How to Build a Production-Ready RAG Pipeline With Vector DBs

The adoption of retrieval-augmented generation (RAG) from research papers to production systems has been rapid. Those who tried it in 2023 are now deploying it at scale for enterprise search, internal knowledge bases, and customer-facing assistants. However, a lot is still between a working prototype RAG and one that can withstand traffic on the road, using real data, and real modes of failure.

This article explains what this gap is, how to plug it, and where most production pipelines fail.