EntityMap aims to fix how AI systems describe businesses, seeks feedback

AI systems are already answering questions about businesses, and too often they are doing it by guessing. EntityMap is trying to change that with an open standard that turns website knowledge into a structured, entity-first index for AI systems, retrieval pipelines and language-model-based applications. Its public consultation runs through June 30, 2026, with formal launch set for July 1.

The core problem is familiar to anyone who has watched a large brand get mangled by an AI answer engine. Products, services, leadership names, office locations and corporate relationships are often scattered across dozens of pages, so a model stitches the fragments together probabilistically. That is how hallucinated product names, invented executives, misquoted capabilities and weak attribution slip into answers. EntityMap’s pitch is to supply a structured source of truth instead of forcing the model to reconstruct one from loose page-level signals.

The project is not trying to replace the old web stack. It is positioned alongside sitemap.xml and schema.org, not in place of them. Sitemaps still tell crawlers which pages exist, and schema still describes what appears on individual pages. EntityMap is aimed at a different layer: what an organization is, what it knows, and how those facts connect across the site, with claims tied back to supporting evidence. The v1.0 technical specification is publicly available and licensed under CC BY 4.0.

The consultation is also a clear call for hands-on input. Developers, publishers, structured-data specialists, AI retrieval practitioners, SEO professionals and data-quality experts are being asked to review the specification, test implementation and send feedback through the community forum and GitHub repository. Fred Laurent, CTO of InLinks and Waikay, said EntityMap tells AI systems what an organization is, what it does, and how its knowledge connects.

For agencies, that turns EntityMap into more than another standards memo. It is a packaging opportunity around AI visibility infrastructure, especially for brands with sprawling product catalogs, many locations or dense corporate structures. Technical SEO, content strategy and digital PR can work together on entity modeling, evidence mapping and structured knowledge maintenance instead of treating schema as a page-level checkbox. InLinks, co-founded and operated by Dixon Jones and Fred Laurent, already centers its work on entity-based SEO software, internal linking automation, schema markup implementation and content auditing based on entities. EntityMap fits that direction neatly, and it gives agencies a way to sell cleaner machine-readable identity before AI systems lock in the wrong version of a brand.