We’re going to do a technical deep dive into Retrieval Augmented Generation, or RAG, one of the most popular Generative AI projects. There is a ton of content about RAG applications with LLMs, but very little addresses the challenges associated with building practical applications. Today you’re going to get the inside scoop from some engineers with that experience.

LLMs can be used to convert documents like emails or contracts to sets of vectors called embeddings. Embeddings can be used to find sets of text that are more similar in meaning. The most common business applications are semantic search, searching based on meaning and not keywords, and document Q&A. Each step presents unique challenges, and we're going to address them today.