New AI-powered mobihome service gives customers stronger WiFi, advanced protection and greater control at no additional cost
PALO ALTO, Calif. and ULAANBAATAR, Mongolia — September 9, 2026 — Plume Design, Inc. (“Plume”), the award-winning global subscriber experience platform serving more than 450 Internet Service Providers (ISPs) across 60 countries, today announced that Mongolian broadband provider Mobinet is deploying the Plume Platform to power its mobihome broadband service.
The new service gives Mobinet customers access to AI-optimized WiFi, advanced cybersecurity protection, parental controls and real-time home network management through an intuitive mobile app. The Plume Platform continuously learns and adapts to each household, helping deliver stronger WiFi coverage, more reliable connectivity and a safer online experience.
“At Mobinet, we believe customers deserve more than fast internet speeds,” said Mr. Bat-Erdene Tuvd, Chief Technology Officer of Mobinet. “By partnering with Plume, we are bringing leading global technology to Mongolia that helps our customers enjoy better WiFi, stronger security and greater control of their digital lives. Just as importantly, it enables us to provide faster support and a better overall customer experience without increasing costs for our subscribers.”
As part of its commitment to customer satisfaction, Mobinet is introducing these advanced capabilities to subscribers without additional monthly charges, bringing world-class connected-home technology to Mongolian households.
“Mobinet understands that customer experience is the true differentiator in today’s broadband market,” said Chris Griffiths, Chief Technology Officer of Plume. “We are proud that after an extensive evaluation process, Mobinet selected the Plume Platform because of its unique ability to deliver smarter, safer and more reliable connectivity to households across Mongolia in a single unified solution.”
The Plume Platform enables Mobinet to provide faster and more proactive customer support. With greater visibility into home network performance, Mobinet can identify and resolve many issues remotely, reducing service interruptions, minimizing technician visits and ensuring smoother complaint handling.
Powered by data from approximately 600 million connected devices worldwide, the Plume Platform continuously optimizes performance, protects connected devices and helps service providers proactively address network issues before they impact customers.
With mobihome powered by Plume, Mobinet is setting a new standard for broadband service in Mongolia by combining high-speed fiber connectivity with AI-driven WiFi optimization, cybersecurity protection and proactive customer care.
The Mobinet deployment reinforces Plume’s continued expansion across the Asia-Pacific region and underscores the platform’s ability to serve ISPs of every size and market position. Plume’s cloud-native, software-only architecture works across CPE hardware, any cloud provider and any operating system, allowing Mobinet to maintain full control of its technology decisions without vendor lock-in. The platform’s containerized design enables seamless software updates and rapid deployment of new capabilities without disrupting subscriber service.
About Mobinet
Mobinet is a leading Mongolian information and communications technology company delivering reliable internet connectivity, digital infrastructure, and enterprise ICT solutions. We provide high-speed fiber internet, dedicated business networks, cloud and data-center services, IP telephony, VPN, cybersecurity, and managed IT solutions. By combining robust network infrastructure with expert technical support, MobiNet helps households, businesses, and public organizations stay connected, operate efficiently, and accelerate their digital transformation.
About Plume
Plume created the first managed WiFi platform for Internet Service Providers (ISPs) in 2016, enabling the company to scale across the globe and expand into managing the entire subscriber experience, including approximately 600 million connected devices, in 50 million homes, on behalf of more than 450 ISPs, across 60 countries. By integrating managed WiFi, cybersecurity and customer care, Plume created the first open, hardware-agnostic SaaS Subscriber Experience Platform for ISPs. Powered by an unmatched global dataset and AI optimization, the Plume Platform builds subscriber confidence through improved WiFi experiences, seamless new service implementation and proactive customer care. Plume’s open-source framework OpenSync® is pre-integrated and supported on the leading silicon, CPE and platform SDKs, and supports leading industry standards like RDK-B and prplWave. Discover more at www.plume.com.
As an Official Technology Partner, Cisco’s Industry-Leading Solutions Will Modernize the University’s Infrastructure to Meet the Demands of Higher Education in the AI Era
SAN JOSE, Calif., and SOUTH BEND, Ind. — September 22, 2026 — Cisco (NASDAQ: CSCO) and Notre Dame Athletics today announced a multi-year partnership to modernize the University of Notre Dame’s network, delivering advanced connectivity, resiliency and operational efficiency powered by Cisco’s latest networking technologies. The collaboration reflects Notre Dame’s commitment to establishing a future-ready learning environment and the importance of a network able to support the demands of higher education in the AI era.
As AI continues to impact all facets of higher education—from research to classroom learning to student life—the demands placed on the network continue to grow exponentially. Notre Dame is investing in a network able to support current and future device loads and AI applications, reflecting the University’s status as a top-tier academic institution and its commitment to being at the forefront of technological innovation for the next decade and beyond.
“Modernizing our campus network is about far more than just replacing hardware; it is about building a foundation for the future of learning, research and campus life. By eliminating years of technical debt and consolidating our infrastructure onto a unified Cisco multi-gigabit platform managed through Cisco Catalyst Center, we have transformed our operations,” said John Buysse, Senior Director Network & Telephony Services at the University of Notre Dame. “Our team now has the proactive, centralized visibility needed to deliver a seamless, secure and fast digital experience to our campus community.”
Cisco’s technology will directly enhance the daily campus experience. For students, this means a seamless, high-performance connectivity experience that supports bandwidth-intensive applications—from immersive virtual reality labs to real-time collaborative projects—ensuring they stay connected from the moment they step on campus. For faculty and staff, the modernized infrastructure provides the reliability needed for teaching and administrative efficiency, ensuring that digital resources are always available.
“In the dynamic world of higher education, speed is a requirement, not a luxury,” said Mike Witzman, Vice President, Public Sector Solutions Engineering at Cisco. “Together, Notre Dame and Cisco are doing more than just connecting a campus; we’re building an AI-ready foundation that will redefine the future of learning for generations of students, faculty and staff. Fast, seamless and reliable connectivity will transform the modern education and research experience, pushing the boundaries of what’s possible.”
The campus-wide deployment relies on Cisco Catalyst Center to automate and assure the end-to-end network. With nearly 1,000 new switches across the South Bend campus, the integration of Catalyst Center and zero touch deployment will allow for consistent configuration across the University’s digital footprint, which will be standardized on the Cisco Catalyst 9300x switch platform.
The partnership also includes utilization of Cisco Professional Services, which will provide ongoing support for the network and help the University to maximize their investment through custom expert guidance throughout the length of the partnership. Additionally, Cisco ThousandEyes will assure the delivery of seamless digital experiences across the campus by providing the University with visibility into every network that can impact performance, across both owned and unowned third-party environments, giving them unmatched insight into how everything is connecting.
This new collaboration with Notre Dame Athletics comes on the heels of Cisco’s recent partnership with Georgetown University to launch one of the largest deployments of Wi-Fi 7 in higher education, further cementing Cisco as the preferred partner of leading universities in the United States.
About Cisco
Cisco (NASDAQ: CSCO) is the worldwide technology leader that is revolutionizing the way organizations connect and protect in the AI era. For more than 40 years, Cisco has securely connected the world. With its industry leading AI-powered solutions and services, Cisco enables its customers, partners and communities to unlock innovation, enhance productivity and strengthen digital resilience. With purpose at its core, Cisco remains committed to creating a more connected and inclusive future for all. Discover more on The Newsroom and follow us on X at @Cisco.
Cisco and the Cisco logo are trademarks or registered trademarks of Cisco and/or its affiliates in the U.S. and other countries. A listing of Cisco’s trademarks can be found at http://www.cisco.com/go/trademarks. Third-party trademarks mentioned are the property of their respective owners. The use of the word ‘partner’ does not imply a partnership relationship between Cisco and any other company.
About Notre Dame Athletics
As it pertains to athletic and academic success, the University of Notre Dame has few peers across the nation. Sponsoring 26 varsity athletic programs, Notre Dame teams have won 38 national championships that span over 100 years of competitive excellence. The University’s first national title was earned by football in 1924, led by legendary head coach Knute Rockne. Notre Dame athletic teams have continued to claim noteworthy national championships recently, including back-to-back titles by men’s lacrosse in 2023 and 2024 and the fencing team earning its 16th team national title in 2026. The Fighting Irish football team also appeared in the 2025 College Football Playoff Championship Game. Notre Dame athletic teams have produced the third-most Academic All-Americans among Division I schools and Fighting Irish student-athletes have ranked first or second among Football Bowl Subdivision teams in the NCAA’s Graduation Success Rating for 18 straight years.
In nearly every conversation I have with networking teams at large enterprises, security comes up as a top priority, right alongside keeping the network running. The AI shift is raising the stakes on both.
Every AI agent and AI-powered experience depends on the network. At the same time, attackers are using AI to find and exploit vulnerabilities faster, distributed workloads create more paths that must be protected, and quantum-era risks are changing how organizations think about long-lived data. Compromised identities and workloads can open paths for lateral movement and amplify breach impact. Networking teams are being asked to assess risk and respond at machine speed without sacrificing availability.
The network has always been part of the attack surface. What’s changed is how much it matters. It’s the one layer that connects every identity and carries every flow across users, devices, workloads, applications, IoT and OT systems, and AI agents. Because it sees connections as they happen, the network can establish and sustain trust, enforce policy close to where traffic moves, and supply the telemetry NetOps and SecOps teams need to detect and respond faster without disrupting the experience. In this blog, we will examine why the network can no longer be passive transport—and how it can become an active security and enforcement layer.
Defense in depth has always assumed multiple layers so that no single failure is fatal. For years, networking teams were often asked to contribute VLANs, access control lists (ACLs), and perhaps a network admission control (NAC) deployment. That role no longer matches the risks networking teams face today.
Infrastructure risk is outpacing traditional protection. AI-accelerated exploitation is compressing remediation windows and increasing exposure before teams can patch. The answer isn’t to abandon patch discipline; it’s to know what you operate, prioritize the exposure that matters most, and apply validated runtime protection while permanent fixes move through change control. This same infrastructure must also become cryptographically agile. Data captured today may be exposed later, so organizations need a practical, phased path to post-quantum migration without wholesale replacement. Trust and security evidence must also remain continuously visible, so teams can support compliance without reconstructing it at audit time.
AI agents, distributed workloads, and quantum risks expand exposure, while lateral movement amplifies the impact of a breach. Networking teams need to understand what’s connecting, authorize least-privilege access, and limit reach wherever traffic moves. Visibility gaps put every experience at risk. Fragmented NetOps and SecOps tools delay root cause, coordinated action, and service restoration. Teams need shared operational context, governed automation, and end-to-end assurance so they can act quickly without breaking legitimate connectivity, performance, or the user experience.
You can assemble parts of a solution from point products: an overlay here, an appliance there, another agent, another console, another policy model. The result is often backhauled traffic, blind spots between tools, and teams reconciling different identities, policies, telemetry sources, and workflows.
What matters is how these pieces work together. The network is uniquely positioned to address these challenges. It connects identities wherever they work; carries the flows attackers try to use; and reaches across campus, branch, WAN, data center, cloud, internet, software as a service (SaaS), remote, and industrial environments. That makes it the right place to keep infrastructure protected and verifiable; limit reach and enforce policy close to where traffic moves; and supply the telemetry needed to strengthen detection, response, and assurance.
This is where Cisco is different. The Cisco secure networking reference architecture brings together networking, security, observability, data, and AI through a unified operating model, a common data platform powered by Cisco Data Fabric, and resilient infrastructure. Common Policy context shares trusted context across the architecture so connected policy engines can make consistent decisions, while extended integrations carry policy, telemetry, threat intelligence, and governed automation across Cisco and third-party environments.
Together, these platform layers keep infrastructure protected and verifiable; protect east-west traffic and workloads; secure the human and agentic workforce; and give teams the shared context to detect, respond, and verify outcomes. In other words, the network stops being passive transport and becomes an active defense layer.
Before building solutions, it’s worth being precise about the outcomes. Secure networking should reduce risk, limit disruption, and keep critical services secure and available. Cisco delivers this platform approach through three connected pillars: Trust the Infrastructure, Secure Every Flow, and Assure Every Experience.
These are not separate workstreams, but one connected design system. Trust the Infrastructure encompasses resilient architecture that stays protected, continuously proves trust, and is ready for post-quantum change. Secure Every Flow is where distributed protection, trusted identity, and machine-speed detection and response come together. Assure Every Experience describes a unified operating model across network and security operations where teams can verify outcomes, accelerate governed action, and make consistent policy decisions using shared context.
What ties the pillars together is how the platform layers work. Resilient infrastructure provides the trusted and available foundation. Cisco Data Fabric powers the common data platform connecting network, security, identity, application, experience, and third-party data. Common Policy context is defined and governed, then shared across the architecture so connected policy engines can make consistent decisions. Policy is enforced at the points closest to the traffic. Extended integrations carry policy, telemetry, shared context, and governed automation across Cisco and third-party environments.
For networking teams, this isn’t about becoming the security operations center (SOC). It’s about putting the infrastructure you already operate to work as an active security and enforcement layer. Here’s how I think about each pillar and what it means for the network operator.
Trust starts with the infrastructure itself. Attackers are moving faster, and a compromised switch or router can give them deep, persistent access that’s hard to spot. The outcome networking teams need is resilient infrastructure that stays protected, makes trust and security evidence continuously visible, and is ready for post-quantum change.
Keeping infrastructure protected means establishing trust at power-on and sustaining it through runtime. With Cisco secure networking, Splunk Exposure Analytics helps teams prioritize the exposure that matters most, while Cisco Live Protect provides validated runtime protection on supported platforms as permanent fixes move through change control.
Trust must also be easy to demonstrate. Platform integrity, software provenance, encryption, access policy, monitoring, and governed change evidence should remain visible so teams can support compliance without reconstructing everything at audit time. Finally, crypto-agile Media Access Control Security (MACsec) and Internet Protocol Security (IPsec), together with supported post-quantum capabilities, give teams a phased path to protecting long-lived data and adopting new algorithms without replacing the entire infrastructure at once.
In this model, networking teams can strengthen protection, demonstrate trust, and modernize cryptography through normal refresh and change cycles. Security becomes part of how the network operates, not another overlay to manage.
Most breaches don’t stop at the point of entry. They spread laterally through east-west traffic that centralized controls may never see.
The desired outcome is straightforward: make it harder for threats to move and easier for teams to reduce their impact. In addition to protecting east-west traffic and workloads by limiting reach and enforcing policy close to where traffic moves, it also means securing people and AI agents with trusted identity and least-privilege access, so each gets only the access needed.
When a threat is detected, the network should help teams respond just as quickly. Shared network and security telemetry, threat intelligence, and connected enforcement points give NetOps and SecOps teams the context to take governed, post-detection action at machine speed and scale; reduce threat impact; and accelerate recovery across campus, branch, data center, cloud, and remote environments.
You can’t secure what you can’t see, and you shouldn’t automate what you can’t verify. Networking teams need a shared operating view, a consistent way to act, and confidence that every action achieved its intended outcome. That means connecting operational and security context, turning insight into governed action with people in control, and making consistent policy decisions using the same trusted context.
Cisco Cloud Control brings inventory, topology, health, assurance, security, and operational context across connected Cisco domains into a unified operating experience. Cisco AI Canvas and Cisco AI Assistant help teams investigate faster and move from insight to governed action, with people in control. Splunk extends monitoring and analytics across Cisco and third-party environments, while ThousandEyes provides visibility across enterprise and third-party paths, including infrastructure you do not own.
Common Policy context is defined and governed to give connected policy engines the same trusted facts, so teams can make consistent decisions. Policy is then enforced at the points closest to the traffic. Together, these capabilities close the loop by verifying security, connectivity, performance, and the resulting digital experience.
The advantage of a platform approach is that you don’t have to address every challenge at once or treat each area as a separate architecture project. Start with the outcome that maps to your biggest concern: build infrastructure that stays protected, continuously proves trust, and is ready for post-quantum change; protect east-west traffic and workloads, secure the human and agentic workforce, and detect and respond at machine speed and scale to reduce threat impact and accelerate recovery; or give NetOps and SecOps teams a shared operating view, governed action, consistent policy decisions, and verified outcomes. As your priorities evolve, build on the infrastructure and tools already in place.
Wherever you begin, bring your hardest questions to the conversations that follow and put the network to work. Because the pillars share a unified operating model, a common data platform, and resilient infrastructure, progress in one area can strengthen the others.
The network is too important to remain passive. Make it one of the strongest, most adaptable layers of your defense without trading away availability, performance, or experience.
A product can pass every test in the lab and still fail in a customer’s hands, for a reason that has nothing to do with bad code, bad luck, or a faulty chip. It happens more often than most engineering teams realize, and almost every time, the real cause turns out to be the same thing.
Picture a device that runs Bluetooth, Wi-Fi, and an AI model, all built into one chip. In the lab, each of these was tested on its own, and each one performed exactly as the datasheet promised. The product shipped. Then customers started reporting dropped connections, batteries draining faster than expected, and the occasional unexplained reset.
Nobody could reproduce it reliably. The hardware checked out fine every time it was inspected. The firmware passed every review. And yet, in the field, the product simply did not behave the way it had in the lab.
Here is what was actually happening. Bluetooth, Wi-Fi, and the AI model were each managing their own power independently, the way radios have always done. Each one woke up, did its job, and went back to sleep, entirely on its own schedule, with no idea what the other two were doing at the same moment.
Most of the time, that was fine. But often, all three would wake up within the same few milliseconds, drawing power from the same shared battery supply at the same instant. When that happened, the battery couldn’t quite keep up, and the voltage dipped just enough to cause a dropped packet, a missed connection, or a reset that looked, from the outside, like it came from nowhere.
That is the entire problem, in one sentence: nobody had told the three of them to take turns.
A few years ago, this simply wasn’t an issue, because it wasn’t physically possible for it to be one. Wireless radios and AI processing usually lived on separate chips, each with its own power supply, completely unaware of the other’s existence. If one drew a spike of current, it had no effect on the other, because they weren’t sharing anything.
That has changed. Modern chips now combine Wi-Fi, Bluetooth, sometimes Thread or Zigbee as well, and a dedicated AI processor, typically an NPU, or Neural Processing Unit, built specifically to run AI models efficiently, all on a single piece of silicon.
Each part of that chip still has its own settings for when to sleep and when to wake, but all of them draw from the same underlying power supply. What looks, on a spec sheet, like several independent components is, in practice, one shared electrical system with several tenants who don’t talk to each other.
That is the shift that created this problem, and it has happened recently across almost every category of connected product.
Most people think the AI Model is the power hog. It may be the memory hog, but it is not the power hog people think. Here is something worth knowing before going further, because it changes where the real risk actually sits.
Engineering teams may assume the AI model is the power-hungry part of the system, since it is the newest and most computationally demanding piece. It usually is not. An analysis compared how much power each part of a typical device draws:
a) Running the AI model, on average: 10 to 100 microwatts
b) Sending a single Bluetooth transmission: 10 to 50 milliwatts, up to 5000 times more than the AI model
c) Sending a single Wi-Fi transmission: 200 to 1000 milliwatts or more, up to a million times more than the AI model
The radios, not the AI, are where almost all of the power goes. Which means a team that spends weeks trimming the AI model to save power is optimising the smallest number on the board, while the two components that actually drive battery life keep operating with no coordination between them at all.
If this were a rare edge case, it might not be worth an article. It isn’t rare, and it’s becoming common every year.
Chip makers are racing to put more of these components on a single die, because customers want smaller, cheaper, more capable products. One of our semiconductor partners, Synaptics, recently launched a chip that combines Wi-Fi, Bluetooth, and a dedicated AI processor on a single piece of silicon.
Another partner, NXP, has done something similar, pairing its processors with dedicated AI accelerators on the same chip. Every one of these announcements makes the underlying problem more common, because every one of them puts more shared tenants on the same electrical supply.
The chip makers can build better individual components. They cannot decide, from inside the silicon, whether a Wi-Fi transmission should wait two milliseconds for a Bluetooth connection to finish first. That decision has to be made by whoever builds the product, in software, because no chip on the market makes that call on its own.
Luckily, we have the privileged relationships to get our grubby little mits on these chips before the general public, so we can figure out the power management well in advance.
None of this shows up as a line item on a project budget. It shows up later, and it costs more the later it shows up.
i) It shows up as customer reviews complaining about battery life that doesn’t live up to marketing claims.
ii) It shows up as support tickets for dropped connections that engineering can never quite reproduce.
iii) It shows up as weeks, sometimes months, spent investigating a hardware issue that keeps mysteriously vanishing the moment a debugging tool gets attached, because the failure only happens under exact, unrepeatable timing conditions.
iv) And in the worst case, it shows up as an emergency firmware update, built under real pressure, months after launch, to fix a problem that a single design review would have caught before the product ever shipped.
Every one of those costs traces back to the same missing piece: nobody on the team ever decided who gets to draw power, and when.
The good news is that fixing this does not require new hardware, a redesigned board, or a more expensive chip. It requires one thing: a single policy, written once, owned by one team, that governs how every radio and the AI model share power across the whole product, rather than each one deciding for itself.
In most embedded systems, there is already a natural place for this policy to live: the software that schedules everything else the chip does. That scheduler already knows what is running and when. Teams simply need to extend it to also decide who gets power and when, instead of leaving that decision to each component individually. Zephyr, one of the most widely used platforms for this kind of work, already has the tools built in for exactly this. Many products never take advantage of those capabilities.
The most advanced version of this doesn’t just react after something asks for power. It predicts what is about to happen, based on the patterns it has already seen, and starts preparing power slightly before the request lands, rather than scrambling after it arrives. That single habit, planning ahead instead of reacting, is quietly becoming the difference between products that behave consistently and products that don’t.
Before your next product goes into production, put these questions to your team:
1. Is there one policy deciding how every radio and the AI model share power, or is it a free-for-all?
2. Was the power budget ever tested with all of them running at the same time, or only tested one at a time on a clean bench?
3. Do you actually know which part of the product is drawing the most power in real customer use, or is that still a guess based on the datasheet?
4. And who owns this decision today, checking that it still holds up every time the firmware changes?
If any of those answers come back uncertain, the gap already exists in your product. It is far cheaper to close now than after a customer finds it for you.
The chip makers keep building better individual radios, faster processors, and more efficient AI accelerators. None of that solves this problem, because the problem was never about any single component.
It is about whether anyone stipulated how those components share the one thing they all depend on. That decision does not belong to the chip. It belongs to the team building the product.
At embedUR, we help engineering teams design, validate, and optimize multi-radio, AI-enabled products, so they behave the same way in the field as they do on the bench.
If your product is heading toward launch, or if you’re trying to understand why a finished design behaves differently in customers’ hands than it did in your lab, talk to our engineering team. We can help you find these gaps before they turn into field failures.
If you enjoyed this post, make sure you catch the next related article also on multi-radio systems: Antenna Placement and Isolation in Multi-Radio Embedded Systems.
AUSTIN, Texas, Sept. 15, 2026 /PRNewswire/ — Silicon Labs (NASDAQ: SLAB), the leading innovator in low-power wireless connectivity, today announced the executive keynote lineup for its seventh annual Works With Summit 2026, an invitation-only gathering of customers, technology leaders and ecosystem partners.
The Technologies Shaping What’s Next
Silicon Labs President and CEO Matt Johnson will open the October 7 keynote at ACL Live at the Moody Theater, joined by Daniel Cooley, senior vice president and chief technology officer, and Manish Kothari, senior vice president of software development.
Together, they will share Silicon Labs’ perspective on the technology, AI tools and ecosystem collaboration required to scale the next generation of intelligent systems as connected devices become more capable and deeply integrated into homes, businesses and infrastructure.
During the keynote, Silicon Labs will unveil new products with new-to-industry performance and capabilities, giving attendees an early look at innovations designed to help advance the next generation of connected products.
“Works With brings together the customers, developers, partners, and innovators shaping the future of connected devices,” said Johnson. “The conversations taking place at the Summit directly contribute to helping turn new technology into industry-leading products and deployments. For leaders building the connected future, it is a must-attend event.”
The keynote will explore how advances in secure, intelligent wireless technology, edge AI and developer tools can help customers build, deploy and manage connected products more effectively. Attendees will also hear Silicon Labs’ perspective on the role of connectivity, power, security and ecosystem collaboration in supporting IoT at scale.
A Forum for the IoT Ecosystem
Works With Summit 2026 will take place October 6-7 across two distinctive downtown Austin venues: ACL Live at the Moody Theater and Silicon Labs’ lakeside headquarters. The invitation-only event will convene some of the industry’s most influential IoT innovators for executive keynotes, focused roundtable discussions, and hands-on technology showcases.
Attendees will explore the decisions shaping the next generation of connected products and deployments, including connectivity, batteries and power, security, Matter and Thread, sub-GHz technologies, Wi-SUN, Z-Wave, asset tracking and AI-enabled IoT development. A sponsor technology lab will provide opportunities to experience new solutions and demonstrations in person.
Together, the Summit will offer a setting for Silicon Labs and its ecosystem to exchange perspectives on how low-power wireless, edge intelligence, developer tools and enterprise practices can come together to support IoT at scale.
Attendance is by invitation only, and space is limited. Interested technology leaders can learn more and request an invitation at silabs.com/about-us/events/works-with-2026. Requests are reviewed by the Silicon Labs team, and submission does not guarantee attendance.
About Silicon Labs
Silicon Labs (NASDAQ: SLAB) is the leading innovator in low-power connectivity, building embedded technology that connects devices and improves lives. Merging cutting-edge technology into the world’s most highly integrated SoCs, Silicon Labs provides device makers with the solutions, support, and ecosystems needed to create advanced edge connectivity applications. Headquartered in Austin, Texas, Silicon Labs has operations in over sixteen countries and is the trusted partner for innovative solutions in smart home, industrial IoT, and smart cities markets. Learn more at https://www.silabs.com.
SOURCE Silicon Labs
The modern smart home includes dozens of connected devices like lights, thermostats, cameras, and speakers, all working together. But who is protecting the network that connects them all? Your router plays an important and invisible role behind the scenes.
The number of connected devices in our homes is growing rapidly, and every unprotected IoT device is an access point that can be exploited if your network isn’t secure. Network-level protection is essential to counter cybersecurity threats. Traditional antivirus software focuses on individual computers or phones, leaving smart home gadgets, gaming consoles, and other IoT devices exposed.
Strong network security works silently in the background as an always-on utility that helps keep sensitive information safer from phishing scams, identity theft, and more. NETGEAR provides internet access with peace of mind, and it all starts with a quality router.
NETGEAR wireless routers deliver powerful Armor Security and robust firmware to help keep your connected life safer.
True digital home network security doesn’t start with your internet service provider (ISP) or at the device; it starts at the network’s core operating system — the router. NETGEAR routers create a protective shield around every single connected device, both seen and unseen. The best smart home security is built into the router settings.
By securing the network with strong WiFi encryption, unique passwords, and NETGEAR Armor, you actively protect your home from unauthorized access.
NETGEAR routers are engineered with security as a core principle. They provide a foundational layer of protection through automatic updates and standards-based security to protect your system from cyberattacks. For comprehensive security, NETGEAR Armor offers advanced, network-wide threat blocking that works to safeguard every device, from your laptop to your smart doorbell, automatically and silently.
Antivirus software protects individual devices from viruses and malware, while router security helps safeguard the entire network by controlling unauthorized access, monitoring traffic, and preventing attacks before they can enter.
Router security is network perimeter protection—it helps protect the traffic entering and leaving your home network. NETGEAR Nighthawk Routers and Orbi Mesh Systems offer:
NETGEAR routers and WiFi mesh systems provide layered network security for your home network, guest network, and smart home IoT wireless network.
Layer 1 (Secure by Design): NETGEAR routers are secure out of the box with automatic firmware updates and the latest WiFi security standards.
Layer 2 (Network-Level Protection): The router is the single point of entry for internet traffic, making it the ideal place to stop threats. This protects devices that can’t run security software themselves (e.g., smart bulbs, thermostats).
Layer 3 (Expanded Peace of Mind): NETGEAR Armor elevates network protection. Key NETGEAR Armor benefits include:
Most smart home devices lack the ability to install security software, making them a prime target for malicious intruders. A secure router is one of the only practical way to protect them. NETGEAR network security runs seamlessly without slowing down your connections.
The Nighthawk App and Orbi App give you remote access for real-time visibility, instant alerts, and automatic protection.
The comprehensive NETGEAR product range includes some of the most advanced WiFi 7 routers on the planet, such as the Nighthawk RS700S Router and the amazing Orbi 970 Series Whole-Home Mesh System. They allow you to connect 200+ home WiFi network devices with multi-gigabit speeds, upstairs and downstairs, from the front door to the back yard.
The best WiFi routers and leading WiFi mesh systems are an investment in your connected lifestyle, whether you are a smart home enthusiast, a busy parent managing multiple devices, or a worker requiring remote access. NETGEAR is the digital gatekeeper for your home, so you can connect with confidence and enjoy total peace of mind.
When you connect laptops, smartphones, and smart home devices to a secure NETGEAR WiFi router, you help protect your entire digital life at the source.
All-new LinkRunner 100G – professional-grade performance and precision tool network engineers need to troubleshoot and upgrade critical 100G fiber links.
COLORADO SPRINGS, Colo., Sept. 9, 2026 – NetAlly today announced LinkRunner® 100G, a handheld tester built to validate and troubleshoot high-speed fiber links increasingly moving beyond data centers and into enterprise networks. With the press of a single button, LinkRunner 100G AutoTest tells a network technician whether a 100G link is healthy — and if it isn’t, exactly what’s wrong. At $8,999 plus an AllyCare Pro subscription, LinkRunner 100G delivers the professional-grade diagnostics network engineers expect from a 100G tester at a price built for enterprise IT.
“AI is driving a networking super-cycle, pushing higher-speed networks beyond the data center and into the enterprise,” said Jeff O’Mara, CEO of NetAlly. “Until today, the tools to support those networks were expensive and highly specialized for big telco providers. Enterprise IT is different. We built LinkRunner 100G to give enterprise network professionals the tool they need to deploy, fix, and upgrade these networks.”
As 25G, 40G, 50G, and 100G networks become more common in enterprise environments, IT teams are being asked to manage fiber networks that operate differently from the lower-speed connections they have traditionally supported. Troubleshooting networks running on twisted-pair copper up to 10G has been eased by rich automation specified by IEEE standards for auto-negotiation of speed, power, and polarity. None of this automation exists for 100G networks, resulting in brittle, hard-coded configurations. Vendors further complicate the space with proprietary and complex transceivers which modify encodings and bit rates to gain advantages in fiber efficiency and bandwidth.
LinkRunner 100G is designed specifically for these new challenges faced by network support teams, allowing technicians to run a full diagnostic at the push of a button, with no specialized fiber training required.
With LinkRunner 100G, network pros solve problems on 100G networks with simple, automated steps:
“Higher-speed fiber is quickly becoming part of the enterprise network, and IT teams need to be ready for it,” O’Mara said. “If you’re responsible for links above 10G, LinkRunner 100G belongs in your toolkit.”
LinkRunner 100G is handheld and battery-powered, so technicians can take it on any call, not just escalations. Results are translated into plain-language answers rather than error codes and can be uploaded to Link-Live, NetAlly’s collaboration and reporting platform, so a technician can share a full report instead of a screenshot.
LinkRunner 100G is now available for $8,999, plus an AllyCare Pro subscription, through NetAlly’s network of authorized resellers. For full details, visit www.netally.com.
What AI Edge Means for Wireless Devices
A few days ago, I was sitting in a far corner of my home, upstairs, trying to build a small tool of my own using Claude. Nothing fancy — just me, a laptop, and an AI model doing the heavy lifting. Because I live in a multi-level house, I’ve got a mesh Wi-Fi system to avoid dead zones. I should’ve been fine, right?
Except I wasn’t. The model kept telling me it was about to give me a fast response. And then… nothing. Minutes went by before my query even landed on the system, and minutes more before the response came back.
Same story a few days later, uploading a video to my YouTube channel. I was excited to get it up, and instead I sat there watching a progress bar crawl. Twice, in two completely different situations, the thing standing between me and a good experience wasn’t the AI. It was my Wi-Fi.
That’s the thing nobody really addresses when they talk about “AI at the Edge.” Everyone’s excited about the models — how big they are, how smart they are, how fast they can reason. But almost nobody’s talking about the fact that all that intelligence has to travel through a wireless link before it ever reaches you. And that link is, frankly, the weakest part of the chain.
So, What Does “AI Edge” Actually Mean?
Let’s back up, because “AI at the edge” sounds like one of those terms that gets thrown around a lot without anyone really explaining it. Here’s the simple version: it means AI processing that happens on devices close to you — your smartphone, a smart hub in your home, or your Wi-Fi access point — instead of way off in some data center.
AI in the network is a different beast: models and processing happening deep inside network infrastructure, in places you never see. That side has plenty of processing power, with massive models and huge datasets, but all that horsepower comes with a tradeoff: latency. The further your request travels, the longer you wait.
Edge AI flips that. It’s built for speed, low latency, and quick answers. But here’s the catch, and it’s the whole point of this article: edge AI is only as fast as the wireless device carrying it. You can run the most advanced large language model in the world on your network. Doesn’t matter. If the last few feet — or the last few walls — between the AI and your device are a choke point, you’re going to feel it. And you’re going to experience it as “AI is slow,” even though the AI did its job in milliseconds.
That’s exactly what happened to me upstairs. Mesh system and all, the wireless portion of my network was the bottleneck dictating how “fast” my AI felt. You can validate a model’s accuracy all day in a lab with a clean connection, but if you don’t test how the RF performance holds up as conditions vary — signal attenuation, degraded power levels, changing interference — you’re not testing the full picture of what the device can actually deliver.
My personal experience reinforces a larger point: wireless testing can’t be an afterthought in AI-edge deployment; it must be central to the conversation.
Enter Wi-Fi 8
This is exactly why the coming generation of wireless technologies — whether it’s Wi-Fi 8 in your home network, 5G on your phone, or 6G on the horizon — matters more now than ever. Past generations mostly chased peak throughput in the form of bigger numbers on a spec sheet. Wi-Fi 8 (the industry’s working name for IEEE 802.11bn) breaks that pattern. With an official designation of “ultra-high reliability,” or UHR, Wi-Fi 8 is built to support higher throughput in poor-signal conditions, lower worst-case latency, and fewer dropped connections. This is especially important as devices roam between access points (APs) via features like Multi-AP Coordination (MAPC), where nearby access points work together instead of competing for airtime.
The emphasis on UHR represents a larger and significant shift away from “how fast can Wi-Fi run under ideal conditions” and toward “how consistently fast is my Wi-Fi as attenuation, power, and interference levels shift.” That distinction matters enormously for AI at the edge.
AI-powered devices aren’t just streaming a video where a little buffering is annoying but survivable. These systems are often making real-time decisions while interacting with voice assistants, AR/VR devices, industrial sensors, and even smart cameras performing on-device inference. Any hiccup in the wireless link doesn’t just slow things down; it can break the entire interaction. Nobody wants to repeat themselves to a smart speaker or discover too late that their security camera is lagging behind reality.
Where Testing Moves the Needle
Performance isn’t just about the client device in your hand — it affects the access point, too. Both ends of the link have to hold up. And here’s the part that’s easy to miss: you don’t have much control over the link itself. You can’t fix the walls in someone’s house, the neighbor’s Wi-Fi network, or a crowded RF band. What you can control is how well your device’s Tx/Rx chain performs when it’s handed a bad link. If you’re not testing that, you’re relying on chance. Designing hardware for a target performance range is one thing. Proving the software actually drives that hardware to hit the target, consistently, is another.
That leads to the next consequential question, which is what does testing actually look like under these new conditions? Broadly, it splits into three categories:
Non-signaling testing measures RF performance in isolation, away from live communication, so problems get pinned to hardware. Considerations here include:
Mission-mode testing, by contrast, deliberately changes channel conditions while the device is running, to see how it adapts in real time. This includes:
Co-existence testing puts the device in a shared, contested RF environment — alongside Bluetooth and neighboring Wi-Fi networks — to see how it holds up on signal power and adjacent-channel levels when it’s not the only radio in the room.
None of this is about recreating every real-world scenario. It’s about knowing, with precision and a great degree of certainty, where a device’s hardware and software start to fall short of spec — and before a user finds out first.
The Bottom Line
Here’s what I keep coming back to: we can build the smartest edge AI in the world, but if we don’t rigorously test the wireless network carrying it, we’re leaving performance — and user trust — on the table. My AI tool wasn’t slow because Claude was slow. My video wasn’t slow to upload because YouTube was slow. In both cases, it was the wireless hop that quietly decided how good my experience was going to be.
That makes the case for treating wireless test as a first-class citizen in AI edge deployment. And it supports the need for taking Wi-Fi, 5G and 6G seriously — not as a marketing spec bump. Wireless communications is the connective tissue that determines whether all that edge AI investment will actually pay off where it matters most: in someone’s hands, in their home, in the moment they need it to just work.
How hotels, restaurants, and entertainment venues can use guest WiFi to create stronger engagement, better follow-up, and more measurable business outcomes.
Guest engagement does not begin after the visit. It begins the moment a guest connects.
For many venues, guest WiFi is still treated as a background service. It works, guests get online, and the interaction ends there.
But for venue teams focused on growth, that connection can do much more. It can support first-party data, more relevant guest engagement, better venue intelligence, and stronger business outcomes over time.
| Starts with A Better Welcome |
→ | Builds Guest Engagement |
→ | Creates Business Outcomes |
The sign-in experience shapes the first impression. If the guest WiFi interaction feels disconnected from the venue brand, it can feel like a generic step instead of part of the visit.
A branded welcome helps the experience feel more intentional, more polished, and more aligned with the property. It sets the tone for what comes next.
The strongest guest engagement strategies feel connected from the first interaction, not added on later.
Guest engagement gets stronger when a venue can continue the relationship after the visit. That requires first-party data collected with permission and a clear value exchange.
The goal is not to collect more fields than necessary. The goal is to collect useful information that can support better follow-up, stronger segmentation, and more relevant communication.
|
01
CaptureCreate a clear value exchange that encourages guests to opt in and stay connected. |
02
UnderstandLearn which audiences, visits, and behaviors are most relevant to the venue. |
03
ReconnectUse that insight to shape outreach that feels timely, useful, and relevant. |
Not every guest should receive the same message. A first-time guest, a repeat visitor, and an event attendee each bring different context to the experience.
The more relevant the follow-up, the better the chance a venue stays connected and creates measurable business outcomes. Relevance matters more than volume.
|
01
Return offers |
02
Event invitations |
03
Loyalty updates |
04
Feedback requests |
Timing has a direct effect on engagement. If a venue waits too long to ask for feedback, the experience becomes less clear and the opportunity becomes easier to miss.
When outreach is timely, guests are more likely to remember what stood out, respond with useful detail, and stay connected to the brand.
Guest engagement improves when timing, relevance, and experience work together.
This is where venues can create more value from interactions they already have, instead of relying only on broad campaigns later.
Generic communication limits guest engagement. Segmentation helps venues tailor outreach to the guest experience instead of treating every visitor the same way.
A useful starting point is simple segmentation based on who visited, why they visited, and what they did next.
A guest connection has more value when it leads to a next step. That next step could be a return visit, an event registration, a loyalty invitation, or a promotion tied to the guest’s interests.
Connection counts alone are not enough. Venue teams need to understand whether guest engagement is producing meaningful outcomes such as audience growth, repeat visits, campaign response, venue intelligence, and revenue growth. The best measurement frameworks help teams decide what to improve next.
