Automated contract analysis and analytical tools are getting increasingly sophisticated, making transactional work more efficient and less lawyers centric.
Thomson Reuters today announced the launch of HighQ Contract Analysis. The product is a contract review and analysis tool that uses machine learning to answer specific questions from legal professionals and then spit out an easy-to-read report. The tool lets you ask such things as “What are the landlord’s maintenance obligations ?” or “Is there a mutual right to break?”
The announcement came as part of the first-ever Thomson Reuters Legal SYNERGY conference, a virtual event that includes product sessions, continuing legal education, and networking.
Here’s how it works: a contract is first downloaded into the HighQ AI Hub. The contract is then classified, and essential facts like parties, deal value, language, and jurisdiction are identified. The new HighQ Contract Analysis pre-trained models can then automatically extract and retrieve defined terms and definitions from within the agreement, divide the document into text snippets, evaluate every snippet against the review questions, and returns text that answers the questions. Users can then assess the answers, comment, annotate and assign risks in the document.
HighQ Contract Analysis also allows users to compare contracts to an identified standard
HighQ Contract Analysis also allows users to compare contracts to an identified standard, enabling reviewers to quickly identify non-standard terms, deviations, and additional risks.
“A typical use case would be for a buyer assessing a purchase of an office block, based in part on a review of all the contracts associated with the properties being purchased,” said Rawia Ashraf, vice president of Legal Practice and Productivity at Thomson Reuters. “The buyer needs to identify key risks, such as how much income is generated by these properties, what properties are likely to
