Agentic incident response
AI Teammates triage alerts, run root-cause analysis, and coordinate remediation automatically, so your team spends less time fighting fires.
Traditional monitoring is manual, reactive, and insufficient
Pinpointing root causes before they impact customers is a competitive advantage. When it comes to detection and resolution, the shortcomings of traditional monitoring tools include:
Tedious Manual Efforts
Teams must sift through voluminous data for the source of active incidents, and then troubleshoot to remediate.
Can't Detect Unknown Issues
When building monitors, teams must attempt to forecast every behavior they need to alert on in advance, which results in only catching known issues.
Alert Fatigue
Nonstop alerts and false positives overwhelm teams, leading to missed alerts and delayed responses.
AI teammates do the heavy lifting
When an incident surfaces, AI Teammates immediately deliver root-cause analysis, severity context, and clear remediation steps, so your team acts on the right fix instead of wasting time figuring out what broke. The SRE Teammate collaborates with the Software Engineer Teammate to push a fix, while the Security Engineer runs a scan to check for vulnerabilities.
Automated Detection
Get automated anomaly detection and analysis across your environment without building predefined alert conditions for every possible failure mode.
Reduced Alert Fatigue
Reduce false positives and gain coverage on both known and unknown behaviors, so the alerts that fire actually mean something.
Faster Time to Resolution
Compress the time from detection to resolution, with AI Teammates that can take autonomous, approval-gated action to fix issues on the spot.
Ready to take the next step?
Learn more about our use cases and how we fit into your observability stack.
“This is not just about doing what you used to do in the past, and doing it a little bit better. This is a new way to see this world of how we collect and manage our observability pipelines.”
Ben Kus, CTO, Box
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