Screen every applicant against the JD — automatically.
Grezlify Hire scores, ranks, and shortlists resumes at scale with the same 15-section review engine candidates trust — then pipes the results into your ATS. Built for Indian hiring stacks like Workday, Darwinbox, Keka, and Naukri, and works internationally with Greenhouse and Lever.
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From inbox to shortlist in four steps
Post a role with its JD
Create a role and paste the job description. The JD becomes the rubric every applicant is measured against — keywords, must-haves, and seniority.
Applicants apply or bulk-upload
Candidates apply through your role link, or upload a folder of resumes — hundreds of PDFs and DOCX at once. Parsed against Indian and global ATS stacks.
Auto-score against the JD
The 15-section review engine scores every resume the moment it lands — JD match, ATS parseability, keyword coverage, red flags. No manual reading.
Rank, shortlist, export
Sort by fit score, shortlist in one click, and push the cut into your ATS via the Review API + webhooks. Export to Workday, Darwinbox, Greenhouse, and more.
Built for screening at scale
Auto-score every applicant
Each resume is scored against your JD the moment it arrives — the same 15-section review engine, run at volume.
Rank + shortlist by fit
Candidates sort by fit score across 8 dimensions. Set a cut-off, shortlist in one click, and skip the manual pile.
Keyword match per candidate
See matched, weak, and missing keywords for every applicant against the JD — so you know exactly why someone ranked where they did.
Review API + webhooks
Pipe scores and findings straight into your ATS. Fire on_review_complete to Workday, Darwinbox, Keka, Naukri, Greenhouse, or Lever.
Volume pricing
Per-seat for your recruiters or per-review for high-throughput screening. INR-first, billed the way Indian teams buy — and USD globally.
Single-tenant + data residency
Deploy single-tenant for full isolation, with data residency in the EU and India for compliance-sensitive hiring.