Giving AI access to your internal documents
How to let an AI agent answer your teams' questions using your own internal documentation, without exposing your data.
Your teams waste time hunting for information scattered across documents. When the person who “knows” is away, everyone waits. RAG lets an AI agent solve that problem.
What is RAG?
RAG (Retrieval-Augmented Generation) lets an AI answer questions using your own documents. In practice, it is an enhanced search that understands context.
Unlike a conventional search engine, which returns a list of files, RAG reads the relevant passages and formulates a concise answer, with its sources cited.
How it works
- Indexing: your documents (PDF, Word, wiki pages) are split into segments and turned into vectors (mathematical representations the AI can compare with one another). This is done once, then kept up to date as documents are added.
- Retrieval: when someone asks a question, the system identifies the most relevant segments.
- Generation: an LLM (large language model) receives the question together with the passages found, then writes an answer based solely on those sources.
The benefits
- Answers in seconds instead of minutes spent digging through folder trees.
- Less dependence on key people: knowledge no longer sits only in the heads of a few colleagues.
- Faster onboarding for new joiners.
What about security?
- Local hosting: the system can run on your own servers or in a private cloud. Your documents never leave your infrastructure.
- No training on your data: the LLM uses your documents to answer, but does not absorb them into its model.
- Access control: existing read permissions are mirrored. A salesperson does not see HR documents.
Putting it in place
- Define the scope: start with a limited set of documents (technical documentation, quality procedures).
- Clean up the sources: remove duplicates and archive obsolete versions.
- Choose the tool: the assistants built into office suites, specialist platforms, or open source builds, depending on how much control you want.
- Test with a pilot group for a month, then widen it out gradually.
In summary
RAG gives your teams instant access to the company’s knowledge. The technology is mature and its security model fits the requirements of a smaller company. The real prerequisite: documents that are up to date.