Building a Retrieval-Augmented Generation (RAG) application for Zendesk Support using Verba and dlt enables companies to get insights from their internal knowledge data, making it easier for everyone in the company to find the right information at the right time. With Verba, users can ask questions and receive relevant answers based on proprietary data, while dlt simplifies the process of loading data from various sources, including CRM data. The application uses Weaviate as a vector database and OpenAI models for generating answers. By following a step-by-step guide, developers can set up Verba, install dlt with Zendesk source, create a pipeline to import data from Zendesk, load data into Verba, and ask Verba questions to retrieve relevant information. This application demonstrates how RAG technology can be applied to real-world problems, enabling companies to improve their knowledge management and decision-making processes.