Paper remains part of daily work in many logistics processes, and probably will for some time.
Structured information adds possibilities: systems can check it, pass it on and use it within a process. This is the purpose of eFTI, the European regulation on electronic freight transport information.
Since January 2026, platforms and service providers have been able to prepare for operation. From 9 July 2027, authorities in all EU member states must accept freight data that companies provide through certified eFTI platforms.
What interests me most is the shared data structure behind it.
When information about orders, goods, vehicles, routes, permits and participants is structured, systems can identify issues earlier:
- Which detail is missing?
- Which information is contradictory?
- Which condition belongs to which transport?
- Who may see which data?
- What needs clarifying before departure?
This is a prerequisite for useful AI in logistics. Even a good system struggles to prepare work reliably when the same information appears differently in five documents.
AI know-how for logistics professionals in 2 minutes
What does machine-readable mean?
Machine-readable information gives individual fields an unambiguous meaning. A system can identify a registration number, a time window, a dangerous-goods attribute or a responsible person.
This allows AI to compare information, apply rules and highlight discrepancies.
Companies can ask whether their essential information is structured so their processes can use it reliably.
At ViMoKi, we work on understanding documents, structuring information and making open points visible. People make the decisions. The aim is to reduce the time teams spend searching and asking follow-up questions.