Veeam introduces Agent Commander, an integrated solution that detects AI risks, protects against them, and recovers from AI errors. This technology combines data security and AI risk management into a single platform for better control and visibility.
With the rapid development of AI, the need for effective protection against errors and risks in AI systems is also growing. Agent Commander, developed following the acquisition of Securiti AI, aims to meet this challenge by providing organizations with real-time insight into their data and AI environments. This makes it possible to accurately monitor AI actions and quickly undo unwanted consequences.
The solution is integrated into the Securiti AI Data Command Center, where data resilience and data security converge. This creates a unified control panel that enables contextual visibility and rapid response.
AI Security
AI agents use massive amounts of data, often without organizations knowing exactly which data is being processed or how. This leads to a dangerous gap in trust and control, especially since traditional security systems are fragmented and cannot react in real time. Agent Commander aims to bridge this gap by providing a unified layer that brings together data resilience, security, and AI risk management.
By combining Veeam’s data resilience and Securiti AI’s Data Command Center, companies gain full visibility into their AI environment. The solution detects hidden risks such as shadow AI and risky agent behavior, and provides detailed controls over data and identities while AI systems are functioning.
Data Command Graph
At the core of Agent Commander is the Data Command Graph, a real-time relational intelligence engine that establishes connections between data, identities, AI models, and agents. This makes it possible to see risks that other systems are blind to, such as compromised identities or exposed data.
Agent Commander offers three capabilities: detection of AI risks with context, autonomous protection of AI pipelines regardless of platform or cloud, and precise recovery from AI errors via context-aware rollbacks. This allows companies to quickly roll back AI actions without having to restore entire systems.