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Simplify 4G & 5G Network Troubleshooting
and Analysis

B-Yond brings machine learning and artificial intelligence to telecom network operators all over
the world.

 

  • More reliable and faster 5G rollouts

  • Automated packet analysis

  • Intelligent root cause identification

  • Network failures knowledge bases

  • Seamless troubleshooting of PCAPs

Join the Largest Network Operators Scaling
Network Protocol Analysis with B-YOND

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1,047,000+

Call Flows
Analyzed

52,000+

Patterns
Identified

300,000+

PCAPs Processed since August 2022

Reduce the Time and Cost to Certify New Devices and Perform Health Checks by 50% or Greater

Streamline post launch optimization and maintenance.

Network Topology Detection

Automatic resolution of network elements' role, name, and topology.

Critical Failure Identification

Instant call flow classification as success vs failure.

Root Cause Analysis

Identify errors and isolate the network function where it occurred.

Detect and Visualize End-to-End Call Flows

Illustrate the sequence of messages on a ladder diagram, with protocol and network element level errors, and golden call
flow comparison.

AGILITY Redefines Test Automation and Accelerates Time-to-Market

Success Story

AGILITY has transformed the network testing landscape for a Tier 1 North American Operator by streamlining processes and significantly reducing time-to-market for new features.
By utilizing Continuous Validation (CV) and Continuous Testing (CT) with a comprehensive AI Repository, B-Yond has achieved remarkable results in network quality and efficiency, enabling the operator to stay ahead in the competitive market.

Decreased OPEX

An average test cost reduction of 50%.

Faster rollouts

Time-to-Market for new features accelerated.

Improved process efficiency

Test life cycles decreased from hours to minutes.

Increased capacity & NPS

10x increase in test capacity improves network quality & hastens resolution times.

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Solve Critical Network Issues
Faster and With Less Effort

Leverage AI and ML to reduce the time and costs of repeated investigations on recurring patterns of network failures.

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