How to Build a Self-Hosted AI Stack with Open Source Tools

This video demonstrates how to replace multiple paid AI subscriptions with a self-hosted stack of open-source tools. It covers local model execution, cost-saving request routing, context compression, and application building on a virtual private server.

■ Self-Hosting Models
- Ollama for running open-weight LLMs locally
■ Managing AI Costs
- Nine Router for unified API access and automatic fallback tiers
- Headroom for compressing context before it reaches the model
■ Deployment and Infrastructure
- Hostinger VPS with a Docker catalog for one-click installation
■ Building Applications
- Diffy for creating visual workflows exposed as APIs
- Open Hands for autonomous coding agents that fix GitHub issues

Developers looking to reduce AI expenses and keep their code private will find a practical path to a self-hosted AI infrastructure. Viewers will learn which open-source projects to combine and how to deploy them on their own server.