A mid-tier London law firm was managing a matter involving a data set of approximately 100,000 documents requiring first-pass review.
The team initially relied on a conventional linear review approach. A group of 10 human reviewers began analysing the data set using standard workflows including keyword searching, file type filtering, image identification, email threading, and deduplication. Basic analytics were applied to prioritise documents, but the process still required reviewers to manually assess a large proportion of the data set.
Despite these efforts, the review quickly became difficult to sustain.
With approximately 83,000–84,000 documents still remaining, the projected timeline for first-pass review was around four weeks. Estimated costs were roughly £70,000, excluding the additional oversight that would likely be required from a review manager.
The process was also highly resource intensive. Reviewers were spending most of their time manually scanning documents rather than focusing on higher-value tasks such as issue analysis or privilege review. The workflow also lacked flexibility – making it difficult to adapt if new data appeared or deadlines accelerated.
Recognising the timeline was becoming unattainable, the firm approached Array for assistance.