Visual Regression Testing with Apify & AI Vision Model

This n8n workflow enables automated visual regression testing for webpages. It starts by reading a list of URLs from Google Sheets, captures baseline screenshots using Apify's web scraping service, and uploads them to Google Drive for storage. A scheduled trigger later initiates the testing phase, recapturing fresh screenshots of the same pages.

Base screenshots are downloaded in parallel alongside the new ones, then both image sets are fed into an LLM node configured for multi-image analysis. The LLM detects visual differences based on custom criteria, providing intelligent insights into UI changes, regressions, or anomalies.

Finally, a report summarizing findings is generated and uploaded to Linear for issue tracking. Benefits include hands-free monitoring of web UIs, reduced manual QA effort, and scalable testing across multiple pages. Use cases: Finance dashboards, e-commerce sites, SaaS apps ensuring visual consistency post-updates; perfect for teams needing proactive regression detection without complex tools.