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Vision-RAG / Multimodal Retrieval (EXPLAINED)

Scenario BasedRAGHard25 min read

Hard RAG interview question on vision-rag / multimodal retrieval — architecture, trade-offs, eval, and production patterns.

TL;DR — Quick Answer

Embed images and text in a shared multimodal space or use VLM captions as text proxies. Retrieve image+text for diagrams and scans; generation may use a VLM with retrieved visual context.

The Interview Question

Explain vision-rag / multimodal retrieval. How would you design, implement, and evaluate this in a production RAG system? Discuss trade-offs and failure modes.

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