This research work aims to design an optimized desktop software R.I.M.A.S. (Real-Time Intelligent Monitoring Advanced System) R.I.M.A.S. is designed to enhance productivity and focus management, particularly for individuals with attention-related challenges like ADHD. The system integrates computer vision, a machine learning model trained on a custom dataset, and voice recognition to track user activity via the desktop camera. R.I.M.A.S. functions as a digital accountability companion, detecting distractions, phone usage, and desk presence. When a user gets distracted, it intervenes with verbal alerts and volume-based notifications, requesting valid reasons for breaks. The built-in voice assistant enables users to interact with the software for task assignments, restricted Internet searches, and desktop application control. Through continuous monitoring of working hours and behavior patterns, R.I.M.A.S. provides personalized feedback to improve focus and time management. This combination of advanced technology and usability makes R.I.M.A.S. an effective productivity enhancement tool. The performance achieved on the custom manually labeled dataset is around 99.01% on training dataset and 78% on test dataset. The precisions achieved for each label are 100%, 100%, 100%, 100%, 97%, and 100%, respectively, for Away, Focused, Idle, On-call, Phone, and Using phone. A study conducted with Usage in real life with 10 users with the primary findings: 35% improvement in focus duration, a 42% reduction in phone-related distractions, and a 28% increase in task completion efficiency.