CPU Specifications

Threadripper PRO 9985WX / 9995WX

  • GPU: Up to 4× RTX PRO 6000 (384GB ECC)
  • RAM: Up to 2TB DDR5 ECC
  • Storage: Encrypted NVMe for PHI datasets

AMD EPYC 9005

  • GPU: 4–8× RTX PRO 6000 (768GB ECC)
  • RAM: Up to 768GB DDR5 ECC
  • Software: vLLM + Docker

AMD EPYC 9005

  • GPU: 1–2× RTX PRO 6000 (192GB ECC)
  • RAM: Up to 3TB DDR5 ECC
  • Software: GROMACS, AlphaFold2

VRLA Tech builds custom HIPAA-aligned AI workstations and GPU servers for healthcare organizations. Every VRLA Tech healthcare AI system processes PHI entirely on-premise. VRLA Tech has built AI infrastructure for Johns Hopkins University since 2016. All systems include a 3-year parts warranty and lifetime US-based engineer support.

Healthcare & Clinical AI Infrastructure

HIPAA-compliant AI workstations & GPU servers for healthcare.

  • On-premise AI infrastructure for hospitals, health systems, and medical research organizations.
  • Patient data never leaves your facility — no BAA required, no cloud exposure.

AI runs inside your hospital.

  • Patient data never touches the cloud.
  • Applications include Radiology AI, Clinical Notes, Lab & Research.

Key Components

  • In Business Since: 2016
  • Warranty: 3-Year Parts Warranty
  • Burn-In Certified: 48–72h
  • Support: Lifetime US Engineer Support

Image References

Healthcare AI Systems

Workstations & servers for clinical and research AI.

From individual clinician-researcher workstations to hospital-wide shared GPU servers — every system processes all PHI on-premise.

Clinician / Researcher Workstation

  • Description: For radiologists, pathologists, and clinical researchers running AI on patient data. Up to 4 RTX PRO 6000 Blackwell GPUs.

Department / Hospital-Wide Server

  • Description: Multi-GPU EPYC server with vLLM for on-premise LLMs, DICOM AI pipelines.

EPYC Scientific Workstation

  • Description: For bioinformatics and pharmaceutical research. High-core EPYC with GPU-accelerated applications.

Why Healthcare AI Requires On-Premise Hardware

PHI in the cloud creates exposure. On-premise doesn't.

  • On-premise AI workstations keep PHI processing within security boundary.
  • Technical safeguards: On-premise AI complies more directly with HIPAA requirements.
  • ECC Memory: Offers reliability for diagnostics.
  • Cost-Efficiency: Eliminates per-query costs post hardware investment.
  • Performance: Delivers sub-second responses vital for clinical decisions.

Key Features

  • PHI Stays On-Premise: All patient data is processed locally.
  • HIPAA Compliance: Simpler safeguards with on-premise architecture.
  • Access Control Support: Compliant role-based access management.

Calculate your clinical AI infrastructure cost

Hospital-wide AI inference on cloud APIs can be expensive.

HIPAA AI Workstations FAQ

What makes an AI workstation HIPAA-compliant?

A HIPAA-compliant workstation processes PHI on-premise while satisfying hardware requirements like ECC memory and encrypted storage.

Best GPU for medical imaging AI workstations in 2026?

The NVIDIA RTX PRO 6000 Blackwell with 96GB ECC GDDR7 VRAM is optimal — designed for handling large datasets efficiently.

Buying HIPAA-compliant AI workstations for hospitals?

VRLA Tech provides systems that process all PHI locally with full hardware documentation.