Aura Logistics: AI-Powered Fulfillment
Logistics & Supply Chain — 8 weeks engagement · 3 engineers
Challenge
Aura Logistics operated three warehouses across the region with entirely manual processes. A four-person team spent 60% of their labor hours on physical inventory counts, cycle tracking, and order picking workflows that hadn't changed in a decade. The fulfillment cycle averaged 12 hours per order, and stockout rates hovered around 15% — burning margin and eroding customer trust.
Solution
We deployed a self-hosted JH Engine cluster with custom workflow nodes built specifically for Aura's warehouse topology. Real-time inventory synchronization now runs across all three facilities via WebSocket-fed dashboards. A custom ML demand forecasting model — trained on 18 months of historical order data — predicts stock depletion 72 hours in advance. Exception routing automatically escalates anomalies to the operations lead.
Before → After
Architecture
- Self-hosted JH Engine with 12 custom nodes
- PostgreSQL for inventory state management
- GPT-4o for natural-language exception summaries
- Custom ML model for demand forecasting
- Shopify API bidirectional sync