Exigent launches AI-powered contract management system for speed to smart data

Exigent, AI-powered contract management system, smart data, AI
Exigent launches AI-powered contract management system for speed to smart data

Legal technology provider, Exigent, has released the latest update to its Contract Management Solution to include AI-based auto-extraction and contextual search for increased speed to data, accuracy and business impact. Exigent’s AI auto-extraction tool, Scarlett, is powered by a machine learning engine set up and trained by legal professionals, financial experts, and data scientists, creating faster and more accurate outcomes.

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Using Exigent’s new CMS automates the once costly, slow and error-ridden manual extraction and input of contract data. The solution extracts smartly selected business and legal terms quickly, automatically placing them into a data lake and making key data accessible at all times in a universal format. All extracted information is then aggregated on dashboards or included in easily buildable reports in seconds. Scarlett has unlimited applications across many industries and departments: the tool can be used by legal, procurement, and other departments across an organization to auto-extract and structure data for powerful, customized analysis. Information is aggregated and used to review and enhance performance, as well as predict business outcomes. Scarlett’s power is already being used by Exigent’s clients for more efficient contract review, to tackle LIBOR transition and for compliance in general (GDPR, POPI, CCPA  and any other clauses that need attention in a contract).

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The new search functionality provides more than just traditional keyword searches. Designed to look for patterns around the words searched to give them meaning in context, the solution not only uncovers relevant phrases, sentences and paragraphs in a document that would otherwise not be discoverable, it also delivers results in just milliseconds. This leads to speed to answers, reducing the risks associated with not having a central repository and eliminating missed documents and time-consuming manual searches for relevant information.