Your private AI.
Your building.
Your data.
Run Llama, Mistral, DeepSeek, or any open-weight LLM on hardware you own. No API bills. No data leaving your network. No vendor dependency. eRacks ships it pre-configured and ready on day one.
Six reasons serious organizations
stop renting and start owning
Cloud AI worked fine for experimentation. Now that AI is in your workflows, the economics and risks have shifted.
Data sovereignty
Your prompts, documents, and outputs never leave your infrastructure. Critical for HIPAA, GDPR, SOC 2, and attorney-client privilege.
Predictable cost
One hardware investment replaces unpredictable monthly API bills. At scale, on-premise is up to 18× cheaper per million tokens.
Zero-latency responses
No network hop, no rate limits, no throttling. Local inference is faster than cloud for interactive applications.
Full customization
Fine-tune on your domain data. Modify system prompts freely. Integrate directly with your internal tools — no API restrictions.
Air-gap capable
Works completely offline. Ideal for secure facilities, classified environments, or locations with restricted internet access.
No vendor lock-in
Switch models freely. Move from Llama to Mistral to Qwen in minutes. Your infrastructure is yours — not a subscription.
Which GPU for which models?
| GPU / VRAM | Model Size Range | Example Models | Tier |
|---|---|---|---|
| RTX 4090 — 24GB | 7B – 32B | Llama 3.3 8B, Qwen 2.5 Coder 32B, Phi-3 Medium, Mistral 7B | Entry |
| RTX 5090 — 32GB | 7B – 70B (Q4) | DeepSeek-R1 32B, Llama 3.3 70B (quantized), Qwen 2.5 72B | Entry+ |
| RTX 6000 Ada — 48GB | 30B – 70B (full) | Llama 3.3 70B (full), Qwen 2.5 72B, DeepSeek-R1 70B | Pro |
| 2× RTX 6000 Ada — 96GB | 70B – 180B | Llama 3 405B (quantized), large MoE models, multi-modal | Pro+ |
| 4× H100 — 320GB HBM | 70B – 405B (full) | Llama 3 405B, fine-tuning any 70B+, custom training runs | Research |
Purpose-built for every
AI workload and budget
The fastest path to a private AI assistant. Single GPU, desktop or 1U rackmount. Run 7B–32B models out of the box.
- Form factorDesktop or 1U
- GPURTX 4090 / 5090 (24–32GB)
- RAM64–128GB DDR5
- Storage2TB NVMe (model weights)
- Pre-installedOllama · Open WebUI · Ubuntu
The professional's choice for on-premise AI. 2U rackmount, Threadripper Pro, up to 512GB RAM, and up to 4 GPUs. Handles 70B models and RAG pipelines at full throughput.
- Form factor2U Rackmount
- CPUThreadripper Pro (up to 96-core)
- GPU1–4× RTX 6000 Ada / PRO 6000
- RAM256–512GB DDR5 ECC
- Storage2–16TB NVMe + ZFS option
- Pre-installedOllama · vLLM · Open WebUI · PyTorch
Turn your internal documents into a private, searchable AI brain. Pre-configured with a vector database, LangChain, and your choice of LLM.
- Form factor2U Rackmount
- GPU1–2× RTX 6000 Ada
- RAM256–512GB DDR5 ECC
- StorageHigh-density NVMe RAID
- Pre-installedQdrant · LangChain · LlamaIndex
Fine-tune your own models on your own data. 4U chassis with up to 8 GPUs, dual EPYC, and full ML training stack pre-installed.
- Form factor4U Rackmount
- CPUDual AMD EPYC
- GPU4–8× H100 / RTX PRO 6000
- RAM512GB–2TB DDR5 ECC
- Pre-installedPyTorch · cuDNN · Jupyter · W&B
Industries choosing on-premise AI
Contract & Document Analysis
Analyze contracts, flag liability clauses, and summarize case files — without sending a word to OpenAI.
HIPAA-Compliant AI
Clinical notes, patient intake, and records review on a server that never touches the public internet.
Private Financial Intelligence
Client data, portfolio analysis, and internal knowledge bases — fully contained inside your perimeter.
Private Code Assistant
Qwen 2.5 Coder and DeepSeek-R1 run locally as your team's code assistant. No IP ever leaves your network.
Air-Gapped Deployments
Fully offline AI for classified or restricted environments. No internet required, ever.
Model Fine-Tuning
Domain-specific model training on proprietary datasets. LoRA/QLoRA fine-tuning on your own hardware.
Local Image & Video AI
Stable Diffusion, video generation, and multimodal workflows running on dedicated hardware you own.
Private Campus AI
Student and faculty AI tools hosted entirely on-premise, without sending academic work to third parties.
What people ask before
buying their first AI server
Can I run ChatGPT-quality AI on my own server?
Yes. Open-weight models like Llama 4, Qwen 2.5, and DeepSeek-R1 match or exceed GPT-3.5 performance on most tasks — and approach GPT-4 on coding and reasoning benchmarks. A single RTX 4090 (24GB) comfortably runs 7B–32B models. The eRacks AILSA-PRO with RTX 6000 Ada handles 70B models at full precision.
What open-source LLMs can I run?
Any model available in GGUF or HuggingFace format: Llama 3/4, Mistral, Mixtral, Qwen 2.5, DeepSeek-R1, Phi-3, Gemma 2, Command-R, and hundreds more. Ollama, which we pre-install, lets you pull and run any compatible model with a single command. New models release weekly and you can run them immediately.
Is this HIPAA or GDPR compliant?
An on-premise AI server is the strongest available architecture for compliance. When inference runs locally, no PHI, PII, or sensitive data ever leaves your network. eRacks ships Ubuntu 24.04 LTS with no telemetry or proprietary software — clean, auditable infrastructure. You should still consult your compliance team, but the data-sovereignty question is definitively answered by keeping everything on-premise.
How much do I save vs. cloud API costs?
At high usage volumes, on-premise inference is up to 18× cheaper per million tokens than premium cloud APIs. A team sending 10 million tokens per day to GPT-4 might pay $15K–$30K per month. A one-time eRacks server at $12,995 pays for itself in 30–60 days — then runs for years.
Do I need IT staff to manage this?
Not necessarily. The AINSLEY-EDGE and AILSA-PRO ship with Ollama and Open WebUI pre-installed, so non-technical staff can use them via a browser interface from day one. We configure Ubuntu for stability and low maintenance. For larger deployments with vLLM or RAG pipelines, basic Linux familiarity helps — or we can provide setup consulting.
Can you pre-install a specific LLM for me?
Yes. Tell us which model you want running at first boot and we'll configure it. Just add a note to your quote request. We can also pre-load multiple models and configure Open WebUI with your branding and default settings.
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