Private AI is not only a model running on a local server. A production solution also requires knowledge ingestion, access rules, monitoring, interfaces and operational ownership.
Choose the architecture based on data sensitivity
Public cloud, private cloud, hybrid and fully on-premise models each have different cost, control and performance characteristics.
RAG connects AI with approved knowledge
Documents and enterprise data are indexed so the model can retrieve relevant context. Access control must follow the user, document and system permissions.
Treat AI as an information system
Logging, evaluation, prompt governance, updates, backup, security and integration APIs are part of the production architecture.