This paper introduces NeuroOCD, an intelligent digital health solution aimed at improving the diagnosis and therapy of Obsessive-Compulsive Disorder (OCD) through an integrated artificial intelligence framework. The platform evaluates the presence, severity, and subtype of OCD using a variety of multimodal technologies, such as facial expression detection, audio biomarkers, adaptive questionnaires, and natural language processing. A predictive analytics engine to assess therapy progress and improve treatment courses, an AI-powered teletherapy module that tracks patient affective states, and a real-time voice assistant to support guided ERP therapy are all features of NeuroOCD. Flask, React Native, and MongoDB are used in the system’s construction to provide scalability, privacy, and modularity. The evaluation’s findings demonstrate good accuracy in predicting therapy sessions (R2 = 0.94), classifying voice intent (93.5%), and recognizing fear (>90%). For OCD management, NeuroOCD represents a revolutionary advancement in digital mental health by providing individualized treatment and increasing remote accessibility.