This chapter presents the implementation of an online proctoring system designed to operate entirely on the client side, addressing the inherent challenges associated with server-side processing in existing exam portals. By shifting the processing tasks to the client side, our system aims to alleviate the burden on servers and reduce network dependency, while ensuring robust face detection and suspicious activity detection capabilities. We have used Siamese technique for face verification and MobileNet model for object detection. Additionally, we have developed a custom browser extension that will detect and disable flagged extensions during the exam. Our system also has the support of a variety of question types including coding, subjective, and multiple-choice questions. Through our implementation, we aim to enhance the efficiency, cost-effectiveness, and security of online exam proctoring, offering a solution that minimizes server load and maximizes performance by leveraging client-side resources.