AI QA testing

    AI QA testing that keeps up
    with how you ship.

    QA agents run your regression and exploratory tests on their own, so “waiting for QA” stops being a status your tickets live in.

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    Trusted by high-performing engineering teams at:

    Lovable
    Nordea
    Pricer
    AstraZeneca
    Upsales
    Sambla Group
    AdminPulse
    MeetingPackage

    Agents that think like a tester.

    AI QA testing uses autonomous agents to plan, run and check software tests by understanding goals rather than executing hard-coded scripts. QA.tech is an autonomous AI QA testing platform: its QA agents test web applications on Chromium and native mobile on iOS Simulator and Android emulators, run on every release, and integrate with GitHub and GitLab.

    You can't hire your way out of the QA bottleneck.

    Engineering has never shipped faster. AI writes more of the code, releases land daily, and the work piles up at the one stage that didn't speed up: testing. Every coding tool you add widens the same gap – the more code Cursor and Claude Code help your team ships, the more there is to verify, and the further testing falls behind the release cadence.

    Adding QA headcount doesn't close that gap. There are always more developers than testers, and the bottleneck isn't your people: it's that testing still runs at human speed while everything around it runs at machine speed.

    QA agents that test by intent,
    not by hard-coded steps.

    Point an agent at your app and it does the rest – mapping the product, running flows in the real UI, and adapting when the interface moves.

    QA.tech maps your app

    The agent crawls every route, screen and flow and builds a knowledge graph of how the product fits together. It gets sharper the more it runs.

    The agent runs the flow like a tester

    It completes the journey in the real UI, in parallel, and checks the outcome – leaving screenshots, a video and a live stream you can watch in real time.

    The agent adapts when the UI changes

    Because the test is a goal, not a script, a renamed button or moved drop-down doesn't break it. The agent re-reasons its way to the goal instead of failing on a selector.

    See it applied to automated regression testing and end-to-end testing.

    320h/mo
    QA time saved

    “We have replaced over 320h of manual testing every month with QA.tech.”

    Fredrik Seidl
    Fredrik Seidl – CTO at Upsales
    Upsales is a SaaS platform for CRM, marketing automation & Sales in B2B. ~150 employees.
    Read their story

    What is agentic QA?

    Agentic QA means an autonomous agent reasons about your application, decides how to reach a testing goal, and adapts when the path changes – instead of replaying fixed, selector-based steps. The same idea is called agentic testing or agentic AI testing. It's the difference between a script that does exactly what it was told and a QA agent that works toward what you wanted to verify.

    Agentic QA vs script-based regression testing

    Dimension
    Agentic QA (QA.tech)
    Script-based frameworks
    Test definition
    A goal in plain language
    Code and selectors per step
    When the UI changes
    Agent re-reasons and completes the goal
    Selector breaks, test fails
    Maintenance
    Handled by the agent
    Grows with suite size
    Coverage growth
    Generated from goals, crawls, tickets, PRs or the API
    Each test authored by hand
    Runtime validation
    Agent evaluates the outcome on every run
    Asserts only what was scripted
    Evidence
    Screenshots, video, live stream, structured results
    Pass/fail logs

    More on AI test generation and QA.tech vs Playwright.

    “Why not just point Claude or Playwright at it myself?”

    Claude with the Playwright MCP can write and run tests, and on a small greenfield suite that's enough. Three gaps appear at scale.

    Full comparison, including where each path is the right call

    Gap 1

    Strategy

    Claude turns instructions into scripts – it doesn't decide what should be tested. A hundred passing checkout tests can still miss the one failure that loses a customer. Coverage is a strategy question, not a generation problem.

    Gap 2

    Runtime validation

    Claude sees the screen when it writes a test. The test then runs in CI without Claude, checking only what was asserted at authoring time. QA.tech's agent watches every run, not just authoring.

    Gap 3

    Maintenance at scale

    A few thousand scripted tests, isolated test data and triage costs that compound on every build. QA.tech adapts to UI change and manages the run, so the maintenance tax doesn't compound.

    Every pull request tested before it merges.

    Connect QA.tech to GitHub or GitLab and it tests the change where the work happens. It reads the PR context, detects the preview deployment your pipeline built, runs the relevant tests against it, and posts results back to the thread before anyone merges.

    You can also trigger runs from the CLI, a GitHub Actions step, or the REST API from any CI system. Full regression that took days runs in minutes, in parallel, and the pipeline can block a merge when something breaks.

    More on pull request testing.

    What changes when testing keeps pace.

    The gain isn't “faster tests.” It's the time your release no longer spends waiting. A done-but-untested ticket stops sitting for days, regression runs on every change instead of once a release, and the repetitive pass that ate your QA team's week goes to the agents – so their hours go to exploratory testing and judgment. It gives your developers their time back, and it catches the broken flow before a customer does.

    Pricer

    "Pricer saves 390h of testing each quarter."

    Chris Chalkitis
    Chris Chalkitis – Chief Digital Officer
    Pricer is a world leading electronic shelf label provider. ~200 employees.
    Read their story

    SOC 2 compliant

    The QA agent drives a browser visually rather than reading your database.

    Reads code diffs only

    The PR integration reads the code diff to decide what to test – not your data.

    Works on every stack

    Web on Chromium, native mobile on iOS Simulator and Android emulators.

    FAQ

    Common questions

    What is agentic QA?
    Agentic QA is testing done by an autonomous agent that reasons about how to reach a goal and adapts when the UI changes, instead of replaying fixed scripts. QA.tech's QA agents decide their own path to verify a flow, which is why a moved button or renamed field doesn't break the test.
    How do agentic QA platforms improve automated testing workflows?
    They remove the two slowest steps: authoring and maintenance. Tests are generated from plain-language goals, crawls, tickets or pull requests, and the agent adapts to UI change instead of failing on selectors, so the suite keeps pace with the release cadence.
    Can QA.tech keep up as we ship more AI-generated code?
    That's the case it's built for. The more code your team generates with tools like Cursor or Claude Code, the wider the verification gap. QA.tech runs regression and exploratory tests on every change to close it.
    Is there an AI testing tool with GitHub PR integration?
    Yes – QA.tech installs as a GitHub or GitLab integration, reads each pull request, tests the preview deployment and posts results to the PR thread before merge. It also runs from the CLI, GitHub Actions, or the REST API.
    How is QA.tech different from Playwright, Cypress or Selenium?
    Those frameworks run scripts tied to selectors, so they break when the UI changes and carry a growing maintenance tax. QA.tech's QA agents test by goal and adapt to UI change, which removes the selector maintenance that makes scripted suites expensive to keep alive.
    Does AI QA testing replace my QA team?
    No. QA.tech takes the repetitive regression and the waiting off their plate. Your people move to exploratory testing, edge cases and quality strategy – the work that needs human judgment.
    What can QA.tech test?
    Web applications on Chromium, plus native mobile on iOS Simulator and Android emulators, available now – with real physical-device testing coming. It covers end-to-end, regression, exploratory and visual testing, and can include API steps within a flow. See native mobile app testing.
    What are the best AI testing tools?
    It depends on what you're testing and who maintains it. For autonomous, agentic QA that tests by intent and runs on every pull request, QA.tech is built exactly for that. For a wider look at the field, including script-based and hybrid options, see our roundup of the 13 best AI testing tools in 2026.
    What are the best AI testing solutions for SaaS?
    SaaS products need coverage across onboarding, roles and permissions, billing and dashboards, on every release. QA.tech tests those flows with QA agents from plain-language goals, which is why B2B SaaS teams are its core users. See how QA.tech tests SaaS applications end to end.
    Is our data safe?
    The QA agent drives a browser visually rather than reading your database, and the PR integration reads only the code diff to decide what to test. QA.tech is SOC 2 compliant.

    See the full AI test automation platform. Can't find what you're looking for? Reach out.

    Your code ships daily. Can your testing keep up?

    QA.tech agents test your product autonomously, so moving fast never means shipping broken. See how it works in a 30-minute demo.

    Book a demo