The foundation for AI is the right infrastructure
Build private, hybrid, and sovereign AI environments on infrastructure designed for high-density workloads, low-latency connectivity, and AI-scale growth.
AI success depends on your infrastructure decisions.
AI workloads demand infrastructure built for scale, connectivity, and physical sovereignty across regions and jurisdictions.
Build the base and own the economics of AI. Run sustained workloads on infrastructure built for long-term scale, then burst into cloud capacity when demand spikes.
Run AI workloads in-region with secure, jurisdiction-bound infrastructure designed for compliance, resilience, and operational control.
Place your AI infrastructure closer to users, clouds, and data sources to support efficient, real-time inference, high-performance AI workloads, and new levels of resiliency.
Connect clouds, partners, models, and data on a single trusted platform with secure, low-latency interconnections.
AI needs more than fabric. It needs a foundation.
Our CTO, Chris Sharp, explains why AI infrastructure depends on real capacity, power, cooling, connectivity, and in-country deployment, not just software routing or policy layers.
Build AI on infrastructure designed for scale
PlatformDIGITAL® is the meeting place where companies, technologies, and data come together, enabling enterprises to overcome Data Gravity, scale securely, connect with ease, and remain AI-ready.
Our high-density environments are built for training, inference, and rapid scaling.
Support training, inference, and high-density compute with power and cooling designed for AI’s heaviest loads.
Energy-efficient systems cut costs and supports compliance initiatives without slowing down your AI.
Work across clouds, partners, models, and providers without locking your AI strategy into a closed environment.
ServiceFabric® gives you secure, carrier-neutral access to clouds, partners, and data, keeping your AI workflows compliant and fast.
Our Pervasive Datacenter Architecture (PDx®) shows you exactly where to deploy, interconnect, and extend AI infrastructure. You go from strategy to results quickly.
Choose the right infrastructure model for your AI strategy
AI workloads require different infrastructure strategies depending on where data lives, how inference runs, and how workloads scale.
AI for IT Operations (AIOps)
Use AI to automate development lifecycles and manage applications across hybrid and multi-cloud environments with secure, reliable infrastructure that keeps uptime high.
AI workflows across multiple clouds
Run machine learning and AI workloads seamlessly across clouds with secure data integration, high-performance compute, and low-latency connectivity.
AI with private infrastructure
Protect proprietary data while running private AI inference on high-density infrastructure with secure, high-speed access to public cloud resources.
AI training and inference in hybrid clouds
Train and run deep learning and large language models across hybrid clouds on secure, low-latency infrastructure that scales reliably with your datasets.
AI training and inference in public clouds
Scale AI training and ML inference in public clouds with high-performance infrastructure that ensures secure, low-latency access to critical data and models.
Built for AI-scale power and density
High-Density Colocation delivers the cooling, power, and interconnectivity today’s AI and HPC workloads demand. With scalable options from 30 kW to 150 kW per cabinet, you get the speed, efficiency, and security to run data-intensive operations with confidence.
