Nowadays, massive volumes of mobility data are being generated from thousands of tracking devices, such as GPS devices, RFID sensors, location-based services, satellites, and wireless communication technologies. This phenomenon can be strongly observed in the maritime domain and as a result, today's industry is flooded with tracking data originating from vessels across the globe that transmit their position at frequent intervals. Automated methodologies able to extract meaningful information and identify mobility patterns from such tracking data are of utmost importance since they can reveal abnormal or illegal vessel activities in due time. To this end, we present a demo of a trajectory classification methodology that is able to classify vessels' trajectories into activities that the vessels are engaged in from AIS data streams in real-time. The goal is to provide maritime authorities with a visualization tool and an API of the vessel trajectories and their activities in real-time. The trajectory classification methodology that is used in this demo achieves a classification performance of over 95%.