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New Data Cleansing Capabilities to be Available at Relativity Trace

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Relativity, a provider of legal and compliance technology, will spotlight new data cleansing capabilities tied to Relativity Trace, an AI-powered communication surveillance tool.

Jordan Domash, General Manager of Relativity Trace, said, “Surveillance teams are overwhelmed by the number of false positives that their legacy surveillance system generates. This leads to hours of time stripped away from pinpointing risk and misconduct that actually matter because time is allocated to reviewing content that should never have been alerted on in the first place. Our team saw an opportunity to provide a solution to this widespread industry problem with email thread deduplication.”

Relativity Trace’s AI-powered data cleansing capabilities include deduplicating email threads in new emails, checking if they have already been analyzed, and preventing them from generating a second alert. Relativity has been investing in email threading capabilities in its e-discovery platform for over a decade and is now expanding this unique capability to communicate surveillance customers within Relativity Trace. With Relativity Trace, reviewers can improve accuracy and speed, and view all data cleansing for communication directly in the review interface, all the while maintaining transparency and defensibility.

Domash concluded, “Relativity Trace offers the most comprehensive capabilities to detect already analyzed email segments within an email thread. What sets Relativity Trace’s email thread deduplication apart from other tools is that it truly understands email segments and allows teams to visualize what’s already been reviewed. This is going to be a game-changing enhancement for our customers and significantly strengthen their ability to detect real risk, quickly.”

The data cleansing capabilities of Relativity Trace enable it to detect emails, electronic signatures, and confidentiality disclaimers. This prevents the system from generating alerts on duplicate or non-authored content, so reviewers will only see the portions of content made by the sender. The speed and accuracy of reviews are also boosted since reviewers can see what content was cleared.

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