AI scores at interview time are matched against manager performance reviews at 3, 6 and 12 months, and the correlation is computed on the customer's own hires. No model is trained on candidate data; the platform reports statistics and the hiring decision stays with people.
Most hiring teams flying blind: they have no idea whether their interview process actually predicts who succeeds. HRBlade closes that loop. Every hire's interview score is matched against later performance reviews, and the reporting is calibrated to your specific roles.
We track AI interview score vs. 6-month manager rating per role family. You see exactly how predictive your hiring is — sortable by role, recruiter and team.
The correlation is computed on your own hiring decisions and your own performance outcomes, so it reflects your roles rather than a generic benchmark. It becomes more reliable as you import more closed-loop history.
After a hire, predict probability of departure within 12 months from interview signals + first 30 days. Surface high-risk hires for proactive manager intervention.
Same model identifies internal candidates ready for promotion based on competency and assessment evolution. Talent intelligence beyond just hiring.
Continuous monitoring of pass-rate and performance correlations across protected groups. Adverse impact alerts within 48 hours of statistical detection.
For every hire, the model surfaces which interview signals were most predictive. Refines your interview process: cut signals that don't predict, double-down on those that do.
Every interview gets a per-competency AI score with confidence intervals. Stored alongside the hiring decision.
At 3, 6 and 12 months, managers grade actual performance. The system matches scores against AI predictions automatically.
Every closed-loop hire updates the model. After ~50 hires per role family, predictions for new candidates in that family beat the global benchmark.
Source: Computed on your own hires
Source: Computed per customer from closed-loop hires
Source: Bias monitoring
Discover that your "culture fit" signal predicts nothing while "problem decomposition" predicts everything. Restructure the interview around what actually works.
Compare per-recruiter hire performance: who's calling it right, who's biased toward certain backgrounds. Coach with data, not anecdote.
High-risk new hires get proactive 30/60/90 check-ins from their manager. Reduce first-year attrition by 18% on customer benchmark.
It can't be — manager ratings always have noise. We use multiple signals (peer review, OKRs, retention) and model-aggregate them. We're explicit about the uncertainty: predictions come with confidence intervals, not point estimates.
Multi-agent AI simulates real team dynamics — before you hire, promote, or reorganize.
9 adaptive cognitive games. 95+ calibrated tasks, psychometric backbone, 10 minutes vs. an hour.
Catch flight risk, burnout, and quiet conflict — with evidence quotes from open-text responses.
The information on this website is provided for general information only and does not constitute an offer or a binding commitment. The binding agreement is the Terms of Use at workspace.hrblade.com/terms; where anything on this site is inconsistent with them, those Terms prevail. Product features, availability and figures shown here may change without notice.
