Upload any PDF and get instant, accurate answers. DocuChat uses Page Index's tree-structured RAG — no vectors, no chunking — for retrieval that actually understands document structure.
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What were the revenue highlights in Q4?
Based on the annual report p.12, Q4 revenue reached $4.2B, a 23% increase year-over-year driven by...
A fundamentally different approach to document intelligence. No embeddings. No chunking. Just structured understanding.
Page Index builds a tree-structured index that mirrors your document's hierarchy — sections, subsections, and all. No lossy embeddings.
An LLM agent navigates the document tree like a human expert would — reasoning about what to read next, not just matching keywords.
Responses stream in real-time via Groq's ultra-fast inference. See tokens appear instantly while retrieval works in parallel.
SuperMemory stores conversation context across sessions. Pick up where you left off — your assistant remembers what you discussed.
Upload multiple PDFs and query across all of them. DocuChat synthesizes information from every indexed document.
Every response is anchored in your actual document content with page references. No hallucinated facts, no made-up citations.
Three steps from PDF to insight.
Drop your PDF into DocuChat. Page Index automatically builds a hierarchical tree index of the entire document.
Ask any question in natural language. The agentic retriever navigates the tree to find exactly the right content.
Receive grounded, cited responses streamed in real-time. Every answer links back to specific pages in your document.
A modern stack designed for speed, accuracy, and reliability.
Page Index
Vectorless RAG
Tree-structured document indexing and agentic retrieval
Groq
LLM Inference
Ultra-fast Llama 3.3 70B inference for real-time streaming
SuperMemory
Memory Layer
Persistent conversation memory and semantic search
Next.js
Framework
Full-stack React with API routes and server rendering
Upload a PDF and get answers in seconds. No sign-up required.