Contract Intelligence with Semantic Search is The Future of Work

AI-based Contract Intelligence with semantic search improves contract management workflow, significantly reducing the time it takes to review contracts and providing an increased level of accuracy. (Graphic:

One of the major definitions of the future of work is enlisting AI to make people more productive.

Spell-check is something we take for granted – could you imagine a world without it? We can – and its a world filled with either an abundance of errors or a lot of expense to hire proofreaders.

Spell-check was once limited to word processing apps but it’s in the browser now, meaning all applications benefit from it.

Likewise, think of AI being sprinkled throughout our workday, in all of our apps, making us more productive and efficient. A world with smarter decisions and better outcomes. Our ability to spot trends and make decisions based on a future we can more clearly predict should excite every business leader.

This is why we were impressed with the news just launched a new release of Contract Intelligence, an AI-based solution for enterprises that need to review and manage a large corpus of contracts and other legal documents. Contract Intelligence utilizes its patented natural language understanding (NLU) approach to automatically and quickly extract, classify and analyze relevant information in documents with a degree of accuracy that is difficult to achieve with manual labor or with other automation tools. Contract Intelligence 4.0 now incorporates semantic search functionality, which enables the search of an entire database or individual documents with a meaning-based approach to find items with similar meanings even if the wording is different.

Thomas Reinemer, COO of

Last October we broke the news and Xilinx Bring NLU Supercomputing to Enterprise Apps and today’s news builds on this trend of bringing more advanced intelligence into the workplace.

“Contract analysis and review has remained a time-consuming and painstaking undertaking for these organizations,” said Thomas Reinemer, COO of “Now we can meet their challenge by providing a more efficient AI-based solution that provides a faster time and minimal effort to train the system to handle new documents, as well as quicker and easier customization of models, with higher accuracy and recall than other solutions.”

Since it was first introduced in 2017, Contract Intelligence has been vetted and implemented by some of the leading insurance, banking, accounting and management consulting firms. It has been found to provide up to an 80% reduction in manual review and data extraction time along with reduced processing costs.

Profile photo of Tim Harper
Tim Harper, AVP, Benefits Operations, Unum

Unum, a leading employee benefits provider, is currently in the process of putting Contract Intelligence into full production to automate and increase the efficiency and quality of workflow in insurance quoting. 

“The solution is uniquely suited to the challenges of large-scale document search and analysis. During our pilot program with, we saw a reduction in the time it takes to review contracts with an increased level of accuracy that enables Unum to deliver more timely and higher quality quotes to our brokers and customers” said Tim Harper, AVP, Benefits Operations, Unum.

Other new features in Contract Intelligence 4.0 are integration with other Business Intelligence solutions, increased administrative ease and workflow improvements.

These include:

  • A dashboard to enable specialists to manage and track the review progress.
  • Task assignment for specialists to assign documents and annotation or review tasks to individual subject matter experts.
  • Built-in OCR capabilities to detect scanned pdf files and convert them into machine-readable files capable of being annotated.
  • Sophisticated table extraction to parse and extract information from tables regardless of the row/column format in the PDF document.
  • Active assistance that includes inline messages pop up to guide users when creating new annotations.

“We’ve really focused on giving enterprise Subject Matter Experts (SMEs) control over their processes, versus a need to have AI experts that remain a scarce commodity in most enterprises,” Reinemer noted.

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