AI Governance
AI you can defend to a regulator.
In regulated care, an AI feature that can't explain itself is a liability, not an advantage. iCura's AI governance model is built to withstand scrutiny — from a registered manager, an inspector, or a board.
Most AI in operational software is a feature. In iCura, governance is the foundation: every AI output is scoped to what a user is permitted to see, explainable in plain language, and routed to a human for approval whenever risk crosses a defined threshold. This is what makes AI adoption possible in a regulated sector — and it is difficult for generic SaaS platforms to retrofit.
The governance model
Four controls that make AI trustworthy in care.
Immutable Audit Trails
Every action is recorded and cannot be altered after the fact.
Policy Enforcement Checkpoints
Governance rules are enforced at the point of action, not after.
Human Approval Workflows
High-risk AI and operational actions require a human decision.
AI Governance Controls
Every AI output is explainable, scoped and auditable.
Our commitment
Three rules iCura's AI never breaks.
Every output is explainable.
If iCura's AI flags a risk or recommends an action, it shows the underlying evidence in plain language — never a bare score or an unexplained alert.
Every output is permission-scoped.
AI never surfaces data a user isn't already entitled to see. Governance is enforced at the data layer, not the prompt.
High-risk actions always reach a human.
Anything above a defined risk threshold — a safeguarding concern, a compliance gap, a financial change — is routed for human approval before it takes effect.
Ask us anything about how the AI works.
Our team will walk your compliance or IT lead through the governance model in detail.