About TypeSafe AI
Overview
TypeSafe AI is an AI lab building machine-native intelligence infrastructure for automation. The company designs models that make decisions inside software rather than produce words for people.
Its first public System One Model, Jev, gives AI the properties of code: typed outputs, calibrated confidence, and reliability. TypeSafe built Jev with a new architecture, a new sampler, and a new training algorithm, Reinforcement Learning for Calibrated Decisions (RLCD).
Key Benefits
- Jev returns typed decisions that software can act on directly.
- Every decision includes an estimate of how confident the model is.
- TypeSafe reports zero hallucinations, with software escalating when confidence is low.
- Jev is reliable, fast, and type-safe — more like code than chat.
- On System One workflows, TypeSafe reports Jev is 193.6x faster and 444.6x cheaper than LLMs.
- Jev is priced at $42 per billion input tokens, 238x lower than Claude Fable 5.1.
How It Works
Developers send Jev structured questions and receive typed decisions with probabilities and confidence. They set thresholds for when Jev acts autonomously and when it asks for review, then combine decisions in code to build larger workflows with control over how the intelligence is used.
Use Cases
- Automation engineers wire Jev into software to make decisions with calibrated uncertainty.
- Platform teams replace human-in-the-loop review with threshold-based autonomous actions.
- Developers assemble Jev decisions in code to build multi-step workflows.
- Teams needing fast, low-cost decisions use Jev where chat LLMs are too slow or expensive.
- Products surface confidence estimates so users can review low-confidence outcomes.
Why Choose This Product
TypeSafe took the opposite research direction from chat. Where RLHF-trained models optimize for human preferences and require humans in the loop, System One Models are built for machines: typed, reliable, fast, and self-consistent, with confidence on every decision. TypeSafe calls Jev's intelligence per dollar off the charts.
TypeSafe AI Pros & Cons
- First public System One Model built for automation
- Typed decisions with calibrated confidence estimates
- Zero hallucinations reported on every decision
- 193.6x faster and 444.6x cheaper than LLMs on System One workflows
- Open to everyone with no waitlist
Key Features
Typed decisions
Jev returns typed outputs that software can act on directly, instead of generating free-form words for people.
Calibrated confidence
Every Jev decision includes an estimate of how confident the model is, so software can act when confidence is high and escalate when it is low.
RLCD training
Jev uses a new training algorithm, Reinforcement Learning for Calibrated Decisions (RLCD), with a new architecture and sampler.
Zero hallucinations
TypeSafe reports zero hallucinations, with every decision carrying a confidence estimate for software to act on.
Code-like speed
TypeSafe reports Jev is 193.6x faster and 444.6x cheaper than LLMs on System One workflows, behaving more like code than chat.
Automation thresholds
Developers set thresholds for when Jev acts autonomously and when it asks for human review.
Composable workflows
Developers combine Jev decisions in code to build larger workflows with control over how the intelligence is used.
TypeSafe AI Pricing
- Typed decisions with calibrated probabilities
- Zero hallucinations with confidence estimates
- Set thresholds for autonomous action or review
- 193.6x faster and 444.6x cheaper than LLMs on System One workflows
Pricing extracted from the product website and may change. Check the source for current details.
Frequently asked questions about TypeSafe AI
What are System One Models? What is Jev?
System One Models are a new class of AI model built for decisions inside software. Jev is TypeSafe's first public System One Model, optimized for automation. You send Jev structured questions and get typed decisions with probabilities and confidence that your software can act on.
Is Jev just a smaller LLM?
No. TypeSafe positions Jev as a different class of model. LLMs are trained with RLHF to satisfy human preferences and produce words for people, while Jev is a System One Model built on a new architecture, sampler, and RLCD training algorithm that produces typed decisions for machines.
How is this different from JSON mode or structured outputs?
Jev returns typed decisions with calibrated probabilities and zero hallucinations, behaving more like code than a text generator. Every decision carries a confidence estimate, so software can act when confidence is high and escalate when it is not.
How can Jev be so fast and inexpensive?
TypeSafe reports Jev is built with a new architecture, a new sampler, and the RLCD training algorithm. On System One workflows the company reports Jev is 193.6x faster and 444.6x cheaper than LLMs, with input pricing at $42 per billion tokens.
Can Jev still get things wrong?
Every Jev decision comes with a confidence estimate, so your software can act when confidence is high and escalate when it is not. This lets systems account for uncertainty and route low-confidence decisions to review rather than acting blindly.
Is TypeSafe AI free?
TypeSafe AI is a paid product. See the pricing section for current plans and starting prices.