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This paper talks about the transformative potential of AI in institutional inspections. Regular visits to schools, colleges, and corporations require constant checking up on whether they are complying with rules meet specific safety standards, and are operating efficiently. Typically, traditional methods of inspection suffer from inefficiency as well as human biases. This research introduces an AI-driven framework that incorporates machine learning, computer vision, and natural language processing to automate and transparently conduct inspections. The system shows high accuracy in anomaly detection, provides real-time reporting, and improves the scalability of inspections. Therefore, this approach reduces costs and overall reliability