TestProject Alternative AI Testing Without Selenium

TestProject was popular because it wrapped Selenium in a friendlier interface and added a free cloud execution layer. When it closed, most teams replaced it with another Selenium wrapper: Katalon, Ranorex, or a custom Playwright setup.

The problem is the model, not the interface. Selenium-based tools require element selectors. Selectors break when developers rename a class, restructure the DOM, or ship a redesign. Your test suite becomes a maintenance burden that grows proportionally with your product.

AI tools that move past the selector model aim to solve this by significantly reducing the manual effort required for updates. This shift works because of the underlying mechanism: a transformer model reads the test intent in plain English, computer vision identifies the relevant UI elements at runtime, and a feedback loop retries failed actions before flagging them. The test does not care what the button's ID attribute is.

That is the gap to evaluate when comparing TestProject alternatives for AI testing. Ask the vendor directly: does the tool use CSS selectors or XPath under the hood? If yes, you have inherited the original problem.

Autosana is built for teams testing iOS apps, Android apps, and websites who do not want to write or maintain test scripts. You write tests in plain English, something like 'Log in with test@example.com and verify the home screen loads,' and an AI agent executes them.

What makes Autosana different from most TestProject alternative AI testing tools is its positioning as the end-to-end testing layer for coding agents. It is not retrofitting AI onto a Selenium core. When you open a pull request, Autosana reads the code diff, generates or updates the relevant tests, runs them via cloud agents, and returns video proof of whether the feature works. The tests evolve with your codebase automatically.

Key capabilities:

• Write end-to-end tests in natural language across iOS, Android, and web from a single platform
• Upload your .app or .apk build to run mobile tests directly
• CI/CD integration via GitHub Actions so tests run automatically on every push
• Schedule automated test runs to catch regressions between releases
• REST API for programmatic test suite creation and custom integrations
• Visual results with screenshots and video proof of each test run
• MCP onboarding for teams already using coding agents

For teams running agentic development workflows, Autosana is the most direct fit. You do not need a dedicated QA engineer to maintain it. Pricing is not publicly listed, so contact the team directly.

The practical case: a startup shipping a React Native app can upload a build, describe the core user flows in English, connect GitHub Actions, and have automated E2E coverage running before the end of the day. No XPath. No Selenium grid setup. No test maintenance queue building up.

Katalon supports web, mobile, API, and desktop testing and has a free tier, which is why it became the default migration path for a lot of ex-TestProject users. Its AI features, StudioAssist for test generation and TrueTest for stability, are addons on top of a fundamentally Selenium and Appium core.

That is a meaningful limitation. StudioAssist helps you write tests faster, but the output is still a script with locators. When your app's UI changes, you still go fix the selectors. The AI reduces creation effort but does not eliminate maintenance effort.

Katalon is a reasonable choice if your team already has QA engineers comfortable with scripted frameworks and wants AI assistance rather than AI autonomy. It is not a fit if you are trying to reduce QA overhead.

Testim uses smart locators and has added agentic automation features. For web UI test stability it is genuinely good. Tests are less brittle than raw Selenium because Testim's locator engine checks multiple element attributes, not just one.

The ceiling is around $300/month (TestCollab, 2026), and the platform is web-focused. If you are testing iOS or Android apps, Testim is not the right tool. If you are web-only and budget is not a concern, it is a viable TestProject alternative AI testing option, but you are paying for stability features that a newer agentic tool gives you by default.

For a deeper look at how Testim compares on natural language capabilities, see our Testim alternative comparison.

Mabl is a low-code platform with auto-healing tests and solid CI/CD integration. It sits between traditional scripted testing and fully autonomous AI agents. You record interactions to generate tests, and Mabl's AI adjusts them when the UI changes.

The auto-healing is real and it works. The limitation is that you still start from a recording or a manual flow definition. You cannot describe intent in plain English and let the agent take over entirely. That means Mabl requires more upfront test authoring time than a natural language platform.

Pricing is custom, which usually means it is priced for enterprise teams. For startup or small engineering teams, that is worth confirming before you invest time in an evaluation.

LambdaTest starts at $15/month and gives you cloud infrastructure for cross-browser and cross-device testing. Its AI features, KaneAI for test generation and HyperExecute for parallel execution, are notable for the price.

KaneAI lets you describe tests in natural language and generates the underlying Selenium or Playwright code. That is useful, but the generated code is still code you need to maintain. It is a code-generation tool, not an autonomous agent.

LambdaTest is the right answer if you need large-scale cross-browser coverage on a budget and have engineers who can maintain generated test scripts. It is not the right answer if reducing manual QA effort is the primary goal. For more detail on how it compares, see BrowserStack alternative AI testing with natural language.

Testsigma lets non-engineers write tests in plain English and integrates with CI/CD pipelines. It supports web, mobile, and API testing. For teams where product managers or manual QA engineers own test creation, it is one of the more accessible options available.

The AI in Testsigma is primarily used for test authoring assistance and smart element detection. It is closer to an AI-assisted platform than a fully autonomous agent. The tests still require human review and occasional maintenance when the app changes significantly.

If your team specifically needs QA for product managers who do not write code, Testsigma is worth evaluating alongside Autosana.

Here is the honest breakdown across the tools covered:

Tool	Natural Language Tests	Mobile (iOS/Android)	No Script Maintenance	Agentic Execution
Autosana	Yes	Yes, both	Yes	Yes
Katalon	Partial (AI-assisted)	Yes	No	No
Testim	Partial	No	Partial	Partial
Mabl	No (recording-based)	No	Partial	No
LambdaTest	Code generation	Yes (cloud devices)	No	No
Testsigma	Yes	Yes	Partial	No

The distinction between "AI-assisted" and "agentic" is not marketing semantics. An AI-assisted tool helps you write and maintain tests faster. An agentic tool takes the intent, executes the test, handles UI changes, and updates itself when the codebase changes. That gap is the difference between cutting test authoring time by 40% and cutting test maintenance by 85%.

For teams on agentic development workflows, shipping daily with coding agents, the agentic testing column is the only one that matters. Every other tool in the list becomes a bottleneck.