Large Language Models are revolutionizing the world right now, but they have significant flaws: their knowledge is not up-to-date, they don't know about your company's specific data, and they start to hallucinate when they don't know the answer to a question.

An often-used technique to counter those points is Retrieval Augmented Generation (RAG), which augments prompts to the LLM with specific knowledge - often fetched from a Vector Database. In this talk, Max will explore the steps needed to develop your own RAG system and then apply various steps to make it highly efficient.