How do I govern AI agents across multi-cloud environments?

Governing AI agents across multi-cloud environments (AWS + Azure + GCP) requires a cloud-agnostic governance layer that enforces consistent policies regardless of which cloud provider the agent is executing on — because each cloud has different IAM models, API patterns, and security primitives.

Multi-cloud governance challenges:

• Inconsistent IAM: AWS IAM roles, Azure RBAC, and GCP IAM all work differently — policies written for one don't translate to another
• API fragmentation: The same "delete database" action uses different APIs across clouds — governance must understand all of them
• Cross-cloud data movement: Agents transferring data between clouds may violate data residency requirements
• Audit consolidation: Each cloud has its own logging system — correlating agent actions across clouds requires a unified audit layer

Exogram sits above the cloud layer. The 8 deterministic policy gates evaluate actions based on semantic meaning (what the agent is trying to do), not cloud-specific API syntax. A destructive database operation is blocked whether it's a DynamoDB DeleteTable, Azure SQL DROP, or BigQuery delete. One governance layer. Every cloud. Same rules.