Endee

Endee is a high-performance, open-source vector database built from the ground up for production AI workloads. Its proprietary Vector Graph Engine (VGE) combines layered memory design, processor acceleration, and intelligent quantization to deliver sub-5ms query latency, 99%+ recall, and up to 10× memory reduction compared to traditional vector databases. Endee supports use cases including AI agents, semantic search, and personalized recommendations, and is trusted by enterprises such as Saint-Gobain and Forbes Marshall.

• Vector Graph Engine (VGE): The core technology unifying layered memory design, processor acceleration, and intelligent quantization for ultra-high performance vector search.
• Sub-5ms Latency: Optimized query response times at any scale, designed for demanding production workloads.
• 10× Memory Efficiency: Stores 10 million vectors in ~10 GB versus ~100 GB for traditional vector databases, cutting infrastructure costs by up to 90%.
• Infinite Horizontal Scale: Handle billions of vectors without performance degradation; horizontal scaling is built in.
• 100% Open Source: Fully open source under a permissive license — fork, modify, and contribute freely via GitHub.
• Developer-First SDKs: RESTful API with official SDKs for Python, TypeScript, Go, and Java to get started in minutes.
• Queryable Encryption (Enterprise): Perform vector similarity searches on encrypted data without decryption, enabling true zero-knowledge security.
• Fully Managed Enterprise Option: On-premise or managed deployment with automated backups, seamless upgrades, ISO 27001/SOC 2/GDPR compliance, and 24/7 dedicated support.
• Hybrid Search & Advanced Filters: Combine vector similarity with metadata filtering for precise, context-aware retrieval.
• Community Driven: Active community with regular updates; join discussions on Discord and Reddit to shape the roadmap.