FairSight finds hidden discrimination in datasets and AI models — measuring fairness, flagging bias, and providing a clear roadmap to fix it before real people are impacted.
Automated systems now make life-changing decisions about who gets hired, approved for loans, or receives medical care. When trained on flawed data, they silently amplify discrimination — at scale, without accountability.
of large companies use AI screening tools that have demonstrated gender or racial bias
higher loan rejection rate for Black applicants vs white applicants with similar credit profiles
of medical AI tools have never been tested for racial or demographic bias before deployment
From raw data to a complete, actionable fairness audit
Drop any CSV file — hiring records, loan applications, medical assessments. We auto-detect column types.
Select protected attributes (gender, race, age) and the outcome variable. We auto-identify the privileged group.
Get a full fairness report with bias scores, visualizations, and a prioritized remediation roadmap.
A complete fairness toolkit for data scientists, compliance officers, and policymakers
Compute Demographic Parity, Disparate Impact, Equal Opportunity, and Predictive Parity — the full fairness toolkit.
Automatically surface features correlated with protected attributes that could encode indirect discrimination.
Detect compounded bias at the intersection of multiple attributes — gender × race, age × disability, and more.
Concrete, prioritized fix strategies: reweighting, fairness constraints, threshold optimization, governance.
Interactive charts and distribution graphs make disparities immediately visible to technical and non-technical audiences.
Export a complete fairness audit report for compliance, stakeholder review, and regulatory documentation.
Same metrics adopted by Google, IBM, Microsoft, and regulatory bodies worldwide
Difference in positive outcome rates across groups
80% rule — unprivileged rate ÷ privileged rate
True positive rate parity across groups
Precision equality — when predictions are positive
Upload a CSV file and get a complete fairness analysis in seconds — free, instant, no signup.
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