Robot Bangla has developed a wearable insole system for gait analysis using artificial intelligence and machine learning techniques. The system is designed to be portable, low-cost, and easy to use, making it a valuable tool for gait assessment both in clinical settings and at home. The system utilizes sensors called IMUs (accelerometers, gyroscopes, and magnetometers) that are placed in the insoles of shoes. The IMU data is transmitted wirelessly to an Android app using Bluetooth technology, and is used to create real-time visualizations of gait information. The system is able to identify individual movements, determine normal gait patterns, and visualize changes in gait patterns in real-time. This information is useful for diagnosing issues that cause pain and for implementing and evaluating treatments to correct gait abnormalities. The system includes a number of features, including real-time dial visualization, visualization of time variation in individual legs, visualization of asymmetry between legs, and boxplot-based visualization. It can be used to capture data for analyzing the stages of various diseases, managing treatment plans, and evaluating treatment outcomes. These diseases include the early stages of diabetic ulceration, Parkinson’s disease, different stages of Alzheimer’s disease, quantification of gait before and after knee surgery, and remote monitoring of gait in older adults for fall risk assessment and exercise to prevent injury. Overall, the system provides a sophisticated gait assessment solution that does not require an expensive and elaborate laboratory setup, and can be used for gait assessment at home or in clinical settings.