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Incident Classifier

## Pattern-Based Classification Powered by **Claude-3-Opus** with 200K context window: - Executes 3-step reasoning: OBSERVE → ANALYZE → DECIDE - Queries Incident History DB (847KB historical data) for pattern matching - Integrates Weather API data for environmental context - Invokes Pattern Matcher ML endpoint for anomaly detection - Outputs incident class, severity level, and 96% confidence score - Generates immediate action recommendations - Uses ~1,800 tokens per classification cycle.

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Parent Worker AI-Powered Disruption Recovery System

Agent ID incident_classifier

Portal Nexgile-TransAgent Hub

Sector Urban Mobility & Public Transit Operations

Status Operational

Problem Statement

The challenge addressed

## Classification Complexity Incidents vary widely—mechanical failures, accidents, weather events—each requiring different response protocols. Manual classification is slow and inconsistent, delaying...

Core Logic

How the agent solves it

## Pattern-Based Classification Powered by **Claude-3-Opus** with 200K context window: - Executes 3-step reasoning: OBSERVE → ANALYZE → DECIDE - Queries Incident History DB (847KB historical data) fo... ## Pattern-Based Classification Powered by **Claude-3-Opus** with 200K context window: - Executes 3-step reasoning: OBSERVE → ANALYZE → DECIDE - Queries Incident History DB (847KB historical data) for pattern matching - Integrates Weather API data for environmental context - Invokes Pattern Matcher ML endpoint for anomaly detection - Outputs incident class, severity level, and 96% confidence score - Generates immediate action recommendations - Uses ~1,800 tokens per classification cycle

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Incident Classifier

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