iManage [1], the company dedicated to transforming how professionals work, today announced iManage Extract 3 [2], an enhanced version of its award-winning artificial intelligence (AI) data extraction application. Extract 3 uses RAVN AI technology to automatically read, interpret and extract key information from large sets of documents and other unstructured data to help organizations automate manual tasks, improve accuracy and reduce costs.
Key features in iManage [3] Extract 3 include:
- Rapid self-training: Users can train iManage Extract 3 to locate and analyze content from documents and datasets relevant to their specific needs, without dependence on AI experts. This enables organizations to deploy new data extraction applications rapidly enabling an agile approach to automating tasks across the enterprise.
- Re-use of previously created data models: Organizations can re-use data extraction models among departments to streamline multiple projects across the enterprise and reduce the cost of deploying advanced AI solutions.
- Seamless integration with other iManage RAVN AI products: iManage Extract 3 integrates with iManage AI products such as iManage Classify [4] to save organizations time and labor by automatically organizing large document sets into specific categories to further expedite the review process.
- Flexible deployment: iManage Extract 3 can be deployed in the iManage Cloud or on-premises to meet client security and information governance requirements.
“iManage Extract 3 delivers powerful automatic data extraction that addresses high-value challenges across the enterprise,” said Peter Wallqvist, VP of Strategy, iManage. “Organizations using Extract have increased efficiency and benefitted from more complete and higher quality data than those relying on manual data extraction. With Extract 3, different departments can quickly and easily harness this power to automate tedious tasks and gain new insights.”
To learn more, visit iManage Booth #506 at Legaltech New York 2018 [5], the largest legal technology event of the year. The event takes place January 30 – February 1 in New York.