Private AI Inference That Never Leaves Your Network
Deploy on-premises, air-gapped AI inference infrastructure for HIPAA, CMMC, ITAR, and data sovereignty compliance. Run state-of-the-art LLMs and custom AI workloads entirely in-house with zero-trust architecture, no vendor lock-in, and no cloud dependencies.
Trusted Since 2002 • BBB Accredited Since 2003 • 2,500+ Clients Served
Run AI Without Compromising Your Data
When cloud AI providers can't meet your compliance, security, or sovereignty requirements, on-premises inference gives you complete control.
100% Data Sovereignty
Your data never leaves your network. No third-party cloud providers, no external APIs, no shared tenancy. Every inference request runs locally on infrastructure you control.
Compliance-First Architecture
Purpose-built for HIPAA, CMMC 2.0, ITAR, GDPR, and NIST 800-171 compliance with zero-trust network architecture, role-based access controls, and comprehensive audit logging.
Production-Grade Performance
Optimized inference pipelines delivering cloud-competitive latency and throughput with quantization, continuous batching, and tensor parallelism.
Predictable Cost Structure
Eliminate per-token pricing and API usage spikes. Fixed infrastructure costs with unlimited usage typically break even within 6-12 months for high-volume workloads.
Why Cloud AI Doesn't Work for Everyone
Cloud-based AI services offer convenience but come with deal-breaking constraints for organizations in healthcare, defense, financial services, and regulated industries.
Sensitive data cannot leave your network. HIPAA protected health information, ITAR-controlled technical data, and financial records subject to Gramm-Leach-Bliley all carry strict data residency requirements. Sending this data to third-party cloud AI providers violates compliance frameworks.
Compliance requirements demand infrastructure control. CMMC 2.0 requires FedRAMP Moderate or on-premises hosting for CUI. NIST 800-171 mandates security controls not always available through cloud AI providers. ITAR prohibits foreign national access to technical data, creating audit challenges with cloud services.
Vendor lock-in limits flexibility. Cloud AI providers change pricing, deprecate APIs, and modify policies without notice. When your core business logic depends on external AI APIs, you're building on sand.
Petronella Technology Group solves these challenges by deploying private AI inference infrastructure with complete control -- on-premises and air-gapped environments running state-of-the-art models with zero external dependencies.
Complete Private AI Inference Solutions
End-to-end infrastructure design, deployment, optimization, and support for on-premises AI workloads.
On-Premises LLM Deployment & Hosting
We deploy production-grade LLM inference running entirely on your premises. Choose from open-source models like Llama 3, Mistral, Mixtral, CodeLlama, and Qwen, or host fine-tuned custom models using vLLM, TensorRT-LLM, and llama.cpp.
Deployments handle 7B to 405B parameter models with quantization to balance quality and hardware requirements. OpenAI-compatible API endpoints let existing applications work without code changes.
Air-Gapped AI Environments for Classified Data
For classified information or CUI, we design completely air-gapped AI inference environments with zero internet connectivity and physically isolated network segments. These systems include offline model registries, local dependency mirrors, and internal container repositories with documented supply chains. Critical for defense contractors with ITAR data, healthcare organizations processing PHI, and government agencies.
Compliance-Ready Infrastructure (HIPAA, CMMC, ITAR, GDPR)
Every deployment is architected with compliance as a first-class concern. HIPAA implementations include FIPS 140-2 encryption, TLS 1.3, PHI audit logging, and role-based access controls. CMMC 2.0 deployments implement all 110+ NIST 800-171 controls with network segmentation, MFA, System Security Plans, and audit evidence packages.
ITAR compliance prevents foreign national access with citizenship verification and audit trails. GDPR includes data minimization, privacy by design, and EU data residency controls.
Zero-Trust Architecture & Confidential Computing
Zero-trust architecture with continuous authentication, microsegmentation, least-privilege access, and comprehensive logging. Network segmentation separates inference APIs, model storage, and admin interfaces with firewall rules permitting only documented data flows.
For highest-security workloads, we implement confidential computing using Trusted Execution Environments (Intel SGX, AMD SEV) where inference runs in hardware-encrypted memory enclaves isolated from the OS.
Inference Optimization & Performance Tuning
We optimize every layer of the inference stack. Quantization (FP16 to INT8/INT4) cuts memory requirements 50-75% without significant accuracy loss. Continuous batching improves GPU utilization. Typical results: 2-5x throughput improvements, 30-50% latency reductions, and 40-60% infrastructure cost savings versus naive deployments.
Your Path to Private AI Inference
From requirements gathering through production deployment and ongoing support.
Requirements Assessment & Architecture Design
Detailed discovery of your use case, compliance requirements, and existing infrastructure. We produce a requirements document and complete architecture design including GPU specifications, network security zones, storage, authentication, monitoring, hardware BOMs, and cost estimates.
Procurement, Provisioning & AI Stack Deployment
We handle hardware procurement, GPU server racking, network configuration, storage setup, and security hardening. Then deploy the full AI stack: NVIDIA drivers, CUDA, Kubernetes with GPU operator, inference frameworks, API gateway, model registry, and OpenAI-compatible endpoints.
Optimization, Security Hardening & Compliance
Performance benchmarking with realistic workloads, batch size tuning, and KV cache optimization. Security hardening with CIS benchmarks, least-privilege accounts, encrypted storage, and intrusion detection. Compliance documentation including System Security Plans, data flow diagrams, and compliance matrices.
Production Cutover & Knowledge Transfer
Coordinated production cutover with parallel validation and documented rollback procedures. Knowledge transfer includes training, runbooks, troubleshooting guides, and 30-90 days of hypercare support.
Ongoing Support & Continuous Improvement
Managed service agreements with 24/7 monitoring, security patch management, model updates, capacity planning, quarterly performance reviews, and compliance audit support with SLAs for uptime and response times.
The Complete AI Infrastructure Partner
Deep security expertise, GPU infrastructure experience, and AI engineering capabilities -- all in one team.
20+ Years of Compliance & Security Infrastructure
Since 2002, we've designed hundreds of HIPAA-compliant systems, CMMC-ready environments for defense contractors, and SOC 2 certified platforms. Through our partner network, our engagements have access to professionals holding CISSP, CISM, CEH, and Security+ certifications, and we have guided organizations through HITRUST, FedRAMP, PCI-DSS, and SOC 2 audits.
GPU Infrastructure & AI Engineering Expertise
Experience spanning NVIDIA datacenter GPU deployments (A100, H100, L40S), AMD Instinct accelerators, multi-node clusters with InfiniBand, and liquid-cooled GPU pods. Our AI engineers understand model architectures, quantization, inference optimization, and the full MLOps lifecycle -- ensuring your private infrastructure delivers the performance your applications need.
Local to Raleigh • Proven Track Record
Headquartered in Raleigh, NC, serving the Research Triangle with on-site support and deploying infrastructure nationally. Over 2,500 clients served since 2002, from small medical practices to Fortune 500 companies. BBB Accredited with an A+ rating since 2003. Client retention exceeds 90%.
Free consultation • No obligation • Same-day response
Secure AI Inference FAQ
Frequently asked questions about on-premises AI deployment, compliance, and private inference infrastructure.
How does on-premises AI inference compare to cloud AI services in cost?
Cloud AI charges per token, scaling linearly with usage. On-premises infrastructure has higher upfront costs but fixed operations. Break-even typically occurs at 500K-2M tokens/day, around 6-10 months, with $10K-$25K monthly savings thereafter. Once hardware is paid for, 10x more inferences cost the same.
Can private AI inference match cloud provider performance?
Yes. Optimized on-premises inference typically delivers equal or better performance. Cloud services add 50-150ms network latency and multi-tenant contention. On-premises deployments achieve 30-80ms end-to-end latency for 70B parameter models with dedicated resources.
What hardware is required for on-premises LLM inference?
Requirements depend on model size. Small models (7B) run on single GPUs like RTX 4090 or L40S. Medium models (13B-34B) need A100-class GPUs. Large models (70B+) require 2-8 GPU setups. Quantization dramatically reduces requirements -- a 70B model needs 140GB VRAM in FP16 but only 35-40GB in INT4. Entry-level deployments start around $25,000; production clusters range $100K-$500K.
How long does deployment take?
Typically 4-12 weeks depending on complexity and hardware procurement lead times. Projects leveraging existing hardware can compress to 3-4 weeks. Air-gapped deployments add 2-4 weeks for offline staging and compliance documentation.
What models can we run on private infrastructure?
Any open-source or custom model: Llama 3 (8B-405B), Mistral/Mixtral, Qwen 2.5, DeepSeek, Gemma 2, plus specialized models for code (CodeLlama, StarCoder), embeddings (BGE, E5), and multimodal tasks (LLaVA). We also host custom fine-tuned models. The only models you cannot run privately are proprietary closed-source models like GPT-4 or Claude.
Is HIPAA compliance possible with on-premises AI inference?
Yes -- on-premises inference is often the only viable path to HIPAA compliance for AI. We implement FIPS 140-2 encryption, TLS 1.3, PHI audit logging, role-based access controls, and automatic session timeouts. Infrastructure deploys within your existing HIPAA-compliant network zones. We provide documentation and sign Business Associate Agreements.
Ready to Deploy Private AI Inference?
Take control of your AI infrastructure with secure, compliant, on-premises inference that keeps your data sovereign and your costs predictable. Schedule a consultation to discuss your requirements.
Trusted Since 2002 • BBB Accredited Since 2003 • 2,500+ Clients Served • Raleigh, NC