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When a resume is uploaded to Equip, AI extracts the candidate’s contact details, work experience, education, and skills into structured fields, then matches those values against Equip’s canonical databases so every profile is searchable and comparable.
Equip’s CV parsing turns an unstructured resume file into a structured candidate profile. The same parser runs whether a candidate applies themselves or a recruiter imports resumes in bulk.

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Where Parsing Happens

Resumes enter Equip through two flows, and both are parsed automatically: For a candidate applying through your job post link, the flow looks like this:
1

Upload a resume

The candidate opens your job post, starts the application, and uploads their resume as a PDF of up to 10 MB.
2

Wait for parsing

Parsing typically takes 30 to 45 seconds. Equip extracts the resume’s contents into the form fields.
3

Review and submit

The candidate checks the pre-filled details, corrects anything the parser got wrong, completes any remaining fields, and submits.
Candidates added through bulk import are marked as email not verified and do not receive stage-change emails until their address is verified. See Bulk CV Import for the full workflow.

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Extracted Fields

The parser extracts the following data from each resume: The extracted values appear on the Candidate Profile under sections such as Experience, Education, and Preferences. They also power dashboard filters, Candidate Search, and Talent Rediscovery.
Parsed data is the raw material for the Job Fit Score. The cleaner the structured profile, the more useful the AI ranking of your applicant pool.

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Normalization

Raw resume text is messy: the same skill, city, or employer can be written a dozen ways. After extraction, Equip normalizes each value against its canonical databases of:
  • Skills
  • Roles
  • Cities
  • Companies
  • Educational institutions
This means “JS”, “Javascript”, and “JavaScript” resolve to one skill, so filters, search, and fit scoring treat them identically.
Institution matching is country-aware. A university name is resolved in the context of its country, which avoids mixing up similarly named institutions in different regions.

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Parsing Failures

Parsing can occasionally fail, and the outcome depends on the flow: Bulk import failure reasons include missing email, missing name, duplicate application, and parsing failure. The batch detail page lists every file by category, so you can see exactly which resumes need attention.
Only supported file types are parsed. Application-form and bulk-import uploads must be PDF files of 10 MB or less. Other formats are rejected before parsing begins.
If a candidate’s resume changes later, a recruiter can replace it from the candidate profile. Replacement uploads accept PDF, DOC, and DOCX files up to 10 MB, and the re-upload is logged in the Candidate Journey.