1. Executive Summary & Design Constraints

Many defense contractors, healthcare networks, and legal institutions require generative AI capabilities but are strictly barred by regulatory compliance (HIPAA, NIST 800-171, CMMC Level 2, ITAR) from streaming proprietary documents to public cloud APIs. This blueprint outlines a hardened, enterprise-grade on-premise deployment utilizing vLLM and TensorRT-LLM hosted on high-memory workstation nodes. The architecture guarantees:

Zero Telemetry / Zero Cloud Egress: Network interfaces are physically or virtually firewalled from WAN gateways.

Deterministic Latency: Predictable token generation speeds independent of third-party API rate limits.

Granular Role-Based Access: Token-level authorization integrated with Active Directory / LDAP.

2. Hardware Topology & Compute Sizing

Metric	Target Specification (Mid-Tier Enterprise)	High-Throughput Cluster
Primary Compute	2x NVIDIA RTX 6000 Ada (96GB VRAM total)	4x NVIDIA H100 NVL (376GB VRAM total)
System Memory	256GB DDR5 ECC Reg	512GB DDR5-5600 ECC Reg
System Storage	2x 1.92TB NVMe PCIe 4.0 (RAID 1 OS)	2x 3.84TB NVMe PCIe 5.0 (RAID 1 OS)
Model Weights Cache	4x 7.68TB U.3 NVMe (RAID 10 Striped/Mirrored)	Direct 100GbE RoCE to TrueNAS Enterprise
Host Connectivity	Dual 10GbE SFP+ (LACP Trunk)	Dual 100GbE QSFP28 (InfiniBand / RoCE)

3. High-Performance Serving Stack (vLLM Configuration)

We employ vLLM with PagedAttention to eliminate memory fragmentation and enable high-concurrency batching across concurrent internal staff requests.

bash

# /etc/systemd/system/vllm-sovereign.service
[Unit]
Description=vLLM Sovereign Inference Daemon
After=network.target nvidia-persistenced.service

[Service]
Type=simple
User=ai-engine
Group=ai-engine
WorkingDirectory=/opt/sovereign-ai
Environment="CUDA_VISIBLE_DEVICES=0,1"
Environment="VLLM_USAGE_SOURCE=production"
ExecStart=/opt/sovereign-ai/venv/bin/python3 -m vllm.entrypoints.openai.api_server \
    --model /opt/models/Llama-3.3-70B-Instruct-AWQ \
    --tensor-parallel-size 2 \
    --max-model-len 8192 \
    --gpu-memory-utilization 0.94 \
    --max-num-batched-tokens 16384 \
    --port 8000 \
    --host 127.0.0.1 \
    --trust-remote-code

Restart=always
RestartSec=10
LimitNOFILE=65536

[Install]
WantedBy=multi-user.target

4. Hardened Reverse Proxy & Internal Client Routing

Direct external access to the raw inference port 8000 is blocked by nftables. A local NGINX or Caddy reverse proxy enforces internal client mutual TLS (mTLS) and API key rate limiting:

nginx

# /etc/nginx/conf.d/ai-proxy.conf
upstream local_vllm {
    server 127.0.0.1:8000;
    keepalive 64;
}

server {
    listen 8443 ssl http2;
    server_name ai-core.internal.jajsolutions.com;

    ssl_certificate /etc/ssl/certs/ai-core-internal.crt;
    ssl_certificate_key /etc/ssl/private/ai-core-internal.key;
    ssl_client_certificate /etc/ssl/certs/ca-chain.crt;
    ssl_verify_client on;

    location /v1/chat/completions {
        proxy_pass http://local_vllm;
        proxy_http_version 1.1;
        proxy_set_header Connection "";
        proxy_set_header Host $host;
        proxy_buffering off;
        proxy_read_timeout 600s;
    }
}

5. Security Verification & Air-Gap Compliance Checklist

[x] Network Quarantine: Verify default gateway on the AI compute subnet does not route traffic across public WAN NAT.

[x] Ephemeral Context Discard: Verify prompt memory is cleared immediately following request termination.

[x] NVMe Encryption: Ensure full LUKS disk encryption is active on all drives storing raw model weights and vector embeddings.

[x] Audit Logging: Route API access events (user, timestamp, token volume, zero prompt content) to centralized internal syslog server.

On-Premise Sovereign AI Architecture: Deploying Frontier LLMs with Zero Cloud Leakage

1. Executive Summary & Design Constraints

2. Hardware Topology & Compute Sizing

3. High-Performance Serving Stack (vLLM Configuration)

4. Hardened Reverse Proxy & Internal Client Routing

5. Security Verification & Air-Gap Compliance Checklist