jev model

Jev is TypeSafe AI's first public System One Model, built for software that needs reliable decisions rather than generated conversation. The official site presents Jev as a machine-native intelligence system for automation: structured state goes in, and typed probabilistic decisions with confidence estimates come out.

Key Features

• Return type-safe structured values that software can use directly, instead of requiring string parsing and validation.

• Attach calibrated probabilities and confidence estimates to decisions so an application can act autonomously above a chosen threshold or escalate uncertain cases for review.

• Use a parallel sampling approach designed for fast, hardware-aware inference and automation workloads.

• Compose classification, routing, scoring, extraction, branching, verification, and guardrail steps into code-based workflows.

• Support real-time applications and large-scale map-reducing workflows where latency, consistency, and predictable output structure matter.

• TypeSafe describes Jev as optimized for System One tasks and early access is available through the official site.

How It Works

A developer sends Jev structured questions together with application state. Jev returns predefined typed decisions, probabilities, and confidence information. The surrounding software can then set autonomous-action thresholds, request human review for uncertain cases, and combine multiple decisions into a larger automation workflow. TypeSafe's launch article compares this approach with LLMs that produce sequential strings and require downstream parsing.

Use Cases

The official materials describe AI-powered workflows such as classification, routing, scoring, extraction, verification, jailbreak detection, and smart if-statements. They also highlight real-time applications, large-data feature extraction, and code-driven automation where consistent structured outputs are more useful than open-ended text.

Pricing and Availability

Jev is presented as available in early access. TypeSafe publishes an input price of $42 per billion tokens, with output described as free to meter on the launch page. Availability, limits, and access requirements may change as the product develops.

Screenshots