Parkinson’s disease (PD) is the second most common neurodegenerative disease and particularly prevalent in Saxony due to its demographics. Fluctuation of symptoms over time represents one of the main challenges for patient care, making it difficult for the clinician to adjust treatment plans. Currently, symptom tracking relies on patient self-reports or difficult to use specialist hardware and software (e.g., body sensor-based systems). This project aims to develop and implement a digital assistant (DA) for mobile devices (e.g., smartphones), which enables continuous home monitoring. The DA interacts with the patient via natural language (speech or text) and is specifically designed to be easy to use and motivate users to continuously use it. The voice and video data gathered during the interaction is analysed via state-of-the-art machine learning algorithms to report the severity of PD symptoms. In the end, clinicians are provided with fine-grained and AI-supported symptom reports, which enable better care for PD patients.