University of Michigan MINTS fund
7
6M
6
1
0.14
- Areas of investment
Summary
The standard case for the fund is to invest in rounds with 3-4 partakers. Despite the University of Michigan MINTS fund, startups are often financed by The Amherst Fund, Intel Capital, The Frankel Fund. The meaningful sponsors for the fund in investment in the same round are The Amherst Fund, Stata Venture Partners, North Coast Technology Investors. In the next rounds fund is usually obtained by Small Business Innovation Research.
The top activity for fund was in 2018. The common things for fund are deals in the range of 5 - 10 millions dollars. The fund is constantly included in 2-6 deals per year.
Among the most popular fund investment industries, there are Nanotechnology, Biotechnology. Besides, a startup requires to be at the age of 6-10 years to receive the investment from the fund. The fund has exact preference in some founders of portfolio startups. Among the various public portfolio startups of the fund, we may underline BlueWillow Biologics, Movellus, Fusion Coolant Systems
Investments analytics
Analytics
- Total investments
- 7
- Lead investments
- 1
- Follow on index
- 0.14
- Investments by industry
- Biotechnology (4)
- Medical (3)
- Information Technology (3)
- Health Care (2)
- Electronic Design Automation (EDA) (1) Show 10 more
- Investments by region
-
- United States (7)
- Peak activity year
- 2019
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
- 9
- Group Appearance index
- 1.00
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 |
---|---|---|---|---|---|
MemryX | 12 May 2021 | Information Technology, Artificial Intelligence | Early Stage Venture | United States, Ann Arbor, Michigan |
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.