How do private AI models compare to cloud AI services like ChatGPT?

Open-source models have reached performance parity with commercial cloud APIs for most business applications. Fine-tuned private models often outperform generic cloud services for domain-specific tasks.

What hardware is needed for private AI deployment?

Requirements depend on model size and concurrent users. Small models run on a single GPU with 24GB VRAM. Enterprise deployments serving hundreds of users require multi-GPU servers.

Can private AI work on an air-gapped network?

Yes. Once deployed, no internet connectivity is required. The system operates entirely offline. Model updates are delivered via physical media following cross-domain transfer procedures.

Is private AI compliant with CMMC Level 2?

Private AI is the most straightforward path to CMMC-compliant AI. By keeping all processing within your existing CMMC boundary, you avoid third-party risk complications of cloud AI services.

How much does private AI infrastructure cost?

Hardware costs range from a few thousand dollars for a single GPU workstation to six figures for enterprise multi-GPU clusters. Total cost of ownership is typically lower than cloud AI API spending for moderate to heavy usage.

Can we start small and scale up later?

Yes. Most organizations start with a single GPU server for a specific use case, then expand. The architecture is designed for horizontal scaling as needs grow.

Which AI models work best for private deployment?

The best model depends on your use case. Meta Llama 3 excels at general tasks. Mistral models offer strong performance in smaller form factors. We benchmark multiple candidates against your specific data.

Do you manage the private AI system after deployment?

Yes. We offer managed services including monitoring, model updates, performance optimization, security patching, and user support via remote management or on-site support.

What is private AI deployment?

Private AI deployment means running AI models on your own infrastructure — on-premise servers, private cloud, or dedicated hosted hardware — instead of sending data to cloud AI APIs. Your data, prompts, and model outputs never leave your network, ensuring complete data sovereignty and regulatory compliance.

What are the benefits of private AI over cloud AI?

Private AI provides complete data control (no data shared with AI providers), regulatory compliance (HIPAA, CMMC, ITAR), predictable costs (no per-token API charges), lower latency, unlimited usage, and protection of trade secrets. Organizations save 40-70% versus cloud GPU costs for sustained workloads.

What hardware do I need for private AI?

Requirements depend on your use case. For inference, a single NVIDIA RTX 4090 or A6000 handles most 7-70B parameter models. For training or large models, multi-GPU servers with H100 or A100 GPUs are needed. We provide custom hardware recommendations based on your model sizes, throughput needs, and budget.

Can private AI match the quality of ChatGPT or Claude?

Modern open-source models like Llama 3, Mistral, and Mixtral achieve comparable quality to commercial models for most enterprise tasks, especially when fine-tuned on your domain data. Combined with RAG, private AI can outperform generic cloud models because it has access to your proprietary knowledge.

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Private AI Solutions

Private AI SolutionsSelf-Hosted LLMs for Regulated Industries

Private AI runs entirely on infrastructure you own. No data leaves your security perimeter. CMMC, HIPAA, and SOC 2 compliance controls built in from architecture through production.

CMMC Registered Practitioner Org|BBB A+ Since 2003|23+ Years Experience

Schedule a Private AI Consultation Call 919-601-1601

Advantages

Why Private AI

Complete data sovereignty with open-source models that match commercial cloud APIs in quality.

Complete Data Sovereignty

Every prompt, document, and response stays within your security perimeter. No external API calls, no cloud processing, no third-party data retention.

Air-Gapped Deployment

For defense and critical infrastructure, we deploy AI on air-gapped networks with zero internet connectivity. Models run entirely offline after initial setup.

CMMC L2 Compliant

Access controls, audit logging, encryption at rest and in transit, incident response procedures built into the architecture. Aligned with CMMC requirements.

No Vendor Lock-In

Open-source models on hardware you control. Upgrade models on your schedule. No proprietary formats, no SaaS contracts, no deprecation surprises.

60-80% Cost Savings

Fixed infrastructure cost eliminates per-query API charges. Self-hosted LLM delivers dramatic savings over cloud AI for moderate-to-heavy usage patterns.

Full Customization

Fine-tune on your data. Add RAG for document retrieval. Integrate with internal systems. Complete control over model behavior and architecture.

The Transformation

Cloud AI vs. Private AI

Cloud AI

Data on Third-Party Servers

Prompts processed by vendors you cannot audit. Retention policies change without notice.

Compliance Gaps

Most cloud AI lacks CMMC, FedRAMP, ITAR certification. Creates third-party risk auditors flag.

Per-Token Pricing Trap

Costs scale linearly. $30/user/month becomes $360K/year for 500 users.

Private AI

Data Never Leaves

100% on-premise processing. Zero external data transmission. You control all retention policies.

Built-In Compliance

CMMC, HIPAA, SOC 2, NIST controls mapped to your specific framework from deployment day.

Fixed Cost, Unlimited Use

One-time build investment. Unlimited users. Cost per query drops as adoption grows.

Infrastructure

Our Private AI Fleet

GPU Hardware

288GB VRAM GPU clusters (3x RTX PRO 6000)
DGX Spark platforms for enterprise workloads
RTX 5090 workstations for development and testing

Models Available

Llama 3 (8B-405B), Mistral, Mixtral, Qwen 2.5
Specialized models for code, medical, legal, financial
Custom fine-tuned models on your proprietary data

FAQ

Frequently Asked Questions

What is a private AI solution?

A private AI solution is a large language model deployed on infrastructure you own or control. No data touches external servers. You maintain complete ownership and control over all AI interactions, model weights, and inference logs.

Do open-source models match cloud AI quality?

Yes. Models like Llama 3, Mistral, and Qwen 2.5 deliver accuracy comparable to proprietary cloud APIs on most business tasks. Fine-tuned on your data, they consistently outperform generic cloud models on domain-specific work.

Can private AI be air-gapped?

Yes. We deploy on air-gapped networks with zero internet connectivity for defense, intelligence, and critical infrastructure clients. Models run entirely offline after initial deployment.

What compliance frameworks are supported?

CMMC Level 2, HIPAA, SOC 2 Type II, NIST 800-171, ITAR, PCI DSS. Controls are mapped to your specific framework and built into the architecture from day one.

How much does private AI cost vs. cloud AI?

Private AI involves a one-time deployment cost with unlimited users and zero per-query fees. Organizations with 50+ users or high-volume workloads typically save 60-80% compared to cloud AI within the first year.

Related Services

Ready for Private AI?

Not sure where to start? Assess your AI readiness first. Complete data sovereignty, compliance controls, and open-source AI that matches cloud quality at a fraction of the cost.

Schedule a Consultation Call 919-601-1601

Private AI Solutions | Self-Hosted LLM & Private LLM for...