RAG chatbot

A RAG chatbot that answers from your documents, and shows where the answer came from.

A RAG (retrieval-augmented generation) chatbot searches your company's own documents, retrieves the most relevant passages, and uses them to write an answer with citations. Flowmoat builds RAG assistants over contracts, policies, wikis and tickets, with permission-aware retrieval so users only see what they are already allowed to access.

Sound familiar?

The problems this solves

Staff spend hours searching shared drives for the right policy, precedent or answer.

A generic AI chatbot invents answers that sound confident and are wrong.

Sensitive documents can't be pasted into a public AI tool.

Search works on exact keywords, so people miss documents that use different wording.

How it works

From first call to working system

01

Ingest

Clean PDFs, Word files and pages, keep metadata, and remove duplicates.

02

Chunk and index

Split by meaning, not by page, and combine keyword and semantic search.

03

Answer with citations

Every answer links to the passage it came from. No source, no answer.

04

Evaluate

Test against real questions from your team before anyone relies on it.

Related reading

Before you decide

Want proof we ship? See products we built and operate

FAQ

Common questions

It is built to answer only from retrieved passages and to say when it can't find a source. We test it against real questions before launch and keep measuring after.

In your cloud account or on your own servers. We can use hosted models or self-hosted ones, depending on how sensitive the documents are.

Yes. Retrieval checks the user's permissions, so the assistant never shows a document the user couldn't already open.

Yes. The same assistant can sit in Slack, Teams, an internal portal, or a customer-facing widget.

Next step

Tell us about the work, and we'll tell you honestly if this fits.

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