HIGHQ Contract Analysis: The AI-powered mending guru for legal experts


Founded in 2008, in Toronto, Ontario, Canada, Thomson Reuters is one of the world’s most trusted providers of answers, helping professionals make confident decisions and run better businesses. Their customers operate in complex arenas that move society forward — law, tax, compliance, government, and media – and face increasing complexity as regulation and technology disrupt every industry.


The HighQ contract analysis is a contract review and analysis software tool that uses machine learning to answer the specific questions legal professionals want to address.


A contract review is a thorough examination of a legal agreement before it is signed to ensure that everything stated in the document is clear and accurate. To sum it up, we can say that it is an extremely critical, time-consuming, and painful part of transaction or contract management. Here the new tool comes to the rescue. HighQ Contract Analysis is AI-powered and 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.


The AI-powered applications have three main features. These are mainly,

  • DATA- It is considered to be the key that runs everything. To train the machine-learning algorithms, data is necessary. In the case of Thomas Reuters, data plays a more important role, as the company serves mostly the data-driven industries. Taking an example of the legal industry we can say that it is data-driven, which implies that it is a collection of regulations, case laws, and other legal administrative opinions that collectively represents the data that attorneys and judges must research, analyze, interpret and reason over.


  • SUBJECT MATTER EXPERTISE- Subject matter experts play a crucial role in error analysis. They drive the generation of training data or learning sets and also validate the performance of machine-learning algorithms. They help the engineers and scientists in understanding the domain and data attributes that are responsible for errors, which drives subsequent iterations of algorithm tuning and development.


  • TECHNOLOGY- Technology drives solution design and development, including that in AI and machine learning. If we particularly look at the applications of Thomson Reuters, it requires designing robust and complex solutions that can deliver the target functionality at scale. For most of their applications, developing a solution is much more than simply applying an algorithm to a data set.

How does the AI-powered tool work?

  • HighQ Contract Analysis is built around legal domains, ranging from real estate leases and sales and services agreements and expanding to areas of intellectual property agreements and employment agreements.

  • For each of these domains, a practical law attorney editor develops a list of questions that reviewers might ask in a contract review exercise.

  • To start the review, the HighQ AI hub ingests the documents, classifies the contracts, and identifies essential facts like parties, deal value, language, and jurisdiction.

  • The tool's pre-trained domain then automatically extracts and retrieves defined terms and definitions from within the agreement. It divides the document into snippets, evaluates it against the reviewed questions, and returns the text that meets the criteria relevant to answering each question.

  • The users can further assess these answers, comment, annotate and assign risks in the document using its intuitive guided review. Users can also analyze their contracts in bulk as well as a single document.

  • Moreover, it allows the users to compare contracts to practical law standard documents.

“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 be vacant, and who is liable for things such as insurance and repair. This is fast, easy work for HighQ Contract Analysis.”


Sophisticated AI and integration


HighQ Contract Analysis provides an integrated experience, enabling customers to view and edit machine-learning extraction results, annotate documents and collaborate with teams – all within HighQ. Users can leverage HighQ collaboration, workflow, and visualization tools to conduct further analysis and generate reports on top of the extracted data.

Since the launch of this AI-powered tool, it has garnered a lot of praise from its clients.


It allows my team to be more mobile, more flexible, more agile, and more collaborative.”, said Seng Chan, General Counsel, Nisbets PLC. (Nisbets PLC is a British multi-channel retailer of catering equipment and supplies. It develops retails and distributes commercial kitchen equipment, catering supplies, and other hospitality products to hotels, restaurants, bars, cafes, schools, and colleges.)

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