DataForB2B

Enrich MULTIPLE professional profiles in one call (1-100 at a time). The profiles are enriched concurrently server-side, so this is much faster and a single round-trip instead of calling enrich_profile in a loop. Use this whenever you have more than one profile to enrich (e.g. a list of people from search_people). Each enrichment flag controls one data source and bills separately, per SUCCESSFUL profile — a profile that fails comes back with an `error` field and costs nothing. Returns `results`: one object per input identifier, each with the requested fields (profile, work_email, personal_email, phone, git_profile) or an error.

enrich_profiles

Enrich a single company with full data from public sources (description, industry, headquarters, employee count, funding, offices, etc.).

enrich_company

Enrich a single professional profile with detailed profile data, work email, personal email, and/or GitHub profile. Each enrichment flag controls one data source and bills separately. To enrich SEVERAL profiles, use `enrich_profiles` (bulk) instead — it runs them concurrently server-side and is far faster than calling this in a loop.

enrich_profile

Search companies using structured filters. Use this for any company search: translate the user's intent (e.g. "AI startups in France that raised Series A") into structured filters on specific columns (industry, country, employee count range, funding stage, founded year, etc.). The available columns and operators are documented on the `filters` parameter. Returns paginated companies matching ALL/ANY filter conditions depending on the `op` of the FilterGroup. If a categorical filter returns few or no results, the `typeahead` tool can resolve the exact stored value — then retry.

search_company

Search job postings on LinkedIn or Indeed by keyword, location, and filters (employment type, remote/onsite, seniority, freshness, employer). Useful for hiring signals: which companies are recruiting for what roles, where.

search_jobs

Search professional profiles using structured filters. Use this for any people search: translate the user's intent (e.g. "AI engineers in Berlin who recently raised") into structured filters on specific columns (country, company size range, funding stage, etc.). The available columns and operators are documented on the `filters` parameter. Returns paginated profiles matching ALL/ANY filter conditions depending on the `op` of the FilterGroup. To find people at a SPECIFIC company you already identified (e.g. via `search_company` or `enrich_company`), filter on `current_company_id` (or `past_company_id`) with that company's `id` (e.g. "org_xxx") — NOT `current_company` (the name), which also matches other companies that happen to share the name and adds noise. To target people by their COMPANY's business (e.g. "founders of AI sales-agent startups"), qualify the company itself: filter `current_company_category` (lowercase, holds precise niche values — "artificial intelligence", "sales automation", "saas" — resolve with `typeahead` type=category) and/or `current_company_industry`, and when no category fits the niche, `current_company_keyword` (full-text on the employer's name/tagline/description — OR several "=" phrase variants). `keyword` searches the PERSON's own headline, so it fits attributes of the person themselves; for a company trait it matches unrelated people ("sales agent" → real-estate agents, sales reps). If a categorical filter returns few or no results, the `typeahead` tool can resolve the exact stored value — then retry.

search_people

Search social posts by keyword on LinkedIn, Twitter/X, or Reddit — or target a single post by URL. Great for intent signals: find people talking about a topic, then use `include` to attach the post's engagers (each reactor / commenter is a lead, with their profile). Two modes: 1. Keyword search: set `keyword` (+ optional filters). 2. Single post: set `post_url` (with `include` to get its engagers).

search_posts

Helper to autocomplete a valid filter value. This is NOT a search tool — call a search tool to actually retrieve people/companies. Use typeahead to resolve the exact stored value for a free-text categorical filter (company, industry, title, skill, school, investor, location, category). Don't hesitate to use it when: the query is complex, you're unsure which filter value or column fits the user's intent, a search returned few or no results, or the user explicitly asks for autocomplete suggestions — then retry the search with the resolved value. Returns canonical values with a popularity bucket. Each returned result costs a small amount of credits; empty result sets are free.

typeahead