AI Hiring / Candidate Screening Automation

Who this is for

Hiring managers, recruiters and staffing teams screening high volumes of CVs and applications by hand.

The problem

Hundreds of CVs per opening means weekends lost to manual screening, duplicate applications slipping through, and good candidates waiting too long for an answer.

What it automates

• Reading and structuring CVs and applications into comparable profiles
• Checking for duplicate applications across channels
• Scoring suitability against the criteria you define — as decision support
• Preparing a shortlist draft with reasons a human can inspect
• Drafting interview invitations and polite status updates for your approval

Typical inputs

• CVs / applications (email, PDF, job-board exports)
• Your role criteria and must-have requirements
• Your communication templates and tone

Typical outputs

• Structured, comparable candidate profiles
• A draft shortlist with visible reasoning — the recruiter decides
• Invitation and update drafts queued for human approval

How delivery works

1. Criteria workshop. We turn the role into explicit, lawful screening criteria you sign off.
2. Build. Intake, structuring, duplicate checks and scoring as decision support.
3. Bias & fairness review. Criteria and outputs reviewed so the AI assists — it never auto-rejects.
4. Supervised use. Recruiters work with shortlist drafts; every decision stays human.

What you get

• A screening workflow that turns CV piles into comparable profiles
• Shortlist drafts with inspectable reasoning — never silent rejections
• Faster, more polite candidate communication (human-approved)
• Documentation incl. the human-decision boundary for compliance

Not included

• Automated rejection or hiring decisions — humans decide, always
• Discriminatory criteria of any kind — we refuse them by policy
• Background checks or assessments (separate, regulated scope)
• Paid tools / API usage / job-board fees (billed separately)

Risks & human control

• AI output is decision support only; a person reviews every profile that is rejected or advanced.
• Criteria are explicit and auditable — no opaque scoring.
• Designed for EU AI Act readiness: hiring is a high-risk domain, so human oversight is the architecture, not a feature toggle.
• Candidate data is minimised and retention rules are agreed before launch.

Example workflow: 180 applications for one role (Example — illustrative, not a client result)

1. Applications collected from inbox and job-board export
2. CVs structured into comparable profiles; duplicates flagged
3. Profiles scored against your signed-off criteria
4. Recruiter reviews the draft shortlist and the borderline cases
5. Invitation drafts prepared — recruiter approves and sends

Products