Qdrant
Open-source vector search engine built in Rust, providing fast and scalable similarity search infrastructure for production AI applications including RAG systems, AI agents, and recommendation engines.
Overview
Qdrant is a Berlin-based company building an open-source vector search engine written in Rust for production AI workloads. The platform provides fast, scalable similarity search with a convenient API, serving as core infrastructure for retrieval-augmented generation (RAG), AI agents, recommendation engines, semantic search, and anomaly detection. Key technical differentiators include native hybrid search combining dense and sparse vectors in a single query, advanced metadata filtering applied during search traversal rather than post-processing, multi-vector support for multimodal retrieval, real-time indexing without full reindex cycles, and efficient quantization reducing memory consumption up to 64x. Qdrant supports deployment across managed cloud, on-premises, hybrid cloud, and edge environments. The Series B round of 0M led by AVP brought total funding to 7.5M, supporting the company's mission to scale composable vector search for enterprise AI.
Funding History
Qdrant raises $50M from AVP to redefine vector search for production AI
Qdrant raises $28M Series A for open-source vector database platform, with Spark Capital participating.
Frequently Asked Questions
- How much funding does AI Funding track for Qdrant?
- AI Funding tracks $78M for Qdrant across 2 funding rounds in this database.
- Who are Qdrant's investors?
- Qdrant's investors include Spark Capital, AVP, Bosch Ventures, Unusual Ventures.
- What does Qdrant do?
- Qdrant is a Berlin-based company building an open-source vector search engine written in Rust for production AI workloads. The platform provides fast, scalable similarity search with a convenient API, serving as core infrastructure for retrieval-augmented generation (RAG), AI agents, recommendation engines, semantic search, and anomaly detection. Key technical differentiators include native hybrid search combining dense and sparse vectors in a single query, advanced metadata filtering applied during search traversal rather than post-processing, multi-vector support for multimodal retrieval, real-time indexing without full reindex cycles, and efficient quantization reducing memory consumption up to 64x. Qdrant supports deployment across managed cloud, on-premises, hybrid cloud, and edge environments. The Series B round of 0M led by AVP brought total funding to 7.5M, supporting the company's mission to scale composable vector search for enterprise AI.
- When was Qdrant founded?
- Qdrant was founded in 2021 and is headquartered in Berlin, Germany.
- Where is Qdrant headquartered?
- Qdrant is headquartered in Berlin, Germany.
Investors
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