Chatbot is an Artificial Intelligence (AI) software that simulates and processes human conversations as if the humans were having a real conversation with another human. They are used in various business applications to help address human queries and assist them with important details. RASA is an open-source machine learning framework for building chatbots. RASA leverages Natural Language Understanding (NLU) to break down user messages into intent and entities which help form an appropriate response for the user’s messages. The RASA conversational assistant has several components that help predict the responses and also tune the model to get better results from the model. This paper will provide the design of a chatbot that handles basic queries of a particular university that could be used on the university website. This paper also explores how individual components of the RASA pipeline help curate the response for the users.