JevTypeSafe AI
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Parallel Decisions APIParallel
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Related Products
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About
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.
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About
Parallel Decisions API is a hosted, web-grounded classification API for developers building software, data-enrichment pipelines, and AI-agent workflows. A request supplies context and one or more bounded questions; the API returns typed answers with probabilities and citations to supporting web sources. Multiple questions can share context in a single request, supporting uses such as company or vendor qualification, lead routing, compliance screening, content filtering, and agent guardrails. By retrieving current web evidence, it can assess facts that may have changed since a model's training data. Developers call the REST endpoint with an API key or access the web_decisions tool through Parallel's MCP server. A hosted playground and documentation support testing and implementation.
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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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
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Audience
Software developers and teams building web-research workflows, data-enrichment pipelines, and AI-agent applications.
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Not Supported
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API
Offers API
Not Supported
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API
Offers API
Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
Input: $0.042 / 1M tokens
Input tokens: $0.042 / 1 million tokens ($42 per billion tokens).
Output tokens: FREE (too cheap to meter).
Free Version
Not Supported
Free Trial
Not Supported
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Pricing
$0.001/request
$0.001 per API request; a request can include up to 100 questions.
Free Version
Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationTypeSafe AI
Founded: 2024
United States
typesafe.ai/
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Company InformationParallel
Founded: 2023
United States
platform.parallel.ai/play/decisions
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Alternatives |
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Categories |
Categories |
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Integrations
Claude Code
Not Supported
Model Context Protocol (MCP)
Not Supported
Parallel
Not Supported
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Integrations
Claude Code
Supported
Model Context Protocol (MCP)
Supported
Parallel
Supported
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