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The LawGeex AI was trained on tens of thousands of NDAs, using custom-built machine learning and deep learning technology. The machine was trained based on an exclusive corpus of documents that presented the LawGeex algorithm with a variety of examples, which allowed it to distinguish between different legal concepts. This level of technology for analyzing legal documents has only been possible with advances in computing over the last five years. Computers convert the text into a numeric representation. The image below is a visualization of how computers read the text. Each dot represents one paragraph in the semantic space. The different colors shown represent different legal issues. Pink dots, for example, represent samples of non-compete issues, and purple ones represent governing law sections. Training an AI engine is similar to training a new lawyer – exposure to different examples is crucial in developing a deep understanding of the legal practice. This research arrives as we have seen an explosion of legal AI.
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