'But our data shouldn't just go outside.' It's one of the first things I hear when I talk to companies in the industry about AI. And it's a completely justified concern.
Customer data, drawings, work orders, pricing agreements — that's sensitive business information. The thought of it ending up in a system of an external tech company doesn't feel right. I completely understand that.
What many people don't know is that it can also be done differently. You don't need an external cloud to use AI.
How does AI work without external cloud?
When most people think of AI, they think of ChatGPT. You type something in, the answer comes back. What happens in between is unclear — and the data goes to OpenAI's servers.
But that's one way to use AI. Not the only one.
There are also AI models that you can run completely locally — on a server that sits with you, in your own network, behind your own firewall. The data never leaves your company. You decide who has access. You decide what happens with it.
We call this a local AI environment or a private AI server.
What do you need for that?
You don't need a data center and you don't need an IT department of ten people either. A modern server — in many cases even a powerful PC with a suitable graphics card — is sufficient to run a usable AI system for an SME business.
What you do need:
- A server that is continuously available in your network
- The right software to run AI models — that is open source and freely available
- A good configuration that fits your use cases
- Someone who sets it up and transfers it to your own team
That last point is exactly what we do. We set up the environment, configure the models and ensure that your team understands how it works and how it is managed. After that it's completely yours.
What can you do with it?
The same things as with an external AI tool — but with your own data, in your own environment:
- Search and summarize documents
- Ask questions about your own technical documentation
- Prepare work orders and quotes
- Build and consult internal knowledge base
- Build automated workflows with tools like n8n
The advantage: the AI has access to your documents, your data, your systems. Not to generic information from the internet. That makes the answers much more relevant.
What are the limitations?
Honesty requires that I also mention this. A locally running AI model is in some cases less powerful than the latest version of GPT-4 or comparable cloud models. For most business applications — searching documents, summarizing texts, preparing work orders — the difference is negligible.
For extremely complex reasoning abilities or the very latest model versions, you sometimes need a hybrid approach. But even then you can choose which data you keep local and which you possibly process externally.
In most projects I guide, a fully local solution is perfectly adequate — and the peace of mind it provides is certainly worth it.
What does it cost in maintenance?
Less than you think. A well-set-up local AI environment runs largely independently. Updates are available — just like with other software — and can be implemented without the system being offline for long.
We ensure a handover where your own IT or a designated employee can take over the management. No permanent dependency on us.
Would you like to know if a local AI environment fits your company and situation? Schedule a no-obligation introduction meeting.