Mabl: AI-Powered Test Automation for Faster, Bug-Free Apps

In an era defined by rapid digital innovation, the integrity, usability, and security of software products have become paramount for businesses across all sectors. The stakes are undeniably high: 2024 alone saw a staggering 211% increase in data breaches compared to the previous year, impacting industries from healthcare to manufacturing, retail, and utilities. Concurrently, customer experience has emerged as a central pillar, particularly for Software-as-a-Service (SaaS) solutions. Proactive detection and resolution of bugs, coupled with improvements in navigation logic and application performance, are not just about retaining existing customers; studies suggest these efforts can double a company’s revenue.

This critical need for quality is where quality assurance (QA), encompassing both manual and automated testing, plays a transformative role. An expert QA team is instrumental in accelerating software engineering cycles, validating application functionality, and preventing the release of flawed software into production. Beyond direct testing, they generate comprehensive documentation that ensures internal teams are aligned, facilitates compliance with regulatory standards, and aids in budget management. Historically, enterprises undergoing digital transformation faced a difficult choice: whether to invest heavily in automated testing or rely on labor-intensive manual QA. Even when automation was deemed essential, many companies defaulted to manual processes due to a significant shortage of skilled Software Development Engineers in Test (SDETs) and their higher compensation rates.

To bridge this burgeoning gap between the demand for test automation and the scarcity of specialized SDETs, technology companies turned to artificial intelligence. This convergence led to the creation of Mabl, an AI-based test automation solution launched in 2017 by former Google engineers Dan Belcher and Izzy Azeri. Their vision was to develop an intelligent, low-code test automation platform that would integrate seamlessly into modern DevOps workflows, enabling organizations to accelerate software delivery without compromising quality. By embedding Mabl into development pipelines, in-house or outsourced IT teams can significantly enhance software quality while achieving substantial reductions in QA costs.

Unlike traditional testing frameworks such as Selenium, Cypress, and Appium, which demand extensive scripting and ongoing maintenance, Mabl leverages AI-driven automation to make testing faster, smarter, and considerably easier to manage. A key advantage lies in its ability to consolidate various testing types—including UI, API, performance, and accessibility—into a single, unified platform, thereby streamlining test management and execution. Whether testing enterprise SaaS platforms, e-commerce websites, customer-facing portals, or internal business applications, Mabl enables teams to identify and resolve issues rapidly, often without requiring deep technical expertise.

Mabl’s capabilities are multifaceted, designed to remove complexity from test automation. Its low-code test authoring feature allows QA engineers, business analysts, and even product managers to create automated tests by simply interacting with an application as an end-user would. Mabl automatically records these interactions and generates the necessary test scripts, eliminating the need for complex coding. For instance, a QA analyst can swiftly set up automated tests for customer logins, product searches, checkout flows, and payment processing for an online store, all without writing a single line of code.

One of the most challenging aspects of test automation is maintaining scripts as applications evolve. UI redesigns, new features, and layout changes frequently cause traditional tests to fail. Mabl addresses this with its AI-powered auto-healing feature, which detects and automatically adjusts tests to even minor application changes, negating the need for manual script updates. This functionality ensures that tests remain robust and relevant, freeing development teams to focus on other critical projects.

Furthermore, Mabl supports data-driven testing, a crucial capability for enterprise applications that rely on dynamic data inputs, such as different user roles or pricing models. Instead of time-consuming manual validation of numerous variations, QA teams can incorporate dynamic datasets into test cases and automate the execution of diverse user scenarios. This allows a logistics company, for example, to simulate countless tracking numbers, customer locations, and delivery statuses to ensure its shipment tracking platform operates flawlessly for all users before launch. Mabl also offers flexibility with both cloud-based and local testing options, catering to varying security and operational needs. While cloud testing provides instant results for distributed teams and streamlines DevOps integration, local testing is preferred for security-critical applications like mBanking and EHR systems, ensuring sensitive data remains on-premises.

Critically, Mabl includes advanced accessibility and performance testing. Customer experience, as previously noted, profoundly influences business success. Despite their importance for user satisfaction and regulatory compliance (particularly in healthcare and public services), software accessibility and performance are often overlooked in QA. Mabl’s built-in accessibility testing identifies issues related to screen readers, color contrast, and keyboard navigation, helping businesses comply with standards like WCAG without additional tools. Its out-of-the-box performance testing features can simulate peak loads, preventing costly downtime and poor user experiences, potentially saving companies millions in lost revenue. An energy company, for instance, could use Mabl to simulate thousands of users logging into a new customer portal simultaneously, validating system responsiveness under heavy load.

Mabl operates in a rapidly expanding global automation testing market, which is growing at an impressive 18.7% CAGR. While numerous low-code platforms such as Katalon, BrowserStack, Tricentis Tosca, Testim, and Leapwork have emerged as alternatives to traditional frameworks, Mabl distinguishes itself as a more intelligent, enterprise-ready solution balancing speed, scalability, and quality. Its AI-powered self-healing tests stand out by automatically adapting scripts to evolving UI elements, new features, or performance parameter changes, significantly reducing test upkeep and accelerating release cycles. Mabl also surpasses many low-code solutions by offering comprehensive test coverage encompassing performance, accessibility, API, and end-to-end UI testing within a single platform, eliminating the need for fragmented toolsets. Moreover, its seamless integration with CI/CD pipelines and DevOps platforms like Azure DevOps, Jenkins, GitHub Actions, Jira, and Slack ensures smooth communication and enables earlier bug detection in the development process, preventing costly late-stage fixes.

For business leaders, Mabl offers a clear competitive advantage: faster, more cost-effective testing that ensures software delivery on time, within budget, and without defects. Leading enterprises, including Barracuda, Charles Schwab, Chewy, DataRobot, JetBlue, NCR, and Stack Overflow, rely on Mabl to minimize costly defects, boost customer satisfaction, and accelerate product release cycles. The adoption of Mabl results in lower QA costs by automating repetitive, high-maintenance tasks, and a faster time to market by identifying and correcting bugs earlier in development. This leads to increased software reliability and customer trust, as studies reveal up to 88% of users are less likely to reuse an application after a poor experience. Furthermore, Mabl fosters seamless collaboration across in-house and distributed IT teams by integrating with popular DevOps tools, transforming quality assurance into a shared responsibility.

A compelling real-world example of Mabl’s impact comes from Live Aware Labs, a Seattle-based innovator in game audience analytics. Live Aware Labs developed a web-based collaboration tool for game testers and developers, enabling them to identify and fix bugs by streaming, recording, and analyzing gameplay videos. As their platform scaled, maintaining high performance, stability, and efficient QA processes became crucial, particularly for optimizing their Windows, macOS, Android, and iOS screen capture applications. The company faced challenges in optimizing legacy components, improving system stability, automating testing workflows, and minimizing regression testing efforts to accelerate product releases. Recognizing these hurdles, Mabl was recommended to automate regression testing, lower costs, and accelerate software delivery. By integrating Mabl’s low-code/no-code capabilities and AI-driven automation, Live Aware Labs achieved a significant decrease in pre-release testing time, increased test coverage faster, and reduced the entry barrier for QA automation. This resulted in a more than 50% reduction in time spent on regression testing for automated areas, critical performance issues resolved in less than a month, and improved streaming and recording quality, all while seamlessly integrating new platform features.