Learn how Text Analytics can Streamline Early Case Assessment and Improve Litigation Readiness and Preparedness

Posted on April 8, 2010

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Text Analytics Offers Option to Search and Analyze Enterprise Information Residing in Original Storage Locations to Yield Insight Sooner and Reduce Costs

Integrated text analytics help make Early Case Assessments more efficient and less costly because:

(i)             Text analytics enable organizations to identify, classify, and sort relevant enterprise information prior to initiating the formal Electronic Discovery Reference Model (EDRM) Collection process and extract entities, facts, relationships, concepts and subtext that will influence the litigation strategy.

(ii)            Legal counsel gains greater insight into potential liabilities and can make informed decisions much earlier in the process.

Traditionally, Early Case Assessments is executed just before the review stage of e-discovery. In order to do this, all data from appointed custodians has to be collected and processed before analysis and review can start. But, a state-of-the-art eDiscovery & Production System should be built on a proven information management platform and it should have the capabilities to analyze information without the need to first collect the data and store it on a collection server. This provides an alternative to waiting for final custodian lists and for their collections to be migrated to the legal hold server for processing. Organizations are saved from potentially unnecessary disruptions and costly collection and processing.

Complementing its various search methodologies (Boolean, wildcard, proximity, and fuzzy searching, but also innovative concept searching), as these are all available in the ZyLAB eDiscovery and Production System, integrates text analytics to manage huge volumes of dispersed and unfiltered data. Here are some key capabilities you should be looking for:

  • Support as many languages and electronic file formats as possible.
  • Auto-classification and sorting based on the content or file properties
  • Extraction of more than 200 types of entities and regular expressions like names, job titles, addresses, and social security numbers.
  • Extraction of events and facts.
  • Extraction of unknown concepts, trends and patterns.
  • Extraction of document and file properties.
  • Detection and recognition of graphical files (also for OCR of non-OCR-ed bitmaps).
  • Detection, recognition and translation of foreign language content, as well as automatic translation.
  • Detection of exact and near-duplicate files.
  • Data Visualization to identify patterns, relationships, trends, and connections in dynamic diagrams or even Google Maps.
  • Native multi-media search on for instance the sound component.

The time is there to once again revolutionizing traditional search methodologies, this time to enable organizations to initiate Early Case Assessments sooner and with a better handle on their information. By focusing on patterns and characteristics our text analytics produce better search results and deeper data analysis, thereby providing quick retrieval of information that otherwise would remain hidden.

This technology has already proven itself in intelligence, security and law enforcement applications, now it is time to use text analytics to streamline early case assessments and improve litigation readiness and preparedness.

For more information:

–       http://www.zylab.com/Pressroom/20100406.asp

–       ZyLAB eDiscovery and Production System

–       White Paper: Litigation readiness and Compliance

–       Brochure; ZyLAB eDiscovery and Production

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