Hyperscale Data expands Michigan data center to fuel NVIDIA’s Blackwell AI infrastructure

Hyperscale Data has begun a significant expansion at its Michigan data campus, setting up the foundation for NVIDIA’s Blackwell architecture.

With AI workloads pushing limits in energy and computation power, Hyperscale’s Michigan buildout aims to deliver high-performance GPU clusters capable of handling deep learning, large language models, and autonomous systems training.

The site is strategically located to access reliable energy and connectivity routes. Michigan’s growing interest in technology investment also gives Hyperscale a solid local base to attract talent and partners.

The company says construction will roll out in phases, focusing first on capacity for NVIDIA’s Blackwell-based servers before expanding to support enterprise clients across North America.

Built around NVIDIA Blackwell

NVIDIA’s Blackwell platform is shaping up to be the backbone of AI performance for the next few years. Built to process massive workloads faster and more efficiently, it gives infrastructure providers like Hyperscale the muscle to host everything from generative AI models to advanced analytics tools.

Hyperscale’s campus will feature dedicated clusters optimized for the B200 Tensor Core GPUs, offering scalability for both training and inference. The company aims to build an environment where clients can spin up GPU capacity on demand without waiting months for deployment.

NVIDIA’s Blackwell architecture brings double the memory bandwidth and compute performance of its predecessor, Hopper, making it ideal for multi-tenant data centers. Hyperscale is betting that by being early to adopt, it can capture the fast-growing AI cloud market that major players like AWS, Microsoft, and Oracle are already competing in.

The reason to select Michigan

Most large data centers in the U.S. cluster around regions like Northern Virginia or Silicon Valley, but Michigan’s rise as a data hub isn’t surprising. Lower real estate costs, access to clean energy, and a stable climate make it an attractive option for hosting dense GPU infrastructure.

Hyperscale’s campus benefits from regional fiber connectivity and strong power grid reliability, which are two factors crucial for maintaining uptime in high-load environments. The company’s CEO said Michigan gives them the “space and scalability” needed to grow sustainably without facing the energy grid strain that’s common in other tech-heavy regions.

Beyond logistics, the expansion will also create jobs for local engineers and technicians, linking the state’s industrial background with the AI-driven future. It’s a good example of how the next wave of infrastructure growth is spreading beyond traditional tech hotspots.

Hyperscale’s expansion will rely on advanced liquid cooling systems and optimized airflow design to manage heat efficiently. The company has committed to using renewable power sources where possible, aiming to align with carbon-reduction goals that major AI companies are now prioritizing.

Each new data hall is being built with modular scalability in mind, meaning it can expand capacity without overhauling existing systems. Hyperscale says its Michigan site uses hybrid cooling technology that reduces water use and improves power usage effectiveness (PUE). The data center is targeting a PUE score below 1.2, which would place it among the most efficient facilities in North America.

This sustainability layer could be key as global AI infrastructure demands continue to challenge environmental benchmarks.