AI Triage System

Overview#

A mass casualty event generates dozens of simultaneous emergency calls within minutes. Each caller describes the same scene from a different vantage point, uses different language, and carries different levels of distress. Human dispatchers working alone face an impossible triage problem. The AI Triage System processes those calls in parallel, synthesises intelligence across all of them simultaneously, and surfaces a prioritised picture to dispatchers in the time it takes to answer a single call.

Designed for emergency dispatch centres and public safety answering points, the system deploys seven integrated AI capabilities to analyse, prioritise, and route emergency calls, ensuring life-threatening situations receive immediate attention even during surge events.

Key Features#

Real-Time Call Transcription: Converts live audio to text with high accuracy across challenging acoustic environments, supporting multi-language detection and speaker separation.
Sentiment and Distress Analysis: Evaluates caller emotional state, urgency, and distress levels from both text and acoustic features across seven emotion categories, enabling automatic escalation when urgency thresholds are exceeded.
Background Audio Classification: Detects critical sounds such as gunshots, explosions, screams, and vehicle crashes in call backgrounds, providing context that callers may not verbally communicate.
Dynamic Priority Scoring (P1-P5): Synthesises transcription keywords, sentiment analysis, and audio classification into a risk score that assigns priority levels with target response times ranging from 60 seconds for P1 to 60 minutes for P5.
Surge Redistribution: Monitors queue depth and operator availability in real time, automatically implementing countermeasures such as callback offers, partner transfers, and AI deflection when capacity is exceeded.
AI Callback System: Autonomously handles low-priority calls through voice interaction, resolving a significant proportion of callbacks without human dispatcher involvement.
Predictive Staffing Alerts: Forecasts call volumes up to 24 hours in advance, enabling proactive staffing adjustments that reduce understaffing incidents and overtime costs.
Emergency Keyword Intelligence: Maintains a weighted dictionary of emergency-critical terms that contribute to real-time risk scoring.
Dispatcher Override Support: Dispatchers retain full authority to override AI priority assignments, with feedback used to continuously improve the algorithm.

Use Cases#

Mass Casualty Events: During surge incidents, the system triages dozens of related calls within seconds, consolidates intelligence for dispatchers, and automatically manages queue overflow to ensure no critical calls are missed. Emergency communications centres serving dense urban areas apply this for major incidents.
Routine Call Deflection: On typical days, AI callback handling frees dispatcher capacity by resolving non-emergency inquiries such as noise complaints and records requests autonomously.
Predictive Staffing: Historical analysis combined with weather, event schedules, and seasonal patterns enables supervisors to adjust staffing before predicted surges, maintaining service levels and reducing unplanned overtime.
Multi-Agency Coordination: Consolidated incident views from multiple related calls provide incident commanders with rapid situational awareness for coordinated multi-agency response.

Integration#

The AI Triage System integrates with existing CAD systems, telephony platforms, and emergency response networks. Staffing recommendations export to workforce management platforms, and the system supports mutual aid agreements with partner dispatch centres for automated call redistribution.

Open Standards#

NENA i3 (NG911 Standard for an IP-Based Emergency Services Network): The system records all triage state changes using the NENA i3 audit action vocabulary, ensuring admissibility and compliance traceability across call ingress, routing decisions, and SIPREC recording events.
OASIS CAP 1.2 (Common Alerting Protocol): Priority escalation events egress as fully conformant CAP 1.2 XML alerts, dispatched to downstream recipients via signed webhook delivery, enabling interoperability with CAD systems and partner PSAPs that consume the CAP namespace urn:oasis:names:tc:emergency:cap:1.2.
OASIS EDXL (Emergency Data Exchange Language): The system serialises situational reports and resource messaging using EDXL-SitRep and EDXL-RM envelope formats, supporting structured information exchange during multi-agency surge events.
SIP / WebRTC: Inbound emergency calls are accepted over SIP (including NG911 i3 SIP trunks) and WebRTC sessions; outbound AI callbacks use the same session abstraction, providing a transport-neutral call surface across PSAP, municipal, and browser-originated calls.
SIPREC (RFC 7245 / RFC 6341): Call recording sessions are initiated and sealed using the SIP Recording protocol, with audit entries written at I3_SIPREC_START and I3_SIPREC_SEAL events to satisfy NG911 evidential requirements.
TIA-102 / Project 25 (P25): Triage priority scores and surge redistribution decisions interoperate with P25 radio talkgroup data, allowing dispatcher alerts to be cross-referenced against radio channel availability during mass casualty events.
GraphQL (June 2018 specification): All triage queries, mutations, and real-time subscriptions are exposed through a typed GraphQL API, with rate-limiting, complexity controls, and tenant-scoped resolvers enforced at the schema layer.
ISO 8601 / BCP 47: Timestamps throughout the triage pipeline are serialised in ISO 8601 format with UTC timezone offsets, and detected caller languages are tagged using BCP 47 language codes, supporting multi-language transcription and audit replay.

Last Reviewed: 2026-02-05 Last Updated: 2026-04-14