How Drizzle:AI Integrates with Qdrant

Modern AI applications, especially those using Retrieval-Augmented Generation (RAG), require a high-performance vector database. Drizzle handles the complex task of deploying, scaling, and managing a Qdrant cluster on Kubernetes. We provide a robust, production-ready vector search engine that your developers can immediately leverage to build next-generation AI features.

Key Features of the Integration

• Production-Ready Deployment: We deploy Qdrant as a scalable and resilient cluster on Kubernetes, ready to handle production workloads for your mission-critical RAG and semantic search applications.
• Optimized for Performance: Our implementation is optimized for high-performance vector search, enabling ultra-fast and accurate similarity searches across millions or even billions of vectors.
• Advanced Filtering and Payloads: Leverage Qdrant’s powerful filtering capabilities. We ensure your deployment can combine vector similarity search with custom payload filtering, giving you more relevant and precise results.
• Seamless Integration with your AI Stack: The Qdrant database is seamlessly integrated with the rest of your AI platform, making it easy for your applications and models to store and retrieve vector embeddings.

Contact us to learn more about Drizzle:AI