parallel sampling

TypeSafe emerges from stealth with its Jev model, designed for automated programmatic decisions. Unlike traditional language models, Jev eschews text generation, processing unstructured state inputs to deliver type-safe, structured values in a single, parallel query. This hardware-aware parallel sampling architecture and Reinforcement Learning for Calibrated Decisions (RLCD) training ensure deterministic logic, high performance, and cost efficiency, making it ideal for complex decision-making in software systems.