WHERE AGENTIC AI BREAKS HERE
Diagnostic hallucination at high confidence
The agent reports a clinically plausible but unfounded answer with no evidentiary trail. The clinician treats it as ground truth.
Patient-side prompt injection
Symptom descriptions and uploaded records carry hidden instructions. Nudged agentic AI applies clinical logic it cannot defend.
Behavioural drift across model updates
The underlying model updates. Clinical behaviour shifts. Without continuous monitoring, nobody catches it until a patient outcome.
Agentic AI generates the clinical recommendation
Symptom presentations, patient records, and consultation history all read inside the autonomous loop.
Disseqt scores it against clinical safety policy and evidentiary support
Diagnostic-hallucination probes, edge-case symptom checks, and the 67+ validator suite all run as a standard runtime gate.
Out-of-scope clinical claims flagged with escalation to clinician sign-off
The clinician reads what triggered the flag, the policy context, and the specific recommendation that needs human override.
FDA, MHRA, EU AI Act, and DCB clinical-safety audit trail
Clinical-safety and regulator artefacts assembled from live consultations, ready for notified-body review on demand.
Per-consultation clinical-safety scoring
Every recommendation evaluated against safety policy and evidentiary support before it reaches the clinician.
Drift detection across model updates
Clinical behavioural shifts caught release-over-release, before a patient outcome surfaces them.
Notified-body-ready evidence pack
FDA, MHRA, EU AI Act, HIPAA, GDPR, and DCB artefacts generated from live consultations, ready on demand.
One pattern, adjacent workflows
The same assurance shape reused across triage, medication review, and adjacent clinical AI workflows.
