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Jev is what happens when you stop forcing AI to talk.

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Pattern Jev AI decision models

Jev is what happens when you stop forcing AI to talk. ​ It’s the first public “System One” model from TypeSafe AI, built for fast decisions inside software—not conversations. ​ You give it: ​ • Unstructured state: text, logs, tickets, documents • A predefined schema: the questions and allowed answers ​ Instead of generating tokens one by one, Jev evaluates the choices in parallel and returns typed values with probability distributions: ​ billing: 92% technical: 6% sales: 2% urgent: 87% ​ TypeSafe trains it with RLCD: Reinforcement Learning for Calibrated Decisions. The goal isn’t better prose, but decisions whose confidence reflects how likely they are to be correct. ​ No free-form text means no malformed JSON, invented fields, or parsing retries. ​ In the attached demo, a browser agent uses Jev to find a Zürich → London flight in 7.1 seconds by choosing each operation and target in real time. ​ LLMs generate the plan. Jev could become the decision engine running inside every software loop.