Crossroads To E-Discovery: Walking the Path of Predictive Coding in 2015 LIVE Webcast

Speaker Firms and Organization:
Stein Mitchell Muse Cipollone & Beato LLP
Sunil Ohri
Of Counsel
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Presented By:
April 20, 2015
1
Partner Firms:
Recommind, Inc.
Hal Marcus
Product Marketing Manager
Manion Gaynor & Manning LLP
Howard P. Goldberg
Partner

April 20, 2015
2
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April 20, 2015
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April 20, 2015
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Partner Firms:
April 20, 2015
6
Recommind is a leader in information intelligence, delivering breakthrough
software applications that harness the power of information to solve concrete
business problems. Recommind customers include AstraZeneca, BMW,
Cisco, Clifford Chance, Marathon Oil, Morgan Lewis, the U.S. Securities and
Exchange Commission (SEC), Swiss Re, the U.S. Department of Energy
(DOE), White & Case and WilmerHale. Recommind is headquartered in San
Francisco and has offices in New York, Boston, London, Sydney and Bonn,
Germany. For more information go to www.recommind.com
Stein Mitchell Muse Cipollone & Beato LLP is a premier, nationally-
recognized litigation firm based in Washington, DC with a 50-year history of
representing clients throughout the United States and abroad in significant
legal matters of national importance. The Firm combines the skills of
seasoned litigators with the flexibility of a dynamic law firm to achieve
extraordinary results for its clients. Its practice focuses on commercial
litigation, antitrust & trade regulation, congressional investigations, white
collar criminal defense, False Claims Act & whistleblower, and significant
health care matters.

Partner Firm:
April 20, 2015
7
Manion Gaynor & Manning LLP (MG&M) is a national law firm focused on Products Liability and Complex Tort Litigation, and
Commercial and Business Litigation with fully integrated offices in Boston, Hattiesburg, Lake Charles, Los Angeles, New
Orleans, Providence, San Francisco and Wilmington.
Our focus on providing strategic, responsive legal counsel in each of our core practices has made us the law firm of choice for
clients facing high-stakes litigation. Clients value our guidance on sophisticated matters ranging from complex commercial and
business disputes, toxic tort and products liability, intellectual property, real estate, employment, to white collar and regulatory
matters.
Our unwavering commitment to excellence is premised on the concept that there is an optimal resolution for every case—
whether through voluntary dismissal, summary judgment, reasonable settlement or trial. We rapidly assess and efficiently
achieve our clients’ desired outcome with a streamlined, efficient operating model and a thorough understanding of their
specific industry and goals. We deliver practical insight on our clients’ most important matters and ensure a successful
partnership through a culture of close collaboration.
Our firm and, therefore, our clients’ defense, are truly integrated. Across offices—across the country—we work as a unified
team actively developing collective knowledge, and providing optimal service. MG&M leverages the unique experience and
skills of our lawyers to their best and highest use, protecting and advancing the interests of our clients wherever they do
business.

Brief Speaker Bios:
Hal Marcus
An IP and antitrust litigator by experience, Hal Marcus began evangelizing legal technology to his colleagues at an Am Law 100 Wall
Street firm before moving West and joining LexisNexis, commencing a career in litigation technology that now spans two decades and
includes executive and general counsel roles at LiveNote, Law.com, and Thomson Reuters. An accomplished public speaker and
industry writer, Hal has led hundreds of MCLE presentations and conference seminars, and contributed to publications by ILTA and
the ABA Litigation Section. Today, Hal is excited to bring his diverse experience to Recommind’s product marketing team, helping to
educate litigation professionals worldwide on some of the most exciting eDiscovery technology available.
April 20, 2015
8
Sunil Ohri
Sunil Ohri is Of Counsel with Stein Mitchell Muse Cipollone & Beato LLP. Bridging the worlds of law and technology for more than two
decades, Mr. Ohri has broad and deep experience in optimizing best practices and workflows to effectively control the document
management life cycle - as part of a larger Information Governance methodology - and bring predictability to the legal spend
associated with Electronic Discovery Reference Model (EDRM). He custom designs solutions for each individual client, with an
understanding that information management practices and processes must fit seamlessly within the organization’s workflow and
culture to succeed. Moreover, as a trusted advisor, he combines this same legal expertise and technological know-how to proactively
guide clients through critical dimensions of modern litigation – i.e., e-discovery and federal rules of procedure, risks, technology, and
cost containment/management – to create a structured and sustainable litigation-prepared environment.

Brief Speaker Bio:
Howard P. Goldberg
Howard P. Goldberg is an experienced trial lawyer who specializes in litigating complex commercial matters. Howard has experience
representing clients involved in a wide variety of commercial cases, focusing on contract disputes, environmental litigation and
commercial real estate litigation. Howard also has significant experience with a variety of settlement mechanisms, including formal
arbitration proceedings and court-assisted mediation programs.
In addition to his case responsibilities, Howard serves on the e-discovery committee for Manion Gaynor & Manning and has significant
experience advising clients on e-discovery best practices, including legal holds, data preservation, and data production, working with
e-discovery vendors and consultants, and managing e-discovery in anticipation of, during, and after litigation.
April 20, 2015
9
► For more information about the speakers, you can visit: http://theknowledgegroup.org/event_name/crossroads-to-e-discovery-walking-the-path-of-predictive-coding-in-2015-live-webcast/

Electronic discovery (e-discovery) involves identification of relevant information for civil litigation or government investigation. Analytical
methods used include computational and review by lawyers. e-Discovery has evolved through predictive coding and information
governance.
Predictive Coding has gained praise as it has revolutionized e-discovery technology for legal applications with its quicker and cheaper
processing cost. Never the less, the use of predictive coding has been controversial because misconceptions remain regarding
predictive coding methods, when it should be used, and how to integrate it into e-discovery workflow. Controversially, some courts are
ordering parties to use predictive coding in e-discovery since they cannot agree upon the definitions of some key words.
The Knowledge Group has assembled a panel of notable experts and professionals that will provide the audience with a current review
of the methods and controversy surrounding Predictive Coding in E-Discovery.
Key topics include:
• Predictive Coding Defined
• Practical Aspects and Defensible Use of Predictive Coding
• Recent case law and developments affecting a client’s options
April 20, 2015
10

Featured Speakers:
April 20, 2015
11
SEGMENT 1:
Hal Marcus
Recommind, Inc.
SEGMENT 2:
Sunil Ohri
Of Counsel
SEGMENT 3:
Howard P. Goldberg
Partner

Introduction
An IP and antitrust litigator by experience, Hal Marcus began evangelizing legal technology to his colleagues at an Am Law
100 Wall Street firm before moving West and joining LexisNexis, commencing a career in litigation technology that now
spans two decades and includes executive and general counsel roles at LiveNote, Law.com, and Thomson Reuters. An
accomplished public speaker and industry writer, Hal has led hundreds of MCLE presentations and conference seminars,
and contributed to publications by ILTA and the ABA Litigation Section. Today, Hal is excited to bring his diverse experience
to Recommind’s product marketing team, helping to educate litigation professionals worldwide on some of the most exciting
eDiscovery technology available.
April 20, 2015
12
SEGMENT 1:
Hal Marcus
Recommind, Inc.

Topics
• What is predictive coding, really?
• Why all the confusion? (nomenclature & concepts)
• Different use cases and workflows
• Predictive coding for prioritized review
• Defending your decision
April 20, 2015
13
SEGMENT 1:
Hal Marcus
Recommind, Inc.

Why Predictive Coding?
April 20, 2015
14
SEGMENT 1:
Hal Marcus
Recommind, Inc.

April 20, 2015
15
SEGMENT 1:
Hal Marcus
Recommind, Inc.
(((master settlement agreement OR msa) AND NOT
(medical savings account OR metropolitan standard area)) OR s. 1415 OR
(ets AND NOT educational testing service) OR
(liggett AND NOT sharon a. liggett) OR atco OR lorillard OR
(pmi AND NOT presidential management intern) OR pm usa OR rjr OR
(b&w AND NOT photo∗ OR phillip morris OR batco OR ftc
test method OR star scientific OR vector group OR joe camel OR
(marlboro AND NOT upper marlboro)) AND NOT
(tobacco∗ OR cigarette∗ OR smoking OR tar OR nicotine OR
smokeless OR synar amendment OR philip morris OR r.j. reynolds OR
(“brown and williamson”) OR
(“brown & williamson”) OR bat industries OR liggett group)
Previous Methods Are No Longer Sufficient

April 20, 2015
16
SEGMENT 1:
Hal Marcus
Recommind, Inc.
“Under predictive coding, the software ‘learns’ a
user’s preferences or goals; as it learns, the software
identifies with greater accuracy just which items the
user wants…”
In re Biomet (N.D. Ind. Apr.
18, 2013)
Predictive Coding Amplifies a Lawyer’s Judgment

Why So Much Confusion?
April 20, 2015
17
SEGMENT 1:
Hal Marcus
Recommind, Inc.
Many Names
TAR (Technology Assisted Review)
CAR (Computer Assisted Review)
Machine Learning
Many Evaluative Terms
Precision Recall
Prevalence Elusion
Estimation Validation
Many Providers
Well over 30 companies claim to
offer some variant of Predictive
Coding technology for discovery
Many Workflows
Iterative Stabilized
Continuous Simple
Targeted Random Sampling

Predictive Coding Is About Categorization
April 20, 2015
18
SEGMENT 1:
Hal Marcus
Recommind, Inc.
Yes
No

The System Must Be Trained
April 20, 2015
19
SEGMENT 1:
Hal Marcus
Recommind, Inc.

The System Must Be Trained
April 20, 2015
20
SEGMENT 1:
Hal Marcus
Recommind, Inc.
Document Model
• 4000 terms
• Term weighting

The Document Model is Compared to the Corpus
April 20, 2015
21
SEGMENT 1:
Hal Marcus
Recommind, Inc.

Yes
No
HIGH
CONFIDENCE
The Documents Are Ranked
April 20, 2015
22
SEGMENT 1:
Hal Marcus
Recommind, Inc.

April 20, 2015
23
SEGMENT 1:
Hal Marcus
Recommind, Inc.
As more documents are reviewed, they are used
to refine the training (known as an “iteration” or
“round”).
The Training Continues (to a point)

April 20, 2015
24
SEGMENT 1:
Hal Marcus
Recommind, Inc.
Machine Reviewed
Non Responsive
80.27%, 96,461
Human Reviewed
Non Responsive
9.51%, 11,428
Human Reviewed
Responsive 10.23%,
12,293
120,171 Documents
The Results Can Be Dramatic

April 20, 2015
25
SEGMENT 1:
Hal Marcus
Recommind, Inc.
*Required only 35% of the collection to be reviewed.
DOCUMENTS
2,000,000
227 Days
81 Days*
COST
$1,636,364
COST*
$582,568
LINEAR
REVIEW
PREDICTIVE
CODING
Savings
$1,053,796
As Can the Savings

Non-Controversial Use Cases
April 20, 2015
26
SEGMENT 1:
Hal Marcus
Recommind, Inc.
1. Review Received Production Sets
“With the massive number of documents produced in
modern litigation, it is too costly to try to review every
document produced. With Predictive Coding, we focus on
the small percentage of documents that actually matter.”
William Greene, Partner
Stinson Leonard Street LLP

April 20, 2015
27
SEGMENT 1:
Hal Marcus
Recommind, Inc.
2. Conduct Internal
Investigations
“Predictive Coding helped our small review team
get to the heart of the matter quickly - and find
documents we wouldn’t otherwise have found.”
Brian Dillon, Partner
Gray Plant Mooty LLP

April 20, 2015
28
SEGMENT 1:
Hal Marcus
Recommind, Inc.
3. Quality Check Manual Review
“Predictive Coding helped us zero in on false positives
quickly, allowing us to complete the second pass
review on deadline with a small, nimble team.”
Attorney Leading the Review

April 20, 2015
29
SEGMENT 1:
Hal Marcus
Recommind, Inc.
4. Enhance Privilege Screening
• Prioritize review of documents that
hit on privilege search terms
• Find other privileged documents
that may have been missed

Despite Overwhelming Judicial Support,
Uncertainty Persists in Production Scenarios
April 20, 2015
30
SEGMENT 1:
Hal Marcus
Recommind, Inc.
1. Do you need to obtain permission first?
2. Must your process be documented in an ESI order?
3. Can you use it on documents already culled with search terms?
4. Must you disclose your ‘seed set’ documents?
5. Can you change your process if circumstances warrant?

April 20, 2015
31
SEGMENT 1:
Hal Marcus
Recommind, Inc.
Producing party has broad discretion…
“The Court is not normally in the business of
dictating to parties the process that they should
use when responding to discovery…(for example)
whether that review should be done by a
paralegal, a junior attorney, or a senior attorney.
Yet that is, in essence, what the parties are asking
the Court to consider – whether…review should be
done by humans or with the assistance of
computers.”
JUDGE RONALD BUCH
Dynamo Holdings v IRS Comm’r
(U.S. Tax Ct, Texas, Sept. 2014)

April 20, 2015
32
SEGMENT 1:
Hal Marcus
Recommind, Inc.
Producing party has broad discretion…
“The Court is not normally in the business of
dictating to parties the process that they should
use when responding to discovery…(for example)
whether that review should be done by a
paralegal, a junior attorney, or a senior attorney.
Yet that is, in essence, what the parties are asking
the Court to consider – whether…review should be
done by humans or with the assistance of
computers.”
“…[petitioners should] retain electronic discovery
experts to meet with respondent's counsel or his
experts to conduct a search acceptable to
respondent…
yet transparency is still expected.
JUDGE RONALD BUCH
Dynamo Holdings v IRS Comm’r
(U.S. Tax Ct, Texas, Sept. 2014)

Two Schools of Thought
April 20, 2015
33
SEGMENT 1:
Hal Marcus
Recommind, Inc.
Statistically Targeted Review
Review is deliberately limited based on
targeted precision and/or recall levels.
Prioritized Review
Review is organized based on continuous
machine learning along with other tools.

Sampling for Estimation
April 20, 2015
34
SEGMENT 1:
Hal Marcus
Recommind, Inc.

Tracking Your Progress
April 20, 2015
35
SEGMENT 1:
Hal Marcus
Recommind, Inc.

Sampling for Validation
April 20, 2015
36
SEGMENT 1:
Hal Marcus
Recommind, Inc.

Defending Your Decision
April 20, 2015
37
SEGMENT 1:
Hal Marcus
Recommind, Inc.
“We’ve reviewed and are
producing 14,645 responsive
documents.”
Production Readiness
“With 95% confidence, the
machine-reviewed data has 464 to
1,788 relevant docs (0.19% to
0.73% relevancy).”
Validation Test Results
“Conducting a full linear review of
the machine-reviewed data would
cost approx. $245,210.”
Cost Estimates
“Trends show steeply diminishing
returns from continuing the
review.”
Iteration Trends

Introduction
Sunil Ohri is Of Counsel with Stein Mitchell Muse Cipollone & Beato LLP. Bridging the worlds of law and technology for
more than two decades, Mr. Ohri has broad and deep experience in optimizing best practices and workflows to effectively
control the document management life cycle - as part of a larger Information Governance methodology - and bring
predictability to the legal spend associated with Electronic Discovery Reference Model (EDRM). He custom designs
solutions for each individual client, with an understanding that information management practices and processes must fit
seamlessly within the organization’s workflow and culture to succeed. Moreover, as a trusted advisor, he combines this
same legal expertise and technological know-how to proactively guide clients through critical dimensions of modern litigation
– i.e., e-discovery and federal rules of procedure, risks, technology, and cost containment/management – to create a
structured and sustainable litigation-prepared environment.
• 25+ Years as an Attorney/Technologist
• Technology Proponent
• Process based methodologies
• Information Governance Advocate
April 20, 2015
38
SEGMENT 2:
Sunil Ohri
Of Counsel

Topics
• To Use, or Not To Use, TAR
• TAR: Panacea or a Placebo?
• Practical Aspects of TAR
• Defensible Use of TAR
April 20, 2015
39
SEGMENT 2:
Sunil Ohri
Of Counsel

To Use, or Not To Use: Purpose
• Reduce review costs and time while still being able to reasonably comply with Discovery production
certification requirements
• Aid in the rapid identification and categorization of documents of likely Responsive and Non-
Responsive documents
• Not to replace legal, professional judgment regarding the correct valuation of a document
April 20, 2015
40
SEGMENT 2:
Sunil Ohri
Of Counsel

To Use, or Not to Use: Means / Mechanisms
• All tools are not created equal
• Significant differences between how tools operate – SPL, SAL, CAL
• Positive/Negative (Absolute) versus Sliding Relevance Scale and Weighted Tokens
April 20, 2015
41
SEGMENT 2:
Sunil Ohri
Of Counsel

To Use, or Not To Use: Data Considerations
• Used on cases regardless of size, but smaller cases will achieve less ROI
• Low richness – such as audio or databases
• Foreign language collection complications
• Non-extractable text heavy collections
April 20, 2015
42
SEGMENT 2:
Sunil Ohri
Of Counsel

Panacea or a Placebo?
• Considered by many as THE solution to ever burgeoning data sizes
• Multiple cases since Da Silva Moore have approved its use and widely adopted by legal practioners to
handle large data volumes
• Judge Peck in Rio Tinto – “it is now black letter law . . . that court will permit” the use of TAR by
producing party provided there is a solid process behind it
April 20, 2015
43
SEGMENT 2:
Sunil Ohri
Of Counsel

Panacea or Placebo? (2)
• But J. Peck recognized in 2011, and nothing has changed, since his Search, Forward article that ESI is
“not clean”
• In the same article J. Peck stated he is “less interested in the science behind the ‘black box’ of the”
technology than the results
• He also said, in connection with using lesser qualified persons to perform a review that “economics
drove the change.” Same situation here.
April 20, 2015
44
SEGMENT 2:
Sunil Ohri
Of Counsel

Panacea or Placebo (3)
• In Rio Tinto, J. Peck states “it is inappropriate to hold TAR to a higher standard than keywords or
manual review”
• Why?
• Keywords and Manual Review are human efforts with known issues and limitations
• TAR is triple stacked technology
April 20, 2015
45
SEGMENT 2:
Sunil Ohri
Of Counsel

Practical Aspects of TAR
• Vetting the different technologies available
• Vetting the expertise of the vendor’s team
• Legal team’s knowledge of client’s language models – particularly from key custodians
• Flexibility to rework the model as additional language models arise in discovery
April 20, 2015
46
SEGMENT 2:
Sunil Ohri
Of Counsel

Defensible Use of TAR
• Deeper understanding of capabilities and limitations of selected TAR solution
• Implement workflow to address the limitations
• Deeper understanding of language models presented in documents
• Transparency
• Judgmental sampling: Seed Sets
April 20, 2015
47
SEGMENT 2:
Sunil Ohri
Of Counsel

Defensible Use of TAR
• Review of machine coded documents between Seed Sets
• Concept analysis of likely non-responsive documents; review multiple samples from different
concepts/areas
• Review likely responsive collection
April 20, 2015
48
SEGMENT 2:
Sunil Ohri
Of Counsel

Fascciola& Favro: Seed Set Law Review Article
• Despite the potential that predictive coding holds, its introduction to the discovery process has not
been universally embraced or free from controversy. There have been disagreements regarding
what is predictive coding, when it should be used, and the process for how to successfully implement it
into a discovery workflow. Moreover, the few judicial opinions on predictive coding are based on
specific fact patterns that make general application for practitioners difficult. These factors have
led to uncertainty regarding the manner in which predictive coding may be used. . . .
April 20, 2015
49
SEGMENT 2:
Sunil Ohri
Of Counsel

Introduction
Howard P. Goldberg is an experienced trial lawyer who specializes in litigating complex commercial matters. Howard has
experience representing clients involved in a wide variety of commercial cases, focusing on contract disputes,
environmental litigation and commercial real estate litigation. Howard also has significant experience with a variety of
settlement mechanisms, including formal arbitration proceedings and court-assisted mediation programs.
In addition to his case responsibilities, Howard serves on the e-discovery committee for Manion Gaynor & Manning and has
significant experience advising clients on e-discovery best practices, including legal holds, data preservation, and data
production, working with e-discovery vendors and consultants, and managing e-discovery in anticipation of, during, and after
litigation.
Howard is admitted to practice in Massachusetts, the United States District Court for the District of Massachusetts, and the
United States Court of Appeals for the First Circuit. He is a member of the American, Massachusetts and Boston Bar
Associations. Prior to joining MG&M, Howard was an associate at Foley Hoag LLP in Boston/pro bono housing cases.
Howard lives in Marblehead with his wife and two sons.
April 20, 2015
50
SEGMENT 3:
Howard P. Goldberg
Partner

Courts Approve Use of Technology Assisted Review
• Formerly an outlier, use of Technology Assisted Review (“TAR”) has been approved for use by Federal
and State Courts
• Not appropriate in all cases
• Counsel must be prepared to present options both to clients and the Court
• In general, document by document review, or culling through the use of search terms or other
methods, may not be appropriate
April 20, 2015
51
SEGMENT 3:
Howard P. Goldberg
Partner

TAR Basics
• Attorneys train the program by identifying a set of relevant documents from a broader set of potentially
relevant materials
– Creation of a seed set and code each document
– Through iterative process, program is trained with additional documents
– QC’d by attorney familiar with case
– Process cycles until predictive coding is sufficiently accurate when compared to attorney review
– Then applies coding to remaining universe of documents, and attorneys review ultimate universe
of responsive documents
April 20, 2015
52
SEGMENT 3:
Howard P. Goldberg
Partner

Predictive Coding In Litigation
• Predictive Coding is here to stay; oftentimes, must convince opponent or client to utilize
• Can be used in many ways
– Early Case Assessment
– Review for discovery responses
– Review of other party’s document production
– Deposition preparation
– Expert preparation
April 20, 2015
53
SEGMENT 3:
Howard P. Goldberg
Partner

Potential Benefits
• Process must be defensible
• Ability to drastically reduce number of documents requiring primary attorney review
• Minimize inconsistent productions
• Identify quickly relevant and key documents
• Superior accuracy over keyword searches and linear review
April 20, 2015
54
SEGMENT 3:
Howard P. Goldberg
Partner

Da Silva Moore v. Publicis Groupe, 287 F.R.D. 182 (S.D.N.Y. 2012) (Peck, Mag. J.),
aff’d, No. 11 Civ. 1279, 2012 WL 1446534 (S.D.N.Y. Apr. 26, 2012) (Carter, J.)
• First Federal court to approve use of TAR
• Judge Peck viewed as suitable replacement for other methods of segregating electronically stored
information
– Both parties agreed to use predictive coding, disagreed as to the details
– Appropriate in certain cases, not required
– Must be part of defensible process, subject to same QC/QA procedures for any document review
– Demonstration of reasonableness
April 20, 2015
55
SEGMENT 3:
Howard P. Goldberg
Partner

In re Actos Prod. Liab. Litig., 2012 U.S. Dist. LEXIS 187519 (W.D.La. Jul. 27, 2012
• Magistrate Judge Doherty, sua sponte, ordered a detailed protocol to govern the use of TAR, to which
the parties had stipulated
• Order included a “Search Methodology Proof of Concept” and stated that the parties “agree to meet
and confer regarding the use of advanced analytics as a document identification mechanism for the
review and production of data.”
April 20, 2015
56
SEGMENT 3:
Howard P. Goldberg
Partner

In re Biomet M2a Magnum Hip Implant Products Liab. Litig., 3:12-MD-2391, 2013 WL
1729682 (N.D. Ind. Apr. 18, 2013); MDL 2391, 2013 WL 6405156 (N.D. Ind. Aug. 21, 2013)
• Defendant, Biomet, employed TAR, using a combination of electronic search functions to identify
relevant documents
• Biomet employed TAR to identify the relevant documents to be produced
• Biomet offered to allow plaintiffs to provide additional search terms, and to review the non-privileged
documents from the 2.5 million set
• Plaintiffs were unhappy that Biomet used keywords, and wanted Biomet to utilize predictive coding
from that set of documents.
• Court ruled that Biomet’s procedures complied with the F.R.C.P. and that plaintiff’s proposal “that
Biomet go back to Square One. . . sits uneasily with the proportionality standard” because it would
entail costs over a million dollars and it appeared likely that few relevant documents would be found.
April 20, 2015
57
SEGMENT 3:
Howard P. Goldberg
Partner

Rio Tinto Pic. v. Vale S.A., 2015 U.S. Dist. LEXIS 24996 (S.D.N.Y. Mar. 2, 2015)
• Endorsement of cooperation among parties
• Parties discussed and agreed on TAR protocols
• Because of “the interest within the e-discovery community about (technology-assisted review (TAR))
cases and protocols, Judge Peck provided additional details concerning TAR
April 20, 2015
58
SEGMENT 3:
Howard P. Goldberg
Partner

Rio Tinto cont.
• Producing parties should not worry about Court approval for TAR
• Transparency and cooperation are important, to a point
• No “one size fits all” approach to TAR protocols
• Depends, in part, on TAR methodology employed by the parties
April 20, 2015
59
SEGMENT 3:
Howard P. Goldberg
Partner

April 20, 2015
60
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April 20, 2015
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April 20, 2015
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► You may ask a question at anytime throughout the presentation today. Simply click on the question mark icon located on the floating tool bar on the bottom right side of your screen. Type
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► Questions will be answered in the order they are received.
Q&A:
April 20, 2015
63
SEGMENT 1:
Hal Marcus
Recommind, Inc.
hal.marcus@recommind.com
SEGMENT 2:
Sunil Ohri
Of Counsel
SOhri@steinmitchell.com
SEGMENT 3:
Howard P. Goldberg
Partner
hgoldberg@mgmlaw.com

April 20, 2015
64
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