📑 What is PageIndex?
PageIndex is a vectorless, reasoning-based RAG (retrieval) framework that simulates how human experts navigate and extract knowledge from long, complex documents. Instead of relying on vector similarity search, it transforms documents into a tree-structured index and enables LLMs to perform agentic reasoning over that structure for context-aware retrieval. The retrieval process is traceable and explainable, and requires no vector database and no chunking.
To learn more, please see a detailed introduction to the PageIndex framework . Also check out our GitHub repo for open-source code, and the cookbooks, tutorials, and blog for additional usage guides and examples.
PageIndex Workflow: Tree index generation, and agentic LLM reasoning over the index for context-aware retrieval
Integrate PageIndex into your agent or application, via MCP and API
Analyze and chat with your documents directly in your browser
Dedicated or private deployment for your organization
Try PageIndex
- PageIndex Chat Platform : Analyze and chat with your documents directly on the web — no setup required.
Integrate PageIndex
- PageIndex Cloud: Integrate PageIndex into your own application or agent. Available via MCP and API.
For Enterprise
- Dedicated or private deployment options are available. Contact us or book a demo to learn more.