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Courses/Self-hosted AI automation for small businesses/Stack map: n8n, Open WebUI, and models

Stack map: n8n, Open WebUI, and models

An SMB doesn't need to start with a huge platform. It needs a clear architecture: interface, automations, models, data, approvals, and logs.

  • Understand the role of n8n, Open WebUI, Ollama, vLLM, and a custom API.
  • Separate chat, automation, model, and data so you can maintain the system.
  • Design a first version that is cheap, private, and scalable.
Terminal
users
  -> Open WebUI: internal chat, models, tools
  -> n8n: workflows, webhooks, approvals, integrations
  -> internal API: business rules and permissions
  -> model:
       local: Ollama / llama.cpp
       GPU production: vLLM
       occasional cloud: external provider
  -> data:
       Postgres / Qdrant / files
  -> operations:
       logs, backups, alerts, limits

Decision rule

  • Open WebUI: private interface for users, models, tools, and knowledge.
  • n8n: visible automations, webhooks, connectors, approvals, and business logs.
  • Ollama: simple local entry point for models on modest CPU/GPU.
  • vLLM: model serving with GPU and higher concurrency.
  • Custom API: permissions, sensitive rules, and operations you don't want left in an editable workflow.
Complete Aulafy mapSee how this lesson fits without leaving your path.

Complete Aulafy map

How all courses connect

This is not a checklist. Start with the foundation, choose an outcome, and go deeper only when your project needs more control.

  1. 1Understand
  2. 2Apply or build
  3. 3Operate with confidence
01

Choose an application

Turn the foundation into a visible outcome: a website, a business improvement, media, or an interactive experience.

Continue into the technical branch when you need to maintain code, data, or infrastructure.

02

Build with code

Prepare your environment, work with coding agents, and run models while keeping control of your projects.

This branch prepares you to design and operate reliable AI systems.

03

Take systems to production

Combine retrieval, agents, evaluation, security, deployment, and model adaptation when the problem requires it.

You do not need every course: choose the component your system needs and return as it grows.

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