Extreme Delivers Industry’s First Proactive, Context-Aware AI Agent for Networking

Extreme Networks, Inc. announced the general availability of Extreme Agent ONE™ Coworker, the next generation of agentic AI for enterprise networking. Now available to all Extreme Platform ONE™ customers worldwide as part of their subscription, Agent ONE Coworker scales IT expertise and delivers recommendations rooted in each team’s specific network environment, enabling them to resolve issues up to 15x faster and move from reactive issue resolution to proactive planning and prevention.

Also Read: CIO Influence Interview with John Elliott, Cybersecurity Author Fellow at Pluralsight

Today’s enterprise environments are complex, and network teams spend hours or days gathering information and troubleshooting while also struggling to hire and retain qualified engineers. Unlike traditional predictive analytics that just surface network anomalies, Extreme Agent ONE Coworker’s “Nudge” skill combines real-time network context, historical trend analysis, and agentic reasoning that delivers recommendations directly into the workflow, telling IT teams what they need to know before they ask so they can start at the fix, not the search.

“Generic AI broadly understands networking. Extreme Agent ONE Coworker understands the intricate details of your network environment, encompassing historical client experience and network performance. That context is the difference between troubleshooting a ticket and fixing the root cause of a problem with documented analysis and recommendations. It turns insight into action and problems into resolutions at machine speed, while keeping people firmly in control. It’s not replacing expertise; it’s scaling it across the enterprise,” said Nabil Bukhari, CTO and President of AI Platforms, Extreme Networks.

New AI Skills Enable Embedded Intelligence Across the Operational Workflow

Within Extreme Platform ONE, Extreme Agent ONE Coworker maps relationships across users, devices, applications, services, and network conditions, delivering accurate, context-based answers so teams can investigate problems without manually assembling the evidence themselves. It shows its reasoning alongside recommendations, so teams can validate conclusions and stay in control.

• The newest skill in Extreme Agent ONE Coworker is “Nudge,” which continuously analyzes your network’s historical performance baseline, current traffic patterns, and platform-wide behavioral trends to identify deviations, proactively surfacing high-confidence issues that require attention.
• “Talk to RRM” continuously optimizes wireless performance by analyzing RF behavior.
• Its “canvas” skill generates dynamic dashboards and customized reports for all audiences.
• Enhanced by Extreme’s optimized knowledge graph, Agent ONE Coworker’s “talk to knowledge” and “talk to data” skills now deliver significantly improved response accuracy, bringing troubleshooting guidance directly into the workflow and slashing time spent onboarding new team members by up to 50%. “Talk to support” now uses live network context to recommend fixes and, when needed, automatically escalates to Extreme’s GTAC team, accelerating time to resolution.

“We’re excited to get started with these new tools. Extreme Agent ONE Coworker will give us the ability to instantly turn network data into context-based insights tailored to each specific audience, so we can quickly get high-level answers that our CIO can use with leadership teams, while our IT team can dive deeper to troubleshoot and optimize network performance,” said Cord C. Scott, Principal Network Engineer, Vandalia Health.

“Enterprise networking is moving beyond first-generation AI. The next era is about context: AI that understands each customer’s unique environment, explains its reasoning, and gives network teams confidence to act. Extreme Agent ONE Coworker is a strong example of that evolution, moving AI from a helpful assistant to a trusted part of network operations,” said Shamus McGillicuddy, VP of Research, Enterprise Management Associates (EMA).