
TypeSafe AI builds machine-native intelligence infrastructure for automation, designed to make decisions within software. Jev is TypeSafe’s first public System One Model, optimized for automation, and it returns structured outputs with probabilities that software can act on.
TypeSafe uses System One models to make fast, structured decisions that software can use directly. Jev evaluates typed questions against a state and returns structured results without text generation or parsing, providing typed values and probability distributions that code can branch on.
Jev delivers calibrated decisions with confidence estimates, so software can decide when to act autonomously or escalate. It produces decisions that are more like code—reliable, fast, and type-safe—rather than human-readable text.
TypeSafe presents information about System One Models and Jev, including how it differs from traditional LLMs, how to get started, and details on questions, patterns, and confidence usage for building systems.
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