Autonomous Refund Desk
Every refund request is judged against your policy, the order, and the customer's history by TypeSafe AI's Jev model in a single sub-second call — approve, reject, or review, with a probability for each and a confidence score. Clear approvals and rejections are emailed immediately; ambiguous, high-value, or low-confidence cases land in the Approvals queue with the model's reasoning attached, so a person only looks at what actually needs judgment.
Templates never consume AI Builder credits. Customize every node visually after import.
How it works
Receive
A webhook trigger takes the refund request with the order and customer fields your system already has.
Decide
An AI Decision node asks Jev two questions at once: approve / reject / review against your written policy, and whether the request shows signs of abuse. Answers come back with probabilities and confidence, not prose.
Act or escalate
Approve and reject branches email the customer. Review — and any answer below 60% confidence — routes to a Human Approval node whose decision then sends the matching email.
Integrations in this template
Every node is swappable — replace any integration with another without rebuilding the flow.
Webhook Trigger
View integration docs →AI Decision
View integration docs →Send Email
View integration docs →Built for
- E-commerce refund and return requests
- Subscription cancellation credits
- Marketplace dispute first-pass triage
Frequently asked questions
What does it cost per request?
TypeSafe bills your own API key per input token — a fraction of a cent per decision — and output tokens are free. Falcon Builder AI credits are not consumed.
Can it issue the refund itself?
Yes — add your payment provider's node (or an HTTP Request to its API) on the approve branch. The template ships with email notifications so you can watch decisions before automating the money movement.
Why not an LLM?
Jev returns a calibrated probability for every option and a confidence score, so the workflow can route on certainty rather than parsing a paragraph. It also cannot be talked into a different answer by a persuasive refund request the way a generative model can.
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