AI-Powered Emergency Staffing System

Core Logic

Powered by GPT-4 Turbo, the Orchestrator parses incoming requests, determines optimal task distribution across specialist agents, manages inter-agent dependencies, and synthesizes final recommendations. It maintains workflow state, handles escalations, and ensures all agents contribute to the final decision within time constraints.

Core Logic

Using GPT-4 combined with a custom rules engine, this agent validates certifications against RDW and CBR databases, checks EU Regulation 561/2006 driving hour limits, verifies rest period compliance, and validates insurance coverage. It performs comprehensive compliance checks per worker with high accuracy.

Core Logic

Employing GPT-4 with a machine learning ensemble, this agent scores workers using weighted criteria: Certifications (40%), Performance History (25%), Travel Distance (20%), and Preferences (15%). It generates detailed match breakdowns with AI reasoning explanations and ranks candidates by overall suitability.

Core Logic

Integrating GPT-3.5 with Maps APIs, this agent geocodes locations, fetches live traffic data, calculates optimal routes using Dijkstra's algorithm with traffic-weighted edges, and provides accurate ETAs with buffer time for parking and check-in. It suggests alternative routes during congestion.

Core Logic

Using GPT-4 Multilingual, this agent generates personalized notifications in the worker's preferred language, optimizes delivery channels (SMS, push, email), tracks message delivery, and handles response processing. It achieves high response rates through contextual personalization.

Core Logic

Powered by GPT-4 with a specialized risk model, this agent performs multi-criteria decision analysis (MCDA), detects anomalies in worker patterns, generates predictive alerts for potential issues, and suggests specific mitigation actions. It provides risk scores with confidence levels and historical context.

Core Logic

Using GPT-3.5 with weather API integrations, this agent monitors real-time conditions, assesses route safety, predicts delays based on precipitation and visibility, tracks storms affecting planned routes, and adjusts travel time estimates accordingly. It provides severity ratings and specific recommendations.

Core Logic

Employing XGBoost and Prophet ML models, this agent analyzes historical request patterns, correlates with external factors (day of week, season, weather, events), and generates hourly/daily demand forecasts. It identifies potential capacity gaps and recommends preemptive worker scheduling.

Core Logic

Using Claude 3.5 Vision with OCR, this agent processes uploaded documents, verifies authenticity through visual analysis and cross-referencing, monitors expiry dates, detects potential fraud indicators, and maintains verification audit trails with high accuracy in document validation.

Core Logic

Powered by GPT-4 with reinforcement learning, this agent analyzes assignment outcomes, identifies successful matching patterns, detects areas for improvement, conducts A/B testing of matching strategies, and continuously optimizes model weights based on client satisfaction and worker performance data.