South Coast Angel Network

Total investments

2

Average round size

2M

Portfolio companies

2

Lead investments

1

Areas of investment
BiotechnologyAnalyticsRetail TechnologyHealth CareMarketingBrand MarketingHuman Computer Interaction

Summary

Besides them, we counted 2 critical employees of this fund in our database.

The usual things for fund are deals in the range of 1 - 5 millions dollars. The important activity for fund was in 2017. The fund is constantly included in less than 2 investment rounds annually.

The typical case for the fund is to invest in rounds with 6 participants. Despite the South Coast Angel Network, startups are often financed by Dreamit Ventures. The meaningful sponsors for the fund in investment in the same round are VisionTech Angels, Spring Mill Venture Partners, Queen City Angels. In the next rounds fund is usually obtained by Align Capital.

Moreover, a startup needs to be at the age of 6-10 years to get the investment from the fund. Among the most popular fund investment industries, there are Marketing, Human Computer Interaction. The fund has no exact preference in a number of founders of portfolio startups. Among the various public portfolio startups of the fund, we may underline eyeQ, SonarMed

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Investments analytics

Analytics

Total investments
2
Lead investments
1
Investments by industry
  • Biotechnology (1)
  • Health Care (1)
  • Human Computer Interaction (1)
  • Analytics (1)
  • Retail Technology (1)
  • Show 2 more
Investments by region
  • United States (2)
Peak activity year
2017

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Quantitative data

Avg. startup age at the time of investment
13
Avg. valuation at time of investment
4M
Group Appearance index
1.00

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
SonarMed 24 Oct 2017 Biotechnology, Health Care Late Stage Venture 3M United States, Indianapolis, Indiana
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.