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<span>March 22, 2026</span>
<span class="divider"></span>
<span>Alexa Amundson</span>
<span class="divider"></span>
<span>8 min read</span>
</div>
<h1 class="article-title">How I Built a Sovereign AI OS for $38/month</h1>
<p class="article-subtitle">Five Raspberry Pis, two cloud droplets, 26 TOPS of AI inference, 18 production domains, 200 agents. The full breakdown of what it costs to own your entire stack.</p>
<div class="article-tags">
<span class="tag">self-hosted</span>
<span class="tag">raspberry-pi</span>
<span class="tag">infrastructure</span>
<span class="tag">cost-breakdown</span>
</div>
</header>
<!-- Article Body -->
<article class="article-body">
<h2>The $150 question</h2>
<p>People ask me what it costs to run BlackRoad OS. They expect a number with commas in it. They expect AWS bills and Vercel invoices and a line item for every API call.</p>
<p>The answer is $150 a month. That covers everything. AI inference, DNS, TLS, object storage, Git hosting, 18 production domains, a VPN mesh, and 200 autonomous agents. All of it.</p>
<p>Here's the exact breakdown.</p>
<h2>The hardware</h2>
<p>The core fleet is five Raspberry Pi boards. These are not test machines or dev toys. They are production servers running 24/7, handling real traffic, serving real websites, running real AI models.</p>
<div class="node-grid">
<div class="node-card">
<div class="node-name">Alice</div>
<div class="node-hw">Pi 4 · 8GB</div>
<div class="node-role">Gateway, Pi-hole DNS, PostgreSQL, Qdrant vector DB, Redis cache, nginx reverse proxy</div>
</div>
<div class="node-card">
<div class="node-name">Cecilia</div>
<div class="node-hw">Pi 5 · 8GB · Hailo-8</div>
<div class="node-role">Primary AI inference (Ollama, 16 models), MinIO object storage, PostgreSQL, InfluxDB</div>
</div>
<div class="node-card">
<div class="node-name">Octavia</div>
<div class="node-hw">Pi 5 · 8GB · Hailo-8</div>
<div class="node-role">Gitea (239 repos), 15 Workers, NATS messaging, Docker, PaaS deploy</div>
</div>
<div class="node-card">
<div class="node-name">Aria</div>
<div class="node-hw">Pi 4 · 4GB</div>
<div class="node-role">Backup node, monitoring agent, secondary DNS</div>
</div>
<div class="node-card">
<div class="node-name">Lucidia</div>
<div class="node-hw">Pi 4 · 8GB</div>
<div class="node-role">334 web apps, nginx, PowerDNS, GitHub Actions runners, Ollama</div>
</div>
</div>
<p>One Hailo-8 AI accelerator gives us 26 TOPS (tera operations per second) of dedicated inference compute. That's enough to run Llama 3, Mistral, Phi, CodeLlama, and a dozen other models simultaneously without touching the CPU.</p>
<p>The total hardware cost was about $1,200 upfront. That's a one-time spend. After that, the Pis draw about 5 watts each. Less than a lightbulb.</p>
<h2>The two cloud servers</h2>
<p>We run two DigitalOcean droplets. These aren't for compute — they're for geography. A Pi cluster in one location can't serve global TLS or provide a public IP that doesn't change every time the router reboots.</p>
<p><strong>Gematria</strong> (NYC3, $12/mo) handles TLS termination with Caddy, serves 151 domains with automatic Let's Encrypt certificates, runs PowerDNS as our authoritative nameserver, and hosts Ollama with 6 models for edge inference.</p>
<p><strong>Anastasia</strong> (NYC1, $6/mo) provides secondary DNS and acts as a backup relay.</p>
<p>All traffic from these droplets flows back to the Pi fleet through WireGuard. The droplets are thin edge nodes. The real compute stays on hardware we physically own.</p>
<h2>The monthly cost</h2>
<table class="cost-table">
<thead>
<tr><th>Item</th><th>Cost</th></tr>
</thead>
<tbody>
<tr><td>DigitalOcean — Gematria (2 vCPU, 4GB)</td><td>$24</td></tr>
<tr><td>DigitalOcean — Anastasia (1 vCPU, 1GB)</td><td>$6</td></tr>
<tr><td>Cloudflare (Pages, D1, Workers, R2)</td><td>$0</td></tr>
<tr><td>Domain registrations (18 domains, amortized)</td><td>~$30</td></tr>
<tr><td>Electricity (5 Pis, ~25W total)</td><td>~$3</td></tr>
<tr><td>Home internet (already paying for it)</td><td>$0</td></tr>
<tr><td>GitHub (free tier)</td><td>$0</td></tr>
<tr><td>Stripe (only charges on revenue)</td><td>$0</td></tr>
<tr class="total"><td>Total</td><td>~$63/mo</td></tr>
</tbody>
</table>
<p>I said $150 in the title because that's the honest upper bound when you include occasional hardware replacements, SD cards, cables, and the one month I accidentally left a third droplet running. The real recurring cost is closer to $63.</p>
<h2>What this replaces</h2>
<p>Here's the cloud equivalent of what we self-host, and what it would cost if we used the standard playbook:</p>
<div class="replace-grid">
<span class="cloud">AWS EC2 / Lambda</span>
<span class="arrow">→</span>
<span class="self">5 Raspberry Pis</span>
<span class="cloud">GitHub Enterprise ($21/user)</span>
<span class="arrow">→</span>
<span class="self">Gitea on Octavia</span>
<span class="cloud">OpenAI API ($0.03/1K tokens)</span>
<span class="arrow">→</span>
<span class="self">Ollama + Hailo-8 (free)</span>
<span class="cloud">Vercel Pro ($20/mo)</span>
<span class="arrow">→</span>
<span class="self">Caddy + Cloudflare Pages</span>
<span class="cloud">AWS S3 ($0.023/GB)</span>
<span class="arrow">→</span>
<span class="self">MinIO on Cecilia</span>
<span class="cloud">Route 53 ($0.50/zone)</span>
<span class="arrow">→</span>
<span class="self">PowerDNS on Lucidia</span>
<span class="cloud">Tailscale ($5/user)</span>
<span class="arrow">→</span>
<span class="self">WireGuard mesh (free)</span>
<span class="cloud">Redis Cloud ($7/mo)</span>
<span class="arrow">→</span>
<span class="self">Redis on Alice</span>
<span class="cloud">Slack Pro ($7.25/user)</span>
<span class="arrow">→</span>
<span class="self">RoundTrip (self-hosted chat)</span>
</div>
<p>A comparable cloud setup for a solo founder would run $200-500/month minimum, scaling to thousands as you add users and inference calls. We pay $63.</p>
<h2>The WireGuard mesh</h2>
<p>Every node connects to every other node over WireGuard. That's 12 bidirectional tunnels forming a full mesh. Traffic between nodes is encrypted end-to-end, even within the same LAN. Internet traffic enters through Gematria, hits the WireGuard tunnel, and lands on whatever Pi node is responsible for that service.</p>
<p>There's no Tailscale. No Zerotier. No managed VPN service. Just raw WireGuard configs generated once and running forever. It took an afternoon to set up. It's been running for months without a single tunnel drop.</p>
<h2>The AI inference layer</h2>
<p>Cecilia runs Ollama with 16 models loaded. The Hailo-8 accelerator handles the matrix multiplication. Inference speed varies by model: Phi-3 runs at about 12 tokens/second, Llama 3.1 8B at about 3.6 tok/s. Not blazing fast, but fast enough for agents that run async and don't need sub-second responses.</p>
<p>For user-facing products that need speed, we use Cloudflare Workers AI as a fallback. It's free-tier and adds about 100 tok/s when the local models are overloaded. But the default is always local. The cloud is the exception, not the rule.</p>
<h2>What I'd do differently</h2>
<p>Three things:</p>
<p><strong>Start with NVMe, not SD cards.</strong> We lost a month debugging I/O errors on Lucidia before realizing the SD card was degrading. Pi 5 supports NVMe boot natively. Use it from day one.</p>
<p><strong>Run fewer models.</strong> Having 16 models loaded looks impressive in a dashboard but 4-5 well-chosen models cover 95% of use cases. Phi for speed, Llama for quality, CodeLlama for code, Mistral for general purpose.</p>
<p><strong>Set up monitoring earlier.</strong> We didn't have proper alerting until month three. By then we'd already had two nodes silently go offline for days without noticing. A simple cron job that pings each node and posts to a webhook would have caught it immediately.</p>
<h2>Is it worth it?</h2>
<p>If you're a solo founder or a small team building AI products, the answer is yes. Not because it saves money — although it does. Because it changes what's possible.</p>
<p>When inference is free, you stop rationing it. Your agents can think longer. They can retry. They can run in the background all day without burning through a budget. You stop optimizing for token count and start optimizing for quality.</p>
<p>When your infrastructure is in the next room, you stop waiting for support tickets. You SSH in and fix it. You understand every layer because you built every layer.</p>
<p>When you own your stack, nobody can shut you down. No terms of service change. No pricing update. No deprecation notice. It's yours.</p>
<blockquote>The real cost of cloud isn't the invoice. It's the dependency. BlackRoad OS costs $63 a month and answers to nobody.</blockquote>
<p>If you want to try it, start with one Pi and one model. That's enough to see what sovereign AI feels like. Then you'll understand why we built the rest.</p>
<p>Details at <a href="https://blackroad.io">blackroad.io</a>.</p>
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<div class="author-bio">Founder and CEO of BlackRoad OS, Inc. Building sovereign AI infrastructure on commodity hardware.</div>
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