PRIVATE AI
Artificial intelligence deployed on your own infrastructure
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 Contracts, reports, PDFs and spreadsheets.
- Databases and applications ERP, CRM and management applications.
- 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.
Deployments adapted to you
The option is chosen according to the infrastructure available and the data location requirements.
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In your datacentre
Execution on your own servers. The model and the data remain inside your perimeter.
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In your cloud provider
Deployment on the cloud provider you already use, under your own contract.
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Hosted by us
A dedicated deployment on our own infrastructure, in European Union regions, accessed through our own gateway. Where the client decides, it can rely on public inference endpoints.
What we can do
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Talk to your data
- Semantic search (RAG) — Finds information in internal documentation by what the question means.
- Natural language (SQL) — Questions in your own language, translated into SQL queries.
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Agents and automation
- Agents — Query systems and carry out tasks within scoped permissions.
- Automation — Integrations between the tools already in use.
Use cases
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Customer service
Answers to the queries customers repeat most, drawn from the company’s manuals, price lists and terms.
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Draft replies
A drafted reply to internal queries, built from the organisation’s own documentation.
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Data extraction from documents
Reading incoming invoices, delivery notes and orders, and posting their fields into the management system.
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Classification and routing
Routing emails, forms and requests to the corresponding area according to their content.
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.