Hall: 4, Stand-Nr.: 4B46 - At LogiMAT, the SAP service provider abat will once again inform visitors about innovative solutions for an intelligent and stable supply chain at booth 4B46 in hall 4. Using practical use cases, experts will demonstrate how AI and RPA can complement and optimize existing SAP solutions such as SAP Extended Warehouse Management (EWM) and SAP S/4HANA Transportation Management (TM).
EWM meets AI: Efficient goods receipt processes
A scenario on the stand shows how products are recognized by artificial intelligence and automatically booked in SAP EWM. The AI analyzes an image of the objects and counts them automatically. The resulting data is seamlessly posted to the EWM system. This use case demonstrates how automation and AI can increase efficiency in warehouse management.
TM and Large Language Models: Natural language as an interface to logistics
Another future-oriented scenario at the abat booth is the integration of Large Language Models (LLMs) into SAP S/4HANA TM. Here, AI specialists will demonstrate an innovative approach to making transport management data accessible via natural language. For example, a user could ask a chatbot: "Are all my transport orders with the destination Munich already planned?" and receive information in real time based on the available data. This use case already shows the potential of how language models can simplify the usability of complex logistics systems.
Combining Innovation and Practice
With these concise practical examples, abat once again shows how the future of logistics can be actively shaped. The focus is on the combination of proven SAP solutions with innovative technologies. Visitors to LogiMAT 2025 can see these groundbreaking developments for themselves and experience how AI, RPA and SAP S/4HANA work hand in hand to make processes more efficient and user-friendly at Stand 4B46 in Hall 4 from March 11 to 13.
EWM meets AI: Efficient goods receipt processes
A scenario on the stand shows how products are recognized by artificial intelligence and automatically booked in SAP EWM. The AI analyzes an image of the objects and counts them automatically. The resulting data is seamlessly posted to the EWM system. This use case demonstrates how automation and AI can increase efficiency in warehouse management.
TM and Large Language Models: Natural language as an interface to logistics
Another future-oriented scenario at the abat booth is the integration of Large Language Models (LLMs) into SAP S/4HANA TM. Here, AI specialists will demonstrate an innovative approach to making transport management data accessible via natural language. For example, a user could ask a chatbot: "Are all my transport orders with the destination Munich already planned?" and receive information in real time based on the available data. This use case already shows the potential of how language models can simplify the usability of complex logistics systems.
Combining Innovation and Practice
With these concise practical examples, abat once again shows how the future of logistics can be actively shaped. The focus is on the combination of proven SAP solutions with innovative technologies. Visitors to LogiMAT 2025 can see these groundbreaking developments for themselves and experience how AI, RPA and SAP S/4HANA work hand in hand to make processes more efficient and user-friendly at Stand 4B46 in Hall 4 from March 11 to 13.
