Property manager reviewing a maintenance request with a photo of a leaking tap on a phone
All case studies
Real Estate & PropTechAI AutomationAI Development

Property operations automation

Maintenance requests triaged, dispatched and closed without a coordinator

Six thousand tenants sent maintenance requests by email, phone, WhatsApp and a portal nobody liked. Three coordinators spent their days asking for photos, calling tradespeople and chasing invoices. We built an AI agent that triages every request, dispatches the right contractor, and keeps the tenant and owner informed until the job is closed.

Client
Residential property management company
Region
Australia
Scale
40 to 70 employees, 6,000 units managed
Timeline
6 weeks

Representative engagement. Client details are anonymised and figures reflect typical outcomes from comparable deployments.

What the client got

0%

Requests dispatched without a coordinator

Emergencies and ambiguous cases still go to a person.

0 hrs

Median time to contractor assignment

Down from more than a day.

0%

Rise in tenant satisfaction score

Driven by status updates and faster first response.

The bottlenecks

  1. Bottleneck 1

    Every request started with a clarification

    Tenants wrote “the tap is broken”. Coordinators replied asking which tap, how bad, and for a photo. A day passed before anyone knew whether it was an emergency.

  2. Bottleneck 2

    Dispatch was manual and slow

    Finding an available plumber meant calling three. Owner approval for anything above the threshold was another email thread.

  3. Bottleneck 3

    Nobody closed the loop

    Jobs were marked done when the invoice arrived. Tenants were not told; owners found out at the monthly statement.

What we built

  1. Step 1

    Multichannel intake with AI triage

    Requests from any channel land in one queue. An LLM classifies the trade, severity and urgency, asks the tenant for a photo or clarification if needed, and flags emergencies (gas, flooding, lockouts) for immediate human attention.

  2. Step 2

    Rule-based dispatch

    Non-emergency jobs go to approved contractors by trade, area and rating, with the request, photos and access details attached. Contractors accept or decline from their phone; declines re-route automatically.

  3. Step 3

    Owner approvals inline

    Quotes above the owner’s delegated limit are sent for one-tap approval with the AI’s summary of the issue and the recommended option.

  4. Step 4

    Status to everyone, invoice to ledger

    Tenants and owners receive updates at each stage. Completed jobs trigger an invoice match against the quote and a posting to the trust accounting system.

The automation workflow

Maintenance request lifecycle

Tenant message to closed job

01

Request

Any channel

02

AI Triage

Trade, severity, photo

03

Dispatch

Approved contractor

04

Owner Approval

If above limit

05

Status Updates

Tenant and owner

06

Invoice Matched

Trust accounting

Step 1 of 6
6 steps · Fully automated
StackMake.comClaudeWhatsApp Business APIPropertyMeTwilioXero

Questions clients ask about this engagement

What counts as an emergency?

A list agreed with the client: gas smell, active flooding, no power, lockouts, security damage. These bypass automation and ring the on-call manager.

Can contractors refuse jobs?

Yes. A decline re-routes to the next contractor by rating and availability. Repeated declines lower a contractor’s ranking.

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Have a similar bottleneck?

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