PageIndex

@PageIndexAI

The last Document AI you'll ever need.

London

Pinned
PageIndex
@PageIndexAI
Oct 31
Jev for RAG? How does the decision model's retrieval performance compare to the top Vector-based model? We announce the Page Search API, faster and more accurate than SOTA embedding models. Learn more: search.pageindex.ai
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PageIndex
@PageIndexAI
20h
Tencent Hy4 surprised us. Hy4 (high) just joined the Pareto frontier on our Financial QA benchmark. ➤ Accuracy: 99.0%, the highest score measured on the benchmark. ➤ Cost: About 1/12 the cost of Claude Opus 5.5 (max) per 100-question run. Congrats @TencentHunyuan ! Try it
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PageIndex
@PageIndexAI
Nov 4
Maps, drawings, scanned forms: PDFs where the answer is in the image, not the text. The hard case for document AI. Page Search agent reads the page, zooms in to search it, and cites the exact region it read. Try it now: search.pageindex.ai/examples/nashv…
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PageIndex
@PageIndexAI
Nov 2
Finding images in PDFs with classic RAG is painful: → PDF parsing → text embedding model → image embedding model → a pipeline to sync them Page Search API: upload, ask, and get the page with the image in seconds. No embeddings. No indexing time. search.pageindex.ai
GIF
PageIndex
@PageIndexAI
Nov 1
Did you know a modern RAG pipeline doesn't need OCR, parsing, embedding models, a vector DB or a reranker? RAG with Page Search: send a query + PDF, get back relevant pages as images, and pass them to a vision LLM. More accurate, simpler, and faster. search.pageindex.ai
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