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HP Autonomy Strengthens EDiscovery Solution With New Information Governance Capabilities

NEW YORK, Jan. 29, 2013 /PRNewswire/ -- HP Autonomy today announced several significant enhancements to its market-leading eDiscovery offering, helping organizations automate and simplify processing of large, diverse data sets.

Part of a comprehensive platform that connects archiving, data protection, enterprise content management, eDiscovery, information governance and meaning-based analytics, the Autonomy solution uniquely enables organizations to lower costs, accelerate processes and achieve superior legal outcomes.   

Proven in the world's most demanding and complex eDiscovery projects, Autonomy continues to be the platform of choice for corporate legal departments, law firms and legal consulting firms around the world. In the last year, the volume of data Autonomy has processed on behalf of its clients for eDiscovery initiatives has increased by more than 80 percent.   

"As an innovative, national law firm, we are continually seeking ways to drive the most value for our clients," said Tom Lidbury, partner, Drinker Biddle & Reath LLP. "Our ability to turn today's data explosion into an advantage plays an important role in this mission, and Autonomy technology is a tremendous asset in helping our clients analyze, review, and act on large volumes of disparate information."

Meaning Based Coding extended to Autonomy Early Case Assessment module

Early Case Assessment (ECA) is a critical phase of the eDiscovery process. At the outset of a case, legal teams must rapidly review large data volumes in order to quickly assess their potential risk, identify key issues and determine what information might require full review and production. Autonomy has extended its Meaning Based Coding (MBC) capability to its ECA module, further enhancing its in-depth eDiscovery analysis capabilities.  

Autonomy's MBC capabilities enable organizations to automate analysis based on the Autonomy Intelligent Data Operating Layer (IDOL), which quickly categorizes data by concepts, ideas and patterns in information. Unlike traditional predictive coding technologies, MBC classifications are carried through to the review and production phase without new processing or indexing. As a result, Autonomy ECA can perform an analysis of the data faster, more accurately and at a lower cost.

Structured data analytics through HP Application Information Optimizer

During eDiscovery, legal teams demand the ability to access and analyze all forms of data relevant to a case. This includes unstructured data in the form of emails, phone conversations, voice mails, social media and web content, as well as mission-critical structured data such as transaction data from customer relationship management or enterprise resource planning systems and financial trade tickets. However, access to traditional structured data, typically stored in complex relational database-based applications, can often be costly and cumbersome, hindering a comprehensive discovery process.

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