Tamnoon builds AI remediation agent Tami on Amazon Bedrock to cut cloud risks by 90%
Tamnoon, an AI-powered cloud security platform, introduced Tami, an agentic remediation system built on Amazon Bedrock that autonomously fixes critical cloud misconfigurations. The system processes findings from tools like Wiz, CrowdStrike, and AWS Security Hub, then investigates, scores safety, and executes fixes—all without touching production—using specialized AI agents for each step. Tamnoon…
Key points
- Tami cuts critical cloud exposures by over 90% in 90 days, per Tamnoon’s data, with zero production issues
- Uses Amazon Bedrock’s multi-model API to assign tasks to specialized AI agents (e.g., investigation, safety scoring, code review)
- Security features include IAM permissions, Bedrock Guardrails, and tenant-isolated AWS environments
The architecture leverages Amazon Bedrock’s multi-model API to match tasks to the best foundation model, from deep investigative reasoning (using Anthropic’s Claude) to high-volume validation and code review. Security is hardened through IAM-scoped permissions, Bedrock Guardrails, and cross-region inference to ensure data stays within AWS boundaries. Tamnoon’s Remediation Confidence Indicator (RCI)—SAFE, RISKY, or AWAITING DATA—guides automation, while backup, verify, and rollback steps mitigate risks. The platform processes 14 million+ alerts across customers, with results typically visible within 90 days, according to Tamnoon’s internal research.
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How Tamnoon built AI-powered cloud security remediation with Amazon Bedrock
AWS Machine Learning Blog · 14 October 2026
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