TypeSafe AI
Machine-native decision models for fast, typed, and confidence-aware automation
TypeSafe AI develops System One models that turn application state into structured decisions rather than free-form text. Its models are designed for software automation, returning bounded choices, scores, and probabilities that applications can validate and act on directly.
Models by TypeSafe AI
Jev 1.14 is TypeSafe AI's System One decision model for fast, machine-consumable judgments. It reads structured or unstructured application state and answers typed questions with bounded choices, ordinal scores, or yes-or-no probabilities with confidence, with stronger multilingual handling. Its 256K-token context window fits long logs, documents, and conversation histories into a single decision for routing, classification, verification, and guardrail workflows.
Jev 1.13 is TypeSafe AI's System One decision model for fast, machine-consumable judgments. It evaluates structured or unstructured application state against typed questions and returns bounded choices, ordinal scores, or yes-or-no probabilities with confidence in a parallel pass. Unlike generative language models, Jev does not produce free-form prose; it is designed for routing, classification, ranking, verification, guardrails, and real-time workflows where software must act on predictable outputs.