Platform leverages 13 years of crowdsourced testing data to deliver intelligent automation and set new industry standards.
Large language models are under threat from a tactic called LLM grooming, where bad actors flood public data sources with biased or misleading content to influence AI training behind the scenes.
A quick internet search provides examples of marketing, brand, and UX issues when localization testing is treated as an afterthought.
Many software applications struggle to handle high user loads, leading to slow performance, crashes, and a poor user experience.
Smartphone users worldwide are expected to reach 7.7 billion by 2028. With such an enormous and growing user base, non-functional requirements like performance, security, reliability, and usability can make or break businesses.
Test case prioritization helps you rank test cases based on importance. It ensures you test the most critical features first. This approach saves time, improves software quality, and helps you catch high-risk defects early.
QA Automation empowers teams to deliver higher-quality software faster by reducing manual effort, minimizing errors, and accelerating the entire testing process.
E-commerce has transformed the way we shop and conduct business. With global retail online sales expected to reach $8.1 trillion by 2026 and digital buyers accounting for 33.3% of the…
When a team working on a SaaS product hands over a new testing build containing bug fixes and new features to the quality assurance (QA) team, the QA team must assess its stability quickly before committing to extensive regression testing.
AI systems are only as reliable as the testing behind them. Red teaming brings a fresh, proactive approach to testing by helping you spot risks early.