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La Poste Develops AI Digital Twin to Strengthen its Logistics Operations

IoT

Business Honor
23 June, 2025

La Poste, in collaboration with Pathway, creates an AI-powered digital twin, allowing real-time ETA predictions, reducing costs, and transforming logistics operations significantly.

The French postal service, La Poste, is currently collaborating with Pathway, a data management business, to develop a digital twin of its entire network. In order to strengthen its logistics operations, the new technology offers major savings in costs, improved productivity, and faster delivery times with the use of real-time AI and IoT data.

More than 16 million GPS points are generated every year by La Poste's logistics network that handles more than 400 truck movements every single day across 17 industrial platforms. Yet it was difficult to use this data effectively because of outdated systems. La Poste is able to handle all of this data in real time due to its collaboration with Pathway and the incorporation of its Rust-based streaming engine. It provides the business better visibility and control over its automobiles through the use of highly accurate sub-second bb (ETA) predictions.

This new technology predicts ETAs, removes and analyzes raw GPS data, and continuously trains and becomes improved based on actual truck arrival times. Neither of these requires replacing La Poste's present infrastructure. Real digital twin—a smart, AI-powered version of the network that offers continuous monitoring, analysis, and alerts—is the final result.

The benefits have been significant. La Poste reduced the cost of capital on its automobiles by over 10% and IoT platform ownership costs by 50%, with additional savings expected to reach 16%. These findings are referred to as a "paradigm shift" with an "enormous" return on investment by Jean-Paul Fabre, Head of Technological Innovation at La Poste. Real-time data is important to modern logistics, according to Claire Nouet, COO at Pathway.

This collaboration reflects a shift towards a future where transport fleets are adaptive and are autonomous machines. Traditional delivery models could soon be replaced by the smart and predictive environment of logistics systems that have the ability to not only respond fast to delays but also to prevent them before they occur.