Post-stroke rehabilitation is pivotal for individuals aiming to regain lost functionalities and improve their quality of life. The integration of innovative technology can enhance this recovery journey. “NeuroFlex”, an IoT-integrated glove, is introduced to aid post-stroke individuals. It has sensors to capture real-time data on hand movements and strength, which is sent to a centralised server. This server, equipped with machine learning algorithms, tailors rehabilitation exercises based on the patient's progress. Such personalization ensures an optimised recovery pathway tailored to each patient's needs. Furthermore, NeuroFlex transmits this data for processing through an explainable machine learning-based monitoring system. This AI framework not only tracks patient progress but also offers insights into its decision-making, enhancing transparency and trust in the rehabilitation process. This offers insights into potential issues, paving the way for timely interventions that can optimise outcomes and avert possible setbacks. Early trials suggest that NeuroFlex surpasses traditional methods in terms of rehabilitation speed and user satisfaction. It represents the fusion of wearable tech, IoT, and machine learning, revolutionising personalised post-stroke care. Additionally, its remote controllability offers opportunities for teleconsultations with therapists, enhancing patient accessibility and convenience.