Digital twins of physical stores often stop at static geometry and inventory. We build living models that embed human behavior, flows, and interventions, turning the store into a testbed where scenarios can be explored before they hit the real floor.

Traditional twins focus on layouts and assets but rarely capture the microscopic human dynamics that drive performance. BIEM turns continuous streams of spatial and behavioral signals into a dynamic representation of the store, allowing retailers to simulate changes in layouts, staffing, content, and processes. By grounding these models in observed patterns rather than assumptions, BIEM makes it possible to test scenarios, compare alternatives, and anticipate side effects at system scale. Retailers gain a defensible basis for de-risking decisions, prioritizing investments, and rolling out changes with a clear expectation of impact.