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Predictive maintenance alerts are only half the story. See how agentic AI and the Geotab MCP Connector turn fault data into action for UK fleets. Predictive maintenance was never the finish line – here’s what comes after the alert? A fault alert three weeks before a breakdown is useful. A fault alert three weeks before a breakdown, automatically matched to your nearest off-peak service slot and cross-checked against the vehicle’s job schedule, is a different thing entirely. That’s the distinction Geotab’s Abhinav Vasu draws in a recent post on predictive maintenance and agentic AI, and it’s one worth sitting with – because most fleets, even ones already running telematics, are still only halfway to what predictive maintenance fleet AI can actually deliver. The alert was never the hard part Ask any fleet operator what keeps them up at night and the answer is almost always unplanned downtime. Ask how much warning they had before their last breakdown, and the answer is usually none. Predictive fleet maintenance closes that gap – an anomaly in engine or component data gets flagged weeks before it becomes a roadside failure. That part of the technology has matured. What hasn’t matured, in most fleets, is what happens after the alert lands. Vasu’s point is that the real value only shows up once warnings are reliable enough to plan around: None of that requires new hardware. It requires trusting the data enough to change how the fleet operates around it and that’s the harder, slower shift. What “acting on it” actually looks like The next step Geotab describes isn’t just detection – it’s a system that finds the nearest available slot, checks it against the vehicle’s operational calendar, and hands the fleet manager a completed recommendation rather than a raw alert. The manager still makes the call. The system has already done the legwork. This is where the Geotab MCP Connector comes in. It’s a live bridge between fleet data and the AI tools fleet managers are already using day to day, ChatGPT, Claude, Microsoft Copilot, so operational questions, alerts, and maintenance scheduling can be handled from inside those tools, without the underlying data ever leaving the Geotab platform. LEVL is a Geotab MCP Connector launch partner, which means we’ve been working with this capability from the start – not as a slide in a roadmap deck, but as something we’re actively building into how our customers manage their fleets. The foundation that makes any of this work There’s a line in Vasu’s piece that’s easy to skim past: the fleets getting the most from this aren’t waiting for the technology to mature – they’re investing now in clean, well-connected data. That’s the unglamorous prerequisite behind every AI capability in this space. A recommendation engine is only as good as the data feeding it; noisy or fragmented data produces noisy or fragmented recommendations, agentic or not. That’s also, not coincidentally, where a lot of our work with fleets starts – getting devices, data feeds, and workflows properly connected before layering anything more advanced on top. Where this leaves fleet managers today You don’t need to have an AI strategy to benefit from this shift. You need: If you’re curious what the MCP Connector looks like in practice for a UK fleet, or want a straight assessment of how ready your current data setup is for it, get in touch with LEVL – we’re happy to walk through it. Source: Abhinav Vasu, “The failure you didn’t predict is more than a repair bill,” Geotab Blog, 18 August 2026.

Predictive maintenance uses real-time telematics data to spot vehicle faults before they cause breakdowns, so repairs get scheduled on evidence, not a fixed calendar. If your workshop still books vehicles in on a fixed interval, you’re likely paying twice: once for the healthy vehicles serviced early, and again for the faults that develop between scheduled visits and turn into breakdowns anyway. Predictive maintenance closes that gap by using what the vehicle is actually telling you, in real time. What is predictive maintenance for fleets? Predictive maintenance (PdM) is a data-led approach to vehicle servicing. Instead of following a fixed mileage or time-based schedule, telematics hardware continuously monitors vehicle health – engine diagnostics, fault codes, tyre pressure, wheel alignment and usage patterns and surfaces developing issues through dashboards and alerts in your fleet management software. It’s the third and most advanced stage in fleet maintenance strategy: Maintenance type How it works Downtime Cost profile Reactive Repairs happen after a breakdown or fault Highest – parts ordered urgently, vehicle off the road until fixed Highest – emergency repairs, hire cover often needed Preventive Vehicles serviced on a fixed schedule (age, mileage, duty cycle) Lower – assuming intervals are correctly set Lower – but faults between services still cause reactive spend Predictive Real-time data flags developing faults before failure Lowest – parts and labour planned in advance Lowest – servicing based on actual need, not a fixed date How does telematics data enable predictive maintenance? A telematics device fitted to each vehicle captures a continuous stream of diagnostic trouble code (DTC) data, giving the workshop visibility into: This data flows into a fleet management platform like MyGeotab, where it’s translated into dashboards and alerts the workshop can act on directly – rather than waiting for a driver to flag a warning light, or for the next scheduled inspection to catch it. The benefits of predictive maintenance for large fleets For fleets running over 100 vehicles, the shift from preventive to predictive maintenance changes how the whole workshop operates: It isn’t without a learning curve. Moving to predictive maintenance takes time to implement properly, and workshop teams need training to triage fault codes accurately – not every alert needs an immediate response, and understanding which ones do is what actually reduces workshop visits rather than adding to them. Where the real-world savings come from The financial case for predictive maintenance rests on three things: fewer emergency repairs, less reliance on hire vehicles to cover downtime, and a longer service life for vehicles kept in better condition throughout. We see the same principle play out with our own customers, even outside pure maintenance use cases. With Milk & More, one of the UK’s largest EV delivery fleets, real-time visibility into vehicle condition and driver behaviour through MyGeotab has helped: None of that came from a fixed schedule. It came from acting on what the data was showing, as it happened. How to start integrating predictive maintenance into your fleet You don’t need to overhaul your entire maintenance process to start benefiting from predictive data. Fleets that make the switch successfully tend to follow the same three steps: Why an open, multi-OEM platform matters for mixed fleets One of the practical challenges for fleets running both EVs and ICE vehicles is getting consistent, comparable data across both. This is where an open, vehicle-agnostic telematics platform matters: it lets a fleet manager see engine health, fault codes and efficiency across every vehicle type on one screen, instead of juggling separate systems for diesel and electric. As UK fleets continue their transition to electric, that kind of multi-OEM visibility, sometimes referred to as multistream telematics, is becoming the baseline standard, not a nice-to-have. Frequently Asked Questions What is predictive maintenance in fleet management? Predictive maintenance is a data-driven approach where real-time telematics data, engine diagnostics, fault codes, tyre pressure and usage patterns, is used to identify developing vehicle faults before they cause a breakdown, allowing repairs to be scheduled proactively rather than reactively. How is predictive maintenance different from preventive maintenance? Preventive maintenance follows a fixed schedule based on mileage, age or duty cycle, regardless of the vehicle’s actual condition. Predictive maintenance uses real-time data to base servicing on actual vehicle health, which reduces both over-servicing and the risk of faults developing between scheduled visits. What data is used for predictive maintenance? Common data points include engine diagnostics and fault codes, tyre pressure, wheel alignment, usage patterns, and – for EVs – battery and charging health. This data is captured by a telematics device and surfaced through a fleet management platform such as MyGeotab. Does predictive maintenance work for mixed EV and diesel fleets? Yes, provided the telematics platform is vehicle-agnostic. An open platform can pull comparable health and diagnostic data across both EVs and ICE vehicles, giving fleet managers a single view rather than separate systems for each vehicle type. How much can predictive maintenance save a fleet? Savings vary by fleet size and fault type, but they come from three main areas: fewer emergency repairs, reduced need for hire vehicles to cover downtime, and longer vehicle service life from proactive health management. Do fleet managers need extra training to use predictive maintenance data? Some, yes. The main investment isn’t in the data itself but in building a triage workflow – knowing which fault codes need immediate action and which can be scheduled into the next maintenance window. Without this, teams can be overwhelmed by alerts rather than helped by them. LEVL Telematics is Geotab’s Elite Specialised Partner and the UK’s No.1 Geotab value added reseller. If you’d like to see what predictive maintenance data looks like for your own fleet, get in touch with our team.

Fleet management software should reduce your operating costs, not add to them. Fleet management software should cut your operating costs, not add to them. Yet plenty of UK fleet operators find their telematics investment falls flat. Having worked with transport managers across the country, LEVL Telematics has seen the same costly mistakes come up again and again — and knows how to avoid them. Here are the six that quietly drain budgets, and how to fix them. 1. Poor data migration Switching providers doesn’t automatically clean up your data — messy records and duplicates just follow you into the new system, often producing worse reporting than before. The fix is a proper audit before transfer: review what you have, standardise formats, and migrate selectively. Bring over what’s genuinely useful and leave the rest behind. It takes upfront time, but it means cleaner reporting and a faster, lighter rollout. 2. Skipping driver training Even the best software is worthless if drivers don’t know how to use it. Treating training as optional almost always backfires — staff notice the neglect, adoption suffers, and you end up paying for features nobody touches. Structured onboarding, hands-on practice with real scenarios, and ongoing support (not a one-off session) drive faster returns and fewer frustrated drivers. 3. No integration planning If your telematics platform can’t talk to payroll, fuel cards, or accounting software, someone ends up manually shuttling data between systems — slow and error-prone. Some fleets don’t discover missing integrations until months after go-live. Confirm compatibility with your existing tools before signing anything, check API availability, and get IT, finance, and operations into the vendor conversation early. 4. Unclear objectives Rolling out new software without defined goals is like driving without a destination — you’re moving, but you can’t tell if you’re getting anywhere. “Improve efficiency” isn’t a target. Set specific, measurable ones instead: cut fuel consumption by 15% in six months, or accident rates by 20% in a year. Clear KPIs make ROI easy to prove and keep teams aligned, even if targets need tweaking as you learn the system. 5. Ignoring the data you collect Modern fleet software throws off huge volumes of data on driving behaviour, fuel use, vehicle health, and routes — but data nobody reviews is just noise. Operators who don’t act on it miss real opportunities to cut fuel costs, prevent breakdowns, and improve safety. Build in regular review schedules, focus reporting on what’s actionable, and use the data to coach drivers directly. 6. Copying old processes A software switch is often used to just recreate the old workflow in a new system — which means recreating the old problems too. It’s actually the ideal moment to question “the way we’ve always done it.” Review current processes, work with your provider to redesign what isn’t working, and phase changes in gradually so teams aren’t overwhelmed. Expect some resistance, but the payoff is often hidden savings you didn’t know were there. Warning signs your implementation is failing A few red flags to watch for: staff running unofficial spreadsheets alongside the “official” system, reports that take longer than they used to, costs that haven’t budged six months in, or drivers describing the software as just another chore. Each of these usually points back to one of the mistakes above. What to look for in fleet software A good platform balances real functionality with usability, supports UK compliance needs (DVSA, FORS, OCRS), and — increasingly — has strong EV support, since more fleets are electrifying and need live data on charging, range, and energy use. Just as important as the software itself is the provider’s implementation support: migration help, real training, and process guidance matter more than a slick demo. About LEVL Telematics: LEVL is a UK telematics provider and authorised Geotab reseller. Rather than just selling software, LEVL works alongside fleet managers to configure systems around their actual operations — covering AI dash cams with in-cab alerts, real-time GPS tracking, predictive maintenance alerts, driver behaviour monitoring, and full EV fleet support. Contact LEVL Telematics to discuss how the right implementation can cut your fleet costs and improve compliance.

See how telematics data helps fleet operators reduce costs, strengthen safety and stay compliant — whatever your mix of vehicles. If you manage vehicles for a living, you’ve almost certainly heard the word “telematics” thrown around in meetings, supplier pitches, and industry articles. But what does it actually mean, and why has it become such a central part of modern fleet operations? This guide breaks it down in plain terms — what telematics is, how it works, and how fleet managers put it to use day to day. What is telematics? Telematics combines two ideas: telecommunications (sending information over a distance) and informatics (using computers to process and interpret data). Put simply, telematics is the technology that lets you monitor a vehicle — or an entire fleet of vehicles, vans, trucks and other mobile assets — remotely, in real time. It’s sometimes referred to as fleet tracking or GPS vehicle tracking, but modern telematics goes well beyond a dot on a map. Today’s systems capture everything from location and speed to engine health, driver behaviour and fuel use, then present it in dashboards and reports that fleet managers can act on. How does telematics work? At its core, a telematics system relies on a small onboard device — often called a “black box” — that plugs into a vehicle’s diagnostic port (OBD-II or CAN-bus, depending on the vehicle type). This device pulls data directly from the vehicle’s systems and uses a built-in SIM and modem to transmit it securely to a cloud-based fleet management platform. From there, fleet management software takes over: decoding the raw data, turning it into readable reports and dashboards, and flagging anything that needs attention through alerts and notifications. The best platforms also apply data analytics to go a step further — helping fleets benchmark their performance against similar operations, or spot vehicle health issues before they turn into breakdowns. The data journey, in short: What data does telematics actually collect? Depending on the hardware and sensors connected, a telematics system can capture a wide range of information, including: Many fleets now pair telematics with dash cameras, creating what’s known as video telematics. Combining location and driving data with video footage gives managers far richer context around safety events — and with AI-enabled cameras, drivers can get real-time in-cab feedback to correct risky habits before they become costly ones. How is telematics used in fleet management? Telematics data touches almost every part of fleet operations. Here’s how fleet managers typically put it to work: Productivity — Real-time GPS tracking, trip reporting and smarter routing and dispatching help teams get more done with the vehicles they already have, and keep customers better informed along the way. Driver safety — In-cab coaching, driver behaviour reporting, collision alerts and AI-powered dash cameras all help build a stronger safety culture and reduce risk on the road. Fleet optimisation — Predictive maintenance and remote diagnostics help catch problems early, while fuel management tools identify idling and other habits that quietly inflate running costs. Compliance — A single view of tachograph data, duty of care obligations, working time rules and vehicle checks makes it far easier to stay on the right side of regulation — and to prove it, if ever asked. Integration — Telematics rarely works in isolation. The most effective fleets connect it with other systems, from dash cam platforms to CRM and ERP software, so data flows freely instead of sitting in silos. Sustainability — By reducing fuel consumption and emissions, telematics also supports fleets on the road to electrification — and helps manage EVs effectively once they’re on the road. Benefits of telematics for larger fleets The value of telematics scales with fleet size. For operations running significant numbers of vehicles, a good telematics platform can deliver: How telematics supports fleet electrification Electrifying a fleet is one of the biggest operational decisions many organisations will make, and telematics data plays a central role at every stage. Before the transition, telematics helps build the case for electrification by revealing: This data allows fleet managers to plan a phased rollout with confidence — matching the right EVs to the right routes and duty cycles, rather than guessing. After the transition, EVs typically need closer monitoring than diesel or petrol vehicles to get the most out of them. Key metrics to keep an eye on include: How to choose a telematics provider Not all telematics platforms are built the same way, and the right choice depends on what your fleet actually needs. A few things worth weighing up: Does it match your operational priorities? Some platforms are built primarily around safety, others around maintenance, compliance or asset visibility. Be clear on what problem you’re solving first. What does onboarding and support look like? A telematics system only delivers value once your team is using it properly and consistently. Strong implementation support makes the difference between a smooth rollout and a stalled one. What’s the real return on investment? The cheapest monthly rate doesn’t always represent the best value. Look at the outcomes a platform helps you achieve — reduced risk, better asset health, fewer breakdowns — rather than price alone. Can it grow with you? Your fleet’s needs will change as it grows or evolves. Look for a platform built on an open architecture, with the flexibility to add integrations, customise dashboards and adjust rules as your operation changes — without being locked in. Why fleets choose LEVL for telematics As a Geotab Elite Specialised Partner, LEVL combines the reach and reliability of Geotab’s global telematics platform with the hands-on, UK-based support that fleet managers actually need day to day. We work with fleets of every size and sector — from logistics and retail to construction and passenger transport — helping them turn telematics data into practical decisions around safety, compliance, fuel use and vehicle uptime. Whether you’re just starting to explore telematics or looking to get more value from an existing system, our team is on hand to help

From lower insurance costs to fewer accidents, AI dash cams are transforming fleet risk management From reducing accidents to lowering insurance costs, AI dash cams are helping fleets take control of risk in real time. Fleet safety technology is evolving rapidly. While traditional dash cams once provided a major step forward in visibility, modern fleets are now shifting towards AI dash cams to improve safety, reduce risk and drive operational efficiency. The difference is simple. Traditional cameras record incidents. AI dash cams help prevent them. The limitations of traditional dash cams in fleet safety Traditional dash cams have long been used across fleets to capture footage and provide evidence after an incident. They offer visibility, but they are inherently reactive. Footage must be manually reviewed, often taking hours of administrative time. Drivers receive feedback long after the event has occurred, limiting the ability to influence behaviour in real time. As a result, traditional dash cams support investigation, but they do little to actively improve driver performance or reduce incidents as they happen. For fleets focused on improving safety outcomes, this delay creates a significant gap between insight and action. How AI dash cams are transforming modern fleets AI dash cams represent the next generation of video telematics. By combining computer vision with telematics data, these systems analyse driver behaviour in real time and provide instant feedback inside the vehicle. AI-powered driver monitoring systems can detect key risk indicators such as distracted driving, fatigue, harsh braking and unsafe following distances. When these behaviours are identified, drivers receive immediate in-cab alerts, allowing them to correct their actions before a situation escalates. This shift from reactive recording to proactive prevention is why AI dash cams for fleets are becoming the new standard. Real-time coaching and its impact on driver behaviour One of the most significant advantages of AI fleet safety technology is real-time coaching. Instead of reviewing incidents days later, fleet managers can rely on systems that intervene in the moment. This immediate feedback loop helps drivers build safer habits over time. Rather than being corrected retrospectively, behaviour is adjusted during the journey itself. Fleets that adopt AI dash cams often see measurable improvements in driver performance, with reductions in risky behaviours and fewer on-road incidents. The value comes not just from the data collected, but from how quickly that data is used to influence outcomes. The business benefits of AI dash cams for fleets Beyond safety, AI dash cams deliver clear commercial benefits. By automatically identifying and prioritising high-risk events, they remove the need for manual video review, reducing operational workload and saving time. The integration of video telematics also strengthens a fleet’s ability to defend against false claims, providing clear, contextual evidence when incidents occur. This can lead to lower insurance premiums and improved claims outcomes. At the same time, fewer incidents mean reduced vehicle downtime, lower repair costs and improved fleet availability. Over time, this contributes to a lower total cost of ownership and stronger overall fleet performance. A shift from reactive safety to predictive risk management The rise of AI dash cams reflects a broader shift in how fleets approach safety. It is no longer enough to simply record and review incidents. Modern fleets are adopting predictive, data-driven approaches that focus on preventing risk before it materialises. AI fleet safety systems enable continuous monitoring, real-time intervention and ongoing performance improvement. Safety becomes embedded into daily operations rather than treated as a post-incident process. This shift is redefining what effective fleet safety looks like. How LEVL supports AI-powered fleet safety At LEVL, we help fleets implement AI dash cams as part of a connected safety ecosystem. By integrating leading video telematics solutions such as Mantis, Lytx and VisionTrack with Geotab’s telematics platform, we provide a unified view of driver behaviour, vehicle performance and risk. This approach enables fleets to move beyond basic monitoring and towards predictive risk intelligence. With real-time insights and automated coaching, organisations can take a proactive approach to safety while improving operational efficiency. The future of fleet safety technology Traditional dash cams laid the foundation for fleet visibility, but AI dash cams are defining the future of fleet safety. Fleets that continue to rely solely on reactive systems risk falling behind. Those adopting AI-powered video telematics are gaining the ability to prevent incidents, improve driver behaviour and reduce operational costs. Book a demo and discover how modern fleets are using AI-powered video telematics to reduce collisions, improve driver behaviour and lower operational costs.

How real-time vehicle visibility helps field service operators cut downtime and make faster, smarter decisions Field service fleet visibility is essential for improving performance, efficiency, and customer experience. Yet many fleets still rely on fragmented, delayed, or incomplete data to make decisions. That gap is where performance is lost. The problem with partial visibility In many fleets, critical information lives in silos. Vehicle tracking, driver behaviour, and maintenance records are all captured – but rarely connected. Managers are left piecing together a picture after the fact, reacting instead of leading. This lack of fleet data visibility slows decision-making and creates inefficiencies across the board. Downtime increases, routes become less efficient, and small issues escalate into costly problems. The impact doesn’t stop internally. Customers feel it too – through delays, missed expectations, and inconsistent service. What happens when fleet visibility improves When field service fleet visibility is achieved in real time and in context, operations shift from reactive to proactive. Decisions that once took hours can be made instantly. Potential issues are identified early, reducing breakdowns and keeping vehicles on the road. Driver performance improves through clear, actionable insights, while routes become more efficient and fuel usage drops. This level of real-time fleet data visibility doesn’t just improve internal operations – it directly impacts customer experience. Accurate ETAs, fewer disruptions, and more reliable service build trust and long-term loyalty. Turning fleet data into actionable insight Collecting data is no longer the challenge. Most fleets already have access to vast amounts of information through telematics and connected systems. The real issue is turning that data into something meaningful. Without clarity, data becomes noise. LEVL helps fleets cut through that noise by transforming complex datasets into clear, actionable insights. Instead of navigating multiple dashboards, teams gain a single, unified view of their operations, making it easier to act quickly and confidently. This is where fleet performance optimisation happens, not from more data, but from better visibility. The fleets pulling ahead The fleets gaining a competitive edge aren’t the ones collecting the most data. They’re the ones using field service fleet visibility to its full potential. They make faster decisions, reduce inefficiencies, and deliver a more consistent service, without adding operational complexity. In a landscape where margins are tight and expectations are high, that advantage compounds quickly. Discover why field service fleet visibility is essential for improving efficiency, reducing downtime, and making smarter real-time decisions.