Controlling AI Costs: Optimize and Chargeback LLM Usage with agentgateway
|Control and Optimize LLM Costs at Scale
As AI agents multiply across enterprise environments, LLM usage visibility and cost control become mission-critical. Traditional monitoring tools struggle to track token consumption, attribute costs, and enforce accountability across multi-agent, multi-org workflows.In this webinar, you'll get a deep technical look at how agentgateway provides gateway-level observability to track usage in real time, calculate costs, enforce budgets, and implement chargeback models across teams.
What you’ll learn:
- A breakdown of LLM consumption challenges in agent-based systems and why token tracking + attribution require more than legacy monitoring
- How to configure agentgateway for usage monitoring: budgets, rate limits, and multi-provider routing (Anthropic, OpenAI, xAI, and more)
- Practical chargeback and reporting techniques for per-user/per-team cost breakdowns and billing system integrations
- A live walkthrough of the agentgateway-llm-consumption-demo, simulating multi-agent usage and visualizing cost flows in Prometheus and Jaeger
Who Should Join
- AI/ML engineers optimizing LLM pipelines in multi-agent architectures
- DevOps, SREs, and platform engineers implementing observability and cost controls
- Finance, billing, and architecture leaders building chargeback models for scalable AI economics
Don’t miss this deep dive into controlling LLM costs with precision. Register now.
