The structured evaluation layer for better hiring decisions
Make fair, consistent, and evidence-based hiring decisions. interviewLog surfaces the evidence from interviews so your team can evaluate candidates with confidence.
73%
reduction in evaluation time
2.4x
more consistent decisions
89%
of hiring teams prefer it
$47K
avg. saved per bad hire avoided
The Problem
Interviews today are subjective, inconsistent, and high-stakes
Your team conducts dozens of interviews, but the evaluation process relies on scattered notes, fading memories, and subjective impressions.
Memory isn't reliable
Interviewers forget 50% of what was said within an hour. Critical details that should inform decisions get lost.
Notes are inconsistent
Different interviewers capture different things. There's no standard for what evidence matters or how to weigh it.
Bias creeps in
Without structure, gut feelings and unconscious bias dominate. Decisions become subjective and hard to defend.
Mistakes are costly
A bad hire costs 30-200% of annual salary. Yet most teams make decisions based on incomplete information.
How It Works
From interview to insight in five steps
interviewLog transforms unstructured interviews into structured evaluations that your entire team can trust.
Upload interview transcript
Import your interview transcript from any recording tool or paste text directly. Video is optional.
Add job description
Provide the role requirements so interviewLog understands what competencies and levels to evaluate against.
Review proposed rubric
interviewLog proposes a structured scorecard based on the role. Customize it to match your hiring bar.
Receive evidence-backed evaluation
See each competency scored with direct quotes and timestamps. Understand exactly why a candidate rates at each level.
Improve future interviews
Get recommendations on questions that weren't covered and how to strengthen your rubric over time.
What Makes This Different
Not another note-taking tool
Transcription tools give you words. interviewLog gives you structured evaluation with evidence you can trust.
| Feature | interviewLog | Note-taking tools |
|---|---|---|
Evidence-based scoring Every score backed by quotes and timestamps | ||
Structured rubrics AI-proposed scorecards aligned to job requirements | ||
Level calibration Clear definition of candidate seniority | ||
Human approval required AI assists, humans decide | ||
Interview improvement Recommendations for better future interviews | ||
Bias awareness Flags potential bias in evaluation |
Key Benefits
Better decisions, better hires
interviewLog helps your team make hiring decisions you can stand behind.
Reduce bias in evaluation
Structure removes subjectivity. Every candidate is evaluated against the same evidence-based criteria.
Define candidate level accurately
Clearly calibrate whether a candidate is junior, mid, or senior based on demonstrated competencies.
Make confident hiring decisions
Present evidence to stakeholders, not opinions. Build consensus around what candidates actually said.
Save time on review and feedback
Reduce hours spent writing feedback. Generate structured summaries for hiring committees instantly.
Example Output
See what an evidence-backed evaluation looks like
Every score is supported by direct quotes from the interview, with timestamps so you can verify.
Senior Software Engineer - Backend
Interview with Sarah Chen • 45 minutes
Technical Problem Solving
Level: Senior
When asked about scaling challenges, the candidate described implementing a distributed caching layer that reduced p99 latency by 60%.
Communication & Collaboration
Level: Senior
Clearly articulated trade-offs between consistency and availability. Used concrete examples from cross-team projects.
Leadership & Influence
Level: Mid
Mentioned mentoring junior developers but couldn't provide specific examples of driving technical direction.
Recommendation: Consider probing deeper on leadership experience in the next round. Suggest behavioral questions about technical decision-making ownership.
Trust & Safety
AI that assists, never decides
We built interviewLog with trust at its core. Your team stays in control of every hiring decision.
Bias awareness built in
interviewLog flags potential sources of bias in your evaluation process and suggests ways to reduce them.
Explainable evaluations
Every recommendation comes with clear reasoning. No black-box decisions—you see exactly why.
Human control and approval
AI surfaces evidence and structures evaluation. Your team makes the final call, always.
Enterprise-grade security
SOC 2 Type II compliant. Your interview data is encrypted at rest and in transit.
Trust your interview decisions — and improve them over time
Join teams who have made hiring more fair, consistent, and evidence-based with interviewLog.
No credit card required • Free pilot for qualified teams