AI Infrastructure for Every Enterprise Sector

Key Challenges

• GPU allocation constraints during peak demand periods
• Balancing training throughput vs. inference latency requirements
• Managing VRAM limitations for ever-larger model sizes
• Cost of cloud GPU compute for iterative research

Recommended Hardware

• NVIDIA H100/H200 SXM5 8-GPU clusters for foundation model training
• RTX PRO 6000 workstations for researcher desktops
• RTX 5090 workstations for ML engineers and developers
• Parallel file storage (Lustre/WekaFS) for training datasets

Example configurations

• AI startup training lab: 4-node H100 cluster + NVMe storage
• Research lab: 8× RTX PRO 6000 workstations + shared NAS
• Production inference: Multi-GPU rack servers with NVSwitch

Why Nexus Compute

We quote H100 and H200 against what distribution can actually confirm on the day, and tell you plainly when a part is constrained rather than quoting a date that will move.

Key Challenges

• HIPAA compliance requirements for data and hardware
• High-resolution medical imaging data storage demands
• AI-accelerated radiology and pathology workflows
• Long hardware lifecycle requirements with FDA compliance

Recommended Hardware

• Dell PowerEdge servers with FIPS 140-2 validated self-encrypting drives
• Synology enterprise NAS for PACS/DICOM imaging storage
• NVIDIA RTX GPUs for medical imaging and pathology AI
• Fortinet appliances for network segmentation and audit logging

Example configurations

• PACS storage: Synology HD6500 with 500TB capacity + hot spare
• Pathology AI lab: 4× RTX PRO 6000 workstations
• Hospital network refresh: Cisco Catalyst + Fortinet NGFW

Why Nexus Compute

We accept purchase orders on the capital budget cycles healthcare procurement runs on, and supply the manufacturer warranty terms, FIPS validation certificate numbers, serial numbers and country of manufacture your compliance team needs to do its own assessment. What HIPAA does and does not ask of hardware is set out in our guide to HIPAA-compliant workstations.

Key Challenges

• Limited capital budgets with slow purchase order cycles
• Multi-department hardware sharing and allocation
• Need for diverse compute for varied research disciplines
• Grant-funded procurement with tight timeline constraints

Recommended Hardware

• Multi-GPU research servers for shared compute clusters
• RTX 5090 workstations for graduate students and researchers
• EPYC-based CPU servers for bioinformatics and simulation
• High-capacity NAS for research data management

Example configurations

• University HPC cluster: 16-node EPYC + 4-node GPU expansion
• Research center: 24× RTX 5090 workstations + 200TB NAS
• CS department: 8-GPU H100 cluster for deep learning lab

Why Nexus Compute

We accept institutional purchase orders and work with university purchasing offices on their own paperwork. We are not currently on a cooperative purchasing vehicle, so ask us early if your institution requires one.

Key Challenges

• Real-time ray tracing for photorealistic architectural visualization
• BIM (Building Information Modeling) dataset management
• VR walkthroughs requiring low-latency GPU compute
• Rendering farm scalability for deadline-driven workflows

Recommended Hardware

• NVIDIA RTX PRO 6000 workstations for Revit and 3ds Max
• RTX 5090 workstations for real-time visualization and Enscape
• Render farm servers with high GPU density
• Synology NAS for BIM project file storage

Example configurations

• Architecture firm: 12× RTX PRO 6000 workstations + NAS
• Visualization studio: 24-GPU render farm + 200TB storage
• BIM management: Synology SA3610 + 10GbE network upgrade

Why Nexus Compute

We quote against the ISV certification list you need (Autodesk, Enscape, Lumion) and can specify systems with validated driver stacks for professional AEC applications.

Key Challenges

• ISV-certified workstations for ANSYS, SolidWorks, CATIA
• Large assembly CAD files requiring massive RAM
• FEA/CFD simulation demanding multi-core EPYC platforms
• Secure CAD data storage and collaboration

Recommended Hardware

• RTX PRO 6000 workstations with ANSYS/SolidWorks certification
• AMD Threadripper PRO workstations for FEA simulation
• EPYC rack servers for CFD cluster compute nodes
• High-IOPS NAS for CAD file libraries and PDM vaults

Example configurations

• Aerospace firm: 20× Threadripper PRO workstations (CATIA)
• Manufacturing: EPYC CFD cluster + NVMe storage tier
• R&D lab: RTX PRO 6000 workstations + SolarWinds PDM

Why Nexus Compute

We validate ISV certification compatibility before quoting and can pre-install certified driver stacks for ANSYS, SolidWorks, CATIA, NX, and other leading engineering applications.

Key Challenges

• 8K/16K video editing and real-time effects processing
• AI upscaling and denoising for post-production workflows
• Massive media asset storage and archive management
• Render farm scalability for VFX and animation deadlines

Recommended Hardware

• RTX PRO 6000 workstations for editorial and compositing
• RTX 5090 workstations for AI-enhanced post-production
• QNAP high-density NAS for media asset management
• GPU render farm servers for VFX and 3D animation

Example configurations

• VFX studio: 30× RTX PRO 6000 + 1PB Quantum storage
• Broadcast network: 8-GPU render nodes + 500TB NAS
• Animation studio: 50-seat DCC workstation refresh

Why Nexus Compute

Media productions run on deadlines. We confirm a delivery date with distribution before you commit to it rather than after, and can configure rental/temporary hardware expansions for peak projects.

Key Challenges

• Low-latency compute for algorithmic trading systems
• Risk modeling and Monte Carlo simulation at scale
• Regulatory compliance (SOX, MiFID II) for hardware
• Fraud detection AI requiring real-time inference

Recommended Hardware

• Low-latency CPU servers for HFT and market data
• GPU clusters for quantitative risk modeling
• Enterprise NAS with immutable audit trail storage
• Fortinet and Cisco security for regulatory compliance

Example configurations

• Hedge fund: Latency-optimized trading servers + 25GbE
• Bank: Risk modeling cluster + 8× GPU servers
• Insurance: Fraud AI inference servers + secure storage

Why Nexus Compute

We understand financial services procurement governance, vendor approval processes, and security documentation requirements. All hardware delivered with full chain-of-custody documentation.

Key Challenges

• FISMA and FedRAMP compliance requirements
• ITAR-controlled hardware for defense applications
• Buy American Act (BAA) procurement compliance
• Classified network air-gap and security requirements

Recommended Hardware

• TAA-compliant server and workstation hardware
• FIPS 140-2 validated storage and security hardware
• Dell and HPE federal government catalog systems
• Cisco federal networking (STIG-compliant configurations)

Example configurations

• Federal agency: TAA-compliant server refresh (200 units)
• State government: Dell EMC VxRail HCI deployment
• Defense contractor: Air-gap secure workstation fleet

Why Nexus Compute

We accept purchase orders and work to your contracting office's documentation requirements. We are not on a GSA Schedule, and we will tell you the country of manufacture for any line so your team can assess TAA applicability themselves.

Key Challenges

• Factory floor AI for quality inspection and defect detection
• IIoT edge computing for real-time process control
• Digital twin simulations for product design
• Supply chain visibility systems requiring robust infrastructure

Recommended Hardware

• Ruggedized edge servers for factory environments
• GPU workstations for digital twin and simulation
• Cisco industrial networking (IE series)
• High-availability storage for manufacturing data

Example configurations

• Auto manufacturer: Computer vision QC inspection (GPU edge)
• Electronics: Digital twin cluster + 100TB dataset storage
• Food processing: IIoT edge compute + industrial networking

Why Nexus Compute

We source ruggedized, industrial-grade hardware rated for demanding factory environments and understand the extended lifecycle requirements of manufacturing OT systems.

Key Challenges

• Balancing cloud costs vs. on-premises GPU compute
• AI feature development requiring developer GPU workstations
• Scalable inference infrastructure for embedded AI features
• Data infrastructure for AI model training pipelines

Recommended Hardware

• RTX 5090 developer workstations for AI feature teams
• On-premises GPU inference servers to reduce cloud spend
• High-performance Kubernetes worker nodes
• NVMe storage for ML pipelines and model registries

Example configurations

• AI startup: 12× RTX 5090 dev workstations + GPU server
• SaaS company: On-prem inference fleet (TCO vs. cloud)
• ML platform: H100 training cluster + WekaFS storage

Why Nexus Compute

We help SaaS companies build the TCO case for on-premises GPU infrastructure vs. cloud, using your own utilization figures and current cloud rates rather than a headline percentage.