Local AI and Homelab Infrastructure
Self-hosted AI and private infrastructure, run rather than theorized.
Private infrastructure. Described as a capability, with no client systems shown.
- Status
- Private
- Type
- Infrastructure
- AI
- Locally hosted
- Access
- Private
- Year
- 2026
- Built by
- Ravion Moyers
What this had to solve.
Some work should not be sent to somebody else's cloud. This is the environment where self-hosted applications and locally run AI models are set up and maintained, which is also where the practical experience behind the automation and AI service comes from.
What was built.
Technology
- Linux server administration
- Self-hosted applications
- Locally run AI models
- Network infrastructure
- Reverse proxy and SSL
Verified from the live site where publicly detectable.
- Self-hosted application environments on owned hardware
- Locally run AI models rather than third party hosted inference
- Server provisioning, reverse proxy configuration, and certificate management
- Network segmentation and private service access
- Automated backup and process supervision
The parts that do the work.
Data stays put
For work that genuinely cannot leave a building, inference happens on hardware you own.
Self-hosted over subscribed
Applications run on infrastructure you control instead of accumulating monthly seats.
Production practices
Process supervision, automatic restarts, certificate renewal, and monitored backups.
What it does now that it could not before.
Work that should not go to somebody else's cloud does not have to. Applications and AI models run on owned hardware behind a reverse proxy with managed certificates and network segmentation, with automated backups and process supervision rather than a one-time setup left to drift. This is also where the hands-on experience behind the automation and AI service comes from, rather than it being a capability claimed from reading about it.
Different business, same capability.
- Linux server administration and production deployment
- Practical experience running AI locally rather than only calling an API
- Infrastructure maintenance rather than one-time setup
Services involved