With consequences for patient safety and the integrity of the pharmaceutical business, drug safety is a crucial issue in healthcare. However, because there is a growing amount and complexity of safety information, it can be difficult to stay educated about medication safety. This research aims to address this problem by leveraging the You Only Look Once Version 8 (YOLOv8) object detection model and creating a system that extracts text from medication labels using Optical Character Recognition (OCR). The system interfaces with backend databases, such as SIDER, to obtain additional information and give consumers a more streamlined understanding of the hazards and components in drugs. Advanced machine vision features are also included in the system for precise medication name detection. The main goal of the project is to provide users with conveniently accessible and clearly understandable information so they may make informed decisions regarding their drugs. By means of an organized approach that encompasses collecting information, model development, and database incorporation, this project seeks to close the communication gap between medical experts and the general public, promoting public health and well-informed healthcare choices.