Available
SLM-Works HR Screener
CV screening and candidate data extraction at scale
Speeds up candidate triage by extracting structured profiles and scoring fit against role-specific hiring criteria.
How it works
Step 1
Parse CV and optional cover letter text.
Step 2
Extract candidate fields and inferred skill signals.
Step 3
Score against weighted role criteria.
Step 4
Output structured profile plus explanation for gaps.
Example
Example input
Batch of CVs for a senior data engineer role.
Example output
{ candidate: '...', score: 81, strengths: ['ETL', 'Python'], gaps: ['AWS cert'], recommendation: 'interview' }
Key features
- Structured candidate profile extraction
- Weighted fit scoring by role profile
- Gap explanations for recruiter transparency
- ATS-ready JSON output
Rollout guidance
- Review fairness and bias controls with HR/legal before deployment.
- Calibrate weighted criteria quarterly with hiring outcomes.
Ideal for
FAQ
Can this make final hiring decisions?
No. It supports shortlist prioritization; final decisions should remain with human hiring panels.
Want this model in your stack?
We can scope a deployment blueprint, evaluation set, and integration plan for your data and infrastructure constraints.