Experiment: keep the team size, simplify the requirements
Look for Self-service. Team size alone should not override the explicit requirements in this policy.
Use the second scenario tab above to load this variation. Compare the returned decision as well as any probabilities: a changed answer can reveal an unclear policy, and an unchanged answer can reveal that the relevant detail was not captured by your question.
Use this pattern in your application
This playground request shape uses the original scenario. It is a reference for the input, not a public integration endpoint. For application integration, follow the official TypeSafe documentation linked in our Jev API guide. Keep API keys on the server and validate the returned type before taking action.
{
"playground": "https://aijev.net",
"language": "JavaScript",
"request": {
"model": "typesafe/jev-1.13",
"state": "Request: We need single sign-on, a security questionnaire, and help onboarding 80 colleagues.\nRouting policy: Enterprise handles SSO or security review. Team onboarding handles assisted setup without enterprise requirements. Self-service handles straightforward purchases. Missing requirements go to review.",
"questions": {
"decision": {
"type": "choice",
"instructions": "Which sales workflow should handle this request under the routing policy?",
"criteria": {
"Enterprise sales": "Enterprise sales",
"Team onboarding": "Team onboarding",
"Self-service": "Self-service",
"Manual review": "Manual review"
}
}
},
"provider": {
"allow_fallbacks": false
}
},
"note": "AIJev Playground request shape only. For application integration, visit https://docs.typesafe.ai."
}
How to evaluate this workflow
Track reroutes, missing-requirement escalations, and time to a useful first response. Audit cases where a large organization is sent to enterprise despite asking for a simple purchase.
Save a held-out set before changing your instructions. Compare new versions against the same examples, and review disagreements instead of assuming a valid response is a correct one. For escalation design, see confidence-based routing.
Frequently asked questions
Is this a lead quality or conversion prediction?+
No. It maps expressed requirements to a workflow. Predicting willingness to buy would require a different objective and separate evaluation data.
Are these results from a real customer deployment?+
No. These are original educational scenarios. The expected outcomes are editorial hypotheses; clicking Run Jev sends the displayed input to the model and shows its actual response.
Can I adapt this example to my own workflow?+
Yes. Replace the context, define your choices or rubric, and test against examples from your domain. The playground uses text input. Do not include credentials or unnecessary personal information.
References & further reading
Background on assigning categories to text. This Jev example is an independent implementation exercise, not a Microsoft integration. See Microsoft Learn: Custom text classification.
For the underlying decision primitives, read TypeSafe’s System One documentation and our guide to Choice, Score, and Noul.
AIJev