With rapid growth in the application of AI, Access Control Systems are walking in a new technology lane. Powered by deep learning technologies or cognitive analytics, login pages can implement more secure, efficient, and easy to use authentication systems. Face Detection and Recognition is emerging as preferred solution to enable secure verification and authentication in login systems. Moreover, Facial Recognition has been applied in many fields from unlocking smartphones through built in camera of smartphones to identification of suspected people by the law enforcement organizations. The goal of this research paper is to provide an easier authentication system using Face Detection and Recognition instead of using usernames and passwords. This paper mainly analyzes the application of Face detection systems to authenticate and login users It presents the prototype system implemented with the usage of a Flask server, requesting face recognition services from Amazon's Rekognition. The prototype receives images of the user instead of his username and password. The received image is analyzed by AWS's Face recognition tools and the ID of the face is sent as a response along with the confidence level of the algorithm used to analyze the face. The prototype is tested with eight different faces and the system authenticate users with 100% accuracy and navigate them to their respective feeds.