How to self-host an open-source Copilot alternative.

Self-hosting makes an alternative yours: your hardware, your keys, your audit trail. Kortix is the open-source AI Management System built for it — one git repo you own, an isolated Linux machine per session, and work that lands through a change request. The steps differ by lane: a coding assistant is lighter than an agent-management system, but the shape is the same.

1. Choose the lane first

Self-hosting a coding assistant (Tabby, Continue.dev, Cline) means serving a model endpoint and pointing an IDE at it. Self-hosting Kortix — the lane C platform — means running a control plane, sandboxes and connectors. Decide which lane you are in before buying hardware: lane C needs real CPU/RAM and disk isolation, not just GPU for inference.

2. Provision a host

• Local / laptop: fine for a coding assistant with a small local model, and for desktop tools like OpenWork.
• VPS / dedicated box: the usual home for a self-hosted completion server (Tabby) or an agent sandbox host.
• Your VPC or on-prem: required when the agents touch company data. This is the deployment Kortix is built for: your VPC, your on-prem rack, your keys.

3. Install and configure

Follow the upstream project's own install path — do not improvise. Examples of the shape:

# A coding-assistant server (Tabby) - see repo README for current flags
docker run -d --gpus all -p 8080:8080 tabbyml/tabby serve --model StarCoder-1B

# Kortix - self-host from Docker images
# see https://github.com/kortix-ai/suna for the current quickstart

Whatever the lane, keep the source of truth in version control. For agent platforms, the configuration is code: agents, skills, connectors and memory as files in a repo you own, so changes are diffable and reviewable.

4. Wire in your models

Most open-source options are model-agnostic: they call a provider through a key you supply, or a local inference server (Ollama, vLLM, llama.cpp). Keep keys in a secret store, not in the repo. Kortix runs Claude, OpenAI, Gemini or any OpenAI-compatible endpoint per agent, per session, per message — all with your keys. This is the difference between "open" as a licence and "open" as an operational reality.

5. Verify and govern

• Confirm the service answers on its port and the model responds.
• For agents, confirm each session gets its own isolated Linux machine and that edits must pass a review step before landing. Kortix lands every change as a change request a human reads as a diff.
• Record an audit trail — open-source platforms vary here, and it matters the moment an agent has write access.