Vector databases power the retrieval layer in RAG workflows by storing document and query embeddings as high‑dimensional vectors. They enable fast similarity searches based on vector distances.| AIMultiple
The effectiveness of any Retrieval-Augmented Generation (RAG) system depends on the precision of its retriever component.| AIMultiple