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CAN-mobile

Cognitive Assistant for Networks mobile application is targeted to meet the challenges of today’s Mobile Network Operators and Managed Services Companies who face ever increasing network maintenance and performance issues as networks expand and become more complex

Cognitive Assistant for Networks mobile application is targeted to meet the challenges of today’s Mobile Network Operators and Managed Services Companies who face ever increasing network maintenance and performance issues as networks expand and become more complex

CAN-mobile

by Chiranjib Bhandary
CAN-mobile
CAN-mobile
CAN-mobile

What is it about?

Cognitive Assistant for Networks mobile application is targeted to meet the challenges of today’s Mobile Network Operators and Managed Services Companies who face ever increasing network maintenance and performance issues as networks expand and become more complex.

CAN-mobile

App Details

Version
1.7
Rating
NA
Size
4Mb
Genre
Business
Last updated
April 5, 2019
Release date
August 1, 2016
More info

App Screenshots

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App Store Description

Cognitive Assistant for Networks mobile application is targeted to meet the challenges of today’s Mobile Network Operators and Managed Services Companies who face ever increasing network maintenance and performance issues as networks expand and become more complex.
Key challenges include:
• An increasing number of repeat visits to network sites
• Site engineers who are not equipped with adequate intelligence to handle operational issues and undertake Root Cause Analysis (RCA)
• Sub-optimal capacity planning for network and manpower resourcing
• Managing large volumes of trouble tickets and alarms

Cognitive Assistant for Networks meets these challenges through Artificial Intelligence driven applications which analyze large amounts of both structured and unstructured data. This includes syslog messages, trouble ticket information, alarm information, network configuration data, traffic measurement data and customer complaints, together with external data such as weather conditions and social networking information. By analyzing this data, the solution significantly reduces the time for RCA, automatically identifies recommended actions and improves network availability.

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