1. Automated Analysis
Every chart and figure is computed from your log by software. Parsing depends on recognising the format; unusual formats may be read imperfectly, for example with inferred severity levels or an assumed year. The “How the Log Was Read” panel shows exactly what was detected.
2. Machine Learning Findings
Anomaly detection, clustering, forecasting and association rules are statistical. They can flag harmless events and miss real problems, especially in short logs. A flagged period means “worth a look”, not “proven incident”.
3. AI-Generated Text
Summaries, root-cause hypotheses, risks and answers are written by large language models and decisions are made by a decision model. They can be wrong, overconfident or incomplete. Verify important conclusions against the underlying data in the dashboard and the log explorer.
4. Security Findings
Security checks use pattern matching and thresholds. They are not a penetration test, a compliance audit or an intrusion detection system. The absence of findings does not mean a system is secure. If a finding suggests a compromise, involve your security team.
5. Recommendations
Suggested settings such as thresholds, timeouts and rate limits are derived from the uploaded period only. Test changes in a safe environment and consider traffic your log didn't capture before applying them in production.
6. Not Financial or Professional Advice
Health scores, outlooks and investor-oriented summaries describe technical behaviour visible in a log. They are not financial, investment, legal or compliance advice.