THE NEED FOR EFFECTIVE INCIDENT RESPONSE

whitePaper | October 11, 2021

AI forms the bedrock to help organizations unlock business value from the deluge of unstructured information. Improving operational efficiency by extracting structured data from unstructured documents enables organizations with faster and contextrich decision-making to adapt and thrive in the new normal.

whitePaper | December 6, 2022

The impact of system downtimes is rapidly rising due to businesses’ increased dependency on data and technology. It can cause loss of opportunities, productivity loss, confidence erosion, SLA penalties, supply chain ripple effects, and most importantly, a damaged reputation.

whitePaper | October 18, 2022

The term Artificial Intelligence for IT Operations (AIOps) combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination.

whitePaper | April 16, 2020

Since its inception in 1983, Green Mechanical has grown from 1 to 3 offices, taking on larger, more complex projects. However, success came with its own unique challenges. With employees spread across multiple cities and states, Green Mechanical built custom workflows for various systems to ensure collaborators had access to the information they needed. That meant employees had to keep track of multiple remote logins to complete simple tasks like printing job cost reports. Additionally, some employees used digital processes, while others used pen-and-paper. As a result, teams were often working off outdated information.

whitePaper | July 28, 2022

Many businesses have recently evolved to support large remote or hybrid workforces. This initial transition was imagined to be temporary, relying on home networks to provide the connectivity needed for work. Now, two years later, companies are contemplating technology improvements to address a more permanent remote workforce.

whitePaper | November 24, 2022

High-profile examples of harm associated with algorithm failure and misuse have garnered significant public concern (e.g. manipulation of the democratic process, discriminatory practice in criminal justice sentencing, and bias against racial and gender categories in the labour market). The field of AI ethics refers to the literature and to the community of people interested in this space. One high-profile manifestation of this is the formation of specialist ethics councils and teams to deliberate on conundrums regarding the use, access and openness of platforms and technologies (such as social media and messaging apps, etc.). For instance, the banning of particular public figures as well as lay users for use of the services in a manner that is not acceptable has been a constant theme in the public debate.