Automation is the way through which the machine can interact with data as well as a user for proper work or communication. A chatbot is a system which accepts user inputs as queries and respond with suggestions based on the previous inputs and trained models. In this paper, a travel chatbot is being modelled using Deep Neural Network (DNN) where it improves the human and machine interaction seamlessly as the user of the bot does not aware whether he/she is interacting with a machine or a human being. This chatbot suggest safest possible routes, secure and cheaper stay, best places for shopping, etc. to the users. This chatbot respond in a minimal time compared to other systems of similar nature. It also uses Long Short Term Memory (LSTM) to understand the sentence and form the sentence according to the previous reply. It also integrates various open APIs to get the recommended ratings from the internet. As per our analytical results, our chatbot outperforms by at least 20% in handling the user queries and suggest possible recommendations to the end users.