This is a concept build. There's no client and no production data behind it. It shows how we wire AI into systems a business already runs.
The problem
Inbound requests arrive in one system, need judgement to sort, and have to end up in another system with the right person. Done by hand it's slow and inconsistent. Done by a black-box automation, nobody can explain what happened when something goes wrong.
What we built
A triage pipeline for inbound cases. Cases are cleaned up, classified by a language model, branched by severity, and routed to the right place, such as a chat channel for urgent issues or an issue tracker for routine ones.
- Clean-up before anything reaches the model
- Classification by intent and severity
- Routing into the tools the team already uses
- A log of every step, so any decision can be traced and replayed
Where humans stay in the loop
Internal routing can run automatically. Anything that would reach a customer goes through a human check first. That's the same rule the Pipeline Builder enforces.
What this demonstrates
AI plugged into the stack you already run, with the logging and review you need to trust it.