This document discusses a solution for improving real-time engagement between humans and machines using collaborative intelligence. It proposes a plug-and-play chat widget and real-time AI engine that can understand customer intentions, suggest answers, and learn continuously from interactions. This solution aims to enhance customer experiences at scale while reducing costs by optimizing human workforces with machine support. It also describes plans to launch related products called Cognospot and Convospot that apply natural language processing and analytics to modern chat platforms.

1. Real-time engagement with human and machine collaborative intelligence

2. Problem
• Effectiveness of online communication
• Cost and scalability of real-time engagement
• Complexity of adopting Machine learning and AI technology

3. What we hear is the need for…
• A mechanism to collect structured and unstructured data in a anonymous
environment
• Algorithms making decisions in real-time
• A platform that supports digital personalization at scale
Executives talk about data and efficiency every day…
• “Do more with less”
• “We could provide a better user experience, but need more people to
scale”
• “With the right data and tools we could get more done”
Challenge

4. An end-to-end cognitive software that brings real-time understanding and engagement to your
customers.
Solution
Plug and play
chat Widget
Real-time A.I
Engine
Knowledge
management
Scales through automation
Superior service with decision support
Reduces cost by optimizing workforce
Monitors activities
Rich user experiences
Easy to implement code
Creates new opportunity
Utilizes experts
Trains & onboards new staff

5. S.U.R.E.
Understand
ReasonEngage
Sense

6. convospot: live engagement and decision support on the “spot”
A plug and play AI service that enhances real-time engagement by collecting intentions and suggesting answers
from natural language understanding (MVP Feb 2018).
cognospot: enhance agent capacity by cognitive computing
The complete version of our cognitive platform which has real-time actionable engagement, deep behavior
understanding, and continuous interactive learning. (early validation)
Product

7. Martech industry worth
$34B in 2017
50% respondents say
they don’t have the
tools they need yet.
16% of technology
budgets going to
martech.
Streaming Analytics
Market
$ 3.08B 2016
$13.7B by 2021
CAGR 34.8%
Driven by: IOT,
Increases in data,
rising spend on real-
time analytics
Online Chat to
grow to $987M in
NA by 2021
● Online Chat
○ B2B companies using chat on
average see a 20% increase in
conversions
○ Live chat is more than 50% cheaper
than handling phone calls.
● There will be a great demand in different large markets for AI and ML
applied solutions
● General e-commerce conversion range 2-3%
● Our offering will increase that % and drive revenue
● A better digital experience built from personalized messaging will extend
brands and also add to the top line
Market

8. Cognospot
Convospot
Competition

9. Real Time Analytics Modern Chat
Cognospot
SaaS + Professional Service
○ The entire cognitive
platform
○ Deeper contextual
understanding of user
behavior
○ Intention analytics
○ API & SDK
Convospot
SaaS
○ Take advantage of our augmented
approach to modern chat
○ Show the value of real-time
engagement aided by analytics
○ Bring “Big data” value to small
companies without the IT investment
Large
Enterprise
SMB
Mid market
Enterprise
Business Model

10. Homer Quan
CTO and co-founder
Chief architecture at Wise
System(Techstar 15)
Yahoo News & Search
Jim LaMarche
CEO and co-founder
Director Cloud Partnerships
at Plumchoice
Sales, Chl Mgt & Global
Business development at
Cisco
Liu Qiang
Mentor on Machine Learning
Assistant Professor at UT Austin
Team