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Use Case - Inventory Management

Inventory Management

Predict what to stock, where to stock, and when — autonomously.

Overview

Nexusphere AI maintains healthy inventory across all locations using predictive demand, real-time signals, and supplier intelligence.

Key AI Steps

  1. 1.SKU-Level Demand Forecasting
  2. 2.Predictive Replenishment Calculation
  3. 3.Safety Stock Optimization
  4. 4.Automated Redistribution Across Warehouses
  5. 5.Shrinkage, Ghost Inventory & Anomaly Detection
  6. 6.Carbon-optimized transfer routing

Impact

  • 30–40% reduction in excess stock
  • 35% fewer stockouts
  • 25% working capital reduction

SKU-Level Demand Forecasting

Machine learning generates precise demand predictions at the individual stock-keeping unit (SKU) level. This granular forecasting enables more accurate planning and reduces uncertainty across the supply chain.

Predictive Replenishment Calculation

Based on forecasted demand, the system calculates the optimal quantity and timing for inventory replenishment. This ensures the right products are restocked at the right time, minimizing both shortages and overstock.

Safety Stock Optimization

Safety stock levels are dynamically adjusted using real-time demand variability and lead-time data. This approach minimizes stockouts while reducing excess inventory and carrying costs.

Automated Redistribution Across Warehouses

The system autonomously manages inventory transfers and balancing across warehouses and storage locations. This improves service levels by positioning inventory closer to demand while maximizing overall network efficiency.

Shrinkage, Ghost Inventory & Anomaly Detection

Advanced anomaly detection identifies unusual discrepancies such as shrinkage, unaccounted-for inventory, or phantom stock records. These insights help prevent losses and improve inventory accuracy.

Carbon-Optimized Transfer Routing

Warehouse transfer routes are selected with carbon impact in mind, minimizing emissions as part of the overall logistics strategy. This supports sustainability goals without compromising operational efficiency.