"That error's showing up again" — Sound Familiar?
We've all seen this, right? The same NullPointerException pops up every Monday morning. Three engineers spend their chai time debugging it. By Wednesday, it's back again.
What if I told you that your system alerts actually have stacktraces that tell the whole story? The error message, the root cause, the fix — it's all hiding in plain sight. But nobody has time to read through 500 lines of logs at 3 AM.
This is where the magic happens. Our AI agents don't just detect patterns — they read the stacktraces, understand the root cause, auto-assign to the right queue, and in many cases — fix it themselves before anyone wakes up.
Pro Tip
Click on any agent card below to learn what it does. Use the quick action buttons to explore each section.
Error Detection
AI parses logs and identifies recurring errors
Pattern Recognition
ML clustering identifies root causes
Smart Routing
Auto-assign to right team & priority
Auto-Healing
Self-remediation fixes issues autonomously
What You'll See on This Page
Agent is active and processing data
Count of items processed by that agent today
Cards lift on hover and expand on click for details
Hover for explanations of complex features
The Brain: 5 AI Agents
Meet your autonomous team. Each agent specializes in one part of the process — from reading error logs to fixing issues before your team wakes up. They work in parallel, learning from each other.
Agentic AI Command Center
LIVE
?
Stacktrace Analyzer
Pattern Detector
Queue Optimizer
Auto-Healer
KB Updater
Smart Routing: Where Issues Go
AI doesn't just detect patterns — it knows exactly which team should fix each issue and how urgent it is. Issues are automatically sorted into Priority 1-4 queues and assigned based on team expertise and current workload.
Intelligent Queue Assignment & Triage
AI-Powered
?
AI Triage Decision Explained
"Payment Gateway Down" was classified as P1 because the stacktrace shows
ConnectionRefusedException
affecting the payment-service pod. Historical data shows this pattern caused 23 customer complaints last month.
Auto-assigned to Platform Team based on skill matching and current workload (2 tickets vs avg 5).
Anomaly Detection
3 ActiveError Rate Spike: 340% ↑
payment-service showing unusual 500 errors
Memory Usage: 94%
checkout-service approaching OOM threshold
Latency Drift: +180ms
api-gateway response time degradation
The Fix: Self-Healing in Action
For known issues, the AI doesn't wait for humans. It automatically applies proven fixes, validates the results, and confirms the issue is resolved — often before your team even sees the alert.
Self-Healing Flow — Live Remediation Pipeline
ZeroOps Active
?
Alert Ingestion
Stacktrace Parse
Root Cause ID
Runbook Match
Auto-Remediate
Verify & Learn
Recent Auto-Healed Issues
Memory Leak - payment-svc
Pod restart + connection pool reset
SSL Certificate Renewal
Auto-renewed via Let's Encrypt
Redis Failover Triggered
Switched to replica in 2.3s
Live ROI Calculator GenAI Powered
Before vs After GenAI
Manual Pattern Detection
Reactive Incident Response
Knowledge Silos
GenAI Decision Explainability Transparent AI
Input: System Alert
Output: AI Decision
AI Confidence Breakdown
Predictive Insights
Next 24hrsMemory Exhaustion - checkout-svc
Based on current memory growth rate of 2.3%/hr
SSL Cert Expiry - api-gateway
Certificate expires in 6 days, auto-renew may fail
DB Connection Spike - payment-db
End-of-month processing expected to hit pool limits