A global leader in industrial automation and wireless control technologies was challenged with high-effort manual testing, fragile automation scripts caused by frequent UI changes, and poor scalability in desktop regression. These challenges drove rising maintenance costs and slowed release validation.

To address this, the company leveraged eInfochips AI Studio’s AI-powered desktop automation. By implementing visual element recognition, natural language–driven test steps, and self-healing AI agents, the team automated critical workflows across desktop environments and improved resilience to UI changes. As a result, they reduced automation engineering effort by approximately 30%, accelerated regression cycles by 70–85% and cut execution effort from 60 to just 17 person-days per release.