Ito is an automated testing platform that uses AI agents to perform behavioral quality assurance on web applications during the pull request process. Rather than forcing developers to write and maintain brittle end-to-end test scripts, Ito analyzes code changes to determine which user paths are most likely affected. It then launches an instance of the application and uses a browser-based agent to navigate those flows autonomously. By interacting with the actual UI, it identifies regressions—like broken buttons or logic errors—that traditional static code analysis usually misses. The tool integrates directly into the development workflow, posting visual reports and video evidence of failures directly into the code repository. Because it is framework-agnostic, it functions across various tech stacks without requiring specific language configurations or deep setup. While it does not replace the need for unit tests, it acts as a high-level safety net for user-facing features. It effectively bridges the gap between slow manual QA and high-maintenance automated scripts, providing a flexible way to ensure that new code doesn't disrupt the existing user experience before it reaches production.
Problem: Software teams often merge pull requests that inadvertently break critical user flows because manual testing is slow and automated scripts are outdated.
Solution: Ito automatically analyzes code changes in a PR to identify and test affected user paths using a browser-based AI agent before the code is merged.
Example: A developer modifies a shared UI component; Ito detects the change and automatically verifies the login and checkout flows in a sandbox to ensure no regressions occurred.
Problem: Traditional E2E testing frameworks like Playwright or Cypress require developers to manually update scripts every time a CSS selector or UI element changes.
Solution: The platform uses scriptless agents that interact with the application like a real user, adapting to UI changes without requiring manual code updates for the tests themselves.
Example: A team migrates their styling from CSS modules to Tailwind; Ito continues to navigate the application successfully without needing its test paths rewritten.
Problem: Testing features behind authentication or multi-factor login often requires complex mock setups or manual intervention.
Solution: Ito handles authenticated sessions and MFA by using provided test credentials, allowing the agent to navigate and validate protected areas of the application autonomously.
Example: An engineering team uses Ito to verify that a new data visualization dashboard correctly loads for users with specific permission levels.
Target audience: Best for: Engineering Managers, QA Leads, Senior Software Engineers
Pricing: Paid · Categories: Code Assistants, Developer Tools, Productivity
Tags: AI, ai agent, developer tools, low-code/no-code, Reporting