Identity Index Centralizes Your Entity Data

Identity Index is a component of Entity API™ that consolidates canonical entity data into a centralized, machine-readable reference. It combines an llms.txt file (direct instructions for LLMs) and a brand fact file (verified entity attributes) so AI systems have a single source of truth when retrieving information about your business.

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{

Identity Index Overview [v1.0] · Updated: 2026-01-24

entity_type: Framework Component
parent_framework: Entity API™
organization: Growth Marshal

component: Identity Index
component_function: Entity verification · Canonical data storage · LLM instruction
component_files: llms.txt · Brand Fact File

related_components: Schema Layer

}

Why having an identity index matters for AI retrieval

AI systems don't guess who you are. They query structured sources. Your identity index gives them a single, canonical reference to pull from.

Establish a Single Source of Truth

Your identity index consolidates entity data into one canonical reference. AI systems get consistent facts about your business, not conflicting information scraped from multiple sources.

Give LLMs Direct Instructions

Your llms.txt file tells AI exactly how to describe your business, what facts are canonical, and what relationships matter. No interpretation required.

Verify Your Entity Attributes

Your brand fact file stores verified data: legal name, founding date, leadership, identifiers, credentials. When AI needs to confirm who you are, this is what it references.

Prevent Hallucination

Without a canonical source, AI fills gaps with guesses. Your identity index gives AI verified facts so it doesn't invent details about your business.

How it works

We create your llms.txt file with direct instructions for LLMs, then build your brand fact file with verified entity attributes. Together, they form a centralized identity index that AI systems query when retrieving information about your business.

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[llms.txt file]:

A dedicated file at your domain root that feeds context directly to large language models. It specifies how your business should be described, what facts are canonical, and what relationships matter.

[canonical identifiers]:

We embed unique identifiers directly into your identity index so AI can disambiguate your entity from every other company with a similar name. No guessing, no conflation.

[brand fact file]:

A machine-readable document consolidating your canonical entity data: legal name, identifiers (LEI, ISNI, ORCID), founding date, leadership, service offerings, and verified credentials.

[sameAs linking]:

We connect your identity index to external authority sources (LinkedIn, Crunchbase, Wikidata, industry directories) so AI can cross-reference and validate your entity across the web.

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Identity Index FAQ

  • An identity index is a centralized, machine-readable reference that consolidates your canonical entity data. It combines an llms.txt file (direct instructions for LLMs) and a brand fact file (verified entity attributes) so AI systems have a single source of truth when retrieving information about your business.

  • An llms.txt file is a dedicated file placed at your domain root that feeds context directly to large language models. It specifies how your business should be described, what facts are canonical, and what relationships matter. Think of it as a README file for AI.

  • A brand fact file is a machine-readable document that consolidates your verified entity data: legal name, founding date, leadership, service offerings, canonical identifiers (LEI, ISNI, ORCID), and credentials. When AI needs to confirm who you are, this is what it references.

  • Without a centralized source of truth, AI systems scrape information from multiple sources and may return conflicting, outdated, or hallucinated details about your business. An identity index gives AI verified facts so it doesn't guess or invent information.

  • AI hallucination happens when models fill knowledge gaps with plausible-sounding but incorrect information. An identity index provides explicit, verified facts about your entity so AI has no gaps to fill. Canonical data in, canonical answers out.

  • sameAs links connect your identity index to external authority sources like LinkedIn, Crunchbase, Wikidata, and industry directories. They tell AI systems that these external profiles refer to the same entity, allowing cross-reference and validation.

  • Schema layer and identity index are the two components of Entity API™. Schema layer connects your entity nodes using structured data with graph properties. Identity index centralizes your canonical entity data in machine-readable files. Together, they make your business fully machine-readable to AI.