Free Lesson
Multimodal RAG: Search Images, Tables, and Text
30 min
Jul 6, 2026 4:30 PM
What you'll learn
One index across three content types
Put images, tables, and text into a single searchable store instead of three disconnected pipelines.
Embed pictures the same way you embed words
Use a multimodal embedding model so an image and a sentence land in the same vector space and can be compared directly.
Answer questions that span formats
Return the right result whether the fact is written in prose, sitting in a table, or visible only in an image.
Why this topic matters
Most RAG setups only read plain text, so the moment a screenshot, a chart, or a table holds the answer, retrieval comes back empty. In this free 30 minute session you watch a single multimodal index get built over a mixed folder of images, tables, and text, then answer questions that pull from all three at once. You see how an image embedding model and a text embedding model sit side by side, and how one query reaches both. You leave able to build retrieval that finds the answer whether it lives in a paragraph, a spreadsheet cell, or a picture.
