Vector Search
Vector search find content by meaning instead of exact words. Text dey converted into high-dimensional embeddings, and similarity metric like cosine distance rank stored vectors by how close dem dey to query vector, returning related passages even when no keywords match.
Synonym dem: semantic search, similarity search, nearest-neighbor search, embedding search
Vector search power semantic retrieval: instead of matching strings, e match meaning. Query dey embedded into di same vector space as indexed content, and index return nearest vectors by distance metric. To stay fast at scale, production systems use approximate nearest-neighbor indexes wey accept tiny accuracy trade-offs for major latency wins. Vector search most effective when paired with keyword search in hybrid retriever, so exact identifiers no lost to pure semantic matching.