Retail & E-Commerce

Inventory distortion costs retail and e-commerce trillions annually. Overstock ties up capital; understock loses sales. Conventional analytics are retrospective - dashboards that explain what happened after the fact. Demand signals are fragmented across channels, and pricing decisions rely on gut feeling or outdated rules. The result: dark data rotting in silos while decisions are made on incomplete information.

Supply chains and merchandising teams operate on probabilistic forecasts that fail to capture causal drivers: weather, events, competitor moves, and shifting behavioral archetypes. The Translator layer of a typical BI stack never connects raw signals to a Logic Engine that can prescribe action. By the time a report surfaces overstock in Region X, the markdown cycle has already begun - and the root cause remains unmodeled.

Without deterministic execution at the decision layer, retail remains reactive. Sentient OS closes the loop from sensor to action.

Sentient OS models supply-demand causality in real-time. Our vector-space architecture captures demand signals across channels and computes deterministic alignment between inventory, pricing, and consumer intent. Real-time pricing optimization, shelf intelligence, and demand forecasting replace autopsy reports with autonomous decision engines. The platform activates your existing data - BI, ERP, POS - and transforms it into millisecond-level action.

The 5-Layer Architecture ingests POS, ERP, and marketplace feeds through the Sensor layer; the Translator normalizes and embeds demand signals into vector spaces. The Logic Engine runs causal analysis on price elasticity, assortment fit, and cross-channel resonance. The DNA and Pattern Recognition layers maintain behavioral archetypes and anomaly detection so the decision layer receives validated, not noisy, inputs.

Command Center modules - Performance Forecasting, Conversion Modeling, Market Fit - surface this intelligence for planners and pricing teams. Deterministic execution means every markdown, replenishment, and promotion decision can be grounded in causal modeling, not correlation.