Cleary Gottlieb has been advancing the development of in-house e-discovery capabilities in the United States and Europe for more than 15 years.
Our e-discovery capabilities go beyond simply deploying off-the-shelf technology. We bring our trademark creative thinking and broad skill set to e-discovery problems, with strategies tailored to a client’s needs—whether that is quickly finding key evidence in a critical internal investigation, gaining litigation advantage over an adversary, designing a defensible investigation plan for regulators worldwide or reviewing contracts in an M&A matter.
Although we have honed our capabilities in document review and predictive coding methodologies, Cleary’s e-discovery group adds value throughout the full e-discovery lifecycle, from defensible preservation and collections, to designing and negotiating e-discovery protocols and litigating e-discovery disputes.
Our integrated global practice includes more than 80 full-time e-discovery professionals, three review centers and data centers in the U.S. and Europe. We choose our teams carefully, and our rigorous processes and training allow us to staff matters with multilingual attorneys who are as fluent in the relevant areas of law as they are in the review process. Cleary’s approach allows our team to absorb and implement globally innovations in the use of artificial intelligence, predictive coding and other advanced technologies as they become available.
In this evolving field, we employ a world-class e-discovery team that is at the forefront of technological developments and change, and the firm is dedicated to working at the leading edge.
Industry leader in the use of advanced technologies in document review and production in litigation, including use of predictive coding technology for our client in Rio Tinto v. Vale, where the judge found that it is now “black letter law” for courts to allow producing parties to use technology-assisted review.
Regular use of advanced analytics on large global company mergers in our U.S. offices to review and produce documents to the U.S. Department of Justice and Federal Trade Commission to comply with in-depth antitrust investigations (“second requests”).
Reduced a client’s costs by 97 percent and increased identification of privileged documents by 33 percent over traditional privilege identification methods by using algorithm-based privilege analytics to identify privileged documents within a dataset of 160,000 responsive documents.
Used advanced technologies in internal investigations and antitrust matters to analyze social networks to locate key documents.
Advised the internal counsel and compliance function for a large investment bank on development of in-house predictive analytics to identify potential future compliance issues.
Negotiated novel predictive review workflows with a regulator that both cut client costs and significantly increased accuracy of identification of relevant data over typical technology assisted review.
Implemented continuous active learning workflows on existing keyword search review populations to decrease client costs and increase efficiency of review by nearly 50 percent.
Created custom index of parsed client data to more effectively perform sentiment analysis on reactions to potential anticompetitive conduct by industry competitor.
Developed custom de-duplication solution and used advanced analytics to minimize EU-based data in scope for a U.S. merger investigation.
Analyzed several million documents to identify and develop processes to remedy data collection gaps resulting from corrupted date fields for an investment bank client and worked with client to develop and implement improved collection procedures.