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What is Nova SensAI?

Rapidly detect and predict outages and issues that affect subscribers, many of which frequently go unnoticed. This methodology reveals the consequences, origins, and fundamental reasons for incidents, enabling prioritization and quicker fault resolution while proactively improving the user experience. It forecasts and identifies disruptions and faults across mobile and fixed networks, as well as in both physical and virtual settings. Abnormal incidents that affect network functionality and user satisfaction are categorized, correlated, and analyzed for enhanced evaluation. Fault locations are pinpointed, and root causes are identified to facilitate effective, coordinated, and targeted interventions. By integrating and analyzing information from diverse source systems, it dismantles silos and delivers cohesive insights. Furthermore, it enhances latency, network performance, and service delivery through a thorough, multi-layered anomaly detection system paired with correlated analytics. The approach also addresses transient degradations and persistent problems that could impede performance, ultimately ensuring an exceptional user experience. This proactive strategy not only boosts operational efficiency but also cultivates customer satisfaction and loyalty, driving long-term business success. Continuous improvements and adjustments based on insights gathered contribute to an adaptable and resilient network infrastructure.

What is Amazon Lookout for Metrics?

To effectively detect irregularities in business metrics, it is crucial to minimize false positives through the application of machine learning (ML). By clustering similar outliers, one can delve into the root causes of these anomalies for a thorough examination. Summarizing these underlying issues and ranking them based on severity ensures that organizations can address the most critical problems first. The integration with AWS databases, storage solutions, and third-party SaaS applications enables ongoing monitoring of metrics and anomaly detection. Additionally, implementing customized automated alerts and responses when anomalies are detected boosts operational efficiency significantly. The Lookout for Metrics tool employs ML to automatically identify anomalies in both business and operational data, while also uncovering their root causes. Detecting unexpected anomalies poses a challenge, especially since conventional methods typically depend on manual processes that often introduce errors. Lookout for Metrics alleviates this complexity, empowering users to identify and analyze data inconsistencies without specialized knowledge in artificial intelligence (AI). Furthermore, this tool enables the monitoring of unusual variations in subscriptions, conversion rates, and revenue, promoting a proactive stance against sudden market shifts. By harnessing sophisticated machine learning approaches, businesses can greatly enhance the precision of their anomaly detection endeavors, ultimately leading to better decision-making and more resilient operations. This strategic application of technology thus not only improves detection but also fosters a culture of continuous improvement within organizations.

Media

Media

Integrations Supported

AWS Lambda
Amazon CloudWatch
Amazon Redshift
Amazon S3
Amazon Simple Notification Service (SNS)

Integrations Supported

AWS Lambda
Amazon CloudWatch
Amazon Redshift
Amazon S3
Amazon Simple Notification Service (SNS)

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

EXFO

Date Founded

1985

Company Location

Canada

Company Website

www.exfo.com/en/products/service-assurance-platform/nova-sensai/

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/lookout-for-metrics/

Categories and Features

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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