Large language models have taken the world by storm, but what if you’d like to use one with your internal text data? LLMs aren’t trained on your data, and finetuning a bespoke LLM is daunting. However, retrieval-augmented generation (RAG) combines LLMs with document search to create powerful generative NLP systems for your text data. In this talk Rob will discuss how to build effective RAG pipelines, as well as how to address potential concerns like privacy and hallucination effects.