The sheer volume of potentially relevant electronically stored information (ESI) in companies and government organizations challenges any organization to understand the costs of e-discovery and prepare for each step of litigation. Even with data already in litigation hold and through a first pass filter there can be a tremendous volume to sift through, leaving many uncertainties.
The question then becomes this: How do you extract the information you need in order to understand the potential costs of a full review without undertaking a full review — and still be prepared for a Rule 26 meet and confer?
iReview Analytics™ is our early case assessment (ECA) tool that gives you the insight you need to be prepared. iReview Analytics utilizes a new class of technologies known as “Text Analytics”, to transform large volumes of unstructured data, such as documents, emails, and publications, into relevant, actionable information. Text Analytics automate most of the human activity traditionally associated with ECA to understand, organize, prioritize and retrieve information from large sources of unstructured data.
iReview Analytics provides advanced Conceptual Search functions based on Latent Semantic Indexing. This search technology enables iReview Analytics to acquire all its search intelligence from the actual documents being indexed. Unlike other solutions, iReview Analytics does not require external dictionaries or thesauri. It works across foreign languages, even searching – and finding – relevant documents in different languages –without prior translation.
iReview Analytics returns to you an analysis of your data that identifies key concepts, categorizes those concepts and then provides you the ability to sample the documents based on the most relevant categories. This early case assessment gives you the information you need to understand costs and prepare for Rule 26 meet and confer at a fraction of the cost of a full review.
iReview Analytics™ Capabilities:
Concept Search – Using advanced mathematic formulas to allow users to find similar, related, and relevant documents based purely on the concepts those documents are discussing – without using keywords, and without retrieving “matching, yet irrelevant” content.
Categorization – Allows users to define categories by means of examples. Based on the exemplars, iReview Analytics automatically categorizes incoming documents.
Instant Context (Contextual Explanation) – Helps users understand unfamiliar terminology. The user clicks on an unfamiliar term and iReview Analytics highlights similar terms found in related text.
Language Analytics – Within any single language, iReview Analytics can be applied to any topic, vocabulary or language that can be represented in the Unicode encoding system. In a cross-lingual mode, users can submit queries in English while searching documents in other languages.
Summarization – Automatically identifies sentences in a document that best represent key concepts, and uses those sentences to give users a quick summary of the entire document.
Dynamic Clustering – Allows a user to point iReview Analytics to a set of documents and then allow iReview Analytics to dynamically group conceptually-similar documents together in a tree-type hierarchy and finally, to apply a descriptive title to each cluster of documents.
Near Duplicate Document Detection – Uses iReview Analytics Dynamic Clustering to identify and group documents that are duplicates and/or near-duplicate documents, as well as identifying the extent of duplication.
