Celect Fashion AI (Nike Proprietary)

Celect (now a core technology within Nike's Direct-to-Consumer stack) represents the pinnacle of Bayesian demand sensing in the fashion industry. The platform's architecture leverages advanced MIT-developed algorithms to predict hyper-local demand at the SKU and store level, even in scenarios with sparse data or high volatility typical of seasonal fashion cycles. By the 2026 market horizon, this technology has evolved into a fully autonomous 'Demand Signal Engine' that bridges the gap between digital consumer behavior and physical inventory allocation. It differentiates itself by moving beyond traditional time-series forecasting, utilizing a proprietary choice-modeling framework that understands how consumers trade off between different products within a localized assortment. This enables retailers to optimize inventory across thousands of nodes, significantly reducing markdowns and stockouts while increasing full-price sell-through rates. The technical core is designed to ingest massive streams of POS, web browsing, and supply chain telemetry data to provide real-time rebalancing recommendations that are execution-ready for ERP and WMS integrations.