Audit-AI

Audit-AI is a sophisticated technical framework and SaaS platform designed to measure and mitigate bias in machine learning models, specifically targeting high-stakes decision-making environments like HR, finance, and healthcare. As of 2026, the tool has positioned itself as a critical component of the AI Trust, Risk, and Security Management (AI TRiSM) stack, facilitating compliance with the EU AI Act and US algorithmic accountability standards. The architecture focuses on identifying disparate impact through rigorous statistical tests, including the Four-Fifths Rule, Fisher’s Exact Test, and Z-tests. Unlike standard monitoring tools, Audit-AI provides a deep-dive into protected class correlations, even when sensitive attributes are not explicitly present in the training data, by identifying 'proxy variables.' Its 2026 market position is defined by its ability to integrate directly into CI/CD pipelines as a 'Fairness Gate,' preventing biased models from ever reaching production. The platform supports both post-hoc auditing and in-training bias mitigation strategies, offering a dual-layer approach to ethical AI development.