Starting situation
In an internationally operating trading company with thousands of branches worldwide, enormous quantities of goods are moved daily. To ensure that logistics processes run smoothly, information on packaging and boxes must be reliably captured and processed.
Up to now, this has primarily meant one thing: a high manual effort. Employees had to check, compare, and validate data. A time-consuming process with a high potential for errors. The goal was therefore to make these processes more intelligent and significantly more efficient through AI-based automation.
Challenges
Process high volumes of logistical data
Large amounts of package and packaging information had to be reliably checked daily.
Reduce manual process steps
Existing testing and validation processes caused a high personnel effort.
Manage different data qualities
Deviating symbols, labels, and inputs complicated automatic processing.
Increase process speed
Validations had to be faster without compromising accuracy.
Ensure high availability
The solution had to be designed for stability and scalability for worldwide deployment.
Reliably integrate AI into operational processes
The neural network had to be integrated into existing processes in a comprehensible and secure manner.
Solution
What our expert says
Alexander Dolgopolsky
Head of Data & Artificial Intelligence
„In the AI environment, success is not solely determined by technology, but primarily by the right use case and its integration into the business process. Then, intelligent automation creates real business added value.“
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