---
title: "Give AI a property file so every tenant reply cites the right lease"
description: "Put each property's lease terms, rules, vendors, and owner limits in one file so Claude drafts tenant replies that cite the right property."
canonical: "https://scalewithsearch.com/articles/ai-for-property-managers"
date: "2026-01-28"
modified: "2026-09-25"
---
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# Give AI a property file so every tenant reply cites the right lease.

You manage six properties: three apartment complexes, two commercial buildings, and one mixed-use building. Each one has its own pet policy. Property A allows pets with a deposit. Property B allows no pets. Property C allows cats only, one per unit, with a deposit and monthly pet rent.

A tenant at Property C emails about pets. You ask ChatGPT for a reply. It writes: "Our property allows pets with an additional deposit and monthly fee. Contact the office for details."

That reply is wrong for Property C. It does not say "cats only." It does not give the one-cat limit. It says nothing about a request for an assistance animal. By the time you correct it, you could have written the reply yourself.

The model is not the problem. It has no record of which property the tenant lives in or what that lease says.

## Why a generic model gets property questions wrong

Property management is several jobs in one role: tenant communication, maintenance coordination, lease enforcement, vendor management, and owner reports. Each property changes the answer to each job.

The differences are concrete:

- lease terms: 12-month or month-to-month, pet rules, utilities included;
- maintenance vendors: HVAC, plumbing, landscaping, snow removal, pest control;
- property rules: quiet hours, parking, guests, amenity access;
- tenant population: students, families, professionals, retirees;
- owner expectations: report schedule, key numbers, approval limits.

Maintenance replies show the gap. Property A offers 24-hour emergency maintenance. Property B handles non-emergency requests within 48 hours. Property C accepts requests only through the tenant portal, not by email. A generic model writes "We will address your request soon" for all three. That sentence is correct for none of them.

## What the property file holds

The fix is one file per portfolio, with one section per property. You write each section once. Claude reads it before it drafts anything.

Use seven parts for each property:

1. Property registry: name, address, type, unit count, and owner contact.
2. Lease terms: standard duration, rent ranges, deposit rules, utilities, pet rules, and parking.
3. Property rules: quiet hours, guest policy, amenity access, and move-in and move-out steps.
4. Tenant overview: operational facts only, such as "Unit 105 is month-to-month."
5. Vendor directory: who handles each trade, how to reach them, the service agreement, and the response time.
6. Owner expectations: report dates, inspection schedule, approval limit, and contact preference.
7. Maintenance calendar: recurring work and upcoming inspections.

A synthetic section for one property looks like this:

```text
## Riverside Apartments (Property C)
type:: apartment complex, 120 units
owner_contact:: owner portal message for routine items, phone for urgent items
pets:: cats only, one per unit
pet_fees:: deposit and monthly pet rent per lease addendum PA-3
assistance_animals:: accommodation request under policy RA-1, not a pet request
maintenance_intake:: tenant portal only; email requests get a portal link
non_emergency_response:: within 48 hours
emergency_line:: 24-hour answering service
plumbing_vendor:: Anderson Plumbing, service agreement SA-11
entry_rule:: adult present, or written entry authorization from the tenant
owner_report:: monthly profit and loss by the 10th
owner_approval:: repairs above the limit in the management agreement
recurring:: boiler service each October; elevator inspection each March
```

Put amounts in the lease addendum and point to it. The file then carries one source for each fee, and a fee change happens in one place.

## Worked example: the pet policy reply

Without the file, you ask: "Draft a reply to this tenant about the pet policy." The model writes a generic paragraph about deposits and fees. The tenant still has no answer.

With the file, you ask: "Draft a reply to the tenant in Unit 407 at Riverside Apartments about the pet policy." Claude reads the Riverside section and drafts:

```text
Hi [tenant name],

Riverside Apartments allows cats only, with a limit of one cat per unit.
The pet deposit and monthly pet rent are in the pet addendum, which I have
attached. If you need an animal because of a disability, reply to this
email and I will send the accommodation request steps.

If you want to add a cat to your lease, reply to this email and I will
send the addendum for signature.

[your name]
```

The draft names the property's rule, the limit, the source of the fees, and the next step. You check it and send it.

## Worked example: the maintenance reply

You ask: "Draft a reply to this maintenance request about a leaking kitchen faucet at Riverside." Claude reads the vendor directory, the response window, and the entry rule:

```text
Hi [tenant name],

Thank you for the report about the kitchen faucet. I have sent the request
to Anderson Plumbing, our plumbing vendor for Riverside. They will contact
you to schedule a visit within 48 hours.

An adult must be home to let them in. If no one can be home, reply to this
email to give written permission for entry.

[your name]
```

Each fact in that reply comes from a line in the file: the vendor, the 48-hour window, and the entry rule. If the tenant had emailed instead of using the portal, the draft would add the portal link, because the file says so.

Entry notice rules come from the lease and from your state's landlord-tenant law. Put the rule that applies in the file. Do not let the model supply a notice period from general knowledge.

Assistance animal rules need the same care. HUD withdrew its 2020 assistance animal notice in September 2025, and state and local fair housing laws add their own rules. Get the current rule for each property's location from counsel. Put that rule in the file as policy RA-1, and let every draft cite it.

## Test the file with replies you already sent

Before you use the file on live requests, check it against answers you know are right. Pick three tenant emails from last month that you answered well. Choose one pet question, one maintenance request, and one parking or guest question, each from a different property.

Start a fresh session and ask for a reply to each one, with the property named and nothing else. Put each draft beside the reply you sent.

A draft passes when it cites the same rule, the same vendor, and the same response window as your reply. It fails when it uses another property's terms or invents a rule the file does not hold. A failure points to a gap in the file, such as a rule you apply from memory. Add that rule, and run the same three emails again.

## Keep tenant data to the minimum

The file lives on your computer. The content does not stay there during a session. Claude Code sends the text it reads to Anthropic's servers to generate each reply. Retention and training terms depend on your Claude plan. Write the tenant overview with that in mind.

Keep operational facts: unit number, lease type, lease end date, and whether an accommodation changes a procedure. Leave out Social Security numbers, bank details, screening reports, and medical information. For an assistance animal, record the approved accommodation and its terms. Do not record the tenant's condition. The [minimum-necessary test for client data](/articles/client-data-in-ai-agent-memory) gives a way to decide each field.

If you manage for several owners, keep each owner's properties in a separate folder. A draft for one owner then cannot cite another owner's terms. The pattern is in [separating business contexts for AI agents](/articles/separate-business-contexts-ai-agents).

## Set up the file in one afternoon

This is not property management software. It is a written record of what you already know.

1. Install Obsidian, which is free to download.
2. Set up Claude Code, which needs a paid Claude plan or an Anthropic API account.
3. Create a folder for the portfolio and a `CLAUDE.md` file at its root.
4. Add one section per property with the seven parts above.
5. Start Claude Code in that folder so it reads `CLAUDE.md` at session start.
6. Ask for three test drafts: a pet reply, a maintenance reply, and an owner report outline.
7. Compare each draft line by line with the lease and the vendor list.

Plan three to four hours for a portfolio of six properties. When you add a property, add its section. When a lease addendum changes, update the pointer and the rule on the same day. When a draft cites a wrong term, fix the file, not the chat, so the [correction reaches every later draft](/articles/corrections-become-system-memory).

## What stays with you

The file does not collect rent, schedule vendors, or enforce a lease. It removes the step where you re-explain lease terms, vendor lists, and property rules before each draft.

You still handle tenant relationships, vendor coordination, and management decisions. Every tenant message and every owner request goes out after your review. A repair above the owner's approval limit still goes to the owner first. For the review step itself, see [who approves what an AI agent sends](/articles/who-approves-what-an-ai-agent-sends).

This setup fits a manager with three to ten properties. It also fits a portfolio with several property types, or a solo operator with residential and commercial units. It fits less well when a property management platform already holds every rule in structured fields and your team drafts inside that platform.

----

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```
