What we automate in operations and support.
Mid-sized company support operations spend 30-50% of their time on manual triage: reading the ticket, deciding category, assigning to who knows, marking priority, checking duplicates. Another 20% goes into writing similar replies to similar questions. And another 15% chasing SLAs that are slipping because nobody looked at the queue in time.
Automatic ticket classification with LLM
Each incoming ticket (email, form, WhatsApp, chat) goes through a model (Claude, GPT-4o) that extracts: category, sub-category, real priority (not the one the customer marks — the one the content indicates), sentiment, and affected product/module. Consistent labeling, routing to the right team from second one.
Replies generated with your knowledge base
For repetitive tickets (how do I X, where do I find Y, known error Z), AI drafts the reply with your knowledge base, FAQs, and historical resolutions. The agent reviews and sends in 30 seconds, instead of writing from scratch. Approved drafts feed back into the system.
Real-time SLA monitoring
Dashboard with the queue prioritized by SLA breach risk, not by arrival order. Slack/Teams alerts 30 minutes before breach. Automatic escalation to manager if a high-priority ticket exceeds threshold without response.
Duplicate detection and pattern recognition
If 5 tickets with the same root come in within 10 minutes, the system groups them, raises a major incident alert, and prepares a comms draft. No duplicates processed twice. One postmortem, not five.
Mondays used to start with 80 tickets in queue and two hours of triage. Now we open the dashboard, see the queue prioritized by SLA, and start with what matters. Radically different feel.
What we don't do
- We don't force you to switch helpdesks. We work with Zendesk, Intercom, Freshdesk, Help Scout, or whatever you use.
- We don't auto-reply to sensitive tickets (incidents, complaints, legal cases). Always human.
- We don't use generic chatbots. Each reply uses your knowledge base, not an empty GPT.