Hello
I have been experimenting with AI in Katalon Studio & one idea I am excited about is whether AI can go beyond test generation and actually suggest smart assertions based on the context of the page or user journey. ![]()
For eg; if a test script navigates to a product checkout page, could AI suggest asserting the presence of “Total Amount,” “Place Order” button /expected price values even without being explicitly told? ![]()
I know Katalon integrates with GPT-based tools but the current use cases I have seen focus mostly on generating test steps / summarizing results.
Has anyone explored or implemented a workflow where AI analyzes the DOM, page structure, or past test data to automatically recommend assertions? ![]()
This would be hugely helpful for reducing human error and accelerating test creation, especially for large web apps. Checked Supercharge Testing with Katalon's AI-Powered Features guide for reference .
This question actually came up while I was trying to explain to a colleague what is ChatGPT and it led to a deeper conversation about how LLMs might improve test quality, not just quantity.
If anyone has used AI for intelligent assertions or validation logic in Katalon, I would love to hear how you approached it.
Thank you !! ![]()