Conversational AI based Chatbot for Bank Information Retrieval using Dialog Flow for RBI /Tax/Defense

One of the most significant breakthroughs in recent years has been the development of transformer-based models, such as Open AI's GPT-3 and Google's BERT. These models leverage large-scale pre-training and fine-tuning to achieve state-of-the-art performance on a wide range of NLP tasks, including Chatbots. GPT-3, for example, can generate human-like text and engage in coherent and contextually appropriate conversations, thanks to its ability to process and generate language based on vast amounts of training data. The application of Chatbots spans numerous domains, including customer service, healthcare, education, and entertainment. In customer service, Chatbots are used to handle routine inquiries, provide support, and improve response times, as demonstrated by studies conducted by companies like IBM and Sales force. Despite their advancements, Chatbots face several challenges that continue to be the focus of research. Ensuring natural and contextually appropriate responses remains a critical issue, particularly in maintaining coherence over extended conversations. In this paper, we are using Dialog Flow as a chatbot, Fast Api as a web framework, Mongo DB as a Database. The user can query Chatbot via multiple mediums like Web, Dialog flow Messenger and Telegram through Text and Voice input. Bank Info Bot is a Chatbot that provides information about banks when the user inputs their IFSC Code using conversational AI.