Securing 40 Billion Won Right After Founding... VC Capital Flocks to Researcher-Led Startups

Founding Teams from Seoul National University and KAIST Dominate in AI and Bio Fields
Verification Based on Corporate Experience, Research Papers, Patents, and National Projects
Early-Stage Investment Becomes a Tight Squeeze for Platform, Commerce, and Content Startups

As the trend toward selectivity and focus intensifies in the venture investment market, founders’ research backgrounds and technology validation experience are emerging as key criteria for investment decisions. This shift comes as venture capital (VC) firms, in the wake of a market contraction, concentrate on identifying “proven teams” to reduce the risk of failure.

On June 2, a representative from the venture investment information provider The VC stated, “Although the investment market is showing signs of recovery, funding is not being distributed evenly across all companies,” adding, “The selective investment trend is being further strengthened, with capital increasingly concentrated in deep tech sectors and proven founding teams.”

Initial Big Deals Over 10 Billion Won Surge... “Selective Investment Strengthened”

This trend is especially pronounced in the early-stage investment market, where large amounts of capital are being funneled into a small number of companies. According to The VC, as of May this year, there were 31 early-stage investment deals exceeding 10 billion won, a 41% increase compared to the same period last year. During the same period, total investment amounted to 829.2 billion won, marking a 169% surge year-on-year. As a result, 75% of all early-stage investment capital was concentrated in initial big deals of 10 billion won or more.

Jongseon Park, a researcher at Eugene Investment & Securities, also analyzed, “In April, three sectors—AI·deep tech·blockchain, manufacturing·hardware, and healthcare·bio—accounted for a high proportion of investments at 66.0%.” This indicates that investment funds are flowing into fields that require technological barriers and research and development capabilities, rather than simple service-based startups.

AsteroMorph and Config Intelligence are prime examples. Both companies, despite being seed-stage startups, each secured investments in the 40 billion won range. AsteroMorph is developing an AI model that analyzes biological and chemical data to propose research ideas and scientific hypotheses. Investors in the latest round included BonAngels Venture Partners, IMM Investment, Mirae Asset Venture Investment, Korea Development Bank, and KDB Capital. The founder, Minhyung Lee, is a graduate of Seoul National University College of Medicine and previously served as the chief scientist for AI at the “K-Moonshot” national strategic project under the Ministry of Science and ICT.

Config Intelligence is a robotics foundation model startup founded by Minjun Seo, an associate professor at the KAIST Kim Jaechul AI Graduate School, with bases in both the United States and Korea. Its recent fundraising round attracted a large number of corporate venture capital (CVC) arms from major companies, including Samsung Venture Investment, Hyundai Motor Zero One Ventures, LG Technology Ventures, and SK Telecom Americas.

“Non-Deep Tech Startups May Face Greater Challenges”

Other notable examples of successful fundraising include Mobilint, a startup founded by Dongju Shin, who conducted AI semiconductor research at KAIST. Exyna was established by Jinyoung Kim, a graduate of Seoul National University’s Department of Computer Science and Engineering, who previously worked at Samsung Electronics, SK Telecom, and SK hynix; the company specializes in CXL-based intelligent memory semiconductors. Holiday Robotics was founded by Kiyeong Song, who previously founded the deep learning-based machine vision company SuaLab and sold it to Cognex in the United States; he has now launched a humanoid robotics startup.

Uncertainty in the exit market is also cited as a reason for tighter scrutiny of founding teams. In highly technical fields, it is difficult for outsiders to quickly assess business viability, so founders’ research achievements, experience working at large corporations, previous startup and exit records, and participation in national research projects are now critical evidence during internal screening and in persuading limited partners (LPs).

Conversely, concerns are rising that the early-stage funding environment may further deteriorate for non-deep tech startups in sectors such as platforms, commerce, and content. The VC representative observed, “At the seed investment stage, 43% of all deals were concentrated in the AI and robotics fields, underscoring a marked bias toward companies with proven technological competitiveness. As elite researcher 'manpower' becomes increasingly important, the early-stage fundraising environment for non-deep tech startups is becoming even more challenging.”

This content was produced with the assistance of AI translation services.