Ontology, knowledge graph, semantic layer… The words sound impressive. The ideas behind them are simple: meaning, connections, consistency, identity, similarity and context.
Plug AI into data that’s poorly defined, duplicated and scattered, and it will give you wrong answers with great confidence. These six foundations teach it what your data actually means.
In practice, most companies don’t need all six on day one. If your teams argue about what a number means, start with the semantic layer. If the same customer appears three times in your systems, start with entity resolution. The graph and GraphRAG come later, once questions start crossing several systems.
The test is simple. Ask your AI assistant a question you already know the answer to, about your own customers or revenue. If it gets it wrong, the problem is rarely the model. It’s the data underneath.
Related serviceAI that knows your business