DECISION MODEL · API ACCESS IN PROGRESS

Meet Jev.

Fast, typed decisions for software. Send state, define the possible outcomes, and get probabilities your code can act on.

Build a request

BeatAPI integration is being verified. No live access is claimed yet.

jev / decision42 ms
QUESTION

Which action should the agent take next?

ask_user0.91
continue0.06
stop0.03
03decision primitives
255choice options supported
1→Nquestions per state
JSONsoftware-ready output
NoulChoiceScoreRoutingGuardrailsVerification
01 / MODEL

WHAT IS JEV?

Not another model that
writes more words.

Jev turns messy application state into bounded decisions. Your code defines what answers are legal. Jev evaluates them in parallel and returns the selected answer, probability distribution, and confidence signal.

Read the complete explanation
01

BOOLEAN PROBABILITY

Noul

Ask whether a statement is true. Receive a number from 0 to 1 instead of a brittle yes/no string.

is_urgent: 0.92

FINITE OPTIONS

Choice

Select one option from a set and keep the complete distribution for thresholds, fallback, and review.

queue: "technical"

ORDERED RUBRIC

Score

Evaluate an ordered scale, preserve uncertainty across levels, and branch with more nuance than labels.

risk: 1.64 / 2
02 / REQUEST

INTERACTIVE BUILDER

Shape a Jev request.
Before you ship it.

Choose a primitive, describe the state, and generate a clean request payload. Nothing is sent from this page.

Decision type

Local builder only. Your text never leaves this browser.

Request shapeReady to copy
03 / CONTROL

HOW IT FITS

Jev decides.
Your code remains in control.

Keep permissions, thresholds, retries, logs, and side effects in deterministic code. Use Jev for the bounded judgment in the middle.

01STATE

Events, text, tool history, or structured application context.

02JEV

Evaluate Noul, Choice, and Score questions in one request.

03CODE

Apply thresholds, validate, branch, log, or escalate to review.

USE CASES

Small decisions.
Serious leverage.

Jev works best when the possible outcomes are known, the decision repeats often, and your software needs a probability—not another paragraph.

01

AGENT SYSTEMS

Route the next tool or subagent

Choice · Tool history → next action
02

SAFETY

Gate risky actions with thresholds

Noul · Proposed action → allow / review
03

OPERATIONS

Score urgency and route support

Score + Choice · Ticket → queue
04

QUALITY

Verify outputs before they ship

Noul · Output + criteria → retry

JEV VS LLMS

Decision primitive,
not prose generator.

Use both models for what they are shaped to do. Jev narrows uncertainty inside code; LLMs produce open-ended language, reasoning, and artifacts.

See the full comparison
OUTPUTJEVLLM
ShapeTyped valueGenerated text
OutcomesDefined firstOpen-ended
UncertaintyProbabilitiesOften inferred
Best roleDecideCreate

FIELD GUIDE · 18 PATTERNS

What can you
actually build?

See concrete patterns for agent verification, LLM evaluation, routing, RAG filtering, reranking, support operations, guardrails, and structured extraction—plus the cases where rules or an LLM are the better choice.

Explore the complete use-case guide
01Agent completion verifier 02LLM-as-a-judge alternative 03RAG evidence filter 04Tool and model router 05Confidence-gated workflow 06Semantic policy check

FAQ

Questions,
decided.

The essential facts about Jev API access, decision primitives, production use, and this independent guide.

01What is Jev?

Jev is a decision model for software. It reads text or structured state, evaluates questions you define, and returns typed answers with probabilities instead of writing an open-ended chat response.

02Is Jev a chatbot or a general-purpose LLM?

No. Jev is designed for bounded decisions inside software: choosing an option, estimating a yes-or-no probability, or scoring an ordered scale. Use a language model when you need prose, code, or open-ended generation.

03What are Noul, Choice, and Score?

Noul returns a probability for a yes-or-no statement. Choice selects among named options and returns the probability distribution. Score evaluates an ordered rubric and returns a probability-weighted position.

04Who created Jev?

Jev is developed by TypeSafe AI as its first System One model. jevapi.io is an independent developer resource and is not the official Jev website.

05Is this the same Jev as the YouTube creator FaZe Jev?

No. This site covers the Jev decision model used in software. It is unrelated to the creator and streamer known as FaZe Jev.

06Can I call Jev through BeatAPI today?

The BeatAPI integration is currently in progress. This site will publish the verified model ID, endpoint, pricing, and runnable examples only after an authenticated request, response, usage record, and task log have been checked end to end.

07What should Jev be used for?

Strong fits include agent routing, support triage, risk scoring, tool selection, output verification, guardrails, and other high-volume decisions where the possible outcomes are known in advance.

08What is a System One model?

TypeSafe uses the term for models that make a fast, direct judgment over options you declare instead of writing an open-ended answer one token at a time. Jev is TypeSafe AI’s first System One model. See Jev vs LLMs for how the interfaces differ in practice.

09What does the Jev API cost?

For the direct TypeSafe API, the current model specifications list $0.042 per million input tokens and free output tokens (checked September 20, 2026). BeatAPI pricing is not published here yet; it will appear only after the integration is verified end to end. Details are in the API guide.

10Does Jev work in languages other than English?

Jev accepts text only. TypeSafe documents English as the primary training language and where accuracy is currently best; other languages are handled but not equally well. Test your own language and domain before relying on a threshold.

11Does a confidence score guarantee correctness?

No. Confidence is a signal, not proof. Production systems should set thresholds, validate outcomes, log model versions, and route uncertain or high-impact cases to human review.

INTEGRATION IN PROGRESS

Make the decision.
Keep the control.

BeatAPI access will open here after the model, billing, and usage path are verified end to end.