AI and Agentic Workflow Governance

Regenemm Healthcare uses AI to support clinical workflows, not to replace clinical responsibility.

Our platform is designed so that AI and agentic assistants operate inside governed healthcare boundaries: role, workflow, consent, data access, audit, provenance, release gates, and human review.

AI can support clinicians, patients, care teams, administrators, and healthcare organisations. In healthcare, AI must be auditable, preserve provenance, respect consent, and support human clinical judgement rather than replace it.

Our Position

Regenemm does not treat AI assistants as autonomous clinicians.

AI systems may assist with clinical documentation, consultation summarisation, patient summaries, patient education drafts, triage support, care-team coordination, missing-item detection, evidence retrieval, billing preparation, medicolegal chronology preparation, home-monitoring workflow support, hospital workflow support, and interoperability workflows.

Material clinical outputs require appropriate human review before clinical reliance, patient-facing release, or external disclosure.

Identifiable patient records are not used to train foundation models by default.

Clinical data processed through Regenemm is handled for declared healthcare, administrative, interoperability, patient-authorised, support, security, or governance purposes.

Agentic Assistants

Regenemm agentic assistants are bounded workflow participants.

They may support tasks such as:

• preparing draft clinical documentation;
• summarising patient context;
• identifying missing workflow items;
• retrieving relevant evidence;
• preparing escalation briefs;
• supporting billing or claim-readiness workflows;
• assisting medicolegal chronology preparation;
• drafting patient education content for clinician review.

Agentic assistants must not:

• make final clinical decisions;
• silently change clinical truth;
• bypass Regenemm Voice as the Hub;
• access patient data outside declared workflow need;
• access clinical servers directly outside declared policy;
• contact patients without an authorised workflow;
• release patient-facing material without an authorised release gate;
• use identifiable patient data for foundation model training by default.

Care Graph Contracts

Regenemm governs agentic workflows through Care Graph Contracts.

A Care Graph Contract defines:

• the workflow purpose;
• the human care-team participants;
• the agentic participants;
• permitted data classes;
• permitted tools;
• forbidden actions;
• escalation rules;
• human review requirements;
• release gates;
• audit events;
• network and runtime boundaries.
• data permanence pathway.

This means AI activity is not free-form. It is governed by declared clinical workflow structure.

Hub-Governed AI

Regenemm Voice acts as the Hub and clinical control plane.

The Hub governs:

• clinical state;
• identity;
• access;
• consent;
• provenance;
• audit;
• workflow orchestration;
• release controls;
• data permanence.

Spokes provide workflow surfaces. AI assistants operate inside those workflows, but durable clinical state and audit records return to the Hub.

The design rule is:

Spokes contextualise.
The Hub governs and persists.

Knowledge Retrieval

The Regenemm Knowledge Base supports evidence retrieval and reference workflows.

Knowledge retrieval may support clinicians, patient education drafts, and agentic workflow context. It does not override patient-specific clinical truth governed by Regenemm Voice.

Provenance and Auditability

Clinical AI must be explainable at the workflow level.

Regenemm is designed to preserve provenance for material outputs, including:

• source documents;
• retrieved evidence;
• clinical context used;
• agent actions;
• tool calls;
• policy checks;
• human review events;
• release decisions;
• state changes.

This supports review, clinical trust, quality assurance, and governance.

Regenemm Link and Patient Control

Regenemm Link is designed as the patient-controlled record and sharing surface.

Where AI supports patient-facing outputs, those outputs should respect:

• patient consent;
• sharing permissions;
• carer or family access rules;
• clinician review requirements;
• patient-safe language;
• release gates.

Patients should remain central to how their information is organised, shared, and used.

Edge Connector and AI Workflows

The Regenemm Edge Connector may securely ingest approved clinical and administrative data flows, including HL7, HealthLink-related messages, pathology, radiology, practice management system signals, and approved local server exports.

Edge Connector data feeds into Regenemm Voice.

AI assistants may use that information only when a declared workflow permits it, and only through governed access pathways.

Regenemm Connect and Interoperability

Regenemm Connect supports standards-based interoperability, including SMART on FHIR, EMR pathways, and MHR-related workflows where configured and authorised.

AI and agentic workflows that interact with external systems must respect:

• identity;
• consent;
• purpose of use;
• data residency;
• audit;
• external-system mapping;
• release controls.

Interoperability is treated as a governed boundary, not an unrestricted data flow.

Clinical Safety Posture

Regenemm's AI governance model is designed around clinical safety.

This includes:

• bounded agent roles;
• least-privilege access;
• declared workflow purpose;
• human review;
• auditability;
• provenance;
• release gates;
• escalation rules;
• data minimisation;
• no patient-data training by default.

AI in healthcare must be useful, but usefulness is not enough. It must be governed.

Human Review

Regenemm is designed for human-centred clinical AI.

AI may assist.
Clinicians decide.
Patients control sharing through Regenemm Link.
Audit persists through the Hub.

Summary

The Hub governs.
The Spokes contextualise.
The Edge Connector ingests.
Link supports patient control.
Connect supports interoperability.
The Knowledge Base retrieves evidence.
Agents assist.
Humans review.
Audit persists.

For questions about AI governance, privacy, or security:

• privacy@regenemm.com
• security@regenemm.com