Hong Kong Exchanges and Clearing Limited and The Stock Exchange of Hong Kong Limited take no responsibility for the contents of this announcement, make no representation as to its accuracy or completeness and expressly disclaim any liability whatsoever for any loss howsoever arising from or in reliance upon the whole or any part of the contents of this announcement.

Yidu医液

Yidu Tech Inc.

醫渡科技有限公司

(incorporated in the Cayman Islands with limited liability)

(Stock Code: 2158)

ANNUAL RESULTS ANNOUNCEMENT FOR THE FISCAL YEAR ENDED 31 MARCH 2025

The board (the "Board") of directors (the "Directors") of Yidu Tech Inc. (the "Company", together with its subsidiaries and consolidated affiliated entities, the "Group") is pleased to announce the annual results of the Group for the fiscal year ended 31 March 2025 (the "Reporting Period", "FY2025"), together with the comparative figures for the fiscal year ended 31 March 2024 ("FY2024"). The results have been reviewed by the Company's audit committee (the "Audit Committee").

In this announcement, "we", "us", and "our" refer to the Company and where the context otherwise requires, the Group.

FINANCIAL HIGHLIGHTS

	Years ended 31 March
	2025	2024	Change (%)
	(RMB'000, except percentages)
Revenue	714,979	807,076	(11.4%)
— Big Data Platform and Solutions	345,888	313,634	10.3%
— Life Sciences Solutions	247,112	324,044	(23.7%)
— Health Management Platform and Solutions	121,979	169,398	(28.0%)
Gross profit	239,182	339,445	(29.5%)
Operating loss	(134,149)	(219,919)	(39.0%)
Loss for the year	(135,223)	(221,242)	(38.9%)

The Board did not recommend the distribution of a final dividend for the fiscal year ended 31 March 2025.

BUSINESS REVIEW

Business Overview

The global medical artificial intelligence industry is undergoing structural transformation, and the deep integration of technological breakthroughs with real-world applications gives rise to a new wave of industrial opportunities. Driven by iterative advancements in underlying AI algorithms and leaps in multi-modal large model technologies, the capability to unlock the value of medical data continues to break new ground. Intelligent paradigms in diagnosis and treatment decision-making, drug R&D, health management, and other scenarios are rapidly being reshaped. In this process, large language models in the medical field have demonstrated the ability to deconstruct complex medical knowledge, gradually evolving from single-point tools to full-chain medical AI solutions, and providing new possibilities for addressing challenges such as uneven distribution of high-quality medical resources and bottlenecks in clinical research efficiency. As a leading enterprise in China's AI healthcare industry, Yidu Tech has always been committed to the deep integration of AI technology with medical needs, promoting the intelligent transformation of the medical industry. With over a decade of in-depth experience in medical scenarios and continuous breakthroughs in medical AI technology, Yidu Tech has established a full-chain intelligent ecosystem spanning “healthcare — pharmaceuticals — insurance”. At this critical juncture for the large-scale deployment of large language models in the medical field, the Company is embracing unprecedented development opportunities.

During the Reporting Period, we continued to deepen our technological breakthroughs and scenario empowerment efforts in proprietary large language models in medical vertical field. Our "AI Medical Brain", YiduCore, has established a full-chain barrier across "data — computing power — algorithms — scenarios". Trained on over 500 billion meticulously cleaned cross-modal datasets and supported by a multi-parameter model matrix (8B/13B/70B/100B), YiduCore has processed 1.15 billion patient visits and 6 billion authorized medical records. Its established disease knowledge graph almost covers all known human diseases, and in collaboration with top medical experts, it has developed over 20 high-value specialized disease datasets. At the computing power level, the Company has become the first in the medical field to achieve full-chain compatibility with both domestic and international high-end chips, driving breakthroughs in algorithm efficiency. In the triage assessment organized by China's National Health Commission, our large language model validated its technological leadership by ranking first. In terms of application scenarios, our AI Middleware integrated with YiduCore's core algorithm engine and DeepSeek, has been implemented in more than 30 leading Grade III-A hospitals. Yidu Tech, with its robust technological reserves and large-scale deployment capabilities, is leading the transition of medical AI from technical validation to industrial value realization.

By deeply integrating technological value with scenario demands, Yidu Tech has established a virtuous cycle of "product iteration — scenario penetration — value feedback", continuously strengthening strategic partnerships with core clients while expanding its new customer network.

As of 31 March 2025, in terms of the Big Data Platform and Solutions Segment, we have provided solutions to 110 top hospitals in China and 44 regulators and policymakers, covering over 4,000 hospitals. We have consistently upgraded and refined our solutions for hospitals and governments. Our AI middleware and EYWA data platform have evolved to versions 2.0 and 5.0, respectively. Leveraging our proprietary large language models, we have launched the "Lingxi Intelligent Management" platform for hospital administration needs and the "Lingxi Intelligent Research" platform for scientific research. The newly upgraded AI Middleware, integrated with DeepSeek, has been deployed in more than 30 leading Grade III-A hospitals. In terms of the Life Science Solutions Segment, the number of life science clients we served reached 132. We achieved a $87.51\%$ revenue retention rate for our top 20 clients in terms of revenue, and 16 out of the top 20 multinational pharmaceutical companies ("MNC") are our clients. For pharmaceutical companies, our proprietary i-Series solution matrix provides a comprehensive service system covering clinical development efficiency optimization, precision study design, and commercialization risk prediction. In the Health Management Platform and Solutions segment, we maintained our advantageous position in core cities, and we were the main operating platform for Shenzhen Hui Min Bao (深圳惠民保) for three consecutive years, with the number of the insured in 2024 program reaching 6.09 million. We were also the main operating platform for Beijing Hui Min Bao (北京惠民保) for four consecutive years, with the cumulative number of the insured reaching 15 million. The number of active users who completed at least one transaction on our health management platform surpassed 24 million.

The Company's focus strategy and operating model remains highly adaptable and resilient in the current complex and challenging market environment. As of 31 March 2025, the Company's total revenue amounted to RMB715.0 million, representing a year-on-year decrease of $11.4\%$ , which was mainly due to the changes in external market environment and product portfolios. However, benefiting from the improvement in internal operational efficiency and enhanced synergies among business segments, the Company's loss for the year narrowed to RMB135.2 million, representing a $38.9\%$ year-on-year decrease. In addition, by continuously strengthening cash management and optimizing the capital usage efficiency, our net cash outflow from operating activities decreased by $23.8\%$ year-on-year. As of 31 March 2025, we had sufficient cash reserves. Our cash and cash equivalents, term deposits, pledged bank deposits, restricted bank balances and deposits amounted to RMB3,309.1 million.

YiduCore

YiduCore, our "AI Medical Brain", serves as the core algorithm engine and technological foundation of Yidu Tech. It continuously improves the precision of medical insights and the intelligence of algorithms by establishing a reinforced closed loop of "data-driven algorithms, algorithm-empowered scenarios and scenario-enhanced data", creating a mutually reinforcing flywheel effect of "technology — application — data" that forms our competitive barrier. Leveraging over a decade of accumulated data resources and algorithmic capabilities, we have built an end-to-end closed loop from data processing and knowledge construction to model training and application scenario. Its self-learning and evolutionary characteristics ensure sustained technological leadership, comprehensively empowering hospitals, pharmaceutical companies, insurers, and public health across the entire value chain.

During the Reporting Period, we have continued the development and training of the large language model in the medical vertical field based on over $500+$ billion finely cleansed and proportionally trained TOKEN corpus, including medical, general, Chinese and English data.

We have performed fine-tuning on tens of millions of data. In addition, we offer multi-parameter model versions with 8 billion, 13 billion, 70 billion, 100 billion 8B, 13B, 70B, 100B parameters to meet diverse scenario requirements.

In terms of data, YiduCore's core engine possesses robust data cleansing and structuring capabilities to ensure high-quality data supply for model training. To date, YiduCore has cumulatively processed and analyzed 6 billion authorized medical records from over 1.15 billion patients, and accumulated deep insights into tens of thousands of diseases. Its disease knowledge graph comprehensively covers all known diseases, while its specialized disease repository spans more than 90 disease categories. Through close collaboration with leading medical experts and researchers, YiduCore has generated 20 specialized disease datasets, delivering actionable insights and knowledge to support critical scenarios such as disease prediction, clinical research, and intelligent diagnosis and treatment.

In terms of computing power, we are the first company in China to successfully adapt high-end domestic and international chips across the entire chain in the medical vertical field. We have expanded compatibility with additional Huawei GPU models, including the 910B, 910B3, 910B4, 300I Duo. Furthermore, we have increased our computing capacity on NVIDIA. In terms of algorithm, Yidu Tech's large language model technology is at the forefront of the industry, demonstrating outstanding performance in the evaluation of large language models in medical field. In September 2024, in the large language model capability assessment for triage scenarios organized by the National Health Commission, Yidu Tech's large language model ranked first.

In terms of application scenarios, Yidu Tech's proprietary AI Middleware has become a key driver for the intelligent transformation of hospitals. This platform, powered by the YiduCore core algorithm engine, processes capabilities such as data governance, model training, and intelligent agent development. Through deep integration with top-tier large language models like DeepSeek, the Yidu AI Middleware has achieved breakthroughs in computational efficiency, model capabilities have also advanced, and development efficiency has been revolutionized, reducing application deployment cycles by roughly 50%. Yidu Tech's proprietary AI Middleware has been deployed in dozens of leading Grade III-A hospitals across the country and continues to expand its hospital network, building an intelligent foundation centered on the YiduCore engine to support whole process management from data governance and model training to business applications. Additionally, doctors can use no-code tool chains to create various types of AI agents tailored to different scenarios. At important sites such as Beijing Cancer Hospital, the number of users of AI agent reached 43% of the total medical staff in the hospital. Based on an AI Middleware, an "AI medical assistant" tool was built and embedded into the doctor's diagnosis and treatment process. This tool can provide real-time personalized decision-making recommendations for patients during the doctor's diagnosis and treatment process. From February to June 2025, the cumulative number of patients served by AI diagnosis and treatment assistant assisting doctors has reached 26,000. The platform supports core application scenarios such as intelligent medical record generation, diagnostic assistance, research services, and operational analysis, becoming a critical infrastructure for hospital digital transformation.

Big Data Platform and Solutions ("BDPS") (AI for Medical)

In the BDPS segment, we provide data intelligence platforms and data analytics-driven solutions for hospitals, healthcare institutions, regulators and policymakers. During the Reporting Period, the revenue of this segment was RMB345.9 million, representing a year-on-year increase of 10.3%. As of 31 March 2025, the total number of our top hospital clients was 110, while the total number of regulator and policymaker clients was 44. During the Reporting Period, our core products underwent comprehensive upgrades:

AI Middleware 2.0: By unifying the management of diverse large language models in the medical field (including general open-source, specialty-enhanced and user-trained models) and incorporating technological upgrades such as hallucination control for large language models, we launched standard intelligent agents for scenarios like triage and medical record structuring. These agents span the entire clinical journey from pre-consultation, in-consultation, and post-consultation, assisting doctors in formulating treatment plans, accelerating clinical research, and enhancing the patient healthcare experience. Within just three months of launch, Our AI Middleware 2.0 has been deployed in more than 30 of leading Grade III-A hospitals. AI Middleware 2.0 can enable medical record writing to shift from traditional 5-minute manual work to 30-second intelligent completion, reduce TNM staging evaluation time by 70%, and empower doctors to create their own customized intelligent assistants in just 1 minute.
Next-generation Data Center Eywa 5.0: By deeply integrating large language models with hospital data platforms, we built an intelligent operational management system covering all scenarios, achieving comprehensive coordination of business process data. Empowered by large language models for multimodal data governance, data flow speed has increased, and the efficiency of data collection, governance and quality control has improved by over 4 times, which significantly reduces labor and computational costs.
Upgraded Intelligent Hospital Management Solution "Lingxi Intelligent Management": The digital brain assisting in building refined hospital operational management has achieved global monitoring and precise intervention from overall hospital operation strategies to departmental execution, thereby creating a closed-loop management system of "data-root cause-decision" and improving hospital operational efficiency by 30%.
Upgraded Intelligent Research Solution "Lingxi Intelligent Research": Based on a large-model-powered multi-modal hospital-wide intelligent research platform, our "Lingxi Intelligent Research" solution is highly adaptable to the full process of clinical research needs, providing researchers with one-stop intelligent support to conduct research more efficiently and accelerate the output of scientific achievements. Compared to the traditional 2-4 weeks required for manual literature matrix compilation by clinical researchers, "Lingxi Intelligent Research" completes the generation of a literature matrix in just 1-2 hours.

Leveraging technical depth and scenario adaptability, our core products have gained high recognition from clients and achieved scaled penetration across different segmented customer bases:

Top Comprehensive Grade III-A Hospital: We assisted a top Grade III-A hospital in Central China in building a self-controlled AI middleware for full-scenario intelligence. Since 2019, we have collaborated with the hospital to establish multiple disease registries integrating over 2.5 billion legally authorised medical data entries. On this foundation of data governance, we successfully deployed an AI middleware supporting domestic large language models like DeepSeek, enabling hospital-wide data sharing and rapid implementation of intelligent applications. Through internal training and technical support, we helped hospital departments quickly adapt, and achieved a seamless transition from data governance to intelligent diagnostic applications.
Top Specialty Hospital: We have also achieved breakthroughs in specialized scenarios at top oncology hospitals, accelerating the digital and intelligent transformation of a leading cancer prevention and treatment center in South China, thereby supporting it to achieve a closed loop from data standardization to clinical application. Leveraging DeepSeek and YiduCore, we assisted the hospital in developing a diagnostic and treatment assistant with features including clinical decision support, automated medical record generation, and AI-powered dialogue. Additionally, we launched China's first "My AI Assistant" platform, enabling doctors to customize their own AI tools. Moving forward, we will continue supporting the hospital in rapidly deploying over 120 intelligent agents. In practical applications at this hospital, AI-powered solutions built on our AI middleware have enhanced multiple aspects of oncology care, including medical documentation and clinical decision-making. On average, a single physician uses the AI assistant more than 150 times per month, improving consultation efficiency by 50%.
Collaboration with Renowned Expert: We have partnered with Academician Teng Gaojun's team to jointly launch China's first intelligent agent for liver cancer diagnosis and treatment. Powered by our large language model and DeepSeek, this intelligent agent deeply learns from the latest authoritative guidelines and expert consensus in liver cancer care. Under the leadership of Academician Teng Gaojun, the core clinical decision-making logic was formulated, translating cutting-edge interventional therapy advancements into standardized decision pathways. This breakthrough enables top medical institutions and experts to digitally consolidate and democratize standardized diagnosis & treatment capabilities, making high-quality care more accessible.
Large-Scale Population Application: During the Reporting Period, we secured the Tianjin Binhai New District Economic and Technological Development Zone Healthcare Big Data Platform Project, with a total project amount exceeding RMB20 million. As the core technology provider, Yidu Tech delivers AI-powered intelligent triage and digital therapeutics services, featuring AI-driven health Q&A, intelligent triage and digital therapeutics for diabetes & hypertension. The platform provides 24/7, precise and convenient medical consultation and auxiliary medical services to residents, offering personalized lifestyle interventions for chronic disease patients to enhance self-management. Through AI technology, we are advancing continuous intelligent health support for the community.

In the future, we will continue to iterate and upgrade our product matrix, to achieve a trinity synergy of broad coverage in general hospitals, in-depth empowerment of specialized hospitals, and the replication of top-tier expert experience. Leveraging the Lingxi Intelligent Management and Lingxi Intelligent Research platforms, we will support the construction of an intelligent collaborative system for multi-scenario applications, empowering both clinical value and scientific research innovation.

Life Sciences Solutions ("LSS") (AI for Life Science)

The LSS segment provides intelligent support for the full life-cycle management of pharmaceuticals and medical devices, from preclinical research to commercialization. Through our proprietary i-Series solution matrix, including the intelligent clinical research software system (Yidu iTrial), investigational ward system (iGCP), remote intelligent clinical trial digital platform (Yidu iDCT), electronic data capture system (iEDC), intelligent patient recruitment (iRecruitment), strategic consulting solutions (Yidu iConsulting), and real-world research solutions (Yidu iEvidence), we have built a comprehensive service system that covers clinical development efficiency optimization, precision research design, and commercialization risk prediction, enabling models to deliver outstanding performance across multiple clinical research scenarios, driving a triple breakthrough in cost reduction, acceleration and quality enhancement.

During the Reporting Period, our revenue from this segment amounted to RMB247.1 million, representing a year-on-year decrease of 23.7%. The gross profit margin increased by 1.4 percentage points to 33.5%. We focus on a high-quality customer base and continuously enhance customer experience by concentrating on full life-cycle solutions empowered by digital and intelligent technology innovation to increase customer repurchase rates. As of 31 March 2025, we achieved a 87.51% revenue retention rate for our top 20 clients in terms of revenue. 16 out of the top 20 MNCs are our clients. In terms of clinical research, we have performed 411 clinical researches, including clinical trials sponsored by registered pharmaceutical companies and investigator-initiated clinical trials ("IIT"). We have performed 275 prospective and retrospective real-world study ("RWS").

During the Reporting Period, the number of hospitals contracted for the iGCP system increased by 23 to 47. Furthermore, in the field of clinical data management, Yidu Tech's iEDC solution has restructured data governance processes through modular technologies: the intelligent database system (iDatabase) enables automatic translation of trial protocols, while the automated data entry system (iCollector) improves data collection efficiency by 50% compared to traditional methods. Combined with automated logic checks (iCheck) and intelligent data cleaning (iReview), it forms a full-chain automated system spanning data collection, quality control and analysis. This solution has reduced manual monitoring efforts in clinical trials by 30%, while the intelligent analysis insight module (iInsight) deeply mines data value, significantly enhancing the quality control of clinical research.

In intelligent patient recruitment, iRecruitment leveraged experience in screening tens of millions of patient data, it broke through the limitations of traditional rule-based engines. Under the premise of strictly implementing the Personal Information Protection Law, obtaining authorizations from medical institutions, and securing patients' informed consent, it safely and compliantly conducted multimodal fusion analysis on de-identified heterogeneous medical data. This approach reduced 90% of manual configuration costs while achieving a

leapfrog improvement in patient matching accuracy by more than threefold. This AI-driven screening model, free from heavy human intervention, provides a highly generalizable and precise enrollment solution for drug and medical device clinical research. Intelligent patient recruitment has been deeply deployed at Sun Yat-sen University Cancer Center and is progressively expanding to more Grade III-A hospitals in alignment with the roll-out of Yidu's AI middleware products.

During the Reporting Period, leveraging our expertise and strengths accumulated in the oncology field, we made further progress in clinical trials for cancer treatment and secured multiple projects, including medical monitoring and pharmacovigilance (PV) services for a Phase III cervical cancer project, a prospective study service for advanced gastric or gastroesophageal junction cancer, data entry for a colorectal cancer project, and clinical trial technical services for a pancreatic cancer project ("CRO Services"). Additionally, we empowered a large-sample RWS on HER2-positive advanced breast cancer conducted by a well-known pharmaceutical company through digital solutions, compressing the research cycle to 14 months, a 40% efficiency improvement compared to traditional models.

During the Reporting Period, Yidu Tech won the tenders for multiple clinical trial projects in the ophthalmology field, including a Phase III clinical trial for an eye drop from a biotech company, with the project value exceeding RMB50 million. Furthermore, we provided clinical trial site management organisation ("SMO") services for a Phase II presbyopia drug treatment project, and will provide SMO and digital clinical trial ("DCT") platform services for a Phase II clinical trial of a cataract eye drop. Additionally, Yidu Tech won the tender for several other ophthalmology clinical research projects, such as an investigator-initiated clinical research project for angle-closure glaucoma surgery and a Phase III project for the rare genetic eye disease BCD, further solidifying our advantageous position in the ophthalmology clinical research.

Yidu Tech has built a deeply vertical and multidisciplinary talent team, with core members averaging over 10 years of experience in clinical research, biostatistics, medical informatics, and artificial intelligence. Through our dual-spiral training system of "technical depth + clinical insight", we have established a comprehensive capability matrix covering protocol design, data governance and AI modeling.

Health Management Platform and Solutions ("HMPS") (AI for Care)

In this segment, we provide AI-enabled health management solutions to cater to multi-level healthcare solutions for tens of millions of urban residents. During the Reporting Period, the revenue of our HMPS segment amounted to RMB122.0 million, representing a year-on-year decrease of 28.0%, mainly due to the changes in product portfolios.

During the Reporting Period, we continued to consolidate our Hui Min Bao (惠民保) business. We enhanced our efforts in the Hui Min Bao (惠民保) projects in China's core provinces and cities. With the support of AI medical technology, the medical insights accumulated by YiduCore, and our rich experience in scenario operations, we have been able to provide and continue to innovate and upgrade one-stop operation solutions for Hui Min Bao (惠民保) in provinces and cities with tens of millions of populations such as Beijing and Shenzhen, which further solidified the advantageous position of our Hui Min Bao (惠民保) business in China's core cities.

During the Reporting Period, we were the main operation platform for Shenzhen Hui Min Bao (深圳惠民保) for three consecutive years, the number of the insured in 2024 reached 6.09 million, and the insurance participation rate was more than 35%, ranking among top performers in China. As of 31 March 2025, Shenzhen Hui Min Bao (深圳惠民保) has provided payouts for nearly 230,000 claims, with the highest cumulative reimbursement for a single individual reaching RMB1.8 million. Beneficiaries have ranged from a one-month-old infant to a 103-year-old senior citizen, truly delivering inclusive healthcare to every segment of the population. In addition, we have served as the main operation platform for Beijing Hui Min Bao (北京惠民保) for four consecutive years. The cumulative number of the insured for Beijing Hui Min Bao (北京惠民保) amounted to more than 15 million, and the cumulative number of claims received has exceeded 370,000 claims, providing timely protection to numerous families affected by illness and benefiting the public in a significant way.

With the empowerment of AI technology, our insurance claim efficiency has been significantly improved. Among policyholders filing claims for "Beijing Hui Min Bao (北京惠民保)", nearly 80% received settlements through express claims processing. By processing data legally authorized by the users and relevant organizations, we may achieve rapid processing of tens of thousands of cases per month, and the time efficiency of claim settlement has been improved by 50%–70% compared with the traditional methods. After applying the expedited claim model, the expedited claim cases do not require the insured to provide medical bills and other claim materials, but rather actively reach out and notify the insured by text messages and phone calls that the claim criteria has been met and the claim can be paid, which significantly shortens the time for claim settlement and reduces the burden of advancing funds on the part of the insured, and greatly improves the experience of the insured in the use of the insurance policy. More than 85% of our customer service is handled by AI intelligent customer service, achieving a second-level response and good user experience as compared with the traditional services. In the future, we will adhere to improving claim efficiency through technology, enhancing claim quality through services, and exploring other claims data-enabled businesses to establish higher professional barriers.

We also provide AI one-stop private health consulting services by leveraging YiduCore's accumulated technology capabilities and medical knowledge. During the Reporting Period, the "Happy Health Technology" mini program, a private health consultant developed based on our proprietary large language model, completed its internal testing and was officially launched and was open to the public for testing. As a multi-scenario, one-stop private health consulting platform, "Happy Health Technology" uses advanced generative AI technology and multi-modal comprehension to provide users with personalized health questions and answers, guidance consultation, report result interpretation, children's fever consultation, health assessment and other professional services, as well as customized health suggestions and plans, enabling everyone to enjoy a new experience of convenient, efficient and personalized health management. According to statistics, "Happy Health Technology" achieves an average visit duration of 316 seconds per user and the continuous use of our users further fed back and enhanced the depth of disease understanding and problem-solving capabilities of our proprietary large language models.

During the Reporting Period, we collaborated with Academician Teng Gaojun’s team from Zhongda Hospital Southeast University to jointly launch China’s first intelligent agent for liver cancer diagnosis and treatment. Powered by dual engines, being DeepSeek and Yidu’s vertical medical large language model, this intelligent agent deeply learns from the latest authoritative guidelines and expert consensus in liver cancer. It provides personalized rehabilitation guidance and lifestyle recommendations tailored to patients’ specific conditions. In terms of report interpretation, the intelligent agent can intelligently identify abnormal indicators, explain medical data and treatment solutions in plain language, simultaneously highlight risks and suggest interventions and facilitate scientific decision-making. Academician Teng Gaojun’s team from Zhongda Hospital Southeast University continues to provide feedback and optimization of response logic, ensuring the professionalism and reliability of medical advice, enabling the standardized diagnostic capabilities of top medical institutions and experts to be digitally preserved and inclusively disseminated.

As of 31 March 2025, the number of active users who have completed at least one transaction on our health management platform exceeded 24 million.

Business Outlook

To achieve our mission to “making precision healthcare accessible to everyone” and maintain a advantageous position in the AI healthcare industry, our strategic planning will be divided into the following key directions: (i) core AI technology optimization and investment: we will continue to increase investment and optimize large language model in the medical vertical field and constantly improve the function of our core algorithm “AI Medical Brain” YiduCore to promote the full-chain integration of large language models in scenarios such as diagnostic assistance, data governance, and scientific research innovation. Through algorithm optimization and computing power upgrades, we will enhance the accuracy and reliability of YiduCore in high-complexity tasks; (ii) deepening disease research and application: we will further integrate large language models with multi-center real-world data to provide AI-driven decision support for core diseases such as tumors and cardiovascular and cerebrovascular diseases, ranging from early screening to personalized treatment, to provide more accurate and efficient medical solutions; (iii) AI empowering customer experience and operating efficiency: we will endeavor to deepen intelligent interaction and process automation to achieve precise delivery, empower services with AI to enhance service quality and operational efficiency, further optimize customer experience, and strengthen customer satisfaction; and (iv) further enriching our ecosystem through strategic partnerships, investments and acquisitions.

In respect of BDPS, we will continue to strengthen our AI-enabled “two-pronged” strategy and reconstruct the healthcare data value chain driving by AI technology. Horizontally, we will continue to (i) further expand the hospital and city-regional networks by continuously iterating our AI product ecosystem, including the AI middleware, data middleware, research platform, and hospital management platform; (ii) enrich the use case scenarios of existing customers, and promote the leap from single-point tools to full-chain AI solutions; and (iii) accelerate the construction of a specialized and scenario-based product matrix, continuously enhance the functionality, reliability and usability of our products in combination with state-of-art AI technology development. Vertically, we will continue to deepen and optimize our research within each key disease area by enabling multisite research to be carried out based on disease dimensions and hospital networks.

In respect of LSS segment, with the constant development of AI technology, and the “patient centered” research and development concept being more integrated throughout full life-cycle of the medicine research and development, we will continue to accelerate the generation of research-grade evidence based on YiduCore to drive the development of our one-stop solutions from analytics-driven clinical development to post-launch commercialization. We will stay focused on (i) further iterate and optimize our i-Series intelligent solution matrix to help pharmaceutical companies reduce new drug development costs and enhance operational efficiency, (ii) generation and application of RWE, (iii) key disease areas we excel at in clinical development, and (iv) preservation and enlargement of our high-quality customer base.

In respect of HMPS segment, we will continue to utilize our disease insights, knowledge and expert network to provide effective health management solutions to benefit more people with “patient-centered, outcome-oriented” care. We will continue to (i) increase the number of active users from diversified channels, (ii) explore new models of AI-enabled health management services, and (iii) enrich user experience to solidify brand loyalty.

As a leading player in the rapidly evolving AI healthcare industry, we will continue to abide by our mission of “making precision healthcare accessible to everyone”, capture the massive market opportunities in China and other regions with independent innovation and high-quality development, and enable stakeholders in the healthcare ecosystem to derive more value from our continuously iterating intelligent “AI Medical Brain”.

MANAGEMENT DISCUSSION AND ANALYSIS

Revenues

Our revenue decreased by 11.4% from RMB807.1 million for the fiscal year ended 31 March 2024 to RMB715.0 million for the fiscal year ended 31 March 2025. The decrease was primarily attributable to the decrease in revenue from Life Science Solutions segment and Health Management Platform and Solutions segment.

Big Data Platform and Solutions. Revenue from Big Data Platform and Solutions remained relatively stable with an increase of 10.3% from RMB313.6 million for the fiscal year ended 31 March 2024 to RMB345.9 million for the fiscal year ended 31 March 2025.

Life Sciences Solutions. Revenue from Life Sciences Solutions decreased by 23.7% from RMB324.0 million for the fiscal year ended 31 March 2024 to RMB247.1 million for the fiscal year ended 31 March 2025, which was mainly due to the impact of a challenging external environment.

Health Management Platform and Solutions. Revenue from Health Management Platform and Solutions decreased by 28.0% from RMB169.5 million for the fiscal year ended 31 March 2024 to RMB122.0 million for the fiscal year ended 31 March 2025, primarily due to the changes in product portfolios.

Cost of Sales and Services

Our cost of sales and services increased by 1.7% from RMB467.6 million for the fiscal year ended 31 March 2024 to RMB475.8 million for the fiscal year ended 31 March 2025. Share-based compensation expenses included in cost of sales and services were RMB5.5 million and RMB2.9 million for the fiscal years ended 31 March 2024 and 2025 respectively.

Big Data Platform and Solutions. Cost of sales and services from the Big Data Platform and Solutions segment increased by 37.7% from RMB176.7 million for the fiscal year ended 31 March 2024 to RMB243.3 million for the fiscal year ended 31 March 2025, primarily due to changes in product portfolios.

Life Sciences Solutions. Cost of sales and services from Life Sciences Solutions decreased by 25.3% from RMB220.0 million for the fiscal year ended 31 March 2024 to RMB164.3 million for the fiscal year ended 31 March 2025, which was mainly due to a roughly proportional decrease in revenue.

Health Management Platform and Solutions. Cost of sales and services from the Health Management Platform and Solutions segment remained relatively stable with a decrease of 3.8% from RMB70.9 million for the fiscal year ended 31 March 2024 to RMB68.2 million for the fiscal year ended 31 March 2025.

Gross profit and gross margin

As a result of the foregoing, our overall gross profit for the fiscal years ended 31 March 2024 and 2025 was RMB339.4 million and RMB239.2 million respectively, and our overall gross margin was 42.1% and 33.5% respectively.

Big Data Platform and Solutions. Our gross margin in Big Data Platform and Solutions decreased from 43.7% for the fiscal year ended 31 March 2024 to 29.7% for the fiscal year ended 31 March 2025, primarily due to the changes in product portfolios.

Life Sciences Solutions. Our gross margin in Life Sciences Solutions remained relatively stable with an increase from 32.1% for the fiscal year ended 31 March 2024 to 33.5% for the fiscal year ended 31 March 2025.

Health Management Platform and Solutions. Our gross margin in Health Management Platform and Solutions decreased from 58.1% for the fiscal year ended 31 March 2024 to 44.1% for the fiscal year ended 31 March 2025, primarily due to the changes in product portfolios.

Selling and marketing expenses

Our selling and marketing expenses decreased by 33.4% from RMB208.9 million for the fiscal year ended 31 March 2024 to RMB139.2 million for the fiscal year ended 31 March 2025, primarily attributable to the decrease in (i) employee benefits and expenses of employees engaging in selling and marketing function from RMB132.9 million to RMB91.5 million; and (ii) business development, promotion and advertising expenses, travelling, entertainment and office expenses for the Group's marketing activities and insurance services from RMB64.6 million to RMB38.4 million.

Selling and marketing expenses as a percentage of revenue decreased from 25.9% for the fiscal year ended 31 March 2024 to 19.5% for the fiscal year ended 31 March 2025.

Administrative expenses

Our administrative expenses decreased by 14.6% from RMB171.3 million for the fiscal year ended 31 March 2024 to RMB146.4 million for the fiscal year ended 31 March 2025, primarily attributable to decreases in employee benefits and expenses of employees engaging in administrative function from RMB123.1 million to RMB100.2 million, which included share-based compensation expenses of RMB25.7 million and RMB9.1 million in the respective years.

Administrative expenses as a percentage of revenue decreased from 21.2% for the fiscal year ended 31 March 2024 to 20.5% for the fiscal year ended 31 March 2025.

Research and development expenses

Our research and development expenses decreased by 19.9% from RMB232.9 million for the fiscal year ended 31 March 2024 to RMB186.5 million for the fiscal year ended 31 March 2025. The decrease in research and development expenses was primarily due to the decrease in employee benefits and expenses for employees engaging in research and development function from RMB152.4 million to RMB103.2 million.

Research and development expenses as a percentage of revenue decreased from 28.9% for the fiscal year ended 31 March 2024 to 26.1% for the fiscal year ended 31 March 2025.

Operating loss

As a result of the foregoing, our operating loss decreased by 39.0% from RMB219.9 million for the fiscal year ended 31 March 2024 to RMB134.1 million for the fiscal year ended 31 March 2025.

Taxation

Income tax expense of the Group increased from RMB0.05 million for the fiscal year ended 31 March 2024 to RMB0.30 million for the fiscal year ended 31 March 2025.

Loss for the year

As a result of the foregoing, our loss for the year decreased by 38.9% from RMB221.2 million for the fiscal year ended 31 March 2024 to RMB135.2 million for the fiscal year ended 31 March 2025.

Liquidity and capital resource

During the fiscal year ended 31 March 2025, we had funded our cash requirements principally by capital contribution from shareholders and financing through issuance and sales of convertible redeemable preferred shares in private placement transactions and proceeds from initial public offering. We had cash and cash equivalents, term deposits, pledged bank deposits, restricted bank balances and deposits of RMB3,409.9 million and RMB3,309.1 million as of 31 March 2024 and 2025 respectively.

Significant investments

On 28 October 2022, Marvelous Panda Inc., a wholly-owned subsidiary of the Company, entered into a subscription agreement for the fund YD Capital I L.P. (the "Fund") with the general partner and became a limited partner of the Fund by making a cash contribution of US$40.0 million to the Fund, representing 40% of the fund commitment. As at 31 March 2025, the cash equivalent to US$6.6 million was paid by the Group. The purpose of the Fund is primarily to (i) make venture capital investments in the healthcare sector, (ii) manage, supervise and dispose of such investments, and (iii) engage in such other activities incidental or ancillary thereto as the general partner deems necessary, appropriate or advisable.

Material acquisitions and disposals

During the fiscal year ended 31 March 2025, the Group did not have any material acquisitions or disposals of subsidiaries, consolidated affiliated entities or associated companies.

Pledge of assets

As at 31 March 2025, the Group had no material pledge of assets.

Future plans for material investments or capital assets

As at 31 March 2025, the Group did not have detailed future plans for material investments or capital assets.

Foreign exchange exposure

During the fiscal year ended 31 March 2025, the Group mainly operated in China with most of the transactions settled in Renminbi. The functional currency of our Company, the subsidiaries and the consolidated affiliated entities that operate in the PRC, and the subsidiary operating in Brunei is U.S. dollar, Renminbi and Brunei dollar, respectively. For the fiscal year ended 31 March 2025, we had currency translation gains of RMB31.4 million and net foreign exchange gains of RMB6.0 million, as compared with currency translation gains of RMB94.8 million and net foreign exchange losses of RMB4.4 million for the fiscal year ended 31 March 2024.

We did not hedge against any fluctuation in foreign currency during the fiscal years ended 31 March 2024 and 2025.

Contingent liabilities

As at 31 March 2025, we did not have any material contingent liabilities (as at 31 March 2024: nil).

Capital commitment

As at 31 March 2025, capital commitment of the Group was nil (as at 31 March 2024: nil).

Investment commitment

As at 31 March 2025, investment commitment of the Group was RMB249.0 million (as at 31 March 2024: RMB256.6 million), mainly for the outstanding contribution from Marvelous Panda Inc., a wholly-owned subsidiary of the Company, to the Fund YD Capital I L.P..

Employees and remuneration

As at 31 March 2025, the Group had a total of 823 employees, with 425 employees based in Beijing, 82 employees in Shanghai and 316 employees in other offices in China and overseas. The table below sets forth the total number of employees by function as at 31 March 2025:

Function	Number of employees
Product Development and Technology	326
Medical Function	277
Sales and Marketing	142
General and Administrative	78
Total	823

The total remuneration cost incurred by the Group for the fiscal year ended 31 March 2025 was RMB417.6 million, as compared to RMB566.3 million for the fiscal year ended 31 March 2024. The Company has also adopted a Post-IPO Share Award Scheme and a Post-IPO Share Option Scheme which was terminated on 25 August 2023 but the provisions of the Post-IPO Share Option Scheme shall remain in full force to the extent necessary to give effect to the exercise of any options granted prior to the termination.

Subsequent Events

As at the date of this announcement, the Group has no significant events occurred after the Reporting Period which require additional disclosures or adjustments.

CORPORATE GOVERNANCE AND OTHER INFORMATION

The Company was incorporated in the Cayman Islands on 9 December 2014 as an exempted company with limited liability, and the shares of the Company were listed on the Main Board of The Stock Exchange of Hong Kong Limited (the “Stock Exchange”) on 15 January 2021 (the “Listing Date”).

The Board is committed to achieving high corporate governance standards. The Board believes that high corporate governance standards are essential in providing a framework for the Group to safeguard the interests of shareholders and to enhance corporate value and accountability.

Compliance with the Code on Corporate Governance Practices

During the Reporting Period, the Company has complied with the Corporate Governance Code (the “Corporate Governance Code”) set out in Appendix C1 to the Rules Governing the Listing of Securities on The Stock Exchange of Hong Kong Limited (the “Listing Rules”), save for the following deviations.

Code provision F.1.1 of the Corporate Governance Code provides that the issuer should have a policy on payment of dividends and should disclose it in the annual report. As the Company intends to retain its available funds and earnings to fund the development and growth of our business, the performance of which will continue to be impacted by the relevant industry’s and economic outlook in the foreseeable future, the Board is of the opinion that it is not appropriate to adopt a dividend policy at this stage. The Board will review the Company’s status periodically and consider to adopt a dividend policy if and when appropriate.

Compliance with the Model Code for Securities Transactions by Directors

The Company has adopted the Model Code for Securities Transactions by Directors of Listed Issuers (the “Model Code”) as set out in Appendix C3 of the Listing Rules as its own code of conduct regarding directors’ securities transactions.

Specific enquiry has been made of all the Directors and the relevant employees and they have confirmed that they have complied with the Model Code during the Reporting Period.

Audit Committee

The Group has established the Audit Committee comprising three members, being Dr. Ma Wei-Ying, Ms. Pan Rongrong and Prof. Zhang Linqi, with Ms. Pan Rongrong (being the Company’s independent non-executive Director with the appropriate professional qualifications) as chair of the Audit Committee.

The Audit Committee has reviewed the audited consolidated financial statements of the Group for the fiscal year ended 31 March 2025 and has met with the independent auditor, PricewaterhouseCoopers (the “Auditor”). The Audit Committee has also discussed matters with respect to the accounting policies and practices adopted by the Company and internal control and financial reporting matters with senior management members of the Company.

Auditor’s scope of work

The figures in respect of the Group’s consolidated statement of comprehensive income, consolidated balance sheet and the related notes thereto for the fiscal year ended 31 March 2025 contained in this announcement have been agreed by the Auditor, to the amounts set out in the audited consolidated financial statements of the Group for the fiscal year ended 31 March 2025. The work performed by the Auditor in this respect did not constitute an assurance engagement in accordance with Hong Kong Standards on Auditing, Hong Kong Standards on Review Engagements or Hong Kong Standards on Assurance Engagements issued by the Hong Kong Institute of Certified Public Accountants and consequently no assurance has been expressed by the Auditor on this announcement.

OTHER INFORMATION

Purchase, sale or redemption of the Company's listed securities

During the fiscal year ended 31 March 2025, the Company repurchased a total of 6,340,800 shares of the Company on the Stock Exchange at an aggregate consideration of approximately HK$22,049,521.63. The repurchase was effected for the enhancement of shareholder value in the long term. During the fiscal year ended 31 March 2025, 3,449,700 shares repurchased were subsequently cancelled.

Particulars of the shares repurchased are as follows:

Month of Repurchase	No. of Shares Repurchased	Price Paid per Share Highest (HK$)	Lowest (HK$)	Aggregate Consideration (HK$)
April	1,261,400	3.64	3.29	4,305,938.49
July	1,840,800	3.58	3.35	6,385,348.15
August	149,200	3.51	3.39	513,306.80
October	3,089,400	3.80	3.34	10,844,928.19
Total	6,340,800			22,049,521.63

Material litigation

The Company was not involved in any material litigation or arbitration during the Reporting Period. The Directors are also not aware of any material litigation or claims that are pending or threatened against the Group during the Reporting Period and up to the date of this announcement.

Use of proceeds from global offering

On 15 January 2021, the shares of the Company were listed on the Main Board of the Stock Exchange. The net proceeds from the global offering (following full exercise of the Over-allotment Option, as defined in the prospectus of the Company dated 31 December 2020 (the "Prospectus")) were approximately RMB3,825 million (the "Net Proceeds"), which are intended to be applied in the manner set out in the Prospectus. There was no change in the intended use of proceeds as previously disclosed.

Set out below is the status of use of proceeds from the global offering as at 31 March 2025 and 2024.

Purpose	% of use of proceeds	Net proceeds (RMB million)	Unutilised amount as at 31 March 2024 (RMB million)	Amount used in the fiscal year ended 31 March 2025 (RMB million)	Unutilised amount as at 31 March 2025 (RMB million)	Actual or expected time of full utilisation
Strengthen our core capabilities	35%	1,339	633	394	239	31 March 2026(1)
Further our business expansion	35%	1,339	130	130	—	30 September 2024
Further enrich our ecosystem through strategic partnerships, investments and acquisitions	20%	765	712	11	701	31 March 2030(1)
Working capital and general corporate purposes	10%	382	125	125	—	31 March 2025

The above Net Proceeds were translated with spot rates on the Listing Date, while the cash and cash equivalents, term deposits, pledged bank deposits, restricted bank balances and deposits as of 31 March 2025 were translated with spot rates on its balance sheet date.

As of 31 March 2025, the Company had utilised RMB2,885 million of the Net Proceeds.

Dividend

The Board does not recommend the distribution of a final dividend for the fiscal year ended 31 March 2025.

Closure of register of members

The Company's annual general meeting (the "AGM") will be held on 29 August 2025, Friday. The register of members of the Company will be closed for the purpose of determining the identity of members who are entitled to attend the AGM from 26 August 2025, Tuesday to 29 August 2025, Friday, both days inclusive, during which period no transfer of shares will be registered. In order to be eligible to attend the AGM, all duly completed transfer forms accompanied by the relevant share certificates must be lodged with the Company's share registrar in Hong Kong, Computershare Hong Kong Investor Services Limited, at Shops 1712-1716, 17th Floor, Hopewell Centre, 183 Queen's Road East, Hong Kong, for registration, no later than 4:30 p.m. on 25 August 2025, Monday.

(1) There has been a delay in the full utilisation of the Net Proceeds as the Board has taken a more prudent approach in light of the volatile macroeconomic environment in recently years. It is expected that the remaining balance of the Net Proceeds allocated to strengthen our core capabilities and to further enrich our ecosystem through strategic partnerships, investments and acquisitions will be fully utilised by 31 March 2026 and 31 March 2030, respectively.

CONSOLIDATED STATEMENT OF COMPREHENSIVE INCOME

	Year ended 31 March
	2025
RMB'000	2024
RMB'000
Revenue from contracts with customers	714,979	807,076
Cost of sales and services	(475,797)	(467,631)
Gross profit	239,182	339,445
Selling and marketing expenses	(139,194)	(208,909)
Administrative expenses	(146,353)	(171,300)
Research and development expenses	(186,480)	(232,927)
Net impairment losses on financial assets and contract assets	(78,612)	(104,905)
Impairment of non-financial assets	100	37
Other income	165,053	155,583
Other gains — net	12,155	3,057
Operating loss	(134,149)	(219,919)
Finance income	2,321	10,510
Finance costs	(2,012)	(3,311)
Finance income — net	309	7,199
Share of losses from investments in associates	(1,085)	(8,473)
Loss before income tax	(134,925)	(221,193)
Income tax expense	(298)	(49)
Loss for the year	(135,223)	(221,242)
Loss is attributable to:
Owners of the Company	(117,788)	(194,944)
Non-controlling interests	(17,435)	(26,298)
	(135,223)	(221,242)

CONSOLIDATED STATEMENT OF COMPREHENSIVE INCOME (CONTINUED)

	Year ended 31 March
	2025
RMB'000	2024
RMB'000
Other comprehensive income
Item that will not be reclassified to profit or loss:
Currency translation differences	81,834	217,649
Item that will be reclassified to profit or loss:
Currency translation differences	(50,420)	(122,837)
Other comprehensive income for the year, net of tax	31,414	94,812
Total comprehensive loss for the year	(103,809)	(126,430)
Total comprehensive loss for the year is attributable to:
Owners of the Company	(88,923)	(104,593)
Non-controlling interests	(14,886)	(21,837)
	(103,809)	(126,430)
Loss per share, basic and diluted (RMB)	(0.11)	(0.19)

CONSOLIDATED BALANCE SHEET

	As at 31 March
	2025	2024
	RMB'000	RMB'000
Assets
Non-current assets
Property, plant and equipment	156,941	80,508
Right-of-use assets	5,588	12,433
Investment properties	2,894	—
Intangible assets	33,953	39,119
Deferred income tax assets	30	294
Investments accounted for using the equity method	39,428	32,717
Investments measured at amortized cost	366,088	191,565
Financial assets at fair value through profit or loss	104,427	21,357
Pledged bank deposits	6,439	5,842
Restricted bank balance and deposits	6,352	6,289
Total non-current assets	722,140	390,124
Current assets
Inventories	12,902	4,407
Trade receivables	449,239	496,367
Contract assets	69,753	90,820
Other financial assets at amortised cost	45,679	51,401
Investments measured at amortized cost	9,598	249,854
Financial assets at fair value through profit or loss	17,000	70,151
Pledged bank deposits	3,217	6,232
Restricted bank balance and deposits	37,570	14,486
Term deposits	1,939,134	1,969,452
Cash and cash equivalents	1,316,397	1,407,620
Other current assets	66,483	73,284
Total current assets	3,966,972	4,434,074
Total assets	4,689,112	4,824,198

CONSOLIDATED BALANCE SHEET (CONTINUED)

	As at 31 March
	2025	2024
	RMB'000	RMB'000
Equity
Equity attributable to owners of the Company
Share capital	136	135
Treasury shares	(13,710)	(4,524)
Other reserves	13,113,631	13,088,220
Accumulated deficits	(9,178,748)	(9,060,960)
	3,921,309	4,022,871
Non-controlling interests	56,433	69,122
Total equity	3,977,742	4,091,993
Liabilities
Non-current liabilities
Lease liabilities	5,551	6,415
Deferred income	69,742	71,295
Total non-current liabilities	75,293	77,710
Current liabilities
Borrowings	121,997	80,000
Trade and other payables	253,488	296,385
Salary and welfare payable	177,805	207,432
Contract liabilities	68,734	49,831
Current income tax liabilities	234	234
Lease liabilities	1,996	8,786
Provisions	11,823	11,827
Total current liabilities	636,077	654,495
Total liabilities	711,370	732,205
Total equity and total liabilities	4,689,112	4,824,198

NOTES TO THE CONSOLIDATED FINANCIAL STATEMENTS

1 General information

Yidu Tech Inc. (the “Company”) was incorporated in the Cayman Islands on 9 December 2014 as an exempted company with limited liability under the Companies Act of the Cayman Islands (Cap. 22, Law 3 of 1961 as consolidated and revised). The address of the Company is Suite #4-210, Governors Square, 23 Lime Tree Bay Avenue, PO Box 32311, Grand Cayman KY1-1209, Cayman Islands.

The Company is an investment holding company and its subsidiaries (together, the “Group”) are primarily engaged in the provision of the following services: i) big data platform and solutions, ii) life sciences solutions, and iii) health management platform and solutions in the People’s Republic of China (“PRC”), Brunei and Singapore.

These financial statements are presented in Renminbi (“RMB”), unless otherwise stated.

2 Summary of accounting policies

The principal accounting policies applied in the preparation of the consolidated financial statements are set out below. These policies have been consistently applied to all the years presented, unless otherwise stated.

2.1 Basis of preparation

(i) Compliance with IFRSs

The consolidated financial statements of the Group have been prepared in accordance with IFRS (“IFRSs”) as issued by International Accounting Standards Board (“IASB”).

The preparation of consolidated financial statements in conformity with IFRSs requires the use of certain critical accounting estimates. It also requires management to exercise its judgement in the process of applying the Group’s accounting policies. The areas involving a higher degree of judgement or complexity, or areas where assumptions and estimates are significant to the consolidated financial statements are disclosed in note 4 of the consolidated financial statements.

(ii) Historical cost convention

The consolidated financial statements have been prepared under the historical cost convention, as modified by the revaluation of financial assets at fair value through profit or loss.

(iii) New and amended standards adopted by the Group

The Group has applied the following standards and amendments for the first time for their annual reporting period commencing 1 April 2024:

Amendment to IAS 1 — Classification of Liabilities as Current or Non-current and Non-current Liabilities with Covenants
Amendments to IFRS 16 — Lease Liability in Sale and Leaseback
Amendments to IAS 7 and IFRS 7 — Supplier Finance Arrangements
Amendments to IAS 21 — Lack of Exchangeability

The amendments listed above did not have any material impact on the amounts recognised in prior and current periods and are not expected to significantly affect the future periods.

(iv) New standards and interpretations not yet adopted

The Group has not early applied the following new and amendments to IFRSs that have been issued but are not yet effective:

Amendments to IFRS 9 and IFRS 7 — Amendments to the Classification and Measurement of Financial Instruments	Effective for annual periods beginning on or after
IFRS 19 — Subsidiaries without Public Accountability: Disclosure	1 January 2026
1 January 2027
IFRS 18 — Presentation and Disclosure in Financial Statements	1 January 2027

IFRS 18 will replace IAS 1 Presentation of financial statements, introducing new requirements that will help to achieve comparability of the financial performance of similar entities and provide more relevant information and transparency to users. Even though IFRS 18 will not impact the recognition or measurement of items in the financial statements, its impacts on presentation and disclosure are expected to be pervasive, in particular those related to the statement of financial performance and providing management-defined performance measures within the financial statements. Management is currently assessing the detailed implications of applying the new standard on the Group's consolidated financial statements.

Management is currently assessing the implication of applying IFRS 18, and preliminarily identified the fair value gains/(losses) on financial assets currently presented in the line item 'Other gains — net' within operating profit would be presented below operating profit, and certain additional disclosures would be added, other than that, there would not be significant impact on the Group's financial position and performance when adopting IFRS 18.

3 Segment information

Disaggregation of revenue from contracts with customers

The Group's business activities, for which discrete financial information are available, are regularly reviewed and evaluated by the Chief Operating Decision Maker. As a result of this evaluation, the Group determined that it has operating segments as follows:

Big data platform and solutions
Life sciences solutions
Health management platform and solutions

	Year ended 31 March 2025
	Big data platform and solutions RMB'000	Life sciences solutions RMB'000	Health management platform and solutions RMB'000	Total RMB'000
Revenue from contracts with customers	345,888	247,112	121,979	714,979
Cost of sales and services	(243,288)	(164,272)	(68,237)	(475,797)
Gross profit	102,600	82,840	53,742	239,182
	Year ended 31 March 2024
	Big data platform and solutions RMB'000	Life sciences solutions RMB'000	Health management platform and solutions RMB'000	Total RMB'000
Revenue from contracts with customers	313,634	324,044	169,398	807,076
Cost of sales and services	(176,699)	(219,998)	(70,934)	(467,631)
Gross profit	136,935	104,046	98,464	339,445

The Company is domiciled in the Cayman Islands while the Group mainly operates its businesses in the PRC. For the years ended 31 March 2025 and 2024, the Group earns approximately 83% and 17%, 86% and 14% of total revenue from external customers located in the PRC and other countries, respectively. As at 31 March 2025 and 2024, the majority of the non-current assets of the Group were located in the PRC and Brunei.

	Year ended 31 March
	2025	2024
	RMB'000	RMB'000
Segment revenue
— recognised over time	335,705	368,894
— recognised at a point in time	379,274	438,182
	714,979	807,076
Segment revenue
— gross	628,133	660,514
— net	86,846	146,562
	714,979	807,076

4 Expenses by nature

Expenses included in cost of sales and services, selling and marketing expenses, administrative expenses and research and development expenses are further analysed as follows:

	Year ended 31 March
	2025	2024
	RMB'000	RMB'000
Employee benefits expenses	417,634	566,252
Outsourcing services fee	220,985	239,834
Cost of hardware and pharmaceutical products	115,165	54,012
Consulting and other professional fee	75,815	71,394
Travelling, entertainment and general office expenses	51,244	56,364
Depreciation of property, plant and equipment	26,614	28,653
Amortization of intangible assets	8,862	7,936
Promotion and advertising expenses	7,987	25,220
Depreciation of right-of-use assets	7,797	10,429
Labour dispatching	5,113	7,071
Auditors' remuneration	4,765	5,915
— Auditor of the Company	3,600	3,900
Taxes and surcharges	2,239	2,611
Other expenses	3,604	5,076
Total cost of sales and services, selling and marketing expenses, administrative expenses and research and development expenses	947,824	1,080,767

5 Income tax expense

	Year ended 31 March
	2025	2024
	RMB'000	RMB'000
Current income tax expense/(credit)	34	(2)
Deferred income tax expense	264	51
Income tax expense	298	49

6 Loss per share

Basic loss per share for the years ended 31 March 2025 and 2024 are calculated by dividing the loss attributable to the Company's owners by the weighted average number of ordinary shares in issue during the years.

The calculation of loss per share is based on the following:

	Year ended 31 March
	2025	2024
	RMB'000	RMB'000
Loss attributable to owners of the Company	(117,788)	(194,944)
Weighted average number of ordinary shares in issue ('000)	1,056,432	1,051,620
Basic loss per share (RMB yuan)	(0.11)	(0.19)

7 Trade receivables

	As at 31 March
	2025	2024
	RMB'000	RMB'000
Trade receivables from contracts with customers
— Third parties	645,180	665,995
Less: allowance for impairment of trade receivables	(204,941)	(169,628)
	449,239	496,367

(a) The credit terms given to trade customers are determined on an individual basis with normal credit period mainly around 180 days. The aging analysis of the trade receivables based on invoice date is as follows:

	As at 31 March
	2025	2024
	RMB'000	RMB'000
— Up to 3 months	196,517	278,888
— 3 to 6 months	51,680	58,128
— 6 months to 1 year	81,400	107,855
— 1–2 years	188,541	97,787
— Over 2 years	136,042	123,337
	654,180	665,995
Less: allowance for impairment of trade receivables	(204,941)	(169,628)
Total	449,239	496,367

(b) Fair values of trade receivables

Due to the short-term nature of the current receivables, their carrying amounts are considered to be approximately the same as their fair values.

8 Trade and other payables

	As at 31 March
	2025	2024
	RMB'000	RMB'000
Trade payables (b)	137,269	170,373
Tax payables	11,687	14,478
Notes payables	4,520	4,611
Other payables:
— Payables for consulting and other service fee	28,418	41,119
— Insurance premium collection payables (c)	3,829	24,986
— Payables for repurchase of options	11,226	11,096
— Insurance claims collection payables	26,681	8,808
— Reimbursement payable to employees	6,654	5,841
— Accrual for marketing and sales promotion expenses	4,033	5,619
— Payables for leasehold and building improvement	4,783	422
— Payables for purchase of property, plant and equipment	570	365
— Others	13,818	8,667
	253,488	296,385

(a) The carrying amounts of trade and other payables are considered to be approximated to their fair values, due to their short-term nature.

(b) Aging analysis of the trade payables based on invoice date at the end of each reporting period are as follows:

	As at 31 March
	2025	2024
	RMB'000	RMB'000
— Up to 3 months	57,088	49,902
— 3 to 6 months	1,921	9,673
— 6 months to 1 year	7,598	20,160
— 1 to 2 years	26,559	31,815
— 2 to 3 years	9,635	57,576
— over 3 years	34,468	1,247
	137,269	170,373

(c) Insurance premium collection payables are insurance premiums collected on behalf of insurance companies but not yet remitted to them as at 31 March 2025.

9 Dividend

No dividend has been paid or declared by the Company or the companies now comprising the Group during the years ended 31 March 2025 and 2024.

PUBLICATION OF THE ANNUAL RESULTS ANNOUNCEMENT AND ANNUAL REPORT

This annual results announcement is published on the websites of the Stock Exchange (www.hkexnews.hk) and the Company (www.yidutech.com). The annual report of the Group for the fiscal year ended 31 March 2025 will be dispatched to the Company's shareholders and made available for review on the same websites in due course.

By order of the Board
Yidu Tech Inc.
Gong Yingying
Executive Director and Chairlady

Hong Kong, 25 June 2025

As at the date of this announcement, the executive Directors are Ms. Gong Yingying, Mr. Xu Jiming, Ms. Feng Xiaoying, and Dr. Xie Li; the non-executive Director is Mr. Zeng Ming; and the independent non-executive Directors are Dr. Ma Wei-Ying, Ms. Pan Rongrong and Prof. Zhang Linqi.