Self-hosted AI vs ChatGPT: which is safe for company data?

Short answer

Self-hosted AI runs the language model on servers you control, so prompts, uploaded files and generated answers never leave your infrastructure. That makes self-hosted AI the safer option whenever company data is confidential, regulated or covered by client contracts. Public services such as ChatGPT are fast to adopt and very capable, but every request is processed by a third party outside your control, which is why they suit public or low-sensitivity work rather than sensitive internal data.

Where does the data actually go?

The safety question is really a data-location question. With a cloud AI service:

• Your prompt and any attached documents are transmitted to the provider.
• They may be retained, logged, or used to improve models, depending on the plan and settings.
• Processing often happens outside the EU, which raises GDPR transfer questions.
• You depend on the provider's security, uptime and policy changes.

With self-hosted AI, the model weights sit on your own VPS, dedicated server or colocated hardware. Data stays inside your network perimeter, logs belong to you, and no prompt is shared with anyone.

GDPR, NIS2 and EU data sovereignty

If you process personal data, GDPR requires you to know where that data is handled and on what legal basis. Sending customer records or HR files to a consumer AI tool is difficult to justify. For companies in scope of NIS2, supply-chain and data-processing controls are now a formal obligation, and "we pasted it into a chatbot" is not an acceptable control. Keeping inference inside an EU data centre, for example CloudHosting's Riga facility, keeps the data under EU jurisdiction and simplifies both your record of processing and your audits.

How to run self-hosted AI

Open-weight models such as Llama, Mistral and Qwen now run well on modest hardware. A common starting point is Ollama on a Linux server:

# Install and run a local model
curl -fsSL https://ollama.com/install.sh | sh
ollama pull llama3.1
ollama run llama3.1

# Expose an internal API for your apps
curl http://localhost:11434/api/generate -d '{
  "model": "llama3.1",
  "prompt": "Summarise this contract clause:"
}'

Sizing guidance: a 7B to 8B model runs on a CPU VPS with 16 GB RAM for light use, while larger models or many concurrent users want a GPU server. For a ready-made stack with a chat interface, document search and access control, CloudHosting's OpenClaw self-hosted AI packages the model, a web UI and storage on EU infrastructure, so you do not assemble it yourself.

When ChatGPT is the right tool

Self-hosting is not always necessary. A public service is reasonable when:

• The content is already public or contains no personal or confidential data.
• You are drafting generic marketing copy, code snippets or brainstorming.
• You have a signed data-processing agreement and a business plan with retention disabled.

A practical policy is to allow cloud AI for public tasks and require self-hosted AI for anything touching customer data, source code, financials or legal documents.

Takeaway

Ask one question before you type into any AI tool: would you be comfortable if this text were stored on someone else's server? If not, use self-hosted AI on infrastructure you control, ideally in an EU data centre, and keep the sensitive data at home.