AI shortlisting, never a black box
Resume parsing, skills scoring, candidate-job match and explainable shortlisting — with bias visibility and a clear breakdown of every score.
Resume parsing
99.2% accuracy on 14 fields, mapped to your taxonomy.
Skills scoring
Competency match, calibrated to your level rubric.
Job match
Multi-factor score with explainable weights.
Shortlist
Top N surfaced, ranked, with reasons.
Bias checks
Demographic parity, audit reports.
Job description AI
Inclusive language, calibrated against your level rubric.
Resumes structured, fields mapped
14 fields extracted with 99.2% accuracy — from name and contact through skills, experience, education and domain. Auto-fills the application; surfaces in search.
- Multi-language parsing (English, Hindi, Tamil, Bengali, more).
- Skills mapped to your taxonomy, not a generic ontology.
- Manual override on every field; corrections feed the model.
A shortlist with reasons attached
Every score is explainable: skill match (40%), experience fit (25%), domain (20%), signal quality (15%). Recruiters and hiring managers see exactly why someone's there.
- Multi-factor scoring with weights you can tune.
- Side-by-side compare of top candidates.
- Hide-and-seek mode — blind review for the first round.
Visible bias, before it costs you
Demographic parity reports across stages and outcomes. Skills scoring is name-blind by default. The AI surfaces drift; you decide the fix.
- Demographic parity reports per stage and outcome.
- Name-blind scoring on first-round review.
- Audit-ready: every model decision logged with inputs.
Common questions
No. Every score has weights and inputs you can inspect. Hiring managers see why a candidate is ranked where they are; recruiters can adjust weights per role.
Name-blind first-round, demographic parity monitoring across stages, and an audit log of every model decision. We surface drift; humans make the call.
In your region (India, EU, US). We do not train models on your data without explicit consent. PII is encrypted at rest and in transit.
Yes — per role family. The defaults are calibrated against industry; you can tune skill / experience / domain weights to match how your team actually decides.