AI-driven RCA cuts down MTTR, removes guesswork, and restores service faster
Find root causes in minutes, not hours. AI-RCA automatically analyzes incidents across all your observability data, provides step-by-step evidence trails, and suggests one-click remediation playbooks. Resolve incidents 40-60% faster with confidence.
The pain points every engineering team faces
Hours spent sifting through logs, metrics, and traces across multiple systems. By the time you find the root cause, user impact has already escalated.
Every minute of downtime costs money and damages reputation. Traditional debugging methods keep MTTR high, especially during off-hours when experts aren't available.
Logs, metrics, and traces live in separate tools. Connecting the dots requires deep expertise and context switching between multiple dashboards.
Hundreds of alerts surface during incidents. Without AI correlation, teams chase false positives or symptoms instead of root causes, wasting precious time.
Not every on-call engineer has deep context about every service. When the expert isn't available, incidents take longer to resolve, increasing business impact.
Each engineer approaches debugging differently. Without standardized RCA processes, resolution times vary wildly, making SLA compliance difficult.
How intelligent root cause analysis transforms incident response
AI-RCA automatically collects and correlates data from logs, metrics, and traces across your entire infrastructure. No more switching between tools or manually connecting data points.
Get a unified view of your system health in seconds, not hours.
Advanced machine learning identifies anomalies, outliers, and patterns that human eyes might miss. AI-RCA detects issues before they become full-blown incidents.
Catch problems early and prevent incidents from escalating.
AI-RCA builds a visual causal graph showing relationships between events, services, and anomalies. Understand not just what failed, but why it failed and what it impacted.
See the full picture of system dependencies and failure chains.
Every root cause comes with a complete timeline showing the incident progression, step-by-step evidence trail, and confidence score. Know exactly why the AI made its decision.
Build trust with transparent, explainable AI recommendations.
Get notified immediately when root causes are identified. Built-in dashboards show incident trends, MTTR improvements, and common failure patterns across your infrastructure.
Stay informed and learn from incidents to prevent future ones.
Pre-approved playbooks let you fix common issues with a single click. For complex incidents, AI-RCA suggests remediation steps with clear instructions.
Reduce manual intervention and cut resolution time by 50%+.
Watch how AI-RCA identifies root causes across logs, metrics, and traces with automated analysis, evidence trails, and remediation suggestions.
Proven outcomes from real engineering teams
No. AI-RCA uses intelligent pattern analysis that works with sampled data. Our algorithms are designed to identify root causes even when some data points are sampled, as long as error logs and anomalies are preserved (which Cost Guardrails does automatically). The AI focuses on signal patterns rather than exhaustive data volume.
Yes. AI-RCA supports all major observability formats including JSON logs, Prometheus metrics, OpenTelemetry traces, Datadog, New Relic, CloudWatch, and many others. It automatically normalizes data across formats to build unified causal graphs.
AI-RCA respects your data retention policies and compliance requirements. All analysis happens on data that's already in your observability platform, and you can configure retention windows to match your compliance needs. Root cause analysis results and evidence trails are stored separately with their own retention policies.
Absolutely. AI-RCA provides full control over confidence thresholds, anomaly sensitivity, and correlation rules. You can override any recommendation, adjust parameters per service or environment, and customize playbooks. The AI learns from your overrides to improve future recommendations.
Typically 2-3 minutes from incident detection to root cause identification with evidence. This includes data collection, correlation analysis, causal graph generation, and confidence scoring. Complex incidents involving multiple services may take 5-10 minutes.
AI-RCA provides full transparency with evidence trails and confidence scores. If you disagree with a recommendation, you can override it and provide feedback. The system learns from corrections and improves over time. Confidence scores below 60% are flagged for manual review.
AI-RCA works immediately with current data, but accuracy improves over time as it learns your infrastructure patterns. For best results, we recommend 1-2 weeks of baseline data, though teams see value within days of deployment.
Yes. AI-RCA can be deployed on-premise or in air-gapped environments. All processing happens locally, and no data leaves your infrastructure. We support both cloud-native and self-hosted deployments.
See how AI-RCA can help your team resolve incidents faster with automated root cause analysis. Get a personalized demo tailored to your infrastructure and use cases.
AI-Powered Investigation