AIP Use Case: Factory IoT AI Agent
Factory IoT AI Agent brings conversational intelligence to industrial operations. It continuously monitors sensor streams from PLCs, machines, and production lines, flags anomalies, and triggers the right workflows—like maintenance tickets, shift notifications, or safety procedures—without operators digging through dashboards.
Running on QueryPie AI’s AI Platform (AIP) with Model Context Protocol (MCP) integrations, the agent connects to IoT data pipelines, historians, MES/SCADA, and IT systems like Jira, ServiceNow, and Slack. When a threshold breach or pattern deviation occurs (e.g., motor vibration spike, temperature drift, or line throughput drop), the agent explains the issue in plain language, provides context (recent trends, affected assets, probable root causes), and initiates corrective actions with approval gates when needed.
Key capabilities include:
- Real-time monitoring and anomaly detection
- Watch telemetry across temperature, vibration, pressure, energy, cycle time, scrap rate, and OEE metrics
- Natural language diagnostics
- Ask “Why is Line 2’s OEE down 5%?” or “Show bearing vibration trends for Press #7 in the last 24 hours”
- Root-cause context and recommendations
- Surface correlated signals, recent work orders, and changeovers; propose actions or SOP steps
- Workflow orchestration
- Open maintenance tickets, notify shift leads, adjust production schedules, and update runbooks automatically
- Safety and compliance support
- Document events, attach logs and charts, and generate audit-ready incident summaries
This use case shows how plants can shorten detection-to-action cycles, reduce unplanned downtime, and standardize response procedures. Operators and engineers get clear, context-rich alerts and hands-free orchestration across OT and IT—while platform and security teams retain centralized governance, approvals, and full audit trails within QueryPie AIP.