Ericsson Ventures

Type

CVC

Status

Active

Location

Stockholm, Sweden

Total investments

25

Average round size

26M

Portfolio companies

21

Rounds per year

0.17

Lead investments

3

Follow on index

0.16

Exits

6

Stages of investment
Early Stage VentureLate Stage Venture
Areas of investment
SoftwareAnalyticsMobileArtificial IntelligenceMachine LearningEnterprise SoftwareBig DataCloud Data ServicesCloud ComputingWeb Hosting

Summary

The venture was found in North America in United States. Ericsson Ventures appeared to be a CVC structure as part of the corporation. The main department of described VC is located in the Santa Clara.

The overall number of key employees were 3.

The top activity for fund was in 2017. Opposing the other organizations, this Ericsson Ventures works on 7 percentage points more the average amount of lead investments. The fund is constantly included in less than 2 deals per year. The top amount of exits for fund were in 2019. The real fund results show that this VC is 11 percentage points less often commits exit comparing to other companies. Deals in the range of 10 - 50 millions dollars are the general things for fund.

The usual cause for the fund is to invest in rounds with 5-6 partakers. Despite the Ericsson Ventures, startups are often financed by Sequoia Capital, New Enterprise Associates, Menlo Ventures. The meaningful sponsors for the fund in investment in the same round are New Enterprise Associates, iGlobe Partners, Wipro Ventures. In the next rounds fund is usually obtained by Zon Capital Partners, Sutter Hill Ventures, Qualcomm Ventures.

Among the most popular portfolio startups of the fund, we may highlight Nicira Networks, Menlo Security, Drawbridge. Among the most popular fund investment industries, there are Network Security, Cloud Computing. For fund there is a match between the country of its foundation and the country of its the most frequent investments - United States. The fund has no exact preference in some founders of portfolio startups. If startup sums 4 or 5+ of the founder, the chance for it to be financed is low. Besides, a startup requires to be at the age of 2-3 years to receive the investment from the fund.

Show more

Investor highlights

Industry focus
Community/Social networkDeveloper ToolsAI/Big DataIoTSecurity Show 3 more
Stage focus
GeneralistPre-SeedSeedSeries ASeries B Show 1 more
Geo focus
Generalist

Discover reliable insights

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

Investments analytics

Analytics

Total investments
25
Lead investments
3
Exits
6
Rounds per year
0.17
Follow on index
0.16
Investments by industry
  • Software (12)
  • Cloud Computing (7)
  • Cloud Data Services (5)
  • Big Data (4)
  • Enterprise Software (4)
  • Show 53 more
Investments by region
  • United States (19)
  • United Kingdom (2)
  • Sweden (3)
  • Israel (1)
Peak activity year
2017
Number of Unicorns
1
Number of Decacorns
1

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
10
Avg. valuation at time of investment
243M
Group Appearance index
0.80
Avg. company exit year
8
Avg. multiplicator
4.70
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
Code Biotherapeutics 07 Jun 2022 Biotechnology, Life Science Early Stage Venture 75M United States, Pennsylvania, Hatfield
Nubis Communications 07 Nov 2023 Cloud Data Services, Electronics, Communications Infrastructure Seed United States, New York, New York
RapidDeploy 29 Apr 2021 Software, Analytics, Productivity Tools, Cloud Data Services, Public Safety Early Stage Venture 40M United States, Texas, Austin

Similar funds

By same location

By same geo focus

By doing lead investments

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.