Stress at work has become a serious problem that affects worker health and business success. Traditional methods of measuring stress, such as self-reports and surveys, are un- reliable and may not provide immediate feedback. To overcome these problems, this paper proposes a real-time stress monitoring system that analyzes facial expressions and detects stress using CNNs. The system is suitable for modern workplaces because it uses MobileNetV2 for fast and scalable processing. It also features a chatbot powered by an artificial neural network (ANN) that provides customized stress reduction recommendations, including relaxation techniques and counseling materials. Based on the pilot test results, the system is accurate and efficient, making it a useful tool for managing stress in different work settings. I