Private document AI: when your docs can’t leave the building

Not every team can send contracts or internal docs to a third-party service. Compliance, NDAs, or plain policy often require that document AI stays private. “Private document AI” usually means one of two things: everything runs on your infrastructure, or you use a provider under strict controls and no training on your data.

Why it matters

• Compliance – Regulated industries (legal, healthcare, finance) may require data to stay in-region or on-prem.
• Confidentiality – Client or deal documents shouldn’t be used to train models you don’t control.
• Trust – Even when it’s allowed, some teams simply prefer that their docs never leave their environment.

Option 1: Fully on your side (Ollama)

MindParse AI supports Ollama so you can run both chat and semantic search on your own servers. Your documents never leave your network. You choose the models, updates, and retention. Ideal for air-gapped or highly controlled environments. We have a separate post on setting up Ollama document Q&A.

Option 2: Cloud with clear boundaries

If you use a cloud AI provider, you connect your own account. We don’t train on your data; we only send it to the provider you’ve configured, per their policies. So you get strong AI without putting docs into a shared training pool.

What to look for

A clear statement that your documents aren’t used for training, support for self-hosted or bring-your-own-key, and a security page that explains where data goes. Our security page spells this out; our pricing page shows plans for teams that need more control or capacity.