Sharing Capital
2
1M
1
0.33
- Areas of investment
Summary
The fund was located in Asia if to be more exact in China. The main department of described VC is located in the Shanghai.
The high activity for fund was in 2015. The fund is generally included in less than 2 deals every year. The usual things for fund are deals in the range of 10 - 50 millions dollars.
Moreover, a startup needs to be at the age of 1 and less years to get the investment from the fund. We can highlight the next thriving fund investment areas, such as Tutoring, Apps. For fund there is a match between the country of its foundation and the country of its the most frequent investments - China. Among the various public portfolio startups of the fund, we may underline Entstudy.com
The usual cause for the fund is to invest in rounds with 2 partakers. The meaningful sponsors for the fund in investment in the same round are Kun Ling Capital. In the next rounds fund is usually obtained by Yuanxi Capital, Tencent Holdings, Greenwoods Investment.
Investments analytics
Analytics
- Total investments
- 2
- Lead investments
- 0
- Rounds per year
- 0.33
- Investments by industry
- Information Services (1)
- Information Technology (1)
- Online Portals (1)
- Investments by region
-
- China (1)
- Peak activity year
- 2015
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
- 8
- Group Appearance index
- 1.00
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 |
|---|---|---|---|---|---|
| Xiaoyuan Siling | 01 Jun 2015 | Information Technology, Online Portals, Information Services | Early Stage Venture | 3M | China, Baoshan District |
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.