Singapore is looking to fuel innovation in the maritime industry, parking SG$60 million in investments to nurture local startups and drive the development of technology that can improve operational efficiency and sustainability. Government agencies SEEDS Capital and Maritime and Port Authority of Singapore (MPA) have issued a call-for-partnership in search of investors keen to jointly invest in early-stage deep-tech startups in the local sector.
These joint investments would aim to cultivate and support startups in developing new business models as well as technology that could enhance operations, safety, and sustainability across different areas within the maritime industry, including shipping, port logistics, port operations, and maritime services.
Because investment risks typically are higher and returns slower with startups that deal with deep technology such as artificial intelligence and medtech, venture capitalists in Singapore are less willing to stick their bets in early-stage startups.Read now
Continued transformation was essential for an industry that played a crucial role in the local economy, according to MPA and SEEDS, which is the investment arm of Enterprise Singapore, a government agency dedicated to promoting local businesses in the global marketplace.
Singapore is home to the world's second-busiest ports, moving 36.6 million twenty-foot equivalent units (TEUs) last year, according to World Shipping Council. Shanghai was the busiest, shipping 42.01 million TEUS in 2018.
Singapore's maritime industry contributes some 7% of the city-state's gross domestic product (GDP) and encompasses more than 5,000 companies, which employ some 170,000 people.
"The advancement of the industry will strengthen Singapore's position as a premier global hub port and international maritime centre, and further boost the growth of complementary sectors such as logistics, manufacturing, and wholesale trade," said MPA and SEEDS.
Partnerships and joint innovation, in particular, were key to accelerating transformation and ensuring the competitiveness of local companies, said Ted Tan, Enterprise Singapore's deputy CEO and chairman of SEEDS. Ted said the $60 million in joint investments and call-for-partnerships aimed to match tech startups with investors and enterprises, so these organisations could co-develop new technology and services to further boost Singapore's position as a maritime hub.
SEEDS said it was keen to work with investors that could identify and jointly invest in Singapore-based deep-tech and early-stage startups in the maritime technology market. These investors should be willing to offer hands-on assistance to guide early-stage startups in product commercialisation as well as mentorship and connection to potential customers in their networks.
Under a Startup SG Equity Scheme, SEEDS said it would match up to a 7:3 split in co-investment for the first S$500,000 and up to S$4 million for each startup. Both local and foreign entities with presence in Singapore can submit their application, which closes December 13.
MPA's assistant chief executive for development, Tan Beng Tee, added: "It is important for the maritime industry to reimagine the way in which it operates and navigate future challenges of disruption and environmental regulation. This is a good opportunity for tech startups to work alongside with us to co-create solutions to shape the future of maritime [in] Singapore."
In a separate statement, MPA said it had completed a five-week programme that included a two-day bootcamp for 24 startups, which led to 10 pitches made to an audience comprising 300 investors, corporate partners, venture capitalists, and maritime professionals.
Hosted by PIER71, an initiative jointly founded by MPA and the National University of Singapore's NUS Enterprise arm, the startup programme saw participants from Singapore, Japan, Denmark, and Canada, three of which won the grand final with their pitches. These included Dravam, which developed a real-time detection system to monitor the quality of marine fuel, and KoiReader Technologies, which machine-learning visual recognition system was touted to improve the accuracy of logistics data for regulatory assessment.
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