Does a vector database enforce permissions?

Not by itself. Access control has to be applied around it, ideally at answer time, or retrieval will happily return passages the person asking should not see.

Do we need one to use AI on company data?

Almost always something plays that role, though it is usually a component inside the platform rather than a database a company runs and tunes itself.

Vector Database

A vector database indexes content by meaning rather than exact wording, so an AI system can find relevant passages even when the words do not match.

Text is converted into an embedding, a list of numbers positioning it in a space where related meanings sit close together. A query is embedded the same way, and retrieval becomes a nearest-neighbour search. This is why a search for "time off policy" can return a document titled "annual leave" without anyone maintaining a synonym list.

It is infrastructure rather than a strategy. A vector store retrieves passages that resemble the question; it does not know which document supersedes which, who owns a record, or whether the person asking is allowed to see the result. Those belong to the layers around it, which is why vector search alone tends to plateau quickly on company data.

Frequently Asked Questions

A keyword index matches words. A vector database matches meaning, which finds relevant material that uses different terminology. Most production systems combine both.