Inside the AI-Powered Tech Support That Boosted Resolution Speed by 60%

A global leader in advanced optical networking equipment was facing mounting challenges in delivering consistent, high-quality support to its worldwide customer base. Despite having skilled engineering and support teams, the company struggled with prolonged debugging cycles, difficulty interpreting complex network alarms, and delays in fault detection and root cause analysis. These inefficiencies frequently led to traffic loss during troubleshooting efforts—resulting in escalating operational costs and declining customer satisfaction. Learn how they leveraged VCTI's AI Center of Excellence for a 60% improvement in issue resolution time.

To address these pressing issues, the company turned to VCTI’s AI Center of Excellence. Leveraging cutting-edge artificial intelligence and machine learning capabilities, VCTI helped transform the client’s support operations. By automating critical diagnostics, streamlining alarm interpretation, and accelerating fault resolution, VCTI delivered measurable improvements in service reliability and efficiency. 

Improving Tech Support Through AI and Machine Learning

Recognizing the need for a smarter, more scalable approach to network support, the customer partnered with VCTI to deploy an AI-driven Hybrid Retrieval-Augmented Generation (RAG) solution. Purpose-built to enhance fault management and streamline debugging workflows, this cutting-edge system combines powerful AI/ML algorithms with robust data engineering to transform how technical teams identify and resolve issues.

The RAG solution intelligently retrieves relevant information from vast engineering knowledge bases and fuses it with real-time data analysis. This enables engineering and support teams to access precise, context-aware insights instantly. This, in turn, empowers them to diagnose faults faster, reduce traffic disruption, and minimize human error.

The result: dramatically shorter resolution times and a significant boost in operational efficiency.

“The RAG-powered platform turned a frustrating debugging process into a streamlined, intelligent operation. It’s a game changer for our support and engineering teams.”

Here’s How We Did It

VCTI’s approach was rooted in a deep understanding of the customer’s operational pain points and a commitment to practical innovation. The deployment of the AI-driven solution was executed in three key phases.

1. Data Integration-To build a reliable foundation for AI-driven insights, VCTI began by unifying a wide array of data sources. Product manuals, historical support tickets, troubleshooting guides, and engineering notes, which had previously been scattered across silos, were consolidated into a centralized, searchable database. This not only streamlined access to critical knowledge but also ensured consistent, accurate responses across teams.
2. RAG Model Deployment- Next, VCTI deployed the Hybrid Retrieval-Augmented Generation (RAG) model tailored to the optical networking domain. This advanced system paired a large language model with the company’s specialized knowledge base. When a query is submitted, the AI intelligently interprets the technical context, retrieves the most relevant data, and generates a clear, step-by-step debugging guide. This has dramatically reduced manual effort and improved first-time resolution rates.
3. Continuous Learning - To ensure the system evolves alongside the network's complexity, VCTI enabled continuous learning capabilities. Each successful resolution is automatically captured, validated, and integrated back into the knowledge base, keeping the AI up-to-date and increasingly more effective with every interaction.

Key Outcomes

 The results were both immediate and measurable. By transforming a fragmented knowledge base into an intelligent, AI-powered support tool, VCTI helped the customer achieve:

• 30–40% reduction in Technical Assistance Center (TAC) costs
• 40% faster root cause analysis
• 60% improvement in overall resolution time

The implementation also led to a marked increase in engineering efficiency and productivity, as routine tasks became faster and more streamlined. Enhanced network visibility provided teams with clearer, real-time insights, enabling more proactive decision-making. Additionally, the solution significantly accelerated onboarding and facilitated seamless knowledge transfer, helping new engineers ramp up quickly and contribute effectively from day one. 

According to the customer, these improvements not only streamlined day-to-day operations but also empowered engineering teams to focus on higher-value tasks, ultimately raising the standard of service across the organization.  

By leveraging VCTI’s AI Center of Excellence and deploying a tailored Hybrid RAG solution, the customer redefined what’s possible in optical network support. What was once a reactive, manual support model is now a proactive, intelligent system that scales with demand and adapts in real time.