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ease
features
design
support

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Description

Identify patterns in operational data that can forecast deterioration and potential failures long before they occur. By employing accurate failure pattern recognition, you can reduce the frequent occurrence of false positives typically associated with traditional model-based approaches. Utilizing low-touch machine learning, you can swiftly distinguish between normal and abnormal behaviors, ensuring equipment protection starts within weeks rather than extending into months. The integration of Aspen Mtell with Aspen Cloud Connect™ provides connectivity to devices that support OPC UA. This method of recognizing operational patterns not only serves as an initial defense against asset decline but also enhances existing maintenance strategies through the deployment of AI-driven agents across various sites or throughout the entire organization. By focusing on precise failure pattern recognition, the challenge of high false positive rates in model-based solutions is effectively mitigated. Moreover, the rapid identification of operational behaviors facilitates timely equipment protection, ensuring that organizations can respond proactively to potential issues as they arise.

Description

Quickly identify and forecast outages and impairments that impact subscribers, many of which often go undetected. This process unveils the implications, sources, and underlying causes of events, allowing for prioritization and expedited fault resolution while enhancing the user experience proactively. It dynamically forecasts and identifies outages and impairments across both mobile and fixed networks, as well as in physical and virtual environments. Abnormal events that influence network performance and user satisfaction are classified, correlated, and grouped for better assessment. Fault locations are isolated, and root causes are diagnosed to enable effective, coordinated, and prescriptive measures. By consolidating and analyzing data from various source systems, it breaks down silos and provides integrated insights. Additionally, it optimizes latency, network efficiency, and service delivery through comprehensive, multi-layered anomaly detection combined with correlated analytics. The system also identifies and resolves transient degradations and recurring issues that can hinder performance, ultimately delivering a superior user experience. This proactive approach not only improves operational efficiency but also fosters customer satisfaction and loyalty.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

SAP Store

Integrations

SAP Store

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Aspen Technology

Founded

1981

Country

United States

Website

www.aspentech.com/en/products/apm/aspen-mtell

Vendor Details

Company Name

EXFO

Founded

1985

Country

Canada

Website

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

Product Features

Preventive Maintenance

Condition Monitoring
Inspection Management
Maintenance Scheduling
Mobile Access
Predictive Maintenance
Purchasing
Reminders
To-Do List
Vendor Management
Work Order Management

Product Features

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