TypeSafe AI's Jev now available on AI Gateway
Jev gives agent loops typed decisions and probabilities without generating prose, offering a smaller control primitive for routing tools, retries, reviews, and guardrails.
Jev accepts shared state and evaluates named questions in parallel, returning typed **Choice, Score, and Boolean** answers with probabilities. It is available through the experimental evaluate API in **AI SDK 7.0.105+**.
Use it for narrow control-plane decisions in agent loops: tool or subagent selection, retry versus stop, risk scoring, and escalation to human review. Preserve question IDs and calibrate its confidence against labeled workflow examples.
Jev accepts shared state and evaluates named questions in parallel, returning typed **Choice, Score, and Boolean** answers with probabilities. It is available through the experimental evaluate API in **AI SDK 7.0.105+**. Use it for narrow control-plane decisions in agent loops: tool or subagent selection, retry versus stop, risk scoring, and escalation to human review. Preserve question IDs and calibrate its confidence against labeled workflow examples. The reported **193.6x speed** and **444.6x cost** advantages come from TypeSafe's own workflow evaluations, so they do not establish performance on your workload. The API is also experimental.
Jev narrows agent-model work to fast, typed control-plane judgments rather than open-ended execution. Its question IDs, probabilities, and parallel evaluation could make routing, stopping, and escalation observable and calibratable, but they complement rather than replace deterministic permissions, idempotency, validation, and recovery. Vendor-reported gains and an experimental API require local labeled evaluation.