QUASAR 16× H200 Micro Data Center Pod

Overview

The QUASAR 16× H200 Micro Data Center Pod is a turnkey, self-contained AI data centre in an enclosure — 16× NVIDIA H200 SXM5 (2,256 GB HBM3e) pre-integrated with integrated liquid-ready cooling, UPS, power distribution, physical security and remote monitoring. It deploys AI compute where there is no built data centre: a factory, warehouse, branch, campus or remote site. You roll it in, connect power and network, and run 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-ready cooling, battery backup and DCIM monitoring into one validated, lockable enclosure — delivered, integrated and burned-in as a single SKU with one warranty and one support contract.

Key highlights

• 16× H200 · 2,256 GB HBM3e — real AI capacity for inference, training and fine-tuning, anywhere.
• Self-contained enclosure — GPU servers, networking, integrated liquid-ready cooling, UPS, PDU, fire suppression and physical security in one lockable unit.
• No server room required — deploy in a warehouse, campus, branch or remote site with just power and network.
• 8× Intel Xeon 6 + 2 TB DDR5 ECC — host compute and memory matched to 16 GPUs.
• 240 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: 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: this is infrastructure plus compute — the NVIDIA H200 SXM5 (141 GB HBM3e, NVLink) handles training-grade workloads. The value is a complete, self-cooled, battery-backed AI site you can place anywhere, not just the GPUs inside it.

AI workload positioning

This sits at the deploy-anywhere stage: a complete AI site in a box. With 2,256 GB HBM3e across 16 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

• Manufacturing — an AI site on the factory campus for vision and digital-twin workloads.
• Retail & logistics — regional AI capacity close to stores and warehouses.
• Healthcare — an on-site clinical AI enclosure keeping PHI in the building.
• Government & defence — a deployable, air-gapped sovereign AI site.
• Energy & mining — AI at remote or rugged facilities with no server room.
• Education & research — a self-contained campus AI pod.

Performance — and how to be sure

We don’t publish inflated peak numbers. The honest picture: 2,256 GB HBM3e across 16× H200 in a self-cooled enclosure 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

• QUASAR (performance 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 pod 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 single-rack self-contained enclosure with integrated liquid-ready 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 enclosure: 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 an enclosure, 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