What is a private LLM?
A private LLM is a large language model that runs entirely inside your own isolated environment. All inputs, context and outputs belong to your organisation; your data is not shared with external tech providers and is never reused to train their public models.
You get the power of modern language models on a foundation of security, compliance and full control.
How does a private LLM work?
A private LLM combines three things: a language model, your data, and an isolated environment.
The model. Usually an open-weight model (such as Llama, Mistral or DeepSeek) that runs inside your own environment, instead of a public service on a third party's servers.
Your data. Through a RAG approach (retrieval-augmented generation) or fine-tuning, the model learns your documents, terminology and context. Answers come from your own knowledge base, not from a generic internet model.
The environment. Everything runs inside your secured infrastructure — on-premise or in a private cloud within the EU. No one outside your organisation has access.
Private LLM versus public AI
Public tools like ChatGPT are convenient, but you lose control over your input. Your data can be stored or used to improve external models. A private LLM runs outside that public environment: you stay in control and prevent business secrets from leaking out.
Read more: Private LLM vs. ChatGPT
When is a private LLM right for you?
A private LLM delivers the most value when at least one of these applies:
- You work with sensitive or confidential data (customer records, case files, medical or financial information).
- You operate in a regulated sector with strict privacy or compliance requirements.
- You hold valuable intellectual property you don't want to expose to public AI.
- You want to stay independent from foreign hyperscalers and rising licence fees.
If you recognise this, a private LLM is often the safer and ultimately more cost-effective route.
Read more: Private LLM for enterprises
