Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Jev is TypeSafe AI’s first public System One Model, a class of AI designed to make fast, structured decisions that software can consume directly. Instead of generating arbitrary strings like a traditional large language model, Jev produces predefined type-safe values accompanied by calibrated probabilities and confidence estimates. Its architecture generates outputs in parallel rather than autoregressively producing one token at a time, allowing the model to prioritize speed and computational efficiency. TypeSafe trains Jev using Reinforcement Learning for Calibrated Decisions, an approach intended to optimize for accurate uncertainty estimates and consistent structured outputs. The model can be embedded into conventional software as an intelligent decision layer for classification, scoring, routing, extraction, branching, and other tasks where hand-written rules would be too rigid. Jev can also be used to judge, verify, guardrail, or detect problematic behavior in outputs from other AI systems. TypeSafe reports typical end-to-end response times between 70 and 500 milliseconds and positions the model for applications where low latency is important. The company also emphasizes schema guarantees, meaning Jev’s outputs are constrained to the structures defined by the application rather than requiring developers to parse and validate unrestricted generated text. Jev is aimed at developers and organizations building automation, real-time software, large-scale data workflows, and production systems that require dependable structured AI decisions.
Description
The Parallel Decisions API is a web-based classification tool designed for developers who create software, enhance data processes, and build workflows for AI agents. When a request is made, it includes specific context along with one or more defined questions, and in return, the API provides structured answers complete with probabilities and references to relevant online sources. This functionality allows multiple questions to be grouped under a single context within one request, enabling various applications such as vendor or company evaluations, lead management, compliance checks, content moderation, and establishing guidelines for agents. By accessing real-time web data, it can evaluate facts that might have evolved since the last training of a model. Developers can interact with the API via a RESTful endpoint using an API key or utilize the web_decisions tool through Parallel's MCP server. To facilitate testing and integration, a hosted playground and comprehensive documentation are available for user convenience. Furthermore, this API empowers developers to make informed decisions by providing up-to-date information that enhances the reliability of their applications.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Claude Code
No
Model Context Protocol (MCP)
No
Parallel
No
Integrations
Claude Code
Yes
Model Context Protocol (MCP)
Yes
Parallel
Yes
Pricing Details
Input: $0.042 / 1M tokens
Input tokens: $0.042 / 1 million tokens ($42 per billion tokens).
Output tokens: FREE (too cheap to meter).
Output tokens: FREE (too cheap to meter).
Free Trial
No
Free Version
No
Pricing Details
$0.001/request
$0.001 per API request; a request can include up to 100 questions.
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
TypeSafe AI
Founded
2024
Country
United States
Website
typesafe.ai/
Vendor Details
Company Name
Parallel
Founded
2023
Country
United States
Website
platform.parallel.ai/play/decisions