Unlocking business documents with RAG

This study offers a compact overview of Retrieval Augmented Generation (RAG), an approach that unlocks information from a company's selected documents using large language models. The most common RAG use case currently is specific chatbots that assist employees with internal tasks. At the AI Advancement Center, Fraunhofer IAO has prototypically implemented several RAG use cases, which illustrate the range of possible solutions in this publication. Furthermore, guideline-based interviews were conducted to analyze the procedures and challenges in implementing RAG production systems in large organizations. Practical recommendations for action are derived from the results, which support companies in successfully and responsibly implementing »the chat with their own data.«.