Scope
Define the role first.
Before a system interacts with anyone, define who it is for, what it should help with, and where its role ends.
Governance
Health intelligence needs control before output.
ClaraWell builds governance into how Health AI is designed, reviewed, and operated, from scope and consent to safety boundaries and oversight.
Governance model
Control is part of our system.
ClaraWell governance defines what a system is for, what it can do, where it should stop, and when a person or clinical team should step in.
Safety
Keep the boundaries visible.
People should be able to understand what the system can do, what it cannot do, and when human support is needed.
Review
Governance continues after launch.
Review how the system performs, track changes, and update or retire it when conditions change.
Responsible oversight
Oversight remains part of the operating model.
ClaraWell systems are designed with defined ownership, appropriate clinical input, deployment review, and accountability for how Health AI is used.
See how ClaraCortex governs AI systemsSafety boundaries
Boundaries define what systems is are allowed to do.
ClaraWell systems make important limits visible, including diagnostic boundaries, consent requirements, escalation points, and when a person should step in.
Compliance infrastructure
Compliance is a design constraint.
Privacy, consent, data minimization, applicable requirements, and accountability are considered as the system is designed.
Auditability & review
Know what changed, when, and why.
ClaraWell designs systems so teams can understand what changed, how the system was performing, and what requires review over time.
Governance principle
Keep governance close to the system.
ClaraWell builds Health AI with visible limits, clear ownership, and defined review pathways from deployment onward.
We believe governance is part of the responsibility of building Health AI well. It should be considered early, remain visible in operation, and continue as systems evolve.
