AI Candidate Evaluation Scorecards
Evaluate candidates fairly with role-specific scorecards, scoring criteria, and consistent grading rubrics.
No credit card required • 14-day free trial
The Problem with Subjective Evaluations
Hiring decisions are often made based on 'gut feeling' rather than skills scorecards.
Scattershot feedback ('seemed nice', 'culture fit') makes candidate comparison impossible.
Inconsistent panel reviews create massive confusion and delay time-to-offer.
How Rifair AI Solves This
Generate structured scorecards aligned to the role's primary requirements.
Give panel interviewers specific guidelines for grading answers (1-5 scale).
Compile feedback into a single dashboard view to compare candidates on skill.
How the Candidate Scorecard Works
Our streamlined AI engines handle the prep so your hiring managers can focus purely on talent.
Define Scorecard Metrics
Input job role, competencies, and interview round type.
Generate Grading Rubrics
Create distinct score metrics for technical, soft, and experience fits.
Conduct Structured Reviews
Interviewers grade candidates based on clear evidence guidelines.
Compare & Hire
View the side-by-side competency comparisons to make objective decisions.
Who Uses Candidate Scorecards?
Unbiased panel review
Compare candidate capability side-by-side using numerical criteria grids.
Standardizing feedback loops
Ensure every panel interviewer uploads structured feedback reports.
Mitigating legal hire risk
Keep documented evidence of skills evaluations for compliance.
Trusted by hiring panels globally
"Rifair AI's scorecards completely removed gut-feel arguments from our candidate review meetings."
