Scrum Ventures

Type

Venture Capital

Status

Active

Location

San Francisco, United States

Total investments

106

Average round size

6M

Portfolio companies

75

Rounds per year

9.64

Lead investments

1

Follow on index

0.25

Exits

12

Stages of investment
SeedEarly Stage Venture
Areas of investment
E-CommerceInternetSoftwareInformation TechnologyMobileArtificial IntelligenceHealth CareAppsBig DataRobotics

Summary

Scrum Ventures appeared to be the VC, which was created in 2013. The main office of represented VC is situated in the San Francisco. The company was established in North America in United States.

The standard case for the fund is to invest in rounds with 6-7 partakers. Despite the Scrum Ventures, startups are often financed by FundersClub, 500 Startups, Polaris Partners. The meaningful sponsors for the fund in investment in the same round are 500 Startups, Lerer Hippeau, Polaris Partners. In the next rounds fund is usually obtained by FundersClub, Y Combinator, Polaris Partners.

The current fund was established by Tak Miyata. We also calculated 4 valuable employees in our database.

Comparing to the other companies, this Scrum Ventures performs on 18 percentage points less the average number of lead investments. Considering the real fund results, this VC is 18 percentage points less often commits exit comparing to other organizations. The top activity for fund was in 2014. Despite it in 2019 the fund had an activity. The usual things for fund are deals in the range of 5 - 10 millions dollars. The top amount of exits for fund were in 2016. The fund is constantly included in 7-12 deals per year. When the investment is from Scrum Ventures the average startup value is 10-50 millions dollars.

Among the most popular portfolio startups of the fund, we may highlight LE TOTE, Noom, Share Practice. 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 Mobile, Robotics. The fund has specific favorite in a number of founders of portfolio startups. If startup sums 5+ of the founder, the chance for it to be financed is low. Besides, a startup needs to be aged 2-3 years to get the investment from the fund.

Show more

Investor highlights

Industry generalist
Yes
Industry focus
GeneralistMobilityFintechIoTAR/VR Show 4 more
Stage focus
Series ASeed
Geo focus
JapanUnited States
Check size
200K — 2M

Discover reliable insights

Find relevant VC investors, identify key contacts and secure funding opportunities.

Investments analytics

Analytics

Total investments
106
Lead investments
1
Exits
12
Rounds per year
9.64
Follow on index
0.25
Investments by industry
  • Information Technology (16)
  • Software (16)
  • Health Care (15)
  • E-Commerce (14)
  • Mobile (13)
  • Show 149 more
Investments by region
  • United States (83)
  • Japan (13)
  • China (2)
  • United Kingdom (1)
  • Israel (1)
Peak activity year
2014
Number of Unicorns
2
Number of Decacorns
2

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
7
Avg. valuation at time of investment
83M
Group Appearance index
0.99
Avg. company exit year
6
Avg. multiplicator
3.09
Strategy success index
0.40

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
Empowerly 06 Oct 2020 Internet, Information Technology, Higher Education, Education, Universities Seed 2M United States, California, San Francisco
Project Admission 23 Jun 2023 E-Commerce, Events, Sports, Ticketing Seed 3M United States, Nashville, Tennessee
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.