Helping organizations build trust in the AI systems they deploy.

Independent bias audits and fairness testing for AI decision systems — producing clear evidence about model performance and group outcomes within agreed frameworks.

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Impact Ratio: 0.94 Sample n = 1,456 IR: 0.76 ⚠
Sample Output — Fairness Metrics
Group A — Impact Ratio0.94 ✓
Group B — Impact Ratio0.88 ✓
Group C — Impact Ratio0.76 ⚠

What You Get

Board-ready audit report
Clear findings, risk-ranked issues, and specific remediation guidance in a format boards and regulators expect.
Reproducible methodology & data artifacts
Complete documentation of how we tested, what we measured, and every assumption we made.
Risk-ranked findings & remediation roadmap
Prioritized issues with concrete steps your team can take to address them.
Optional quarterly monitoring
Ongoing assessment as your models, data, and populations evolve over time.

Why It Matters

AI decisions at scale deserve the same rigor as financial reporting.

When AI systems make decisions that affect people — who gets a loan, who gets hired, who gets flagged — independent review strengthens credibility with regulators, customers, and boards.

01

Regulation is accelerating

From New York City's bias audit requirements for hiring AI to Singapore's FEAT principles for financial institutions, the compliance landscape is expanding. Organizations that prepare now avoid scrambling later.

02

Independence builds confidence

Internal validation teams do important work. Independent review complements that work by providing an external perspective that carries weight with regulators, investors, and the public.

03

Patterns hide in intersections

A system might treat each group fairly in isolation — but compound disadvantage where groups intersect. Proper intersectional analysis reveals what surface-level testing misses.

How It Works

From scoping to evidence in weeks, not months.

Most engagements complete within 2–4 weeks of receiving data.

01

Scope & Discovery

We identify the AI systems, decisions, populations, and frameworks relevant to your audit. You provide data; we handle the rest.

02

Test & Analyze

We run fairness analysis across all required demographic groups and intersections, using reproducible methodology aligned to your regulatory framework.

03

Report & Recommend

You receive a clear findings report with risk-ranked issues, impact ratios, and specific remediation guidance — written for decision-makers, not data scientists.

04

Monitor & Support

AI systems drift over time. Quarterly monitoring ensures your models stay fair and compliant as data, populations, and regulations change.

Who We Serve

Sectors where AI decisions carry the highest stakes.

Financial Services

Credit scoring, fraud detection, insurance underwriting, and algorithmic trading. We help banks and fintechs demonstrate fair outcomes aligned with FEAT and fair lending requirements.

HR Technology

AI-driven hiring screens, candidate scoring, video interview analysis, and promotion algorithms. Independent audits structured for regulatory compliance and public disclosure.

Public Sector

Government agencies deploying AI for citizen services, risk assessment, and resource allocation. Audits aligned to NIST AI RMF, AI Verify, and applicable government mandates.

Get Started

Ready to know where you stand?

We'll tell you if you're a fit and what data we'd need — then you decide.

hello@trustminerva.com