Depression is a serious and debilitating disorder, which is under treated. Internet-based treatments delivering access to online treatment programs show promise to broaden the reach of treatment effectively for some patient groups, but is hampered by a rigid one-size-fits-all format. The PERSONAE project aims to develop a unique digital mental health service model for depression that is flexible, data-driven, and personalised. To achieve this goal, the project proposes to develop four major components and unite them into one coherent service model. 1) Matching level of clinician contact to the patients’ needs. 2) Intelligent adaptation of the content of the online treatment program to each patient's specific symptom profile. 3) Machine learning algorithms for early detection of patients at risk of treatment failure. 4) A simple, coherent and personalised user experience. National and international experts have convened in this consortium building on the knowledge from the IFD project ENTER regarding mobile monitoring and blended care and building on research demonstrating a large potential for unguided self-help and the use of machine learning algorithms in screening and assessment procedures as well as incorporating promising new research regarding adaptive programs. The service is designed to be implementated immediately post-project both nationally and internationally. PERSONAE = depression + digital treatment + personalisation