30-Day Local AI-Stack Quickstart
Basics · 8 min
Want to build a local AI stack? This day-by-day guide shows you how to go from zero to a production-ready, GDPR-compliant AI stack in 30 days.
What You'll Have at the End
- Docker Swarm Cluster (3 Nodes)
- Ollama with local LLMs (Llama 3, Mistral)
- n8n Workflow Automation
- Monitoring with Prometheus + Grafana
- 100% GDPR-compliant
Phase 1: Foundation (Day 1-7)
- Day 1: Hardware Check - Minimum 8GB RAM, Ubuntu 22.04
- Day 2: Docker Installation
- Day 3: Network & Security - UFW, SSH hardening
- Day 4-5: Docker Compose Basics
- Day 6-7: Documentation
Phase 2: AI Core (Day 8-14)
- Day 8-9: Ollama Installation
- Day 10-11: Model Selection (Llama 3 8B, Mistral)
- Day 12-13: Chat Interface (Open WebUI)
- Day 14: RAG Basics (ChromaDB)
Phase 3: Automation (Day 15-21)
- Day 15-16: n8n Installation
- Day 17-18: AI Workflows
- Day 19-20: Build Your Own Workflows
- Day 21: Integration & Testing
Phase 4: Production (Day 22-30)
- Day 22-23: Monitoring (Prometheus + Grafana)
- Day 24-25: Alerting
- Day 26-27: Security Hardening
- Day 28-29: Backup & Recovery
- Day 30: Review & Optimization
Related articles: Ollama Tutorial · Docker Basics
For implementation support, find resources at ai-engineering.at.
Next step: move from knowledge to implementation
If you want more than theory: setups, workflows and templates from real operations for teams that want local, documented AI systems.
Why AI Engineering
- Local and self-hosted by default
- Documented and auditable
- Built from our own runtime
- Made in Austria
Not legal advice.