AI that decides.
Software that acts.
A simple credit-union use case: read a member’s service request, choose the right team, and flag uncertainty for a person.
01 · Input
A member’s service request02 · Typed decision
Team + urgency signal03 · Controlled action
Suggest routing or ask a person
1. Pick a synthetic request
2. See a structured answer
Choose an example, then make the decision.
No chatbot reply. A fixed set of outputs your software can use.
A 60-second walkthrough
- Try Lost debit card. Notice the selected team and urgency signal.
- Try Branch appointment. The service destination changes.
- Try Unclear request. The review rule sends it to a person.
Provider note: hosted access through jevtypesafe.org is independent of TypeSafe AI; its site identifies Workers AI as its inference provider.
Workshop concept only. No real member data, account access, lending decisions or transactions. The confidence threshold is illustrative and would need evaluation before deployment. Sample-mode values are teaching fixtures. Live-mode values come from the hosted API, with no claim of independent calibration.
Official sources: TypeSafe launch · API documentation