Ingest
Clean PDFs, Word files and pages, keep metadata, and remove duplicates.
RAG chatbot
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?
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
Clean PDFs, Word files and pages, keep metadata, and remove duplicates.
Split by meaning, not by page, and combine keyword and semantic search.
Every answer links to the passage it came from. No source, no answer.
Test against real questions from your team before anyone relies on it.
Related reading
The vendor wants you on their new AI tier. You do not need it. Four patterns for adding AI to the system you already have.
The pilot impressed everyone in the room. Then it stalled for six months. The reasons are boringly consistent, and all five are avoidable.
Want proof we ship? See products we built and operate
FAQ
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.