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Based on actual clinically verified products, we sequentially expand common infrastructure and AI for each field.
TRACTION
This is not a demo, but rather something that has been verified in actual clinical settings.
The selection criteria were refined through actual cases such as freckles, dark spots, and freckles. Since the product is still in operation, investors can check verification speed and field suitability together.
We have already secured a network of medical institutions that can provide initial introduction and feedback. Hospitals are not a distribution channel but a base for verification and expansion.
We are jointly developing industry-academic AI to quantify plastic surgery wound evaluation. The fact that development began with research and clinical trials connected is a trustworthy foundation for subsequent expansion.
It is a five-layer interlocking differentiation that cannot be replicated by creating one AI in one field.
Why this structure is hard to copy
The interpretation and inference infrastructure that is commonly used across all outpatient departments is an asset that cannot be replicated by AI in one field. As the number of medical departments increases, the value increases.
DermatoScan AI is clinically verified as the first verification case, and the standard for external AI stores is secured. Verification data itself is an asset that latecomers cannot match.
The six initial collaborating hospitals (over 50 specialists) and Ulsan University's industry-academia channels serve as the basis for introduction and verification. A trust-based healthcare network cannot live on advertising.
AI builds trust based on the authority of medical staff through an augmentation, not replacement structure. Because medical staff remain the decision-making body, resistance to field adoption is low.
The representative's combination of non-reimbursement clinical expertise and technical capabilities is a rare combination in the market. Problem definition and technology implementation in clinical settings are carried out within one team.
Market
If you look at the size of AI in one field, it may seem small, but the story is different when it is common to all outpatient care. We look at the market by combining infrastructure subscriptions, AI services by sector, and patient support fees.
This is the entire available market, including global medical AI services, medical connection, talent training, and remote consultation.
This is a market that the common infrastructure and AI ecosystem of all outpatient clinics, including skin and plastic surgery, are directly targeting.
This is the market for non-coverage treatment for Korean foreigners and services for domestic medical institutions that will realistically be reached within three years.
Business Model
The profit structure was separated from the procedure price so as not to distort the judgment of the medical staff and the patient's choice. Because trust as a medical AI is the starting line.
| revenue source | structure |
|---|---|
| Common infrastructure subscription (Dockie-talkie · Clinical Copilot) | Monthly subscription per medical institution |
| AI services by field (DermatoScan · WoundScan) | 300,000 to 1 million won per month per medical institution |
| Patient Assistance Fee (flat rate) | 300,000 to 1 million won per patient |
| External AI store launch | Model unconfirmed, phased |
All four revenue sources are fixed or fixed rates unrelated to the price or type of treatment. The incentive has been removed from the structure itself.
About 1.15 million won
Average sales per patient
About 800,000 won
Contribution profit per patient
3-Year Target
We aim to achieve annual sales of approximately KRW 5 billion through introduction of medical institutions, accumulated patients, and expansion of the AI product line.
100
Introduction medical institution
5,000 people
cumulative patients
3 types+
AI product line
About 5 billion won
annual sales goal
Roadmap
Verification and development are secured first through support and accelerated through initial investment. The two tracks are not a competition, but an order.
We are conducting DermatoScan verification and Dockie-talkie clinic testing, and developing WoundScan in parallel. We are proceeding with applying for government support and operating the first hospital to which Apgujeong Tune Clinic has been applied.
We launch Clinical Copilot with a seed round. We are launching common infrastructure services for hospitals and expanding AI in new areas.
We are launching an external AI store ecosystem and pursuing overseas expansion and Series A, focusing on Southeast Asia and the Middle East.
Funding
In parallel, we promote verification of venture companies (R&D company track) to ensure policy and tax benefits and reliability of follow-up funding.
By 2026, we will secure a foundation for verification and development without diluting our shares through government and institutional programs. Apply mainly for programs suited to medical AI.
After securing the first verification cases and internal AI verification data, we will proceed to attract initial investment from major domestic investors and healthcare investment companies.
Team
A physician-founder with clinical authority, a doctor-developer product team, and specialty advisors work inside one validation loop.
Leads strategy, clinical validation, and first-in-clinic rollout as a physician-founder with direct clinical authority.
Leads backend engineering and AI systems so conversations, images, and clinical notes become one reviewable data flow.
Leads product and design, turning complex clinical workflows into operational screens and decision flows clinicians can actually use.
Leads business development and partnerships, expanding the clinical validation loop through partner hospitals and academic channels.
Public background is summarized.
Reviews medical consistency and clinical risk so product boundaries remain aligned with physician final judgment.
Focused on medical-advisory responsibilities.
Co-develops WoundScan AI with AetherHeal.
FAQ
We've compiled the most frequently asked questions during the investment review process.
We share key indicators and business plans.