What is RAG, and why does it matter for business AI?

By DevSoftTech · Updated October 2026

RAG stands for retrieval-augmented generation. Instead of asking an AI to answer from memory, the system first searches your documents, then gives the most relevant passages to the model to write the answer.

Why it helps. The AI uses your latest facts, can cite its sources and is less likely to invent answers. You also avoid expensive model training every time your documents change.

How it works. Documents are split into pieces and stored in a vector database such as pgvector or Qdrant. When someone asks a question, the closest pieces are found and sent to a model such as Claude with clear instructions.

Where it is used. Employee help desks, product support, policy lookups, legal and finance document review, and research libraries.

What to watch. Quality depends on clean documents, good chunking, permissions per user and regular testing. We build an evaluation set so you can see accuracy before and after every change.