SAP

Type

Corporate investor

Status

Active

Location

Hong Kong, China

Total investments

38

Average round size

49M

Portfolio companies

30

Rounds per year

0.73

Lead investments

4

Follow on index

0.18

Exits

12

Areas of investment
InternetSoftwareInformation TechnologyB2BArtificial IntelligenceMachine LearningSaaSEnterprise SoftwareCyber SecurityOpen Source

Summary

In 2017 was created SAP, which is appeared as Corporate Investor. The fund was located in Europe if to be more exact in Germany. The main office of represented Corporate Investor is situated in the Walldorf.

Besides, a startup requires to be at the age of 4-5 years to receive the investment from the fund. Among the most popular portfolio startups of the fund, we may highlight LinkedIn, Virtustream, Cortera. For fund there is no 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 Software, Internet. The fund has no exact preference in a number of founders of portfolio startups. When startup sums 4 of the founder, the probability for it to get the investment is little.

The fund was created by Hans-Werner Hector, Hasso Plattner. Besides them, we counted 43 critical employees of this fund in our database.

Comparing to the other companies, this SAP performs on 23 percentage points more the average number of lead investments. The fund is generally included in less than 2 deals every year. The top activity for fund was in 2000. Despite it in 2019 the fund had an activity. Speaking about the real fund results, this Corporate Investor is 10 percentage points less often commits exit comparing to other organizations. The usual things for fund are deals in the range of 10 - 50 millions dollars. When the investment is from SAP the average startup value is more than 1 billion dollars. The higher amount of exits for fund were in 2012.

The usual cause for the fund is to invest in rounds with 4-5 partakers. Despite the SAP, startups are often financed by Sapphire Ventures, Intel Capital, General Catalyst. The meaningful sponsors for the fund in investment in the same round are Sapphire Ventures, Volition Capital, Intel Capital. In the next rounds fund is usually obtained by Sapphire Ventures, Volition Capital, Intel Capital.

Show more

Investor highlights

Stage focus
Seed

Discover reliable insights

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

Investments analytics

Analytics

Total investments
38
Lead investments
4
Exits
12
Rounds per year
0.73
Follow on index
0.18
Investments by industry
  • Software (21)
  • Information Technology (10)
  • Enterprise Software (7)
  • Artificial Intelligence (7)
  • Cyber Security (6)
  • Show 51 more
Investments by region
  • United States (27)
  • Germany (5)
  • Israel (3)
  • Canada (1)
Peak activity year
2023
Number of Unicorns
5
Number of Decacorns
6
Number of Minotaurs
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
16
Avg. valuation at time of investment
729M
Group Appearance index
0.71
Avg. company exit year
16
Avg. multiplicator
4.93
Strategy success 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
Aleph Alpha 06 Nov 2023 Software, Information Technology, Artificial Intelligence, Machine Learning Early Stage Venture 500M Baden-Württemberg, Heidelberg, Germany
ThreatConnect 01 Dec 2015 Software, Analytics, Information Technology, Network Security, Security Early Stage Venture 16M United States, Arlington, Virginia
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.