Designing an End-to-End RAG Architecture from Scratch

Building an AI-powered application is easy to describe.

Upload documents → ask a question → get an answer.

Actually building that flow is a different story.

While working on Guidely, an internal knowledge assistant, I wanted to understand what happens between those two endpoints. More importantly, I wanted to design the system so that each part had a clear responsibility and could be tested independently.

The result was an end-to-end Retrieval-Augmented Generation (RAG) system built around a simple pipeline:

Designing an End-to-End RAG Architecture from Scratch

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