# What is Jev?

> Jev is TypeSafe AI's typed decision model: structured state goes in, and a constrained decision that software can validate comes out.

## Why it exists

Some product decisions need a direct, bounded answer: which team should own a request, how risky is a transaction, or whether a person should review a case. Jev is designed for that decision boundary.

## Jev versus a normal LLM

A normal LLM is typically used to understand or generate open-ended language. Jev is presented as a System One model for typed decisions. It can sit beside an LLM: one makes a bounded decision, while the other can explain it in prose.

## Choice, Score and Noul

Choice picks one allowed option. Score returns a bounded numeric assessment. Noul answers yes or no with a probability. The application defines the allowed values and remains responsible for validation.

## Real use cases

Teams can use typed decisions for ticket routing, fraud or risk triage, eligibility checks, prioritization and deciding when human review is required. Start with a mock boundary and test the decision against known cases.

## System One versus System Two

TypeSafe AI uses System One to describe rapid, constrained decisions and System Two to describe slower, open-ended reasoning. The homepage comparison is a frontend simulation; its timing is not a universal benchmark.

## Limitations and what Jev is not

Jev is not a general chatbot, a workflow engine or a guarantee that an output is correct. Typed output reduces ambiguity, but it does not remove the need for input checks, monitoring, policy controls and human oversight.

## How to try it

Browse JevSkills to understand the ecosystem, then use TypeSafe AI's current documentation to choose a supported setup. Keep credentials on the server and validate returned values before a real action.

## Best resources

Start with the JevSkills FAQ for direct answers, Explore for source-screened projects and Learn for primers. For product behavior and current integration details, consult TypeSafe AI's documentation directly.

Source: [TypeSafe AI: Introducing System One Models and Jev](https://typesafe.ai/blog/introducing-system-one-models-and-jev)