California-based Applitools has rolled out a new feature that enhances its testing platforms with auto-correcting LLM capabilities, which is seen as fairly new within the industry.
The American-Israeli company, which is a provider of AI-based automated visual testing and monitoring solutions, and serves dozens of banks and financial services players in North America, said that the new feature is part of a range of expansions to its fairly popular Intelligent testing Platform.
The firm claims the new tool will help its platform to stand out from its rivals because it “enables QA teams, manual testers, product owners and designers to achieve efficiency and reliability in the testing processes with the most flexible authoring experience ranging from fully autonomous to AI-assisted to no-code recording.”
Moreover, “supporting teams can expand their existing code-based tests and leverage AI to quickly create new tests to boost test coverage,” Applitools shared in an email.
In essence, the feature introduces AI-assisted interactive custom flow authoring.
“This allows users to debug tests in real-time with an interactive browser, combining writing steps in plain English and recording them interactively,” the firm explained.
“This approach speeds up authoring and enhances tests with an auto-correcting LLM, making the process more efficient and reliable.”
Codeless testing
The new capabilities come a few months after Applitools attracted attention within the QA space with the launch of a new platform that combines code-based testing with codeless autonomous testing capabilities.
Applitools, which was founded in 2013, claimed the new tool is “the first fully autonomous test automation solution” that automatically generates tests on websites and multi-page web applications and uses natural language processing to allow developers, test engineers and business users to author automated tests using plain English.
Berry, since November of last year the CEO of Applitools, called the new tester “a game-changer”.
He stressed that the platform “empowers tech-savvy individuals and non-developers to leverage autonomous testing to ensure flawless digital experiences.”
Berry explained that “by harnessing visual AI and generative AI, we continue to advance UI test automation to streamline testing processes and expedite the delivery of flawless digital experiences.”
Berry added that “by fostering cross-team collaboration and putting app and digital asset quality control in all hands, bugs are prevented from reaching production so customers can save resources and invest in innovation and mission-critical endeavours.”
Crowded sector
The new Applitools solution is the latest addition in an increasingly competitive and crowded space as firms are racing to develop and deliver new digital products and testing features to the financial services sector, primarily since the demand for such solutions is surging.
According to a recent report by TCGen, enterprises that reduce their time to market accrue greater revenue over time.
Applitools’ COO Moshe Milman, who co-founded the company, told QA Financial recently that “as we look ahead, the role of test automation and AI in financial services will only continue to grow. It’s important for firms to stay proactive, not only in adopting these technologies but also in continuously refining their approach to ensure they remain at the forefront of innovation.”
He stressed that “embracing tools which leverage AI to enhance testing accuracy and efficiency while reducing costs, is a step towards maintaining competitive advantage in a rapidly evolving industry.”
As development time continues to speed up, pressure is mounting on development and testing teams to deliver digital experiences that render accurately all the time.
Increasingly, businesses are faced with the challenge to validate the functionality and appearance of their digital assets across multiple screens, browsers and devices, with UI/UX updates required multiple times a week or, in some cases, every day.
As a result, traditional testing tools struggle to match the pace of development, resulting in trade-offs between test coverage, velocity and quality.
This often leads to issues such as bugs in production, reduced release confidence, increased costs, slow feedback loops, and delayed timelines, prompting businesses to establish large and costly QA organizations, causing silos and inefficiencies.
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