AI for Property Management
AI for property management: every property's numbers, without the spreadsheet marathon
I build finance and operations systems for multi-location property operators. One live dashboard across every location, month-end packets that build themselves, and occupancy next to the numbers it drives.
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Where property operators lose the most time
Month-end close means exporting the general ledger and reconciling it in Excel, one property at a time
Nobody can say which property is behind budget this month, or why, without a day of spreadsheet work
Occupancy lives in one system and financials in another, so nobody sees them side by side
What Gets Built
What AI for property management looks like in practice
Most of the time a property team loses goes to the same few jobs: pulling reports, checking the ledger, building the close, and chasing occupancy. These four systems take those jobs over. They sit on top of the software you already run, so nothing gets replaced.
Live P&L dashboard across properties
Every location's P&L in one place: revenue and NOI against budget, month-over-month variance flags, a six-month trend, run-rate projections for partial months, and a plain-English AI summary for each location when new data lands.
GL exports that load themselves
The accounting system (Yardi, in the build below) already emails daily general ledger exports. A watcher picks them up and loads them into the dashboard. Nobody downloads, renames or forwards a file.
Month-end packets per property
A close packet for each location, built from the same data: income statement against budget, balance sheet, cash flow, AR and AP aging, and occupancy. Delivered as a PDF and an Excel workbook.
Occupancy next to the financials
Occupancy pulled daily for every location, backfilled for prior months and locked automatically at month end, so the close numbers don't drift.
A Real Build
25N Coworking: five locations, one dashboard
25N runs five coworking locations across the Chicago and Dallas-Fort Worth metro areas. The finance team was reconciling general ledger exports in Excel location by location, with no single view of occupancy or how each location stood against budget.
I started with a competitive analysis for the leadership team, delivered 9 hours after kickoff. Then I built the finance side: a live dashboard fed from the daily GL exports their accounting system already sends, a rules-based GL check that flags problem entries before the close, a month-end financial packet for each location, and occupancy pulled daily. The finance team reviewed every round, and their feedback went straight back into the build.
What Was Delivered
- ✓Live financial dashboard rolling up all 5 locations, refreshed daily
- ✓GL check that flags entries breaking per-account rules before the close
- ✓Automatic ingestion of the daily GL exports the accounting system already emails
- ✓Month-end financial packet per location, in PDF and Excel
- ✓Daily occupancy tracking with historical backfill and month-end lock
How I Help
Start with a free audit, then a scoped build
Free AI Audit
Free · Delivered in minutes
For when you know the reporting eats your team's week but don't yet know what to automate first.
Get your free AI audit →Finance Dashboard + Close Automation
Scoped to your properties · Priced per project
For when the close eats days every month and you want every property's numbers in one place.
See client work →Want to talk it through first? See how I work as an AI consultant for small business, or read about AI for coworking spaces.
FAQ
Questions about AI for property management
What does AI for property management actually do?
It takes the repetitive finance and reporting work off your team. For a multi-location operator that means pulling accounting data in automatically, flagging GL entries that look wrong before the close, and building the month-end packet for each property. It also writes a plain-English summary of what changed at each location, so you read that before you open a spreadsheet.
Do we have to switch from Yardi or our current software?
No. The build reads what your systems already produce. In the engagement on this page, Yardi kept running exactly as before, and the dashboard picks up the GL exports it already emails every day.
Have you built this for a real estate operator?
Yes. 25N Coworking runs five locations across Chicago and Dallas-Fort Worth, and I built their finance dashboard, GL check, month-end packets and occupancy tracking. Coworking is my deepest real estate work so far, so it's the example on this page.
Where should a property manager start with AI?
Start with the free AI audit. It scores your business on five areas and ranks automation ideas by estimated annual savings. You'll know where the biggest opportunity is before you spend anything.
Is our financial data kept confidential?
Yes. Dashboard access is limited to named logins, and your data is used only to produce your deliverables. I don't share client information with third parties.
About
Who's behind the analysis
Founder
Max Wexley
New York City
I'm a finance analyst by day and a builder by night. I built Wex Advisory because competitive intelligence was either out of reach for small businesses (locked behind $10,000 retainers) or too shallow to be useful.
Every report I deliver is one I'd want to receive myself: specific, actionable, and grounded in real data, not guesswork. The goal is simple: give growing companies the same quality of insight that larger competitors take for granted.
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