Bias and Fairness Reviews
Detect and address hidden bias in your AI systems. We evaluate design, data, and decision processes to ensure fairness across the full lifecycle of your algorithms.
Fairness isn’t a feature — it’s a foundation
Unchecked bias in AI systems can amplify discrimination, erode trust, and harm those most vulnerable. Our Bias & Fairness Reviews go beyond surface metrics to examine where, how, and why bias emerges — and what to do about it.
We combine statistical testing, contextual analysis, and stakeholder insight to assess fairness through a lens that’s technical, ethical, and grounded in human rights.
What we examine:
Dataset representativeness and sampling bias
Disparate impact across demographic groups
Fairness trade-offs in model design and deployment
Labelling and annotation practices
Alignment with fairness benchmarks and legal frameworks
What you receive:
A clear, actionable report outlining risks, mitigation strategies, and design recommendations — so you can build systems that serve equitably and perform responsibly.