Customer Support Automation
Resolve 60% of tickets without a human. Route the rest to the right person with context pre-loaded. Brand voice preserved.
Modern AI support isn't a chatbot that frustrates customers. It's a triage + resolution layer that handles routine tickets (refunds, tracking, sizing, account questions) and routes the rest to humans with full context. Done well, customer satisfaction goes up while cost per ticket goes down.
What we deliver
- Incoming ticket (Plain / Intercom / Help Scout / Zendesk) → AI categorise
- 60%+ resolve automatically (status-of-X, refund, FAQ-shaped queries)
- 40% route to the right human pod with suggested-reply pre-drafted
- Customer Slack mentions auto-summarised + logged
- NPS < 7 → automatic CSM Slack alert with retention play
Tangible outputs
Triage model trained on your historical tickets + brand-voice-calibrated reply templates + dashboard tracking deflection rate / CSAT / time-to-resolution.
FAQs
Will customers know they're talking to AI?
Our pattern: AI handles the routine query, brands the response as 'AI-assisted' transparently, escalates anything edge-case to a human. Customers prefer instant AI to slow human.
How does it handle our brand voice?
Initial training on 50-100 of your historical replies calibrates voice. Ongoing supervised learning refines as you go. The first 4 weeks include heavy human review to lock voice.
What about edge cases / angry customers?
Sentiment analysis triggers human escalation automatically. AI never closes a ticket where the customer expresses frustration.