1. AutoClassifying Documents at Their Source: PowerHouse Behind the Firewall
Monday, July 24, 2016
1:00 pm ET
Sandra Serkes, President & CEO
Valora Technologies, Inc.

2. What is File Classification?
The creation of metadata (information about a file) to assist in storage, retention, analysis & data mining, risk control, forecasting, etc.
Commonly used file classification components
File and folder naming
Creation Date, Last Modified Date
Author, Source, Custodian, Path
Emerging classification components
Keywords, themes
Content sensitivity
Languages
Intended Audience and/or Responsible Party
Most programs will let a user (or administrator) create metadata for classification purposes.
Watch as I show you how easy, intuitive and practical this is!

3. A Better Way: AutoClassification!
AutoClassification does not rely on people to create their own metadata. Instead, a set of linguistic and pattern-matching rules create the classification content (metadata) and schema (storage hierarchy).
AutoClassification is a much better option for
Large volumes of data
Consistent labelling and file storage
People or circumstances where manual metadata creation is tedious, wasteful, time-consuming or impossible
Sensitive information
IG & Records scenarios with high scrutiny (litigation, investigatory, regulatory, etc.)
Cost reduction

4. What is AutoClassification?
Computer software that is custom-configured to a particular environment
Software contains recognition algorithms for
Document Type
Content analytics
Indexing & Tagging
Recommended locations & naming
“Middleware” that sits between current file locations (includes Archive) and intended file locations (includes deletion), providing an intelligent filter and metadata creation/enhancement for all content.
Valora’s AutoClassification engine is called

5. PowerHouseTM & BlackCatTM 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

6. PowerHouse Architecture With BlackCat
Administration
Console
PowerHouse
Configuration Editor
PowerHouse
Quality
Control
BlackCat
End-users
User Interface
SharePoint/O365
SharePoint
iManage
OpenText
Intake Transfer
Agent
Export
Transfer
Agent
Relativity
Exchange
BlackCat
Data Transfer
Filesystem
PowerHouse Processing
Components
PowerHouse Controller
BlackCat
Controller
BlackCat
Web Server
Processing
BlackCat Document
DataBase
BlackCat
Filesystem Cache
PH Tracking
DataBase PH
Temporary Filesystem
Storage

7. How does AutoClassification Work?
Files are analyzed by a sequence of processing and tagging
Processing (aka Intake) is the process of “ingesting” data into an analytics engine
Creating OCR for scanned images
Extracting text for native files &
Speech to text for audio/video files
Translating content to English
Re-ordering or re-aligning pages
Applying redactions
Tagging (aka Coding, Indexing, Sequencing) is the process of extracting key information and attributes about each document
Document Type, Important Dates
Key Names & Phrases
Topics, Keywords & Themes
File, Content and DocType attributes
Relation to other documents (duplicate, related, attached, contradictory, etc.)
native
text
text
fielded data

8. Classifying a patent application with data mining (analytics)
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 . . .

9. Classifying an email with data mining (analytics)
Author
Doc Type &
Implied attachment
range
Matter indicator
& validation
Author Validation
& Contact Info
Implied matter:
Passaro ( )

10. Intake – PowerHouse – Output
PH Web Portal
Hosted Repository
OCR/Text Extraction
Translation/Transcription
Unitization
Coding/Tagging
Rules/Disposition
Redaction
Exceptions
Shared Server Poll
Folder Taxonomy

11. PowerHouse Portal
Users drag & drop files into the portal for immediate, automatic loading into PowerHouse. PowerHouse responds with an automatic acknowledgement .

12. AutoClassification Live Demo
PLEASE NOTE:
Time permits only a quick tour of BlackCat (and PowerHouse supporting it). If you would like to see a more in-depth presentation, please contact us at:  

13. 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

14. Who We Serve
Corporate Legal Departments with complex document/data/content management needs
Litigation
Risk Exposure
Compliance
Records
Information Governance
Government Agencies with limited resources for document/data/content monitoring, analysis, management
Investigations
Their Advisory Counsel The law firms, consultancies and service providers who support these entities

15. (this is Valora’s story, too)
Valora Technologies
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) “ ”

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