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@ -7,13 +7,13 @@ Traditional vector-based retrieval relies heavily on semantic similarity. Howeve
**[PageIndex](https://vectify.ai/pageindex)** is an indexing system that builds search trees from long documents, making them ready for reasoning-based RAG. **[PageIndex](https://vectify.ai/pageindex)** is an indexing system that builds search trees from long documents, making them ready for reasoning-based RAG.
## ☁️ Cloud API (Beta) ### ☁️ Cloud API (Beta)
Please try our [hosted API for PageIndex](https://pageindex.vectify.ai/). Please try our [hosted API for PageIndex](https://pageindex.vectify.ai/).
The hosted version uses our custom OCR model to recognize PDFs more accurately, providing a better tree structure for complex documents. The hosted version uses our custom OCR model to recognize PDFs more accurately, providing a better tree structure for complex documents.
Leave your email in [this form](https://ii2abc2jejf.typeform.com/to/meB40zV0) to receive 1,000 pages for free. Leave your email in [this form](https://ii2abc2jejf.typeform.com/to/meB40zV0) to receive 1,000 pages for free.
## **⭐ What is PageIndex** # **⭐ What is PageIndex**
PageIndex can transform lengthy PDF documents into a semantic **tree structure**, similar to a "table of contents" but optimized for use with Large Language Models (LLMs). PageIndex can transform lengthy PDF documents into a semantic **tree structure**, similar to a "table of contents" but optimized for use with Large Language Models (LLMs).
It’s ideal for: financial reports, regulatory filings, academic textbooks, legal or technical manuals or any document that exceeds LLM context limits. It’s ideal for: financial reports, regulatory filings, academic textbooks, legal or technical manuals or any document that exceeds LLM context limits.