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What is Jev?

Jev is a low-latency System One Model from TypeSafe AI built for structured decision-making rather than open-ended text generation. TypeSafe describes System One Models as a new class of frontier models intended to make fast decisions that can be consumed directly by application code. Jev takes unstructured information as input and returns predefined typed outputs with probabilities and confidence scores instead of generating unrestricted natural-language strings. Its parallel sampling architecture produces outputs in a single query rather than sequentially generating one token at a time, which is designed to reduce latency and inference cost. The model is trained with Reinforcement Learning for Calibrated Decisions, which focuses on producing well-calibrated probabilities for structured System One tasks. TypeSafe positions Jev as a software-native intelligence layer for tasks including classification, routing, scoring, extraction, decision branching, and other workflows that benefit from probabilistic logic. It can also be applied to model evaluation and safety workflows by scoring, judging, verifying, guardrailing, or detecting jailbreaks in prompts, reasoning traces, and generated outputs. The company reports service response times of roughly 70 to 500 milliseconds and says this can make Jev suitable for interactive and real-time applications where traditional frontier models may introduce too much latency. Jev is designed to return consistent schemas without type errors, allowing its results to be incorporated into code without the same parsing and validation steps commonly required for free-form LLM responses. TypeSafe also highlights map-reduce style processing over large datasets as a potential use case, where the model can turn large amounts of unstructured information into structured features and insights.

What is Fern?

Effortlessly create SDKs and documentation similar to Stripe's, customized specifically for your API. With type-safe SDKs available in popular programming languages, Fern simplifies the intricate process of generating and distributing client libraries, allowing your team to focus on developing the API itself. You can easily import your API definition in either OpenAPI format or Fern's simpler alternative. Select from an array of code generators, including TypeScript, Python, Java, Go, Ruby, C#, and Swift, to meet your specific requirements. Fern also manages semantic versioning and publishes packages to multiple registries such as npm, pypi, and maven, ensuring smooth integration into your projects. Additionally, you can benefit from visually appealing API documentation that reflects your brand's identity, providing a consistent user experience. This not only enhances the functionality of your API offerings but also improves their overall presentation, making them more attractive to potential users. Such comprehensive tools empower your development process and elevate your API's accessibility and usability.

Media

Media

Integrations Supported

Integrations Supported

Sayari

API Availability

API Availability

Pricing Information

Input: $0.042 / 1M tokens
Input tokens: $0.042 / 1 million tokens ($42 per billion tokens).

Output tokens: FREE (too cheap to meter).

Pricing Information

$250 per month

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

TypeSafe AI

Date Founded

2024

Company Location

United States

Company Website

typesafe.ai/

Company Facts

Organization Name

Fern

Date Founded

2022

Company Location

United States

Company Website

buildwithfern.com

Categories and Features

AI Decision Models

Not specified

AI Models

Not specified

Categories and Features

API Documentation

Not specified

API Management

Not specified

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