Try Jev AI

EXPLORE THE JEV MODEL

Try Jev AI.

Experience how Jev makes fast, structured decisions with probabilities instead of generating free-form text.

Try the PlaygroundWhat is Jev AI?

Independent demo & learning resource. Not affiliated with TypeSafe AI.

state+question+choicesdecision + probabilities

01 / EXPLORE THE PATTERN

Jev Decision Playground

Interactive Demo
INPUT

The context your software needs to evaluate.

03Choices4 / 8

Runs locally in your browser. No account or API key needed.

OUTPUTEXAMPLE PREVIEW

Selected decision

Billing
Billing96%
Technical Support2%
Sales1%
Other1%

Illustrative output

Illustrative probabilities for this preset, not a Jev prediction.

This is not a live Jev call. Demo values and execution time do not measure Jev’s accuracy or speed.

That’s the idea behind Jev: software asks a structured question and gets a typed decision with probabilities—not a paragraph of generated text.

02 / EXAMPLE USE CASES

One pattern. Many decisions.

Load a preset into the playground.
See what a structured decision looks like.

Customer Support Routing

Send each request to the right team.

Agent Tool Selection

Choose the tool that fits the next step.

Risk Assessment

Add a review step before a risky action.

Agent Loop Decision

Know when to continue, retry, or stop.

03 / A DIFFERENT OUTPUT

What is Jev AI?

Jev is TypeSafe AI’s System One Model designed for fast, structured decisions inside software.

Give it the relevant state and a focused question. Your application receives an answer it can use to choose a route, select a tool, or request a review.

Learn what Jev is

TRADITIONAL LLM

Text

Text

An open-ended response
for a person to read.

JEV

State + Question

Typed Decision
+ Probabilities

A bounded answer
for software to act on.

04 / THE DECISION PATH

How Jev works

A focused question connects your application’s state to its next action.

Traditional LLM workflow

  1. Input
  2. Prompt
  3. Generate Text
  4. Parse
  5. Validate
  6. Decision

Jev workflow

  1. State + Structured Question
  2. Typed Decision
  3. Probabilities

A simplified comparison. LLMs also offer structured outputs; your application still needs validation and decision policies.

05 / BUILD WITH DECISIONS

Jev API

Developers can use Jev for structured decision tasks such as routing, scoring, classification, verification and agent control.

Explore the Jev API
Decision pattern · illustrative pseudocode
state     → "Customer requests a refund"
question  → "Which team should handle this?"
choices   → [Billing, Technical, Sales]

decision  → Billing

// Your application decides what happens next.
routeTo(decision)

See the API guide for a request based on official documentation.

06 / CHOOSE THE RIGHT TOOL

Jev vs LLM

Jev vs LLM
Jev and traditional language model comparison
AttributeJevTraditional LLM
Primary taskStructured decisionsText generation
OutputTyped decision + probabilitiesFree-form text
Good forRouting, scoring, classificationWriting, reasoning, conversation
IntegrationDecision-orientedGeneral-purpose

Jev is not necessarily a replacement for an LLM. They can work together: an LLM can develop a plan, while Jev evaluates a bounded decision within the workflow.

QUESTIONS, ANSWERED

A little more context.

New model. Different interface.
Here are the essentials.

What is Jev AI?

Jev is TypeSafe AI’s System One Model for structured decisions inside software. It evaluates state against typed questions and returns answers with probabilities.

Who created Jev?

Jev was created by TypeSafe AI. TryJevAI.com is an independent resource and did not develop the model.

What is a System One Model?

System One is TypeSafe AI’s term for a model focused on fast, bounded judgments. You supply context and define the answer space; the model returns a decision that code can use.

Is Jev an LLM?

TypeSafe AI describes Jev as a System One Model rather than a conventional text-generating LLM. Its interface centers on choices, scores and yes/no probabilities, rather than conversation.

What is Jev used for?

Example uses include routing support requests, selecting agent tools, classifying content, scoring against a rubric, and checking whether an agent should continue or ask for help.

Does Jev have an API?

Yes. TypeSafe AI publishes an HTTP API and SDK documentation. Vercel also lists Jev in its AI Gateway catalog. Check the current official documentation for access requirements and integration details.

Can I try Jev online?

You can explore the decision pattern in this site’s Interactive Demo. It runs locally with illustrative values and does not call Jev. To try the actual model, follow TypeSafe AI’s official documentation to its playground.

Is TryJevAI.com the official Jev website?

No. TryJevAI.com is an independent demo and learning resource. It is not affiliated with, endorsed by, or operated by TypeSafe AI.