Until recently, at Brunner S.A.C, fuel tracking and management were done manually, causing delays and increasing costs due to lack of control and theft risks. Nowadays, automated systems are in place that facilitate fuel management using statistical technologies and business intelligence, allowing for more efficient management. This study focused on implementing a Business Intelligence-based web platform to optimize fuel management at Brunner S.A.C. The primary objective was to improve sensor data collection and analysis through dashboards, detecting fuel theft early and monitoring each vehicle's route for more rational fuel use. The research question was: To what extent could fuel control in Brunner's vehicles be improved with a Business Intelligence web application? The general hypothesis was that "Fuel control in Brunner's vehicles would significantly improve with this web platform." ...