Singapore-based artificial intelligence (AI) healthcare startup UCARE.AI has raised an undisclosed amount in a Series A round backed by Southeast Asia’s oldest insurance group Great Eastern, venture capital firm Walden International, investor Peter Lim, and WPGrowth Ventures.
The latest funding round brings UCARE.AI’s total funding to date to $8.2 million, inclusive of seed and Series A rounds, founder and CTO Neal Liu told DEALSTREETASIA in an interaction.
The closing of the Series A round comes two years after UCARE.AI received its seed funding. Liu said the company was bootstrapping to develop the AI engine and refine its product and market fit during its two-year stealth mode.
In a statement, Christina Teo, co-founder and CEO of UCARE.AI, said the capital raised will be used for talent acquisition and market expansion into the region.
“We know we’re in the right place, at the right time, to succeed,” Teo said.
The startup said it uses its predictive engine, using proprietary deep learning and neural network algorithms, to help prioritise healthcare resources to reduce preventable hospitalisation, potentially resulting in “significant annual savings in the industry”.
It also claims a highly accurate predictive capability by correctly identifying the risk of rehospitalization for a segment of Singaporeans.
“In a world of rising healthcare costs, AI has shown it can improve health outcomes and improve quality of lives. This is a huge market opportunity,” said Yong Soo Ping, Executive Director of Walden International, one of the startup’s backers.
UCARE.AI said it will continue to leverage its predictive capability and online machine learning algorithms to serve patients, providers, and payers.
In an interaction with this portal, Liu said there is currently no dominant player in Southeast Asia’s AI-powered healthcare industry, even with the many healthcare startups that are already operating in the region.
He cited complexity of medical care and barriers to entry as among the reasons why the region still has not seen a dominant player.
“Diagnosis and risk assessment is established through several complex levels of decision making. Part of this decision making is rational but another part of it is instinctual and influenced by protocol and policy. While AI has the potential to achieve these goals, changes take time to advance,” Liu said.
Additionally, Liu stressed that machine learning requires a high volume of data and obtaining this data is no easy feat. Given recent scandals due to data breaches, it is inevitable that companies are hesitant to share their customers’ information, he said.
With the latest funding, UCARE.AI is eyeing further expansion in Southeast Asia, Taiwan, and China.
“From a continuous machine learning perspective, SEA is attractive as it offers greater diversity in people, race, diet, lifestyle, genetic makeup, and disease patterns. From a business model perspective, Taiwan and China offer scale and size,” Liu said.