Anomalyse provides a machine‑learning based anomaly detection platform that automatically learns normal behavior from multi‑dimensional sensor streams and delivers real‑time, explainable alerts. The solution enables proactive predictive maintenance, process optimization, and energy monitoring with minimal setup and integration via APIs, helping industrial operators prevent failures and improve equipment efficiency.
Funding
Funding not disclosed
Founders
Product
Problem
Industrial operators generate large volumes of sensor and operational data, yet they often lack timely, understandable insights to act on that data. Existing SCADA and reporting tools rely on static rule‑based alarms, providing limited context and causing reactive responses to downtime, inefficiency, and waste.
Solution
Anomalyse offers a machine‑learning based anomaly detection platform that automatically learns normal behavior from multi‑dimensional sensor streams and flags deviations in real time. The system delivers explainable alerts that identify not only that an abnormal condition exists but also why it occurred, enabling proactive maintenance, process optimization, and energy monitoring. With minimal setup and no need for machine‑specific models, the platform integrates with existing data pipelines and presents actionable insights through a web interface, helping asset operators prevent failures and improve overall equipment efficiency.
Target Audience
Primary customers are OEMs, plant managers, and asset operators in manufacturing, process, and energy-intensive industries seeking to improve equipment reliability and operational efficiency.
Features
- General‑purpose ML engine that models normal asset behavior directly from raw sensor data without prior machine knowledge
- Real‑time anomaly scoring with explainable diagnostics to pinpoint root causes of irregularities
- Pre‑built applications for predictive maintenance, process insight, and energy usage monitoring
- Scalable architecture that handles high‑frequency, multi‑dimensional data streams from diverse industrial environments
- Simple integration via APIs, requiring minimal configuration and no extensive data labeling
- Cloud‑hosted analytics with secure data transmission and role‑based access controls