Agent Commander: Veeam's solution for AI security challenges

Veeam has launched Agent Commander, a solution designed to combine data resilience with AI security, providing organisations with visibility and control over AI systems and associated risks.

  • Wednesday, 4th March 2026 Posted 3 months ago in by Sophie Milburn

Veeam Software has introduced Agent Commander, a solution designed to help organisations identify AI risks, protect AI systems and remediate AI errors. The launch follows Veeam’s acquisition of Securiti AI, combining capabilities from both organisations into a unified platform for managing data and AI environments.

Agent Commander aims to provide organisations with visibility and control across their data and AI estates. A key feature is its ability to reverse certain AI-related actions where necessary, enabling businesses to address risks while continuing to expand AI usage within defined controls.

As AI becomes more embedded in enterprise operations, data risk and AI risk are increasingly interconnected. Organisations often operate with distributed controls and separate systems for protection, governance and recovery, which can limit holistic oversight. This fragmentation can result in sensitive data being used in ways that are not fully monitored or governed.

Agent Commander introduces a unified control plane intended to deliver contextual visibility, policy enforcement and recovery capabilities. The platform integrates data resilience, data security and AI risk management into one operational framework.

Central to the solution is Veeam’s Data Command Graph, an intelligence engine that maps real-time connections between data, identities, AI models and autonomous agents across production and backup environments. It is designed to identify risk scenarios involving compromised identities, exposed data and automated processes by analysing how these elements interact.

The platform supports organisations in detecting AI risks such as shadow AI and anomalous agent behaviour, applying governance controls to AI pipelines, and reversing AI-driven actions when required. It is positioned to provide context-aware recovery with limited disruption to operations.

By combining AI-related visibility with data resilience capabilities, the solution reflects an approach where AI protection and recovery are integrated into existing infrastructure. As AI moves further into operational use, the platform is intended to support organisations in managing governance, security and recovery within a single system.

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