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Description

BlinqIO's AI test engineer operates much like a human test automation engineer, taking input in the form of test scenarios or descriptions, determining the necessary actions to execute them on the application or website being evaluated, and generating test automation code that integrates seamlessly into your CICD system. Whenever there are changes to the application's UI or workflow, the AI test engineer promptly updates the code to reflect these modifications. With its limitless operational capacity available around the clock, achieving high-quality software releases with no risk becomes entirely feasible. It not only autonomously generates automated tests and scripts but also runs these tests, troubleshoots issues, and documents any bugs by creating tickets in the task management system for the R&D team to address. Furthermore, it continuously updates and maintains the test automation scripts in response to any failures caused by UI alterations, executing these tasks by interacting directly with the application under test. This innovative approach enhances efficiency and reliability in the testing process, allowing teams to focus on other critical aspects of development.

Description

Conventional software testing relies on the assumption that systems behave in predictable ways. In contrast, AI systems often exhibit unpredictability, uncertainty, and a lack of reliability, which introduces significant risks for products utilizing AI technology. To address these challenges, we are creating a forward-thinking platform dedicated to the testing and evaluation of AI, aiming to enhance safety, robustness, and dependability. It's essential to have confidence in your AI solutions before deployment and to maintain that trust continuously over time. Our team is rapidly refining the most comprehensive enterprise AI testing platform available, and we eagerly welcome your insights. By signing up, you can gain early access to our prototypes and influence the trajectory of our product development. We are a dedicated team committed to tackling the complexities of AI testing on an enterprise scale, drawing motivation from our valuable customers, partners, advisors, and investors. As the capabilities of AI expand within various business tasks, the associated risks to these enterprises and their clientele also increase. With new reports emerging daily highlighting issues like AI bias, instability, and errors, the need for robust testing solutions has never been more pressing. Addressing these challenges is not just a goal; it is a necessity for the future of responsible AI deployment.