Process to identify unexpected items or events in data sets to enable real-time monitoring and surveillance. Allows you to have full transparency and control over your data.
When digitized workflows do not work correctly, it can be difficult to identify the source of the problem in big amounts of data. With rapid changes and pending innovations, it is even harder to filter for these errors. With workflows interconnected, errors in data can create chaos and lead to serious problems.
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Protect your business and workflows effectively with anomaly detection. It finds errors in data sets by identifying patterns that do not match the ones considered as normal behavior. While it is based on machine learning it can additionally be verified by a human counterpart.
In recent years, we have built up expertise in many challenging areas. We identify anomaly scenarios in complex technical equipment, customer communication and sales as well as user behavior on web applications.
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Algorithms can automatically analyze data sets to identify differences in patterns. This is done with high accuracy using artificial intelligence that identifies patterns with very high precision in real-time.
Anomaly detection identifies the slightest difference in data and alerts you immediately. This seamless monitoring ensures you the highest security standards. For example, learning directly about a leaking pipe enables you to take the right actions to protect production and employees.
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Classification of data is crucial to information security, especially when dealing with large volumes of data, including sensitive data.
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Automatic control of processes by using a network to connect controllers, sensors, operator terminals and actuators. Less time-consuming and repetitive tasks through automation.
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Simulation of natural intelligence in machines programmed to learn with experience and interpret contexts. Able to interact and cooperate with other digital systems.
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