Ekara by IP-Label • Incident Guard
Stop wasting time on false alerts.
Focus on real incidents with AI.
Every hour, analysts lose up to 15 minutes investigating irrelevant alerts. Ekara Incident Guard uses artificial intelligence to filter noise, prioritize critical incidents, and accelerate resolution — so your teams can focus on what truly impacts your users.
AI-driven incident intelligence
Turn alert noise into actionable insights. Let AI support your teams — not overwhelm them.
Alert noise
Filter irrelevant incidents
AI triage
Smart classification & recommendations
SLA reliability
Clear and accurate reporting
Problem & Solution
Why incident triage has become critical
In complex IT environments, monitoring generates a high volume of alerts — but not all of them matter. Without intelligent filtering, teams lose time, confidence, and performance.
The problem: too many alerts, not enough value
IT and DevOps teams are overwhelmed by alerts generated from synthetic monitoring. A large portion of these incidents are actually false positives.
- Alert fatigue slows down decision-making
- Time wasted investigating non-critical incidents
- Difficulty identifying issues that truly impact users
- KPI and SLA metrics distorted by irrelevant incidents
- Loss of trust in monitoring tools
The solution: AI-powered Incident Guard
Ekara Incident Guard analyzes every incident and automatically detects recurring patterns using artificial intelligence.
Incidents are classified, enriched, and submitted for human validation — enabling you to filter out irrelevant alerts while maintaining full traceability.
The result: more reliable monitoring, faster decision-making, and continuous performance improvement.
Ready to eliminate false incidents?
See how it works →How Incident Guard works
A hybrid approach combining artificial intelligence and human validation to eliminate noise, improve incident accuracy, and continuously enhance your IT performance.
Incidents detected
Synthetic monitoring & real user anomaly detection
Data collected
Scenarios, performance metrics, and contextual execution data
AI analysis
Correlates incidents, detects patterns, and automatically identifies false positives using machine learning.
Classification
Intelligent prioritization of critical vs non-critical incidents
Human validation
Expert review ensures accuracy and continuous improvement
Ekara dashboard
Reliable KPIs, relevant incidents, and noise-free SLA reporting
Outcome
Less noise, more performance
More efficient teams, faster decisions, and a clear, reliable view of your IT performance.
Use cases for Incident Guard
Adapt your monitoring to complex environments and eliminate false incidents in critical operational contexts.
Frequent deployments
Quickly identify incidents related to new releases and avoid false positives during continuous deployment cycles.
Multi-region environments
Distinguish local issues from global outages and prioritize incidents based on real user impact.
Reliable SLA reporting
Remove false incidents from your metrics to ensure accurate, actionable SLA reporting.
Deliver measurable results for your teams
Turn your monitoring into a powerful driver of operational performance.
⏱ Reduce MTTR
Identify critical incidents faster and significantly shorten resolution times.
⚡ Save time
Eliminate unnecessary investigations and focus your teams on high-impact issues.
📊 Reliable KPIs
Get accurate metrics without false positives to support better decision-making.
👥 Boost productivity
Reduce alert noise and enable your teams to operate more efficiently every day.
Incident Guard
Ready to eliminate false incidents?
Discover how Incident Guard can reduce alert noise, improve your MTTR, and give you a clear, reliable view of your IT performance.
Incident Guard
Ready to eliminate false incidents?
Discover how Incident Guard can reduce alert noise, improve your MTTR, and give you a clear, reliable view of your IT performance.
Frequently asked questions
Everything you need to know about Incident Guard and intelligent incident triage.
What is a false positive in monitoring?
A false positive is an alert that signals an incident which, in reality, has no actual impact on users.
How does Incident Guard improve MTTR?
By filtering out non-critical incidents and prioritizing real issues, your teams can respond and resolve problems faster.
Does AI replace IT teams?
No, it supports them. Human validation remains essential to ensure accurate and reliable decision-making.
What types of environments are supported?
All complex environments, including multi-region, cloud, SaaS, and mission-critical applications.