ROOF-TO-ROOM OPTIMIZATION SUITE FOR DATA CENTERS
LESS ENERGY | LESS RISK | MORE SUSTAINABLE | UP-AND-RUNNING IN WEEKS
WE'RE ON A MISSION
Reduce 1% of all global energy used for cooling data centers.
This single percentage could be the equivalent electrical consumption of 159 million Dutch households by 2030.
A daunting task, yes, but for data centers, it’s the only way to develop and contribute to sustainable digital infrastructure, bound to grow in the coming decades.
CHALLENGES
Despite a surge in demand for data center services, data centers face quite some challenges:
- Tight(ening) sustainability regulations and societal pressures
- Unprecedented energy price increases
- No or less energy availability
- The impact of climate change which puts existing cooling capabilities at risk
These challenges require an immediate response to benefit from the demand for cloud services.
Yet, most measures are often based on physical changes within the current infrastructure and – therefore – pretty hard to implement with a less favorable ROI.

Tight environmental & sustainability regulations

Unprecedented price increases of energy

Less or even no available power (grid shortcomings)

Climate impact of rising temperatures & less cooling resources
THE ROOF-TO-ROOM DATA CENTER OPTIMIZATION SUITE
Using existing sensor data, we’ve created a platform that brings the whole data center into an optimal state, transcending ánd improving optimizations within single pieces of equipment like CRAHs or chillers, taking into account – amongst others – the impact on overall maintenance as well.

Your data center into an optimal state
Less costs
ROI OF LESS THAN 1 YEAR
LESS RISK
DECREASE MAINTENANCE
MORE SUSTAINABLE
>25% LESS ENERGY
NON-INTRUSIVE
USE EXISTING SENSORS
About the optimization suite
Interactions between the mechanical and electrical equipment, along with their associated setpoints, control schemes, and feedback loops, make it extremely difficult to determine a data center’s ‘optimal state.’ Traditional engineering formulas often won’t work because they fail to capture such complex interdependencies, as previously acknowledged by The Uptime Institute. However, by applying advanced Machine Learning algorithms to all this sensor data (we currently process over 200 billion sensor readings), the platform detects patterns in a data center that were previously unknown due to this complexity.
Unraveling these patterns, our products offer clear and easy-to-use answers to many roles within the data center organization, like senior leadership, operational managers, site engineers, and data analysts. Depending on their needs, they can move through all these patterns themselves with advanced root-cause-analysis, receive timely and automated reports whenever the most critical patterns change, or are directly handed recommendations on the most optimal settings, reducing cooling energy and increasing operational reliability at the same time.

What customers say?

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