Knowledge graph
A knowledge graph is a database of things, like companies, people and products, and how they're connected, used by search engines and AI.
A knowledge graph is a database of things and the links between them. Each thing, called an entity, is a company, a person, a product or a place, with facts attached. The links say how they relate: this person founded that company, that company makes this product, the product is sold in these countries.
Search engines and AI systems use knowledge graphs to tell things apart and to answer facts quickly. If they have your brand in theirs, with the right facts, they're less likely to mix you up with someone else.
How it works
Think of it as a map of dots and lines. Fernhill Coffee is a dot. Its founder is a dot. Bristol is a dot. Lines between them say "founded by" and "based in." Ask "who founded Fernhill Coffee?" and the answer is one line away.
Google introduced its Knowledge Graph in 2012, and it's where the knowledge panels beside Google results come from. Wikidata is a public knowledge graph that anyone can read and edit.
Why it matters for AI search
A language model doesn't store facts in a neat graph. It learns from text. But the graph's facts end up in a lot of that text, and platforms can look things up in a graph too. A brand that's a clear, well-described entity is easier to get right.
For example, if two businesses called "Kestrel" exist, one a coffee roaster and one a drone maker, a graph that knows which is which helps an answer about "Kestrel coffee" name the right one.
How to get your brand into one
Describe your business the same way everywhere. Add Organization structured data to your site, with links to your official profiles. Keep your Google Business Profile up to date, and add your company to Wikidata if it meets the rules there.