I built an AI support-agent prototype and realized the hard part is not the chatbot it is the handoff and audit trail. Looking for critique from people who run support/CX workflows.

I’ve been building RelayOps, a prototype AI support agent for telecom/subscription-style support. The goal is not just “answer the user.” I’m testing a narrower question: > Current version: * processes a sample support-ticket queue * auto-resolves low-risk reversible cases * escalates billing/account-risk cases * blocks unsafe actions * writes one audit record per ticket * creates human handoff tickets with owner/reason/evidence/deadline * shows decisions in a live console * exports JSONL/CSV audit records On my current 50-ticket sample queue: * 27 auto-resolved * 20 human handoffs * 3 unsafe blocks * 0 unsafe auto-actions * 0 billing escapes Important caveat: this is sample data, not production traffic. I’m not claiming product validation yet. The part I’m trying to understand now: For people who have run support, CX, SaaS ops, or billing/account workflows: 1. What would you need in the handoff record before trusting an AI agent to escalate correctly? 2. What actions would you never allow an agent to auto-execute? 3. What audit fields would matter if a customer later disputes the decision? 4. What would make this useful enough to test on anonymized tickets? Please do comment for repo or demo.