Problem

Lilli Trans Sp. z o.o., a taxi operator handling nearly one million kilometers per month, identified the need to optimize its route planning process. The dynamic nature of operations and numerous constraints—such as passenger counts, time windows, and maximum driver working hours—made dispatcher decisions increasingly inefficient. The goal of the project was to develop an artificial intelligence algorithm that would reduce the number of kilometers driven while ensuring passengers were transported smoothly to their destinations.

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Solution

We developed an AI-based algorithm that analyzes ride demand and operational conditions in real time, such as passenger numbers and time windows. Based on this data, it generates optimized route recommendations for dispatchers, who then make the final decisions. The algorithm also considers maximum driver working hours to ensure compliance with regulations. Our solution was integrated with the client’s internal system, and the data collected during operation is archived for historical analysis and continuous model improvement.

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Result

With the implementation of the Edge AI algorithm, Lilli Trans Sp. z o.o. reduced the number of kilometers driven, generating monthly savings of several tens of thousands of PLN. The system improved operational efficiency and eased the workload of dispatchers, allowing them to focus on overseeing ride execution. Our solution contributed to more efficient fleet utilization, strengthening the company’s position in the transportation market.