Appian surveyed 500 senior banking and asset management executives from around the world about the drivers, challenges, and opportunities on the path to automation maturity. We classified survey respondents as either automation leaders, laggards, or part of the mainstream.
Companies looking for digital transformation need to set up their teams for success. Modern development teams can release faster using an innovative suite of testing solutions. The integration with Xray and Functionize fits seamlessly into agile Jira workflows and incorporates AI/ML to speed up testing. The Xray-Functionize integration provides you with easy creation of automated tests, more visibility into testing results, and the capacity to increase team collaboration.
Last month, we unveiled Appian 21.3 with new product enhancements that help customers develop apps and automations even faster. And now, we’re excited to announce updates to Appian RPA that simplify the already-easy Appian low-code experience even more—including the reveal of the new Appian RPA task recorder that allows you to record browser automations right from your workflow designer.
A good browser, good apps, a good camera, and fast networking in your smartphone are just expected today. – Thorsten Heins This quote shows the dependency we have on browsers, the web, and mobile phones today. But how did we come so far? Technological development and robust testing have helped us reach where we are. When it is about multiple devices and browsers – the role of cross-browser testing can not be under-estimated.
The whole point of cross-browser testing is to deliver consistent user experiences across various browsers. When we build websites or web apps, some of their features aren’t compatible with some browsers; with cross-browser testing, we can ensure uniform experiences. While performing cross-browser testing, we generally check for the following: When we perform cross-browser compatibility testing, it’s easy to discover such bugs and fix them before our product goes into production.
With the explosion of the machine learning tooling space, the barrier to entry has never been lower for companies looking to invest in AI initiatives. But enterprise AI in production is still immature. How are companies getting to production and scaling up with machine learning in 2021? Implementing data science at scale used to be an endeavor reserved for the tech giants with their armies of developers and deep pockets.
