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Reports That Actually Help You Decide
Every LayersRank interview produces a comprehensive candidate dossier: confidence-weighted scores, dimension breakdowns, specific strengths and concerns, integrity signals, and complete response transcripts. Designed for the 60-second scan when you're triaging a pipeline, and the deep dive when you're making a final call.
Candidate Report
Priya Sharma — Senior Backend Engineer
82
91% confidence
Technical
85 ± 3
Behavioral
79 ± 5
Contextual
83 ± 4
The problem with interview feedback
Interview feedback in most organizations is nearly useless for decision-making.
The casual version
“Seemed pretty good. Technical skills were solid. Maybe a bit quiet? I'd say lean yes but could go either way.”
What does “pretty good” mean relative to other candidates? “Lean yes but could go either way” is not a recommendation — it's an abdication of judgment.
The formal version
Communication 4/5, Technical Skills 4/5, Problem Solving 3/5, Culture Fit 4/5. Overall: 3.75/5.
What did the candidate say to earn these numbers? What's the difference between a 3 and a 4? The numbers create an illusion of precision while communicating almost nothing.
Neither version answers the questions that actually matter:
Should we advance this candidate over the others?
What specifically makes them strong or weak?
What should the next round focus on?
How confident should we be in this evaluation?
Can we defend this decision if questioned?
LayersRank reports are designed around these questions.
Report structure
Eight sections, each serving a specific purpose in the decision workflow.
01
Header Summary
Who, what role, when, bottom-line verdict
02
Score Overview
Overall score with confidence and dimension breakdown
03
Key Strengths
3-5 demonstrated strengths with evidence
04
Areas to Probe
Gaps and uncertainties with suggested follow-ups
05
Question Details
Individual scores, summaries, and notes per question
06
Integrity Summary
Behavioral flags or clean confirmation
07
Comparison Context
Ranking against others in the pipeline
08
Full Transcript
Complete responses for reference and audit
Section 01
Header summary
At a glance: who this is and what the evaluation concluded.
Candidate Report
Priya Sharma
Senior Backend Engineer
Feb 15, 2026 · LR-2026-SBE-004721 · 38 min · 12/12 questions
STRONG CANDIDATE
Advance to Final Round
Configurable verdicts
Strong Candidate
Exceeds threshold with high confidence. Advance without reservation.
Worth Interviewing
Meets threshold with some uncertainty. Advance with probes planned.
Borderline
Near threshold. Decision depends on pipeline depth and role needs.
Below Bar
Below threshold. Recommend not advancing unless exceptional circumstances.
Customize labels, thresholds, and language to match your organization's terminology.
Section 02
Score overview
The quantitative assessment at multiple levels of detail.
Overall Assessment
78
Overall Score
89%
Confidence
±4
Range: 74-82
Dimension Breakdown
Overall Score
Weighted combination of dimensions. The single number for ranking when you need one.
Confidence
How reliable this assessment is. 89% means you can trust this score for decision-making.
Interval
The uncertainty range. Narrow intervals indicate consistent signals across evaluation approaches.
Section 03
Key strengths
The 3-5 things this candidate demonstrated particularly well, with evidence.
Clear system design thinking
Explained notification service architecture with thoughtful trade-offs between real-time WebSocket delivery and batch processing. Unprompted consideration of failure modes and horizontal scaling approach.
Source: Q4, Technical
Strong debugging methodology
Described systematic production debugging process: reproduce in staging, isolate through binary search of components, instrument with targeted logging, verify fix doesn't introduce regression.
Source: Q6, Technical
Effective technical communication
Explained CAP theorem trade-offs in accessible language without sacrificing accuracy. Adjusted explanation depth appropriately when describing to technical vs. non-technical audiences.
Source: Q7, Technical; Q9, Behavioral
Relevant scale experience
Direct experience with systems handling 50K+ requests per second. Specific examples of performance optimization with quantified results (reduced p99 latency from 340ms to 89ms).
Source: Q4, Q5, Technical
Why this section is useful
Specificity: Each strength includes what was demonstrated, not generic praise.
Evidence source: Links to the specific question(s) where it appeared. Click through to verify.
Actionable: Reference strengths in subsequent rounds for continuity. Share with candidates during offers.
Section 04
Areas to probe
Specific gaps, concerns, or uncertainties to explore in subsequent rounds — with ready-to-use suggested probes.
Stakeholder management experience
Q8, Behavioral · Score: 68 ±9 · 74% conf
Response about cross-functional collaboration described outcomes but lacked specific examples of navigating disagreements or competing priorities.
Suggested probe
"Tell me about a time when engineering and product had fundamentally different views on priority. How did you navigate that?"
Leadership and mentorship depth
Q10, Behavioral · Score: 71 ±7 · 78% conf
Mentioned mentoring junior engineers but provided limited detail on approach or outcomes. May have informal experience rather than structured leadership.
Suggested probe
"Can you walk me through how you've helped a junior engineer grow? What was your approach, and what was the outcome over time?"
Motivation specificity
Q11, Contextual · Score: 72 ±4 · 88% conf
Response about interest in role was generic ("exciting technical challenges," "growing company"). Limited evidence of specific research into what the role involves.
Suggested probe
"What specifically about this role attracted you versus other opportunities you're considering?"
Areas are ordered by importance — combination of dimension weight, confidence level, and severity. If you're advancing, these define your final round agenda. Instead of generic re-evaluation, you probe specific uncertainties.
Section 05
Question-level details
For each question, the detailed evaluation with response summary, strengths, and gaps.
Q4: System Design
Technical
85 ±3
94% confidence
Video · 4:32 · Difficulty 8/10
“Walk through how you would design a notification service handling 10 million daily active users. Consider different notification types, delivery guarantees, and scale requirements.”
Response Summary
Proposed a multi-tier architecture separating ingestion, processing, and delivery layers. Discussed trade-offs between real-time WebSocket delivery for in-app notifications versus batch processing for email digests. Considered failure modes including dead-letter queues for retry handling. Addressed scale through horizontal sharding by user ID with consistent hashing.
Strengths
- Unprompted failure scenario consideration
- Clear trade-off articulation
- Quantified scale reasoning
- Practical experience evident
Gaps
- Observability/monitoring not discussed
- Schema evolution not addressed
- Mobile push specifics not covered
View Full Response →
Every question has this level of detail. You can trace any dimension score back to the individual questions that contributed to it.
Section 06
Integrity summary
Behavioral flags if any. Clean confirmation if none. At a glance, you know if there's anything to investigate.
Clean
Paste Events: 2 (minor)
Tab Switches: 5 (brief, scattered)
Typing Pattern: Normal
Response Timing: Expected ranges
Face Verification: Confirmed (98.7%)
FLAG STATUS: NONE
Flagged
Paste Events: 7 (3 on technical Qs)
Tab Switches: 16 (avg 41s, correlated)
Typing: Q6 134 WPM, 0 corrections
Timing: Q4 done in 2m18s (expected 6-8m)
Face Verification: Confirmed
FLAG: REVIEW RECOMMENDED
See the Integrity Detection page for full detail on what triggers flags and how to handle them.
Section 07
Comparison context
See relative performance against other candidates in the same pipeline.
Pipeline: Senior Backend Engineer · 6 Candidates Evaluated
This candidate: Priya Sharma · Ranking: #2 of 6
| # | Candidate | Overall | Technical | Behavioral | Contextual |
|---|---|---|---|---|---|
| 1 | Rahul | 82±3 | 86±2 | 78±4 | 81±3 |
| 2 | Priya ← | 78±4 | 82±3 | 74±6 | 79±3 |
| 3 | Amit | 75±5 | 79±4 | 71±5 | 74±5 |
| 4 | Sneha | 72±4 | 74±3 | 72±4 | 69±5 |
| 5 | Vikram | 68±6 | 71±5 | 65±7 | 67±5 |
| 6 | Deepa | 64±4 | 68±3 | 61±5 | 63±4 |
Priya and Rahul are close (gap within combined uncertainty). Differentiate based on dimension fit or final round.
Clear separation between top 2 and rest of pipeline. If advancing 2, these are the clear choices.
Uncertainty-aware comparison
Intervals show when ranking differences are meaningful vs. within noise. Priya at 78±4 and Rahul at 82±3 overlap — don't assume Rahul is definitively better.
Dimension comparison
Maybe this candidate ranks #2 overall but #1 on technical. If technical matters most for the role, that's relevant.
Section 08
Full transcript
Complete access to everything the candidate said, for verification, deeper evaluation, or audit.
Q1: Tell us about yourself and what attracted you to this role.
Video · 2:14
“Thanks for having me. I'm currently a senior engineer at TechCorp where I've spent the last three years working on their payments infrastructure. Before that, I was at a startup called DataFlow where I built their initial data pipeline from scratch.
What attracted me to this role specifically is the scale you're operating at. I saw from your engineering blog that you're handling over 50 million transactions daily, and the challenges around consistency and latency at that scale are exactly what I want to be working on...”
Full transcript continues for all 12 questions...
Verification
If a summary or score seems off, check the source. See exactly what the candidate said.
Communication style
Summaries capture content, not style. Watch the video or read the transcript for tone and clarity.
Deeper evaluation
Hiring managers can review responses before the final round to prepare better questions.
Audit trail
Complete documentation of what the evaluation was based on, if a decision is ever questioned.
Formats
Report formats
Available in multiple formats for different use cases.
Web Dashboard
Interactive reports in the LayersRank interface. Click to expand, watch video, compare side-by-side. Best for active evaluation.
PDF Export
Professional PDF for stakeholders without LayersRank access. All sections except embedded video. Formatted for printing or archival.
Executive Summary PDF
Condensed one-page version: Header, Score Overview, Key Strengths, Areas to Probe, Verdict. For leadership who need the conclusion, not the detail.
ATS Integration
Summary scores and verdict sync to your ATS (Workday, Greenhouse, Lever). Link to full report for detail. ATS stays the system of record.
JSON API
Full report data available programmatically. Build custom dashboards, aggregate analytics, feed into your own decision tools.
Customizing reports
Match reports to your organization's needs.
Dimension names and weights
Rename dimensions to match your language. "Technical" becomes "Functional Skills." Adjust weights per role template — Staff Engineer at 50% technical, Engineering Manager at 45% behavioral.
Verdict thresholds and labels
Set what scores qualify for each verdict. Change "Strong Candidate" to "Definitely Interview." Set the threshold at 80 instead of 75 if your bar is higher.
Section visibility
Choose which sections appear per export format. Executive PDFs might only show Header, Scores, Verdict. External views might exclude Integrity Details.
Branding
Enterprise plans include white-label options. Your logo, your colors, your company name. Reports look like they come from your organization.
How different users use reports
Recruiters
Triage and routeScan Header and Score Overview (30s). Check Integrity (10s). Read Strengths and Areas to Probe (1-2 min). Route.
Key question: Should this candidate advance, and to whom?
Report elements used: Verdict, overall score, integrity flags, comparison context
Hiring Managers
Evaluate and prepareReview shortlisted reports. Compare candidates. Read Areas to Probe to prepare final round questions. Reference Question Details if needed.
Key question: Which candidates should I prioritize, and what should I ask them?
Report elements used: Dimension breakdown, strengths, areas to probe, question details
Engineering Leaders
Calibrate and decideReview final-round candidates. Assess fit with team needs. Make hire/no-hire recommendation.
Key question: Does this candidate have what my team needs?
Report elements used: Dimension breakdown (relevant dimensions), specific strengths and concerns, comparison
Leadership
Verify and approveReview executive summary. Check score meets threshold. Verify no integrity flags. Approve or request more.
Key question: Can I approve this advancement with confidence?
Report elements used: Overall score and confidence, verdict, integrity summary
Legal / Compliance
Audit and documentReview full report including all scores, transcripts, and evaluation details. Verify defensible process.
Key question: If this decision is challenged, can we defend it?
Report elements used: Complete report, evaluation criteria, score traceability, audit trail
Frequently asked questions
How long does report generation take?
Standard turnaround is within 24 hours of interview completion. Most reports are ready in 4-8 hours. Priority turnaround (same-day, often within 2 hours) is available on Scale and Enterprise plans.
Can hiring managers edit reports?
Hiring managers can add notes and comments. They can override the verdict (e.g., advance a borderline candidate based on other factors). They cannot change scores or evaluation evidence. Original AI assessment remains visible for audit purposes.
How long are reports retained?
Configurable based on your data retention policy. Default is 24 months. GDPR deletion requests are honored within required timeframes.
Can candidates see their reports?
You control this. Some organizations share reports as feedback (helps employer brand, improves candidate experience). Others keep reports internal. The platform supports either approach.
What if I disagree with a score?
Add your perspective in notes. If you consistently disagree with certain types of scores, contact us — it may indicate calibration issues worth investigating. Your feedback helps us improve.
Can reports be used in legal proceedings?
Reports document an objective, structured evaluation process. This is generally helpful if decisions are challenged. However, consult your legal team about specific situations. We provide audit trails and process documentation to support defensible hiring.
See the report that changes how you hire
Download a complete sample report. See exactly what you'd get for every candidate — from 60-second verdict to full question-by-question detail.