Bridge Data Centres: Sustainability at the Hyperscale Level

· Source: AI Magazine · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cloud Computing & IT Infrastructure, Emerging Technologies & Innovation · Depth: Intermediate, short

Summary

Bridge Data Centres (BDC), a Bain Capital portfolio company headquartered in Singapore, has expanded its data center capacity five to six times in the Asia-Pacific (APAC) region over the past three years. The company focuses exclusively on hyperscale clients, providing infrastructure for AI-driven computing. BDC has pioneered hyperscale campuses in Malaysia, including the first in Johor, and has implemented advanced cooling technologies like direct-to-chip liquid cooling and immersion cooling, achieving a Power Usage Effectiveness (PUE) below 1.2 and Water Usage Effectiveness (WUE) of 1.6. BDC aims for net-zero carbon emissions by 2040, with over 50% of energy at one Malaysian campus from solar power, and has developed a municipal wastewater recycling project. The company employs a vertically integrated delivery model and modular design to accelerate deployment, planning to more than double APAC capacity in 12-18 months and expand beyond the region.

Key takeaway

For CTOs evaluating data center partnerships in APAC, Bridge Data Centres' focus on hyperscale, vertical integration, and advanced cooling technologies like direct-to-chip and immersion cooling offers a compelling model for rapid, sustainable AI infrastructure deployment. You should assess their PUE below 1.2 and net-zero by 2040 targets against your own ESG and operational efficiency goals, especially given their proven ability to integrate renewable energy and water recycling in challenging climates.

Key insights

Hyperscale data centers are prioritizing sustainable, vertically integrated, and rapidly deployable infrastructure for AI workloads.

Principles

Method

BDC's method involves close collaboration with hyperscale clients on technology stacks and site selection, in-house teams for end-to-end delivery, and modularized design for faster construction and deployment.

In practice

Topics

Best for: CTO, Director of AI/ML, VP of Engineering/Data, Investor

Related on AIssential

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by AI Magazine.