Redline Capital Management

Type

Venture Capital

Status

Active

Location

London, United Kingdom

Total investments

45

Average round size

49M

Portfolio companies

28

Rounds per year

4.50

Lead investments

10

Follow on index

0.38

Exits

7

Stages of investment
Early Stage VentureLate Stage Venture
Areas of investment
SoftwareAnalyticsInformation TechnologyArtificial IntelligenceMachine LearningAppsEnterprise SoftwareBusiness IntelligenceComputerData Center

Summary

Redline Capital appeared to be the VC, which was created in 2014. The leading representative office of defined VC is situated in the Luxembourg. The venture was found in Europe in Luxembourg.

Deals in the range of 10 - 50 millions dollars are the general things for fund. The fund is constantly included in 2-6 deals per year. The typical startup value when the investment from Redline Capital is 500 millions - 1 billion dollars. The important activity for fund was in 2017. Despite it in 2019 the fund had an activity. Speaking about the real fund results, this VC is 15 percentage points more often commits exit comparing to other organizations. Comparing to the other companies, this Redline Capital performs on 12 percentage points less the average number of lead investments. The increased amount of exits for fund were in 2018.

The typical case for the fund is to invest in rounds with 4-5 participants. Despite the Redline Capital, startups are often financed by Walden Riverwood Ventures, Skyline Ventures, Upscale. The meaningful sponsors for the fund in investment in the same round are Intel Capital, Walden International, Atlantic Bridge. In the next rounds fund is usually obtained by Walden International, Shawbrook Bank, GV.

The overall number of key employees were 4.

Besides, a startup needs to be aged 4-5 years to get the investment from the fund. Among the most successful fund investment fields, there are Software, Big Data. Among the various public portfolio startups of the fund, we may underline ironSource, SambaNova Systems, Innovium For fund there is no match between the location of its establishment and the land of its numerous investments - United States. The fund has exact preference in a number of founders of portfolio startups. In case when startup counts 4 of the founder, the chance for it to get the investment is meager.

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Investor highlights

Industry focus
SecurityAnalyticsB2B/EnterpriseCloud/InfrastructureFintech Show 4 more
Stage focus
GeneralistPre-SeedSeedSeries ASeries B Show 1 more
Geo focus
AlbaniaAustriaBelgiumBosnia and HerzegovinaBulgaria Show 39 more

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Investments analytics

Analytics

Total investments
45
Lead investments
10
Exits
7
Rounds per year
4.50
Follow on index
0.38
Investments by industry
  • Software (23)
  • Artificial Intelligence (14)
  • Analytics (13)
  • Information Technology (10)
  • Machine Learning (9)
  • Show 58 more
Investments by region
  • United States (26)
  • Israel (7)
  • United Kingdom (11)
  • Germany (1)
Peak activity year
2020
Number of Unicorns
2
Number of Decacorns
2
Number of Minotaurs
1

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Quantitative data

Avg. startup age at the time of investment
7
Avg. valuation at time of investment
296M
Group Appearance index
0.98
Avg. company exit year
5
Avg. multiplicator
3.34

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
ECARX 25 Feb 2021 Automotive, Information Services, Artificial Intelligence Early Stage Venture 200M Zhejiang, Shangcheng District, China
Parallel Health 08 Feb 2021 Biotechnology, Health Care, Wellness Seed 750K United States, California, San Francisco
Prosimo.io 29 Jun 2022 Cloud Infrastructure Early Stage Venture 30M United States, California, Santa Clara
SambaNova Systems 01 Apr 2019 Software, Analytics, Artificial Intelligence, Machine Learning, Computer Early Stage Venture 150M United States, California, Palo Alto

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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.