At their simplest, both QA Wolf and Mabl improve the QA process with automated testing and help teams move away from slow, error-prone manual checks. But that’s about where the similarities end.
QA Wolf is a full-service testing solution that scales with your growing app—whether you're adding new features, adjusting workflows, or expanding coverage, it adjusts seamlessly to keep up. It’s built on the open-source Playwright framework to make sure your team isn’t locked into a single vendor. We offer a zero-flake guarantee and only charge our customers per test under management to deliver 80% automated end-to-end test coverage in weeks — not years.
Mabl is a self-service testing tool where licensed users—whether developers or testers—are responsible for building and maintaining their own test suite. While its point-and-click platform simplifies the tech stack by using a tightly integrated proprietary framework and runner, the tool comes with a significant lock-in risk, limiting flexibility compared to other DIY solutions.
A solution like Mabl is for simpler apps and websites where the majority of tasks are repetitive and don’t need to integrate with third-party services, like “adding items to cart” on Shopify. However, it isn’t enough for testing most custom-built software.
On the other hand, QA Wolf is for more sophisticated websites that involve more complex workflows — from integrations with solutions like Plaid to validating generative AI output is correct to testing localization.
Mabl is ideal for websites powered by CMS-style platforms like Shopify, Magento, or Wordpress where the software is not the product or business. The workflows for these kinds of sites rarely use complex technologies like Canvas API, legacy tech like iFrames, or have multi-user interactions.
QA Wolf, on the other hand, was designed for product- and engineering-driven organizations. The product is the business, it’s custom-built, has a roadmap and 10+ developers releasing code at least twice a month. When the pace of development makes it difficult or impossible to maintain a functioning test suite, that’s when QA Wolf makes sense.
The rest of this guide explains why different teams find more or less value with each solution:
Testing capabilities refers to how well a solution can automate, execute, and maintain tests across all the different product workflows and user journeys, whether they’re simple or complex.
Mabl’s testing capabilities perform well for simple, linear workflows like "Add to Cart" functions, where user actions are predictable and easier to automate. Its low-code approach makes it simple to set up and manage tests with a few clicks, using pre-built actions like "Click" and "Input." This makes Mabl ideal for teams with fewer integrations and less frequent updates.
On the other hand, QA Wolf’s custom-coded tests are built for teams with more complex, fast-changing applications. This is because it’s custom-coded in JavaScript using Microsoft Playwright. It enables our QA experts to set up and manage complex workflows, manage intricate integrations, and account for evolving application logic.
For teams building or maintaining dynamic applications with multiple dependencies and frequent releases, QA Wolf adapts to complex workflows and custom scenarios, making sure even the most nuanced user journeys are thoroughly tested. This keeps the test suite healthy and ready for fast-paced changes.
For example, let’s say you’re testing a multi-step checkout process that involves adaptive pricing and discount code validation. If the pricing logic changes based on user location or cart contents, a low-code tool may not allow you to customize the test to account for these variables.
Without the ability to modify the code, you’d be left with coverage gaps — which opens the door to a slew of other challenges like potential bugs making it into production.
A low-code tool like Mabl leaves gaps in your test coverage because it can’t automate many critical workflows. With gaps in your automated test coverage, you’ll inevitably deal with…
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QA cycle time measures the speed and effectiveness of your quality assurance process. Dev teams need to consider QA cycle times when choosing a testing tool because faster, more efficient cycles allow for quicker releases with minimal downtime, keeping the development processes on track.
In other words, QA cycle time is the total time it takes for a developer or QA team to:
The QA cycle ends once every test in your suite passes or when all issues have been appropriately documented and flakes have been corrected.
Mabl works for teams that release less than once a month because it caters to slower, more predictable QA cycles. Its low-code platform simplifies test management with minimal upkeep, which can work for teams that don’t need to make frequent code changes or updates. Mabl’s easy test creation process allows teams with simpler products to ensure testing without needing constant intervention, making it an option for teams on a less aggressive release schedule.
Alternatively, a solution like QA Wolf is ideal for teams that release daily or are moving toward continuous deployment because it’s built to handle the rapid pace of frequent releases. Its custom-coded tests are flexible enough to maintain a healthy test suite even as features and updates are constantly added. It's able to catch and address failures quickly, minimizing disruptions to the development cycle and allowing teams to push updates confidently with quicker cycle times that don’t sacrifice testing quality.
Efficient QA cycle times are a must for a few reasons:
The tools and best practices you use impact these cycle times, which in turn determine the success of your software deployment process.
Both test run limits and restrictions on parallel executions directly impact testing frequency, project timelines, and budget management. QA Wolf doesn’t burden you with any of these limits. However, in Mabl’s case, one of three things happen:
Tool-only solutions like Mabl are positioned as quick, easy ways to build and run automated test suites. While Mabl leans on “self-healing AI” to address common testing issues, the reality is that the bulk of QA involves investigating more complex failures and maintaining tests.
Mabl’s “self-healing AI” fails to fully eliminate the need for manual intervention because “self-healing” only addresses surface-level issues like minor UI changes. It doesn’t resolve deeper, more complex failures, like those caused by broken integrations or database issues.
Consider that about 9-16% of tests fail and that investigating and repairing a test takes an hour on average. In fact, it can take anywhere from 10 minutes to a week because a lot of it depends on the complexity of the test and the severity of the failure.
For example, a simple UI test failure may take about 10 minutes to resolve. But debugging a failure in an integrated system test that involves multiple APIs or databases could stretch out to several days. So if we average one hour per test for maintenance, a suite of 250 tests will need 25 hours of maintenance work every time it runs.
Teams that practice continuous deployment, or want to, will need anywhere from one to three QA engineers for every 10 developers just to give timely feedback on PRs as they merge and maintain a healthy test suite. This means tool-only solutions like Mabl will almost always equal more out of pocket costs teams often fail to plan for.
In that case, what happens when teams under-invest in test maintenance?
Suite uptime or suite health, refers to the operational status of the entire test suite. Specifically, the proportion of tests that are functioning correctly and are ready to execute at any given moment. In a healthy test suite, all or most tests are up-to-date and can be run without issues.
Factors that influence the health of a test suite, include:
If you choose a limited testing solution without expert human oversight, your test suite can suffer from poor maintenance and decreased uptime. It’s why expert human testers are vital to making sure the suite is running smoothly, catching edge cases, and addressing issues before they pile up and disrupt your CI/CD pipelines. Otherwise, you’ll set yourself up to deal with:
Unlike Mabl, QA Wolf provides full-service suite maintenance with human expertise in the loop ready to take action whenever something breaks. With its multi-agent system, QA Wolf maintains a healthy test suite that frees up your dev teams to focus on what matters: shipping quality code.
Guiding GUIDEcx to 80% coverage saved $642K/yr. Watch the case study ⟶
Each solution's pricing model — the way they charge for its product or services — also impacts your testing outcomes.
Mabl charges based on user seats and test runs. This means your costs will increase the more tests you run, which may limit how frequently you can test if you’re trying to control expenses. It’s why this model tends to work for smaller teams that only need to run a handful of tests per month.
QA Wolf, on the other hand, charges for tests under management. This flat-fee model includes unlimited test runs and maintenance, so you’re not penalized for running more tests. By separating costs from the number of runs, teams are incentivized to test as often as necessary—whether it's for small bug fixes or full regression suites—without worrying about a long list of additional expenses piling up.
The key difference here is that Mabl’s pricing model can create a trade-off between cost and coverage, whereas QA Wolf’s model encourages more thorough testing. With Mabl, you’ll need to incur the additional cost of hiring full-time or contract staff to set up and manage the tool — QA Wolf comes with QA experts already included.
But how? QA Wolf’s pricing is structured in a way that encourages frequent and thorough testing, since teams pay based on the number of tests managed rather than per test run. This makes sure that the cost directly reflects the effort required to keep tests up-to-date and relevant, rather than penalizing teams for needing to run more tests as their product grows and evolves.
Choosing a pricing model that supports the outcome you’re trying to achieve will make the difference between reliable QA testing and inconsistent testing and coverage. If you opt for a usage-based pricing model like Mabl’s, teams will tend to face a number of challenges:
Tuning up Shopmonkey’s test suite saved them $600K+/yr. Watch the case study ⟶
Mabl charges by the number of test runs and seats you use, charging premiums once you reach test run and parallelization limits. By including everything — literally everything — test creation, maintenance, parallel execution, bug reporting, AI-fueled suite management, and more — in one transparent charge per test under management, QA Wolf effectively aligns their pricing with their clients' objectives. Namely, running a lot of tests quickly and frequently.
QA Wolf is a hybrid platform & service that helps software teams ship better software faster by taking QA completely off their plate.
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