The 3-Step FinOps Framework for AI
A practical 3-step framework to measure, track, and optimize your LLM spending—without compromising quality. Battle-tested across dozens of AI teams.
LLM optimization isn't about spending less—it's about spending smarter. While some teams burn through their AI budget delivering basic features, others build sophisticated experiences for a fraction of the cost. That efficiency gap compounds fast. Don't be on the wrong side of it.
So you've landed here! Someone raised concerns about the cost of your chatbot, agent, or workflow, and now you're wondering what to do next. You're not alone.
Common reasons teams start exploring FinOps for AI:
- Unit economics don't work - you're paying more to serve customers than they're paying you
- Unexpected cost spikes - everything was fine until your provider's invoices started flooding your inbox
- Proactive optimization - you want to build efficiently from day one (kudos for that!)
No matter what brought you here, there's good news: LLMs can deliver exceptional results and cost less than what you're currently paying.
Start with the foundation.
You might want to jump straight to optimization, but here's the truth: you can't optimize what you can't measure. That's why we recommend a structured approach, battle-tested across dozens of organizations:
- Know your objective and who's in charge
- Know what you're spending on, down to a feature and responsible team
- Optimize your apps, one use case at a time
Let's walk through each step: