Resume Parser
Candidate screening

Screen Candidates with Structured Resume Data

Apply the same criteria to every applicant

The problem

Manual screening is inconsistent: reviewers tire, and different recruiters apply different standards to the same role.

The solution

Resume Parser gives you structured fields for every applicant: roles with dates, educations, locations, links, and languages, plus markdown role descriptions. Your own screening logic runs against those fields and applies the same rules to everyone. The parser does not screen or rank candidates itself.

How it works

  1. 1

    Define criteria per role

    Decide what is required (for example a language at a stated level or a minimum number of years in similar roles) and what is a preference.

  2. 2

    Parse every application

    Send each PDF to the API. Responses can take up to 60 seconds.

  3. 3

    Apply your rules

    Your code evaluates the fields and the description text against the criteria and produces a shortlist.

  4. 4

    Recruiter reviews the shortlist

    People make the decision; the structured data shows why each candidate was flagged.

Key benefits

Same rules for every applicant

Criteria evaluated in code apply identically to the first and the last application.

Computable experience

Numeric start and end dates let you calculate time in each role.

Languages with levels

Languages listed on the CV come back with their stated levels.

Questions

Frequently asked questions

No. It returns structured data. Screening and ranking logic is yours.

There is no skills field. Search the markdown description of each role for the skill and add up the durations of those roles.

That depends on your criteria and jurisdiction. Use job-relevant criteria, apply them consistently, keep a human in the decision, and check the rules that apply to you.

Prototype your criteria on real parsed data

Use the 50 free parses per month on resumes from a recent posting.

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