Ai Brain Docs Solution Oct 2012

© ai-one inc. 2012 © ai-one inc. 2012

Intelligence delivered ai-one™

Faster Document Review for Legal Professionals with a

Personal Intelligent Agent

October 2012

BETA

© ai-one inc. 2012

Meet Your New Assistant(s)

You train them,

multiply them,

share them.

No overtime,

no benefits,

no complaints.

© ai-one inc. 2012

• 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

Quick Facts

© ai-one inc. 2012

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.

Big Idea

“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

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.

What we do different

“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

Customer-Problem-Solution

Solution

Personal intelligent agent can read documents to flag those needing review by the professional user

Problem

Documents must be

read by experts and

they don’t have

solutions they can

initiate, train and

launch quickly and

easily. Experts burn

out reading

thousands of similar

documents and

quality suffers

Customer

Expert legal, financial or compliance professional in enterprise or professional services firm

© ai-one inc. 2012

• 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

Solution Benefits

© ai-one inc. 2012

• Engagement Letters

• Sales/Marketing materials

• PR/8-K events

• Employment Agreements

• Non-disclosure Agreements

• Option Agreements

• Leases

• SEC Filings

• Email and messaging

• Free text in forms

• Social media

Document Types | Processes

• High Volume

• Operations Documents

• Multi-Language (later

release)

• Compliance

• Review & Encoding

• Manuals

• Surveys

© ai-one inc. 2012

paragraph level

concept discovery

ai-one NathanApp

conceptual

fingerprints

personal

intelligent

agents

the brain

the analytics

ai-BrainDocs Intelligence discovered

content library

• compliance

• eDiscovery

Product Overview

we

b

storage

email

databases

documents

© ai-one inc. 2012

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

Product Features

© ai-one inc. 2012

Prototype Screen Shot

Input Fields for

creating concept

Agents

Input Fields for

known “always

include” and “never

include” words

Files ranked by

highest concept

score paragraph

Columns

display

document rank

and link to the

paragraph with

highest

similarity score

Export options

© ai-one inc. 2012

• 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

Quick, Iterative Train & Test Cycle

© ai-one inc. 2012

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

Early Adopter (beta) Solution

Hardware Software Operating System

Processor: 1 x Intel Xeon CPU @

2.8 GHz

Memory: 8 GB of RAM

Storage: ~ 30 GB

• OS: ~15 GB

• Application & Server: ~ 5 GB

• Remaining: ~ 10 GB to store

content library (or higher if

necessary)

Microsoft .NET Framework 4

Java SE Runtime Environment Version

7u6 (or higher)

Apache Tomcat Version 7.0.29 (or

higher)

Web Browser:

• Google Chrome v21 (or higher)

• Mozilla Firefox v15 (or higher)

• Internet Explorer v9 (or higher)

Windows 7 64bit

Windows Server 2003 64bit

Windows Server 2008 64bit

© ai-one inc. 2012 © ai-one inc. 2012

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. 5711 La Jolla Blvd.,

Bird Rock

La Jolla, CA 92037

Ph: +18585310674

[email protected]

Follow us on Twitter @ai_BrainDocs

Website www.ai-braindocs.com