We document how we implemented AI agents, route automation, and demand prediction for a logistics company, achieving 40% savings in operational costs.
A logistics company with over 200 vehicles and operations in three countries hired us to optimize their processes with AI. We implemented autonomous agents for route assignment, a demand prediction model based on historical data and weather, and an automatic alert system for preventive fleet maintenance. Within six months, the company reduced operational costs by 40%, improved delivery times by 25%, and decreased mechanical incidents by 60%.