Machine learning has been of significant help as it has helped businesses in abundant ways. ML is a subset of AI and does not need to be directly trained like AI to perform tasks. ML is used for prediction analysis in businesses, which we will learn in this case study. Alibaba created a solution that can forecast time-based on initial partial trajectories. For someone in the logistics business, this is indispensable. It is important to predict how long a driver will have his taxi occupied. If a dispatcher got estimates about the taxi driver’s current ride time, they could better recognize which driver to allocate for each pickup request.


Most on-demand taxi platforms require a way to know the estimated time which driver will be occupied. Our client was using Google Matrix API for this purpose, but they discovered that it was highly unreliable in their country. Thus, our client approached us to build a robust and reliable solution that could make their business processes much easier. Therefore, Alibaba Systems built these robust solutions using machine learning models to predict the approximate time the driver will stay busy with the taxi. Though it might be super accurate, however, the difference would be negligible and reliable to the previous solutions they used.

The Business Challenge




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