Quickstart

Resolve a free-text company/brand name (or LinkedIn company URL, or bare domain) to its canonical LinkedIn company identity: org_id, canonical name, domain and confidence. Returns ranked candidates when the match is ambiguous. Call this first to get an org_id for the other tools.

curl -X POST https://api.gtm.dev/v1/tools/resolve_company \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"query":"stripe"}'

Fetch firmographics for a company: name, domain, industry, employee size range, HQ location, description, follower count and logo. Address the company by org_id (from resolve_company), domain, or name.

curl -X POST https://api.gtm.dev/v1/tools/enrich_company \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"domain":"stripe.com"}'

Find companies running ads in a country (LinkedIn Ads + Meta Ad Library), ranked by impressions then ad count. Optional keyword narrows to ads whose copy or landing pages mention it. Returns advertiser company identity, ad counts and platforms, paginated with limit/offset.

curl -X POST https://api.gtm.dev/v1/tools/who_is_advertising \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"keyword":"crm","country":"US"}'

Find companies actively hiring for a role (e.g. "sales development", "machine learning engineer"), ranked by open-role count. Optionally filter by country and minimum number of openings, and paginate with limit/offset. Data is a weekly-refreshed index of LinkedIn + Indeed job postings.

curl -X POST https://api.gtm.dev/v1/tools/who_is_hiring \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"role":"sdr","geo_country":"United States","min_openings":5}'

Find recently funded companies, newest round first. Filter by funding stage (e.g. "series_a", "seed"), lookback window in months (default 12), and minimum total funding in USD. Paginate with limit/offset.

curl -X POST https://api.gtm.dev/v1/tools/find_funded \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"stage":"series_a","months":6}'

List the technologies detected on a company's website (CRM, analytics, marketing automation, infrastructure, ...), grouped by category. Address the company by org_id (from resolve_company) or domain.

curl -X POST https://api.gtm.dev/v1/tools/company_tech \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"domain":"rippling.com"}'

Describe the list you want in plain language and get the executed company list back in ONE call — we extract the criteria, choose between taxonomy filters and semantic search, canonicalize every value against the graph's real vocabularies, run the search, and return the rows plus the exact plan applied (in the same shapes search_companies / concept_search accept, so you can iterate deterministically). Supports excludes ("...but not staffing agencies"). When the description names people (titles/roles), the response includes a ready-made find_people follow-up. Companies only — chain find_people for the humans.

curl -X POST https://api.gtm.dev/v1/tools/build_list \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"description":"US payroll and HR software companies, 200+ employees, not staffing agencies","limit":25}'

One company's advertising footprint across the public LinkedIn and Meta ad libraries: per-platform ad counts, impression floors where available, first/last seen dates, and up to 10 recent ads with copy snippets and landing domains. Address the company by org_id (from resolve_company), domain, or name.

curl -X POST https://api.gtm.dev/v1/tools/company_ad_activity \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"domain":"hubspot.com"}'

Fetch one company's funding profile from the funding index: total raised, number of rounds, last round type and date, investor names, IPO / operating status, stock symbol and founded date. Address the company by org_id (from resolve_company), domain, or name. has_funding_data is false when the company has no profile in the funding index (~40% coverage of the company index).

curl -X POST https://api.gtm.dev/v1/tools/company_funding \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"domain":"hubspot.com"}'

One company's active hiring breakdown from the hiring index (weekly-refreshed LinkedIn + Indeed job postings, last 60 days): open-role counts per role/function and country, plus totals. Address the company by org_id (from resolve_company) or domain. Empty roles means no recent postings on record.

curl -X POST https://api.gtm.dev/v1/tools/company_hiring \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"domain":"hubspot.com"}'

Describe your ideal customer in plain language (e.g. "API-first payroll for global teams") and get semantically ranked companies from the company graph — meaning-based matching over millions of company embeddings, not keyword search. Optionally narrow by country or employee size range, and paginate with limit/offset (the semantic neighborhood is bounded: match quality degrades past the first ~200 rows, so offset+limit is capped at 200).

curl -X POST https://api.gtm.dev/v1/tools/concept_search \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"query":"API-first payroll for global teams","country":"US","limit":25}'

Find people at a company from the people graph. Anchor on one company (org_id, domain, or name), then filter by titles, seniority, function, or location. Returns names, titles, locations and LinkedIn profile URLs — no contact details. Pagination: limit only (no offset yet — the people graph pages by internal cursor, not row offset); total_matching and page.has_more tell you when a company has more matching people than one call returns.

curl -X POST https://api.gtm.dev/v1/tools/find_people \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"company":"rippling.com","function":"sales","seniority":"vp"}'

Find the companies most similar to a seed company by embedding similarity over the company graph. Give one seed (org_id, domain, or name) and get its nearest neighbors — ideal for expanding a target list from your best accounts. Paginate with limit/offset (the similarity neighborhood is bounded: match quality degrades past the first ~200 rows, so offset+limit is capped at 200).

curl -X POST https://api.gtm.dev/v1/tools/lookalikes \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"seed":"rippling.com"}'

Normalize a free-text job title ("sdr", "head of eng", "vp sales") into canonical title strings plus a seniority and function guess. Titles resolve against the live title vocabulary (abbreviation-aware, typo-tolerant) layered over a curated shorthand map. Seniority values: owner, cxo, vp, director, manager, senior, entry, training. Functions follow LinkedIn's function vocabulary (sales, marketing, engineering, ...).

curl -X POST https://api.gtm.dev/v1/tools/normalize_title \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"title":"head of eng"}'

Turn a plain-language targeting description (ICP, persona, market) into canonical, ready-to-use filters — the recommended FIRST call when you are unsure of exact vocabulary. Returns company filters (for search_companies / size_tam), people filters (for find_people), a concept_query (for concept_search when meaning matters more than filters), a filters-vs-semantic strategy recommendation, and suggested next tool calls. Resolution runs against the graph's real vocabularies, so returned values always match what the search tools accept.

curl -X POST https://api.gtm.dev/v1/tools/plan_targeting \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"description":"VP+ finance leaders at mid-market US SaaS companies that feel API-first"}'

Build a structured research brief for one company: what they do, recent signals (funding, launches, hiring, expansion), concrete outreach hooks, and sources. Combines the company graph with live web research. Optionally steer it with a focus (e.g. "why would they buy sales tooling").

curl -X POST https://api.gtm.dev/v1/tools/research_company \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"company":"rippling.com","focus":"why would they buy sales tooling"}'

Canonicalize a free-text place — a country code or name ("US", "United Kingdom"), a city ("Bengaluru"), or a state/region ("Karnataka") — to the canonical geo labels used across the company and hiring indexes. Returns the country (with ISO-2 code), a [city, region, country] hierarchy when uniquely resolvable, and candidates[] when the name is ambiguous (e.g. "Springfield").

curl -X POST https://api.gtm.dev/v1/tools/resolve_geo \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"query":"Bengaluru"}'

Firmographic company search over the company index (~9M companies), ranked by LinkedIn follower count. Supports complex targeting: combine multiple industries/categories to INCLUDE (they OR together — a company matching any of them qualifies) with industries_exclude/categories_exclude to SUBTRACT, plus employee size range, HQ country/region/city, a name substring, or has_domain. At least one filter is required. Paginate with limit/offset (default 25 per page); the filters echo shows the canonical labels actually applied and the page object tells you if more rows exist. Use size_tam with the same filters to count the full matching universe.

curl -X POST https://api.gtm.dev/v1/tools/search_companies \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"industries":["payroll","hr software"],"industries_exclude":["staffing"],"country":"US","limit":50}'

Count how many companies in the company index (~9M companies) match a firmographic filter set — the TAM behind a search_companies page. Takes the same filters as search_companies (at least one required), including the multi include/exclude industry and category lists (includes OR together, excludes always subtract), and returns {count, filters} with the canonical filters actually applied.

curl -X POST https://api.gtm.dev/v1/tools/size_tam \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"industry":"software","country":"IN","size_range":"51-200"}'

Find companies detected running a technology (e.g. "hubspot", "salesforce", "segment") via website tech-stack scans, ranked by detection confidence. Optionally filter by HQ country and employee size range, and paginate with limit/offset. The tool input is matched against the scanner's tool vocabulary (exact name preferred, fuzzy fallback); matched_tools echoes what was searched.

curl -X POST https://api.gtm.dev/v1/tools/who_uses_tech \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"tool":"hubspot","country":"IN","size_range":"51-200"}'