Content Analytics is targeted at extracting knowledge from heterogenous data sources, mainly natural language text. Here, recent models based on neural networks (deep learning) open up possibilities for improving search, tagging, categorization, and exploration. DeepCA's mission is to interlink neural models with conventional semantic knowledge modelling using ontologies. A cognitive service for text and knowledge graph analysis will be developed that can easily adapted for the exploration of new domains and leads to innovative solutions for semantic text annotation and search in heterogenous case bases. Through this, DeepCA will form the basis for an end-user centric, efficient knowledge engineering. DeepCA is conducted in collaboration with the company partners Empolis and SER, and with the German Research Center for Artificial Intelligence (DFKI) and the University of Trier as academic partners. The project is funded by the Federal Ministry of Education and Research.