EntityMap launched: the JSON file that tells AI engines who your brand is

Why do AI retrieval systems guess at your brand identity today?#

AI retrieval systems extract knowledge from text, but inferring organizational identity from unstructured crawl data is expensive and error-prone. A typical brand homepage contains a headline, a value proposition, and a navigation menu. Nothing tells Gemini, Perplexity, or ChatGPT which knowledge category the brand owns, which entities it connects to, or how authoritative it is in that domain.

Fact 1: 45% of marketing leaders cannot measure their brand's presence in AI-generated answers, and only 9% have tools to track all relevant metrics across AI platforms, per Semrush's 2026 AI Visibility Index, which analyzed 126 million AI search prompts across ChatGPT, Gemini, Google AI Mode, and AI Overviews from January through April 2026.

Fact 2: Only 30% of brands maintain visibility from one AI-generated answer to the next on the same topic, per the AirOps 2026 State of AI Search report, because AI retrieval systems rely on probabilistic entity resolution, and brands without explicit entity signals lose consistency across repeated queries.

Without a structured entity declaration, every AI retrieval system has to piece together who you are from crawled fragments, Wikipedia mentions, and co-occurrence with related entities across billions of training tokens. EntityMap replaces that inference process with a direct declaration: here is who we are, here is what we know, here is where the evidence lives.

What goes inside an entitymap.json file?#

The EntityMap specification defines four primary declaration blocks. Each block maps to a specific question AI retrieval systems ask when deciding whether a brand qualifies as a relevant source for a given query.

Organization identity block: The canonical name of the organization, its primary URL, Wikipedia article URL if one exists, Crunchbase profile URL, LinkedIn company page URL, and founding date. AI systems use these anchors to resolve entity mentions across web pages and to distinguish your brand from identically-named organizations in other categories.

Knowledge domain block: The specific topics the organization holds expertise in, tagged to recognizable industry classifications. This tells Perplexity that your entity is relevant when a user asks about AI visibility monitoring for SaaS brands.

Entity relationship block: Connections between your organization and related entities: technology partners, industry bodies, named researchers in your category, or categories against which your brand is compared. AI systems weight citation probability based on co-occurrence in entity graphs.

Evidence pointers block: A ranked list of URLs pointing to the organization's most authoritative content, ordered by credibility signal strength. This is the AI-readable equivalent of a priority sitemap for your most citable pages.

Fact 1: Fred Laurent designed EntityMap to complement existing schema.org Organization markup, not replace it: entitymap.json extends the entity graph declaration layer to give AI systems a structured file they can process in a single crawl, per the EntityMap specification at InLinks.

Fact 2: Brands with active third-party trust signals (external citations, Wikipedia articles, Crunchbase profiles) are cited 75 times more often in AI-generated answers than brands without those signals, per [Semrush's 2026 AI Visibility In