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LEA Partners

Investor type Private Equity Firm


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This summary is composed by our algorithm based on the analysis of the deals. If you think that some of this information is not accurate, please let us know about it and provide any supporting evidences if possible. Such cases will be analyzed by our ML-algorithm and implemented in our database, which will improve this summary.
Total investments 19
Average round size
The average size of a deal this fund participated in
Portfolio companies 15
Rounds per year 0.95
Lead investments 4
Follow on index
How often the fund supports its portfolio startups at next rounds
Exits 2
Key employees 7
Stages of investment
Early Stage Venture
Late Stage Venture
Private Equity

Areas of investment

  • Software
  • Information Technology
  • Artificial Intelligence
  • Machine Learning
  • SaaS

LEA Partners appeared to be the VC, which was created in 2002. The company was established in Europe in Germany. The main department of described VC is located in the Karlsruhe.

The standard case for the fund is to invest in rounds with 2-3 partakers. Despite the LEA Partners, startups are often financed by TEV | Tengelmann Ventures. The meaningful sponsors for the fund in investment in the same round are Wecken & Cie., Vito Ventures, VC Fonds Baden-Wurttemberg.

Besides, a startup needs to be aged 2-3 years to get the investment from the fund. Among the most popular fund investment industries, there are B2C, Indoor Positioning. Among the various public portfolio startups of the fund, we may underline, sevDesk, INTRANAV For fund there is a match between the country of its foundation and the country of its the most frequent investments - Germany. The fund has exact preference in a number of founders of portfolio startups.

Besides them, we counted 5 critical employees of this fund in our database.

Considering the real fund results, this VC is 3 percentage points less often commits exit comparing to other organizations. The fund is generally included in 2-6 deals every year. The high activity for fund was in 2017. This LEA Partners works on 12 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 5 - 10 millions dollars. The higher amount of exits for fund were in 2019.

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Typical Co-investors
LEA Partners is more likely to invest in rounds together with the following funds:
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Funds from Germany
Funds with similar focus located in Germany:
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Funds with similar focus acting as lead investors:

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Notable deals

CompanyIndustryRound SizeDateInvestorsLocation


Human Resources
$14M08 Mar 2022 Karlsruhe, Baden-Wurttemberg, Germany


Information Services
Mobile Apps
Peer to Peer
Property Management
Real Estate
$30M03 Feb 2022 Stuttgart, Baden-Württemberg, Germany


Developer Tools
Productivity Tools
Software Engineering
Web Apps
Web Development
$5M20 Jan 2022 Delaware, United States


Information Technology
$2M17 Dec 2021 Karlsruhe, Baden-Wurttemberg, Germany


Artificial Intelligence
Information Technology
Machine Learning
Small and Medium Businesses
$4M17 Sep 2021 Heidelberg, Baden-Wurttemberg, Germany

Aleph Alpha

Artificial Intelligence
Information Technology
Machine Learning
$23M27 Jul 2021 Heidelberg, Baden-Württemberg, Germany


Cloud Computing
Information Technology
Small and Medium Businesses
$59M25 May 2021 Germany, Baden-Württemberg, Germany

Quality Match

$5M01 Mar 2021 Heidelberg, Baden-Wurttemberg, Germany

Aleph Alpha

Artificial Intelligence
Information Technology
Machine Learning
$6M27 Jan 2021 Germany, Baden-Württemberg
Quality Match raises $6 million to build better AI datasets

– Quality Match, a Heidelberg, Germany-based quality data annotation provider, today announced that it raised a €5 million ($6 million) seed round from LEA Partners.
– The company says it’ll use the proceeds to expand its team and accelerate product development.
– Training AI and machine learning algorithms requires plenty of annotated data. But data rarely comes with annotations.
– The bulk of the work often falls to human labelers, whose efforts tend to be expensive, imperfect, and slow.
– It’s estimated most enterprises that adopt machine learning spend over 80% of their time on data labeling and management.
– In fact, in a recent survey conducted by startup CloudFlower, data scientists said that they spend 60% of the time just organizing and cleaning data compared with 4% on refining algorithms.


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