AI-Powered Candidate Screening & Ranking for Recruiting Teams
Stop Spending 23 Hours
Screening Resumes Per Hire.
Upload your job description. Upload your candidate pool. Get every applicant assessed, ranked, and summarized against your job description — instantly.
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Works alongside ·Greenhouse·Lever·Bullhorn·Workday·Any ATS
The Math
0 hrs
reported average hours screening resumes per hire
$0
avg. cost per hire (SHRM, 2022)
0+ hrs
to read 250 resumes manually
< 2 min
PER SCREENING SESSION WITH RESUME AUTOPSY
Sources: Shortlistd (2025); SHRM Human Capital Benchmarking Report (2022).
What the output looks like
Kubernetes and CI/CD expertise matches the JD across every dimension — AWS certs seal it
Solid infrastructure background; missing Terraform and the team leadership the JD requires
SRE experience partially transfers but gaps in cloud cost ownership and cross-team coordination
Junior-level cloud exposure; 3 years short of the seniority the role demands
On-prem Linux background has no meaningful overlap with the cloud-native JD requirements
Jordan Mills — expanded view (sample)
Jordan Mills identified as candidate — speaks first and consistently refers to personal ownership of infrastructure described on the resume
Demonstrated SkillsSkills from the job description that the candidate actively backed up with specific examples during the interview.
- Walked through a real multi-region EKS outage with clear ownership of the recovery — credible and specific, matches resume claims
- Articulated CI/CD architecture decisions with reasoning on trade-offs; referenced the 400-engineer GitHub Actions pipeline directly
- Demonstrated working knowledge of AWS cost optimization beyond surface-level answers — gave specific numbers from a previous cost-reduction initiative
Gaps AddressedResume weaknesses or missing areas that the candidate clarified or provided new context for during the interview.
- Team leadership gap from resume analysis partially resolved — candidate has mentored two junior engineers and led incident response, though no formal direct reports yet
Unsupported ClaimsResume strengths the candidate couldn't back up, contradicted, or walked back when questioned during the interview.
- Resume mentions 'chaos engineering familiarity' but candidate could not name a specific tool or describe a real fault injection exercise when asked directly
Notable ResponsesStandout moments from the interview — specific answers that were particularly strong, revealing, or memorable.
When pushed on scaling beyond current team size, gave a thoughtful answer about delegation patterns and hiring bar — signals leadership readiness
Proactively flagged a limitation in their CloudFormation knowledge without being asked — honesty is a good sign
CommunicationHow clearly and effectively the candidate communicated — structure, conciseness, and command of language.
Concise and technically precise. Answers stayed on-topic without prompting. No rambling, no over-explaining. Strong communicator for a senior IC.
Overall AssessmentOverall evaluation tying interview performance to role fit, referencing specific things the candidate said.
Resume score holds up under interview scrutiny. The chaos engineering gap is confirmed but candidate is self-aware about it. The leadership gap is smaller than the resume suggested. Recommend advancing to the team-fit round.
Seven years of dedicated DevOps experience across fintech infrastructure, with direct Kubernetes cluster management and CI/CD pipeline ownership at scale. The strongest alignment is in AWS and Terraform — the gap is in chaos engineering practices the JD lists as preferred.
Strengths
- Kubernetes at Scalehigh"Manages 30+ EKS clusters across 4 AWS regions" maps directly to the JD's multi-region cluster requirement.
- CI/CD Pipeline Ownershiphigh"Built GitHub Actions pipelines supporting 400+ engineers" — the JD asks for 500+, but the architecture transfers.
Gaps
- No Team Lead ExperiencedealbreakerThe JD requires managing a team of 3–5 engineers. The resume shows IC work only — no direct reports or people management mentioned.
- No Chaos EngineeringsignificantThe JD lists Gremlin or Litmus as preferred. No mention of chaos practices anywhere on the resume.
- CloudFormation GapminorThe JD lists CloudFormation alongside Terraform, but the candidate's IaC experience is Terraform-only.
Keywords
Experience Alignment
Seven years exceeds the five-year minimum. Staff-level scope aligns with the senior IC role. Fintech infrastructure background is a direct match for the industry context.
Overall Assessment
Strong shortlist candidate. The Kubernetes and CI/CD depth directly answers the core of the JD. Chaos engineering is a preference, not a requirement — worth probing in the technical screen rather than screening out.
AI-generated assessment — not a professional evaluation or predictor of hiring outcomes.
↑ Open any candidate for the full diagnostic — resume analysis, interview transcript breakdown, and keyword coverage.
Sample output.
Why candidates ranked — not just scores
QUALIFICATION CHECKLIST — Priya Sharma · Sr. DevOps Engineer JD
5+ years infrastructure / cloud engineering
"6 years SRE and platform engineering across AWS and GCP" — experience range and scope align
Kubernetes / container orchestration at scale
"Managed EKS clusters for 3 services" — present but limited scope; JD requires multi-region fleet ownership
CI/CD pipeline ownership (500+ engineers)
"Maintained Jenkins pipelines for 80-person org" — solid foundation but significantly under the scale requirement
Terraform infrastructure-as-code ownership
No evidence found in resume
Team lead experience (3–5 direct reports)
No evidence found in resume
Every requirement in your JD gets classified. You see exactly why a candidate ranked where they did.
What You Get
01
Evidence-backed scores
Every fit score (0–100) is backed by evidence quotes your hiring manager can actually read.
02
Qualification checklist
MATCH / PARTIAL / MISS per JD requirement — not a black-box number.
03
JD calibration
Fine-tune scoring requirements before any resume is processed. Promote, demote, or add criteria.
04
Match verdicts
Strong Match / Partial / Weak / Mismatch at a glance — with reasoning behind every verdict.
05
Interview analysis
Upload transcripts for AI-powered evidence-based evaluation of how candidates held up.
06
Candidate notes
Status tracking and recruiter notes per candidate — shortlist without a spreadsheet.
07
Batch processing
Up to 8 candidates per session on Starter, 15 on Pro — processed in parallel.
08
CSV + PDF export
Export ranked results and full candidate reports for team sharing and hiring manager review.
09
Privacy first
No training on your data. All content encrypted at rest. Sessions expire automatically.
Match verdicts are AI-generated estimates and should be reviewed with human judgment.
How It Works
Paste or upload your job description.
Optionally review and adjust the AI-extracted job requirements before scoring begins — promote, demote, or add criteria to match exactly what you're hiring for.
Upload your candidate pool of resumes.
Receive a ranked list with scores, verdicts, and one-line summaries.
Optionally upload interview transcripts for AI-powered candidate evaluation — see who held up under questioning.
Pricing
Try it free first — 1 session, 3 candidates, no card required.
Free Trial
Free
3 candidates / session
1 session lifetime
✓Evidence-backed fit scores
✓Qualification checklist (MATCH/PARTIAL/MISS)
✓PDF report
✓Interview transcript analysis
Starter
$29/mo
8 candidates / session
15 sessions / month
✓Evidence-backed fit scores
✓Qualification checklist (MATCH/PARTIAL/MISS)
✓PDF reports + CSV export
✓Interview transcript analysis
✓Candidate notes & status tracking
Pro
$59/mo
15 candidates / session
30 sessions / month
✓Everything in Starter
✓PDF reports + CSV export
✓Interview transcript analysis
✓Candidate notes & status tracking
✓Priority processing
All plans — including the free trial — include qualification checklists, PDF reports, interview transcript analysis, and CSV export. Paid plans cancel anytime.
Cancel anytime. No lock-in. No sales call required.
Why we built this
Resume Autopsy started from a simple observation: reading 200 resumes manually is a terrible way to find the best candidate. Not because recruiters aren't good at their jobs — but because the human brain isn't designed to hold 200 consistent mental comparisons while also tracking 14 different job requirements.
We built this to do the systematic part — extract every JD requirement, check every resume against every requirement, flag what's present and what's missing — so you can spend your time on what actually requires human judgment.
We built it for recruiting agencies and independent recruiters who screen real candidate pools — not enterprise HR teams with implementation budgets and 6-month onboarding timelines. No per-seat pricing. No contract. Start today.
Eduardo
Founder, Resume Autopsy
Frequently Asked Questions
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