Use Cases
What you can build and test with TestMu AI
Real workflows for testing web apps, mobile apps and AI agents. Two are written out end to end, and 36 more link straight to the setup steps. Start with the one closest to yours.
Last Updated on:
Find your use case by product or category
2 of 2 use cases
Performance Testing
Run performance tests at scale
Spread load across machines and regions without owning a generator fleet, and without the replication trap that quietly inflates your user count.
Test Orchestration
Cut test execution time for high-velocity releases
Find which of the six segments in a run actually responds to more machines, then split the suite you already have from a single config file.
Start from where you actually are
Most teams arrive with one of four problems. Pick the line that sounds like yours.
You already have a test suite
Keep the framework and the tests. Move the execution onto cloud machines and split the run so wall-clock time drops.
You are starting with no tests
Author in plain English against a worked scenario close to your own product, then run what comes out.
Your users are on mobile
Reproduce the bug on the actual handset and OS build it was reported on, not on an approximation of it.
You are shipping an AI agent
Evaluate where a multi-step agent leaves the intended path, across text and voice interactions.
The workflow library
36 more jobs people bring to the platform, grouped by the product that does the work. Each group gives you both halves: the documentation that has the setup steps, and the guides and tutorials that explain the thinking behind them.
KaneAI
Author tests in natural language, then run them the way you run everything else.
Set it up
HyperExecute
Orchestration for suites that have outgrown a single machine.
Set it up
Automation Testing Cloud
Browser and OS coverage for Selenium suites.
Set it up
Real Device Cloud
Real hardware, for the bugs emulators do not reproduce.
Set it up
App Automation
Appium and Espresso suites on an Android and iOS fleet.
Set it up
SmartUI Visual Testing
Pixel, layout and document comparison as a build step.
Set it up
Accessibility Testing
WCAG checks while you build, and again on every run.
Set it up
Test Manager
Case libraries, run tracking and issue links in one place.
Set it up
Test Intelligence
What failed, what is flaky, and why.
Set it up
Browser Cloud
Cloud Chrome for agents and long-running automation.
Set it up
MCP Server
Drive the platform from the AI assistant you already use.
Set it up
Agent Testing Platform
Evaluation for agents that reason over several steps.
Set it up
Platform & Integrations
The plumbing around the runs: CI, tunnels and access.
Set it up
Questions people ask before they start
What counts as a use case on this page?
A specific job, not a product tour. Each entry names the outcome someone was after, such as cutting pipeline time or reproducing a device-specific bug, and links to the page or documentation that shows the setup. The four detailed pages walk through a full workflow. The workflow library links straight to the documentation for the rest.
Do I have to rewrite my existing tests to use any of this?
No. HyperExecute takes the framework you already run, described in a single YAML file, and executes that same suite on cloud infrastructure. Selenium, Appium and Espresso suites run as they are. Rewriting is only on the table if you choose to author new tests in KaneAI.
Which product should I start with?
Start from the problem. If runs are too slow, start with HyperExecute. If you have no tests yet, start with KaneAI. If bugs only appear on certain handsets, start with the Real Device Cloud. If you are shipping an AI agent rather than an app, start with the Agent Testing Platform.
Can I test a build that is not deployed anywhere yet?
Yes. A tunnel connects the cloud browsers and devices to a build running on your machine or inside a private network, so you can test a localhost or staging build before it is publicly reachable.
Can I test AI agents and not just web and mobile apps?
Yes. The Agent Testing Platform evaluates agents that reason across several steps, including LangGraph reasoning paths and voice agents handling realistic call scenarios, so you can see where an agent leaves the intended path.
Do these workflows fit into my CI pipeline?
Yes. Runs can be wired into the CI tool you already use so a build is gated on real test results, and AI-authored suites can execute automatically on each commit.
Where do the exact setup steps live?
In the documentation. Every entry in the workflow library links directly to the doc for that job, and the documentation goes deeper than a directory can on frameworks, integrations and platform capabilities.
Not seeing your workflow here?
The docs go deeper than a directory can: every framework, every integration, every platform capability. If you would rather talk it through, a solutions engineer can map your stack to a working setup.
TestMu AI for Enterprise
Get access to solutions built on Enterprise grade scurity, privacy, & compliance