Qdrant is an open-source vector database designed for efficient similarity search and storage of high-dimensional embeddings. It is optimized for AI and machine learning applications, enabling fast and accurate retrieval of relevant data points using vector similarity (e.g., cosine or dot product). Qdrant supports filtering, payload storage, and real-time updates, making it well-suited for use cases like semantic search, recommendation systems, and generative AI. With a user-friendly API and integrations with popular ML frameworks, Qdrant simplifies the deployment of scalable, production-ready vector search solutions.