AI Troubleshooting for Industrial Networks At a Glance
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Improve productivity and operational uptime by maximizing network availability
In today’s factory, the production line runs on the network. Every robot, sensor, and controller that keeps operations running smoothly depends on sustained connectivity to function. And when that connectivity fails, the consequences can be extremely costly. Aside from the financial toll, a single point of failure in Operational Technology (OT) can cascade into production halts, safety incidents, regulatory exposures, and supply chain disruptions. Time is of the essence to minimize the fallout, which is why the speed at which OT teams can detect, diagnose, and resolve network issues is paramount.
Given the specialized focus of many OT roles, members of these teams have various levels of networking expertise or troubleshooting experience. And oftentimes, escalation is necessary to resolve issues. When a connectivity issue strikes during production, the clock is already running: each minute spent opening a ticket, waiting for an available network specialist, and walking them through the problem is another minute of halted production. The result is a gap between where the problem lies and where the expertise lives, something that’s measured in lost production time that can never be recovered.
From firefighting to frontline resolution
Closing this gap between these network issues and where the expertise to fix them lives, requires more than faster escalation paths. For most organizations, that means putting the expertise directly in the hands of the OT team from the moment it is needed.
Imagine a system that doesn’t wait for a human to notice a problem, but instead proactively surfaces it. A system that doesn’t require network engineers to interpret the data but translates it into language and context that the OT team already understands. And one that doesn’t simply identify what broke but informs the team exactly how to fix it – all in the time that it takes to read a notification.
This is the foundation of an agentic approach to industrial network operations: continuous monitoring, automated diagnosis, and actionable guidance delivered instantly to those closest to the problem.
Smarter network diagnostics for rapid resolution with AgenticOps
Cisco’s AI troubleshooting for industrial networks is an ambient agentic AI system designed to empower OT teams by simplifying network troubleshooting and monitoring in industrial settings. By continuously monitoring the network and notifying OT teams of any network issues it finds, it delivers both root cause analysis and actionable remediation steps, providing the necessary expertise to help teams identify and resolve problems quickly.
AI troubleshooting for industrial networks gathers data from the network to identify, troubleshoot, and recommend fixes for any issues it detects. It significantly simplifies operations for OT teams by translating complex network addresses into familiar asset names and accurately mapping operational locations to the underlying network topology. Its diagnostics and recommendations are backed by Cisco’s extensive experience in complex networking environments. This streamlined approach is critical for OT teams who cannot afford the time required for traditional troubleshooting.
AI troubleshooting for industrial networks:
● Proactively notifies users of networking issues with guidance to rapidly resolve the issue
● Provides a clear visualization of the network topology that helps identify and isolate the exact location of any networking fault
● Features an intuitive easy-to-use natural language conversational interface
● Automatically logs every alert and user interaction for streamlined auditing processes and post-incident review
The easy-to-use AI troubleshooting for industrial networks user interface
AI troubleshooting for industrial networks is installed locally to keep your network and production data secure. It gathers network data and uses AI to analyze the data, summarize the results, and provide clear answers on how to fix any issues it detects.
Proactive notifications: AI troubleshooting for industrial networks offers continuous, proactive monitoring that detects a broad spectrum of potential failures. Whether it identifies an asset going offline, detects physical cable damage, observes a switch experiencing a power failure, or encounters other network-related irregularities, it gathers all relevant telemetry data, performs a comprehensive root-cause analysis, and pushes a notification to the user containing the findings and a clear, actionable recommended fix. You’ll have all the information you need to fix issues on the spot, helping you minimize downtime and keep your production running smoothly.
Interactive topology: Beyond monitoring, the solution maintains and displays a full, searchable network topology at all times. It intelligently highlights malfunctioning equipment directly on the map, making it effortless for users to spot malfunctioning equipment as issues arise. You can easily drill down into any part of your network map to see exactly what’s happening, giving you the clear, detailed information you need to make quick decisions.
Conversational interface: Users can interact with the agentic system through simple, natural language prompts, treating it like a knowledgeable networking expert specifically trained to understand OT language and use cases. Using the conversational interface, users may ask for help with specific problems (such as “Why does paint-area-plc01 go down?), or more general network state, (such as “Show me what’s connected to [switch name]” or “What VLANs are configured on [IP address or switch name]?”).
To support continuous improvement and operational accountability, the solution automatically preserves a comprehensive record of every alert generated and every interaction between the user and the AI. All historical data is kept on-site and remains completely off the cloud. It allows for detailed post-incident analysis and internal audits. By maintaining this audit trail, your team can effectively learn from past events, identify recurring trends, and ensure full transparency across your network operations.
AI troubleshooting for industrial networks offers significant advantages for manufacturing and similar industrial environments:
● Maximize operational uptime: Get all the information you need to resolve any detected issues in a one-click notification, making it easier to maintain uptime.
● Visualize your entire network with a real-time map: Gain instant clarity with an accurate, real-time map of your complex network, including all sensors, controllers, robots, machines, and other endpoints.
● Empower your teams and boost productivity: Enable your entire OT team to solve network issues quickly and confidently, regardless of their networking skill level, and reduce the need for escalations.
● Free your networking experts: Reduce the burden on your networking specialists by AI-powered routine diagnostics and troubleshooting, freeing them to focus on strategic initiatives and innovation instead of constant firefighting.
● Build a repository of institutional knowledge: With every alert and user interaction automatically preserved, you create a valuable, searchable audit trail for post-incident analysis and regulatory compliance. This allows your team to learn from past troubleshooting sessions, identify recurring trends, and maintain complete transparency and accountability.
If you’re ready to explore how these advanced solutions can benefit your manufacturing environment, we invite you to view this short video and schedule a live consulting session with a Cisco industrial expert. Simply fill out this form to connect with us and discover tailored strategies to accelerate your network troubleshooting and performance with AI.
If you would like to experience the capabilities of AI troubleshooting for industrial networks firsthand, please scan the QR code below to sign up for our beta program or use this form.
