What is a vector database?
A vector database stores text, images, or audio as embeddings — numeric representations of meaning — and retrieves items by similarity rather than exact matching. It is the component that lets a search for "time off policy" return a document titled "paid leave guidelines" with no shared keywords.
Embeddings place semantically similar content close together in a high-dimensional space. Retrieval becomes a question of proximity, which is what allows a system to find the relevant passage without the query and the document sharing vocabulary.
In a retrieval-augmented system, the vector database is the retrieval half. Its quality has an outsized effect on the final answer: if the right passage is not returned, no model can compose a correct response from what it was given.
Where this shows up in our work
Related terms
Got an idea? Let's make it real.
Tell us about your problem. We'll come back within one business day with a take, a rough plan, and a call invite.