ControlMonkey addresses the persistent gap between intended infrastructure state defined in Terraform and the actual cloud environment that accumulates manual changes over time. The platform continuously scans cloud accounts to detect infrastructure that was created or modified through console clicks rather than code, then automatically generates corresponding Terraform configurations that bring those resources under version control and IaC governance.
The AI-powered code generation engine reverse-engineers cloud resources into well-structured Terraform modules following best practices for naming conventions, resource organization, and module composition. Rather than producing monolithic configuration files, ControlMonkey creates modular, reusable code that fits naturally into existing Terraform repositories. The generated code includes proper variable extraction, output definitions, and dependency declarations.
With $7M in seed funding, ControlMonkey targets the growing problem of infrastructure governance in organizations that have adopted IaC but struggle with enforcement. The platform provides policy guardrails that prevent direct cloud console modifications, alerts teams when drift is detected, and automates the remediation process by generating pull requests with the Terraform code needed to reconcile differences between desired and actual state. This closed-loop approach turns IaC from an aspiration into a continuously enforced reality.