PageIndex

Vectorless, reasoning-based document retrieval engine that navigates hierarchical content structures for precise, verifiable insights.

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Product Overview

What is PageIndex?

PageIndex is a document analysis and retrieval framework designed to extract accurate answers from long, complex files without relying on vector databases, embeddings, or arbitrary chunking. By transforming documents into hierarchical tree structures that preserve natural document layout and context, PageIndex enables language models to reason through sections like a human expert reading a table of contents. Available via hosted chat, Python SDK, REST API, and Model Context Protocol (MCP), it provides fully traceable citations and explainable context trails for high-stakes analysis.

Key Features

Hierarchical Tree Indexing
Converts documents into multi-level tree structures that retain natural sections, subsections, and logical context without arbitrary text chunking.
Vectorless Reasoning Retrieval
Replaces approximate vector similarity search with structured model reasoning, navigating document nodes directly to target information.
Traceable Page-Level Citations
Delivers verifiable answers backed by exact page and section references with fully auditable reasoning paths.
Developer & MCP Integration
Integrates into existing agent workflows and development stacks through a Python SDK, REST API, and Model Context Protocol (MCP) server.
Enterprise Scale File System
Extends tree-based reasoning across large-scale document repositories, supporting massive multi-document search and retrieval.

Use Cases

Financial Analysis & Due Diligence : Investment teams and analysts can reliably extract metrics, footnotes, and risk factors across dense financial reports and 10-K filings.
Legal & Compliance Review : Legal teams can audit complex contracts, regulatory policies, and lengthy compliance bundles with exact source verification.
Technical Documentation Navigation : Engineers and product teams can pinpoint specifications, architecture guidelines, and manuals without loss of surrounding context.
Enterprise Knowledge Search : Organizations can deploy structured document search across internal files without managing embedding pipelines or vector databases.
Scientific & Academic Research : Researchers can query extensive papers, clinical trial data, and literature surveys with evidence-backed citations.

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StoreClaw

Sponsor

An autonomous commerce engine for online sellers that monitors, executes, and grows your store across all major e-commerce platforms — 24/7, without manual intervention.