Watch this recording for a hands-on webinar where we’ll guide you through the end-to-end process of building a Retrieval Augmented Generation (RAG) application—from raw, unstructured data to a production-ready chatbot. In this session, you’ll learn how to turn your enterprise data into a powerful foundation for a context-aware AI assistant using Databricks and Unstructured.

We’ll show you how to clean, structure, and intelligently chunk documents with Unstructured, then walk through how to store the results and their embeddings in Delta Tables—optimizing for both performance and manageability. You’ll see how Databricks makes it easy to set up and maintain Vector Search endpoints, enabling fast and accurate retrieval during chatbot interactions.

Throughout the recording, we’ll cover the critical stages of a RAG pipeline, including data preparation, embedding generation, vector search implementation, and LangChain-based chatbot deployment. We’ll also share practical tips to help you deploy your RAG application.