Using AI to Analyze Rental Leases and Uncover Hidden Risks

The author analyzed around 100 rental lease agreements using AI and found common patterns like hidden fees, clauses allowing landlords to change conditions, automatic renewal terms, and early termination penalties. The article discusses how lease agreements are often long, written in legal language, and not designed for clarity, creating a gap between what people sign and what they understand.

Details

The author decided to test using AI to analyze rental lease agreements, as most people don't fully read their leases due to the complexity of the legal language and length of the documents. After running around 100 leases from different U.S. states through an analysis system, the author found consistent patterns of hidden or poorly explained fees, clauses allowing landlords to change certain conditions, automatic renewal terms buried in the contract, and early termination penalties that can be costly. While these may not be illegal, they are easy for renters to miss. The author argues that lease agreements are designed to be long (often 30-50 pages) and written in complex legal language, creating a gap between what people sign and what they actually understand. Natural Language Processing (NLP) can help address this by extracting key clauses, simplifying the language, highlighting potential risks, and providing contextual understanding - especially when combined with state-specific knowledge. To explore this further, the author built a tool called GoLeazly that allows users to upload a lease, get a risk score, identify clauses worth reviewing, and understand the contract in plain English. The goal is to help renters better understand what they're signing, not to replace legal advice.