PRIVATE AI
AI that never leaves the building
Artificial intelligence projects built on your own infrastructure. The documents, the databases and the record of what gets asked all stay where they already are.
What data the AI works with
- Documents Internal documentation, in its current location.
- Databases The existing ones, with no copy to another system.
- The AI Execution on your own server or private cloud.
- Audit Who asked what, and what was answered.
Documents are not incorporated into third-party models or training processes.
WHAT THAT MEANS IN PRACTICE
- Documents are not incorporated into third-party models or training processes.
- The execution environment is determined by the client and can be changed later.
- The audit log is the client’s property and exportable.
Four places it can run
The option is chosen according to the infrastructure available and the data location requirements.
-
In your datacentre
Execution on your own servers. The model and the data remain inside your perimeter.
-
In your cloud provider
Deployment on the cloud provider you already use, under your own contract.
-
On Oracle Cloud
Managed inference endpoints or a dedicated deployment, in European Union regions. Access runs through our own gateway in both cases. The model is changed without touching the application.
-
The database does not move
The database remains in its current location, with no copy or export. Compute runs where GPU is available, over a private tunnel.
What we can do
-
Talk to your data
- Semantic search (RAG) — Finds information in internal documentation by meaning rather than exact wording.
- Natural language (SQL) — Questions in your own language, translated into SQL queries.
-
Agents and automation
- Agents — Query systems and carry out tasks within scoped permissions.
- Automation — Integrations between the tools already in use.
Use cases
-
Draft replies
Replies to repeated queries drafted from the internal documentation.
-
Data extraction from documents
Reading incoming documents and posting their fields into the management systems.
-
Classification of incoming items
Routing emails, forms and requests to the corresponding area according to their content.
-
Case summaries
Synthesis of case files with many documents, with a reference to the source document.
Common questions
- Do I have to buy a server?
- Not in every case. Where there is existing infrastructure or a contracted cloud, deployment is carried out on it. Sizing is matched to the expected volume of use.
- Does this replace someone on my team?
- That is not the usual purpose of these projects. The most common use is to reduce the time spent locating internal information and answering repeated queries.
- What if I want to change model in a year?
- The model is replaceable. The application layer is built decoupled from the specific model, so a change does not require rebuilding the rest.
- How long before something is visible?
- It depends on the state of the source data, which accounts for most of the work.
Each case is assessed against the documentation and databases it starts from.