# What are the best AI Software Testing Tools for QA teams testing across devices?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">I'm researching AI Software Testing Tools specifically for QA teams that need coverage across multiple devices and browsers, not just a single environment. Within <a class="a a--md" elv="true" href="https://www.g2.com/categories/ai-software-testing-tools">AI Software Testing Tools</a>, <strong>Perfecto</strong>, <strong>Katalon</strong>, and <strong>ACCELQ</strong> are the names that come up most for cross-device testing.</p><ol>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/perfecto/reviews"><strong>Perfecto</strong></a>: built around a cloud lab of real devices and browsers, making it a common choice specifically for teams that need to validate across many device and OS combinations.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/katalon/reviews"><strong>Katalon</strong></a>: supports web, mobile, and API testing from one platform, useful for QA teams consolidating cross-device coverage into a single tool.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/accelq/reviews"><strong>ACCELQ</strong></a>: combines AI driven test creation with broad device and browser support, appealing to teams wanting less manual scripting per platform.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/tricentis-tosca/reviews"><strong>Tricentis Tosca</strong></a>: enterprise grade cross-platform testing, a fit for larger QA organizations with complex device matrices.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/testrigor/reviews"><strong>testRigor</strong></a>: plain English test authoring that reduces the scripting burden when extending coverage across new devices.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/testsigma/reviews"><strong>Testsigma</strong></a>: cloud based test execution across web, mobile, and API, aimed at teams wanting to scale device coverage without managing their own device lab.</li>
</ol><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">For QA teams testing across a genuinely wide device matrix, how much of that coverage came from the tool's own device lab versus your team maintaining physical devices anyway?</p>

##### Post Metadata
- Posted at: 14 days ago
- Net upvotes: 1


## Comments
### Comment 1

AI Software Testing Tools reviews on G2 for cross-device coverage describe the device lab as the actual product decision, with AI test creation as a secondary factor layered on top. Perfecto&#39;s cloud lab of real devices is answering the post&#39;s core question most directly, since coverage across many device and OS combinations depends on actually having those devices available somewhere, which is a fundamentally different claim than Katalon&#39;s consolidation of web, mobile, and API testing into one interface without necessarily changing how many physical devices sit behind it.
ACCELQ, combining AI-driven test creation with broad device support, is trying to reduce the scripting burden and the device question at the same time, while testRigor&#39;s plain-English authoring is really solving the scripting burden alone and depends on whatever device access sits underneath it separately. Testsigma and Tricentis Tosca both lean on cloud execution rather than an owned device lab point at the same underlying tradeoff the post&#39;s own closing question raises, since a team still maintaining physical devices anyway is really paying for that coverage twice, once through the tool&#39;s subscription and once through hardware upkeep.


##### Comment Metadata
- Posted at: 12 days ago
- Author title: Marketing





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