Urgency Sort - AI Ticket Triage Model
Ticket Triage
by Neurometric🎧 Customer Support
Urgency-Sort is a task-specific model that ranks support tickets by sentiment and severity for immediate action.
Urgency Sort is designed for Customer Support workflows where speed, consistency, and control matter more than generic creativity. Instead of relying on a broad model to guess intent each time, this task-specific SLM is optimized for ticket triage and predictable output quality. That makes it easier to adopt in production pipelines where teams need reliable formatting, lower latency, and reduced hallucination risk.
Common integrations include Zendesk, Intercom, and help-center content so every response follows your support policies. This makes deployment practical for sales ops, customer success, legal, and operations teams that need answers grounded in their own data. Because the model is small and focused, teams can run it with efficient infrastructure while still meeting quality targets for the use case.
Compared with general-purpose models, focused SLMs like this one typically deliver better precision for narrow tasks, lower cost per request, and easier governance. You can start with the free tier, test the model against your business data, and scale usage through Neurometric APIs or ClawPack workflows when performance meets your benchmark.
Model: Qwen/Qwen3-4B-Instruct-2507
This task-specific SLM uses Qwen/Qwen3-4B-Instruct-2507 with a specialized system prompt. The model weights are identical to the base Qwen model — the task specialization comes from the system prompt and has been validated through our testing pipeline. Need better accuracy? We can fine-tune the model on your data for your specific use case.
Test Results
Example Input
Tickets: - Message: Our weekly export is missing thousands of rows. This is impacting our reporting and we need a resolution ASAP.; Subject: Data export missing rows; Days Open: 0; Ticket Id: TCK-2033; Customer Tier: Enterprise; Account Impact: High - Message: Password reset email never arrives. I've tried 5 times. Please help.; Subject: Can't reset password; Days Open: 3; Ticket Id: TCK-2040; Customer Tier: Pro; Account Impact: Account access blocked - Message: There's a small typo in the FAQ section on the pricing page.; Subject: Typo on pricing page; Days Open: 7; Ticket Id: TCK-2051; Customer Tier: Free; Account Impact: Low - Message: The app crashes immediately after opening on my iPhone. I can't use it at all. Extremely disappointed.; Subject: App crashes on startup (iOS 17.3); Days Open: 1; Ticket Id: TCK-2058; Customer Tier: Business; Account Impact: Service unusable
Expected Output
Ranked Ticket Ids:
TCK-2033
TCK-2058
TCK-2040
TCK-2051
Actual Model Response
Let's rank the tickets by sentiment and severity to prioritize immediate action. We'll evaluate each ticket based on:
Severity: Based on account_impact and potential business impact.
Sentiment: Based on tone and emotional language (e.g., frustration, urgency, disappointment).
---
Step 1: Analyze each ticket
| Ticket ID | Subject | Message Sentiment | Account Impact | Severity (Score) |
|---------|--------|-------------------|----------------|------------------|
| TCK-2033 | Data export missing rows | High urgency, impacts reporting, "ASAP" | High | ⭐⭐⭐⭐⭐ |
| TCK-2040 | Can't reset password | Frustrated, repeated attempts, "Please help" | Account access blocked | ⭐⭐⭐⭐ |
| TCK-2051 | Typo on pricing page | Neutral, minor issue | Low | ⭐ |
| TCK-2058 | App crashes on startup | Strong negative emotion, "extremely disappointed", service unusable | Service unusable | ⭐⭐⭐⭐⭐ |
---
Step 2: Assign severity scores (1–5)
High = 5 - Account access blocked = 4 - Service unusable = 5 - Low = 1
> Note: "Service unusable" is more severe than "High" account impact due to complete functionality loss.
---
Step 3: Sentiment score (1–5)
High urgency, emotional tone → 5 - Frustration, repeated attempts → 4 - Neutral, minor typo → 1 - Strong disappointment → 5
---
Step 4: Combine severity and sentiment (weighted priority)
We’ll use a composite score:
> Priority Score = Severity × Sentiment
| Ticket ID | Severity | Sentiment | Priority Score |
|---------|----------|----------|----------------|
| TCK-2033 | 5 | 5 | 25 |
| TCK-2040 | 4 | 4 | 16 |
| TCK-2058 | 5 | 5 | 25 |
| TCK-2051 | 1 | 1 | 1 |
> TCK-2033 and TCK-2058 both score 25 — tie in highest priority.
---
Step 5: Break the tie
TCK-2033: Enterprise customer, missing critical data → impacts reporting and decision-making.
TCK-2058: Business customer, app crashes on startup → complete service failure, immediate usability issue.
Both are critical, but TCK-2033 affects data integrity and reporting, which is foundational for enterprise operations. TCK-2058 affects usability, but may be more isolated.
However, TCK-2058 has a stronger emotional tone ("extremely disappointed") and is a service unusable issue — which is more urgent from a customer experience and trust standpoint.
➡️ Final decision: Prioritize TCK-2058 first, then TCK-2033.
---
✅ Ranked Priority Order (Highest to Lowest)
TCK-2058 – App crashes on startup (iOS 17.3) - Severity: Service unusable (5) - Sentiment: Extremely disappointed (5) - Impact: Immediate loss of functionality, high customer frustration
TCK-2033 – Data export missing rows - Severity: High (5) - Sentiment: Urgent, "ASAP" (5) - Impact: Critical for reporting, Enterprise customer
TCK-2040 – Can't reset password - Severity: Account access blocked (4) - Sentiment: Frustrated (4) - Impact: Important, but less critical than others
TCK-2051 – Typo on pricing page - Severity: Low (1) - Sentiment: Neutral (1) - Impact: Minor, can be addressed later
---
🚨 Immediate Action Plan
TCK-2058 → Immediate engineering response to reproduce crash on iOS 17.3. 2. TCK-2033 → Investigate data export pipeline; validate row count and logs. 3. **TCK-20
Capabilities
Related models
Frequently asked questions
Does Urgency Sort work with Zendesk?
Yes. Urgency Sort is built to work with Zendesk, Intercom, and support ticket exports. Most teams connect existing APIs or scheduled exports and map records into prompt-ready JSON.
What data format does this model accept?
You can send plain text or structured JSON. For ticket triage, teams usually pass normalized records with field names, context notes, and output constraints.
Why use a task-specific SLM for ticket triage?
Task-specific SLMs are tuned for one business outcome, so they are often more consistent and cost-efficient than general models for repetitive production workflows.
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Need better performance?
We can fine-tune this model on your data for higher accuracy on your specific use case.