Digital Tech Fund

Total investments

5

Average round size

2M

Portfolio companies

3

Lead investments

2

Follow on index

0.40

Areas of investment
LogisticsTransportationSoftwareHealth CareSaaSManufacturingConsultingTourismFleet ManagementTravel Agency

Summary

Moreover, a startup needs to be at the age of 4-5 years to get the investment from the fund. Among the most popular portfolio startups of the fund, we may highlight Nektria. We can highlight the next thriving fund investment areas, such as Health Care, Transportation.

The usual cause for the fund is to invest in rounds with 3-4 partakers. Despite the Digital Tech Fund, startups are often financed by VCDE Venture Partners, HOWZAT Partners, Fabrice Grinda. The meaningful sponsors for the fund in investment in the same round are VCDE Venture Partners, HOWZAT Partners, BA4V. In the next rounds fund is usually obtained by VCDE Venture Partners, HOWZAT Partners, BA4V.

The fund is constantly included in less than 2 investment rounds annually. The real fund results show that this VC is 40 percentage points more often commits exit comparing to other companies. The common things for fund are deals in the range of 1 - 5 millions dollars. The top activity for fund was in 2017.

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Investments analytics

Analytics

Total investments
5
Lead investments
2
Follow on index
0.40
Investments by industry
  • Transportation (4)
  • Tourism (3)
  • Travel Agency (3)
  • Manufacturing (1)
  • Health Care (1)
  • Show 6 more
Investments by region
  • Germany (3)
  • Luxembourg (1)
  • Spain (1)
Peak activity year
2018

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Quantitative data

Avg. startup age at the time of investment
9
Avg. valuation at time of investment
1M
Group Appearance index
0.80

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
itravel 03 May 2017 Transportation, Tourism, Travel Agency Early Stage Venture 3M North Rhine-Westphalia, Cologne, Germany
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.