How to Self-Host AI Agents with Docker Compose
Learn how to deploy and manage AI agents on your own infrastructure using Docker Compose, with automatic dependency wiring and production-ready configurations.
Self-hosting AI agents gives you complete control over your data, costs, and infrastructure. Unlike cloud-hosted solutions, running agents locally means your prompts, embeddings, and outputs never leave your network. With Docker Compose, spinning up a full AI agent stack is as simple as a single command.
Why Self-Host?
Cloud AI services charge per token and retain your data. For teams processing sensitive documents or running high-volume workflows, self-hosting can reduce costs by 80% or more. Tools like better-openclaw generate production-ready Docker Compose files with all services pre-wired — databases, vector stores, reverse proxies, and monitoring — so you can go from zero to a running stack in under five minutes.
The Core Stack
A typical self-hosted AI agent setup includes an LLM runtime like Ollama, a vector database like Qdrant for semantic memory, a workflow engine like n8n for orchestration, and a PostgreSQL database for persistent state. better-openclaw resolves all dependencies automatically: selecting n8n will pull in PostgreSQL, and choosing the Research Agent skill pack adds Qdrant, SearXNG, and Browserless.
Getting Started
Run npx create-better-openclaw@latest and follow the interactive wizard. Select your services, choose a reverse proxy (Caddy or Traefik), and the generator produces a complete docker-compose.yml, .env with randomized secrets, proxy configs, and monitoring dashboards. Run docker compose up and your AI agent infrastructure is live.