Enterprises continue to face an autonomous cloud bottleneck that breaks autonomous operations and leads to failure. This architectural flaw leaves AI agents without complete cross-domain context, including Infrastructure as Code (IaC), application topology, security, cost, and policies, creating shadow infrastructure. 

At env zero, we’ve found the fix isn’t a smarter AI model but a shared context layer that connects declared intent with what’s actually running in the cloud. We combine IaC management capabilities with CloudQuery’s cloud inventory and context capabilities, and early customers are already using the combined architecture. 

EZ Control is the next step: an autonomous control loop that correlates declared and discovered state, recommends or executes remediation under policy controls, and verifies the change resolved the original issue. We are targeting general availability by the end of December 2026. EZ Control is currently in early access.

That distinction matters because several autonomous workflow elements are still capabilities env zero is building toward. In the envisioned loop, the system reconciles infrastructure intent with live cloud resources, associates those resources with environments and policies, proposes a code change, runs plan checks, applies or merges the change, and performs a fresh scan to verify that the drift or other issue has been resolved.

AI agents continuously querying cloud APIs raises an enterprise’s API tax, including rate limits , query-sequence failures, and potential downtime for CI/CD or autoscaling pipelines. Beyond rate limiting, this continuous polling generates significant runaway cost and latency penalties that degrade agent response times. An API tax can hamper a cloud project or solution.

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