We built something similar internally after AI spend on support-ticket triage kept beating estimates. Routing itself wasn't the hard part, it was that our dashb

We built something similar internally after AI spend on support-ticket triage kept beating estimates. Routing itself wasn't the hard part, it was that our dashboard only tracked immediate task completion, and had no idea a cheaper model had quietly produced a worse answer that the customer reopened a week later. We ended up tagging every response with which model handled it and joining that against reopen rate a month out, and the gap on the cheap tier was bigger than we expected going in. Curious if Tokenless has thought about exposing a delayed quality signal like that, not just pass/fail at the time of the call.