Everlaw Clustering
Group millions of documents to see the big picture without needing a single keyword search.
Group millions of documents to see the big picture without needing a single keyword search.
Uncover the architecture of your data by turning it into an organizational map. Everlaw Clustering helps you separate the signal from the noise early in your case lifecycle, giving you a clear roadmap of where to focus your attention first.
Everlaw Clustering supports visualization of up to 25 million documents on a single screen, so you don’t waste time toggling between different views. Whether in early case assessment or full document discovery, Everlaw makes identifying and exploring vast data sets simple.
Understand your data at a global scale, with key visualizations of concept clusters and document relationships to find critical evidence. Effortlessly transition from a high-level overview of millions of documents down to the finest detail of a single page with the intuitive ease of a digital map, without switching tools or losing context.
Preserve relationships between documents, even across different clusters and zoom levels. Explore your evidence with a fluid user interface, allowing teams to identify key documents as they understand their data and construct more compelling narratives.
Seamlessly integrate core search and review tools directly into your visual map to uncover multidimensional insights. By overlaying Predictive Coding models, search results, and coding decisions in the same view, you can visualize the progress of your entire case and pinpoint critical evidence within even the most massive data sets.
Everlaw Clustering starts working the moment data is ingested, without someone having to build queries or define categories. Visualize documents in your data set by conceptual similarity, without requiring user input.
Find the evidence that manual review and keyword search are most likely to miss. Clustering lets you see documents at the highest levels, even across massive data sets, or zoom in to explore specific clusters, individual documents, and outlier evidence.
Competing software might take me a day to train the attorney. I can do that in Everlaw in less than 90 minutes.
Document clustering helps legal teams analyze discovery data by grouping documents based on conceptual similarity, so they can understand the shape of a data set without needing keywords, coding, or prior knowledge first.
Legal teams can use Everlaw Clustering to explore unfamiliar data, spot themes, find related evidence, prioritize what to review first, and QC review decisions across large discovery sets.
Everlaw Clustering uses AI to analyze document contents and organize them into concept-based groups. By exploring these clusters, legal teams can quickly identify major themes, topics, and relationships within their case materials.
Document clustering supports early case analysis by helping lawyers quickly see the major concepts, isolate potentially important themes, and narrow a large corpus into the subsets worth deeper review.