Long-term Fund Oversubscribed Over 2x: Behind Desai's IPO as First Medical Imaging Large Model Stock

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Source: New Yellow River Tech Trends

With the continuous evolution of artificial intelligence technology, the integration of AI and healthcare is gradually moving from the lab to clinical applications. As a typical high-barrier sector, the commercialization capability and technical pathways of medical AI are becoming focal points for capital market attention.

On March 20, Hangzhou Desi Biotechnology Co., Ltd. (hereinafter referred to as “Desi”) officially launched its Hong Kong IPO, planning to issue 7,999,200 H-shares at a price range of HKD 95.6 to HKD 112.5 per share.

Before submitting to the Hong Kong Stock Exchange, Desi had completed ten rounds of financing, raising approximately RMB 397 million in total. In the international placement phase of this IPO, the company received subscriptions from multiple long-term funds, achieving over-subscription by more than twice. In the current market environment, the entry of long-term capital reflects the market’s recognition of the long-term value of medical AI platform companies. If the final offering price hits the upper limit, the company may be included in the Hong Kong Stock Connect, further enhancing liquidity in the secondary market.

01 Full-Platform Pathway Established, Supporting Commercialization and Market Share

Market recognition is primarily based on the company’s proven commercialization capabilities.

Since its founding in 2016, Desi has developed a diversified product portfolio including six medical imaging software and three commercial medical devices. Its core product, AI AutoVision®, focuses on intelligent chromosomal karyotype analysis and was recognized as a “Class III Innovative Medical Device” by the National Medical Products Administration in May 2025.

According to Frost & Sullivan data, based on 2024 sales revenue, Desi holds a 30.6% market share in China’s chromosomal karyotype analysis sector, ranking first.

From an industry landscape perspective, while many players are involved in the medical imaging AI track, most are limited by R&D costs and data barriers, mainly focusing on lung nodules, fundus screening, and similar scenarios, resulting in relatively narrow application scenes.

Single-point breakthroughs can enable quick deployment, but in actual hospital use, they often lead to fragmented systems and fragmented user experience. In contrast, Desi has chosen a differentiated path—evolving from single tools to a full-platform approach. Its multi-product portfolio and cross-scenario coverage give it a certain scarcity value in the current domestic medical AI market.

Desi’s financial performance further confirms the initial success of this model. In the first three quarters of 2025, the company achieved revenue of RMB 112 million, a year-over-year increase of about 470%. Additionally, benefiting from higher gross margins in technology licensing and expanded direct sales channels, the company’s overall gross profit margin increased from 42.9% in 2024 to 75.9%.

02 Building a Large-Model Foundation to Enable Scalable Replication

If commercialization validates the feasibility of the path, then underlying technological capabilities determine the future growth ceiling.

The healthcare industry demands high accuracy, and the direct application of general large models (like ChatGPT) in medical scenarios still faces uncertainties; traditional specialized AI models, meanwhile, face high training costs and long R&D cycles.

Against this backdrop, Desi has launched the iMedImage® medical imaging foundation model. As a trillion-parameter-level general visual model, it can cover over 90% of clinical diagnostic scenarios.

More importantly, its advantages in R&D economics are significant. Compared to traditional specialized models, its development cycle, funding requirements, and training data needs are drastically reduced (to one-tenth, one-hundredth, and one-hundredth, respectively). This means the model can be developed faster and cheaper, providing a practical basis for large-scale replication.

From industry trends, the development of medical AI is resonating with hierarchical diagnosis and treatment policies. Primary healthcare institutions have long faced shortages of high-quality doctors, and devices equipped with advanced AI models are expected to significantly improve diagnostic capabilities at the grassroots level.

By developing its own foundation model, Desi combines technological capability with real clinical needs, effectively addressing core industry pain points.

03 Continued R&D Investment and Long-Term Platform Valuation

In its IPO fundraising plan, Desi has clearly committed to strengthening its technology and product capabilities. Public information shows that about 49% of funds will be used for R&D and commercialization of its core product, AI AutoVision®, and about 20% for enhancing the iMedImage® foundation model and AI technology.

Ongoing R&D investment is also key to maintaining technological barriers and platform advantages.

From a valuation perspective, Desi’s current valuation of HKD 8.5-10 billion is not low, already reflecting market expectations of its “medical AI large model platform” scarcity premium.

However, from a long-term view, the reasonableness of this valuation depends on two factors: whether the data flywheel effect can be sustained and strengthened, and whether the low sales cost advantage can translate into profit realization.

If the company maintains its high growth trajectory and continues expanding application scenarios for its models, its valuation is likely to be gradually realized through future performance.

Text: New Yellow River Tech & Health Research Institute Zhou Wei

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