Retrofitting a Data Center for AI-Driven Workloads
Client Overview
Industry: Enterprise Data Centers & AI Infrastructure
Company Size: 200,000 sq. ft. facility
Location: Silicon Valley, California
Service Provided: Data Center Retrofit for AI Expansion
Challenge: Increased cooling demands, rising energy costs, and power limitations due to AI-driven workloads
The Challenge
An enterprise data center in Silicon Valley faced a rapid increase in AI-powered workloads, leading to escalating power demands and inefficient cooling performance. The facility, originally designed for traditional enterprise workloads, was not optimized for AI training models, which require:
High-density rack configurations
Advanced cooling solutions to manage heat output
Greater power efficiency to reduce operational costs
Without intervention, the data center risked power inefficiencies, overheating, and increased downtime, impacting business performance. The client needed a scalable, cost-effective retrofit to support its AI infrastructure without rebuilding from scratch.
Our Approach
To future-proof the data center, our firm developed a targeted retrofit strategy focusing on three core areas:
1. High-Efficiency Cooling System Upgrades
Integrated liquid cooling technology to manage heat from AI processors.
Installed hot/cold aisle containment to optimize airflow and prevent overheating.
Deployed real-time AI-driven temperature monitoring to adjust cooling dynamically.
2. Power Infrastructure Optimization
Upgraded to high-density power distribution units (PDUs) to support AI workloads.
Integrated smart energy management software to balance loads efficiently.
Enhanced renewable energy integration (solar + battery storage) to cut electricity costs.
3. Scalable, Modular Infrastructure for Future Growth
Designed modular AI-ready rack systems that allow incremental expansion.
Implemented edge processing capabilities to reduce latency for AI inference.
Ensured compliance with GRI, CSRD, and ESG sustainability goals.
Results & Impact
Within 8 months, the retrofitted data center achieved the following results:
40% Increase in Cooling Efficiency “ Reduced heat buildup and lowered energy use.
30% Reduction in Power Costs “ Improved energy management reduced operational expenses.
AI Workload Capacity Increased by 3X “ Scalable infrastructure allowed seamless expansion.
Sustainability Gains
Lowered PUE from 1.8 to 1.3, achieving industry-leading efficiency.
Zero Downtime During Retrofit “ Phased implementation ensured uninterrupted operations.
Key Takeaways
Biggest Success: Transformed a legacy data center into an AI-ready infrastructure without a costly rebuild.
Applicable Industries: Enterprise data centers, AI research facilities, and cloud computing providers.
Next Steps for Potential Clients: Is your data center struggling to keep up with AI-driven workloads? We can help. Contact us today.
