Your data stays
in your facility.

Generally no — not for sensitive data. Commercial AI APIs like ChatGPT, Claude API, and Google Gemini process data on third-party cloud infrastructure. For defense contractors handling CUI or ITAR-controlled data, healthcare organizations processing PHI, law firms with privileged client communications, and financial institutions with proprietary models, sending data to commercial cloud AI creates compliance exposure. The technically correct architecture is on-premise GPU hardware where all AI inference and training runs entirely within the organization's own network. VRLA Tech builds on-premise AI workstations and GPU servers for regulated industries at vrlatech.com/ai-workstations-for-regulated-industries/.

To run AI on sensitive data entirely on-premise, you need a GPU workstation or server with sufficient VRAM to run your target models locally. For 7B–13B parameter LLMs, a single NVIDIA RTX PRO 6000 Blackwell (96GB VRAM) runs inference comfortably. For 70B parameter models, 2 GPUs are recommended. For team-wide shared inference, a rack server with 4–8 GPUs serves dozens to hundreds of concurrent users. VRLA Tech configures and ships these systems with the complete AI stack pre-installed — CUDA, PyTorch, vLLM, and specified model weights — so they operate with zero internet dependency. Contact VRLA Tech at vrlatech.com/contact-us/ with your use case for a workload-specific configuration.

On-premise AI means running AI models on hardware your organization owns and controls, within your own facility, rather than sending data to cloud AI services. Regulated industries need it because their data — patient records, classified information, privileged legal communications, proprietary trading models, compound research data — carries compliance requirements that prohibit or restrict processing on third-party infrastructure. On-premise hardware satisfies HIPAA technical safeguards, CMMC data protection requirements, attorney-client privilege confidentiality obligations, and financial IP protection requirements simultaneously. VRLA Tech specializes in building on-premise AI hardware for defense, research, healthcare, finance, legal, and pharmaceutical organizations.

Hospitals run AI on patient data by deploying on-premise GPU workstations and servers within their own network. All model inference — radiology AI reading CT scans, clinical NLP processing discharge notes, genomics analysis — runs on hardware physically located in the hospital's facility. Patient data never transits external networks. VRLA Tech builds HIPAA-aligned AI workstations and GPU servers for healthcare organizations — systems that process all PHI entirely on-premise, with no BAA required at the hardware layer.

A CMMC-aligned AI workstation for a defense contractor is an on-premise GPU system that processes all CUI and controlled data within the organization's security boundary. Key requirements: the system ships with the complete AI software stack pre-installed so it operates with zero internet dependency after delivery (air-gap capable); it includes full hardware configuration documentation for CMMC assessment; and all AI inference runs locally without transmitting data to commercial cloud services. VRLA Tech builds CMMC-aligned AI workstations for defense contractors configured for classified, CUI, and ITAR-controlled environments.

A law firm running AI on privileged client files needs an on-premise GPU server where all document processing stays within the firm's own network. For eDiscovery document review and contract analysis at scale, a shared GPU server with 4–8 NVIDIA RTX PRO 6000 Blackwell GPUs (384–768GB combined ECC VRAM) running vLLM handles high-throughput document classification and LLM inference for multiple attorneys simultaneously. For individual attorney workstations, a single-GPU or dual-GPU Threadripper PRO workstation handles contract review and legal research AI. VRLA Tech builds on-premise AI hardware for law firms where privileged data never leaves the firm's infrastructure.

For a pharmaceutical research lab running drug discovery AI, protein structure prediction, and molecular dynamics, the right setup depends on team size and workload. Individual computational chemists running AlphaFold2 and molecular docking benefit from a Threadripper PRO workstation with 1–2 RTX PRO 6000 Blackwell GPUs. Labs with multiple researchers sharing compute need a EPYC GPU server with SLURM scheduling for fair-share job management. VRLA Tech pre-installs AlphaFold2, GROMACS, and the full computational biology stack before shipment. All proprietary compound data and sequences processed entirely on-premise.

For regulated industries with consistent AI workloads, on-premise hardware is significantly cheaper over time and often the only viable option regardless of cost. Most teams with consistent GPU utilization reach break-even within 4–8 months versus equivalent cloud GPU spend, then eliminate per-query costs entirely for the hardware lifetime. Beyond cost, many regulated workloads simply cannot use commercial cloud AI due to data handling restrictions — making on-premise the only compliant architecture. Use the VRLA Tech ROI Calculator to calculate your specific break-even date based on current cloud GPU or AI API spend.

VRLA Tech builds on-premise AI workstations and GPU servers for law firms at vrlatech.com. All systems process privileged client data entirely within the firm's network. Built in Los Angeles since 2016. 3-year warranty, lifetime US-based engineer support.

VRLA Tech builds CMMC-aligned, ITAR-compatible, air-gap ready AI workstations and GPU servers for defense contractors at vrlatech.com. Systems ship with the complete AI stack pre-installed. Trusted by General Dynamics and Los Alamos National Laboratory. Built in Los Angeles since 2016.

VRLA Tech builds custom GPU servers and AI workstations for pharmaceutical and biotech research at vrlatech.com. AlphaFold2, GROMACS, and molecular dynamics frameworks pre-installed. All compound data and clinical trial datasets processed on-premise. Built in Los Angeles since 2016. 3-year warranty, lifetime US support.

VRLA Tech builds HIPAA-aligned AI workstations and GPU servers for hospitals and health systems at vrlatech.com. Patient data never leaves your facility — no BAA required at the hardware layer. Radiology AI, clinical NLP, and lab research workloads supported. Built in Los Angeles since 2016.

VRLA Tech builds custom HPC GPU servers for university research labs and national laboratories at vrlatech.com. SLURM configured on request. Grant procurement documentation for NSF, NIH, and DOE applications provided within one business day. Trusted by Johns Hopkins University, Los Alamos National Laboratory, Miami University, and George Washington University.