Services

Services

Making Healthcare AI Viable: Turning Good Intentions Into Trusted Systems

At Viable Health AI, we help healthcare organizations bridge the gap between innovation and trust.

AI projects rarely fail because of technology—they fail because governance, fairness, and communication weren’t built in from the start. Our work ensures your AI initiatives are designed, governed, and communicated responsibly, so they succeed with both clinicians and patients.

Our Focus Areas

AI Governance and Accountability

Most medical AI pilots before they’ve defined who is responsible for monitoring them or the impact they might have on patients. We help organizations put guardrails in place early—so oversight isn’t an afterthought.

Our approach builds on leading frameworks from the FDA, WHO, and NIST, helping your teams:

  • Explore governance processes that survive beyond pilot phase
  • Assess accountability for bias, drift, and data quality
  • Align compliance, IT, and clinical leadership around shared oversight
  • Translate policy language into practical workflow steps

Outcome: Measurable governance that builds confidence internally and externally.

Bias Detection and Equity Evaluation

Unrecognized bias can quietly distort AI results and harm patient trust. We help you identify and reduce these risks through governance-driven reviews and fairness assessments that fit your real data environment.

Our work includes:

  • Reviewing datasets for representativeness and systemic bias
  • Advising on bias detection tools and interpretive frameworks
  • Translating results into executive and patient-facing language

Outcome: AI systems that support health equity rather than magnify disparities.

Patient Communication and Trust Strategy

Even the most accurate model fails if clinicians and patients don’t trust it.

We specialize in helping health systems communicate AI’s purpose and limitations clearly, respectfully, and transparently.

Our approach includes:

  • Co-creating patient-facing materials that explain AI in plain terms
  • Supporting clinician communication training on AI-supported care
  • Developing messaging frameworks that align with your institutional ethics and brand voice

Outcome: Informed patients, confident clinicians, and fewer barriers to adoption.

Responsible Data Stewardship

Every trustworthy AI system starts with trustworthy data.

We help organizations strengthen their data governance practices by focusing on ethical handling, transparency, and accountability:

  • Assessing data access, consent, and provenance policies
  • Mapping governance structures to evolving regulatory guidance
  • Advising on transparency and explainability standards

Outcome: Data practices that make AI safer, auditable, and sustainable.

Engagements

Governance Readiness Review – A 3-week diagnostic assessing AI governance maturity and patient communication readiness.

  • Bias and Equity Advisory – A focused review of fairness and representativeness within AI projects.
  • Trust Communication Workshop – A guided session helping teams explain AI confidently to clinicians, boards, and patient communities.

Why Organizations Choose Viable Health AI

Hospitals and health systems choose Viable Health AI because we speak both languages—clinical and patient—and help leadership translate AI ambition into responsible, sustainable action.

We don’t build models.
We make them Viable.

About the Founder

Viable Health AI was founded by Dan Noyes, a Certified Patient Leader with more than 25 years of consulting experience for organizations such as Georgetown University, University of Virginia, Pfizer, and Rubbermaid.

After a life-changing diagnosis, Dan rebuilt his expertise around responsible AI and data governance, earning over 40 certifications from Stanford, Johns Hopkins, Wharton, and Google Cloud.

His lived experience shapes every engagement, ensuring that innovation in healthcare remains accountable to the people it serves.

Contact

dan@viablehealthai.com
linkedin.com/in/dannoyes
(585) 230-9565

Typical response time: 24–48 hours.