On-premise AI platform
GPU servers, model serving, storage and monitoring set up inside your own data centre or dedicated tenancy.
Private AI · On-premise AI · Self-hosted LLM
Private AI that knows your business.
An internal AI assistant grounded in your own documents, code and systems, running on infrastructure you control. Integritasec builds the hosting and the AI together, in a private cloud, on-premise or in an air-gapped network.
What is included
Private AI, end to end.
Self-hosted LLM
Open language models running on your hardware, sized to your workload, for cases where nothing may leave the network.
RAG on company data
Retrieval-augmented generation over your knowledge base, tickets, wikis and repositories, respecting existing access rights.
Claude in your own cloud account
Claude and other leading models used through your own cloud tenancy and data controls when a managed model is acceptable.
Private cloud hosting
The internal cloud underneath: Kubernetes, networking, backups and security, built and operated for you.
Security and compliance
Access control, encryption, logging and data boundaries designed with ISO 27001 practices in mind.
When to call
Signs it is time.
- Company policy forbids public AI tools
- Staff paste internal data into public chatbots anyway
- Knowledge is scattered across wikis, tickets and drives
- Regulators or customers ask where your data goes
- You want AI but work in an air-gapped environment
Tools in daily use
- Claude
- Open models
- Kubernetes
- OKD
- VMware
- PostgreSQL
- Elastic
- Prometheus
- Grafana
How it works
Start with a short assessment, continue with a fixed-scope project, or keep a set number of days each month. See ways to work together.
Related guides
Questions
Common questions.
What is private AI?
Private AI means running AI models and the data they use inside infrastructure you control, so prompts, documents and answers are not shared with a public service or used to train someone else's model.
Can a large language model run on-premise?
Yes. Open models can be self-hosted on your own GPU servers, including in networks with no internet access. The right model size depends on your use case, number of users and hardware budget.
How does an AI assistant learn our company data?
Usually through retrieval-augmented generation (RAG): your content is indexed inside your environment and the assistant looks up the relevant passages when answering. Fine-tuning is added only where it clearly pays off.
Related services
Book a call
Talk it through. Thirty minutes, no slides.
Bring the problem as it is. You will leave with a clear view of what it would take to fix.