Lingping Gao, Founder, CEO and Chairman of NetBrain Technologies – Interview Series

Lingping Gao, Founder, Chief Executive Officer, and Chairman of NetBrain Technologies, established the company in 2004 with a mission to simplify network management. Prior to founding NetBrain, Mr. Gao was the Chief Network Architect at Thomson Financial, where he managed the complexities of large enterprise networks and experienced the challenges of maintaining network performance.

Mr. Gao has experience within multiple areas of business, including management, engineering, and international business within the networking, software, and automotive industries. He holds a BS and a BA in Automotive Engineering from Tsinghua University and an MS in Engineering from Yale University.

Founded in 2004, NetBrain is the market leader for network automation. Its technology platform provides network engineers with end-to-end visibility across their hybrid environments while automating their tasks across IT workflows. Today, more than 2,400 of the world’s largest enterprises and managed services providers use NetBrain to automate network documentation, accelerate troubleshooting, and strengthen network security—while integrating with a rich ecosystem of partners. NetBrain is headquartered in Burlington, Massachusetts, with employees located across the United States and Canada, Germany, the United Kingdom, India, and China.

What inspired you to start NetBrain in 2004? Were there any specific challenges you faced at Thomson Financial that led you to see a gap in network management?

Early in my career, I spent five years as a network engineer at Thomson Financial. I remember getting pulled into the NOC on my way out of the building one day and spending all night helping troubleshoot a problem. It turns out that a Cisco switch had been upgraded and, it changed an important configuration. I remember wondering why it took so long, even though we had a whole team of smart engineers working on it. Surely, there must be a better way.

I realized that the reason troubleshooting was so difficult was a lack of data. During those long nights, engineers always ask the same few questions. What devices is my network made of? What does the baseline look like? Who made this, and why is it configured this way? I started NetBrain to make it easier to answer those questions.

I knew that if network data was more easily accessible, problems could be solved much more quickly. At that first job, you’d have to take a pager and a stack of network diagrams with you whenever you went on vacation! My vision for NetBrain was to give engineers fast and easy access to the network data they need to solve problems and a way to easily automate their tasks so they can be scaled up and done proactively instead of reactively. If we can catch and fix an issue before it affects an end-user then no one has to spend all night troubleshooting! Now, 20 years later, my vision is coming to fruition with NetBrain.

NetBrain pioneered no-code automation for network management. What was the thought process behind developing a no-code solution instead of traditional scripting or programming-based automation?

We wanted to solve the critical challenges facing network operations teams by lowering the barrier to adopting and using network automation while making it accessible to all levels of IT skillsets. We see automation as harnessing the expertise of network engineers to create automation, making the platform more useful and ingrained in the culture of network operations.

Script-based DIY network automation requires an engineer who knows coding such as Python and has a high level of networking and CLI knowledge. There are just not enough people with that particular skill set (and they’re expensive!). Projects that pair coders with network engineers end up producing relatively few automations that can only address a limited set of problems instead of stopping recurrences.

No-code automation makes it easy enough to deploy and scale automation across hybrid networks that it can be used for many problems – really any repetitive task. This leads to a change in mindset where NetOps and other IT teams will look to automation as their first solution for most problems, rather than a “last resort” reserved for only a few high-priority issues.

AI is increasingly shaping enterprise IT operations. How does AI enhance NetBrain’s network automation capabilities, particularly in troubleshooting and security enforcement?

AI-powered features were a major update in NetBrain’s most recent version, Next-Gen Release 12 (R12). One of these capabilities includes a GenAI LLM Co-Pilot, which can assess, orchestrate, and summarize network automation results using natural language. This AI Co-Pilot serves as a technology translator, enabling users to engage with no-code automation without the need for extensive training. We plan to continue expanding our AI capabilities in upcoming releases.

Our chatbot also functions as a virtual self-service tool, allowing operations and security teams to gather essential network information, thereby conserving valuable NetOps resources for more strategic activities. Users can pose questions in natural language, facilitating intuitive problem resolution and automating troubleshooting, change management, and assessment workflows.

Broadly, we see automation as the way to scale NetOps processes up to machine scale and AI as the way people can interact with those automations and the network overall. Together, they help bridge the knowledge gap within IT teams by capturing years of expert experience and making it available to engineers of all levels. Nearly every enterprise has an engineer who knows how to solve every networking issue. But what do you do when that person is on vacation, in a different country, or unavailable? Automation and AI help share that person’s knowledge with the rest of the IT team without requiring deep engineering and coding skills.

Can you walk us through how NetBrain's Digital Twin technology works and how it benefits organizations managing hybrid and multi-cloud networks?

NetBrain’s Digital Twin is a live model of a client’s multi-vendor networks that incorporates Intent, traffic forwarding, topology, and device data and supports no-code automation and dynamic maps. Unlike other digital twins, our intent layer houses a large collection of network configurations and service-level designs essential for effectively delivering any and all application requirements.

Another unique feature of our digital twin is that it provides real-time data across all layers, creating a more seamless, integrated system. Our customers are guaranteed live calculations of baseline and historical forwarding paths across multi-cloud and hybrid environments, as well as real-time topology and configurations of ​​traditional, virtual, and cloud-based components with our hybrid network. This, combined with Network Auto-Discovery, removes the necessity of manually creating static network maps and continuously updates every component of the connected multi-vendor network. The benefit of real-time data is the ability to work more efficiently internally without the worry of human error while working in a single device that supports the discovery of traditional, virtual, and cloud-based devices.

Many companies struggle with network downtime and troubleshooting. How does NetBrain’s AI-driven automation help reduce Mean Time to Repair (MTTR)?

NetBrain reduces MTTR by making troubleshooting more efficient and streamlined. Our AI-powered automation does this in several ways:

• Automatically create shareable incident summary dashboards.
• Conduct automated monitoring to detect troubleshooting issues before they affect a user
• Automatically conduct basic diagnostic tests whenever a ticket is opened
• Automatically close tickets
• Suggest remediations or possible causes for issues
• Give other IT teams easier access to network data

Even small time savings compound quickly at scale – one of our customers estimated that NetBrain saved them 16,000 troubleshooting hours in 2022 on about 63,000 tickets by automating a series of routine diagnostic tests. All in all, these capabilities make troubleshooting more efficient and reduce MTTR directly. They also enable level 1 engineers to solve more problems on their own and reduce escalations. This is often called “shifting left.” It frees up more time for senior engineers to spend on more difficult troubleshooting.

With the rise of hybrid cloud and SDN environments, how does NetBrain ensure end-to-end network observability and compliance across diverse infrastructures?

NetBrain ensures comprehensive network observability and compliance across hybrid cloud and SDN environments. We seamlessly support multi-cloud infrastructures like AWS, Microsoft Azure, and Google Cloud Platform, as well as traditional networks, SD-WAN, and SDN deployments.

Our platform enables clients to monitor cloud configuration changes in real time, automate continuous compliance assessments, and track evolving network configurations through an intuitive dashboard. Additionally, NetBrain provides multi-layered security observability, continuously evaluating cloud security across network, server, data, and application layers.

For SDN fabrics, NetBrain enhances visibility and makes SDN knowledge easily shareable across teams. By leveraging automation, organizations can scale SDN expertise while accelerating incident response. Our “Shift Left” approach proactively identifies root causes and resolves data center issues earlier in the network support lifecycle, significantly reducing MTTR.

How has NetBrain adapted to new cybersecurity challenges, especially with growing concerns about network security vulnerabilities?

Cyber threats are evolving rapidly, and traditional, reactive security approaches can no longer keep up. NetBrain has adapted by making network security proactive and automated, helping IT find misconfigurations and vulnerabilities before they can be exploited by attackers.

We offer Triple Defense Change Management, which validates every network change against security policies before, during, and after implementation. This ensures compliance and prevents unintended exposure. Our automation also continuously audits configurations, detects drift, and integrates with ITSM and security platforms to enforce best practices in real-time.

By leveraging AI and automation, NetBrain helps enterprises reduce human error, improve response times, and prevent security gaps, ensuring networks remain secure without adding operational overhead.Given NetBrain’s ability to eliminate outages and improve security enforcement, do you see a future where AI-driven networks become fully autonomous?

As AI-driven networks continue to advance, they are gradually replacing traditional networking methods. However, full autonomy remains a future possibility rather than an immediate reality.

AI plays a crucial role in streamlining NetOps by automating labor-intensive tasks. For example, identifying and cataloging IT infrastructure components—traditionally a time-consuming process—can now be significantly accelerated. With AI-powered Digital Twin technology, tasks like diagnosing a BGP tunnel issue can be reduced from two hours to just ten minutes. AI also helps bridge the knowledge gap within IT teams by capturing and distributing years of expert experience to engineers of all levels. When an issue arises, AI can not only assist with diagnosis but also recommend corrective actions, next steps, and follow-up procedures—dramatically reducing response times and enabling teams to resolve problems faster.

That said, AI still has limitations. While it can analyze data, suggest optimizations, and automate certain processes, it cannot make decisions, take accountability, or approve network changes without human oversight. Given the complexity and high stakes of enterprise networking, AI’s recommendations must be validated by engineers to prevent costly errors and downtime. Until AI can demonstrate greater reliability and contextual decision-making, fully autonomous networks will remain an aspiration rather than a reality.

NetBrain now serves over 2,500 enterprise customers, including one-third of Fortune 500 companies. What do you think has been the key to your success in scaling and gaining enterprise adoption?

Our success comes from fundamentally transforming how enterprises manage their networks. Traditional, reactive troubleshooting no longer scales, so we pioneered no-code network automation to make network operations proactive, not just reactive.

A key differentiator is our Digital Twin, which provides real-time visibility into the entire hybrid network, allowing teams to automate diagnostics, enforce golden engineering standards, and prevent outages before they happen. Combined with our ITSM-integrated troubleshooting and Triple Defense Change Management, enterprises can scale automation across even the most complex environments—without requiring an army of developers.

Ultimately, NetBrain makes automation accessible, enabling teams to resolve issues faster, enforce design intent, and keep business-critical applications running smoothly. Automation combined with accurate network mapping and deeper network insight lets us solve many NetOps challenges without additional overhead.

Looking ahead five years, how do you see the landscape of network automation evolving, and what role do you envision NetBrain playing in shaping the future of AI-driven network operations?

Over the next five years, network automation will move beyond scripted tasks and reactive troubleshooting to AI-driven, intent-based automation that dynamically adapts to changing network conditions. The days of manual diagnostics and fragmented tools are numbered — automation will be the backbone of network operations, ensuring resilience, security, and agility at scale.

AI will make that automation accessible and lower the barrier to usability at all levels in operations. It will make it easier to obtain and tailor network data into digestible and meaningful information so teams can reduce risk and gain efficiencies faster.

NetBrain is at the forefront of this evolution. Our Digital Twin provides a live model of the network, allowing AI to understand its design intent and enforce it proactively. We are pioneering GenAI-driven troubleshooting, self-healing networks, and deeper ITSM integrations so enterprises can shift from manual intervention to fully autonomous operations. Our vision is simple: make network automation intuitive, scalable, and indispensable — turning every engineer into an automation expert without requiring them to code.

In the next few years, AI-driven network operations won’t be a luxury, it will be a necessity. NetBrain is leading that charge, ensuring enterprises stay ahead of complexity while keeping networks secure, compliant, and always available.

Thank you for the great interview, readers who wish to learn more should visit NetBrain.