Classic cloud FinOps
Even before talking about AI, most organizations pay for cloud resources that are underused or misconfigured. Classic cloud FinOps means making these costs visible, attributing them to the right teams or projects, and right-sizing resources to match actual usage.
- Visibility into costs by service and by team
- Systematic tagging of resources
- Resource rightsizing
- Cost allocation (showback / chargeback)
What is generative AI FinOps?
Generative AI FinOps applies the same principles of cost visibility and control, but to token consumption by AI models (Claude, ChatGPT, Gemini, etc.). Without tracking, the cost of an AI assistant can go from a few dollars to thousands of dollars per month within a few weeks, simply because its use has spread across the organization.
Token tracking
Measure consumption by use case, team, or application.
Model selection
Balance cost and quality based on the task (a smaller model is often enough).
Caching and batch processing
Avoid paying multiple times for the same requests.
Budgets and alerts
Get notified before costs spiral out of control, not after.
Our methodology
1. Inform
Make costs visible and understandable for the teams involved.
2. Optimize
Adjust resources, models, and usage patterns to reduce waste.
3. Operate
Put budgets, alerts, and recurring reviews in place to maintain control.
Typical results
[Statistics to be validated with the client before final publication]
Cloud/AI cost reduction observed within 90 days on comparable engagements
Typical timeline for a first Inform → Optimize → Operate cycle
Frequently asked questions
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