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.
A developer built a specialist System One model on an RTX 3070 by fine-tuning ModernBERT-base with LoRA adapters on banking, spam, and sentiment datasets, then distilled knowledge from Qwen2.5-7B using teacher logits. The model achieved 88.5% on banking intent classification and 98.9% on spam detection, with selective prediction reaching 99% accuracy on high-confidence examples.