Measurement Labs offers a cloud‑based platform that ingests and normalizes sensor data from industrial protocols such as OPC‑UA, MQTT, and Modbus, then applies real‑time analytics, anomaly detection, and predictive maintenance models.
Funding
Funding not disclosed
Founders
Product
Problem
Operators of physical assets often collect large volumes of sensor data that remain siloed, unprocessed, and difficult to interpret, leading to delayed detection of issues and suboptimal performance across utilities, infrastructure, manufacturing, and robotics.
Solution
Measurement Labs provides a cloud‑based platform that ingests data from diverse industrial sensors, applies advanced analytics—including anomaly detection and predictive modeling—and visualizes results on real‑time dashboards. The system normalizes and enriches raw measurements, delivering actionable insights that enable operators to monitor asset health, anticipate failures, and optimize processes without extensive custom development. Integration points such as APIs and connectors allow seamless incorporation into existing control systems and workflows, supporting continuous improvement of complex physical environments.
Target Audience
Primary customers are asset operators and engineering teams in utilities, infrastructure management, manufacturing plants, and robotics deployments seeking to turn sensor data into operational intelligence.
Features
- Unified data ingestion engine supporting common industrial protocols (OPC-UA, MQTT, Modbus, etc.) and edge device streams
- Real‑time analytics pipeline with built‑in anomaly detection, trend analysis, and predictive maintenance models
- Customizable, interactive dashboards that surface key performance indicators and alert operators to critical events
- Open API and SDKs for embedding insights into SCADA, ERP, or custom applications
- Scalable cloud architecture designed for high‑frequency, high‑volume sensor streams across multiple sites