RAG means handing your AI the right page from your own documents before it answers. It is powerful when your knowledge base is large, changing, or per-customer. It is also something a lot of teams build too early. Here is the honest decision.
You run a Java product and want to add an AI feature. There are two real framework choices. Here is the honest comparison across providers, RAG, tools, Spring fit, and the one thing that decides it for most teams.
The API price page says a few dollars per million tokens and looks cheap. That is not what your AI feature will cost. Here is the real formula, a worked example, the levers that cut the bill, and when self-hosting actually pays.
Multi-tenancy means one running application serves many customers while keeping their data apart. Here is what it means, the apartment-building analogy that makes it click, the three models, and how tenants stay separated, with links to go deep on each.
Row-Level Security is one layer, not the whole answer. Real tenant isolation is defense in depth across the data, the API, and the keys, so that no single mistake exposes another customer. Here are the layers and where each one earns its place.
The question is not which one wins, it is where you draw the isolation boundary. Here is how single and multi-tenant differ on cost, isolation, compliance, and ops, and why most SaaS that scales ends up running both at once.
