Stay on top of healthcare AI bias risk

Fairsense is an AI bias risk observability platform designed for healthcare and cross-functional governance.

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A screenshot of fairness analysis results showing a low risk score for training dataset bias and high risk for model fairness. The screenshot is overlayed on top of a 3-dimensional graph structure, abstractly representing multi-stakeholder collaboration.

Distrust slows down adoption of innovative AI solutions

Accelerated AI growth is facing stakeholder distrust and rising regulatory and compliance risk

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Current AI development processes fail to root out AI bias in healthcare solutions

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Relying solely on technical accuracy and performance puts your business at risk

Getting AI fairness right in healthcare requires clinical, legal, and ethical inputs. Our platform guides your team through defining fairness, to quantifying and identifying areas of bias, so that you can apply targeted mitigations to reduce bias risk.

Diagram with bubbles representing distinct socio-technical factors of fairness, with fairness at the center. The bubbles surrounding fairness include demographics, training datasets, existing health disparities, harms & benefits, feasibility, end user experience, clinical context, laws, regulations, and policies.

Measure, monitor, and mitigate healthcare AI bias at scale

From one model to 1,000, Fairsense makes it easy for cross-functional teams to observe, de-risk, and report on the fairness of their models.

Graphic of a line with data points on it, representing continuous monitoring.

Reduce healthcare inequities instead of amplifying them

Comply with existing & emerging regulations

Build trust with administrators, clinicians & patients