Huqan is a deterministic, local-first governance and verification layer for AI-assisted work. It evaluates claims and selected agent actions against evidence, provenance, context, and policy; protects canonical memory from unsupported writes; routes risky operations through explicit approval paths; and records consequential decisions with inspectable Trust Receipts. Not an LLM or universal truth engine.
I’m building Huqan around a simple gap in AI workflows: generating an answer and trusting that answer are not the same event.
Huqan adds a deterministic, local-first boundary around claims, memory admission, and selected agent actions. It makes evidence, provenance, policy, approval, risk, and the final decision inspectable through Trust Receipts.
I’d love feedback from people building agents, local-first tools, and security-sensitive automation: What do you consider essential in an AI agent monitoring application?