Our client, a global construction and engineering company, faced uncertainties relating to cost and scope of effort after receiving a third-party request for documents. The potential for expanding data volumes and rising production requests meant that the cost and timeline associated with manual review was prohibitive – even with an in-house review team.
The matter was a prime candidate for the application of TAR. The client also needed a consultative partner, as they anticipated the potential for additional incoming data. Epiq proposed a solution which was able to scale with expanded data volumes, that also utilised our extensive eDiscovery capabilities, which included processing, hosting, TAR and analytics consulting, and managed review services.
The Epiq TAR consulting team engaged the client from the outset of the case. From citing case law supporting predictive coding, to providing demos of the tools, Epiq outlined the workflow and illustrated the nuances of best practice. Epiq then executed a client-driven proof-of-concept exercise to train the predictive model on a small sample set of client documents. An in-house subject-matter expert successfully trained the predictive coding tool and it was agreed upon to go ahead with the larger data set, further reducing review time and costs.
Epiq significantly reduced the amount of human review required and helped the client acquire substantially more data after initial setup with little additional effort. In total, Epiq helped the client reduce the human review population from 2.1 million documents to 152,000 documents.