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Customer service teams often struggle with the high volume and ambiguity of support tickets, especially when customers use vague or unclear language. For one customer support team, this challenge translated into longer resolution times, frustrated agents, and declining customer satisfaction. AiSynapTech stepped in with a powerful AI solution to streamline the ticket categorization process—and the results were transformative.
In a typical day, this customer support team processed hundreds of tickets, many of which lacked clarity or were missing context. Agents spent valuable time deciphering customer intent before they could even begin resolving the issue. This inefficiency caused:
Delayed response and resolution times
Agent fatigue and lower productivity
Ineffective ticket routing, leading to escalations and miscommunication
Dropping CSAT (Customer Satisfaction) scores
The need for a smarter, faster way to understand and route tickets became critical for the team's performance and service quality.
AiSynapTech began with an in-depth discovery phase to understand the client’s support processes, ticket data, and CRM architecture. The key goals were to reduce manual intervention and accelerate ticket handling from the moment a customer hits “submit.”
We leveraged our expertise in Natural Language Processing (NLP) and machine learning, focusing on:
Understanding the customer’s true need—even when expressed in ambiguous terms
Identifying key data points within the message (e.g., product names, error codes)
Seamlessly routing categorized tickets to the appropriate department or specialist
Using historical ticket data, we trained a custom intent and entity recognition model tailored to the company’s unique ticket patterns and customer language.
AiSynapTech deployed a fully integrated Intent Detection System within the client’s existing CRM. The system automatically:
Scans incoming tickets in real-time
Analyzes customer language using NLP models
Extracts relevant entities (like issue type or account details)
Categorizes and routes the ticket to the correct team or queue
The AI system continuously learns from newly resolved tickets, improving classification accuracy over time.
Key features included:
Confidence thresholds to allow human-in-the-loop review for uncertain cases
Transparent ticket annotations so agents could see how the AI classified the intent
Feedback loops allowing agents to correct misclassifications, further training the model
KPI
Before AiSynapTech
After AiSynapTech
Avg. Resolution Time
24 hours
14.4 hours
Auto-Routed Tickets
10%
65%
CSAT Score
78%
91%
Within just a few weeks of deployment, the customer support team experienced measurable performance improvements:
40% Reduction in Average Resolution Time
65% of Tickets Automatically Routed Without Agent Intervention
Significant Increase in Customer Satisfaction Scores (CSAT)
Improved Agent Productivity & Lower Burnout
“AiSynapTech didn’t just give us a tool—they gave us a smarter, more scalable way to support our customers. The intent detection system lifted a huge burden off our agents and made a real difference in how quickly we respond. Our customers noticed the change almost immediately.”
— Director of Customer Experience
