Local AI on Linux.

Run Ollama, Open WebUI, and local RAG on your own Linux hardware—headless servers, workstations, or custom builds. Full control, no vendor lock-in.

Why Linux for Local AI?

Headless & server-ready

No display needed. Run on rack servers, NUCs, or old workstations. SSH in, serve the stack over your network—Ollama and Open WebUI work the same.

GPU flexibility

NVIDIA and AMD GPUs are first-class on Linux. Scale inference with consumer or datacenter cards; Ollama and llama.cpp use them natively.

No lock-in

Open source stack on an open OS. Swap distros, move to different hardware, or replicate the setup elsewhere—you own the full chain.

Automation & ops

systemd, Docker, or both. Script updates, backups, and restarts. Integrate with your existing Linux tooling and monitoring.

Cost-effective scaling

Reuse existing servers or buy commodity x86/ARM boxes. Often cheaper than equivalent Mac hardware when you need raw GPU throughput.

Data stays local

Same data-sovereignty story as Mac: models and RAG data live on your machine. No telemetry, no cloud dependency for inference.

Installed on custom hardware.

We install and configure the Local AI stack on your Linux machines—whether you already have a server, a workstation with a GPU, or want a spec for a new build.

  • Existing servers: Ubuntu, Debian, or other distros—we add Ollama, Open WebUI, and optional RAG/vector DB, then harden and document the setup.
  • Workstations: Single powerful Linux box with GPU for a team; we size it and set up multi-user access via Open WebUI.
  • New builds: We recommend specs (CPU, RAM, GPU, storage) for headless or desktop Linux rigs and handle the full install.

What gets installed.

Ollama

Model runtime and API. We install from the official Linux package or script and configure models (e.g. Llama) for your GPU.

Open WebUI

Browser UI for chat and admin. Runs as a service; we set users, roles, and optional RAG/knowledge-base wiring.

RAG & vector store

Optional: Chroma or similar for document indexing. We configure ingestion and connect it to Open WebUI so the AI answers from your docs.

Service management

systemd units (or Docker) so services start on boot and restart on failure. We document commands for updates and logs.

Next steps

If you have a Linux server or want to spec one for Local AI, we can scope the install and custom hardware for your team size and use cases.

Talk about Linux + Local AI