Reducing Customer Support Costs by 47% With AI Agents
A growing enterprise SaaS company was spending $1.2 million annually on customer support. NaulX implemented custom AI support agents to resolve repetitive tier-1 tickets, route complex cases to human agents, and improve response consistency. The new support workflow reduced annual operating costs by $564,000 and increased customer satisfaction from 72% to 89%. Customer support had become one of the company’s largest operational expenses.
Key Results
47%
Support cost reduction
$564K
Estimated annual savings
89%
Customer satisfaction
8 weeks
Implementation timeline
The Challenge
The company was spending approximately $1.2 million each year on customer support.
A review of its support operations identified several problems:
A high percentage of tickets involved repetitive tier-1 questions
Response times increased during peak support periods
Customers sometimes received inconsistent answers across different channels
Human agents had limited time for complex product and account issues
Ticket routing and categorisation required manual work
Support costs were increasing alongside customer growth
Expanding the team was becoming difficult to sustain financially
The company did not want a generic chatbot that simply returned scripted responses. It needed a support system capable of understanding customer intent, retrieving approved product information, completing routine actions, and escalating requests when human judgement was required.
Our Solution
NaulX built custom AI support agents using the company’s existing product documentation, help-centre articles, approved support responses, and internal knowledge base.
The agents were designed to work alongside the human support team rather than replace it.
What the AI agents handled
The support agents were configured to:
Answer common product and account questions
Guide customers through standard troubleshooting steps
Categorise incoming support tickets
Identify customer intent
Retrieve answers from approved documentation
Generate summaries for human agents
Route tickets to the correct team
Detect low-confidence and sensitive requests
Escalate complex issues to a human agent
Provide responses outside normal business hours
The system also recorded common questions that could not be answered confidently. These gaps were reviewed and used to improve the knowledge base over time.We built custom AI agents trained on their product documentation and knowledge base.
Results
- Within the eight-week implementation period, the company reported:
- 47% reduction in customer support costs
- $564,000 in estimated annual savings
- Customer satisfaction increased from 72% to 89%
- Faster responses for common support questions
- More consistent answers across support channels
- Reduced repetitive workload for human agents
- Improved routing of complex tickets
- Greater support capacity without proportional hiring growth
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