LEI Company Ownership — GLEIF 🌐

foXLabs US filings series: SEC EDGAR financials · SEC enforcement · Federal contractors

🎉 Turn GLEIF into clean, structured entity + ownership data — no login, no API key, one row per legal entity, with the LEI, legal name, status, jurisdiction, address and parent/child relationships. Built for B2B sales, lead generation, KYB / compliance and market-research teams.

🔍 What is the LEI Company Ownership — and when should you use it?

Give this actor company names or LEI codes and it returns matching legal entities from the Global Legal Entity Identifier Foundation (GLEIF) registry — as clean, deduplicated rows you can filter, export or feed to an AI agent. Every run reads the source live.

Use it when you need: a LEI entity company list for outreach; formation / status monitoring; or a canonical registry record for KYB and due diligence.

Use something else when: you need commercial firmographics like revenue or headcount — GLEIF is legal-entity identity and ownership, not financials.

🤖 Use with AI agents

Already on the Apify MCP server? Ask for this Actor by name: foxlabs/lei-company-ownership.

Your agent can pay for its own runs. This Actor is pay-per-event with agentic payments, so an agent can discover it, run it and settle the bill over x402 (USDC on Base) or Skyfire — no Apify account or API token of its own. Billing is the same either way: per delivered record, never for errors.

Otherwise paste this into Claude, ChatGPT, Cursor or any MCP-enabled assistant:

I want to pull LEI entity company records using the Apify Actor `foxlabs/lei-company-ownership`.
Input: `names`, `leis`, `jurisdiction`, `status` and more — see the Input table below. `maxResults` caps how many results are returned.
Start with: {"names":["Volkswagen AG","Apple Inc"],"maxResults":12}
Ask me what to look up, run the Actor, then summarise the rows as a table.

The machine-readable API, MCP config and OpenAPI definition live at apify.com/foxlabs/lei-company-ownership.md.

📋 Overview

Everything you need to turn the Global Legal Entity Identifier Foundation (GLEIF) registry into clean, structured data — in one actor, with no login, cookies or API key.

Why teams pick this actor:

• ✅ Whole registry, one call — name or ID in, matching companies out.
• 🧹 No empty-promise columns — only fields this registry actually fills; degenerate columns are removed.
• 🔗 Stable identifiers — every row carries the source's own IDs, ready to join across runs and to other Fox Labs actors.
• 💰 Per-row pricing — a minimal price per delivered row, no subscription.
• 🤖 Agent-ready — MCP + x402 agentic payments.

✨ Features

• 🔍 Name or ID lookup — relevance-ranked name search or exact registry-ID lookup.
• 🏢 Full entity profile — status, legal form, formation date, address and the registry’s own contact fields.
• 🧹 Clean schema — deduplicated camelCase rows, ready for CSV/Excel/JSON.

🎬 Quick Start

curl -X POST "https://api.apify.com/v2/acts/foxlabs~lei-company-ownership/runs?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"names":["Volkswagen AG","Apple Inc"],"maxResults":12}'

🚀 Getting Started (3 steps)

1. Choose your targets — company names or LEI codes.
2. Set the cap — maxResults limits how many results are returned.
3. Run and export — get a clean dataset as JSON, CSV or Excel.

📥 Input

{"names":["Volkswagen AG","Apple Inc"],"maxResults":12}

Field	Type	Description
names	array	Legal entity names to look up — e.g. "Apple Inc", "Volkswagen AG". Returns matching LEI records. A common name matches many unrelated entities ("Apple Inc" also…
leis	array	Exact 20-character LEI codes for precise lookup (e.g. "HWUPKR0MPOU8FGXBT394").
jurisdiction	string	Browse all entities in a jurisdiction: ISO-2 country (e.g. "DE", "US") or ISO sub-region (e.g. "US-CA"); leave empty for all. Combine with Status to filter…
status	string	Filter browsed entities by legal status.
includeOwnership	boolean	Attach each entity's direct & ultimate parent and direct children (the corporate hierarchy). On by default — this is what sets it apart from a plain LEI lookup.…
includeIsins	boolean	Attach the securities (ISINs) issued under each entity, plus a total count (isinCount). Off by default — adds one API call per entity; turn on for securities /…
maxResults	integer	Maximum number of entities to return (1–50000). Note: names are searched in order and this is a global cap — a name with many namesakes can use up the whole…

📤 Output

One row per result, saved to the dataset. Every row carries scrapedAt. Lookups that cannot be completed are reported in the run log rather than silently dropped.

Field	Description
lei	Lei
legalName	Legal Name
otherNames	Other Names
legalForm	Legal form / entity type
category	Category
entityStatus	Entity Status
registrationStatus	Registration Status
jurisdiction	Jurisdiction of formation
registeredAs	Registered As
legalAddress	Legal Address
headquartersAddress	Headquarters Address
creationDate	Creation Date
lastUpdated	Last Updated
crossReferences	Cross References
source	Source
license	License
sourceUrl	Public registry URL for the record
ownership	Ownership

💼 Use cases

1. Entity resolution — resolve a company name to its LEI. Input: names or LEI codes. Output: LEIs + legal names. Use: deduplicate a counterparty list.

2. Ownership mapping — map parent/child legal entities. Input: company names or LEIs. Output: parent/child relationships. Use: build a corporate-group graph.

3. KYB / regulatory — verify a legal entity by LEI. Input: the LEI or name. Output: the canonical GLEIF record. Use: confirm identity and jurisdiction.

🔗 Integration

JavaScript / Node.js

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_TOKEN' });
const run = await client.actor('foxlabs/lei-company-ownership').call({"names":["Volkswagen AG","Apple Inc"],"maxResults":12});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items[0]);

Python

from apify_client import ApifyClient
client = ApifyClient('YOUR_TOKEN')
run = client.actor('foxlabs/lei-company-ownership').call(run_input={"names":["Volkswagen AG","Apple Inc"],"maxResults":12})
for item in client.dataset(run['defaultDatasetId']).iterate_items():
    print(item)

Automation (n8n / Zapier / Make): schedule or webhook → HTTP request to the actor API with your input → handle the JSON dataset → push to a sheet, CRM or dashboard.

📊 Pricing

Pay-per-event: per delivered record. Empty or failed lookups are never billed. View current pricing.

❓ FAQ

Do I need an account, login or API key? No. This reads the Global Legal Entity Identifier Foundation (GLEIF) registry.

What do I search by? Company names or LEI codes.

How current is the data? Every run queries the source live, so results are as fresh as the registry.

What ownership data is included? Direct and ultimate parent relationships (where reported to GLEIF), plus the LEI, legal name, jurisdiction and registration status.

Can I export to CSV / Excel / JSON? Yes — directly from the Apify dataset.

🐛 Troubleshooting

• Fewer rows than expected — raise maxResults, or refine the input.
• A name returns an unexpected entity — it matched a similar registered name; search the exact registry ID.
• No rows for a name — try the entity’s exact legal name or its registry ID.

⚖️ Is it legal to scrape this data?

This actor reads a public government business registry published as open data. Results can still contain personal data (e.g. a registered agent’s name); personal data is protected by the GDPR and similar laws, so only process it with a legitimate basis. See Apify’s blog post on the legality of web scraping.

🤝 Support & contact

• 🌐 Website: data.foxlabs.com.tr
• 📧 Email: info@foxlabs.com.tr
• 🐛 Issues: open a ticket in the Actor’s Issues tab
• 🧰 More clean B2B data actors: Fox Labs on Apify

Changelog

0.3.9 — 2026-09-20 — README examples corrected against the real input schema

• The README's code examples did not match this Actor. They used queries and maxResultsPerQuery — keys that do not exist in this Actor's input schema — with a placeholder value, and the input table listed those same phantom fields. Anyone who copied the AI-agent, cURL, JavaScript or Python example got a failing run. Every example now uses the real schema and matches the Console prefill: {"names":["Volkswagen AG","Apple Inc"],"maxResults":12}
• The input table is regenerated from input_schema.json, so it lists the fields the Actor actually accepts.
• Removed claims carried over from the same generator template where present: "formation / status monitoring", "a canonical registry record for KYB and due diligence", "every row carries query", and industry described as a NACE code.
• No code, output field or pricing change.

0.3 — 2026-09-07

• Enabled AI-agent payments (x402) + rebuilt the README to the full standard (What-is / when, AI-agents + x402 agentic payments + MCP, Overview, Features, Use cases, Integration, FAQ, Troubleshooting, Support & contact).

0.0

• Initial release: data from the Global Legal Entity Identifier Foundation (GLEIF) registry by name or registry ID.