Trust, Evidence and Governance
Trust, evidence and governance
Built for trust, not theatre.
Kalibra uses structured data, visible reasoning, human review, and clear limitations to support safer AI-assisted health workflows.
Explore by workflow
Kalibra routes, prioritises, and drafts. Humans decide.
Kalibra supports clinical workflows. It does not replace clinical judgement, issue autonomous diagnoses, or bypass qualified professionals.
How trust is designed into the workflow
Human decision authority
Clinicians retain responsibility for diagnosis, interpretation, treatment decisions, and final approval.
Visible reasoning
Kalibra should show why something was surfaced: markers, trends, rules, context, and sources.
Hybrid intelligence
Deterministic logic supports consistency and auditability. LLMs may support synthesis and wording.
Clear limitations
Not emergency care
Kalibra is not designed for urgent or emergency medical situations.
Not autonomous diagnosis
Outputs should be reviewed by qualified professionals where clinical decisions are involved.
Not autonomous prescribing
Recommendations require the appropriate human review, scope, and approval.
Security and governance areas
Data protection
- Access controls
- Encryption at rest and in transit
- Role-based permissions
- Consent where relevant
Clinical governance
- Clinician-in-the-loop review
- Output review and override
- Protocol approval workflows
- Audit trail and provenance
FAQ
Is Kalibra a medical device?
Positioning depends on market, deployment model, and regulatory advice. Website copy should avoid diagnostic or autonomous treatment claims.
How does Kalibra reduce hallucination risk?
It is not designed as a free-form chatbot. It uses structured data, deterministic logic where appropriate, visible reasoning, and human review.
Can a clinician override Kalibra?
Yes. Clinician override is not a bug. It is the point.
Request the security and governance pack.
For procurement, partnership, or clinical governance review, request the supporting materials most relevant to your use case.
healthcare AI governance
Questions to ask before using AI in a health workflow
Responsible healthcare AI starts with a clear boundary: what the system can prepare, what it cannot decide and where a qualified person must review the result.
Kalibra Pro at a glance
Kalibra Pro is health intelligence and continuous-care workflow software for clinics, care teams and digital-health providers. It brings supported labs, records, assessments and wearable signals into a practitioner-controlled workflow.
- Product
- Kalibra Pro
- Category
- Health intelligence and continuous-care workflow software
- Designed for
- Clinics, care teams and digital-health providers
- Works with
- Supported labs, records, assessments and wearable signals
- Workflow
- Context preparation, practitioner review, approved Actions and follow-up
- Clinical boundary
- The EHR remains the system of record. Qualified practitioners retain diagnosis, treatment and final approval.
Where does Kalibra use AI?
Structured rules and scoring can support known workflow logic. Language models may support synthesis and drafting where appropriate. Clinical decisions and final approval remain with qualified people.
Can clinicians see why something was surfaced?
Kalibra is designed to expose the markers, trends, rules, context and sources behind a surfaced priority instead of presenting an unexplained answer.
What should a procurement team review?
The review should cover data location, access controls, consent, retention, subprocessors, incident handling, auditability and the exact role of AI in the proposed workflow.
Is Kalibra compliant in every market and use case?
No blanket website claim can answer that. Compliance depends on the market, deployment, intended use, contracting and regulatory advice. Kalibra provides deployment-specific governance information during review.
