Overview
[Product intro] PageIndex is a reasoning-based document retrieval engine with a vector-database-free architecture. It turns documents into tree-like hierarchical indexes that mimic how human experts read and extract information, then uses large language models for reasoning retrieval. [Core features] Structured index: convert PDFs into directory-like trees that keep full document hierarchy. Reasoning retrieval: tree search for context-aware extraction without vector similarity matching. Traceability: clear page and section citations with transparent, explainable retrieval. Zero infra: no vector DB, chunking, or embedding pipeline. On the FinanceBench financial-document analysis benchmark it reaches 98.7% accuracy—suited to financial reports, legal docs, technical manuals, and other long professional documents. Open-source repo: https://github.com/VectifyAI/PageIndex
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【产品介绍】PageIndex 是一款基于推理的文档检索引擎，采用无向量数据库架构。该产品通过将文档转换为树状层级索引结构，模拟人类专家的阅读和信息提取方式，利用大语言模型进行推理式检索。【核心功能】结构化索引：将 PDF 文档转换为类似目录的树状结构，保留完整文档层级推理式检索：通过树搜索实现上下文感知的信息提取，无需向量相似度匹配可追溯性：提供明确的页面和章节引用，检索过程透明可解释零基础设施：无需向量数据库、文档分块或嵌入管道该产品在 FinanceBench 金融文档分析基准测试中达到 98.7% 准确率，适用于金融报告、法律文件、技术手册等专业长文档分析场景。项目开源地址：https://github.com/VectifyAI/PageIndex