Every document and chat history you already have, turned into one searchable archive. Answers come from what your organisation actually knows — not the open web.
RAG turns scattered documents and conversation histories into one indexed, searchable archive. Every agent in the suite queries it through Floe — so answers come back grounded and sourced, not invented.
The same content gate runs every time, for every agent. Nothing reaches the archive unchecked.
Every platform connected to RAG — every model, every tool — leaves a trace: how much it's used, by whom, for what. That's not just searchable. It's the evidence for deciding what to keep funding and what to quietly retire.
Conversations indexed per platform, today. The shape of this changes every time a tool gets adopted, ignored, or replaced — and now there's a record of it.
And it's not just counts. Every conversation is tagged and retrievable — so a manager can see exactly what the team is actually using AI for, not just how often they're using it.
That's the difference between "we have AI tools" and "here's what to keep funding, what to consolidate, and who needs retraining."
Already indexing 6,000+ files and 940+ conversation histories.
No deck, no demo required.
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