Enhancing Rail Madad with AI-Powered Complaint Management System

Indian Railways’ Rail Madad facilitates passenger grievance reporting but relies heavily on manual triage across 52 departments, creating bottlenecks for multimedia complaints. This research presents an AI-driven pipeline for automated multimodal complaint intake, urgency detection, and intelligent routing. Our approach integrates computer vision, natural language processing, and machine learning to process diverse complaint formats while ensuring ethical compliance. The proposed system demonstrates significant improvements: 89.1% classification accuracy, 57% reduction in processing time, and 28% improvement in customer satisfaction through evaluation on 17,847 real-world complaints collected over 18 months.