Critical cloud exposures pile up faster than security teams can close them. Cloud-native application protection platforms (CNAPP), cloud providers, and posture scanners generate more findings than any team can triage, and risk accumulates in the gap between detected and fixed. Most findings sit untouched, not because they’re hard to fix. Someone must investigate context, identify the owner, confirm the fix won’t break production, and then do it at a volume that outpaces headcount.

In this post, we share how Tamnoon built Tami, an agentic cloud remediation orchestrator on Amazon Bedrock, to close that gap. Tami autonomously investigates findings ingested from CNAPP and cloud-native sources and assesses whether remediation is safe. It then generates and orchestrates the fix with guardrails and governance wherever a change touches a customer’s cloud. The approach drove an over 90 percent reduction in critical cloud exposure in 90 days with zero production issues.

About Tamnoon

Tamnoon is an AI-powered cloud security remediation platform that works alongside CNAPPs. Its AI assistant, Tami, helps human cloud security experts investigate, prioritize, and safely remediate misconfigurations and issues across customer environments in AWS, Azure, Google Cloud, and other cloud providers.