Embedding

An Embedding is a fixed-length vector produced by a model so that semantically similar inputs sit close together in vector space. Embeddings power semantic search, clustering, classification, deduplication and the retrieval step of RAG.

Embed every paragraph in your docs once, store the vectors, then at query time embed the user's question and return the closest paragraphs — even if they share no exact keywords.