Enable Vision RAG with Voyage AI’s multimodal embeddings to search PDFs, presentations, and visually rich documents without heavy parsing or OCR.

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Vision RAG extends traditional retrieval-augmented generation to handle multimodal documents by using multimodal embeddings instead of OCR. Voyage AI's voyage-multimodal-3 model uses a unified encoder architecture to process both text and images, enabling direct indexing and search of complex documents like PDFs, slides, and diagrams. The tutorial demonstrates building a vision RAG pipeline that extracts insights from GitHub Octoverse charts by embedding images with Voyage AI, performing vector similarity search, and generating answers using Anthropic's Claude vision model.

Vision RAG: Enabling Search on Any Documents

Voyage AI’s latest multimodal embedding model