Free AI Resume Parser for Structured CV Data
A resume parser turns PDF, DOCX, scanned, and image CVs into structured candidate data. Review contact details, skills, work history, and education beside the original, then export JSON, Excel, CSV, Word, or text.
- Review extracted fields beside the original
- Correct the result before export
- Download JSON, Excel, CSV, Word or TXT
Upload your document to get started
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What This Resume Parser Extracts
The parser converts a resume or CV into named candidate fields while retaining the document's raw text for review. Fields appear only when the source resume contains them.
Contact Details
Name, email address, phone number, and location.
Professional Summary
The candidate's profile or summary when one appears in the resume.
Skills
Technical and professional skills found in the document.
Work History
Job titles, employers, date ranges, and role descriptions.
Education
Degrees, institutions, and graduation years shown in the CV.
Raw Resume Text
Editable text that preserves headings, lists, paragraphs, and useful reading order.
What Is Resume Parsing?
Resume parsing is the conversion of an unstructured resume or CV into structured candidate data. Instead of returning one block of text, a parser separates contact details, skills, employers, job titles, dates, and education into fields that can be reviewed, exported, and mapped into another system.
Resume parsing is more than OCR
Optical character recognition recovers readable text from scans and images. Resume parsing adds structure by identifying what each piece of text represents, such as a company, role, employment date, skill, or degree. The original and extracted result should still be checked before the data is used.
From structured export to an ATS
DocuGenie exports JSON, Excel, and CSV for structured workflows, plus Word and TXT for review or reuse. It does not connect directly to an applicant tracking system. Import fields and formats vary, so map the exported columns to the destination system's current requirements.
How to Parse a Resume into Structured Data
Upload
Add a PDF, DOCX, scan, or supported resume image.
Extract candidate fields
The parser organizes contact details, skills, work history, education, and raw text.
Review and export
Check the result against the original, make corrections, and choose an export format.
Resume Parsing Workflows for Small Teams
Use the same structured field set across incoming CVs, then review each result before it becomes part of a hiring workflow.
Incoming Applications
Extract contact details, skills, work history, and education before comparing candidates.
ATS Migration Preparation
Create reviewable JSON or spreadsheet records, then map them to the destination system.
Candidate Databases
Standardize resume fields before adding them to a searchable talent pool or internal database.
ATS Readability Checks
See which names, dates, skills, and roles a parser can recover from a finished resume.
Hiring Manager Review
Turn a small stack of resumes into consistent profiles without adopting an enterprise parser.
Contractor Records
Standardize freelancer and contractor experience before staffing a project.
Review, Correct, and Export the Result
Automated extraction removes repetitive typing; the review workspace keeps you in control of the candidate record.
Original Beside Result
Check the source document while reviewing the extracted profile.
Editable Review
Correct extracted text before copying or downloading it.
Multi-File Workspace
Queue several resumes and review each result separately.
Five Export Formats
Download JSON, Excel, CSV, Word, or TXT.
Structured and Text Views
Switch between candidate fields and the resume's extracted text.
100+ Resume Languages
Parse resumes across major world languages and mixed-language CVs.
How We Compare
Use basic OCR when you only need readable text. Use a resume parser when you need candidate details separated into named fields for review and export.
| Feature | DocuGenie | Basic OCR |
|---|---|---|
| Returns structured candidate fields | ✓ | ✕ |
| Separates work and education histories | ✓ | ✕ |
| Shows an editable review result | ✓ | Usually plain text |
| Exports JSON, Excel, CSV, Word, and TXT | ✓ | Varies |
| Supports scanned and image resumes | ✓ | ✓ |
| Leaves candidate decisions to your team | ✓ | ✓ |
Choose the Resume Parsing Workflow That Fits
DocuGenie is designed for browser-based extraction and human review. Another category may fit better when you need an embedded API, self-hosting, or automatic delivery.
Switching from an enterprise parser API?
Choose an API-first platform when parsing must run inside your product, at high volume, or in a controlled hosting environment.
Switching from a built-in ATS parser?
Use the parser already in your ATS when its fields are reliable and no separate review or export workflow is needed.
Switching from basic OCR?
Use OCR when plain readable text is enough and you do not need candidate fields separated into a stable structure.
Switching from a custom extraction platform?
Choose configurable extraction when every team needs a different schema or document-specific field set.
Resume Parser FAQ
Common questions about using Resume Parser
A resume parser converts an unstructured resume or CV into structured candidate fields. It identifies details such as a name, contact information, skills, work history, employment dates, and education so the result can be reviewed, exported, and mapped into a spreadsheet, database, or applicant tracking workflow.
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Resume Parser is one of 17 document tools in DocuGenie
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