Cognitive Investment
11
3M
6
1
0.20
- Areas of investment
Summary
The overall number of key employees were 1.
Deals in the range of 5 - 10 millions dollars are the general things for fund. The fund is constantly included in less than 2 investment rounds annually. The important activity for fund was in 2017.
The typical case for the fund is to invest in rounds with 3-4 participants. Despite the Cognitive Investment, startups are often financed by Kakao Ventures, SGI Venture Capital, NCSOFT. The meaningful sponsors for the fund in investment in the same round are Songhyun Investment, Neoplux, MG Investment. In the next rounds fund is usually obtained by Stonebridge Ventures, Kakao Ventures.
Among the various public portfolio startups of the fund, we may underline Watcha We can highlight the next thriving fund investment areas, such as Personalization, Video Streaming. Besides, a startup requires to be at the age of 6-10 years to receive the investment from the fund.
Investments analytics
Analytics
- Total investments
- 11
- Lead investments
- 1
- Follow on index
- 0.20
- Investments by industry
- Apps (2)
- Food and Beverage (2)
- Content (1)
- Point of Sale (1)
- Ticketing (1) Show 5 more
- Investments by region
-
- South Korea (5)
- Japan (1)
- Peak activity year
- 2018
Discover reliable insights
Leverage validated data, identify key contacts and secure funding opportunities for your business.Quantitative data
- Avg. startup age at the time of investment
- 7
- Avg. valuation at time of investment
- 609K
Need more data?
Get access to full data about investors, including their team, contact information, and historic data.
Latest deals
Company name | Deal date | Industry | Deal stage | Deal size | Location |
---|---|---|---|---|---|
LATELY | 01 Apr 2018 | E-Commerce, Fashion | Early Stage Venture | 2M | Seoul, Seoul-t'ukpyolsi, South Korea |
At Unicorn Nest, we combine cutting-edge technology with human expertise to build one of the most reliable venture capital databases in the market. Our process begins with automated AI-enhanced data collection, leveraging the full potential of Large Language Models (LLMs).
Later, our team of analysts takes it further with manual verification, using proprietary tools for data cleaning and validation to ensure accuracy and reliability. We cross-check and enhance our findings through press and media monitoring, integrating information from trusted news outlets and venture capital aggregators. Finally, we stay ahead of the curve by monitoring social networks like LinkedIn and X.com.