Network demands are surging as businesses adopt AI across more applications, branches, and cloud environments. At the same time, networking and security teams are under growing pressure to protect distributed users, devices, applications, and data—without adding more operational complexity.
In today’s distributed, cloud-first environments, legacy overlay security can’t protect high-bandwidth AI workloads, remote users, hybrid branches, and dynamic data flows.
To safely scale AI initiatives while protecting corporate data and preventing data leakage—and without overwhelming already-stretched IT teams—growing businesses need embedded network security, infusing protection into the network itself.
AI and agentic workloads demand massive bandwidth and create complex, unpredictable traffic patterns. Data now flows dynamically across hybrid environments, remote branches, cloud applications, and multicloud infrastructures. In fact, a single agentic task generates 450% more traffic than a human doing equivalent work. Securing that movement requires a more agile, intelligent network.
At the same time, attackers are using AI to increase the volume, speed, and sophistication of cyberattacks. Phishing campaigns are now hyper-personalized, malware is adapting to evade detection, and automated bots are probing networks for weaknesses at an unprecedented scale.
AI-era threats require AI-assisted network and security operations. By integrating AI directly into network devices and leveraging AI-enabled SecOps tools, networking and security teams can move from reactive firefighting to faster detection, prioritization, troubleshooting, and response. This can help growing businesses adopt AI with more operational confidence, while helping lean teams reduce manual investigation and contain risk faster.
Traditional overlay security adds appliances and software to existing infrastructure. This often creates more operational complexity: fragmented visibility, disjointed consoles, inconsistent policy enforcement, and bottlenecks that can slow performance.
Some businesses may look into upgrading a firewall appliance or investing in new routers, but with this add-on approach, traffic may need to be routed out of its way to a security checkpoint and back again. That added latency and complexity can be especially challenging for AI workloads, distributed users, and cloud-first environments.
Embedded network security changes the model. Instead of treating security as a separate layer, protection is integrated across the network fabric itself, including routing, switching, wireless access, cloud access, and identity-aware controls. The network becomes a point of visibility, intelligence, and enforcement.
In this model, every node becomes both a sensor and an enforcer, and every connection becomes a point of visibility and control.
Moving away from fragmented point solutions and adopting a secure networking model can help reduce operational complexity, improve resilience, and give lean IT teams more consistent control across distributed environments.
The Cisco approach to secure networking is a model that can support business continuity, modernization, and scale without a linear increase in tools or manual work.
Secure networking starts by embedding protection into the infrastructure, not bolting it on piecemeal. Cisco 8000 Series Routers with built-in Cisco firewall provide protection at the WAN edge, helping organizations secure distributed environments and support cloud-managed security. Cisco Wi-Fi 7 and Cisco Smart Switches extend embedded security directly into campus and branch infrastructure, where users, devices, and applications connect.
Cisco Multicloud Fabric (announced at Cisco Live 2026) helps IT connect sites directly to clouds and cloud-to-cloud with built-in security, end-to-end visibility, and a fabric that scales with AI workloads.
These solutions help IT teams gain visibility and enforce policy closer to where activity begins, whether supporting remote employees, securing branch connectivity, or protecting regulated environments where consistent access control and uptime are critical.
The agentic AI era requires a network that can support true innovation while defending against rapidly evolving threats. At Cisco Live 2026, the secure harness for agentic AI was announced: Cisco Cloud Control.
Cisco Cloud Control is an AI-native management solution for orchestrating and securing enterprise IT infrastructure. Cisco Cloud Control gives humans and agents a unified operations platform that brings every Cisco domain and third-party tool into one environment—one login, one view, one operating model.
Cisco also delivers AI tools to enhance security operations. Cisco AI Assistant and AI Canvas make ops more actionable by helping teams detect threats faster, simplify management, and respond more effectively. These capabilities can reduce the burden on lean IT teams by making complex network and security tasks easier to understand and act on.
With intelligence built into the operating model, teams can move from manual investigation and reactive troubleshooting to more proactive, AI-assisted operations.
Firewalls remain essential, but modern security can no longer rely on firewall-centric thinking alone. Users, devices, applications, and data now operate across branch locations, cloud services, software-as-a-service (SaaS) platforms, remote environments, and hybrid infrastructures.
Cisco’s approach to secure networking goes beyond the firewall by integrating protection across routing, access, and cloud environments. Secure routers and firewalls help protect traffic moving between sites, clouds, and users while SASE extends identity-aware protection to cloud applications and remote users.
This equips IT teams with consistent control across WAN edge, campus, branch, cloud, and remote access environments.
In distributed environments, trust cannot be assumed based on location. A user in the office, a remote employee, a branch device, and a cloud application all need consistent, identity-aware access control.
Cisco Access Manager enables unified access control across users, devices, and applications. It helps organizations verify who and what is connecting, apply appropriate policy, and reduce the risk of unauthorized access.
Together with Cisco SASE for Meraki, organizations can extend secure, identity-aware access to remote users and cloud applications without multiplying management tools.
For many growing businesses, the biggest security challenge isn’t just the number of threats. It’s the number of tools required to manage them.
Cisco helps simplify operations through a unified platform that brings networking and security together across routers, firewalls, wireless, switches, access control, SASE, and AI-powered operations. This integrated approach helps lean IT teams maintain high performance and strong security while reducing complexity.
Policies can be applied more consistently. Visibility improves across users, devices, branches, and clouds. AI-assisted capabilities help teams investigate, troubleshoot, and respond faster. The result? Integrated security and network performance that lean teams can manage more consistently across distributed environments.
For teams building a business case, the Cisco secure networking model can also support tool consolidation and operational efficiency discussions.
As a maritime technology company helping the shipping industry improve vessel efficiency and reduce emissions, Silverstream Technologies depends on digital collaboration and dependable access across a growing global business.
For a company focused on serving customers across a complex maritime ecosystem, the network is more than infrastructure. With the Cisco Meraki dashboard and Cisco Secure Client, Silverstream strengthened the technology foundation needed to support its operations, connect teams, and scale securely.
The company now enforces consistent policies, encryption, and monitoring across all facilities and remote connections—including a London HQ with more than 1600 detectable wireless networks.
Silverstream’s secure, cloud-managed Cisco network also helps it achieve ISO 27001 certification by adhering to the rigorous data protection standards demanded by the world’s leading shipbuilders.
YMCA of Niagara is a mission-driven organization with a goal to deliver better digital experiences across distributed locations. Supporting multiple facilities, programs, staff, members, and guests requires reliable connectivity and simplified IT operations.
With Cisco Meraki switches and SD-WAN appliances, YMCA of Niagara transformed their network foundation to better support secure access and consistent connectivity across community environments. Thanks to the Cisco Premier Breach Protection Suite, YMCA of Niagara deploys threat detection and response across network, cloud, endpoint, and email, with integrated tools like XDR Premier and Cisco Secure Email Threat Defense combined with 24/7 managed services.
By moving to the centralized Cisco Meraki dashboard, their IT team is now spending less time managing complexity and more time supporting the services and experiences people rely on. They have achieved an 80%+ decrease in mean time to resolution (MTTR) and 70% reduction in support incidents with Cisco.
The AI era has rewritten the rules of enterprise technology. To keep pace with business demands while defending against automated, intelligent threats, organizations can no longer rely on fragmented, bolt-on security tools.
The future belongs to those who build security from the ground up. By unifying networking and security into a single embedded architecture, IT teams can simplify daily operations, reduce complexity, and build more consistent availability, policy control, and operational resilience.
It’s time for your network to do more than connect your business. With Cisco, your network actively defends itself—everywhere—so you can scale assuredly as you grow.
New tiered program delivers deeper GTM support, named account management, and co-marketing investment for MSPs growing their security practice on DNSFilter
WASHINGTON, D.C., June 30, 2026 — DNSFilter, a global leader in AI-powered protective DNS and content filtering, today announced a significant expansion of its MSP Partner Program. The enhanced program introduces a structured three-tier model designed to meet MSPs where they are and invest more deeply in those growing their security services practice.
New research from DNSFilter reveals the scale of the commercial pressure MSPs are navigating with 85% of MSP leaders surveyed admitting there is a security capability they cannot effectively deliver today as they spend more time stitching tools together than stopping threats. The financial impact is direct: 49% cite security tool licensing costs as their single biggest obstacle to growing security revenue, 26% point to an unmanageable tech stack, and 23% to training overheads.
AI-Phishing top concern among MSPs surveyed
The top threats MSPs are most worried about over the next 12–18 months are operating at a layer that most current tools do not cover:
The common thread: these attacks operate at the DNS and web layer, before the endpoint agent can intervene. By the time an endpoint agent sees a threat, the user has already clicked, the page has loaded, and the resolution has happened. 38% of MSPs say they cannot effectively deliver protection against AI-generated threats today with 30% saying they cannot deliver network-level visibility beyond the endpoint.
The Security Opportunity MSPs Are Sitting On
DNSFilter’s 2026 MSP Research* found that 47% of MSP leaders cannot effectively deliver security posture reporting for compliance or cyber insurance purposes, the second-largest capability gap in the market, behind only advanced threat detection. For MSPs serving finance, healthcare, manufacturing, and legal clients, that gap is both a risk and a missed revenue opportunity.
“Our research makes the commercial reality facing MSPs impossible to ignore, but the flip side of that is a real opportunity we want to help our partners capture. When our partners succeed, more businesses get protected. That’s the outcome we’re building for,” said Ken Carnesi, CEO and Co-Founder of DNSFilter.
Built for MSPs from Day One: Introducing the Three-Tier MSP Partner Program
Today, more than 6000 MSPs use DNSFilter, and last year the company made its largest MSP investment to date, acquiring Zorus and launching CyberSight to identify phishing infrastructure and lookalike domains before they reach client networks.
The new enhanced MSP Partner Program builds on this foundation with a three-tier structure designed to match the level of investment DNSFilter makes to the level of commitment an MSP brings:
DNSFilter Select Partner: Partners get immediate access to our multi-tenant platform and the DNSFilter Partner Edge Portal, white-label campaign assets, self-paced training, and volume-based pricing with no application form, no approval queue, and no long-term contract standing between them and a security layer their clients will feel.
DNSFilter Accelerator Partner: By invitation or application, for MSPs committed to growing their security services practice. Accelerator Partners receive a named account manager, sales engineer support for demos and POCs, co-marketing resources backed by MDF investment, and a dedicated annual business review so growth conversations are grounded in actual numbers, not guesswork.
DNSFilter Strategic Partner: DNSFilter’s deepest commitment, reserved for partners going all-in on security services growth. Includes custom enablement, joint selling motions, co-branded/white-label marketing, ongoing MDF, and a dedicated DNSFilter team aligned to the partner’s revenue goals. When a Strategic Partner wins, DNSFilter wins with them.
“The MSP community is where cybersecurity protection actually gets delivered to the businesses that need it most. With this next chapter in our program, we’re putting more resources, more people, and more structure behind the partners who are growing with us. If you’re an MSP who’s been thinking about making DNSFilter a bigger part of your stack, this is the right time” said Dan Cucchi, VP of MSP and Channel Sales, DNSFilter.
“DNSFilter has been a core part of our security stack for years, and this new MSP program reflects exactly what we’ve always valued about this partnership, a team that understands how MSPs operate and builds programs to match,” said Rick Dupuis, Sr. Manager, Technical Solutions, Mainstay Technologies. “For Mainstay, DNS protection isn’t optional; it’s a non-negotiable first layer of defense for every client we onboard. Having a partner program that reinforces that model with the right pricing, support, and tooling makes it easier for us to deliver consistent security outcomes at scale.”
“Being part of DNSFilter’s MSP program isn’t just about adding another tool to our stack, it’s about aligning with a team that genuinely understands how we operate and what our clients need. DNSFilter has earned that trust. The platform delivers where it matters: reliable protection, a management experience built for multi-tenant environments, and a support team that treats us like partners. That’s what makes the relationship sticky and what makes it easy for us to put DNSFilter in front of our clients with confidence,” commented Charles Love, COO, ShowTech Solutions.
For more information please read our blog or visit the Partner Page for further details.
*About the Research Methodology
Survey of 100 senior-level cybersecurity and IT professionals at US-based Managed Service Providers. Fieldwork conducted in spring 2026. Respondents hold titles of Director level and above. Full report can be found here
About DNSFilter
DNSFilter is a cybersecurity company that protects every click, leveraging AI-driven content filtering and threat protection to block threats up to 10 days earlier than competitors. DNSFilter’s solution secures workers wherever they are, helping organizations boost productivity, minimize compliance risk, and protect corporate brands on public Wi-Fi networks. Trusted by more than 45,000 organizations worldwide, DNSFilter enables organizations to deploy powerful protection in minutes while gaining deep visibility into their security posture. Learn more at dnsfilter.com
Media Contacts:
Rebecca Cradick
Vice President, Global Communications and Investor Relations
media@dnsfilter.com
 Measuring where a person or object is with Bluetooth Low Energy (BLE) is like finding a bakery by its smell. You know it is close, you just can’t tell if it is 10 metres ahead or 30 metres to your left. Ultra-Wideband (UWB) gives you an edge. It measures the same distance the way a tape measure does: accurate to the centimetre. That precision is why UWB is showing up in applications where BLE cannot deliver. Every one of those applications is a firmware team solving a problem BLE never forced them to think about.
Most of the content written about UWB fixates on Real-Time Location Systems (RTLS: infrastructure-heavy tracking systems that monitor the positions of assets and people across a large space using fixed anchor hardware).
That coverage has its place. However, the five applications where firmware teams are doing the most interesting work “right now” go largely unwritten about: autonomous robot follow-me, child presence detection tied to automotive safety ratings, gesture recognition without cameras, contactless vital sign monitoring, and peer-to-peer ranging in consumer devices. Two of these are what regulation mandates. But all five are firmware-intensive in ways warehouse tracking never is.
This article covers all five. It includes: why UWB fits each problem, what the firmware actually has to do, and which silicon fits each use case. As for the alternatives, catch a more detailed read in our other post – UWB vs BLE vs Wi-Fi: A Firmware Engineer’s Decision Framework.
A UWB pulse lasts less than one nanosecond, the time it takes light to travel roughly 30 centimetres. That timing precision is what makes UWB a ruler rather than a radio.
Here is what “wide frequency bandwidth” means in plain terms. Narrow-band radios broadcast the way someone holds a long note on a saxophone: by the time the note reaches you directly, the echo bouncing off the wall is already on top of it.
The two blur into one sound. UWB broadcasts the way a drummer plays a single sharp hit: direct sound and echo arrive as two distinct beats you can tell apart. Spreading across 500 MHz gives the receiver that sharp-beat resolution. It separates the direct signal from its wall-reflected copies cleanly.
For firmware engineers, this shifts the problem from filtering and estimating to measuring and acting.
The five applications below all exploit that shift in different ways.
An autonomous follow-me robot is a wheeled or legged machine that follows a specific person through a shared workspace: a nurse down a hospital corridor, a warehouse picker between aisles, a logistics worker on a factory floor. The robot carries the tools, parts, or load the person would otherwise push on a cart. The design brief sounds simple. Stay a fixed distance behind the person. Close enough to be useful. Far enough to be safe. Never hit them.
The environment is where the job gets hard. For instance, in situations where: another person steps between the robot and the operator or the operator turns around and walks back to grab something from the cart. The robot has to spot the reversal, stop and hold its ground, then swing around and start following again once the operator heads off.
KUKA’s KMR iiwa, one of the most capable mobile robots on factory floors today, uses laser scanners to navigate for exactly these reasons. The same problem now shows up in humanoid robotics. Unitree’s G1 humanoid is already being paired with UWB tracking modules from vendors like Weston Robot. Once a humanoid is meant to share spaces with people, the robot must know the exact position of the person it follows, within a few centimetres, at all times.
BLE Received Signal Strength Indicator (RSSI) fails in these conditions because signal strength is a guess. The same received power could mean the operator is 2 metres directly ahead, or 8 metres away behind a steel shelf. UWB works differently. It timestamps when a radio signal is sent and when it comes back, divides by the speed of light, and returns a distance accurate to centimetres.
Think of it the way a ship uses sonar: send a pulse toward the seabed, wait for it to return, measure the round-trip time, and the depth is calculable to within metres.
TWR does the same thing between two UWB radios, at the speed of light: the tag sends a timestamped message, the anchor responds with its own timestamp, and the round-trip time reveals a distance accurate to centimetres. A UWB tag worn by the operator and an anchor node mounted on the robot exchange these ranging messages on a timed schedule.
The firmware on the robot side runs a ranging scheduler: a task that wakes the radio, collects the distance measurement, and passes it to the motion controller before putting the radio back to sleep. For heading estimation (knowing which direction to follow, in addition to how far), firmware teams typically fuse UWB readings from two or three tag positions with data from an Inertial Measurement Unit (IMU: a sensor that measures acceleration and rotation, used here to track which way the robot is turning).
Silicon that fits: the Qorvo DW3120 handles TWR with interrupt-driven firmware integration that maps cleanly onto a Real-Time Operating System (RTOS: the software layer that manages when each firmware task runs on the processor). For battery-operated operator tags where current draw is the binding constraint, Spark Microsystems documents the SR1000 at sub-mW active receive current at 0.85 Mbps in its product documentation.
For teams evaluating autonomous mobility systems: UWB follow-me removes the “clean environment” assumption from your testing checklist. The system works where your robot actually operates.
By 2026, Child Presence Detection (CPD) has become a requirement for top safety ratings in major markets, led by the European New Car Assessment Programme (Euro NCAP: the body that rates vehicle safety across Europe). Euro NCAP started awarding CPD points in 2023. From January 2025, the system must also detect a child aged three to six who climbs into an unlocked car on their own and becomes trapped when it locks. The US Hot Cars Act pushes a parallel regulatory path.
Two standards bodies carve up the CPD problem between them: Euro NCAP sets the detection requirements (what the system must spot, and how reliably), while the FiRa Consortium (Fine Ranging Consortium: the industry body that governs how UWB devices from different vendors talk to each other) sets the interoperability rules for the UWB radios themselves. For automotive suppliers and Tier 1 integrators, Euro NCAP’s CPD requirement is already scoring your competitors. This is an engineering deadline with a date attached, and a 5-star rating on the line.
The challenge is physical. A sleeping infant’s chest rises and falls three to eight millimetres with each breath. A heartbeat moves the chest by 0.2 to 0.5 millimetres. Cameras need good lighting and a clear view of the child. A closed car on a hot day gives you neither.
Think of UWB in-cabin sensing the way a bat navigates a cave. A bat reads the echo of its own chirp to map everything around it: walls, gaps, moving prey, without needing to see any of it.
A UWB radar node reads the echo of its own pulse, and a breathing chest changes that echo in a pattern no inanimate object in the car produces. The firmware configures the radio in radar mode rather than ranging mode, collects pulse-return data at a high repetition rate, applies signal averaging to filter out road vibration, and extracts the respiration waveform from what remains.The FiRa Consortium sets the interoperability rules for UWB ranging. The CPD sensing requirements (what the system must detect and how reliably) are governed by Euro NCAP.
Silicon that fits: NXP’s Trimension is the company’s family of UWB chips — the same line BMW uses for its Digital Key Plus passive entry system. NXP’s published documentation for in-cabin UWB sensing covers the Trimension CPD configuration in detail. The chip built for this job in production vehicles is the NCJ29D6A. It combines UWB ranging with short-range radar on a single chip and carries AEC-Q100 qualification (Automotive Electronics Council standard 100: the industry test suite that confirms a chip survives the temperature swings, vibration, and humidity a car endures over its lifetime). For CPD specifically, that matters because the chip has to keep working in a parked car that hits 70°C on a hot afternoon.
For product teams in automotive, consumer electronics, and industrial control: UWB gesture recognition works in any lighting condition, captures no image data, and runs five to seven recognised gestures at above 90% accuracy in production conditions. The privacy compliance burden disappears before it reaches your legal team.
Camera-based gesture systems face three challenges firmware teams rarely budget for up front. The first is the privacy compliance burden image capture brings with it. The second is processing demand most embedded platforms cannot spare. The third is a hard dependency on lighting conditions. UWB sidesteps all three.
Every UWB transmission channel produces a Channel Impulse Response (CIR). Think of the CIR the way a musician reads a room. Strike the same chord in an empty warehouse and in a tiled bathroom, and the note sounds different: same source, but completely different reflection profile.
When a hand moves between two UWB nodes, the CIR shifts in a pattern that matches the gesture. The firmware grabs the CIR frames at a fast update rate, hands them to a machine learning model running on the main microcontroller, and outputs the gesture in under 50 milliseconds.
How many gestures can UWB tell apart? A 2020 study hit 95% accuracy across eight hand gestures. The gestures were four swipe directions (left-right, right-left, up-down, down-up), two diagonal swipes, and two rotations (clockwise and counterclockwise). A 2021 public dataset stretched the count to twelve. In production cars, where a false positive is dangerous, vendors keep the menu tighter: five to seven gestures, accuracy above 90% once the model is trained on the actual cabin layout.
The implementation challenge is throughput. Raw CIR data coming off the radio must move to the classifier without stalling other firmware tasks. On an RTOS, that means a dedicated high-priority interrupt service routine handing data to a processing queue, with the classifier running as a lower-priority task against a timestamp-matched buffer. Teams that underestimate this pipeline are the ones who end up with gesture latency measured in seconds rather than milliseconds.
Silicon that fits: Where most ranging chips hand you a distance and nothing else, Qorvo DW3220 gives you the full raw reflection data directly. That full reflection fingerprint is what the classifier trains on and runs against. A mature driver ecosystem means the radio is up and feeding data quickly. The firmware problem left to solve is the interesting one: building the model.
For medical device teams and automotive OEMs: contactless vital sign monitoring removes the need for electrodes, adhesives, or patient compliance. The sensor reads breathing and heartbeat at up to five metres of clear line-of-sight. It works whether the patient cooperates or not.
UWB can detect breathing and heartbeat through air, without touching the patient. The physics is the same impulse-radar principle used in contactless monitors in neonatal intensive care units (NICUs), where it has been tested against ECG and chest-impedance sensors on more than thirty premature babies in published clinical studies. Microwave radar has been used to monitor vital signs in clinics since the mid-1970s. UWB takes the same physics and shrinks it to fit the power budget and board space embedded engineers work with.
Each UWB pulse reflects off the chest wall. As the chest moves with each breath, the return time of the reflected pulse shifts by picoseconds (trillionths of a second), corresponding to a displacement of millimetres. The firmware averages thousands of pulse returns to pull this signal out of noise, applies bandpass filters tuned to the frequencies of human respiration (12 to 20 cycles per minute) and heartbeat (60 to 100 beats per minute), and produces a clean waveform a host processor can interpret.
A useful frame for picturing this: press your wrist gently against a drumhead while someone taps the other side of the drum. You feel the vibration clearly, even though your wrist is nowhere near the source. UWB reads the equivalent of that vibration through open air, without any physical connection to the patient. Working range for reliable respiration detection is up to approximately 5 metres under clear line-of-sight conditions.
Applications include neonatal monitoring, in-vehicle occupant detection as a complement to the CPD use case above, and eldercare systems where reducing physical contact with a sensor matters. A patient who moves or removes a wired monitor in the night still has a chest wall that can be monitored.
Silicon that fits: Novelda’s X4M200 is a dedicated Impulse-Radio UWB (IR-UWB: the sub-category of UWB that uses short, repeated radar-like pulses specifically for sensing rather than communication) respiration sensor. Novelda’s own product documentation confirms its 0.4 to 5-metre sensing zone for breathing detection, and the IR-UWB approach it uses is independently validated in peer-reviewed literature.
Fixed-infrastructure positioning is expensive. RTLS forces you to mount anchors on ceilings, calibrate them, run a location engine on a server, and pay to keep all of it running. That cost shuts a lot of useful applications out of the market.
Peer-to-peer (P2P) UWB ranging removes the infrastructure entirely. Two devices with UWB radios trade timestamped messages and work out the distance between them directly. No anchors. No server.
What this unlocks: Apple’s AirTag uses P2P UWB to point you to a misplaced wallet within a few centimetres. BMW’s Digital Key Plus uses it for hands-free entry: the owner’s phone ranges against a UWB node inside the car door, and the lock opens when the phone is authenticated and inside the permitted zone.
The Car Connectivity Consortium (CCC: the industry body that sets the standard for how phones unlock cars) defines this in its Digital Key 3.0 standard, covering both the ranging protocol and the security on top of it. Industrial proximity warning, asset pairing without a network, and contactless payment confirmation are all live build areas.
What firmware has to solve: The hard problem is not ranging. It is scheduling. When dozens of P2P devices range at the same time in a tight space like a car park, a warehouse loading dock, or a busy office, the protocol has to decide who talks when. If it gets that wrong, measurement collisions stack up into delays.
Think of P2P ranging like two people standing at opposite ends of a street, each holding a stopwatch synchronised to the same clock. One calls out, the other records the time of arrival and calls back. From those two timestamps and the known speed of radio waves, both can calculate the distance between them to within centimetres.
The firmware manages two roles: initiator (the device that sends the first ranging message) and responder (the device that timestamps receipt and replies). At product scale, the hard firmware problem shifts from ranging to scheduling: when dozens of P2P devices are ranging simultaneously in a confined space, the protocol must handle contention without measurement collisions stacking up into delays.
Silicon that fits: Qorvo documents the DW3xxx series for consumer and industrial P2P ranging in its “UWB in Digital Car Key” whitepaper, which details ranging performance in CCC Digital Key 3.0-compliant deployments. For automotive-grade implementations requiring both CCC compliance and AEC-Q100 qualification, NXP’s Trimension SR150 product documentation maps the chip directly to the CCC Digital Key 3.0 specification.
None of the five applications above uses ceiling anchors. None requires a cloud location engine. Strip away the RTLS framing that dominates most UWB content, and what remains is a single consistent capability: precise distance measurement between two points, executed in firmware, at close range.
That is the thread. Between two devices. Between a radar node and a chest wall. Between a robot and the operator it follows.
The firmware architecture that serves all five looks the same at its core: a ranging or radar engine producing raw measurements, a decision layer acting on those measurements against a threshold or model, and a power manager keeping the radio asleep between sessions. Master that pattern once, and it transfers across every application in this article.
One constraint carries across all five applications: line-of-sight matters, but the meaning is more specific than zero obstacles. Commercial UWB ranging chips operate in the 6 to 9 GHz band. At those frequencies the signal passes through drywall, wood, and glass with some loss of accuracy. It degrades sharply through brick and reinforced concrete. It is effectively blocked by metal: steel shelving, car door pillars, aluminium cabinets, copper plumbing in a wall. Water absorbs UWB too, which is why a human body itself blocks the signal.
The practical rule for firmware teams: a UWB node needs a clear radio path to its target, free of metal obstructions, with at least twenty centimetres of clearance from any nearby metal that could distort the antenna. A metal cabinet between a UWB node and a patient’s chest, a car door pillar between two ranging nodes, a steel shelf between a robot and its operator tag will all wreck measurement quality. Antenna placement is an architecture decision. Finalise it before the software stack takes shape.
The volume in UWB over the next product cycle is coming from these five firmware problems, driven by regulatory mandates, consumer product adoption, and the specific gap that centimetre-level ranging fills where BLE cannot.
Where does your current product sit against that list, and what does the firmware architecture need to look like when UWB joins the stack?
embedUR’s firmware team has integrated UWB ranging across automotive, consumer, and industrial applications. If you are evaluating UWB for any of the applications covered here, a 30-minute architecture review maps your requirements to a firmware topology and flags integration risks before any code is written.
If you enjoyed this article, discover even more of UWB’s capabilities in our next blog post – UWB Beyond Ranging: What IEEE 802.15.4ab Means for Your Firmware.
This month, I had the opportunity to attend Unify 2026, hosted by the Connectivity Standards Alliance (CSA). As a senior campaign manager on the Global Marketing team, I work closely with Product Marketing to translate product strategy into integrated campaigns that educate and engage audiences around emerging technologies, thought leadership, and Silicon Labs solutions. Unify gave me a valuable opportunity to hear directly from the people shaping these technologies and to better understand where the industry is headed.
The goal of Unify was to bring together leaders and product makers across the IoT ecosystem to explore the future of connected technology. Through technical sessions, product demonstrations, and networking, the event highlighted the industry’s shared goal of accelerating adoption of open, interoperable IoT standards.
After experiencing a range of panels and networking events, I left with one overarching takeaway: the future of IoT isn’t just about connecting devices, it’s about building smarter, more secure, and more interoperable experiences through collaboration.
Photo courtesy of the CSA
The event opened with IoT pioneer Kevin Ashton, best known for coining the term “Internet of Things”. His message challenged us to think beyond today’s smart home devices and imagine technologies that solve meaningful, everyday problems.
Rather than creating connected products simply because we can, Ashton encouraged us to focus on innovations that genuinely improve people’s lives, including ways to detect if someone is sick or making everyday chores easier with a self-folding dryer. Think bigger!
Photo courtesy of the CSA
Although there was a dedicated security panel, security quickly emerged as a theme throughout the entire conference.
The key message we heard consistently was that security is now a baseline expectation. Consumers, enterprises, and regulators expect connected devices to be secure from day one, and that responsibility extends across every layer of the ecosystem from silicon and devices to networks, applications, and cloud services.
This reinforced Silicon Labs’ approach to security. Security isn’t treated as just a feature, it’s a foundational design principle. Through features like Secure Boot, Secure Over-The-Air updates, and through third-party security evaluations and testings, we help customers build products that are protected throughout their lifecycle. As an active contributor to Matter, Thread, Zigbee, Bluetooth, Wi-SUN, and Z-Wave, we’re also helping strengthen the security of the broader IoT ecosystem.
Photo courtesy of the CSA
One of my favorite parts of the week was watching fellow Silabers take the stage to share their expertise.
Colin Cureton, Product Line Vice President of Home, explored one of today’s hottest topics: Edge AI.
As AI continues to transform the industry, IoT devices are becoming more intelligent and capable of making decisions locally rather than relying entirely on the cloud. Running AI at the edge reduces latency, improves privacy, and enables faster, more reliable decision-making for applications ranging from manufacturing and smart buildings to predictive maintenance and energy management.
For me, the main takeaway was that the future of IoT is about more than just connecting devices. It’s about enabling devices to think and respond in real time.
Rob Alexander, Principal Product Manager and Vice Chair of the CSA Board of Directors, spoke about how companies can actively shape the future of Matter by participating in alliances.
The key message here was that Matter evolves through collaboration. The standard can’t be built in a silo. It needs to be shaped through contributions from Alliance members, technical working groups, implementation feedback, and real-world experience. Rather than waiting for new capabilities to arrive, companies have an opportunity to help define what’s next.
Our very own Campaigns Team Manager and Vice President of Marketing for Thread, Ann Olivo, joined two sessions focused on Thread and Matter. She helped attendees better understand how the technologies work together and where they fit into a product roadmap.
One of the biggest misconceptions addressed throughout the week was the idea that it’s “Thread or Matter.” In reality, it’s both.
Thread provides the reliable, low-power mesh networking foundation for many connected devices, while Matter builds on that foundation to deliver interoperability across ecosystems. Together, they allow manufacturers to focus less on ecosystem-specific development and more on building innovative, high-quality products.
The conversations also reinforced that these technologies extend far beyond the smart home. From commercial buildings and energy management to industrial and enterprise deployments, Thread and Matter are enabling connected solutions at much larger scales.
In fact, Silicon Labs is already demonstrating this through our Large-Scale Matter over Thread Deployment in our Boston office, proving that Matter-over-Thread networks can deliver reliable, enterprise-scale performance. Check out our white paper on Matter over Thread to learn more.
Photo courtesy of the CSA
Beyond the sessions, the demo showcase offered a chance to see the latest innovations up close. At the Silicon Labs booth, attendees experienced demos featuring technologies like Aliro, while our booth neighbor, Thread Group, demonstrated how Thread connects devices across a growing ecosystem.
Some of my most engaging conversations actually happened between sessions. Whether attendees were just beginning to explore Thread or were already building Matter products, it was clear that people were excited to learn more and contribute to open standards.
I left Unify energized, both by the expert-led panels and the collaboration I saw firsthand between the companies driving the industry forward.
I gained a much deeper appreciation for the work happening across the CSA community. From security and AI to interoperability and open standards, every company has a role to play in shaping the future of IoT.
Seeing Silicon Labs contribute not only through our technology, but also through leadership, technical expertise, and active participation in standards development made me especially proud to be part of the team helping build what’s next!
There’s a conversation happening in boardrooms and IT departments around the world, and it sounds something like this: “We need a reliable network, but everything we’re being shown is either way too much or not enough.”
It’s a real dilemma. On one side, there are solutions engineered for massive corporations: powerful, feature-rich, and built to handle complexity at a scale most organizations will never reach. On the other hand, there are low-cost alternatives that look attractive on paper until outages start, hidden maintenance costs pile up, and the network becomes a liability rather than an asset.
Neither path was designed for the reality of most mid-sized businesses. And the outcomes prove it.
Enterprise solutions from global vendors come with a long list of capabilities, most of which will never be used. What follows is predictable: budgets that don’t add up, deployment timelines that stretch for months, and integrators stuck in endless negotiation cycles with margins that barely justify the effort. The technology works, but the fit is wrong.
Cheap now almost always means costly later. Unreliable performance, frequent downtime, and the slow accumulation of replacement and maintenance expenses quietly erase any upfront savings. Worse, an unstable network doesn’t just cost money; it costs trust, productivity, and opportunity.
NETGEAR Enterprise’s proposition is straightforward: enterprise-grade quality and reliability, with pricing built for the real scale of your business.
Solutions designed for the largest corporations aren’t always the right fit for growing organizations —even ambitious, multi-site ones. What most businesses actually need is robust, scalable, and battle-tested technology that matches their operational reality, whether that’s a regional retail chain, a multi-campus education group, a logistics network, or a fast-growing mid-sized company.
The equation changes completely. You eliminate overpaying for features you’ll never touch. You keep the robustness and reliability that modern operations demand. Deployment becomes simpler, channel profitability improves, and growth is supported without compromising the underlying network.
The conversation shifts from “which solution is cheaper?” to “which solution is better designed for our reality?”
The NETGEAR Enterprise portfolio gives you networks built to grow, scalable infrastructure that delivers the performance larger or multi-site operations need, without the complexity and overhead of solutions never designed for businesses like yours. Whether you need centralized visibility, simplified management, or robust infrastructure that can scale with your ambitions, there’s a solution built for where you actually are and where you’re going.
You don’t need to overspend to operate like a modern, competitive business. The right network isn’t the most expensive one; it’s the one built for where you actually are and where you’re going.
If you’re evaluating how to modernize your network without exceeding your budget, or you’re a partner looking for solutions that deliver real value and better margins, let’s talk.
By Sajid Khan, Director, New Business Growth – IoT BUÂ
While much of the hype around AI centers on consumer applications, the Industrial Internet of Things (IIoT) is undergoing a major transformation driven by real-time insights, autonomy, and predictive analytics. These capabilities are helping the industrial sector boost productivity, streamline operations, and reduce costs. It’s no wonder that IIoT applications are growing rapidly, with a projected CAGR of 24.7% over the next eight years.
To unlock the latest IIoT capabilities, OEMs and developers need reliable, high-performance, and energy-efficient silicon designed for intelligent edge applications.
A silicon portfolio built for IIoT
MediaTek Genio empowers IIoT developers and designers looking to create intelligent, differentiated products. Our portfolio is designed to meet a broad range of performance and power requirements, from low-power edge devices to premium AI-enabled systems.
On the value-tier side, our solutions support low-power IIoT devices with a balance of multimedia support, efficiency, and versatility. Our mainstream platforms take performance to the next level with advanced generative AI, neural processing, and high-performance compute. For more demanding industrial AI workloads, our new MediaTek Genio Pro series has rewritten what’s possible for intelligent industrial systems.
Industrial systems, upgraded
Let’s explore three key IIoT segments that MediaTek Genio powers:
A new generation of AI-ready IIoT applications
With customer appetite for real-time connectivity, intelligence, and automation continuing to rise, demand for advanced IIoT capabilities will only accelerate. MediaTek is helping OEMs, developers, and manufacturers build the next generation of intelligent industrial systems with high-performance, energy-efficient platforms designed for AI-driven edge applications.
Learn more about MediaTek’s portfolio for IIoT applications >
Stadium Wi-Fi has become mission-critical. Fans expect instant sharing, mobile ticketing, in-seat ordering, and real-time highlights. Staff need reliable connectivity for operations, security, POS, and venue apps. And venue operators are under pressure to turn connectivity into measurable business outcomes.
That is why we are excited to announce that GoZone WiFi will be participating in the upcoming Wi-Fi NOWÂ webinar:
Connected stadiums Webinar: Networks driving experience, engagement, & revenue
Wednesday, July 8
7:00 pm CEST / 10:00 am PDT
Register here: Reserve your spot
Our speaker will be Wayne Newton, VP Sales & Business Development at GoZone WiFi, joining a panel of stadium connectivity leaders to discuss what is changing, what is working, and what is next.
Stadiums represent one of the ultimate challenges in Wi-Fi networking. You are serving tens of thousands of users in a high-density environment where demand spikes instantly, usage patterns change by the minute, and the physical environment is complex.
At the same time, expectations have never been higher:
The result is a simple truth: stadium Wi-Fi is no longer just an IT project. It is a business platform.
The webinar session will explore the latest advances in stadium connectivity, including:
As Wi-Fi standards evolve, the conversation is also shifting toward what next-generation capabilities enable, including:
This webinar brings together a strong lineup of industry leaders:
At GoZone WiFi, we work with venues and large public spaces to help them get more from their guest Wi-Fi.
Reliable stadium Wi-Fi is the foundation, but the opportunity is bigger than access. With the right approach, venues can turn guest connectivity into:
In other words, the network becomes a tool for both fan experience and business performance.
If you are involved in stadium connectivity, fan experience, or venue operations, this session is built for you, including:
The event is live and free to attend. Register here to watch:
We hope you can join us on July 8 and be part of the discussion on what is next for stadium Wi-Fi, Wi-Fi 7, and the future of connected venues.
Brussels, Belgium – June 24, 2026 – The undersigned organisations representing the European connectivity ecosystem – including fibre operators, ISPs, semiconductors, hardware and software manufacturers, online pharmacies, tourism, and consumer electronics retail –  and fully committed to strengthening Europe’s digital infrastructure, welcome the European Commission’s proposal for a Digital Networks Act (DNA).1 However, we note that, in its current form, the proposal does not sufficiently recognise the critical role of Wi-Fi® as a key enabler of European connectivity.
Without adequately prioritising Wi-Fi as a key enabler of the 2030 Digital Decade targets – including gigabit-capable connectivity for all European households, full 5G coverage of populated areas, and ensuring that 90% of SMEs reach at least a basic level of digital intensity2 – achieving these objectives will become significantly more difficult, ultimately undermining Europe’s broader digital ambitions.
Fibre (FTTH), mobile, satellite, and Wi-Fi must be recognised as complementary and interdependent layers of Europe’s connectivity ecosystem. While each technology plays a distinct role in enabling high-performance networks, Wi-Fi serves as the critical final link that ensures gigabit connectivity effectively reaches end users across homes, businesses, public services and industrial environments. Therefore, as full-fibre transition is completed, Wi-Fi performance will become a critical factor in delivering the end-user experience and the full benefits of next-generation broadband connectivity. Indeed, for most Europeans, Wi-Fi is the primary gateway to the internet, delivering Gigabit connectivity from the network termination point to end-user devices where connectivity is consumed. Today, Wi-Fi carries over 90% of indoor internet traffic across homes, hospitals, businesses, public services and industrial environments. It is also a foundational technology that SMEs and industries rely on for edge computing, automation, robotics and AI-driven applications.3 Beyond industry, advanced Wi-Fi connectivity is increasingly essential to Europe’s travel and visitor economy, underpinning digital and AI-driven services across smart destinations, cultural heritage sites and tourism SMEs — making it a key enabler of innovation and competitiveness across the full breadth of the European economy.
Current spectrum policy highlights the need for the DNA framework to effectively recognise the critical role of Wi-Fi connectivity. Insufficient access to spectrum is increasingly constraining Wi-Fi performance and thereby impedes implementation of advanced use cases. Recent studies indicate that growing Wi-Fi traffic congestion is limiting the ability of gigabit connectivity to effectively reach more than 50-60% of indoor environments.4 Europe is falling behind. Leading economies such as the United States, Canada and South Korea have already opened the entire 6 GHz band for Wi-Fi use, accelerating innovation in immersive education, healthcare services, smart manufacturing, and sustainable technology. 5This is not merely a spectrum policy debate, but a strategic policy choice with significant implications for Europe’s technological sovereignty, industrial competitiveness, technological leadership, and long-term innovation capacity.6
In this context, to ensure that the DNA fully reflects the role of Wi-Fi as a strategic component of Europe’s connectivity infrastructure, we urge the co-legislators to address the following elements in the proposal:
Article 17 – Union Radio Spectrum StrategyÂ
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Article 27 – “Use it or share it” principleÂ
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Article 28 – Radio Spectrum DatabaseÂ
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The DNA represents a unique opportunity to establish a forward-looking and technologically balanced policy framework that will effectively guide Europe towards the Digital Decade objectives. Such a framework should accurately reflect the evolving connectivity landscape and ensure that integral components of the connectivity ecosystem, including Wi-Fi, are recognised and prioritised as strategic elements of Europe’s digital infrastructure.
The signatories to this statement represent a broad cross-section of hundreds of European and global connectivity players, including internet service providers, fibre network providers and operators, hardware and software manufacturers, semiconductor manufacturers, consumer electronics retail, online pharmacies, tourism innovation, and global industry associations focused on spectrum-sharing, advancing Wi-Fi and wireless broadband connectivity.
How the convergence of AI maturity, rising network complexity, and a widening talent gap is reshaping enterprise IT and what RUCKUS’s Agentic Operations means for the teams managing it.
For decades, network operations have followed a familiar pattern: engineers monitor dashboards, triage alerts, diagnose root causes, and apply fixes, often under pressure, and often at 2 a.m. Each generation of tooling automated part of that loop, but the operating model itself remained largely human-driven.
That model is straining under the weight of three converging pressures:
Network complexity is outpacing human capacity. Modern enterprise environments span wireless, wired, and multiple services simultaneously. The number of variables a human can effectively process during a live incident is finite; the networks generating those variables are not.
The talent gap is widening. Experienced engineers are retiring faster than new experts can be developed. Hard-won operational knowledge, the kind that lets a senior engineer diagnose a client issue in minutes, walks out the door with them and doesn’t come back easily.
AI models are finally capable enough to help. For years, “AI in networking” mostly meant dashboards with smarter labels. That has changed. With stronger language reasoning and domain-specific tuning, AI systems can now interpret network conditions, identify failure patterns, and support, or in some cases execute, operational decisions in ways that weren’t practical before.
These three forces aren’t arriving independently. They’re arriving together, and they’re arriving now.
The journey toward autonomous networking hasn’t been a single leap, it’s been a deliberate progression through four distinct operational stages:
Stage 1: Observability: The foundation. Network-wide telemetry, performance metrics, health dashboards, and historical trend analysis across deployment types. Without this raw signal, nothing above it works. Teams went from flying blind to having visibility.
Stage 2: AIOps Insights: Machine learning models identify user experience degradation, correlate events across the network, and surface actionable incidents before they escalate. This is where the industry moved from reactive operations, fixing what broke, to proactive operations: catching what’s about to break.
Stage 3: Automated Remediation: Intent-based AI translates high-level operational goals into specific network actions. Automated remediation workflows close the loop from detection to resolution without requiring manual intervention for every event.
Stage 4: Agentic Operations: The frontier. AI agents with natural-language understanding, expert-level reasoning, and autonomous decision-making, operating within a governed framework, explaining their actions, and increasingly handling what used to require a skilled engineer on-call.
Each stage amplifies the one beneath it. Agentic AI without a foundation of observability, insight, and remediation is just a chatbot. The full stack is what makes agents operationally meaningful.
The term “agentic AI” is becoming overused. It’s worth being precise about what it means for network operations, and what it doesn’t.
An agentic system doesn’t just surface information or suggest actions. It can reason about a problem, take corrective action, and explain its decisions in plain language. The distinction matters: moving from “here’s an alert” to “here’s what I diagnosed, here’s what I did about it, and here’s why” is a fundamentally different operational experience.
There are two meaningful forms this takes in a network context:
Interactive agents respond to natural-language questions from operators. Instead of navigating multiple screens or running command-line workflows, an engineer asks, “Why is client ABC experiencing slow connections?” The agent investigates across the stack and returns an explanation with recommended next steps. The interface is conversational; the reasoning is expert-level.
Autonomous agents are system-initiated, they monitor continuously, predict conditions, and respond to network events within policy guardrails without waiting for a human to intervene. They handle auto-remediation, security response, and compliance workflows, then log what they did and why.
The common thread is that both types operate in natural language, both are designed to reflect the reasoning patterns of experienced network engineers, and both aim to make advanced operations accessible, even to teams without deep networking expertise.
RUCKUS’s answer to this shift is Agentic Operations, a new class of AI-powered agents now rolling out as part of the RUCKUS One platform. What makes the approach credible is that it isn’t built on a single product launch. It sits at the top of a carefully constructed AI stack, with each layer already deployed in production across thousands of customer environments.
The first three layers, observability, AIOps incident detection, and intent-based automated remediation, are live. They have already reduced mean time to resolution for incidents and eliminated hundreds of manual hours typically required for network fine-tuning. Agentic Operations builds on that proven foundation, introducing advanced autonomous reasoning as the next layer rather than a replacement for what’s already working.
The platform spans both wireless access points and wired ICX switching infrastructure through a unified management experience. That matters because real-world network issues rarely respect domain boundaries, a wireless client problem often traces back to a wired switch misconfiguration, and an agent that can only see one side of that equation will miss the root cause.
For interactive agents, the operational engine is DSE, the Digital Systems Engineer, an AI-powered assistant embedded in RUCKUS One. RUCKUS positions DSE not as a single generalist model, but as an orchestrator coordinating specialized agents with clearly defined scopes and domain-specific competence.
When an operator asks, “Why is the guest Wi-Fi slow in the lobby?”, the orchestrator decomposes the request, routes subtasks to the right specialist sub-agents, and synthesizes the results into a coherent answer. This architecture reflects a practical lesson from enterprise AI deployment: focused sub-agents with specific skillsets and bounded authority are easier to validate, govern, and improve over time than a single agent trying to do everything at once.
Governance: Autonomy Without Chaos
Giving AI agents the ability to change network configuration is powerful. Without guardrails, it’s also risky. RUCKUS’s governance model rests on four pillars:
The operating model is explicit: autonomous networking with human oversight. AI handles speed and complexity; humans retain responsibility for judgment, policy, and strategy.
RUCKUS Networks is rolling out Agentic Operations as part of the RUCKUS One platform. DSE and related agent capabilities are in active development, with customer-facing availability expanding over time.
Agentic Operations is rolling out in stages, but the directional arc is clear:
Near-term: Interactive agents improve troubleshooting, analytics, and guided remediation, giving IT teams an expert co-pilot for everyday operations.
Mid-term: Autonomous agents take on common remediation workflows, security response patterns, and performance optimization tasks within explicit policy boundaries.
Long-term: Self-optimizing networks increasingly tune themselves around business intent, user behavior, and predictive models, while people stay focused on governance and outcomes.
The destination, networks that increasingly help solve their own problems with humans focused on what requires human judgment, is being built layer by layer. For teams managing growing infrastructure with flat or shrinking headcount, that shift isn’t just a capability upgrade. It’s a different way of working.
120 times in a 100-minute presentation. Yes, that’s the count for the number of times speakers mentioned Artificial Intelligence (AI) at a recent tech conference! [1] It’s a reflection on how AI is on everyone’s mind, with enterprises large and small, eager to understand and explore how to use it in their operations.
Concepts such as agentic AI, autonomous systems, predictive intelligence, and frictionless customer experiences are dominating conversations in boardrooms and leadership agendas across industries.
AI is now a business priority, and the hunger to adopt it, is peaking with the eagerness to adopt AI stemming from the conviction of its potential to dramatically boost enterprise growth, performance, and revenue.
Yet, in practice, how many of these businesses have applied AI? Do real-life cases exist? How easy or difficult is it to put these into action?
At Aprecomm, we have asked ourselves the same question. Over the last few years we’ve been actively exploring AI, embedding it into our processes, and into our algorithms to meet real world needs and deliver tangible results.
This persistence has paid off. In February this year, at The Fast Mode Awards 2026, one of the telecom industry’s latest and most competitive recognition programs, Aprecomm and broadband service provider, Fibernet, were recognized with the AI & GenAI Pioneer | Telco – Impact award – an award that validated our efforts in delivering measurable impact through the application of AI technologies.
ACT Fibernet (ACT) is a valued and key Aprecomm customer, and one of India’s largest fixed-line broadband providers. ACT faced a deceptively simple challenge on the surface: customer churn was holding back potential growth and undermining planning certainty. The reason was customer impatience with the WiFi quality at home.
It wasn’t just a speed problem. It was the channel interference from neighboring networks, lag from device congestion, and bandwidth hogging by background applications that was quietly degrading the experience of the subscriber. And that gap between “the internet is working” and “the internet feels broken” is where trust was eroding and leading to churn.
The traditional “reactive” response of waiting for a complaint, dispatching a technician, and resolving the issue was no longer satisfying the customer. Moreover, it was also expensive, slow, and by the time it was resolved, the customer had already decided that they were unhappy.
ACT Fibernet needed something fundamentally different. They needed an AI that could see the problem before the customer did.
Aprecomm’s platform is built around a core insight: Quality of Experience (QoE) is not the same as Quality of Service. A network can be technically healthy while still delivering a poor experience. What matters is what the subscriber actually experiences. Like the video call that stutters, the game that lags, and the stream that buffers.
To close this gap, Aprecomm put into action, an AI-powered solution across ACT Fibernet’s home subscriber base.
The solution was Aprecomm-developed agentic AI solution, ACT SmartWi-Fi®. This platform works to optimize every device and application to enable a superior WiFi experience delivering among several other benefits, improved speed, reduced latency, and enhanced reliability.
Here is how the Aprecomm’s AI works in actual practice:
Continuous, real-time monitoring. The AI platform monitors WiFi performance at the application level. It monitors not just whether the connection is alive, but how each application is performing across every connected device. This generates a continuous stream of data that forms the basis for all downstream decisions.
Intelligent channel optimization. WiFi channels are a shared, contested resource. The AI continuously analyses channel utilization across the environment and automatically shifts devices and access points to less congested channels. This happens invisibly without subscriber involvement or a wait for a problem to be reported.
Traffic management by application priority. Not all traffic is equal. A video call has different latency requirements than a file download. Aprecomm’s QoE engine classifies traffic by application type and manages bandwidth allocation, accordingly, ensuring that high-priority, real-time applications get what they need, even when the network is under load.
Predictive issue resolution. Rather than waiting for a threshold breach or a support call, the platform identifies patterns that precede degradation and acts proactively. A device that is consistently underperforming, a channel that is trending toward saturation, a router exhibiting early signs of stress — the AI flags and responds to these signals before they become visible to the subscriber.
Unified visibility for support teams. ACT Fibernet’s support teams gained access to a real-time dashboard showing network health across the entire subscriber base. When a call comes in, agents have full context: device history, recent channel changes, application performance data. First-call resolution improves because the agent is no longer diagnosing blind.
Results started showing at the six-month mark post the deployment across ACT Fibernet’s home subscriber base.
Quality of Experience (QoE) scores rose significantly. As the AI optimized channels, managed traffic, and resolved issues proactively, subscribers began experiencing the kind of consistent, reliable connectivity that broadband providers promise but rarely deliver at scale. A 3X times improvement in speed was recorded. Latency dropped by 15%. Device QoE scores improved by an average of 20% over the 1.35m homes where deployment was complete.
Support call volumes fell. With the AI catching and resolving issues before subscribers noticed them, the volume of inbound support calls dropped by 25%.
As the experience improved and complaints decreased, subscriber retention improved. The customers who had been leaving because of unpredictable WiFi quality had fewer reasons to leave.
The ACT Fibernet deployment illustrates something that is easy to miss in the broader AI conversation: genuine AI maturity lies in its appropriate and specific use in the application.
Aprecomm deployed a system with a precise understanding of how WiFi degrades, how application performance maps to subscriber experience, and how proactive intervention translates into business outcomes. The AI use is interesting because the outcome is measurable and commercially useful.
For ISPs evaluating AI investments, this distinction matters enormously. Instead of focusing on whether a platform uses AI, it is more important to ask how AI is used and if it is successfully closing the gap between what the network provides and the experience subscribers expect.
For ACT Fibernet, over six months of deployment, the answer was yes. Ravi Karthik, Chief Marketing and Customer Experience Officer of ACT Fibernet, stated “We are thrilled to see the transformative impact of ACT SmartWi-Fi® on our customers’ digital lives. Our initial launch data validates our commitment to delivering our promise—ensuring a significantly superior online experience for our customers. Whether streaming on a Smart TV, working on a laptop, or browsing on a mobile device, ACT is redefining what high-performing internet looks like in Indian homes.”
Aprecomm manages over 7 million home and business locations and partners with more than 50 service providers worldwide. The company won both the Analytics & Intelligence Champion and the AI & GenAI Pioneer awards at The Fast Mode Awards 2026.
[1] https://timesofindia.indiatimes.com/technology/tech-news/sundar-pichai-responds-to-viral-ai-ai-ai-meme-elon-musk-tempted-to-join-in-the-fun/articleshow/110244042.cms
