Detect customer experience issues
Detect stability issues
Detect equipment failures using IoT data
Perform root cause analysis in seconds
Detect data quality issues
Detect security breaches
How our anomaly detection solutions work
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.
Accelerate the Journey to AI
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.
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.