Nebari Ventures

Total investments

5

Average round size

8M

Portfolio companies

5

Rounds per year

0.83

Exits

2

Stages of investment
Early Stage VentureLate Stage Venture
Areas of investment
Consumer GoodsFood and BeverageFood ProcessingOil and GasSnack FoodMiningPrecious MetalsMineral

Summary

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

The fund is generally included in less than 2 deals every year. The high activity for fund was in 2018. The typical startup value when the investment from Nebari Ventures is 10-50 millions dollars. Deals in the range of 5 - 10 millions dollars are the general things for fund.

We can highlight the next thriving fund investment areas, such as Consumer Goods, Food and Beverage.

The typical case for the fund is to invest in rounds with 9-10 participants. Despite the Nebari Ventures, startups are often financed by Yale University, Vast Ventures, Simon Ventures. The meaningful sponsors for the fund in investment in the same round are Tim Armstrong, TGZ Capital, TACK Ventures.

We also calculated 1 valuable employee in our database.

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Investments analytics

Analytics

Total investments
5
Lead investments
0
Exits
2
Rounds per year
0.83
Investments by industry
  • Food and Beverage (3)
  • Mining (2)
  • Food Processing (1)
  • Consumer Goods (1)
  • Snack Food (1)
  • Show 3 more
Investments by region
  • United States (3)
  • Canada (1)
  • Australia (1)
Peak activity year
2018

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Quantitative data

Avg. startup age at the time of investment
8
Avg. valuation at time of investment
9M
Group Appearance index
0.60
Avg. company exit year
-20

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
Iris Nova 20 Dec 2018 Consumer Goods, Food and Beverage Seed 15M United States, New York, New York

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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.