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:
These are illustrative configurations and values. The primitive pages describe the available configuration options and full response fields.
Read the AI primer to learn how System One models work and how they are trained.
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.
Fast judgments inside a larger workflow
For a refund request, your application can:- Build a state containing the customer’s message, the relevant transactions, and the refund policy.
- Ask independent questions together: whether a refund was requested, whether the evidence indicates a duplicate charge, and whether the policy supports a refund.
- Combine the answers with deterministic checks in code, then route the case for action or review.
Call a System One model
Call a System One model through one of our client SDKs orPOST /v1/systemone in the HTTP 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 to prepare the input and Primitives (Questions) to explore the types of questions you can ask.
