Overview#
During a major incident, a dispatch centre's phone lines fill with calls that range from genuine emergencies to status inquiries from concerned residents. Every second a dispatcher spends on a routine inquiry is a second not spent on the situation requiring immediate action. The AI-Powered Deflection and Intelligent Dispatch module addresses this directly: it triages incoming requests in real time, resolves what can be automated, and delivers complex cases to human operators with full context already assembled.
Deployed as an AI deflection panel within dispatch consoles, the module augments rather than replaces human dispatchers. AI-generated suggestions and automated handling options are presented for dispatchers to accept, modify, or override based on their professional judgement.
Key Features#
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Intelligent Request Triage: AI analysis of incoming requests classifies urgency, identifies request type, extracts key entities, and recommends routing to either automated resolution or human dispatch with confidence-scored justification.
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Automated Deflection: Routine requests including status inquiries, information lookups, and standard procedure questions are resolved automatically through conversational AI with knowledge base integration.
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Dispatcher Augmentation Panel: An AI assistant panel within the dispatch console provides real-time suggestions including response templates, relevant case history, resource recommendations, and priority assessments.
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Context-Aware Routing: Routes complex requests to the most appropriate operator based on request type, required expertise, current workload, shift schedule, and geographic proximity.
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Escalation Detection: Continuous monitoring of automated interactions detects situations that require human intervention, automatically escalating with full conversation context when the AI reaches its confidence or capability threshold.
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Knowledge Base Integration: The AI draws on organisational knowledge bases, standard operating procedures, and historical case resolutions to provide accurate and consistent automated responses.
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Performance Analytics: Tracks deflection rates, resolution accuracy, escalation patterns, and dispatcher workload impact to continuously optimise AI routing rules and response quality.
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Multilingual Support: Handles incoming requests in all platform-supported languages with automatic language detection and responses delivered in the caller's language.
Use Cases#
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Emergency Call Triage: AI pre-screens incoming calls to identify true emergencies requiring immediate dispatch versus non-emergency requests that can be handled through automated information services or callback scheduling.
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Non-Emergency Request Handling: Automatically resolves routine requests such as report filing status checks, office location inquiries, and procedure questions without requiring dispatcher involvement.
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Dispatcher Workload Management: During high-volume periods, AI deflection handles the surge of routine requests while human dispatchers focus on complex and urgent situations that require professional judgement.
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After-Hours Coverage: Provides intelligent automated handling of requests received outside normal operating hours, resolving what can be automated and queuing the rest with priority classification for the next shift.
Integration#
This module integrates with the PSAP dispatch system for call handling workflow, the AI/LLM orchestration layer for conversational AI capabilities, the knowledge base for response content, and the work order execution system for automated task creation from deflected requests. Analytics feed into the operations dashboard for workload and performance reporting.
Open Standards#
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NENA i3 / NG9-1-1 (NENA-STA-010.3): The intelligent dispatch layer integrates with the NENA i3 functional architecture, using the Emergency Services Routing Proxy (ESRP) for policy-based PSAP routing and the Emergency Incident Data Object (EIDO) schema for structured incident handoff between the AI triage engine and CAD systems.
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LoST, Location-to-Service Translation (RFC 5222): Location-based call routing queries a LoST server to resolve the correct PSAP URI before a deflected or escalated call is dispatched, ensuring geographic accuracy in routing decisions.
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PIDF-LO, Presence Information Data Format Location Object (RFC 4119 / RFC 5491): Caller location is encoded as PIDF-LO XML and submitted to LoST and ESRP endpoints, supplying the dispatch engine with standards-compliant geo-context at the point of routing.
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Additional Data (RFC 7852 / NENA-STA-012): The platform's Additional Data Repository populates dispatcher augmentation panels with RFC 7852 provider, subscriber, and service data blocks retrieved per call, giving dispatchers richer context before they handle an escalated request.
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GraphQL (June 2018 specification): The AI triage and intelligent dispatch domains expose their query, mutation, and subscription surfaces as GraphQL APIs, enabling the dispatch console and analytics layer to fetch triage scores, routing decisions, and workload metrics in a single typed request.
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WebSocket (RFC 6455): Real-time AI suggestions, escalation alerts, and workload updates are pushed to dispatcher consoles over persistent WebSocket connections, avoiding polling and minimising latency between AI triage decisions and human action.
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ITU-T E.164: All incoming phone numbers ingested by the triage pipeline are normalised to E.164 international format before classification, routing, and case-history matching, ensuring consistent identification across channels.
Availability#
- Enterprise Plan: Full AI deflection and dispatch augmentation included
- Professional Plan: Basic AI triage included; advanced deflection and dispatcher panel available as add-on
Last Reviewed: 2026-03-02 Last Updated: 2026-04-14