

Liquid Cooling
GPU clusters operating at 40–100kW per rack exceed the limits of air cooling. Our dedicated liquid cooling production facility delivers thermally validated, fully integrated AI infrastructure that’s production-ready before it reaches your data center floor.
LIQUID COOLING BY THE NUMBERS
reduced energy consumption
reduction in carbon footprint
better performance in HPC tasks
LIQUID COOLING FOR ENTERPRISE-SCALE AI & HPC INFRASTRUCTURE
AHEAD DEDICATED RACK SCALE INTEGRATION FACILITY
We operate 350,000+ sq ft of purpose-built AI infrastructure production capacity — including 75,000 sq ft of dedicated rack integration and thermal deployment space — engineered for high-density AI programs at enterprise scale. We deploy complete and fully tested solutions from our facilities to yours, including the racks, servers, liquid cooling infrastructure, and networking. All engineered for reliability, resilience, and security.
Our diverse team of hardware and AI experts can design and implement infrastructure solutions that are exceptionally reliable, resilient, and secure.

AHEAD’S HANDS-ON INNOVATION LAB
Our AI Infrastructure Validation Center benchmarks liquid cooling architectures against real production workloads before deployment to ensure your AI environment performs as designed.
The Lab features both rack-scale and direct-to-chip cooling. Experience facility chiller cooling demos that simulate real-world deployment scenarios, or see side-by-side comparisons of thermal efficiency and power consumption to make data-driven infrastructure decisions.
It’s your sandbox to tweak until your infrastructure meets your specific requirements.

SOLUTIONS ALIGNED WITH YOUR AI JOURNEY
AHEAD helps determine your AI opportunity, define use cases and data requirements, and set a course for AI that turns potential into an acceleration plan.
AHEAD modernizes your data foundation and your digital core, edge, and cloud, to set you up for success with AI.
AHEAD pairs, tunes, and automates your machine learning and AI models with use cases and requirements on top of a strong data foundation.






