TypeSafe AI

TypeSafe AI takes the opposite research direction from chat-first LLMs. Instead of optimizing for human-preference prose, it builds System One Models for decisions inside software. The first public model, Jev, accepts structured state and typed questions, then returns answers your code can use directly — with probabilities and calibrated confidence.

That design trades free-form generation for reliability: no hallucinated strings, type-safe outputs, and thresholds so automation can act when confidence is high and ask for review when it is not. TypeSafe positions Jev as dramatically faster and cheaper than general LLMs on System One workflow tasks, with published input pricing around $42 per billion tokens.

Jev is not a chatbot or coding agent. If you need long-form writing or open-ended conversation, use a chat model. If you need fuzzy decision rules — classify, route, score, guardrail — that compose like code, TypeSafe is aimed at that automation layer.