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Mobile·Retail

Inventory Scanner

Store staff used paper clipboards for stock counts, leading to 12% inventory discrepancy.

Overview

We built a mobile inventory scanning app that uses the phone camera for barcode recognition, syncs counts in real time, and flags discrepancies immediately — replacing paper-based stock counts that took days and had 12% error rates.

Client

A retail chain with...

Timeline

10 weeks

Team

1 engineer

Industry

Retail

The Challenge

A retail chain conducted quarterly inventory counts using paper clipboards and manual data entry. The process took days per store, had significant error rates, and results were outdated by the time they were processed. Shrinkage was hard to detect because counts were too infrequent and inaccurate.

Our Approach

1

Built camera-based barcode scanning with ML-powered recognition for fast, accurate reads

2

Implemented real-time sync to central inventory management as items are counted

3

Created location-based counting workflows that guide staff through zones systematically

4

Added discrepancy flagging and resolution tracking so variances are investigated immediately

Key Results

12→3%

Discrepancy Rate

4 hrs

Count Time per Store

Weekly

Count Frequency

10 wks

Delivered In

Inventory count time reduced from days to hours per store

Discrepancy rate dropped from 12% to under 3%

Counts can now be done weekly instead of quarterly

Shrinkage identified and addressed much faster

Inventory counts used to shut down the store for two days. Now two people do it in half a day with their phones. We count weekly now and actually know what we have in stock. The shrinkage problem became obvious once we had accurate numbers.

Regional Manager, Retail Chain

Tech Stack

FlutterTensorFlow LiteNode.jsPostgreSQLRedis

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