Hands-On RAG for Production

Chapter 4. Deploying RAG to Production

Now that you know all the components of a RAG pipeline, both basic and advanced, you can easily put together a pretty good proof of concept (POC). For a first POC, it is typical to pick a use case with significant value to the organization, where the initial investment is relatively low. This way you get to learn how this actually works, and understand first-hand how RAG works.

Getting a RAG proof of concept up and running is a lot of fun. You take a powerful large language model, point it at your documents or data, implement vector similarity between query and chunk embedding vectors in a vector database, and voilà—you can start asking questions and get real answers, based on the content of the documents.

If you do this as a side project, it takes only a modest amount of time and effort. However, if your goal is to build a production-grade RAG application that is scalable, secure, and fast, and that provides a mission-critical service to your company—that’s a whole other story.

Moving from a POC to a production-grade deployment of a RAG application presents enterprises with many challenges spanning technical, operational, and organizational domains. As you scale your RAG application, you often confront latency bottlenecks, vendor integration complexities, data security requirements, and interdisciplinary expertise gaps.

In this chapter, we dig deeper into some of these challenges and, where possible, discuss strategies to address them or ...