Every AI or Machine Learning project is unique: diverse data sets with different variables, integrations in or with existing software or hardware and different expectations and goals to be pursued. The decision as to how a business case should be set up technically in practice is an important factor in its ultimate success. In this...
Arcadis and Trendskout partnership
A Global Leader redefining the boundaries of AI
A versatile AI platform that would be capable of connecting to a variety of data sources, generating new insights and suggesting improvements. This was on Arcadis’s wish list when their leadership team reached out to Trendskout. What started as a pilot program quickly grew into a successful partnership for continuous innovation. One of the first focus areas was the organization’s energy consultancy. We take a look behind the scenes at this global leader that is redefining the boundaries of the use of AI.
Finding the right AI for a global business
As an international design and consultancy firm for natural and built assets, Arcadis is a leading global player. With business units across a wide range of sectors, this multinational company employs over 27,000 people in 70 countries. Roughly 800 employees are spread across six Arcadis offices in Belgium. The company has a long tradition of innovation. As a result, it was looking for a way to embed AI in its consulting activities, for improved business decision-making.
Arcadis’s main priority was a partner with a comprehensive, scalable and open AI platform. The platform would need to be able to act as a catalyst for the knowledge and resources already present in the business. The main aim? A faster time-to-market through AI applications, for instant added value.
Key requirements for the platform:
- Easy connection to existing databases and integration into third-party programs,
- Algorithms and AI models tailored to every business case,
- Fast ramp-up of pilot projects,
- Ability to process input and feedback from human experts,
Upon analysis of the global AI platform market, Arcadis decided that the Trendskout platform would be able to provide the best fit-for-purpose technology. Its open approach and the potential for scaling up were amongst the deciding factors. After a few successful try-outs, Arcadis and Trendskout entered into a full partnership. The energy consulting department was one of the first business units that was set for a full transformation. It soon became clear that the Arcadis consultants and engineers and the Trendskout AutoML platform would be able to reinforce each other to generate new insight.
“The Arcadis consultants are able to uncover hidden ROI measures, thanks to Trendskout’s AI analysis.”
Open technical approach
We applied the basic principles of the Trendskout software – connect, analyse, automate– to the approach of the Arcadis energy experts. The aim was simple: to combine the human knowledge of the engineers with in-depth, data-driven insight based on the Trendskout AI – all in search of additional ROI. The Arcadis team wanted to get a new perspective on the impact of particular energy-saving measures for buildings, to support its energy consultants in their task.
The technical setup was straightforward. The Arcadis team simply connected the various data sources on its building portfolio through the Trendskout API. Based on these data, the algorithm was set to work, helping the Arcadis consultants to discover new patterns.
The new interaction between artificial and human intelligence soon brought about its first results. Large quantities of previously untapped data on buildings – surface area, destination, year of construction or previously implemented energy-saving measures, to name only a few – were received as parameters by Trendskout’s AutoML software. Next, the algorithms set to work to cluster the available data and detect anomalies.
After refinement by the Arcadis consultants and energy specialists during the AI training stage, Trendskout’s machine learning algorithms were able to generate new, predictive insights. The platform was able to provide a more accurate analysis into potential energy-saving measures for specific types of buildings, taking into account detailed contextual factors.