PageIndex

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# PageIndex: Vectorless, Reasoning-based RAG

<p align="center"><b>Reasoning-based RAG&nbsp; ◦ &nbsp;No Vector DB, No Chunking&nbsp; ◦ &nbsp;Context-Aware Retrieval&nbsp; ◦ &nbsp;Reads Like a Human</b></p>

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  <a href="https://pageindex.ai/developer">🌐 Website</a>&nbsp; • &nbsp;
  <a href="https://developer.pageindex.ai/">☁️ Cloud</a>&nbsp; • &nbsp;
  <a href="https://docs.pageindex.ai">📖 Docs</a>&nbsp; • &nbsp;
  <a href="https://pageindex.ai/blog">📝 Blog</a>&nbsp; • &nbsp;
  <a href="https://pageindex.ai/contact">✉️ Contact</a>&nbsp;
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<details open>
<summary><h2>Updates</h2></summary>

- [Oct '26] 🔥 [**Page Search API**](https://search.pageindex.ai): find the pages that answer each question in about a second, and send your LLM only those. *Cut 97% token cost on document question answering*; more accurate and faster than vector search ([benchmark](https://github.com/VectifyAI/page-search-benchmark)).
- [Aug '26] [**PageIndex SDK**](#quickstart): **local** and **cloud** modes — one client to index, retrieve, and chat on your machine (with your own LLM API key) or on [PageIndex Cloud](https://developer.pageindex.ai/).
- [Aug '26] ⚡ [**PageIndex Flash**](https://pageindex.ai/blog/pageindex-flash): fast tree index generation for text-based PDFs, now the default indexing method in PageIndex SDK local mode.
- [Scale PageIndex to Millions of Documents](https://pageindex.ai/blog/pageindex-filesystem): *PageIndex File System* is a file-level tree indexing layer that lets PageIndex reason over an entire corpus, not just a single document.
- [PageIndex App](https://app.pageindex.ai): a human-like document analysis agent for long professional documents.<!-- Also available via [MCP](https://pageindex.ai/developer) or [API](https://pageindex.ai/developer). -->

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# What is PageIndex?

Are you frustrated with vector database retrieval accuracy for long and complex documents? Vector-based RAG retrieves by semantic **similarity**. But **similarity ≠ relevance** — what retrieval actually needs is relevance, and relevance requires **reasoning**. On professional documents that demand contextual understanding, domain expertise, and multi-step reasoning, similarity search misses what is relevant but not similar, and returns what is similar but not relevant.

Inspired by AlphaGo, **[PageIndex](https://vectify.ai/pageindex)** replaces the vector index with a **hierarchical tree index** and lets an LLM **reason** its way through it, th