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Telecom / IT Ops

Network Operations: Predictive Ticket Suppression & Automated FLT

Eliminate false-positive alert storms and auto-resolve Level 1 tickets with ML-powered pattern recognition and agentic triage.

0%
Fewer Tickets
0-min
MTTR
0%
Auto-Resolved
$0K
Saved

Challenge

  • 12,000+ false-positive tickets generated per month
  • NOC engineers spend 60% of time on non-issues
  • Alert fatigue leads to missed real incidents
  • Manual triage averages 45 minutes per ticket

Solution

ML models learn normal patterns and suppress false positives while agentic auto-triage diagnoses, correlates, and resolves real issues autonomously — predictive and agentic working in cohesion.

Predictive ML Agentic Workflow
1 Pattern Learning ML
2 Anomaly Detection
3 Intelligent Ticket Mgmt
4 Context Analysis
5 Diagnostic Agent
6 Correlation Agent
7 Triage Decision
8 Documentation Agent
Device Event Pattern Recognition Suppress? Yes Auto-Close No Context Analysis Diagnostics Agent Correlation Agent Triage Auto-Resolve Enrich & Route Escalate

Results

75%
Ticket reduction
90%
False-positive elimination
65%
L1 auto-resolution
8-min
Mean time to resolve
$420K
Annual savings

Why Multi-Method Matters Here

ML Learns PatternsModels distinguish normal fluctuations from real anomalies
Rules Enforce PolicyDeterministic logic governs escalation thresholds and SLAs
Workflows OrchestrateMulti-step diagnostic sequences run in coordinated order
LLMs Understand ContextNatural language analysis of logs, alerts, and documentation

Deploy in 4 Weeks. See Results in 60 Days.

From pilot to production with proven multi-method architecture. Start with one use case and expand across your organization.

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