Automate Supply Chain Execution Across Your Network
AI agents for supply chain execution - from detection to corrective action at scale
Beamup deploys purpose-built AI agents to automate supply chain execution across stockouts, excess inventory, shrink, split shipments, and labor inefficiencies - across stores, DCs, warehouses, and in-transit operations.
Purpose-Built AI Agents for Supply Chain Execution
Stockout Prevention Agent
Predicts and prevents stockouts before shelves go empty
Predicts and prevents stockouts before shelves go empty
Misplaced or phantom inventory
Multi-echelon inventory issues
Supplier performance issues
Impact: 20% fewer stockouts
Excess Inventory Agent
Identifies and corrects excess inventory before it becomes stranded
Idle Inventory in low-demand locations
Overstock caused by slow execution of demand shifts
Excess safety stock driven by order minimums/lot sizes
Impact: 20% less overstock
Split Shipment Agent
Detects and prevents split shipments caused by execution gaps
Orders split due to inventory misalignment
Partial fulfillment caused by operational errors
Multi-shipment orders caused by OMS logic errors
Impact: Millions saved annually
In-Transit Agent
Detects in-transit losses and systemic risk across shipments.
Delays, damage and loss
High-risk carriers, lanes, or routes
Suspicious activity/theft monitoring
Impact: Reduced concessions, protected margin
Inventory Shrink Agent
Identifies theft and execution failures before margin is impacted
Theft (internal or external)
Process failures in stores or warehouses
Inventory discrepancies and execution gaps
Impact: Protected revenue, lower losses
Fulfillment Execution Agent
Resolves fulfillment issues by automating corrective actions end-to-end
Manual exception triage and ticket handling
Training and process gaps
Throughput bottlenecks during peak periods
Impact: Seconds vs. hours of resolution time
Beyond Reporting - Execution, Automated
Beamup replaces dashboards and alerts with AI agents that detect execution issues, identify root causes, and resolve them automatically at scale.
