1. Use case and data
We pick the process and the documents worth starting with, and review which permissions must be respected.
AI automation · Private AI
Private AI on your own infrastructure
Generative AI over your contracts, case files and internal documents, running on your infrastructure. Your data is never sent to an AI provider.
When it makes sense
When this way of working fits
- Confidential or personal data that cannot leave the company.
- Regulated sectors with obligations about where information is hosted.
- Intellectual property and R&D you do not want to expose to a third-party service.
- Companies that cannot use public AI because of internal policy or client contracts.
How it works
The journey of a query
One question, four steps and no data outside your environment.
- UsersThey sign in with their Microsoft account and only see what they could already see.
- InterfaceOur own application with corporate sign-in: no new accounts and no shared passwords.
- Model on your serverThe open model runs on your infrastructure or in a private cloud in the European Union.
- Your documentsQueried with each user's permissions and never sent to an external provider.
What it includes
Four phases, from trial to operation
2. Pilot
We test it with two or three real processes and real users, and measure quality before widening it out.
3. Production
Named users, query logging, backups and monitoring from our SOC.
4. Ongoing operation
Model updates, quality reviews and cost control as usage grows.
Security
What is not negotiable
- Each user only queries the documents they can already open: permissions are neither duplicated nor relaxed.
- Data connectors are read-only, so the AI never changes your systems.
- Every query is logged so you can audit what was asked and what answer was given.
- Protection against hidden instructions in documents: a file cannot change the model's behaviour.
Common questions
Questions about Private AI on your own infrastructure
Is it as good as ChatGPT or Copilot?
For working on your own documents it is usually enough. In complex reasoning, the best cloud models are still ahead. We measure it in the pilot before deciding.
Do I need to buy servers?
It depends on the case: a GPU server on your premises or a private cloud in the European Union. We size it in the assessment.
Who sees my data?
Only your authorised users. We access it solely to operate the service and every access is logged.
Which models do you use?
Open models such as Qwen, Gemma, Mistral or gpt-oss, chosen by licence, language and use case. They are examples of available technology: we are not a partner of, or accredited by, any of them.
How does it fit with the EU AI Act?
The systems you run also fall within the scope of the Act: transparency duties, data control and, where applicable, high-risk requirements. See AI governance
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