Workday Ventures

Type

CVC

Status

Active

Location

San Francisco, United States

Total investments

76

Average round size

41M

Portfolio companies

52

Rounds per year

8.44

Lead investments

2

Follow on index

0.32

Exits

11

Stages of investment
SeedEarly Stage VentureLate Stage Venture
Areas of investment
SoftwareAnalyticsInformation TechnologyHuman ResourcesRecruitingArtificial IntelligenceMachine LearningSaaSEnterprise SoftwareBig Data

Summary

Workday Ventures is the famous VC, which was founded in 2015. The company was established in North America in United States. Workday Ventures seemed to be an CVC arrangement as part of the organization. The leading representative office of defined VC is situated in the San Francisco.

We also calculated 3 valuable employees in our database.

Speaking about the real fund results, this VC is 12 percentage points less often commits exit comparing to other organizations. When the investment is from Workday Ventures the average startup value is 100-500 millions dollars. The fund is generally included in 2-6 deals every year. The increased amount of exits for fund were in 2019. This Workday Ventures works on 4 percentage points less the average amount of lead investments comparing to the other organizations. The usual things for fund are deals in the range of 10 - 50 millions dollars. The top activity for fund was in 2019.

The usual cause for the fund is to invest in rounds with 4-5 partakers. Despite the Workday Ventures, startups are often financed by New Enterprise Associates, Madrona Venture Group, Amplify Partners. The meaningful sponsors for the fund in investment in the same round are Salesforce Ventures, Madrona Venture Group, Amplify Partners. In the next rounds fund is usually obtained by Salesforce Ventures, Index Ventures, Storm Ventures.

For fund there is a match between the country of its foundation and the country of its the most frequent investments - United States. Besides, a startup requires to be at the age of 2-3 years to receive the investment from the fund. Among the most successful fund investment fields, there are Human Resources, Analytics. Among the most popular portfolio startups of the fund, we may highlight Automation Anywhere, Vida Health, League Inc.. The fund has no specific favorite in a number of founders of portfolio startups. When startup sums 5+ of the founder, the probability for it to get the investment is little.

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Investor highlights

Industry focus
FintechFuture of WorkAnalyticsProductivityBlockchain/Crypto/Web3 Show 1 more
Stage focus
Series DSeries ASeries ESeries FSeries B Show 1 more

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Investments analytics

Analytics

Total investments
76
Lead investments
2
Exits
11
Rounds per year
8.44
Follow on index
0.32
Investments by industry
  • SaaS (33)
  • Software (28)
  • Artificial Intelligence (22)
  • Machine Learning (20)
  • Human Resources (18)
  • Show 74 more
Investments by region
  • United States (61)
  • Nicaragua (1)
  • Canada (7)
  • United Kingdom (2)
  • Ireland (2)
  • Show 3 more
Peak activity year
2021
Number of Unicorns
9
Number of Decacorns
9

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Quantitative data

Avg. startup age at the time of investment
8
Avg. valuation at time of investment
681M
Group Appearance index
0.86
Avg. company exit year
4
Avg. multiplicator
4.58
Strategy success index
0.90

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
10Lines 27 Jun 2021 Robotics, Navigation, Internet of Things, Indoor Positioning Seed 826K Harju maakond, Tallinn, Estonia
Northstar 13 Oct 2022 Financial Services, FinTech, Human Resources, Employee Benefits Early Stage Venture 24M United States, California, San Francisco
Paradox 27 Dec 2021 Information Technology, Human Resources, Artificial Intelligence, Machine Learning Late Stage Venture 200M United States, Arizona, Scottsdale

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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.