Construction has officially begun on the first phase of the Snyder AI data center campus in Snyder, Texas, marking the transition of the project from planning into active development as demand for AI computing infrastructure continues to accelerate across the United States.
The project is being developed by Energy Vault for Crusoe Cloud under a previously announced commercial agreement. The initial phase will deliver 8 megawatts (MW) of powered shell capacity, with the campus designed to expand to 25 MW in a planned second phase. According to the companies, the first facilities are expected to enter commercial operation in the first quarter of 2027.
Modular Design Accelerates AI Capacity Deployment
Rather than following the multi-year timelines typical of conventional data center projects, Energy Vault is building the Snyder campus around a modular deployment strategy that can bring computing capacity online much faster. Crews have begun installing fiber, preparing the site, constructing electrical infrastructure, and completing other enabling works ahead of the deployment of Crusoe’s prefabricated Spark modular data center units.
The project reflects a broader shift in the AI infrastructure market toward modular campuses that shorten deployment timelines while reducing some of the risks associated with large, multi-year construction programs. As hyperscalers and AI cloud providers race to secure power and computing capacity, developers increasingly favor sites that offer faster power delivery and allow phased expansion as demand grows.
An Integrated Platform for AI Computing
At Snyder, the campus is designed as more than a traditional powered shell development. Plans call for an integrated infrastructure platform that combines utility power, electrical distribution systems, N+1 power redundancy, battery energy storage systems (BESS), and modular data center buildings capable of supporting AI training, fine-tuning, and inference workloads.
Under the commercial structure announced by the companies, Energy Vault will purchase ten Crusoe Spark modular data center units, which Crusoe will lease back as powered infrastructure to operate its cloud computing services. The arrangement allows Energy Vault to own the physical infrastructure while Crusoe deploys and operates AI computing capacity for customers.
The development also highlights how AI infrastructure providers are experimenting with new ownership and financing models that separate infrastructure assets from cloud operations. Similar approaches are becoming more common as developers seek to accelerate deployments while reducing upfront capital requirements for cloud providers.
A Scalable AI Infrastructure Strategy
Energy Vault positions Snyder AI as the first step in a broader powered AI infrastructure strategy that integrates land development, electrical infrastructure, battery storage, and modular computing facilities into a repeatable development platform. The company says this model addresses some of the industry’s biggest challenges, including power availability, site readiness, deployment speed, and infrastructure reliability.
West Texas AI infrastructure
Snyder AI adds another significant AI infrastructure investment to West Texas, where abundant land, an expanding transmission network, and access to large-scale energy resources continue to draw data center developers. Although the initial 8 MW phase remains modest compared with other developers’ gigawatt-scale AI campuses across Texas, the project shows how smaller modular deployments can complement hyperscale developments and help satisfy rapidly growing demand for AI computing capacity.
Crews will continue construction through 2026, completing the site’s core electrical and utility infrastructure before installing the Crusoe Spark modular data center units. If the current schedule remains on track, Crusoe Cloud will bring the first computing capacity at Snyder AI online in the first quarter of 2027.
The Snyder campus adds to a growing pipeline of AI infrastructure projects taking shape across West Texas as developers pair large-scale data centers with dedicated energy strategies. Another major example is the proposed Alpha Digital Campus, a 2 GW hyperscale development that will receive power through a joint venture between Liberty Energy and PowerBridge, highlighting the region’s expanding role in supporting energy-intensive AI computing.
The project also aligns with a growing wave of AI infrastructure investments that integrate dedicated power generation with hyperscale computing campuses. In Kentucky, Brookfield and NextEra Energy recently unveiled plans for a $100 billion AI Data Center Campus at the DOE Paducah Site, where up to 4.6 GW of new power generation and battery storage will support more than 1.2 GW of AI computing capacity without relying solely on existing grid resources.
Project Factsheet: Snyder AI Data Center Campus
Project Name: Snyder AI Data Center Campus
Location: Snyder, Scurry County, Texas
Developer: Energy Vault, Inc.
Customer/Tenant: Crusoe Cloud
Project Type: Powered AI infrastructure campus featuring modular AI data center infrastructure.
Project Status: Under construction.
Construction Commenced: July 2026.
Phase 1 Capacity: 8 MW of powered shell capacity.
Future Expansion: Planned expansion to 25 MW in a second phase.
Target Commercial Operation: First quarter (Q1) 2027.
Data Center Platform: Crusoe Spark modular data center platform.
Modular Deployment: Energy Vault will purchase ten Crusoe Spark modular data center units, which Crusoe will lease back as powered shell infrastructure.
Campus Infrastructure: The campus combines powered land, electrical infrastructure, N+1 power redundancy, battery energy storage systems (BESS), and modular data center facilities.
Construction Activities: Site preparation, fiber installation, electrical and power infrastructure construction, and enabling works to support deployment of the modular data center units.
Primary Workloads: AI model training, fine-tuning, and inference through Crusoe Cloud.
Development Model: Energy Vault is developing the campus as the first phase of its broader powered AI infrastructure strategy, integrating land development, electrical infrastructure, battery storage, and modular computing facilities.
Key Objective: Deliver AI-ready infrastructure faster than conventional data center developments by using prefabricated modular facilities and power-ready sites.
Industry Significance: Snyder AI demonstrates a scalable approach to AI infrastructure development that addresses key industry bottlenecks, including power availability, site readiness, deployment speed, infrastructure reliability, and the growing demand for AI computing capacity.
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