Omidyar Ventures

Type

Venture Capital

Status

Active

Location

Redwood City, United States

Total investments

23

Average round size

26M

Portfolio companies

14

Rounds per year

2.56

Lead investments

2

Follow on index

0.35

Exits

2

Areas of investment
Freight ServiceTransportationSoftwareInformation TechnologyHuman ResourcesArtificial IntelligenceMachine LearningSaaSEnterprise SoftwareDeveloper APIs

Summary

In 2015 was created Omidyar Technology Ventures, which is appeared as VC. The main department of described VC is located in the Redwood City. The venture was found in North America in United States.

The current fund was established by Pierre Omidyar. We also calculated 2 valuable employees in our database.

The important activity for fund was in 2018. Comparing to the other companies, this Omidyar Technology Ventures performs on 16 percentage points less the average number of lead investments. When the investment is from Omidyar Technology Ventures the average startup value is 100-500 millions dollars. The fund is constantly included in less than 2 deals per year. The increased amount of exits for fund were in 2016. Speaking about the real fund results, this VC is 7 percentage points less often commits exit comparing to other organizations. The common things for fund are deals in the range of 10 - 50 millions dollars.

The typical case for the fund is to invest in rounds with 6-7 participants. Despite the Omidyar Technology Ventures, startups are often financed by Chicago Ventures, Allen & Company, Sierra Ventures. The meaningful sponsors for the fund in investment in the same round are Emergence, Sigma Prime Ventures, Sierra Ventures. In the next rounds fund is usually obtained by Singtel Innov8, Red Sea Ventures, Greylock Partners.

The fund has no exact preference in some founders of portfolio startups. When startup sums 4 or 5+ of the founder, the probability for it to get the investment is little. Besides, a startup requires to be at the age of 4-5 years to receive the investment from the fund. We can highlight the next thriving fund investment areas, such as Transportation, Machine Learning. Among the various public portfolio startups of the fund, we may underline Convoy, Fundbox, Attivo Networks For fund there is a match between the location of its establishment and the land of its numerous investments - United States.

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Investor highlights

Industry focus
B2B/EnterpriseAI/Big DataFintechEcommerce
Geo focus
Generalist

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Investments analytics

Analytics

Total investments
23
Lead investments
2
Exits
2
Rounds per year
2.56
Follow on index
0.35
Investments by industry
  • Software (8)
  • Transportation (6)
  • Freight Service (6)
  • Artificial Intelligence (6)
  • SaaS (6)
  • Show 45 more
Investments by region
  • United States (18)
  • Canada (1)
  • India (2)
  • Netherlands (1)
Peak activity year
2018
Number of Unicorns
4
Number of Decacorns
4
Number of Minotaurs
2

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Quantitative data

Avg. startup age at the time of investment
9
Avg. valuation at time of investment
648M
Group Appearance index
1.00
Avg. company exit year
3
Avg. multiplicator
12.87
Strategy success index
1.00

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
20 Jan 2016 Social Media, Video, Advertising, Social Media Marketing, Media and Entertainment, Advertising Platforms, Content Creators, Content Marketing Venture - Series Unknown 350K Spain, Madrid
Nervana 04 Jun 2015 Software, Information Technology, Artificial Intelligence, Machine Learning, Big Data, Cloud Computing, Hardware, Open Source Early Stage Venture 20M United States, California, San Diego
Phenom People 24 May 2018 Software, Information Technology, Human Resources, Recruiting, Artificial Intelligence, Machine Learning, SaaS, CRM Early Stage Venture 22M United States, Pennsylvania
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.