Real EstateComplex automationSeveral jobs working together: multi-stage pipelines with state, branching on rules or AI decisions, approvals or escalations, 4+ systems, AI agents that act, or reconciliation across sources. Usually rolled out in stages.

Applications screened before the competition calls back

For: Letting agency handling 80 move-ins a month

Typical impact

Screening: 5 days down to 6 hours

Letting agencies handling eighty move-ins a month can take five days to screen each applicant, and the best tenants sign elsewhere. Document collection, credit and background checks, scoring and decision letters run in one Make flow, typically cutting screening to six hours.

Typical results

80

Move-ins handled monthly

-75%

Applicant drop-off

0

Checks missed

Figures reflect typical results for this kind of automation.

The challenge

Good applicants apply to three properties at once, and the fastest yes wins. The agency's screening meant emailing for documents, waiting days for replies, manually ordering credit checks, and passing files between three staff members. Five days later, a quarter of approved applicants had already taken a flat somewhere faster.

Before and after

Before With the automation

Screening turnaround

−95%
120 hours
6 hours

Applicant drop-off

−75%
24%
6%

Staff time per application

−86%
3.5 hours
0.5 hours

The automation

We built an end-to-end screening pipeline in Make. A submitted application immediately opens a document checklist — ID, payslips, references — with automated WhatsApp chases for anything missing. The moment the file is complete, credit and background checks fire via API, and the results are scored against the agency's rubric. Clear passes get an approval letter automatically, clear fails a polite decline, and only borderline cases wait for a human decision.

How it works

  1. 01

    Application in

    The applicant's submitted form kicks off the screening flow instantly — no queue, no inbox.

  2. 02

    Documents collected

    A checklist requests ID, payslips, and references, with automated WhatsApp chases for gaps.

  3. 03

    Checks run

    Credit and background checks fire via API the moment the document file is complete.

  4. 04

    Rubric scored

    Results are scored against the agency's rubric; only borderline cases route to a human.

  5. 05

    Decision out

    An approval or polite decline letter generates and sends, with the full file archived against the tenancy.

Starts from

  • Rental application
  • Applicant documents

Delivers

  • Credit & background checks
  • Rubric score
  • Automated decision letter

The impact

Screening turnaround typically falls from five days to six hours, and applicant drop-off from a quarter to about six percent. Staff time per application shrinks from three and a half hours to thirty minutes, and units fill before competitors have even replied.

Questions about this automation

What starts the screening process?

A submitted rental application starts it immediately. The applicant receives a document checklist for ID, payslips and references, and anything missing is chased automatically over WhatsApp. Staff do not need to open an inbox or email the applicant, and the file shows at a glance which documents are still outstanding.

How are credit and background checks handled?

Once the document file is complete, credit and background checks are requested through the providers' APIs without anyone ordering them by hand. The results return to the applicant's file and are scored against the agency's own rubric, which sets the thresholds for income, references and credit history.

Does the automation make the final decision on every applicant?

Only clear cases are decided automatically: a clear pass generates an approval letter and a clear fail a polite decline. Borderline scores go to a staff member with the full file attached. This is a multi-step build, usually rolled out in stages, starting with document collection and adding checks and letters after.

Real Estate

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