Havenrock

Total investments

3

Average round size

5M

Portfolio companies

2

Lead investments

1

Follow on index

0.33

Areas of investment
Asset ManagementFinTechAnalyticsFinanceArtificial IntelligenceMachine LearningBig DataPredictive AnalyticsNatural Language ProcessingData Visualization

Summary

Among the most popular fund investment industries, there are Machine Learning, Asset Management. Besides, a startup needs to be aged 4-5 years to get the investment from the fund. Among the most popular portfolio startups of the fund, we may highlight SESAMm.

The usual cause for the fund is to invest in rounds with 3 partakers. Despite the Havenrock, startups are often financed by Pole Capital, Caisse du2019Epargne, Bourgogne Angels. The meaningful sponsors for the fund in investment in the same round are Caisse du2019Epargne, Angelsquare.

The important activity for fund was in 2019. The fund is constantly included in less than 2 deals per year. The common things for fund are deals in the range of 1 - 5 millions dollars.

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Investments analytics

Analytics

Total investments
3
Lead investments
1
Follow on index
0.33
Investments by industry
  • Finance (3)
  • Artificial Intelligence (2)
  • Predictive Analytics (2)
  • Machine Learning (2)
  • Data Visualization (2)
  • Show 8 more
Investments by region
  • France (3)
Peak activity year
2019

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Quantitative data

Avg. startup age at the time of investment
6
Group Appearance index
0.67

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
SESAMm 28 Jan 2021 Asset Management, Impact Investing, FinTech, Analytics, Finance, Artificial Intelligence, Machine Learning, Big Data, Predictive Analytics, Natural Language Processing, Data Visualization Early Stage Venture 8M Ile-de-France, Paris, France
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.