The Challenge: Automating Complex Troubleshooting Cases

AI is finally able to deliver what network operators have been waiting for: faster, smarter, and more scalable network troubleshooting for complex L3-L4 network issues.

In recent years, operators have been using ML and automation for L1-L2 network issue detection and remediation, but until now, complex troubleshooting has remained a slow, manual process that strains teams and delays recovery. To put it simply, manual troubleshooting hasn't been able to keep up with the most complex 20% of network issues that lead to 80% of MTTR.

For complex support cases, operators have been forced to rely on senior engineers to analyze Packet Capture (PCAP) files and correlate what they see to documentation when complex network troubleshooting scenarios arise — slowing resolution times, driving up costs, and increasing downtime.

Consequences can be significant: SLA violations, customer churn, lost revenue, and engineers doing tedious tasks and stuck in reactive mode instead of optimizing network performance.

B-Yond’s AGILITY enables operators to break this cycle.

AGILITY Changes Everything

By combining AI and ML-powered packet analysis with real-time knowledge access, AGILITY acts as Incident Co-Pilot—enabling faster root cause analysis (RCA) and remediation for complex issues, reducing network downtime, and allowing telcos to scale operations without overwhelming senior staff.

In this article, we’ll show you how outdated network troubleshooting methods are holding teams back—and how AGILITY provides faster recovery, lower costs, and a path to autonomous network operations.  With the addition of TelcoGPT and Knowledge as a Service (KaaS), Operators are able to deliver knowledge from standards documentation, system design documents, and support tickets, when and where engineers and operations personnel need it most.

The Cost of Manual Troubleshooting Network Problems

Before we explore how modern network troubleshooting tools like Incident Co-Pilot and TelcoGPT KaaS are reshaping network operations, it’s crucial to understand just how damaging the traditional approaches to dealing with network problems can be.

Troubleshooting Conundrum: The 20% of Cases Responsible for 80% of MTTR

For some years now, Operators have implemented and improved ML-based analytics and automation systems to troubleshoot recurring issues that take place in a network.  These are the 80% of issues that account for 20% of MTTR today. When troubleshooting complex network issues however, engineers may spend hours – or days! – manually analyzing PCAP files and researching documentation to diagnose root causes and their fixes—all while network outage impacts customers.

As issues drag on, war-room triage sessions consume valuable resources, pulling senior personnel away from strategic work as troubleshooting balloons in complexity. SLA penalties, churned customers, and damaged reputation are too often the result.

At the end, it all leads to inefficient operations and revenue loss.

The Cost of Complex Network Troubleshooting

When complex network issues arise, manual reactive network troubleshooting can take an enormous financial toll.

Downtime eventually translates to revenue loss, while the pressure to resolve issues contributes to burnout and attrition among top-tier engineers. And the problem worsens when critical knowledge is isolated within a handful of experts.

This leads network operations and engineering leadership to ask some common questions:

1. How can we improve network availability when complex diagnostic work is manual and resource-intensive?
2. How can we better utilize our most experienced engineers for more strategic work when they are repeatedly pulled into operational firefighting?
3. How can we make all of our company knowledge and experience combined with industry standards documentation available to our people when and where they need it?

How Incident Co-Pilot Transforms Troubleshooting

To answer these questions, operators need network troubleshooting tools that can process massive amounts of data quickly, accurately, and consistently.

With Incident Co-Pilot powered by AGILITY, telcos are now able to streamline the most tedious aspects of network troubleshooting to improve network availability and provide more reliable performance for their customers.

Incident Co-Pilot acts as an ever-present network expert for packet diagnostics, handling the analysis and diagnosis of PCAP data with reference to documentation so that engineers can focus on high-value tasks. Incident Co-Pilot replaces outdated, manual troubleshooting processes with AI-driven efficiency, through:

Automated Call Flow & Topology Visualization

Topologies are built directly from PCAPs, without reliance on potentially outdated network documentation, to provide a clear visualization of “what is” versus “what should be”.

Automation of Diagnostic Recommendations

AGILITY executes trained machine learning algorithms on hundreds of features extracted from packet captures in near real-time to classify call flow failures and provide diagnostics and recommendations based on industry standards or even private documentation.

Active Learning

Incident Co-Pilot also improves its accuracy over time by learning via user feedback, enabling L1 and L2 operations teams to diagnose issues in minutes or seconds that could normally take hours for experts. 

TelcoGPT + Knowledge as a Service Integration

Adding TelcoGPT + KaaS, engineers can gain instant access to public and private knowledge, further enhancing diagnostic investigations or engineering work with standards and private documentation through chat.

The Competitive Advantage of Incident Co-Pilot

This proactive approach helps operators better utilize their most valuable resources, doing less reactive network troubleshooting freeing time for more strategic work.

Key Advantages

By delivering automated insights and eliminating bottlenecks, Incident Co-Pilot enhances network availability and frees engineers to focus on higher-value projects.

Traditional tools simply can’t compete with its speed, precision, or scalability.

Automated RCA

PCAPs are processed in less than three minutes, rapidly pinpointing root causes and providing recommendations with intelligent classification and correlation.

Reduced Escalations

AGILITY integrates seamlessly into your workflow via API.  80%+ of core network incidents are diagnosed automatically and results delivered via email, slack, or JSON – wherever your team needs them.

Fewer War Room Scenarios

Lengthy troubleshooting sessions are minimized with real-time, AI-assisted insights for faster decision-making.

Active Learning

As mentioned earlier, diagnostic accuracy is further improved over time by learning from past incidents through user feedback, preserving institutional knowledge.

The Result for Modern Businesses in Telecommunications

By automating RCA and integrating with existing workflows, Incident Co-Pilot enhances overall network availability and operational efficiency while relieving pressure on your top operations and engineering personnel.

Adding TelcoGPT and “Knowledge as a Service” leveraging your private documentation, you make the breadth of standards and company knowledge available to your people wherever and whenever they need it. 

TelcoGPT Provides the Knowledge Engineers Need, When and Where They Need It

TelcoGPT combined with private Knowledge as a Service provides engineers with real-time access to public and proprietary knowledge, enhancing diagnostics, remediation, and planning.  Combined with AGILITY, the system makes the most complex troubleshooting accessible via chat.

Benefits of TelcoGPT and Knowledge as a Service

Purpose-built for troubleshooting, network planning, and problem-solving, it delivers consistent, validated insights—instantly. That means:

Accelerated RCA

Real-time insights further enable faster diagnosis and remediation.

Consistency Across Teams

Centralized knowledge tears down silos and ensures all authorized personnel seamlessly work from the same reliable base of information.

Enhanced Planning and Decision-Making

Engineers are empowered to make accurate, data-driven decisions utilizing public knowledge standards including 3GPP, ITU, and IETF, combined with private documentation including system design documentation, ticketing information, and more.

The Result

TelcoGPT ensures engineers and operations personnel have immediate access to critical knowledge, whether troubleshooting live networks or planning upgrades—making it an essential tool for streamlined network engineering and operations.

B-Yond Answers The Questions Network Operators Are Asking

Whether you are an operations team troubleshooting the network, a research team testing in labs, or engineers planning a network upgrade, — B-Yond’s AGILITY and TelcoGPT + Knowledge as a Service provide diagnostics automation and timely, accurate access to knowledge that is unique in the industry.  B-Yond has developed these products through decades of telco domain expertise combined with an industry-leading AI and ML data science practice.

Earlier in this article, we identified three questions network operators are confronted with when network issues occur:

1. How do we reduce MTTR when complex troubleshooting is a manual process?
2. How do we reduce the pressure placed on our top-tier engineers?
3. How do we make critical knowledge available where and when it is needed?

B-Yond offers answers to those questions.

AGILITY as an Incident Co-Pilot addresses operational challenges in an automated way that previously only top engineers could tackle.  TelcoGPT plus private Knowledge as a Service puts company and standards information at the fingertips of operations personnel and engineers where and when they need it.

This combination empowers engineers to solve issues faster and more consistently, whether improving test accuracy and shortening test cycles in lab environments or helping reduce MTTR and improve network availability in production networks.

Automate Your Complex Troubleshooting

AGILITY is the AI-driven solution that revolutionizes automation for the most difficult network troubleshooting issues.

Without it, operators remain trapped in outdated, manual processes that drain resources, slow down diagnostics, and leave networks vulnerable to prolonged downtime.

With AGILITY, operators can:

• Improve diagnostic quality with automated, data-driven insights.
• Reduce downtime by accelerating RCA and remediation.
• Scale operations efficiently, minimizing reliance on top-tier engineers.

Improve Your Operational Efficiency

The old model of network troubleshooting doesn't work for complex problems in today's mobile networks.

With AGILITY, operators can move beyond reactive manual troubleshooting and embrace a more proactive, automated, and scalable approach that meets the demands of today’s networks and prepares them for tomorrow’s challenges.

By automating complex network diagnostics and delivering real-time knowledge access, AGILITY and TelcoGPT simplify network troubleshooting and planning.

The result?

More efficient network engineering and operations that improve network availability and accelerate planning, helping to keep you at the front of a rapidly evolving industry.

Don’t settle for outdated diagnostic processes and siloed knowledge. Experience how B-Yond’s AI-driven systems for troubleshooting and knowledge delivery can help accelerate your journey towards autonomous networks.

Book a demo today.