How data centers improve their sustainability with AI – an interview with the Dutch Data Center Association

Editor’s note:
This interview was originally published by the Dutch Data Center Association and references Lucend by its former name, Coolgradient. It is republished here with permission and lightly edited for formatting. All content reflects the context and naming at the time of original publication.

How data centers improve their sustainability with AI – an interview with the Dutch Data Center Association

Artificial Intelligence (AI) is one of the most frequently used terms in the data center industry. However, this also brings the risk of losing sight of the bigger picture. That’s why Jasper de Vries, co-founder of Coolgradient (now Lucend), explains in this interview with the Dutch Data Center Association how AI can truly add value to data centers.

Everyone interacts with a data center every 18 seconds. It’s a quote from IDC’s Data Age 2025 that fascinates De Vries, because almost no one is aware of it. “A data center is very complex, but incredibly important for our society. At the same time, there is a lot of potential to optimize the data center with data and AI. That’s why René van Gompel (co-founder) and I started building the Coolgradient platform.”

The Coolgradient Platform

Today, the Coolgradient platform is used worldwide by various data centers. But how does the platform work?
“We use all data points from chillers, cooling towers, IACs, CRACs, CRAHs, UPSs, and PDUs within the data center. We then use this data to better understand how the data center behaves under different conditions and determine the most effective settings based on those insights. Machine learning helps us automatically generate and validate these insights. The goal is to reduce the data center’s power and water usage and increase its reliability and resilience.”

According to De Vries, one thing is essential to note: Coolgradient is not a dashboard company. “Insights alone are useless if no concrete action follows. You need to know what to do to improve your efficiency. That’s why our platform’s AI focuses on: 1) automatically detecting optimizations, and 2) automatically translating them into the right solutions for your specific data center. These are then presented as recommendations, and the platform quantifies their impact. This last step is necessary so people immediately know what the solution is.”

FruitPunch AI Challenge

To highlight how AI enables data centers to gain insights and act on them, Coolgradient partnered with FruitPunch AI, an online platform offering “AI for good” challenges.
De Vries explains: “We started talking with Sako Arts, CTO of FruitPunch AI, about collaborating on a challenge. The goal is to create broader awareness for sustainability within data centers. Additionally, we want to increase awareness within the market itself.”

He emphasizes that sustainability improvements do not require expensive CapEx:
“For example, a typical chiller can cost around €400,000 — and you might need ten of them on your roof. That’s an enormous investment, while you can already make significant progress using the sensor data you already have.”

The AI For Greener Data Centers challenge demonstrates how AI can be effectively deployed in data centers using various machine learning techniques — including reinforcement learning — to accelerate the implementation of an automated operating system.

This article was originally published by the Dutch Data Center Association and can be found here.