MillerKnoll AI
AI Leverage

What AI actually does here.

An AI research agent for the Product Innovation team — a deterministic orchestrator that routes across Internal Research, Synthesis, and Targeted queries and returns a grounded, four-lens read of MillerKnoll’s end-user research.

Button-based routing
3 predictable routes

Deterministic orchestration

Rosie routes across Internal Research, Synthesis, and Targeted with explicit button selection instead of ambiguous intent detection — making the agent’s behavior predictable and testable rather than a black box.

End User Research
cited, 4 lenses

Four-lens grounded synthesis

The Internal Research capability turns MillerKnoll’s own research library into a structured read across UX, Customer Insights, Business Strategy, and Knowledge Gaps — with evidence-rigor levels and required citations back to source.

Knowledge-graph signal
→ Data Science

A POC that proved the data

The highest-value output wasn’t the agent — it was the discovery that the research corpus was ready for a knowledge graph, which redirected the work to the Data Science team. The POC de-risked a much larger initiative.