[
  {
    "id": 245,
    "name": "Directed Edge",
    "slug": "directed-edge",
    "former_names": [],
    "small_logo_thumb_url": "/company/thumb/missing.png",
    "website": "http://directededge.com",
    "all_locations": "San Francisco, CA, USA",
    "long_description": "Directed Edge delivers Amazon-like \"People who bought this also bought...\" and \"We think you'd also like\"-style recommendations to other sites, using existing data being collected such as purchase or click histories. Recommendations are served in real-time via a REST API, with language bindings in several programming languages to make integration easy.",
    "one_liner": "Product recommendations.",
    "team_size": 2,
    "industry": "Consumer",
    "subindustry": "Consumer -> Home and Personal",
    "launched_at": 1326790627,
    "tags": [
      "Artificial Intelligence",
      "Machine Learning",
      "Recommendation System"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2009",
    "status": "Active",
    "industries": [
      "Consumer",
      "Home and Personal"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": false,
    "url": "https://www.ycombinator.com/companies/directed-edge",
    "api": "https://yc-oss.github.io/api/batches/summer-2009/directed-edge.json"
  },
  {
    "id": 253,
    "name": "Fanchatter",
    "slug": "fanchatter",
    "former_names": [],
    "small_logo_thumb_url": "/company/thumb/missing.png",
    "website": "http://fanchatter.com",
    "all_locations": "Minneapolis, MN, USA",
    "long_description": "FanChatter fuels your fans so they can promote you better than any ad ever could.\n\nOur customers are big guys (NBC Universal, Clear Channel, Gannett) and little guys (bloggers all over the world) who pay us to source and showcase the most abundant yet least leveraged marketing material on the planet...\n\nPure, voluntary social chatter about your interest. FanChatter offers you the tools to find it, refine it, and make it multiply.\n\nAnd that is the future of advertising.",
    "one_liner": "FanChatter aggregates, amplifies and empowers fan content on every…",
    "team_size": 11,
    "industry": "B2B",
    "subindustry": "B2B -> Marketing",
    "launched_at": 1326790698,
    "tags": [
      "Social",
      "Recommendation System"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Summer 2009",
    "status": "Inactive",
    "industries": [
      "B2B",
      "Marketing"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": false,
    "url": "https://www.ycombinator.com/companies/fanchatter",
    "api": "https://yc-oss.github.io/api/batches/summer-2009/fanchatter.json"
  },
  {
    "id": 25969,
    "name": "Shaped",
    "slug": "shaped",
    "former_names": [
      "shaped.ai Inc."
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/241b1f1931647920258ef5ae6571461ada0b62f1.png",
    "website": "https://shaped.ai",
    "all_locations": "New York, NY, USA",
    "long_description": "Connect your data. Train your models. Query text, user or session context and retrieve relevant results in milliseconds. Explore our case studies to see how we’ve helped leading brands drive significant engagement and revenue: https://www.shaped.ai/case-study. ",
    "one_liner": "The real-time retrieval engine for search, feeds, and agents.",
    "team_size": 25,
    "industry": "B2B",
    "subindustry": "B2B -> Infrastructure",
    "launched_at": 1646119340,
    "tags": [
      "Search",
      "AI",
      "Recommendation System"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": true,
    "nonprofit": false,
    "batch": "Winter 2022",
    "status": "Active",
    "industries": [
      "B2B",
      "Infrastructure"
    ],
    "regions": [
      "United States of America",
      "America / Canada"
    ],
    "stage": "Growth",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": false,
    "url": "https://www.ycombinator.com/companies/shaped",
    "api": "https://yc-oss.github.io/api/batches/winter-2022/shaped.json"
  },
  {
    "id": 27734,
    "name": "Rubber Ducky Labs",
    "slug": "rubber-ducky-labs",
    "former_names": [
      "Rubber Ducky Labs",
      "Inc."
    ],
    "small_logo_thumb_url": "https://bookface-images.s3.amazonaws.com/small_logos/80d1f55be06d00fd52db1ea9553e87aa6f8ac9d1.png",
    "website": "https://www.rubberduckylabs.io/",
    "all_locations": "San Francisco, CA, USA; Remote",
    "long_description": "We built Rubber Ducky Labs to help e-commerce teams effortlessly improve product discovery through better metadata. Our tool enables non-technical users to leverage multi-modal AI on product catalogs—just upload a CSV and start tagging metadata in minutes.",
    "one_liner": "AI Powered Product Discovery",
    "team_size": 2,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1671139016,
    "tags": [
      "Artificial Intelligence",
      "E-commerce",
      "Recommendation System"
    ],
    "tags_highlighted": [],
    "top_company": false,
    "isHiring": false,
    "nonprofit": false,
    "batch": "Winter 2023",
    "status": "Inactive",
    "industries": [
      "B2B",
      "Engineering, Product and Design"
    ],
    "regions": [
      "United States of America",
      "America / Canada",
      "Remote",
      "Fully Remote"
    ],
    "stage": "Early",
    "app_video_public": false,
    "demo_day_video_public": false,
    "app_answers": null,
    "question_answers": false,
    "url": "https://www.ycombinator.com/companies/rubber-ducky-labs",
    "api": "https://yc-oss.github.io/api/batches/winter-2023/rubber-ducky-labs.json"
  }
]