Enterprise Investment Scheme

Total investments

8

Average round size

2M

Portfolio companies

6

Lead investments

2

Follow on index

0.25

Areas of investment
SoftwareFood ProcessingAppsManufacturingVirtual RealityEventsTelecommunicationsMedia and EntertainmentService IndustryWeb Hosting

Summary

We also calculated 4 valuable employees in our database.

The usual cause for the fund is to invest in rounds with 2 partakers. Despite the Enterprise Investment Scheme, startups are often financed by Venture Capital Trust, Millhouse LLC, Low Carbon Innovation Fund. The meaningful sponsors for the fund in investment in the same round are Calculus Capital, Venture Capital Trust. In the next rounds fund is usually obtained by Calculus Capital.

Moreover, a startup needs to be at the age of 6-10 years to get the investment from the fund. Among the various public portfolio startups of the fund, we may underline Weedingtech We can highlight the next thriving fund investment areas, such as Fitness, Sports.

The fund is constantly included in less than 2 deals per year. The top activity for fund was in 2017. The usual things for fund are deals in the range of 1 - 5 millions dollars. Considering the real fund results, this VC is 5 percentage points more often commits exit comparing to other organizations.

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Investments analytics

Analytics

Total investments
8
Lead investments
2
Follow on index
0.25
Investments by industry
  • Telecommunications (3)
  • Service Industry (3)
  • Web Hosting (2)
  • Virtual Reality (2)
  • Events (2)
  • Show 13 more
Investments by region
  • United Kingdom (7)
  • Belgium (1)
Peak activity year
2017

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Quantitative data

Avg. startup age at the time of investment
9
Avg. valuation at time of investment
2M
Group Appearance index
0.50

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Latest deals

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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.