Qdrant is an open-source vector database designed to store embeddings and find the most similar items in milliseconds. It powers semantic search, recommendations, and RAG systems, offering filtering, scaling, and a simple API. Written in Rust for speed, it can run locally, in Docker, or as a managed cloud service. A Casablanca e-commerce shop could use Qdrant to let customers search products by meaning, so a query like «warm winter jacket» returns relevant items even without exact keyword matches.