Cato Networks is expanding its SASE platform with new capabilities designed for an AI-driven security landscape, where organizations must both secure AI usage and rely on AI to counter evolving threats.

One addition focuses on infrastructure. Cato has embedded GPU-based processing across its global network to bring intelligence closer to traffic flows. This architecture allows the platform to analyze activity, apply policies, and run AI models in real time without relying on external processing layers. The result is faster inspection, consistent performance, and the ability to scale analysis across distributed environments.

The second addition centers on governance and protection of AI itself. The new capabilities give enterprises a way to monitor how employees use third-party AI tools, apply safeguards to internally developed models, and maintain control over autonomous systems. These functions are integrated into the broader platform rather than delivered as a separate product, allowing teams to manage policies, visibility, and enforcement from a single system.

This approach reflects a broader shift in cybersecurity. As AI adoption accelerates, organizations are moving toward security models that combine traditional controls with AI-enhanced detection and response. That shift is driving demand for platforms that can handle large-scale data inspection and decision-making in real time without adding operational overhead.

Cato’s platform is built on a private backbone that dynamically routes traffic based on network conditions such as latency and packet loss. By continuously optimizing how data moves between users, applications, and cloud environments, the company positions its infrastructure as a foundation for delivering these newer AI-driven capabilities at scale while maintaining performance.

Learn more: Press Release

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