FAISS (Facebook AI Similarity Search) is an open-source library for efficient similarity search and clustering of dense vectors, providing exact and approximate nearest-neighbour algorithms that scale to billions of embeddings. It implements index structures such as inverted files and product quantisation, with GPU acceleration for high-throughput retrieval. FAISS is widely used as the vector index backend for semantic search and retrieval-augmented generation pipelines.