Cost-aware B2B lead enrichment that stops gathering data once it has enough evidence to decide. Confidence-gated routing, human review, and auditable Decision Receipts.
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Updated
Sep 2, 2026 - Python
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supasbase
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A production-oriented Agentic RAG ecosystem using a deterministic state-machine architecture (LangGraph) to eliminate LLM hallucinations. Engineered for privacy-first environments, it features local embedding generation, Qdrant vector search, and high-speed inference for high-accuracy document intelligence.
python state-machine render netlify privacy-first fastapi vector-database qdrant supasbase llm generative-ai langchain langgraph agentic-rag
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Updated
Jun 10, 2026 - Python
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