Unstoppable integrates TypeSafe Jev for model routing

Defaulting to 70B+ parameter generative LLMs for basic routing and tool arbitration is one of the most wasteful anti-patterns in modern AI development, and dedicated decision engines like Jev are set to become mandatory infrastructure.

• –Latency and Cost Compression: Offloading classification, routing, and guardrail checks to sub-500ms typed decision models cuts latency by orders of magnitude while drastically reducing inference spend.
• –Schema Reliability in Agent Loops: Structured, probabilistic outputs (choices, scores, boolean decisions) eliminate the fragility and parsing failures common to free-form LLM routing.
• –Tiered Model Orchestration: As autonomous agent harnesses scale, the multi-tiered paradigm—pairing fast System 1 evaluators with heavy System 2 reasoning models—will dominate production architectures over single-model stacks.