Cato Networks’ groundbreaking AI-driven platform, Network Stories for Cato XDR, is set to transform network incident detection and response, promising swifter action and enhanced collaboration between security and operations teams.
In an innovative leap within the networking and cybersecurity landscape, Cato Networks has unveiled its groundbreaking AI-driven solution aimed at revolutionizing how networking and security incidents are detected and managed. This move typifies the ongoing evolution in the supportive technologies businesses employ to ensure operational continuity and protect against cyber threats. Based in Tel Aviv, Israel, Cato Networks, a pioneer in Secure Access Service Edge (SASE), introduced the addition of network incident detection and response tools into its Cato SASE Cloud platform, marking a milestone in integrated network security management.
The conventional approach to managing network incidents often involves manual intervention, where Network Operations Centre (NOC) and Security Operations Centre (SOC) teams work in silos, sifting through vast amounts of data to diagnose and respond to incidents. This can be a time-consuming and error-prone process, often leading to prolonged downtimes and operational disruptions. However, with Cato Networks’ latest innovation, dubbed Network Stories for Cato XDR, the use of advanced AI algorithms is set to transform this landscape by offering instantaneous identification of network disruptions and conducting root cause analysis. This not only promises to slash response times from hours to mere minutes but also fosters enhanced collaboration between NOC and SOC teams.
Shlomo Kramer, CEO and co-founder of Cato Networks, emphasized the value of leveraging advancements in one domain to benefit another, illustrating the integrated approach of Cato’s SASE platform. By extending their security-trained AI to assist NOC teams, Cato is poised to redefine network management efficiency, making it faster and more proactive.
One pertinent example of the potential impact of Cato’s innovation is illustrated by Element Solutions Inc. (ESI), a leading specialty chemicals company that relies on Cato SASE Cloud. The company, which uses Cato for connecting and securing its widespread operations, including 118 locations, cloud instances, and nearly 4,000 remote users, has welcomed Network Stories as an essential tool to streamline their network management processes. As highlighted by Brandon Benchley, a senior network engineer at ESI, the time savings and operational enhancements offered by this solution address a significant pain point for their network team.
Network Stories for Cato XDR’s capability to diagnose incidents by identifying the root cause behind various network disruptions represents an essential step forward in ensuring network reliability. By prioritizing incidents based on criticality and summarizing them through generative AI into human-readable explanations, NOC teams can now tackle the most vital issues efficiently, with a comprehensive set of tools at their disposal for incident response.
Moreover, Cato’s initiative underscores the growing necessity for closer SOC-NOC collaboration, as noted in their 2023 SASE Adoption Survey, where a significant majority of respondents recognized the need for or were actively pursuing greater integration between their security and networking teams. The convergence facilitated by Cato’s platform is a testament to the evolving IT landscape, where the seamless management of network and security responses becomes crucial.
In an era where the resilience and security of network infrastructures are paramount, Cato Networks’ forward-thinking approach exemplifies a significant leap towards a more integrated, efficient, and secure operational environment for businesses globally. As organizations continue to navigate the complexities of modern cybersecurity and networking challenges, solutions like Cato’s Network Stories for Cato XDR stand out as essential tools in ensuring the agility and robustness needed to secure their digital futures.