For developing AI-powered assistants that provide real-time, accurate responses to queries, retrieval-augmented generation (RAG) leverages large language models (LLMs) in conjunction with private organizational data. Fivetran plays a crucial role in powering RAG applications by offering over 700 managed connectors and ELT pipelines that centralize data from various sources into data lakes and cloud data warehouses. This ensures that the data feeding the LLMs is fresh, compliant, and continuously updated, allowing for the development of intelligent and scalable AI features without the burden of manual data management. The integration of Fivetran with RAG enables businesses to enhance customer support, streamline internal processes, and personalize user experiences by automatically retrieving and synthesizing data. This creates a reliable infrastructure for offering advanced AI features in SaaS products, reducing the need for engineering-intensive data management efforts and allowing developers to focus on innovative applications.