Revolutionising Fleet Operations Through the Lens of AI-powered Analytics: Why We Invested in CameraMatics
Commercial fleets move the world’s economy. They carry parcels, deliver food, maintain our utilities, and build our cities. Yet operators of these fleets sit at the intersection of multiple converging pressures: increasing insurance premiums, rising fuel prices, and heightened regulatory scrutiny on driver safety, compliance and ESG reporting. The scale of the challenge is striking, with fuel accounting for 27% of the cost to run a HGV, fuel cost inflation is driving meaningful margin pressure. Road safety is increasingly under scrutiny, with over 43,000 vehicle-related fatalities in North America alone annually, 10,000 more per year than a decade ago and regulatory frameworks, like London’s Direct Vision Standard, are raising baseline requirements for large vehicle operators. This leaves fleet operators, many running thousands of vehicles, to managing all of this simultaneously, while also navigating the long-term shift towards electrification, demanding capital and operational transformation.
On top of the operational challenge, commercial transport is one of the largest sources of greenhouse gas emissions globally. Heavy duty trucks alone release almost 2 GtCO₂ worldwide annually, almost 5% of all global CO2 emissions. Cutting out inefficient fleet usage patterns and driving practices are a key way for any fleet operator to improve not just their emission footprint but also lower their total cost of ownership. However, many fleet operators do not have the operational insights available to unlock these inefficiencies and remain increasingly under pressure to show improved sustainability, as environmental disclosure requirements continue to become industry mainstream.
We believe the problem is structural, fundamentally driven by the widening mismatch of demand and supply of heavy vehicle drivers, where the lack of labour coupled with increasingly complex worksite conditions and the pressures of demanding schedules, is gradually increasing the risks that driver faces every day and indirectly the operational cost of the fleet operators. Historically commercial fleets have, if at all, tracked their vehicles using traditional dashcams and basic telematics systems. However, these systems are dated technologies and never designed for this new environment. Many fleet managers are therefore often working with incomplete, fragmented, or lagging datasets to optimise their businesses from both an economic and environmental standpoint. For example, traditional telematics provides limited coverage on mission critical areas around the vehicle, creating blind spots that leave external risks unaddressed. More importantly, traditional dashcams only focus on recording events once they occur, offering little help in enabling behavioural change to prevent the incidents from happening in the first place.
These pressures have driven the emergence of the video telematics market, which has been consistently growing 3x faster than basic telematics, reflecting the urgency with which operators are seeking economical solutions. Actionable video intelligence provides fleet managers the necessary visibility and predictive oversight to not just improve safety records but drive better fleet economics through greater fleet uptime, streamlined insurance workflows and reduced premiums, improve fuel efficiency and lower emissions. The proprietary data generated and analyzed in turn become core infrastructure on how these fleet operators manage their businesses going forward.
Enter CameraMatics, an AI-powered fleet intelligence platform that utilises video, sensor data, and machine learning to prevent accidents, coach drivers, manage compliance, and manage emissions across an entire commercial fleet from a single interface. This breadth is delivered as a genuinely integrated platform with flexibility and scalability in mind rather than a bolt-together of separate tools. This has set CameraMatics apart from point solutions, to earned trust from logistics, construction, utilities, field services and distribution enterprise fleets, such as Royal Mail, XPO, Calor Gas and US-listed Installed Building Products (IBP). Their emissions intelligence layer is a dimension we find particularly compelling. The platform’s emissions reporting and fuel efficiency optimisation tools gives fleet operators, for the first time in many cases, a clear, auditable view of their full emissions footprint, and a route to tackle it. Blume has been tracking the business since 2024, and its ability to demonstrate strong ROI, mission criticality with inherent positive climate impact fits exactly the type of technology businesses that Blume seeks to back.
Having built a world-class product and established strong market position in its home market of Ireland as well as the UK, the company is at an inflection point and ready to scale, both into the enterprise segment, and across geographies into the US and continental Europe. We are highly excited to partner with Mervyn and Simon, co-founders of CameraMatics to drive growth forward and build a category defining company.
Blume Equity is a European growth equity climate firm with offices in Amsterdam and London. Blume Equity partners with high-growth scale-ups across energy, industry and resilience. The Blume Equity team works in close partnership with management teams on the growth journey, drawing upon the team’s deep scale-up and sustainability expertise.
Sources:
Logistics UK — The Logistics Report 2025
U.S. Department for Transportation
International Renewable Energy Agency
Road safety and environmental impact sit at the heart of the commercial fleet challenge. Vehicle-related fatalities in North America have risen to over 43,000 annually — 10,000 more deaths per year than a decade ago — even as the industry has access to more technology than ever before. Heavy duty trucks alone contribute almost 2 GtCO₂ every year, nearly 5% of all global emissions, making decarbonisation of commercial transport an urgent priority. Yet the tools most operators rely on are fundamentally ill-suited to the task: traditional dashcams record incidents after the fact, offering little capability to change driver behaviour and prevent those incidents from occurring in the first place.