Authors - S. Kirthica, K. Subha, S. Arul Murugan, V. Deepak Kumar, M. Dhivagar, S. Kanishka Abstract - In contemporary society, effective grievance redressal is vital for transparency, accountability, and public trust. Traditional systems often face issues like manual processing, delays, and poor user engagement. To overcome these challenges, we propose VOICE, an AI-driven grievance management platform that automates the complaint lifecycle—from classification and similarity detection to assignment and tracking. Leveraging natural language processing (NLP), speech-to-text, and automated prioritization, VOICE reduces human intervention and improves response times. It also incorporates community-driven upvoting, real-time notifications, and performance monitoring to enhance user engagement and system transparency. Designed for scalability and ease of use, VOICE can be deployed across institutions, communities, and national systems. By combining automation, intelligence, and user-centric features, VOICE represents a significant advancement in modern grievance redressal.
