Chasing Unicorns and Clouds: Managing APIs and microservices

whitePaper | September 13, 2022

Companies are going digital, whether their IT infrastructure is ready or not. Digital transformation initiatives like migrating to cloud promise speed, adaptability and reduced costs to effectively respond to today’s real-time, customer-focused world.

whitePaper | August 10, 2020

Data is the most important asset businesses have. As the world has become increasingly digital, data has grown in volume and value. In fact, this most valuable resource of modern society doubles in volume every year and that growth rate is likely to accelerate even further. Of course, this creates a challenge: how to store data securely and how to be sure that every operation with data is secured? Today loss of data means loss of everything: business, identity, future, and even life in some cases.

whitePaper | January 11, 2023

Improving the trustworthiness of artificial intelligence (AI) systems is a shared priority for the private and public sectors, as indicated by prolific research and guidelines in recent years.

whitePaper | November 23, 2022

The modern distributed workplace—including enterprises with thousands of branches and remote workers—requires updated approaches to cloud, networking, and security infrastructure. Cloud migration has opened the door to a huge increase in sophisticated applications, requiring networks that can carry traffic to an increasingly remote workforce. In turn, this creates a unique set of new requirements for security, including special capabilities to handle unpredictable locations of users, applications, and traffic flows.

whitePaper | December 27, 2022

Welcome back to our white paper series about how to use AI and data throughout the new business and underwriting processes. In the first white paper we discussed the importance of product design and the benefits of using AI.

whitePaper | September 23, 2022

It’s been several years since organizations began adopting artificial intelligence (AI) to improve their business; few have come close to mastering its existing capabilities. A small number of organizations in our research aim to become AI-driven—a status we define as AI and machine learning underpinning almost everything the enterprise does—by 2025. However, this elite group—who we term “AI leaders”1—as well as the many others looking simply to embed AI more firmly in the enterprise foundations face formidable challenges to achieving their objectives.