Koala Fund

Total investments

36

Average round size

7M

Portfolio companies

33

Lead investments

8

Follow on index

0.08

Stages of investment
SeedEarly Stage Venture
Areas of investment
SoftwareFinancial ServicesAnalyticsInformation TechnologyHuman ResourcesRecruitingInformation ServicesFinanceArtificial IntelligenceConsulting

Summary

The typical case for the fund is to invest in rounds with 2-3 participants. Despite the Koala Fund, startups are often financed by Triniti Capital, ShareLink Capital, Dark Horse Ventures. The meaningful sponsors for the fund in investment in the same round are ShareLink Capital, Triniti Capital, PurpleSky Capital. In the next rounds fund is usually obtained by ShareLink Capital, Lakala, Dark Horse Ventures.

Among the most popular portfolio startups of the fund, we may highlight Mofang HR. Among the most successful fund investment fields, there are Artificial Intelligence, Human Resources. Moreover, a startup needs to be at the age of 1 and less years to get the investment from the fund.

Considering the real fund results, this VC is 0 percentage points less often commits exit comparing to other organizations. The usual things for fund are deals in the range of 5 - 10 millions dollars. The high activity for fund was in 2017. The fund is constantly included in less than 2 deals per year.

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Investments analytics

Analytics

Total investments
36
Lead investments
8
Follow on index
0.08
Investments by industry
  • Information Technology (7)
  • Financial Services (5)
  • Software (4)
  • Analytics (4)
  • Consulting (4)
  • Show 57 more
Investments by region
  • China (34)
  • Germany (1)
Peak activity year
2017

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Quantitative data

Avg. startup age at the time of investment
6
Group Appearance index
0.86

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
KeenData 18 May 2022 Information Services, Consulting, Database Early Stage Venture 15M Liaoning, Chaoyang, China
Riskeys 01 May 2017 Seed
How we get our data

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.