How we index images for RAG

Kapa built an AI assistant that indexes images from technical documentation by generating text descriptions once at indexing time using a cheap vision model, then retrieves these descriptions as text during queries rather than processing raw images. This approach reduces per-query overhead to just 1-6% compared to text-only retrieval while significantly improving answer quality, avoiding the prohibitive costs and technical limitations of processing images at query time with multimodal models.