Virtual Operator 2.0: AI-Driven Automation for Operators
Virtual Operator 2.0 marks a major step forward with AI-powered automation of operator work and gives companies the opportunity to improve both efficiency and precision in their system monitoring processes. With the new version, operators can also more easily build their own scenarios that automatically support their daily work. With the help of advanced machine learning and prediction techniques, Virtual Operator now offers more intelligent and proactive solutions.
What’s new in Virtual Operator 2.0:
- Machine learning:
- Virtual Operator learns from the operator’s actions and suggests improvements based on previous actions. This contributes to a more efficient and automated work process with reduced error handling.
- Prediction
- By analyzing historical data, Virtual Operator can now predict likely events in the next hour. The system also identifies from which nodes/devices these events can be expected to occur, giving operators an opportunity to act proactively. Technically, a graph database is used, which is integrated into the new version.
- Flexible choice for floating time windows
- Users can now choose between two types of time windows: LastOccurrence or FirstOccurrence, allowing for greater customization in analytics.
- Optimized event management
- The operator can now choose whether to acknowledge or suppress grouped or symptom-related events, creating a more structured and relevant incident response.
The updated version is now available for implementation. Get in touch with us and we will plan an upgrade.
