Exploring the Tools That Make Agile Parallel Development Possible

whitePaper | July 31, 2020

Microsoft 365 provides organizations with a range of efficient, new-style productivity and collaboration tools that are widely embraced across the world. However, Microsoft 365 comes with some shortcomings in certain key areas, such as security, auditing, archiving, backup and recovery, data protection, and more. Relying solely on the native capabilities in Microsoft 365 can lead to challenges, such as missed security threats and the inability to recover accidentally deleted data – all of which can be costly.

whitePaper | August 9, 2020

Even before the COVID-19 pandemic, the pace of change in the financial services industry was exhausting. The challenges just kept coming: from the 2008 financial crisis to a raft of fintech newcomers and established brands pivoting into the industry, a panoply of regulations and the looming threat of a recession — to name a few.

whitePaper | October 20, 2022

Artificial intelligence has already started to have an impact on urban settings at an unprecedented pace, with sophisticated solutions being deployed in the streets, at airports and in other city installations. In fact, cities are becoming experimental sites for new forms of artificial intelligence and automation technologies that are applied across a wide variety of sectors and places.

whitePaper | May 4, 2022

The pandemic has brought about significant economic disruption, thereby increasing the need for banks and financial institutions to be more agile. However, Covid-19 is not the only factor that drives automation and digitalization in the credit and lending process in credit institutions. Incumbent banks are increasingly facing pressure from neobanks, these having the strategic advantage of being “born digital”. In addition, customers demand fully digitalized processes with regard to the ease of use and fast turnaround times.

whitePaper | April 25, 2023

Artificial Intelligence (AI) is changing our world. In the future, AI will be essential to cybersecurity and application security testing. Organizations require AI to secure assets that power their business. As cyber-attacks become more sophisticated and widespread and leverage AI, organizations will need to rely on AI-powered security solutions to protect their systems and data.

whitePaper | January 5, 2020

Machine learning (ML) is an application of artificial intelligence (AI) that allows systems to automatically learn and improve from exposure to more data without being explicitly programmed. ML focuses on the development of computer programs that can access data and use it to learn for themselves.1 While AI represents the broader concept of machines being able to carry out tasks in an intelligent way, machine learning is a current application of AI based on the idea that we can give machines access to data, and they can use that data to learn for themselves.