Transforming Customer Support with Agentic AI

Problem

As the client scaled globally, their support team faced an exponential rise in customer tickets – especially during off-hours.

Customers expected immediate answers, but the support queue grew longer, response times slowed down, and inconsistencies in replies became frequent.

Even though the company had a rich internal knowledge base, it remained underutilized – agents struggled to search it efficiently, and content updates lagged behind real-world needs.

The pressure on support staff led to burnout, rising operational costs, and decreased customer satisfaction.

Solution

SmartCat implemented a modular Agentic AI system to act as the client’s first line of support.

The system was designed to understand natural language queries, semantically search internal documentation, and generate high-quality responses without human input.

It integrated directly into the company’s existing support stack (including Zendesk and Slack), offering an out-of-the-box experience with minimal friction.

Crucially, it didn’t just automate – it learned. With every resolved query and agent correction, the AI grew smarter, closing knowledge gaps and continuously improving resolution accuracy.

Results

• 40% reduction in time-to-first-response
  
• 30% fewer agent escalations
  
• 60% of repetitive queries resolved autonomously
  
• 2x increase in knowledge base usage
  

Smart Tip

Let AI handle the repetitive – free your people for the human moments.

Smart Fact

The AI found 5 common customer issues that were missing from the help center. After adding them to the knowledge base, the number of support tickets on those topics dropped, and both customers and agents got faster answers.

About the Client

Mid-sized B2B SaaS company with a 20+ person support team handling global users.
Existing tools included Zendesk, internal documentation, and Slack.
Strong culture of technical excellence, but limited capacity for 24/7 human support.

Technologies Used

• NLP / NLU
  
• Sentence-BERT embeddings
  
• Vectorized Knowledge Base
  
• Retrieval-Augmented Generation (RAG)
  
• Slack & Zendesk Integrations
  

Feedback loops (RLHF)