Support Agent | Delivered-Not-Received Workflow
I built this so the LLM has one job: turn a messy customer message into structured case data. The rest of the workflow is explicit.
When a customer says a package was marked delivered but never arrived, the system retrieves the evidence, applies policy, checks authority, and either issues an idempotent refund or routes the case to a human.
A missing-package claim can end in a refund. The system needs to make a good decision without giving the model uncontrolled access to money or customer state.
Customer message → structured case → evidence lookup → policy checks → authorization → refund or human review.
Workflow behavior, authorization, duplicate actions, failure recovery, model extraction, tracing, and a staged rollout plan.
In the synthetic base case, the workflow covers 70% of eligible cases. It frees roughly 1,200 hours of support and review work each month and produces about $46K in monthly net value in the model. These are modeled results. I would validate the assumptions with a real customer before expanding the deployment.
The LLM can classify the case. Policy and authority live elsewhere. Money moves only after the workflow passes those checks.
Public demo uses scripted extraction and makes no provider calls. Free hosting may take about 30–60 seconds to wake after inactivity.
