How it Works
Every ticket spawns above the scene and falls to the glowing classifier hub at the centre. There it is scored twice: a confidence score for its intent, and an urgency score built from its sentiment. The urgency check runs first — if a ticket reads as critical (an irate customer, an explicit churn threat) it shoots straight up to the manager node, skipping every queue. Otherwise the confidence gate decides: a high-confidence prediction is handed to whichever support agent currently has the lightest load; a low-confidence one is diverted to human review instead of risking a wrong automated response.
Agents glow brighter as their active load rises and dim as tickets resolve and free up capacity, so the ring visually tracks who is overloaded in real time — exactly the signal a skill-aware routing model uses instead of blind round-robin assignment.
Frequently Asked Questions
What is intent classification in customer support automation?
A transformer model reads a ticket's free text and assigns it to one of 15-20 intents — order status, return request, complaint, and so on — each backed by roughly 500 labeled example phrases, so the downstream system knows what the customer actually wants before deciding how to handle it.
Why does raising the confidence threshold send more tickets to human review?
Every classification carries a confidence score, and the system only automates when that score clears the threshold. Raising θ_conf makes the gate stricter, so a larger share of borderline predictions fall below it and get handed to a person instead of being auto-routed.
How does sentiment-driven urgency scoring work in this simulation?
Each ticket gets a sentiment value; the urgency score blends the negativity of that sentiment with a small random chance of an explicit churn phrase like "switching to a competitor." When the score clears the critical threshold, the ticket is flagged for escalation regardless of how confident the intent classifier is.
Why do critical tickets bypass the agent queue entirely?
The escalation check runs before the confidence gate. Catching a customer's frustration at the moment of expression, rather than after a slow queue, is often the entire difference between a saved account and a lost one, so critical tickets route straight to a manager instead of waiting in line.
How does the simulation decide which agent gets a ticket?
At assignment time every agent is scored, and the ticket goes to whichever agent currently has the lowest active load — a simplified stand-in for a supervised routing model that predicts each agent's probability of successfully resolving that category of ticket.