Noise Reduction and AI Automated Root Cause Analysis Solution | ZIF.AI

Ingestion and Correlation of Diverse Data

Applies Advanced Intelligent Incident Analytics (AIIA) to uncover valuable insights.

  • Analyzes a wide variety of heterogenous data sets from different data sources
  • Processes petabytes of data in seconds
  • Uses historical and real time data to detect patterns
  • Identifies usage patterns, user behavior and end user sentiments using natural language processing and text analytics

Eliminate Noise and Uncover Insights

ZIFTM seamlessly incorporates data & detects anomalies to optimize your IT operations

Ingestion and Correlation of Diverse Data
Noise Nullification
Accelerated Root Cause Analysis
Anomaly Deduction

Noise Nullification

Eliminates duplicate incidents, false positives and any alerts that are insignificant.

  • Filters up to 99.9% of noise
  • Correlates related alerts and sorts events using deep learning techniques
  • Identifies significant alerts and sorts them based on criticality and business priority
  • Eliminates false positives with reinforcement learning techniques

Accelerated Root Cause Analysis

Identifies root causes of incidents even when they are driven by events that cross siloes.

  • Isolates the 20% of the assets that contribute to 80% of the problems through infrastructure heat maps
  • Identifies the real root cause of incidents by differentiating between correlation and causality
  • Back tracks interactive user journeys and data flows to pinpoint exactly where the problem occurred

Anomaly Deduction

Detects exceptions before they become an incident and cause any negative impact.

  • Detects miniscule exceptions that tend to accumulate and result in incidents later
  • Automatically detects and sorts exceptions
  • Detects and prioritizes code level exceptions and failed requests for critical applications
  • Detects surges in application hits and lags in application response

Other Features