See Structured Healthcare AI Governance in Practice

Generic GRC platforms are built to manage policies, tasks, and third-party risk. Onboard AI is purpose-built for healthcare AI governance. It provides a structured AI risk evaluation pipeline — including intake and triage, assessment automation, healthcare-specific testing using FHIR standards, and a longitudinal Canonical Product Profile that captures lifecycle oversight.
Onboard AI does not replace GRC. It operationalizes AI governance within healthcare.

No. Onboard AI can ingest tickets from existing enterprise systems, running a parallel workflow for deep, healthcare-specific AI risk evaluation, then can send the package back to your existing enterprise management tool. While Onboard AI offers a robust workflow web application, it can also be utilized purely via APIs.

Assessments align with recognized healthcare risk frameworks such as CHAI, NIST, WHO, Join Commission, etc. and relevant state and federal regulatory requirements. 

Additionally, AI testing and monitoring is uniquely built for healthcare, leveraging FHIR APIs and data, plus recognized healthcare evaluation benchmarks.

By enforcing consistent requirements in the form of controls, evidence, ownership and mitigations, AI tools under evaluation are quickly identified according to their risk profiles. This allows AI implementers to make faster, more informed decisions based on standardized heuristics. The result is fewer stalled pilots, less work and clearer accountability.