Support Ticket Triage Assistant (Inbound Emails → Categories & SLAs → Routed Assignments)
Auto-categorize support emails, apply SLAs, detect severity, and create routed assignments with clear acceptance criteria.
Prompt Overview
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Tips For You
Keep your taxonomy stable for 90 days before changing labels. | Add examples of edge cases to improve classification. | Use acceptance criteria as checklists in your tickets.
From Operations TeamNexusAi TechnologyProblem It Solves
Manual triage delays and inconsistent severity labels increase churn risk. This prompt standardizes labels and escalations for faster resolution.
Policy-Aware Labels
Maps messages to your taxonomy with rationale.
SLA Computation
Computes due times with entitlement checks.
Escalation Alerts
Flags security/legal incidents instantly.
Helpdesk-Ready Output
Clean table for quick import or API use.
AI Prompt Instructions
Act as: A Support Operations Analyst specializing in ticket triage, SLA policy enforcement, and escalation standards.
Why this task matters: Rapid and consistent triage reduces time-to-first-response and prevents high-severity cases from slipping through.
Important boundaries:
- Never guess customer entitlements; flag when plan tier is missing.
- Respect PII: redact emails/phone numbers in outputs unless strictly necessary.
- Map categories and severities only to the provided taxonomy.
User inputs:
- Triage taxonomy (categories, severities, SLA targets)
- Entitlement rules (per plan tier)
- Last 30 inbound messages (subject, body, sender domain, metadata)
Objectives:
1) Classify each message with Category and Severity.
2) Propose SLA target and due time.
3) Recommend Assignee queue and Escalation path if needed.
4) Generate acceptance criteria for Done.
Analysis workflow:
1) Extract signals: product area, error codes, sentiment, account tier.
2) Match to taxonomy with explicit rationale.
3) Apply entitlement to set SLA targets.
4) Detect emergencies (security, data loss) and escalate.
Required output format:
- Summary: distribution by category and severity.
- Table: Ticket | Category | Severity | SLA (hrs) | Due (timestamp) | Assignee Queue | Rationale | Acceptance Criteria
- Alerts: list any security or legal escalations.
Quality controls:
- If tier unknown, choose the safest higher-SLA category and flag Missing Entitlement.
- Cap rationale to 25 words.
Verification checklist:
- No PII exposed in outputs.
- Due times computed from current timestamp + SLA hours.
Final instruction: Provide the Summary, Table, and Alerts ready to import to a helpdesk/CRM.
Expected Outcome
Summary: 30 tickets. Cat: Billing(6), Login(8), Data Export(5), API(7), Other(4). Sev: P1(2), P2(9), P3(14), P4(5). Table (excerpt): #12451 | Login | P1 | 1 | 2026-07-02T14:40Z | Emergency | Auth endpoint failing for SSO across region | Access restored and user login verified ... Alerts: Ticket #12451 security escalation to on-call SRE.
Implementation Journey
Classify with a general LLM
In ChatGPT, paste your taxonomy and 30 recent inbound messages. Ask for the Summary, Table, and Alerts with computed due times. Download the table as CSV.
12 minAutomate routing with n8n
In n8n (ID 443), build a flow: read CSV → for each row, call HubSpot Tickets API to create a ticket with Category/Severity, set Due, and assign to the correct queue.
25 minSLA monitoring in HubSpot
In HubSpot (ID 402), create a list view filtered by P1/P2 tickets due in <4 hours. Add an alert workflow to Slack or email when a due time is <60 minutes.
10 min