A boutique litigation firm encountered an atypical matter with an enormous dataset that required rapid assessment. Instead of validating coding at scale, the team needed to pinpoint a handful of key documents that could shape litigation strategy. The dataset included over 104,000 documents promoted to review. Tight deadlines eliminated the possibility of a prolonged, traditional review process and, with nearly 70,000 excluded from AI eligibility, we needed a multi-pronged approach that would address the varied datatypes.
Sandline leveraged Relativity’s Air for Review to accelerate early document analysis. Our team iterated GenAI prompts and refined search logic to surface clusters of potentially significant materials—without reviewing tens of thousands of records line by line. AI review narrowed 34,643 documents into focused categories such as “relevant,” “borderline,” and “not relevant,” while targeted sampling quickly validated results. The 70,000 documents excluded from AI were sampled and searched through traditional means to ensure key substance was unearthed. We used the insights gained from the documents found through our AI workflow and applied similar terms for searching across the AI-ineligible set of documents. This hybrid approach enabled the client to concentrate on substance instead of process.
The approach delivered what mattered most: uncovering the right documents at the right time. Within days, the client had a defensible, organized subset of information that guided next steps in litigation strategy. By applying GenAI-assisted review intelligently, Sandline transformed a weeks-long manual process into a streamlined, strategic workflow that saved significant time and cost while meeting an expedited timeline. GenAI allowed us to become subject matter experts in quick order, allowing us to zero in on hot documents faster than by traditional means alone.