Built on 3 Clouds. Governed on one Control Plane.
A global CPG company is building AI agents across multiple clouds, regions and frameworks. With Lyzr, it brought governance and transparency to all of them under one control plane.
A Fortune 50 company running at global scale.
A Fortune 50 CPG company, building a central platform for AI agent development, governance and deployment across the enterprise. Its products reach consumers more than 1 billion times a day, across 200+ countries.
What breaks when every team builds on a different cloud.
Teams were building agents across 3 cloud environments, each with its own tooling and its own blind spots.
No shared registry
No single place to register, discover or manage the agents being built across the organization, whatever framework or cloud they were built on.
Fragmented visibility
Logs, traces and cost data sat separately in each cloud. No one view of what every team was building, what data it touched, or what it was costing.
A mobility problem, not just a tooling problem
Teams needed to keep working on the platforms they already use. Any fix that meant migrating them off those tools was not viable.
Governance had to sit above the stack, not replace it
The company needed oversight across all of its AI development without changing how agents get built and shipped.
Why the native cloud tooling could not cover this.
Each cloud governs what runs inside it. None of them can see what is running in the other 2. To close that gap without disrupting anyone, 4 things had to be true at once.
Register every agent in one place
One registry for every agent in development, whatever cloud or framework it was built on.
Move agents between clouds
Support portability by capacity or cost, without breaking existing workflows.
Bring observability into one view
Aggregate logs, traces and cost data from every environment into a single place.
Leave the authoring layer alone
Sit underneath the tools teams already build with, rather than replacing them.
A control plane under the tools teams already use.
The core of the build is a control plane: a governance and orchestration layer that sits beneath AI development activity across every cloud environment.
Built to unify multiple clouds, one at a time.
Deployment is planned as a phased, multi cloud Kubernetes rollout: one major cloud provider first, then the other 2 already in use across the organization.
The platform is designed to run inside the client’s own cloud environment, with an initial phase deployed in an implementation partner’s environment before migrating fully across.
Governance built into the deployment path, not bolted on after.
Governance is part of the path an agent takes to production. Every deployment passes the same checks, whichever cloud it lands on.
Same 3 clouds. One governed path.
Nothing changes about how teams build. Everything changes about what happens after they hit deploy.
No view across clouds.
No way back out.
What the control plane fixes.
The control plane becomes the single governance layer across every cloud the enterprise builds on.
The rollout, cloud by cloud.
Rollout goes cloud by cloud: first, then second, then third, with the regional workstream running alongside.
Got a use case in mind?
Platform, engineers and governance all in. We’ll map your workflow against the same 4 tests this one had to pass.