We Will Help You
Detect customer experience issues
We build solutions that collect multiples of application metrics and use machine learning models to detect anomalies in real time. Our algorithms can detect unexpected drops and spikes in traffic, conversion rates, session durations, and other mission-critical business metrics. Near real-time anomaly detection helps to quickly react to issues that affect user experience and minimize losses.
Detect equipment failures using IoT data
Our data scientists have analyzed numerous case studies and real-life projects to develop a comprehensive toolkit of computer vision algorithms for anomaly detection. We work with a wide range signals and data sources, including IoT sensor data, imagery, and video streams, to detect anomalies and prevent larger failures and outages.
Detect stability issues
Our outlier detection solutions can monitor an extremely large number of system metrics in data centers and clouds, correlate them, and identify complex anomalous patterns and outliers that involve multiple metrics and cannot be detected through the analysis of individual metrics in isolation.
Perform root cause analysis in seconds
We put a lot of emphasis on the operational aspect of anomaly detection, including speed and convenience of incident investigation. Our tools analyze the dependencies between metrics and automatically identify the segments potentially related to the current incident in the full volume of data. This helps operations teams to quickly perform root cause analysis and troubleshoot the issue.