RAG Orchestration Studio

Design and compare RAG architectures before coding

2 followers

Design and compare RAG architectures before coding

2 followers

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.

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Launch tags:Open Source•Developer Tools•Artificial Intelligence

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I built RAG Orchestration Studio because I think many teams start RAG design too late in the stack. The default path is usually embeddings, vector database, framework, top-k retrieval, then hope the architecture fits the problem. But many real-world retrieval problems depend on more than semantic similarity. They depend on structure, relationships, metadata, temporal context, and precision. RAGOS is an attempt to make that design layer more explicit. It is a browser-based environment where users can explore different RAG patterns, visually design workflows, compare strategies side by side, and think through tradeoffs before committing to implementation. I would especially love feedback on: • which retrieval patterns feel most useful in practice • where the workflow design experience is unclear • what evaluation or comparison features would be most valuable next

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28d ago

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p/rag-orchestration-studio

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28d ago

How are you deciding between vector, graph, hybrid, and vectorless RAG?

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:

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