Resources
Insights, guides, and best practices for structured hiring.
AI Self-Preference Bias in CV Screening: What the Research Shows
A 2025 study found AI systems prefer their own rewritten CVs by 67–82%. We break down the research, what it means for employers, and how structured, deterministic screening avoids this bias.
Zero-Training AI in Hiring: How to Verify Candidate Data Never Trains Models
A practical guide for HR, legal, and security teams to validate zero-training AI claims in hiring platforms with architecture and audit evidence.
Reproducible AI Hiring Evaluations: Deterministic Scoring for Audit-Ready Decisions
How deterministic AI evaluation improves hiring consistency, reduces decision noise, and supports audit-ready interview scoring.
9 Hiring Reports That Actually Drive Decisions
A practical operating model that maps nine hiring reports to cadence, owner, trigger, and action for measurable recruiting outcomes.
EU-Only Data Residency for Hiring AI: Architecture, Controls, and Audit Checklist
A practical guide to EU-only data residency for AI hiring systems covering region pinning, isolation controls, encryption, and audit readiness.
The True Cost of Hiring the Wrong Person
Research-backed analysis of the direct, hidden, and cascading costs of bad hires — and the evidence that structured hiring prevents them.
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