Thomson Reuters launches AI-powered HighQ Contract Analysis
Thomson Reuters has launched HighQ Contract Analysis, a contract review and analysis tool that uses machine learning to answer the specific questions legal professionals want to address in an easy-to-read report. HighQ Contract Analysis uses machine learning and pre-trained models to help attorneys increase efficiency, reduce risk, and accelerate the contract-review process for transaction due diligence, compliance review and contract investigation. Integrating with HighQ, the company’s foundational asset in the collaboration and workflow automation market, the new tool extends customers’ transaction workflow with richer insights and greater automation.
“AI-powered applications require three key ingredients—data, subject matter expertise and technology?and HighQ Contract Analysis builds upon Thomson Reuters decades-long leadership in AI-driven products for legal professionals,” said Andy Martens, head of Research Products at Thomson Reuters. “HighQ Contract Analysis begins with the deep knowledge of Practical Law editors who use their expertise to develop proprietary contract review templates specific to legal domains, and then leverages the work of AI experts at Thomson Reuters Labs to train and validate its machine-learning models. The result is a highly tailored, guided review that saves our customers’ time and costs, and improves the accuracy and insights of the contract review process.”
HighQ Contract Analysis is built around legal domains, beginning with real estate leases and sales and services agreements and soon extending to other areas, including intellectual property agreements and employment agreements. For each domain, Practical Law attorney editors develop a list of key questions reviewers might want to ask in a contract review exercise. For example, the tool can find answers to questions such as, “What are the landlord’s maintenance obligations?” or “Is there a mutual right to break?”
To kick off the review, the HighQ AI Hub ingests the document, classifies the contract, and identifies essential facts like parties, deal value, language and jurisdiction. The new HighQ Contract Analysis pre-trained domain models 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 meets the criteria relevant to answering each question. Its intuitive Guided Review interface allows users to assess those answers, comment, annotate and assign risks in the document. Users can analyze contracts in bulk as well as review a single document. HighQ Contract Analysis also allows users to compare contracts to an identified company standard or Practical Law standard documents, enabling reviewers to quickly identify non-standard terms, deviations and additional risks.
Later this year, Thomson Reuters says, HighQ Contract Analysis will also release its AI Model Trainer, which will provide an end-to-end process to manage, re-train, and evaluate the machine-learning data models to refine their analysis of a user’s own contracts. Longer term, users will be able to define their own models, managing the questions and facts to match their, and their client’s, expectations.
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