Water supply operations in many Indian Urban Local Bodies (ULBs) continue to rely on manual processes that lack transparency, efficiency, and accountability. Citizens often have limited access to information regarding supply schedules, connection status, and billing details. Grievances are frequently reported through informal channels, resulting in poor traceability and lack of resolution assurance. This paper introduces CiviCare, a full-stack AI-enabled web platform designed to digitise and optimise municipal water governance for Indian ULBs. The system manages the complete lifecycle of a water connection, including application submission with document verification, site inspection, administrative approval, Consumer Number generation, and rule-based annual billing. A rule-driven Natural Language Processing (NLP) module is implemented to automatically classify and prioritise citizen complaints, which are then assigned to field plumbers through generated work orders with defined Service Level Agreements (SLAs). Water supply information is recorded daily by municipal officers and presented transparently through ward-level dashboards. The platform further integrates a Gemini AI-based chatbot for citizen interaction and Twilio SMS services for proactive notifications. Evaluation results demonstrate improvements in complaint resolution visibility, fairness in billing, and efficiency in managing water connections when compared to existing municipal systems.
municipal water management, ULB digitisation, grievance management, NLP classification, smart governance, billing transparency, citizen services, India.
Tanishka Ashish Shah, Dhanashri Jamdar Pingale, Purva Hanumant Pawar, Sakshi Santosh Tupe, Sweety Mohite. CiviCare: An AI-Powered Smart Water Governance and Grievance Resolution System for Urban Local Bodies in India. Indian Journal of Modern Research and Reviews. 2026; 4(5):318-324
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