100 places a Jev decision model fits · 100 practical explanations, with an example for every use case
Small, specific questions. Structured answers. Jev, from TypeSafe AI, evaluates supplied context and returns a predefined choice, a rubric score, or a yes/no probability. Its role in these examples is to classify, route, score, or check evidence.
These are potential applications, not verified deployments. Each example assumes text or structured records as input; images and audio need to be processed upstream.
How to read the examples. Every scenario and result is fictional. They illustrate the question, the type of answer, and the next workflow step. Numeric probabilities are invented examples, not measured confidence or evidence of model accuracy.
Noul — A 0–1 probability that a yes/no statement is true. Use for one specific evidence or policy check.
Score — A level on a defined, ordered rubric. Use for relevance, completeness, or severity.
Choice — One option from a list you define. Use for categories, routing, or candidate selection.