FLAGSHIP CAPABILITY · INFRASTRUCTURE SUPPLY & DEPLOYMENT

Turnkey AI & High-Performance Computing Infrastructure

Patel Galaxify Solutions supplies, stages, and deploys high-density GPU compute servers, low-latency InfiniBand fabrics, and parallel NVMe storage for enterprise machine learning, research clusters, and data-intensive computing across India.

Pan-IndiaFreight & Delivery
100% GenuineOEM Warranty
On-SiteRack Staging & Testing
24/7 SLAAMC Maintenance
Enterprise High-Density GPU Computing Server Rack

High-Density GPU Node Architecture

Multi-accelerator topology with high-speed PCIe 5.0 lanes

Flagship
CAPABILITIES & HARDWARE SOURCING

Enterprise AI & HPC Infrastructure Capabilities

Building modern AI computing clusters requires specialized hardware across multiple disciplines. We engineer and supply every layer of the compute cluster stack.

Compute Layer

High-Density GPU Compute Nodes

Sourcing and deploying multi-GPU server architectures supporting NVIDIA HGX and PCIe accelerators (including H100, H200, L40S, and A100 classes). Engineered for intense deep learning, tensor mathematics, and parallel execution.

Configurable 4-way, 8-way SXM/HGX and multi-PCIe chassis
Dual Intel Xeon Scalable or AMD EPYC high-core host CPUs
Up to 2TB–4TB enterprise DDR5 ECC host system memory
PCIe Gen 5 high-speed expansion lanes for direct accelerator-to-NIC routing
Workload Sizing

AI Training vs. Inference Architectures

Differentiating dense, high-bandwidth interconnected nodes for foundational model training and parameter fine-tuning from energy-efficient, low-latency 1U/2U configurations designed for production model inferencing.

Massive memory bandwidth and NVLink mesh for multi-GPU training
Low-power PCIe accelerators optimized for token generation throughput
Precision quantization support (FP8, FP16, BF16, INT8)
Redundant low-latency power supplies engineered for peak tensor spikes
Network Layer

Ultra-Low Latency Fabric & Interconnect

Eliminating inter-node bottlenecks with non-blocking 400Gb/s InfiniBand and high-speed RoCE (RDMA over Converged Ethernet) fabrics. Enables GPUDirect RDMA for seamless memory-to-memory communication across cluster nodes.

NVIDIA Quantum-2 InfiniBand (NDR 400Gb/s) switching architecture
Spine-leaf topologies designed for non-blocking all-reduce operations
GPUDirect RDMA bypassing host CPU and memory subsystems
High-speed QSFP optical transceivers, active optical cables (AOC), and DACs
Storage Layer

All-Flash Parallel Storage Integration

Supplying high-throughput NVMe parallel storage tiers capable of saturating multi-GPU ingestion pipelines during training runs, paired with high-capacity secondary storage for massive raw datasets and checkpointing.

NVMe All-Flash arrays delivering millions of random IOPS
GPUDirect Storage (GDS) direct paths from NVMe drives to GPU VRAM
Parallel file systems and NFS integration for distributed model checkpointing
Multi-petabyte scalable storage shelves for long-term dataset retention
Physical Layer

Turnkey Rack Integration & Cabling

Certified staging, rack elevation design, and structured cabling for high-density environments. Our engineers handle precision mounting, rail installations, and clean airflow dressing in standard 42U and 48U enclosures.

Heavy-duty 42U and 48U server enclosures rated for high static weight
Precision cable management separating power and high-speed fiber
Out-of-band management network cabling (iDRAC, iLO, BMC)
Physical factory staging and pre-delivery burn-in testing
Facility Infrastructure

Power Density & Thermal Engineering

AI clusters operate at significantly higher power densities than standard enterprise workloads. We assist teams in planning power phase balancing, three-phase intelligent PDUs, and cold-aisle thermal containment.

High-density power planning supporting 15kW to 35kW+ per rack
Monitored and switched three-phase intelligent power distribution units
Thermal load calculations and cold/hot aisle containment design
Preparation and coordination for direct-to-chip liquid cooling setups
SYSTEM TOPOLOGY

Interconnected Infrastructure Architecture

AI performance is determined by the weakest link in the cluster. Below is an illustrative breakdown of how compute, networking, storage, power, and orchestration integrate into a balanced enterprise AI factory.

* Note: Sample architecture is illustrative. Final configuration is custom-sized to workload specs.
Multi-Rack High-Performance Computing Cluster Layout

Full-Stack AI Cluster Fabric

High-density compute nodes interconnected by low-latency spine-leaf network

Architecture Sizing Principle

We balance PCIe 5.0 root complexes, memory channels per socket, and GPU-to-NIC topology to eliminate starvation during distributed all-reduce operations.

LAYER 01

GPU & Host Compute Layer

Enterprise GPU servers equipped with high-density accelerators connected via high-speed internal crossbars (NVLink/NVSwitch). Powered by high-TDP multi-core x86 processors providing memory channels and PCIe 5.0 root complexes.

NVIDIA HGX / PCIe AcceleratorsIntel Xeon / AMD EPYC Host ProcessorsDDR5 ECC Memory Modules
LAYER 02

Interconnect & Cluster Fabric

Dedicated high-bandwidth fabric switches enabling distributed all-gather and all-reduce collective communications across nodes without CPU intervention through GPUDirect RDMA.

NVIDIA Quantum-2 400Gb/s InfiniBandRoCE v2 Converged 100G/400G SwitchesOptical Transceivers & Fiber Trunks
LAYER 03

Parallel Data Ingestion & Storage

Multi-tiered enterprise storage architecture. Ultra-fast NVMe flash feeds training data directly into accelerator memory to keep GPU utilization near 100%, backed by petabyte-scale storage arrays for deep archives.

All-Flash NVMe TierParallel File System ProtocolMulti-Tier Object/NAS Secondary Storage
LAYER 04

Power, Cooling & Physical Enclosure

Heavy-duty enterprise racks engineered to handle concentrated physical weight, dual-redundant 3-phase power feeds, intelligent circuit-level metering, and structured airflow containment.

Intelligent Switched 3-Phase PDUs42U/48U Heavy Load EnclosuresAirflow Blanking & Thermal Containment
LAYER 05

Cluster Orchestration & Systems Layer

Commissioned base system software stack including bare-metal OS hypervisors, GPU driver toolkits, fabric diagnostics, and orchestration frameworks ready for client workload schedulers.

Enterprise Linux / Hypervisor BaseCUDA, NCCL & Driver Stack ValidationSlurm / Kubernetes Scheduler Readiness
TARGET APPLICATIONS

Engineered for Demanding Enterprise Workloads

Different computational workloads stress hardware in distinct ways. We tailor hardware bills of materials to your exact algorithmic and dataset demands.

Natural Language Processing

Generative AI & LLM Engineering

Infrastructure sized for distributed parameter training, parameter-efficient fine-tuning (LoRA), and high-concurrency API inferencing of foundation models.

Recommended Hardware Profile:

8-Way HGX GPU nodes, NDR InfiniBand fabric, high-throughput NVMe storage

Image & Video Processing

Computer Vision & Autonomous Systems

High-throughput parallel processing clusters for video frame extraction, object detection models, defect inspection, and real-time inference at scale.

Recommended Hardware Profile:

PCIe and HGX GPU compute, multi-channel 25G/100G Ethernet ingest

High-Performance Computing

Scientific Simulation & Genomics

Massive memory footprints and double-precision floating-point performance for computational fluid dynamics (CFD), molecular docking, and genomic alignment.

Recommended Hardware Profile:

Dual-socket high-core compute nodes, MPI-optimized low-latency InfiniBand

Quantitative Analytics

Financial Modeling & Algorithmic Trading

Ultra-low-latency deterministic compute clusters for Monte Carlo options simulations, tick-by-tick market data backtesting, and real-time risk assessment.

Recommended Hardware Profile:

Dense high-frequency compute, FPGA/GPU acceleration, low-latency switching

Enterprise Big Data

Accelerated Data Analytics & Vector Search

Accelerating columnar database queries, distributed vector indexing, and embedding search over multi-terabyte enterprise knowledge bases.

Recommended Hardware Profile:

Large host system RAM, NVMe flash arrays, high-density PCIe GPUs

DELIVERY LIFECYCLE

From Workload Sizing to On-Site Validation

High-value AI hardware demands rigorous engineering discipline. Our phased deployment model protects your capital investment and ensures day-one operational stability.

STAGE 01

Workload Discovery & Sizing

We analyze your target models, dataset sizes, concurrency requirements, and budget constraints to calculate necessary GPU counts, memory bandwidth, and power draw.

STAGE 02

Architecture Design & BOM Formulation

Our infrastructure specialists generate an optimized, vendor-neutral Bill of Materials (BOM) specifying servers, GPUs, interconnects, optical cables, and power components.

STAGE 03

Authorized Technology Sourcing

Procuring 100% genuine hardware through verified national distributor channels with direct manufacturer warranties, formal tax invoices, and insured freight.

STAGE 04

Staging, Rack Mounting & Cabling

Physical rack installation, component burn-in, structured cabling dressing, PDU phase balancing, and clean data center power-on by certified technicians.

STAGE 05

Fabric & Driver Validation

Initialization and verification of hardware health, out-of-band management (BMC/IPMI), InfiniBand link integrity, and NVIDIA NCCL all-reduce bandwidth testing.

STAGE 06

Handover & Lifecycle Support

Comprehensive documentation handover, warranty registration, and tailored Annual Maintenance Contracts (AMC) with dedicated replacement parts logistics.

ENGINEERING SPECIFICATIONS

Technical Discovery Checklist for RFQ

Preparing to issue an inquiry or tender? These 8 critical technical parameters ensure our infrastructure team can return an exact, commercially viable hardware specification.

Parameter 01

Target Workloads & Frameworks

Specific frameworks (PyTorch, TensorFlow, vLLM, DeepSpeed) and precision requirements (FP8, FP16, BF16, FP64) guide GPU selection.
Critical
Parameter 02

Accelerator Architecture (HGX vs. PCIe)

Determines inter-GPU bandwidth needs. Large training models require NVLink HGX mesh; independent inference tasks often thrive on PCIe nodes.
Critical
Parameter 03

Host Processor & System Memory

Adequate host PCIe lanes prevent GPU starving. Minimum recommended host memory is typically 1.5× to 2× the aggregated GPU VRAM capacity.
High
Parameter 04

Inter-Node Interconnect Bandwidth

Single-node setups use standard networking; multi-node distributed training requires 100G/200G/400G InfiniBand or RoCE to avoid communication sync pauses.
Critical for Clusters
Parameter 05

Dataset Volume & Ingestion Speed

Calculates whether high-IOPS NVMe all-flash or hybrid tiered storage is necessary to keep GPU compute engines fully fed during training epochs.
High
Parameter 06

Data Center Power & Thermal Budget

Verifies available circuit breaker amperage, PDU capacity, and room air-conditioning (BTU/hr) to safely sustain 10kW to 35kW+ rack thermal loads.
Mandatory Facility Check
Parameter 07

Physical Enclosure Space & Location

Number of contiguous rack units (RU) available, floor load ratings for heavy server chassis, and delivery dock logistics at the destination site.
Operational
Parameter 08

Budget Parameters & Procurement Window

Allows formulation of phased rollouts or prioritized Bill of Materials aligned with corporate procurement cycles and capital allocation.
Commercial
FREQUENTLY ASKED QUESTIONS

Enterprise AI & HPC Infrastructure FAQ

Common questions from enterprise IT heads, engineering managers, and procurement committees regarding sizing, supply, and support.

Does Patel Galaxify Solutions supply complete AI server hardware or software development?

Patel Galaxify Solutions is an enterprise IT infrastructure supply, engineering, and deployment company. We supply physical GPU servers, storage arrays, networking fabric, and turnkey rack infrastructure, and provide on-site installation, commissioning, and maintenance. We do not build proprietary software applications or SaaS platforms; our core business is delivering and supporting the mission-critical hardware platform that powers your AI applications.

How do you determine whether we need SXM/HGX nodes or PCIe GPU servers?

The decision depends on model architecture and inter-GPU communication intensity. Distributed training of foundation models and large LLMs requires massive tensor sharing across GPUs, where NVIDIA HGX with NVLink (providing up to 900GB/s internal bandwidth) is essential. For model inferencing, computer vision, or fine-tuning smaller models, PCIe-based accelerators are substantially more modular, energy-efficient, and cost-effective.

What typical lead times should we anticipate for enterprise GPU hardware?

High-density enterprise GPU accelerators (such as H100, H200, and dense HGX platforms) have dynamic global supply cycles. Through our ₹45Cr+ annual procurement volume and established relationships with authorized national distributors, we track verified allocations and provide transparent, realistic delivery schedules for Indian enterprises, avoiding unverified promises.

Can Patel Galaxify Solutions deploy AI hardware at our third-party colocation data center?

Yes. We deploy infrastructure in enterprise data centers, corporate server rooms, and third-party colocation facilities across India (including Bengaluru, Mumbai, Delhi NCR, Hyderabad, Chennai, and tier-2 tech hubs). Our engineers handle structured unboxing, rail mounting, fiber dress cabling, and coordinate with data center facility teams for power turn-on.

What ongoing support and maintenance options do you provide for AI clusters?

We offer comprehensive and non-comprehensive Annual Maintenance Contracts (AMC) tailored to enterprise clusters. Support tiers include 8x5 Next Business Day (NBD) response and 24x7 Mission-Critical 4-hour SLA response, backed by staged buffer spare parts and on-call hardware escalation engineers across India.

How does Patel Galaxify Solutions ensure genuine hardware with valid warranty?

Every server, GPU card, storage controller, and switch supplied by Patel Galaxify Solutions is sourced strictly through authorized national distributor channels. All equipment ships with original factory packaging, verified OEM serial numbers, direct manufacturer warranty coverage, and formal GST tax invoices.
ENTERPRISE RFQ & QUOTATION

Ready to Size & Procure Your AI/HPC Cluster?

Send our technical infrastructure desk your target workloads, desired GPU specifications, or formal RFP. We return validated Bill of Materials (BOM), power/thermal sizing, and competitive commercial pricing.

Direct Phone / WhatsApp: +91 7023837035patelgalaxifysolutions@gmail.com