KMN Capital

Total investments

2

Average round size

7M

Portfolio companies

2

Exits

2

Areas of investment
InternetSoftwareRetail TechnologyApps

Summary

The fund is constantly included in less than 2 deals per year. Deals in the range of 10 - 50 millions dollars are the general things for fund. The top activity for fund was in 2004. When the investment is from KMN Capital the average startup value is 100-500 millions dollars. The increased amount of exits for fund were in 2006.

The usual cause for the fund is to invest in rounds with 7-8 partakers. Despite the KMN Capital, startups are often financed by Viola Credit, Nippon Investment & Finance Co. Ltd. (NIF), Earlybird Venture Capital. The meaningful sponsors for the fund in investment in the same round are Vertex Ventures, Vertex Ventures Israel, Valley Venture Capital. In the next rounds fund is usually obtained by Vertex Ventures, Viola Credit.

Besides, a startup needs to be aged 6-10 years to get the investment from the fund. Among the most successful fund investment fields, there are Retail Technology, Apps. Among the various public portfolio startups of the fund, we may underline MoreCom, Identify Software

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Investments analytics

Analytics

Total investments
2
Lead investments
0
Exits
2
Investments by industry
  • Retail Technology (1)
  • Software (1)
  • Internet (1)
  • Apps (1)
Investments by region
  • Israel (1)
  • United States (1)
Peak activity year
1997

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Quantitative data

Avg. startup age at the time of investment
24
Avg. valuation at time of investment
355M
Group Appearance index
1.00
Avg. company exit year
6
Avg. multiplicator
28.44

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
Identify Software 31 Jan 2004 Internet, Software, Apps Early Stage Venture 15M North District, Israel, Israel
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.