An EntityMap is an entity-first, machine-readable index of a website's knowledge, published to the EntityMap v1.0 open standard so AI systems can read a business correctly.
An EntityMap is an entity-first, machine-readable index of a website's knowledge, built to the EntityMap v1.0 open standard. Instead of describing pages, it describes the things a business is about, its products, people, claims and relationships, in a structured form AI systems can parse. It helps assistants read your business accurately. K&C publishes its own at /entitymap.html.
AI assistants do not read a website the way a person does. They try to extract entities, the products, people, places, claims and relationships, and assemble them into an understanding of what a business is and does. When a site only offers prose and page links, the assistant has to infer that structure, and inference is where mistakes creep in.
A traditional sitemap lists pages. It tells a crawler where the URLs are, but nothing about meaning. An EntityMap is different. It is entity-first, so it states plainly what the entities are and how they connect, in a form a machine can read without guessing. That reduces the room for an assistant to misread or invent.
This matters more as AI Search grows. The cleaner and more explicit your machine-readable knowledge, the more likely the engines are to describe you accurately and cite you confidently. The EntityMap v1.0 open standard gives that structure a shared shape, so any AI system that supports it can read your business the same correct way.
K&C practises what it advises. We publish our own EntityMap at /entitymap.html, with a machine-readable version at /entitymap.json, both built to the EntityMap v1.0 open standard. It lets AI systems read K&C properly: who we are, what AI Visibility Strategy is, how the AI Visibility Score works, and how our terms relate.
For clients, a clean entity layer supports the Source Quality and Narrative Fit dimensions of our methodology. If the engines can read your structured knowledge without guessing, they are more likely to cite you accurately and place you correctly in the answer. Ambiguity in your entity layer becomes ambiguity in how the AI describes you.
When we assess a brand, we look at whether its knowledge is legible to machines, not just to humans. Where it is not, improving the entity layer is one of the practical levers we use to change the answer the engines give. It is a quiet, structural part of being found and cited.
An EntityMap is not a magic switch, and we never present it as one. It works alongside accurate sources and a consistent narrative, giving the engines a clean foundation to build on. But it is one of the most concrete, controllable things a business can publish, because it speaks the engines' own language. For a consultancy whose mission is to be read correctly by AI, publishing one is the obvious place to lead by example. Be Known. Be Cited.
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