Extracting clauses from legal documents is a complex task that requires an understanding of the legal domain and its technical language. Machine learning and natural language processing (NLP) programs are used to understand the meaning of clauses and classify them. The most commonly used language model in the legal domain is the FILAC model, but it has limitations and does not help with crafting arguments or understanding more about the case. To overcome these limitations, the team at 1000ML developed a better classification system.