We present an interactive demo of SENNA, our end-to-end Natural Language Processing (NLP) system. The demo leverages Torch7, which provides an efficient Matlab-like environment for machine-learning algorithms. As the user types in characters, the demo displays (in a smooth and real time fashion) the outcome of a wide variety of NLP tasks (Part-Of-Speech tags, Chunking, Name Entity Recognition, Semantic Role Labeling, and Parsing). Torch7 GUI features are used to embellish the output results, as well as the interactive experience.