Private & open-source AI · 7 min read · Updated
How to Run Private AI on Your Own Computer (Small Business Guide)
Run AI models on your own computer so prompts and files stay in-house. Beginner tools like Jan and Ollama, hardware needs, honest limits and setup steps.
What private, local AI means
Private AI means running an AI model on a computer you control instead of sending your prompts to a cloud service. Free apps such as Jan and Ollama run open models on an ordinary laptop or desktop. Your documents and questions stay on the machine. The trade-off is that local models are usually less capable than the best cloud assistants.
For law firms, accountants, clinics, consultants and anyone handling confidential client material, sending data to an outside AI service raises real questions. Business plans from major providers offer data protections, but some owners want certainty, or have clients who ask for it.
The job is to get useful AI help with drafting, summarizing and searching documents, without the data leaving your control. For the wider world of self-hosted software, see our open-source AI guide.
Tools for this job
Our shortlist for this job. Each tool links to its full listing with pricing notes, tradeoffs and other options.
| Tool | Role | Why it fits | Pricing | Setup |
|---|---|---|---|---|
 Jan | Easiest start | A free desktop app that downloads and runs open models locally, so prompts and files never leave the machine. | Free and open source | Beginner (self-hosted) |
 Ollama | Best for most | Runs open models on Mac, Windows and Linux with simple commands and provides a local engine other private tools can use. | Free and open source | Beginner (self-hosted) |
 AnythingLLM | Best for chatting with documents | A desktop app that lets you ask questions of PDFs and documents using local models, with no server required. | Free and open source; hosted option | Beginner (self-hosted) |
 Open WebUI | Best for a small team | A self-hosted, ChatGPT-style interface with user accounts and document chat, usually paired with Ollama. | Free and open source; enterprise options | Intermediate (self-hosted) |
 LibreChat | Mix local and cloud models | A self-hosted team chat app that works with local models and major AI providers, keeping chat history on your server. | Free and open source | Intermediate (self-hosted) |
What to look for
- Ease of install. A desktop app with a normal installer is the right start for non-technical owners.
- Offline operation. Confirm it works with the internet disconnected.
- Model choice. Good tools let you try several open models and switch easily.
- Document chat if you want answers from your own files.
- Team features such as user accounts and permissions, for shared setups.
- Active project. Check recent releases and documentation on GitHub.
The tool options, briefly
Jan is a desktop app for Mac, Windows and Linux that runs open models locally. It feels like a chat app and is the gentlest starting point.
Ollama runs open models such as Llama, Gemma and Qwen with a one-line command and exposes a local connection that other private tools use. It is the engine behind many setups.
AnythingLLM is a desktop app or server for chatting with PDFs, documents and websites using local or cloud models.
Open WebUI gives a team a polished chat interface on your own server, with accounts and document chat. LibreChat is similar and works well when you want local models alongside paid cloud providers.
Developers may also use llama.cpp or LocalAI. Browse the local and private AI category or all open-source repos.
Costs to watch
- Software. The apps listed are free and open source, though some offer paid hosted or enterprise versions.
- Hardware. More memory and a stronger graphics chip let you run bigger, better models. This is the main cost.
- Time. Setup, model updates and troubleshooting take hours, especially for team servers.
- Help. A consultant for a shared setup may be worth it.
- Cloud mixing. If you connect cloud providers to tools like LibreChat, you pay those providers for usage. Check current pricing.
Honest limits and risks
- Lower quality. Local models generally trail the best cloud assistants at reasoning and writing, especially on modest hardware.
- Speed. Answers can be slow on older machines.
- Privacy is only as good as your security. A laptop without disk encryption or a team server exposed to the internet can be a bigger risk than a reputable cloud plan.
- Not every feature stays local. Web search, cloud model connections and some plugins send data out. Check settings.
- Licenses. Open models come with their own licenses. Check commercial use terms for each model.
- Confidentiality duties remain. Professional rules on client data still apply. Local AI helps, but it does not replace your obligations.
If you would rather have it set up for you, Garner Digital can set up and secure a private AI workspace for your team.
How to know it is working
- Quality on your real tasks, compared side by side with a cloud assistant using sample data.
- Adoption. Is the team actually using it, or quietly going back to cloud tools?
- Time saved on the private job you picked.
- Maintenance hours each month.
Private AI pairs well with private meeting transcription. See our AI meeting notes guide.
How to set it up
Pick one private job
Choose a task where privacy matters and quality needs are modest, such as summarizing internal documents, drafting from confidential notes or searching your own policies.
Check your computer
Recent computers with plenty of memory, especially Apple silicon Macs or PCs with a capable graphics card, run local models best. Older laptops can still run small models, slowly.
Install a desktop app
Install Jan or Ollama from the official website only. Download a small, well-known model first.
Test on real tasks
- Run the same task through the local model and a cloud assistant using non-sensitive sample data.
- Compare quality and speed.
- Try a larger model if your hardware allows.
Add document chat
If the test works, add AnythingLLM to ask questions of your files. Start with a small, organized folder.
Scale to the team carefully
For shared use, set up Open WebUI on a dedicated machine with user accounts, backups and no public internet exposure. Get help if nobody can maintain it.
Frequently asked questions
Can I run ChatGPT on my own computer?
Not ChatGPT itself, but you can run open models that do similar work. Apps such as Jan and Ollama download models like Llama, Gemma or Qwen and run them locally. They are usually less capable than the best cloud assistants, but handle drafting, summarizing and document questions well enough for many tasks.
What computer do I need for local AI?
A recent computer with plenty of memory works best, especially Apple silicon Macs or Windows PCs with a capable graphics card. More memory lets you run larger, better models. Older laptops can run small models, but slowly. Test with a small model on the machine you already have first.
Is local AI completely private?
The model runs on your machine, so prompts and files are not sent to an AI provider. Privacy still depends on your security: disk encryption, strong passwords, backups and not exposing servers to the internet. Features like web search or cloud model connections send data out, so check settings.
Is private AI good enough for business work?
For many everyday jobs, yes: summarizing documents, drafting from notes, rewriting text and searching your own files. For complex reasoning or polished long-form writing, cloud models are usually stronger. Many businesses use local AI for confidential material and a business-plan cloud assistant for everything else.
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