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How Wink built CV parsing and candidate matching into its ATS

Wink is an applicant tracking system for SMEs, recruitment agencies and public employers. All five HireLayer APIs run inside it: CVs fill candidate profiles on their own, and every job gets its candidates matched and ranked.

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Jules DesclousCo-founder | Product · Wink
Illustration: a CV file is sent to HireLayer CV Extract with POST /api/v3/parser. The response fills a candidate profile in Wink: photo from info_resume.face_url, contact details from info_candidate, experience from work_experiences, education from educations and skills from skills. Below, HireLayer Match gives the candidate a fit of 0.87 for a Senior Full Stack Developer job, with one criterion ideal and one potential, and HireLayer Rank places them first of 12 applicants.
Company
Wink · applicant tracking system
Station F, Paris
Customers
500+ companies
SMEs, agencies, public sector
HireLayer APIs
All five
Parsing, criteria, skills, matching, ranking
Integration
CV import and open jobs
Server-side API calls

The need

Why an ATS like Wink needs parsing and matching

  • CVs from every channel

    Applications arrive from 70+ job boards, a career site and bulk imports, as PDFs, Word files or scans.

  • A profile, not a file

    Wink promises recruiters that a CV fills the candidate profile on its own: photo, contact details, experience, education, skills.

  • The right candidates for each job

    Wink promises to match relevant candidates from the CV database to each job automatically.

The integration

How HireLayer runs inside Wink

Wink’s servers call HireLayer at two moments the ATS already has: a CV arrives, a job opens. Wink stays the system of record.

For every CV

  1. Wink

    A CV is imported

    Job board application, career site or bulk import.

  2. CV ExtractResume Parsing APIPOST/api/v3/parser→ Candidate profile as JSON
  3. SkillsSkills Matching APIPOST/api/v1/skills/match→ Skills mapped to a catalog
  4. Wink

    The profile fills in

    Searchable in the CV database.

The candidate profile, field by field

  • PhotoFrom info_resume.face_url
  • Contact detailsFrom info_candidatefull_name, email, phone_number, location
  • ExperienceFrom work_experiences[]
  • EducationFrom educations[]
  • SkillsFrom skills[]

Outcomes

What the integration brings

In the product

  • Five AI features, no models to maintain

    Parsing, job criteria, skills, matching and ranking stay on the HireLayer side, behind one API key.

  • One schema for every file

    13 file formats, from PDF and Word to phone photos, come back as the same JSON.

For recruiters

  • Profiles filled on import

    No retyping, even when dozens of CVs are imported at once.

  • Relevant candidates first

    Each candidate gets a fit per criterion, and every job its candidates in order.

Wink in numbers

companies recruit with Wink
500+
job boards Wink publishes to
70+
saved per application by CV parsing
2 min+

Figures published by Wink on wink-lab.com. The time saved per application is Wink’s own estimate for its CV parsing feature.

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