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QoEtient, powered by GenAI, offers a transformative solution for quality testing, automating the testing process to enable QA teams to deliver faster and more efficiently while significantly reducing costs. The platform's True No-Code functionality allows video tests to be written in plain English, instantly generating powerful automated tests. These tests are designed to automatically adjust to changes in the app's interface, ensuring continuous testing and smooth releases without the need for manual scriptwriting.
By drastically reducing test setup time, QoEtient enables development cycles to accelerate, achieving up to 80-85% faster test setup. The time required for test case automation is cut down from 200 person-days to just 30, thereby expediting release cycles. Additionally, the platform lowers maintenance costs through effortless updates, allowing teams to focus on feature development rather than time-consuming scriptwriting. With QoEtient, businesses can maintain uncompromising quality and ensure a flawless user experience through precise and efficient automation.
Features

Adaptive testing
Automated testing adapts seamlessly as the video application evolves.

Accelerated failure analysis
Automatically generates clear, concise summaries of failed tests, pinpointing the root cause of the issue

Multi-screen Access
Automate testing of multiscreen functionalities like Chromecast

Smart alerting
Configurable alert management to notify of anomalies

Flexible Data Management
Aggregated data storage on cloud for data analysis and visualization

Rich Device Farm Support
STB, Roku, Mobile, Smart TV, Fire TV, Web browser and more
User Types
QA Teams
QA Teams
QoEtient offers a cutting-edge solution for QA teams, enabling automated test processes that effortlessly adapt to changes in the video application’s interface. Say goodbye to manual script updates and the risk of broken tests with every UI update. QoEtient’s True No-Code Testing feature eliminates the need for script maintenance, saving valuable time and resources. As your app evolves, QoEtient ensures that testing remains smooth and efficient, empowering your team to focus on strategic testing initiatives and accelerating development cycles.
Development Teams
Accelerate Test Cycles and Boost Product QualityDevelopment Teams
Accelerate Test Cycles and Boost Product QualityFor development teams, root causes with precision. It distinguishes genuine failures from those caused by script or environment issues, reducing analysis time from days to minutes. This empowers development teams to implement fixes faster, thereby enhancing product quality and improving customer satisfaction. With deeper insights available on the QoEtient dashboard, teams can triage more effectively and prevent future issues, streamlining the testing process and ensuring a reliable user experience.
Compliance Teams
Uncompromising Security and Privacy in TestingCompliance Teams
Uncompromising Security and Privacy in Testing
QoEtient ensures that video testing remains secure and compliant with privacy standards. The platform's tests are designed with security in mind, preventing vulnerabilities or unauthorized access to sensitive user data. Additionally, QoEtient adheres to strict security protocols, safeguarding both test data and intellectual property. Its test automation algorithms interact exclusively with the application's public interface, avoiding any interaction with private user data, ensuring that your testing process does not compromise user confidentiality. This combination of ease of use, robust security, and privacy features allows teams to conduct flawless video testing while maintaining user trust.
Technology
QoEtient 2.0 is an AI-powered, true no-code automated test executor designed to interpret and run natural language test cases directly on a compatible device under test. It begins by setting up a detailed understanding of the application's functionality, screens, and available actions. Once this initial app context is established, users can simply write test cases in plain, natural language—just as they would describe them in a manual testing scenario.
QoEtient 2.0 interprets the intent behind these test cases and executes them without requiring any coding, configuration, or pre-built block assembly. Beyond delivering standard test execution results such as logs, step outcomes, and pass/fail statuses, QoEtient 2.0 also provides AI-generated insights into test failures. These insights help identify the underlying reasons behind failed test cases, offering valuable context and accelerating troubleshooting.

Information Hub
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What is QoEtient 2.0?
QoEtient 2.0 is an AI-based, true no-code automated test executor that can read and understand test cases written in natural language. It can automate tests on compatible devices, provide regular test results, and offer AI-generated insights on test failures. QoEtient 2.0 is not a full test automation framework but a no-code executor library that can be integrated into existing test automation systems.
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How does QoEtient 2.0 differ from traditional script-based automation?
Unlike traditional script-based automation, which requires programming skills and constant maintenance, QoEtient 2.0 uses natural language test cases. This eliminates the need for coding knowledge and reduces maintenance efforts, as QoEtient 2.0 can adapt to changes in the application without manual intervention.
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What are the four stages of QoEtient 2.0's operation?
The four stages are: 1) Understanding the App under test, 2) Understanding the Test Case, 3) Executing the Test Case, and 4) Providing test outcomes. These stages involve describing the app, interpreting natural language test cases, executing tests, and delivering comprehensive results.
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How can QoEtient 2.0 be integrated into existing test automation systems?
QoEtient 2.0 can be integrated by connecting integration points, including instructing SE on how to view and control specific device types, connecting SE's test results to existing reporting systems, and using QoEtient 2.0's interfaces to start it with necessary information like test cases, app details, and device information.
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What are Device Control Adapters in QoEtient 2.0?
Device Control Adapters are implementations of interfaces defined within QoEtient 2.0 that allow it to interact with various devices and applications. These adapters enable QoEtient 2.0 to access, view, and control different device types without direct dependencies on third-party libraries.
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How does QoEtient 2.0 handle reporting?
QoEtient 2.0 generates events during test execution containing detailed information about the test's progress. Interested parties can subscribe to these events and access detailed report data. This approach allows QoEtient 2.0 to remain decoupled from specific reporting systems while enabling data consumption by various reporting mechanisms.
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How does QoEtient 2.0's licensing work?
Each QoEtient 2.0 license permits the creation of one QoEtient 2.0 instance, which can run one test case on one device at a time. Multiple licenses allow for parallel test execution across multiple devices. The licensing system is integrated within the QoEtient 2.0 library and controls instance initialization based on available licenses.
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Are there any cloud costs associated with using QoEtient 2.0?
Yes, QoEtient 2.0 integrates with generative AI APIs hosted in the AWS cloud, resulting in minimal charges for each execution. The exact costs depend on the complexity of the test case and whether instruction regeneration is required.
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Can QoEtient 2.0 detect issues beyond the primary objective of a test case?
Yes, QoEtient 2.0 has human-like abilities to note down anomalies or bugs while testing another test case, even if they are not the primary objective of that test.
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How does QoEtient 2.0 compare to no-code automation systems?
While no-code automation systems use pre-coded blocks that users assemble visually, QoEtient 2.0 is a true no-code solution. It eliminates the need for block assembly by directly interpreting natural language test cases, making it more efficient and resilient to changes in the application.
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How does QoEtient 2.0 understand the app under test?
During the initial onboarding stage, users provide QoEtient 2.0 with a description of the app in natural language, following a specified format. This description includes details about each screen, functionalities, unique identifiers, and navigation options. A typical app description contains about 500 lines of natural language information, representing the app's screens and functionalities.
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What kind of test outcomes does QoEtient 2.0 provide?
QoEtient 2.0 provides real-time feedback on test execution progress, reporting outcomes for each test step. It delivers a clear verdict (pass, fail, or could not test) for each test case. Additionally, QoEtient 2.0 offers a comprehensive summary of the execution, including noteworthy observations and potential issues that might require further investigation.
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How does QoEtient 2.0 adapt to changes in the application being tested?
QoEtient 2.0's true no-code approach allows it to adapt to changes in the application without manual intervention. By interpreting natural language test cases and cross-referencing them with the app description, QoEtient 2.0 can adjust its execution strategy automatically when the application evolves, reducing the need for test maintenance.
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Can QoEtient 2.0 work with different types of devices and platforms?
Yes, QoEtient 2.0 is designed to work with various device types and platforms. Using Device Control Adapters, QoEtient 2.0 can interact with different devices such as Android phones, iPhones, browsers, and set-top boxes. These adapters allow QoEtient 2.0 to view and control specific device types without being directly dependent on device-specific libraries.
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How does QoEtient 2.0 contribute to reducing the cost and effort associated with test maintenance?
QoEtient 2.0 significantly reduces test maintenance costs and efforts by eliminating the need for coding or assembling pre-coded blocks. Its ability to understand and execute natural language test cases, coupled with its adaptability to application changes, means that users spend less time updating and maintaining test cases. This results in a more efficient and cost-effective testing process.