Evidence before inference
Clinical information and AI output should remain connected to supporting evidence and provenance.
SAFE BY DESIGN
Safe by design — fast by architecture.
NEYQOR is designed around provenance, traceable sources, explicit authority boundaries and fail-closed behavior.
PATIENT
CONTEXT
EvidenceTimelineAICare teamSignalsSourceCONTEXT
HUMAN AUTHORITY BOUNDARY
AI may assist. Clinical authority remains human.
Clinical evidence→Verified context→AI assistance→Clinician review→Clinical action
Evidence before inference · Human authority remains human · Fail closed · Minimal necessary change
NEYQOR SAFETY MODEL
Clinical AI should never require blind trust.
Safety is treated as an architectural property, not a disclaimer.
Human authority remains human
AI can assist interpretation and workflow without silently becoming a clinical authority.
Fail closed
Unclear identity, provenance or authorization stops the workflow rather than triggering assumptions.
Bounded interfaces
Integrations are permitted through explicit contracts and trust boundaries.
Separation of evidence and diagnosis
Raw clinical evidence is not automatically diagnosis, severity, causality or truth.
Minimal necessary change
Safe, verified behavior is not changed merely for architectural neatness.
“Är det inte säkert för vården, bygger vi det inte.”
If it is not safe for healthcare, we do not build it.
NEYQOR
One patient. One clinical context.
Connected clinical workspace.
Safe by design — fast by architecture.