Harrison.ai (Annalise.ai)

Patient arrives at A&E and undergoes an urgent chest X-ray or head CT.

Images are automatically routed to the Harrison.ai engine via PACS integration.

The AI analyzes the scan in 20 to 90 seconds, detecting life-threatening abnormalities like a pneumothorax or intracranial hemorrhage.

The case is immediately flagged and escalated to the top of the radiologist's RIS worklist for prioritized review and immediate intervention.

Patient undergoes a routine CT Chest or Chest X-ray.

The AI processes the image specifically scanning for up to 167 features, including subtle nodules or masses.

The radiologist is provided with an AI overlay highlighting regions of interest as a 'second pair of eyes'.

The radiologist confirms the finding, triggering an early-stage oncology pathway and multidisciplinary team review.

Scans are uploaded from peripheral clinics to the central teleradiology cloud network.

The AI pre-processes the entire batch of incoming studies.

The teleradiologist opens the studies with AI findings already pre-populated as a reference layer.

The radiologist validates the findings rapidly, significantly reducing the time spent dictating standard normal or clearly abnormal reports.

A trauma patient receives a CT Brain or Chest scan to rule out acute injury.

The AI, which evaluates for 120+ findings simultaneously, detects a chronic, unrelated issue (e.g., an early aneurysm or minor lung nodule).

The AI highlights this incidental finding alongside the primary trauma assessment.

The clinical team arranges outpatient follow-up for the incidental condition, improving holistic patient care.

Hospital deploys Harrison.ai across its entire enterprise imaging network.

AI filters and triages thousands of scans daily, ensuring the highest acuity cases are handled first.

Clinicians utilize AI to confidently manage lower-acuity imaging during out-of-hours shifts.

The institution tracks productivity metrics, showcasing reduced turnaround times and fewer missed clinical findings.