Auditory verbal hallucinations are one of the most common symptoms in schizophrenia, contributing substantially to distress, functional impairment, and relapse risk. Existing therapeutic approaches, including pharmacological treatment and structured psychotherapies such as cognitive behavioral therapy for psychosis and AVATAR therapy, show promising clinical outcomes. However, scalability remains limited due to resource intensity and reliance on specialized personnel. Against this background, we describe the rationale, prototype architecture, and prospective validation roadmap for GOBLIN—a digital platform prototype combining personalized voice conversion, webcam-based eye-tracking, and large-language-model-assisted clinical documentation and decision support. The platform is intended to support clinician-supervised therapeutic workflows and between-visit monitoring following prospective validation. GOBLIN is intended to investigate whether an integrated digital workflow could address key limitations of current care models in schizophrenia and psychotic disorders, including fragmented follow-up, limited responsiveness to rapid symptom changes, and lack of scalable intervention tools. Our conceptual prototype is the first step toward leveraging the potential of digital, AI-driven platforms to complement existing treatment modalities and improve long-term management of psychosis-related symptoms. The system’s modules are intended for clinician-supervised research workflows and remain investigational. This manuscript does not report completed clinical validation, therapeutic efficacy, diagnostic performance, relapse-prediction performance, or validated safety outcomes. Such capabilities remain to be evaluated prospectively through staged technical, usability, safety, and clinical studies before clinical implementation can be considered.