I ve been building RAG Orchestration Studio around one core idea: RAG is not just a vector database pattern, it is a retrieval architecture problem.
A lot of teams still start with embeddings, a vector DB, and top-k retrieval, then try to force the problem into that shape. But many real-world retrieval systems depend on structure, relationships, metadata, temporal context, and precision requirements.
I m curious how others here are thinking about retrieval design in practice.
When you work on RAG systems, how do you decide between:
RAG Orchestration Studio is a browser-based environment for exploring and designing retrieval architectures. It helps teams compare vector, graph, hybrid, and vectorless RAG patterns, visually design workflows, and think through tradeoffs before committing to implementation. Built for practitioners who want to treat RAG as an architecture problem, not just a vector database pattern.
