The chatbots and intelligent virtual assistants market is expected to grow at a CAGR of 22% between 2020 and 2025, potentially reaching nearly $14 billion by 2025. There are different types of chatbots, including rule-based bots, retrieval-based bots, and conversational AI bots, which are the most advanced and can have human-like conversations. Rasa is an open-source framework for building chat and voice-based AI assistants that allows for customization and responsiveness to individual users. Rasa uses machine learning to identify user intent, extract specific details, and manage dialogue flow. In this tutorial, we build a financial AI chatbot using Rasa that can assist with common banking inquiries. The tutorial covers setting up a Rasa project, defining intents, creating conversation flows, and defining responses. We also explore a real-world case study of a finance chatbot that can answer questions about account balances and loan eligibility. Finally, we discuss the potential for scaling up and exploring more advanced features with Rasa.
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