Trust Resource Center
Educational resources to help healthcare organizations evaluate AI vendor trust, governance, security, compliance, and procurement risk with confidence.
Understanding AI Vendor Trust
What vendor trust means for healthcare AI and the signals that matter most — governance, security, compliance, transparency, and operational stability.
Read guideAI Governance Fundamentals
Core governance concepts: policies, human oversight, accountability, model lifecycle, and auditability for AI systems.
Read guideHealthcare AI Risk Management
A structured approach to identifying, assessing, and mitigating healthcare AI risk across the vendor lifecycle.
Read guideProcurement Risk Assessment Guide
How to weigh governance, security, compliance, and integration complexity in healthcare AI procurement decisions.
Read guideSecurity Due Diligence Checklist
A practical checklist for security review before vendor adoption — encryption, access controls, logging, and incident response.
Read guideAI Compliance Evaluation Guide
Evaluating HIPAA, BAA availability, SOC 2, ISO 27001, and HITRUST documentation for AI vendors.
Read guideVendor Governance Best Practices
Industry best practices for governing AI vendors across the lifecycle — intake, review, monitoring, and renewal.
Read guideTrust Score Methodology
How the VNDRIQ Vendor Trust Score is calculated across ten weighted categories using registry data.
Read guideGovernance Maturity Methodology
The five-level AI Governance Maturity Model — Foundational, Developing, Established, Advanced, Leading — and its assessed indicators.
Read guideThese resources are educational and informational, not legal or compliance advice. The VNDRIQ Trust Score and Governance Maturity Model are informational frameworks based on registry data, not certifications or guarantees.