AI-Based Smart Government Grievance System

Citizens use public grievance systems to report problems involving services such as roads, water supply, sanitation, electricity and local administration. A complaint may be written in everyday language, may contain incomplete information, or may be sent to the wrong department. These issues can make complaint handling harder to organise, particularly when many requests arrive at the same time. India already has the Centralised Public Grievance Redress and Monitoring System (CPGRAMS), which supports online grievance submission, status tracking and feedback. The project described in this paper is an academic prototype concept that explores how a web-based complaint workflow could be supported by optional artificial-intelligence (AI) features. The proposed system uses Python and Flask for the web application, HTML, CSS and JavaScript for the interface, and SQL for structured storage. After a suitable labelled dataset becomes available, natural language processing could be used to suggest a complaint category, priority level and likely department. Similarity matching and short summaries are also considered as support features. These outputs should remain recommendations that an authorised person can review, rather than automatic final decisions. At the time of writing, the team reports that a website/prototype has been developed, but a final dataset and quantitative model evaluation have not been supplied. Therefore, this paper describes the system design and evaluation plan without claiming model accuracy or proven performance gains.