Visual QA Checker for BilaUnwan.pk

An AI-powered visual quality assurance tool that detects layout shifts, broken links, and UI regressions across publishing workflows—saving time and ensuring a polished user experience.

Visual QA Screenshot

Visual QA Checker for BilaUnwan.pk

A production-grade, automated QA tool built to monitor and detect visual anomalies, broken links, and layout drifts across the BilaUnwan.pk publishing platform. This solution was tailored for a fast-paced content environment with minimal manual QA.

Business Challenge

  • Frequent layout shifts across devices and browsers
  • Manual testing was slow and error-prone
  • Content updates caused hidden frontend regressions
  • Dead links and UX bugs affected reader trust

Solution Highlights

  • Automated screenshot crawling of live pages
  • ML-based detection of visual inconsistencies
  • Real-time alerts via email, Slack, Telegram
  • Dead link reporting dashboard
  • Retrainable pipeline with issue labeling

Impact

  • Reduced manual QA time by 80%
  • Rapid bug discovery after each update
  • Cross-device and cross-browser coverage
  • Enabled confidence in scaling content campaigns

Tech Stack

Frameworks: FastAPI, React
DevOps: Docker, GitHub Actions
ML Tools: MLFlow, Custom CV Models
Others: Python, Puppeteer, Slack API

Why It Matters

FursanStudio's solution helped a grassroots publishing platform implement enterprise-grade QA — affordably and flexibly — without vendor lock-in or technical overhead.

Project information