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Static network diagrams can only tell you so much. They may show how the network was designed, but they rarely reflect what is actually happening right now. For NOC engineers and network teams, that gap can lead to slower troubleshooting, missed issues, and too much manual investigation.In this hands-on NetBrain Essentials lab from our partner WWT, you’ll see how NetBrain helps teams move beyond outdated diagrams and operate with live network intelligence. The workshop walks through dynamic topology mapping, network discovery, intent-based automation, automated diagnostics, and scheduled compliance checks.You’ll learn how NetBrain can help discover devices, validate standards, troubleshoot incidents, and reduce manual work using repeatable workflows built on real network data. The lab also covers Quick Intent, scheduled dashboards, rule checks, and map-driven workflows that can help teams respond faster when issues happen.Whether you’re a NOC engineer, network administrator, or infrast

For network operations, that context needs to include live topology, device state, configurations, forwarding paths, Network Intents, diagnostics, and signals from the systems around the network.That is where NetBrain’s MCP Integration comes in.With support for Model Context Protocol, NetBrain connects its live network intelligence with the enterprise AI ecosystem your organization already uses. Instead of leaving AI tools to work from disconnected tickets, static diagrams, or incomplete documentation, MCP gives them access to real network context from NetBrain.NetBrain as an MCP ServerNetBrain can expose real-time network intelligence to external AI tools and custom LLMs that support MCP. This includes topology, device state, configurations, Golden Configs, detected drift, Network Intents, live forwarding paths, diagnostic context, and operational data.This allows external AI tools to reason with current network context instead of guessing from outdated or incomplete information.NetBr

Hi Support Team,As most of our customers is running in mission critical environment, sometime with air-gapped network, so using public AI LLM like OpenAI or ChatGPT etc. will be a challenge. I understand that NetBrain can also integrate with local deployed AI inferencing servers, however an enterprise grade inferencing server also costs very high.One possible option is to use AI API proxy servers like LiteLLM Proxy or Apache APISIX or Kong AI Gateway etc., the dual home proxy server could be located in restricted DMZ zone which has limited internet connection to Open AI platforms, while NetBrain can point the AI proxy to the API server.I am wondering if NetBrain has any similar deployment cases in your customer’s environment. It will be appreciated if you could provide some references or ideas for this type of deployment. Best Regards,Andong  

We’re excited to announce that the NetBrain Power User Training program has been refreshed to give customers more flexibility in how they build hands-on automation skills.The goal remains the same: help engineers become confident NetBrain Power Users who can automate diagnostics, assess networks at scale, and turn everyday troubleshooting steps into repeatable workflows.The updated program is designed to fit into network operations, not interrupt them. Power User Training is now offered as two independent, stand-alone instructor-led courses:NB210-ILT Building Diagnostic Runbooks NB220-ILT Network Assessment Automation WorkshopCustomers can take one course, take both, and choose the schedule that works best for them. Completing two consecutive training days is no longer required to earn credit.Participants will receive a certificate of completion at the end of each session. Customers who complete both NB210 and NB220 will also receive a Training50 License for one year, which includes 1

Agentic NetOps is creating a lot of momentum, but the real question for network teams is how to turn that vision into operational reality.Our latest blog breaks down what it takes to make AI agents trustworthy in real network environments, especially across multivendor networks, complex tool stacks, and teams managing constant change.A few key themes covered:Why trusted network context is critical for AI agents How topology, path, intent, and automation work together Where Agentic NetOps can support diagnosis, remediation, change validation, and compliance Why every organization’s path will look differentThe big takeaway: getting started matters. Agentic NetOps is not just about moving faster — it is about moving with the right context, control, and confidence.Read the full blog here: https://www.netbrain.com/blog/agentic-netops-the-real-work-ahead/

Most AI tools can talk about networks. NetBrain’s new AI Agents are built to work with the reality of yours.When an incident hits, engineers often have to jump between tickets, alerts, dashboards, runbooks, device data, and past tribal knowledge just to understand what is happening. Every handoff adds time. Every missing detail adds risk.With NetBrain 12.3a, AI Agents bring that context together. Built on NetBrain’s Context-Aware Digital Twin, Network Intents, and Agent Skills, they help teams move from manual investigation to guided diagnosis and action with the right network context in place.With AI Agents, teams can:Trigger deep diagnosis from tickets, alerts, or webhooks Run root cause analysis across your actual topology and operational data Ask natural-language questions about runbook results Validate change impact before pushing updates Capture senior engineer knowledge through reusable Agent SkillsThe result is not generic AI giving generic answers. It is agentic automation gro

Hi NetBrain Team,While we embrace the agentic AI capability brought by NetBrain, I am wondering if NetBrain complies to any AI standards such as ISO 42001 and ISO 42005 as below:ISO/IEC 42001 - The world’s first AI management system standard, providing valuable guidance for this rapidly changing field of technology. It addresses the unique challenges AI poses, such as ethical considerations, transparency, and continuous learning. For organizations, it sets out a structured way to manage risks and opportunities associated with AI, balancing innovation with governance.ISO/IEC 42005 - AI technologies are rapidly reshaping industries, economies and daily life — offering immense benefits, but also raising ethical, social and environmental concerns. ISO/IEC 42005 plays a crucial role in ensuring these impacts are responsibly addressed. By guiding organisations through structured impact assessments, it enables them to align AI development with values such as fairness, safety, and human-centre