GAVel’s lucid UI interface, unified dashboards and heat-maps offer real-time, end-to-end visibility into an enterprise’s operations, processes and user experience. It integrates multiple streams of information to provide a 360° view, better root cause analysis and predictions. It enables enterprises to view day-to-day functioning of IT operations, leading to improved transparency and setting expectations with users, to reduce negative CSAT.
Siloed events generated from siloed IT operations monitoring tools are aggregated and correlated using advance machine learning algorithms. Patterns are self-learned and unlearned by algorithms to provide a high accuracy in correlations. 99.99% of events are correlated by GAVel, which removes the alert fatigue in an enterprise.
Streaming events from various IT operations monitoring tools are processed by our event correlation engine to identify the underlying sub sequences. Unsupervised machine learning algorithms auto-tunes parameters based on the enterprise’s data streams to derive higher accuracy in correlation.
GAVel’s root cause analysis models identifies the root cause with a probable value to the event or events that may have caused the spike or anomaly. Learning from past data GAVel also provides remediation steps for the identified problem, resulting in reducing MTTR by 95%.
GAVel’s Artificial Intelligence drives noise reduction generated from IT operations monitoring tools by 95%. Supervised and unsupervised algorithms suppress alerts or events that are not actionables based on the alert pattern identified. You get the advantage of Zeroing in on the critical events that impact business continuity.
Driven by Machine Learning algorithms, GAVel integrates seamlessly with traditional performance monitoring tools to PREDICT performance degradation and capacity utilization bottlenecks. Real time analytics on alerts from infrastructure monitoring tools helps forecasting system utilization breaches thus paving the way for preventive actions.
GAVel uses predictive algorithms and statistical models from past incidents to help assign accurate estimated time to resolution thereby improving customer satisfaction. Auto triaging of incidents using GAVel’s virtual supervisor helps in productivity improvements by a minimum 40%. Along with self-help features for incident resolution, GAVel offers extensive flexibility that can be integrated with any ITSM tool.
Using a combination of NLP & text analytics, GAVel helps organizations gain perceptions of consumer sentiment, customer behavior, user satisfaction reports, trending patterns and provides an overall sentiment score. The platform helps to gain insights into brand strengths & weaknesses, and drives competitive metrics to create benchmarks and branding strategies.