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

Transcription

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

2 DISCOVER WHAT YOU NEED TO WIN Zm fr E-Discvery is an integrated platfrm fr e-discvery analytics and predictive cding. Zm s advanced analytics enable yu t zm in n the data that s imprtant t yur case. Supprting the full e-discvery cycle, Zm is used t make sense f the data cllectin, pinpint key dcuments, cull the cllectin and rganize the review. RE-ENGINEERING THE E-DISCOVERY 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. Zm is fully integrated with all majr e-discvery platfrms via a streamlined wrkflw. Figure 1: Relevance Training Status DATA IMPORT Zm extracts text and metadata frm either raw ingest data r a hsting system (e.g., Relativity, LAW, IPRO, iconect) and creates the search index. Cmprehensive search, reprting and data prfiling capabilities enable effective early case assessment. 2

3 ANALYTICS AND PREDICTIVE CODING Zm utilizes advanced analysis technlgies specifically designed t address the prblems f e-discvery. Multi-dimensinal analysis f the data cllectin is perfrmed using a brad range f text analysis technlgies, including: 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. 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 early case assessment (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-duplicates r structured accrding t threads. Search functins include cmplex search, fuzzy search, cnceptual search, find similar, search term expansin, etc. Themes - Themes is a grund-breaking applicatin fr intuitively explring dcument cllectins. By imitating the way humans review and think abut dcuments, Themes makes it easy fr users t brwse a list f themes, drill dwn, find similar dcuments, r jump t a related theme. Drawing n emergent research in text analytics technlgies, Themes analyzes and maps the thematic intercnnectins between cntent acrss a dcument repsitry. This allws legal strategists and investigatrs t quickly grasp the essence f a cllectin, find the dcuments they need and make better strategic decisins. Relevance - Relevance 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, 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 & BATCHING 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 cntaining Equivi analytics result t the relevant review platfrm. A patented batching mdule creates review batches cmprised f clsely related dcuments. This applicatin uses multiple analytical verlays t create dcument batches that take priritized accunt f threads and families, near-duplicate sets, themes and relevance scres. By assigning hmgeneus batches t reviewers, this capability increases the speed and reduces the cst f dcument review. threads and near-duplicates are always kept tgether, while relevance scres enable review priritizatin. SMARTER E-DISCOVERY, LESS RISK, LOWER COSTS The Zm platfrm streamlines e-discvery by minimizing review vlumes, maximizing reviewer prductivity and ensuring defensibility: Find ut mre Use Themes t brwse the cllectin, find interesting tpics and deep dive int specific dcuments Zm in n key dcuments t estimate case risk and winnability Priritize review effrts by fcusing n the key data Lwer risk Discharge discvery bligatins by finding mre f the relevant data Reduce review incnsistencies by gruping near-duplicate sets and threads Enable systematic QA f review by crss-matching relevance scres against human review tags Reduce csts Filter nn-relevant dcuments t significantly reduce review vlumes and csts, and in sme cases even eliminate the need fr first-pass review Determine the size f the review set using the decisin-supprt envirnment in rder t address prprtinality cnsideratins 4

5 Stratify review by assigning high-ptential dcuments fr high-grade review, and lw-ptential dcuments fr lw-cst review Accelerate review speed via set-centric review based n near-duplicates and threads grupings, as well as rganizing review by thematic clusters BOTTOM LINE: CHOOSE ZOOM ONLY FOR CASES YOU WANT TO WIN Zm is widely acknwledged as the premium slutin fr analytics and predictive cding in e-discvery. Prven in thusands f e-discvery cases, Equivi s specialized cre technlgies give leading service prviders, law firms and crpratins the decisive edge they need t win a case. By helping reviewers zm in n the critical dcuments in a cllectin, Zm enhances strategic decisin-making, minimizes review csts and mitigates risk. Yu win, and s d yur clients. ABOUT EQUIVIO Equivi prvides analytics sftware fr e-discvery and infrmatin gvernance. Users include hundreds f crpratins, law firms and gvernment agencies. 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. 5