Warehouse AI Copilot

Warehouse staff spend 40% of their time searching for items instead of picking, packing, and shipping. Pick paths are suboptimal, sending workers crisscrossing the warehouse instead of following efficient routes.

Stockouts and overstock alternate in a frustrating cycle — you either don't have what customers need or you're paying to store what they don't. Manual cycle counts consume labor hours that could be spent on value-adding work.

Pick efficiency improves by 35%. Workers follow optimized routes that minimize travel time and maximize picks per hour.

Stockout rate drops from 8% to 2%. Demand forecasting ensures the right inventory is available at the right time without overstocking.

Cycle count time drops from 4 hours to 45 minutes. Warehouse utilization improves by 20% through better slotting and layout optimization.

Depot connects to your WMS and analyzes inventory levels, order patterns, and warehouse layout to build a real-time optimization layer over your existing operations.

The pick path planner generates optimal routes for each wave of orders, accounting for item locations, priority levels, and worker capacity. Routes update dynamically as conditions change.

Demand forecasting and auto-replenishment rules trigger reorder recommendations based on sales velocity, seasonality, and lead times — keeping inventory levels optimized without manual intervention.