AgentOps Meets FinOps: Governing AI Costs Across a Hybrid Agent Portfolio

You’ve built the agents. You’ve deployed the copilots. Maybe you’re running local models through frameworks like OpenClaw and Ollama alongside Azure OpenAI endpoints. Now the real question hits: what does all of this actually cost — and who’s tracking it? As AI architectures go hybrid — spanning cloud inference, local models, and multi-agent orchestration — traditional cloud cost management isn’t enough. Organizations need FinOps discipline that covers the full spectrum: token consumption across commercial APIs, compute costs for local inference, model routing decisions that trade cost for latency, and the hidden operational overhead of running AI in multiple places at once. 

This session bridges AgentOps and FinOps for the hybrid AI era. We’ll share patterns from real environments where teams are balancing Azure-hosted models with local alternatives, show how to build cost visibility across the entire AI portfolio, and walk through a cost assessment framework that helps leaders make informed build-vs-buy-vs-run-locally decisions. You’ll leave with a practical playbook for getting ahead of AI spend — no matter where your models run.