TypeSafe AI founder Diogo Almeida coined the product category around Jev in September 2026. A decision model reads backbone representations, scores every schema option in one pass, and returns calibrated probabilities on noul (yes/no), choice (pick one), or score (a number) fields. Training often combines label-smoothed cross-entropy, Brier loss, and RLCD (Reinforcement Learning for Calibrated Decisions). Later hosts such as Cloudflare Clef keep a Jev-compatible API. The hop is complementary to reasoning LLMs and is not deterministic.