Juniper Networks Inc. is harnessing the power of AI-driven network management to transform network operations and establish a new standard in the industry.

In July, the company, which just celebrated its 15^th anniversary on the New York Stock Exchange, highlighted its commitment to AI innovation with the launch of its Ops4AI Lab, a multi-vendor facility designed to validate end-to-end automated AI data center solutions. This lab is just one part of Juniper’s broader initiative to continually enhance its AI-Native Networking Platform, further solidifying its role as a key player in the growing enterprise AI community. With these advancements, Juniper is not just keeping pace with technological change; it’s setting the standard for what modern networking can achieve.

TheCUBE is live on set at our CUBE East studios, on the floor of the NYSE, during the Juniper Networks AI-Native NOW event.

“AI is becoming the foundation for modern networks, enabling us to automate and simplify everything from deployment to operations, creating a more efficient and resilient infrastructure that meets the demands of today’s digital world,” according to Praveen Jain, senior vice president and general manager of AI clusters and cloud-ready data center at Juniper Networks, who spoke to theCUBE.

During the recent Juniper Networks AI-Native NOW event — during theCUBE’s inaugural broadcast from our CUBE East studios on the floor of the New York Stock Exchange — theCUBE, SiliconANGLE Media’s livestreaming studio, captured insights on how Juniper uses AI-native innovation to evolve AI-driven network management and operations. Join theCUBE Research’s John Furrier, executive analyst, and Bob Laliberte, principal analyst, as they talk with Juniper leaders and its customers, discussing AI-native networks, the Juniper-MIST AI partnership and more. (* Disclosure below.)

Here are three key insights you may have missed from the event:

1. Predictive, self-healing intelligence removes traditional barriers to AI-native network management, enabling seamless and reliable enterprise connectivity.

As enterprises strive to enhance connectivity and operational efficiency, AI-native networking is emerging as a critical enabler of seamless, reliable and user-centric network experiences. Juniper delivers groundbreaking solutions integrating advanced AI technologies to ease adoption and deliver next-generation networking solutions, according to Manoj Leelanivas, chief operating officer at Juniper.

Juniper’s AI-native networking platform focuses on surpassing traditional connectivity to deliver a superior user experience, Leelanivas pointed out. The platform uses extensive telemetry data collected over eight years to simplify network operations and provide end users with a superior and reliable experience.

“Networking has to be all about the experience … the AI-Native network is all about providing that,” Leelanivas told theCUBE. “We have this amazing cloud-native platform, which has been using the telemetry, running our AI engine on top of it. We are almost at a point where the network is almost self-healing — 80 to 90% of the problems are corrected by our Marvis AI engine.”

Juniper’s Manoj Leelanivas talks with theCUBE Research’s Bob Laliberte about why an AI-native network is a game-changer in today’s computing environment.

Juniper’s recently announced blueprint is designed to minimize the complexity of AI adoption and integration by offering a structured approach that accelerates deployment and adoption, according to Leelanivas. The blueprint includes curated programs and training to help organizations quickly achieve AI comfort and operationalize AI-driven network management, delivering much higher value compared to other solutions. To get organizations up and running quickly, the company has simplified the adoption phase, from testing to procuring to deploying to operations, according to Leelanivas.

“We are able to deliver almost nine times the value compared to anything else out in the industry. We are really creating a self-driving network that is very easy to adopt,” he said.

Juniper also offers flexible enterprise agreements and its innovative Marvis Minis, a digital twin for networks, to tailor network management to specific needs, according to Leelanivas. This solution, which allows organizations to model and preemptively address network issues, ensures impeccable execution of critical operations such as major video conferences.

“You have the ability to do these digital twins across the network … an amazing new invention which further amplifies our focus on the experience-first network,” Leelanivas said. “More importantly, it actually simplifies the adoption curve, easing the adoption curve for our customers.”

Here’s the complete video interview with Leelanivas:

2. Juniper’s advanced Ethernet capabilities overcome the challenges of AI-driven network management, providing a simplified, high-performance network infrastructure.

AI applications, particularly those involving GPU-driven workloads, require networking infrastructures that efficiently support extremely high bandwidth demands and handle congestion. Traditional methods of simply increasing bandwidth no longer suffice, making it essential to develop networks that can automatically manage and optimize traffic.

Ethernet remains a cornerstone for AI network infrastructures because it’s cost-efficient and familiar to most organizations, according to Juniper’s Jain. The company, recently acquired by Hewlett Packard Enterprise, further enhances Ethernet’s value by integrating advanced capabilities that help ensure high performance and reliability for AI workloads. Organizations can use these enhancements with their existing skills and infrastructure while achieving the high-level performance modern AI environments require. This integration highlights the importance of AI-driven network management in improving infrastructure.

“Ethernet always wins,” Jain told theCUBE. “There’s economics of Ethernet, there’s a familiarity of Ethernet … we are adding some Ultra Ethernet capabilities into this new network, but you’re familiar, so it’s easy to operate that.”

Juniper’s Praveen Jain and theCUBE Research’s Bob Laliberte talk about AI networking solutions and how Juniper is meeting the demands of the AI era.

Juniper has extended its AI-native solutions, initially developed for simpler network operations, to manage the complexities of AI-driven data centers. Organizations can automate and simplify AI workload management by applying the company’s Marvis and MIST [AI] technologies to the data center environment, reducing the need for extensive manual intervention.

“We have taken the same technology and applied it to the data center,” Jain said. “So, same simplification, same trouble ticket reduction in data center … now we are applying it to a networking for [an] AI solution.”

Juniper uses its Juniper Validated Designs approach, providing a pre-tested, integrated ecosystem that includes networking, GPUs, storage and other critical elements, Jain noted. Additionally, Juniper’s lab environment allows customers to test their AI workloads in a controlled setting, ensuring the deployed solutions perform effectively in real-world scenarios.

“It’s all about [the] entire ecosystem tested together,” Jain said. “Not only did we build our network, but also, we used that network to train the workloads. We brought in Nvidia GPUs … ecosystem partners like WEKA storage … we brought in compute, we brought in other elements all together.”

Here’s the complete video interview with Jain:

3. AI-driven network management enhances reliability and user experience across sectors, empowering companies to shift from reactive problem-solving to strategic innovation.

As organizations across industries continue to rely on advanced networking solutions, AI-driven technology has become increasingly integral to ensuring seamless operations and first-rate user experiences. Dartmouth College and SiriusXM Radio Inc. provide compelling examples of how AI, mainly through Juniper’s Mist AI platform, innovates AI-driven network management, reduces support demands and enables strategic innovation.

Driven by poor connectivity and design and a bad user experience, Dartmouth College became an early adopter of Mist AI and revolutionized the school’s networking infrastructure, according to Bryan Ward (pictured, left), lead infrastructure engineer at Dartmouth College. The school has dramatically improved network management and enhanced the user experience for network operators and campus users alike.

“Marvis, the Mist [AI] virtual network assistant, is my first go-to tool whenever I have to log into the system, look at data, troubleshoot issues or try to be proactive,” Ward told theCUBE. “It has sped up my time to resolution and my time to design by so much. I could do the job myself in hours; Marvis can do it in seconds.”

Dartmouth’s advancements highlight the importance of a user-centered approach in AI-native networking, according to Jean English (pictured, center), chief marketing officer at Juniper. She noted, “… a great [user] experience that was really the forefront of the thinking of AI-native networking.”

Juniper’s Sudheer Matta and SiriusXM’s Jonathan Orlando talk about how Mist AI and SiriusXM’s collaboration with Juniper drive digital transformation.

Similarly, SiriusXM Radio Inc.’s integration of advanced technologies, including the Mist AI platform, has transformed its network operations, especially in high-stakes environments such as studio facilities, where reliability is paramount, according to Jonathan Orlando, vice president of network engineering at SiriusXM.

“Typically, you have your users who would complain about a wireless issue,” Orlando told theCUBE. “These are talents … celebrities and musicians that come into our office. So you definitely don’t want to make them upset. You want to make sure that they’re happy and everything is working as the production needs are required.”

As a result of Mist AI’s automation and simplicity features, both Dartmouth and SiriusXM have significantly reduced their number of IT support requests, freeing their teams to focus on higher-value strategic projects. This shift has created opportunities to explore new services and initiatives that directly contribute to institutional goals, such as sustainability efforts at Dartmouth and innovation in broadcast environments at SiriusXM.

“A significant decrease in reports of issues when it comes to the wireless environment, right?” Orlando affirmed. “The flexibility that it gives us to set up our … events environments … significantly reduced our IT support requests over time.”

Building on these operational improvements, Sudheer Matta, senior VP of product management at Juniper, highlighted the broader implications of AI in networking across various industries. AI is not just a tool, but a powerful force driving digital transformation, optimizing IT resources and shifting organizations from reactive to proactive networking management. This shift allows organizations to create better digital experiences for their users, making the network a critical part of the overall business strategy.

“The network as a platform is the outcome we see in retail, in healthcare, in higher ed, in enterprise,” Matta said. “The fastest deployment, fewest tickets, and a digital platform … enables you to do digital experiences indoors as well. With that, the need for AI to help drive that forward — that’s awesome as well.”

Here’s the complete video interview with Ward and English:

To watch more of theCUBE’s coverage of this event, here’s our complete event video playlist:

(* Disclosure: TheCUBE is a paid media partner for the Juniper Networks AI-Native NOW event. Neither Juniper Networks Inc., the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Image: SiliconANGLE