~80%
Earth's surface with no viable cloud alternative
$226M
Armada total raised (Founders Fund, M12, Shield Capital)
<5ms
On-site inference latency — mostly theoretical today
400 Gbps
InfiniBand bandwidth required for frontier AI training
Insight 01
The real value is compute availability, not speed
The "edge is faster" narrative is mostly marketing. The defensible case is bringing GPU capacity to the ~80% of Earth where no cloud alternative exists. Bandwidth economics — processing 5 Gbps of camera video locally vs. routing it to Virginia — is the strongest near-term commercial argument.
Insight 02
Starlink dependency is the single biggest product risk
Atlas routes entirely through Starlink. Russia actively jams GPS and Starlink terminals in Ukraine. The unsolved problem: Galleon-to-Galleon mesh when all satellite links are simultaneously denied. goTenna solves the last mile; the node-to-node backbone in contested environments is still open.
Insight 03
Armada is an inference play — and that defines everything
Frontier training requires 10,000+ GPUs at 400 Gbps in one room. Armada can't compete there. But inference is stateless, parallelizable, and runs well on a Galleon. As AI shifts toward agentic, real-time, and autonomous applications, the edge inference market grows — and Armada's timing is right for that shift.
🔬
First Principles
Decomposed "data center" layer by layer rather than accepting the term as monolithic
🎯
Use Case Stress-Test
Separated claimed value drivers from actual value drivers for each scenario
📐
Diagrams for Clarity
Visual rendering forced precision — you can't draw a vague architecture diagram
🎓
Domain Depth as Lens
PhD MANET background surfaced the Galleon mesh gap that generic analysis would miss