Your own ChatGPT, without your company data leaving your organisation.
Private AI: internal AI applications that run entirely within your own environment. The same power as a modern chatbot, but with your data behind your boundaries — with your own access control, logging and free choice of models.
What is private AI?
Private AI (or your own ChatGPT) are AI applications that run entirely within your own (cloud) environment, so your company data never leaves your organisation. You work with existing models or a private LLM, but with your own access control and logging — suitable for sensitive and regulated data.
- Data stays within your own environment
- Works with existing models (GPT, Claude, open-source)
- Access control and logging under your own management
- Suitable for sensitive and regulated data
Why private AI?
More and more organisations want to use AI seriously, but get stuck on one question: is our data actually allowed in here? Contracts, customer data and internal knowledge do not belong in a public chatbot just like that. Private AI solves this by running the application within your own environment.
The difference from a public chatbot is control. With the free or standard versions you send information to a shared service and have little grip on what happens to it. With private AI everything runs behind your own login, your data does not leave your organisation, and you never unintentionally train third-party models with what you enter.
Private AI is not a different kind of AI. You use the same strong models, but in a walled-off setup. That lets you connect AI to your own knowledge sources — think of an internal assistant that knows your handbooks and procedures — and set up the environment exactly the way your security and compliance team wants.
We are not a vendor that throws a licence over the fence. As forward deployed engineers we help build the environment, integrate it into your work and stay involved until your people benefit from it every day.
What makes AI 'private'?
Your own tenant or environment
The AI runs within your own (cloud) environment, behind your own login and network boundaries. Not a shared public chatbot, but a walled-off place that is yours alone.
No training on your data
What you enter is not used to train third-party models. Your documents, customer data and internal knowledge stay yours and do not leave your organisation.
Access control & logging
You decide who may reach which data and which assistant. Everything can be logged and traced, so you are demonstrably in control towards security, audit and regulators.
Free choice of models
Work with the strongest existing models (GPT, Claude) or with open-source models you host yourself. We choose per task what fits your requirements for privacy, quality and cost.
What you get from us
Setup of your private environment
A walled-off AI environment within your own tenant or via a private endpoint you manage, set up to your requirements for privacy and compliance.
Integration with existing models
A connection to the models that fit best — commercial via a private endpoint or open-source self-hosted — so you are never locked into one vendor.
Access & data governance
Access control, logging and clear agreements on which data may go where. Demonstrably in control towards security, audit and regulators.
Working internal assistant + assurance
An assistant that knows your organisation and gets used, plus a handover with agreements on management, monitoring and adding new knowledge sources.
How do we approach it?
From data scan to a working, managed private environment — step by step.
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Needs & data scan
1 weekWe map out which processes benefit from an internal AI assistant and which data it needs to work with. We also classify how sensitive that data is.
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Architecture & hosting choice
1 weekBased on your requirements for privacy, compliance and budget, we determine where the AI runs: your own cloud tenant, a private endpoint at a model vendor, or self-hosted open-source models.
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Setting up the private environment
2-4 weeksWe build the walled-off environment: models, access control, logging and the connection to your own knowledge sources. All within your boundaries, nothing outside them.
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Integration & rollout
2-3 weeksWe surface the assistant where your people work and roll out in phases, with a first group of users we support closely.
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Assurance & management
ongoingWe hand over with clear agreements on management, monitoring and adding new knowledge sources, so the environment grows with your organisation.
What do organisations use private AI for?
For sensitive data
AI on confidential information
Contracts, personnel files or customer data that should never end up in a public chatbot. With private AI your people can still search and summarise that information safely.
For regulated sectors
Compliance without concessions
Healthcare, finance and government work under strict rules on data processing. A private environment with access control and logging makes AI usable without crossing those boundaries.
For your own knowledge
An assistant that knows your organisation
An internal assistant that answers based on your handbooks, procedures and documentation. Employees find in seconds what is otherwise hidden in folders and mailboxes.
Private AI is closely tied to where your AI runs and the knowledge you surface. Read how we set up AI in your own environment and how an AI knowledge system surfaces your internal knowledge, or compare the options in our overview of AI tools for business.
Want to know first if your organisation is ready for private AI?
The AI Readiness Scan shows where you stand, from data quality to policy and buy-in. A good starting point before you set up your own AI environment.
Take the AI Readiness Scan
Frequently asked questions about private AI
Where does my data live, and does it stay within my environment?
Yes — that is the whole point of private AI. The solution runs within your own (cloud) environment or via a private endpoint you manage. Your documents and data are processed within those boundaries and do not leave your organisation. With self-hosted open-source models, even the processing stays entirely on your infrastructure.
Which models can I use?
Both the strongest commercial models (GPT, Claude) via a private, walled-off connection and open-source models you host yourself. We choose per task: sometimes a top model via a private endpoint is the best fit, sometimes a lighter open-source model that runs entirely within your walls. We weigh quality, privacy and cost together.
What about GDPR and the AI Act?
Private AI actually makes it easier to comply with GDPR, because you know exactly where data lives and who can reach it. It also helps for the AI Act: you have logging, access control and a clear processing boundary. We align the setup with your obligations — read what the EU AI Act means for you.
What is the difference from just using ChatGPT?
With public ChatGPT you send data to a shared service where you have little grip on processing and retention. With private AI everything runs within your own environment, with your own access control and without your input training third-party models. You get the same convenience, but with the control an organisation needs.
Do we need our own AI experts in-house for this?
No. As forward deployed engineers we build and help manage the environment, and only hand over once it works. We set it up so your own people can move forward with it, with clear agreements on management and expansion.
Ready for your own ChatGPT that respects your data?
Book a no-obligation call. In 30 minutes we'll sketch what a private AI environment could look like for your organisation and what a logical first step is.