Company Registry Search - UK, France & Global LEI

Search three official company registers with one query and get a single flat table back. Each row has the same columns no matter which register it came from, so a mixed export opens cleanly in a spreadsheet without any reshaping.

Source	Register	Key needed
uk	Companies House Public Data API	Included, or bring your own
france	SIRENE, via the French government's recherche-entreprises API	None
global	GLEIF Legal Entity Identifier register	None

What data can I extract?

54 columns per row, the same columns whichever register answered:

• Identity - registered name, trading name, previous names, the registration number used by its own national register, LEI, French VAT number, head-office SIRET, BIC codes
• Status and form - active / dissolved / ceased, entity category (general, fund, branch, sole proprietor, association, public body), legal form with GLEIF's ISO 20275 codes resolved into readable English, plus the raw form code for machine joins
• Dates - incorporation, dissolution, and when the register itself last changed the record
• Location - registered office address, city, postal code, country, region; the separate operating headquarters address for LEI rows; latitude and longitude for French rows
• Size and activity - SIC / NAF activity code, industry section in English, INSEE size class, employee band, whether the entity is a registered employer, total and open establishment counts
• Money - turnover and net income in euros with the fiscal year they belong to, for French companies that file publicly
• People - named directors with their roles, and the count of currently appointed officers
• Group structure - direct and ultimate parent name and LEI
• UK compliance - accounts due and last made-up dates, whether accounts are overdue, confirmation statement due date, registered charges, insolvency history, undeliverable registered office
• Provenance - source register, jurisdiction, LEI registration status and next renewal date, and the record's public URL on the register's own site

Directors, previous names, UK compliance columns and group parents come from per-record endpoints; switch on include_details to fetch them. Every result is written to the default dataset and can be downloaded as JSON, CSV, Excel, or XML.

All 54 columns

Identity — company_name, establishment_number, lei, lei_next_renewal_date, lei_registration_status, parent_lei, parent_name, previous_names, registration_number, trade_name, ultimate_parent_lei, ultimate_parent_name, vat_number

Status — active_establishment_count, company_type, entity_category, has_charges, has_insolvency_history, is_employer, size_category, status

Dates — dissolution_date, financials_year, incorporation_date, last_updated

Location — address, city, confirmation_statement_next_due, country, headquarters_address, headquarters_city, headquarters_country, latitude, longitude, postal_code, region

Money — net_income, revenue

People — officer_count, officers

Contact — url

Counts and measures — accounts_last_made_up_to, accounts_next_due, accounts_overdue, employees, establishment_count

Other detail — activity_section, bic_codes, certifications, jurisdiction, legal_form_code, registered_office_undeliverable, sic_codes, source_registry

Input example

{
  "search_terms": ["Tesco"],
  "sources": ["uk", "france", "global"],
  "active_only": true,
  "include_details": true,
  "max_items": 50
}

max_items is a hard output ceiling, split evenly across the selected registers and search terms, so no single register can crowd out the others.

include_details buys the columns that only per-company endpoints publish - UK directors, previous names, accounts and confirmation-statement due dates, charges and insolvency history, and the direct and ultimate parent of an LEI row. It costs two extra requests per UK record and two per LEI record, so a detailed run takes noticeably longer. French rows carry everything in the search response and are unaffected either way.

Output example

One UK row, with include_details on. Columns the register does not publish for this entity come back as null; the full 54 are in the dataset schema.

{
  "source_registry": "companies_house",
  "jurisdiction": "GB",
  "company_name": "VODAFONE GROUP SERVICES NO.2 LIMITED",
  "previous_names": "VODAFONE GROUP SERVICES LIMITED, VODAFONE AIRTOUCH GROUP SERVICES LIMITED, RACAL TELECOM CENTRAL SERVICES LIMITED",
  "registration_number": "02370135",
  "status": "active",
  "company_type": "ltd",
  "legal_form_code": "ltd",
  "incorporation_date": "1989-04-05",
  "dissolution_date": null,
  "address": "Vodafone House, The Connection",
  "city": "Newbury",
  "postal_code": "RG14 2FN",
  "country": "United Kingdom",
  "region": "Berkshire",
  "sic_codes": "69102, 69201, 78200, 82990",
  "officers": "VODAFONE CORPORATE SECRETARIES LIMITED (corporate-secretary), GOSTOVIC, Stevan (director), PRETORIUS, Sugnet (director), RAGGETT, Andrew Thurston (director)",
  "officer_count": 4,
  "accounts_next_due": "2026-12-31",
  "accounts_last_made_up_to": "2025-03-31",
  "accounts_overdue": false,
  "confirmation_statement_next_due": "2027-03-13",
  "has_charges": false,
  "has_insolvency_history": false,
  "registered_office_undeliverable": false,
  "url": "https://find-and-update.company-information.service.gov.uk/company/02370135"
}

A French row instead fills trade_name, latitude / longitude, establishment_number (SIRET), activity_section, size_category, establishment_count, revenue, net_income, financials_year, vat_number and certifications; a GLEIF row fills lei, bic_codes, the headquarters_* columns, entity_category and, with include_details, parent_name / ultimate_parent_name.

Every row carries every column. A value the source does not publish is returned as null rather than being omitted or merged into a neighbouring field.

Matching records across registers

GLEIF publishes each entity's number in its own national register, and this Actor maps it to registration_number - the same column the UK and French rows use. Tesco PLC is 00445790 in both the GLEIF row and the Companies House row, so joining the two sources is a straight key match rather than fuzzy name comparison.

Common use cases

• Entity resolution across jurisdictions during vendor or counterparty onboarding
• KYC and sanctions-adjacent research where the registration number has to come from an official source
• Enriching a CRM or master-data table with registered names, numbers and addresses
• Finding the subsidiaries of a group by name stem across several countries at once

Use with AI agents and MCP

Apify's MCP server can discover and call this Actor from an AI workflow. Example intent:

Find active companies called Tesco in the UK, French and global registers and return their registration numbers and registered addresses.

Use the JSON from Input example as the tool arguments. The strict input schema rejects unsupported parameters, and the documented dataset schema tells the agent how to interpret each returned field.

Pricing and cost control

Output is billed per result at $0.003 per result (about $3.00 per 1,000 results), plus a $0.0002 Actor-start charge billed once per gigabyte of memory at run start. Use max_items to cap both output volume and charges. The price shown on the Apify Store listing is authoritative.

max_items limits both output volume and result-based charges. Start with the bounded default, inspect the rows, then scale deliberately.

Reliability

The Actor validates input, bounds pagination, and treats each register independently: a register that rate-limits, errors or returns a short page logs a warning and keeps the records it already has instead of failing the run. Records that match more than one search term are deduplicated on source and registration number. A production default-input canary is monitored by the fleet.

Bringing your own Companies House key

The UK source works without any setup. It runs on a shared Companies House key whose quota - 600 requests per five minutes - is shared by everyone running this Actor, so a very large or time-critical UK run can hit the ceiling and stop early with a rate-limit warning in the log.

If that matters to you, register a free key at developer.company-information.service.gov.uk, choose application type REST, and paste it into companies_house_key. The field is stored encrypted. Your key is then used for the whole run and only your own quota applies.

Limitations and responsible use

• A name search returns similarly named entities. The registers match on the name as it is registered, so a trading name or a misspelling may miss.
• Coverage is what each register publishes. A company that exists but has no LEI has no GLEIF row; a UK company dissolved decades ago may predate the digital record.
• active_only is applied by the source where the source supports it. Turn it off to include dissolved and ceased entities.
• SIC codes are present on roughly two of every three Companies House records; French legal form is returned as the INSEE catégorie juridique code.
• This tool supplies public reference data, not a KYC decision.

Source licences: Companies House data is published under the Open Government Licence v3.0, SIRENE under Licence Ouverte 2.0, and the GLEIF register under CC0. Use the data lawfully, respect the source terms, and independently validate records before making consequential decisions.

FAQ

What does include_details actually add?

UK directors and previous names, accounts and confirmation-statement due dates, registered charges, insolvency history and whether the registered office is undeliverable; and for LEI rows, the direct and ultimate parent. None of that is in the search responses, so it costs two extra requests per UK record and two per LEI record. Leave it off for a fast name-and-address lookup.

Does it need my own API key?

No. All three registers work out of the box. A Companies House key of your own is optional and only affects which rate-limit quota the UK source draws on.

Why do some rows have an LEI and others do not?

Only the GLEIF register issues LEIs, and only entities that have registered for one appear there. UK and French rows carry an LEI only when the same company also appears in GLEIF.

Can I search several company names in one run?

Yes. search_terms takes up to 25 names, and every name is searched in every selected register. Records that match more than one term are returned once.

Can I export the results?

Yes. Download the default dataset as JSON, CSV, Excel, or XML, or retrieve it through the Apify API.

How do I control cost?

Set max_items to the most records you want returned, and narrow sources to the registers you actually need.

Can an AI agent call it?

Yes. The Actor has strict input and semantic output schemas and can be called through Apify's MCP tooling.

What happens when one register is down?

The run continues. A failing register logs a warning and contributes no rows; the others still return their records.