TOSHIBA TEC CORPORATION

Total investments

7

Average round size

5M

Portfolio companies

7

Rounds per year

0.09

Lead investments

1

Areas of investment
SoftwareRetailAnalyticsRetail TechnologyArtificial IntelligenceMachine LearningBig DataComputer VisionGroceryShopping

Summary

Besides, a startup requires to be at the age of 4-5 years to receive the investment from the fund. Among the most popular fund investment industries, there are Big Data, Analytics. Among the most popular portfolio startups of the fund, we may highlight ABEJA.

The typical case for the fund is to invest in rounds with 3 participants. Despite the TOSHIBA TEC CORPORATION, startups are often financed by Salesforce Ventures, PNB-INSPiRE Ethical Fund 1 Investment Business Limited Liability Partnership, Innovation Network Corporation of Japan. The meaningful sponsors for the fund in investment in the same round are Sage Capital, NVIDIA, ITOCHU Corporation. In the next rounds fund is usually obtained by Topcon Corporation, TBS Innovation Partners, SBI Investment.

The fund is generally included in less than 2 deals every year. The top activity for fund was in 2017. The common things for fund are deals in the range of 5 - 10 millions dollars.

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Investments analytics

Analytics

Total investments
7
Lead investments
1
Rounds per year
0.09
Investments by industry
  • Artificial Intelligence (2)
  • Machine Learning (2)
  • Software (2)
  • Retail Technology (2)
  • Retail (2)
  • Show 15 more
Investments by region
  • Japan (5)
  • New Zealand (1)
  • United States (1)
Peak activity year
2024

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Quantitative data

Avg. startup age at the time of investment
6
Group Appearance index
1.00

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
MUSE 11 Jun 2024 Robotics, Intelligent Systems Seed 5M Tokyo, Kantō, Japan
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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.