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The growing international mental health care burden highlights the urgent need for scalable, effective, and affordable therapeutic alternatives. While conventional psychotherapy is constrained by scope and personalization, digital therapeutics promise to be a better option. This paper introduces a new personalized digital therapy platform based on artificial intelligence (AI) and machine learning to provide customized, evidence-based treatment for mental health. The platform employs a multi-modal strategy, processing user-reported information, in-app behavior patterns, and embedded biofeedback, to dynamically change therapeutic material, exercises, and support features. A 150-participant randomized controlled trial was performed to evaluate the effectiveness of the platform compared with routine care. Outcomes revealed statistically significant depressive and anxiety symptom reduction, with a significantly greater level of patient engagement and compliance with the control group. These results validate the platform's ability to provide effective and highly tailored care. The success of the platform illustrates a viable mechanism for bridging barriers to conventional therapy, improving patient outcomes, and expanding access to mental health care. Future research will involve the integration of virtual reality elements to enhance the therapeutic experience even further.