Architecting Intelligent Support with Agentic AI

Delighting Your Customers and Empowering Your Support Teams
In today’s fast-paced digital world, customers expect instant, accurate, and personalized support. Traditional customer service models are struggling to keep up, leading to long wait times, inconsistent responses, and rising operational costs.

SmartCat’s Agentic AI addresses these challenges by embedding intelligent, modular agents into your support ecosystem. These agents understand customer intent, retrieve answers from your existing knowledge base, assist human agents in real time, and learn continuously from every interaction – transforming support from a cost center into a strategic asset.

Problem

Customer expectations were rising fast. The client’s support team was bogged down by repetitive requests, fragmented documentation, and growing pressure to deliver 24/7 service. Agents wasted time searching for information. As a result, customers experienced delays and inconsistent answers. Valuable insights from support interactions were not being captured or reused, and the cost of scaling human support was becoming unsustainable.

Solution

SmartCat deployed a custom-built Agentic AI system, integrating NLU and RAG into the client’s support workflow. The AI agent handled FAQs and simple queries autonomously. Additionally, it assisted human agents in real time with answer suggestions, related documentation, and resolution history. A feedback loop enabled continuous learning from agent-approved responses, which were added back to the knowledge base. The system was integrated directly into Zendesk, Slack, and the client’s internal documentation stack.

How It Works: A Look Under the Hood

Think of our Agentic AI as a highly skilled digital assistant. Here’s a simplified breakdown of its process:

1. Customer Interaction: A customer initiates a chat on your website, asks a question, or requests support.
   
2. Intelligent Processing: The AI agent analyzes the customer’s language to understand what they need. It can identify keywords, sentiment, and the core issue.
   
3. Knowledge Retrieval: The agent then searches your comprehensive knowledge base – product manuals, FAQs, past support tickets, as well as successful solutions provided by your best human agents. It’s like having an expert researcher who has read and remembered everything.
   
4. Answer Generation & Delivery:
   • For FAQs & Simple Questions: The AI can often provide an instant, accurate answer directly to the customer.
     
   • For Complex Support: However, if the question is more complex or requires human intervention, the AI can:
     
     • Provide the human agent with a summarized version of the problem and relevant articles or past solutions from the knowledge base.
     • Suggest potential next steps or troubleshooting guides.
     • Escalate the chat to the appropriate human agent seamlessly.
       
   • In setups powered by our Company Mind Assistant (CMA) powered by SmartCat, the workflow is optimized for high-trust environments. Instead of responding directly to the customer, the AI generates a suggested reply based on context and prior knowledge. Then, this suggestion is sent to a human agent within the same live thread, where it can be quickly reviewed, adjusted if needed, and approved before being delivered. Consequently, this approach ensures both speed and control, especially in cases where human judgment or brand-sensitive language is essential.
     
5. Learning Loop: Finally, every interaction, whether handled fully by AI or with human assistance, is fed back into the system. This helps the AI learn, refine its understanding, and improve its future responses. The AI agents themselves can even contribute new, structured answers to the knowledge base based on successful resolutions.

Results

• 70–80% of repetitive inquiries resolved autonomously
• 50% faster resolution for FAQ-level tickets
• 35% drop in agent escalations
• 3x increase in active knowledge base usage
  Improved agent satisfaction and reduced burnout
  

Smart Tip

Let your AI agents handle the repetitive grunt work – so your human agents can focus on moments that truly matter.

Smart Fact

Within the first month, Agentic AI discovered 7 undocumented high-frequency support issues – allowing for immediate knowledge base updates and a measurable drop in new tickets.

About the Client

A mid-sized B2B SaaS company with a global customer base and a 30-person support team. The company used Zendesk, Slack, and internal documentation tools. They had a culture of technical excellence but lacked the resources to scale support around the clock.

Technologies Used

• Transformer-based NLU (e.g. BERT, GPT)
  
• Sentence-BERT for vector embeddings
  
• Retrieval-Augmented Generation (RAG)
  
• Stateful Dialog Management
  
• Feedback loops (explicit + RLHF)
  
• Zendesk and Slack integrations
  
• Internal KB indexing