Document Review
Rising volumes and complexity of electronically stored information (ESI) have been the propelling forces behind skyrocketing e-discovery costs. At the same time, recent amendments to the Federal Rules of Civil Procedure (FRCP) and court rulings have mandated stiffer requirements to all parties involved. As a result of these converging factors, the old basic competencies just don't cut it anymore.
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What is required these days is a means of not only managing volume and complexity of ESI, but also of measuring the quality of results. Since no single solution can be the panacea for all possible situations, flexibility of technologies—which translates into flexibility of choice—is the only way to go.
Culling now can kill you later
Learn more about document review  C-Evidence™ Review Platform Cataphora Collection Engine Cataphora Production Technology Enhanced Review
Still other linear review platforms provide the old standby of easily licensed data clustering technology. Clustering categorizes datasets by dividing them into large subgroups that have some level of statistical similarity in terms of their content. Unfortunately, this method cannot measure the precision and recall (over-inclusiveness or under-inclusiveness) of the results and thus is generally no better or worse than keyword culling. A growing number of linear review platforms are incorporating simple social network widgets that display messages based on email threads, sometimes allowing for work folders or tags. While many of these widgets look impressive, they do not work with documents other than email. More importantly, these widgets do not provide the multidimensional framework that is needed to model normal data relationships and to detect and flag anomalies from those norms. For example, they cannot identify patterns of data deletion, detect anomalies in behavior, or separate high-value content from the routine. One of the biggest flaws of these platforms is their complete dependence upon data content. Whether boolean searches are performed or whether some kind of statistical clustering is used, documents that do not contain intrinsic content (such as logs of phone calls) will always be ignored—no matter the causal relationship that these documents may have with other highly relevant ESI. Cost savings and defensibility
The multidimensional data model underlying the Cataphora Organizational Behavior Risk Analysis (COBRA) platform provides users with the flexibility to combine a variety of methods and technologies for maximum efficiency and measured results. This translates into enormous cost savings combined with defensibility of process. Add to the equation Cataphora's advanced analytics and advanced data reporting, and there is no truly viable alternative.
Cataphora provides software and solutions that allow customers to access these combinations in the following ways: Categorized manual review combines the power of Cataphora's patented Discussions with measured, defensible linguistic categorization, clustering, and flexible workflow for quick and easy access to the most relevant ESI first. Choosing in addition to use Cataphora's standard Non-Responsive Categorization will defensibly eliminate as much as 30% or more ESI from the need to review altogether, while Cataphora's Privilege Language Identification protects users from inadvertent waiver of privilege. Technology enhanced review: This system automatically distributes small numbers of human relevance decisions over large volumes of complex ESI. The objective is to reflect high-quality attorney decisions consistently by arriving at a categorization rule that replicates reviewer decisions based upon randomly chosen samples. Cataphora's patent-pending Query Fitting Tool balances each variable before arriving at the best available solution for a particular set of ESI. The results are defensibly measured precision and recall (knowing what was left in and what was left out), eliminating the need to perform full manual review and slashing review costs. The system segregates privileged information, and identifies confidentiality status. Read more about Technology Enhanced Review. Collection Engine
Whether in the context of litigation support, investigative purposes, or any other scenario requiring extensive data analysis, data collection is an essential component: it is vital that the collection is conducted in a legally sound and defensible manner, with an unassailable audit trail and no risk of spoliation. At the same time, it is essential that the collection process does not disrupt the normal business operations of the organization.
Cataphora's Collection Engine (CCE) is a key part of Cataphora's offerings and is currently available both as a portable collection appliance and as an enterprise component to be deployed within the corporate firewall. The collection engine includes a network spider and optionally allows the direct connection of media. The product was carefully designed to meet organizations' legal and business operations needs. Logs and reports are generated, collections can be scheduled to run with minimal human intervention, and a full audit trail is created to fully document each step of the process and preserve the chain of custody. Most importantly, in order to overcome the limitations of most collection tools currently available, CCE has been architected to operate safely and non-intrusively within the corporate network: for example, it recognizes the current level of network load and automatically throttles its behavior accordingly. Production
Cataphora's production capacities are virtually limitless in scope of complexity and volume, and our pristine production deliverables are the pride of the industry. We offer numerous production output format options, including any combination of the following:
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