Corvic AICorvic AI
PredictionAnalyticsReportingManufacturingEnergyTransportation

Sensor Data Intelligence

Transforms multi-modal sensor data into real-time predictive insights.

The Sensor Data Intelligence agent ingests high-frequency data streams from IoT sensors, SCADA systems, edge devices, and industrial control networks, fusing time-series signals from vibration, temperature, pressure, flow, and acoustic sensors into a unified analytical model. This multi-modal composition captures complex equipment behavior patterns that single-sensor monitoring systems miss entirely.

The agent's predictive engine continuously evaluates equipment health by learning normal operating envelopes and detecting subtle deviations that precede failures — often weeks or months before conventional threshold-based alarms would trigger. Anomaly detection algorithms distinguish between benign operational variations and genuine degradation signatures, reducing false alarm fatigue while catching the early warnings that matter.

For operations and maintenance teams in manufacturing, energy, and transportation, the agent enables a transition from calendar-based preventive maintenance to condition-based predictive maintenance. This shift typically delivers 25-40% reductions in unplanned downtime, extends equipment service life, and optimizes spare parts inventory. Real-time dashboards and automated alert routing ensure that the right personnel receive actionable intelligence at the right time.

Playbook

How this agent gets built

A reusable plan that composes your data into a working agent. Corvic handles ingestion, orchestration, and deployment automatically.

PlaybookPredictive equipment healthFuse high-frequency IoT, SCADA, and edge signals to learn normal operating envelopes and predict failures weeks before threshold alarms would trigger.
You provide
IoT sensor streamsSCADA historyAsset & maintenance records
Connectors
IoT / MQTT brokerSCADA historianCMMS
Plan6 steps

Ingest high-frequency streams from IoT sensors, SCADA, edge devices, and control networks.

Uses
Stream connectorsTime-series ingest
Produces
data.telemetry
Run concurrently

Top to bottom; steps on the same row run in parallel. Click a step to see what it does.

Final outputPredictive maintenance alerts + equipment health dashboard
Capabilities
Real-time monitoring
Predictive analytics
Multi-sensor fusion
Anomaly detection

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