Consilio, a Symphony Technology Group (STG) company and global leader in eDiscovery software and services, today reported a dramatic increase in the use of advanced analytics tools in its Global RPM review platform, including tools such as predictive coding, conceptual search, near duplication, email threading, and conceptual indexing.
More than 90 percent of Consilio clients are using one or more of these advanced analytics technologies in their cases today, up from less than 50 percent just one year ago.
“The increased focus on predictive coding and our other advanced analytics tools is both exciting and expected,” said Andy Macdonald, CEO of Consilio. “Our clients all over the world are increasingly interested in creating defensible workflows with these text classification technologies, including civil law jurisdictions in continental Europe and Asia that are less familiar with linear review models. Since the launch of Global RPM® version 5 early in 2012, we’ve seen a significant migration of clients who prefer to use these advanced analytics capabilities, to improve accuracy and lower cost.”
Consilio’s advanced analytics tools hold several advantages for clients:
“We continue to see data points that suggest predictive coding and advanced analytics will be embraced on a global basis,” said Macdonald. “U.S. court systems and regulatory agencies have been influential in raising awareness and acceptance of predictive coding. In Europe and Asia, where large-scale eDiscovery and document review are still evolving, our clients are eager to explore different ways to reduce the exponential increase in data volumes. It was important for us to develop our capabilities to be fully ready for this wave of global adoption. ”
“Our predictive coding technology differs from others available today in that our engine will report back on specific documents within the training set it believes the reviewers have miscoded,” said Pete Feinberg, Vice President of Products at Consilio. “Furthermore, the technology leverages dynamic parameter optimization, automatically tuning the models to the unique complexities of the documents in each review, which results in fewer iterative cycles needed to reach the desired recall and precision goals. Because of this, we’re able to help clients achieve their desired recall and precision rates in less time and with less cost.”
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