Citi has issued a research report stating that a sum-of-the-parts valuation based on net present value is the most appropriate method to assess the fair value of YIDU TECH (02158). The company's various business segments all possess scalable business models and are continuously improving efficiency through AI technology. The price target is set at HK$11.00, corresponding to a weighted average cost of capital of 12.5% and a perpetual growth rate of 3.0%.
Specifically, the bank projected revenues, operating profits, and net profits for the company's business segments for the period FY26E–FY35E and conducted NPV calculations based on these forecasts. On a per-share basis, the valuation is broken down as follows: 1) Big Data Platform and Solutions: HK$2.8; 2) Life Sciences Solutions: HK$2.0; 3) Health Management Platform and Solutions: HK$2.7; and 4) Net Cash: HK$3.4. A "Buy" rating was assigned.
Key points from Citi's analysis include the following: YIDU TECH officially launched Yidu Evidence in March 2026. The company's CEO, CFO, and Head of Investor Relations held a product briefing in Beijing on April 9. Yidu Evidence is an AI-driven clinical evidence platform for physicians, similar to OpenEvidence, designed to bridge the gap between real-world medical data and evidence-based medical decision-making. The launch of this product is expected to further deepen YIDU TECH's connection with the physician community, strengthen its Big Data Platform and Solutions business within hospital networks, and explore a new token-based payment model.
Compared to other "x-evidence" type products launched by internet companies, YIDU TECH's advantage is seen as its deep integration with hospital internal medical data and a more profound understanding of physicians' clinical workflows. Notably, the company's BDPS backlog in China already exceeds RMB 400 million, with new orders signed in the first half of FY26 increasing 19% year-over-year. Against a backdrop of ongoing supportive national policies, a positive outlook is maintained for the BDPS business.
Yidu Evidence is positioned as an "AI Native, Physical AI" clinical intelligence product that integrates real-world data with advanced AI reasoning capabilities. Its capabilities are built upon years of accumulated specialized disease datasets, validation practices in real hospital settings, and specialized intelligent agents developed in collaboration with clinical experts. When a physician initiates a query, the system automatically executes a comprehensive backend process, primarily involving three stages: 1) Evidence Retrieval: searching within curated clinical guidelines and medical literature; 2) Grading Assessment: evaluating the authority and timeliness of sources based on established systems like GRADE, rather than relying on paid rankings; and 3) Logical Integration: synthesizing the retrieved results into a structured, evidence-based medical answer with clearly cited sources.
Yidu Evidence has built an evidence evaluation system based on large-scale, multi-source medical knowledge. This system covers over 30,000 authoritative guidelines selected from more than 40,000 guidelines, over 5 million high-quality research articles filtered from more than 30 million papers, and a knowledge database co-developed with authoritative institutions. Crucially, Yidu Evidence continuously tracks the latest research developments from top global medical journals, enabling physicians to access cutting-edge medical evidence promptly and addressing the long-standing issue of update lag in traditional knowledge bases.
Yidu Evidence currently offers two versions: a hospital edition and a physician edition. It employs a hybrid "B2B + B2C / B2B2C" business model. Revenue for the hospital version is primarily generated through hospital procurement, while the physician version is funded by pharmaceutical companies for academic promotion purposes. For individual physicians, most daily personal use is free; however, a token-based billing model will be applied for high-value scenarios like complex comprehensive case analysis.
Potential risks highlighted include: 1) a relatively short operating history and lack of stable profitability; 2) uncertainties related to the tender and bidding process; 3) intensifying industry competition; 4) legal and compliance risks; 5) regulatory risks potentially limiting the use of personal data; and 6) data security and privacy breach risks.
Comments