built on cross-referenced factsProduction-ready outputs built on cross-referenced facts
The highest accuracydocument extraction for your AI
Drop a document. Ask anything.
Get accurate answers, with sources.Drop a document. Ask anything. Get accurate answers, with sources.
$ pip install proofpudding
from proofpudding import PDF
PDF.load("tesla_10k_2024.pdf").extract("List all subsidiaries")[0]
{
"name": "Tesla Motors Netherlands BV",
"jurisdiction": "Amsterdam, NL",
"ownership": "100%",
"_proof": { "page": 142, "text": "wholly-owned subsidiary...",
"bbox": [0.12, 0.34, 0.88, 0.41] }
}Put it to the test
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No signup required. Your document is processed and deleted.
Document extraction
that proves itself
Every answer traced back to the source
Any document or language
PDFs, scans, tables, forms. 200+ pages. Japanese, Korean, Arabic, Thai, Chinese, and more.
Evidence for every answer
Every value links to the exact page and source text. Verifiable by default.
Predictable costs
Pay per extraction, not per token. Budget based on task complexity.
Best-in-class accuracy
Production-ready outputs built on cross-referenced facts. No guessing, no gaps.
Minimal code, maximum data
Load, extract and use in a few lines of code
from proofpudding import PDF
doc = PDF.load("contract.pdf")
Works with your stack
Native integrations for every major agent framework
Pay per extraction
No subscriptions, no minimums
Questions
PDF (native and scanned), DOCX, images (PNG, JPG). More coming soon.
Our agent processes documents up to 200 pages. For longer documents, contact us.
All languages Claude supports, with particular strength in English, Japanese, Korean, Chinese, Arabic, Thai, and European languages.
Documents are processed and deleted. We don't store your data.
LlamaParse converts documents to markdown for RAG. We extract structured data from specific queries. Parsing ≠ extraction.
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$ pip install proofpudding