Direct answer
Private and secure AI work starts by deciding what information the system actually needs, who may access it, which providers are appropriate and where human review is required.
Design considerations
Secure AI design can include data minimisation, provider evaluation, retention settings, access controls, private knowledge bases, retrieval boundaries, logging and auditability.
RAG and knowledge access
Retrieval-augmented generation can help systems use approved knowledge without exposing unnecessary source material, but it still needs permissions, indexing rules and testing.
Limitations
No page should make absolute security promises. The right design depends on the data, user permissions, providers, integrations and risk tolerance.