AI Customer Support Agent
Primary Infotech deployed an autonomous AI customer support agent designed to handle common customer inquiries without constant human intervention. The system reduced response time from hours to seconds while increasing automated resolution.
- Response Time
- < 3s
- Resolution Rate
- 80%
- Cost Reduction
- 60%
01
The Challenge
The client was receiving more than 5,000 support tickets every month. Response times stretched into hours, customers were churning, and the support team was stuck answering the same questions again and again.
Over 60% of inquiries were routine — billing questions, password resets and onboarding help — yet each one still waited in the same queue as genuinely complex issues.
02
Our Solution
We built a multi-model AI agent powered by GPT-4 and grounded in the client's own knowledge. A retrieval-augmented generation (RAG) layer pulls the most relevant passages from help-centre articles, historical tickets and product documentation before every answer.
The agent resolves routine requests end-to-end through tool calls into billing and account systems. Anything complex, sensitive or low-confidence is escalated to a human specialist with a structured hand-off summary, so customers never repeat themselves.
03
Technology
A retrieval pipeline indexes documentation and resolved tickets into a vector store. The agent layer uses function calling for account actions, with guard-rails and confidence thresholds deciding when to escalate.
- GPT-4
- RAG
- LangChain
- Pinecone
- Python
- Zendesk API
04
AI Architecture
-
1
Ticket intake
Email, chat and in-app messages normalised into one queue
-
2
Retrieval
Relevant help articles and past tickets fetched from the vector store
-
3
Reasoning agent
GPT-4 drafts an answer and decides on tool calls
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4
Guard-rails
Confidence and policy checks gate every response
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5
Human hand-off
Low-confidence cases escalate with a full summary
05
The Results
Within the first month, the agent was autonomously resolving 80% of incoming tickets. Average first response time dropped from 4.2 hours to under 3 seconds, and customer satisfaction rose by 32%.
The support team now spends its time on complex, high-value conversations instead of password resets.