ContractNerd: An AI Tool to Find Unenforceable, Ambiguous, and Prejudicial Clauses in Contracts
Contractual agreements often contain clauses that are unfair, creating unjust suffering in one party to the agreement. ContractNerd leverages advanced Large Language Models (LLMs) to analyze contractual agreements and identify issues across four categories: missing clauses, unenforceable clauses, legally sound clauses, and legal but risky clauses. By using a structured methodology that integrates LLM-based clause comparison, enforceability checks against jurisdiction-specific regulations, and assessments of risk-inducing traits, ContractNerd provides a comprehensive analysis of contractual terms. To evaluate the tool’s effectiveness, we compare its analyses with those from existing platforms on rental clauses that have led to court litigation. ContractNerd’s interface helps users (both drafters and signing parties) to navigate complex contracts, offering actionable insights to flag legal risks and disputes.
Authors
- Dennis E. Shasha (ORCID: https://orcid.org/0000-0002-7036-3312)
- Haowen Yuan
- Musonda Sinkala
- Yuge Duan
Institutions
- Courant Institute of Mathematical Sciences (US)
- New York University (US)
Publication Details
- Journal
- Electronics
- Published
- 2025-10-28
- DOI
- https://doi.org/10.3390/electronics14214212
- Primary Topic
- Artificial Intelligence in Law
- Type
- article
- Field-Weighted Citation Impact
- 0.00