Dedicated AI training capacity
A fit for organizations that have outgrown office-adjacent infrastructure and need a clearer path for dense GPU training environments, predictable thermal behavior, and disciplined commissioning.
AI Data Centers
Modular AI Infrastructure for Production Workloads
Deploy high-density AI capacity with a clearer operating model, disciplined commissioning, and long-term serviceability. The NOMAD platform is designed for dense AI workloads that need modular capacity, two-phase immersion cooling, and a more supportable path than improvised facility expansion.
2P
Dual-Phase Immersion Cooling
Thermal architecture designed to support dense GPU environments with stable operating conditions.
GPU
High-Density GPU Infrastructure
Built for enterprise AI training and inference with repeatable deployment standards.
2MW
2 MW Modular Capacity
Add capacity in practical phases while maintaining serviceability and clear operating controls.
NOC
24/7 Monitoring and Support
Observability and response workflows focused on uptime, performance consistency, and risk control.
Where a Modular AI Data Center Makes the Most Sense
This is typically the right conversation when a team has moved past ad hoc rack expansion and needs a cleaner facility strategy for dense AI operations, phased growth, and accountable uptime.
Private inference and sovereign AI environments
Useful when data-control requirements make shared platforms a poor fit and the project needs isolated capacity, operational ownership, and infrastructure built around private deployment rules.
Staged expansion instead of oversized first spend
A modular path matters when the project timeline, power delivery, or GPU procurement cycle is moving in phases and the team needs room to expand without rebuilding the entire operating model.
What VMS Helps Coordinate
The platform is only one part of the project. The real work is aligning power, thermal strategy, facility operations, delivery sequencing, and the production handoff around how the compute will actually be used.
POWER
Utility, power, and rack envelope planning
We scope the practical inputs first: power envelope, rack density, upstream networking, and what can be commissioned on the schedule the client is actually working against.
THERMAL
Two-phase immersion strategy
E3's NOMAD platform is designed around two-phase immersion cooling for dense AI infrastructure, which changes the thermal conversation from generic air management to a more deliberate density and serviceability model.
OPS
Commissioning and operating discipline
The value is not just capacity. It is how the environment is brought online, monitored, handed off, and kept supportable once the compute is in production.
EXPAND
Growth path beyond the first deployment
A modular footprint gives teams a way to plan expansion around real workload growth, procurement timing, and operating cost instead of guessing everything up front.
Related Capacity Planning Resources
The strongest AI infrastructure decisions connect facility design, GPU procurement, and production operations instead of treating them as separate buying motions.
HPC Server Inventory
Review the current sourcing path for Dell, Supermicro, and HPE GPU systems if the project also needs server selection and accelerator planning.
Private AI Planning Articles
Read practical guidance on HPC procurement, immersion cooling, AI infrastructure operations, and private deployment planning before the build is finalized.
Managed IT Operations
If the AI environment also needs monitoring, security controls, or integration with a broader IT operating model, review the MSP service path as well.
Request a Project Review
Send the power envelope, deployment timeline, workload mix, and expansion assumptions. We will map the next practical step instead of sending generic platform filler.
AI Data Center FAQ
Answers to the common questions clients ask when they are evaluating a modular AI infrastructure path instead of expanding around an improvised facility footprint.
What is the best fit for a modular AI data center instead of a traditional room buildout?
A modular approach is usually strongest when the project needs dense AI capacity, a phased expansion path, and a cleaner thermal and operating model than a piecemeal room retrofit can offer. It is especially relevant when the compute demand is moving faster than the rest of the facility.
Why does two-phase immersion cooling matter for dense AI workloads?
Two-phase immersion changes the thermal design conversation for dense GPU infrastructure by supporting tighter thermal control and higher density than many traditional air-cooled layouts. The right fit still depends on the operating model, serviceability, and facility goals around the deployment.
Can VMS help coordinate the project beyond the facility platform itself?
Yes. The platform decision only matters if the full path is coherent. We help connect facility planning, GPU server sourcing, commissioning, network handoff, and the operating ownership that follows the initial deployment.
Do you publish standard pricing for NOMAD deployments?
No. Capacity planning, cooling strategy, site assumptions, and deployment scope are all project-specific. We scope the environment against the workload and timeline first, then respond with the practical next step.
Ready to Scope Capacity?
Share your power envelope, timeline, and workload profile. We will map a practical deployment path.
Request Consultation