Qdrant is a high-performance open-source vector database and similarity search engine purpose-built for AI applications that require fast, scalable retrieval of high-dimensional vector embeddings. It offers HNSW indexing for millisecond similarity search at billion-vector scale, rich payload filtering, on-disk storage options, and a managed cloud offering for production deployments. AI engineers building RAG applications, recommendation systems, semantic search, and multimodal AI products choose Qdrant for its combination of search performance, feature richness, and the developer experience of a purpose-built vector-native database.