Ask retail data a question in plain English and get a governed, cited, multi-format answer back — safely.
Retail teams sit on large transactional datasets but can’t query them without an analyst and a wait. The hard part of a natural-language layer over that data isn’t the chat UI — it’s the security and governance around it: who can ask what, what’s safe to execute directly, and what needs retrieval instead.
Dual-path orchestration — deterministic warehouse queries and non-deterministic RAG retrieval run in parallel and merge into one response
AI security layer for jailbreak and prompt-injection defense, plus per-user category access control
Multi-format responses generated in parallel — summary, table, chart and export
A recommendation engine that reads the same governed data to suggest next actions
Automatic primary/secondary LLM fallback so the assistant stays available
Full conversation history and AI observability from day one
Designed and reviewed against all ten — see how I evaluate every architecture.
I design and ship systems like this one — from architecture through to production.
