---
title: "Support triage and reply drafts: AI Use Case"
description: "Classify incoming tickets, find the relevant answer, and draft a reply for an agent to check."
url: https://lidvizion.ai/use-cases/support-triage/
site: Lid Vizion
index: https://lidvizion.ai/llms.txt
---

[Use cases](https://lidvizion.ai/use-cases/) · Customer support

# Support triage and reply drafts

Classify incoming tickets, find the relevant answer, and draft a reply for an agent to check.

[Talk through this workflow](https://lidvizion.ai/contact/?need=ai-workflow&from=%2Fuse-cases%2Fsupport-triage%2F#write) · [Automate the repeatable](https://lidvizion.ai/services/automation/)

Where it starts

## The trigger.

A ticket or support email arrives.

How it runs today

- Tickets are sorted by hand.
- Agents search the knowledge base for every answer.
- Similar questions get different answers.

The workflow

## Four bounded steps.

Each step has an owner and a stop rule.

1. 01 / Classify
   Topic, urgency and customer are identified.
2. 02 / Retrieve
   Relevant articles and past answers are found.
3. 03 / Draft
   A reply is drafted with its sources.
4. 04 / Send
   An agent edits and sends; unclear cases escalate.

Where people stay in control

## Approval points.

- No reply is sent without an agent.
- Refunds and account changes always escalate.

How we would measure it

## Against a baseline.

Measured before and after, on the same work.

### Time to first reply.

### Tickets reopened.

### Answer consistency on common topics.

Related

## Go deeper.

- [Automate the repeatable](https://lidvizion.ai/services/automation/): Give recurring work an owner, a trigger, and a stop rule.
- [Embeddings and feature vectors](https://lidvizion.ai/resources/basics/embeddings-feature-vectors/): How models turn text, images and records into numbers that can be compared.
- [Triage support requests with AI](https://lidvizion.ai/guides/triage-support-requests-with-ai/): A four-step playbook to classify, route and draft replies for incoming support requests, with an agent approving every customer-facing message.
- [How to automate customer support triage](https://lidvizion.ai/answers/how-to-automate-customer-support-triage/): How can a company use AI to triage customer support requests without hurting the customer experience?

More use cases

## Other places to start.

[All use cases](https://lidvizion.ai/use-cases/)

- [At-risk customer alerts](https://lidvizion.ai/use-cases/at-risk-customer-alerts/): Customer support Spot customers who may be about to leave from support tickets, usage and account notes, and give the account owner a short summary to act on.
- [Return and refund requests](https://lidvizion.ai/use-cases/return-and-refund-requests/): Customer support Check each return or refund request against your policy and order records, prepare the response and the system updates, and send anything outside policy to a person.
- [New customer onboarding](https://lidvizion.ai/use-cases/new-customer-onboarding/): Customer support Guide each new customer through the first weeks with timely, relevant steps based on what they bought and what they have done so far, and alert a person when someone gets stuck.

An illustrative workflow pattern, not a result from a specific customer.

Bring the messy version

## One workflow. A better way to run it.

Show us the tools, the handoffs, and the part that keeps slowing your team down.

[Let’s map your workflow](https://lidvizion.ai/contact/) · [Read our approach](https://lidvizion.ai/approach/)