Jev AI Model

FREE ONLINE PLAYGROUND · PAID API CREDITS

Jev AI Model

Classify, score, and route text with Jev AI Model. Get structured results and probabilities, try the online playground for free after sign-in, and use paid credits when you connect your application through the API.

Try the free playgroundAPI quickstart

STATE → QUESTIONS → DECISIONS

01Structured answers

02Multiple questions at once

03Probabilities included

01 / WORKBENCH

Jev AI Model playground

Start with an example, change the input, and inspect a structured answer. Sign in to run decisions for free; no API credit purchase is required.

Decision workbench

Text or JSON evaluated independently by every question.

Questions 1/8

routechoice

Options

Free after sign-in · API uses credits

Draft saved in this browser · Your draft will be restored after sign-in.

Your next decision starts here.

Run the loaded example or edit the input. Results are returned by the model.

choicescorenoul

Your draft will be restored after sign-in.

02 / UNDERSTAND THE OUTPUT

A clear answer to a specific question

Jev AI Model gives developers a place to turn text and context into decisions that software can use. Describe the situation, define the question, and inspect the returned answer and probabilities. A support ticket becomes a route; a policy check becomes a yes-or-no judgment; a quality review becomes a score with explicit criteria.

The underlying Jev model is a System One model from TypeSafe AI. This independent service brings that decision workflow into a browser workbench and a paid API. With Jev AI Model, you can develop the question interactively, keep a useful configuration, and carry the same request structure into your application once you have tested it.

CHOICE

Choose a category

Use a choice question when your application needs one label from a defined set. In Jev AI Model, each option has a name and a description, so you can explain what belongs in billing, technical support, or account access. Inspect the probability distribution as well as the selected label, especially when two options overlap.

Write distinct criteria and include an explicit fallback for inputs that do not fit. The result can inform a queue assignment, a search filter, or the next step in an agent.

SCORE

Measure on a scale

A score question is useful when a label alone loses information. Define ordered levels for relevance, urgency, or completeness, and explain what each level means. Jev AI Model returns a score along that scale, making it possible to compare inputs using a shared rubric instead of an open-ended written opinion.

Keep the order consistent and test examples near each boundary. A score only becomes useful when the people and systems consuming it agree on what the scale represents.

NOUL / YES–NO

Check a statement

Use noul for a focused yes-or-no question, such as whether a source supports a claim or whether a request needs review. The yes probability from Jev AI Model lets your application choose a threshold. It expresses the model's judgment about the supplied evidence; it is not a guarantee that the statement is true.

Ask one question at a time and describe how missing evidence should be treated. Keep consequential actions behind your own business rules and review process.

Better inputs begin with the decision you need to make. Give Jev AI Model the relevant message, policy, and known facts, while leaving out unrelated conversation. Text, JSON objects, and arrays can organize that context. The workbench helps you inspect the request before running it, so you can see exactly what the model will receive.

03 / START FROM A REAL TASK

Practical Jev AI Model workflows

These editable recipes show how to connect a question to an application decision. Open a recipe in Jev AI Model, replace its sample state with your own text, and adjust the criteria to match your product. Each example is a starting point for testing, not a ready-made policy for every business.

Route customer requests

A customer reports a duplicate charge. Use Jev AI Model to distinguish a billing issue from a technical fault or an account access problem, then pass the selected label to your support system. Include enough context to separate a refund request from a failed checkout.

Try ambiguous tickets as well as clear ones. Keep an other category for requests outside the available teams, and decide when uncertain results should reach a person.

Open and customize recipe

Choose an agent's next step

Some requests need a record lookup; others need a language model or human review. Jev AI Model can classify the incoming task against routes you define, giving your application a structured signal before it starts the next operation.

Describe each route's capabilities and limits. Your application remains responsible for executing tools, checking permissions, handling failures, and deciding whether the proposed route is appropriate.

Open and customize recipe

Check claims against evidence

Place a claim beside the source passage and ask whether that passage supports it. With Jev AI Model, a citation check becomes a specific decision whose input and result can be reviewed together, rather than a vague request to judge an entire document.

Test missing evidence, partial support, and direct contradictions. The supplied passage sets the scope: this check does not independently browse the web or establish that the source itself is correct.

Open and customize recipe

04 / DEVELOP WITH EVIDENCE

From a promising example to a tested workflow

One convincing answer is a useful beginning, but it does not tell you how a decision behaves across your traffic. Develop a Jev AI Model workflow with representative inputs, explicit expected outcomes, and a repeatable comparison. The workbench combines editable questions, saved configurations, run history, and a small evaluation workspace to support that process.

Open the full workbench
  1. 01

    Define the decision and its boundaries

    Start with the action your application needs to take. In Jev AI Model, name the question clearly, choose its type, and describe the criteria in language another person could apply. Add examples that sit outside the normal case. If a ticket mentions both billing and login, specify which issue should control its route.

  2. 02

    Read more than the winning answer

    Inspect the answer, available probabilities, and request details together. When a Jev AI Model result looks surprising, first check whether the input contains the evidence your criteria require. A high probability is not measured accuracy. It needs to be checked against labeled examples from your own domain before you use it as an automation threshold.

  3. 03

    Compare two configurations on the same cases

    Capture configuration A, revise the question, then capture configuration B. The evaluation workspace in Jev AI Model runs both against the same supplied states, with up to 25 cases in a comparison. Add expected answers where available, inspect individual failures, and export the report. A change that fixes one ticket may still make another class of tickets worse.

  4. 04

    Keep a useful baseline and revisit it

    Save the configuration you want to keep, revisit private web run history, and rerun difficult cases after an edit. Before connecting Jev AI Model to a live workflow, decide how your application handles missing answers, uncertain results, and request errors. Repeat the evaluation when your policy, input format, or model choice changes.

Evaluation separates model behavior from application policy. Jev AI Model produces the decision signal; your product decides what happens next. Set a review path for cases that should not proceed automatically, and judge the workflow by the outcomes that matter to your users.

Designed for developers

Connect Jev AI Model to your application

Move a tested question from the browser into your backend using the same state and question structure. The Jev AI Model workbench provides request examples in cURL, JavaScript, and Python, so you can inspect the payload before connecting it to an existing service. Create an API key in your account and send it as a Bearer token from your server.

A successful Jev AI Model API response includes structured answers and request usage information. Check the response status before reading the answers, record the request identifier for troubleshooting, and handle errors explicitly. Keep the API key out of browser code and public repositories. Your integration controls the next action, whether that is assigning a queue, requesting a review, or invoking another tool.

API calls use paid credits. Browser runs remain free after sign-in, allowing you to refine the input and criteria before purchasing credits for an application integration. Read the request and response examples in the documentation alongside the generated code.

Explore API docs ↗Manageable API keys ↗

POST /v1/systemone

typesafe/jev-1.13

// Server-side JavaScript (Node 20+ or Bun). Set JEV_API_KEY.
const response = await fetch("https://jevaimodel.net/v1/systemone", {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${process.env.JEV_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
  "model": "typesafe/jev-1.13",
  "state": "I was charged twice for order A-4471. Please refund the duplicate payment.",
  "questions": {
    "route": {
      "type": "choice",
      "instructions": "Which team should handle this ticket? Use other when no option fits.",
      "criteria": {
        "billing": "Payments, charges and refunds",
        "technical": "Bugs and product errors",
        "account": "Login and account access",
        "other": "None of these teams"
      }
    }
  }
}),
});
const body = await response.json();
if (!response.ok || body.code !== 0) throw new Error(body.message);
console.log(body.data.result.answers);
console.log(body.data.creditsUsed);

05 / UNDERSTAND THE SERVICE

Try freely. Connect when you are ready.

Free signed-in web use

Sign in to use the Jev AI Model playground without buying an API credit pack. Load a recipe, edit its state, and run your own questions. Saved configurations and web history help you return to earlier work. This is a practical place to understand the outputs and develop a useful question before writing integration code.

Paid API credits

Choose a credit pack when you want to call Jev AI Model from your application. All packs provide the same API capabilities; the difference is the credit balance. Successful requests are billed on actual input tokens, with a minimum of one credit. Use the calculator below to estimate consumption, then compare that estimate with real request usage.

Usage you can inspect

The Jev AI Model account area separates web activity from API usage and gives you a credit history to review. A request identifier helps connect an API call to its usage record. Private web history stores the state and answers so you can revisit a decision; API usage records track request metadata without storing the full request and answer bodies.

Pricing

Web runs are free after sign-in. Buy API credits when you connect your application.

Every pack includes the same API capabilities. Successful requests are billed on actual input tokens, with a minimum of 1 credit.

Starter

$10

Credits for your first API integration.

  • 100,000 credits, no expiry
  • Choice, score, and noul questions
  • Probability and confidence results
  • Online playground
  • API key management
  • Request usage & credit history
Recommended

Pro

$100

Credits for ongoing runs and evaluation.

  • 1,000,000 credits, no expiry
  • Choice, score, and noul questions
  • Probability and confidence results
  • Online playground
  • API key management
  • Request usage & credit history

Volume

$1,000

A larger credit pack with 10% extra credits.

  • 11,000,000 credits (10% extra included)
  • Choice, score, and noul questions
  • Probability and confidence results
  • Online playground
  • API key management
  • Request usage & credit history

Estimate your API credits

Estimate with your average input tokens, including state and questions. Each request is rounded up separately.

Credits per request

1

Estimated total credits

10,000

Credit value at selected pack rate

$1.00

max(1, ceil(input_tokens × 420 / 1,000,000))

Minimum 1 credit per successful API request. Output tokens are free. Failed provider calls are not billed. Estimates exclude taxes; actual charges use reported tokens. Pack purchase amounts are separate.

Jev models benchmark

Put Jev model benchmarks in context

Use independent benchmarks as background when evaluating Jev AI Model. The linked comparison identifies its source, model versions, and snapshot date, so you can understand what the published scores describe. A benchmark result is evidence about that evaluation, not a promised accuracy rate for your own tickets, policies, or documents.

For a deployment decision, pair those results with your own labeled cases in Jev AI Model. Compare answer quality, uncertainty, response time, and observed credit use on inputs that resemble the work your product will actually receive.

Decision quality & calibrationSpeedCost per decision
Explore the benchmark

Jev 1.13.0

#1 · JevBench v1.3.0

74.4

Score

SemIf

#2 · open rebuild

73.1

Score

djev

#3 · hosted preview

73.0

Score

JevBench v1.3.0 · 52 systems · 534 decisions · snapshot: Sep 21, 2026

Questions about Jev AI Model

Find the right starting point for Jev AI Model, whether you are exploring Jev AI for the first time or adding a Jev model decision to an existing application.