company_search
Find companies that fit — by industry, size, country, revenue, website tech, the tools their team uses inside, hiring, funding and what they are researching now — without people. Returns one row per company: name, domain, LinkedIn page, industry, size, country, revenue range, funding, website tech stack, intent topics, the company's own public emails, and why it matched. team_uses sees internal tools a website scan never does (Snowflake, dbt, Kafka, Gong), counted from current employees' skills, with how many people use each; the tool's own maker is left out. researching is buyer intent: topics the company's people read about lately. Each company returned costs one request of the user's quota; start with a small limit, then page with next_cursor. This is the first step of account-based work: pick the accounts here, then person_search with the same filters or with domains finds the people, and company_signals profiles one account in depth. Present the total and the companies with the reason they matched.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Companies per page, 1-100. Each company returned costs one request. | |
| cursor | No | next_cursor from the previous page, to continue the same search. | |
| filters | Yes | Filters, combined with AND; values inside one list combine with OR. At least one is required. industries ['Software Development'], company_size_min / company_size_max (employees), company_countries ['United States'], revenue_min / revenue_max (USD a year, mostly US companies), technologies ['HubSpot'] (runs on the company website), team_uses ['Snowflake','dbt'] (tools the team uses inside, from current employees' skills — two people or more), company_hiring true, funded_since '2025-06', founded_after 2018, researching ['CRM'] (topics the company's people read about lately — buyer intent). |