AI Based Online Complaint Management System

Authors: Mr. M Anand, Balamurugan M, G Murali Krishna, Nakkala Lokesh

Abstract: In the contemporary era of digital transformation, efficient and automated complaint management systems have emerged as essential components of organizational service frameworks. This paper presents a comprehensive web-based online complaint management system developed using the Flask framework and database technologies in Python. The proposed system leverages modern web development techniques to perform real-time registration, tracking, and resolution of user complaints with high reliability. By integrating structured data storage models for complaint categorization and processing, the system enables efficient grievance handling that eliminates reliance on traditional manual-based mechanisms. The application provides an intuitive web interface that facilitates user complaint submission and administrative verification through structured input forms. Experimental results demonstrate that the system achieves processing efficiency exceeding 95% under optimal conditions, with consistent performance across varying operational scenarios. The lightweight architecture enables straightforward deployment on standard web servers, making the solution viable for diverse applications including service monitoring, issue tracking systems, and grievance redressal platforms in both academic and enterprise environments.

DOI: https://doi.org/10.5281/zenodo.19510108