Free · buyer-side
The AI Spend Governance Framework.
AI infrastructure is the fastest growing line on the cloud bill, and it behaves nothing like compute. This framework gives you the controls to govern token costs, GPU capacity, provisioned throughput, and capacity reservations before they outrun the budget, across AWS, Azure, GCP, and OCI.
A buyer side framework with controls and a worked allocation example. Figures are indicative and verified against billing data on real engagements.
For the operating model behind these controls, read the FinOps operating model guide or the cross cloud guide.
- The four AI cost drivers, tokens, GPU capacity, provisioned throughput, and capacity reservations, and how each is billed.
- Why inference token cost, not training, is where most budgets quietly leak.
- A discipline for Azure OpenAI and managed model endpoints that keeps spend attributable.
- When to reserve GPU capacity and when reservations become stranded cost.
- Allocation and unit economics for AI, so cost maps to a product and a request.
- Guardrails and anomaly alerts tuned for workloads that can ten times overnight.
Independent · buyer-side
Put a defensible number on your cloud spend.
No provider in the room, no published price list. Tell us your footprint and we will scope the savings against your billing data.