Since historical data is stored in the system, and these data quantities are often quite extensive, users find it challenging to filter out the necessary information. Additionally, there are instances where providing clients with an appropriate price is required, while ensuring that the price remains profitable for the company. It can take time to review past orders, suitable routes, cargo quantities, vehicle selection, and transshipment volumes. All of these factors contribute to the final cost, which needs evaluation.

At this juncture, a developed module comes into play, designed to assist with artificial intelligence. By assessing all criteria, it presents the best price that suits both the client and the company. The system aids in determining whether a price is beneficial and will yield profit. The system operates on a recommendation principle, with the user making the final decision, which they can adjust according to their preferences.