With PLUS, you gain the ability to systematically extract information, analyze and manage vast amounts of data that are too large or complex to be dealt with by traditional review methodologies. PLUS deploys the technology and expertise necessary to handle complex unstructured data and will assist in organizing the data to gain greater insight in order to make more intelligent decisions.
Early Case Assessment (“ECA”) is the process of identifying, analyzing and filtering down an initial document data set. When used properly, ECA allows case teams to evaluate the cost and risk of a legal issue, build a litigation strategy and discovery plan all while reducing time and saving money. PLUS integrates early case assessment (ECA) and investigation capabilities into its review platform, enabling your team to use whatever search and analysis tools are required to quickly dig into matters, gain a comprehensive understanding of the data at the onset of a case and quickly uncover the truth behind your data.
The goal of ECA is to quickly analyze and synthesize data into a preliminary understanding of the document corpus. The PLUS team has created specific ECA workflows to quickly reveal the size, scope and data modeling to support decision making strategies of the case through rapid identification of critical information about the data.
Legal Operations teams should apply analytics to unstructured data to evaluate, predict and improve discovery review performance. PLUS confers with clients at every stage of a project to determine the most effective analytics tools to apply to gain an efficient review workflow. Whether your review is conducted in-house or managed externally, PLUS offers a full suite of Relativity analytics features to help identify critical information quickly including:
PLUS dramatically reduces the time and complexity involved in email review mails by identifying email relationships and extracting and normalizing email metadata. With email thread visualization, you can see the structure of an email thread, navigate across emails, and identify missing information within a thread. Additionally, identifying the inclusive emails drastically decreases the number of records to review, preventing repetitive work while ensuring all the content is covered.
We identify textually similar documents and group them for batch review based on the similarity, or create new document sets for further analysis. Near-duplicate identification saves you time when tagging highly similar documents with the issues in your case.
PLUS allows you to deliver the most important groups of documents to review teams quickly, enabling you to organize and prioritize your review sooner rather than later. Clustering automatically identifies and groups documents with similar concepts without the need for user input. It labels those groups by the most prevalent meaning in each one and visually represents how the groups relate to one another.
PLUS automatically gathers all variations of custodian’s email and arranges them as a single entity. Additional information about the custodian can be entered and leveraged from case to case. This is especially helpful for privileged logs.
Understanding the interactions between the people in your case is critical to uncovering the truth. It’s not easy to see who’s been talking to whom with conversations taking place across multiple channels with multiple people, let alone what they’ve been talking about. Our communication analytics can be used to visualize communication frequencies, patterns, and networks between the entities linked to the documents in the view.
The PLUS system allows subject matter experts the ability to automatically organize and prioritize unreviewed documents into categories and determine whether documents are responsive or non-responsive. The PLUS team leverages categorized documents to help find important documents from an opposing production and ensure quality control by automatically identifying documents similar to those already tagged.
PLUS assists lawyers in finding the most relevant documents with two powerful technology assisted review (TAR) workflows: Continuous Active Learning (CAL) and sample-based learning (Predictive Coding). PLUS maximizes the efficiencies of these workflows to get to the most relevant documents faster. The end result is a less costly and tedious discovery experience.
Regardless of the volume of data and number of documents in your review, you can handle them more efficiently and with more transparency than ever before. PLUS utilizes TAR technologies, protocols, and workflows to help case teams accomplish more legal and data discovery tasks than just culling data, including: