What do the TestMu AI agents do?

They cover each QA stage, from planning to analysis. KaneAI turns requirements, Jira tickets and plain-English prompts into tests, Kane CLI checks a change in a real browser from the terminal, HyperExecute runs suites in parallel, SmartUI and the Accessibility Testing Agent add visual and WCAG checks, Auto Healing repairs broken locators, and Test Intelligence points to the likely cause of a failure. For the wider topic, see this guide to AI agent testing.

Can TestMu AI agents replace QA testers?

No. They take on repetitive work, such as writing regression tests, updating broken locators and sorting failures, so testers spend more time on exploratory testing, risk and release decisions. People stay in control: KaneAI test plans are reviewed before they run, healed steps are logged for review, and root cause analysis suggests a likely cause for a person to confirm.

How do TestMu AI agents handle flaky tests?

Auto Healing builds a new locator when a DOM change breaks a selector, so a moved or renamed element does not fail a valid test. HyperExecute can retry a failed test command up to five times, and you can limit retries to errors that match patterns you set, so a real assertion failure still fails. Test Intelligence flags tests whose results change between runs and ranks them by severity, so the team can fix the cause.

Are results from TestMu AI agents deterministic?

Not every step. An AI step can take a different path from one run to the next, so the tests you keep are fixed. KaneAI exports Selenium, Playwright and Appium code that runs the same steps every time, and a Kane CLI test saved as a test.md replays its unchanged steps from cache with no LLM cost. When a page changes and a step is re-authored, the change is recorded for review. Root cause analysis output is a lead to verify, not a verdict.

How do TestMu AI agents fit into a CI/CD pipeline?

HyperExecute runs from any CI tool that can call a command, with documented setups for GitHub Actions, Jenkins, GitLab, Azure DevOps and CircleCI. Kane CLI exits with 0 on a pass and 1 on a fail, so a pipeline can gate a merge on it. KaneAI tests run on HyperExecute or as exported code in your existing pipeline, and the TestMu AI GitHub App runs them on a pull request and posts the results back.

Which TestMu AI agent should an enterprise team start with?

Start where the suite hurts most. If writing tests is the bottleneck, start with KaneAI, which turns requirements into tests and exports code your team owns. If runs are slow or flaky, start with HyperExecute: Boomi reports 78% faster testing with it. If developers ship code with coding agents, add Kane CLI so each change is checked in a real browser before it merges.

AI Agents by TestMu AI
for the Full Testing Lifecycle

TestMu AI agents are AI agents that test software. They plan, write, run, heal and analyze tests for web and mobile apps: KaneAI and Kane CLI turn plain-English intent into tests, HyperExecute runs them in parallel, Auto Healing repairs broken locators and Test Intelligence points to the likely cause of a failure.

Trusted by 3M+ users. TestMu AI is positioned as a Leader in the 2026 Gartner Magic Quadrant for Agentic Software Quality Assurance Platforms and recognized in The Forrester Wave: Autonomous Testing Platforms, Q4 2025.

Get Started

TestMu AI Agents by QA Stage, From Plan to Analyze

Eight agents across five stages: plan, author, execute, heal and analyze. Each row says what the agent does and who on the team uses it.

TestMu AI agents by QA stage: what each agent does and who uses it
QA stage	Agent	What it does	Who uses it
Plan, author	KaneAI	Turns PRDs, Jira tickets, images, audio, video or a GitHub PR into a test plan you approve, then writes the tests and exports Selenium, Playwright or Appium code.	QA engineers, manual testers and product managers
Author, execute	Kane CLI	Runs a plain-English check from the terminal in a real browser, an Android Emulator or an iOS Simulator, and returns a pass or fail with steps, screenshots and logs.	Developers, and coding agents such as Claude Code, Cursor and Codex
Execute	HyperExecute	Splits a suite across just-in-time cloud machines and runs it in parallel, up to 70% faster than a traditional grid, with retries, logs and reports in one place.	QA automation, DevOps and release engineers
Execute	SmartUI	Compares screenshots across browsers, devices and resolutions, filters rendering noise and dynamic content, and checks builds against Figma designs.	QA engineers, front-end developers and designers
Execute	Accessibility Testing Agent	Scans websites and native apps with automated WCAG checks, in CI, on a schedule or on real devices with screen readers, and ties each fix to the rule it fails.	QA teams, front-end developers and accessibility specialists
Heal	Auto Healing	Builds a new locator when a DOM change breaks a selector, so the run continues, and shows each healed locator next to the original.	Automation engineers running Selenium and Playwright suites
Analyze	AI Root Cause Analysisin Test Intelligence	Reads the command, network and console logs of a failed test and returns a likely cause with fix steps: a lead to verify, not a verdict.	SDETs and QA engineers triaging failed runs
Analyze	Test Intelligence	Tracks results across runs, flags flaky tests, groups similar errors and shows the trends that tell you whether a build is ready to ship.	QA leads and engineering managers

Not sure where to start? See the agents run on your own app and pipeline.

How TestMu AI Agents Heal Tests and Analyze Failures

AUTO HEALING

Auto Healing Agent Fixes Broken Locators During a Run

When a DOM change breaks a selector, the agent matches the page against the element it last found, builds a new locator and keeps the test running.

Explore Auto Healing Agent

Set autoHeal: true for Selenium and Playwright tests
Works on the cloud grid and on HyperExecute runs
See each healed locator next to the original selector

Auto Healing showing a healed CSS selector beside the original XPath selector

TEST INTELLIGENCE

Test Intelligence Finds Flaky Tests and Likely Root Causes

Test Intelligence reads results across runs, ranks tests by how often they fail, groups similar errors and generates root cause analysis on demand.

Explore Test Intelligence

RCA reads network, console and framework logs together
Generate RCA from Test Manager or a HyperExecute job
Each report lists a likely cause and remediation steps

Test Intelligence failure analysis with errors identified, flaky test detection and a Generate RCA button

TestMu AI Agents vs Scripted Tests and AI Coding Agents

Who writes the test, what breaks when the UI changes and what proof a run leaves behind, across three ways teams test. Reviewed October 2026.

Top Choice

Features

TestMu AI agents

Scripted tests

AI coding agents

Who writes the test

Agent, from plain English

Engineer, in code

Agent, in code

Main job

Test the app as users do

Repeat fixed checks

Write and change code

When the UI changes

Step heals, change logged

Fails until edited

Re-prompt to fix tests

Proof of a pass

Steps, screenshots, logs

Runner logs and reports

Its own report

Repeat runs

Saved steps replay from cache

Same steps every run

Varies with the prompt

Where it runs

TestMu AI cloud or locally

Your grid or CI

Your editor or terminal

Best for

Coverage with less upkeep

Stable, fixed flows

Building features fast

Agent Testing and Agent Assurance for Your Own AI Agents

The agents above test the apps you build. To test an AI agent your team ships, pick the product by what that agent does.

Agent Testing for Customer-Facing AI Agents

Agent Testing checks AI agents that reach people through chat, voice, phone, image or video. Its testing agents run realistic conversations and inputs against yours and score the results on metrics such as hallucination, bias and completeness, before and after release.

Agent Assurance for AI Agents That Take Actions

Agent Assurance tests agents that act, from the terminal with Rook CLI: coding, workflow and back-office agents that call tools, write files and use APIs or MCP servers. It reads the agent code, writes scenarios, runs the agent for real and checks what the agent did against evidence, marking anything it cannot confirm as Unable to Verify. It is self-serve, with a 14-day free trial.