CREAIOps brings AI-assisted root cause analysis to the moments that matter most. Instead of waiting until the post-incident review, on-call teams get ranked RCA hypotheses, supporting reasoning, and a clear path to validation — all reviewable by a human before any change.
Traditional RCA happens after the incident is closed, when memory and signals have already faded. During the incident, the team is reacting; days later, someone writes up the conclusion. The result is slower recovery, repeat incidents, and weaker problem management.
CREAIOps generates RCA hypotheses while the incident is still open. Multi-agent reasoning spans every relevant lens — application, infrastructure, network, security, database, and business impact — and ranks the most likely causes for human validation.
Likely causes scored by weighted consensus, each with the reasoning that produced it.
Agents publish the context, assumptions, and observations they relied on — making validation faster.
Application, infrastructure, network, security, database, and business-impact perspectives in a single workspace.
Exportable reasoning trail and approved runbook draft for problem management and compliance.
After a series of repeat timeouts, the SRE lead submits the anonymized scenario into CREAIOps. Multi-agent reasoning highlights a database-pool exhaustion hypothesis alongside an upstream rate-limit hypothesis — both with supporting context. The team validates the database hypothesis and approves a runbook draft for the next occurrence.
Root cause analysis AI uses machine reasoning to help teams identify the most likely cause of an incident. CREAIOps generates ranked RCA hypotheses with supporting reasoning from multiple domain agents — so engineers can validate the right candidate faster.
No. CREAIOps surfaces likely hypotheses ranked by weighted consensus and supporting context. A qualified human reviewer is required to validate the cause before acting.
CREAIOps accelerates the analysis phase and produces an auditable reasoning trail, but does not replace the human-led post-incident review. It gives reviewers a structured starting point.
Specialist agents look at application, infrastructure, network, security, database, and business-impact lenses independently. Combining their hypotheses reduces single-perspective bias and surfaces causes that one team might overlook.
Use anonymized inputs only. CREAIOps is designed to reason from anonymized incident context, not raw production data, secrets, or regulated information.
Try the AI incident reasoning workspace with anonymized inputs. No setup. No card. Human approval stays with you.