Extract structured data from research papers.

ParseFlow helps researchers extract tables, citations, metadata, and key findings from academic papers — building structured literature databases without manual data entry.

The old way vs. the ParseFlow way

❌ The Old Way

Researchers manually copy data from tables in PDF papers into spreadsheets, type out citation details, and create literature databases by hand. A systematic review of 100 papers takes weeks of data extraction.

✅ The ParseFlow Way

Define schemas for the data you need — study characteristics, results, citations — and let ParseFlow extract it from all 100 papers. Export to CSV for meta-analysis or database import.

Example extraction schema

Define this schema once in ParseFlow, then reuse it across all your academic research documents.

{
  "title": "string",
  "authors": ["string"],
  "journal": "string",
  "year": "number",
  "doi": "string",
  "abstract": "string",
  "methodology": "string",
  "sample_size": "number",
  "key_findings": ["string"],
  "limitations": ["string"],
  "keywords": ["string"]
}

Input → Output

Input (PDF)

A published journal article PDF with title page, abstract, methodology section, results tables, discussion, and reference list.

Output (Structured Data)

Title: Effects of AI-Assisted Learning on Student Outcomes, Authors: [Chen et al.], Journal: Educational Technology Research, Year: 2024, DOI: 10.1234/etr.2024.567, Sample size: 450, Key finding: 23% improvement in test scores.

Automate academic research today

Stop copying data by hand. ParseFlow extracts structured data from your PDFs in minutes — entirely on your Mac.

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