Published Paper Details:

In today's rapidly evolving technological landscape, the swift and accurate handling of service complaints is crucial for maintaining customer satisfaction and operational effectiveness. Conventional complaint management methods often rely on manual processes that are slow, error-prone, and inefficient. These limitations result in delayed resolutions and poor user experience. To address these challenges, this project presents VISION-AI: Visual Intelligence System for Optimized Complaint Registration and Assignment Using AI, an integrated solution that combines the capabilities of Artificial Intelligence. The VISION-AI system offers a user-friendly complaint submission interface via a Telegram bot, allowing users to register issues using text and images. To reduce manual data entry and minimize human errors, the platform employs Optical Character Recognition (OCR) using Tesseract, which automatically extracts fault codes from submitted images. Complaint data is processed and managed through a Flask-API and securely stored in a SQLite database, for efficient data retrieval and analysis.. It also incorporates the (MCTS) algorithm to predict the most effective technician. Designed for scalability and future enhancement, planned upgrades to VISION-AI include real-time technician tracking, predictive maintenance, and a fully decentralized complaint resolution process, aiming to deliver a smarter, more robust, and highly responsive service management system.