The connected car is no longer a future prospect, but an established reality.
Sensors, ECUs and onboard systems generate a continuous flow of information every day, describing the vehicle’s health status, usage patterns and performance over time. This information asset continues to grow as vehicles evolve, becoming increasingly software-defined and integrated into complex digital ecosystems.
Today, the real challenge is no longer data collection, but the ability to transform data into knowledge and value across the entire mobility value chain. Fleet managers, rental operators, insurers, OEMs and service providers all require reliable, up-to-date and actionable information to support operational decisions, optimize costs and improve the end-customer experience.
Adding further complexity is the fact that vehicle data accompanies the asset throughout its entire lifecycle: from deployment to day-to-day operations, from maintenance to remarketing, and ultimately to decommissioning. Each phase generates different types of data, often collected by different systems and stakeholders, creating information silos that are difficult to integrate and fully leverage.
It is within this context that Car Remote Diagnostics plays a key role as one of the most strategic applications of advanced telematics. Every vehicle produces a wealth of technical data on a daily basis — from mileage and battery status to engine parameters, fault codes and maintenance-related information. In most cases, however, this data remains locked inside the vehicle, is not properly historized, and is highly fragmented, as it depends heavily on the brand or model.
The true value of remote diagnostics does not lie in the mere availability of data, but in the ability to turn it into timely and informed decisions. Anticipating failures, planning maintenance activities, reducing unplanned downtime and optimizing operating costs all mean translating technical information into concrete actions. In a context where vehicle efficiency directly impacts service profitability, the shift from a reactive to a predictive approach represents a paradigm change for all mobility stakeholders.
Without a platform capable of collecting, normalizing and making this data accessible in a structured way, much of its value remains untapped. Remote diagnostics is designed precisely to overcome this fragmentation. Through interoperable data management, it becomes possible to build a continuous, consistent and holistic view of vehicle health across its entire lifecycle, enabling new models of maintenance, prevention and service.
In a market characterized by strong technological heterogeneity, data interoperability is the true enabler for overcoming the limitations imposed by closed architectures and fragmented information. Today, each brand adopts different protocols, data formats and access logics. This fragmentation makes it difficult — if not impossible — to build a unified view of vehicle status, especially in multi-brand environments such as corporate fleets or rental operations. Without a layer of normalization, data remains tied to the individual vehicle, losing much of its operational and strategic value.
This is where interoperability becomes essential. It is not merely a technological issue, but a key enabler of new service models. From predictive maintenance to proactive fleet management, from reduced operational downtime to total cost of ownership optimization, the ability to integrate and orchestrate vehicle data becomes a tangible competitive advantage.
Looking ahead, as software-defined vehicles continue to evolve and the number of available data sources increases, interoperability will become even more central. Only platforms capable of managing complexity, ensuring scalability and fostering integration across diverse ecosystems will be able to support the growth of remote diagnostics and, more broadly, data-driven mobility.