Vector Search

Definition

Finding relevant content by comparing embedding vectors for semantic closeness rather than matching exact keywords.

Vector search indexes content as embeddings and, for a given query embedding, returns the passages whose vectors are nearest in meaning. It underpins the retrieval stage of most AI answer engines, allowing them to surface conceptually relevant material that a keyword search would miss. For visibility, it means the framing and clarity of your ideas matter more than exact phrasing, because the engine matches on meaning and then decides which passage to quote.