Lingping Gao, Founder, Chief Executive Officer, and Chairman of NetBrain Technologies, established the corporate 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 huge enterprise networks and experienced the challenges of maintaining network performance.
Mr. Gao has experience inside multiple areas of business, including management, engineering, and international business throughout 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, greater than 2,400 of the world’s largest enterprises and managed services providers use NetBrain to automate network documentation, speed up troubleshooting, and strengthen network security—while integrating with a wealthy ecosystem of partners. NetBrain is headquartered in Burlington, Massachusetts, with employees positioned across america and Canada, Germany, the UK, India, and China.
What inspired you to start out NetBrain in 2004? Were there any specific challenges you faced at Thomson Financial that led you to see a spot in network management?
Early in my profession, I spent five years as a network engineer at Thomson Financial. I remember getting pulled into the NOC on my way out of the constructing someday and spending all night helping troubleshoot an issue. It seems that a Cisco switch had been upgraded and, it modified a vital configuration. I remember wondering why it took so long, although we had a complete team of smart engineers working on it. Surely, there have to be a greater way.
I spotted that the explanation troubleshooting was so difficult was a scarcity of information. During those long nights, engineers at all times ask the identical few questions. What devices is my network product of? What does the baseline appear like? Who made this, and why is it configured this fashion? I began NetBrain to make it easier to reply those questions.
I knew that if network data was more easily accessible, problems may very well be solved way more quickly. At that first job, you’d must take a pager and a stack of network diagrams with you each time you went on vacation! My vision for NetBrain was to provide engineers fast and easy accessibility to the network data they need to resolve problems and a technique to easily automate their tasks in order that they could be scaled up and done proactively as an alternative of reactively. If we will catch and fix a problem before it affects an end-user then nobody 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 as an alternative of traditional scripting or programming-based automation?
We wanted to resolve 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 within the culture of network operations.
Script-based DIY network automation requires an engineer who knows coding comparable to Python and has a high level of networking and CLI knowledge. There are only not enough individuals with that individual skill set (and so they’re expensive!). Projects that pair coders with network engineers find yourself producing relatively few automations that may only address a limited set of problems as an alternative of stopping recurrences.
No-code automation makes it easy enough to deploy and scale automation across hybrid networks that it will probably be used for a lot of problems – really any repetitive task. This results in a change in mindset where NetOps and other IT teams will look to automation as their first solution for many problems, slightly than a “last resort” reserved for under a number of 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 serious update in NetBrain’s most up-to-date version, Next-Gen Release 12 (R12). One in every of these capabilities features a GenAI LLM Co-Pilot, which might assess, orchestrate, and summarize network automation results using natural language. This AI Co-Pilot serves as a technology translator, enabling users to interact with no-code automation without the necessity for extensive training. We plan to proceed expanding our AI capabilities in upcoming releases.
Our chatbot also functions as a virtual self-service tool, allowing operations and security teams to collect essential network information, thereby conserving priceless 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 because the technique to scale NetOps processes as much as machine scale and AI as the best way people can interact with those automations and the network overall. Together, they assist bridge the knowledge gap inside 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 the right way to solve every networking issue. But what do you do when that person is on vacation, in a unique country, or unavailable? Automation and AI help share that person’s knowledge with the remainder of the IT team without requiring deep engineering and coding skills.
Are you able to walk us through how NetBrain’s Digital Twin technology works and the way it advantages organizations managing hybrid and multi-cloud networks?
NetBrain’s Digital Twin is a live model of a client’s multi-vendor networks that comes with Intent, traffic forwarding, topology, and device data and supports no-code automation and dynamic maps. Unlike other digital twins, our intent layer houses a big collection of network configurations and service-level designs essential for effectively delivering any and all application requirements.
One other unique feature of our digital twin is that it provides real-time data across all layers, making a more seamless, integrated system. Our customers are guaranteed live calculations of baseline and historical forwarding paths across multi-cloud and hybrid environments, in addition to real-time topology and configurations of traditional, virtual, and cloud-based components with our hybrid network. This, combined with Network Auto-Discovery, removes the need of manually creating static network maps and constantly updates every component of the connected multi-vendor network. The good thing about real-time data is the flexibility to work more efficiently internally without the concern of human error while working in a single device that supports the invention of traditional, virtual, and cloud-based devices.
Many corporations 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:
- Mechanically create shareable incident summary dashboards.
- Conduct automated monitoring to detect troubleshooting issues before they affect a user
- Mechanically conduct basic diagnostic tests each time a ticket is opened
- Mechanically 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 – certainly 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. Additionally they enable level 1 engineers to resolve more problems on their very own and reduce escalations. This is commonly called “shifting left.” It frees up more time for senior engineers to spend on harder 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, in addition to traditional networks, SD-WAN, and SDN deployments.
Our platform enables clients to watch cloud configuration changes in real time, automate continuous compliance assessments, and track evolving network configurations through an intuitive dashboard. Moreover, NetBrain provides multi-layered security observability, constantly 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 within the network support lifecycle, significantly reducing MTTR.
How has NetBrain adapted to latest cybersecurity challenges, especially with growing concerns about network security vulnerabilities?
Cyber threats are evolving rapidly, and traditional, reactive security approaches can not sustain. NetBrain has adapted by making network security proactive and automatic, helping IT find misconfigurations and vulnerabilities before they could be exploited by attackers.
We provide 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 constantly audits configurations, detects drift, and integrates with ITSM and security platforms to implement best practices in real-time.
By leveraging AI and automation, NetBrain helps enterprises reduce human error, improve response times, and forestall 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 change into fully autonomous?
As AI-driven networks proceed to advance, they’re step by step replacing traditional networking methods. Nonetheless, full autonomy stays a future possibility slightly than a direct reality.
AI plays an important role in streamlining NetOps by automating labor-intensive tasks. For instance, 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 could be reduced from two hours to only ten minutes. AI also helps bridge the knowledge gap inside IT teams by capturing and distributing years of expert experience to engineers of all levels. When a problem arises, AI cannot only assist with diagnosis but additionally 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 will probably 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 have to be validated by engineers to stop costly errors and downtime. Until AI can reveal greater reliability and contextual decision-making, fully autonomous networks will remain an aspiration slightly than a reality.
NetBrain now serves over 2,500 enterprise customers, including one-third of Fortune 500 corporations. What do you’re thinking that has been the important thing to your success in scaling and gaining enterprise adoption?
Our success comes from fundamentally transforming how enterprises manage their networks. Traditional, reactive troubleshooting not scales, so we pioneered no-code network automation to make network operations proactive, not only reactive.
A key differentiator is our Digital Twin, which provides real-time visibility into all the hybrid network, allowing teams to automate diagnostics, implement golden engineering standards, and forestall outages before they occur. Combined with our ITSM-integrated troubleshooting and Triple Defense Change Management, enterprises can scale automation across even probably the most complex environments—without requiring a military of developers.
Ultimately, NetBrain makes automation accessible, enabling teams to resolve issues faster, implement design intent, and keep business-critical applications running easily. 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 long run of AI-driven network operations?
Over the following 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 times of manual diagnostics and fragmented tools are numbered — automation might 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 in any respect levels in operations. It’ll make it easier to acquire and tailor network data into digestible and meaningful information so teams can reduce risk and gain efficiencies faster.
NetBrain is on the forefront of this evolution. Our Digital Twin provides a live model of the network, allowing AI to know its design intent and implement it proactively. We’re pioneering GenAI-driven troubleshooting, self-healing networks, and deeper ITSM integrations so enterprises can shift from manual intervention to completely autonomous operations. Our vision is straightforward: make network automation intuitive, scalable, and indispensable — turning every engineer into an automation expert without requiring them to code.
In the following few years, AI-driven network operations won’t be a luxury, it’s going to be a necessity. NetBrain is leading that charge, ensuring enterprises stay ahead of complexity while keeping networks secure, compliant, and at all times available.
