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.
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.
- 01 / Read
Extract the request type, location, description and any photos.
- 02 / Check
Match the location to existing open requests and flag likely duplicates.
- 03 / Route
Assign each request to the right crew or department, with urgent hazards flagged for immediate review.
- 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 repeatableGive recurring work an owner, a trigger, and a stop rule.Client vs. server: where code runsWhat belongs in the browser or app, and what must stay on a server you control.Get resident requests to the right crewA 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 AIHow 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.
Customer support
Support triage and reply drafts
Classify incoming tickets, find the relevant answer, and draft a reply for an agent to check.
See the workflow Customer supportAt-risk customer alerts
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.
See the workflow Customer supportReturn and refund requests
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.
See the workflowAn 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.
---
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/)