90% More Precise QR Scanning and 50% Faster Deployments

We built a high-performance QR reader with 2-meter range and introduced agile workflows with Atomic Design training and CI/CD pipelines.

The Challenge

QR code scanning optimization and development team efficiency improvement

TrackPlan FM's asset management platform was built for Industry 4.0 — but their QR code scanning system was holding operations back. The scanner had limited range and poor format support, forcing warehouse workers to get uncomfortably close to large machinery just to scan asset codes.

This created bottlenecks in shipment processing and increased error rates. Compounding the problem, the development team lacked structured workflows — no component architecture, no automated testing, and manual deployments that took days and introduced regressions.

Workers were spending more time fighting the scanner than managing assets — a tool meant to accelerate operations had become the biggest bottleneck.

Our Approach

How we tackled it

QR Reader Rebuild

Engineered a new QR code reader from scratch using Camera API, achieving accurate scanning at distances up to 2 meters with multi-format support.

Atomic Design Migration

Migrated legacy React components to an Atomic Design architecture, creating a modular and maintainable component library.

CI/CD Pipeline Implementation

Set up automated testing with Jest and CI/CD pipelines that eliminated manual deployments and regression risks.

The Solution

High-performance QR reader and modular architecture

We rebuilt the QR code reader from scratch, engineering it to scan accurately at distances up to 2 meters — a game-changer for scanning large industrial equipment. The new reader supported multiple barcode formats and was integrated directly into the web platform using Camera API and modern JavaScript.

Beyond the scanner, we transformed the team's development practices: migrating legacy React components to an Atomic Design architecture, training the team on modular component patterns, and implementing CI/CD pipelines that automated testing and deployment.

Results