Documentation Index Fetch the complete documentation index at: https://docs.descovo.com/llms.txt
Use this file to discover all available pages before exploring further.
The company search endpoint lets you query Descovo’s database of 47M+ companies using a rich set of filters: industry, headquarter location, employee count, funding stage, keywords, and more. All filters work together — the API applies them in combination and returns only companies that satisfy every condition you specify. Credits are charged per company returned.
Endpoint: POST https://api.descovo.com/v1/company-searchAuth: apiKey in the request bodyRequest parameters Company filter criteria. All sub-fields are optional; combine them to narrow results. Show searchParams properties
Full-text search terms matched against company descriptions. Example: ["artificial intelligence", "machine learning"].
Partial name match. Returns companies whose name contains this string. Example: "Descovo AI".
searchParams.headquartersCountryCode
ISO 3166-1 alpha-2 country codes for the company headquarters. Examples: "US", "GB", "DE".
searchParams.headquartersStateName
US state names (or equivalent for other countries) for the company headquarters. Examples: "California", "New York".
searchParams.headquartersLocation
Free-form location strings. Example: "San Francisco Bay Area".
searchParams.employeeCountV2
Filter by number of employees. searchParams.employeeCountV2.min
Minimum employee count (inclusive).
searchParams.employeeCountV2.max
Maximum employee count (inclusive).
searchParams.totalFundingUSD
Filter by total funding raised, in USD. searchParams.totalFundingUSD.min
Minimum total funding in USD.
searchParams.totalFundingUSD.max
Maximum total funding in USD.
searchParams.lastFundingUSD
Filter by the most recent funding round amount, in USD. searchParams.lastFundingUSD.min
Minimum last funding amount in USD.
searchParams.lastFundingUSD.max
Maximum last funding amount in USD.
Funding stage filter. Accepted values include "SEED", "SERIES_A", "SERIES_B", "LATE_STAGE".
searchParams.industriesV2
Structured industry slugs. Examples: "artificial-intelligence", "fintech", "software".
Restrict results to specific company domains. Example: ["example.com", "another.io"].
searchParams.linkedinSlugs
Restrict results to specific LinkedIn organization slugs. Example: ["microsoft", "google"].
Filter by top-level domain. Examples: ".io", ".ai".
searchParams.specialFlags
Internal company flags such as "high-growth" or "bootstrapped". Contact your account manager for available values.
IDs of saved company exclusion lists. Companies on these lists are removed from results.
Number of companies to return per page. Maximum is 1000.
Pagination cursor from the previous response’s nextCursor. Omit or pass null for the first page.
Response fields Array of company objects matching your filters. output.data[].preferred_name
Company’s preferred display name.
Known web domains for this company.
output.data[].linkedin_primary_slug
Primary LinkedIn organization slug.
output.data[].standard_industries
Normalized industry tags, e.g. ["artificial-intelligence", "software"].
output.data[].employee_count_consensus
Estimated employee count range with min and max.
output.data[].location_consensus
Headquarters location with city and country_code.
output.data[].total_funding_consensus
Total funding raised with usd amount.
output.data[].funding_stage
Current funding stage, e.g. "SERIES_A".
Pass this value as cursor in your next request to fetch the next page. null when there are no more results.
Credit charge details for this request. charged-now for company search results.
chargeInfo.creditsCharged
Total credits deducted — one credit per company returned.
Example Request: find AI startups in the US with 50–500 employees that have raised at least $5M { "apiKey" : "sk_live_xxx" , "searchParams" : { "keywords" : [ "artificial intelligence" , "machine learning" ], "headquartersCountryCode" : [ "US" ], "employeeCountV2" : { "min" : 50 , "max" : 500 }, "totalFundingUSD" : { "min" : 5000000 }, "industriesV2" : [ "artificial-intelligence" ], "stage" : [ "SEED" , "SERIES_A" , "SERIES_B" ] }, "pageSize" : 25 , "cursor" : null , "companyExclusionListIDs" : [] }
Response: { "output" : { "data" : [ { "preferred_name" : "Descovo AI" , "domains" : [ "descovo.ai" ], "linkedin_primary_slug" : "descovo-ai" , "standard_industries" : [ "artificial-intelligence" , "software" ], "employee_count_consensus" : { "min" : 10 , "max" : 50 }, "location_consensus" : { "city" : "San Francisco" , "country_code" : "US" }, "total_funding_consensus" : { "usd" : 2000000 }, "last_sort_key" : "opaque_sort_cursor" } ], "nextCursor" : "eyJsYXN0X3NvcnRfa2V5IjoiYWJjMTIzIn0" }, "chargeInfo" : { "method" : "charged-now" , "creditsCharged" : 25 } }
Notes For large-scale account prospecting — finding and enriching hundreds or thousands of companies — use an audience workflow . You can pass company search params directly to an audience, then enrich and export at scale.
Credits are charged per company returned. Use a small pageSize while testing filters to keep costs low.
Keep searchParams identical between pages; only change cursor.
See Pagination for the full cursor model.
See Credits for per-operation costs.
