Private LLM Deployment

Total Data Sovereignty with Self-Hosted Open-Source LLMs

For organizations handling regulated data (healthcare, finance, defense, enterprise legal), sending proprietary information to public AI cloud APIs is unacceptable. Quantum Bases specializes in private LLM deployment, bringing state-of-the-art open-source models directly into your private AWS, Azure, GCP, or bare-metal server environment. We leverage high-throughput inference engines like vLLM, TensorRT-LLM, and TGI to serve open-source models (such as Llama 3, DeepSeek-R1, and Mistral) at a fraction of commercial API costs while guaranteeing 100% data privacy. Additionally, we perform LoRA and QLoRA fine-tuning on your proprietary datasets to achieve domain-specific mastery.

5.0 · Clutch Verified · 200+ clients served
vLLM

Production-ready vLLM implementation.

Hugging Face

Production-ready Hugging Face implementation.

PyTorch

Production-ready PyTorch implementation.

Llama 3

Production-ready Llama 3 implementation.

Our Scope

What is included in Private LLM Deployment

Every engagement covers these core deliverables. No hidden add-ons, no scope creep surprises.

Private VPC Infrastructure Provisioning (AWS EC2 GPU, GCP Cloud Run, Azure ML)

SLA-backed engineering implementation of private vpc infrastructure provisioning (aws ec2 gpu, gcp cloud run, azure ml) tailored to your system architecture.

High-Performance Inference Engine Setup (vLLM & TensorRT-LLM)

SLA-backed engineering implementation of high-performance inference engine setup (vllm & tensorrt-llm) tailored to your system architecture.

Model Fine-Tuning (LoRA, QLoRA, SFT, DPO) on Domain Data

SLA-backed engineering implementation of model fine-tuning (lora, qlora, sft, dpo) on domain data tailored to your system architecture.

Model Quantization (AWQ, GGUF, FP8) for Reduced GPU Memory Footprint

SLA-backed engineering implementation of model quantization (awq, gguf, fp8) for reduced gpu memory footprint tailored to your system architecture.

Air-Gapped & On-Premise GPU Server Deployment

SLA-backed engineering implementation of air-gapped & on-premise gpu server deployment tailored to your system architecture.

Custom OpenAI-Compatible API Server Gateway

SLA-backed engineering implementation of custom openai-compatible api server gateway tailored to your system architecture.

How We Work

From kickoff to delivery

A repeatable, transparent process we have refined across 200+ projects. No guesswork on your side.

NDA signed before kickoff
Weekly progress updates
Dedicated project manager
Start the process
1

Model Selection

2

Dataset Preparation

3

Fine-Tuning & Quantization

4

VPC Serving Deployment

Get Started

Ready to build your Private LLM Deployment project?

A free 30-minute call. We review your requirements, identify risks early, and give you an honest assessment of what it takes to ship this right.

No commitment required
Response within 24 hours
Fixed-price or milestone billing
NDA signed before any discussion
ISO 27001-aligned security practices
5.0 rated on Clutch & Top Rated on Upwork

Book a Free Strategy Call

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Key Operational Challenges

What We Solve in Private LLM Deployment

Challenge #1

Strict regulatory requirements prevent using public cloud APIs like OpenAI or Claude.

Production Solution

Fully air-gapped or private VPC model hosting with zero external internet telemetry.

Challenge #2

Unpredictable public API pricing scaling exponentially with high token volumes.

Production Solution

Fixed infrastructure cost model using self-hosted GPU instances with high token throughput.

Challenge #3

Base LLMs lack specialized domain knowledge for industry jargon and internal specs.

Production Solution

Custom LoRA/QLoRA fine-tuning on proprietary enterprise documentation and codebases.

Frequently Asked Questions

Expert Guidance on Private LLM Deployment

Is a private LLM as smart as GPT-4o?

Fine-tuned models like Llama 3 70B or DeepSeek-R1 often match or exceed GPT-4 performance in specific specialized enterprise domain tasks.

What GPU infrastructure is required?

We optimize models using quantization (FP8/INT4), allowing high-speed serving even on budget single or dual GPU setups.

SLA-Backed Execution

Ready to deploy production-grade Private LLM Deployment?

Talk directly with our senior software architects. No sales fluff, just clear engineering blueprints, cost estimates, and rapid execution.

Plan Your Private LLM DeploymentContact Engineering Team