Company Data Lookup: Wikidata & GLEIF (no LinkedIn)

Give it a list of companies and get one clean profile each: industry, headquarters, country, founding date, employee count, revenue, stock tickers, website, LinkedIn and other social links, and logo. For companies with an LEI, it also adds the legal entity from the GLEIF register: the exact legal name, registered address, business-register number, legal form and status.

You can name a company four ways: its name (Infosys), its website (stripe.com), its Wikidata id (Q312) or its LEI (335800TYLGG93MM7PR89).

By FtryTech.

Why this one

• Clean data you may reuse. Every field comes from Wikidata and the GLEIF Global LEI Repository. Both publish their data under CC0, so you can put it in your CRM, product or AI dataset with no licence worry. Each row says "dataLicense": "CC0-1.0".
• No LinkedIn scraping, no login, no proxies, no browser. The Actor calls the public APIs that Wikidata and GLEIF publish for reuse. Runs are fast, cheap and do not break when a website changes.
• Companies only, no personal data. It never returns CEOs, founders, directors, emails or phone numbers. GLEIF sole proprietors (private people) are refused.
• Website to company. Paste a list of domains and get the companies behind them, matched on the official website each company lists.
• Legal entity matching (KYB). Registered address, register id and registration number (for example India's CIN, a US state file number or a UK company number).

Who it is for

• Sales and marketing teams: enrich an account list with industry, size, HQ and LinkedIn URL before outreach.
• Data and product teams: fill a company table with stable ids (Wikidata, LEI, OpenCorporates, SEC CIK) that join to other datasets.
• Compliance and procurement: confirm a supplier's legal name, registered address and registration number from the GLEIF register.
• AI agents: one call answers "what is this company, where is it, how big is it". Every input has a default, and an empty answer is an explicit row.

Input

Only companies matters, and even that has a default.

{
  "companies": ["Infosys", "stripe.com", "Q312", "335800TYLGG93MM7PR89"],
  "maxMatchesPerQuery": 1,
  "includeLegalEntity": true,
  "language": "en"
}

Field	Default	Meaning
companies	["Infosys"]	Names, websites, Wikidata ids or LEIs, one per line (up to 500 per run).
maxMatchesPerQuery	1	How many matches to return per line (1 to 10). Raise it for an ambiguous name and choose.
includeLegalEntity	true	Add the GLEIF legal entity for companies that have an LEI. Same price either way. LEI lines always read GLEIF.
language	en	Language for names, descriptions, industries and places (de, fr, es, hi, ja ...). Falls back to English.

Output

Each row has a type.

company (shortened):

{
  "type": "company",
  "query": "Infosys",
  "matchedBy": "name",
  "source": "wikidata+gleif",
  "name": "Infosys limited",
  "description": "Indian multinational technology company",
  "website": "https://www.infosys.com/",
  "domain": "infosys.com",
  "industries": ["IT service management"],
  "country": "India",
  "headquarters": "Bengaluru",
  "foundedAt": "1981-07-02",
  "employees": 200364,
  "employeesAsOf": "2017-03",
  "stockExchanges": ["Bombay Stock Exchange", "National Stock Exchange of India", "Nasdaq", "New York Stock Exchange"],
  "tickers": ["500209", "INFY"],
  "linkedinUrl": "https://www.linkedin.com/company/infosys",
  "xUrl": "https://x.com/infosys",
  "crunchbaseUrl": "https://www.crunchbase.com/organization/infosys",
  "logoUrl": "https://commons.wikimedia.org/wiki/Special:FilePath/Infosys_logo.svg",
  "wikidataId": "Q26989",
  "wikipediaUrl": "https://en.wikipedia.org/wiki/Infosys",
  "lei": "335800TYLGG93MM7PR89",
  "openCorporatesId": "in/L85110KA1981PLC013115",
  "legalName": "INFOSYS LIMITED",
  "legalAddress": "ELECTRONICS CITY, HOSUR ROAD, BANGALORE, IN-KA, 560100, IN",
  "registrationAuthorityId": "RA000394",
  "registrationNumber": "L85110KA1981PLC013115",
  "legalFormCode": "DDKQ",
  "jurisdiction": "IN",
  "entityStatus": "ACTIVE",
  "leiStatus": "ISSUED",
  "dataLicense": "CC0-1.0"
}

The other fields are aliases, instanceOf, dissolvedAt, isDefunct, legalForm, revenue, revenueCurrency, revenueAsOf, parentOrganization, parentWikidataId, facebookUrl, instagramUrl, youtubeUrl, githubUrl, wikidataUrl, secCik, legalCountryCode, headquartersAddress and leiLastUpdatedAt. A field the sources do not know is null (or an empty list). source says where the row came from: wikidata, gleif (an LEI that Wikidata lacks) or wikidata+gleif.

no_results (free): written when a line finds nothing. Its reason is one of:

reason	When
not_found	No company matches the name, website, id or LEI.
not_a_company	The match is a person, or the LEI belongs to a sole proprietor. People are never returned.
invalid_entry	The line is not a name, website, Wikidata id or LEI.
fetch_failed	Wikidata or GLEIF did not answer. Run the line again later.

message says what to try next. You are never charged for these rows.

Pricing (pay per event)

Event	Price
Company profile (one company row, with the GLEIF legal entity when there is one)	$0.0008 ($0.80 per 1,000)
no_results rows	free

Apify also charges its standard tiny run-start fee. The run stops cleanly at your spending limit.

Tips

• Ambiguous names: "Mercury" can be many companies. Use the website or the Wikidata id, or set maxMatchesPerQuery to 3 and choose.
• Domains are the most exact input for well-known companies. Names work best as the full or legal name ("Tata Consultancy Services").
• Coverage: Wikidata holds well-known companies of every size, worldwide. The GLEIF register holds over 2.7 million legal entities. A small private firm may be in neither.

For AI agents (MCP)

• Call it with only companies. Every other input has a sensible default.
• Read type first. A no_results row explains an empty answer in reason and message.
• matchedBy says how the line was read (name, domain, wikidata_id or lei). For a name, check name and description before you trust the match.
• Employee counts and revenue carry an "as of" date. Read it before you compare companies.

Limits

• The data is as current as Wikidata's volunteers and the LEI issuers keep it. Employee and revenue figures can be a few years old; the ...AsOf fields say how old.
• Name search returns the best-known company with that name.
• GLEIF covers only entities that hold an LEI (common for listed companies, banks, funds and exporters).

Questions or a field you need? Open an issue on the Actor's Issues tab.