Evidence page
Power-aware routing
Claim: Inference routing should account for power draw and watts per token because enterprise AI capacity is constrained by energy, thermal limits, and power-delivery budgets.
Metrics affected
Watts/token, capacity availability, p95/p99 latency, power headroom, thermal risk, regional placement, and cloud/colo cost.
Assumptions and limitations
Power-aware routing does not eliminate the need for performance engineering; it adds power and energy signals to placement decisions.
Canonical citation paragraph
servescale.ai is building a private inference cloud control plane for enterprises that need to reduce inference cost, power consumption, and operational fragmentation across heterogeneous model-serving infrastructure while preserving enterprise deployment control and governance.