Octomind's AI agent agent mimics human users (i.e., clicks input fields, signs up for newsletter) to navigate apps, interprets app intent, and identifies all relevant user flows. Â
AI test case discovery
Our AI agent traverses the publicly accessible code in the DOM and uses the vision capability of the underlying multimodal LLM to add visual context when code insight is insufficient. Â
AI-based automated step generation
Our AI mimics user behavior to interact with apps as a human would to reach the goal of a user flow.
We record and store each test case's interaction chain and generate the corresponding Playwright code deterministically on the fly immediately prior to test execution.
AI auto-maintenance
Available soon.
Octomind automatically determines if test failures are caused by user flow behavioral changes, the test code itself, or bugs in the code.
In the case of a behavioral change, we pinpoint failing interactions, and deploy the AI Agent to detect new desired interaction that will allow us to achieve the test case's goals.
fight flaky tests with AI
Available soon. Â
We already deploy a variety of techniques to fight test flakiness. Yet, it's not enough.
That's why we are investigating the best ways to implement AI-based analysis of unexpected site behavior, like temporary pop-ups or toasts, and further improve testing performance.
blogtopus: on AI, agents and app testing
50% developer rants, 50% tech news commentary, 100% cephalopod opinions on all things software. It's worth the read. Â Guaranteed.
We have launched the beta version. Browse our docs at your own pace or request a personalized demo, if you need to talk to our devs. Or just start for free, today.
