Qdrant

Qdrant's valuation is not publicly disclosed.

Investor information for Qdrant is not publicly available at this time.

No public funding round data is currently available for Qdrant.

Qdrant has approximately 50-200 employees.

Qdrant builds a high-performance vector similarity search engine and managed vector database service optimized for production AI applications requiring fast nearest-neighbor retrieval at scale. The engine is implemented in Rust for memory efficiency and throughput, and supports filtered vector search, payload indexing, and hybrid dense-sparse retrieval in a single system.\n\nThe company raised approximately 28 million USD and serves AI engineering teams across Europe and North America building recommendation systems, semantic search, computer vision pipelines, and RAG-based applications that require low-latency retrieval over large embedding collections. Qdrant is open-source with a managed cloud offering, following the commercial open-source model common in developer infrastructure.\n\nThe vector database market is consolidating around a handful of well-funded players as enterprises standardize their AI data stacks and look for production-grade infrastructure with strong SLAs and support. Qdrant differentiates from pure-cloud competitors through its Rust-based performance characteristics and its strong adoption in European markets where data sovereignty concerns make self-hosted options more commercially attractive than US-operated managed services.