Once the documents are collected, algorithms decide on their relevance for the judict database. With an automated process based on NLP techniques (natural language processing), all documents classified as relevant are added. Subsequently, the documents are mapped to the legal acts and the specific articles they relate to. We do this with algorithm-based pre-sorting followed by manual quality control. With this two-step process, we guarantee the constant up-to-dateness and high quality standard of the judict database. As of now, we have processed more than 61,000 documents. To learn more about this, see
here.