80% of alerts are noise that wastes engineering time
SRE teams spend hours triaging false positives instead of solving real problems that impact customers
Mean time to resolution suffers without full context
Correlating logs, metrics, and traces across services requires manual effort and deep tribal knowledge.
Reactive firefighting consumes 40% of SRE capacity
Without proactive detection, teams discover issues only after users are already impacted.
Automate SRE Operations with Intelligence and Human Oversight
Coming Soon
Auto-discover infrastructure, filter alert noise, and accelerate root cause analysis with AI that learns your environment—keeping humans in control of critical decisions that impact SLO
Intelligent Discovery
Auto-discover infrastructure, services, and dependencies from your existing observability stack—no manual mapping required.
Discovers from Grafana, Prometheus, Loki, and Jaeger
Maps AWS, GCP, and Azure cloud infrastructure
Builds service topology and dependency graphs
Loads relevant skills based on discovered entities
Alert Intelligence
Cut through alert noise with automated correlation, deduplication, and severity classification by blast radius.
Auto-categorize by severity and service impact
Suppress noise and correlate related alerts
Enrich alerts with RCA and deployment context
Predictive patterns from historical incidents
Actionable Root Cause Analysis
Trace incidents across service dependencies and correlate logs, metrics, and events to identify probable causes fast.
Pre-built RCA workflows for common failure scenarios
Anomaly detection across metrics and logs
Dependency mapping for impact assessment
Error pattern recognition and signatures
Human-in-the-Loop Remediation
Execute remediation workflows for common scenarios with full audit trails and human approval for every action.
Service restarts, scaling, and traffic routing
Deployment rollback with approval gates
Complete audit trails for every action
50+ pre-built remediation tasks ready to use
SLO Tracking
Track error budget consumption in real-time and prioritize incidents by SLO impact, not just alert severity.
Suggests proven fixes from 50+ pre-built workflows while keeping engineers in control—every action requires explicit approval.
Reliability You Can Experience
More accuracy in incident enrichment
Every alert arrives with context—related deployments, dependency maps, and probable causes attached.
Discover services automatically
No more manual service catalogs or stale topology docs. Aiden maps your infrastructure continuously.
Reduce alert noise with intelligent correlation
Stop drowning in duplicate alerts. Aiden groups related incidents and suppresses known false positives.
Driving Outcomes
50%
Faster Root Cause Analysis
70%
Reduction in Alert Noise
90%
Faster Issue Detection
Frequently Asked Questions
What observability tools does Aiden integrate with?
Aiden integrates with Grafana, Prometheus, Loki, Jaeger, Datadog, Dynatrace, NewRelic, and Google Cloud Monitoring. We also connect with PagerDuty, Jira, Slack, and Microsoft Teams for incident management.
Does Aiden automatically fix issues without human approval?
No. Aiden uses human-in-the-loop remediation—every action requires your approval before execution. Full audit trails are maintained for compliance and accountability.
How long does it take to discover my infrastructure?
Initial discovery runs when you connect your observability stack. Most environments complete discovery within hours. You can schedule recurring discovery or trigger it manually.
What if Aiden doesn't support my specific tech stack?
Aiden works with AWS, GCP, Azure, Kubernetes, and common databases and message queues. Check our integrations page for the full list, or contact us about specific requirements.
How is Aiden different from traditional AIOps platforms?
Unlike AIOps tools that require extensive setup, Aiden auto-discovers your environment and ships with 50+ pre-built tasks. We integrate with your existing observability stack rather than replacing it.