DRACO 64× H200 Containerized Micro Data Center

Overview

The DRACO 64× H200 Containerized Micro Data Center is a turnkey, self-contained AI data centre — 64× NVIDIA H200 SXM5 (9,024 GB HBM3e) pre-integrated with integrated liquid (cdu) cooling, UPS, power distribution, physical security and remote monitoring in an ISO shipping container. It places real AI capacity where there is no built data centre — a campus, remote site — and runs private AI on-premises, in INR, on a GST invoice.

Engineered to remove the need to build a server room, it bundles the GPU servers, networking, integrated liquid (cdu) cooling, battery backup and DCIM monitoring into one validated unit — delivered, integrated and burned-in as a single SKU with one warranty and one support contract.

Key highlights

• 64× H200 · 9,024 GB HBM3e — real AI capacity for training and inference, anywhere.
• Self-contained container — GPU servers, networking, integrated liquid (cdu) cooling, UPS, PDU, fire suppression and security in one unit.
• No server room required — deploy with just site power and network.
• 32× Intel Xeon 6 + 8 TB DDR5 ECC — host compute and memory matched to 64 GPUs.
• 960 TB NVMe NVMe + InfiniBand NDR 400G — local storage and a low-latency fabric for distributed jobs.
• DCIM remote monitoring + BMC/IPMI — full remote management of power, cooling, environment and compute.
• On-prem data sovereignty — data and models stay at the site; DPDP-friendly, air-gappable.
• Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable.

AI workload fit (what it actually runs — honestly)

• Local training & inference (primary): train, fine-tune and serve large models at the site over the InfiniBand fabric.
• Large-model serving: serve 70B-class models across the enclosure.
• Vision, multimodal & agentic: production AI services co-located with operations.
• Engineering note: the H200 (141 GB HBM3e, NVLink) handles training-grade workloads; the enclosure provides liquid cooling and power so a full GPU cluster runs where there is no data centre.

AI workload positioning

This sits at the deploy-anywhere stage: a complete AI site in a container. With 9,024 GB HBM3e across 64 GPUs plus its own power and cooling, it is sized to sustain real local AI where there is no data centre — the owned alternative to backhauling to the cloud or building a server room.

Industry use cases

• Government & defence — a deployable, air-gapped sovereign AI site.
• Manufacturing & energy — an AI site on the campus or at a remote/rugged facility.
• Telecom — regional AI capacity at the network edge.
• Healthcare — an on-site clinical AI enclosure keeping PHI in the building.
• Neocloud / providers — rapidly-deployable regional GPU capacity.
• Disaster-recovery & events — temporary, self-powered AI capacity.

Performance — and how to be sure

We don’t publish inflated peak numbers. The honest picture: 9,024 GB HBM3e across 64× H200 in a self-cooled container is sized for local training and serving. Want certainty? Request a free benchmark of your models on this exact configuration before you buy; we’ll send back real performance plus the power and cooling envelope.

Series & upgrade path

• DRACO (flagship micro-DC tier) — this.
• Capacity ladder: half-rack pod → single-rack pod → dual-rack pod → containerized → modular data center.
• When to step up: for more capacity, move to a larger containerized or modular RDP data center — talk to an architect about the site.

On-prem vs cloud — the TCO case

A self-contained container removes both the cost of building a server room and the recurring cost of cloud: you own the compute, power and cooling as one asset, with no egress and full data residency. RDP pricing is fixed in INR with a GST input-credit-eligible invoice — ask for a 3-year TCO comparison including facility savings.

Software & day-one readiness

Ships pre-integrated and validated: NVIDIA driver, CUDA, cuDNN, NCCL, the InfiniBand stack, Docker and NVIDIA Container Toolkit, with Kubernetes/Slurm, PyTorch and vLLM / Triton / TensorRT-LLM on Ubuntu LTS, plus DCIM monitoring. Optional managed operations.

Power, cooling & rack integration

A iso-container (containerized) with integrated liquid (cdu) cooling, integrated UPS, PDU and fire suppression — it provides its own thermal and power envelope; you supply site power and network. (Exact power draw, BTU, battery runtime and footprint confirmed in the design package.) Full DCIM and out-of-band management.

Deployment, warranty & support

• Made to order, integrated and burned-in in India; lead time confirmed at quote.
• Delivered as one unit: GPU servers, networking, cooling, UPS/PDU, security, monitoring, and the pre-installed AI software stack.
• Onsite warranty + AMC with pan-India coverage, site-level support and an RMA/escalation path (exact terms confirmed at quote).

Why RDP

14 years of Make-in-India infrastructure and 300,000+ devices shipped. Indian OEM, INR pricing, GST tax invoice (HSN 8471), pan-India onsite engineers, GeM availability, and DPDP / sovereign-AI-ready deployment.

Buy with confidence

This is a turnkey AI data centre in a container, made to order — talk to an RDP solution architect, size the capacity, cooling and power for your site, get a 3-year TCO, and benchmark your own models before you commit. Request a quote to begin.

Specifications