Orchestrating an Effective Operating Model for RPA

whitePaper | April 1, 2021

White paper about sustanable drain system.

whitePaper | June 6, 2022

With ongoing advancements in converging technologies, energy generation and usage and other business models, the construction industry has an opportunity to transform the way it functions. Challenging conventional norms could be the key to solving many of the bottlenecks the industry has faced for years. At the same time, there are inherent risks associated with transformative shifts. The time is right to take advantage of the potential financial, environmental and societal rewards.

whitePaper | November 11, 2022

Concrete is an outstanding building material. It is widely available, economical, hard and durable like stone, and easy to work with – all attractive properties for the construction industry. However, concrete also has its disadvantages. The cement contained in concrete consumes a lot of energy during its production process and emits large amounts of CO2. This, combined with the enormous demand for concrete and the simultaneous low recycling rate, makes concrete less-than-friendly for the environment.

whitePaper | August 18, 2022

In 2022 alone, we’ve seen major reforms to building safety legislation. Five years after the Grenfell fire, we are starting to see regulation come into force to ensure more is done to protect residents and tighten up standards across our built environment.

whitePaper | December 30, 2021

Many argue tha the major driver to better manage this complexity is the engineering paradigm of Industry 4.0. To succeed in this new age, engineers must look for solutions to adapt engineering to a more dynamic world. This white paper introduces a solution to address the engineering challenges of the modern-day industrial revolution.

whitePaper | May 12, 2022

Machine learning is powering most of the recent advancements in artificial intelligence including autonomous systems, computer vision, natural language processing, predictive analytics, and a wide range of applications among the seven patterns of AI. However, in order for these systems to be able to create accurate generalizations, these machine learning systems must be trained on data. The more advanced forms of machine learning, especially deep learning neural networks, require significant amounts of data to be able to create models with acceptable levels of accuracy.