Zero-Cost AI Infrastructure: A Complete Architecture

The Problem

AI infrastructure is expensive. Cloud GPU instances cost $2-5/hour. API calls add up. Most AI projects burn through credits before producing value.

The Solution: Sovereign Infrastructure

Own the hardware. Run open-source models. Build your own communication backbone.

Architecture

Queen (orchestrator)
    │
    ├── NATS Server (message bus, TLS + auth)
    ├── CEREBRO (PostgreSQL agent registry)
    ├── Worker pool (multi-agent execution)
    └── Hugo Site (content flywheel on CF Pages)

Cost Breakdown

Component	Technology	Cost
Message Bus	NATS (open source)	$0
Agent Registry	PostgreSQL + pgvector	$0
Worker Runtime	systemd on local GPU	$0
Content Platform	Hugo + Cloudflare Pages	$0
File Storage	GitHub	$0
Total		$0

Key Decisions

NATS over Kafka/RabbitMQ — Lighter, faster, built-in auth, JetStream
PostgreSQL over dedicated vector DB — pgvector extension, one DB for everything
Hugo over WordPress — Static = fast = free hosting = no security holes
systemd over Docker for workers — Simpler, auto-restart, no orchestration overhead

Scaling Model

Start with 1 queen + 1 worker. Scale to 7 direct workers. Each can manage 3 sub-workers.

Depth	Agents	Total
0	1	1
1	7	8
2	13	21
3	39	60

Result: 60-agent mesh. $0/month.