RAG Decision Helper

Not every AI app needs a vector database, and some need much more than one. Answer six questions about your project and get a live architecture recommendation with the reasoning spelled out.

How the recommendation works: each answer adds or subtracts points for five candidate architectures, and the highest score wins (ties go to the simpler option). Treat it as a starting point, not gospel - real projects often combine approaches, like fine-tuning a model for tone while using RAG for facts. One rule holds almost universally: start with the simplest architecture that could work, measure quality on real queries, and only add moving parts (rerankers, agents, fine-tunes) when the measurements say you need them.