Company Finder – B2B Companies by Industry, Size & Location

Find the B2B companies you should be selling to — by industry, headcount and location — and get back a clean, deduplicated company list with a website domain and real firmographics on every row. Describe the niche (software companies, marketing agencies, logistics, fintech) and where (Austin, TX, Berlin, Netherlands), optionally a headcount band, and every company comes back with its domain, industry, size band and headcount range, headquarters, founded year, company type, description, specialties, social profiles, phone and address. Or paste a list of company names, domains or profile URLs and get the same firmographics for each.

Company data on the market is fragmented: one tool searches a professional network, another scrapes a map, a third resells a stale database dump. None of them gives you a single row per company that your next steps can chain on. This Actor assembles the list the way a good SDR would — business listings, public company profiles and the company's own website, merged and deduplicated by domain — and returns only what passes your filters.

Company finder: what you get

One row per company:

Field	What it tells you
name, domain, website, linkedinUrl	The company and the two keys everything else chains on
industry, industries[], specialties[], listingCategory	What the company does — its declared industry, listing categories and specialties
companySize, employeesMin, employeesMax, employeesOnProfile	Headcount band (1-10 … 10000+), the range behind it, and how many people list the company as their employer
headquarters, city, region, country, hqMatchesLocation	Where it is headquartered (ISO country code when known) and whether that is inside the location you searched — listings also return companies with an office or landing page in a city
foundedYear, companyType	How old it is and how it is owned (Privately Held, Public Company, Nonprofit, …)
description, tagline, followers, logoUrl	For the first line of your e-mail and for qualification
phone, address, googleMapsUrl, rating, reviewsCount	Listing details when the company has a physical presence
socials{}	Profile, X/Twitter, Facebook, Instagram, YouTube
sources[], matchedQueries[], status	Where each row came from (listing, profile-search, profile, website, input), which of your searches found it, and whether the profile could be read (enriched) or only the website (website_only) / the listing (listing_only)

Three dataset views: Companies (one line per company), Firmographics (size, founded, type, HQ, industry), Contact channels (website, phone, address, socials).

Two ways in

• Search — keywords × locations: ["software companies", "SaaS"] in ["Austin, TX", "Denver, CO"]. Optional filters: companySizes (headcount bands), foundedAfter / foundedBefore, companyTypes, requireIndustryMatch, requireHqInLocation. Companies from every source are merged and deduplicated by domain; maxCompanies caps the list (and the price).
• Enrich — companies: names (Gong), domains (gong.io) or profile URLs, mixed. Every entry comes back with the same firmographics — the enrichment step for a list you already have (for example the domains another Actor produced).

How the list is built

1. Discovery — two built-in sources, both on by default: business listings for the niche in each location (strong for anything with an address) and public company profiles found through web search (strong for remote-first, B2B and tech companies with no storefront). Turn either off under Sources & enrichment.
2. Website — each company's home page is read for the description, social profiles (including the company's profile link), phone and the structured organization data sites publish.
3. Public profile — the company's public profile is read for industry, headcount band, headquarters, type, founded year, specialties, description and follower count. A profile found by name is kept only when it is verifiably the same company (same website or matching name), never a namesake.
4. Filters and dedup — size, founded, type and industry filters are applied to the enriched row; rows are deduplicated by domain (then profile); only delivered rows are charged. When a filter is set and the fact is unknown, the company is dropped unless Keep unknown is on — and every drop is counted by reason in the run summary, so a thin result is explainable.

No login, no cookies, no third-party data vendors, no nested scrapers — every source is built in.

Chain it into a prospecting pipeline

Company Finder is the top of an outbound funnel. Its domain column is exactly what the next steps take:

• People — pass the domains to a decision-maker finder to get the people to contact at each company by title and seniority.
• E-mails — pass name + domain to an e-mail finder & verifier.
• Tech stack — pass the domains to a technology lookup to filter by CRM, marketing automation, ecommerce platform.
• Hiring signals — pass the companies to a hiring-intent scraper as a watchlist to see who is scaling which team.

Every row is flat JSON with stable field names, so an agent can map columns without a transform step.

Who uses it

• Outbound / GTM agents — a keyword-discoverable, MCP-callable tool that builds a target-account list unattended and returns a typed dataset.
• SDR and RevOps teams — ICP lists by niche and city with headcount and founded-year filters already applied, ready for a sequencer.
• Agencies and consultants — local and regional company lists for a vertical, with the website, phone and socials on the same row.
• Data teams — a firmographics enrichment step for any list of domains.

Set it up in a minute

1. Enter one or more Industry or niche keywords and Locations (or paste Companies to enrich).
2. Optionally pick Company size bands and open More filters for founded year and company type.
3. Start. Rows arrive as each company is finished; the run summary is in the OUTPUT record.

Advanced settings (collapsed) control the sources, enrichment depth, per-query limits, country/language, concurrency and the proxy used for company profiles (residential by default — profiles rate-limit datacenter traffic).

Use it from an agent or the API

{ "keywords": ["software companies"], "locations": ["Austin, TX"], "companySizes": ["11-50", "51-200"], "maxCompanies": 100 }

{ "companies": ["gong.io", "lemlist", "https://www.linkedin.com/company/stripe"] }

Agents may also pass industries, location (single), domains, websites or urls, or objects { "name": "...", "domain": "...", "location": "..." }. Results are in the default dataset (?view=companies, ?view=firmographics, ?view=contacts); the run summary (candidates per source, drops by reason, charges) is in the OUTPUT record of the run's key-value store. Through the Apify MCP server, call inovaflow/company-finder with the same input.

Output example

{
  "name": "Gong",
  "domain": "gong.io",
  "website": "https://www.gong.io/",
  "linkedinUrl": "https://www.linkedin.com/company/gong-io",
  "industry": "Software Development",
  "industries": ["Software Development"],
  "specialties": ["Revenue Intelligence", "Sales Enablement", "Conversation Analytics"],
  "companySize": "1001-5000",
  "employeesMin": 1001,
  "employeesMax": 5000,
  "employeesOnProfile": 1834,
  "headquarters": "San Francisco, California",
  "city": "San Francisco",
  "region": "California",
  "country": "us",
  "hqMatchesLocation": true,
  "description": "Transform how your revenue team wins with AI. The Gong Revenue AI Operating System brings customer data, insights, and workflows together in one trusted place.",
  "tagline": "AI OS for Revenue Teams",
  "foundedYear": 2015,
  "companyType": "Privately Held",
  "followers": 345251,
  "socials": { "linkedin": "https://www.linkedin.com/company/gong-io", "twitter": "https://twitter.com/gong_io", "facebook": null, "instagram": null, "youtube": "https://www.youtube.com/c/GongIo" },
  "sources": ["profile-search", "website", "profile"],
  "matchedQueries": ["sales software · San Francisco, CA"],
  "status": "enriched"
}

Pricing

Pay per event: $0.01 per company record delivered with a domain, plus a small per-run start fee. Companies without a website, duplicates and companies your filters drop are never charged — so a 500-company sweep filtered down to 80 matches costs $0.80.

Good to know

• Size, founded and type come from the public company profile. Companies without a profile (or with an unreadable one) keep their listing and website facts and are reported with status: website_only / listing_only; with a size filter on they are dropped unless you turn on Keep unknown.
• Listings need a location. A keyword without any location is searched through company profiles only.
• Web search coverage for profile discovery is a few dozen companies per keyword × location; use several keywords (synonyms, sub-niches) and several locations to build big lists.
• Results reflect what companies publish about themselves; sources[] and status tell you what was read for each row.