What the AI is doing
Every application is scored against the job you created — not against other candidates. The model reads the CV, the structured fields the applicant fills in, and the answers to your screening questions, then compares them to the job description and required skills.
The five scoring dimensions
- Experience match — years and relevance of past roles.
- Skill match — overlap between required skills and the candidate's CV and answers.
- Education match — qualifications versus what the role calls for.
- Keyword relevance — domain-specific language from the JD.
- Screening quality — depth and clarity of structured answers.
How scores are used
Each application receives a 0–100 score and a recommendation tier (Priority, Strong fit, Review). Candidates at or above your configured threshold can be auto-invited to the next stage; everyone else still appears in your dashboard with a clear breakdown.
Scores are decision-support, not decision-makers. Recruiters always make the final call.
What it does not do
- It does not use gender, ethnicity, age, marital status, or photographs to score anyone.
- It does not learn from your hiring decisions in a way that re-ranks past applicants.
- It does not reject candidates on its own — only your threshold + recruiter action moves a candidate forward.