“What’s unique about these models is that they are customized and purpose-built for networking, pre-trained on high-volume telemetry, alarms, and flow data across diverse environments,” IBM stated. “Unlike purely statistical machine learning, rule-based tools, or generic LLMs, these Time Series Foundation Models offer deep contextual understanding of network behavior. This approach was created to enable more accurate network observations – to find typically subtle hidden issues and even provide early-warning of degradations, which is essential for building trust in an autonomous system, intended to provide an improved signal-to-noise ratio.”
“As networks become mission-critical, downtime and slowdowns are no longer justifiable. Technical leaders must move beyond reactive firefighting to intelligent, performance-driven operations. Network-native AI is now essential—not just for resilience, but for continuous optimization, automation and delivering always-on digital experiences,” IBM stated.
According to IBM, its Network Intelligence service features:
