Sovereign Infrastructure

Hardware &
The Full Stack.

Everything running under the hood — from dual RTX 3060s to vLLM production inference, OpenClaw agent orchestration, and n8n automation. Your data never leaves the building. Here's exactly how we built it.

The Sovereign Advantage

Your Tower.
Accessible Anywhere.

The real power of sovereign AI isn't just owning your compute — it's that your full 14B-parameter brain runs at home, and you access it from anywhere in the world. Your laptop becomes a thin client. ClawMcGraw does the heavy lifting on the tower.

🖥️
Whidbey Tower
ALWAYS ON · INFERENCE ENGINE
CPUi7-10700K 8C/16T
RAM64 GB DDR4
GPU 0RTX 3060 12GB — Qwen3-14B
GPU 1RTX 3060 12GB — Coder-7B
RuntimevLLM · WSL2 Ubuntu
Uptime99.9% · Always listening
🔒
Tailscale
Encrypted mesh VPN
💻
Your Laptop / Phone
ANYWHERE · THIN CLIENT
InterfaceDiscord · Browser · API
AccessCafe · Hotel · Field site
LatencyLocal network speed
n8n Hub47+ workflows via browser
ControlFull stack from any device
DataNever leaves the tower
Under The Hood

Technology &
Infrastructure.

Sovereign AI means you know exactly what's running, where it's running, and who owns it. Here's the full stack.

LLM Runtimes

Three runtimes, each with a job. We pick the right one per deployment.

Ollama
Local Dev / Prototyping

The fastest way to run models locally. One command, model downloaded, chat running. Perfect for development, testing architectures, and client demos before committing to production.

One-command model management
REST API at localhost:11434
Supports Qwen, Mistral, Llama, Phi
CPU + GPU inference, no config needed
llama.cpp
CPU-Optimized / Edge

Pure C++ inference engine. Runs full models on CPU when GPU isn't available. Our go-to for client deployments on standard hardware — no GPU required, still fast enough for production workloads.

Runs on CPU — no GPU required
GGUF quantized model format
4-bit to 8-bit quantization options
Server mode with OpenAI-compat API
vLLM
Production GPU — What We Run

PagedAttention-powered GPU inference. This is what ClawMcGraw runs on our tower — Qwen3-14B-AWQ on GPU 0, Qwen2.5-Coder-7B on GPU 1. Maximum throughput for production multi-agent systems.

PagedAttention for max GPU utilization
AWQ quantization — 12GB VRAM per model
OpenAI-compatible API at :8000/:8001
Continuous batching, multi-model routing
Hardware Tiers

We help clients choose the right hardware for their workload — or deploy to their existing machines.

Starter
CPU-ONLY INFERENCE
CPUModern i5/i7 8+ cores
RAM32GB minimum
GPUNot required
Runtimellama.cpp (GGUF)
Models7B Q4 — fits in RAM
Best ForSingle-agent workflows, light automation
What We Run
Sovereign
OUR ACTUAL STACK
CPUIntel i7-10700K (8C/16T)
RAM64GB DDR4
GPU2× RTX 3060 12GB
RuntimevLLM (multi-GPU)
Models14B AWQ + 7B AWQ simultaneous
Best ForFull multi-agent production stack
Professional
SINGLE GPU
CPURyzen 7 / i7 modern
RAM32–64GB
GPURTX 3060/4060 Ti 12–16GB
RuntimeOllama or vLLM
Models14B AWQ or 7B full
Best ForMost small business deployments
OpenClaw Platform
MULTI-MODEL AI AGENT FRAMEWORK · OPEN SOURCE

OpenClaw is the open source agent framework we built and run every deployment on. It's the connective tissue between your LLM runtime, your tools, your memory, and your automation workflows. Skill-based, multi-model, and built for real business operations — not toy chatbots.

n8n Automation Hub

Our n8n instance runs 47+ active workflows. Here are three examples of what a real deployment looks like inside n8n.

Security Architecture

Local inference isn't just about cost — it's the only way to guarantee your business data never leaves your infrastructure.

Integration Ecosystem

Every tool in the stack plays together. These are the integrations we actively use and deploy.

Recommended Setups

Two real examples of what a complete GMTek deployment looks like for different business types.

// Ready to Deploy

Want This Stack
For Your Business?

We spec the hardware, build the agents, wire the automations, and hand you the keys. Most clients are live in two weeks.