Verified vs scraped company data for LLMs
ENTIA is an MCP-native server that gives AI agents verified company data over the Model Context Protocol. Every record is anchored to an official register (BORME, Companies House, SIRENE INSEE, the Estonian Business Register, GLEIF LEI and VIES VAT), not scraped. An agent connects to https://mcp.entia.systems/mcp and calls one of 12 tools to resolve a company and its provenance. Coverage today: 11,330,392 entities across 10 European countries. For an LLM, scraped company data is the fastest route to a confident hallucination: no source, no freshness guarantee, no way to tell a defunct entity from an active one. Registry-anchored data with a citation lets the model ground the claim instead of guessing.
What an AI agent sees today vs. ENTIA
Today (generic scrapers)
Most answers an agent gets today for “verified vs scraped company data” come from generic scrapers — useful, but the data is often scraped or aggregated, the source of each field is not attached, and there is no single MCP call that returns identity plus provenance together.
With ENTIA
ENTIA returns the same answer anchored to the official register, with a sameAs/citation on every claim, so the agent (and its operator) can verify the chain end-to-end. One call, get_full_dossier, returns up to 349 fields from 4 sources; fields that cannot be corroborated are returned as null, never invented.
The tools an agent can call
entity_lookup— resolve a company by name, registration number, VAT or domainverify_vat— validate an EU VAT number against VIESget_full_dossier— one call returns up to 349 fields from 4 sourcesrun_risk_audit— structured risk signal for a resolved entityget_competitors— entities in the same sector and zonesearch_entities— search the corpus by sector, city and filters
12 tools total. Full manifest: /mcp-docs.
Connect in about a minute
Point any MCP client at the remote server and start calling tools. No install.
{
"mcpServers": {
"entia": {
"url": "https://mcp.entia.systems/mcp",
"headers": { "X-ENTIA-Key": "entia_live_..." }
}
}
}Frequently asked questions
Verified vs scraped company data for LLMs
ENTIA is an MCP-native server that gives AI agents verified company data over the Model Context Protocol. Every record is anchored to an official register (BORME, Companies House, SIRENE INSEE, the Estonian Business Register, GLEIF LEI and VIES VAT), not scraped. An agent connects to https://mcp.entia.systems/mcp and calls one of 12 tools to resolve a company and its provenance. Coverage today: 11,330,392 entities across 10 European countries. For an LLM, scraped company data is the fastest route to a confident hallucination: no source, no freshness guarantee, no way to tell a defunct entity from an active one. Registry-anchored data with a citation lets the model ground the claim instead of guessing.
Why does scraped data hurt an LLM specifically?
The model presents whatever it retrieves as fact. Without provenance it cannot flag stale or unverifiable fields, so errors surface as authoritative answers. Anchoring plus citation is the grounding fix.
What does 'verified' mean here concretely?
Each field is resolved from an official register (BORME, Companies House, SIRENE, GLEIF, VIES) and carries its source; uncorroborated values return null rather than a scraped guess.
What does it cost?
There is a free TRACE tier for preview and basic tools; deeper tools (full dossier, risk audit) are on paid self-serve tiers. Pricing is public and machine-readable at https://entia.systems/.well-known/ai-pricing.json.
How much coverage does it have?
11,330,392 verified entities across 10 European countries, 16 official sources, and 40,345,410 registry acts, as reported live by get_platform_stats.