The latest advancements in conversational AI have led to a surge in chatbot adoption, driven by tools like Rasa, the leading conversational AI platform. Building a chatbot that can identify information-seeking intents and perform question answering on a large-scale database of documents is now possible with the integration of Haystack, a powerful question-answering technology. By combining Rasa's dialogue flow management capabilities with Haystack's ability to extract relevant information from unstructured text, developers can create more robust chatbots capable of handling long-tail informational user requests. This integration enables chatbots to trigger external services like Haystack, providing context-dependent responses and improving overall conversational flow. The process involves setting up a Haystack service accessible via REST API, configuring Rasa to call the Haystack API, defining intents and actions, and training the model to recognize information-seeking utterances. With this powerful combination, developers can build more intelligent chatbots that provide accurate and informative responses to users' queries.