1. Data Mining Documents for Corporate Legal
Wednesday, October 29, 2014
2:00 pm ET
Speaker: Sandra Serkes, President Valora Technologies, Inc.

2. “ ” Valora Technologies Data Mining for Corporate Legal
Bedford, MA software firm specializing in machine-assisted document processing capabilities (aka analytics)
World experts in the automated analysis, indexing, mining and presentation of documents, data & content
20 staff, 200+ clients, 1,500,000+ pages every week
Customers: corporate legal departments, government agencies, and their professional advisory colleagues (law firms & consultancies)
Target market: those who wish to harness and profit from the 2.5 quintillion bytes of document & content data being created each day, aka “Big Data”
Objective: to overtake traditional information repository creation (manual data entry), management, analysis (search, review) and workflow (retention, production, routing) with high quality, low cost, scalable technology & best practices in analytics.
Provide cost competitive document analytics solutions in the United States
Provide efficient, world-class, targeted solutions to data, document & content utilization problems
The power of Big Data is the story about the ability to compete and win with few resources and limited dollars Forbes, March 2012
(this is Valora’s story, too) “ ”
Why Data Mine Documents?
2 Examples of Data Mining in Use by Corporate Legal
Document Data Visualization
Valora’s Analytics & Data Mining Solutions

3. Why Data Mine Documents?
Document is a loose term here. Really, it means any structured or unstructured form of textual or metadata content.
Voic s, tweets, texts, websites, audio & video files, receipts and transactions are all “documents” as far as data analytics are concerned.
Litigation
Doc Review & Productions
Investigations
Compliance
Legal, regulatory & ethics
Financial & investor
Health & safety
Business Intelligence
Information Governance
Management & control
Cost savings
Exposure mitigation
We data mine documents to learn where they are & what they say.
Ultimately, we gain management and control over the contents, storage, access, retrieval, use and exposure of our information.

4. Does your organization know what exactly your documents hold?
EXPIRED

5. How wise is either strategy?
“We know what’s in our data, but we aren’t dealing with it.”
“We don’t know what’s in our data”
Courts, shareholders, consumers, government agencies, watchdog groups, media spotlight reports and more demand that we DO know what is in our data and that we actively manage and control it responsibly.
VERSUS

6. Facebook Tinkers With Users’ Emotions in News Feed Experiment
Why talk about this now?
608,087,870
– total number of records containing sensitive personal information involved in security breaches in the United States since January 2005
Source: Privacy Rights Clearinghouse, June 2013
Big Data is a big deal
Everyone is talking about it: clients, investors, media, employees, management, government
Increasing data breach events keep the conversation alive
So do exploitations of information power
And reactions to that power
People now expect that organizations are routinely collecting and mining data on their behavior, purchases, searches, posts, etc.
They are starting to demand ethical, compliant & competent management of that data
Costs to perform large-scale, complex analytics & hosting have come down enough to be financially viable for most organizations
Facebook Tinkers With Users’ Emotions in News Feed Experiment
6/24/2014
Google removes search results in wake of EU privacy ruling
6/26/2014

7. Typical Corporate Legal Document Populations
Messages + attachments, calendar entries, notifications…
Business Documents
Contracts
Financials
Reports
Sales & marketing materials
Client & patient data
Supplier information
Media & social media

8. Content & Context
You know what content is – WHAT does the document say?
Good for searching & comparing body text
Good basis for data analytics
Context is everything else
WHO wrote this, saw this, knew this, received this authorized this?
WHEN was it sent, received, modified, copied, stored, deleted?
WHY was this created? What was the intent, basis, plan, pattern of behavior?
WHICH version of this content is the most important, recent, comprehensive, damaging?
Predictive Analytics goes beyond content analysis into context and trend analysis.

9. Drawbacks to Classification without Context (Classification alone)
Treats all document contents the same
Misses the notion of document context (who, what, where, when and how)
particularly has important attributes as a communication mechanism
Makes retain/delete decisions on content only
Oversimplifies inherent or explicit decisioning hierarchies
Duplicative content vs. “best” content
Assumes all content instances are equal
Assumes Backfile/Batch methodology only
Weak solution for Day Forward document creation or intake
Does not inform creation or approval of content
Focused on cleanup, rather than asset management
Assumes no future value of past or content, ignores business value
Does not prioritize results for future use
Relegates to IT tool, rather than IG strategy
Unable to adapt to ongoing maintenance or contextual changes
Assumes technology is independent of policy creation & enforcement
Ignores evolving capabilities to define policy and ensure compliance
Ignores PII, PHI & other content sensitivities
Assumes all content instances are equal
Exists outside of data visualization
Missed opportunity for information presentation, forward-use asset management

10. “ ” Valora Technologies
First Example of Data Mining Documents for Corporate Legal
Bedford, MA software firm specializing in machine-assisted document processing capabilities (aka analytics)
World experts in the automated analysis, indexing, mining and presentation of documents, data & content
20 staff, 200+ clients, 1,500,000+ pages every week
Customers: corporate legal departments, government agencies, and their professional advisory colleagues (law firms & consultancies)
Target market: those who wish to harness and profit from the 2.5 quintillion bytes of document & content data being created each day, aka “Big Data”
Objective: to overtake traditional information repository creation (manual data entry), management, analysis (search, review) and workflow (retention, production, routing) with high quality, low cost, scalable technology & best practices in analytics.
Provide cost competitive document analytics solutions in the United States
Provide efficient, world-class, targeted solutions to data, document & content utilization problems
The power of Big Data is the story about the ability to compete and win with few resources and limited dollars Forbes, March 2012
(this is Valora’s story, too) “ ”
Data Mining for Information Governance:
Enterprise Management, Classification & Control

11. Enterprise Email Management is a very good Case In Point
Universal Issue
Involves several key IG problems:
Storage/hosting
Content analysis & classification
Context – correspondence, notification & record, date/time/file signatures, transmission & attachments, custodianship, etc.
Administration, management & maintenance
Elements of Backfile and Day Forward records management
ESI is generally easier & lower cost to tackle than paper files
Because of Context, EEM is a hot button issue with real budgets available
Investor & media attention
Customer concerns
Risk & compliance danger zone
Predecessor to managing social media

12. How a computer classifies an email with data mining (analytics)
INDEXING/TAGGING
for Records & IG
How a computer classifies an with data mining (analytics)
Author
Doc Type &
Implied attachment
range
Matter indicator
& validation
Author Validation
& Contact Info
Implied matter:
Passaro ( )

13. Additional Info Data Analytics Determine
What DocType is this?
An with an attachment
Who created this? Who is the author?
Stuart Trumbull, Partner at DCH
Who is receiving this? Why?
Roberta Halstrom, paralegal
Work instruction/direction
What is the Author-Recipient relationship?
Supervisor-subordinate
What are important words, patterns & concepts?
“please file”
“Motion in Limine”
“Passaro matter”
“ ”
How is attachment related?
Author match
Passaro match
Key Motion content
What else is known about this party?
Wrote 14 s that day
94% of “Passaro” mentions include him as auth/recip/cc
7 instances as Pleading Author w/ Passaro matter(s)
Halstom & assistant/associate on 48% of Trumbull+pasaro content
What other context can be inferred?
Tuesday = 5/13/14
15 date-correlated instances of 5/13/14 with Passaro docket
Tone is neutral-friendly, professionally appropriate
What presents better visually?
Topics over time
Relationship between Trumbull & others
Passaro matter against other matters

14. “ ” Valora Technologies
Second Example of Data Mining Documents for Corporate Legal
Bedford, MA software firm specializing in machine-assisted document processing capabilities (aka analytics)
World experts in the automated analysis, indexing, mining and presentation of documents, data & content
20 staff, 200+ clients, 1,500,000+ pages every week
Customers: corporate legal departments, government agencies, and their professional advisory colleagues (law firms & consultancies)
Target market: those who wish to harness and profit from the 2.5 quintillion bytes of document & content data being created each day, aka “Big Data”
Objective: to overtake traditional information repository creation (manual data entry), management, analysis (search, review) and workflow (retention, production, routing) with high quality, low cost, scalable technology & best practices in analytics.
Provide cost competitive document analytics solutions in the United States
Provide efficient, world-class, targeted solutions to data, document & content utilization problems
The power of Big Data is the story about the ability to compete and win with few resources and limited dollars Forbes, March 2012
(this is Valora’s story, too) “ ”
Data Mining for Litigation & eDiscovery:
Document Review & Production

15. INDEXING/TAGGING for eDiscovery DocType = Patent Application
Date Format = US
DocType = Patent Application
Date = 10/18/2007
Author = Patent Authors, Author City, Author Country
Assignee = RIM
Tone = Neutral to slightly positive
Embedded Graphic with Title
Other Data Capturable Data Elements:
Patent Number
Filing Date
Key Phrases & Terms
Managing PTO
Implied/Attached Docs
Bar Code Present
And many more . . .

16. Litigation Document Review Manual
Indexing/Tagging
ANALYSIS/RULES
For eDiscovery
Litigation Document Review Manual
Determining Responsiveness
The document should be marked responsive if any of the following conditions are present:
Mentions or discusses the specific protocol for handling simultaneous voice and data actions
Is a design document or graphic that shows the specific protocol for handling simultaneous voice and data actions
Discusses or is related to patent ‘009
Mentions Apple Inc. or Apple Computers, Inc. or is a communication from/to anyone at Apple Computer, Inc., or apple.com.
And so on…
Rule: Responsive for Protocol Discussion
When: [FullText] contains any of <Voice protocol key phrases 12> and [FullText] contains any of <Data protocol key phrases 25> and [DocType] is not any of [Brochure, Press Release, Website], ...
Rule: Responsive for Patent ‘009
When: Any document in the Attachment Family matches: [FullText] contains any of <Patent '009 key phrase list 4>, or Parent of Attachment Family matches: Any of [Author, Recipient, CCs] contains any of <Patent '009 experts contact list 23>, …
Rule: Responsive for Apple When: [FullText] contains (fuzzy match) any of <Apple key phrase list 7>, or Any of [Authors, Recipients, CCs] contains any of <Apple contact list 15>, or [Author] matches …
-7-

17. “ ” Valora Technologies Data Mining Documents for Corporate Legal
Bedford, MA software firm specializing in machine-assisted document processing capabilities (aka analytics)
World experts in the automated analysis, indexing, mining and presentation of documents, data & content
20 staff, 200+ clients, 1,500,000+ pages every week
Customers: corporate legal departments, government agencies, and their professional advisory colleagues (law firms & consultancies)
Target market: those who wish to harness and profit from the 2.5 quintillion bytes of document & content data being created each day, aka “Big Data”
Objective: to overtake traditional information repository creation (manual data entry), management, analysis (search, review) and workflow (retention, production, routing) with high quality, low cost, scalable technology & best practices in analytics.
Provide cost competitive document analytics solutions in the United States
Provide efficient, world-class, targeted solutions to data, document & content utilization problems
The power of Big Data is the story about the ability to compete and win with few resources and limited dollars Forbes, March 2012
(this is Valora’s story, too) “ ”
Data Presentation & Visualization

18. What is Data Visualization?
Simple visual representation of relationships and patterns in document data
Common examples
Graph sales over time
Distribution by ethnicity
Word Clouds & Heat Maps
USA Today-style graphics
Use of charts, graphs, dashboards, animation and sound to help convey important connections
Data visualization is a general term that describes any effort to help people understand the significance of data by placing it in a visual context. -TechTarget

20. “ ” Valora Technologies
How Valora Technologies Data Mines Documents & Presents Information Visually
Bedford, MA software firm specializing in machine-assisted document processing capabilities (aka analytics)
World experts in the automated analysis, indexing, mining and presentation of documents, data & content
20 staff, 200+ clients, 1,500,000+ pages every week
Customers: corporate legal departments, government agencies, and their professional advisory colleagues (law firms & consultancies)
Target market: those who wish to harness and profit from the 2.5 quintillion bytes of document & content data being created each day, aka “Big Data”
Objective: to overtake traditional information repository creation (manual data entry), management, analysis (search, review) and workflow (retention, production, routing) with high quality, low cost, scalable technology & best practices in analytics.
Provide cost competitive document analytics solutions in the United States
Provide efficient, world-class, targeted solutions to data, document & content utilization problems
The power of Big Data is the story about the ability to compete and win with few resources and limited dollars Forbes, March 2012
(this is Valora’s story, too) “ ”
PowerHouseTM Automated Data Mining Services Platform
BlackCatTM Hosting & Data Visualization Presentation Layer

21. PowerHouse & BlackCat Architecture
BlackCat Presentation Layer
PowerHouse Platform Layer
PH AutoProcessors
(Pattern-Matching
Algorithms & Rules)
PH Quality Control
User Interface (QCUI)
PH Admin
Console (Admin)
SQL Server Database Layer

22. PowerHouse Platform Capabilities
AutoUnitization
Ability to distinguish the beginning & end of documents, as well as determine which documents incorporate other documents as attachments
AutoCoding
Identify and label documents by type (balance sheet, tax form, memo, etc.), relevant people (authors, recipients, cc/bcc), date and subject/title.
AutoReview
Identify and labeling documents by groupings (dupes/near dupes, conversation threads, issues/clustering) and disposition (responsive, privileged, “hot,” etc.)
AutoRedaction
Ability to identify & markup documents to “black out” select information (such as PII – private identification information, patient data or privileged information)
AutoTranslation
Automatic translation of non-English documents to English text. Supports dozens of originating languages.
Electronic File Processing (EFP)
File Conversion to TIF/PDF format, text and metadata extraction, de-NISTing, cross-custodian de-duplication, filtering/culling, analytics
OCR
Optical Character Recognition for converting images to searchable text
NearDuplicateDetection
Identify documents that are highly similar, if not identical across custodians and the entire population. Includes cross-correlation of paper & electronic documents
ThreadGrouping
Join separated conversation threads into a consistent stream from start to finish
AutoBusinessRules
Identify and label documents by workflow treatment, retention plans, compliance audit or other groupings.
Initiate notifications or other actions based on incoming data
Audio & Video Files Mining
Identify key data elements from audio or video content

23. Litigation & eDiscovery
Selected Valora Client Use Cases of Document Data Mining for Corporate Legal
Records Management
Litigation & eDiscovery
AutoIndex 400,000 files per day for 4 months
AutoRedact SSN & TID from credit applications
Host online “Bidder’s Library” of 100 years of scanned records
AutoBusiness Rules for document retention & compliance
Convert paper medical records to digital format with embedded indexing
AutoReview 1.5M files for responsiveness, privilege, & hotdocs
AutoIndex 3M FOIA request documents
AutoTranslate Japanese, Spanish, French & German docs to English
Oversee & manage 6-city simultaneous data collection & conversion
AutoRedact personally identifying information (PII)

24. Typical Problems Valora Solves
Legal/Litigation/eDiscovery Problems
Too many documents to review, cull & produce by hand
Cost-effective alternative solutions to contract attorney & offshore labor “armies”
Missing, poor, or ineffective metadata
Re-unitization, organization, indexing & redacting of documents
Bridging multi-language document populations to English
Records Management Problems
Help automate defensible deletion efforts for IG
Organize & control loose documents on shared drives, desktops, networks & devices
Eliminate expensive and information-poor storage options
Serve as automated intake for multiple content generation sources
Business Intelligence Problems
Organize & control decades of contracts & agreements
Provide brand integrity/protection data mining of public/private documents
Forecast & trending of topics, people & locations over time
Loose, shared files analysis & control
Health Care Problems
Heavy expense & time converting hardcopy medical records to EMRs/EHRs
Cannot keep up with fax server data collection
Cost effective alternative solutions to “armies” of temp data entry coders

25. Why Valora? Mature & Stable Company Owner Operated Domestic Business
– Brings years of experience and subject matter
expertise to every engagement, small or large
– Long term Government contract (Mega 2-4)
requires annual financial and security review
Owner Operated Domestic Business
– Simple to get things done!
– Your data and documents stay here in the US
Time Tested Proprietary Technology
– Our software has been used since 2003 giving
you the advantage of the system having learned
1,000’s of document types and document
attributes
– Easily customized to meet your needs and
demands
Lightning Fast Processing
– Automated processes means fast turn around
allowing you to meet unrealistic deadlines
– Same day service – In by 9 out by 5!
Unique service offerings
– We automate our solutions allowing you to
virtually eliminate manual labor, reducing time
and cost
• Redaction, Audio/Video coding, Translation, Review
– We process across paper and electronic
collections giving you the advantage of working
with only 1 service provider
Flexible Pricing
– Pricing models designed to meet your specific
document processing needs
– Subscription based models that offer
predictability

26. Valora Technologies, Inc.
Thank You!
For More Information:
Valora Technologies, Inc.
101 Great Road, Suite 220
Bedford, MA 01730