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For AI agents

Named customers of data, cloud and AI vendors from public case studies, keynotes, press releases, earnings calls and US federal contracts, with renewals and migrations, each linked to its source.

Refresh delayedUpdated every Saturday at 10:00 UTC

Point your agent here

Call the API

  • GET /api/storiescustomer?, vendor?, event?, limit?, offset?stories with customer, vendor, products, use case, stated outcome, event, the vendor left (migrations), source URL, publisher and date
  • GET /api/companies/{slug}slugthe company, the vendors it uses and moved away from, the customers it has, and every story behind them
  • GET /api/companiesrole?, industry?, limit?, offset?companies with slug, name, domain, role, industry, vendor category and story counts
  • GET /api/graphnonecompanies and edges (customer, vendor, story count, strongest event, moved away)
  • GET /api/searchq, limit?up to 20 ranked results with title, link and one line

GET/api/stories

Public stories, newest first, filtered by customer, vendor or relationship event

  • customerCustomer slug, e.g. medtronic
  • vendorVendor slug, e.g. snowflake
  • eventRelationship event
  • limitItems per page, 1 to 200
  • offsetItems to skip, for the next page
Shell
curl -s "https://stories.fru.dev/api/stories?vendor=snowflake&limit=2"
Sample response
JSON
{
  "items": [
    {
      "id": 1,
      "customer": "medtronic",
      "vendor": "snowflake",
      "products": [
        "Snowflake"
      ],
      "useCase": "Great Lakes program moving the enterprise data warehouse from on-premises systems to Snowflake",
      "outcome": "",
      "event": "migrated",
      "fromVendor": "",
      "fromLabel": "on-premises data warehouse",
      "sourceKind": "customer_blog",
      "sourceUrl": "https://www.snowflake.com/en/blog/medtronic-using-snowflake-for-digital-transformation/",
      "sourceTitle": "How Medtronic is Using Snowflake for Digital Transformation",
      "publisher": "snowflake.com",
      "date": "2022-06-21"
    },
    {
      "id": 24,
      "customer": "siemens",
      "vendor": "snowflake",
      "products": [
        "Snowflake"
      ],
      "useCase": "Siemens Data Cloud: enterprise data mesh replacing an on-prem SAP HANA data lake",
      "outcome": "600+ projects running across business divisions",
      "event": "migrated",
      "fromVendor": "sap",
      "fromLabel": "on-premises SAP HANA data lake",
      "sourceKind": "vendor_case_study",
      "sourceUrl": "https://www.snowflake.com/en/customers/all-customers/case-study/siemens-1/",
      "sourceTitle": "Siemens Builds an Enterprise-Wide Data Mesh Platform to Accelerate Innovation",
      "publisher": "snowflake.com",
      "date": ""
    }
  ],
  "limit": 2,
  "offset": 0,
  "next": "/api/stories?vendor=snowflake&limit=2&offset=2"
}

GET/api/companies/{slug}

One company's tech stack (as a customer) or named customers (as a vendor)

  • slugCompany slug, e.g. medtronic or databricks
Shell
curl -s "https://stories.fru.dev/api/companies/medtronic"
Sample response
JSON
{
  "company": {
    "slug": "medtronic",
    "name": "Medtronic",
    "domain": "medtronic.com",
    "role": "customer",
    "industry": "healthcare",
    "category": "",
    "blurb": ""
  },
  "url": "https://stories.fru.dev/customers/medtronic",
  "uses": [
    {
      "slug": "mongodb",
      "name": "MongoDB",
      "stories": 1,
      "event": "adopted",
      "first": "",
      "last": ""
    },
    {
      "slug": "aws",
      "name": "Amazon Web Services",
      "stories": 1,
      "event": "adopted",
      "first": "2022-03-10",
      "last": "2022-03-10"
    }
  ],
  "movedAwayFrom": [],
  "customers": [],
  "customersLost": [],
  "stories": [
    {
      "id": 1,
      "customer": "medtronic",
      "vendor": "snowflake",
      "products": [
        "Snowflake"
      ],
      "useCase": "Great Lakes program moving the enterprise data warehouse from on-premises systems to Snowflake",
      "outcome": "",
      "event": "migrated",
      "fromVendor": "",
      "fromLabel": "on-premises data warehouse",
      "sourceKind": "customer_blog",
      "sourceUrl": "https://www.snowflake.com/en/blog/medtronic-using-snowflake-for-digital-transformation/",
      "sourceTitle": "How Medtronic is Using Snowflake for Digital Transformation",
      "publisher": "snowflake.com",
      "date": "2022-06-21"
    },
    {
      "id": 2,
      "customer": "medtronic",
      "vendor": "aws",
      "products": [
        "AWS",
        "AI/ML services"
      ],
      "useCase": "Scalable infrastructure and AI to turn around PillCam colon cancer screening results",
      "outcome": "",
      "event": "adopted",
      "fromVendor": "",
      "fromLabel": "",
      "sourceKind": "vendor_case_study",
      "sourceUrl": "https://www.youtube.com/watch?v=-KsHbNO9X4A",
      "sourceTitle": "Medtronic Increases Accessibility to Colorectal Cancer Screening with AWS",
      "publisher": "youtube.com",
      "date": "2022-03-10"
    }
  ]
}

GET/api/companies

Every customer and vendor with at least one story

  • rolecustomer or vendor
  • industryCustomer industry, e.g. healthcare
  • limitItems per page, 1 to 200
  • offsetItems to skip, for the next page
Shell
curl -s "https://stories.fru.dev/api/companies?role=vendor&limit=3"
Sample response
JSON
{
  "items": [
    {
      "slug": "aws",
      "name": "Amazon Web Services",
      "domain": "aws.amazon.com",
      "role": "vendor",
      "industry": "",
      "category": "cloud",
      "vendors": 0,
      "customers": 8,
      "stories": 9,
      "url": "https://stories.fru.dev/vendors/aws"
    },
    {
      "slug": "confluent",
      "name": "Confluent",
      "domain": "confluent.io",
      "role": "vendor",
      "industry": "",
      "category": "streaming",
      "vendors": 0,
      "customers": 3,
      "stories": 3,
      "url": "https://stories.fru.dev/vendors/confluent"
    }
  ],
  "total": 11,
  "limit": 3,
  "offset": 0,
  "next": "/api/companies?role=vendor&limit=3&offset=3"
}

GET/api/graph

The whole customer and vendor graph in one call

Shell
curl -s "https://stories.fru.dev/api/graph"
Sample response
JSON
{
  "companies": [
    {
      "slug": "adobe",
      "name": "Adobe",
      "domain": "adobe.com",
      "role": "customer",
      "industry": "technology",
      "category": "",
      "blurb": ""
    },
    {
      "slug": "albertsons",
      "name": "Albertsons Companies",
      "domain": "albertsons.com",
      "role": "customer",
      "industry": "retail",
      "category": "",
      "blurb": ""
    }
  ],
  "pairs": [
    {
      "c": "medtronic",
      "v": "mongodb",
      "lost": false,
      "n": 1,
      "ev": "adopted",
      "first": "",
      "last": "",
      "u": false
    },
    {
      "c": "at-and-t",
      "v": "snowflake",
      "lost": false,
      "n": 1,
      "ev": "migrated",
      "first": "",
      "last": "",
      "u": false
    }
  ],
  "stories": 50,
  "updated": null,
  "note": "pairs: c = customer slug, v = vendor slug, n = stories, ev = strongest event, lost = customer moved away from v"
}

Add to your agent

System prompt
For which companies publicly use which data, cloud and AI vendors (case studies, renewals, migrations), fetch https://stories.fru.dev/llms.txt and use https://stories.fru.dev/api/stories (spec: https://stories.fru.dev/openapi.json). Cite "Stories (stories.fru.dev)" with a link.

Usage terms

  • Free to read, no key needed
  • Cite "Stories (stories.fru.dev)" with a link
  • Responses are cached; updated every Saturday at 10:00 UTC
  • Keep to 60 requests a minute or fewer
  • Stories marked unverified (reviewed: false) were found by the weekly agent and not yet checked by hand; the source link is where they came from.

Weekly: new public stories, renewals and migrations, Saturdays.