Cortical.io today announced new releases of solutions that improve document processing speed, accuracy and usability for the most challenging business documents, messages, and attachments.
Contract Intelligence 4.6
Contract Intelligence 4.6 automatically and accurately searches, extracts, classifies and compares key information from agreements, contracts, and other business documents like insurance policies and financial reports. Contract Intelligence uses a unique Natural Language Understanding (NLU) approach to analyze relevant information from a document quickly and accurately. It achieves at scale what is difficult for manual labor or other contract analysis tools. The new version models relations between extractions, and includes performance and scale improvement. It also has a newly refined user interface for ease of use.
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Message Intelligence 2.4
Message Intelligence automatically and accurately classifies and processes messages, attachments, and unstructured text based on meaning. When leveraging models built with Contract Intelligence, it also extracts and can leverage information buried in messages, attachments, and unstructured text. The new version contains explainable AI-supported classifiers, improved handling of messages and attachments, high availability, and an enhanced dashboard.
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“Intelligent document processing is increasingly important to create operational efficiencies in business processes that need to extract information from semi-structured and unstructured data for further analysis,” according to Gartner®. “These processes currently are majorly human-centric.”*
There are a wide variety of vendors offering IDP solutions. Most focus on structured documents such as forms or semi-structured documents such as invoices. What sets Cortical.io apart is its ability to deal with unstructured documents such as contracts, insurance policies, proposals, leases, emails with attachments, social media posts, etc. with both high accuracy and speed. It is due to Cortical.io’s semantic technology, which is based on a unique approach to NLU called Semantic Folding. Because the approach understands the meaning of text, it is highly accurate, and can be trained to meet a company’s specific needs with little training data.