Watch 47 Applications Get Screened in 28 Minutes.
A real screening run on a sample Senior Product Manager role. Scoring logic, ranked shortlist, reasoning notes — exactly what your recruiters receive.
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Synthetic candidate data used. Scoring model and output format are identical to client builds.
A Ranked Shortlist. Ready in 30 Minutes.
This is the exact format your recruiters receive — score, tier, reasoning, and a recommended action for every candidate.
Candidate score breakdown
Multi-axis fit analysis
Every shortlisted candidate is scored across the criteria that matter for the role — leadership, domain fit, SaaS background, communication, and tenure. The radar gives recruiters an instant read before they open the CV. Example: Sarah Chen.
Candidate relevance after a 30-day calibration with your team
Scores stabilise at 85–92% candidate relevance after a short calibration with your team — monitored weekly through the first 30 days.
| # | Candidate | Score | Tier | Action | AI Note |
|---|---|---|---|---|---|
| 1 | Sarah Chen | 87/100 | A | Shortlist | Strong SaaS background, 6 yrs PM, led teams of 8+. |
| 2 | Marcus Webb | 81/100 | A | Shortlist | Solid fintech PM. Missing B2B SaaS but strong roadmap ownership. |
| 3 | Priya Nair | 74/100 | B | Hold | Relevant domain. Shorter tenure warrants a conversation first. |
| 4 | James Okafor | 61/100 | B | Hold | Consumer background — limited enterprise exposure for this role. |
| 5 | Lisa Park | 38/100 | C | Reject | Junior profile. No evidence of leadership at required scale. |
Sample output using synthetic candidate data.
Your Next 10 Roles Could Be Shortlisted by AI.
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