Cliqus is a free web and mobile engine that suggests the most relevant information to you based on your specific interests. How? By learning how other users with similar interests react to information that might interest you. Yep, that is social filtering.

2. Problem
Faster than real time…
…So much info, so little time.
In all the Internet, and while I have those 5
minutes…
What is most interesting?
What is most useful?

3. Whose problem is that?
• He / She works or studies
• Has limited time to browse entertainment
content
• Does not want to waste that time in vain on low
quality and irrelevant information

4. How many such people are there?
• 18-34 age groups*
• Have FB account
• Are active mobile users
Around 450 - 500 million users globally
*Most active FB user groups, acc to FB statistics

5. Solution
CLIQUS web and mobile
Collaborative filtering Most relevant info
by people with in least time
similar interests

6. HOW?
1. Users browse and react to info
2. Cliqus learns likes of each user
3. Cliqus builds a network cloud of like-minded
people
4. Cliqus shows each user relevant info,
“approved” by relevant people

7. Benefits
• Convenient: No active search needed
• Accurate: human, not machine filtering
• More fun: users are masters of their free time

8. Company revenue is made on
Step 1: Affiliate advertizing
Step 2: Fremium mobile apps
Step 3: Social advertising
Step 4: Recommendation engine API for
service providers

9. Competition
Different from Google News:
• In Google News user is a passive consumer
• In CLIQUS user is an active creator
CLIQUS is more than news.

10. Competition
Different from FB Wall:
• FB Wall – irrelevant content from irrelevant
people
• CLIQUS – targeted only at relevant information

11. Competition
Different from social media aggregators:
• Social media aggregators – irrelevant information
overflow, user is lost
• CLIQUS – select and valuable information is
displayed, user navigates easily

12. Competition
Different from StumbleUpon and delicious:
• StumbleUpon and delicious force users to
make an action
• CLIQUS just watches users’ behavior

13. Exit plan
SaaS recommendation engine:
• Can be plugged into any web store
• Based on human filtering and collaborative
recommendation
• More relevant than Amazon recommendation
engine

14. Team
Valeriy Kamensky, Developer Eugene Volchek, Architect, Developer
6 years in community systems and B2C/C2C 7 years in enterprise system development
portals development
Brings innovation to proven standards
Managed teams of 5-15 people
Understands core principles of how CLIQUS
Solves operational challenges of the growing should work
system
Pavel Avramenko, Business Development Darya Nehaychik, Marketing
15 years in IT on technical and managerial
positions 6 years in sales and marketing in IT
sphere
Founder and CEO of mobile applications Processes around 50 startup project
Development and publishing company requests per year
Defines product development strategy Strong skills: positioning, branding,
target market identification and approach

15. Our contact information
Klika Technologies
Floor 1, 3 Chapaev str.
Minsk 220000 Belarus
+375 29 757 3138
info@cliqus.com
www.cliqus.com