Company profile
Channel
Exhibition Participation History
#SEOUL VRAR EXPO 2021
Company Overview
Representative
Park Seon-gyu
Company Type
Service
Year founded
2015
Business
Service
Event
IT·Information Communication
Number of employees
5 to 49 people
Annual turnover
More than KRW 1 billion ~ less than KRW 12 billion
Address
278 Beotkkot-ro, Geumcheon-gu, Seoul (Gasan-dong)
Featured Products
Metaverse Online Exhibition
Representative number
+82-504-1361-0648
Company Introduction
No. 1 online exhibition solutions provider Immersive metaverse content platform
Competitive edge
Dataking has the following competitive advantages:
1) The company has a broad lineup of platforms satisfying the essential requirements of contactless living (social distancing, travel restrictions, contactless transactions, etc.). As it began nurturing these businesses even before the COVID-19 outbreak, the company is better-positioned than rivals to capitalize on market growth. 2) All of the company’s solutions are executed via online streaming (no downloads required). As such, its market penetration should increase rapidly with 5G deployment. 3) The company’s core technology, computer vision-based object detection and content curation utilizing neural-network learning methods, is expected to generate added value over the long term thanks to the accumulation of user behavioral data.
Competitive edge
Dataking has the following competitive advantages:
1) The company has a broad lineup of platforms satisfying the essential requirements of contactless living (social distancing, travel restrictions, contactless transactions, etc.). As it began nurturing these businesses even before the COVID-19 outbreak, the company is better-positioned than rivals to capitalize on market growth. 2) All of the company’s solutions are executed via online streaming (no downloads required). As such, its market penetration should increase rapidly with 5G deployment. 3) The company’s core technology, computer vision-based object detection and content curation utilizing neural-network learning methods, is expected to generate added value over the long term thanks to the accumulation of user behavioral data.
