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# 📄 PageIndex # 📄 PageIndex
Are you frustrated with vector database retrieval accuracy for long professional documents? Traditional vector-based RAG relies on semantic *similarity* rather than true *relevance*. But what we really need in retrieval is **relevance** — which requires **reasoning**. When working with professional documents that demand domain expertise and multi-step reasoning, similarity search often falls short. Are you frustrated with vector database retrieval accuracy for long professional documents? Traditional vector-based RAG relies on semantic *similarity* rather than true *relevance*. But what we truly need in retrieval is **relevance** — which requires **reasoning**. When working with professional documents that demand domain expertise and multi-step reasoning, similarity search often falls short.
**Reasoning-based RAG** offers a better alternative: enabling LLMs to *think* and *reason* their way to the most relevant document sections. Inspired by AlphaGo, we propose to use *tree search* to perform structured document retrieval. **Reasoning-based RAG** offers a better alternative: enabling LLMs to *think* and *reason* their way to the most relevant document sections. Inspired by AlphaGo, we propose to use *tree search* to perform structured document retrieval.
**[PageIndex](https://vectify.ai/pageindex)** is a *document indexing system* that builds *search tree structures* from long documents, making them ready for reasoning-based RAG. **[PageIndex](https://vectify.ai/pageindex)** is a *document indexing system* that builds *search tree structures* from long documents, making them ready for reasoning-based RAG.
Self-host it with this open-source repo, or try our [Cloud service](https://pageindex.vectify.ai/) — no setup required, with advanced features like OCR for complex PDFs.
Built by [Vectify AI](https://vectify.ai/pageindex). Built by [Vectify AI](https://vectify.ai/pageindex).
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``` ```
You can customize the processing with additional optional arguments: You can customize the processing with additional optional arguments:
```bash ```
--model OpenAI model to use (default: gpt-4o-2024-11-20) --model OpenAI model to use (default: gpt-4o-2024-11-20)
--toc-check-pages Pages to check for table of contents (default: 20) --toc-check-pages Pages to check for table of contents (default: 20)
--max-pages-per-node Max pages per node (default: 10) --max-pages-per-node Max pages per node (default: 10)
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# ☁️ Cloud API (Beta) # ☁️ Cloud API (Beta)
Don’t want to host it yourself? Try our [hosted API](https://pageindex.vectify.ai/) for PageIndex. The hosted version uses our custom OCR model to recognize PDFs more accurately, providing a better tree structure for complex documents. Don’t want to host it yourself? Try our [hosted API](https://pageindex.vectify.ai/) for PageIndex. The hosted version uses our custom OCR model to recognize PDFs more accurately, providing a better tree structure for complex documents.
You can also explore results visually with our [web Dashboard](https://pageindex.ai/files) — no coding needed.
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.
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