Workflow · Customer support
AI-Assisted Support Inbox Triage
Classify incoming support emails, draft replies from approved help content and escalate anything sensitive to a person.
The workflow at a glance
Goal: Cut first-response time on routine questions while making sure sensitive conversations always reach a person.
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Step 1: Trigger
New email arrives in the support inbox
The help desk or email account triggers the workflow for every new conversation, not for replies in existing threads.
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Step 2: Data
Collect context
Pull the sender's previous tickets and, for stores, their latest order — only the fields a reply actually needs.
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Step 3: AI step
Classify and check for escalation
The AI returns a topic from a fixed list, a sentiment label and whether any escalation trigger is present (legal threat, safety, chargeback, VIP).
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Step 4: AI step
Draft a reply from approved content
For routine topics only, the AI drafts a reply using your help articles and macros, and lists the article it relied on.
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Step 5: Human review
Agent approves, edits or takes over
The draft appears as an internal note. An agent sends it, edits it or handles the case personally. Escalations skip the draft entirely.
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Step 6: Action
Send, tag and log
The reply is sent, the ticket is tagged with the topic, and the AI output is logged for weekly review.
Why this workflow
Most support teams answer the same handful of questions all day. This workflow uses AI for the mechanical part — sorting the inbox and writing a first draft — while a person keeps control of what customers receive. It’s a safe first step before deploying a fully autonomous AI agent, and it shows you exactly where your help content falls short.
What you need
- A shared support inbox or help desk with an API or native automation (most do).
- An automation platform such as Zapier or n8n, or the built-in AI features of your help desk.
- A short, current set of help articles or saved replies covering your most common questions.
- A written list of escalation triggers.
If your help desk already includes an AI agent — Fin by Intercom, Zendesk AI, Tidio’s Lyro or Gorgias — you can run the same approach inside that product, starting in a “suggest, don’t send” mode where available.
Build it
- Define your topic list. Keep it short (six to ten topics), based on an audit of recent tickets. Add “other” as a catch-all.
- Write the classification prompt. Ask for structured output with allowed values only. Our support templates include a ready-made classification prompt.
- Write the drafting prompt. Include your tone rules, the relevant help article text and the instruction to say “No approved answer found” rather than guess.
- Route by result. Escalations go to a senior agent; routine topics get a draft as an internal note; “other” goes to the normal queue.
- Log everything. Store the topic, escalation flag and whether the draft was sent unchanged, edited or discarded.
- Test with 30 past emails before going live, including angry, vague and multi-question emails.
Example classification output
{"topic": "shipping_delay", "sentiment": "frustrated", "escalate": false, "reason": "Asks for delivery date on order"}Validate the output before routing: if the topic isn’t on your list or the JSON is malformed, send the ticket to the normal queue.
Variations
- Chat instead of email: the same logic applies, but keep drafts very short.
- Multilingual inboxes: ask the AI to detect the language and draft in it, and route languages your team doesn’t speak for review by a fluent colleague.
- Moving to autonomy: once drafts for a topic are sent unchanged for several weeks, consider letting an AI agent answer that topic directly, with an easy route to a person.
Read the full method in our AI customer support automation guide.