FAQs

Absolutely. ContextAI supports BDD (Behavior Driven Development) syntax, allowing you to generate test scripts from Gherkin-style requirements. The platform parses Given-When-Then steps and converts them into executable tests. It helps align business and QA teams by keeping test design behavior-focused. The AI can also enhance BDD scripts with dynamic validations. This is ideal for Agile and DevOps practices.

Yes, ContextAI encourages modular and reusable test design. Common test steps can be created as reusable components or subflows. These modules can then be used across multiple test cases, saving time and ensuring consistency. Updates to shared steps automatically reflect across all linked tests. This improves maintainability and reduces duplication.

Yes, tests can be executed manually within the ContextAI platform without relying on a scheduler. This is useful for exploratory testing, ad hoc validations, or debugging. Manual runs provide the same insights, logs, and visual results as scheduled runs. Testers can choose specific scripts or suites to run instantly. It adds flexibility to the test execution workflow.

Yes, ContextAI includes features to support structured release management workflows. It allows tagging tests to specific releases or builds. You can track test readiness, coverage, and results by release cycle. Integration with CI/CD tools ensures seamless promotion from testing to production. This aligns QA efforts with the overall software delivery pipeline.

ContextAI enables environment management by allowing users to define and configure different test environments (e.g., staging, QA, production). You can set environment-specific variables, data, and configurations. During execution, tests are run in the appropriate context automatically. This ensures accurate results and reduces environment-related issues. Centralized management simplifies governance across multiple teams.

Yes, ContextAI supports cross-browser testing. It allows you to validate web applications across all major browsers including Chrome, Firefox, Safari, and Edge. You can configure tests to run in parallel across browsers. The platform ensures visual and functional consistency in different browser environments. AI-driven validation ensures differences are accurately detected.

Yes, ContextAI provides robust mobile testing capabilities across Android and iOS devices. You can run tests on real devices, emulators, or device clouds. The platform supports functional, visual, and performance validations for mobile apps. Parallel execution is available to speed up test cycles. It ensures your app behaves reliably across diverse mobile environments.

Yes, ContextAI supports parallel test execution to accelerate test cycles. You can run multiple test cases or test suites simultaneously across different browsers, devices, or environments. This significantly reduces overall test duration and enhances efficiency. It's particularly useful for large regression runs or cross-platform testing. The platform automatically manages test distribution and resource allocation.

Absolutely. ContextAI comes with an inbuilt test scheduler that allows users to plan executions in advance. You can configure test runs based on specific times, frequencies, or events. Scheduled runs help in managing overnight testing or aligning with deployment pipelines. The system also supports recurring schedules for continuous testing. Notifications and reports are sent post-execution.

Parameterization in ContextAI allows you to run the same test with multiple sets of data. You can define datasets at the test or suite level using internal or external data sources. This supports data-driven testing and improves coverage. Parameter values can be reused across steps and environments. The platform also supports secure handling of sensitive test data.

Yes, ContextAI offers seamless integration with CI/CD tools like Jenkins, GitHub Actions, Azure DevOps, and GitLab. You can trigger test executions automatically as part of your deployment workflows. Results are returned in real-time and linked back to the build process. This ensures fast feedback for development teams. It supports both cloud and on-premise DevOps pipelines.

Yes, ContextAI provides a powerful execution scheduler. It enables users to plan test runs in advance, repeat them on a schedule, or trigger them via CI/CD. You can define environment, data set, and browser/device combinations for each run. It helps ensure testing continuity even without manual intervention. The scheduler dashboard provides visibility into upcoming and past executions.

Yes, ContextAI allows you to visualize real user journeys using interaction flows captured during test recording or execution. The visual representation helps understand the navigation and actions taken during a test. It’s useful for identifying deviations or optimizing user flows. This insight also aids in root cause analysis when issues are encountered. The journeys are mapped across devices and environments.

ContextAI captures detailed logs, screenshots, network traces, and console errors during each test run. When a test fails, these artifacts are analyzed and highlighted by the AI engine. The system correlates issues with application behavior and previous test data. This allows you to pinpoint where users may face issues. You also get user impact scoring to prioritize fixes.

Yes, the platform provides a visual dashboard that highlights automation coverage across features, user stories, platforms, and browsers. You can easily identify which areas are well-tested and which are not. Test heatmaps and coverage graphs provide actionable insights. This helps guide prioritization and resource allocation. It’s especially helpful during release readiness checks.

Yes, ContextAI offers comprehensive API testing capabilities. You can create, execute, and validate REST and SOAP APIs with support for authentication, headers, and payload assertions. The tool also enables chaining API calls and integrating them into UI workflows. Detailed logs and performance metrics are available. This allows unified testing across layers of your application.

Yes, ContextAI fully supports mobile testing across Android and iOS. You can test native, hybrid, and web apps on real devices or emulators. The platform supports gestures, sensors, and device-specific conditions. It also allows cross-device execution and visual validation. Mobile test scripts can be created through recording or AI-assisted design.

Yes, ContextAI supports automation of Salesforce, Oracle, SAP, and other packaged or low-code applications. It handles dynamic DOMs, shadow DOMs, and iframe-based UI structures that are common in enterprise apps. AI auto-healing ensures stability even when underlying selectors change. The platform is optimized to work with complex enterprise UIs. It simplifies testing for traditionally difficult platforms.

Yes, ContextAI provides native support for database testing. You can connect to SQL and NoSQL databases, execute queries, and validate data before, during, or after UI/API tests. The platform allows parameterized queries and supports verification of data consistency, integrity, and transactions. This ensures accurate end-to-end test coverage. Sensitive data can also be masked or secured during testing.

Yes, ContextAI includes accessibility testing capabilities through its AxeTOS engine. It checks compliance with ADA, WCAG, and Section 508 standards. The AI can detect accessibility violations in real time and offer remediation suggestions. The platform also supports runtime remediation of accessibility issues. This helps ensure inclusive user experiences for all users.

Yes, ContextAI offers AI-powered visual testing to detect layout shifts, broken elements, and rendering issues. It captures baseline screenshots and compares them against future runs using smart visual diff algorithms. The AI filters out false positives and highlights meaningful changes. This ensures pixel-perfect UI validation across devices and browsers. It’s ideal for applications with dynamic or visual-heavy interfaces.

Yes, ContextAI allows users to run performance tests alongside functional tests. You can measure load times, response delays, and system resource usage during test execution. The platform provides detailed performance metrics at step, page, and system levels. Integration with performance testing tools is also supported for deeper analysis. This helps in identifying bottlenecks and optimizing performance before release.

ContextAI supports exploratory testing through its Recorder and Session Tracking tools. Testers can freely interact with the application while their actions are captured for replay or automation. For persona-based testing, the platform allows the simulation of user behavior profiles and paths. These are useful in understanding real-world usage and edge cases. It blends structured and exploratory testing seamlessly.

ContextAI integrates with a wide array of third-party tools across CI/CD (Jenkins, GitLab, GitHub Actions), Test Management (Jira, TestRail), Communication (Slack, Teams), Bug Tracking (ServiceNow, Azure DevOps), and Device Labs (BrowserStack, Sauce Labs). API hooks are also available for custom integrations. These integrations streamline workflows and enhance productivity. You can centralize quality engineering across your entire DevOps stack.