Algorithmic Hiring Risk & Workforce Equity Consulting

Your hiring algorithm is now a legal witness. Make sure its testimony holds up.

Automated applicant tracking and AI screening tools sit at the center of employment discrimination exposure today — under Title VII, the ADA, and a growing patchwork of state AI-hiring laws. Fair Hire audits the systems, trains the people who run them, and builds the documentation trail that protects your organization before a claim is filed.

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Built from forensic-level audit methodology

AI / ATS audits

Independent technical review of your screening system's decision logic, scoring, and disparate-impact exposure.

Workforce training

Practical guidance for recruiters and managers overseeing AI-flagged candidates.

Litigation readiness

Discovery-grade documentation review, before opposing counsel asks for it.

Why this matters now

Most employers can't answer one simple question

When a candidate was rejected, was that decision made by a person, or by the algorithm — and is that distinction documented anywhere? That single gap is where discrimination claims are won and lost. Regulators and plaintiffs' attorneys are increasingly focused on exactly this question, and most ATS platforms were never built to answer it clearly. Fair Hire closes that gap before it becomes a lawsuit.

How we're different

Built from real case analysis, not a checklist

Generic compliance training treats AI hiring bias as an HR policy problem. It isn't — it's a technical and evidentiary problem. Our audit methodology is built from close, technical analysis of how these systems actually behave: rejection logic, scoring criteria, cross-platform data flows, and vendor integration architecture. We deliver findings the way a forensic reviewer would — dated, specific, and defensible.

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Who we serve

Built for the people who buy this work

Employers

Using ATS or AI-driven screening tools who want to know their real exposure before it's tested in litigation.

Employment law firms

Needing a technical co-consultant for clients facing algorithmic discrimination claims.

ATS & screening vendors

Wanting to reduce liability designed into their own products.