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AI Inquiry Triage Case Study for a Regional Service Business
An AI layer was introduced to classify incoming inquiries, detect urgency, and suggest the next action to operators.
Project summary
The client handled 120-180 daily inquiries from email, web forms, and messaging channels.
Operations staff manually routed messages to the right person, creating delays.
The project goal was to reduce first-response time without increasing headcount.
Problem
- Response quality and speed varied by shift.
- Urgent requests were buried in a shared inbox.
- Sales staff spent time on low-quality or irrelevant inquiries.
Solution
- AI classification by request type: new sales, support, urgent service, administration.
- Priority rules to automatically flag urgent requests.
- Draft response and next-step suggestion for operators with mandatory human approval before sending.
- CRM integration to assign each inquiry to the right owner.
Stack used
Measurable result
- 42% reduction in first-response time (median 94 min to 55 min).
- 31% fewer manual message-routing tasks.
- 18% increase in qualified inquiries passed to sales during the first 30 days.
Implementation notes
What made rollout successful
- Clear owners for each inquiry category.
- Minimal disruption to existing operations tooling.
- Weekly review of classification misses and rule tuning.
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