Platform Launch: Q3 2026

Governance audit methodology for high-stakes artificial intelligence in healthcare and public administration.
Precision ethics. Clinical defensibility.

Early access enquiries are open. Submissions are triaged and responded to in priority order.

Founder: Walter Brown | LinkedIn
Walter Brown provides independent, evidence-based auditing of Health AI systems, utilizing a proprietary methodology to identify and mitigate implicit ethical risks, algorithmic bias, and health inequalities for public and private sector stakeholders.
Consent: By submitting this form, you agree that Ethical Alpha Audit™ may use your details to respond to your enquiry. If you tick "Keep me updated", we may also send occasional launch updates.
Privacy | Legal & Reliance Boundary

Methodology

Ethical Alpha Audit applies governance-first evaluation to high-stakes artificial intelligence. The framework emphasises non-compensatory safety thresholds, documented accountability, bias mitigation, explainability, and deployment monitoring.

Read the methodology overview

Research and outputs

The project sits at the intersection of AI governance, health equity, innovation policy, and public accountability. The site provides a home for white papers, implementation notes, and future scholarly outputs.

View current research themes

Governance and security

Responsible disclosure information, privacy materials, and legal boundaries are published as part of the site’s governance posture. Machine-readable files are also available for search engines and standards discovery.

Review the security policy

Site resources: Sitemap | Standard manifest | security.txt | llms.txt