Self-hosting
Self-hosted AI for teams: what it really takes
Self-hosted AI for teams means running the AI models and the software around them on computers you control. Your data stays with you, but you also take on the work a vendor would otherwise do. Before you start, it helps to know what that work is.
Why teams self-host
- Control of data: questions and documents stay on your own network, which settles most AI data privacy questions.
- Offline use: the work can carry on with no internet connection.
- One shared tool: the team stops spreading work across separate personal AI accounts.
If none of these matter to you, a hosted service is usually simpler. To compare the choices, see our guide to private AI for business.
The parts a team needs
A single person can run a local model in an afternoon. A team needs more, because several people, their documents and their access all have to be handled:
| Part | What it does | Common way to get it |
|---|---|---|
| Model runner | Runs the AI models | Ollama, vLLM |
| Chat interface | Where the team asks questions | LibreChat, OpenWebUI |
| Accounts and access | Controls who gets in and what they can see | Often built into the interface, or added separately |
| Document handling | Reads files, including tables and scans | A retrieval pipeline and a vector database |
| Safe place to run code | Lets the AI work on data without touching anything else | A sandbox you set up |
| Hosting basics | Keeps it reachable and recoverable | Certificates, storage, backups, monitoring |
Build your own stack, or use a packaged one?
Building from open-source parts gives you the most choice, and the most to look after. Onyx, a vendor in this market, estimates a do-it-yourself stack typically takes two to four months to set up, and warns that upgrading one part can break another. That figure comes from a company selling the alternative, so treat it as a rough guide, but the point holds: the parts have to be made to work together, and kept working.
Build it yourself if you have engineers to spare and want to choose every part.
Use a packaged product if you want the team working soon and would rather not own the joins between the parts.
How SyncMind handles it
SyncMind's on-premise AI assistant is one packaged option. It comes as a desktop installer for Windows, with these parts included:
- Models: run through Ollama. SyncMind measures each computer and downloads what it can run.
- Several computers: computers share the work, and a light one uses the team's AI over the network.
- Team chats: team and personal chats, with an administrator account and invite codes.
- Documents: reads PDFs, Office files, images and scans, so your team can chat with company documents.
- Sandbox: each run of code gets its own folder and cannot open network connections.
- Agent Log: every step is shown as it happens.
What self-hosting still leaves with you
A packaged product removes the assembly, not the responsibility. These stay yours:
- The computers: buying them, powering them and replacing them. Answers can only be as quick as your hardware allows.
- Backups: your data is on your machines, so keeping it safe is on you.
- Fewer features: with no internet there is no web search. SyncMind's on-premise edition also lists fewer team features than its API edition, as the pricing page shows.
If you need something specific, such as single sign-on or Mac and Linux support, ask us before you plan around it.
Questions
What does self-hosted AI mean?
The AI models and the software around them run on computers your team controls, rather than on a vendor's servers.
Can a small team self-host AI?
Yes, if it has computers to run the models and someone to look after them. SyncMind measures each computer and downloads the models it can run, and a computer with too little power uses the team's AI over the network.
Does self-hosted AI work without internet?
It can. SyncMind's on-premise edition works with no internet connection, though it cannot search the web.
What if we would rather not run our own computers?
Then self-hosting is probably the wrong choice. SyncMind's API edition runs on any laptop with hosted models, but your questions go to the model provider.
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