Overview
Less Time Piecing Signals Together, More Time Resolving
When something breaks, the first challenge is rarely a lack of data — it's too much of it, scattered across dashboards, alert channels and log tools, with no single view of what's actually related. AI Incident Management pulls those signals together automatically, linking alerts, logs, traces and metrics that belong to the same underlying incident so responders start from a correlated picture instead of a blank investigation.
As the incident evolves, ObserverIQ keeps the timeline current and generates a plain-language summary of what happened, in what order, and what's changed — reducing the manual triage work that typically falls on whoever picks up the page first.
Capabilities
Signal Correlation
Automatically links related alerts, logs, traces and metrics into a single incident view.
Automated Timelines & Summaries
Plain-language summaries of what happened and when, updated as the incident progresses.
Noise Reduction
Duplicate and low-value alerts are suppressed so responders focus on what matters.
Context-Aware Routing
Incidents route to the right team faster based on correlated context, not guesswork.
Recommended Actions
Suggested next steps drawn from patterns across similar past incidents.
Post-Incident Reporting
Structured incident records ready for review, retrospectives and reporting.
What's Included
- Cross-signal correlation across metrics, logs, traces and alerts
- Automated incident timelines and summaries
- Alert de-duplication and noise reduction
- Context-aware routing to the right responders
- Recommended actions based on historical incident patterns
- Integration with existing alerting and ticketing tools
- Structured post-incident summary reporting
- 24/7 monitoring integration and support