NSF Award
1721878
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to render the tedious, time-consuming, and expensive manual process of contract review and negotiation as archaic. The outcome from the proposed research will accurately review and negotiate in-bound contracts based on a user's history of reviewing and negotiating just a handful of similar contracts and will result in (a) a 50-90% reduction in companies' contract review and negotiation time and (b) standardized risk across all contracts within an organization. Furthermore, the proposed research will provide small and medium-sized businesses with the ability to afford and obtain the same quality of legal review of in-bound contracts as the largest and most sophisticated companies in the world. <br/><br/>This Small Business Innovation Research Phase I Project will develop the first system to automate edits in contracts through semantic sentence alignment with deep learning techniques. The proposed research will expand upon state-of-the-art methodologies for unsupervised learning of distributed representation of various length text segments and then launch the first and only machine learning platform that automates contract review and negotiation with semantic editing capabilities.
