[HN]score: 0.35
Kapa's RAG Image Indexing: Vision Descriptions at Index Time Cut Query Overhead to 1–6%
June 2, 2026
Kapa describes images once at indexing time using a cheap vision model, stores text descriptions, and retrieves them alongside text chunks, reducing per-query overhead to 1–6% over text-only RAG while producing statistically significant answer quality improvements. The approach avoids sending raw images to the model at query time, making it cost-effective at scale across millions of technical documentation images.
HOW THIS AFFECTS YOU
●
builderYou can adopt this index-time vision description pattern today to add image-aware retrieval to your RAG pipeline with minimal per-query cost increase.
●
researcherThe statistically significant quality improvement with a lightweight indexing-only vision pass is a concrete data point for multimodal RAG architecture decisions.