Podcast Interview
Dr. Shmuel Kliger on Causely, Causal AI, and the Challenging Journey to Application Health
Causal AI for IT
Bridging observability with automated orchestration for self-managed, resilient applications at scale.
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Blog
Can AI-Powered Causality Crack the RCA Code for Cloud-Native Applications?
Podcast Interview
Endre Sara on Security Platforms
The IT market problem
Every second, huge volumes of data are generated by observability and monitoring tools, capturing metrics, logs, and traces about all aspects of complex, dynamic applications.
Yet it’s still up to humans to troubleshoot and make sense of all this data. They are locked in a never-ending cycle of responding to alerts, identifying root cause, and determining the best action for remediation. The process hasn’t changed fundamentally in decades – and it’s still labor-intensive, reactive, and costly.
71%
ITOps teams say monitoring data is not actionable
55%
IT issues are escalated, taking over 10 hours to resolve on average
$855K
Average cost of an unplanned outage or downtime
The first causal AI platform for IT
Causely removes the need for human troubleshooting by capturing causality in software, closing the gap between observability and action.
For the first time, the entire lifecycle of detection, root cause analysis, and remediation of defects in applications is fully automated. With Causely, defects are identified and resolved in real time, so applications can scale with high performance and resilience.
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Causely for cloud-native applications
The first Causely service, built for service owners and their teams who build and support cloud-native applications, detects and remediates application failures in complex environments.
Want to see it in action?
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