Property Expense Review AI

Inspiration

Reviewing property expenses manually can take a lot of time, especially when comparing repairs, maintenance, supplies, and other operating expenses across different periods.

I wanted to build a simple AI-assisted expense review tool that could make this process faster and easier.

What it does

Property Expense Review AI helps users review property expense data and identify items that may need further attention.

The goal is for users to upload expense or general ledger data, then use explainable review rules to:

• identify unusually high expenses
• detect possible one-time expenses
• organize expenses by category
• highlight items that may require follow-up
• generate simple questions for further review

How I built it

I used AI-assisted coding tools to help define the project scope, organize the requirements, and build the application step by step.

Instead of starting with a large accounting system, I focused on one specific workflow: reviewing property expenses and identifying transactions that deserve attention.

Challenges I ran into

One challenge was deciding what should count as an "unusual" expense.

A large expense is not always a problem. For example, a repair may be unusually high because it was a one-time project rather than a recurring operating expense.

This means the tool needs to provide useful context instead of simply flagging every large transaction.

What I learned

I learned how to turn a real-world problem into a smaller software project and how to work with an AI coding agent to plan, build, and test an application.

I also learned that defining the problem clearly before coding makes it easier for AI tools to produce useful results.

What's next

Next, I would like to add:

• year-over-year expense comparisons
• support for multiple properties
• automatic categorization of transactions
• AI-generated follow-up questions
• exportable expense review reports

Built With

• codex
• css
• csv
• github
• html
• javascript