Data Visualization and Clustering

February | 2024

Welcome to our "AI Insights," where we aim to unravel the mysteries of AI and delve into its intrinsic value. In this edition, our focus is on Data Visualization & Clustering.

Data visualization and clustering technology, powered by AI, uncovers patterns in document content and groups them into clusters. This type of technology mirrors our everyday experiences, seen in apps and websites suggesting purchases or songs using AI.

Utilizing Clusters to Discover Relevance

The technology seamlessly categorizes similar documents, displaying the data in dynamic clusters. Subsequently, you can perform searches on these interactive clusters. The analytics index identifies similarities, continuously refining and reanalyzing groups based on your search criteria. Users can then reevaluate and redefine search criteria and clusters, facilitating strategic decision-making and providing the flexibility to dig deeper into data clusters to discover relevance.

Outside Counsel & In-house Case Teams Working Together

In traditional workflows, Outside Counsel will lead review strategy, craft search terms, and negotiate results with Opposing Counsel, while in-house case teams typically assume a passive role. PLUSnxt, however, incorporates data visualization and clustering into all RelativityOne cases, streamlining this process. This technology organizes data into interactive clusters, allowing users to refine searches and strategically make decisions.  Unlike the traditional approach, where in-house counsel often stays detached from the search strategy and results, PLUS encourages participation and collaboration from in-house teams throughout the process.

In the PLUS approach, a collaboration between outside counsel and in-house case teams is beneficial. Rather than relying on arbitrary adjustments or deletions of keywords to achieve a lower document count, PLUS emphasizes a more meaningful strategy. By leveraging cluster analytics that considers content relevance, the focus shifts from mere hit counts to a deeper understanding of the data's significance. This collaborative and informed approach ensures a more accurate and purposeful eDiscovery process, where search terms align with the meaningful context of the data.

With clustering and data visualization, case teams can actively participate in analyzing document clusters and offering feedback, including identifying relevancy and potentially privileged documents. This process enables a more focused approach than search term reports, allowing for interactive refinement and tagging to prioritize documents. This feedback can include identifying irrelevant content, pointing out unrelated materials, or confirming the relevance of specific documents. This strategic feedback loop empowers the case team to actively collaborate with in-house counsel, contributing to improved results.

Evolving towards Efficiency

Although it may require a shift in the typical workflow, the benefits are substantial. Leveraging data visualization and clustering technology saves time and enhances document review efficiency. PLUS integrates these tools into every project, making it an integral part of our standard operating procedure. By offering this as part of our RelativityOne instance, PLUS aims to empower clients to utilize these advanced capabilities for more efficient and effective results.

Our automated workflows and analytics index are systematically activated for every new workspace, reflecting our commitment to efficiency and a streamlined approach. We encourage clients to utilize these features based on our successful track record with law firms and corporate clients who consistently return to PLUS, aiming to achieve the same success on more projects.

Learn "AI Insights" from PLUSnxt