---
title: "Public service request routing: AI Use Case"
description: "Classify incoming service requests from residents, such as potholes, streetlights, missed collections or blocked drains, add the location and a short summary, flag duplicates and route each one to the right crew or department."
url: https://lidvizion.ai/use-cases/public-service-request-routing/
site: Lid Vizion
index: https://lidvizion.ai/llms.txt
---

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

# Public service request routing

Classify incoming service requests from residents, such as potholes, streetlights, missed collections or blocked drains, add the location and a short summary, flag duplicates and route each one to the right crew or department.

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

Where it starts

## The trigger.

A resident submits a request by web form, app, email or phone note.

How it runs today

- Staff read and re-key every request before it reaches a crew.
- Several reports of the same problem create duplicate work orders.
- Urgent hazards wait in the same queue as routine requests.

The workflow

## Four bounded steps.

Each step has an owner and a stop rule.

1. 01 / Read
   Extract the request type, location, description and any photos.
2. 02 / Check
   Match the location to existing open requests and flag likely duplicates.
3. 03 / Route
   Assign each request to the right crew or department, with urgent hazards flagged for immediate review.
4. 04 / Update
   Send the resident an acknowledgement and status updates as the request moves.

Where people stay in control

## Approval points.

- Dispatchers review every request flagged as urgent or unclear.
- Crews and supervisors decide priority and scheduling.
- Resident contact details are used only for updates on their request.

How we would measure it

## Against a baseline.

Measured before and after, on the same work.

### Time from submission to assigned crew.

### Duplicate work orders created.

### Requests reassigned after routing.

Related

## Go deeper.

- [Automate the repeatable](https://lidvizion.ai/services/automation/): Give recurring work an owner, a trigger, and a stop rule.
- [Client vs. server: where code runs](https://lidvizion.ai/resources/basics/backend-client-vs-server/): What belongs in the browser or app, and what must stay on a server you control.
- [Get resident requests to the right crew](https://lidvizion.ai/guides/get-resident-requests-to-the-right-crew/): A four-step playbook to agree request types and owners, extract location and details, flag duplicates and urgent hazards, and keep residents updated as requests move.
- [How to route resident service requests with AI](https://lidvizion.ai/answers/how-to-route-resident-service-requests-with-ai/): How can a city, county or public works team use AI to sort residents’ service requests, catch duplicates and get urgent hazards seen sooner?

More use cases

## Other places to start.

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

- [Support triage and reply drafts](https://lidvizion.ai/use-cases/support-triage/): Customer support Classify incoming tickets, find the relevant answer, and draft a reply for an agent to check.
- [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.

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/)