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A future-proof Machine Learning platform for Stolt-Nielsen

Set the standard

Stolt-Nielsen, an international player in logistics and shipping, has been using AI technology for some time. For instance, to provide faster price indications and to better match capacity supply and demand.

However, these models were developed both internally and externally, data was hosted and managed at different locations, and that was causing increasing challenges around scalability and manageability. Stolt-Nielsen's question was:

Can you build us a platform on which we can land our various AI initiatives, now, and in the future, including a fixed set of standards and managed within our own organization?


Based on this issue, we mapped out a new architecture and developed a Machine Learning platform in Azure. On this platform, not only the already existing machine learning use case can run, but it also provides a standard on which new AI use cases can be developed.