As enterprises accelerate artificial intelligence adoption, securing AI driven environments has become a critical priority for cybersecurity leaders. The launch of a new GPU powered SASE platform from Cato Networks, signals a shift toward integrating advanced compute capabilities with security infrastructure to address the growing complexity of AI threats and workloads.
Cato Networks has introduced two major innovations to its SASE platform aimed at securing enterprise AI adoption at scale. The company unveiled Cato Neural Edge, a GPU powered enforcement layer, alongside Cato AI Security, a unified solution for AI governance and protection. Together, these capabilities are designed to deliver a security platform built specifically for the demands of the AI era.
The introduction comes at a time when organizations are increasingly relying on AI systems such as copilots, chat based tools, and autonomous agents. These technologies create new security challenges, as traditional controls were not designed to inspect conversational interactions, contextual data flows, or AI driven workflows. Without proper safeguards, enterprises face risks including data leakage, intellectual property exposure, and compliance violations.
Matan Getz, Vice President of AI Security at Cato Networks, highlighted the dual role of AI in modern cybersecurity. “AI is changing both sides of the equation: the threats we face and the defenses we need,” said Matan Getz, vice president of AI security at Cato Networks. “With Cato Neural Edge and Cato AI Security, we are empowering enterprises to strengthen AI-driven defense and govern enterprise AI without sacrificing performance or adding operational complexity.”
Cato Neural Edge addresses the infrastructure requirements of AI powered security by deploying NVIDIA GPUs across the company’s global private backbone. The system operates within more than 85 points of presence, enabling real time inspection and analysis of network traffic without relying on external cloud processing. This approach allows for high frequency execution of AI models, real time semantic analysis, and scalable inspection of global traffic flows while maintaining consistent performance.
By embedding AI processing directly within its network infrastructure, Cato aims to eliminate the latency and fragmentation associated with sending data to external GPU environments. This design ensures that intelligence and enforcement remain tightly integrated, providing more predictable and efficient security outcomes.
Complementing this infrastructure is Cato AI Security, which unifies governance and protection across various AI use cases. The platform enables organizations to manage employee interactions with AI tools, secure internally developed AI applications, and enforce policies for autonomous agents. It can operate as a standalone solution or as part of the broader Cato SASE platform, sharing a unified control plane and policy engine.
Marc Crudgington, Vice President of Cybersecurity and IT Infrastructure at Crane Worldwide Logistics, emphasized the benefits of integrated security architecture. “One of the biggest advantages for us is that AI security isn’t another console or separate enforcement layer. It’s built directly into the Cato SASE Platform,” said Marc Crudgington, vice president of cybersecurity and IT infrastructure at Crane Worldwide Logistics, a global logistics company. “We can govern AI usage, secure homegrown AI applications, and manage agent workflows using the same policy engine and data lake that already protect our network and cloud environments. That unified architecture reduces complexity and ensures consistent enforcement everywhere AI operates.”
The introduction of a GPU powered SASE platform reflects a broader industry trend toward combining high performance computing with cybersecurity. As enterprises scale AI adoption, integrated solutions that deliver both AI for security and security for AI are expected to play a central role in protecting modern digital environments.
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