Email is the biggest time sink. Same questions, same info, same responses with different names. AI handles the repetitive stuff. Team focuses on what requires thought.
How It Works
Handles Well
FAQ responses, appointment confirmations, status updates, document requests, simple support, acknowledgment emails.
Should Escalate
Complaints, legal/compliance, money disputes, complex support, VIP clients, low-confidence classifications.
Build Steps
1. Audit email
30 days. Categorize everything. 60-80% fall into fewer than 15 categories.
2. Knowledge base
Per category: standard response, personalization variables, tone, links, escalation triggers.
3. Pipeline in n8n
Email trigger > extract details > classify via Claude > route > generate response > confidence check (below 85% = human review) > send/queue > log.
4. Prompts
Classification: categories + confidence + escalation rules. Response: template + context + tone + signoff.
5. Human review queue
Original email + AI draft + approve/edit/reject. Slack notification, draft folder, or simple web UI.
6. Test
50 emails covering all categories plus edge cases. Target: 90%+ classification accuracy.
7. Shadow mode
First week: generates but doesn't send. Compare to team's actual responses.
8. Go live
Auto-send highest-confidence only. Human review for rest. Expand gradually.
Optimization
FAQ
Customers notice? Not with good config matching your tone and style.
Cost? Under $300/month for hundreds of daily emails.
Attachments? Text-based processed. Complex route to human.
Speed? 30-60 seconds auto-response.
Wrong response sent? Shadow mode + gradual expansion + confidence thresholds = under 2% error. Always have feedback mechanism.
Multiple languages? Yes. Claude handles dozens. Add language detection to classification.