SSPLAXAI Infra
Power, compute, and inference routing.
Data Center Power Readiness
Can the AI capacity plan come online under power, cooling, equipment, budget, and policy limits?
An AI campus wants to bring new GPU capacity online, but the compute plan is ahead of the physical site. Firm utility capacity arrives in stages. Non-firm power can bridge part of the gap, but only for flexible load. Onsite generation is available, but it is more expensive and pushes against carbon policy. Transformer gear, cooling, and GPU hall commissioning all move on different schedules.
Model ServingAI Inference Routing
Which serving mix absorbs the traffic growth without exceeding GPU, latency, budget, or carbon limits?
Inference traffic routes across four serving paths: a local small model, a local frontier pool, an external API, and a CPU batch fallback. The cheap path (CPU fallback) can absorb only limited traffic before it breaches the latency SLA. The fast paths are running into GPU-hour and quota limits.