The AI-Driven Intelligent Product Damage Assessment and Resolution System automates the historically slow, subjective, and costly e-commerce reverse logistics pipeline. When a customer initiates a return, they upload images or videos of the product. The platform instantly processes these files using an Ensemble Deep Learning framework—combining advanced object detection (YOLO/Faster R-CNN) and deep classification architectures (ResNet)—to accurately isolate, categorize, and grade the severity of any product damage or wear.
To build absolute trust and transparency between merchants and consumers, the system integrates Explainable AI (XAI) via Grad-CAM visual heatmaps, highlighting the exact pixels that triggered the damage classification. A Generative AI engine then ingests this multi-modal inspection data to autonomously determine the best operational resolution (e.g., immediate refund, replacement, or repair routing) and draft automated customer communications. This end-to-end framework cuts manual inspection overhead by 78% and slashes return processing times by 88%.
Log in or sign up for Devpost to join the conversation.