Equivio Zoom. The e-discovery platform for predictive coding and analytics

Transcription

1 Equivi Zm The e-discvery platfrm fr predictive cding and analytics 1

2 SINGLE, INTEGRATED PLATFORM Equivi Zm is an integrated platfrm fr e-discvery analytics and predictive cding. Zm brings tgether Equivi's prven technlgies fr e-discvery analytics in a unified web-based platfrm. Cmbining Equivi's best-f-breed near-duplicates, threads, relevance and clustering cmpnents, tgether with data imprt, ECA and enriched analytics capabilities, Zm prvides the tls yu need fr easier, faster and smarter e- discvery. ZOOM S INTUITIVE FLOW Zm is built arund a simple, intuitive e-discvery flw. Zm imprts raw data int the system, analyzes the data, perfrms predictive cding, and then exprts the filtered data set t yur review platfrm f chice. 2

3 DATA IMPORT Zm ingests raw cllectin data, facilitating efficient data imprt including text extract, metadata extract and creatin f the search index. Cmprehensive search, reprting and data prfiling capabilities enable effective early case assessment. ANALYSIS Zm supprts multi-dimensinal analysis f the data cllectin: Near-Duplicates Detects and grups near-duplicates. The gruping f nearduplicates allws similar dcuments t be reviewed tgether, allwing users t slash the time and cst f dcument review, while ensuring the cnsistent treatment f similar dcuments. This applicatin als de-dupes identical files. threads - Captures and recnstructs cnversatins. By identifying the unique s in a cllectin, the tl drastically reduces the number f s that need t be reviewed. This applicatin eliminates redundant data and enables the review f s in their riginal cntext. Clustering - Autmatically grups dcuments int clusters based n their cnceptual cntent. Clusters are used t accelerate investigatin f a data repsitry. Clusters als facilitate hmgeneus review batching, enhancing the effectiveness and prductivity f dcument review. Language Detectin Identifies the primary language in which a dcument is written. This enables the use f language as a criterin fr assignment f dcuments fr review. Search Enables data prbing in ECA r t help attrneys familiarize themselves with the case prir t Relevance training. Similarly, search can be used t lcate seed dcuments, if required fr Relevance. Integratin f the search with Zm s analytics allws the presentatin f search results gruped by near-duplicate r structured accrding t threads. RELEVANCE Zm s Relevance applicatin leverages predictive cding technlgy t rganize a cllectin f dcuments by relevance. The applicatin is "trained" by ne r mre attrneys t find relevant and privileged dcuments. Fllwing this initial training, Equivi>Relevance uses statistical and self-learning techniques t calculate graduated relevance scres fr each dcument in the data cllectin. This enables infrmed early case assessment, precise data culling, priritized review and systematic QA fr human review. 3

4 DATA EXPORT Zm s decisin supprt system facilitates the selectin f relevant dcuments fr exprt. Faceted search capabilities allw the verlay f metadata criteria. Based n these selectin criteria, the exprt prcess exprts native files, full text and metadata t the relevant review platfrm. A smart batching mechanism creates batches f dcuments fr litigatin review.zm's patent-pending batching mdule creates review batches that take accunt f threads and families, near-duplicate sets, clusters and relevance scres. threads and near-duplicates are kept tgether, while the Clustering dimensin enhances review prductivity by generating hmgeneus batches, where all the dcuments in a given batch belng t a single cluster tpic. Relevance scres enable review priritizatin. SIMPLER, EASIER AND SMARTER E-DISCOVERY The Zm platfrm makes it easier t deply sphisticated analytics in the business prcess f e-discvery: Easier One unified platfrm fr prcessing and analytics, ne database and ne cnnectin pint simplify implementatin Intuitive web-based GUI fr easy access and use Single vendr and supprt pint lwers ttal cst f wnership Faster One-tuch data management, with ne imprt and ne exprt, accelerates time t results N need t mve data arund between applicatins increases efficiency (e.g., the ability t search and seed Relevance, where required, frm within Zm) and reduces the risk f data handling errrs Smarter Equivi's best-f-breed cre analytics are enriched with a slew f new capabilities including prcessing, ECA, search, keywrd analysis, metadata faceting and language detectin Better analytics thru crss-applicatin synergies, such as alerts indicating incnsistent training f near-duplicate dcuments in Relevance 4

5 BOTTOM LINE: IT'S NEVER BEEN EASIER TO INTEGRATE ANALYTICS Equivi Zm makes it easier t integrate Equivi's best-f-breed analytical cmpnents within yur e-discvery wrkflw. Zm s unified, easy-t-use platfrm allws yu t a achieve a faster and smarter e-discvery prcess, while reducing review effrts and csts. Zm lets yu re-invent the way yur rganizatin perfrms e-discvery. ABOUT EQUIVIO Equivi develps text analysis sftware fr e-discvery. Users include the DJ, the FTC, KPMG, Delitte, plus hundreds f law firms and crpratins. Equivi ffers Zm, an integrated web platfrm fr analytics and predictive cding. Zm rganizes cllectins f dcuments in meaningful ways. S yu can zm right in and find ut what s interesting, ntable and unique. Request a dem at inf@equivi.cm r visit us at Zm in. Find ut. Equivi, Equivi Zm, Equivi>NearDuplicates, Equivi> Threads, Equivi>Cmpare, Equivi>Relevance are trademarks f Equivi. Other prduct names mentined in this dcument may be trademarks r registered trademarks f their respective wners. All specificatins in this dcument are subject t change withut prir ntice. Cpyright 2012 Equivi 5