Use cases
AI-driven operation optimization.
Root Cause Identification
Quickly identify root causes of quality fluctuations and defects to increase quality and consistency, eliminate sources of defects, optimize maintenance schedules, improve machine calibration, and offer targeted operator training.
Machine-Level Anomaly Detection
Tap into a real-time stream of machine sensor data to detect trends and anomalies as they unfold across multiple sensor dimensions such as noise, vibration and temperature.
Predictive Maintenance
Deploy a solution in weeks using pre-built ML models with live and historic data — and shift from facility-by-facility maintenance to a global view of machine health.
In-line Quality Control
Monitor production in real time to detect quality deviations as they happen, before defects reach the end of the line.
Who we help
Built for operations and automation leaders.
Automation Directors
Equipment data is trapped in controllers and isolated systems.
Operations Directors
No real-time visibility into downtime, energy or quality.
Industrial Solutions Architects
Need a proven, scalable edge-to-cloud data architecture.
Equipment manufacturers (OEMs)
Want connected, data-driven services on top of their products.