1. Text Analytics for
Social, Survey & Government Data
Dr. Stuart Shulman
Founder and CEO - Texifter
stu@texifter.com

2. Pronounced “TECH-sifter” the
metaphor and logo were derived
from an old fashioned flour sifter
The Company: Founded in 2009

3. Business Summary
• Cloud-based tools for collaborative & crowd source text analytics
• Twitter data access via free and premium channels
• Strategic partners with SurveyMonkey & Gnip (acquired by Twitter)
• Government, private sector, and academic customers
• Public comments, voice of customer/employee, and other text data
• Any text analytics problem where information overload is a factor

4. Two Linked Products

5. Business Model
• Month-to-month and yearly recurring licenses
• New offer: perpetual licenses ($250,000) with on site maintenance
• One-time and recurring premium Twitter data sales
• Access to every undeleted Tweet in history
• E-commerce and traditional billing methods
• Major pricing variables:
• The number of users
• Base price declines as # of users scales up
• The type of users
• Professional versus Enterprise feature sets based on computational resources
• The volume of data stored or acquired
• The number of live social data feeds
• A choice between free & premium Twitter data

7. New 5-Country Distributor Agreement

8. Value Proposition
• Instant cloud launch; nothing to install or maintain
• Enterprise-wide application for MR, HR, social, and legal use cases
• Unique functional capabilities including:
• De-duplication and clustering algorithms
• Custom machine classifiers & word sense disambiguation tools
• Reusable and scalable language models
• Custom search & filtering
• Fast, accurate, distributed, crowd source human coding
• Patent in 2016: “CoderRank for enhanced machine learning”

9. Patent issued 2016 and trademark issued in 2017
Intellectual Property
CoderRank is to text analytics what PageRank was to search.
Just as Google assumes not all web pages are created equal,
Texifter argues that not all humans are created equal. When
training machines, it is best to rely on the humans most likely
to create valid observations. We proposed a unique way to
rank humans on trust and knowledge vectors.

10. Current Market Niche
• Large-scale survey, social, email, and public comment analytics
• Multi-channel market research and voice of customer engagement
• Human resources for employee engagement
• Government agencies (GSA Schedule 70 contract vehicle)
• Legal eDiscovery and document redaction
• Not #bigdata
• The more neglected and common #mediumdata problems
• Optimal projects currently in 10,000-1,000,000 document range

11. Competition

12. Target Opportunity: Owners of App/Product Reviews
Requirements:
Rebuild as Big Data Solution Running on Linux
Time & Cost to Beta: 6 months and $500,000

13. Some of Our Past & Current Customers