Local-first open-source knowledge graph builder and RAG wiki with CLI and desktop app.
Best for: Developers building a persistent second brain with AI agent integration, Researchers compiling personal knowledge graphs from diverse sources
Open lakehouse format for multimodal AI with fast random access and hybrid search.
Best for: ML engineers building multimodal retrieval (RAG, image/video search) systems, Data scientists managing large-scale embedding stores with hybrid search
Open-source document intelligence engine for 98+ formats
Best for: Developers building high-throughput document extraction pipelines for RAG or data lakes, Teams needing polyglot SDK support (Python, TypeScript, Rust, Go, etc.) in microservices
MemOS gives AI agents persistent memory and growth with millisecond-level recall
Best for: Developers building AI agents that need long-term memory across sessions, Startups adding persistent memory to chatbots without infrastructure
API-first document parsing for AI agents and RAG pipelines
Best for: AI engineers building RAG pipelines over complex documents (tables, formulas, chemical structures), Developers needing a simple pay-per-page API for parsing PDFs, DOCX, and images
Sub-10ms real-time semantic search for voice AI and copilots — no vector DB needed.
Best for: Voice AI and conversational agent developers needing <10ms context retrieval, Teams building real-time copilots where every ms impacts user experience
Fastest RAG API for AI agents: cited answers in 300ms.
Best for: Teams building AI agents needing real-time, grounded document answers, Developers wanting a turnkey RAG API without infrastructure management
