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Customers won’t churn because of ugly UI. They’ll churn because your software can’t get them paid. MedTech products are now expected to handle not just clinical, but also financial workflows. Poor revenue cycle functionality leads to billing errors, compliance risks, and poor customer satisfaction.

Cost optimization is again a priority for tech companies. Some engineers are uneasy about AI replacing them with codeless test automation (TA). But are these platforms as powerful as their marketing? What ROI can businesses expect in a real-world setting? What exactly do you need to maximize the return?

There has been considerable talk about AI software development. Will AI replace human engineers? Can startups make production-level software with AI? Beyond the hype and fear-mongering, there’s very little empirical evidence of its use on commercial projects.

Codeless test automation has surged in popularity, promising to streamline the testing process without extensive coding knowledge. However, despite the growing interest, there remains a significant lack of detailed information about the implementation of no-code QA tools in real-world projects. This gap in knowledge leaves many organizations, including ours, cautious about their adoption.

Low-code development has recently exploded as one of the biggest trends in software development. It can skyrocket engineer productivity, cut time to market, and decrease project costs. Gartner predicts that by 2024, 65% of all software development will be low-code. Yet, the tech isn’t without its challenges.

Recruiters are almost always rated based on two measurements: time to hire and quality of recruitment. That’s why more and more recruiting specialists are asking themselves, “How can we make recruiting faster and more effective?”. Here at MindK, we believe that AI is part of the answer.

Automation is a significant step for each business. An epidemic digitalization of workflows, including human resource processes, brings both hope and fear, enthusiasm and caution. In this article, we are going to clear all the blind spots and determine what process is more or less suitable for HR automation and why.