Faiss is an open-source library developed by Facebook AI Research, designed for efficient similarity search and clustering of dense vectors. It's particularly useful when dealing with very large datasets that require fast nearest-neighbor searches, which are common tasks in machine learning and AI applications. Faiss uses various indexing and quantization techniques to optimize search speed and resource usage, making it suitable for large-scale data processing.