Iron Fund
2
1M
2
0.33
1
- Stages of investment
- Areas of investment
Summary
In 2015 was created Iron Fund, which is appeared as VC. The venture was found in North America in United States. The main department of described VC is located in the Atlanta.
The usual cause for the fund is to invest in rounds with 1 partaker. In the next rounds fund is usually obtained by TechSquare Ventures ., TechSquare Labs, David Krantz.
Among the various public portfolio startups of the fund, we may underline Hirewire For fund there is a match between the country of its foundation and the country of its the most frequent investments - United States. Among the most popular fund investment industries, there are Human Resources, Mobile Payments.
The fund is generally included in less than 2 deals every year. Deals in the range of 1 - 5 millions dollars are the general things for fund. The top activity for fund was in 2015.
Investments analytics
Analytics
- Total investments
- 2
- Lead investments
- 1
- Rounds per year
- 0.33
- Investments by industry
- Mobile Apps (2)
- Internet (1)
- Marketplace (1)
- Employment (1)
- Human Resources (1) Show 2 more
- Investments by region
-
- United States (2)
- Peak activity year
- 2015
Discover reliable insights
Leverage validated data, identify key contacts and secure funding opportunities for your business.Quantitative data
- Avg. startup age at the time of investment
- 5
Need more data?
Get access to full data about investors, including their team, contact information, and historic data.
Latest deals
| Company name | Deal date | Industry | Deal stage | Deal size | Location |
|---|---|---|---|---|---|
| 01 Mar 2018 | Consumer, Mobile Apps, Mobile Payments | Seed | United States, Atlanta, Georgia |
Similar funds
By same location
By same geo focus
By doing lead investments
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.