Process Automation increases efficiency, reduces costs, and minimizes errors, allowing you to focus on more important tasks. Some use cases for process automation include: Any multi-step business process can be automated, turning it into a valuable asset for any organization.

Today's consumers are more health-conscious than ever, leading many to turn to mobile apps to manage their health and well-being on the go. According to Insider Intelligence, over two-thirds of Americans have used a health-related app in the last year. As a result of this shift in behaviour, healthcare providers now have a unique opportunity to reach out to new audiences and form stronger relationships with their customers.

The pressure to deliver high-quality software faster than ever is a constant challenge in today's competitive environment. Traditional testing approaches that focus on late-stage defect detection often lead to costly rework and delays. To address this, Shift Left Testing has emerged as a proactive strategy that emphasizes integrating testing activities earlier in the Software Development Lifecycle (SDLC) as we discussed in our previous post about where testing currently was going in 2024.

With the world revolutionizing at a fast pace, digital wallets have become the new banking norm, allowing customers to do things on the go. Online transactions have already become an integral part of our lives, rather becoming an an essential aspect, particularly with the acceleration of digital transformation services. Of course, there are many options for making payments online, including digital wallets, bitcoin, online banks, and credit cards.

Digital transformation is accelerating rapidly, yet many businesses are still wondering how to proceed. For most, it will require a shift in thinking and operational activities. Succeeding in this transformation will require you to make critical choices surrounding more efficient workflows, data security, and profitability. One of the four pillars of digital transformation is IT uplift, which focuses on improving the IT infrastructure.

Software applications often perform well during short-term testing but encounter issues during continuous use.

When was the last time you used a chat service and noticed messages arriving out of order? It’s likely that you can’t think of one. Getting messages to arrive in the right order is more or less job number one of a chat service. Sounds simple. But scale this to millions of users across a global network and it becomes a complex distributed computing problem. Even at smaller scales, message ordering isn’t guaranteed once you go beyond a simple, direct connection between two users.

It’s November 2024 and I think it is safe to say, AI is officially everywhere. People are talking about it in cafés worldwide. So are your kids. Or your parents. Or grandparents. It may have been integral to your last car buying experience and has been used as a recommendation engine by your at-home/connected devices that hear you and want to improve your life by recommending products they think you need. It is pervasive and getting more so every day.

Enterprise organizations collect massive volumes of unstructured data, such as images, handwritten text, documents, and more. They also still capture much of this data through manual processes. The way to leverage this for business insight is to digitize that data. One of the biggest challenges with digitizing the output of these manual processes is transforming this unstructured data into something that can actually deliver actionable insights.

Today, cyber defenders face an unprecedented set of challenges as they work to secure and protect their organizations. In fact, according to the Identity Theft Resource Center (ITRC) Annual Data Breach Report, there were 2,365 cyber attacks in 2023 with more than 300 million victims, and a 72% increase in data breaches since 2021. The constant barrage of increasingly sophisticated cyberattacks has left many professionals feeling overwhelmed and burned out.