Private AI for businesses
What it is, how it works on your own documents, and how it differs from using ChatGPT or Copilot directly.
What is private AI?
An AI assistant that answers using your company's documents, running inside your own infrastructure and sending nothing to a third party.
Answers with your documents
Manuals, contracts, policies, quotes. The answer comes from there, not from the model's generic memory.
RAG: searches before answering
It first retrieves the relevant passages from your documents, then writes the answer from them.
Cites the source, doesn't improvise
Every answer is anchored to an actual document from your company, not to whatever the model learned during training.
Why your business needs private AI
This goes beyond a technical choice. It's about protecting what makes your business competitive.
Protects what sets you apart
Your processes, your contracts, the way you solve problems. That's what sets you apart. If every query about that knowledge goes through an external provider's cloud, you depend on their infrastructure and their data-use policy for something that should be exclusively yours.
Real privacy and confidentiality
Payroll, customer data, intellectual property, ongoing negotiations: if a cloud provider ever has a breach, the legal and reputational risk is yours, not theirs. With your own perimeter, you decide who has access, and it's logged.
The cost of waiting
While you evaluate whether it's worth it, competitors who already adopted AI well are pulling ahead in response speed and in how they leverage their own internal knowledge. That gap gets harder to close the longer you wait.
From question to cited answer
Your documents, indexed
Manuals, contracts and policies are processed once and become searchable in plain language.
Retrieval of the relevant passage
For every question, the system finds which fragments of which documents contain the answer.
The model writes, without inventing
The answer is generated from those specific fragments, citing the document and page.
All inside your perimeter
Documents, search and model run on your infrastructure. Nothing leaves for a third party's cloud.
A dedicated server in your own offices
In practice, private AI lives on a physical machine (or a small cluster, depending on volume) connected to your internal network, inside your office or your own datacenter. It's not another provider's cloud account with more locks on it: it's hardware you control.
That server hosts the language model, the search over your documents, and all the orchestration between them. Your employees' questions never leave your network, not for training and not for querying.
Sized to fit
Hardware is calculated from your document volume and concurrent users, so it's neither oversized nor short.
On top of your current storage
It connects to the folders, intranet or document manager you already use. Nothing has to move to get started.
What you gain with private AI
Full control of your data
It never leaves your perimeter, whether for answering or for training anything.
Protects your competitive edge
Your internal knowledge never feeds or gets exposed to a third party's infrastructure.
Native GDPR compliance
There's no third-party transfer to audit, so compliance comes by default rather than as a patch.
Predictable cost
No variable bill per token or per call to an external API that grows with your adoption.
Works without depending on the internet
Once deployed it runs inside your network, with no dependence on an external service's uptime.
Traceable and auditable
Every answer cites its source document and page, so you know exactly where each piece of data came from.
Scales with you
The same server covers more use cases as adoption grows across the company.
No intellectual property leakage
Contracts, quotes and proprietary processes never pass through a model you don't control.
Private AI vs ChatGPT
ChatGPT, Copilot and similar tools are excellent generalist assistants. What they aren't is a tool built to answer using your company's internal, confidential knowledge.
Before you ask
Is this the same as using ChatGPT Enterprise or Microsoft Copilot?
No. Those tools still process your data in the provider's cloud, even under enterprise contracts. Private AI runs both the model and the search inside your own infrastructure, so there's no data transfer to a third party at any point.
Do I need powerful servers of my own?
It depends on document volume and concurrent users. A pilot with a few hundred documents runs on moderate hardware, no dedicated GPU required. We size the exact hardware for your case before starting.
Where exactly does the server get installed?
Inside your network, in your own offices or your datacenter if you already have one. It's not a virtual machine in a third party's cloud with extra locks on it: it's physical hardware under your control, connected only to your internal infrastructure.
Does it stop working if the internet goes down?
No, once deployed. The model and the search run inside your local network, so availability depends on your own infrastructure, not on an external service.
Is it slower or worse than ChatGPT?
For general knowledge questions it doesn't compete, ChatGPT has far more world knowledge behind it. For questions about your own documents, private AI answers more precisely because it searches the real source instead of guessing.
Can I try it before committing to anything?
Yes. We start with a concrete, narrow case using your own documents, measurable within weeks, before talking about anything bigger.
Let's see it with your data
A 30-minute call to figure out which case makes sense to start with in your company.