TypeSafe AI Releases Jev: A System One Model That Returns Typed, Calibrated Decisions Instead of Text
The ChatGPT moment in 2022 taught AI to talk to people. One of its builders now bets the next moment is AI that talks to software, not people. TypeSafe AI released Jev. Jev is transformer-based, but it is not a large language model. It does not generate text. You send a state and typed questions. It returns typed decisions with probabilities that code can branch on. Is it deployable? Yes, as a hosted API in early access behind a waitlist. TypeSafe has not published weights, a parameter count
TypeSafe AI released Jev, a transformer-based model that differs fundamentally from large language models by returning typed decisions with probabilities instead of text. Rather than generating words for human readers, Jev accepts a state and typed questions, then outputs structured answers that code can use to make branching decisions. The model uses a new training approach called Reinforcement Learning for Calibrated Decisions instead of the RLHF tuning used in standard chat models, addressing issues like overconfidence and mode dropping that keep humans in the loop. Jev is available as a hosted API and costs $0.042 per million input tokens, with reported response times between 70 to 500 milliseconds, making it applicable to tasks like email triage, command safety, and agent guardrails where fast, reliable decisions matter more than natural language output.
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