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Our AI analyzes your historical data to build custom models specific to your business. It learns patterns, preferences, and behaviors unique to your operations—continuously improving accuracy as you use the system. Your data never trains shared models.

Absolutely. You can begin with core functionality and enable AI features gradually as you become comfortable. AI capabilities are modular—turn them on when ready, no migration required.

AI suggestions are always reviewable—you maintain final control. The system includes feedback mechanisms so it learns from corrections. Confidence thresholds let you auto-approve high-certainty actions while flagging edge cases for human review.

Priority and SLA design requires balancing customer expectations with operational reality: (1) Priority levels - typically 4 levels: Critical (system down, revenue impact), High (significant impact, workaround exists), Medium (limited impact, can wait), Low (questions, feature requests). (2) SLA definition - set response time (first reply) and resolution time for each priority. Example: Critical 1hr response/4hr resolution, High 4hr/24hr, Medium 8hr/48hr, Low 24hr/5 days. (3) Business hours - define SLA hours (24/7 for critical? business hours for others?). (4) Escalation rules - automatic escalation when approaching SLA breach. (5) SLA pausing - pause timer when waiting for customer response. (6) Customer tiers - different SLAs for premium customers. Monitor: SLA compliance rate (target >95%), average response/resolution times, trends by priority and category.

Smart routing reduces resolution time and improves first-contact resolution: (1) Auto-categorization - use keywords, forms, or AI to classify tickets by type. (2) Skills-based routing - match ticket category to agent expertise (billing experts handle billing tickets). (3) Load balancing - distribute tickets evenly across available agents to prevent backlogs. (4) Customer history - route returning customers to same agent when possible for continuity. (5) Priority routing - critical tickets go to senior agents or dedicated queue. (6) Time-zone routing - route to agents in appropriate time zone for faster response. (7) Round-robin vs. pull - assign automatically or let agents select from queue (higher engagement but risk of cherry-picking). Implementation: start simple with category-based routing, add sophistication as you learn patterns.

Automation eliminates repetitive work: (1) Auto-acknowledgment - immediate confirmation when ticket is received. (2) Auto-categorization - classify tickets based on keywords, forms, or AI analysis. (3) Auto-assignment - route to appropriate queue or agent. (4) SLA triggers - alerts when approaching breach, automatic escalation. (5) Status updates - notify customers when ticket status changes. (6) Follow-up reminders - alert agents on tickets waiting for customer response. (7) Satisfaction surveys - automatically send after resolution. (8) Macros and templates - pre-written responses for common issues. (9) Merge duplicates - identify and combine related tickets. (10) Auto-close - close tickets after X days without customer response (with warning). Start with high-volume, low-complexity automations for immediate impact.