documents.\n* **Parallel and scalable to any lab:** We are vendor agnostic, and integrate with different robotics (Chemspeed, Unchained, Opentrons, etc.) and labs performing experiments manually.\n\n**Pilot Program:** Our team will work on integrating Agentic solutions tailored to your lab's specific problems, whether you use lab automation or not. We want to speed up molecular discovery.\n\n# **👥 Our Team:**\n\n![uploaded image](/media/?type=post&id=92473&key=user_uploads/2507050/92133d6c-ba4b-4722-9115-8c45405366aa)\n\nWe are Zlatko and Andres, and in the past, we have:\n\n1. Worked with big pharma (Roche), Chemical Robotics ([**Chemspeed**](https://chemspeed.com/)), and big chemical data ([**MaxPlanck**](https://www.mis.mpg.de/));\n2. Pioneered [**AI agents**](https://www.nature.com/articles/s42256-024-00832-8) for chemistry and [**retrosynthesis**](https://arxiv.org/abs/2503.08537) (at EPFL);\n3. Invented [**new chemistry**](https://onlinelibrary.wiley.com/doi/10.1002/anie.202211168);\n\nNow we want to integrate it into a seamless platform, where anyone who wants to run experiments gets extra **brainpower** and an **additional pair of hands**.\n\n# 🙏 Our Ask:\n\nDo you know anyone in chemistry working in the pharmaceutical or biotech industry?\n\nWe would love a warm intro!\n\nSend us an email at:\n\n[founders@b12-labs.com](mailto:founders@b12-labs.com) or send them to our website: [b12-labs.com](http://b12-labs.com)", "url": "https://www.ycombinator.com/launches/O3V-b-12-chemistry-copilot-for-pharma-biotech", "votes": 37, "created_at": "2025-07-31T16:18:49.754Z" } ] }, { "id": 30703, "name": "Physical Turing", "slug": "physical-turing", "former_names": [ "Riff", "GoRiff" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c87367cd52d809c0b9a6f05ef79f3c162b4dd082.png", "website": "https://physicalturing.ai/", "all_locations": "New York City, NY, USA", "long_description": "Physical Turing is a neo robot deployer. Our core tech lets us deploy any robot fast, and every deployment produces the real-world data we use to train our own intelligence.\r\n\r\nWe're starting by automating industrial inspection and security tasks, which have historically had labor shortages due to their safety risks.", "one_liner": "Next generation robot deployer", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1752283172, "tags": [ "Robotics", "B2B", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/physical-turing", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/physical-turing.json", "year_founded": 2025, "city": "New York City", "country": "US", "linkedin_url": "https://www.linkedin.com/company/physical-turing", "x_url": "https://x.com/rifflab", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/c87367cd52d809c0b9a6f05ef79f3c162b4dd082.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/ec9a6ee68dafa82450d8affd515bbf47d968e5e4.png" ], "primary_partner": { "name": "Tyler Bosmeny", "url": "https://www.ycombinator.com/people/tyler-bosmeny" }, "founders": [ { "user_id": 2491351, "full_name": "Adith Reddi", "title": "Founder/CEO", "founder_bio": "Building Physical Turing | Berkeley CS, music producer (1M+ streams), AI whiz", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/adithreddi/", "x_url": "https://x.com/adithreddi", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/cf79654eb9926f610e9226cea25b3ce23786f144.jpg" }, { "user_id": 2545325, "full_name": "Kenny Zhang", "title": "Founder/CTO", "founder_bio": "Building Physical Turing | Berkeley CS, Music Producer, Formerly @ Tencent, Amazon", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/kenny-zhang-jinlin/", "x_url": "https://x.com/Zerkka0819", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f477208af46421413842cbf7e2345d5b82c4aa44.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 92151, "title": "Riff – Cursor for music production", "tagline": "Riff is a music editor w/ superpowers — make music without needing extreme technical chops.", "body": "Hey YC!\n\nWe’re Adith and Kenny — the founders of Riff!\n\n# **TL;DR**\n\n[Riff](https://goriff.com) is a **music editor with superpowers** where experienced producers can be 10x more productive and hobbyists can delight in making music without needing technical chops.\n\n[**https://youtu.be/bjyjtr8-yz8**](https://youtu.be/bjyjtr8-yz8)\n\n# **Problem**\n\n**Slow**\n\n🖥️ ❌ Legacy music production software is clunky and weighed down by archaic UX.\n\n**Repetitive**\n\n🎧 ❌ Musicians sometimes spend hours making changes that should realistically happen in minutes. With legacy software, there is no high-signal way of getting your creativity down.\n\n**High skill barrier**\n\n🎸❌ The difficulty of existing tools blocks people with musical interest but no patience to learn complex audio engineering.\n\n# **Solution**\n\nRiff is an AI music editor meant to make music creation easier, yet still keeps the artist in charge.\n\n🤘 Add sounds in your style directly into the editor using AI\n\n![uploaded image](/media/?type=post&id=92151&key=user_uploads/2491351/381a389e-ba7a-41c9-9954-b5994667ec53)\n\n🎵 Arrange sounds with AI\n\n![uploaded image](/media/?type=post&id=92151&key=user_uploads/2491351/d7011ba4-8c5c-4c3b-b46c-0f73dedce6c2)\n\n# **Team**\n\nAdith and Kenny met at Berkeley through a music collective they started (now 1200+ artists large).\n\n🎹 Adith has been making music for \\~5 years, has 1M+ streams on Spotify, and is deep into audio AI.\n\n🥁 Kenny has been making music for \\~8 years, Ex-Tencent Ex-Amazon, and releases frequently on Spotify.\n\n# **Who’s it for?**\n\nIn the short run, we’re targeting aspiring musicians who are between entry level music software like GarageBand and BandLab. Very soon, we’ll have enough features that we can directly compete with FL/Ableton/Logic/Pro Tools and get experienced producers onboard.\n\n# **Our Asks**\n\n**If you answer yes** to any of these questions, would be great if you can **share this post** with your network:\n\n* Do you know someone who has always wanted to make music but finds the tools too hard?\n* Do you know professional artists who can sing/play instruments but do not know digital music production?\n\nYou can reach out to us here: [founders@goriff.com](mailto:founders@goriff.com) or 610-762-5102\n\n![uploaded image](/media/?type=post&id=92151&key=user_uploads/2491351/0674ebe1-dc13-4e4a-9c79-5c4599a4829f)\n\nThanks for your time everyone!\n\nBest,\n\nAdith and Kenny\n\n![uploaded image](/media/?type=post&id=92151&key=user_uploads/2491351/a37461fa-e46b-4ef8-b5f6-a4f71352d3c7)\n\n", "url": "https://www.ycombinator.com/launches/NyJ-riff-cursor-for-music-production", "votes": 80, "created_at": "2025-07-15T14:10:27.207Z" } ] }, { "id": 30712, "name": "Relling", "slug": "relling", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e003594279b3a4474845b643ff2ee16c26f34a1a.png", "website": "https://relling.co", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "deploying the first billion robots for manufacturing", "team_size": null, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1756070413, "tags": [ "Robotics", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2025", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/relling", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2025/relling.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/107829108/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/e003594279b3a4474845b643ff2ee16c26f34a1a.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": 2707563, "full_name": "Anya Singh", "title": "Founder/CTO", "founder_bio": "chess player", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/anya-singh/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/180178bdbd6050c5bf36936482b695846168c79a.jpg" } ], "jobs": [ { "id": 95370, "title": "Robot Learning Engineer", "url": "https://www.ycombinator.com/companies/relling/jobs/iQ4YH9e-robot-learning-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$120K - $170K", "equity_range": "0.10% - 0.30%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 95371, "title": "Partnerships Lead, Specialty Manufacturing", "url": "https://www.ycombinator.com/companies/relling/jobs/U34pXE8-partnerships-lead-specialty-manufacturing", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Sales", "role_type": null, "salary_range": "$120K - $170K", "equity_range": "0.10% - 0.30%", "experience": "6+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 97830, "title": "Business Operations Intern", "url": "https://www.ycombinator.com/companies/relling/jobs/ZFJwHfg-business-operations-intern", "location": "San Francisco, CA, US", "type": "Internship", "role": "Operations", "role_type": null, "salary_range": "$20 - $100 / hourly", "equity_range": "", "experience": null, "visa": "US citizen/visa only", "skills": [] }, { "id": 99957, "title": "Software Engineer Intern", "url": "https://www.ycombinator.com/companies/relling/jobs/H005USc-software-engineer-intern", "location": "San Francisco, CA, US", "type": "Internship", "role": "Engineering", "role_type": "Robotics", "salary_range": "$20 - $60 / monthly", "equity_range": "", "experience": null, "visa": "US citizen/visa only", "skills": [ "C++", "Python" ] }, { "id": 99958, "title": "Software Engineer, Perception ", "url": "https://www.ycombinator.com/companies/relling/jobs/nX7Gp7O-software-engineer-perception", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$120K - $170K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 100284, "title": "Growth and Content Lead Intern", "url": "https://www.ycombinator.com/companies/relling/jobs/UrTtzOc-growth-and-content-lead-intern", "location": "San Francisco, CA, US", "type": "Internship", "role": "Marketing", "role_type": null, "salary_range": "$20 - $50 / hourly", "equity_range": "", "experience": null, "visa": "US citizen/visa only", "skills": [] }, { "id": 109217, "title": "Marketing Lead Generation Specialist (Paid & Search)", "url": "https://www.ycombinator.com/companies/relling/jobs/ipBV0cN-marketing-lead-generation-specialist-paid-search", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Marketing", "role_type": null, "salary_range": "$20 - $50 / hourly", "equity_range": "", "experience": "1+ years", "visa": "Will sponsor", "skills": [ "Microsoft Azure", "Marketing design", "Figma", "Photoshop" ] } ], "news": [], "launches": [] }, { "id": 30728, "name": "OS3", "slug": "os3", "former_names": [ "Observee" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/bd88161755dbb4d7513a2dc91e69b26930313524.png", "website": "https://os3robotics.com/", "all_locations": "San Francisco, CA, USA", "long_description": "OS3 is building the platform that makes intelligent robots accessible to every business.\r\n\r\nToday, robotics is constrained by two fundamental bottlenecks: hardware is too expensive to deploy at scale, and robots are difficult to train because high-quality robotics data is scarce and costly to collect. \r\n\r\nWe built OS3 to solve both.\r\n\r\nOur two-person team designed and a US-made mobile humanoid robot for a fraction of the cost of commercial alternatives. On the intelligence side, instead of relying on expensive robot-generated training data, we trained our own video-action model on 150,000 hours of real-world video spanning more than 2,000 tasks. Every deployed robot feeds new experience into our reinforcement learning pipeline, self improving robot fleet over time.\r\n\r\nThis creates a robot that can be deployed across industries to automate repetitive, physical work without requiring a new robot or training pipeline for every task. Our robots are already deployed in hotels, with customers now expanding the platform into biotech, hospitals, and data centers, including a wet lab at Stanford.\r\n\r\nOur mission is to do for robotics what Apple did for personal computing: take technology that was once expensive, specialized, and inaccessible and make it powerful and usable at massive scale. We’re building toward a world with billions of intelligent robots, and OS3 is the platform that makes that possible.", "one_liner": "Affordable, intelligent humanoid robots built to deploy at scale", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1753297896, "tags": [ "Hardware", "Robotics", "B2B", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "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/os3", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/os3.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/os3", "x_url": "https://x.com/os3robotics", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/bd88161755dbb4d7513a2dc91e69b26930313524.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": 1427209, "full_name": "Rishabh Chanana", "title": "Founder", "founder_bio": "Built a computer at 10. First line of code at 12. Built & programmed a robot at 17.\n\nGrad School at UCSD, Robotics & AI. NLP research with Harvard and Georgia Tech. Trained LLMs at ServiceNow & built patented ML systems.\n\nNow soldering and training robots at OS3.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/risos8200/", "x_url": "https://x.com/risos8200", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5ef6e03c90f9e979491f4a8676962acf0df0db05.jpg" }, { "user_id": 1909563, "full_name": "Chris Hailey", "title": "Founder", "founder_bio": "Co-Founder at OS3. Ex-Coinbase software engineer on the asset addition team, generated over $19 billion of trading volume. Turned a YC hackathon winning project into a $10K MRR idea. Undergrad CS from USC with Presidential Merit scholarship. Serial marathon runner, most recently completed the 2025 Oakland Marathon in 3 hours 12 minutes.", "is_active": true, "linkedin_url": "https://linkedin.com/in/chrishailey8", "x_url": "https://x.com/realChrisHailey", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/8ef8f471703ec1718bd79c1c35df1da5a33528f6.jpg" } ], "jobs": [ { "id": 100908, "title": "Mechanical Design Engineer - Robot Parts & Enclosures (Contract)", "url": "https://www.ycombinator.com/companies/os3/jobs/r2aKeWa-mechanical-design-engineer-robot-parts-enclosures-contract", "location": "San Francisco, CA, US / Remote (IN)", "type": "Contract", "role": "Engineering", "role_type": "Hardware", "salary_range": "₹360K - ₹800K INR", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizenship/visa not required", "skills": [ "CAD Design" ] } ], "news": [ { "title": "Meet The YC Startups Betting On What Comes Next", "url": "https://www.forbes.com/sites/dariashunina/2026/09/03/meet-the-yc-startups-betting-on-what-comes-next/", "date": "Sep 03, 2026" } ], "launches": [ { "id": 110139, "title": "OS3: Intelligence and Machines for Physical Labor", "tagline": "Semi-humanoid hardware & Model based on 150k hours of Videos. Preorders Live Now", "body": "**TL;DR: OS3 is building semi-humanoid robots for physical labor. Our first robot, H.A.L.E 1.0, is built for everyday human tasks, and our first model is based on 2,000+ distinct real-world tasks and 150,000 hours of video data. We are opening up pre-orders to all with shipments starting this Fall.**\n\n**Physical AI Problem:**\n\nA lot of teams and businesses want to build and deploy in the robotics space. But they have to source parts or buy hardware from different vendors. Furthermore, the recent import ban makes it even harder for beginners and startups to use the latest hardware, unless they are willing to spend tens of thousands of dollars. Post hardware, constant data collection is needed to adapt open or closed-source models to the ever changing hardware choices. In other words, everyone keeps reinventing the same wheel of modern robotics development over and over again. \n\n**Our solution:**\n\n[**Video Link**](https://youtu.be/dDwaQbZYPLQ)\n\nWe built OS3: Both the hardware from ground up and the model to control the hardware. Our first robot, H.A.L.E. 1.0 (Human Aligned Life Enhancing), is designed to handle a wide range of everyday physical tasks, and we are presenting the prototype unit today.\n\nOur goal is towards pushing American robotics forward while ensuring the state of the art is available to all. \n\n**Hardware and Model:** \n\nIt features a bimanual embodiment with an omni-directional base, full height control to pick up objects directly from the ground while being able to reach top shelves, and a battery that can last a whole work day. Additionally, our design is primarily focused on safety and user-friendliness; a person can start and stop a task at just the touch of a screen on the back of the robot or a mobile app. \n\nThe intelligence layer is a two system architecture, with a high level planner layer and a lower level execution layer. The model has been trained on 150,000 hours of video data spanning over 2,000 real world tasks. Technical report coming soon, once evaluation runs finish. Hardware specs and engineering deep dive posted on our website.  \n\n**Preorders Live now** \n\nShipments begin Fall 2026.\n\nOur strong supply chain enables us to make our first low-cost robot starting at just under $10k for businesses to deploy (available in private beta now) and under $15k for developers to experiment with. We are already working with hospitality providers and biotech companies to deploy our robots. \n\n[**Order Link**](https://os3robotics.com/deploy/)**: 99 dollars deposit fully refundable**\n\nWe are also working on our own custom actuators right now, enabling even higher payload for our robots. Happy to discuss more if your business involves such use cases.\n\n**Talk to us:** [hi@os3robotics.com](mailto:hi@os3robotics.com) or book some time [here](https://cal.com/os3robotics/bf?overlayCalendar=true). ", "url": "https://www.ycombinator.com/launches/SeR-os3-intelligence-and-machines-for-physical-labor", "votes": 7, "created_at": "2026-08-11T19:00:00.126Z" } ] }, { "id": 30821, "name": "Efference", "slug": "efference", "former_names": [ "Remnant Robotics" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/54d1482241918ee48c1c994945fd8c443280d29b.png", "website": "https://efference.ai", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "", "team_size": 12, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1762259214, "tags": [ "Robotics", "Computer Vision" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/efference", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/efference.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "", "x_url": "https://x.com/EfferenceAI", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/54d1482241918ee48c1c994945fd8c443280d29b.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Pete Koomen", "url": "https://www.ycombinator.com/people/pete-koomen" }, "founders": [ { "user_id": 1945409, "full_name": "Gianluca Bencomo", "title": "Founder/CEO", "founder_bio": "-", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/gianluca-bencomo-326469133", "x_url": "https://x.com/gianlucabencomo/", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/abf3b37c947d65d07ff29aff6adf54e459eb04ac.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 95175, "title": "Efference - Helping robots see like humans do", "tagline": "Efference is building the most intelligent robotic camera on the market -- at half the cost. ", "body": "![uploaded image](/media/?type=post&id=95175&key=user_uploads/1945409/8214e17c-76b2-4c77-9b83-f11af13ff298)\n\nHey YC, I’m Gianluca. I’m building robotic cameras (stereo cameras) that treat vision as a software problem, not a hardware problem – just like humans do.\\\n\\\nWe are actively taking pre-orders with delivery in March: https://efference.ai/preorder\n\n[**https://youtu.be/0v0p2t3y4fI**](https://youtu.be/0v0p2t3y4fI)\n\nMany robotics founders that I talk to are frustrated with current stereo cameras. They are expensive, require calibration, and still produce unreliable depth measurements despite their costs. Vision shouldn’t be an additional bottleneck when training robotic policies is already hard enough.\n\nOur insight is that humans don’t have precise sensors: our eyes are noisy and imprecise but we run extremely sophisticated algorithms on top of them. Robotics already embraced this philosophy for arms (_cheap hardware + great algorithms_ → \\[Zhao et al., 2023\\]). We’re applying it to cameras by developing better algorithms.\n\nWhat we built:\n\n* A 3D perception model that combines stereo triangulation + learned priors about objects and environments.\n* It runs in real time (unlike current neural depth approaches).\n* We are distilling the model into our own hardware and shipping model wrappers for Realsense/ZED cameras so you can run these cameras better.\n\nCheck out the designs (going into production soon):\n\n[**https://www.youtube.com/watch?v=oOmf4k2ZwaY**](https://www.youtube.com/watch?v=oOmf4k2ZwaY)\n\n**Does it work?**\n\nSelf-Driving: [**https://www.youtube.com/watch?v=0f058JAk64A**](https://www.youtube.com/watch?v=0f058JAk64A)\n\nRobotic Manipulation (via Functional Manipulation Benchmark): [**https://www.youtube.com/watch?v=GyV12gqGOMY**](https://www.youtube.com/watch?v=GyV12gqGOMY)\n\nAnd many more demos coming to the YouTube channel: [https://www.youtube.com/@Efference](https://www.youtube.com/@Efference%5C)\n\n**Why do we need this?**\n\nConverting a vehicle to full autonomy can cost upwards of **$100,000**. The economics are terrible: the sensor stack dominates lifetime cost, keeping cost-per-mile high and slowing deployment. A stereo-vision stack like ours cuts that cost by **10–100×**. Lower integration cost → cheaper replacements → larger fleets → autonomy that scales. We know we can drive a car using a stereo camera because that is what humans use. It’s just a matter of getting the camera to work as well as the one humans have.\n\nThe same dynamic applies to humanoids, perhaps at an even greater scale. Companies like Unitree ship tens of thousands of robots every year, all with stereo cameras, and consumers often complain about quality. We’re building a camera that is both **affordable and usable**, so teams can actually build with it. As humanoid production scales to millions of units per year, we hope to be the camera that scales with it.\n\nIn urban drone environments, GPS fails. Reliable RGB-D depth enables SLAM, safe navigation, and collision avoidance; critical for companies like Skydio operating in urban valleys. Again, drones are another vertical that requires thousands of cameras per year that are cheap and effective.\\\n\\\n**Additional Background**\n\nAny two-dimensional image is consistent with an infinite number of possible 3D worlds. “Seeing” is not just recording sensory input but resolving ambiguity; selecting the _most probable_ world given the available evidence **\\[Born & Bencomo, 2021\\]**.\n\nHumans and nearly every other mammal have evolved the same solution to this problem over the past 500 million years of evolution: stereo triangulation + data-driven inference. We integrate every available depth cue – shadows, perspective, occlusions, and much more – along with what we know about objects and the environment to accurately represent 3D scenes and act accordingly.\n\nRobots do not do this, but they need to.\\\n\\\n**Team**\n\n![uploaded image](/media/?type=post&id=95175&key=user_uploads/1945409/2474fb24-fae7-4604-a549-2a875fad6452)\n\nI spent the past four years at Princeton (on-leave from PhD) studying foundational topics in machine learning and neuroscience. I funded my research by writing two successful NSF grants to build biologically-inspired vision models based on the **fruit fly connectome** where the general research direction for myself and certainly my collaborators was the question of **“how do we make this fruit fly live inside a computer simulation?”**\n\nPrior to Princeton, I spent two years at Harvard Medical School studying visual decision-making in primate models and publishing influential theoretical work on **dopamine’s role in schizophrenia and its effects on visual perception**. I did my undergraduate degree in Biochemistry and got to do some cool non-vision work at the NASA Jet Propulsion Laboratory, figuring out a **new way of converting CO2 into O2 on Mars** that recycled water and did not require heat (e.g. MOXIE).\n\nGenerally, I like to work on really hard problems.\n\n**The Ask**\n\nIf you’re a roboticist, I’d love to learn what vision requirements matter most to you. If you know teams in autonomous vehicles, drones, or humanoid robotics, and believe this product is cool, sharing / intros would mean a lot.\n\nWe are actively taking pre-orders with delivery in March: https://efference.ai/preorder\n\nThank you — Gianluca.\n\n**\\[Born & Bencomo, 2021\\] [https://karger.com/bbe/article-abstract/95/5/272/47302/Illusions-Delusions-and-Your-Backwards-Bayesian](https://karger.com/bbe/article-abstract/95/5/272/47302/Illusions-Delusions-and-Your-Backwards-Bayesian)**\n\n**\\[Zhao et. al., 2023\\] [https://arxiv.org/abs/2304.13705](https://arxiv.org/abs/2304.13705)**", "url": "https://www.ycombinator.com/launches/Ol5-efference-helping-robots-see-like-humans-do", "votes": 122, "created_at": "2025-11-04T22:53:53.320Z" } ] }, { "id": 30904, "name": "Tensr", "slug": "tensr", "former_names": [ "Core", "Tensr", "Core" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7f3743327b1fc85ded6caddbd532e0c600eb2cb0.png", "website": "https://tensr.com/", "all_locations": "Emeryville, CA, USA", "long_description": "Robotic factories that build robotics in the US. Currently operating a 12,000 sqft factory in the Bay Area and actively manufacturing customer orders for some of the largest robotics companies in the US and the International Space Station.\r\n\r\nWe’re a group of Berkeley graduate robotics researchers who previously won a full scale autonomous IndyCar competition at 160mph.", "one_liner": "Robotic factories that build robots", "team_size": 7, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1763065446, "tags": [ "Deep Learning", "Hardware", "Robotics", "Automation", "Industrial" ], "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/tensr", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/tensr.json", "year_founded": 2025, "city": "Emeryville", "country": "US", "linkedin_url": "https://www.linkedin.com/company/tensrinc/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/7f3743327b1fc85ded6caddbd532e0c600eb2cb0.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": 2763027, "full_name": "Eric Berndt", "title": "Founder/CEO", "founder_bio": "Robotic factories that build robots in the US. Prev Robotics researcher @ UC Berkeley where I raced autonomous Indy500 cars at 160mph", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/ekberndt/", "x_url": "https://x.com/ekberndt", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/8136fef854af650d0b22ac083d6585e09121a8ed.jpg" }, { "user_id": 916548, "full_name": "Adith Sundram", "title": "Founder/CTO", "founder_bio": "Founder @ Tensr. Robotics, ML and Controls @ UC Berkeley", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/adithsundram", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/dd20d8f9a84f4b33da6805740257605ff2175494.jpg" }, { "user_id": 2763062, "full_name": "C.K. Wolfe", "title": "Founder", "founder_bio": "Founder, Tensr. CS PhD (AI, Robotics), UC Berkeley. Former Technical Program Manager, UC Berkeley robotics lab under Berkeley AI Research (BAIR). Secured $17M+ in DARPA and industry sponsorship across Stanford and UC Berkeley via AI Racing Tech (2024). Team Manager during top-ranked U.S. league season. Editor-in-Chief of UC Berkeley BAIR’s official AI research publication (BAIR Blog).", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/ckwolfe/", "x_url": "https://x.com/ckwolfeofficial", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9656e4b1ee0b0c58c5a7df8df5bcb18614685e68.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 112228, "title": "Tensr - Robotic Factories that Build Robots from Humanoids to Robots for the International Space Station", "tagline": "Robotic Factories that Build Robots", "body": "Robotic factories building robots. Today we have a 12,000 sqft factory in the Bay Area manufacturing everything from full humanoids to robots for the International Space Station.\n\nOur thesis: Revitalizing domestic manufacturing means driving costs down through automation. We are building an autonomous factory that is able to autonomously process a new order end to end from prototyping to large batch production. That means supply chain management, design for manufacturing, industrial machine retooling, robotic adaptation, quality inspection, packaging, and logistics all automated. Goal: Create a factory that can autonomously go from placed customer order to completed unit scale manufacturing run in 24 hours.\n\nWe are currently manufacturing production runs from top labs, full humanoids, and even have a partnership to manufacture robotics for the International Space Station. We've also built supply chain relationships in electronics, actuators, SMT, computing, pneumatics, and raw material suppliers.\n\nA snippet of some of our machines in the factory:\n\n![uploaded image](/media/?type=post&id=112228&key=user_uploads/2763027/777065e0-e83d-4501-8799-8c490e883851)\n\n![uploaded image](/media/?type=post&id=112228&key=user_uploads/2763027/30775e59-e171-4949-b959-3dc06ffa5322)\n\n## **Manufacturing at the Core**\n\nThis isn't just a robotic manipulation company. Its a manufacturing company.\n\nInternally we have pipelines autonomous building large databases of actuators, and raw tracking and trying to predict what items will need to order now to meet our next day targets.\n\n## **The Harness**\n\nThe entire factory is a data harness we can \"backprop\" learnings through from errors in the customer designs, failed supply chain prediction, slow retoolings, to inaccurate robotic manipulation. Our core belief is that robotic machine learning should not rely on human data to scale but instead learn to improve from its own mistakes in the real world in real time. This closes the manufacturing data gap that currently limits large-scale factory automation.\n\n![uploaded image](/media/?type=post&id=112228&key=user_uploads/2763027/2baf7c74-80e3-49bb-a6bf-712ce0fb30fc)\n\n![uploaded image](/media/?type=post&id=112228&key=user_uploads/2763027/4ed0acb3-e1bc-4210-b4d0-b3f3614bc8da)\n\n## **Any Robot Anywhere**\n\nOur thesis is simple. We should be able to make an robot for any environment whether that be a humanoid for the factory floor or a robot for Low Earth Orbit. We currently have a partnership with the ISS to manufacture a robots for the space station.\n\nNASA Houston, Johnson Space Center\n\n![uploaded image](/media/?type=post&id=112228&key=user_uploads/2763027/e4558cfa-cf98-447a-acaf-7e83650e73a7)\n\n## **Team**\n\nAt heart we're a team of Roboticists. Before Tensr we were the leads for a Berkeley lab's autonomous racing team where we raced autonomous full-scale IndyCars at over 160mph as the ML, Sim, and Robotic Controls leads.\n\n![uploaded image](/media/?type=post&id=112228&key=user_uploads/2763027/c3772faa-f515-4ee0-b32e-2e586b3ae8e3)\n\nWe previously worked in industrial automation, aerospace manufacturing, medical device manufacturing, Berkeley AI Research (BAIR), physics simulation, and secured $17M+ in DARPA / industry sponsorship for UC Berkeley / Stanford research.\n\nOur founding engineers range from Berkeley Robotics PhD, ex-NASA, to 10+ years of manufacturing experience.\n\n## A Better World\n\nOn a personal note, not only do I believe we have the opportunity to build a great business but also to make a positive impact on the world. Automate away environmentally harmful materials, eliminate waste 0.1% at a time, and drive steady-state COGS toward only the fundamental inputs (materials and electricity), unlocking strong margins while collapsing the price of everyday goods / cost of living.\n\nLets build a better world :)\n\nA full view of our vision here:[ tensr.com/whitepaper](https://www.tensr.com/whitepaper)", "url": "https://www.ycombinator.com/launches/TC8-tensr-robotic-factories-that-build-robots-from-humanoids-to-robots-for-the-international-space-station", "votes": 6, "created_at": "2026-08-25T21:00:00.441Z" }, { "id": 95506, "title": "Tensr: Building Autonomous Robotic Factories", "tagline": "Building fully autonomous robotic factories that make scaling hardware as effortless as scaling on AWS", "body": "We're building fully autonomous robotics factories at Tensr to create the AWS of manufacturing. Our factories will receive on-demand orders from customers and spin up robots to operate industrial machinery, package, and ship the finished product all in 24 hours.\n\n![uploaded image](/media/?type=post&id=95506&key=user_uploads/2763027/704a7eb3-1ffc-4fc3-b806-32f3fd256418)\n\n[**https://youtu.be/HLijIfoDfpA**](https://youtu.be/HLijIfoDfpA)\n\n**Problem**\n\nMoving fast in manufacturing today doesn't exist. Iterating designs for manufacturing takes months of back and forth getting samples from China and pre-ordering manufacturing capacity several months before the holiday rush, only then to wait several weeks for shipping praying there isn't a strike at the docks. At the same time we see the complete collapse of America industrial capacity as American workers and experience leave the field and contracts are sent overseas.\n\n**Solution**\n\nWith the robotics revolution, for the first time it is possible to fully reimagine the factory floor - moving from rigid lines to modular stations, even in high mix settings. However, we believe that automating manufacturing is more than just deploying a foundation model or a humanoid into an existing factory.\n\nFactories need to be designed from the ground up _around_ robots, not the other way around.\n\nOver the past few weeks we turned our living room into an autonomous factory floor, with stations for CNC, moving stock, and a focus on assembly. After demo day, we'll expand to a full manufacturing facility, and start supporting batch orders of all sizes from other companies throughout the country. Currently we also are in talks to provide our own assembly models to other distributors.\n\n![uploaded image](/media/?type=post&id=95506&key=user_uploads/2763027/706f70f4-47a7-4466-8281-5cf6d081da43)\n\n![uploaded image](/media/?type=post&id=95506&key=user_uploads/2763027/e6420b31-3e74-49d3-b751-c901c5379665)\n\n**Team**\n\nWe're a battle-hardened team of UC Berkeley graduate robotics researchers (from Berkeley AI Research (BAIR)) who met in a lab, previously worked on and managed multiple DARPA contracts and led an autonomous IndyCar team where we raced full scale autonomous Indycars at 160mph (250kmh) as the Machine Learning, Simulation/Team Manager, and Robotics Control leads respectively.\n\n\\- [Eric Berndt](https://x.com/ekberndt) - MS/BS EE/CS, UC Berkeley, CoFounder + CEO\n\n\\- [Adith Sundram](https://www.linkedin.com/in/adithsundram/) - MS/BS ME, UC Berkeley, CoFounder + CTO\n\n\\- [C.K. Wolfe](https://x.com/ckwolfeofficial) - Current PhD AI/Robotics, UC Berkeley, CoFounder\n\nIn addition, our team brings direct operational experience from Rockwell Automation (industrial automation), aerospace manufacturing, and FDA-regulated medical-device production\n\n![uploaded image](/media/?type=post&id=95506&key=user_uploads/2763027/f907544d-cb70-45d2-b043-708a6739e40c)\n\n**Our Ask**\n\nWe're offering early manufacturing / prototyping pilots for hardware companies of all sizes as the new year starts and we open our first facility. If you or anyone you know fits in this bucket, reach out to [**founders@tensr.com**](mailto:founders@tensr.com)!\n\n![uploaded image](/media/?type=post&id=95506&key=user_uploads/2763062/4e53c620-4423-4e57-b0cf-a25b750d0539)\n\n", "url": "https://www.ycombinator.com/launches/OqQ-tensr-building-autonomous-robotic-factories", "votes": 365, "created_at": "2025-11-14T01:26:45.320Z" } ] }, { "id": 30928, "name": "Darwin", "slug": "darwin", "former_names": [ "Thesis Labs", "Thesis", "Darwin", "Thesis" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/834b16b30c5de79bf9dbcd0a4819289bfa937936.png", "website": "https://darwinrobotics.ai", "all_locations": "San Francisco, CA, USA", "long_description": "Darwin Robotics creates general-purpose robots to build and maintain the machines civilization runs on.\r\n\r\nWe're starting with AI infrastructure, where skilled technicians perform a long tail of physical work across assembly, installation, commissioning, and maintenance. Our robots learn new tasks from demonstrations rather than being explicitly programmed for each workflow.\r\n\r\nFirst deployments are planned for early 2027.", "one_liner": "Robots to build civilization", "team_size": 4, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1762476616, "tags": [ "Hard Tech", "Machine Learning", "Robotics", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Fall 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": [ { "question": "How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)", "answer": "We are brothers and have been building things together our whole lives. We grew up in the Caribbean with our mom, obsessed with math and computers. Sergio taught himself calculus from MIT OpenCourseWare at 12, published mathematics as a teenager, and later worked on AI and robotics at Stanford, Nvidia, and Google X. Luigi studied math and CS at Columbia, then co-founded a payments company where he scaled engineering from zero to billions in transaction volume.\r\n\r\nAs kids, we built worlds in Minecraft. Now, we’re building robots." }, { "question": "What is your long-term vision? If you truly succeed, what will be different about the world?", "answer": "We sit at the dawn of a new era in civilization. AI is beginning to solve problems across science and mathematics that were previously impenetrable. Yet this intelligence is still largely confined to the screen.\r\n\r\nWe believe the next frontier is physical. Our goal is embodied artificial general intelligence.\r\n\r\nWhen we succeed, billions of intelligent robots will work alongside humans, performing useful work and expanding what humanity is capable of." } ], "url": "https://www.ycombinator.com/companies/darwin", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/darwin.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/darwin-robotics-inc", "x_url": "https://x.com/darwin_robotics", "fb_url": null, "cb_url": null, "github_url": "https://github.com/Darwin-Robotics-Inc", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/834b16b30c5de79bf9dbcd0a4819289bfa937936.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/415cd09f20efd72acec243c4e7b73ccb3b01cd35.png" ], "primary_partner": { "name": "Tom Blomfield", "url": "https://www.ycombinator.com/people/tom-blomfield" }, "founders": [ { "user_id": 455353, "full_name": "Sergio Charles", "title": "Founder/CEO", "founder_bio": "Robots to build civilization. Prev: AI R&D at Google X, NVIDIA, and Stanford AI Lab, working with Chelsea Finn on autonomous RL for robotics and Andrew Ng on computer vision. Stanford B.S. Math & CS, M.S. Stats.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/sergio-charles-5a8052134/", "x_url": "https://x.com/eigentopology", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ba455346463b0d6acae18a8bcd3d2bba294bfdb5.jpg" }, { "user_id": 1021038, "full_name": "Luigi Charles", "title": "Founder", "founder_bio": "Building Westworld. Previously founded a fintech payments startup, scaling volume from zero to billions. Columbia CS & Math.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/luigicharles", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ca6e645d2ffabef7f901b4d6e1aec82d02f81657.jpg" } ], "jobs": [ { "id": 96229, "title": "Member of Technical Staff, AI & Robotics", "url": "https://www.ycombinator.com/companies/darwin/jobs/R8xvEoc-member-of-technical-staff-ai-robotics", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$120K - $170K", "equity_range": "0.75% - 2.00%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [ "C++", "Git", "Python", "Torch/PyTorch", "Machine Learning", "Deep Learning", "Reinforcement learning (RL)", "CUDA", "Microcontrollers", "Diffusion Models" ] } ], "news": [], "launches": [ { "id": 95309, "title": "δ Thesis: Building the frontier of AI discovery", "tagline": "Making it possible for researchers anywhere to discover the next Transformer or invent the next AlphaFold.", "body": "Thesis is an applied AI lab accelerating the frontier of AI discovery.\n\nWe're making it possible for researchers anywhere to discover the next Transformer or invent the next AlphaFold.\n\n**Mission**\n\nOur mission is to make state-of-the-art AI discovery 10x faster and 10x cheaper. The big labs are racing to get there, but their need to productize and turn a profit has already weighed them down. Thesis embraces rapid experimentation and novel fundamental research. Our singular focus, outcome-driven mindset, and early results give us confidence that we can get there first.\n\n**Results**\n\nThesis is state-of-the-art on OpenAI’s Machine Learning Engineering benchmark ([MLE-Bench](https://github.com/openai/mle-bench?tab=readme-ov-file#mle-bench)).\n\nMLE-Bench tests how well AI systems can train ML models autonomously, a first step toward self-improving systems. We achieved this result in the record time of 1 month and with only $10k in compute. Agents will get you far, but not far enough. Our methods mix old school with new, and have already outperformed teams of researchers at Microsoft, Google, Meta, and Baidu.\n\n![uploaded image](/media/?type=post&id=95309&key=user_uploads/455353/310c8083-1512-40c3-8e31-c1cc941f3634)\n\n**Team**\n\nLuigi and Sergio are brothers. Back in 2021, Sergio [wrote about a future where AI could create its own algorithm](https://cs229.stanford.edu/proj2021spr/report2/82285254.pdf)s. With today's foundation models, that future is suddenly within reach.\n\nSergio worked on AI R&D at Google X, Nvidia, and Stanford’s AI Lab (SAIL). He has published work at NeurIPS and ICML, and has worked with Chelsea Finn and Andrew Ng.\n\nLuigi built Sphere, a fintech company that processes billions of dollars every year in global cross-border payments. Sphere was recently valued at $250 M+ in its Series A round.\n\n**10 Year Vision**\n\nThe holy grail of AI is building self-improving systems that, guided by human creativity, enable breakthroughs and new paradigms achieving state-of-the-art results under resource constraints.\n\nIn the limit, our engine will expand beyond ML to every domain of science, from computational biology, to theoretical mathematics and physics. Thesis will autonomously discover new knowledge and become the driving force behind humanity’s scientific progress.\n\n**Our Ask**\n\nWe collaborate with leading institutions, startups, and independent researchers around the world. If you’re interested in what we’re building, please get in touch: \\[[ask@thesislabs.ai](mailto:ask@thesislabs.ai)\\](mailto:[ask@thesislabs.ai](mailto:ask@thesislabs.ai))", "url": "https://www.ycombinator.com/launches/OnF-thesis-building-the-frontier-of-ai-discovery", "votes": 232, "created_at": "2025-11-11T16:40:14.609Z" } ] }, { "id": 30930, "name": "Cortex AI", "slug": "cortex-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/1c9246b8eba5ba12a7373a930ea46cc687dddb98.png", "website": "https://cortexrobot.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Cortex AI builds the world’s most diverse and large-scale real-world workplace robot & egocentric dataset — where the physical world becomes the next training and evaluation set for embodied AI.\r\n\r\nWe power frontier labs developing robotics foundation models and general-purpose robots by providing the data they need:\r\n1️⃣ Egocentric Data — real-workplace human video with hand/body pose, depth, and subtask labels.\r\n2️⃣ Robot Data — trajectories collected from manipulators and humanoids in real industry settings.\r\n3️⃣ Human-in-the-Loop Rollouts & Evals — real-world deployments with remote operators who recover robots when they fail, capturing data that feeds back into training and continuously improves models.\r\n\r\nAdditionally, through the Cortex Marketplace, workplaces get paid to host data-collection and evaluation sessions, while labs access the in-the-wild data that truly matters. This draws on Lucas’s previous experience as co-founder of Carousell, a C2C marketplace that scaled to a $1B+ valuation.", "one_liner": "Large-scale real-world robot & human data for embodied AI", "team_size": 3, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1760045430, "tags": [ "Reinforcement Learning", "Robotics", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/cortex-ai", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/cortex-ai.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/cortexairobot", "x_url": "https://x.com/cortexairobot", "fb_url": null, "cb_url": null, "github_url": "https://github.com/cortexairobot", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/1c9246b8eba5ba12a7373a930ea46cc687dddb98.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Garry Tan", "url": "https://www.ycombinator.com/people/garry-tan" }, "founders": [ { "user_id": 53734, "full_name": "Lucas Ngoo", "title": "Founder/CEO", "founder_bio": "Founder and CEO of Cortex AI. We're building the world's most diverse real-world, real-workplace, and industry-scale egocentric + robot dataset. Prior to Cortex AI, Lucas was the co-founder and CTO of Carousell (valued at $1B+).", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/lucasngoo", "x_url": "https://x.com/lucasngoo", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1b1f0f258b2fb62b1c7c32ca14e38ec0350b7ff4.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 95318, "title": "🦾 Cortex AI — Large-Scale Real-World Data for General-Purpose Robotics", "tagline": "Turning the real physical world into the next dataset for general-purpose robotics.", "body": "We’re building the world’s most diverse _real-world, real-workplace_ egocentric + robot dataset — where the **real physical world itself** becomes the next training and eval set for embodied AI.\\\n\\\n🌍 **The Problem**\\\nMost robotics datasets today are captured in lab environments or simulated settings — far removed from the **real physical world** where robots actually need to operate.\\\n\\\nThese datasets helped build the foundation models we have today, but the **next phase** of embodied AI needs to learn directly from the real world — from the noise, diversity, and complexity of real workplaces.\\\n\\\n🤖 **The Solution**\\\n\\\nFrontier labs use **Cortex AI** through 3 stages:\\\n1️⃣ **Get real-world egocentric data** → for world model + robotics foundation model pretraining\\\n2️⃣ **Collect real robot data** in real workplaces\\\n3️⃣ **Roll out policies** across real-world environments → the best evals happen in the real world, with our operators providing human-in-the-loop support to capture recovery data\\\n\\\nhttps://youtu.be/HD-weWSzy4Y\n\n\\\n🏭 **Cortex Marketplace**\\\nWe’re also launching the **Cortex Marketplace**, where _real workplaces get paid_ to host egocentric-capture and robot-teleop sessions — fueling a scalable pipeline of high-quality, real-world robotics data.\\\n\\\n👥 **The Team**\\\nPrior to Cortex AI, **Lucas Ngoo** co-founded and served as CTO of Carousell, scaling it from an idea into a $1B+ valuation marketplace used across Asia.\\\n\\\n🙏 **Our Ask**\\\nIf you work with or know teams at **frontier robotics labs** (humanoid companies, robotics foundation model research groups and teams), please make an intro ([lucas@cortexrobot.ai](mailto:lucas@cortexrobot.ai)) — we’d love to collaborate, thank you!\n\n🔗 [cortexrobot.ai](https://cortexrobot.ai)\\\n📩 [lucas@cortexrobot.ai](mailto:lucas@cortexrobot.ai)\n\n![uploaded image](/media/?type=post&id=95318&key=user_uploads/53734/069d07db-9cdf-4720-96b4-a7077818cb06)\n\n", "url": "https://www.ycombinator.com/launches/OnO-cortex-ai-large-scale-real-world-data-for-general-purpose-robotics", "votes": 20, "created_at": "2025-11-08T15:29:09.944Z" } ] }, { "id": 30934, "name": "Tornyol", "slug": "tornyol", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/32e3f0b4a6932eaa071b0b63031b269de4048c47.png", "website": "https://tornyol.com/", "all_locations": "Paris, Île-de-France, France", "long_description": "Tornyol builds micro-drones that kill mosquitoes. We use smartphone microphones, car park assist sensors and some clever DSP and control to transform 40-gram toy drones into mosquito killers. Because these drones are so cheap and fast, we will lower the cost of mosquito control by 100x which will enable the eradication of mosquitoes from cities, saving more than a million people each year from Malaria, West Nile, Dengue, etc. ", "one_liner": "We build micro-drones that kill mosquitoes. ", "team_size": 7, "industry": "Consumer", "subindustry": "Consumer -> Consumer Electronics", "launched_at": 1761986194, "tags": [ "Hardware", "Robotics", "Drones" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2025", "status": "Active", "industries": [ "Consumer", "Consumer Electronics" ], "regions": [ "France", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/tornyol", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/tornyol.json", "year_founded": null, "city": "Paris", "country": "FR", "linkedin_url": "https://www.linkedin.com/company/tornyol/", "x_url": "https://x.com/tornyolsystems", "fb_url": null, "cb_url": null, "github_url": "github.com/mosquitorgnole", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/32e3f0b4a6932eaa071b0b63031b269de4048c47.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": 1250342, "full_name": "Alex Toussaint", "title": "Founder/CEO", "founder_bio": "Built one of the first in-air phased array sonar when I was 18. Worked on aerial guidance and navigation. Now building micro-drones that kill mosquitoes.\n\nhttps://alextoussaint.com\n\n", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/alex-toussaint-51a439189/", "x_url": "https://x.com/alextoussss", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3e686ab9fccb273e6202af5ff0020bbd13e1e13f.jpg" }, { "user_id": 2515354, "full_name": "Clovis Piedallu", "title": "Founder/COO", "founder_bio": "French engineer, working on autonomous mosquito-killing micro-drones ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/clovispiedallu/", "x_url": "https://x.com/ClovisPiedallu", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/dc5e38c6e3ab9641c13073fea9dee85000534f00.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 95287, "title": "Tornyol: micro-drones that kill mosquitoes", "tagline": "Enjoy mosquito-free evenings thanks to Tornyol", "body": "TLDR We’re eradicating mosquitoes (700k people killed each year) with micro-drones.\n\nHey YC!\n\n[Clovis Piedallu](https://www.linkedin.com/in/clovispiedallu/) and [Alex Toussaint](https://www.linkedin.com/in/alex-toussaint-51a439189/) are building [Tornyol](https://tornyol.com/), **a micro-drone that kills mosquitoes**. We use smartphone microphones, car park assist sensors and some clever DSP and control to transform 40-gram toy drones into mosquito killers. Because these drones are so cheap and fast, we could lower the cost of mosquito control by 100x to enable the eradication of malaria.\n\nOur upcoming product is a micro-drone + base station that patrols your garden 24/7 and eliminates any mosquito in the zone. After a few days of action, you’ll notice that you can enjoy mosquito-free evenings and dinners. Enjoy a mosquito-free life for just $50/month (if you save your spot **right now for just $100**)!\n\nhttps://www.youtube.com/watch?v=dDa9pFzeJvE\n\n![uploaded image](/media/?type=post&id=95287&key=user_uploads/1250342/2697e87e-51cb-405e-bf8b-e4446880f4cc)\n\n# How it started\n\nAlex has been passionate about ultrasonic sonars for a while, building [one of the first air-gapped ultrasonic phased array sonars.](https://www.alextoussaint.com/2021-04-28_How-I-built-an-ultrasonic-3d-scanner.html) Alex then worked at MBDA Systems, supplier of UK-FR missiles where he did outstanding work in navigation and control. That’s when long-time friend [@Clovis Piedallu](https://bookface.ycombinator.com/user/2515354) and him had the (at first) stupid idea of building mosquito-killing drones. After proving from napkin math that this could lead to mosquito eradication, we got a $28k grant from [Scott Alexander, Vitalik Buterin](https://manifund.org/projects/build-anti-mosqu) and [some big twitter buzz.](https://x.com/alextoussss/status/1778460625196261863) Since, we’ve made enormous strides in the field including the first detection and tracking of a mosquito with an ultrasonic phased array, plus some fancy algorithms which are detailed more [here](https://hackaday.com/2025/03/25/supercon-2024-killing-mosquitoes-with-freaking-drones-and-sonar). We’ve made a lot of progress since in the control department, but can’t share much more without nuking an ongoing patent. The TLDR of that is **we believe we can eradicate mosquitoes from a square kilometer of land with just 10 40-grams drones, slashing the cost of mosquito control by 100x**\n\n# The tech, with a few more details\n\nWe send an ultrasonic pulse using a regular ultrasonic transmitter (the one you can find in the HC-SR04 arduino modules, or on cark park assist sensors) then listen for the echoes using an array of smartphone microphones. This phased array of smartphone microphone allows us to get a directional recording of all echoes in the scene. To classify the echoes, we plot a spectrogram of the echoes as a function of time. Whenever a mosquito beats its wings, the movement produces irregular doppler effect. By measuring that alternating doppler effect, we get a 2D image that’s unique to each mosquito. We then detect the species and sex of the target we have in front of us. Here’s what these signatures look like.\n\n**Wasp (phase, STFT, FFT)**\n\n![uploaded image](/media/?type=post&id=95287&key=user_uploads/1250342/e34717d5-91b3-435f-b7b3-33eacfa00d77)\n\n**Mosquito (phase, STFT, FFT)**\n\n![uploaded image](/media/?type=post&id=95287&key=user_uploads/1250342/21bf0588-a122-48c8-9a62-60426d8e7b94)\n\n![uploaded image](/media/?type=post&id=95287&key=user_uploads/1250342/8bb71855-e1f9-4ea0-922f-06da6690c1c5)\n\nOur phased array sonar (Xilinx XC7A100T and 380 PDM Microphones). We’ve miniaturized it since.\n\nThen, by using some very clever control algorithms, we ram our autonomous tinywhoop into the mosquitoes and away from the walls.\n\n# Our current development status\n\nMost systems are working in isolation, and we’re doing a push to have them all working together. Our miniaturized DSP+Controls processor is currently in the PCB factory, and all algorithms have been tested either on separate benches or in simulation. We’re currently killing mosquitoes in simulation, and are working hard to kill them in the real world.\n\n# Asks\n\nMosquitoes are a terrible problem worldwide **700k people killed each year, 700M catching a mosquito-borne disease and 4 billion people at risk of Dengue**.\n\nWe’re looking for early adopters for who mosquitoes are a big nuisance to proof-test our first drones when they work before we deploy them to areas where failure’s not an option. If that sounds like you, please pre-order and enjoy all the perks (limited edition color, 30% discount) that come from our small $100 refundable reservation.\n\n# CTA\n\n[tornyol.com](http://tornyol.com): $100 refundable deposit to get exclusive, early and discounted acess to our solution.\n\n[founders@tornyol.com](mailto:founders@tornyol.com):\\_for any contacts to big businesses, government entities and NGOs who could be clients.\n\nLooking forward to your questions!\n\n[Clovis Piedallu](https://www.linkedin.com/in/clovispiedallu/) and [Alex Toussaint](https://www.linkedin.com/in/alex-toussaint-51a439189/) for a mosquito-free world.", "url": "https://www.ycombinator.com/launches/Omt-tornyol-micro-drones-that-kill-mosquitoes", "votes": 70, "created_at": "2025-11-07T17:48:40.465Z" } ] }, { "id": 30947, "name": "Philon", "slug": "philon", "former_names": [ "Philon", "Spatial AI" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/c55c56d8a17e50d5a5504f506e783c2b8c9f8a61.png", "website": "https://philon.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Building open-source general-purpose robots capable of performing unsafe, repetitive or boring tasks.", "one_liner": "General Purpose Robots", "team_size": null, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1761067885, "tags": [ "Robotics", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/philon", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/philon.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/94854659", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/c55c56d8a17e50d5a5504f506e783c2b8c9f8a61.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": 2367289, "full_name": "Alexandros Petkos", "title": "Founder", "founder_bio": "Building General Purpose Robots", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/alexandros-petkos/", "x_url": "https://x.com/alex_petkos", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2334445a73b87d24bc5aac380f045775e996fc16.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 95567, "title": "Spatial AI: Large datasets for robot foundation models", "tagline": "Collecting large-scale real-world data to teach robots how to navigate the world and complete tasks.", "body": "![uploaded image](/media/?type=post&id=95567&key=user_uploads/2367289/61a41a40-748f-4ef4-8196-4b5ca76ef86d)\n\n**Spatial AI** ([**https://spatial-ai.com/**](https://spatial-ai.com/)) is building large datasets for robot foundation models.\n\n**Open Source**: [**https://huggingface.co/datasets/spatial-ai/sea-small**](https://huggingface.co/datasets/spatial-ai/sea-small)\n\n![uploaded image](/media/?type=post&id=95567&key=user_uploads/2367289/5313b99e-aa0b-46d4-b4d4-cd9983bedecd)\n\n**The Problem:**\n\nThe biggest obstacle to bringing robots into everyday life is the software. We need far more capable models to control general-purpose robots effectively and enable them to carry out tasks in the physical world.\n\n![uploaded image](/media/?type=post&id=95567&key=user_uploads/2367289/7a226006-47e9-4c89-bcd2-b09ce89cb241)\n\n**The Solution:**\n\nTo train capable models, we need vast amounts of high-quality data. Our first dataset SEA (Spatial Everyday Activities) is the largest well-curated egocentric dataset of people performing tasks.\n\n**Story:**\n\nI’ve been building humanoids and dynamic robots for nearly a decade, starting in my garage when I was a kid.\n\nhttps://alexandros-petkos.com/humanoid-work\n\nhttps://alexandros-petkos.com/quadruped-work\n\nAlex", "url": "https://www.ycombinator.com/launches/OrP-spatial-ai-large-datasets-for-robot-foundation-models", "votes": 23, "created_at": "2025-11-17T19:55:18.588Z" } ] }, { "id": 30987, "name": "Lightberry", "slug": "lightberry", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e293e7e459ca366271fd5317cd8af37ed2cd6625.png", "website": "https://lightberry.com", "all_locations": "San Francisco, CA, USA", "long_description": "We build brains for robots.\r\n\r\nWe work with manufacturers like Unitree to make robots listen, speak, and act. You can program your robot out of the box by literally talking to it, no coding involved.\r\n\r\nRobots running Lightberry are emotionally intelligent, always on, and fully autonomous. Just like in Star Wars!", "one_liner": "Robots with soul", "team_size": 3, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1761343459, "tags": [ "Hard Tech", "Hardware", "Robotics", "Design", "Conversational AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Fall 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/lightberry", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/lightberry.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/lightberryinc", "x_url": "https://x.com/lightberry", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/e293e7e459ca366271fd5317cd8af37ed2cd6625.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Garry Tan", "url": "https://www.ycombinator.com/people/garry-tan" }, "founders": [ { "user_id": 255747, "full_name": "Ali Attar", "title": "Founder/CEO", "founder_bio": "Founder @Lightberry (F25) 💛", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/attarali", "x_url": "https://twitter.com/aliatttar", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/fc8e4cc390f95fd1cb22381c69d3e994240bed1e.jpg" }, { "user_id": 187048, "full_name": "Stephan Koenigstorfer", "title": "Founder/CTO", "founder_bio": "Founder @ Lightberry 💛", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/stephankoe", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5a8868edb0a4206fafe6b4d0157e327fe6e9b1dd.jpg" }, { "user_id": 2052513, "full_name": "Stephan Wolski", "title": "Founder/Head of Robotics", "founder_bio": "Self driving cars, trucks, and humanoids.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/stephan-wolski/", "x_url": "https://x.com/StephWolski", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/aaf21d7f88280fe68894078fb1ca2cae4d0b2bd0.jpg" } ], "jobs": [ { "id": 90164, "title": "Senior/Staff Software Engineer, Voice AI", "url": "https://www.ycombinator.com/companies/lightberry/jobs/J1rOMLl-senior-staff-software-engineer-voice-ai", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$130K - $280K", "equity_range": "0.25% - 1.00%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] }, { "id": 90199, "title": "Robotics Engineer", "url": "https://www.ycombinator.com/companies/lightberry/jobs/zMM4MQ4-robotics-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$150K - $225K", "equity_range": "0.25% - 1.00%", "experience": "3+ years", "visa": "Will sponsor", "skills": [] } ], "news": [], "launches": [ { "id": 95161, "title": "Lightberry - Robots with Soul", "tagline": "We’re building brains for robots - so they can talk, act, listen and feel. ", "body": "![uploaded image](/media/?type=post&id=95161&key=user_uploads/187048/b726300c-0e1d-4190-87ac-44a8bc4a2ed3)\n\nGreetings dear humans – we’re building **Lightberry: the social brain for robots.**\n\nWe work with manufacturers like Unitree and Booster to make robots listen, speak, and act. You can program your robot out of the box by literally talking to it, no coding involved.\n\nRobots running Lightberry are:\n\n* emotionally intelligent\n* always on\n* fully autonomous\n\nJust like in Star Wars!\n\nhttps://www.youtube.com/watch?v=aJZ3pcFyfg4\n\n### **Why?**\n\nWe’ve seen robots on stage: folding laundry, serving popcorn, doing backflips… But before robots get deployed in homes, offices, and shops, they need to become good at **interacting with people**.\n\nSlapping ChatGPT realtime on it is not enough, every manufacturer tried that already. It responds to every little noise, lacks personality, and needs to be teleoperated.\n\nLightberry makes robots **contextually aware**, **customizable**, and **autonomous**.\n\n_We’ll let our robot Mini-Pi say it in its words:_\n\n[**https://youtu.be/e1gD57WY74s**](https://youtu.be/e1gD57WY74s**)\n\n### **Is it just a voice pipeline on top of a robot?**\n\nNo. Lightberry robots have agency. They **decide** when they want to speak or move. Our robots can **see the world** around them, **navigate it** without hitting obstacles, and have an internal **monologue of thoughts**.\n\n_Here’s our robot Koko’s hot-take:_\n\n[**https://youtu.be/Y7SN58Cdvs4**](https://youtu.be/Y7SN58Cdvs4**)\n\n### **What can your robots do?**\n\nRobots running Lightberry are being deployed to interact with people: homes, offices, shops, conferences, etc. Our software works on many different robots: Unitree G1, Fourier GR-2/N1, Booster T1/K1, High Torque Mini-Pi/Mini-Pi+ …\n\n_Here are a few robots we’ve deployed Lightberry on – meet Koko, Synthia, Alfred, Blake, Minnie, and Bradford:_\n\n![uploaded image](/media/?type=post&id=95161&key=user_uploads/187048/60dd09f1-41ed-488c-bb73-546727f5d606)\n\n### **Ask**\n\n**We want to deploy as many robots in the real world as possible.** If you want to:\n\n* Hire a robot for a people-facing gig (conference, sales, marketing, receptionist, concierge…)\n* Integrate Lightberry into your robot (if you’re building hardware!)\n\n**Please email us at [founders@lightberry.com](mailto:founders@lightberry.com).**\n\nThanks,\n\n[**@Ali Attar**](https://bookface.ycombinator.com/user/255747) & [**@Stephan Koenigstorfer**](https://bookface.ycombinator.com/user/187048)\n\n![uploaded image](/media/?type=post&id=95161&key=user_uploads/187048/c6837400-65bf-4cb7-a943-52615e648ae8)\n\n_Yes, it walks around me!_", "url": "https://www.ycombinator.com/launches/Okr-lightberry-robots-with-soul", "votes": 178, "created_at": "2025-11-04T17:34:27.623Z" } ] }, { "id": 30991, "name": "Forge Robotics", "slug": "forge-robotics", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fc718543c8da7c7d1c6d5308ecd4cde3ca18269c.png", "website": "https://forge-robotics.com", "all_locations": "San Francisco, CA, USA", "long_description": "Forge Robotics is changing the way that metal parts are fabricated. We are enabling a future where our intelligent robotic system completes all steps needed to take raw metal stock and transform it into fully welded parts. \r\n\r\nBeginning with welding, we are building a robot-mounted vision system and AI feature detection that creates a real-time 3D map and tells the arm exactly where to go at every instant.", "one_liner": "A robotics intelligence system for metal fabrication", "team_size": 1, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1762659715, "tags": [ "Robotic Process Automation", "Robotics", "Industrial" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2025", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/forge-robotics", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2025/forge-robotics.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/forge-robotics", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/fc718543c8da7c7d1c6d5308ecd4cde3ca18269c.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": 2972389, "full_name": "Robert Cormican", "title": "Founder/CTO", "founder_bio": "CEO and Founder of Forge Robotics. With a deep background in Mechatronics, Image Quality and Computer Vision and Silicon Development/Semiconductor Manufacturing", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/robert-cormican-a4405990/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/60f5c6a0a8856605cc957c1a4ba6d20ea552717d.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 95362, "title": "Forge Robotics - The Future of Manufacturing", "tagline": "Forge Robotics gives manufacturing companies the ability to make parts fully autonomously", "body": "Hey everyone, we’re [Eoin ](https://www.linkedin.com/in/eoincobbe)and [Robert](https://www.linkedin.com/in/robert-cormican-a4405990), co-founders of Forge Robotics.\n\nWe are completely changing the way that metal fabrication is done. Companies can no longer afford to deal with massive labour shortages and rising costs of outdated processes. Forge is on the journey to enable companies to take in raw stock metal and output completed metal parts without human intervention.\n\n# TL;DR\n\nForge is building a system that turns dumb, human-programmed industrial welding robot arms into autonomous members of the workforce.\n\nFrom here, we will deliver autonomous factory units that handle all processes in metal fabrication, from handling cut parts and positioning them for assembly, to welding and cleaning up final assemblies.\n\nTo get involved, contact us @ [eoin@forge-robotics.com](https://eoin@forge-robotics.com)\n\nhttps://www.youtube.com/watch?v=5vxp75bUlIY&t=38s\n\n# 🏭 The Problem\n\nManufacturing is an industry that has been all but left behind for the past 20 years compared to the advances in software development, self-driving vehicles, and all other fields that AI has revolutionised.\n\n**Labour shortages**\n\nManufacturing of defence equipment, construction machines, and automotive make up the backbone of much of the American economy. In the U.S, there are 400,000 unfilled welding positions, and that is expected to rise to 600,000 by 2030.\n\n**Push to reshore**\n\nOEMs and Tier 1 manufacturers are pushing to reshore their manufacturing, but traditional methods of operation mean that they are failing to operate profitably when competing with manufacturing in offshore economies.\n\n**Failure of current automation**\n\nCurrent industrial robots can only achieve a very narrow set of well-defined manufacturing tasks because of the way robots are programmed. Traditionally programmed welding robots end up with around 10% of parts needing rework due to the delta in geometry from part to part.\n\n![uploaded image](/media/?type=post&id=95362&key=user_uploads/2795202/eb13105f-47fa-4312-b8c7-185ecac7e04a)\n\n# 🦾 Our solution\n\nForge provides a vision system and robotic intelligence that creates a sub-mm map, identifies all features and weld seams, and autonomously controls the welding robot arms.\n\nMetal fabrication companies will now:\n\n* No longer have to **manually program** robotic arms\n* Achieve **99% first pass line yield**, up from the current 90%\n* Use robotic welding arms in many previously infeasible situations\n\n![uploaded image](/media/?type=post&id=95362&key=user_uploads/2795202/82ef4c04-835c-4a20-a6b6-85698177d54b)\n\n# ♾️ Fully autonomous production\n\nUsing the manufacturing intelligence system that we are working on for factories today, we will be delivering fully autonomous modular factory units that handle all of the metal manufacturing processes to take raw steel parts to finished welded assemblies. Saving companies **Tens of millions** per year by changing the way they manufacture.\n\n# 🤝 Ask\n\nCan you introduce us to companies in the metal manufacturing industry? We are currently taking on as many pilot customers as we can!\n\nIf this is a future that excites you and you want to find out how you can be part of it 👉Contact Eoin @ [eoin@forge-robotics.com](https://eoin@forge-robotics.com)\n\nFind out more @ [www.forge-robotics.com](https://forge-robotics.com/)", "url": "https://www.ycombinator.com/launches/Oo6-forge-robotics-the-future-of-manufacturing", "votes": 285, "created_at": "2025-11-10T15:00:31.012Z" } ] }, { "id": 31043, "name": "Advanced Metal Research", "slug": "advanced-metal-research", "former_names": [ "Gradient Robotics" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/d5a7969eb6dca800d7d66a510da584091e078f33.png", "website": "https://advancedmetalresearch.com/", "all_locations": "Los Angeles, CA, USA", "long_description": "America does not just need more welders. It needs welding knowledge that can scale.\r\n\r\nThe American Welding Society projects 320,500 new welding professionals will be needed by 2029, with about 80,000 jobs to be filled annually from 2025 to 2029. More than 157,000 current welding professionals are approaching retirement. Welders are only a small share of the skilled-trades workforce, but welding accounts for an outsized share of projected capability demand. \r\n\r\nThe market calls it a labor shortage. AMR sees a learning bottleneck.\r\n\r\nWe are building American-made robotic welding cells that combine computer vision to provide real-time seam tracking and post-weld inspection to turn welding from a scarce manual process into a closed-loop manufacturing system that learns from every weld as it happens.", "one_liner": "Machine intelligence for American Welding", "team_size": 3, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1778801477, "tags": [ "Hardware", "Robotics", "Manufacturing" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 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/advanced-metal-research", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2026/advanced-metal-research.json", "year_founded": 2025, "city": "Los Angeles", "country": "US", "linkedin_url": "https://www.linkedin.com/company/advanced-metal-research/", "x_url": "https://x.com/amrwelding", "fb_url": null, "cb_url": null, "github_url": "https://github.com/gradient-industrial-robotics", "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/d5a7969eb6dca800d7d66a510da584091e078f33.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Garry Tan", "url": "https://www.ycombinator.com/people/garry-tan" }, "founders": [ { "user_id": 2387747, "full_name": "Angus Muffatti", "title": "Founder/CEO", "founder_bio": "+Last startup hit first $1m in 18 months &\n$10m val at last investment from largest\naussie real estate group\n+ 3 published ML & AI optimisation papers\n+ Designed & built liquid bi-propellant\nrocket engines & test facility", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/angusmuffatti/", "x_url": "https://x.com/dirtman", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/646784bdfdad91fa4bd900a67f40c8583fd68bc8.jpg" }, { "user_id": 2392080, "full_name": "Julian Fried", "title": "Founder", "founder_bio": "Building robotic welding equipment | Prev. Welding foreman in Eastern PA 🇺🇸", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/julian-fried-460691226", "x_url": "https://x.com/JulianFried", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9dfec594b322db9fff20733f9980b38f0e6d6fb3.jpg" }, { "user_id": 1654103, "full_name": "Stephen Lin", "title": "Founder", "founder_bio": "Founder at Advanced Metal Research. Previously at NASA working on spacewalks and planetary exploration. Built systems used by mission control for 19 spacewalks to date enabling real-time telemetry & monitoring of EVAs.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/stephen-lin-0/", "x_url": "https://x.com/Perandex", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/8e89340e2cecc6871ebdb5fe3b69da1781422744.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 31047, "name": "Waddle Labs", "slug": "waddle-labs", "former_names": [ "Waddle" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f525546cff510b464f7877004fcc10c8f0b97843.png", "website": "https://www.waddlelabs.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "LLMs that control robots", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1784890498, "tags": [ "Developer Tools", "Generative AI", "Robotics", "Automation" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "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/waddle-labs", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/waddle-labs.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/waddlelabs/", "x_url": "https://x.com/theWaddleLabs", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/f525546cff510b464f7877004fcc10c8f0b97843.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": 2132817, "full_name": "Hanming Ye", "title": "Founder", "founder_bio": "Interested in how natural intelligence arises. I also like machines such as 3D printers and robots. \n\nhttps://dozenducc.github.io/", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/hanming-ye-0467b01aa", "x_url": "https://x.com/DozenDucc", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5b813f423ca4b4732c54817689193d5602190bf5.jpg" }, { "user_id": 1853600, "full_name": "Yiding Song", "title": "Founder", "founder_bio": "Interested in systems that learn theories about the world with human-like efficiency.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/yiding-song-vincent/", "x_url": "https://x.com/yiding_song", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b7078e0f6f101f74db1f4584bb6cd102051bb9f0.jpg" } ], "jobs": [ { "id": 109947, "title": "Founding Research Engineer", "url": "https://www.ycombinator.com/companies/waddle-labs/jobs/RaRUAQK-founding-research-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$175K - $350K", "equity_range": "1.00% - 2.00%", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [ "ML", "Python", "Torch/PyTorch", "Distributed Systems", "Fine-tuning", "Evals", "AI Agents", "Diffusion Models" ] } ], "news": [], "launches": [ { "id": 107821, "title": "Waddle Labs - Agents that control robots", "tagline": "Claude Code for robotics - prompt your robot to do physical tasks", "body": "Waddle is the Claude Code for robotics. Connect our API to your robot and type a prompt, then our agents write code to achieve the task in \\~20 minutes.\n\n![uploaded image](/media/?type=post&id=107821&key=user_uploads/2132817/afc74f28-33c6-450c-80c3-7f2d263f213d)\n\n### **Our Hypothesis**\n\nRobot intelligence today depends either on large end-to-end VLAs or classical approaches.\n\n\\- VLAs are difficult to customise and steer, require huge amounts of data to train, and don’t yet generalise across embodiments and environment. They face limited deployment.\n\n\\- Meanwhile, classical approaches are widely deployed for their reliability and explicit control, but are often brittle and costly to redevelop in new setups.\n\n_Does this tradeoff have to be inevitable?_\n\n**Our hypothesis:** By using agents to control robots, we combine the generalisation of VLAs with the speed and reliability of classical approaches. \n\n### **Our Solution**\n\nOur agents decomposes a goal into subtasks, and completes each subtask by viewing camera feeds, writing control code, and calling models like VLAs. The agent outputs a program that you can run and iterate on by talking to our agents. \n\n**Where we've been using Waddle internally:**\n\n\\- **Create a working policy in 20 minutes** (\"Write a program to package the box\")\n\n\\- **Generate data for model training** (\"Pick and place lego bricks at random positions 1000 times\")\n\n\\- **Facilitate robotics auto-research** (\"I am tuning a policy overnight. Reset the scene after each trial”)\\\n\\\nBecause our agents are LLMs, they inherit properties of the underlying models. Agents and the code they write are inherently generalist, so they work with any robot and any environment without additional data. Moreover, agents excel at long-horizon planning and can decompose a physical goal into subtasks, verify each stage, and re-plan on failure.\n\n**Interested in trying our agents via our preview API?** Sign up at \\[our website\\]() or email [founders@waddlelabs.ai](mailto:founders@waddlelabs.ai)\n\n### **Our Research**\n\nWaddle's agents enable new forms of scaling that we are very excited about:\n\n\\- **Scaling compositional generalization:** Our agent first wrote the “fold_grasp” skill while flipping a package; another agent later used it to fold a t-shirt. Over time, agents accumulate a library of skills, enabling future agents to compose them and achieve harder tasks.\n\n\\- **Scaling multi-robot cooperation:** Imagine an entire fleet of robots collaborating to achieve a task. For VLAs, this is a nightmare. For Waddle, simply hook up more agents. A master agent spawns subagents, coordinating multiple robots working concurrently.\n\n\\- **Scaling from scale:** We evaluated Opus 4.8, Fable 5, and GPT 5.6 Sol on a suite of manipulation tasks: larger models with larger thinking budgets consistently produce better policies. As foundation models improve, so do our robots.\n\n### **The Team**\n\nWe are @Yiding Song (Vincent) and @Hanming Ye. We met at MIT’s Research Science Institute, where Vincent was working on multimodal astrophysics models and Hanming was researching topology in the math department. Since then, we’ve become roommates at Harvard where we are either doing ML research or breaking robots - usually both.\n\nThere will be millions of robots in the future. Our mission is to enable everyone to take part in building them.", "url": "https://www.ycombinator.com/launches/S33-waddle-labs-agents-that-control-robots", "votes": 11, "created_at": "2026-07-27T17:45:25.918Z" } ] }, { "id": 31152, "name": "Fern", "slug": "fern-bot", "former_names": [ "ProactiveAI", "Ishiki Labs", "Fern (Formerly Ishiki Labs)" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/937df36cb9a1992b6e2ab4f4415451f1ad6f7174.png", "website": "https://fern.bot", "all_locations": "", "long_description": "Fern provides RL environments for robotics companies powered by a foundational world model. Companies can plug and play their robot policies completely in software with varying starting scenes of their production environment, and we'll produce RL heads on top of your existing policies to improve speed and success rate. Our customers get a continual learning flywheel where their production robots improve every week.", "one_liner": "RL environments for robotics companies", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1768297786, "tags": [ "Robotics", "Infrastructure" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2026", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "Unspecified" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/fern-bot", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/fern-bot.json", "year_founded": 2025, "city": null, "country": null, "linkedin_url": "https://www.linkedin.com/company/fernbot", "x_url": "https://x.com/ishikilabs", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/ishiki-labs ", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/937df36cb9a1992b6e2ab4f4415451f1ad6f7174.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/9aa481a01c92aff3ef9ad6396f367ccbff24cd03.png" ], "primary_partner": { "name": "Gustaf Alstromer", "url": "https://www.ycombinator.com/people/gustaf-alstromer" }, "founders": [ { "user_id": 2972207, "full_name": "Amit Yadav", "title": "Founder/CEO", "founder_bio": "Cofounder and CEO at Ishiki Labs (W26). Previously: Research Scientist, first in LlaMA team training multimodal LLMs and then in Reality Labs at Meta training video assistant for smart glasses. PhD from Purdue University with 20+ publications at top conferences like CVPR, NeurIPS, and ICASSP", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/amit-kumar-singh-yadav", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5df16b6162b4b3786dc3815473d7c24badaeff21.jpg" }, { "user_id": 3201791, "full_name": "Robert Xu", "title": "Founder", "founder_bio": "Co-founder & CTO of Ishiki Labs (W26). Previously worked on multi-modal AI and Orion AR glasses at Meta and research infra at Citadel Securities.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/robert-xu/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0946e3006e82ae99c29383b458713393504b6926.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 97949, "title": "Fern – Realtime Socially Aware AI for Meetings", "tagline": "Fern joins every meeting as–either invisible copilot or active participant–so every conversation runs like a top 1% professional", "body": "**TL;DR**\\\n[Fern](https://www.ishikilabs.ai/download) is a realtime AI that joins your meetings as either an invisible copilot or an active participant– your choice! It realtime proactively coaches you through every conversation so you always show up like a top 1% professional.\n\nHey everyone, we're Amit and Robert, cofounders of Ishiki Labs.\n\n**The Problem**\n\n_“AI meeting assistant” has become synonymous with a note-taker waiting to summarize at the end. That's not a meeting assistant. That's a fancier transcript._ \n\nBuilding a realtime AI meeting copilot is hard in two distinct ways.\n\nThe invisible assistant must understand the live meeting context at blazing speed and surface the right thing at the right moment – questions to ask, things you're missing, who you're talking to. Timing is everything. Current AI is purely reactive. Making AI an active participant in discussion is even harder. AI has no social awareness – every pause becomes a prompt, every gap an invitation to speak.\n\nAI that is socially aware and proactive is an unsolved problem. That's what we're building.\n\nThe cost of this gap is real. Cofounders, AEs, recruiters, investors – in discovery calls, sales meetings, investor conversations. The moments that matter most, and AI is absent from all of them.\n\n**How Fern Solves it**\n\n[Fern](https://www.ishikilabs.ai/download) joins your meetings as a true participant or an invisible copilot – your choice. It has two modes:\n\n**Full Presence**: Fern joins visibly, listens, and speaks up when invited. It offers realtime opinions, deep research, and can complete tasks like filing notes or sending emails on the spot. Built for internal product, engineering, and strategy meetings. Watch the demo- \n\n**Shadow Mode**: Silent and invisible to everyone else. You get a private realtime feed: live summaries, questions to ask, things you're missing, context on who you're talking to. A sharp colleague whispering in your ear – with fully customizable insights. Built for client calls, investor meetings, and any conversation where you want invisible support.\n\nBoth modes include a post-meeting summary, transcript, and full insights.\n\n**Team**\n\nWe're both ex-Meta. Amit is an AI Scientist from LLaMA (now Meta Super Intelligence Lab) and Reality Labs – PhD in AI, 20+ publications at NeurIPS/CVPR, trained multimodal assistants for smart glasses. Robert was systems and infra lead in Reality Labs, with four years building low-latency multimodal systems at Meta and Citadel Securities. \n\nOur mission: make AI socially timed and contextually aware – so every conversation you have runs like a top 1% professional.\n\n**Our Ask**\n\nDownload [Fern](https://www.ishikilabs.ai/download) and if you're a founder or AE who lives in high-stakes conversations and don’t want to settle for AI note-takers, reach out: [team@ishikilabs.ai](mailto:team@ishikilabs.ai)", "url": "https://www.ycombinator.com/launches/PTp-fern-realtime-socially-aware-ai-for-meetings", "votes": 26, "created_at": "2026-02-19T15:09:16.569Z" } ] }, { "id": 31223, "name": "Datoric", "slug": "datoric", "former_names": [ "Flow AI", "Arzule" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fa894803120df3a3a9250c66e4232e33e2a223d0.png", "website": "https://www.datoric.com", "all_locations": "San Francisco, CA, USA", "long_description": "Datoric develops custom datasets for voice models, robotics, and world models, treating research, collection, verification, and production as one continuous process. We work closely with frontier model teams to turn emerging limitations and model failures into testable data hypotheses, while running our own experiments ahead of customer demand. This allows us to operationalize validated methods into repeatable collection systems at scale.\r\n\r\nData is collected through private invite-only applications separated by modality, customer, and trust level. Every submission remains linked to the contributor, device, task, session, consent, rights, and processing history that produced it, giving our internal QA and fraud models the context to detect problems that may appear legitimate in the finished file. Each collection reveals new failure cases and quality signals that improve the systems behind the next dataset.\r\n\r\nOnce a collection method is validated, we scale it up as a solution to the model failure and it also becomes a reusable data recipe for future custom projects or independently collected, rights-cleared data products. ", "one_liner": "The secure training data R&D engine for physical AI", "team_size": 2, "industry": "B2B", "subindustry": "B2B", "launched_at": 1767154035, "tags": [ "Machine Learning", "Robotics", "Data Labeling", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/datoric", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/datoric.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/arzulehq/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/fa894803120df3a3a9250c66e4232e33e2a223d0.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Harshita Arora", "url": "https://www.ycombinator.com/people/harshita-arora" }, "founders": [ { "user_id": 1486120, "full_name": "Nikhil Reddy", "title": "Founder/CEO", "founder_bio": "CEO @ Datoric. Prev Quant & SWE Intern. Math/Econ/CS @ UChicago; Bypassed Google OAuth 2.1 and QA systems on data annotation platforms to automate training tasks in 2023, then disclosed the loopholes to the affected platforms.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/nikhilrreddy", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/85cf42094155ddf41c9ca0e99b42a85e2ed763d1.jpg" }, { "user_id": 2310490, "full_name": "Jeffrey Lin", "title": "Founder/CTO", "founder_bio": "CTO @ Datoric. Prev AI/ML & SWE Intern. Math & CS & Robotics at NYU. Created a bounding box algorithm for more efficient labeling as Head of Data for the NYU Robotics Team. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jeff-j-lin", "x_url": "https://x.com/Jeffjinlin", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4f3068998c884af4a2668f4da4bbe3efa8e796d3.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 108251, "title": "Datoric | Trustworthy data for the next generation of models", "tagline": "Collecting the human experience AI needs, securely.", "body": "Datoric provides custom, security-first training data for voice models, robotics, and world models. Our private, project-specific contributor systems have led to a dramatic improvement in quality for customers and helped us generate nearly seven figures in revenue over the last 30 days.\n\n## **Our background**\n\nIn 2023, we built large-scale automations that completed paid LLM training tasks across major crowd-work platforms by bypassing QA testers. We earned six figures in three months, and even helped fix some of the vulnerabilities that we found. From this experience, we learned just how easily training data can be compromised, and how it can lead to unsafe model behavior.\n\n\n\n## **The problem**\n\nLabs are searching for the high-quality, authentic human data their models need, but quality and provenance become harder to control at scale, especially when relying on outside data providers. Poor-quality or compromised data can distort model behavior, while unqualified contributors, automated submissions, unclear instructions, and weak consent records can still slip through QA. At the same time, data providers hold concentrated stores of customer data, contributor identities, and payments that attract fraud and security threats.\n\n## **What we built**\n\nDatoric manages the full collection process for multilingual speech, egocentric video, and action-conditioned data. We collect this data through more than 300,000 active contributors who record conversations, everyday tasks, and other project-specific activities through our private apps. Because Datoric has no public marketplace or open upload system, every collection can run inside its own isolated environment, keeping customer projects separate and limiting unauthorized access. Each recording also remains linked to the verified contributor who created it and the consent they provided. This blocks automated or manipulated submissions and protects quality throughout the collection process rather than leaving it to final QA.\n\n## **Traction**\n\nWe’ve seen a major uptick in quality compared to other providers, and in the last 30 days, Datoric has generated nearly seven figures in revenue.\n\n## **Our ask**\n\nWe would love introductions to teams building voice models, robots, or world models that need difficult, custom human-generated data.\n\nSend us your hardest collection specification at [**founders@datoric.com**](mailto:founders@datoric.com), or visit [**datoric.com**](http://datoric.com).", "url": "https://www.ycombinator.com/launches/S9z-datoric-trustworthy-data-for-the-next-generation-of-models", "votes": 4, "created_at": "2026-07-29T16:22:25.416Z" } ] }, { "id": 31224, "name": "Servo7", "slug": "servo7", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f0947dcd80dc342c9f938f52c6f4959bc0b1b157.png", "website": "https://servo7.com", "all_locations": "Amsterdam, NH, Netherlands", "long_description": "We deploy robots in warehouses to automate the most demanding job in logistics: unloading loose-loaded containers.\r\n\r\nOur customers include 3PLs (CEVA, Stord), distributors (DHL, PostNL) and many more logistics companies.", "one_liner": "Container unloading robots for warehouses", "team_size": 3, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1769385653, "tags": [ "Robotics", "Logistics", "Automation", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2026", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "Netherlands", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/servo7", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/servo7.json", "year_founded": 2025, "city": "Amsterdam", "country": "NL", "linkedin_url": "https://www.linkedin.com/company/servo7", "x_url": "https://x.com/Servo7Robotics", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/f0947dcd80dc342c9f938f52c6f4959bc0b1b157.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": 2067100, "full_name": "Pieter Becking", "title": "Founder/CEO", "founder_bio": "Co-Founder of Servo7: Robots that unload containers in warehouses\n\nPreviously: Deep Reinforcement Learning at Boeing & LLM Engineer & shipped working Hyperloop. Built & sold recruitment tech startup.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/pieterbecking/", "x_url": "https://x.com/pieterbecking", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b03fe8d0079f7616bfd9b0d8a2186ac2917faf5c.jpg" }, { "user_id": 2827656, "full_name": "Jasper van Leuven", "title": "Founder/CTO", "founder_bio": "Co-Founder of Servo7: Robots that 10x industry workers. Previously: Developed autonomous defence systems and deployed them in Ukraine. Built the first video generation model for autonomous driving before cosmos & sora.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jasper-van-leuven-14a3ba1b6/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5a6bca74226ed2b3f26646eab57a36cd13bfade8.jpg" } ], "jobs": [ { "id": 101951, "title": "Founding Hardware Engineer", "url": "https://www.ycombinator.com/companies/servo7/jobs/yPnmJfu-founding-hardware-engineer", "location": "Amsterdam, NH, NL / Amsterdam, North Holland, NL", "type": "Full-time", "role": "Engineering", "role_type": "Hardware", "salary_range": "", "equity_range": "", "experience": "3+ years", "visa": "US citizenship/visa not required", "skills": [] } ], "news": [], "launches": [ { "id": 97659, "title": "Servo7 - Robots for Industry", "tagline": "Simple and rapidly deployed robots for industry work", "body": "Hey everyone, we’re [@Jasper](https://bookface.ycombinator.com/user/2827656) and [@Pieter](https://bookface.ycombinator.com/user/2067100), co-founders of [@Servo7](https://bookface.ycombinator.com/company/31224). We build simple and rapidly deployed robots for industry work.\n\n**TL;DR**\n\nToday, implementing robotics means redesigning your entire facility around a robot. This is inefficient and unnecessary. With Servo7, you don’t have to do any of that. Our robots adapt to your environment.\n\n\n\n**Problem**\n\nCurrently, industry robots are rigid single-purpose machines. Complete floor plans are redesigned around a single robot. As a result, the installation process is complex and inefficient.\n\nThis discourages many businesses from pursuing automation at all. That’s a missed opportunity.\n\n**Solution**\n\nInstead of adjusting the floorplan, redesigning the conveyor belts, and the outflow, our robots just work in the existing process.\n\nWe’re using AI models to train wheeled humanoids and robot arms. Once the robots are implemented, they’ll keep learning on the job: performing the tasks faster to increase throughput. The implementation of our robots is much faster and easier.\n\n![uploaded image](/media/?type=post&id=97659&key=user_uploads/2067100/e4f3ba51-26b4-4115-8b48-01502d7b9b6d)\n\n**How we got here**\n\nWe have been deploying robots and automating repetitive work for years, even in highly regulated industries like the military and hospitals. But, we also know the slow pain of traditional control methods. So we turned to AI to control robots, and found a much better way. Instead of pre-programming every possible movement, we put the robot to work with just a few demonstrations. We quit our jobs that same day to start Servo7.\n\nToday, we’re working with warehouses and CPG brands to automate their fulfillment.\n\n**Ask**\n\nIf you’re working in logistics, assembly, or manufacturing, our robots can help you improve your operations!\n\nReach out to us at [founders@servo7.com](mailto:founders@servo7.com) to chat. Cheers!", "url": "https://www.ycombinator.com/launches/PP9-servo7-robots-for-industry", "votes": 26, "created_at": "2026-02-09T17:41:22.358Z" } ] }, { "id": 31226, "name": "Libra Robotics", "slug": "libra-robotics", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e588f98ac537da3d55ea3c2b43b0bd505524c7f8.png", "website": "https://www.librabots.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Infrastructure faces rapid expansion and labor shortages. Today, robots struggle to scale to meet customers’ high-mix work needs. Libra builds AI that engineers robots for new tasks across embodiments. We go from each new infra task to field-deployable robots 10x faster. Today, our robots are working on solar farms and piloting in data centers. Contractors pay for completed work as a service, not robots.", "one_liner": "The robot workforce for infrastructure", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1783647531, "tags": [ "Hard Tech", "Robotics", "Construction", "Energy", "AI" ], "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/libra-robotics", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/libra-robotics.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/librabots", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/e588f98ac537da3d55ea3c2b43b0bd505524c7f8.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": 3178817, "full_name": "Jermaine Zhao", "title": "Founder/CEO", "founder_bio": "Full-stack robotics engineer with an EE & ME background from Stanford. Built and deployed robots across industrial automation, agriculture, and utility-scale solar. Founder of Libra Robotics.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jermaine-zhao-9439202a2/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/54d431097cd70fba6fbe8902e21879a923482e82.jpg" }, { "user_id": 2782328, "full_name": "Yaojing Huang", "title": "Founder/COO", "founder_bio": "Stanford Civil Engineering+CS | PhD defended in Construction Robotics\n\nDissertation on shared robotic platforms and reusable construction skills across tasks. Research at Center for Integrated Facility Engineering and the Stanford Robotics Center; taught Stanford’s Construction Robotics course; worked with 40+ contractors and robotics companies worldwide.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/yaojing-h-0b903620b/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9f3184f01d6822e5211831c041bd669f65ee31b5.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 122276, "title": "Libra Robotics: The robot workforce for infrastructure", "tagline": "One intelligence layer, many robots. Across solar farms, data centers, and beyond.", "body": "Hey everyone 👋 We're Jermaine and Yaojing, co-founders of Libra Robotics. **We'll present & demo at YC's F26 Demo Day!** If you're attending, we'd love to connect.\n\n**TL;DR:** Infrastructure faces rapid expansion and labor shortages. Today, robots struggle to scale to meet customers’ high-mix work needs. Libra builds AI that engineers robots for new tasks across embodiments. We go from each new infra task to field-deployable robots 10x faster. Today, our robots are working on solar farms and piloting in data centers. Contractors pay for completed work as a service, not robots.\n\n\n\n\\[A simplified walkthrough of how Libra’s AI takes a real data center customer's task from initial requirements to robotic deployment - autonomously designing, simulating, testing, and improving along the way.\\]\n\n**The Problem**\n\nInfrastructure has a labor shortage. Robotics has a scalability problem.\n\nUnlike factories, infrastructure work is high-mix: tasks, designs, and environments constantly change. Single-task robots need custom engineering per task; general-purpose robots need enormous data to become reliable. **Neither scales to thousands of changing tasks.**\n\n**Our Approach**\n\nInstead of building one robot that does everything, we build **reusable robotic capabilities and AI that engineers them into new tasks.**\n\nMany infrastructure tasks share the same physical challenges: handling heavy components, precise positioning, alignment, and fastening. We've built a common set of robotic capabilities around these operations, designed to work across different robots and installation tasks.\n\nOur hardware-agnostic AI selects the right robot configuration and tooling, reuses existing skills, and engineers what is missing for each new task, reducing the need for custom engineering.\n\nIt validates solutions in simulation, then autonomously designs and runs physical experiments on our in-house robotic testbeds, stress-testing solutions against real-world variability (such as unexpected obstacles, changing environmental conditions, etc.). When a test fails, the system **diagnoses the failure, recovers, and iterates autonomously** - without human engineers in the loop. Through **recursive self-improvement (RSI)**, it continuously refines its approach toward field-ready performance.\n\n**Every task adds reusable knowledge, making the next one faster and cheaper to automate.**\n\n**GTM & Traction**\n\n**We deploy AI-powered robot crews to perform infrastructure work**, starting with solar installation and data center electrical work, including prefab MEP and busway installation. \n\n**We're already beyond the lab:**\n\n→ **Robots already deployed** on real solar construction sites\n\n→ **Signed commercial agreements** for solar installation\n\n→ **Data center pilots underway** for MEP automation\n\nWe land with one high-value task, then expand into more work for the same customer. Our goal is to achieve 100 million hours of robotic work annually by 2031.\n\n![uploaded image](/media/?type=post&id=122276&key=user_uploads/3178817/7e72e897-d6d4-4ed6-a547-0f5889a68de0)\n\n\\[Libra’s robots in action on solar farms\\]\n\n**Who We Are**\n\nYaojing did her Stanford PhD on the exact problem Libra solves: one shared robotic platform with reusable skills that generalizes across construction tasks. She has worked with 40+ contractors and construction robotics companies.\n\nJermaine previously led a team to build and deploy autonomous agricultural harvesting robots from the ground up, tackling complex manipulation, precision harvesting, and multi-robot coordination in unstructured real-world environments. He brings end-to-end experience turning robotics research into reliable, field-deployed systems.\n\n**Our Ask**\n\nWe're looking for introductions to:\n\n* **Data center GCs, EPCs & Prefab contractors** interested in deploying robots for prefab MEP installation, busway installation, and other electrical fit-out tasks.\n* **Solar EPCs & installers** with upcoming utility-scale projects interested in robotic installation.\n* **Robotics engineers & researchers** working on sim-to-real, autonomous robot engineering, and multi-embodiment learning who want to build with us.\n* **Investors** who are interested in backing the robot workforce companies for AI era.\n\nKnow someone we should talk to? We'd love an introduction!\n\nReach us at [founders@librabots.com](mailto:founders@librabots.com).", "url": "https://www.ycombinator.com/launches/VoC-libra-robotics-the-robot-workforce-for-infrastructure", "votes": 14, "created_at": "2026-10-15T15:49:58.924Z" } ] }, { "id": 31232, "name": "Remy AI", "slug": "remy-ai", "former_names": [ "Bright Eyed Labs" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/94f9d60cdf58d3c7fc724152a315ad834ec78eec.png", "website": "https://www.tryremy.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Building robots and training models for automating manipulation in warehouse, starting with e-commerce 3PLs", "one_liner": "Automating dexterous tasks in warehouses with AI-powered robots", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1770934019, "tags": [ "Robotics", "Logistics" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 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/remy-ai", "api": "https://devasheeshg.github.io/yc-api/batches/winter-2026/remy-ai.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/remy-ai-2025", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/94f9d60cdf58d3c7fc724152a315ad834ec78eec.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": 1182398, "full_name": "Oscar Brisset", "title": "Founder/CEO", "founder_bio": "Oxford, AI Engineer at BCG X, now working on end-to-end learning for robotics ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/oscarbrisset/", "x_url": "https://x.com/oscar__2025", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/fc84e0375af73a1add39a9246fee99dc88fe7766.jpg" }, { "user_id": 3174376, "full_name": "Ben Kaye", "title": "Founder/CTO", "founder_bio": "Oxford engineering '22 and PhD tbd. Expertise in Spatial AI", "is_active": false, "linkedin_url": "https://www.linkedin.com/in/ben-kaye-0/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/86a40536614763d9bfb931829495fdc91289e407.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 97934, "title": "🤖📦 Remy AI - Dexterous robots for e-commerce 3PLs", "tagline": "Existing automation options for 3PLs are expensive and inflexible. We're building robots to change that.", "body": "Hi YC ! We’re Oscar and Ben and we’re building Remy AI.\n\n**TL;DR:** we're bringing the robotics revolution to the little guy by building AI-powered robots for e-commerce 3PLs.\n\n![uploaded image](/media/?type=post&id=97934&key=user_uploads/1182398/680c2630-17bb-498d-b1d1-1ad64cf55623)\n\n**⚠️The problem**\n\nWarehousing to this day remains highly manual. Whether it’s for inbound receiving, picking, or even truck loading, **more than 80% of warehouses in the US** have little to no automation.\n\n**E-commerce 3PLs** in particular suffer from this. Unlike large retailers or shippers, their inventory mix and volumes are **highly variable**, given their smaller size and greater exposure to e-commerce trends. Their contracts renew on an annual basis, their customers regularly go out of business, and the brands they work with frequently release new products.\n\nMost of the automation out there is designed for the big players. Stacker cranes, 2D/3D shuttles, or even more recently AMR-based systems - these all only make sense to invest in above a certain scale and predictability.\n\n![uploaded image](/media/?type=post&id=97934&key=user_uploads/1182398/487a824f-d1aa-4c7b-942e-add0a872b111)\n\nWhat _80% of 3PLs look like: rows of shelves of plastic totes and cardboard boxes with at best a couple conveyors._\n\n**Why is automation so limited?** Because existing solutions are expensive ($100-150K incl. solution + installation + servicing), bulky, and inflexible. They’re usually some mechanical system + a PLC that perform one rigid task repetitively with little to no room for customisation beyond some initial configurations. As a result, most 3PLs aren’t able to leverage these and stick to manual options.\n\n![uploaded image](/media/?type=post&id=97934&key=user_uploads/1182398/d87e20be-7be0-4950-a13c-1ea2671ad916)\n\n_Current automated packing stations: rigid mechanical systems with limited adaptability_\n\nYet this long tail of 3PLs is huge: \n\n* 70K 3PLs in the US\n* $1.2 trillion global market size\n* Growing at +8% per year given relentless rise of e-commerce\n\n**✅ The solution**\n\n**Remy AI is building flexible automation for e-commerce 3PLs.**\n\nWe deploy a robotic system that:\n\n* Adapts to new SKUs **without needing to be re-trained or re-programmed**\n* Can be dropped into **existing work stations** with minimal modifications\n* Can perform **dexterous tasks** that existing robots struggle with\n\nWe leverage a versatile bi-manual mobile platform which allows our system to be deployed on a **wide range of tasks**:\n\n* Mobile picking\n* Packing stations\n* Kitting\n* Receiving\n* …\n\nAnd crucially, we do this at a **50% lower cost** than existing solutions, by replacing mechanical complexity with intelligence.\n\n\n\n**🧠 How do we achieve this?**\n\nRecent developments in ML & robotics have made it possible to bring a human level of adaptability to robots. Whereas before you’d have to use a deterministic pipeline that would map specific object morphologies to pre-determined grasps, large pre-trained robotics & vision models now enable robots to generate trajectories and grasps by themselves, adapting in real-time to changing environments.\n\nCombined with recent advances in simulation and robot learning, we’re able to deploy highly customised systems by taking just a couple photos of the customer’s environment, generating that environment in simulation, to then fine-tune our robot to that specific deployment. Supplementing this with real world data captured at the customer’s site + a rigorous domain randomisation pipeline + our own error recovery algorithms, we’re able to deploy systems with production-grade reliability in days not months.\n\n**🤝🧑‍💻Our team**\n\nWe’ve been working in this problem space for several years. We met 7 years ago when we were both undergrads at Oxford.\n\n![uploaded image](/media/?type=post&id=97934&key=user_uploads/1182398/a0d166e5-4cb6-4a5b-8579-89f74288a061)\n\n**Oscar (CEO)** - AI engineer at BCGX, built ML infra for Fortune 500s, data engineer previously\n\n**Ben (CTO)** - PhD ML Oxford, embedded systems patent pending, robotics masters\n\n**Ask**\n\nWe’d love to chat to more e-commerce 3PLs and brands that handle their own warehouses. Reach out to us at [founders@tryremy.ai](mailto:founders@tryremy.ai). Thanks!", "url": "https://www.ycombinator.com/launches/PTa-remy-ai-dexterous-robots-for-e-commerce-3pls", "votes": 14, "created_at": "2026-02-18T17:21:02.655Z" } ] }, { "id": 31301, "name": "OpenVector", "slug": "openvector", "former_names": [ "TeleOps", "BotZero", "Foveal" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/54df715903ce304e2b9e3b2fe1f375caf7811ea6.png", "website": "https://openvector.com", "all_locations": "San Francisco, CA, USA", "long_description": "OpenVector transforms any existing camera into an automated 24/7 workforce without requiring new hardware. We've built the world's fastest vision-language model inference engine that allows users to simply describe a task in plain English and automatically build a custom AI vision model to monitor their feed. When it detects an important physical event—like a stalled production cycle, a safety violation, or a waiting customer—it operates a computer just like a human to take immediate action. It integrates with legacy systems, makes calls, sends emails, updates a POS/CRM, or triggers webhooks in real time. OpenVector enables any camera to do real work.", "one_liner": "AI that turns any camera to an autonomous worker with real-time vision", "team_size": 4, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1785369468, "tags": [ "Robotics", "Computer Vision", "Infrastructure", "Industrial" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/openvector", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/openvector.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://linked.com/in/openvectorlabs", "x_url": "https://x.com/openvectorlabs", "fb_url": "https://www.facebook.com/profile.php?id=61591381283372", "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/54df715903ce304e2b9e3b2fe1f375caf7811ea6.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Jon Xu", "url": "https://www.ycombinator.com/people/jon-xu" }, "founders": [ { "user_id": 633157, "full_name": "Andrey Gizdov", "title": "Founder/CEO", "founder_bio": "Dropped out of PhD. Computer Vision @ Harvard.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/andreygizdov/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/994295941ffb048fecb964921a35db1494d051b3.jpg" }, { "user_id": 2384953, "full_name": "Vishal Urlam", "title": "Founder", "founder_bio": "CMU'23, ECE'20 | MIT GrandHack '25 | Kellogg Design Challenge '23", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/vishal-urlam/", "x_url": "https://x.com/vishalurlam", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/398802b070ebc9a50a9873e3441541de12ccedfb.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 108360, "title": "OpenVector - Self-improving AI that turns any camera into an autonomous worker.", "tagline": "Most cameras just record. We give them the ability to do real work.", "body": "**TLDR;** OpenVector turns existing cameras into an automated 24/7 workforce. Describe a task in plain English, and it auto-builds a custom vision model that takes real-time actions on a computer when it spots an event.\n\n**Ask;** If you or someone you know runs physical operations (manufacturing, logistics, retail, security) and wants to automate visual tasks without buying new hardware, we’d love to connect!\n\n**Our Launch Video:**\n\n\n\n**Our Team:**\n\nOpenVector was founded by a team of builders and engineers obsessed with bringing self-improving visual intelligence to the physical world.\n\n* [Andrey Gizdov](https://www.linkedin.com/in/andreygizdov/), CEO, dropped a fully-funded **PhD** scholarship from Fulbright, worth **$170,000**, with invitations at **Harvard and MIT**, where he worked on real-time vision models.\n* [Vishal Urlam](https://www.linkedin.com/in/vishal-urlam/), CTO, previously automated camera systems and network protocols for Tata, the **second-largest network infrastructure in the world**. CMU embedded systems engineer.\n\n**Problem**:\n\nMany important business moments happen in the physical world: Someone tailgates. A production cycle stalls. A worker skips a step in the manufacturing process. A customer arrives, and no one responds. There are over 1 billion cameras worldwide, but they only record it for later. For physical operations, the best technology available to catch these events in real-time has been a human staring at a monitor.\n\n**Solution:**\n\nOpenVector is an AI that brings action to any camera.\n\n* **Plain English to AI Model:** No coding or expensive setup. Simply describe your task in plain English, and OpenVector automatically builds the best AI vision model for it, and watches your camera feeds 24/7. It’s an app that takes 2 minutes to download and set up, and works with any camera.\n* **Acts Like a Human:** OpenVector operates a computer just like a human based on what it sees.\n* **Legacy Integration:** It automatically integrates with your existing systems to make a call, send an email, update your POS or CRM, or trigger a webhook the second an event happens.\n* **Zero New Hardware:** Works entirely with the cameras you already have installed (custom end-to-end solutions also available).\n\n**We’ve Already Started:**\n\nOpenVector is already live and seeing use cases across security, retail, manufacturing, and logistics. We are tracking production cycle efficiency directly from existing CCTV, ensuring good-manufacturing-practices, and catching physical design errors.\n\n**Now Onboarding:**\n\nOpenVector is ready to deploy on your camera feeds today. Contact us if you’re tired of cameras that only watch and want them to actually do work for you. [founders@openvector.com](mailto:founders@openvector.com)\n\n![uploaded image](/media/?type=post&id=108360&key=user_uploads/633157/46faabca-90e0-4c69-a364-138588d733d5)\n\n", "url": "https://www.ycombinator.com/launches/SBk-openvector-self-improving-ai-that-turns-any-camera-into-an-autonomous-worker", "votes": 16, "created_at": "2026-07-31T18:00:43.590Z" } ] }, { "id": 31333, "name": "PerfectBit, Inc.", "slug": "perfectbit-inc", "former_names": [ "Gikl, Inc", "PerfectBit" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/900c210e3f57ee42221dbb5ea21f81418b553e70.png", "website": "https://perfectbit.ai", "all_locations": "San Francisco, CA, USA", "long_description": "PerfectBit builds learned policies for robots that do real work. We train manipulation and control policies that hold up outside the lab, in the unstructured environments where real tasks actually happen. Founded by two alumni of Meta's Superintelligence org: Péter Vajda led Media GenAI foundation-model R&D (Emu, Movie Gen, image and video editing), and Seiji Yamamoto led teams in the Core Llama group across LLM pre-training and post-training, inference optimization, and computer vision. We're early, deliberately quiet about the details, and hiring the first researchers who will shape what this becomes. San Francisco, on-site.", "one_liner": "Robotics", "team_size": 3, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1773359306, "tags": [ "Machine Learning", "Robotics", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Spring 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/perfectbit-inc", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2026/perfectbit-inc.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/perfectbit", "x_url": "https://x.com/PerfectbitAI", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/900c210e3f57ee42221dbb5ea21f81418b553e70.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Garry Tan", "url": "https://www.ycombinator.com/people/garry-tan" }, "founders": [ { "user_id": 3007971, "full_name": "Seiji Yamamoto", "title": "Founder", "founder_bio": "Led teams in the Core Llama group at Meta Superintelligence Labs. Senior Staff Research Scientist across 9 years at Meta spanning LLM pre-training and post-training, inference optimization, full-duplex speech models, and computer vision vision models. Before tech: PhD in Physics, published in Proceedings of the National Academy of Sciences and Physical Review Letters, co-authored with Fields Medalist. Educated at Stanford, Rice, Columbia, post-doc at a National Lab. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/seiji-yamamoto-a630897/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b3404aa262c227d308c4e89f01657ebd082beaef.jpg" }, { "user_id": 45070, "full_name": "Peter Vajda", "title": "Founder", "founder_bio": "\nI worked as Director of Media Generation at Meta before 2026 for 11 years.\nI was managing the Media GenAI foundation model research and development, including efficient media generation, text to image generation (Emu), image editing, Movie gen, text to video, video editing and character consistent image and video generation. Previously, led efficient deep learning for computer vision teams supporting on-device models for AR/VR. \nI was Assistant Professor at Stanford University", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/p%C3%A9ter-vajda-9a03aaa/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0315fd092411900f3bed846cb6807bfb6d6290d6.jpg" } ], "jobs": [ { "id": 96987, "title": "Hiring Research Scientists and Research Engineers at PerfectBit", "url": "https://www.ycombinator.com/companies/perfectbit-inc/jobs/snGw8px-hiring-research-scientists-and-research-engineers-at-perfectbit", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$100K - $300K", "equity_range": "0.10% - 3.00%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [ "C++", "Python", "Deep Learning", "Reinforcement learning (RL)", "Computer Vision", "CAD Design", "Blender", "LLMs", "Transformers", "AI Agents", "Multimodal AI", "Diffusion Models" ] } ], "news": [], "launches": [ { "id": 101365, "title": "PerfectBit: AI Training data, correct by construction", "tagline": "Specialized data for the world's most powerful models.", "body": "# **TL;DR**\n\n_PerfectBit creates high-quality training data that's correct by construction. We verify against physics simulators, scientific databases, formal proof systems. It's what models need to cure hallucination, close common-sense gaps, and reach superintelligence. Reinforcement Learning from Verified Rewards (RLVR) was an early step in this direction. We go further. LLMs, robotics, AI for Science, and more._\n\n\n\n# **The problem: the failures standing between today's models and superintelligence**\n\nFrontier labs are bottlenecked on four data problems:\n\n* **Hallucination.** Models trained on noisy web scrapes produce confident, fluent statements that are wrong.\n* **Common-sense failure.** Models that solve graduate-level math still trip on trivial problems for a five-year-old.\n* **Information scarcity.** Scientific facts, formal derivations, peer-reviewed findings — they're a thin minority of tokens in any open-web scrape, drowned out by orders of magnitude of recipes, marketing copy, forum chatter, and AI-generated slop. Scaling the scrape doesn't change the ratio.\n* **Human annotation doesn't scale.** It's slow, expensive, and capped at human ability — superintelligence won't come from labeling at human throughput.\n\n# **What we do**\n\n* PerfectBit creates high-quality training data that's correct by construction. Every sample is generated against an oracle — physics simulator, scientific database, formal proof system — and verified before it ships, in text, code, image, audio, or video. For LLMs, we project observations about the world into natural language; for verticals like robotics and AI-for-science, we ship purpose-built datasets.\n\n# **Why us**\n\nWe've trained the models we're now building data for.\n\n* **Peter Vajda** — Former **Director of Media Generation at Meta**. Eleven years at Meta. Most recently led Media GenAI foundation-model R&D: **Emu** (text-to-image), image editing, **Movie Gen**, text-to-video, video editing, character-consistent generation. Earlier led efficient deep learning for computer vision powering on-device Augmented Reality and Virtual Reality (AR/VR) models. **Assistant Visiting Professor at Stanford** before Meta. PhD in Computer Science.\n* **Seiji Yamamoto** — Led teams in the **Core Llama group at Meta Superintelligence Labs**. Nine years at Meta as a **Senior Staff Research Scientist** across LLM pre- and post-training, inference optimization, full-duplex speech, and computer vision. **PhD in Physics**, publications in **Proceedings of the National Academy of Sciences** and **Physical Review Letters** (co-authored with a Fields Medalist). Stanford, Rice, Columbia; postdoc at a National Lab.\n\nBetween us: foundation-model training across text, image, video, and speech, shipped to billions of users — plus scientific chops to design the verifier stacks.\n\n# **We’d love to talk more**\n\nWe're talking to a small number of frontier AI labs about pilot engagements.\n\n* **Heads of data / data partnerships** at frontier labs\n* **Research leads** running pre-training, mid-training, post-training, or reasoning programs and shopping for a corpus that doesn't exist yet\n* **Model-training teams** preparing a next-gen training run who want a correct-by-construction supplement in the mix\n* **Researchers in formal methods, scientific computing, or domain-specific simulators** who want to contribute a verifier stack — we'd love to talk\n\nWe're also **hiring research scientists and engineers in San Francisco** (in-person). If you've shipped foundation-model training, built formal/simulation tooling or spent time developing AI training data at production scale, please reach out.\n\n# **Contact**\n\n* **Web:** [**https://perfectbit.ai**](https://perfectbit.ai)\n* **Email:** [**founders@perfectbit.ai**](mailto:founders@perfectbit.ai)\n* **Founders:** Peter Vajda, Seiji Yamamoto", "url": "https://www.ycombinator.com/launches/QMv-perfectbit-ai-training-data-correct-by-construction", "votes": 8, "created_at": "2026-05-14T19:03:28.026Z" } ] }, { "id": 31341, "name": "Most Robotic", "slug": "most-robotic", "former_names": [ "Instance" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/16ccadcbd2ec474ed470efbc872763f4a7984ec0.png", "website": "https://mostrobotic.com/", "all_locations": "San Francisco, CA, USA", "long_description": "We're a robotics research lab pushing what's possible with physical AI.\r\n\r\nWe're MIT computer scientists & friends since middle school, with robotics research backgrounds and industry experience at NASA JPL, SpaceX, and AWS.", "one_liner": "Research lab building the most robotic household in the world", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1782761102, "tags": [ "Robotics", "AI" ], "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/most-robotic", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/most-robotic.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/mostrobotic/", "x_url": "https://twitter.com/mostrobotic", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/16ccadcbd2ec474ed470efbc872763f4a7984ec0.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/5d0a5df4551ace828d9502da4d71b644d4143a15.png" ], "primary_partner": { "name": "Ankit Gupta", "url": "https://www.ycombinator.com/people/ankit-gupta" }, "founders": [ { "user_id": 3107325, "full_name": "Claire Mao", "title": "Founder/CEO", "founder_bio": "MIT Math + CS. Aerospace research @ MIT Media Lab; prev @ NASA JPL", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/clairemao-/", "x_url": "https://x.com/clairemao78", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/8bc8742026b7ae3d795367ca9cbc052f0035d9c3.jpg" }, { "user_id": 2386225, "full_name": "Lucy Cai", "title": "Founder/CTO", "founder_bio": "MIT CS + AI. Robotics research @ MIT LIS Lab; prev @ SpaceX, Amazon (AWS)", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/lucy-cai/", "x_url": "https://x.com/LucyCai9", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7e3c58d6a8b486439a545ea902cf0dd6981d51ed.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 105382, "title": "Instance: Automated evaluation for robot policies, starting with the success detector", "tagline": "Today, evaluating a robot policy means humans have to watch the robot roll out, mark success, and reset the scene – we're automating that.", "body": "**TL;DR:** We’re **automating robot evaluation**– the loop where you wait for your robot to roll out, judge its success, and then reset the scene. Today, we’re launching step one: a **success detector** that automatically tells you whether your robot actually completed its task. Book a demo with [founders@instancelabs.ai](mailto:founders@instancelabs.ai) and we’ll visit your office to show you how it works!\n\n\n\n**The problem**\n\nIn Lucy’s robotics research this past year, she **spent way too much time being a babysitter for her robot**. Her project was to get a humanoid to find objects around a room, so her days went like this: start a rollout, watch the robot open all the drawers in the room for 30 minutes, mark success/fail in a spreadsheet, then get up, close all the drawers, and put the objects back where they started. Then do it again, and again, and again. Some days ended with back pain, and for weeks she couldn’t work on anything else because she was stuck doing exactly this.\n\nThat was one robot, in one lab, running a single policy. Industry teams run fleets of robots across dozens of policies, with **multiple people assigned to sit and watch each one**. Every robotics team we’ve talked to has some version of this– and it will only grow as robot foundation models scale.\n\n**Our solution**\n\nInstance is building the **autonomous evaluation rig for robot learning**: your robot rolls out, we judge success, a second robot resets the scene, and the next rollout starts– with no humans in the loop at all.\n\nToday, we’re starting with the success judge. Point us at a task description and your video rollouts, and we return a verdict with detailed subtask captions. We benchmarked our verifier against 10,000+ held-out, human-labeled episodes across 7 robot platforms, and it resulted in **higher accuracy than Claude Opus 4.8, at a fraction of the latency.**\n\n**Try it**\n\nTry it at [demo.instancelabs.ai](http://demo.instancelabs.ai) – drop in a video, or record one from your phone and watch it get verified live.\n\n**Team**\n\nWe’re Claire and Lucy, MIT grads and friends since middle school! \n\nClaire studied math and CS at MIT. At NASA JPL, she built software to simulate planetary atmospheres, and at the MIT Media Lab, she researched sustainable propulsion for spaceflight. She loves working where software meets the physical world.\n\nLucy studied CS at MIT and completed her MEng in MIT's Learning and Intelligent Systems lab. She’s an experienced robotics researcher, and has in the past worked on satellite software at SpaceX, LLM unit testing at Amazon, and brain computer interfaces at Blackrock Neurotech.\n\n**Our ask**\n\nIf you are:\n\n* training robot policies\n* running evals\n* deploying robots in the real world\n* or can intro us to someone who is,\n\nEmail us ([founders@instancelabs.ai](mailto:founders@instancelabs.ai)) to book a demo. We’d love to swing by your office with sweet treats to show you how it works!\n\n![uploaded image](/media/?type=post&id=105382&key=user_uploads/3107325/d03f1074-ae6e-4ab3-acdd-81ff69be93b6)\n\n", "url": "https://www.ycombinator.com/launches/RPi-instance-automated-evaluation-for-robot-policies-starting-with-the-success-detector", "votes": 36, "created_at": "2026-07-13T20:48:30.605Z" } ] }, { "id": 31359, "name": "Twolabs", "slug": "twolabs", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f6140e69d64bb482f52d28db6644ebb4a4c700ef.png", "website": "https://twolabs.ai", "all_locations": "San Francisco, CA, USA", "long_description": "We build verifiable reinforcement-learning environments, evaluations, and proprietary training datasets to improve frontier AI models and robot policies.\r\n\r\nWe focus on complex, underexplored domains like PCB and chip design, embedded systems, robotics, and specialized coding environments, where high-quality training data is scarce and existing models fall short.\r\n\r\nOur long-term goal is to develop self-improving training infrastructure that can autonomously generate increasingly challenging tasks, evaluate performance, and continuously advance model capabilities toward recursive self-improvement.", "one_liner": "RL environments for underexplored domains.", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1779755220, "tags": [ "Robotics", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2026", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/twolabs", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2026/twolabs.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/twolabsai", "x_url": "https://x.com/twolabsai", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/f6140e69d64bb482f52d28db6644ebb4a4c700ef.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/63ed0b28129d2701e0f24516537dca2b2befabe9.png", "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/ac9409276a8d3f419d504d97a1983067bea7eb19.png" ], "primary_partner": { "name": "Aaron Epstein", "url": "https://www.ycombinator.com/people/aaron-epstein" }, "founders": [ { "user_id": 2115411, "full_name": "Sardor Rahmatulloev", "title": "Founder/CEO", "founder_bio": "Co-Founder & CEO of Twolabs. Previously at Meta Superintelligence Labs, combat robots at Cornell, and built humanoid robots.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/sardor-rahmatulloev", "x_url": "https://x.com/bysardr", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1546aff34234f33a2ffe9cb98cf054ac86d57c7e.jpg" }, { "user_id": 2317491, "full_name": "Danyal Ahmad", "title": "Founder/CTO", "founder_bio": "Co-Founder & CTO of Twolabs. Former Salesforce MTS with an MS in AI from Georgia Tech.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/danyalahmad1/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3fb2e8e7fe3d5fd607cf158c562444cfce65d5c2.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 101964, "title": "Twolabs - Humanoid robots for caregiving", "tagline": "Socially intelligent humanoids to assist the elderly.", "body": "**TL;DR -**\n\n[Twolabs](https://www.twolabs.ai/) builds humanoid robots for caregiving.\n\nOur robots will assist at nursing homes and senior living centers to take care of the elderly, starting with feeding, dressing, medication, daily tasks, and companionship.\n\nWe have our first robot design Tobi, are actively training VLAs, and building the social intelligence layer. Check out our [launch video](https://youtu.be/70T6AzTqIHc?si=CwZwf999yWGGNFk3).\n\n**What we do**\n\nTwolabs builds semi-humanoid robots for nursing homes and senior living communities. We're building the robot to achieve the following goals for the elderly:\n\n* **Everyday help.** Feeding, dressing, medication reminders, fetching objects, the daily physical work of getting through a day.\n* **Mobility support.** A stabilization aid so residents can walk safely, plus wayfinding around the facility.\n* **Companionship.** Conversation, presence, real social support, so a resident isn't alone all day.\n\nWe build the full stack in-house, the robot hardware and all the AI that makes it socially capable. Most of robotics right now is chasing warehouse manipulation, moving boxes and folding laundry. We think the harder and more important problem is robots and people working closely together.\n\n![uploaded image](/media/?type=post&id=101964&key=user_uploads/2115411/ee3141ab-259b-402a-8ee5-5e10b8ce37fd)\n\n**The backstory**\n\nI'm [Sardor](https://www.linkedin.com/in/sardor-rahmatulloev). I was born in Samarkand, Uzbekistan, moved to the US at six, and studied CS at Cornell. At Cornell I led a 40+ engineer team building autonomous combat robots. We were ranked top 5% nationally; most of my team went on to defense tech and semiconductors. My faculty advisor was Professor Tapo Bhattacharjee, who runs one of the leading caregiving robotics labs in the country. After Cornell I joined Meta Superintelligence Labs at 23 years old, working on GPU optimization, foundation model training, and AI infra. I left to start Twolabs. (I also got to be the first Uzbek founder to get into YC.)\n\n[Danyal Ahmad](https://www.linkedin.com/in/danyalahmad1/) is my co-founder, and we have known each other for over nine years, since high school. We interned together at Salesforce in 2024 and have built a lot of products together since. Danyal has an MS in AI from Georgia Tech, and fine-tuned video models at Salesforce.\n\nWe started Twolabs because our grandparents face a lot of health conditions as they grow older, and we wanted to build a robot that can assist them in their daily lives. The need is everywhere: the US is short hundreds of thousands of caregivers and the gap widens every year as the population ages. A caregiver costs a facility around $60K/year, turnover is brutal, and the work is physically and emotionally exhausting. Meanwhile the people who need help, getting out of bed, eating, not being alone all day, don't get enough of it. A robot doesn't replace caregivers. It takes the repetitive physical load off them so one caregiver can do more for more residents, and residents get help when they actually need it.\n\n**Our bet**\n\nMost robotics companies fall into one of two camps:\n\n* **Task robots** that can do physical work but can't relate to a person.\n* **Social robots** that can hold a conversation but can't actually do anything.\n\nEach succeeds at one half of the problem. But we think a truly helpful robot has to handle both, completing the physical task and engaging with the person in front of it. Too many humanoids are optimizing for task completion alone. We're betting the robots that actually help people will need to be socially intelligent to do it.\n\nThe other half of our bet is how robots are built. Companies have to be vertically integrated to win in robotics right now. We build the hardware and the AI together, because at this stage of Physical AI the models need to be specific, not general-purpose.\n\n**Where we are**\n\nPrototype design completed and our AI stack in active development. We're advised by Professor Zackory Erickson at Carnegie Mellon, whose research is at the leading edge of assistive robotics.\n\n![uploaded image](/media/?type=post&id=101964&key=user_uploads/2115411/551aef43-2a9c-4786-831c-ea4c32f77551)\n\n**Our asks**\n\n1. **Engineers and research scientists.** If you or someone you know is proficient in VLA research, reinforcement learning, or robotics foundation models, we're hiring AI engineers and research scientists.\n2. **Investors.** Investors in robotics, humanoids, healthcare, or hard tech, especially anyone who's been close to elder care.\n\nContact us directly at [sardor@twolabs.ai](mailto:sardor@twolabs.ai) and [danyal@twolabs.ai](mailto:danyal@twolabs.ai). And check out our website at [twolabs.ai](http://twolabs.ai).", "url": "https://www.ycombinator.com/launches/QWa-twolabs-humanoid-robots-for-caregiving", "votes": 8, "created_at": "2026-05-26T14:52:49.982Z" } ] }, { "id": 31375, "name": "Hub", "slug": "hub", "former_names": [ "Hub", "Hub.xyz" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4807c17f08dbbfbdd8f51297746a838ba6db58c1.png", "website": "https://hub.xyz", "all_locations": "San Francisco, CA, USA", "long_description": "Hub is a multimodal lab providing real world data to frontier labs and robotic companies.", "one_liner": "Real-world training data for frontier AI labs and robotics.", "team_size": 40, "industry": "B2B", "subindustry": "B2B -> Infrastructure", "launched_at": 1773429014, "tags": [ "Robotics", "Crowdsourcing", "Big Data", "Infrastructure", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Spring 2026", "status": "Active", "industries": [ "B2B", "Infrastructure" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/hub", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2026/hub.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/hub-xyz", "x_url": "https://x.com/hubdotxyz", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/4807c17f08dbbfbdd8f51297746a838ba6db58c1.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Harj Taggar", "url": "https://www.ycombinator.com/people/harj-taggar" }, "founders": [ { "user_id": 3369916, "full_name": "Armin Kiani", "title": "Founder/CEO", "founder_bio": "CS & robotics. \nMicrosoft Innovation Award, 2020. \nWorked at Freedelity, Belgium's largest consumer-data platform.\nspeeding embodied agi with hub.xyz", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/armin-k-3439033ab/", "x_url": "https://x.com/xarmin", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/cfe1e5dd284cd517f46c254fc8c238c747cc1666.jpg" }, { "user_id": 3035977, "full_name": "Tim Sprecher", "title": "Founder/COO", "founder_bio": "Co-founder @ Hub, real-world training data for frontier labs.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/tim-sprecher-2a705220a/", "x_url": "https://x.com/tim404x", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/89d71ffcde838d447280bf34120d31b53f88d279.jpg" } ], "jobs": [ { "id": 99443, "title": "Field Operator - Brazil", "url": "https://www.ycombinator.com/companies/hub/jobs/uJPqDL4-field-operator-brazil", "location": "SP, BR / State of São Paulo, BR / São Paulo, SP, BR / São Paulo, State of São Paulo, BR / Remote (SP, BR; State of São Paulo, BR)", "type": "Contract", "role": "Operations", "role_type": null, "salary_range": "$100 - $2K / monthly", "equity_range": "", "experience": "1+ years", "visa": "US citizenship/visa not required", "skills": [] }, { "id": 114525, "title": "Machine Learning Engineer", "url": "https://www.ycombinator.com/companies/hub/jobs/ghznA3v-machine-learning-engineer", "location": "Paris, IDF, FR / Paris, Île-de-France, FR", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$90K - $120K", "equity_range": "0.02% - 0.20%", "experience": "3+ years", "visa": "US citizenship/visa not required", "skills": [] } ], "news": [], "launches": [ { "id": 103084, "title": "Hub: real-world training data for frontier AI labs and robotics", "tagline": "Leveraging a global human network to collect data that don’t exist yet.", "body": "Hub provides real-world training data to frontier AI labs and robotics companies. We went to 7-figure revenue agreement on data delivery during the last weeks, working with some of the biggest names in AI and robotics.\\\n\\\n**Why now**\n\nThe gap between frontier models is closing, and internet-scale data is largely exhausted. The only edge left is real-world data that humans have to produce. Every lab now wins or loses on its edge cases, and edge cases need specific data captured by specific people: data that doesn't exist anywhere online. Whoever can go collect the right data first ships the better model first. Human labor is half of global GDP, and almost none of it has been recorded yet.\n\n**What Hub does**\n\nWe capture this data through a global network of humans, across all continents. We route and activate the exact people who fit a lab's brief and deliver in days, not the months it takes to source a generic dataset off the shelf. Because we collect the data ourselves, we can attest its provenance, which you can't do for data you didn't capture. Our ML and QA pipelines then verify and enrich it, so we meet the hardest dataset requirements labs throw at us. The moat isn't the data, it's how fast we can go get it.\n\n**Traction**\n\nFrom 5-figure to 7-figure in revenue agreement on successful data delivery. We now work with some of the biggest frontier AI labs and robotics companies in the world.\n\n**The ask**\n\nTwo asks: —> You're building frontier models or robots and data is your constraint. \\\n—> You're a top robotics engineer, a PhD whose research touches robotics or egocentric data, or someone with deep experience at a leading robotics lab, we're hiring. \\\n\\\nReach out here: [founders@hub.xyz](mailto:founders@hub.xyz).", "url": "https://www.ycombinator.com/launches/Qoe-hub-real-world-training-data-for-frontier-ai-labs-and-robotics", "votes": 1, "created_at": "2026-06-15T14:57:21.570Z" } ] }, { "id": 31419, "name": "StableBrowse", "slug": "stablebrowse", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ed9bc479aa95e772450f53b3ce34a581c2a1e4b7.png", "website": "https://stablebrowse.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "Building the Data Infrastructure layer for Physical AI. ", "team_size": 3, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1774843315, "tags": [ "Robotics", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 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/stablebrowse", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2026/stablebrowse.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/stablebrowse/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/ed9bc479aa95e772450f53b3ce34a581c2a1e4b7.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": 1022491, "full_name": "Deepit Shah", "title": "Founder/CEO", "founder_bio": "Founder @ StableBrowse | Ex-Amazon | UIUC - CS", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/deepit-shah/", "x_url": "https://x.com/deepitshah5", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f33bf28206493d6e6f6096a4ba197395c3295386.jpg" }, { "user_id": 1788727, "full_name": "Jay Mehta", "title": "Founder/CTO", "founder_bio": "StableBrowse | Ex-Amazon | Purdue CS", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jaymehta003", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2b4f29d89bb0329510b299a3749a8a2b49b50e88.jpg" }, { "user_id": 1853933, "full_name": "Somansh Shah", "title": "Founder/COO", "founder_bio": "buildling @StableBrowse | Ex-Amazon | Ex-Founding Eng", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/somanshshah", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/840cfefca7cfc1389c83e7ce0658b8c0588e1087.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 101987, "title": "StableBrowse - Browser Layer For AI Agents", "tagline": "We enable agents to navigate the web with 70% fewer tokens and 4x faster execution.", "body": "**TL;DR**: StableBrowse is the browser layer for AI agents. We transform dynamic websites into structured knowledge graphs that capture how sites truly work, giving agents persistent memory to complete tasks reliably without starting from scratch every time.\n\n**Ask**: If you’re building agents that browse the web, scrape data, fill forms, monitor prices, or work inside authenticated portals, we’d love to talk! Reach us at [team@stablebrowse.ai](mailto:team@stablebrowse.ai) or schedule a demo at [stablebrowse.com](http://stablebrowse.com).\n\n\n\n**Problem**: AI agents are increasingly being used for real web workflows like tracking competitor pricing, applying for loans, updating CRM records, booking travel, submitting expense reports, and navigating legacy enterprise systems.\n\nMost browser agents still treat every interaction like it’s the first time, repeatedly asking an LLM what to click next. This works in demos, but breaks in production because websites constantly change through:\n\n* Pop-ups and modal interruptions\n* Login and authentication flows\n* Slow-loading dropdowns and forms\n* Layout and UI updates\n* Dynamic page behavior\n\nAs a result, agents become unreliable, expensive to run, and difficult to scale across real-world workflows.\n\n**Solution**: StableBrowse gives AI agents persistent memory of how websites actually work by converting websites into structured execution graphs. Instead of rediscovering workflows every run, StableBrowse learns websites once and reuses that knowledge across future executions.\n\nWe convert pages into structured states, turn buttons and forms into reliable actions, extract clean structured data instead of raw HTML, and detect when websites change to keep workflows reliable over time.\n\nAt runtime, StableBrowse handles:\n\n* Navigating known workflows\n* Filling forms and completing submissions\n* Extracting clean, structured data\n* Handling date pickers and dropdowns\n* Detecting when websites change\n* Returning usable outputs instead of raw HTML\n\nThis allows the LLM to focus on user intent instead of fragile browser interactions. The results are dramatic: 70–80% lower token usage, 3–4× faster workflows, and up to 98% success rate.\n\n![uploaded image](/media/?type=post&id=101987&key=user_uploads/1853933/3903c45b-f3a3-4e2d-84dd-f2bb28a9eaf2)\n\n\\\n**Background**: We started StableBrowse after running into these same frustrations ourselves while building browser agents. Our team brings experience from Amazon (agentic commerce), AWS EC2 Nitro, applied AI research, and multiple fast-growing startups.\n\n![uploaded image](/media/?type=post&id=101987&key=user_uploads/1853933/6d012d9d-28ba-49a0-98f2-bcc1e03b979d)\n\n", "url": "https://www.ycombinator.com/launches/QWx-stablebrowse-browser-layer-for-ai-agents", "votes": 37, "created_at": "2026-05-26T19:48:52.452Z" } ] }, { "id": 31456, "name": "General Instinct", "slug": "general-instinct", "former_names": [ "Bitstream" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/e506831e9805799a19c0fa94ac85f0578ee4374e.png", "website": "https://general-instinct.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Making robot post-training and deployment scalable.", "one_liner": "Deployment infrastructure for Physical AI", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1779088548, "tags": [ "Robotics", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2026", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/general-instinct", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2026/general-instinct.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/general-instinct/", "x_url": "https://x.com/gen_Instinct", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/e506831e9805799a19c0fa94ac85f0578ee4374e.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": 2022270, "full_name": "Bill Jiao", "title": "Founder/CEO", "founder_bio": "worked on Siemens' first multimodal foundation model, secured 2 patents on tardigrade proteins as a junior in high school, now building edge intelligence for physical AI.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/zhandong-jiao", "x_url": "https://x.com/BillJiao930", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/524ded9c0f2c5c51662b75aa35a6b47d0230b153.jpg" }, { "user_id": 2697564, "full_name": "Guanming Wang", "title": "Founder/CTO", "founder_bio": "Ex Google DeepMind reinforcement learning researcher with robotics research published at ICRA at age 17. Previously conducted robotics research at UCL robotics institute and Tsinghua University.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/guanming-wang", "x_url": "https://x.com/Guanming717", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/229264e545e631dc6b28622345796c47929eedd6.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 101508, "title": "General Instinct - The deployment layer for physical intelligence", "tagline": "Deploy frontier AI models onto constrained edge hardware for robots, drones, and physical AI systems.", "body": "# \\*\\*\\*\\*\n\n**TL;DR**: General Instinct distill, quantize, and deploy large frontier AI onto limited hardware on drones, old PCs, and robots.\n\n![uploaded image](/media/?type=post&id=101508&key=user_uploads/2022270/81b34033-67b0-41d9-9f7a-563ed2884da3)\n\n**Problem**:\n\nPhysical AI (robots, drones, IoT) teams can now get frontier models to do impressive things in the lab. The hard part is getting those models to work reliably in production.\n\nSome common patterns:\n\n1\\. Models works well in the cloud, but fails on edge in production.\n\n2\\. Custom use-cases like robots operating in the wild or in space requires on device inference.\n\n3\\. Using Gemini for everything is simply too expensive.\n\nWe built a custom, no code pipeline to solve this problem.\n\n**What we’re building:**\n\nOur first product: **Instinct Edge**. Give us a model, a target device, and a latency budget. We return an offline runtime that hits the budget on hardware like Jetson, mobile NPUs, ARM CPUs, Apple Neural Engine, and Snapdragons.\n\nUnder the hood, this combines compression recipes, custom CUDA / Metal / ARM NEON kernels, and a continuous data-to-serving pipeline.\n\nOne production example: a multimodal classifier on Jetson Orin NX with 111 ms cold start, 100% of decisions inside a 150 ms budget, and zero cloud calls.\n\n**How you can help**:\n\nIf you or anyone you know are running large vision models on edge and are having problems fitting them onto your hardware, let us know by emailing [founders@general-instinct.com](mailto:founders@general-instinct.com)!\n\n", "url": "https://www.ycombinator.com/launches/QPE-general-instinct-the-deployment-layer-for-physical-intelligence", "votes": 10, "created_at": "2026-05-19T06:17:38.703Z" } ] }, { "id": 31486, "name": "Ornadyne", "slug": "ornadyne", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/a1b22be817e9ad2d1f4b3a606e7b94d10bc6a8d6.png", "website": "https://ornadyne.com/", "all_locations": "Los Angeles, CA, USA", "long_description": "Ornadyne builds flapping-wing drones for reconnaissance that look, fly, and sound like birds.\r\n\r\nToday’s drones are easy to detect acoustically, visually, and electronically. As counter-UAS systems improve, traditional quadcopters and fixed-wing UAS systems are becoming increasingly ineffective for close-range surveillance. \r\n\r\nFlapping-wing aircraft have existed for years, but have lacked the performance, endurance, and control required for real-world deployment. We’re changing that by engineering a high-performance, stealth-optimized system built from first principles for efficiency, autonomy, and reliable field use.\r\n\r\nThe final frontier of surveillance won’t look like machines; it will look like wildlife already in the sky. \r\n\r\nMaybe birds aren't real?", "one_liner": "We're building robot birds for surveillance.", "team_size": 4, "industry": "Industrials", "subindustry": "Industrials -> Drones", "launched_at": 1777342640, "tags": [ "Hard Tech", "Robotics", "Drones", "Aerospace", "Defense" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Spring 2026", "status": "Active", "industries": [ "Industrials", "Drones" ], "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/ornadyne", "api": "https://devasheeshg.github.io/yc-api/batches/spring-2026/ornadyne.json", "year_founded": 2026, "city": "Los Angeles", "country": "US", "linkedin_url": "https://www.linkedin.com/company/ornadyne/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/a1b22be817e9ad2d1f4b3a606e7b94d10bc6a8d6.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": 1504179, "full_name": "Geourg Kivijian", "title": "Founder/CEO", "founder_bio": "Co-founder & CEO of Ornadyne. Award-winning engineer (IEEE/AIAA) recognized for pioneering work in flapping-wing robotics. Previously led coordination systems for Mars Sample Return at NASA's Jet Propulsion Laboratory and lunar rovers at Astrolab. Now scaling Ornadyne to bring bio-inspired stealth and efficiency to the next generation of flight. www.geourgkivijian.com", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/geourg-kivijian/", "x_url": "https://x.com/geourgkivijian", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e337453d3b319353220202f1fe100ab8ce774327.jpg" }, { "user_id": 3374971, "full_name": "Armen Arakelyan", "title": "Founder/CTO", "founder_bio": "Co-founder & CTO at Ornadyne, building autonomous flapping-wing aircraft. Previously a Starship components engineer at SpaceX. Before that, I led machining at USC Rocket Propulsion Laboratory at the University of Southern California, helping the team set the amateur rocketry altitude world record at 144 km.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/armen-arakelyan-171b71219/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2145da603ff13a23eff254476a2594ae5eed387b.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 100617, "title": "Ornadyne - Robot Birds for Reconnaissance", "tagline": "Autonomous bird-like drones for military reconnaissance.", "body": "**TL;DR:** Ornadyne is building robot birds for surveillance: drones with cameras for the military that look, fly, and sound like real birds**🦅**\n\n### The Problem(s):\n\nTraditional drones have two main problems:\n\n1. Propellers are **loud**\n2. They don’t blend in; they’re **visually obvious**\n\nThis makes traditional fixed-wing and quadcopter drones extremely detectable, and inadvertently easy to shoot down and run away from.\n\n\n\n---\n\nThis isn’t new. The U.S. used to lead flapping-wing flight, but **today, Europe and China are far ahead. Ornadyne is bringing the U.S. back into the lead.**\n\nWe're building autonomous ornithopters with hour-class flight times, low acoustic signatures, and natural bird-like flight. This makes Ornadyne's drones harder for humans and counter-UAS systems to detect, classify, and target.\n\n![uploaded image](/media/?type=post&id=100617&key=user_uploads/1504179/a361939c-74a4-427b-a2ef-a96f6cdc2884)\n\n---\n\n### The Founders:\n\n**Geourg’s** Master's thesis is built on 2+ years of research and development in flapping-wing drones. His work has received multiple awards through AIAA and IEEE conference publications. He is ex- NASA JPL, and ex-Astrolab, where he worked on Mars and lunar missions.\n\n**Armen** engineered Starship components at SpaceX and previously led machining at USC Rocket Propulsion Laboratory, helping the team set the amateur rocketry altitude world record at 144 km.\n\nBoth founders have been best friends since middle school.\n\n![uploaded image](/media/?type=post&id=100617&key=user_uploads/1504179/60143f25-5da7-45dd-93a0-0be77f9c5b45)\n\n### Ask:\n\nIf you work in defense tech or are building in the space, we’d love to connect. Introductions to anyone who might be interested in working with us would be much appreciated.", "url": "https://www.ycombinator.com/launches/QAr-ornadyne-robot-birds-for-reconnaissance", "votes": 30, "created_at": "2026-05-01T00:54:15.289Z" } ] }, { "id": 31509, "name": "Rodeo Robotics", "slug": "rodeo-robotics", "former_names": [ "Lasso (temporary, naming conflict exists)", "Lasso" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ed94f83ed341c4f879d7c08c2570c04ba145e07c.png", "website": "https://www.rodeorobotics.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Rodeo builds a robotic technician that automates maintenance so fleets can get vehicles back on the road sooner. Initial deployments focus on oil changes at centralized depots, where routine maintenance competes for scarce technician time.\r\n\r\nCofounders Michael Hazard and Colby Duke met at Applied Intuition, where they worked with OEMs like Toyota and General Motors to bring software and autonomy to vehicles. They saw firsthand how much manual work it takes to keep vehicle fleets running, and learned how to make autonomy reliable through structured testing, real-world data, and human intervention.\r\n\r\nThey’re now applying their experience to the roughly $600B annual US vehicle maintenance market. The average US vehicle is older than ever, driving up maintenance demand at a time when shops already struggle to hire and retain technicians. That gap leaves fleets facing costly downtime and preventable breakdowns.\r\n\r\nDespite this need, vehicle maintenance has resisted traditional automation. Service information is fragmented and unreliable, and vehicle hardware varies significantly between makes and models. Rodeo builds on advances in robotic foundation models to learn maintenance skills that transfer across vehicles.\r\n\r\nRodeo pairs robots with human technicians who ensure each job is completed correctly, handling work the robots can’t yet perform autonomously. These deployments generate training data for Rodeo’s models through both teleoperation and hand tools augmented to record how technicians work. This lets Rodeo earn revenue while collecting the data needed to automate more of each job and improve margins.", "one_liner": "Robots for vehicle maintenance.", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1791737469, "tags": [ "Hard Tech", "Robotics", "AI", "Automotive" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2026", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/rodeo-robotics", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/rodeo-robotics.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/ed94f83ed341c4f879d7c08c2570c04ba145e07c.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": 1723748, "full_name": "Michael Hazard", "title": "Founder/CEO", "founder_bio": "Building robots for vehicle maintenance. Four years at Applied Intuition bringing software and autonomy to vehicles. Google APM. Stanford CS.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/michael-hazard", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1236858457295e3981b938e3e2d34b656f23c372.jpg" }, { "user_id": 2583456, "full_name": "Colby Duke", "title": "Founder/CTO", "founder_bio": "Building robots for vehicle maintenance. Previously the tech lead of Applied Intuition's neural simulation team.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/colby-duke/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/64bba9bf9ad1bada6772cc26492eff670a931e2f.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 31569, "name": "Proprio Robotics", "slug": "proprio-robotics", "former_names": [ "Proprio" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3aeac99898de10d679342b3768b7bc6047f56469.png", "website": "https://www.propriorobotics.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Proprio Robotics is building state-of-the-art physical intelligence to automate the entire data center lifecycle—from buildout to maintenance to decommissioning. There are currently 400,000 unstaffed data center technicians positions in the United States alone, which means the massive compute needs of AI are being bottlenecked by labor constraints. Proprio is solving this by building robots that do it instead, and is deploying data center maintenance robots starting Q1 2027. ", "one_liner": "Robots to maintain and assemble data centers", "team_size": 1, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1784630562, "tags": [ "Robotics", "AI" ], "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/proprio-robotics", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/proprio-robotics.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/proprio-robotics", "x_url": "https://x.com/ProprioRobotics", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/3aeac99898de10d679342b3768b7bc6047f56469.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": 2910355, "full_name": "Anirudh Pai", "title": "Founder/CEO", "founder_bio": "Founder, CEO of Proprio\nEECS M.S @ U.C Berkeley BAIR\nComputer Vision & Dexterous Robotic Manipulation", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/apai25", "x_url": "https://x.com/apai253", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d7ea9eb84630296f5984aa38b7f2f590f6b9f920.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 106864, "title": "Proprio Robotics - Autonomous Data Centers", "tagline": "Autonomous robots to build, maintain, and decommission data centers.", "body": "\n![uploaded image](/media/?type=post&id=106864&key=user_uploads/2910355/e9094f01-f5e9-4c30-93c6-81d8f041957d)\n\n### **Physical AI for Data Centers**\n\nOver the next five years, more than $7 trillion is projected to flow into data center buildout. But the supply chain is still heavily manual and fragmented, and can’t keep pace with current demand. **Proprio Robotics** is building autonomous robots for the entire data center lifecycle—assembly, maintenance, and decommissioning.\n\nSee our [launch video!](https://www.youtube.com/watch?v=999uFeKGyVY)\n\n### **The Problem**\n\nBuilding and running AI compute infrastructure requires dealing with delicate and fragile components that traditional automation simply cannot do. As a result, servers are manually assembled by hand overseas, and spend weeks in transit before they are integrated into racks and delivered to data centers. Once they get there, labor constraints exacerbate the issue of maintenance. Today, hundreds of thousands of technician positions go unfilled in the United States. Finally, when the servers are retired, there is no efficient way to extract valuable components inside like GPUs and memory.\n\n### **What We're Building**\n\nWe develop physical AI models and custom hardware, purpose-made to give robots the dexterity and intelligence to perform various server-related manipulation tasks.\n\n* **Assembly** **-** Autonomous robots can assemble servers onshore without driving up labor costs, supporting the growing need to bring ODMs back to the United States.\n* **Maintenance** **-** We use the same technology for live data center maintenance. We built a working AI data center in our office, and our robot can actively maintain it 24/7. We’re deploying this technology to commercial data centers in the coming months.\n* **Decommissioning** **-** Our robots also break down previous-generation servers and pull out reusable parts, and we're working with enterprise circular programs and IT Asset Disposition companies to return scarce components to circulation.\n\n### **Why This Matters**\n\nThe immense demand for compute requires new innovation. \n\nTo solve power and cooling constraints, operators are building data centers away from the grid, near nuclear facilities, on the water, and in space—environments where it’s not easy to staff humans. With autonomous data centers, we can take human ergonomics and labor constraints out of the picture and redesign entire facilities from scratch.                    \n\n### **Who We Are**\n\nWe're graduate robotics researchers out of **Berkeley AI Research** and **Harvard AI and Robotics Lab**. Anirudh’s spent years working at one of the country's leading robotics labs, training dexterous manipulation models alongside NVIDIA's GR00T team. Raghav’s led research centered on reinforcement learning and humanoid world models. Both of us are extremely excited to bring this expertise to the AI compute industry, where robotic automation will be indispensable for meeting demand.\n\n### **Our Ask**\n\nAs we advance our technology, we’d like to push for more commercial deployments. If you / anybody you know works in any stage of the AI compute lifecycle, we’d love to chat. Reach out to us at [founders@propriorobotics.com](mailto:founders@propriorobotics.com) :)", "url": "https://www.ycombinator.com/launches/Rnc-proprio-robotics-autonomous-data-centers", "votes": 9, "created_at": "2026-07-22T17:09:29.434Z" } ] }, { "id": 31582, "name": "Edgerun", "slug": "edgerun", "former_names": [ "Edgerun Industries" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/8fb84bc8b7f8d02b776dec7685bbaf102fdadf1c.png", "website": "https://edgerun.com", "all_locations": "San Francisco, CA, USA", "long_description": "Edgerun builds military exoskeletons. The first product is a 10-pound hip system that fits over existing kit and doubles a soldier’s range. Since April 2026, Edgerun built over a dozen iterations of their product through continuous field tests with Ukrainian fighters and secured $150M+ in LOIs. Founder David Venegas previously co-founded Durin (autonomous mining robotics) and worked at Stoke Space (at 19) and Hadrian. He is a high-school dropout, state-championship runner, adventure athlete, and pilot. Edgerun is a Y Combinator company backed by General H.R. McMaster, Cyan Banister, Joshua Steinman and Jason Miller. edgerun.com", "one_liner": "Military exoskeletons", "team_size": 5, "industry": "Industrials", "subindustry": "Industrials -> Defense", "launched_at": 1787343759, "tags": [ "Hard Tech", "Hardware", "Robotics", "Defense" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "Industrials", "Defense" ], "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/edgerun", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/edgerun.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/edgerun", "x_url": "https://x.com/edgerun_inc", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/edgerun-industries", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/8fb84bc8b7f8d02b776dec7685bbaf102fdadf1c.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": 1393855, "full_name": "David Venegas", "title": "Founder/CEO", "founder_bio": "Founder of Edgerun, pro-human expansionist, state-championship runner, adventure athlete, and pilot.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/david-venegas-m/", "x_url": "https://x.com/davidvenegas", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c10fbaaf669d694298a5fa036ff23e69baf933f4.jpg" } ], "jobs": [ { "id": 109346, "title": "Principal Engineer, Embedded Systems", "url": "https://www.ycombinator.com/companies/edgerun/jobs/6Pn7CiI-principal-engineer-embedded-systems", "location": "Palo Alto, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Embedded systems", "salary_range": "$220 - $325", "equity_range": "0.75% - 2.00%", "experience": "11+ years", "visa": "US citizen/visa only", "skills": [ "C++", "Firmware" ] }, { "id": 109347, "title": "Mechanical Engineer", "url": "https://www.ycombinator.com/companies/edgerun/jobs/ugTXhoh-mechanical-engineer", "location": "Palo Alto, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Mechanical", "salary_range": "$120 - $180", "equity_range": "0.25% - 0.75%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "CAD Design", "Design systems" ] }, { "id": 109348, "title": "Electrical Engineer", "url": "https://www.ycombinator.com/companies/edgerun/jobs/6YuWGTT-electrical-engineer", "location": "Palo Alto, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Electrical", "salary_range": "$120 - $180", "equity_range": "0.25% - 0.75%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "PCB design" ] }, { "id": 109349, "title": "Firmware Engineer", "url": "https://www.ycombinator.com/companies/edgerun/jobs/0LmpEaM-firmware-engineer", "location": "Palo Alto, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Embedded systems", "salary_range": "$140 - $190", "equity_range": "0.25% - 0.75%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "C++", "Firmware" ] }, { "id": 109350, "title": "Software Engineer", "url": "https://www.ycombinator.com/companies/edgerun/jobs/U3cSW0r-software-engineer", "location": "Palo Alto, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$150 - $200", "equity_range": "0.25% - 0.75%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [ "Amazon Web Services (AWS)", "C", "C++", "Python", "Data Warehousing", "Data Analytics" ] }, { "id": 110829, "title": "Supply Chain Engineer", "url": "https://www.ycombinator.com/companies/edgerun/jobs/Ecz1f6N-supply-chain-engineer", "location": "Palo Alto, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Hardware", "salary_range": "$110 - $160", "equity_range": "0.25% - 0.75%", "experience": "3+ years", "visa": "US citizen/visa only", "skills": [] } ], "news": [], "launches": [ { "id": 112214, "title": "Edgerun: The 10 lb Military Exoskeleton", "tagline": "Powered exoskeleton that assists every step a soldier takes under combat load", "body": "**TL;DR:** Edgerun builds powered legs for soldiers. A 10 lb exoskeleton worn at the waist that adds assistance to every step and cuts the effort of moving under a combat load by 30-45%. Since May, we've run 100+ field tests with Ukrainian operators out of our Kyiv field office.\n\n\n\n**▍The problem**\n\nEvery system on the modern battlefield has been upgraded. The human carrying it has not.\n\n* For 2,500 years the soldier's load sat around 40 lbs. In the last 40 years it **doubled, then doubled again**.\n* A US infantryman now carries **90-140 lbs** into a fight. The Army's own field manual sets the limit at 48 lbs.\n* On deployment, load carriage causes **twice as many** evacuations as enemy contact.\n* The Pentagon and VA spend **$9.3B a year** on the injuries it leaves behind.\n\nBattles are won through speed and surprise. Load kills both.\n\n**▍Why now**\n\nSixty years of military exoskeletons died the same death. The device cost more to carry than it gave back. SOCOM's TALOS burned $400M before it was cancelled in 2019.\n\nThat all changed in the last 18 months. The humanoid robotics boom produced one-pound actuators that put out 30+ Nm of torque, and 21700 cells crossed 450 Wh/kg. The components finally exist. They’re getting better every quarter.\n\n![uploaded image](/media/?type=post&id=112214&key=user_uploads/1393855/cd255b24-3429-4270-9670-e28fc8df360b)\n\n**▍What we built**\n\nOur first exoskeleton is a bilateral hip system worn at the waist. It reads your gait in real time and adds torque at the moment your hip drives forward. The hip produces about 60% of the force in loaded walking, so assisting it gives the most help-per-pound of anything you could strap to the body.\n\n* Under 10 lbs with batteries\n* 30-45% less metabolic cost under a combat load\n* On in 5 seconds, off in one\n* 12+ hours on hot-swappable drone-class batteries\n* Quasi-direct-drive actuators, composite structures, CAN bus. Nothing exotic by design.\n\nThe soldier arrives at the objective still able to fight, patrols 10 km farther, and keeps a body that lasts past one tour.\n\n![uploaded image](/media/?type=post&id=112214&key=user_uploads/1393855/94bf48a9-0ba6-4ce7-94a2-f467cae9657c)\n\n![uploaded image](/media/?type=post&id=112214&key=user_uploads/1393855/883d1e98-900a-420a-b7ff-e56cc8911c0c)\n\n**▍Ukraine**\n\nOur field engineers work out of a Kyiv office, alongside operators from infantry, special operations, and National Guard units who provide structured feedback every day. [Balistyka](https://balistyka.ua/), one of Ukraine's leading body armor makers, is an integration partner, helping us ensure our system fits the kit soldiers already wear.\n\n![uploaded image](/media/?type=post&id=112214&key=user_uploads/1393855/89a30d39-fe11-421c-abe7-32961da8d1bd)\n\n**▍The mission**\n\nDefense is the first customer, not the last. Read the mission at edgerun.com/mission", "url": "https://www.ycombinator.com/launches/TBu-edgerun-the-10-lb-military-exoskeleton", "votes": 7, "created_at": "2026-08-25T16:19:00.453Z" } ] }, { "id": 32128, "name": "Mass Magnetics", "slug": "mass-magnetics", "former_names": [ "Mass Energy Company" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/26161cef0e683292e39a5da2d6258b38702473a0.png", "website": "https://massmagnetics.com/", "all_locations": "Boston, MA, USA", "long_description": "Mass Magnetics turns recycled rare-earth scrap into high-performance permanent magnets, made in America. The materials we supply are the backbone of electric motors, sensors, speakers, hard drives, and electronics.\r\nOur process enables DFARS-compliant magnets for defense, aerospace, and industrial manufacturers who demand domestic supply without compromising on quality.\r\nOperations in Greater Boston, MA (Greentown Labs) and Columbus, IN.", "one_liner": "USA-made magnetics for robotics and defense. ", "team_size": 3, "industry": "Industrials", "subindustry": "Industrials -> Defense", "launched_at": 1786735839, "tags": [ "Hard Tech", "Robotics", "Drones", "Manufacturing", "Defense" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "Industrials", "Defense" ], "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/mass-magnetics", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/mass-magnetics.json", "year_founded": 2026, "city": "Boston", "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/26161cef0e683292e39a5da2d6258b38702473a0.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Vivian Midha Shen", "url": "https://www.ycombinator.com/people/vivian-midha%20shen" }, "founders": [ { "user_id": 3652354, "full_name": "Eric Silver", "title": "Founder/CEO", "founder_bio": "Founder at Mass Magnetics. Worked in pilot cathode production for lithium-sulfur battery chemistries. Now I'm fixing American magnet supply chains. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/energyeric/", "x_url": "https://x.com/2998x10tothe8", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c8160b42bdee61a0dff0fef65dd723b8cae326e3.jpg" }, { "user_id": 3637161, "full_name": "Matthew Groll", "title": "Founder/CTO", "founder_bio": "Co-founder and CTO at Mass Magnetics. Former NASA/Columbia/MIT. Previously worked on thermal systems and guidance/navigation at NASA Johnson Space Center for ISS and Artemis lunar missions. Also previously worked as a Member of Technical Staff at Draper Laboratory. Studied Mechanical Engineering at Columbia, captaining the Formula SAE team and Robotics Club, then earned a Masters in Manufacturing from MIT.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/matthew-groll/", "x_url": "https://x.com/matthewxgroll", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/68e632830dda51ab14dec0fac18967c93ed5c8ed.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 110611, "title": "Mass Magnetics: USA-made magnets", "tagline": "Vertically integrated magnet manufacturing for aerospace, robotics and defense.", "body": "### **TL:DR; Mass Magnetics makes American magnets in minutes.**\n\n🧲🧲🧲🧲🧲🧲🧲🧲🧲🧲🧲🧲🧲🧲🧲🧲🧲🧲🧲🧲🧲🧲🧲🧲🧲🧲\n\n![uploaded image](/media/?type=post&id=110611&key=user_uploads/3652354/be41c9e5-378d-452f-a111-10380035f14d)\n\n**Every electric motor runs on rare-earth magnets.** EVs, drones, robots, wind turbines, guided munitions: nearly all of them are dependent on Chinese magnets. On January 1st, 20270, [regulation changes will make it illegal to deliver anything that walks, drives, or flies to US Defense if it contains a magnet produced in covered countries like China.](https://www.massmagnetics.com/comply) The domestic supply chain meant to replace it doesn't exist yet. **Mines take a decade to permit, and the ore they pull up leaves radioactive tailings behind, making permitting magnet mining a nightmare.**\n\nWe’re[ ](https://www.linkedin.com/in/energyeric)the founders, [Eric Silver](https://x.com/metalscontent) and [Matthew Grol](https://www.linkedin.com/in/matthew-groll/)l (left and right in the pic below). We’ve known each other since grade school. Since then, Eric’s built multiple battery pilot production lines and materials science labs in the Midwest for NSF-funded companies. Matthew’s built exquisite aerospace gear including Moon-regolith melters and ultra-precise guidance systems for the world’s foremost labs at NASA, Draper, and MIT. **Together we’re making one bet: America's rare-earth problem isn't a mining problem.**\n\n![uploaded image](/media/?type=post&id=110611&key=user_uploads/3652354/2046e9de-2db6-47e8-91fc-651e31e5a834)\n\n**Mass Magnetics’ unfair advantage is sitting in end-of-life electric vehicles, hard drives, and industrial equipment.** The team uses AI models and robotics trained on real scrap to sort metallurgy by exact grade and chemistry. Then, a rapid-sintering process takes that reclaimed mass to a finished magnet in 3 minutes, where conventional approaches take over 4 hours. The result is a magnet as strong as anything imported, with no radioactive footprint or bureaucratic permitting, fully compliant for US defense.\n\n**If you build robots, drones or motors visit our site and reach out at [outreach@massmagnetics.com](mailto:outreach@massmagnetics.com) and get your magnets.**\n\n![uploaded image](/media/?type=post&id=110611&key=user_uploads/3652354/797eff3c-6d9d-4ffc-894b-664aece1ba74)\n\n", "url": "https://www.ycombinator.com/launches/Sm3-mass-magnetics-usa-made-magnets", "votes": 7, "created_at": "2026-08-18T14:30:00.079Z" } ] }, { "id": 32156, "name": "Enact", "slug": "enact", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6f79f9bbc22f20d6e3465ca66081c4a646834064.png", "website": "https://enact.company", "all_locations": "San Francisco, CA, USA", "long_description": "Enact creates the physical environments to benchmark and hill climb robotics models on high-value tasks. We find where robots fail, and fix them with our in-house training loop.", "one_liner": "Real-world RL environments for robotics models", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1786311090, "tags": [ "Reinforcement Learning", "Robotics", "AI" ], "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/enact", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/enact.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/enact-company/?viewAsMember=true", "x_url": "https://x.com/enact_labs", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/6f79f9bbc22f20d6e3465ca66081c4a646834064.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Jon Xu", "url": "https://www.ycombinator.com/people/jon-xu" }, "founders": [ { "user_id": 2406199, "full_name": "James Stevens", "title": "Founder/CEO", "founder_bio": "Founder & CEO @ Enact", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/james-stevens-440362200", "x_url": "https://x.com/jamesw_stevens", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c605b46207ec2b29443db68751da93ca45c507c0.jpg" }, { "user_id": 3594727, "full_name": "Govind Chada", "title": "Founder/CTO", "founder_bio": "Founder at Enact. Previously: Robotics research in Chelsea Finn’s IRIS Lab at Stanford AI Lab, Meta Reality Labs.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/govind-chada", "x_url": "https://x.com/govindchada", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/bffdb6ffe1344f591c02771b2dceccd816fe305e.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 109880, "title": "Enact: post-training infrastructure for robotics models", "tagline": "Enact generates the data and evaluations needed to make robotics models reliable in the real world.", "body": "**TL;DR: Enact helps teams deploy robots that work in the real world. We roll out policies, generate failure / recovery data, and run in-house evaluations so robots can complete real tasks in production.** \n\n[**https://www.youtube.com/watch?v=dam0tQBIezY**](https://www.youtube.com/watch?v=dam0tQBIezY)\n\n**The Problem**\n\nRobotics models can look flawless in choreographed demos and still fail when an object slips, the scene shifts, or the robot makes an early mistake. Those failures push the policy into states its training data never taught it to recover from. **Robotics models must train on edge cases to be reliable in the real world.**\n\n**What We Built**\n\nEnact turns a policy’s failures into targeted recovery datasets for teams training robotics models. We use the data to fine-tune models and run real-world evaluations, verifying our data improves reliability.\n\n**We’re already serving our first customers: finding where their robots fail and collecting the targeted recovery data needed to make them robust.**\n\n* Roll out an existing model on a physical robot.\n* Identify recurring failure states.\n* Recreate those states and demonstrate how to recover.\n* Retrain with the new trajectories added in.\n* Repeat\n\n**Targeted recovery data pushes success rates above 99%.**\n\nOn our controlled packing task using pi0.5 on the YAM 6DoF arms:\n\n* 200 ordinary expert demonstrations: 90/100 successful physical rollouts\n* 250 ordinary expert demonstrations (more of the same data): 89/100\n* 200 expert demonstrations plus 50 targeted recovery demonstrations: 99/100\n\n![uploaded image](/media/?type=post&id=109880&key=user_uploads/2406199/e1b83c19-6e1d-4dda-adcf-258398bc1676)\n\n**We’re continuing to longer-horizon tasks such as industrial kitting, lab automation, and electronics recycling**\n\nLonger-horizon tasks need substantially more base and recovery data, but the loop is the same: find failures, target missing behaviors, retrain, repeat.\n\n**Who We Are**\n\nWe’re James Stevens and Govind Chada, and we met at Stanford. Govind researched real-world robot adaptation in Chelsea Finn’s IRIS Lab and co-developed recovery methods published at top robotics conferences. Together, we built Enact’s in-house data and evaluation operation and are already serving robotics teams. We started Enact to make robotics models work reliably outside the lab.\n\n**Our Ask**\n\nTraining a robot foundation model or deploying a policy that fails on a real task? Tell us the model, task, and where it breaks, and we’ll make it work.\n\nEmail: [founders@enact.company](mailto:founders@enact.company)", "url": "https://www.ycombinator.com/launches/SaG-enact-post-training-infrastructure-for-robotics-models", "votes": 16, "created_at": "2026-08-11T14:30:00.204Z" } ] }, { "id": 32168, "name": "Synapse Semiconductor", "slug": "synapse-semiconductor", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/37650fbbc73ea1ea0b895fd819e93836825d1520.png", "website": "https://synapsesemi.org", "all_locations": "Durham, NC, USA", "long_description": "We want to push machines to where humans cant go. \r\nPresidential early career award winning Duke Semiconductor ECE Faculty Tania Roy and Sanjeev Chauhan are building a frontier semiconductor research lab. Their focus is on solving physical AI challenges from the semiconductor device level and building products around the moat of impossible to copy innovation. Their first work is on a new vision sensor that can run neural network filters right in the camera pixels and only collect data that machines care about. As physical AI develops, machines needs to understand the world around them if they aim to interact with them.\r\n", "one_liner": "New semiconductors that merge compute and vision", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials", "launched_at": 1785109099, "tags": [ "Edge Computing Semiconductors", "Hard Tech", "Robotics", "Defense", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "Industrials" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/synapse-semiconductor", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/synapse-semiconductor.json", "year_founded": null, "city": "Durham", "country": "US", "linkedin_url": "https://www.linkedin.com/company/synapse-semiconductor/", "x_url": "https://x.com/SynapseSemi", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/37650fbbc73ea1ea0b895fd819e93836825d1520.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": 1383306, "full_name": "Sanjeev Chauhan", "title": "Founder/CEO", "founder_bio": "I like to break things and build things\n\n2 IEDM publications, 3 years Seed Stage VC, scaled deaplearning.com to 300k users, Stanford Linear Accelerator National Lab ML Researcher, IPAC 1st Author", "is_active": true, "linkedin_url": "https://linkedin.com/in/sanjeev-one", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ed6ba01db61837566ea4234d9d7ec34da6e0e4c1.jpg" }, { "user_id": 3682345, "full_name": "Tania Roy", "title": "Founder", "founder_bio": "Academic by profession, entrepreneur by nature. Love to control the user interface to reality.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/tania-roy-ba272b24/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/22e5f2656b361e2b88271fcd468b9cc08d0ba91f.jpg" } ], "jobs": [ { "id": 106484, "title": "Founding Engineer - RETINA", "url": "https://www.ycombinator.com/companies/synapse-semiconductor/jobs/T7HUC4J-founding-engineer-retina", "location": "San Francisco, CA, US / Durham, NC, US", "type": "Full-time", "role": "Engineering", "role_type": "Electrical", "salary_range": "$1M", "equity_range": "10.00%", "experience": "1+ years", "visa": "US citizen/visa only", "skills": [ "Verilog", "VHDL", "Computer Vision" ] } ], "news": [ { "title": "Duke ECE Hardware Startup Selected for Y Combinator | Duke Pratt School of Engineering", "url": "https://pratt.duke.edu/news/synapse-semiconductor-y-combinator/", "date": "Jun 08, 2026" } ], "launches": [ { "id": 107691, "title": "Synapse Semiconductor: We put a neural network inside the camera pixel.", "tagline": "Semiconductors to push machines where humans cant go.", "body": "\n\n**TLDR:** Synapse Semiconductor builds image sensors that process **AI on the sensor** itself. Each pixel captures light and runs neural-network computation in the same device, replacing the need for a GPU while cutting the power and latency of edge vision.\\\n\\\n\\\nA camera has no use by itself. Its value is only when its information gets evaluated. How can a camera that only has value when combined with a GPU support local intelligence? GPUs will get better, yet the fundamental problem is the separation of the camera and the GPU. Solving that separation will unlock bountiful innovation in machine perception. \n\n**RETINA: a chip designed like the human retina which runs neural network operations in the camera pixel.** \n\n\\\nWe have compressed the whole edge AI vision hardware stack into **one wafer**. CNNS, VLMS, etc can run on just one chip that senses light. Our compute transistors are also the same photosensors that see light. There is no longer separation between compute (Nvidia Jetson Nano) and a camera (RealSense Depth Camera). \\\n\\\nIf you are building robotic perception, drones, and vision systems for physical AI —> [book.synapsesemi.org](http://book.synapsesemi.org)\n\n![uploaded image](/media/?type=post&id=107691&key=user_uploads/1383306/bfa2012d-1c74-47b5-bdad-3127e94cd8bf)\n\n", "url": "https://www.ycombinator.com/launches/S0x-synapse-semiconductor-we-put-a-neural-network-inside-the-camera-pixel", "votes": 57, "created_at": "2026-07-27T03:40:58.979Z" } ] }, { "id": 32206, "name": "DeepReach Inc.", "slug": "deepreach-inc", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/165caaebecbd3f0b9470bb5817a0a1817520c935.png", "website": "http://www.deepreach.ai", "all_locations": "San Francisco, CA, USA", "long_description": "Physical AI — robots and world models — is bottlenecked on one thing: diverse,\r\nreal-world data at massive scale showing how humans actually do work in the\r\nphysical world. It was never written down, and you can't buy it, because no one\r\nhas ever captured it. Only real local experts, the people who do this work every\r\nday, can produce data this authentic and valuable.\r\n\r\nDeepReach builds the network that reaches them. We design and manufacture\r\nwearable stereo capture devices, then place them with local data partners who\r\nrun collection as their own business — in warehouses, workshops, farms, kitchens\r\nand repair shops. They own the local relationships; we supply the hardware, the\r\nsoftware platform, the quality pipeline and the payments. Anyone can run a data\r\nbusiness.\r\n\r\nThat structure is what produces diversity. Instead of thousands of hours inside\r\none environment, we deliver hours spread across thousands of environments —\r\nwhich is what actually makes robot policies generalize.\r\n\r\n475 devices in the field and 100+ data partners are live across 7 countries, adding new\r\npartners every week. They've collected nearly 150,000 clips in the past three\r\nmonths, with volume roughly doubling month over month. Our data is in production\r\nwith multiple frontier model and robotics companies, and we're scaling to\r\n10,000+ devices across 50 countries.", "one_liner": "Network for Physical AI Data Business", "team_size": 6, "industry": "B2B", "subindustry": "B2B", "launched_at": 1786563914, "tags": [ "Hardware", "Machine Learning", "Robotics", "Computer Vision", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "B2B" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": [ { "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": "Chris and I are from the same hometown and have known each other for ten years, long before either of us thought about robots.\r\n\r\nIn that time I built two companies around the same problem: how do you organize people you'll never meet, in places you'll never visit, to do consistent work? The first was HireIO, a cross-border staffing platform out of Silicon Valley. The second was Talex, an expert network for LLM data annotation — around 70,000 people across ten countries. Chris went the other direction: a CS PhD at USC in computer vision, ML infrastructure at Meta, then founding ML engineer at Aven.\r\n\r\nRunning an annotation network for language models, I kept hitting the same wall from the supply side. Text was running out, and the next generation of models wasn't going to learn from the internet. It was going to learn from the physical world — and nobody had captured it. What a warehouse picker, a line cook or a phone repair technician knows is real expertise, and none of it was ever written down. You can't buy that data, because it doesn't exist yet. Chris was hitting the same wall from the model side, watching what was missing from training sets.\r\n\r\nThe default answer at the time was to put a lab in one city and record thousands of hours in the same room. That produces volume, not diversity, and robot policies don't generalize from volume. What the models needed was the opposite shape: a few hours each from thousands of different real workplaces, all over the world. Which meant the bottleneck wasn't an AI problem. It was a distributed human network problem — reaching thousands of ordinary businesses across dozens of countries, and giving the people already working in them a reason to capture what they do. That was the problem I'd spent two companies learning to solve.\r\n\r\nWe started DeepReach in 2025. Chris owns perception and the data engine; I own the network, hardware operations and the commercial side. Ten years of knowing each other means we skipped most of the negotiation that takes co-founders their first year." }, { "question": "What is the core problem you are solving? Why is this a big problem? What made you decide to work on it?", "answer": "Core problem: robot models can't generalize, because the data they learn from all looks the same.\r\n\r\nPhysical AI needs to see how work actually happens — a mechanic torquing a bolt, a baker shaping dough, a technician opening a phone. None of it was ever written down. The internet captured what people say about the world; it never captured how people act in it. So unlike language models, this generation can't be trained on scraped text. Every hour has to be collected on purpose. \r\n\r\nToday the field has roughly tens of thousands of hours of this data against a need estimated in the hundreds of millions. But the gap isn't really a volume gap. It's a diversity gap. The standard approach is to build a lab, hire operators, and record for months in one controlled space. That yields thousands of hours that all look alike, and a policy trained on it fails the moment the lighting, the counter height, or the tool changes. Our customers' acceptance specs now reflect this directly: they cap how much of a delivery can come from any single environment type, and reject batches that are too concentrated. Diversity is the binding constraint, and it's now contractual.\r\n\r\nDiversity is hard for an economic reason, not a technical one. Collecting one hour each from a thousand real workplaces means negotiating access to a thousand real businesses — each with an owner who has no reason to let a stranger film their operation, in a country where you have no presence. That cost is why everyone else builds the lab instead. It's a distribution problem wearing an AI problem's clothes. \\\r\n\\\r\nThat's why we built the company as a network rather than an operation. The people who already work in those places, and already have the trust and the access, run collection as their own local business. We give them the hardware, the software and the payments. Access stops being something we buy and becomes something the network already has. \\\r\n\\\r\nI decided to work on this from the supply side. I'd spent two companies building cross-border human networks — a staffing platform, then a 70,000-person annotation network across ten countries — and kept watching demand arrive for data that no existing structure could produce. The bottleneck was never the model. It was that nobody had built the network that reaches the physical world." }, { "question": "What is your long-term vision? If you truly succeed, what will be different about the world?", "answer": "The long-term vision is a network that can reach any workplace on earth, and a record of how human work is actually done.\r\n\r\nConcretely: 10,000+ devices, 50 countries, one million commercial scenes, ten million task types. Every deployment adds to what we call the Human Skill Library — a permanent record of how people do physical work, built from the inside by the people who do it. Much of this knowledge exists nowhere else. It lives in the hands of a mechanic who has been doing the job for thirty years, and when he retires it's gone. Text and video on the internet captured what people say about work. Nobody has captured the work. \r\n\r\n\\\r\nIf we succeed, two things are different：\\\r\nFirst, robots stop being confined to the places that can afford to build around them. Today automation only pays at Amazon scale — a facility large enough to redesign itself for the machine. That's a rounding error of the world's actual workplaces. A policy trained on a million real environments doesn't need the environment to change; it works in a repair shop with bad lighting and a counter at the wrong height. That's the difference between robotics as a capability the largest companies buy and robotics as infrastructure a small business can use.\\\r\nSecond, the people whose work teaches these models are inside the economy that results. The last generation of AI was trained on data scraped from people who were never asked and never paid. This one has to be collected on purpose, from real workers in real workplaces, which means it can be built the other way — as something people opt into and earn from. We already have data partners in ten countries running this as a business they own. At 10,000 operators that isn't a side effect of how we source data. It's the point." } ], "url": "https://www.ycombinator.com/companies/deepreach-inc", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/deepreach-inc.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/in/timothyli-deepreach/", "x_url": "https://x.com/DeepReach_AI?s=20", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/deepreach-ai", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/165caaebecbd3f0b9470bb5817a0a1817520c935.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/482534d82410b1adf1774b961acd50c6704093e0.png" ], "primary_partner": { "name": "Brad Flora", "url": "https://www.ycombinator.com/people/brad-flora" }, "founders": [ { "user_id": 3114257, "full_name": "Chris Liu", "title": "Founder/CTO", "founder_bio": "Co-founder at DeepReach Inc. Founding MLE & tech lead of Aven scaling to #1 in DM volume in the US. Research Scientist at Meta working on core ML systems. PhD in computer vision from USC. B.S. from Peking University.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/drxcliu", "x_url": "https://x.com/drxcliu", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1f9e9212493e67c1bb9a3a913e2ab4c6fa9b897e.jpg" } ], "jobs": [ { "id": 112083, "title": "VP / Head of Global Data Partner Network & Operations", "url": "https://www.ycombinator.com/companies/deepreach-inc/jobs/r0itCEs-vp-head-of-global-data-partner-network-operations", "location": "San Jose, CA, US", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "$150K - $200K", "equity_range": "0.50% - 1.00%", "experience": "3+ years", "visa": "Will sponsor", "skills": [] } ], "news": [], "launches": [ { "id": 110389, "title": "DeepReach: Launch a real-world data business today", "tagline": "Multi-million-dollar contracts secured with frontier AI labs — and growing", "body": "**TL;DR:** DeepReach is a global data network that equips local entrepreneurs with wearable devices to capture the real-world operation data for Physical AI training. By decentralizing collections across thousands of entrepreneurs who have access to local businesses, they provide high-diversity training data that cannot be accessed elsewhere. DeepReach already signed multiple-million-dollar contracts with frontier AI labs.\\\n\\\n**DeepReach is building a global network for real-world human data to train Physical AI.**\n\nWe enable local entrepreneurs to operate data-collection businesses using our wearable capture devices, while we provide the hardware, software, QA, and customers.\n\nThe result is a distributed network that produces the diverse human demonstrations Physical AI labs cannot obtain anywhere else. Every new data partner expands the diversity and value of the network.\n\nIn just three months, DeepReach has helped **150+ entrepreneurs** build data businesses employing **1,000+ local experts** across **7 countries**. Together, they’ve collected **500,000+ real-world operation clips**, captured **150,000+ professional skill demonstrations**, and secured **several million dollars in customer contracts** with frontier AI labs and robotics companies.\n\n▶ **Watch how it works:** \n\n---\n\n# **The Problem**\n\nFrontier AI is already learning from the physical world.\n\nThe challenge is no longer collecting data, it’s collecting **diverse** real-world data at scale.\n\nMost companies solve this by building collection labs or hiring workers directly. Both approaches scale headcount, but neither scales access. The hardest part is reaching millions of real workplaces across different industries, countries, and working conditions.\n\nWithout that diversity, AI struggles to generalize beyond a small number of controlled environments.\n\n---\n\n# **What We Built**\n\nInstead of building another data collection company, **we built a platform where entrepreneurs launch independent real-world data businesses.**\n\nDeepReach provides the wearable devices, software platform, quality infrastructure, customer demand, operational support, and payments. **Entrepreneurs build and grow the businesses.**\n\nThey recruit local experts, develop trusted relationships with local businesses, and continuously expand into new industries, communities, and real-world environments.\n\n**Every new business expands the platform’s reach into the physical world, creating access to places, people, and skills that centralized data collection simply can’t reach.**\n\nThe result isn’t a larger workforce, it’s **a growing ecosystem of independent data businesses** that continuously expands the world’s supply of diverse real-world data for Physical AI.\n\n---\n\n# **Where We Are**\n\nIn just three months:\n\n* **150+ entrepreneurs** have launched data businesses on DeepReach\n* Those businesses now employ **1,000+ local experts** across **7 countries**\n* **500,000+ real-world operation clips** collected\n* **150,000+ professional skill demonstrations** captured\n* **Several million dollars in signed customer contracts** with frontier AI labs and robotics companies\n* Scaling toward **10,000+ devices** across **20 countries**\n\n# **Where This Goes**\n\nOur model is simple: labs list the tasks and environments they need, our entrepreneurs pick up the orders and go record them, and every delivery makes the network more capable of fulfilling the next one. It also compounds into something bigger, what we call the **Human Skill Library**: a growing record of how people interact with the physical world.\n\nMost of this knowledge has never been documented. It lives in the hands of experienced workers, passed down through practice rather than words, and it often disappears when they retire.\n\nOur vision is to preserve and scale humanity's physical knowledge, so every AI system can learn from the collective experience of human work.\n\n# **About Us**\n\n\\\nTim built HireIO into a leading global workforce company with 15 millions in annual revenue, then founded [Talex.ai](http://Talex.ai), an AI-powered expert network, before starting DeepReach. Chris comes from a computer vision background. We discovered the problem firsthand while labeling data for robotics startups: the real bottleneck wasn’t annotation, it was capturing diverse real-world human skills at scale.\n\n![uploaded image](/media/?type=post&id=110389&key=user_uploads/1294315/9bb8c293-ab57-42aa-b756-58562e546b78)\n\n---\n\n# **How You Can Help**\n\nIf you’re building frontier AI systems and need more diverse real-world data, we’d love to talk.\n\nIf you’re an entrepreneur interested in building a real-world data business, applications are open here: [www.deepreach.ai/join](https://www.deepreach.ai/join)\n\nTim Li\\\nFounder & CEO, DeepReach AI\n\n[**tim.li@deepreach.ai**](mailto:tim.li@deepreach.ai)", "url": "https://www.ycombinator.com/launches/SiT-deepreach-launch-a-real-world-data-business-today", "votes": 470, "created_at": "2026-08-13T18:33:15.556Z" } ] }, { "id": 32260, "name": "Manifold", "slug": "manifold-2", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/98f03122e41743439cec57f8152eac9cd506d714.png", "website": "https://www.manifoldindustries.ai/", "all_locations": "Los Angeles, CA, USA", "long_description": "The US Warehouse industry spends $75bn on labor each year. Yet, only 10% of US warehouses have any form of automation, because existing robotics are too expensive and hard to integrate. \r\n\r\nManifold deploys autonomous robots that handle picking, loading / unloading, and palletizing — priced by pick. Integration in hours. No upfront costs. No retrofitting. No need to rebuild the operation around the robot. \r\n\r\nOur mission is to make it easy for any warehouse to adopt robotics.", "one_liner": "Drop-in robotic labor that works on Day 1", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1784541343, "tags": [ "Hardware", "Warehouse Management Tech", "Robotics", "Logistics", "Supply Chain" ], "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": true, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/manifold-2", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/manifold-2.json", "year_founded": 2026, "city": "Los Angeles", "country": "US", "linkedin_url": "https://www.linkedin.com/company/manifoldindustries", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/98f03122e41743439cec57f8152eac9cd506d714.png", "app_video_url": "https://bookface-images.s3.us-west-2.amazonaws.com/bf-public_profile/32318/app_video.mp4?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAQC4NIECAOYE2QNZ5%2F20261020%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20261020T022739Z&X-Amz-Expires=60&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEHEaCXVzLXdlc3QtMiJIMEYCIQDZr7mht6VpZroejzIM4ovdqqWjmh9u8AZ4wJ%2BcxZeHaQIhAN0TyP1C5dfPpTpdf3vcwz%2B044IBUbnJ55rbsOHYRWQWKuUDCDoQABoMMDA2MjAxODExMDcyIgxycpAO09Mq3A1cvyQqwgN39qg2Ox70YWArW8Z19bx1LbIV2O3f8r7xSc%2BDpl3XtmT02s9DHm%2FdyEMimOoBk5McFrR%2FThfgO9h1Zcmt1NqN1y6d1lWIsDAdluAWIqXM089dX1KVjFmsSwg8hWS2%2F4ysZFTLuD5VBUHeANJPyfmRKN9Kb4JepbPSE01eipdz4aqPxRqz%2FVUJEYLUTh5YJM6jJKNzl5l2mnWSSFiFdUfT5OS16LHDCYH4PGt9WRY2iseRxMu7FZcICWM0P8aN14WLxKsu1H0yVxk8LS%2BNbXezGhQnkMsa3bf7aMNU7x4TSs7KyM01QgiCZxC01YV43U4O8vFENPThr%2FHtKaAvtZ0%2BXSTwUE691O8mG15thNVkorInjIhilxdazy%2BzEYcGsAMNZtfx0Bd5Xn43Xf7b%2Fie4vv0d0RCHqbCGLmxRHj5VG3Pdta5Kju3%2Fpb8n%2FKmRjY%2FtuIfi9oTYAjc4PVyikHTm8UXURiHmaM0tqXZjxyh0iIponEKehSmtjmjudiXLWICFBoPhEXeaUeyK2AT6btvH4fclsQa0qRmkxdgguiWvrYxLKhNNfPLTc5QA0jlPSRoDJ%2F%2BxNHLFrGusOX7IwU6hfRMw6P3a1gY6pAETos2BWzWJY973oh8s1gy0zFzSYQP7N%2B39nIjIA7I0ymOVnRNJktoZRF6GV9DH3ymBPT2fnMgKvEaFAqVR%2F0WVwXz3ixgSwFGrvlwPr39cuFnKBEcdnivQJOXkexjqUxi9alVn76GV8ONTXD1ZupAQeLYI09gLaaAmJlyJPRAUCybD64XlECdPqS2TV2e%2FZlA5duJD1GekpDGthoc0y8PIc1ahwA%3D%3D&X-Amz-SignedHeaders=host&X-Amz-Signature=42ea8e2882267580076ab7c55512b80c4f199c59a9ac3a17a1898ff3c4ae9bc2", "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Jon Xu", "url": "https://www.ycombinator.com/people/jon-xu" }, "founders": [ { "user_id": 3169788, "full_name": "Nicolas Yeh", "title": "Founder/CEO", "founder_bio": "Founder at Manifold. Grew up in a 3rd-gen supply chain family business (major consumer products supplier to US retailers). Previously at Balyasny Asset Management covering analog semiconductors ($1B+ book). Before that, Hotel Acquisitions at Starwood Capital Group, where he sourced a $60M hotel sale and was sole analyst responsible for asset management of Extended Stay America ($7.6B JV with Blackstone). BA from UPenn.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/nicolas-yeh/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2b04b9f9fd580701776cb120a1b47e822cd2f803.jpg" }, { "user_id": 3614218, "full_name": "Joshua Ibrahim", "title": "Founder/CTO", "founder_bio": "Founder at Manifold. PhD in Applied Mathematics from Caltech. Previously Software Engineering Intern at Facebook, working on Messenger P2P services and Instagram's misinformation detection systems. MS and BS in Electrical and Systems Engineering from Penn.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/joshibrahim/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2290e4ffd9df33d56490b230a84f5929381117ae.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 112000, "title": "Manifold - Robotic labor for the supply chain industry", "tagline": "Robotic labor for the supply chain industry", "body": "**What if you could hire a robot the same way you hire a temp worker?** \n\nNick grew up working in his family’s 3rd-generation distribution business, where he saw firsthand how much warehouses still depend on manual labor. The obvious answer should have been robotics, but for true labor replacement, existing robots were too expensive, inflexible, and difficult to deploy. As a result, most warehouses still say they’re “not ready” for automation.\n\nNick came together with his best friend Josh, a fellow UPenn alum and PhD at Caltech specializing in safety-critical control for robotics, to solve this problem.\n\nManifold is building robotic labor for the supply chain industry. Its robots perform picking jobs from start to finish faster than humans, with no upfront cost or infrastructure changes. Customers simply pay per pick, at a cost below human labor.\n\nThey’re already deploying robots to perform more than **5 million picks across multiple warehouses.**\n\nIf you’re a warehouse operator, reach out to [nick@manifoldindustries.ai](mailto:nick@manifoldindustries.ai)\n\n", "url": "https://www.ycombinator.com/launches/T8S-manifold-robotic-labor-for-the-supply-chain-industry", "votes": 4, "created_at": "2026-08-24T18:00:00.769Z" } ] }, { "id": 32518, "name": "Agency Tool Company", "slug": "agency-tool-company", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/244ddf9b0965c4c601170d71dd660ad1a89f8792.png", "website": "https://agencytool.com", "all_locations": "Denver, CO, USA", "long_description": "Agency Tool Company ships software to robots in the field 20x faster than a Docker pull with ATC Deploy, sending only the bytes that changed and resuming when the network drops. Deployment tooling is the connection between the lab & the field that continually bottlenecks robotics scaling and lacks a strong robotics-native solution. Deploy is live today with 3 launch partners across ag, construction, and logistics robotics.\r\n\r\nOur second product, ATC Build, offers embedded-compute as a CI service so devs can run tests and validate their software on the actual target hardware. Build supports the Nvidia Jetson lineup, Raspberry Pi, and a number of other embedded platform targets.\r\n\r\nJack Morrison and Davis Foster founded and sold Scythe Robotics after deploying hundreds of autonomous mowers across the country; Agency Tool Company is building the robotics deployment platform across hardware and software they wish they had.\r\n\r\nLearn more at https://agencytool.com", "one_liner": "Reliable infrastructure to build, deploy and manage real-world robots.", "team_size": 3, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1784914207, "tags": [ "Developer Tools", "Robotics", "Automation", "Infrastructure", "Self-Driving Vehicles" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/agency-tool-company", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/agency-tool-company.json", "year_founded": 2026, "city": "Denver", "country": "US", "linkedin_url": "https://www.linkedin.com/company/agency-tool-company", "x_url": "https://x.com/agencytoolco", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/244ddf9b0965c4c601170d71dd660ad1a89f8792.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Harshita Arora", "url": "https://www.ycombinator.com/people/harshita-arora" }, "founders": [ { "user_id": 3668961, "full_name": "Jack Morrison", "title": "Founder/CEO", "founder_bio": "Founder and CEO at Agency Tool Company. Previously founder/CEO at Scythe Robotics, building autonomous electric outdoor equipment from 2018-2026 and successfully exiting to ASI. Earlier co-founded Replica Labs (mobile 3D scanning) and worked as a computer vision engineer at Occipital on the Structure Sensor. BA Computer Science from Bowdoin.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/morrisonjack/", "x_url": "https://x.com/jackmorrison", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/13172ea12c502ccffb1824b2ef8e356abeabdfae.jpg" }, { "user_id": 253511, "full_name": "Davis Foster", "title": "Founder", "founder_bio": "Founder at Agency Tool Company - making it easier to scale robots. Previously co-founded Scythe Robotics ('18-26), made autonomous commercial mowers, acquired by ASI in 2026. Built and shipped hundreds of robots still operating across the country. Thiel Fellow.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/davisfoster", "x_url": "https://x.com/davistfoster", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3b4566280f9b3ba7c4ea23beb319e78fbf6db999.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 107934, "title": "Agency Tool Company: The build and deployment platform for robotics", "tagline": "Field Robots Faster with ATC Deploy", "body": "Today we're sharing Agency Tool Company and our first product, ATC Deploy: a faster, more reliable way to ship software to robots wherever they are. It moves updates up to 20 times faster than docker pull or scp and works with any software stack already in use.\n\n\n\n## The updates that took until 2 a.m.\n\nDavis and I spent eight years building Scythe Robotics and putting hundreds of autonomous mowers to work across the country. For years, we deployed software with a tool I'd cobbled together for our first few robots. As the fleet grew, deployment became an ordeal: engineers stayed up until 2 a.m., we coordinated with customers to move robots out of sheds and into LTE coverage at set times, and failed transfers restarted from zero. Shipping a fix could take more coordination than building it. We had models to train and customers to serve, so the tooling limped along with incremental bandaids.\n\nWe've since heard the same story from robotics teams across industries. That deployment becomes a hidden bottleneck: teams become release-averse, feedback loops slow and improvements stall. Stitched-together web and IoT tools barely work if you know which scripts to run and who to call, so they survive, even if it means every update is distracting from improving the product.\n\n## What we built\n\nATC Deploy ships whatever you already run: OS images, Docker images, or any file tree. Run “atc ota push user@robot”, and it sends only the changed bytes, then restarts your software through hooks you define—way faster than a docker push.\n\nInstall takes one “curl | sh” command and a config file so you can get back to work fast. Interrupted transfers resume where they stopped, and an offline robot can receive updates by USB if you need. There's no new runtime, packaging format, or operating system to adopt.\n\n## Shipping to robots today\n\nATC Deploy already ships software to robots at Burro, which has deployed more than 750 machines worldwide, Tempo, polishing concrete across several US states and Canada, and Gather, who is scaling their 99.9% accurate inventory drones nationwide. Their teams spend less time managing delivery and more time improving the robot.\n\n**Operate a robot fleet? Join the ATC Deploy waitlist at [agencytool.com](https://agencytool.com/).** Know a team that should be using it? Send them this post, or to [mailbox@agencytool.com](mailto:mailbox@agencytool.com).\n\nIt's time to build robots.\n\n![uploaded image](/media/?type=post&id=107934&key=user_uploads/253511/2f53d874-b652-4819-b734-bd52256958d8)\n\n", "url": "https://www.ycombinator.com/launches/S4s-agency-tool-company-the-build-and-deployment-platform-for-robotics", "votes": 6, "created_at": "2026-07-28T15:54:16.451Z" } ] }, { "id": 32552, "name": "6thSense", "slug": "6thsense", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/24cb943ce2196a35afe2b7d03f61eab2d4ec937a.png", "website": "https://6thsense.dev", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "Nervous System for Physical AI", "team_size": 4, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1782449364, "tags": [ "Robotics" ], "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/6thsense", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/6thsense.json", "year_founded": null, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/6thsenseai", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/24cb943ce2196a35afe2b7d03f61eab2d4ec937a.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/e4fdc2d7bcabc67030a4042e4ff79a3d9e187aea.png" ], "primary_partner": { "name": "Tyler Bosmeny", "url": "https://www.ycombinator.com/people/tyler-bosmeny" }, "founders": [ { "user_id": 3429291, "full_name": "James Baek", "title": "Founder/CEO", "founder_bio": "Founder & CEO at 6thSense. Founding member at Ibebu (Series C). Security Specialist, US Army (USFK). Exited a six figure content creation business and built numerous faceless brands. BME & Biochem at Georgia Tech. Growth Hacker\n", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/james-baek1/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1cb03c9cf75088d5d10002833f9baf36b05998c2.jpg" }, { "user_id": 1407900, "full_name": "Ronak Agarwal", "title": "Founder/CTO", "founder_bio": "Founder & CTO at 6thSense. ML at Amazon. Production infrastructure at DoorDash. Built autonomous drone delivery at Chick-fil-A. Built several startups before 6thSense, including Qard. Georgia Tech CS & Economics graduate (Intelligence + Modeling & Simulation); left a CS master's in Data Science & Systems Architecture. AI/ML & Systems Builder.", "is_active": true, "linkedin_url": "https://linkedin.com/in/ronak-agarwal9", "x_url": "https://x.com/ronakgt", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/338442a428cd26e2dd42028368b6924295dff73a.jpg" }, { "user_id": 3367434, "full_name": "Alex Hyungwoo Noh", "title": "Founder/COO", "founder_bio": "Founder at 6thSense. Bio/ML scholarship from Samsung at age of 17. UChicago CS/Econ. Ex-Army Recon. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/hyungwoonoh/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/f41a76394905402b8f244c67a750e1792d0e33dd.jpg" }, { "user_id": 2055952, "full_name": "Matt Wulff", "title": "Founder/CPO", "founder_bio": "Co-Founder of 6thSense (YC S26). Lead Vision Guided Robotics (ME) @Tesla at 20yo, Homeschooled, First Company at 16yo, Build Rockets for fun, Lead Tactile Data Capture at Mecka AI, Dreamer and adrenaline junky", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/makeitmatto/", "x_url": "https://x.com/makeitmatto", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/1fce472f4227cba7507f4caf1b2de54916ed016b.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 104007, "title": "6thSense — Giving Robots Touch", "tagline": "Giving Robots Touch", "body": "6thSense builds wearable tactile sensing rigs that capture how human hands interact with the world — pressure, contact, grip, and pose — across touch, vision, depth, force, and 3D hand pose, all in real environments. We sell that multimodal data to the companies training the next generation of dexterous robots.\\\n\\\n\n\nRobots are getting good at seeing. They're still terrible at touching. That's because there's almost no data capturing what a hand actually feels while doing real tasks in real homes. Lab data doesn't cut it. We go anywhere and capture the missing layer that manipulation models need to learn fine motor control.\n\nWhat makes our data different is the hardware we built to collect it. Our tactile sensing devices are designed and manufactured in-house, purpose-built to capture the richest touch signal in the industry — with scale in mind from the very beginning, enabling us to actually solve the tactile data problem. Every sensor maps directly to how robotic skin needs to work: a 1-to-1 analog for the tactile arrays going into the next generation of robot hands. That means the data we collect today doesn't just train better policies. It transfers directly to the hardware it's meant to run on. The team comes from Tesla, Mecka, Samsung, DoorDash, and Amazon, with expertise across hardware, sensors, ML, robotics, and software at scale. If you're training a manipulation policy or need custom tactile data, reach out.", "url": "https://www.ycombinator.com/launches/R3X-6thsense-giving-robots-touch", "votes": 7, "created_at": "2026-07-05T16:58:56.478Z" } ] }, { "id": 32553, "name": "Nori", "slug": "noril1", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/4b7cc06bfd9d08d6eae3bc20eca8c056f893bf8b.png", "website": "http://norirobotics.com", "all_locations": "San Francisco, CA, USA", "long_description": "We manufacture Nori: A sub-$2000 bimanual mobile manipulator that can clean rooms, restock shelves, and fold clothes. Nori can handle basic tasks out of the box, and its software lets anyone teach Nori to automate work specific to their home or business. \r\n\r\nNori aims to solve the robotics data bottleneck. By deploying affordable robots to customers around the world, we can gather the diverse data required to train the next generation of generalist robotic policies. Every user of Nori makes Nori smarter.\r\n\r\nSince launching 6 weeks ago we have already deployed our first robot and have over $440k+ in sales.\r\n\r\nWe can bring general-purpose robotics to homes and businesses that could never afford it before. There are 132.7 million households and 8.4 million employer business locations in the U.S. At $1,688 per robot, selling just one Nori to 0.5% of them represents a $1.2B market opportunity in the U.S. alone. ", "one_liner": "The most capable American-made humanoid robot for $1,688", "team_size": 5, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1783099451, "tags": [ "Hard Tech", "Hardware", "Robotics" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "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": [ { "question": "What is the core problem you are solving? Why is this a big problem? What made you decide to work on it?", "answer": "Robots are finally capable enough to be useful, but they're priced like cars, not appliances. A capable humanoid costs $20,000+, so general-purpose robots stay in labs and pilots instead of homes. \r\n\r\nIt's a big problem because household labor is one of the largest unpriced markets in the world. Today's answer is a stack of single-task machines, a dishwasher, a washer, a vacuum, each $600 to $1,000 and doing exactly one thing. Whoever ships a general-purpose robot at appliance prices doesn't win a niche, they open consumer robotics the way the PC opened computing.\r\n\r\nWe're robotics researchers from Columbia (RoboPIL, CGUI). After years watching \\[$100K research robots struggle with tasks cheap hardware could handle\\], we realized the gap between lab robots and home robots isn't intelligence, it's cost discipline. Nobody was going to fix that from inside a lab, so we left to build it: a $1,688 robot anyone can teach." } ], "url": "https://www.ycombinator.com/companies/noril1", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/noril1.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/norirobotics/", "x_url": "https://x.com/NoriRobotics", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/4b7cc06bfd9d08d6eae3bc20eca8c056f893bf8b.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": 2661900, "full_name": "Antonio Sitong Li", "title": "Founder/CTO", "founder_bio": "Antonio is the founder of Nori Robotics. He studied Computer Science and Architecture at Columbia, where he held research fellowships with the Laidlaw Scholars Program, the Data Science Institute, and the Graphics & UI Lab. His research focused on teaching robots new tasks through VR demonstrations.\n\nHe also holds a national patent for a computer-vision system, and previously co-founded Truely, which grew to 2,000+ users and 1.5M+ impressions.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/antonio-sitong-li/", "x_url": "https://x.com/AntonioSitongLi", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/31394af155bdf33ce5bb832507516ea31b4407bd.jpg" } ], "jobs": [ { "id": 117560, "title": "Data Operations Lead", "url": "https://www.ycombinator.com/companies/noril1/jobs/njoB5k2-data-operations-lead", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "$100K - $150K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 117561, "title": "Full-Stack Engineer", "url": "https://www.ycombinator.com/companies/noril1/jobs/cERiSKM-full-stack-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Full stack", "salary_range": "$100K - $150K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [] }, { "id": 117562, "title": "Multimodal Engineer", "url": "https://www.ycombinator.com/companies/noril1/jobs/boIEFcs-multimodal-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$130K - $200K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [] }, { "id": 117563, "title": "VLM Researcher", "url": "https://www.ycombinator.com/companies/noril1/jobs/3VxHqDs-vlm-researcher", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$150K - $250K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [] }, { "id": 117564, "title": "LLM Researcher", "url": "https://www.ycombinator.com/companies/noril1/jobs/2LGcxo3-llm-researcher", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Machine learning", "salary_range": "$150K - $250K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [] }, { "id": 117565, "title": "Applied AI Engineer, Agents & Robot Learning", "url": "https://www.ycombinator.com/companies/noril1/jobs/ZSfyL0x-applied-ai-engineer-agents-robot-learning", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$150K - $200K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [] }, { "id": 117566, "title": "Design Engineer", "url": "https://www.ycombinator.com/companies/noril1/jobs/XrKBJq1-design-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Design", "role_type": "Product design", "salary_range": "$100K - $130K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [] }, { "id": 117567, "title": "Social Media & Content Marketer", "url": "https://www.ycombinator.com/companies/noril1/jobs/jVWzI5j-social-media-content-marketer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Marketing", "role_type": null, "salary_range": "$35 / hourly", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] }, { "id": 117568, "title": "Electrical Engineer", "url": "https://www.ycombinator.com/companies/noril1/jobs/Exs6QKi-electrical-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Electrical", "salary_range": "$110K - $120K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [] }, { "id": 117569, "title": "Robot Assembly & Automation Technician", "url": "https://www.ycombinator.com/companies/noril1/jobs/qciFkKu-robot-assembly-automation-technician", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Operations", "role_type": null, "salary_range": "$47.8K - $58.2K", "equity_range": "", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] } ], "news": [ { "title": "American Humanoid Robot Launches For Just $1,688, Delivery This Fall, Made In San Francisco", "url": "https://www.forbes.com/sites/johnkoetsier/2026/08/18/american-humanoid-robot-launches-for-just-1688-delivery-this-fall-made-in-san-francisco/", "date": "Aug 20, 2026" } ], "launches": [ { "id": 111315, "title": "Nori: The $1688 humanoid robot", "tagline": "Most humanoids cost 16k, ours cost 1.6. 19 DOF, 1.5 KG lift per arm", "body": "Hey YC! 👋\\\n\\\nI’m Antonio from Nori Robotics\n\nWe manufacture humanoids in SF, and we do it at 10% the cost of the competition \n\n**Our ask:** If you are doing any development related to robotics and you think that Nori can be useful, fill out this [form](https://docs.google.com/forms/d/e/1FAIpQLSdcHJxwXCBo5dz7IbIQ30akCu5JaD5Tbv5dP9gIQxvbJQR-3Q/viewform?usp=dialog) or reach out to me on: [X](https://x.com/AntonioSitongLi) or [linkedin](https://www.linkedin.com/in/antonio-sitong-li/). \n\nHere is a video demo of what Nori can do 👇\n\n\\\n\\\nLearn more at [norirobotics.com](http://norirobotics.com)\n\n\\\n**Nori Specs:**\n\n19 DOF\n\n\n\n55 kg linear lift\n\n\n\n1.5 kg payload per arm (2 arms)\\\n\n\nMicrophone array + Speaker (full-duplex speech dialogue)\n\nRpi 5 4GB compute module \n\n4 \\* 720p 30 fps camera", "url": "https://www.ycombinator.com/launches/SxP-nori-the-1688-humanoid-robot", "votes": 16, "created_at": "2026-08-20T18:30:00.323Z" } ] }, { "id": 32586, "name": "Greypoint Industries", "slug": "greypoint-industries", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b0d5898f7b8fc2ee6fc19f6de3dae045123c7608.png", "website": "https://greypointindustries.com/", "all_locations": "San Francisco, CA, USA", "long_description": "We build LEGION, a drone swarm that identifies, geolocates, and tracks every emitter on the battlefield using the enemy’s own radio signals. LEGION enables our warfighters to precisely track previously obscured targets like jammers, command posts, and drone operators so they can proactively respond to threats instead of reacting to them.", "one_liner": "Building drone swarms that hunt hidden enemies.", "team_size": 4, "industry": "Industrials", "subindustry": "Industrials -> Defense", "launched_at": 1782765221, "tags": [ "Hardware", "Robotics", "Drones", "Defense" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "Industrials", "Defense" ], "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/greypoint-industries", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/greypoint-industries.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/greypoint-industries/?viewAsMember=true", "x_url": "https://x.com/Greypoint_", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/b0d5898f7b8fc2ee6fc19f6de3dae045123c7608.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": 3676390, "full_name": "Darcy Zhang", "title": "Founder/CEO", "founder_bio": "Co-Founder at Greypoint Industries.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/darcy-zhang-021134243/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5337a388dc0b683be08ad652cef050e1fd9af004.jpg" }, { "user_id": 3676391, "full_name": "Nic Chu", "title": "Founder/COO", "founder_bio": "Co-Founder at Greypoint Industries.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/nicchu/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2c6aa1d0091b93ae6f6641c720d544f1c7126a60.jpg" }, { "user_id": 3558298, "full_name": "Jordan Khoo", "title": "Founder/CTO", "founder_bio": "Co-Founder at Greypoint Industries. Previously led project with autonomous loitering munition project with Lockheed Martin Skunkworks.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jordankh00/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2363824c9001ce22d79d36c04d0ab6555b86edfa.jpg" }, { "user_id": 3676397, "full_name": "Steven Xu", "title": "Founder/CPO", "founder_bio": "Co-Founder at Greypoint Industries. Previously at Bosch Quantum Sensing building satellite sensors. Led research project on detection of UAVs using passive radar. Presidential Scholar at UBC.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/sxu22/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/9cffa849cc769fd0df23fe0a5e3b4c24fb8e7736.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 108367, "title": "Greypoint Industries: Drone swarms that find drone operators", "tagline": "Greypoint Industries builds drone swarms that find enemy drone operators on the battlefield.", "body": "[Greypoint Industries (YC S26) Launch Video](https://youtu.be/y9jC4A7Fg04)\n\nGreypoint Industries builds drone swarms that find enemy drone operators on the battlefield.\n\nOver 70% of casualties in Ukraine come from drones. The entire defense space is focused on building interceptors to shoot them down. While they’re treating the symptom, we’re going after the root cause: the drone stations. They’re hidden in bunkers, behind terrain, and fly the drones that kill our warfighters and civilians. Today, soldiers have no way to reliably geolocate operators on the battlefield.\n\nGreypoint Industries built LEGION, a drone swarm that identifies, geolocates, and tracks every emitter on the battlefield using the enemy’s own radio signals. LEGION enables our warfighters to precisely track previously obscured targets like jammers, command posts, and drone operators so they can proactively respond to threats instead of reacting to them.\n\nGreypoint has just won a contract with the Canadian Government, demoed with the Armed Forces, and successfully geolocated a target using their aerial platform. The founding team brings experience from the Canadian Infantry, General Dynamics, Bosch Quantum Sensing, and TerraSense Analytics.\n\nDefend the West. Deploy Greypoint.\\\n\\\nFind out more at .", "url": "https://www.ycombinator.com/launches/SBr-greypoint-industries-drone-swarms-that-find-drone-operators", "votes": 10, "created_at": "2026-07-30T23:00:42.765Z" } ] }, { "id": 32621, "name": "Aktoria Robotics", "slug": "aktoria-robotics", "former_names": [ "Phi Robotics" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/87a10d62adb927072657a9be3281af92a78ab9c6.png", "website": "https://aktoria.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Enabling robot deployment & autonomy ", "one_liner": "Human as API for robots", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1784175637, "tags": [ "Robotics", "Enterprise Software" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "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/aktoria-robotics", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/aktoria-robotics.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/aktoria-robotics", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/87a10d62adb927072657a9be3281af92a78ab9c6.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": 3108880, "full_name": "Jaskaran Singh Walia", "title": "Founder", "founder_bio": "Ex - Researcher @ (Microsoft, MIT, CMU, Cambridge, NUS)\n\n", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jaskaranwalia", "x_url": "https://x.com/karanwxliaa", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/bb7e6a357374ed42415aee6999d0568b1d2dc6ce.jpg" }, { "user_id": 1125677, "full_name": "Shreenabh Agrawal", "title": "Founder", "founder_bio": "Robotics grad @ CMU. Physics & Quantum Technology @ IISc Bangalore.\nIndia's Prime Minister awardee, highest civilian honor for young achievers.\n", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/shreenabh/", "x_url": "https://x.com/ShreenabhA", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/64c61d6ba30010f5699e5b194f9a5ff2aa45b8ef.jpg" } ], "jobs": [ { "id": 109688, "title": "Robot Learning Researcher (VLA / Foundation Models)", "url": "https://www.ycombinator.com/companies/aktoria-robotics/jobs/WlROHB1-robot-learning-researcher-vla-foundation-models", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Science", "role_type": "Research", "salary_range": "$450K - $600K", "equity_range": "1.00% - 2.00%", "experience": "Any (new grads ok)", "visa": "Will sponsor", "skills": [] }, { "id": 116148, "title": "HR Manager (India)", "url": "https://www.ycombinator.com/companies/aktoria-robotics/jobs/sIDJZkE-hr-manager-india", "location": "Noida, UP, IN / Noida, Uttar Pradesh, IN", "type": "Full-time", "role": "Recruiting & HR", "role_type": "Operations", "salary_range": "₹700K - ₹1.4M INR", "equity_range": "", "experience": "6+ years", "visa": "US citizenship/visa not required", "skills": [] } ], "news": [], "launches": [ { "id": 109426, "title": "Aktoria Robotics is the teleoperation layer to speed up robot deployments", "tagline": "A 24-hour global network of trained operators, powered by our low-latency teleop software.", "body": "**Aktoria Robotics is the teleoperation layer that speeds up robot deployments.**\n\n[https://drive.google.com/file/d/1UQchwD0U_FFdP9X3FDKJ7UjqXRW_zh24](https://drive.google.com/file/d/1UQchwD0U_FFdP9X3FDKJ7UjqXRW_zh24/view?usp=sharing)\n\nEvery \"autonomous\" robot you've seen this year had a human behind it. Full autonomy isn't here yet, and building an in-house teleop team is slow and expensive. That's the bottleneck standing between a working robot and a real deployment.\n\nAktoria Robotics is a 24-hour global network of trained robot operators across India, Mexico, and the USA, powered by our low-latency teleop software (40ms cross-country) at at least 50% less than the cost of in-house operators. Robotics companies plug in and ship deployments faster.\n\n**The team:** We're Jaskaran Singh Walia and Shreenabh Agrawal, ML and Robotics grad students at CMU. Shreenabh (ex-Zoox) has first-author papers at top robotics conferences. Jaskaran has authored 15+ papers and researched at MIT, Cambridge, and Microsoft Research.\n\n**Our ask:** If you're deploying robots and need reliable teleop, book a call through aktoria.com. Intros to robotics teams requiring teleop are hugely helpful, reply here or reach us at [founders@aktoria.com](mailto:founders@aktoria.com).", "url": "https://www.ycombinator.com/launches/SSw-aktoria-robotics-is-the-teleoperation-layer-to-speed-up-robot-deployments", "votes": 6, "created_at": "2026-08-06T15:00:00.066Z" } ] }, { "id": 32716, "name": "Neuromorphic", "slug": "neuromorphic", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/470f3b57cd018aad9c127e64e5b952d32a64d435.png", "website": "https://www.neuromorphic.vision/", "all_locations": "San Francisco, CA, USA", "long_description": "We are building robots that can work autonomously in existing wet labs. Unlike traditional lab automation, which requires dedicated equipment and fixed workflows, our robot moves between workstations, manipulates existing scientific equipment, transports lab materials, and executes experiments using the same lab infrastructure as a human technician. We make the robots easy to manage through natural interfaces like Slack, email, and phone. Our goal is to make deploying robots in wet labs as easy as onboarding a new employee, and to accelerate scientific research!", "one_liner": "Building robots to automate wetlabs", "team_size": 3, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1786056544, "tags": [ "Hard Tech", "Robotics", "B2B", "Biotech", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "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/neuromorphic", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/neuromorphic.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/neuromorphic-vision", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/470f3b57cd018aad9c127e64e5b952d32a64d435.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": 3607343, "full_name": "Vatan Aksoy Tezer", "title": "Founder/CEO", "founder_bio": "Founder at Neuromorphic. Previously Lead Robotics Engineer at Augmentus, deploying motion planning algorithms to production with sub-mm accuracy and leading a team of 5. Before that, built navigation stacks from scratch at KABAM Robotics (deployed 100+ robots) and scaled ASRS systems at Rapyuta Robotics (1000+ robots to production). Core maintainer of MoveIt at PickNik Robotics. MS in CS from Sabanci University, BS in Astronautical Engineering from Istanbul Technical University.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/vatanaksoytezer/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d22faa66df9b9d4a1f2250b01fe1287fe3e28347.jpg" }, { "user_id": 2794176, "full_name": "Ege Doganay", "title": "Founder/CTO", "founder_bio": "Founder at Neuromorphic (YC S26). Robotics and AI research at Bilkent University. Research fellow at Nanyang Technological University. Published research in top AI and robotics conferences. Won HackMIT, Stanford XR, MIT Reality Hack.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/ege-doganay/", "x_url": "https://x.com/_doganay_ege", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/dda0ccf712da9c5904e6a14ea227c1d7210f36b9.jpg" }, { "user_id": 3316337, "full_name": "Cem Toker", "title": "Founder/COO", "founder_bio": "Founder at Neuromorphic. Co-founded ErgoFlow, building LLM routing and training acceleration. Previously developed static calibration algorithms for industrial robots at Zeeko achieving 30% higher precision. Engineering at Cambridge. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/cem-seref-toker", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/938e49a805b6e2d5c1ed6645ef6db6e8f54dcb9d.jpg" } ], "jobs": [ { "id": 112214, "title": "Forward Deployed Engineer", "url": "https://www.ycombinator.com/companies/neuromorphic/jobs/eae51Em-forward-deployed-engineer", "location": "San Francisco, CA, US", "type": "Full-time", "role": "Engineering", "role_type": "Robotics", "salary_range": "$100K - $150K", "equity_range": "0.50% - 1.50%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [ "Python", "CAD Design" ] } ], "news": [], "launches": [ { "id": 109550, "title": "Neuromorphic - Building an embodiment-agnostic “brain” that makes robots fast to deploy", "tagline": "We make robots smarter, and faster to deploy. Starting with wet labs!", "body": "Hi everyone! We’re Cem, Ege, and Vatan, the founders of Neuromorphic 👋\\\n\\\n**TL;DR** Neuromorphic is building an embodiment-agnostic “brain” that makes robots fast to deploy, and easy to manage through natural interfaces like Slack, email, and phone. Our goal is to make deploying robots in wet labs and other physical industries as easy as onboarding a new employee.\n\n\\\n\\\n**The Problem**\\\nTo make robotics mainstream, we believe two problems have to be resolved:\\\n1\\. Deployment: Robots are still too slow, expensive, and engineering-intensive to deploy and adapt to new tasks and environments.\\\n2\\. Interaction: Managing and controlling robots remains too technical.\\\n\\\n**What We’ve Built**\\\nNeuromorphic packages sensors, compute, and software into a “brain” that can be attached to any robot body. An onboard LLM orchestrator turns natural-language instructions into workflows made up of reusable robotic skills, such as navigating, picking up an object, opening a refrigerator, or inspecting an area. Individual skills can be of various types; they could be AI models we develop, like Vision-Language Models and Video Action Models, or just plain code. Sensor-based safety loops monitor every action to ensure reliable execution.\n\nWe are also giving robots emails, phone numbers, and Slack access to make human-robot interaction more intuitive than using dashboards. The robots then respond to queries and take actions using the onboard LLM.\\\n\\\n**Traction**\\\nWithin a week of our first conversation with a leading biotechnology company, we deployed our robot in their wet lab, which is capable of operating autonomously 24/7, and already completed over 1500 tasks.\\\n\\\n**The Team**\n\n![uploaded image](/media/?type=post&id=109550&key=user_uploads/3607343/b28b023b-f328-4c5d-9181-720e96e5b1a3)\n\n\\\nCem: Second-time founder and did robotics research at Cambridge University. Previously built LLM routing and training acceleration, and did precision robotics.\\\n\\\nVatan: Maintained multiple open-source robotics libraries, most notably MoveIt, one of the most popular motion-planning frameworks for robotics. Led various teams in robotics startups from Series A to Series C in Japan and Singapore. Deployed over a thousand robots.\\\n\\\nEge: Did Robotics and AI research at Bilkent University. Research fellow at Nanyang Technological University. Published research in top AI and robotics conferences. Won HackMIT in 2024.\\\n\\\nCem and Ege first met as teammates in the FIRST Robotics Competition. They reached out to Vatan for mentorship and robotics advice. We spent the next three years building robots and winning competitions together. We remained close and eventually reunited to start Neuromorphic!\\\n\\\n**Ask**\\\nWe're looking for warm intros to wet lab, biotech, and physical-industry operators. If you have a repetitive physical process and have wondered whether a robot could do it, email us at [founders@neuromorphic.vision](mailto:founders@neuromorphic.vision) or [book a call here](https://cal.com/team/neuromorphic/meet-the-founders-of-neuromorphic).", "url": "https://www.ycombinator.com/launches/SUw-neuromorphic-building-an-embodiment-agnostic-brain-that-makes-robots-fast-to-deploy", "votes": 73, "created_at": "2026-08-10T15:00:00.364Z" } ] }, { "id": 32750, "name": "Ultrasonium", "slug": "ultrasonium", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/734dc12d12265ba8890bf4ef5e7e564bdb629a87.png", "website": "https://ultrasonium.com/", "all_locations": "Boston, MA, USA", "long_description": "The technologies that define this century, including data centers, rockets, satellites, and robots, are built from complex metal parts. As these systems advance, the parts get harder to make. Past a certain complexity, casting and machining stop working, and the advanced methods that remain are slow, expensive, and hazardous.\r\n\r\nUltrasonium has invented a new manufacturing method to make these critical parts 15x faster and 75% cheaper than the methods they replace, in the U.S. and at scale. Solid metal feedstock goes in and a finished part safely comes out, controlled by a physical AI layer and novel control processes. \r\n\r\nThe systems that matter most, in aerospace, energy, and compute, are demanding metal geometries that can't be machined or cast and are too expensive and slow to make with incumbent methods, at a moment when domestic manufacturing capacity is a national priority.\r\n\r\nOur founding team has built and innovated some of the most complex engineering systems known to man: quantum computers, superconductors, nuclear reactors, and novel aerospace alloy processing methods. ", "one_liner": "Metal manufacturing, faster, cheaper, and more versatile.", "team_size": 5, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1785870310, "tags": [ "Hard Tech", "Hardware", "Robotics", "Manufacturing" ], "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/ultrasonium", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/ultrasonium.json", "year_founded": 2026, "city": "Boston", "country": "US", "linkedin_url": "https://www.linkedin.com/company/ultrasonium/", "x_url": "https://x.com/Ultrasonium", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/734dc12d12265ba8890bf4ef5e7e564bdb629a87.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": 3735756, "full_name": "Jack Qiu", "title": "Founder/CEO", "founder_bio": "Founder & CEO of Ultrasonium. Inventor, physicist, and engineer with a PhD in EECS from MIT, with research spanning quantum computing, cryogenics, plasma research, signal processing, hardware control, and advanced manufacturing. First author of a Nature Physics publication in collaboration with MIT Lincoln Laboratory under IARPA and DoD programs. Former researcher at Lawrence Berkeley National Laboratory. BA in Physics from UC Berkeley.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jack-q-a1b81546/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/10afaa4d3df89c18be993661d93702c07d1f3782.jpg" }, { "user_id": 3748345, "full_name": "Hunter Brown", "title": "Founder", "founder_bio": "Founder & VP, Engineering at Ultrasonium\n\nStarted my R&D career working at national labs by age 15. I have contributed to the ITER fusion reactor and CERN through labs at NHFML and LBNL. I have led teams of fabricators and designers in both research and industry. I am passionate about hard tech and moving groundbreaking research ideas into real products. \n\nI lead the Ultrasonium team on the novel and cutting edge technology we implement in our manufacturing process. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/hunterpbrown/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/525b78441a81f2ea58c6801c81cc2f8643e4e421.jpg" }, { "user_id": 1892793, "full_name": "Chris Carter", "title": "Founder", "founder_bio": "Founder & Chief Scientific Officer at Ultrasonium. PhD candidate on leave from MIT researching novel metal matrix materials and 3D printed metal heat treatments under NSF GRFP, MIT UCEM, GEM, and .406 Venture fellowship programs. Previously at Argonne National Laboratory working on 3D printed steel. Led metal melt pool simulations for NASA-funded multi-university project. Patent holder and publisher on metal printing. MS in Mechanical Engineering from MIT, BS from University of South Carolina.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/christopher-p-carter/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/d2c39cf3788b615d4686293df632fc23d11aab12.jpg" }, { "user_id": 2875171, "full_name": "Alexander Urbanski", "title": "Founder", "founder_bio": "Founder & Chief Research Officer of Ultrasonium. Former founder of the DOE-funded nuclear energy startup Bay State Energy and inventor of the Nuclear Thermoelectric Generator. Studied physics and computer science at Boston University. First hire at Phase3D - built and commercialized metals manufacturing technology deployed across NASA, USAF, and companies across four continents. Former metals manufacturing research engineer at Argonne National Laboratory. Dropped out of mech-e grad program. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/aurban42/", "x_url": "https://x.com/urban_alex42", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/453e1928db84e3ca68b98855a033c46f98ebc438.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 113464, "title": "Ultrasonium: Shaping the Future of Metal Manufacturing", "tagline": "We make the world’s most difficult metal parts faster, cheaper, and more versatile.", "body": "**The problem**\n\nThe technologies that define this century, including data centers, rockets, satellites, robots, etc., are built from complex metal parts. As these systems advance, the parts get harder to make. Past a certain complexity, casting and machining stop working, and the advanced methods that remain are slow, expensive, and limited in the alloys and geometries they can process.\n\n**What we built**\n\nUltrasonium has invented a new method to make these critical parts. Solid metal feedstock goes in and a finished part comes out, controlled by a Physical AI layer and novel control processes.\n\nWe produce near-net-shape complex metal parts up to 15× faster, 75% cheaper, and with far greater alloy versatility than conventional manufacturing methods, at scale in the U.S.\n\n\n\n![uploaded image](/media/?type=post&id=113464&key=user_uploads/3735756/dbd12c5d-1203-4e50-9939-980a218df45a)\n\n**Why now / why us**\n\nThe systems that matter most, in aerospace, defense, energy, and compute, are demanding metal geometries that can’t be machined or cast and are too expensive and slow to make with incumbent methods, at a moment when domestic manufacturing capacity is a national priority.\n\nOur founding team has worked on some of the most difficult engineering systems in the world, including quantum computers, superconductors, nuclear reactors, and advanced aerospace alloy processing. Between the four of us, we have backgrounds in physics, metallurgy, advanced manufacturing, controls, hardware, and commercialization.\n\nJack Qiu (CEO) completed his PhD in Electrical Engineering and Computer Science at MIT and published pioneering quantum computing work in Nature Physics. Chris Carter (CSO) left to join Ultrasonium during the 5th year of his PhD program at MIT after more than six years of research in state-of-the-art metallurgy and materials processing. Alexander Urbanski (Chief Research Officer) previously founded a DOE-funded nuclear startup and was the first hire at Phase3D, where he built and commercialized metal manufacturing monitoring technology. Hunter Brown (VP, Engineering) began working at national labs when he was 15, studied physics at UC Berkeley, and contributed to the ITER fusion reactor.", "url": "https://www.ycombinator.com/launches/TW4-ultrasonium-shaping-the-future-of-metal-manufacturing", "votes": 6, "created_at": "2026-09-02T19:54:37.419Z" }, { "id": 109239, "title": "Ultrasonium: A new way to make complex metal parts, 15x faster and 75% cheaper", "tagline": "Ultrasonium makes the most difficult metal parts for the world's most important systems 15x faster and 75% cheaper. ", "body": "\n**The problem**\n\nThe technologies that define this century - data centers, rockets, satellites, robots, etc. - are built from complex metal parts. As these systems advance, the parts get harder to make. Past a certain complexity, casting and machining stop working, and the advanced methods that remain are slow, expensive, and hazardous.\n\n**What we built**\n\nUltrasonium has invented a new method to make these critical parts. Solid metal feedstock goes in and a finished part safely comes out, controlled by a physical AI layer and novel control processes. We produce near-net-shape complex metal parts 15x faster and 75% cheaper than the methods they replace, in the U.S. and at scale.\n\n \n\n![uploaded image](/media/?type=post&id=109239&key=user_uploads/2875171/55d1e111-fc43-450d-a83c-2c191d88d909)\n\n\n**Why now / why us**\n\nThe systems that matter most, in aerospace, defense, energy, and compute are demanding metal geometries that can’t be machined or cast and are too expensive and slow to make with the incumbent methods, at a moment when domestic manufacturing capacity is a national priority.\n\nOur founding team has built and innovated some of the most complex engineering systems known to man - quantum computers, superconductors, nuclear reactors, and novel aerospace alloy processing methods. Jack Qiu (CEO) completed his PhD in Electrical Engineering and Computer Science at MIT and has published pioneering quantum computing work in Nature Physics. Chris Carter (CSO) dropped out during the 5th year of his PhD program at MIT and has over a half dozen years of experience researching state of the art metallurgy and materials processing systems. Alexander Urbanski (Chief Research Officer) previously founded a DOE-funded nuclear startup and was the first hire at Phase3D where he built and commercialized metals manufacturing monitoring technology. Hunter Brown (VP, Engineering) began working at national labs when he was 15, graduated from UC Berkeley Physics, and contributed to the ITER fusion reactor.", "url": "https://www.ycombinator.com/launches/SPv-ultrasonium-a-new-way-to-make-complex-metal-parts-15x-faster-and-75-cheaper", "votes": 8, "created_at": "2026-08-05T17:31:24.990Z" } ] }, { "id": 32752, "name": "Moving Atoms", "slug": "moving-atoms", "former_names": [ "Run Lobster", "RunLobster", "Demon AI", "RunDemon", "Avicenna Care", "Agent Insurance" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ee4bd602221f77fc05dda940b7202523dd2b9d10.png", "website": "https://movingatoms.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Our first model, Atom 1, pre-trained on the internets video, and fine tuned for physics. \r\nIt has been action conditioned, so you can simulate robot actions within it.\r\nThis lets Robot Labs train their robots using GPUs instead of relying on human collected manual data that is slow and expensive.\r\nIn unseen and hard to replicate environments, this is the only path to getting ANY training data.", "one_liner": "Virtual Reality for Training Robots", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1786481200, "tags": [ "Hard Tech", "Robotics", "Virtual Reality", "Data Labeling", "AI" ], "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/moving-atoms", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/moving-atoms.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/ee4bd602221f77fc05dda940b7202523dd2b9d10.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": 1776350, "full_name": "Shehryar Saroya", "title": "Founder/CEO", "founder_bio": "Previously AI @ TikTok (Core Recomendation Algorithm). \nMaths @ Oxford.", "is_active": true, "linkedin_url": "https://linkedin.com/in/shehryar-saroya", "x_url": "https://x.com/SaroyaShehryar", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/eba8f18828b5f957663aea131e4a12ec89f9afbb.jpg" }, { "user_id": 2375000, "full_name": "Ahmad Saroya", "title": "Founder", "founder_bio": "Studied Mathematics @ Oxford, Trained Neural nets for GCHQ\nBritish Mathematical Olympiad Gold Medalist. ", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/ahmad-saroya-a05400237/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/ab9fc0f9df4310e5df12d2db3ff69d64e603d611.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 32913, "name": "Pacific", "slug": "pacific", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/196624bfab919b6dd989cb601af1771954cb562e.png", "website": "https://pacific.space", "all_locations": "San Francisco, CA, USA", "long_description": "We mass-produce modular data centers that deploy on stalled infrastructure projects losing billions per week.\r\n\r\nDelayed infrastructure projects hemorrhage $1B a week in the US alone - Pacific mass-produces modular data centers that deploy on those sites in days and turn their unused power into revenue.\r\n\r\nData centers are stuck for years waiting for power, while delayed construction sites across the world sit on unused interconnects, losing billions of dollars per week in interest on trillions of dollars of debt. Our pods deploy on those sites and generate revenue for them in days. They use diamond wafers in the cooling system so pods run anywhere on earth, even a desert. \r\n\r\nWe'll use the same mechanisms we're building today to deploy compute across the galaxy.\r\n", "one_liner": "Mass-producing and financing micro data center incredibly quickly.", "team_size": 6, "industry": "Industrials", "subindustry": "Industrials", "launched_at": 1786300632, "tags": [ "Fintech", "Robotics", "Space Exploration", "Manufacturing", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "Industrials" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/pacific", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/pacific.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/pacific-compute", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/196624bfab919b6dd989cb601af1771954cb562e.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": 3218344, "full_name": "Harper Dammann Smith", "title": "Founder/CEO", "founder_bio": "Founder and CEO of Pacific - Grew my drone startup to $1M in revenue at 18; left school to shoot expeditions for Red Bull on 7,000m peaks. Studied aerospace engineering; dropped out after selling my first company. Now mass producing modular data centers that deploy in days turning unused power into Ai factories.\n\nI'll go to space one day.\n", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/harper-dammann-smith/", "x_url": "https://x.com/harperdammann?s=21", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/3e20832d513b9aced0007904f88c4e05ba173221.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 109996, "title": "Pacific: Mass-producing and deploying micro data centers for Earth and Space", "tagline": "Pacific mass produces micro data centers for Earth and space, faster than anyone else.", "body": "**Building the toughest super computers for earth and space**\\\n\\\n**TL;DR:** Data centers are stuck for years waiting for power, while delayed construction sites across the world sit on unused interconnects, losing $1B per week in the US alone, in interest on trillions of dollars of debt. Our pods deploy on those sites and generate revenue for them in days. They use diamond wafers in the cooling system so pods run anywhere on earth, even a desert.\n\n\n\n**The deal**\n\nIf you need compute (GPU hours, tokens, capacity for a training run) send us a note. We sell short and long-term contracts below market rate.\n\nIf your data has to stay on-prem (**defense, CUI, CMMC)**, we sell managed, modular pods directly and are already working with large aerospace companies.\n\n**We're building factories**\n\nSpaceX didn't just build rockets, they built rocket factories. We do the same and our first factory stands up over the next few months, potentially funded by the state of Missouri. We vertically integrate the critical components that currently carry multi-year lead times: transformers, switchgear and power distribution, and by taking control of our own supply chain we ensure we can build pods fast enough.\n\n**Financed like aircraft**\n\nOur pods are financed like aircraft - debt at **\\~5-6%, not 11-15%**. A data center is a risky construction loan: money stuck in a half-built site for years, and if it fails the lender holds a building and a pile of GPUs priced by a brutally volatile market - the banks are freaking out. Our pods leave the factory fully functional, earns the moment it's connected to power, and can be repossessed and redeployed: the profile of equipment finance, far faster and cheaper.\n\n**Traction**\n\nToday we have $95M in LOI’s for our hosted compute and a further $27M for direct sales of our pods. Our first two clusters go live in Missouri this month, followed by the first modular factory.\n\n**Our asks**\n\n* **Compute buyers and offtake.** We'd love to speak to anyone buying compute, or setting up on-prem deployments, or needing CMMC compliance. Introductions to procurement teams at OpenAI, Anthropic, or any startup constrained by access to cheap compute would be incredible.\n* **Hiring.** Data center engineers, electrical engineers, any data center nerds you know.\n* **Financiers.** These projects run on capital from infra investors and tech lenders. If you've worked in that world, we'd love to chat.\n* **Construction sites.** If you sell to construction sites, work in construction, mining, or fab production, or own a site yourself - we will put a money machine on it. Let's chat.\n\n**Join us as we build supercomputers for the galaxy!**\n\n![uploaded image](/media/?type=post&id=109996&key=user_uploads/3218344/e8f50721-c56b-4585-9abf-7d11cf11d5c3)\n\n", "url": "https://www.ycombinator.com/launches/Sc8-pacific-mass-producing-and-deploying-micro-data-centers-for-earth-and-space", "votes": 10, "created_at": "2026-08-12T17:30:05.717Z" } ] }, { "id": 33012, "name": "Cosmic Robotics", "slug": "cosmic-robotics", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/610b3f44c95c65ea346121a48c57b8c81a3788ce.png", "website": "https://www.cosmicrobotics.com/", "all_locations": "San Francisco, CA, USA", "long_description": "Our mission is to build a city on Mars. \r\n\r\nCosmic-1, the first equipment in our fleet, is an autonomous robot capable of heavy-lift manipulation. Its been deployed on some of the largest solar farms in the US, more than doubling labor productivity across tens of thousands of panel installs. \r\n\r\nWe're scaling in solar, expanding in data centers, and building lunar construction robotics under contract with NASA.", "one_liner": "Autonomous construction on Earth and beyond", "team_size": 8, "industry": "Industrials", "subindustry": "Industrials", "launched_at": 1783106253, "tags": [ "Hard Tech", "Robotics", "Construction", "Aerospace" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2026", "status": "Active", "industries": [ "Industrials" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/cosmic-robotics", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/cosmic-robotics.json", "year_founded": 2024, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/cosmic-robotics/", "x_url": "https://x.com/cosmic_robotics", "fb_url": null, "cb_url": "https://www.crunchbase.com/organization/cosmic-robotics", "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/610b3f44c95c65ea346121a48c57b8c81a3788ce.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": 522502, "full_name": "James Emerick", "title": "Founder/CEO", "founder_bio": "Co-founder, CEO at Cosmic Robotics (YC S26). Previously robotics engineer at Built Robotics deploying autonomous earthmoving robots in production, and research engineer at Autodesk Research building adaptive platforms for construction. MS/BS in Mechanical Engineering from UPenn.", "is_active": true, "linkedin_url": "https://linkedin.com/in/jamesemerick", "x_url": "https://x.com/JamesAEmerick", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/c3984e6d72a7fc6fad1faf754e9630152d5177fa.jpg" }, { "user_id": 403781, "full_name": "Lewis Jones", "title": "Founder/CTO", "founder_bio": "Co-founder, CTO at Cosmic Robotics (YC S26). Previously propulsion engineer at Relativity Space and prior experience at SpaceX, NASA JPL, and NASA JSC. Forbes 30 under 30. BS in Mechanical Engineering and Economics from Caltech.", "is_active": true, "linkedin_url": "https://linkedin.com/in/lewis-c-jones", "x_url": "https://x.com/thelcjones", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e307c9f2c5673760099031abcf82a9d8ea9dbff9.jpg" } ], "jobs": [], "news": [ { "title": "Cosmic Robotics' robots could speed up solar panel deployments | TechCrunch", "url": "https://techcrunch.com/2025/04/16/cosmic-robotics-is-building-robots-to-speed-solar-power-deployments-for-data-centers/", "date": "Apr 16, 2025" } ], "launches": [ { "id": 106899, "title": "Cosmic Robotics: Autonomous construction on Earth and beyond", "tagline": "Robotic construction equipment to build a city on Mars. We’re proving the technology by building large-scale infrastructure on Earth — utility-scale solar farms and hyperscale data centers.", "body": "Hey everyone 👋\n\nWe’re [James](https://www.linkedin.com/in/jamesemerick/) and [Lewis](https://www.linkedin.com/in/lewis-c-jones/) - co-founders of [Cosmic Robotics](https://www.cosmicrobotics.com). \n\n**TL;DR**\n\n**We build robotic construction equipment to build a city on Mars**. We’re proving the technology today by building large-scale infrastructure on Earth – utility-scale solar farms and hyperscale data centers. Our first machine, Cosmic-1, has already installed tens of thousands of solar panels in the field and more than doubled the productivity of traditional crews.\n\n \n\n**❌ The problem**\n\nAfter working at NASA JPL, SpaceX, and Relativity Space, we believe rockets are no longer the limiting factor to space exploration and that the first humans will land on Mars by 2034. **The new bottleneck is construction**. We won't be sending thousands of construction workers to Mars to build the energy, compute, and housing needed to sustain even a small city. **It has to be built by robots that don't exist yet**.\n\nOn Earth we have a similar problem - **we’ve lost the ability to build**. Construction productivity has declined for 50 years while manufacturing and agriculture became 10-15x more productive through automation. **The missing technology is robotic manipulation for the tasks still done by hand**: lifting, placing, fastening.\n\nMeanwhile, there is a generational infrastructure buildout happening right now. **$7 trillion** is going into AI data centers, power, and compute over the next six years, **more than the Apollo Program, Manhattan Project, and Interstate Highway System combined**. 40% of US data center projects are running behind schedule, and the skilled labor shortage is the #1 cause. \n\n**🤖 What we've built**\n\nCosmic-1 is a 10,000 lb autonomous robot capable of heavy-lift manipulation. In solar, it picks up 90 lb panels and places them onto racking with millimeter precision in any environment: 100-degree heat, freezing rain, snow, and dust. It seamlessly integrates into existing construction processes. Across tens of thousands of cycles it has more than doubled the labor productivity of solar installation, on some of the largest solar projects in the US.\n\n![uploaded image](/media/?type=post&id=106899&key=user_uploads/522502/bb5f86ec-a23b-4ffd-a173-87f36ce6fb1c)\n\n**👬 The Team**\n\nWe come at this problem from two angles. James (CEO) grew up on construction sites, then spent his career bringing robots to the field with Built Robotics and Autodesk Research. He learned you don't change the oldest industry in the world by disrupting it; you earn your way in by giving crews better tools.\n\nLewis' (CTO) life ambition is to build a city on Mars. His work at NASA, SpaceX, and Relativity Space spans rocket engines, launch vehicles, satellites, space stations, and, yes, Martian robots. When it became clear the space industry was well on its way to Mars, he went looking for the construction robots. When he didn't find them, we started Cosmic.\n\nWe’ve brought together a team of industry experts with experience building robots, rockets, drones, self-driving cars, humanoids, and nuclear reactor operations. We know what it takes to get a machine to show up day-in-day-out on the jobsite.\n\n![uploaded image](/media/?type=post&id=106899&key=user_uploads/522502/87f30a8e-6f83-490e-8bef-04225d1a525e)\n\n**🚀 What's next**\n\nWe're scaling in solar, taking Cosmic-1 into data center construction, and working with NASA on lunar construction robotics. Revenue and data from deployments on Earth train the systems we'll deploy on Mars.\n\n**🙏 Our asks**\n\n1. **Know a hyperscaler or neocloud construction team?** Please connect us.\n2. **Share this post** and [follow our journey](https://www.linkedin.com/company/cosmic-robotics/).\n\n👉 Contact us at [james@cosmicrobotics.com](mailto:james@cosmicrobotics.com) | [cosmicrobotics.com](http://cosmicrobotics.com)", "url": "https://www.ycombinator.com/launches/RoB-cosmic-robotics-autonomous-construction-on-earth-and-beyond", "votes": 28, "created_at": "2026-07-23T17:36:46.436Z" } ] }, { "id": 33053, "name": "Shiraz AI", "slug": "shiraz-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/93d2ffb0a884b8a3781f59266189d89f4b30d975.png", "website": "https://shiraz.ai", "all_locations": "San Francisco, CA, USA", "long_description": "We deploy robots that learn new tasks from a single human demonstration in the factory. We're starting in contract manufacturing, where lines change every week and both traditional automation and today's VLAs fall over.\r\n\r\nOur founding team has 20+ years of experience in robotics. Navid was part of the core team that productized Spot at Boston Dynamics and led manipulation projects there. Before that, he was at Rethink Robotics. Mojtaba led whole-body control and manipulation efforts at Amazon Robotics and was a Research Assistant Professor at Northwestern University.", "one_liner": "Robots that learn on the job", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1786517990, "tags": [ "Generative AI", "Robotics", "Manufacturing" ], "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/shiraz-ai", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/shiraz-ai.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/shiraz-ai/", "x_url": "https://x.com/shiraz_ai", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/93d2ffb0a884b8a3781f59266189d89f4b30d975.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Jon Xu", "url": "https://www.ycombinator.com/people/jon-xu" }, "founders": [ { "user_id": 585458, "full_name": "Navid Aghasadeghi", "title": "Founder/CEO", "founder_bio": "Founder at Shiraz AI (YC S26). Previously Senior Staff Robotics Engineer at Boston Dynamics, where he was part of the core team that brought Spot from R&D to commercial deployment and led industrial manipulation. Previously Principal Robotics Engineer at Rethink Robotics, where he developed full-stack controls for Sawyer and led force control development. Also founded GenZArt, an AI consumer app that scaled to 1M users. PhD in ECE from UIUC.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/navid-aghasadeghi-356b077b", "x_url": "https://x.com/realnavida", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/b08976791c20954393282468d399741e7e6a659f.jpg" }, { "user_id": 2722145, "full_name": "Mojtaba Mozaffar", "title": "Founder/CTO", "founder_bio": "Founder at Shiraz AI. Previously Senior Applied Scientist and tech lead at Amazon Robotics, leading high-impact work in perception, policy learning, and manipulation. Before that, Research Assistant Professor at Northwestern directing AI and robotics research. PhD in Mechanical Engineering and Robotics from Northwestern.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/mojtaba-mozaffar/", "x_url": "https://x.com/MozaffarMojtaba", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2eac2883bfdf8e59573461acba516e0ea179ed74.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 110367, "title": "Shiraz AI: Robots that learn on the job", "tagline": "Deploy robots that learn new tasks from a single human demonstration in the factory", "body": "**TL;DR:** We deploy robots that learn new tasks from a single human demonstration in the factory. A new task shows up on the floor? You just film it once on your phone and the robot picks it up. No sitting around collecting data. No engineer flying out to your site. No overnight fine-tuning. You show it, and the robot learns.\n\n\n\n**❌ The problem**\n\nManufacturing is full of constantly changing, high-mix production tasks, which are among the hardest to automate. A line that's packing one product today is building something completely different next week. Every factory owner we talk to says the same two things: they can't find enough people to do the work, and the automation solutions they've tried have been too expensive and too rigid, often ending up gathering dust in a corner.\n\n**✅ What we do**\n\nWe're developing a robot foundation model whose core capability is adapting instantly to new variations of a task. You give the model a human demonstration video as context, and it bridges the embodiment gap to execute the task itself. This in-context learning is the missing piece in today's VLA approaches, and it's what changing manufacturing environments need.\n\nWe deliver the complete system: robot hardware, foundation model, and on-site deployment. We're already deploying robots at customer sites.\n\n**👋 Who we are**\n\n![uploaded image](/media/?type=post&id=110367&key=user_uploads/585458/0832cd2d-2dfc-41b0-8de6-d29897b6c8d3)\n\nBetween the two of us, we have 20+ years of experience in robotics. Navid was part of the core team that productized Spot at Boston Dynamics and led manipulation projects there; before that, he was at Rethink Robotics. Mojtaba led whole-body control and bimanual manipulation efforts at Amazon Robotics and was a Research Assistant Professor at Northwestern University.\n\n**🙏 Our ask**\n\nDo you have a manufacturing task that needs automating, or know someone who does? Let us know and we'll automate it.\n\nReach us at: [founders@shiraz.ai](mailto:founders@shiraz.ai)", "url": "https://www.ycombinator.com/launches/Si7-shiraz-ai-robots-that-learn-on-the-job", "votes": 63, "created_at": "2026-08-12T20:00:00.186Z" } ] }, { "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": 33349, "name": "Robocurve", "slug": "robocurve", "former_names": [ "Telos", "Robocurve PBC" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/1cfdafb2f71eef92d986496e842d5218b330742b.png", "website": "https://robocurve.org", "all_locations": "San Francisco, CA, USA", "long_description": "Robocurve builds open-source tools and independent benchmarks to measure how well robots can do real-world jobs. Instead of relying on unverified demo videos from frontier labs, we score their models on reproducible benchmarks that anyone can trust.\r\n\r\nToday there are no well-run, standardized robotics benchmarks. Labs evaluate in-house, and no independent group has stepped in to run continuous benchmarking as a service. The result is that no one actually knows how good anyone else is, or where the real frontier sits.\r\n\r\nGood benchmarks require operating and maintaining physical hardware and real-world setups. Simulation only goes so far, since models that look strong in sim can show large performance gaps once deployed in the real world. Building real-world benchmarks means coordinating job-domain experts, evals engineering, and hands-on robotics all at once.\r\n\r\nFrontier labs are targeting general-purpose robotics by 2028, yet the field of robotics evals barely exists. Whoever builds the trusted measure of robot capability becomes the reference everyone relies on. We combine backgrounds in AI evals and robotics to build and grow this field as fast as possible. We already shipped v1 of our open-source framework, Inspect Robots, and ran our first pilot scoring a frontier model on a real robot.", "one_liner": "Evals for robots", "team_size": 3, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1783378088, "tags": [ "Hard Tech", "Hardware", "Robotics", "Open Source", "AI" ], "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/robocurve", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/robocurve.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/robocurve/", "x_url": "https://x.com/robocurve", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/1cfdafb2f71eef92d986496e842d5218b330742b.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": 2392672, "full_name": "Jay Chooi", "title": "Founder/CEO", "founder_bio": "Founder and CEO of Robocurve. MA Statistics and BA CS/Math from Harvard. Jay builds evals of frontier AI and forecasts its progress. Previously Research Fellow at MATS, researcher at the UK AI Security Institute, and top contributor to Inspect Evals, the UK government's AI eval framework. Published at ACM EC, ICML, ACL, and EMNLP. Called the 2024 election correctly in all 50 states. Won a Rhodes Scholarship. Gold medal at the International Olympiad on Astronomy and Astrophysics.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jeqcho", "x_url": "https://x.com/chooi_jeq", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5df96d3283ec234b3a09c35933b2582a7ef1a067.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 112513, "title": "Robocurve — Real-World Evaluations of Physical AI", "tagline": "Real-world evals for robots", "body": "Hi, I’m [Jay](https://www.linkedin.com/in/jeqcho/), co-founder of [Robocurve](http://robocurve.org). We measure and reports what frontier robots can actually do in the real world.\n\nOur launch video \n\nFrontier labs are racing to build general-purpose robots within two years, yet no one knows what today's robots are truly capable of. Demo videos of robots performing narrow, cherry-picked tasks proliferate, but there are no rigorous, continuous, standardized benchmarks for robotics.\n\nRobocurve builds benchmarks for robots and the AI models that control them, to help the world understand how far robotics has come and how fast it's moving. Our benchmarks range from playing Jenga and making a sandwich to constructing a data center.\n\nGeneral-purpose robots could arrive before the end of the decade, with far-reaching implications: accelerated data center buildouts, explosive economic growth from a fully automated economy, and intensified geopolitical competition between the US and China. Real-world evaluations from Robocurve will help clarify the timeline to general-purpose robots so that society can prepare for their arrival well ahead of time.\n\n[Jay](https://www.linkedin.com/in/jeqcho/) is a Rhodes Scholar and a top contributor to UK AI Security Institute's Inspect Evals. He has published papers in ICML, EMNLP, ACL, ACM EC and his research has been featured in MIT Technology Review. Previously, he spent time at AWS Bedrock, MATS, and Harvard where he completed his BA and MA with a highest honors thesis on AI and democracy.\n\nIf you build robots or AI models, reach out! We'd love to put them to the test. Learn more at [robocurve.org](http://robocurve.org).", "url": "https://www.ycombinator.com/launches/TGj-robocurve-real-world-evaluations-of-physical-ai", "votes": 12, "created_at": "2026-08-27T20:30:00.743Z" } ] }, { "id": 33408, "name": "Salem Robotics Inc", "slug": "salem-robotics-inc", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/fbf386dc8fa91340ed1cce1b80613f66e88ee12d.png", "website": "https://salemroboticsinc.com", "all_locations": "San Francisco, CA, USA", "long_description": "Our software turns any robot we deploy into an everyday independent worker at your facility. They are able to walk sites, handle instruments, overcome obstacles, collect measurements, and generate auditable compliance records, replacing hours of mandatory manual surveys and inspections. Built by Los Alamos robotics veterans and deterministic-manipulation researchers, we started in nuclear and are already expanding to other hazardous industries.", "one_liner": "Deploying robots to replace workers in hazardous spaces", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1783052221, "tags": [ "Hard Tech", "Robotics", "Energy", "Defense", "Industrial" ], "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/salem-robotics-inc", "api": "https://devasheeshg.github.io/yc-api/batches/summer-2026/salem-robotics-inc.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/salem-robotics/", "x_url": "https://x.com/salemroboticshq", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/fbf386dc8fa91340ed1cce1b80613f66e88ee12d.png", "app_video_url": null, "dday_video_url": null, "company_photos": [ "https://bookface-images.s3.us-west-2.amazonaws.com/attachments/4593ea24a36e629876ca1a48e9e7db1a683530c2.png" ], "primary_partner": { "name": "Jon Xu", "url": "https://www.ycombinator.com/people/jon-xu" }, "founders": [ { "user_id": 3403013, "full_name": "Caleb Horan", "title": "Founder/CEO", "founder_bio": "Co-founder and CEO at Salem Robotics. Previously a published robotics PhD student at UT Austin, developing task planning for autonomous systems. NRC Fellow. Deployed multi-robot teams at Los Alamos National Laboratory's Plutonium Division. MS in Robotics from UT Austin.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/caleb-horan", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e7cff240bcb1484bcdff91bb1419d9c25f3162cf.jpg" }, { "user_id": 3208433, "full_name": "Janak (Crasun) Panthi", "title": "Founder/CTO", "founder_bio": "Co-founder and CTO at Salem Robotics Inc. PhD in Robotics from UT Austin (Dec. 2026). 6 yrs industry experience leading product development and deploying quadruped robots in nuclear facilities. US Army.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/janak-panthi", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/19b6a7b10bbd6739abbb938281eb9c068eebf9c0.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 108976, "title": "Salem Robotics - Autonomous robots for hazardous spaces", "tagline": "We deploy robots to perform autonomous inspections and surveys in hazardous spaces, like nuclear. ", "body": "We're [Caleb](https://www.linkedin.com/in/caleb-horan) and [Janak](https://www.linkedin.com/in/janak-panthi), PhD roboticists from UT Austin. We've spent a combined 15 years in nuclear, 10 of which deploying autonomous robots at Los Alamos National Lab, and we're building Salem Robotics.\\\n**TLDR:** Our software turns robots into independent survey and inspection workers at your facility.\n\n[Launch Video](https://youtu.be/7xObOE6knZM)\n\n## **Life and death pain worth $Millions/year**\n\nAt every nuclear facility, highly trained radiation-protection teams spend hours each day walking the site, filling out hand-drawn maps, and searching for something life-threatening: radiation. IN THE BEST CASE they find nothing, and still have to return to their posts to transcribe the data into a computer before doing the actual high-value work they were assigned. These surveys are time-consuming, dangerous, expensive, and prone to data inconsistencies that carry direct regulatory consequences.\n\nThe same pain exists well beyond nuclear. Whether it's gas-leak inspection or ammonia surveys, similar workflows run across oil, gas, chemical, biological, space, and other hazardous facilities.\n\n## **What we do**\n\nAn operator defines the work from a simple dashboard; the robot then navigates the site, handles instruments, opens doors, turns valves, collects measurements, and generates structured, auditable, compliance-ready reports. We're hardware-agnostic, so plants run our software on robots they already own, many of which sit in a closet today as \"$200k paperweights, \" or we can provide the right robot for the job. Our stack is designed for safety-critical infrastructure and comes with theoretical safety guarantees, exactly what regulators and plant leadership require. Our core manipulation framework was not possible before and is based on **breakthrough founder research** published and presented at the most prestigious IEEE journals and conferences in the world. \n\nWe're already in active contract-scoping conversations across the nuclear industry and oil & gas.\n\n**Our asks**\n\n* Intros to operations or innovation leaders in nuclear or similar hazardous sites (oil, gas, chem, bio, space).\n* Advice from founders who've sold into safety-critical industrial environments.\n* Sites where routine surveys are frequent, hard to staff, or particularly painful? We'd love to hear about them.\n\nComments, Emails, and DMs welcome. \\\n[Engage@salemroboticsinc.com](mailto:Engage@salemroboticsinc.com)", "url": "https://www.ycombinator.com/launches/SLg-salem-robotics-autonomous-robots-for-hazardous-spaces", "votes": 29, "created_at": "2026-08-04T19:00:03.963Z" } ] }, { "id": 34365, "name": "Runtime.si", "slug": "runtimesi", "former_names": [ "Lambda Robotics", "Runtime" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/461a9d05728add7a3449b82167ac418e94d301eb.png", "website": "https://runtime.si/", "all_locations": "San Francisco, CA, USA", "long_description": "Runtime is building the evaluation layer for physical intelligence. 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We combine operating procedures, enterprise data, and expert feedback to capture the rules and judgment behind complex processes. In customer-specific RL environments, we optimize the agent harness around each company’s systems, constraints, approvals, and exceptions.\r\n\r\nWe’re connecting to industrial hardware to bring live production data into the same feedback loop. 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Previously built systems for factories powering a $2B+ steel manufacturer (worthington steel), shipped medical devices for a $100B+ company (Stryker), and worked on projects for NASA astronauts.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/oscar-rangel", "x_url": "https://x.com/oscarrangelmora", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/821bac69e02067b2b3f58a5c4df05546e8881c37.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 35127, "name": "Rhem Labs", "slug": "rhem-labs", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/36cbf39bb5d034d7765e7ee595b7fac4dc2358e5.png", "website": "https://rhem.ai", "all_locations": "San Francisco, CA, USA", "long_description": "Rhem Labs builds smart home care devices that help older adults and people with complex care needs live independently. ", "one_liner": "Home care technology for aging parents and their families", "team_size": 2, "industry": "Healthcare", "subindustry": "Healthcare -> Consumer Health and Wellness", "launched_at": 1790296181, "tags": [ "Robotics", "Health & Wellness", "Consumer Products" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Fall 2026", "status": "Active", "industries": [ "Healthcare", "Consumer Health and Wellness" ], "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/rhem-labs", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/rhem-labs.json", "year_founded": 2025, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/rhem-labs/", "x_url": "https://x.com/rhem_labs", "fb_url": "https://www.facebook.com/p/Rhem-Labs-61589516291255/", "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/36cbf39bb5d034d7765e7ee595b7fac4dc2358e5.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Kulveer Taggar", "url": null }, "founders": [ { "user_id": 1690205, "full_name": "Jacob Shen", "title": "Founder/CTO", "founder_bio": "Founder and CEO of Rhem Labs. Previously Founding Engineer at Mattoboard. Researcher at Berkeley AI Research Lab, designing scalable autonomous driving systems. CS & DS @ UC Berkeley.", "is_active": true, "linkedin_url": "https://linkedin.com/in/jacobshenn", "x_url": "https://x.com/jacobshenn", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7ca561b3c3e92baf0165872ddf890095c47ccc12.jpg" } ], "jobs": [ { "id": 104064, "title": "Founding Creative Generalist", "url": "https://www.ycombinator.com/companies/rhem-labs/jobs/TCR7cgZ-founding-creative-generalist", "location": "San Mateo, CA, US", "type": "Full-time", "role": "Marketing", "role_type": null, "salary_range": "$70K - $110K", "equity_range": "0.50% - 1.50%", "experience": "Any (new grads ok)", "visa": "US citizen/visa only", "skills": [] } ], "news": [], "launches": [ { "id": 117929, "title": "Rhem Labs: Health assistant robots for your parents", "tagline": "Rhem handles everything that doesn’t need a pair of hands, while keeping you in the loop.", "body": "## TLDR:\n\n**Aging at home has a visibility problem. Small changes in health and routine can go unnoticed for weeks or months, until the first obvious sign is something serious. Rhem is a tabletop robot that helps families see those changes earlier, while giving parents the everyday support they need to stay independent longer. Rhem was designed with older adults in mind, but it’s for anyone who wants help getting things done and staying on top of their health.**\n\nPreorders are open now at \n\n\n\n## \n\n## The Problem\n\n**At some point, you start paying attention to your parents differently.**\n\nMaybe there was a scare. Maybe Mom missed an appointment. Maybe Dad sounds more tired. Or maybe nothing happened at all. You just start wondering whether everything is as fine as they say.\n\nIf you don’t live with them, you mostly get snapshots: a call, a text, a FaceTime.\n\n**You don’t see the full day.**\n\nYou don’t know if routines are slipping, something is getting harder, or a small change is becoming a pattern.\n\n**We learned this the hard way with my grandmother.**\n\nBefore her stroke, she was sleeping badly, talking less, and seemed unlike herself.\n\nThe signs were there. But my dad had a newborn and a full-time job. My grandfather was working too. Everyone cared, but no one saw the whole picture.\n\n**We each saw pieces. No one put them together until something much bigger happened.**\n\n## **How it works for your parents**\n\nRhem lives in the home and becomes the easiest way for your parent to get things done and keep track of their health.\n\nThey just need to say:\n\n“Remind me after dinner.”\n\n“When is my appointment?”\n\n“Order our usual groceries.”\n\n“Tell Jacob I need a ride tomorrow.”\n\nRhem can browse websites, make calls, manage reminders, answer questions, place supported orders, and follow up.\n\n**If it doesn’t require a pair of hands, Rhem can probably handle it.**\n\nThey can also take supported wellness readings on Rhem, keep track of routines, and see how things change over time.\n\nWhen something needs you, **Rhem brings you into the loop through the rhem connect app.** You can answer a question, add context, or help finish the task. **Help Rhem once, and it remembers how to do it next time.**\n\n![uploaded image](/media/?type=post&id=117929&key=user_uploads/1690205/9adf4655-4900-4fe0-bdec-29e333c8a3dd)\n\n## **How it works for families**\n\nYour parent gets an assistant. **You get a clearer picture of how they’re doing.**\n\nThe Rhem app brings together health readings, routines, requests, completed tasks, and alerts. You can see what changed, what Rhem handled, and when you’re needed.\n\nFrom anywhere, you can send reminders, leave voice messages, ask Rhem to check in, talk to your parent, or ask about information they’ve shared.\n\nOver time, Rhem helps you spot patterns. **One bad night may mean nothing. A month of worse sleep, missed appointments, and changes in routine is something you want to know about.**\n\n![uploaded image](/media/?type=post&id=117929&key=user_uploads/1690205/c7652236-3ca9-40a0-9ea8-d1e2160852fc)\n\n## **Why we built Rhem**\n\n**We’re a father-and-son team, and our family spent nearly two decades caring for loved ones at home.**\n\nBefore my grandmother had a stroke, there were signs that something was changing. She was sleeping badly, talking less, and seemed unlike herself. We all noticed pieces of it, but nobody had the full picture until much later.\n\nMy aunt had a different problem. A brain tumor left her with limited mobility, so a lot of everyday things depended on someone else being available. Making a call. Looking something up. Ordering something. Figuring out what needed to happen next.\n\nA lot of the time, she didn’t need someone physically next to her. She needed someone who could help her get things done.\n\nThat’s where Rhem came from.\n\n**We wanted something that could notice when things were changing, help with the everyday stuff, and bring family in when they were actually needed.**\n\nThe goal is simple: give our parents more independence, while letting us spend more time being their family instead of managing everything around them.\n\n## **Team**\n\nJacob: Berkeley CS & DS, researcher at Berkeley AI Robotics Lab with a focus on full stack autonomous driving and edge computing, founding engineer at Mattoboard.\n\nHuey: Executive leader with 30+ years of experience building smart hardware with embedded software at scale and leading global operations across North America, Europe, and Asia. \n\n![uploaded image](/media/?type=post&id=117929&key=user_uploads/1690205/2ae2c872-97c6-4ff3-9c05-dde53439c9b4)\n\n## Why order now\n\nIf you’re ordering a Founding Edition, thank you.\n\nWe know we’re asking you to trust a new company and buy something for someone you care deeply about. We don’t take that lightly.\n\n**Every Founding Edition includes:**\n\n* **Founding Price of $1099 before our price increase to $1499 on Jan 20th**\n* **1 x Halo Non-wearable Fall Detector ($80 Value)**\n* **2 years of Rhem Plus included ($480 Value)**\n* **2 x Merch Pack & Goodies**\n* **Direct access to our team** for setup, questions, and feedback\n\n**Thank you for being here at the beginning. We can’t wait for Rhem to start making your parents’ lives a little easier.**\n\nPreorder now at: \n\n**_Here's to more good years with the people who raised us. 💙_**\n\n**— Jacob & Huey**", "url": "https://www.ycombinator.com/launches/Ug5-rhem-labs-health-assistant-robots-for-your-parents", "votes": 7, "created_at": "2026-10-06T16:00:00.079Z" } ] }, { "id": 35224, "name": "Micora", "slug": "micora", "former_names": [ "Micora Energy" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/7fc1316658ceceb944d2c372912cac6b6db9e5ec.png", "website": "https://micora.com", "all_locations": "San Francisco, CA, USA", "long_description": "Micora builds a solar-farm-in-a-box that can be shipped anywhere and built without specialized labor. We have designed a new type of solar farm micorgrid that is palletized, lightweight, and deployable. Our system autonomously builds 100kWp of capacity per day and is easily scalable to MWs of capacity which is a size currently only serviced by slow moving and at capacity EPCs. \r\n\r\nAs demand from data centers, advanced manufacturing, and electrification strains existing power infrastructure, the ability to deploy substantial generation quickly is becoming increasingly valuable and unavailable. We are the only company that services utility-scale power needs in weeks. 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Morgan’s Healthcare Investment Banking group and was a founding team member at Pear Suite, an AI-enabled platform and provider network for community health workers (CHWs).", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/frederik-mareels", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/4fdab93252435eafd388ed9da5f52fe7125f97ed.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 35290, "name": "Antropi Robotics", "slug": "antropi-robotics", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b8c101f20a3b29a6ae368d81297168e49391e75a.png", "website": "https://www.antropi.world/", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "Autonomous CNC factories for faster hardware", "team_size": 0, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1786284917, "tags": [ "Robotics", "Manufacturing" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2026", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/antropi-robotics", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/antropi-robotics.json", "year_founded": null, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/antropi-robotics/", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/b8c101f20a3b29a6ae368d81297168e49391e75a.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": 2771579, "full_name": "Naman Gupta", "title": "Founder/CEO", "founder_bio": "Founder at Antropi Robotics.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/namangupta24/", "x_url": "https://x.com/namaangupta", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/198dcb03b52084327028f3f0ed3bbe71ee8f2090.jpg" }, { "user_id": 2771603, "full_name": "Shubh Agarwal", "title": "Founder/CTO", "founder_bio": "Founder at Antropi Robotics.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/shubhagarwal566/", "x_url": "https://x.com/Shubh__Agarwal_", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/595067adc4990aba2aa8149c62d3b0ae87788190.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 123265, "title": "Antropi Robotics | CNC parts in days, from autnomous factories", "tagline": "Turning your designs into precision metal parts in days", "body": "👋 **Hey Everyone!** I’m Naman. My best friend Shubh and I are building **Antropi Robotics**.\n\n**We make inspected CNC parts for hardware teams.** Our first factory is live and already shipping parts to customers with **lead times under 7 days**.\n\n**Our goal:** a network of autonomous factories across the US, making and delivering parts locally in as little as 24 hours.\n\n\n\n## ⚙️ Problem\n\nBefore starting Antropi, I spent six months running my dad’s CNC machining business in India. The biggest lesson was simple: **automating the machine is not the same as automating the factory.**\n\nA CNC machine can cut automatically. But someone still has to plan the job, load the machine, inspect the part, and decide what to do when something goes wrong.\n\nFor hardware teams, this becomes a familiar cycle. Prepare drawings. Request quotes. Go back and forth on manufacturing details. Wait for a production slot. Wait for the parts.\n\n**Every week spent waiting is a design iteration you don’t get before your next demo.**\n\nAdding a robot to load the machine fixes one step. It does not tell the factory whether the part is correct, or what should happen next.\n\n## 🤖 Solution\n\nWe’re building **dark factories: autonomous factories designed to run 24/7.** Our Factory OS connects job planning, CNC machines, robots, and inspection into one system.\n\nSoftware turns CAD into machining programs and checks them in simulation, with an engineer approving them before production.\n\nRobots load and unload. Machines cut. **Every part is inspected.**\n\nInspection feeds back into production, so the system can make supported corrections or stop the machine before a problem repeats.\n\n![uploaded image](/media/?type=post&id=123265&key=user_uploads/2771579/275935ea-e97d-40e7-b0fa-cc9d04977486)\n\nFor you, it’s simple: upload your CAD, confirm your requirements, and receive inspected parts with an inspection report.\n\n**You buy parts. We handle the factory.**\n\nWe’re also building agent ordering through our MCP server and a **Rush option** for priority production.\n\n![uploaded image](/media/?type=post&id=123265&key=user_uploads/2771579/c7d0124b-0e12-4a10-b4ca-322ecac60205)\n\n\n## 🌎 Vision\n\n**One factory is the start. The network is the point.**\n\nOur long-term plan is hundreds, eventually thousands, of microfactories across the US, close to the teams building hardware. The same Factory OS will coordinate production across the network.\n\nAutonomy removes waiting inside the factory. Local production puts the finished part closer to you.\n\nThe target: **American-made precision at China-competitive prices**, with local delivery in as little as 24 hours for supported parts.\n\nShenzhen-like speed, without needing to build in Shenzhen.\n\n![uploaded image](/media/?type=post&id=123265&key=user_uploads/2771579/e012541d-ba88-4809-9423-a1935c878aec)\n\n\n## 🛠️ We’ve spent nine years getting hardware built.\n\nShubh and I met in college in 2017. We both studied computer science, built Mars rovers together, and competed internationally. We also spent plenty of days in CNC shops waiting for parts.\n\nBefore running my dad’s business, I was the first employee and Chief of Staff at Accio Robotics, a warehouse automation company in India, participating in its journey from the first product through scaling and acquisition.\n\nShubh completed his Master’s in Robotics at the University of Pennsylvania, working with robotic manipulators. After his master’s, we started Antropi.\n\nWe have experienced this problem as the people waiting for parts and as the people responsible for making them.\n\n**Now we’re building the factories we wish we’d had.**\n\n## 🙌 Ask\n\n**Need CNC parts?** Send us your most challenging part and we’ll get it done. \n\n👉 [www.antropi.shop](http://antropi.shop)\n\n**Know a team scaling production?** We’d appreciate introductions to hardware or procurement teams at Series B+ companies in computing infrastructure, robotics, medical devices, and energy.\n\nWe’re happy to start with one part and earn the next order.\n\n**Naman & Shubh**\n\nAntropi Robotics", "url": "https://www.ycombinator.com/launches/W49-antropi-robotics-cnc-parts-in-days-from-autnomous-factories", "votes": 5, "created_at": "2026-10-19T18:00:00.087Z" } ] }, { "id": 35389, "name": "Open Actuation", "slug": "open-actuation", "former_names": [ "Pendulum Robotics" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/04bbecc591031b8b78b9a43b4f8c9cd329829f72.png", "website": "https://openactuation.com", "all_locations": "Los Angeles, CA, USA", "long_description": "We design and manufacture high-mix drone motors and robotic actuators in LA.\r\n\r\nDJI, Apple, and Ford don't settle for OTS components. Likewise, the teams that win the Western robotics market will build seamless machines from tightly integrated software and hardware. \r\n\r\nOpen Actuation designs motors and actuators around your robot's unique form factor and mission - then we rapidly bring them to life with proprietary software and tooling geared for high-mix machining and assembly. We've designed and built motors for top drone OEMs and can assemble thousands of motors per month at our first factory in LA.\r\n\r\nWe're doing for motion components what 3D printing has done for structural components. This enables hardware teams to build and iterate at the speed of software so they can create elegant, reliable, ROI-positive robots and win massive markets.", "one_liner": "Quick-turn, purpose-built motors & actuators for all", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1790141770, "tags": [ "Hard Tech", "Robotics", "Drones", "Manufacturing", "Electronics" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2026", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/open-actuation", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/open-actuation.json", "year_founded": 2026, "city": "Los Angeles", "country": "US", "linkedin_url": "https://www.linkedin.com/company/143885703", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/04bbecc591031b8b78b9a43b4f8c9cd329829f72.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Charlie Warren", "url": null }, "founders": [ { "user_id": 1253977, "full_name": "Jon Facer", "title": "Founder/CEO", "founder_bio": "Founder at Open Actuation - electric motors and actuator mfg.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/jon-facer-a88341145/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/5613a845c13d368aec637282de95932c4733fa86.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 35454, "name": "Shepherd Robotics", "slug": "shepherd-robotics", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/aeedcbe594abc3d35bb21642c507ec105a0f502a.png", "website": "https://shepherdrobotics.ai/", "all_locations": "San Francisco, CA, USA", "long_description": "Shepherd Robotics builds general purpose robots for skilled physical work across AI infrastructure and advanced manufacturing. Our robots are powered by robot foundation models and use modular, flexible hardware designed to adapt to different environments and tasks. We train our systems on a combination of real world and simulation data so they can learn complex manipulation skills and generalize across workflows. We also provide integration into customers’ existing workflows, starting with data center construction and operations, electrical manufacturing and testing, and electronics manufacturing, where traditional automation struggles with variability, dexterity, and changing environments. ", "one_liner": "Robots for high skilled labor powering AI infrastructure", "team_size": 4, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1789000982, "tags": [ "Hardware", "Robotics", "Manufacturing", "Automation", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2026", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/shepherd-robotics", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/shepherd-robotics.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/aeedcbe594abc3d35bb21642c507ec105a0f502a.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Charlie Warren", "url": null }, "founders": [ { "user_id": 987072, "full_name": "Feifei Duan", "title": "Founder/CEO", "founder_bio": "Cofounder and CEO at Shepherd Robotics. Ex-Waymo and Chef Robotics engineer.\nTrained large transformer models at Waymo and deployed robots into large food factories at Chef Robotics.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/feifei-duan-607255125", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/e18794d104befc26ce95ece503c146710f1faed3.jpg" }, { "user_id": 778599, "full_name": "David Fang", "title": "Founder/CTO", "founder_bio": "David Fang is co-founder and CTO of Shepherd Robotics. Previously, he was a Research Scientist at Dyna Robotics working on large-scale robot learning, and building ML systems for autonomous driving at Cruise.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/da-fang-8273b7116/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/2ec6f51146461b14b10ea90c0da6865162e995e2.jpg" }, { "user_id": 2562853, "full_name": "Kai Ru", "title": "Founder", "founder_bio": "Founder at Shepherd Robotics. x Cruise & Rivian self driving cars, planning, research, foundational models.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/pengkai-r-07086633/", "x_url": "", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/223c45b3097c524878bc0283aafac05c2146b6d9.jpg" } ], "jobs": [], "news": [], "launches": [] }, { "id": 35455, "name": "Deploy", "slug": "deploy", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/6d01c6f3a4b9cb73c5468cd6441f7c93909edb6a.png", "website": "https://deployrobotics.co/", "all_locations": "San Francisco, CA, USA", "long_description": "Deploy's core belief is that robots should be useful. Getting a generalist robot to do real work is fundamentally the same problem across industries. We build everything between the model and the task to bring generalist robots to the businesses that actually need them.", "one_liner": "The generalist robot deployment company.", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1789089952, "tags": [ "Robotics" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2026", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/deploy", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/deploy.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "https://www.linkedin.com/company/deployrobotics", "x_url": "https://x.com/deployrobo", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/6d01c6f3a4b9cb73c5468cd6441f7c93909edb6a.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Christopher Golda", "url": "https://www.ycombinator.com/people/christopher-golda" }, "founders": [ { "user_id": 3593535, "full_name": "Sahith Reddy Chada", "title": "Founder", "founder_bio": "Deploying generalist robots at Deploy. Research Engineer at Honda Research Institute building vision-language-action models and world models for robotics and autonomous vehicles. MS Robotics from UMn, BTech Aerospace Engineering from IIT Kanpur.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/sahith-reddy-chada", "x_url": "https://x.com/sahithchada", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/7420ef4a0d182dfb06daee92dc8e49c3fa294297.jpg" }, { "user_id": 3445935, "full_name": "Irene Grace Karot Polson", "title": "Founder", "founder_bio": "Deploying generalist robots at Deploy. Previously Autonomy Engineer at AeroVect, deploying self-driving vehicles at airports, flight data at Airbus. MS Robotics from UPenn, BS Aerospace from IIT Kanpur.", "is_active": true, "linkedin_url": "https://www.linkedin.com/in/irene-grace-karot-polson/", "x_url": "https://x.com/irenekarrot", "avatar_thumb_url": "https://bookface-images.s3.us-west-2.amazonaws.com/avatars/0d0cff2b295376185f768d9e81a3e11d369263c8.jpg" } ], "jobs": [], "news": [], "launches": [ { "id": 121648, "title": "Deploy - The Generalist Robot Deployment Company", "tagline": "We turn generalist robots into a reliable workforce. ", "body": "Hello world, we’re [Irene](https://www.linkedin.com/in/irene-grace-karot-polson/) & [Sahith](https://www.linkedin.com/in/sahith-reddy-chada/), co-founders of [Deploy](https://deployrobotics.co/)!\\\n\\\n**TL;DR:** Deploy puts generalist robots, aka humanoid arms, to work in real businesses as a service. You pay for the work getting done (packing, kitting, returns, manufacturing, data center maintenance), not the robot.\n\n\n\n**Problem:** \\\nThe world was full of physical tasks no technology could automate till now. Generalist robot models can finally handle the messy, variable work that traditional automation never could: mixed orders, returns, tasks that change every day.\n\nBut a capable model isn't the same as a robot reliably doing the job on your floor. Most robotics projects stall in the gap between a good demo and a shift that runs 24/7. \n\n**Solution:** \\\nDeploy closes that gap. We’re the generalist robot deployment company. We turn generalist robots into reliable workers, and our customers pay for completed work, not the robot.\n\n**How it works:** \\\n→ We break each new task into a sequence of steps and track progress in real time\\\n→ The system knows what's done, what's next, and when a robot needs help\\\n→ Every human intervention becomes training data, so the robots get better the longer they run\n\n**The backstory**\\\n[Irene](https://www.linkedin.com/in/irene-grace-karot-polson/) and [Sahith](https://www.linkedin.com/in/sahith-reddy-chada/) have been building robots for over a decade, from opposite ends of the stack. Sahith built robot models at Honda Research Institute. Irene deployed autonomous vehicles in safety-critical airport environments. We kept hitting the same wall: deployment. Deploying across different robots and different models is fundamentally the same problem. If it’s one problem, one platform can solve it. So we’re building Deploy.\n\n![uploaded image](/media/?type=post&id=121648&key=user_uploads/3445935/cd171680-2427-4c8f-80fc-ceb223d46485)\n\n**Ask:** \\\nCan you introduce us to 3PLs, brands, warehouses or distribution centers that could benefit from rolling out robotics as a workforce? Reach us at [founders@deployrobotics.co](mailto:founders@deployrobotics.co) or [deployrobotics.co](http://deployrobotics.co).", "url": "https://www.ycombinator.com/launches/Ve4-deploy-the-generalist-robot-deployment-company", "votes": 7, "created_at": "2026-10-14T14:30:00.140Z" } ] }, { "id": 35523, "name": "twentyfour26", "slug": "twentyfour26", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ceb91f5325b460f109e85bc25abd1618a24863cb.png", "website": "https://twentyfour26.com/", "all_locations": "San Francisco, CA, USA", "long_description": "twentyfour26 builds autonomous CNC machining cells for rapid prototyping, so hardware teams can iterate with software speed.", "one_liner": "On Demand CNC Prototyping ", "team_size": 2, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1786424480, "tags": [ "Robotics", "Manufacturing", "Industrial" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2026", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": null, "url": "https://www.ycombinator.com/companies/twentyfour26", "api": "https://devasheeshg.github.io/yc-api/batches/fall-2026/twentyfour26.json", "year_founded": 2026, "city": "San Francisco", "country": "US", "linkedin_url": "", "x_url": "", "fb_url": null, "cb_url": null, "github_url": null, "logo_url": "https://bookface-images.s3.amazonaws.com/small_logos/ceb91f5325b460f109e85bc25abd1618a24863cb.png", "app_video_url": null, "dday_video_url": null, "company_photos": [], "primary_partner": { "name": "Charlie Warren", "url": null }, "founders": [ { "user_id": 2845196, "full_name": "Hemant Mahendru", "title": "Founder/CEO", "founder_bio": "Co-founder at twentyfour26. 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Compute costs keep soaring amidst a global LPDDR shortage; NVIDIA just doubled the prices of Jetsons in July.\n\n**We're taking a contrarian bet that the future is moving inference _off the robot_ and _into the cloud._**\n\n![uploaded image](/media/?type=post&id=115448&key=user_uploads/3499827/4ca20fc9-00a8-4043-bc43-d51b8b5d0cbf)\n\nHow do we do this? 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