

SurgeAI™ is an ARC2 agentic AI product concept for organizing perioperative information, monitoring configured clinical data, tracking patient progress, and delivering source-aware alerts to authorized clinicians while the surgical team retains control.
All information below is simulated for product demonstration.
SurgeAI correlates the synthetic procedure timeline with configured data streams. Clinically significant interpretations remain subject to qualified clinician review.

Demo: procedure checkpoint reached. Review current phase and planned next milestone.

Demo: blood-pressure trend changed within the synthetic dataset. Review trend display.

Demo: a related imaging study is available for clinician review.
Each themed agent has a bounded duty and can identify itself when delivering an alert.











Checkpoint reached.

Trend review available.
The mobile view is designed as a companion display: current patient context, procedure progress, synthetic vital trends, recent agent messages, and acknowledgement controls. For a production deployment, authentication, session timeout, device policy, secure transport, access logging, and hospital-approved notification workflows would be required.
Every alert carries the responsible agent's image, name, color theme, timestamp and message.
Acknowledgement is recorded separately from clinical acceptance so the system can distinguish “seen” from “acted upon.”
Future workflow can support New → Seen → Acknowledged → Resolved with authorized-user timestamps.
Organize permitted imaging, labs, history, medications, allergies, preparation status and procedure checklists for clinician review.
Track configured physiologic data, procedure phase, documented events and relevant context while surfacing source-aware notifications.
Track recovery milestones, documented observations, permitted monitoring data and follow-up status through configured clinical workflows.
SurgeAI™ is presented here as a clinical monitoring and decision-support concept, not an autonomous surgeon or emergency response system. Production use would require appropriate clinical validation, quality management, cybersecurity, privacy controls, institutional governance, interoperability validation and applicable regulatory review. Important AI outputs should expose source data, timestamps, uncertainty and an audit trail.
Contact: admin@arc2.tech