In this project, we aim to develop a fine-grained aspect-based sentiment and emotion analysis architecture, which is multilingual (English, Dutch, French and German) and which is completely data-driven. The system should also be adaptable: users should be able to correct the output of the system on their data as the basis for retraining the system on the corrected data, leading to a more qualitative output which becomes increasingly tailored to company-specific data. The prototype will also be accompanied by two dashboards: a dashboard which provides a comprehensive visulatisation of the data and an annotation dashboard which allows to correct data and retrain the machine learning architecture.