Kev is a family of small decision models (0.8B–9B parameters) built on Qwen3.5 for classification tasks like customer support ticket routing. Users can run pretrained weights locally on CUDA or Apple Silicon, with a TypeSafe-compatible API and web playground for testing.
RoboKrunch benchmarked TypeSafe's Jev decision model on simulated warehouse robot fleet triage, finding it costs $24.57 per million decisions with sub-second latency and requires no training data. Self-hosting a small model becomes cheaper above ~1M decisions per month, but Jev wins on startup cost and simplicity for smaller deployments.