@cevenif: Traditional RAG is being directly overturned by a tool called PageIndex. It doesn't need vector databases, embeddings, chunking, or even similarity search. Instead, it builds a tree index for documents, allowing LLMs to drill down layer by layer like a human. On FinanceBench, it achieved 98.7%...
Summary
PageIndex is an open-source tool that builds a tree index of documents, eliminating the need for vector databases and embeddings, enabling efficient LLM retrieval. It achieves 98.7% accuracy on FinanceBench.
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The traditional RAG approach is being upended by a tool called PageIndex. It doesn’t use vector databases, embeddings, or chunking, and even skips similarity search. Instead, it directly builds a tree-structured index for documents, allowing LLMs to drill down layer by layer like a human.
On FinanceBench, it achieved 98.7% accuracy, leaving existing vector-based solutions behind. The project is open-source, and those working on document analysis and AI retrieval should keep an eye on it.
https://chat.pageindex.ai
PageIndex Chat
Source: https://chat.pageindex.ai/ PDF758Pages
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