Vector database
Also: vector databases, vector store
A store built for embeddings, so you can quickly find texts with a similar meaning.
An embedding turns a piece of text into a position on a map. Texts that mean similar things land close together, even with different words. Searching by meaning means looking for the nearest neighbours on the map.
The fuller definition
A vector database stores vectors and associated metadata and supports similarity-based retrieval. Many systems combine vector search with filters or other search methods.
Go deeper
Related phrasing can be nearby in an embedding space. Real embeddings have many dimensions, and the model determines similarity. Nearby does not mean legally relevant or factually correct.
A concrete example
A query vector retrieves nearby passage vectors while filtering to the correct matter ID.
The distinction that matters
Vector similarity does not replace document permissions, source provenance, or exact searches.
Related terms
Embedding
A list of numbers used to compare items such as texts. Texts with similar meanings may have similar lists.
Documents & retrievalSemantic search
Searching by meaning rather than by exact words, so 'delay' can find 'postponed'.
Documents & retrievalMetadata
Information about a file rather than its contents, such as its author, date, and page count.
Where it is taught
How document-grounded AI answers workSource and further reading
Sentence Transformers · Semantic searchThe definition and example are written for this library. The link gives background, official documentation or legal authority as labelled. Legal scope depends on the jurisdiction and current text; product features depend on release and settings.