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ERP & Enterprise Software

SwiftStock: Inventory AI

Client
Retail Pulse
Timeline
8 Months
DjangoPythonReactRedisCelery
SwiftStock: Inventory AI
Primary Result
Zero Stock-outs
The Challenge

Understanding the Friction.

Poor distribution was causing stock-outs in 20% of locations while others were overstocked.

Project Goals

  • 01.Zero stock-outs for core products
  • 02.Automate 100% of inter-warehouse transfers
  • 03.Reduce dead stock by 30% in 6 months
The Blueprint

Our strategic Protocol.

01

Logistics Audit

Mapping the transfer bottlenecks in the current fleet.

02

Logic Implementation

Building the AI transfer engine in Django.

03

Scale Up

Stress testing across 100 simultaneous warehouse nodes.

Business Impact

Quantifiable Velocity.

0%
Stock-out Rate
-30%
Dead Stock
+40%
Logistics Speed

For the first time in years, our shelves are always full and our waste is at zero. Perfect engineering.

M
Michael Scott
Regional Manager @ Retail Pulse

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