Signia Venture Partners

Type

Venture Capital

Status

Active

Location

Menlo Park, United States

Total investments

126

Average round size

10M

Portfolio companies

82

Rounds per year

11.45

Lead investments

12

Follow on index

0.34

Exits

21

Stages of investment
SeedEarly Stage Venture
Areas of investment
Real EstateSoftwareInformation TechnologyMobileGamingFinanceSaaSAppsMobile AppsAdvertising

Summary

In 2012 was created Signia Venture Partners, which is appeared as VC. The main department of described VC is located in the Menlo Park. The fund was located in North America if to be more exact in United States.

The current fund was established by Ed Cluss, Rick Thompson, Sunny Dhillon, Zaw Thet. We also calculated 8 valuable employees in our database.

The standard case for the fund is to invest in rounds with 5-6 partakers. Despite the Signia Venture Partners, startups are often financed by Data Collective DCVC, Morado Ventures, Webb Investment Network. The meaningful sponsors for the fund in investment in the same round are Morado Ventures, Index Ventures, Founders Fund. In the next rounds fund is usually obtained by Data Collective DCVC, Morado Ventures, Index Ventures.

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 Gaming, Apps. Among the various public portfolio startups of the fund, we may underline Cruise Automation, Udemy, Sense Moreover, a startup needs to be at the age of 2-3 years to get the investment from the fund. The fund has no exact preference in a number of founders of portfolio startups. In case when startup counts 5+ of the founder, the chance for it to get the investment is meager.

The fund is constantly included in 2-6 deals per year. The usual things for fund are deals in the range of 5 - 10 millions dollars. Opposing the other organizations, this Signia Venture Partners works on 12 percentage points less the average amount of lead investments. The high activity for fund was in 2011. Despite it in 2019 the fund had an activity. The increased amount of exits for fund were in 2014. Considering the real fund results, this VC is 0 percentage points less often commits exit comparing to other organizations.

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Investor highlights

Industry generalist
Yes
Industry focus
GeneralistSecurityCybersecurityGoodsGaming/Esports
Stage focus
Seed
Geo focus
Generalist
Check size
500K — 3M

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Investments analytics

Last fund

Fund size
USD 85000000
Fund raised date
2019-09-06

Analytics

Total investments
126
Lead investments
12
Exits
21
Rounds per year
11.45
Follow on index
0.34
Investments by industry
  • Software (35)
  • Information Technology (19)
  • Mobile (18)
  • Advertising (13)
  • Gaming (13)
  • Show 140 more
Investments by region
  • United States (116)
  • China (4)
  • Norway (1)
  • Colombia (1)
  • Finland (1)
  • Show 2 more
Peak activity year
2017
Number of Unicorns
1
Number of Decacorns
2
Number of Minotaurs
1

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Quantitative data

Avg. startup age at the time of investment
8
Avg. valuation at time of investment
79M
Group Appearance index
0.90
Avg. company exit year
4
Avg. multiplicator
0.09
Strategy success index
0.30

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
AION Prosthetics 04 Mar 2021 Robotics, Manufacturing, Medical Device, Electronics Seed 100K United States, Nebraska, Lincoln
Cryptolab Inc. 29 Aug 2017 Software, Cyber Security, Cloud Computing, Information and Communications Technology (ICT), Search Engine Seed 300K United States, California, San Jose
Kintsugi 15 Aug 2023 Seed 2M United States, California, San Francisco
Waitroom 23 Mar 2022 Enterprise Software, Video Streaming, Video Conferencing Seed 3M United States, California, La Jolla

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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.