WASABI Contextual BOT

Conversational Artificial Intelligence (AI) chatbots are getting huge attention from Industries and AI communities. With the development of Natural Language Processing (NLP) and Deep Learning algorithms the application of artificial intelligence in chatbots is taking sharp turns. Today we are seeing a wave of conversational AI sweeping across industries and every brand is looking to add AI-based solutions. Natural Language is an intuitive way for users to interact with the technology. Conversational AI bots not only recognize the human requests but it also emphasizes on the context of the request. By understanding context, a chatbot can respond to different and unexpected user inputs and drive the conversation when user drifts from regular conversation path. Contextual chatbot can give better and appropriate response when user asks domain specific questions. In any organization, it becomes handy and useful for the users if they can access the data in a personalized way. Rasa is an open source machine learning framework which is used for building contextual AI assistants and chatbot. In this paper we discuss an efficient way to design a chatbot using RASA framework which made things easier for the employees during pandemic and continue to do so by providing them information related to their work in organization.