From PDF to LLM Answers,
With Source Verification
Build document Q&A experiences with pinpoint source highlighting. No hallucination anxiety. Users see exactly where answers come from.
The Pipeline
PDF in, verified answers out. Every step optimized for RAG.
Three Building Blocks
Each component works standalone. Together, they're a complete RAG toolkit.
PyMuPDF4LLM
Extracts text with layout awareness. Tables stay tables. Headers stay headers. Output optimized for LLM consumption.
- Layout-preserving extraction
- Table detection & formatting
- Image extraction with captions
- Chunk-ready output
Source Locator
Maps quoted text from LLM responses back to exact PDF positions. Fuzzy matching handles extraction differences. Zero token cost.
- Fuse.js fuzzy matching
- No additional LLM calls
- Handles whitespace & encoding diffs
- Returns exact coordinates
MuPDF WebViewer
Full PDF viewer in pure JavaScript. Highlight, annotate, redact. All client-side — no server roundtrips, works air-gapped.
- One-line integration
- WebAssembly performance
- Programmatic highlighting
- Works with any framework
// 1. Extract PDF to Markdown
const markdown = await pymupdf4llm.to_markdown(pdfBuffer);
// 2. Get answer from your LLM (with source quotes)
const answer = await yourLLM.ask(markdown, question);
// 3. Locate source in PDF
const coordinates = sourceLocator.find(answer.sourceText);
// 4. Highlight in WebViewer
webViewer.highlight(coordinates);
Built for RAG Developers
Any workflow where users need to verify AI answers against source documents.
Contract Analysis
Ask questions about contracts and instantly see the exact clause. No more manual searching through 100-page agreements.
Financial Report Q&A
Query earnings reports and 10-Ks. Highlight the exact figures and footnotes that support the answer.
Academic Paper Review
Search across papers and pinpoint methodology sections, citations, or specific findings instantly.
Internal Knowledge Base
Turn policy documents and SOPs into a Q&A system. Employees get answers with source verification.
See It in Action
Try the demo or talk to us about your RAG project.