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We propose an automated pipeline for robustly identifying neurological disorders from interactive therapeutic exercises, which are gathered via the mobile therapy app myReha. The app captures speech and cognitive parameters from over 30.000 tasks in various scenarios. Users get immediate and highly accurate feedback for pronunciation and coherency for language tasks, while voice recordings are fed to a feature extraction pipeline in the backend. These features are then used to construct speech characteristics, which are highly indicative of different neurological disorders, such as acquired aphasia after stroke. The data is visually presented in a web application nyra.insights, which allows medical professionals to quickly derive recommendations for treatment and closely monitor outcomes. During the Show and Tell session, users can experiment with the interactive myReha app and experience the real-time speech analysis capabilities via the nyra.insights web platform.