Anomaly detection

Minimize risks in your customer-facing, manufacturing, and IT management processes using machine learning.

Our clients

How our anomaly detection solutions work
Autonomous anomaly detection using unsupervised algorithms

We extensively use unsupervised machine learning algorithms to detect outliers and anomalies even in settings where “normal” metric patterns and thresholds are unknown. This eliminates the need for manual threshold management, enables the detection of complex multi-metric patterns, and allows scale-out to dozens of use cases and thousands of metrics.

Ready for extreme volumes of data
Our solutions are designed to monitor a very large number of metrics in real time, detect unusual patterns that involve multiple metrics at the same time, and automate root cause analysis at scale.
Simplified root cause analysis
We integrate our solutions with incident management and alerting systems to automatically send notifications and create tickets for operations teams. Notifications include most relevant segments of metrics that are potentially related to the incident. This helps to quickly react to incidents, reduce the amount of time needed for investigation, and prevent failure propagation or security-related losses.
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We provide flexible engagement options to design and build an automated anomaly detection solution for your company. Contact us today to start with a workshop, discovery, or proof-of-concept (POC).


We offer free half-day workshops with our top experts in anomaly detection to discuss your  challenges, potential areas of improvement, and industry best practices.

Proof of concept

If you have already identified a specific use case that needs to be solved, we usually can start with a 4-8 weeks proof-of-concept project to deliver tangible results and business value.


If you are in the stage of requirements analysis and strategy development, we can start with a 2-3 weeks discovery phase to identify right use cases for anomaly detection or predictive maintenance, design your solution using industry best practices, and build an implementation roadmap.