French Company Search: SIRENE, SIREN & SIRET

Search France's official company register by name, activity, postcode, department, size or legal form. Export SIREN, SIRET, VAT, address and officer data. This Actor turns the French public company-data API backed by the SIRENE register into bounded, structured datasets for analysis, enrichment, monitoring, and AI-agent workflows.

What data can I extract?

• Company and establishment identifiers (SIREN and SIRET)
• Registered and trade names, legal status and activity codes
• Headquarters address, workforce band, VAT number and officers
• Filters for department, postcode, NAF activity, legal form and active status

Every run writes flat records to the default dataset. Download results as JSON, CSV, Excel, XML, or access them through the Apify API.

All 98 columns

Identity — association_id, foundation_id, has_ademe_aid, has_deminimis_aid, health_facility_ids, hq_siret, hq_trade_name, is_training_provider, legal_name, match_siret, match_trade_name, name, primary_officer_name, siren, training_provider_ids, vat_number

Status — diffusion_status, entertainment_licence_status, has_gender_equality_index, has_ghg_report, hq_is_employer, hq_status, inclusion_employer_type, is_association, is_education_facility, is_entertainment_contractor, is_food_safety_listed, is_government_body, is_health_facility, is_heritage_company, is_inclusion_employer, is_law_firm, is_organic_certified, is_qualiopi_certified, is_responsible_purchasing, is_rge_certified, is_social_economy, is_sole_trader, match_is_employer, match_is_headquarters, match_status, status

Dates — closure_date, company_size_year, creation_date, employees_year, financials_year, hq_closure_date, hq_creation_date, hq_employees_year, last_updated, last_updated_insee, last_updated_rne, match_closure_date, match_creation_date, match_employees_year

Location — hq_address, hq_city, hq_latitude, hq_longitude, hq_postal_code, hq_region, match_address, match_city, match_latitude, match_longitude, match_postal_code, match_region

Money — net_income, revenue

People — local_authority_code, local_authority_insee_code, officer_count, officers, primary_officer_role

Counts and measures — company_size, employees, establishment_count, hq_employees, match_employees, open_establishment_count

Other detail — acronym, activity_section, artisan_activity_code, collective_agreements, hq_commune_code, hq_department, hq_epci_code, hq_naf_code, hq_naf_code_2025, legal_form_code, match_commune_code, match_department, match_epci_code, match_naf_code, match_naf_code_2025, naf_code, naf_code_2025

Input example

{
  "query": "boulangerie",
  "department": "75",
  "active_only": true,
  "max_items": 100
}

max_items is a hard output and billing ceiling. The default input is intentionally limited to 10 records so Store tests and first runs stay inexpensive.

Output example

{
  "siren": "Example siren",
  "name": "Example organization",
  "legal_name": "Example legal name",
  "acronym": "Example acronym",
  "status": "RECRUITING",
  "naf_code": "Example naf code",
  "naf_code_2025": "10.71G",
  "artisan_activity_code": "1071CB",
  "activity_section": "Example activity section",
  "legal_form_code": "Example legal form code",
  "company_size": "Example company size",
  "company_size_year": "2023",
  "employees": "Example employees",
  "employees_year": "Example employees year",
  "creation_date": "Example creation date",
  "closure_date": "Example closure date",
  "last_updated": "Example last updated",
  "last_updated_insee": "2026-05-07T14:31:50",
  "last_updated_rne": "2026-08-26T12:42:48",
  "diffusion_status": "public",
  "establishment_count": 10,
  "open_establishment_count": 10,
  "vat_number": "Example vat number",
  "officers": "Example officers",
  "officer_count": 10,
  "primary_officer_name": "GUILLAUME FAURY",
  "primary_officer_role": "Président de SAS",
  "revenue": 75869141
}

70 further columns are omitted here for length — the full list is above, and every column appears in the export whether or not the source populated it.

Use with AI agents and MCP

Apify's hosted MCP server can discover and call this Actor. A suitable agent request is:

Find 100 active bakeries in Paris and return SIREN, headquarters address, activity and VAT data.

Use this exact Actor input:

{
  "query": "boulangerie",
  "department": "75",
  "active_only": true,
  "max_items": 100
}

The Actor succeeds with a nonempty default dataset and exposes its default dataset through the top-level Output schema.

Pricing and cost control

Output is billed per result at $0.002 per result (about $2.00 per 1,000 results), plus a $0.0005 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.

Use max_items to cap returned and billable records. Invalid input is rejected before unnecessary work wherever possible.

Common use cases

• Source-specific research and market intelligence
• Structured exports for spreadsheets, warehouses and BI systems
• Entity enrichment and monitoring pipelines
• Retrieval and data collection by AI agents

Reliability

The Actor uses bounded pagination, retries transient upstream failures, deduplicates records where the source exposes stable identifiers, and fails explicitly when the source cannot provide usable output. Production default-input canaries verify a nonempty structured dataset in under five minutes.

Limitations and responsible use

• Coverage, field availability and update timing are controlled by the upstream public source.
• Optional fields can be null or absent when the source does not publish them.
• This Actor does not bypass authentication, access controls, CAPTCHAs, or source rate limits.
• Customers remain responsible for lawful use, applicable source terms, and restrictions on downstream decisions.

FAQ

What is the best way to run this French company search Actor?

Start with the 10-record default, inspect the dataset, then increase max_items and narrow the available filters for your use case.

Do I need my own API key?

No external API key is required unless the Input tab explicitly says otherwise. Apify credentials are used normally when invoking the Actor through Apify APIs or MCP.

Can an AI agent call it?

Yes. The strict input schema acts as the tool signature, and the dataset plus Output schemas describe the returned records.

Can I export the results?

Yes. Apify datasets support JSON, CSV, Excel, XML and API retrieval.

Support and changes

Open an issue on the Actor page with a redacted input and run ID. See ./CHANGELOG.md for contract and maintenance updates.