The COVID-19 global pandemic has affected the world in such a way that it has forced new systems to inhibit Augmented Reality (AR) technologies so as to avoid physical contact and also the business have turned to remote work mode. The Augmented Reality solution to help us through pandemic challenges and it may just represent the future of world business. Virtual try-on is an advanced way of trying a product. In this project, we examined and reviewed the existing works where they augment the face data and based on training models employed output is displayed as a blend of virtual and real object. Among many approaches, our emphasis is on models which inhibit deep learning and machine learning models with generative adversial networks which are faster and more accurate. We are comparing various technologies for e-business that are trying to create a virtual image using web camera. The proposed model will work in the following way: When a person enters beside camera’s vision, Camera will start capturing the live video stream of him which is nothing but a short video of specified frames. The deep learning algorithm works in background will capture the facial encodings of the person based on product which he wishes to try. Each time a new person enters into our portal (when he come’s infront of camera), dynamic input of his face video stream is taken and based on the product which he/she wishes to buy facial encodings of that part is extracted and virtual product will be blended along with specified facial part. Final product will be a virtual try-on experience where in a person could actually visualize how his product would look when he actually wears it. The enhanced product is created by integrating deep learning and classical machine learning approaches, with the input given to the convolutional neural network being processed. For better interface with the user a website built using HTML and CSS is used to develop a front-end framework.