How to Govern AI Agents at Scale | Ezhilarasan Natarajan, CoreStack

The cloud and AI giants earn more when you spend more, so who makes sure you aren't overspending?

Ez Natarajan built CoreStack into an AI governance company approaching $100M in annual recurring revenue, on the bet that the referee has to be independent.  Ez spent years in the partner ecosystem that helped build Microsoft Azure before it even had a name, watching enterprises stall because the cloud rewrote every rule for cost, security and operations. CoreStack, now in its 10th year, is a multi-cloud governance platform. It connects to a company's AWS, Azure and Google Cloud accounts, finds every workload, and fixes cost and compliance problems automatically. Its largest customer spends about $1 billion a year on cloud.

In this conversation with host Akshay Datt, Ez explains why hyperscalers welcome software that cuts their customers' bills, and why the world has less than one GPU per person. He also argues that every software company, CoreStack included, will move to token-based pricing. With AI budgets rising and per-seat SaaS under pressure, his case for independent AI governance and cloud cost optimization comes at a good time.

👉Why AWS and Microsoft treat CoreStack as a top partner even though it cuts their customers' cloud bills: a CFO's budget freeze would hurt them far more.

👉How CoreStack lets customers decide when it acts on its own, taking automatic action in dev and test environments while keeping a human in the loop for production.

👉What the GPU shortage really looks like: less than one GPU per human today, while Ez estimates each person needs 10 and Sam Altman needs 1,000.

👉How AWS and Anthropic split token revenue differently by region, and why Google, Amazon and Microsoft are hedging across OpenAI, Anthropic, Gemini and Nvidia at once.

👉Why Ez plans to take CoreStack public instead of selling to a cloud or AI giant, arguing that AI governance has to sit outside the companies it polices.

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