Our monitoring systems, built on the Zabbix platform, use AI-powered analytics and recommendations to help identify and prioritize issues more quickly, thereby reducing downtime and the time spent on resolution. By combining the efficient and rapid data analysis capabilities of artificial intelligence with the historical and trend data collected by Zabbix, we can generate fast and targeted reports.
Our solution helps lower the entry barrier for operators: with the explanations generated and displayed by AI, the system can be operated successfully even with a shorter learning curve.
Real-time alarm evaluation
The solution automatically analyzes incoming alarms and, using language models, immediately places them in context. Operators do not simply see an error message; instead, they receive a structured evaluation—written in Hungarian—of the nature of the problem and its possible causes.
Intelligent priority management
In larger environments, hundreds or even thousands of alerts may be received daily. By analyzing all active issues simultaneously, the system identifies the most critical ones and displays the cases requiring immediate action in a configurable Top N list.
Operational recommendations and verification steps
For each alert, the system recommends specific, actionable steps: verification commands, configuration settings, and a sequence of actions. This is particularly useful when training junior colleagues or in situations where the necessary knowledge is scattered across various sources.
Recognizing correlations and categorization
AI is capable of grouping similar problems and identifying hidden correlations. It analyzes the situation not only on a per-server basis but also on a per-service or per-environment basis, enabling the identification of true root causes more quickly and through alternative pathways.
Controlled data management and flexible deployment
The solution supports the use of both on-premises and cloud-based AI models. Sensitive infrastructure identifiers (server names, IP addresses) can be anonymized before being fed into the model, ensuring compliance with data protection and security requirements.
Human control and decision-making
AI does not make independent incident management decisions; rather, it supports the work of analysts. Every recommended action can be verified and reviewed, and the final decision remains with the experts.
Measurable operational benefits
After implementation, teams respond more quickly to critical incidents, spend less time filtering through alarm noise, and have more capacity for proactive, higher-value-added tasks. At the L1 level, staff can be recruited more quickly and cost-effectively, their competencies are strengthened, and the number of unnecessary escalations decreases.