mabl

mabl is a cloud-native, AI-driven test automation platform designed to integrate quality engineering directly into the software development lifecycle. Unlike script-heavy frameworks such as Selenium or Cypress, mabl enables teams to create, execute, and maintain end-to-end tests through a low-code interface while leveraging machine learning to auto-heal tests when the application UI changes — reducing test maintenance time by up to 40% according to customer case studies.

Founded in 2017 by former HubSpot engineering leaders Izzy Azeri and Dan Belcher, mabl has grown to serve over 300 enterprise customers including Charles Schwab, jetBlue, and GoFundMe. The platform processes millions of test executions monthly and has raised over $76 million in venture funding as of 2024.

Core Capabilities

mabl supports browser testing (Chrome, Firefox, Edge, Safari), API testing, accessibility testing (WCAG compliance), and performance testing within a single unified platform. Tests are created via a Chrome extension recorder or a visual drag-and-drop editor, making it accessible to QA engineers without deep programming expertise. For teams that prefer code, mabl also supports custom JavaScript snippets within test flows.

The platform's auto-healing engine uses ML models trained on millions of test executions to detect UI changes — such as renamed selectors, moved elements, or layout shifts — and automatically update test steps without manual intervention. mabl reports that auto-healing resolves approximately 30% of potential test failures before they surface.

CI/CD and Integration Ecosystem

mabl integrates natively with over 40 tools across the DevOps pipeline, including Jenkins, GitHub Actions, GitLab CI, CircleCI, Azure DevOps, Jira, Slack, PagerDuty, and Datadog. Its CLI and REST API allow teams to trigger test plans from any pipeline, and deployment events can be linked to automatic regression runs.

Reporting and Insights

The platform provides detailed test analytics including execution history, flakiness detection, visual change comparisons via pixel-level screenshot diffing, DOM snapshots, HAR file captures, and performance metrics such as page load time and largest contentful paint (LCP). AI-powered root cause analysis highlights the most likely cause of test failures, reducing triage time.

Security and Compliance

mabl is SOC 2 Type II certified and supports SSO via SAML 2.0, SCIM user provisioning, role-based access control, and data residency options in the US and EU. The platform encrypts data at rest (AES-256) and in transit (TLS 1.2+).

As of early 2026, mabl continues to expand its AI capabilities with features like intelligent test generation from user stories and natural language test step suggestions, positioning itself as one of the more mature AI-native testing platforms available.