Conversational Systems provide a natural way for human interaction. One conversational system is usually composed by spoken language understanding, state tracking, dialogue manager and natural language generation subsystems. The current methods are usually limited by the small number of domains it can support and the inflexible dialogue manager. In addition, it's difficult to make use of the user feedback to improve the system. In this talk, we will talk about the practice of applying deep learning algorithms to solve some of these problems in Maluuba and also list the main challenges for this problem.