Inception Asset Management

Total investments

3

Average round size

7M

Portfolio companies

2

Follow on index

0.33

Areas of investment
AccountingFinanceSmall and Medium BusinessesBig DataRoboticsIndustrialIndustrial Automation

Summary

Among the most popular portfolio startups of the fund, we may highlight Invert Robotics. Among the most successful fund investment fields, there are Small and Medium Businesses, Industrial Automation.

The usual cause for the fund is to invest in rounds with 3-4 partakers. Despite the Inception Asset Management, startups are often financed by AMP New Ventures, Powerhouse Ventures, New Zealand Venture Investment Fund. The meaningful sponsors for the fund in investment in the same round are Yamaha Motor Ventures & Laboratory Silicon Valley, New Zealand Venture Investment Fund, Finistere Ventures.

The top activity for fund was in 2019. The fund is constantly included in less than 2 investment rounds annually. The common things for fund are deals in the range of 5 - 10 millions dollars. The average startup value when the investment from Inception Asset Management is 10-50 millions dollars.

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Investments analytics

Analytics

Total investments
3
Lead investments
0
Follow on index
0.33
Investments by industry
  • Robotics (2)
  • Industrial (2)
  • Industrial Automation (2)
  • Accounting (1)
  • Small and Medium Businesses (1)
  • Show 2 more
Investments by region
  • Netherlands (2)
  • Australia (1)
Peak activity year
2019

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Quantitative data

Avg. startup age at the time of investment
10
Avg. valuation at time of investment
13M
Group Appearance index
1.00

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
Invert Robotics 02 May 2019 Robotics, Industrial, Industrial Automation Early Stage Venture 8M Netherlands, North Brabant, Breda
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.