Proof-based hiring
Stop matching keywords.
See the actual work.
VettAI replaces resume screening with verified evidence. We cross-check LinkedIn identity, pull real GitHub contribution data, probe every portfolio link, and hand candidates a short role-specific exercise. You get a ranked shortlist with citations — not vibes.
Free to start. Bring your own team. SOC 2 Type II in progress.
How a VettAI review actually works.
1
Verified identity
Candidates sign in with LinkedIn OIDC so their name and primary email are cryptographically confirmed before anything else runs.
2
Public signal
We pull GitHub profile + recent repos, fetch every linked project, and rank the candidate against the contributor list of the repos they claim.
3
URL probing
Every portfolio link is fetched. We extract author, publish date, and check if the candidate's name actually appears on the page.
4
Personalized exercise
Gate-pass candidates get a 10-minute scenario generated for this role and their background. No trick questions, no take-homes.
What makes this different.
Other "AI hiring" tools grade resumes. We refuse to. The resume is self-reported text. Every claim in our review tab either has a verifiable source behind it or is labelled self-reported — honestly.
Commit-level attribution
If a candidate claims "led project X", we check whether their GitHub login is actually a top contributor to that repo — with commit counts and date windows.
AI-authored resume detection
We flag resumes whose tone and numbers read as LLM-polished without substance. The exercise then becomes the real source of signal.
Clickable citations
Every verdict on the review page links to the LinkedIn profile, GitHub repo, or URL we actually fetched. No black box.
Per-tenant data isolation
Row-level security at the database layer. AES-256-GCM PII encryption. Your candidates' data never leaves your workspace.
11 min
Average candidate application time.
63%
Reported reduction in time-to-shortlist.
4.7/5
Average candidate-reported fairness score.