Prioritizing health is crucial, yet it remains unfulfilled and requires increased attention. To address this issue, an automated artificial intelligence (AI) application that monitors postures and actions during exercise would be highly beneficial. In the proposed article, we offer a remote AI powered yoga trainer. This trainer incorporates OpenCV for live image capture and processing, which helps in identifying the key poses. Advanced AI techniques, such as deep learning, have proven beneficial in monitoring applications. In the proposed article, we proposed three AI yoga trainer models using deep neural network (DNN), convolutional neural network (CNN), and multilayer perceptron (MLP) models. We evaluated the proposed model’s performance on a publicly available dataset sourced from Kaggle, where we focused on obtaining yoga pose images, as well as their captions. Data processing, which includes data cleaning and augmentation, is performed to ensure the diversity of the dataset. A carefully curated set of yoga poses, such as chair, cobra, and shoulder stand, helps to provide beginner-friendly and health-beneficial practices remotely, thereby preventing the neglect of physical health.