Private AI for business, on your systems with your data under control
We install AI models on your infrastructure so you can query documents and automate tasks without sending sensitive information to an outside service. First we check with you whether it pays off, because the cloud is often enough.
Your data stays on your systems.
You want to use AI, but your data can't leave
- Contracts, case files or customer data can't go to an outside service for legal or contractual reasons.
- Some of your staff already paste internal information into public AI tools and nobody controls it.
- Your knowledge is scattered across documents and folders, and finding a reliable answer takes too long.
What private AI includes
Comparison against the cloud
Before you invest, we compare the private option with a cloud service based on how sensitive your data is, your usage volume and your real cost.
A model on your infrastructure
We select and install an open model on your server or in a private environment you control, sized for your users and your tasks.
Search across your documents
An assistant with retrieval over your documentation (RAG) that answers with a citation, so anyone can check where each fact comes from.
Permissions and traceability
Access by user and role, so each person only queries what they can already see, with usage logs that follow your internal policy.
Connection to your processes
Integration with your internal systems and n8n workflows to classify, extract or summarise information inside your network.
Quality evaluation
We test the system with real questions from your company before delivery, and we make clear what it does well and where it needs human review.
The MAPS method applied to your private AI
Map
We sort your data by sensitivity and study your use cases and volume. That tells us whether you need private AI, the cloud or a mix of both.
Activate
We deploy the model and the most valuable use case, such as document search, with a small group of users.
Position
We bring the AI to where the work happens: we connect it to your team's tools and give them a safe alternative to public AI tools.
Systemise
We measure answer quality, usage and system load, update documents and models, and add use cases according to their return.
A good fit if
- You handle confidential information such as case files, contracts, plans or customer data.
- Legal or contractual duties limit what you can send to third parties.
- You will use AI heavily and steadily, with many users or many documents.
- You want your system to stay the same even if a vendor changes its prices or terms.
Not for you if
- Your data isn't sensitive and a cloud service with good terms covers you.
- Your use will be occasional: paying per use will cost you less than running your own infrastructure.
- You always need the full power of the most advanced model, which tends to reach the cloud first.
Price
From €7,900
Prices exclude taxes.
Frequently asked questions
How much does private AI cost?
From €7,900, excluding tax. The final price depends on the use cases, the volume of documents, the integrations and whether we can use your existing infrastructure or need new hardware.
When does it beat a cloud service?
It pays off if your data can't leave your control, if usage is heavy and steady, or if you need independence from a vendor. With occasional use or low-sensitivity data, the cloud is usually the better choice and we will say so.
Does it work as well as ChatGPT or Gemini?
For focused tasks like querying documents, classifying or summarising, a well-configured open model gives good results. For complex reasoning, the most advanced cloud models tend to be ahead. We test with your real questions before you decide.
How long does it take to implement?
It depends on hardware availability, how organised your documents are, the integrations and the time needed to validate with your team. We give you a plan once mapping is done.
Who owns the system and the data?
You do. The data, indexes, configuration and code stay on your infrastructure, with the documentation you need. Your data doesn't leave your environment or train third-party models, and open models are used under their licences.
Who maintains the system?
Private AI needs updates, backups and supervision, and you should budget for that. We can take it on under a maintenance agreement, or your technical team can do it using the documentation we deliver.
How far can your business go?