An artificial intelligence routing policy is the set of conditions and priorities used by a model router. It can map request types to model pools, apply capability requirements, prefer lower cost or latency and define fallback behavior when a model is unavailable.
Policies should be configurable, versioned and evaluated against the organization's own workload. Feedback from quality, cost, latency, caching and user preferences can support careful updates over time.
Acronyms and aliases
model routing rule set synonymAI routing policy variantartificial intelligence routing policy variant
Related terms
Frequently asked questions
What does an AI routing policy contain?
It can contain task classifications, eligible model pools, rankings, cost and latency limits, preferences and failover rules.
How often should a model routing policy change?
It should change when validated workload evidence shows better choices or when model capability, pricing or availability changes.
