Riverbed Released Network 360 AI Solutions

The company integrated agentic AI into its existing network monitoring products to enhance operational visibility.

Updated on Sept. 23, 2026 in Artificial Intelligence

Isometric editorial illustration of matte data server blocks and fiber-optic cables, representing digital infrastructure visibility.
Riverbed released its Network 360 suite, integrating agentic AI into established platforms to improve network visibility for complex hybrid cloud environments. AI Illustration. Upload story photo >

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Riverbed announced its new Network 360 suite, which integrates Riverbed IQ and Riverbed Q into its established AppResponse and NetProfiler platforms. The suite is designed to provide advanced network visibility for hybrid cloud environments.

Why it matters

Network monitoring tools currently require intensive manual analysis to manage the increasing complexity of modern hybrid environments. By applying Generative and predictive AI, these new tools aim to streamline the identification of network issues.

The suite utilizes Riverbed IQ to apply causal and predictive AI to operational data, while Riverbed Q provides a natural language interface for investigations. Additionally, NPM+ extends network visibility to remote users and cloud environments.

The players

Riverbed

Riverbed is a technology company specializing in network performance, visibility, and optimization solutions for enterprise clients.

The details

Riverbed IQ correlates network evidence to identify causes and anticipate potential issues, while Riverbed Q enables users to perform investigations via conversational natural language. These offerings are designed to lay the groundwork for future autonomous network actions.

Timeline

  1. Riverbed announced the Network 360 suite on September 23, 2026.

The Tech Race

This release follows a broader industry pattern of integrating conversational AI agents to simplify technical infrastructure management. It represents a shift toward AIOps as companies look to automate tasks previously handled by manual human analysis.

Network professionals can expect to utilize a natural language interface to speed up their troubleshooting workflows for hybrid environments. These tools aim to reduce the time required to correlate evidence when diagnosing complex network issues.

The takeaway

The integration of agentic AI represents a transition toward systems that can proactively manage network health rather than just reporting errors. Practitioners should prepare for a shift toward conversational interfaces as the primary method for interacting with complex data sets.

Further reading

Learn more about advancements in this space in the Artificial Intelligence section.

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