The Continuity Layer
Run your own AI · A local AI server for the house

A private AI for the whole house

thecontinuitylayer.com/open/learn/house-server

Checked 6 November 2026. US dollars. No affiliate links.

One machine with enough memory runs the model. Everyone else uses it from a browser, on their phone or laptop, with their own account and their own chat history. Nothing goes out of the house.

By the end

A ChatGPT-style page at a local address, with an account for each person, running on your own model.

What you need

  • One always-on computer with 16GB or more; 24GB-plus for better models. See the hardware guide.
  • Docker installed on it (Docker Desktop on Mac or Windows).
  • About an hour.

Set it up

  1. 1
    Run Open WebUI with Ollama bundled in one container. This is the command from Open WebUI's quick start; replace the secret with a long random phrase of your own and keep it out of anything you share:
    docker run -d -p 3000:8080 \
      -v ollama:/root/.ollama \
      -v open-webui:/app/backend/data \
      -e WEBUI_SECRET_KEY=<a-long-random-phrase> \
      --name open-webui --restart always \
      ghcr.io/open-webui/open-webui:ollama
    Add --gpus=all after -d if the machine has an NVIDIA card.
  2. 2
    Open http://localhost:3000 on that machine and create the first account. The first account becomes the administrator.
  3. 3
    In the admin settings, download a model (for example gemma4:12b) and set the context to 8,192 or more.
  4. 4
    Turn on new sign-ups under the admin authentication settings. New accounts wait as pending until you approve them.
  5. 5
    On the other devices, open http://<that-computer's-local-address>:3000. Find the address in the machine's network settings.

Make it the household's

  • Give each person a model with their own instructions (see custom models).
  • Add shared documents for everyone to ask about (see chat with your documents).
  • Turn on memory per account if people want the AI to remember facts about them across chats.

Every app that can sit in front of a local model is compared in local AI apps.