Parse hundreds of resumes in minutes.
ParseFlow extracts candidate names, contact details, skills, work experience, and education from PDF resumes — perfect for recruiters processing high volumes of applications.
The old way vs. the ParseFlow way
Recruiters manually review each resume, copying candidate details into an ATS or spreadsheet. With 200 applications for a single role, it takes days just to create a structured shortlist.
Drop all 200 resumes into ParseFlow. In minutes, you have a structured spreadsheet with every candidate's name, skills, experience, and education — ready to filter and shortlist.
Example extraction schema
Define this schema once in ParseFlow, then reuse it across all your resume / cv parsing documents.
{
"name": "string",
"email": "string",
"phone": "string",
"location": "string",
"summary": "string",
"skills": ["string"],
"experience": [{
"company": "string",
"title": "string",
"start_date": "string",
"end_date": "string",
"description": "string"
}],
"education": [{
"institution": "string",
"degree": "string",
"year": "number"
}]
}Input → Output
A two-page PDF resume with contact info, professional summary, skills section, work history, and education.
Name: Thomas Müller, Email: t.mueller@email.de, Location: Berlin, Skills: Python, SQL, Machine Learning, TensorFlow, 3 positions extracted (Senior Data Scientist at TechCo, 2022-present), Education: M.Sc. Computer Science, TU Munich, 2019.
Automate resume / cv parsing today
Stop copying data by hand. ParseFlow extracts structured data from your PDFs in minutes — entirely on your Mac.
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