[ { "id": 150, "name": "Custora", "slug": "custora", "former_names": [], "small_logo_thumb_url": "/company/thumb/missing.png", "website": "http://custora.com", "all_locations": "New York, NY, USA", "long_description": "Custora is an advanced segmentation platform designed to help online retailers better understand and market to their customers. We’re on a mission to remove the “mass” from marketing with software tools that focus on customers as individuals with unique needs and interests. Our software employs the state-of-the-art in customer analytics methodologies and integrates directly with marketing tools (ESPs, display, Facebook Custom Audiences, Google Customer Match) to help marketers deliver more relevant, meaningful communications. \n\nWe’re excited to work with some of the leading retail innovators including Teleflora, Bonobos, 7 for All Mankind, and many more retailers spread throughout the world. Our offices are located in the Flatiron district of Manhattan. We work hard, work together, and care deeply about building a meaningful business, collaborative team, and exceptional culture that we’re proud to be a part of.\n\nAnd yes, we're hiring. Check out https://www.custora.com/careers for details.", "one_liner": "Custora is a predictive analytics platform for e-commerce marketing…", "team_size": 11, "industry": "B2B", "subindustry": "B2B -> Analytics", "launched_at": 1326789820, "tags": [ "E-Commerce", "Analytics", "Retail Tech" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2011", "status": "Acquired", "industries": [ "B2B", "Analytics" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/custora", "api": "https://yc-oss.github.io/api/batches/winter-2011/custora.json" }, { "id": 493, "name": "RADAR", "slug": "radar", "former_names": [ "Skip", "Automaton", "NoQ" ], "small_logo_thumb_url": "/company/thumb/missing.png", "website": "https://goradar.com", "all_locations": "New York, NY, USA", "long_description": "RADAR is an RF Sensing platform built to automate and augment retail store processes. Our technology offers unprecedented speed and location accuracy, which allows stores to:\r\n\r\n1) Manage inventory efficiently, through automated inventory counts, improved in-store replenishment and instantaneous customer stock checks\r\n\r\n2) Eliminate checkout lines altogether through our autonomous checkout tool.\r\n\r\n3) Measure all customer-product interactions, giving physical stores the same insight into consumer behavior and product performance as online stores.\r\n\r\nhttps://goradar.com", "one_liner": "RADAR is building technology to completely transform the in-store…", "team_size": 120, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1354492792, "tags": [ "Retail Tech", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2013", "status": "Active", "industries": [ "B2B", "Retail" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/radar", "api": "https://yc-oss.github.io/api/batches/winter-2013/radar.json" }, { "id": 804, "name": "Dealyze", "slug": "dealyze", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/1374fe13d174c148fb1387b6b1974226f5411900.png", "website": "http://dealyze.com", "all_locations": "San Francisco, CA, USA", "long_description": "Dealyze is an in-store digital custom rewards and referral program with automated marketing tools for small businesses that is proven to bring back customers. Tailored to your specific needs, Dealyze ensures every transaction is a chance to build a relationship. Our mission is to bring a powerful digital marketing platform to any store. We hope to even the playing field by doing our part in building the next generation of business tools. Dealyze has the backing of top-tier investors including Y-Combinator. The company is headquartered in Silicon Valley.\r\n\r\nVisit www.Dealyze.com to learn more about the company, schedule a demo, or just inquire about joining us.", "one_liner": "Dealyze helps national retailers build exceptional customer and…", "team_size": 6, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1416306327, "tags": [ "Retail Tech", "Retail" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2015", "status": "Inactive", "industries": [ "B2B", "Retail" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/dealyze", "api": "https://yc-oss.github.io/api/batches/winter-2015/dealyze.json" }, { "id": 929, "name": "Prayas Analytics", "slug": "prayas-analytics", "former_names": [ "Prayas Analytics MetricBoy", "SimpleMoney" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/5239f1a49fa06d125e98d56bb9e5a5fd04d9f05a.png", "website": "http://prayasanalytics.com", "all_locations": "New York, NY, USA", "long_description": "Prayas Anaytics helped retailers A/B test their stores, the way eCommerce companies A/B test their websites. We did this by continuously collecting data on customer movement using existing security cameras already in a retailer's stores. \r\n\r\nWe were a Y Combinator backed company (S15) and worked with several retailers including Barneys, Payomatic, and multiple Fortune 200 retailers.", "one_liner": "A/B testing for brick-and-mortar stores.", "team_size": 2, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1430156128, "tags": [ "SaaS", "Computer Vision", "Retail Tech" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2015", "status": "Inactive", "industries": [ "B2B", "Retail" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/prayas-analytics", "api": "https://yc-oss.github.io/api/batches/summer-2015/prayas-analytics.json" }, { "id": 1058, "name": "Caper", "slug": "caper", "former_names": [ "QueueHop" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/45034c22d81491a4e49c2c46c3c822d2d820941d.png", "website": "https://www.caper.ai/", "all_locations": "", "long_description": "Caper focuses on compacting Amazon-Go's technology (image recognition, sensor fusion and artificial intelligence) into a smart shopping cart, allowing each shopper to throw her groceries into the cart and self-checkout without cashiers. The technology is looking to fundamentally transform physical retail and rapidly scale into existing grocery stores.", "one_liner": "Plug-and-play cashier-less retail powered by computer vision and AI", "team_size": 15, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1447654816, "tags": [ "Artificial Intelligence", "Cashierless Checkout", "Computer Vision", "Retail Tech" ], "tags_highlighted": [], "top_company": true, "isHiring": false, "nonprofit": false, "batch": "Winter 2016", "status": "Acquired", "industries": [ "B2B", "Retail" ], "regions": [ "Unspecified" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/caper", "api": "https://yc-oss.github.io/api/batches/winter-2016/caper.json" }, { "id": 1603, "name": "Standard AI", "slug": "standard-ai", "former_names": [ "Standard Cognition" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/06e2c69e078611382e48b1e2dbdf6cdf9d2e89cd.png", "website": "https://standard.ai", "all_locations": "San Francisco, CA, USA; Milan, Lombardy, Italy; Remote", "long_description": "Standard Cognition is an artificial intelligence platform that allows buyers to grab what they want without having to go to a cashier.", "one_liner": "AI-powered checkout for retail.", "team_size": 150, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1493264508, "tags": [ "Retail Tech", "Retail", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Summer 2017", "status": "Active", "industries": [ "B2B", "Retail" ], "regions": [ "United States of America", "Italy", "America / Canada", "Europe", "Remote", "Fully Remote" ], "stage": "Growth", "app_video_public": false, "demo_day_video_public": true, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/standard-ai", "api": "https://yc-oss.github.io/api/batches/summer-2017/standard-ai.json" }, { "id": 1912, "name": "Inokyo", "slug": "inokyo", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/dc7d9010a87027e6273b47d80643278ca2e03619.png", "website": "https://www.inokyo.com", "all_locations": "San Francisco, CA, USA", "long_description": "", "one_liner": "We bring physical stores to the digital age with cashierless checkout.", "team_size": 10, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1524708162, "tags": [ "Cashierless Checkout", "Retail Tech" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2018", "status": "Inactive", "industries": [ "B2B", "Retail" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/inokyo", "api": "https://yc-oss.github.io/api/batches/summer-2018/inokyo.json" }, { "id": 11919, "name": "Taobotics", "slug": "taobotics", "former_names": [ "Taobotics LLC (深圳朝闻道智能信息科技有限公司)", "Taobotics", "Taobotics LLC (深圳朝闻道智能信息科技有限公司)" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3d0e3ce55ca8677b9d988629af543689812cee7b.png", "website": "http://www.taobotics.com", "all_locations": "Shenzhen, Guangdong, China", "long_description": "", "one_liner": "Autonomous robots for retails. ", "team_size": 11, "industry": "Industrials", "subindustry": "Industrials -> Manufacturing and Robotics", "launched_at": 1540872262, "tags": [ "Robotics", "Retail Tech" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2019", "status": "Active", "industries": [ "Industrials", "Manufacturing and Robotics" ], "regions": [ "China", "East Asia" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/taobotics", "api": "https://yc-oss.github.io/api/batches/winter-2019/taobotics.json" }, { "id": 12041, "name": "Maitian.ai", "slug": "maitian-ai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/cb5be1c92ec05006ff45634b3add27f2e9ab7e77.png", "website": "https://maitian.ai", "all_locations": "Singapore, Singapore", "long_description": "Open, grab-n-go marketplace powered by computer vision. We invite partners like chained restaurants to run most of the logistics. By giving them more customers, we get a cut of each sale ;)", "one_liner": "We make $1,000 Amazon Go stores.", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1541561697, "tags": [ "Retail Tech" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2019", "status": "Inactive", "industries": [ "B2B", "Retail" ], "regions": [ "Singapore", "Southeast Asia" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/maitian-ai", "api": "https://yc-oss.github.io/api/batches/winter-2019/maitian-ai.json" }, { "id": 12527, "name": "matagora", "slug": "matagora", "former_names": [ "Matagora Inc.", "Matagora" ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/618092b9f9611a5482457ec1415c39b04deacbf0.png", "website": "https://www.matagora.com", "all_locations": "Montreal, QC, Canada; Remote", "long_description": "At Matagora, our team brings over a decade of retail experience. Our mission is to empower independent retailers with the tools they need to compete with big box stores and effectively level out the playing field. One of the biggest challenges we see is staffing — many retailers struggle to maintain consistent, reliable, and properly trained team members to handle back-office tasks, marketing, ecommerce, POS management, and basic tech know-how.\r\n\r\nThat’s why we offer affordable, ecommerce expertise as a service. Retailers no longer have to worry about high turnover, constant retraining, or trying to learn everything themselves. Instead, they can stay focused on what they love: curating great products and delivering an amazing in-store experience — while we handle the rest. And since it’s a simple expense, it’s easy to plan for and write off, too.", "one_liner": "Empowering local retailers with tech that works for them.", "team_size": 5, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1679586248, "tags": [ "Marketplace", "Marketing", "Retail Tech", "Retail" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2019", "status": "Active", "industries": [ "B2B", "Retail" ], "regions": [ "Canada", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/matagora", "api": "https://yc-oss.github.io/api/batches/summer-2019/matagora.json" }, { "id": 13240, "name": "Vori", "slug": "vori", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/ce04cea0c7c1fdd2893b4d50aca57d665d3153ef.png", "website": "https://www.vori.com", "all_locations": "San Francisco, CA, USA; East Palo Alto, CA, USA", "long_description": "Vori offers a modern operating system designed for the grocery industry. VoriOS helps independent and regional grocers streamline their inventory management, ordering, and supplier coordination, allowing them to operate more efficiently and profitably. The platform integrates real-time data to optimize stock replenishment and improve pricing strategies. Founded in 2019, Vori empowers grocers with technology that levels the playing field against larger retailers.", "one_liner": "Vori is a modern operating system for supermarkets", "team_size": 29, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1584148900, "tags": [ "Grocery", "SaaS", "Retail Tech" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2020", "status": "Active", "industries": [ "B2B", "Retail" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Growth", "app_video_public": true, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/vori", "api": "https://yc-oss.github.io/api/batches/winter-2020/vori.json" }, { "id": 13349, "name": "SprintAI", "slug": "sprintai", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/88ed649d4ffefdc8e5652f12e5915dd242bed4ff.png", "website": "https://www.getsprint.ai/", "all_locations": "Bengaluru, KA, India", "long_description": "AI Platform that powers the brands & retailers of tomorrow. SprintAI helps the brands in better decision making & automating various processes in Inventory Management & Omnichannel Fulfilment.", "one_liner": "AI-led platform for inventory and fulfillment optimization", "team_size": 10, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1599935349, "tags": [ "Machine Learning", "SaaS", "Retail Tech" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Winter 2020", "status": "Inactive", "industries": [ "B2B", "Retail" ], "regions": [ "India", "South Asia" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/sprintai", "api": "https://yc-oss.github.io/api/batches/winter-2020/sprintai.json" }, { "id": 22055, "name": "Drapr", "slug": "drapr", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/95e53cdae8e9da9ed50d96445eabb8bd2cde68a6.png", "website": "https://drapr.com", "all_locations": "Berkeley, CA, USA", "long_description": "Drapr lets shoppers try on clothing, online. Apparel brands use Drapr to make more money online. ", "one_liner": "Try on clothing online", "team_size": 7, "industry": "Consumer", "subindustry": "Consumer -> Home and Personal", "launched_at": 1597608715, "tags": [ "SaaS", "E-commerce", "Retail Tech" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2020", "status": "Acquired", "industries": [ "Consumer", "Home and Personal" ], "regions": [ "United States of America", "America / Canada", "Remote", "Partly Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/drapr", "api": "https://yc-oss.github.io/api/batches/summer-2020/drapr.json" }, { "id": 23598, "name": "SwiftSku", "slug": "swiftsku", "former_names": [ "SwiftSku", "Inc." ], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/3bb40b858fa07c3be03a29e849b4171670bbe91c.png", "website": "https://swiftsku.com", "all_locations": "New York, NY, USA; Remote", "long_description": "SwiftSku connects the $650B convenience store industry with management and analytics. \r\n\r\nSwiftSku’s app connects to point of sales at convenience stores in real time, enabling owners to remotely manage and monitor their stores. We take the guesswork out of running a convenience store with predictive analytics, dashboards, and reports.\r\n\r\nSwiftSku's CEO, Mit Patel, grew up managing the inventory, pricebook, and reporting of his family’s convenience stores, and, when vendors would come by, he’d bridge the language barrier as a translator. More than 85% of independent convenience stores are owned by Indian families like Mit’s.\r\n\r\nSolving convenience store owners' pains of today leads to SwiftSku's greater vision of optimizing the supply chain, facilitating a retailer agnostic consumer to brand relationship, and providing real time insights to brands and retailers.", "one_liner": "Management and analytics software for convenience stores", "team_size": 35, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1614638915, "tags": [ "Fintech", "SaaS", "B2B", "Analytics", "Retail Tech" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2021", "status": "Active", "industries": [ "B2B", "Retail" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/swiftsku", "api": "https://yc-oss.github.io/api/batches/winter-2021/swiftsku.json" }, { "id": 29834, "name": "Rastro", "slug": "rastro", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/447ef3f5bdd55f339b07fe098ff620ccfd86af36.png", "website": "https://rastro.ai", "all_locations": "London, England, United Kingdom", "long_description": "We help distributors and manufacturers turn catalog chaos into launch-ready products. Share vendor data, pull online specs and pricing, fuzzy match to your database, generate images, and output products in your exact schema.", "one_liner": "The fastest way to launch product catalogs.", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1721284235, "tags": [ "Artificial Intelligence", "Manufacturing", "Retail Tech", "Retail" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Summer 2024", "status": "Active", "industries": [ "B2B", "Retail" ], "regions": [ "United Kingdom", "Europe" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/rastro", "api": "https://yc-oss.github.io/api/batches/summer-2024/rastro.json" }, { "id": 30031, "name": "Getcho", "slug": "getcho", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/b0bca661527cf93aad335c4ac4c75dfec9d20d7d.png", "website": "https://getcho.app/", "all_locations": "New York, NY, USA; Remote", "long_description": "Getcho is a local delivery platform for high-value goods. \r\n\r\nWe are building a high-reliability delivery network on top of high-volume, unreliable fleets, just like how TCP builds reliable end-to-end networking on top of an unreliable base network (IP).", "one_liner": "The reliability platform for last-mile delivery", "team_size": 3, "industry": "B2B", "subindustry": "B2B -> Supply Chain and Logistics", "launched_at": 1725840551, "tags": [ "SaaS", "Delivery", "Logistics", "E-commerce", "Retail Tech" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2024", "status": "Active", "industries": [ "B2B", "Supply Chain and Logistics" ], "regions": [ "United States of America", "America / Canada", "Remote", "Fully Remote" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/getcho", "api": "https://yc-oss.github.io/api/batches/fall-2024/getcho.json" }, { "id": 30103, "name": "Metreecs", "slug": "metreecs", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/0896c8d6a3292048c3275f782ddd6f5a282d3e4a.png", "website": "https://www.metreecs.com", "all_locations": "", "long_description": "Metreecs helps retailers plan, buy, and allocate products using AI-demand forecasting. We prevent overstock and out-of-stock situations, allowing clients to eliminate waste, free up capital, and drive higher sales.", "one_liner": "AI-powered demand forecasting for retail", "team_size": 6, "industry": "B2B", "subindustry": "B2B -> Retail", "launched_at": 1729012958, "tags": [ "Machine Learning", "Retail Tech", "AI" ], "tags_highlighted": [], "top_company": false, "isHiring": false, "nonprofit": false, "batch": "Fall 2024", "status": "Active", "industries": [ "B2B", "Retail" ], "regions": [ "Unspecified" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/metreecs", "api": "https://yc-oss.github.io/api/batches/fall-2024/metreecs.json" }, { "id": 30318, "name": "Wildcard", "slug": "wildcard", "former_names": [], "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/f6dd000652c5e77966ee483897c0ffed9dac2d80.png", "website": "https://wild-card.ai", "all_locations": "San Francisco, CA, USA", "long_description": "Wildcard is the AEO and GEO platform designed specifically for e-commerce and retail brands. We help merchants improve visibility across AI search and AI shopping platforms like ChatGPT, Google AI Overviews, Gemini, and Amazon Rufus.\r\n\r\nWildcard tracks how brands, categories, collections, and SKUs appear across AI search results, identifies visibility gaps, and turns those insights into actions. We use AI agents to enrich product data, generate SEO, AEO, and GEO content, create collection and comparison pages, build FAQs, and improve off-site discoverability across Reddit, YouTube, blogs, and other sources.\r\n\r\nAs AI shopping evolves, Wildcard is building the infrastructure brands need to win in agentic commerce, including support for emerging standards like the Agentic Commerce Protocol (ACP) and Universal Commerce Protocol (UCP).", "one_liner": "AEO/GEO for E-Commerce and Retail", "team_size": 0, "industry": "B2B", "subindustry": "B2B -> Engineering, Product and Design", "launched_at": 1738308751, "tags": [ "Artificial Intelligence", "Generative AI", "E-commerce", "Marketing", "Retail Tech" ], "tags_highlighted": [], "top_company": false, "isHiring": true, "nonprofit": false, "batch": "Winter 2025", "status": "Active", "industries": [ "B2B", "Engineering, Product and Design" ], "regions": [ "United States of America", "America / Canada" ], "stage": "Early", "app_video_public": false, "demo_day_video_public": false, "app_answers": null, "question_answers": false, "url": "https://www.ycombinator.com/companies/wildcard", "api": "https://yc-oss.github.io/api/batches/winter-2025/wildcard.json" } ]