Angivest Ventures

Total investments

3

Average round size

2M

Portfolio companies

3

Rounds per year

0.60

Stages of investment
Seed
Areas of investment
E-CommerceSoftwareInformation TechnologyB2BRetail TechnologyEnterpriseArtificial IntelligenceMachine LearningSaaSBrand Marketing

Summary

In 2017 was created Angivest Ventures, which is appeared as VC.

When the investment is from Angivest Ventures the average startup value is 5-10 millions dollars. The fund is generally included in less than 2 deals every year. The high activity for fund was in 2018. The common things for fund are deals in the range of 1 - 5 millions dollars.

Among the most popular portfolio startups of the fund, we may highlight COMMERCE.AI. Moreover, a startup needs to be at the age of 1 and less years to get the investment from the fund. Among the most successful fund investment fields, there are Internet, Software.

The typical case for the fund is to invest in rounds with 5 participants. Despite the Angivest Ventures, startups are often financed by monashees, Wayra, Plug and Play. The meaningful sponsors for the fund in investment in the same round are Plug and Play, Alchemist Accelerator, monashees.

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Investments analytics

Analytics

Total investments
3
Lead investments
0
Rounds per year
0.60
Investments by industry
  • SaaS (2)
  • B2B (2)
  • Information Technology (1)
  • Retail Technology (1)
  • Machine Learning (1)
  • Show 7 more
Investments by region
  • United States (3)
Peak activity year
2018

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Quantitative data

Avg. startup age at the time of investment
6
Avg. valuation at time of investment
2M
Group Appearance index
1.00

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
back4app 03 May 2018 Internet, Software, B2B, SaaS, PaaS Seed 730K United States, California, Sunnyvale
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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.