Artificial intelligence is entering the operational management of tachograph data with an approach focused less on detecting infringements and more on handling their documentation. This is the context in which the solution developed by the Dutch company Roadsoft is positioned, designed to automate the entire cycle from analysing tachograph files to creating a compliance dossier ready for potential inspections. The system addresses a widespread challenge among transport companies: the difficulty of demonstrating in a structured way that violations have been properly managed.
The starting point remains the data generated by digital tachographs, periodically downloaded from heavy goods vehicles and driver cards. These data flows are integrated with telematics platforms and automatically sent to Roadsoft’s cloud system, including through integrations with other operators. The software verifies the completeness and correctness of the downloaded material, reducing the risk of penalties linked to missing data or incomplete archives.
Once acquired, the data are analysed in line with European rules on driving and rest times, particularly Regulation 561/2006, alongside national provisions. Regulatory developments and clarifications on the use of second-generation tachographs have tightened controls, increasing pressure on companies. In this context, Roadsoft transforms each detected infringement into an operational task, assigned with priority and responsibility, moving beyond the logic of a simple list of violations.
A key element of the system is the AI-based Digital Assistant, which intervenes automatically when an anomaly is identified. The system generates an event and initiates direct contact with the driver via phone call or WhatsApp message. The driver receives a clear explanation of the infringement, including date, time and operational context, translated into accessible language rather than technical codes. During the interaction, the artificial intelligence guides the dialogue with structured but adaptable questions, aimed at gathering information to contextualise the violation. The system is designed to obtain complete and consistent responses, reducing fragmented communication. The information collected may include operational causes, planning issues, clerical errors or exceptional circumstances affecting how the infringement is interpreted.
A significant feature is the system’s ability to interpret natural language and convert it into structured data. Roadsoft explains that drivers’ responses are summarised and automatically linked to the original event, eliminating manual tasks such as listening to recordings or transcribing conversations. This makes it possible to build an information base that can also be used for further analysis, for example to identify recurring violations or issues related to specific routes or clients. At the end of the process, the system generates a digital infringement dossier. The conversation is automatically transcribed and organised into structured fields such as reason, responsibility and planned corrective actions. This approach allows companies to demonstrate not only the existence of a violation but also the actions taken to manage it.
All stages are recorded in a complete audit trail, including detection, contact with the driver and any subsequent actions. Roadsoft highlights that this element is central to demonstrating “active management” of infringements, an aspect that is becoming increasingly important in inspections by European authorities. The system’s impact is primarily seen in reducing the internal administrative burden. Cases analysed by Roadsoft indicate that activities such as phone calls, email exchanges and manual file updates are automated, enabling transport managers to focus on more complex cases. In this context, artificial intelligence does not replace decision-making but supports the operational and repetitive aspects of the process.
