Audience

Software developers, AI engineers, automation teams, infrastructure builders, and enterprises that need low-latency, type-safe, probabilistic AI decisions for production software and structured workflows

About Jev

Jev is a System One Model from TypeSafe AI designed for fast, structured decision-making inside software and automated workflows. Unlike conventional large language models that generate free-form text token by token, Jev accepts unstructured state and returns predefined type-safe values with calibrated probabilities and confidence scores. The model uses a parallel sampling architecture and a training approach called Reinforcement Learning for Calibrated Decisions, which is optimized for producing reliable probabilistic decisions rather than conversational responses. Jev is intended for tasks such as classification, routing, scoring, extraction, branching logic, verification, guardrails, and other AI-powered workflows where structured outputs can plug directly into application code. TypeSafe reports end-to-end response times ranging from about 70 to 500 milliseconds and says Jev can be substantially faster and more efficient than frontier language models on System One-style workloads.

Pricing

Starting Price:
Input: $0.042 / 1M tokens
Pricing Details:
Input tokens: $0.042 / 1 million tokens ($42 per billion tokens).

Output tokens: FREE (too cheap to meter).

Integrations

No integrations listed.

Ratings/Reviews

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Company Information

TypeSafe AI
Founded: 2024
United States
typesafe.ai/

Videos and Screen Captures

Jev Screenshot 1
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Product Details

Platforms Supported
Cloud
Training
Documentation
Support
Online

Jev Frequently Asked Questions

Q: What kinds of users and organization types does Jev work with?
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Q: What type of training does Jev provide?
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Jev Product Features