Automated Visual Webpage Regression Testing Workflow

This n8n workflow automates the process of visual regression testing for websites using AI vision models. It compares current webpage screenshots against baseline images stored in Google Drive to identify unexpected visual changes. The workflow is split into two main parts: Part A generates and uploads base images, which serve as reference points for future comparisons; Part B captures new webpage screenshots and compares them to the base images to detect differences. It leverages Apify for webpage screenshots, Google Sheets for tracking URLs and images, Google Drive for storing images, and an AI model (Google Gemini) to analyze visual differences. Results are summarized and reported in Linear, helping teams quickly identify UI regressions and maintain brand consistency. This workflow is especially useful for QA teams, developers, and digital agencies aiming for continuous visual quality assurance across website updates.