AIP Use Case: Baggage Operations AI Agent

Baggage Operations AI Agent brings AI-driven coordination to airport operations by unifying data across BHS, scanners, flight schedules, and airline DCS. Through natural language, operations teams can check real-time bag status, identify chokepoints, and trigger corrective actions—without wading through multiple dashboards or terminals.

Powered by QueryPie AI’s AI Platform (AIP) and Model Context Protocol (MCP) integrations, the agent connects to baggage handling systems, RFID/barcode readers, flight operations systems, and communication channels like Teams/Slack. It correlates bag scans, conveyor states, belt load, makeup position status, and flight ETD/ETA to predict misconnect risk and preempt delays. When issues arise—like belt jams, scanner outages, or gate changes—the agent explains the impact in plain language, suggests actions, and orchestrates alerts and tasks across stakeholders.

Key capabilities include:

• Real-time tracking and risk prediction

  • Query bag positions, transfer times, and misconnect risk; detect jams or device outages from telemetry

• Disruption management

  • Propose recovery actions (reroutes, manual pulls, extra staffing) and open tasks with handlers or stations

• Cross-team orchestration

  • Coordinate updates among airline OCC, airport ops, and ground staff; log actions and confirmations

• Passenger service integration

  • Generate proactive notifications to customer service for high-risk connections or mishandled bags

• Analytics and reporting

  • Monitor SLA compliance, turnaround times, choke points, and device reliability trends

This use case shortens response times, reduces mishandled bags, and improves on-time performance. Operations teams gain a conversational command center that turns complex, distributed signals into clear decisions and coordinated actions—while IT and security teams retain governance and full audit trails within QueryPie AIP.