HR AI Trust
AI Trust for hiring algorithms, fair-pay, and EEOC compliance.
Built for hr AI risk
HR-AI is under direct regulatory pressure: NYC Local Law 144, Colorado AI Act, EEOC AI guidance, EU AI Act high-risk classification, GDPR Article 22 for automated decisions, and state-level AI hiring laws. Infrarails scores hiring + compensation + performance models for bias; Infrarails Consulting maps your AI use to the disclosure + audit obligations regulators now expect.
- Every AI interaction scored against hr-specific failure modes, not generic safety checks
- Mapped directly to the regulations your auditors cite — EEOC AI Guidance and NYC Local Law 144, among others
- Signed, replayable evidence built for the exact review your regulator or carrier will run
Disparate impact in hiring algorithms
Resume screening / video interview / assessment tools that produce statistically disparate outcomes for protected groups.
Compensation-AI fairness gaps
Pay-equity models or salary-recommendation engines that perpetuate or amplify gender / racial pay gaps.
Performance / promotion bias
AI-assisted performance reviews or promotion recommendations that disadvantage protected classes.
GDPR Article 22 violations
Fully-automated employment decisions made without the legally-required human review for EU candidates / employees.
How hr teams run Infrarails
One policy, scoped to your hr obligations — evaluated on every AI interaction, not just at audit time.
curl -X POST https://api.infrarails.ai/v1/evaluate \
-H "Authorization: Bearer YOUR_KEY" \
-d '{"policy": "hr_compliance", "prompt": "...", "response": "..."}'Evaluate
Continuous bias scoring across hiring / compensation / performance models
Govern
Local Law 144 bias-audit pipeline + Colorado AI Act impact assessments + GDPR Art. 22 review queues
Monitor
Drift detection on protected-class outcomes over time
Guard
Candidate-PII redaction + automated-decision review gating
Regulatory Mapping
Every AI system in your hr estate mapped against the frameworks your regulators actually cite — kept current as the rules change.
Audit-Ready Evidence
Every evaluation produces a signed, tamper-evident record — the artifact your auditors, examiners, or carrier will ask to see.
EEOC AI GuidanceNYC Local Law 144Colorado AI Act (SB-24-205)EU AI ActGDPR Article 22State AI-hiring laws
What a typical hr engagement looks like
Anonymised profile drawn from sector patterns — not a specific client.
Profile
Fortune 500 HR organisation using AI in resume screening + interview scoring + compensation recommendations
Drivers
- NYC Local Law 144 annual bias-audit deadline
- EU GDPR Art. 22 review queue backlog ahead of GDPR audit
- Internal pay-equity report flagging algorithmic patterns
Bundle
Regulatory Readiness Program against NYC LL144 + Colorado AI Act + GDPR Art. 22 (4 months) → AI Governance Framework Design (6 weeks) → AI Readiness Assessment focused on shadow-AI across recruiting (2 weeks)
Outcome
Annual bias-audit pipeline running on Infrarails with public summary auto-generated; GDPR Art. 22 review queue operationalised; documented evidence for upcoming Colorado AI Act impact assessment obligations.
Talk to the HR practice
60-90 minute scoping call, routed to the hr practice lead. Free.