AI-Assisted Analytics

Observability

Automated
Healing

HEAL AIOps
platform

The Architecture

HEAL AIOps
platform

The Architecture

Under-the-Hood

Transfer Learning
based anomaly
detection

Transfer Learning
based anomaly
detection

Faster outliers – less training data

Self supervised and
semi supervised
learning

Self supervised and
semi supervised
learning

Lower MTTI, Improved precision (no false positives), recall (lesser missed alerts) over time

High impact
metrics

High impact
metrics

Enhanced observability, less storage and memory requirement

Relevance scores

Relevance scores

Ranked events, reduced noise, increased focus on critical problems, faster root cause

Alert correlation

Alert correlation

Improved observability, reduced alert volumes, faster root cause

Solution
recommendation

Solution
recommendation

Impact radius analysis, next best action recommendation based on similar incidents

Capacity
forecasting

Capacity
forecasting

Analysis of future infra-related chokepoints, better resource planning

Data
agnostic

Data
agnostic

Input data from various source - alerts, log, metric data Auto normalize input data

Operational friendly
Dashboards

Operational friendly
Dashboards

Out of the box plugins for enterprise dashboarding tools

State-of-the-art patented AI/ML

Monitoring – Day 1

30 Day Historic Data

  • 95.5% of application performance problems avoided using early warning
  • 105 hrs/month/application downtime averted
  • 67% reduction in MTTR
  • 1100-man hrs/month saved in RCA identification

Monitoring – Day 2

  • Reduce Alert overload by 87%
  • Reduce False Alerts by 96%

Monitoring – Day 30

30 Day Historic Data

  • 80% reduction in storage requirement by identifying top 5% metrics
  • Reduced application infra / config related outages by 10% (month-on-month)

Broadest technology support

  • Observe
  • Explain
  • Prevent

HEAL's Machine Learning Engine

Marketplace certifications

The future of observability is here

30 Day Free Trial