VentureTECH

Total investments

4

Average round size

2M

Portfolio companies

5

Rounds per year

0.33

Lead investments

2

Stages of investment
Early Stage Venture
Areas of investment
BiotechnologyInformation TechnologyHealth CareHospitalManufacturingMedicalConstructionPharmaceuticalEnergyDrone Management

Summary

VentureTECH appeared to be the VC, which was created in 2009. The main department of described VC is located in the Selangor. The fund was located in Asia if to be more exact in Malaysia.

Among the most popular fund investment industries, there are Manufacturing, Hospital. Among the most popular portfolio startups of the fund, we may highlight Aerodyne Group. Besides, a startup requires to be at the age of 4-5 years to receive the investment from the fund. For fund there is a match between the location of its establishment and the land of its numerous investments - Malaysia.

The standard case for the fund is to invest in rounds with 2 partakers. Despite the VentureTECH, startups are often financed by Drone Fund. The meaningful sponsors for the fund in investment in the same round are Kejora Ventures, InterVest, Gobi Partners.

The top activity for fund was in 2018. The fund is constantly included in 2-6 investment rounds annually. Speaking about the real fund results, this VC is 47 percentage points more often commits exit comparing to other organizations. The usual things for fund are deals in the range of 10 - 50 millions dollars.

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Investments analytics

Analytics

Total investments
4
Lead investments
2
Rounds per year
0.33
Investments by industry
  • Health Care (2)
  • Biotechnology (2)
  • Manufacturing (1)
  • Medical (1)
  • Drone Management (1)
  • Show 8 more
Investments by region
  • Malaysia (5)
Peak activity year
2018

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Quantitative data

Avg. startup age at the time of investment
20

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Latest deals

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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.