Your next engineer
already left evidence.
80% of engineering resumes are AI-inflated or unverifiable. HireAI cross-checks every claim against real GitHub commits — so you only interview candidates who actually built what they say they did.
No credit card required · 2 free analyses on signup · Cancel anytime
AUTHENTICITY
9.2/10
INFLATION
2.8/10
GITHUB MATCH
8.8/10
ATS passes the resume. Not the engineer.
Traditional ATS scores keywords. A candidate who types “Kubernetes, microservices, PyTorch” into their resume will outscore someone who actually built those systems. Worse — AI tools now write entire resumes that score 95% on ATS and contain zero real experience.
72%
of developers admit to exaggerating technical skills on resumes
~80%
of AI-generated resumes pass standard ATS filters undetected
3–5 hrs
average time wasted per fake candidate who reaches the interview stage
From upload to shortlist in minutes.
Upload Resumes
Drop up to 100 resumes (PDF or DOCX). No formatting requirements — our parser handles every resume layout automatically.
Cross-Check Signals
We extract each candidate's GitHub profile and analyse commit frequency, repository quality, code consistency, and whether their stated skills match their actual push history.
Get Your Report
Receive a ranked top-10 shortlist with individual Authenticity, AI Inflation, and GitHub Match scores. Export any candidate as a PDF report to share with your team.
Resumes describe. GitHub proves.
When a candidate writes “Built a microservices architecture handling 50k RPS”, we check if they have a single repo with meaningful commits. Commit frequency, code volume, repository quality, and technology consistency are all scored automatically. A 2-commit repo with a copied README is flagged instantly.
- Commit frequency and recency scoring
- Repository quality vs. listed project claims
- Technology stack consistency across repos
- Copy-paste and tutorial-repo detection
AI Inflation Score
High InflationWeaknesses
- Suspiciously precise metrics with no methodology.
- Zero GitHub activity matching claimed stack.
Catch the resume ChatGPT wrote.
Even if a candidate passes GitHub verification, our AI analyses the resume text itself — sentence structure, suspiciously round metrics, absence of failure mentions, and uniform bullet formatting. Resumes with a high AI Inflation Score are flagged before they reach your interview queue.
- AI-generated language pattern detection
- Suspiciously precise metrics with no methodology
- Uniform bullet structure indicating templated writing
- Cross-referenced against actual GitHub contribution depth
The gap between filtering and verifying.
One-time credits. No subscription traps.
Buy once, use when you need. Credits never expire.
Start with 2 free analyses — no credit card required.
Starter
150 credits
- Up to 50 resumes/batch
- Core GitHub analysis
- Authenticity scoring
- No PDF export
Growth
500 credits
- Up to 100 resumes/batch
- PDF export included
- JD matching included
- All core features
Pro
1,500 credits
- Up to 100 resumes/batch
- All features included
- Priority support
- PDF export included
Agency plan — $299 · 5,000 credits · All features · For recruiting agencies and teams View all plans →
“We cut our engineering interview no-shows by half after switching to HireAI. The GitHub check alone has saved us at least 6 hours of wasted interview time.”
Head of Engineering
B2B SaaS (YC '23)
“Our ATS was passing candidates who couldn't answer basic questions about the frameworks they listed. HireAI's inflation score is now our first filter.”
Technical Recruiter
Fintech Startup
Stop guessing who can actually build.
Analyse your first two candidates free. No credit card, no commitment — just proof.
2 free analyses · No card required · Results in under 60 seconds
Frequently asked questions
Everything you need to know about how HireAI verifies engineering talent. Can't find what you're looking for?
Reach out to our team →Most Applicant Tracking Systems (ATS) just match keywords on a resume. HireAI goes deeper. It doesn't just read what a candidate claims to know — it analyzes their actual GitHub activity, commit history, and real-world project contributions to verify their skills automatically.