Axians: AI improves network troubleshooting capabilities

Companies like Axians are increasingly leveraging artificial intelligence (AI) for managing enterprise networks. New solutions address growing network complexity and a shortage of skilled professionals by improving network troubleshooting and stability.

Traditional network troubleshooting is labor-intensive and prone to errors. In large, complex networks, identifying and resolving faults requires analyzing vast amounts of log data. AI systems, such as Juniper MIST's Marvis, meet this challenge. These platforms analyze data and use machine learning to automatically detect and correct network anomalies and issues.

The objective of these solutions is to establish "Self-Healing Networks." Such networks can minimize downtime by resolving problems immediately. Automation reduces manual intervention, leading to significant cost savings. Continuous monitoring and adaptation ensure optimal network performance.

AI enables automatic error detection and correction, implements redundant and fault-tolerant systems, and provides adaptive network control. It also facilitates proactive maintenance by addressing potential issues before they escalate.

Cloud-based AI platforms, like Juniper MIST, offer the necessary computing power for efficient network management. Axians states that AI does not replace human labor but frees up experts for more strategic and creative tasks, such as network design.