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POST
/
company
/
search
Search company
curl --request POST \
  --url https://app.fullenrich.com/api/v2/company/search \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "offset": 20,
  "limit": 20,
  "search_after": "WzE1LjUzNDU2MywiYjQ5MDBiYmQtOTg5MS01Mzk1LWIyODUtOWEyOGNiZThjOTM3Il0=",
  "names": [
    {
      "value": "Microsoft",
      "exact_match": true,
      "exclude": false
    }
  ],
  "domains": [
    {
      "value": "microsoft.com",
      "exact_match": true,
      "exclude": false
    }
  ],
  "professional_network_ids": [
    {
      "value": 1234,
      "exact_match": true,
      "exclude": false
    }
  ],
  "professional_network_urls": [
    {
      "value": "https://www.linkedin.com/company/fullenrich",
      "exact_match": true,
      "exclude": false
    }
  ],
  "keywords": [
    {
      "value": "innovative and practical products",
      "exact_match": false,
      "exclude": false
    }
  ],
  "specialties": [
    {
      "value": "AI safety",
      "exact_match": false,
      "exclude": false
    }
  ],
  "industries": [
    {
      "value": "Software Development",
      "exact_match": false,
      "exclude": false
    },
    {
      "value": "Computer Hardware Manufacturing",
      "exact_match": false,
      "exclude": false
    }
  ],
  "types": [
    {
      "value": "Public Company",
      "exact_match": true,
      "exclude": false
    }
  ],
  "headquarters_locations": [
    {
      "value": "San Francisco",
      "exact_match": false,
      "exclude": false
    }
  ],
  "founded_years": [
    {
      "min": 2015,
      "max": 2024,
      "exclude": false
    }
  ],
  "headcounts": [
    {
      "min": 100,
      "max": 500,
      "exclude": false
    }
  ],
  "company_ids": [
    {
      "value": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
      "exclude": false,
      "exact_match": true
    }
  ]
}
'
{
  "companies": [
    {
      "id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
      "name": "Anthropic",
      "domain": "anthropic.com",
      "description": "AI safety and research company building reliable, interpretable, and steerable AI systems.",
      "year_founded": 2021,
      "headcount": 2610,
      "headcount_range": "1001-5000",
      "company_type": "Privately Held",
      "locations": {
        "headquarters": {
          "line1": "548 Market St",
          "line2": "San Francisco, CA 94105, US",
          "city": "San Francisco",
          "region": "California",
          "country": "United States",
          "country_code": "US"
        },
        "offices": [
          {
            "line1": "111 8th Ave",
            "line2": "New York, NY 10011, US"
          }
        ]
      },
      "social_profiles": {
        "professional_network": {
          "id": 1234,
          "url": "https://www.linkedin.com/company/anthropic",
          "handle": "anthropic",
          "connection_count": 125000
        }
      },
      "specialties": [
        "artificial intelligence",
        "machine learning",
        "AI safety"
      ],
      "industry": {
        "main_industry": "Software Development"
      }
    }
  ],
  "metadata": {
    "total": 20523,
    "credits": 22.5,
    "offset": 0,
    "search_after": "WzE1LjUzNDU2MywiYjQ5MDBiYmQtOTg5MS01Mzk1LWIyODUtOWEyOGNiZThjOTM3Il0="
  }
}

Documentation Index

Fetch the complete documentation index at: https://docs.fullenrich.com/llms.txt

Use this file to discover all available pages before exploring further.

The Company Search endpoint allows you to search for companies by size, industry, location, founding year, specialties, and more. It is designed to help you build clean company lists for prospecting, enrichment, or market analysis. How filters work If you filter by company industries [“Technology, Information and Internet”, “Financial Services”] and company locations [“France”, “United States”], the API returns results where the company industry is either Technology, Information and Internet or Financial Services, AND the company location is either France or United States. In other words, a result must satisfy at least one value in every filter category you specify. Within a category, values act as OR: a result matches if it fits any of the values. Across categories, the logic is AND: a result must match all categories to be returned. If you want to retrieve one specific company, you can search directly using its professional network URL or domain for an exact match. Search API pricing For a full list of supported filters and accepted values (industries, company types, seniority levels, etc.)

Predefined Filter Values

For a full list of supported filters and accepted values (industries, company types, seniority levels, etc.)

Authorizations

​
Authorization
string
header
required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Body

application/json
​
offset
integer

Number of companies to skip (use this for pagination). Maximum value is 10,000. To paginate beyond 10,000 results, use search_after instead.

Example:

20

​
limit
integer

Number of companies to return (default: 10, max: 100)

Example:

20

​
search_after
string

Cursor-based pagination. Pass the search_after value from the previous response to get the next page. Works at any point in the result set, but is required to access results beyond the 10,000 offset limit.

Example:

"WzE1LjUzNDU2MywiYjQ5MDBiYmQtOTg5MS01Mzk1LWIyODUtOWEyOGNiZThjOTM3Il0="

​
names
object[]

Filter by company names. Use exact_match for precise company name matching.

Example:
[
  {
    "value": "Microsoft",
    "exact_match": true,
    "exclude": false
  }
]
​
domains
object[]

Filter by company domains (e.g., 'google.com', 'microsoft.com'). Exact match recommended.

Example:
[
  {
    "value": "microsoft.com",
    "exact_match": true,
    "exclude": false
  }
]
​
professional_network_ids
object[]

Filter by professional network IDs.

Example:
[
  {
    "value": 1234,
    "exact_match": true,
    "exclude": false
  }
]
​
professional_network_urls
object[]

Filter by professional network URLs.

Example:
[
  {
    "value": "https://www.linkedin.com/company/fullenrich",
    "exact_match": true,
    "exclude": false
  }
]
​
keywords
object[]

Filter by description of company

Example:
[
  {
    "value": "innovative and practical products",
    "exact_match": false,
    "exclude": false
  }
]
​
specialties
object[]

Filter by specialties of company

Example:
[
  {
    "value": "AI safety",
    "exact_match": false,
    "exclude": false
  }
]
​
industries
object[]

Filter by company industries (e.g., 'Software Development', 'Computer Hardware Manufacturing', 'Housing and Community Development', 'Warehousing', 'Financial Services'). See Industries for the full list.

Example:
[
  {
    "value": "Software Development",
    "exact_match": false,
    "exclude": false
  },
  {
    "value": "Computer Hardware Manufacturing",
    "exact_match": false,
    "exclude": false
  }
]
​
types
object[]

Filter by company types (e.g., 'Public Company', 'Privately Held', 'Nonprofit', 'Self-Employed', 'Partnership', 'Educational', 'Government Agency'). See Company Types for the full list.

Example:
[
  {
    "value": "Public Company",
    "exact_match": true,
    "exclude": false
  }
]
​
headquarters_locations
object[]

Filter by headquarters locations (city names, regions, or countries)

Example:
[
  {
    "value": "San Francisco",
    "exact_match": false,
    "exclude": false
  }
]
​
founded_years
object[]

Filter by founding years. Useful for targeting startups (recent years) or established companies.

Example:
[
  {
    "min": 2015,
    "max": 2024,
    "exclude": false
  }
]
​
headcounts
object[]

Filter by company headcounts (number of employees). Use ranges to target specific company sizes (e.g., startups: 1-50, mid-size: 50-500, enterprise: 1000+).

Example:
[
  { "min": 100, "max": 500, "exclude": false }
]
​
company_ids
object[]

Filter by specific company IDs

Response

OK

​
companies
object[]

Array of companies matching the search criteria. Returns empty array if no results found.

​
metadata
object