Logistics & Supply ChainReactNode.jsMQTT

WareFlow — Warehouse Automation System

An intelligent warehouse management system with barcode/RFID integration, automated pick-pack-ship workflows, and real-time inventory visibility across locations.

Project Overview

WareFlow is a warehouse management system built for a 3PL provider operating 4 fulfillment centers totaling 800,000 square feet. The platform manages inbound receiving, inventory slotting, pick-pack-ship workflows, and outbound shipping with carrier rate shopping. MQTT handles real-time communication with barcode scanners and RFID readers on the floor, while Redis powers the task queue that distributes work to pickers. The system processes over 2.4 million orders per month with a 99.8% picking accuracy rate.

Timeline

16 Weeks

Team Size

7 Engineers

Platform

React + Node

Industry

Logistics

Key Results

2.4M

Monthly Orders

99.8%

Pick Accuracy

52%

Faster Fulfillment

4

Warehouses Live

The 3PL provider ran on a legacy WMS from 2012 that could not scale beyond 500K monthly orders. Picking errors averaged 3.2%, costing over $400K annually in returns and reshipping.

Legacy WMS limited to 500K orders/month — the business was outgrowing it

Picking error rate of 3.2% causing $400K+ in annual return and reship costs

No real-time inventory visibility — stock counts updated in nightly batches

Manual carrier selection costing 15-20% more than optimal shipping rates

We designed a real-time event-driven architecture using MQTT for device communication and Redis for task orchestration. The system uses zone-based wave picking and intelligent slotting to minimize picker travel distance.

Built an MQTT-based device layer for real-time barcode scanner and RFID communication

Implemented zone-based wave picking with AI-optimized walk paths reducing travel by 38%

Created dynamic inventory slotting that moves high-velocity SKUs closer to pack stations

Integrated rate shopping across 8 carriers with automated label generation

WareFlow scaled the operation from 500K to 2.4M monthly orders without adding warehouse staff. Picking accuracy improved from 96.8% to 99.8%, and average fulfillment time dropped from 4.2 hours to 2 hours.

Scaled from 500K to 2.4M monthly orders with the same workforce

Picking accuracy improved from 96.8% to 99.8%, saving $380K annually

Average order fulfillment time reduced from 4.2 hours to 2 hours

Shipping costs decreased 18% through automated carrier rate shopping

Technologies Used

ReactNode.jsMQTTRedis

WareFlow let us 5x our order volume without hiring a single additional picker. The accuracy improvement alone saved us nearly $400K in the first year. Our 3PL clients now get same-day fulfillment as standard.

Lisa Chen

COO, PrimeFulfill Logistics