AI Factory in a Box
Prefabricated. High-density. Ready to deploy
AI Factory in a Box is a prefabricated modular AI data center designed to deliver high-density GPU compute (50–100 kW per pod) with integrated liquid cooling and rapid deployment capabilities.
What Is the AI Factory in a Box?
AI Modular data centers are designed for high-performance computing to support Artificial Intelligence (AI) and Language Models (LMs).These units can have any layout according to your needs, location, available power, cooling options, and many more.
- A single Pod compute density ranges from 50-100kW
- Designed for AI accelerators such as NVIDIA H100/H200, AMD MI300X, and other high core CPUs, high TDP GPUs, etc.
- Supports other chips and accelerators based on client requirements
- Vendor-agnostic approach across all equipment
- Designed for maximum flexibility
The Infrastructure Gap in Modern AI Deployment
Traditional data centers were not designed for the scalability, thermal and power demands of today’s AI workloads. GPUs get hot, dense, and hungry. Retrofitting massive facilities leads to locked capacity with no opportunity for scaling, cooling inefficiency, inflexibility and costly downtime.
PodTech’s AI Factory in a Box was engineered from the ground up to solve this problem. Thermal management is integrated into the pod from the factory.
AI Factory in a Box | Traditional Data Center | |
Deployment Time | Weeks. Factory-built and tested before delivery, with minimal on-site work required | Months to years. Requires full construction, MEP installation, and commissioning on site |
Cooling Efficiency | Engineered-in thermal management with PUE as low as 1.2. Liquid cooling designed around GPU density from day one | Cooling typically retrofitted or generalized. Average PUE of 1.58. Struggles with high-density GPU thermal loads |
Scalability | AI modular data center allows capacity to be added incrementally as AI workloads grow | Scaling requires new construction phases, significant capital expenditure, and long lead times |
Cost Predictability | These prefabricated structures feature fixed investments with less uncertainty onsite. | Construction-based systems face risks of overspending, delivery issues, and uncontrolled costs. |
Built for What AI Actually Demands
Cooling Options
- Direct-to-chip liquid cooling for maximum thermal efficiency within GPU infrastructure
- Enclosed hot/cold aisle containment for mixed workloads
- In-row cooling for more optimized cooling
- Rear-door heat exchangers for hybrid deployments
- Custom configurations for unique site or climate conditions
Energy Efficiency
- Lowest PUE at 1.2
- Significantly below the global data center average of 1.58
- 83% of all consumed power goes directly to compute
Prefabricated Modular Design
- Factory-built and tested before delivery
- Faster deployment than stick-built data centers
- Scalable pod infrastructure, multiple pods can be interconnected
- Reduced construction risk and on-site labor
How Deployment Works
- Site Evaluation & Thermal Modeling: Before specifying your hardware, PodTech’s engineers will perform an evaluation of your site, power, climate, and workload characteristics.
- Pod Design: The pod is designed based on your power density, cooling, MEP, and rack configuration needs for your workload.
- Factory Build & Commissioning: Your pod is built and commissioned in our factory before shipping.
- On-Site Integration: The pod arrives deployment-ready. Connection to power, network, and site utilities is straightforward.
- Operational Handover: PodTech provides documentation, monitoring integration, and ongoing support options.
Who Deploys the AI Factory in a Box?
Enterprise AI Teams
Organizations building proprietary LLM training clusters or scaling inference capacity without waiting for a lengthy data center build-out for enterprise private AI.
Cloud & Colocation Providers
Operators adding GPU-dense AI capacity to existing campuses using a repeatable, fast-to-deploy pod GPU infrastructure.
Government & Defense
Secure, self-contained AI compute for classified inference, autonomous systems, and sovereign AI infrastructure in non-standard environments to support AI workloads.
Research Institutions
Academic AI labs and HPC centers needing high-density compute quickly without a purpose-built facility capital commitment.
Edge AI Operators
Edge inference in AI for industrial, energy, and telecom firms where conventional data center infrastructure is impractical.
Frequently asked questions
What is an AI Factory in a Box?
Prefabricated data center pods made by PodTech Data Center designed specifically to handle AI and ML applications in GPUs. These pods offer 50-100 kW output along with PUE of upto 1.2.
How does this differ from a modular data center?
Unlike a modular data center, which is a generic type of data center, the AI Factory in a Box is custom-built for AI workloads and is equipped with unique thermal capabilities, including liquid cooling and power density.
What GPU hardware is compatible?
NVIDIA H100, H200, Blackwell GPUs, AMD Instinct series, and other AI accelerators with high TDPs.
Can more than one pod be installed at once?
Yes, the pod technology scales. You can connect several pods to form an AI compute campus.
What exactly does a 1.2 PUE ratio mean?
It means that only 0.2 kW of energy is required to operate the infrastructure in comparison with 1 kW of energy for computing. This saves on operational energy costs compared to the world average of 1.58.
Ready to deploy AI infrastructure that performs at scale?
PodTech’s AI Factory in a Box is available for enterprise, colocation, government, and edge deployments globally.