ParseMe reads structured application forms — scanned or PDF — and pushes candidate data directly into your ATS or hiring spreadsheet.
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Employment Application Form
PERSONAL INFORMATION
Full Legal Name: Jordan Lee
Email: jordan.lee@email.com Phone: (312) 555-0122
Address: 1840 N Damen Ave, Chicago, IL 60647
POSITION & AVAILABILITY
Position Applied For: Senior Account Manager
Desired Salary: $95,000/yr
Date Available: 06/01/2026 Type: ☑ Full-time ☐ Part-time
AUTHORIZATION
Are you legally authorized to work in the U.S.? ☑ Yes ☐ No
Will you now or in the future require sponsorship? ☐ Yes ☑ No
How did you hear about us? LinkedIn
Extracted Data
Every field ParseMe can pull from job applications.
| Field | Type | Description |
|---|---|---|
| applicant_name | string | Full legal name |
| string | Email address | |
| phone | string | Phone number |
| position_applied | string | Position applied for |
| salary_requirement | number | Desired salary |
| available_start | date | Earliest start date |
| work_authorized | boolean | Legally authorized to work |
| requires_sponsorship | boolean | Requires visa sponsorship |
| referral_source | string | How they heard about the role |
Auto-create ATS candidate records from emailed application PDFs
Run eligibility screening before a recruiter reads a single resume
Track source attribution across all applications automatically
Export application data into your hiring analytics dashboard
Every document type in your industry — all in one platform.
ParseMe reads PDF, Word, and image resumes — extracting skills, experience, education, and contact info into a clean ATS-ready format regardless of layout.
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ParseMe parses signed or unsigned offer letters — pulling salary, title, benefits, and contingencies so your HR team can verify accuracy before onboarding begins.
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Automate application intake