Every score has a source.
Every decision has proof.
After every interview, AI evaluates behavioral and technical performance using research-backed frameworks — deterministically. Same transcript, same score, every time. Every rating linked to transcript evidence, with human ratings alongside.
STAR framework — weighted by what predicts performance.
What a candidate actually did and achieved matters most. That's why actions and results carry the majority of the evaluation weight — grounded in 85+ years of I/O psychology research.*Schmidt & Hunter (1998) — The Validity and Utility of Selection Methods in Personnel Psychology, Psychological Bulletin 124(2) · Sackett et al. (2021) — Updated Validity Estimates · Campion, Palmer & Campion (1997) — Structured Interview Design · McDaniel et al. (1994) — Structured Interview Validity Meta-Analysis
Situation Clarity
How well the candidate described the context and challenge.
Action Depth
What the candidate actually did — the strongest predictor of future performance.
Result Specificity
Whether outcomes were measurable and concrete.
Reflection
Evidence of learning and growth from the experience.
Three axes. Scored independently. Fully transparent.
Each axis scored on a five-point scale — then compared to the expertise level your role actually requires.
Technical Accuracy
Correctness of knowledge — are the facts and concepts right?
Implementation Quality
Practical application — can the candidate turn knowledge into a workable approach?
Problem Solving
Analytical reasoning — does the candidate consider trade-offs and alternatives?
The proof behind every score.
Supporting Quotes
Every score links to exact quotes — with timestamps, audio playback, and full transcript. Click any quote to hear the original recording or read it in context.
Score Rationale
Written explanation of why each score was given, including missing concepts and specific recommendations for follow-up.
Consistency Validation
Automated checks catch contradictions — like high scores without supporting evidence. Inconsistencies are flagged for your review, never silently changed.
Dual Rating System
AI rating + interviewer rating — independent and side by side. When both exist, the overall is the average. Human judgment is always part of the equation.
Cross-interview behavioral profiling — insight, not scoring.
After interviews are complete, the system synthesizes behavioral signals across all transcripts into a single qualitative profile.
Communication Patterns
How the candidate communicates, explains, and articulates ideas — extracted from transcript evidence across all interviews. You see patterns, not just answers.
Collaboration & Initiative
Evidence of teamwork, stakeholder management, proactivity, and self-direction. Each insight backed by quotes with confidence levels — nothing based on gut feel or AI guesswork.
Evidence-Gated Confidence
Confidence levels are tied directly to how much evidence exists. Few quotes means low confidence. The system never overstates what it knows.
No Personality Profiling
Task-relevant behavioral signals only. No personality traits, emotional states, or psychological profiles — EU AI Act Article 5 compliant. Insight for your team — decisions stay human.
Non-Native Speaker Protection
Transcripts are generated by speech recognition, which can misinterpret accents and non-native speech. Grammar, pronunciation, and fluency issues are automatically filtered from evaluations — only task-relevant behaviors count.
Make hiring decisions you can stand behind.
Stop debating what a candidate said. Structured frameworks score performance the same way every time, link every rating to transcript evidence, and give your team a shared language for hiring decisions.