Use case · Customer support

A support inbox that sorts itself

A shared support inbox mixes urgent problems, simple questions and messages that belong to another team. We sort each message as it arrives, route it and prepare a draft reply from your own data, so agents start with the answer half written.

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Support inbox

Where is my order? → DeliveryEmail14:05
Damaged item received → Complaints, urgentForm14:11
Invoice with company details → AccountsEmail14:20
Do you ship to Slovenia? → Draft readyChat14:26

How you know you have this problem

Everybody reads every message to find the ones meant for them
Urgent complaints wait behind routine questions
The same questions are answered from scratch every day
Messages are missed when the person who usually handles them is away

What we build

How it works once it is running

01
Read each message
An AI step identifies the topic, the urgency, the language and details such as an order number.
02
Route it
The message is tagged and assigned to the right queue or person by your rules. Unclear messages go to a general queue, not to a guess.
03
Prepare the answer
For common questions, the workflow looks up the order or the relevant help article and drafts a reply for the agent.
04
Agent sends
The agent reviews, edits and sends. Replies go out automatically only for the topics you explicitly allow.

What you get

Topics, urgency and language tagged on every message
Routing rules you can read and change
Draft replies grounded in your orders and help content
A weekly summary of what customers asked about

What we need from you

Access to the support inbox or helpdesk
Your list of topics and who handles each
Past replies or help articles to ground the drafts
Agreement on which replies, if any, may be sent without review

Tools we typically use: n8n, Make, Zendesk, Freshdesk, Gmail, Outlook, Claude or GPT models
Services involved: AI integrations, Business automation

See it built

Illustrative exampleAn online store with a 3-person support teamA support assistant that knows the order and the policyCommon questions get a drafted answer built from order data and the store’s own help pages; an agent approves anything sensitive.AI integrationsBusiness automationOpen example

Questions about this use case

Do we need a helpdesk tool for this?

No. It works on a shared mailbox with labels and assignments. A helpdesk becomes worth it as the volume and the team grow, and we can help you choose one.

What stops the AI from sending a wrong answer?

By default it sends nothing. It drafts, and an agent decides. Drafts use only the order data and help content it was given, and say so when the answer is not there.

Does it work in Croatian and English?

Yes. Current models handle both well, along with the other languages your customers are likely to write in. The draft is written in the language of the message.