
System One model for typed decisions, not chat
Jev is TypeSafe AI's first System One frontier model: unstructured state in, typed probabilistic decisions out. Instead of generating text, Jev returns Choice, Score, and Noul answers with calibrated probabilities your code can act on. Parallel sampling delivers ~70-500ms responses, about 20-200x faster and 40-400x cheaper than comparable LLM workflows, with output tokens free. Early access via the waitlist on typesafe.ai.
Jev by Typesafe is a System One model that converts unstructured input into typed probabilistic decisions, providing outputs such as Choice, Score, and Noul with calibrated probabilities. It offers rapid response times of 70-500ms and is significantly more cost-effective than traditional LLM workflows.
Scored deterministically. Only candidates that fire a story trigger are sent to a model, so this one has no written angle.
Gaps in our data, not findings about the product. Their weight is redistributed across the 5 we did measure.
A source that found nothing is a measurement. A source that has not run is a gap. Neither means the launch lacks the thing.