1. BETA
Faster Document Review for Legal Professionals with a
Personal Intelligent Agent
October 2012
ai-one™
Intelligence delivered
© ai-one inc. 2012

2. Meet Your New Assistant(s)
You train them,
multiply them,
share them.
No overtime,
no benefits,
no complaints.
© ai-one inc. 2012

3. Quick Facts
• ai-BrainDocs is a personal intelligent agent (software
bot) for finding concepts within documents of any
language.
• Customers are legal, financial and compliance
professionals
• Markets include multi-billion dollar eDiscovery and
eGRCM (Governance, Risk & Compliance)
• First customer shipped
• Early Adopter Version Released October 2012
• Personal (cloud) Version Launch December
© ai-one inc. 2012

4. Big Idea
Professionals armed with a personal intelligent agents
they train to identify relevant concepts can save
companies, legal firms and government agencies
massive amounts of time and money.
“digital data growth is explosive and digital data is the stuff of
business and business disputes”
- Gartner Magic Quadrant for eDiscovery May 2012
© ai-one inc. 2012

5. What we do different
Our solution is the ONLY one built with an ai-one “brain”
(uses ai-Fingerprint technology) that addresses
weaknesses of existing language tools, is language
agnostic, works at the paragraph (concept) level and
derives relevance from the context of use within the
document.
“Electronically stored information contains human language, which
challenges computer search tools. These challenges lie in the ambiguity
inherent in human language and tendency of people within networks to
invent their own words or communicate in code.”
- Best Practices Commentary on the Uses of Search and Information Retrieval
Methods in eDiscovery, Sedona Conference
© ai-one inc. 2012

6. Customer-Problem-Solution
Customer Problem Solution
Expert legal, Documents must be
financial or read by experts and
compliance they don’t have
professional in
solutions they can
enterprise or
professional initiate, train and
services firm launch quickly and
easily. Experts burn Personal intelligent
out reading agent can read
thousands of similar documents to flag
documents and those needing
quality suffers review by the
professional user
© ai-one inc. 2012

7. Solution Benefits
• Relevant document accuracy
• Timeliness- faster project turnaround
• Productivity- review more documents faster
• Higher job satisfaction
• Cost effective on small projects
• Tighter compliance- risk mitigation
• Integration with other eDiscovery processes
© ai-one inc. 2012

8. Document Types | Processes
• Engagement Letters • High Volume
• Sales/Marketing materials • Operations Documents
• PR/8-K events • Multi-Language (later
• Employment Agreements release)
• Non-disclosure Agreements • Compliance
• Option Agreements • Review & Encoding
• Leases
• Manuals
• SEC Filings
• Surveys
• Email and messaging
• Free text in forms
• Social media
© ai-one inc. 2012

9. Product Overview
conceptual personal
fingerprints intelligent
the analytics
agents
we paragraph level
documents b
storage
ai-BrainDocs concept discovery
databases Intelligence discovered
email
content library
• compliance
• eDiscovery the brain
ai-one NathanApp
© ai-one inc. 2012

10. Product Features
1. Agent(s) defining the concept are created by user loading example
paragraphs for concept “fingerprint”
2. Documents to be analyzed are batched and imported into ai-
BrainDocs case libraries (similar process to indexing).
3. User directs Agent(s) to analyze a library to rank by concept
similarity score
4. User evaluates performance of Agent and continues training or
saves for production
5. Workflow queue is created and tagged documents are processed
6. User (Admin) customizable output
© ai-one inc. 2012

11. Prototype Screen Shot
Export options
Input Fields for
creating concept
Agents
Columns
display
document rank
and link to the
paragraph with
Input Fields for
highest
known “always
Files ranked by similarity score
include” and “never
highest concept
include” words
score paragraph
© ai-one inc. 2012

12. Quick, Iterative Train & Test Cycle
• Test runs measured
performance against sparse
vs rich concept definitions
• 200 documents per test
• Docs were sales contracts
• Scores in “rich” case shows
known target docs (black
bars) isolated at top of list
• Dynamic confidence color
bands show user the
improved accuracy as
concept definition is
enriched
© ai-one inc. 2012

13. Early Adopter (beta) Solution
Features:
• Concurrent Users
– Batch Processing of Content Library: 1
– Agent Creation: 5
– Concept Similarity Analysis: 5
• Max Number of Documents in Content Library: 1,000 per batch
• Max Number of Agents: No Limits
• Document Types: Microsoft Word, Adobe PDF (readable), Plain Text
Hardware Software Operating System
Processor: 1 x Intel Xeon CPU @ Microsoft .NET Framework 4 Windows 7 64bit
2.8 GHz Java SE Runtime Environment Version Windows Server 2003 64bit
7u6 (or higher) Windows Server 2008 64bit
Memory: 8 GB of RAM Apache Tomcat Version 7.0.29 (or
higher)
Storage: ~ 30 GB Web Browser:
• OS: ~15 GB • Google Chrome v21 (or higher)
• Application & Server: ~ 5 GB • Mozilla Firefox v15 (or higher)
• Remaining: ~ 10 GB to store • Internet Explorer v9 (or higher)
content library (or higher if
necessary)
© ai-one inc. 2012

14. If you’re an early adopter of new
technology and want to work with us
to integrate, trial and test ai-
BrainDocs, let’s talk.
Ready now? Give me a call to
setup a demo.
Tom Marsh, COO
ai-one inc. Follow us on Twitter @ai_BrainDocs
5711 La Jolla Blvd.,
Bird Rock
Website www.ai-braindocs.com
La Jolla, CA 92037
Ph: +18585310674
tm@ai-one.com
© ai-one inc. 2012