I built RelayOps, an open-source prototype for auditable AI support-agent routing. The goal is not to make a better chatbot. It is to test whether an AI support system can safely decide when to respond, act, block, or hand off. Current features: scoped customer/device tools deterministic access gate route safety for billing/account-risk requests guardrails for invented prices, discounts, and PII per-turn decision traces human handoff context local FAQ/RAG with citations Qwen LoRA intent eval optional local LLM composer public canned guardrail demo Honest scope: synthetic/sample data only no production users no real customer data not production-ready One eval detail I’m trying to keep honest: in-set safe-route: 1.000 held-out novel-phrasing safe-route: 0.786 The lower number is the more important one. Repo: https://github.com/patibandlavenkatamanideep/relayops Feedback welcome, especially on eval framing and whether the held-out routing setup is convincing submitted by /u/Fit_Fortune953 [link] [Kommentare]

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