-
- News
- Books
Featured Books
- smt007 Magazine
Latest Issues
Current IssueProduction Software Integration
EMS companies need advanced software systems to thrive and compete. But these systems require significant effort to integrate and deploy. What is the reality, and how can we make it easier for everyone?
Spotlight on India
We invite you on a virtual tour of India’s thriving ecosystem, guided by the Global Electronics Association’s India office staff, who share their insights into the region’s growth and opportunities.
Supply Chain Strategies
A successful brand is built on strong customer relationships—anchored by a well-orchestrated supply chain at its core. This month, we look at how managing your supply chain directly influences customer perception.
- Articles
- Columns
- Links
- Media kit
||| MENU - smt007 Magazine
HPE Accelerates Self-driving Network Operations with New Mist Agentic AI-native Innovations
August 26, 2025 | BUSINESS WIREEstimated reading time: 3 minutes
HPE announced major innovations to its HPE Juniper Networking portfolio, advancing its AI-native Mist platform to deliver agentic AIOps through more autonomous, intelligent and proactive network operations. New enhancements include agentic AI-powered troubleshooting, expanded visibility and control of self-driving actions, a generalized Large Experience Model (LEM) and new AIOps features for data centers—designed to reduce IT complexity and assure exceptional user experiences from client to cloud.
These new capabilities bolster GreenLake Intelligence, HPE’s next-generation approach to autonomous IT and agentic AIOps, which deploys specialized AI agents within a multi-layered IT architecture. This enables real-time problem-solving, proactive optimization and smarter decision-making across networking, storage and compute. The agentic AI capabilities within Juniper Mist shift IT from reactive to proactive management, laying the groundwork for significant improvements in performance and efficiency.
“Today’s networks must do more than connect—they must understand, adapt and act,” said Rami Rahim, EVP, president and general manager, HPE Networking. “With these new digital experience twin and agentic AI capabilities in Juniper Mist, we continue to turn the network into a proactive partner for IT, capable of solving problems before they impact users. This is a major leap toward truly self-driving operations, helping our customers simplify complexity, reduce costs, and deliver exceptional digital experiences at scale.”
Agentic AI: Accelerating self-driving operations
HPE Juniper Networking has helped lead the transition to cloud-native, AI-native self-driving operations over the past decade with a unique focus on assuring user experiences from client to cloud. Marvis AI analyzes telemetry across the wired, wireless, WAN and data center domains, and creates automated workflows to simplify operations and lower costs. AI-driven support leverages trouble ticket data to continually train and increase the efficacy of the Marvis AI engine. Plus, a 100 percent API-driven model works with external systems and applications, like Zoom, Teams and ServiceNow to quickly identify and fix the root cause of problems.
Building on these core foundational elements for agentic AI, the latest innovations to the Mist platform bring even more automation insight and assurance to customers and partners:
Enhanced conversational capabilities. The Marvis AI assistant has augmented conversational capabilities that facilitate real-time troubleshooting. By leveraging an agentic AI framework, customized insight is provided with self-driving agents that collaborate across the wired, wireless, WAN, client and application domains.
Expanded Self-Driving Actions. The Marvis Actions dashboard now supports the autonomous remediation of more network issues, including misconfigured ports, capacity issues and non-compliant hardware—with full IT oversight.
Generalized Large Experience Model (LEM). LEM is an AI model unique to HPE Juniper Networking that analyzes billions of data points from applications like Zoom and Teams to easily troubleshoot the performance of common collaboration tools and predict future issues. Now enhanced with Marvis Minis—twins that simulate user experiences—LEM can predict future application experiences without real-time data from the applications themselves. This is fed into the Marvis AI engine where self-driving actions can be taken to optimize future performance, prior to users even being present.
AI for Data Center Operations. The Marvis AI Assistant for Data Center integrates with Apstra’s contextual graph database to deliver intelligent insights and lay the groundwork for autonomous service provisioning. Marvis Minis also extends to the data center for continuous service validation and application assurance pertinent to data center networks.
HPE is uniquely positioned to unlock exceptional customer value by applying AIOps and agentic AI across multi-vendor full stacks, integrating outcomes from networking, compute, storage, virtualization, containerization, and applications.
The latest Marvis data center capabilities complement HPE OpsRamp, an AIOps-powered IT operations management (ITOM) platform designed to simplify and automate the management of hybrid, multi-cloud, and on-premises IT environments with full-stack observability and advanced agentic workflows tailored for the modern data center.
“Networks are more distributed and complex than ever, yet 93 percent1 of organizations say they’re critical to business success. Operations teams need tools that speed resolution, boost efficiency and ensure user experience at scale. For over a decade, HPE Juniper Networking solutions have pioneered the use of AI in network operations, accelerating the journey toward self-driving networks,” said Bob Laliberte, principal analyst at theCUBE Research. “With its latest advances in agentic AI and GenAI, powered by Marvis, HPE is delivering real autonomous capabilities that enable predictive intervention, letting ops resolve issues before users even notice.”
These innovations build on HPE’s decade-long leadership in AI for networking, helping enterprises, cloud providers and telcos drive greater efficiency, reliability and user satisfaction.
Testimonial
"Advertising in PCB007 Magazine has been a great way to showcase our bare board testers to the right audience. The I-Connect007 team makes the process smooth and professional. We’re proud to be featured in such a trusted publication."
Klaus Koziol - atgSuggested Items
Yamaha Boosts Surface-Mount Programming Efficiency with Latest Software Release
10/14/2025 | Yamaha Robotics SMT SectionYamaha Robotics SMT Section has introduced enhanced software tools to accelerate new product introduction (NPI) using YSUP-PG, the program generator for the company’s surface-mounters and inspection systems.
Western Digital Opens Expanded System Integration Test Lab to Accelerate Innovation in the AI and Cloud Era
10/14/2025 | BUSINESS WIREWestern Digital, the backbone of the AI-driven data economy, announced the opening of its expanded System Integration and Test (SIT) Lab, a state-of-the-art 25,600 square foot facility designed to accelerate customer success and unlock faster time to value.
Wiley Launches Interoperable Platform to Power Scientific Discovery in World's Leading AI Technologies
10/14/2025 | BUSINESS WIREWiley, a global leader in authoritative content and research intelligence, announced the launch of Wiley AI Gateway, the industry's first AI-native research intelligence platform that provides researchers access to trusted content from world-leading scholarly publishers through a single endpoint.
Momentus Signs $15 Million Global Agreement with Solstar Space
10/14/2025 | BUSINESS WIREMomentus Inc., a commercial space firm specializing in satellite solutions and in-space infrastructure, announced a three-year reciprocal services agreement with Solstar Space (Solstar).
AI Storage Demand Accelerates HDD Replacement as NAND Flash Suppliers Shift Toward High-Capacity Nearline SSDs
10/14/2025 | TrendForceTrendForce’s latest investigations reveal that the surge in AI inference applications is creating a strong need for real-time data access and rapid processing of large data sets.