EmoConsult is a cutting-edge platform created to assist and support IT professionals and students in improving their well-being and managing stress via the use of cutting-edge technologies. This study investigates how machine learning and facial emotion recognition can be combined to offer wellness solutions and personalized content recommendations. EmoConsult provides personalized content, including music, movies, and therapeutic activities like yoga and exercise, by assessing users’ moods or states of mind in real time. EmoConsult’s deep learning classification model, which is trained on labelled datasets of hand gestures and facial expressions to identify moods, is evaluated in this study for accuracy. The site also makes expert mental health consultations more accessible, which improves user support. The study also emphasizes how user-centric design, strong privacy safeguards, and Mediapipe-based landmark identification contribute to the development of a useful stress-reduction application. In order to demonstrate EmoConsults’ potential to transform stress management and mental health support, this study examines the efficacy of its emotion detection algorithms, user experience design, and privacy safeguards.