The fresh funding will also be invested in accelerating the company’s international commercial expansion, which will focus on Asian markets. The round was led by Nabtesco Technology Ventures with participation from The Signal Group and existing investor ETF Partners.
Nabtesco Technology Ventures is the corporate venture capital arm of Nabtesco Corporation – a Japanese leader in shipping automation with a 40 per cent market share. The Signal Group is a maritime, technology and investment firm and developer of The Signal Ocean Platform, a SaaS platform for the commercial optimisation of shipping. ETF Partners (The Environmental Technologies Fund) is a European sustainability focused venture capital fund.
The funding follows a rigorous technical due diligence process carried out by the investors, which involved months of research, technical tests to check the accuracy of the AI models that the company has developed, and strict competitive analysis to explore how DeepSea scored against fellow technological companies and competitors in the industry. The investment is expected to future-proof the company and demonstrate that DeepSea is trusted by sector-specialised investors.
In parallel with the investment, DeepSea Technologies and Nabtesco will begin a commercial and research cooperation which will see DeepSea’s partnership with Nabtesco’s sales network, the development of joint products and the participation in joint research on technologies that will reshape the future of the maritime industry.
Similarly, in addition to The Signal Group’s capital participation, further collaboration opportunities will be explored following the funding.
Roberto Coustas, co-founder and CEO of DeepSea Technologies, said: “With Nabtesco’s support in Asian markets, we are certain that we will be able to assist shipping companies in the region to realise the commercial value of AI technology to improve their bottom line. The investment that we are announcing today opens the next chapter of DeepSea, as a global player in the performance and optimisation space.”