Last updated: 2026-10-21

🎧 Customer Support Triage

Sort incoming support tickets by category and urgency, suggest a draft reply from your knowledge base, and escalate the complex ones to a human.

⏱ 8 hours 💵 Model usage plus your ticketing plan 📊 medium ⭐ Hermes

The problem

Support teams drown in repetitive tickets. 'How do I reset my password', 'What's the difference between the Pro and Team plan', 'Is there an Android app'. A human answers the same 20 questions every day. Real problems — the ones that need a human — get delayed because the queue is full of easy ones.

The outcome

Every incoming ticket gets classified (category, urgency, billing-related?) and matched to a knowledge-base answer. The agent drafts a reply; humans review and send with one click. Complex or angry tickets skip the draft and route directly to senior support with context pre-loaded.

Why Hermes

Support volume is continuous, not batch, so you want an agent that stays up. Hermes runs as a gateway with memory, tools and scheduled jobs, but ticketing and knowledge-base access come from tools you connect and vet. Plan for a real search index over your help centre rather than leaning on memory.

Alternatives worth considering

  • OpenClaw — If you prefer explicit control over every prompt and want to self-host for data residency
  • IronClaw — For regulated industries (healthcare, finance) where the audit log is the key feature

Setup steps

  1. Step 1: Connect ticketing system

    Zendesk/Intercom/Freshdesk all have APIs. Read tickets, post internal notes (not external replies), add tags. No customer-facing actions without human approval.

  2. Step 2: Index your KB and past tickets

    Put your help centre and an export of resolved tickets (with their final resolutions) into a search tool or vector store the agent can query (see our RAG and embedding glossary entries). Memory alone will not hold thousands of tickets.

  3. Step 3: Write the classification schema

    Category (billing, technical, account, other), urgency (low/medium/high), sentiment (neutral/frustrated/angry), type (question/bug/feature request/complaint). Explicit schema beats 'figure it out'.

  4. Step 4: Implement the 'never auto-reply' rule

    Drafts go to internal notes. A human clicks 'send'. Exception: automated acknowledgments ('we got your ticket, ref #12345') — those are safe to auto-send.

  5. Step 5: Build the escalation path

    Angry sentiment or high urgency → skip draft, flag for senior agent with a summary of past tickets from the same customer. Context routing is more valuable than auto-reply.

Example prompt

Classify this ticket (category, urgency, sentiment). Find relevant KB articles and similar past tickets. If the answer is well-covered by KB, draft a reply using our past tone. If sentiment is angry or urgency is high, skip the draft and write an internal note for the senior agent.

Pitfalls to avoid

  • Auto-sending replies. Customer support is the worst place to learn an agent hallucinated. Draft-only, always.
  • Using stale KB content. The agent will confidently quote an answer that's no longer true. Re-index your KB weekly and have it flag conflicting information.
  • Ignoring the drip-drip of low-quality drafts. Agents review drafts in seconds and don't always edit. Low-quality drafts become shipped replies. Measure customer satisfaction by ticket category and intervene when a category trends down.

Cost breakdown (monthly)

ItemCost
Hermes (open source, self-hosted)$0 for the software
Model API (scales with ticket volume)See the model pricing table
Search index or vector storeDepends on your choice

Cost: Model usage plus your ticketing plan. Model rates change often; check the model pricing table or the cost calculator for current figures.

Related guides

← Back to all use cases · Compare platforms at the decision guide.