SLATEMOTH / INSIGHT
Model routing in production AI systems
What model routing is, what signals can inform it, and why routing should be separated from reliability and policy controls.
Definition
Model routing chooses where an AI request should execute. The decision can consider capability, modality, latency, availability, policy, price and workload requirements.
Routing is not the whole gateway
Routing answers where a request should go. Reliability controls answer what happens when execution fails. Policy controls answer what is allowed. Metering answers what happened.
Signals that can matter
Useful signals may include requested modality, context size, tool requirements, provider health, regional constraints, latency targets and configured economic limits.
Rules and adaptive selection
Deterministic policies are easier to audit. Adaptive selection can improve outcomes when reliable feedback exists. A practical system can use deterministic eligibility first.
Operational principle
A routing decision should be explainable after the fact. Preserve enough decision context to understand why a provider or model was selected.