Case Study: Fortune 500 Tech Company saves $700,000 on privilege review with Text IQ

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A Fortune 500 tech company faced an upcoming wave of litigation that would require reviewing hundreds of thousands of documents, with privilege review expected to be the most time-consuming and expensive part of the process. Traditional methods using contract attorneys were costly, slow, and prone to inconsistent errors and false positives, so the company looked for a better way and turned to Text IQ.

Text IQ provided its AI-powered privilege review solution, using unsupervised machine learning and its Social Linguistic Hypergraph to identify privilege based on context, relationships, and company language. In the company’s first 900,000-document matter, Text IQ identified 18 previously unknown attorneys, surfaced more than 5,000 privileged documents that search terms would have missed, and saved more than 20,000 attorney hours. The result was a 2-week review instead of 13 weeks, a $700,000 net savings on the matter, and an estimated $900,000 reduction versus traditional review.