> ## Documentation Index
> Fetch the complete documentation index at: https://docs.typesafe.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# System One

> System One models make fast, structured decisions for software. Jev is TypeSafe's flagship model and the first System One model.

System One models are a class of AI models built to make fast, structured decisions that software can use directly. A System One model evaluates a [state](/concepts/state) and returns typed answers and probabilities.

Jev is TypeSafe's flagship model and the first System One model.

Like an LLM, a System One model understands natural-language input. It returns typed decisions and probabilities rather than generated text.

## How it differs from an LLM

System One models are trained for calibrated decisions: their probabilities are optimized against outcomes to reflect uncertainty. Calibration is measured across groups of predictions; it does not guarantee that an individual answer is correct.

System One models do not write replies, produce code, or generate explanations of their reasoning. You define the possible answers through [primitives](/primitives):

| Primitive                    | Question                              | Example answer space                          | Example output      |
| ---------------------------- | ------------------------------------- | --------------------------------------------- | ------------------- |
| [Choice](/primitives/choice) | Which team should handle this ticket? | `billing`, `technical`, or `account`          | `choice: "billing"` |
| [Score](/primitives/score)   | How frustrated is this customer?      | 0 = calm, 1 = frustrated, 2 = very frustrated | `score: 1.4`        |
| [Noul](/primitives/noul)     | Does this message request a refund?   | True or false                                 | `noul: 0.95`        |

These are illustrative configurations and values. The primitive pages describe the available configuration options and full response fields.

Read the [AI primer](/introduction/machine-learning-primer) to learn how System One models work and how they are trained.

<Note>
  The System One name comes from the concept Daniel Kahneman popularized in his book *Thinking, Fast and Slow*. System 1 thinking is fast and intuitive. System 2 is slower and more deliberate. Here, the emphasis is on fast, focused judgments.
</Note>

## Fast judgments inside a larger workflow

For a refund request, your application can:

1. Build a state containing the customer's message, the relevant transactions, and the refund policy.
2. Ask independent questions together: whether a refund was requested, whether the evidence indicates a duplicate charge, and whether the policy supports a refund.
3. Combine the answers with deterministic checks in code, then route the case for action or review.

Once you have seen the primitives in action, you can combine them into a larger system. Because System One models return typed, constrained outputs rather than free-form text, your code can inspect and combine its answers into predictable workflows. See [How to build with TypeSafe](/concepts/how-to-build-with-system-one) for the full workflow.

Answers from System One models also include [confidence](/confidence), so you can decide when to act and when to escalate to a person or a reasoning model.

## Call a System One model

Call a System One model through one of our [client SDKs](/sdk) or `POST /v1/systemone` in the [HTTP API](/api). The `model` field selects which model handles the request. The examples in these docs use `jev-latest`, which is also the SDK default.

Start with [State](/concepts/state) to prepare the input and [Primitives (Questions)](/primitives) to explore the types of questions you can ask.