What is Jev AI?
Jev is a structured decision model from TypeSafe. It evaluates context against questions and returns typed answers, rather than composing a conversational response.
Read the guide ↗Jev AI guides for workflows you can verify.
Learn how to evaluate Jev, choose confidence thresholds, review uncertain results, and estimate value before putting AI decisions into a business workflow.
Choose AI confidence thresholds from evidence
A threshold is a business rule. It trades automated coverage against the mistakes your team is willing to accept and the cases a person must review.
Read the guide ↗Human-in-the-loop AI decisions with clear ownership
A review flag is useful only when a person can act on it. Decide who receives uncertain cases, what context they need, and how long a case can wait.
Read the guide ↗Jev vs structured outputs: choose by the task
Both approaches can return machine-readable results. The useful distinction is whether you need a bounded decision or generated content that follows a schema.
Read the guide ↗Evaluate AI classification before automating work
A convincing demo is one example. An evaluation measures how the rule behaves across the messages your team actually receives, including the cases you wish were rare.
Read the guide ↗Batch text classification without losing failed rows
Use the workspace batch tool to test several messages with the same labels and instructions. A useful export shows both the successful decisions and the rows that need attention.
Read the guide ↗Estimate AI automation ROI before buying
Enter your own assumptions below. The result is an estimate of labor capacity and cost, not a promise of revenue or an instruction to reduce staffing.
Read the guide ↗