Tamnoon has introduced major enhancements to its cloud security platform, expanding its AI engine, Tami, into a skill-based remediation orchestrator designed to help enterprises respond to cloud threats more efficiently and safely. The update reflects growing industry demand for automated security operations as organizations face increasingly complex risks driven by AI-powered development and autonomous systems.
According to the company, Tami has been trained using more than six million real-world cloud remediation cases across over 800 customer environments. The upgraded system now coordinates specialized AI-driven remediation “skills” tailored to each organization’s infrastructure, enabling faster and more precise responses to security vulnerabilities.
These include the Remediation Confidence Score and the Safe Vulnerability Patching Simulator. The first one is used by the company’s platform to determine the impact of proposed solutions, classifying them as safe, risky or dangerous based on how they could affect the operations of the client’s system once deployed. The latter enables security teams to simulate the behavior of patches by testing them against the application in a sandboxed environment.
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According to Tamnoon, the move came after many companies faced increasing difficulty in matching up to the magnitude and velocity of AI-powered attacks. This is evidenced by the fact that, in the current environment, the average amount of time needed for addressing important cloud security alerts has risen to 128 days, and fewer companies have been able to fix vulnerabilities as quickly as they release their applications.
“Frontier AI is reshaping the cloud attack surface exponentially,” the company noted, emphasizing that conventional security playbooks and isolated automation tools are no longer sufficient for modern cloud environments.
Idan Perez, CTO and Co-Founder of Tamnoon, said: “Tami isn’t one agent, it’s an orchestrator. We’ve built the layer that coordinates remediation skills generated for each customer’s environment, with the safety controls to ship in production. The Confidence Score and Patching Simulator are the new skills. Soon, customers and partners will edit existing and add their own. Tami finishes the job, across every class of cloud risk.”
The announcement highlights a broader shift within cybersecurity toward agentic AI defense models capable of automating remediation while maintaining governance and operational safety. As AI adoption accelerates across enterprise software development and cloud infrastructure, security providers are increasingly focused on reducing response times, limiting exposure risks, and enabling organizations to scale protection without overburdening security teams.