Most people don’t fully read their lease agreements.
Not because they don’t want to — but because they’re hard to understand.
So I decided to test something:
👉 What if we analyze leases using AI?
Over the past few weeks, I ran around 100 rental lease agreements from different U.S. states through an analysis system.
The results were surprisingly consistent.
Common Patterns Across Leases
Here’s what kept showing up:
Hidden or poorly explained fees
Clauses allowing landlords to change certain conditions
Automatic renewal terms buried deep in the contract
Early termination penalties that can cost thousands
None of these are necessarily illegal.
But they are very easy to miss.
The Real Problem
Lease agreements are:
long (often 30–50 pages)
written in legal language
not designed for clarity
This creates a gap between what people sign and what they actually understand.
Why AI Makes Sense Here
Natural Language Processing (NLP) can:
extract key clauses
simplify legal language
highlight potential risks
provide contextual understanding
Especially when combined with:
👉 state-specific knowledge
What I Built
To explore this further, I built a small tool called GoLeazly.
It allows users to:
upload a lease
get a risk score
identify clauses worth reviewing
understand the contract in plain English
The goal isn’t to replace legal advice —
but to help people understand what they’re signing.
Most renters aren’t careless.
They just don’t know what to look for.
Question
How do you usually review a lease before signing?
Do you read everything — or just trust it’s standard?