Squish Alternative: AI Testing With Natural Language

Squish is genuinely good at what it does. It handles Qt apps, supports cross-platform desktop UI testing, and has years of enterprise polish. The problem is not Squish itself. The problem is the underlying model: scripted, selector-based automation that breaks when the UI changes.

Every time a button moves, a locator changes, or a new screen appears, someone has to update the test. On a fast-moving team, that someone is usually a developer who would rather be shipping. Qt's own blog from 2026 describes using AI assistants like Cursor, Claude Code, and GitHub Copilot to generate Squish scripts faster (qt.io, 2026). That is AI-assisted script generation layered on top of Squish, not a replacement of the brittle model itself.

Real alternatives eliminate the script model entirely. Instead of generating better XPath selectors, they understand test intent. Instead of flagging failures, they adapt. That is the gap worth closing.

Autosana is the clearest break from the Squish model available in 2026. You write tests in plain English, for example 'Log in with test@example.com and verify the home screen loads,' and an AI agent executes the flow automatically. No selectors. No scripts. No build step before you can test.

For teams building iOS and Android apps, Autosana lets you upload your .app or .apk build and run end-to-end tests immediately. Website testing works the same way: enter a URL and write flows in natural language. The test agent provides visual results with screenshots after each run, so you can see exactly what happened without decoding a stack trace.

The CI/CD integration with GitHub Actions means tests run automatically in your deployment pipeline. Autosana also generates and updates tests based on pull request context and code diffs, so your test suite evolves with your codebase rather than lagging behind it. PR-level end-to-end testing comes with video proof, which is exactly the kind of artifact that makes code reviews meaningful.

For teams using agentic development workflows, Autosana connects directly via MCP onboarding and supports local test execution that loops with your coding agent. This is not a GUI testing layer bolted onto a script runner. It is natural language test automation designed around the way modern teams actually ship software.

Positioning is honest: Autosana is best for mobile and web teams who are done writing test scripts and want a system that keeps up with fast development cycles.

testRigor lets you write tests in plain English and runs them across web, mobile, and desktop. Its self-healing approach means tests adapt when UI elements shift, reducing the maintenance burden that makes Squish painful at scale.

It is a reasonable Squish alternative AI testing option for teams with mixed platforms, though it skews toward web and is less focused on the mobile-native testing use case. Teams looking for deep iOS and Android coverage will find Autosana more purpose-built for that workflow.

Applitools integrates with existing test frameworks rather than replacing them, so teams moving off Squish would still need another tool to handle test authoring and execution. For teams where visual consistency is the primary concern, Applitools is strong. For teams who want to eliminate scripting entirely, it is only part of the answer.

Testim uses heuristic AI to stabilize locators, which reduces test flakiness on web apps. It is closer to a Squish replacement for web-only teams than for mobile teams. Self-healing kicks in when element attributes shift, but the underlying model still requires test creation through a recorder or manual flow setup.

If you are evaluating Testim as a Testim alternative for natural language testing, check how much test authoring still requires technical input before committing.

Functionize targets enterprise teams with large legacy test suites, particularly those running data-driven tests across web applications. Its AI layer handles test generation and maintenance at scale.

The tradeoff is complexity. Functionize is built for large QA organizations managing thousands of tests, not for small teams who want to start testing a new mobile app this afternoon. The Functionize alternative comparison breaks down where it fits and where it does not.

Mabl combines test creation, execution, and analytics in a single platform for web apps. Its AI catches regressions across visual, functional, and performance dimensions. It integrates well with CI/CD pipelines and is popular with SaaS teams. For teams shipping iOS or Android alongside a web product, a platform like Autosana can manage both from a single interface.

There are four things worth evaluating before you sign a contract.

Test authoring. Can a non-engineer write a test without reading documentation first? If the answer requires a workshop, the tool is not actually simpler than Squish.

Platform coverage. If you test iOS, Android, and web, confirm all three are first-class citizens. Not checkboxes. Not "supported via Appium integration." First-class.

Self-healing specifics. Ask for the self-healing success rate on locator changes. Vague claims about "AI-powered healing" are common. Concrete numbers are rare. Push for them.

CI/CD integration depth. Running tests manually is not a workflow. Look for GitHub Actions support at minimum, with clear documentation on how test results surface in pull requests.

Autosana covers all four directly. Agentic AI for Mobile App Testing explains what the agentic execution model looks like under the hood if you want the technical breakdown before evaluating any platform.