Artificial intelligence in logistics beyond the use of robots.

One of our customers, a company that distributes large and expensive machine parts for its regular customers, had a problem; Long-term storage of these parts was expensive and impractical because demand was irregular and difficult to predict. The customer sought our help to reduce warehousing costs while ensuring they always had enough parts in stock to service their customers.

Our team of experts in artificial intelligence sat down to find a solution; We developed a similarly structured AI pipeline as in the presented use case on customer relationship management to model customer demand and make predictions about demand. In this way, the customer was able to optimize its inventories and reduce storage costs without experiencing delivery bottlenecks. Both jobs are a good example of how similar problems can be solved regularly with similar algorithms, but can also differ significantly due to different data frequencies.

We are proud to have been able to help improve our client’s operations and help them become more competitive. By leveraging AI and data analytics, we were able to develop a solution that accurately and efficiently modeled our customers’ needs, reducing storage and inventory management costs.


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