AI Warehouse Operations Optimizer

Overview

A warehouse optimization platform for distribution centers, 3PLs, and high-volume e-commerce ops. The system reads from your WMS in real time, models the current state of every bin, every active wave, and every active picker, and computes the optimal pick path for each picking task based on actual bin locations and travel distance. It re-ranks SKU placement weekly based on order frequency (high-velocity items move closer to the dock; slow-movers move out). It tracks pick rate, accuracy, and SLA conformance at the picker level and surfaces patterns for ops management. The picker UX is a clean turn-by-turn screen on the existing handheld; the back-end is the heavy lift.

The Challenge

Warehouse optimization is a real operations-research problem. Pick path computation has to be fast (sub-second per task), correct (no shortcuts that send pickers through a closed lane), and adaptive (when bin contents change mid-wave, the optimization re-runs). SKU slotting recommendations have to respect physical constraints (weight limits, height limits, hazmat zones). The system has to integrate cleanly with the WMS you already paid for — usually as an overlay, not a replacement. And the picker UX has to be so simple that nobody pushes back during rollout.

Our Approach

We model the warehouse as a graph (bins as nodes, aisles and crossovers as edges) with travel costs derived from actual measured shift data. Pick path optimization runs as a constrained traveling-salesman variant solved in real time per task. SKU slotting uses weekly ABC analysis on actual order volume combined with physical constraints to produce a re-slotting plan with estimated labor savings. Integration with the WMS (Manhattan, Korber/HighJump, SAP EWM, NetSuite WMS, custom) is via API. The picker UX is a thin overlay on existing handhelds. Throughput, accuracy, and SLA dashboards run in real time.

Key Features

• Real-time per-task pick path optimization
• Weekly SKU slotting recommendations with estimated labor savings
• Picker-level performance metrics (rate, accuracy, SLA)
• WMS integration (Manhattan, Korber, SAP EWM, NetSuite, custom)
• Constraint-aware (weight, hazmat, height, zoning)
• Live wave dashboard for ops management
• Picker UX on existing handhelds — no new hardware
• Shift-level reports for performance reviews

Results

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