Auto-reply to billing inquiry
Personalised response sent to VIP customer within 4 minutes including account-specific billing details
Classify, respond, and escalate tickets 24/7
Every employee has a defined role, skill set, and model optimised for their work.
Oversees ticket flow, handles escalations, maintains quality standards
Categorises incoming tickets by type, urgency, and department
Drafts personalised responses using customer history and KB articles
Updates knowledge base articles based on common ticket patterns
See how the team collaborates to deliver structured, high-quality outputs.
Real outputs from real runs. Every piece is structured, actionable, and tracked.
Personalised response sent to VIP customer within 4 minutes including account-specific billing details
47 tickets about password reset in last 7 days -- possible UX issue on reset page
Current article missing info about annual vs monthly billing. Proposed addition covers 60% of billing tickets.
142 tickets handled, 94% auto-resolved, avg response time 3.2 minutes, 3 escalations
Handles routine tickets instantly -- billing questions, how-to guides, status checks. Escalates complex issues to humans.
Classifies every incoming ticket by type and urgency. Routes to the right department. No ticket sits unread.
Identifies gaps in your KB from ticket patterns. Drafts new articles. Keeps existing articles current.
No credit card required. Connect your tools and let your new team get to work. Cancel anytime.
Free tier includes 1 team with 100 runs/month. No card needed.
Yes -- in Executor mode, the team can send approved responses directly. Alex reviews and auto-approves responses that match high-confidence patterns. Unusual or complex tickets are escalated for human review.
The team detects sentiment in incoming tickets. High-emotion tickets are automatically flagged for human review. Jordan's responses are calibrated for empathy and de-escalation, but the team never sends an automated response to a genuinely upset customer.
Every response is logged with full context. You can review any response, correct it, and the team learns from the correction. Approval rates typically improve from ~70% in week 1 to ~90% by month 3.