Nirmata’s AI-Powered Remediations: A Smarter Way to Fix Policy Violations

Nirmata’s AI-Powered Remediations: A Smarter Way to Fix Policy Violations Why AI Remediations for Policy as Code? How It Works Designed for Developer Velocity and Platform Efficiency Where to Find It What’s Next Every modern enterprise strives for faster software delivery without compromising on security and compliance. As cloud-native environments grow in scale and complexity, so does the burden of identifying and fixing misconfigurations across clusters, pipelines, and cloud infrastructure. Today, we’re excited to announce a major leap forward in our mission to simplify cloud governance: AI-Powered Remediations , which is now available in preview in Nirmata Control Hub (NCH). Security and platform teams often face a growing backlog of policy violations—from missing labels to insecure container configurations to overly permissive network rules. Manually investigating each violation, understanding its root cause, and crafting a compliant fix takes time—and that time adds up. With AI Remediations, we’re dramatically reducing the Mean Time to Remediation (MTTR ). Instead of spending hours chasing down documentation or writing YAML from scratch, teams can now review and apply context-aware fixes in minutes. And the benefits go beyond speed: Dev teams are no longer blocked by vague policy errors. Instead, they receive concrete, explainable suggestions to fix issues early. Platform engineers can spend less time triaging violations and more time building scalable, reliable infrastructure. Security teams have peace of mind knowing issues aren’t just detected—they’re getting resolved faster than ever. Whether it’s a Deployment, ConfigMap, NetworkPolicy, or any Kubernetes resource, if it violates a rule enforced by your Kyverno policies in NCH, we can generate a fix.