Jev is the AI that decides inside your software.

System One Models are a new class of AI model built for decisions inside software. Jev is TypeSafe’s first public System One Model, optimized for automation. Send Jev structured questions and get typed decisions with probabilities and confidence that your software can act on.

Jev is neither small nor an LLM, hence being off the intelligence Pareto curve.

Jev’s efficiency comes from optimizing for a different task. It’s built for structured decisions inside software, with an interface and training approach designed for that purpose. It understands language, but doesn’t generate free-form text or function as a chatbot.

Valid JSON gives software a format it can read. But forcing an LLM into that format can leave some of its intelligence on the table. System One Models are trained for structured decisions from the start, returning typed answers with calibrated probabilities. Your code can use those probabilities to decide when to act, request more information, or escalate.

Jev replaces sequential generation with parallel computation, answering multiple structured questions in a single request. That makes it fast and efficient enough to bring intelligence to everyday decisions in your software, including ones that never justified the cost before.

Fun fact: the jump from sequential to parallel is similar to that made by the transformer over RNNs (the breakthrough underlying today’s AI revolution).

Nobody has actually asked us because nobody thinks this is possible... but yes we can. If you have a use case that needs a speedier Jev, contact us at sales@typesafe.ai and tell us more.

We can serve Jev profitably at our current prices. Our goal is to make intelligence more affordable over time as we improve the technology.

Jev is designed for common-sense judgments: classifying content, routing requests, scoring responses, and evaluating information. You can combine these decisions within your code to form larger workflows. Some tasks requiring extended reasoning, such as complex mathematics or chess-like planning, may be better suited to large reasoning models.

Yes. Jev guarantees the shape of its answers, not that every decision is correct. If you provide a list of categories, it can’t invent a category outside that list, but it can choose the wrong one. Uncertainty is a feature! You can use Jev’s provided probabilities and confidence to set the threshold for when your software acts autonomously and when it needs further review: higher for higher-stakes decisions, lower when errors are less costly.

Determinism means returning the same result for an identical input. This is less valuable than consistency. We define consistency as making similar decisions when the meaning stays similar, even if the wording changes. Jev is designed for consistency.

Join the waitlist! Jev is in its early days, and we’d love to hear how you’re using it, what you’re building, and any issues you run into. Join our Discord to ask questions, share feedback, and meme with our team.