Deployment and operation of language models and AI services on your own servers – your data stays within the company.
Many companies cannot allow sensitive data to be sent to external cloud providers. For them we build a private AI environment running inside the company: open-weight language models (such as Llama, Mistral or Qwen), a company chat interface and an API.
We assess your needs, size and source the hardware (GPU server), install and tune the models, then operate and update the system on an ongoing basis.
What you get
- Hardware sizing and GPU server selection
- Installation and optimisation of open-weight LLMs (vLLM, Ollama)
- Company chat interface with single sign-on (SSO)
- OpenAI-compatible internal API for your own applications
- Monitoring, backups, updates and security maintenance
Benefits
- Full data sovereignty and GDPR compliance
- Predictable costs independent of per-token pricing
- Works without an internet connection
- Models customisable to your domain
Technologies
- vLLM
- Ollama
- Open WebUI
- NVIDIA GPU
- Docker
- Kubernetes
Frequently asked questions
What hardware do we need for private AI?
It depends on the number of users and the model size. A small team is often fine with a powerful GPU workstation; for heavier loads we recommend a dedicated GPU server – we determine this precisely during the assessment.
Are open models as good as cloud services?
For most business tasks (summarisation, document search, email drafting, data extraction) today's open models perform very well, especially combined with RAG.