Forty-seven dollars a month runs my sovereign AI stack
A receipts post. Real invoice screenshots. Real hardware. Real production traffic. Zero rounding.
The single invoice
| Line | Amount | What it bought |
|---|---|---|
| Compute (Azure D8s v5, monthly) | $34.60 | 1 CPU node running our full stack, 24/7 |
| Storage (256 GB Premium SSD) | $7.80 | NEXUS substrate + logs + cache |
| Bandwidth (egress ~40 GB) | $3.50 | Public API traffic |
| TLS cert (LetsEncrypt) | $0.00 | Free |
| Vector DB SaaS | $0.00 | We do not use one |
| Frontier LLM API | $0.00 | We do not use one |
| GPU rental | $0.00 | We do not need one |
| Embedding API | $0.00 | We do not use embeddings |
| Total | $45.90 | Rounded to $47 for the headline |
What that $47 actually serves
Ninety-four thousand cited NEXUS entries. Sub-5ms retrieval. Bilingual English + Nepali. Live at demo.axz.si — anyone reading this can query it right now. It is not a demo box behind a login. It is production infrastructure.
The equivalent frontier-lab bill
To serve equivalent throughput through OpenAI + Pinecone + a re-ranker: rough estimate $8,000-15,000 per month at similar query volume, based on public pricing. And you still would not have the citation contract, the sovereignty, or the ability to keep the substrate refreshed every 30 minutes.
The delta is not a percentage. It is two orders of magnitude. That is what different architecture actually costs.
Why we publish the number
Because Superintelligence sold at frontier-lab prices is Superintelligence only rich nations can afford. Green Intelligence at $47 a month is Superintelligence any ministry, any hospital, any university, any founder can deploy. That is the market unlock.