What Is RAG? A Simple Guide to Connecting AI to Your Business Documents

Large language models can write and reason, but they don't know your business: your prices, procedures, contracts or product sheets. When they don't know, they can produce a plausible but wrong answer. RAG (*Retrieval-Augmented Generation*) solves this problem.

The idea in one sentence

Before answering, the AI retrieves the relevant passages from your documents, then writes its answer from those passages and shows its sources.

How it works, step by step

1. Collect: gather the useful sources (PDFs, website pages, Notion, Google Drive, databases).
2. Chunk: split documents into coherent passages, neither too short nor too long.
3. Index: turn each passage into a vector (embedding) and store it in a search index, often combined with keyword search.
4. Retrieve: for each question, find the passages closest in meaning to the question.
5. Generate: the model writes the answer from those passages only and cites its sources.

Practical use cases

• Customer support: answer frequent questions instantly from your terms, guides and product sheets.
• Internal assistant: let your team find a procedure or a contract clause by asking in plain language.
• Onboarding: help new hires find information without constantly interrupting colleagues.
• Pre-sales: draft answers from your offers, references and technical documentation.

What separates good RAG from bad RAG

• Document quality: up-to-date sources without duplicates or contradictions.
• Chunking and retrieval: hybrid search (meaning + keywords) is better at finding exact references such as a product code.
• Instructions: the assistant must be able to say “I don't know” rather than guess.
• Evaluation: test the assistant on a set of real questions before and after every change.
• Access rights: people should only retrieve documents they are allowed to see.

What about data privacy?

You can use providers that don't train on your data, or run open-source models on your own servers when information must never leave your infrastructure. The right choice depends on how sensitive your documents are.

Want an assistant that truly knows your business? Explore our AI agent development service or read our 6 AI agent use cases for small businesses.