Vector search is a technique for retrieving semantically similar items by comparing their vector embeddings rather than exact keyword matches. It powers recommendation systems, semantic search engines, and retrieval-augmented generation pipelines. Libraries like FAISS, Pinecone, and Weaviate enable efficient nearest-neighbor search across millions of high-dimensional vectors.