The Challenge
- 40+ Days of training time on fragmented infra.
- Costs are spiralling with no visibility.
- No real-time inference capability.
- Data scientists managing complex infra.
Large-Scale GPU Clusters and SuperPODs Built for the Ambitious AI Era
Accelerate your large scale AI initiatives with latest GPU models - NVIDIA B200, B300, GB200, NVL72 and AMD MI300X - seamlessly delivered through our fully managed AI ecosystem.
You're Ready for AI,
but Is Your Infrastructure Ready?
Five gaps separate AI ambition from AI production and they all point to the same infrastructure problem.
82
%
Infrastructure Readiness Gap
7
%
Data Readiness Gap
84
%
Cost Forecast Gap
25
%
Pilot-to-Production Gap
50
%
GPU Utilisation Gap
We handle the AI complexity. You own the outcomes.
-
Up to 60% TCO reduction
-
Up to 30× Inference acceleration
-
Up to 4× Faster iteration cycles
-
10-day 50B-parameter model training
-
Up to 50% GPU utilization improvement
AI is racing. It's Compounding at
$4.8 trillion and growing.
ESDS is building one of India's largest AI clusters
>8208
NVIDIA B300 GPUs
17.83
PB
VAST AI storage
14
B+
Parameter models tested and validated
SuperPOD
NVIDIA validated
How did a Leading Research Lab
Train a 50B-parameter model in 10 days & cut costs by 60%?
The ESDS Solution
The lab shifted to NVL72 GPU SuperPODs with optimized containers, high-bandwidth NVLink and managed MLOps.
The Outcome
- 10 days Model training time
- 60% Cost reduction
- 30× Faster inference
- 4× Quicker iterations
You’ve Got High Dimensional Data.
We’ve Got Powerful GPUs.
Get access to industry-leading NVIDIA & AMD GPUs designed to accelerate deep learning, GenAI, scientific computing and model inference.
For gen AI, LLMs, 3D graphics rendering and video processing.
Optimized for AI inference, graphics and scalable training workloads, the L40S delivers performance for enterprise-grade GenAI and visual computing tasks.
Specifications
1466 TFLOPS, fp8 733 TFLOPS fp16, 91.6 TFLOPS fp32, supported fp64
| Instance | vCore | RAM (in GB) | GPU (in Memory) |
|---|---|---|---|
| Instance 1 | 8 | 16 | 12 |
| Instance 2 | 16 | 32 | 24 |
| Instance 3 | 24 | 64 | 32 |
| Instance 4 | 64 | 128 | 48 |
Dedicated single, dual or quad L40S configurations for performance-locked workloads.
Each instance considers a fixed L40S count per server — predictable performance, no neighbour contention, ideal for production AI inference and 3D pipelines.
| Instance | vCore | RAM (in GB) | Standard |
|---|---|---|---|
| Instance 1 considering single L40S in each instance | 24 | 128 | 1 |
| Instance 2 considering Dual L40S in each instance | 48 | 256 | 2 |
| Instance 3 considering Quad L40S in each instance | 96 | 512 | 4 |
Total GPU
16
Total Servers
2, each having 8 NVL GPUs
Rated Power per Server
~ 3.5KW
Server Spec
BUILD 1 (2 Qty) — Air Cooled Dense GPU Platform with 8 × L40S PCIE GPU — No NVL Bridge
- 2 × AMD Epyc Turin 9655 (64C/128T) CPU · 3.2 GHz Base Frequency · ~256M Cache · ~360W
- 24 × 64GB 6400 MT/s DIMMS (1536 GB)
- 8 × NVIDIA L40s (48 GB) PCIE GPU
- 2 × 480GB SSD M2 for OS/BOOT on RAID 1
- 8 × 1.92 TB Gen 5 NVMe for Scratch
- 1 × Quad Port 10G Base T
- 2 × Dual Port 100G NIC for Ethernet Traffic
- 2 × Dual Port 100G NIC for Storage Connectivity
- 8 × 3000W PSU (4+4 Redundant)
Ideal for dev teams, research organizations with diverse tasks.
H200 is engineered to push GenAI, LLMs and deep learning workloads further, with HBM3e memory and performance per watt.
Specifications
989.5 TFLOPS fp8, 494.75 TFLOPS fp16, 16.7 TFLOPS fp32, supported fp64
| Instance | vCore | RAM (in GB) | Standard |
|---|---|---|---|
| Instance 1 | 24 | 256 | 1 |
| Instance 1 | 16 | 32 | 24 |
| Instance 1 | 24 | 64 | 32 |
Total GPU
16
Total Servers
2, each having 8 NVL GPUs
Rated Power per Server
~ 7.5KW
Server Spec
BUILD 2 (2 Qty) — Air Cooled Dense GPU Platform with 8 × H200NVL PCIE GPU — 4Way NVL Bridge
- 2 × AMD Epyc Turin 9555 (64C/128T) CPU · 3.2 GHz Base Frequency · ~256M Cache · ~360W
- 24 × 96GB 6400 MT/s DIMMS (2.3 TB)
- 8 × NVIDIA H200NVL (141 GB) PCIE GPU · 4 WAY GPU BRIDGE (NVAIE License Included)
- 2 × 480GB SSD M2 for OS/BOOT on RAID 1
- 8 × 1.92 TB Gen 5 NVMe for Scratch
- 1 × Quad Port 10G Base T
- 2 × Dual Port 100G NIC for Ethernet Traffic
- 2 × Dual Port 100G NIC for Storage Connectivity
- 8 × 3200W PSU (4+4 Redundant)
DGX B200 — Next-Gen AI Platform with 8 × B200 GPUs and Blackwell Architecture
For GenAI, LLMs, simulation workloads and memory-intensive deep learning models
- 2 × AMD EPYC 9455 48C 300W 3.15GHz
- 24 × 96GB 6400 MT/s DIMMS
- 8 × AMD MI300X 192GB 750W 8-GPU
- 2 × 1.92 TB SSD
- 8 × 1.92 TB Gen 5 NVMe
- 1 × Quad Port 10G Base T
- 2 × Dual Port 100G NIC for Ethernet Traffic
- 2 × Dual Port 100G NIC for Storage Connectivity
Enabling you to overcome complex AI challenges with fully managed solutions
01
Captive GPU Design Consultancy
Blueprint in-house GPU clusters, high-density pods or isolated, regulated environments, built for scalability, compliance and cost control.
02
GPU Infrastructure Supply, Deploy & Operations Services
End-to-end lifecycle for NVIDIA (B200/B300/GB200/NVL72) rack design, high-speed networking, thermal planning and performance tuning.
03
Dedicated Managed GPU Infrastructure-as-a-Service
Run AI on fully isolated, high-performance GPU clusters with guaranteed resources, compliance-ready controls and managed orchestration.
04
Managed CPU Cloud & Dedicated Managed GPU Infra Services
Execute large-scale training and distributed pipelines with elastic GPU clusters, low-latency interconnects intelligent scheduling.
05
Managed GPU Cloud
Consume GPUs on demand like a utility, secure multi-tenant or dedicated pods, built-in orchestration, 24×7 monitoring and expert support.
