We help organizations derisk AI early, so ROI aligns with real-world use.
Designing proportional governance infrastructure for AI systems.
How We Work
Identify where AI risk emerges in operations — and derisk it early
- Clarity — We help you determine whether AI risk is material and what governance infrastructure is appropriate before you scale.
- Discovery — A structured phase to identify risk exposure, map accountability, and design proportional oversight mechanisms.
- Proportional Design — Governance effort that scales with risk — ensuring real-world readiness without over-engineering.
Assess Your Organization's AI Risk Exposure
If you’re already building or experimenting with generative AI and Agentic AI, understanding where risk may scale is a useful first step.
Our program, Agentic Village, includes an online Agentic AI Risk Assessment designed to help teams reflect on governance readiness, autonomy, and impact, without legal overreach or heavy up-front process.
Get Started Today
Our online risk assessment only takes minutes. You'll receive a risk score and summary report, with option to pay for deeper analysis.
Resources And Insights
Frequently Asked Questions
Please reach us at brian@health-vision.ai if you cannot find an answer to your question.
Start with the Clarity Session. We quickly determine whether AI risk is material in your use context and define the next step (baseline score, governance alignment, or 90-day plan).
You get: a 1-page summary + initial decision/outcome boundary snapshot + next-step recommendation.
The Clarity Session is designed for materiality triage. We assess where AI touches decisions, how reversible errors are, and what harm or compliance exposure exists.
You get: a materiality call + initial boundaries + recommended path forward.
Use the AI Maturity Score / Readiness Assessment to establish a defensible baseline across governance, oversight, security, and operational readiness.
You get: scorecard + gap heatmap + prioritized fixes + proportional controls recommendations.
Videos and Multimedia
Terminator vs Tricorder: Marketing and CX Implications for Responsible AI in Life Sciences
Find out about the Transparency-Containment Paradox and more.
Invited Presentation at the 2025 BioPharma eMarketing Summit, Philadelphia, PA, April 23-24, 2025.
AI Governance in Healthcare Explained
The Three Pillars of AI Governance: Transparency, Observability, and Explainability.
Featured on "Pivoting to Web3 Podcast" with Donna Mitchell, April 2025.
AI Literacy Training for Health Care Staff
Why You Need AI Literacy and Coaching, and How We Help.
Webinar interview with Jose Garcia, "Talk Coded."
Health AI: Privacy and Security
Guest Speaker on: SenzMate Connecting the Future Webinar Series #10. May 2025.
(Brian M. Green speaks starting at 40:12)
Contact Us
Health-Vision.AI LLC
Join Our Mailing List
Sign up for our newsletter!
Copyright © 2026 Health-Vision.AI, LLC - All Rights Reserved.
This website uses cookies.
We use cookies to analyze website traffic and optimize your website experience. By accepting our use of cookies, your data will be aggregated with all other user data.