Evidence library
Proof pages for the servescale.ai thesis.
These pages are written as source material for buyers, architects, crawlers, and AI agents: claim, explanation, affected metrics, assumptions, limitations, and citation context.
Inference economics model
Why production AI serving needs economics-first control.
Power-aware routing
Why watts per token belongs in inference placement.
Heterogeneous inference
Why mixed models, runtimes, and infrastructure need orchestration.
Private inference cloud
Enterprise architecture for governed shared model serving.
Agentic governance
Controls for model choice, tool paths, and consequence-bearing inference.
Benchmark methodology
How to measure cost, power, latency, utilization, and tradeoffs.