Total investments

2

Average round size

125M

Portfolio companies

2

Rounds per year

0.02

Areas of investment
SoftwareInformation TechnologyArtificial IntelligenceSecurity

Summary

In 1937 was created Saab, which is appeared as Corporate Investor. The company was established in Europe in Sweden. The main department of described Corporate Investor is located in the Stockholm.

The top activity for fund was in 2008. Deals in the range of 1 - 5 millions dollars are the general things for fund. The fund is constantly included in less than 2 investment rounds annually.

We can highlight the next thriving fund investment areas, such as Security. For fund there is no match between the country of its foundation and the country of its the most frequent investments - Norway. Besides, a startup requires to be at the age of 6-10 years to receive the investment from the fund. Among the most popular portfolio startups of the fund, we may highlight Opax.

The standard case for the fund is to invest in rounds with 2 partakers. The meaningful sponsors for the fund in investment in the same round are Equinor.

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Investments analytics

Analytics

Total investments
2
Lead investments
0
Rounds per year
0.02
Investments by industry
  • Software (2)
  • Security (1)
  • Information Technology (1)
  • Artificial Intelligence (1)
Investments by region
  • Germany (1)
  • Norway (1)
Peak activity year
2008
Number of Unicorns
1
Number of Decacorns
1

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Quantitative data

Avg. startup age at the time of investment
12
Avg. valuation at time of investment
885M
Group Appearance index
1.00
Strategy success index
0.75

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
Helsing 14 Sep 2023 Software, Information Technology, Artificial Intelligence Early Stage Venture 246M Berlin, Berlin, 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.