JieJie Tech Files IPO Prospectus: Pioneering Medical AI with Two Flagship Products and Partnerships Across 100+ Hospitals Within Six Months of Founding

Leveraging the tailwinds of artificial intelligence and its team’s strengths, Jiejie Technology, founded in June 2017, secured RMB 6 million in angel funding by September from a well-known pharmaceutical group.

Leveraging the extensive backgrounds in healthcare accumulated by its investors and founding team, Jiejie Tech has developed two medical AI products. The company is currently completing deployments at 100 hospitals, with negotiations underway for an additional 200 hospitals.

Jiejie Tech was founded in June 2017, focusing on exploring the applications of AI in medical imaging and cognitive reasoning computing. Shao Xuejie, founder and CEO of Jiejie Tech, told VCBeat that the company has two business lines: one is a computer vision product named “Xiao Jie,” which includes developed screening systems for pneumoconiosis and pulmonary nodules; the other is product research based on natural language recognition and cognitive computing, which has not yet been launched.

As a medical AI company, what gives Jiejie Tech such strong product R&D and marketing capabilities, and how does it stand out among the myriad of competitors in the medical AI sector? VCBeat has conducted a follow-up report on this matter.

“Founding Jiejie Technology was a return to my roots!” Shao Xuejie described himself this way when recounting his entrepreneurial journey.

The first company founded by Shao Xuejie was Yijie Imaging, which positioned itself as a SaaS-based live streaming cloud service provider for the healthcare industry. Prior to this, Shao served as the Chief Machine Learning Advisor for the Hospital Quality Monitoring System (HQMS) under the Bureau of Medical Administration and Hospital Supervision of the National Health and Family Planning Commission, and as a Partner at the Business School of Allpanda Management Consulting Group. During this period, he was responsible for algorithm research and assisted enterprises in producing research reports. He also participated in the construction of China’s first medical cloud, attempting to migrate data from five hospitals to the cloud. However, it later became evident that this was not a challenge solvable by individuals alone, but rather required government-led infrastructure and coordination. Consequently, he left his corporate roles to embark on an entrepreneurial venture.

In 2017, the AlphaGo incident enabled Shao Xuejie to recognize the immense future prospects of artificial intelligence and provided an opportunity for him to return to his core expertise. Consequently, he engaged in discussions with Yin Haijian, Marketing Director at Kingdee Software, and Yu Yongping, Director and Executive Deputy General Manager of Xinhua Kangmei Health Think Tank Co., Ltd., and they decided to jointly establish Jiejie Technology.

Yin Haijian possesses extensive experience in healthcare and marketing, complemented by the drive and ambition of youth. Yu Yongping has also dedicated over 30 years to the medical industry, serving as a consultant for multiple pharmaceutical companies while holding the title of Chief Physician. With a shared consensus on the project's viability, the three joined forces to develop the initial model for Jiejie Technology.

Shao Xuejie told VCBeat, “The shift from traditional machine learning to the recent rise of deep learning represents a natural progression. The combination of data mining and GPUs has made possible many studies that were previously unfeasible.”

Shao Xuejie once compiled his insights and practices in healthcare into a book—*Medical Revolution: Theory and Practice of Medical Data Mining*.

The book not only contains Shao Xuejie’s reflections on the deep-seated issues in China’s healthcare sector, as well as product design and development in the medical software market, but also introduces the progress made by the research team led by Shao Xuejie in applying machine learning to predict myocardial ischemia events based on baseline resting heart rate, explore the association between type 2 diabetes and pancreatic cancer, and investigate the relationship between atrial fibrillation and renal function.

Shao Xuejie also highlighted another key member of the team, Professor He Wen, Chief Physician in the Department of Radiology at Beijing Friendship Hospital. As a pioneer in artificial intelligence for medical imaging in China, Professor He Wen’s team began working on computer-aided interpretation of pulmonary nodules as early as 2007. Throughout the product development process, Professor He Wen was involved in nearly every technical milestone and parameter adjustment.

Shao Xuejie introduced that, currently, Jiejie Technology’s AI-powered tumor diagnosis and treatment robot comprises two major modules:

First, the computer vision module with the “DR Imaging Misdiagnosis Early Warning System for Pneumoconiosis” as its flagship product has been launched; the pneumoconiosis early warning system is currently undergoing clinical testing at several Grade A tertiary hospitals.。

VCBeat learned at the Asian Occupational Health Conference held in Guangzhou in December 2017 that there have been approximately 30,000 new cases of occupational diseases annually in recent years. Pneumoconiosis is the most common occupational disease in China, accounting for about 90% of all reported cases. Experts in occupational disease prevention and control stated that pneumoconiosis is preventable but incurable. The current challenges in prevention and control lie in the difficulties of diagnosis and certification. The key measure is to urge employers to implement dust control measures, ensuring that dust concentrations in workplaces meet national standards. Patients with pneumoconiosis should receive early diagnosis and treatment.

Additionally, Jiejie Technology’s lung nodule screening product has also taken shape.

Shao Xuejie stated that Jiejie Technology’s first product module primarily consists of artificial intelligence products based on computer vision, including but not limited to the CT Imaging Misdiagnosis Warning System for Lung Cancer, the Thyroid Cancer Imaging Diagnosis and Treatment System, the Breast Cancer Imaging Diagnostic System, the Prostate Cancer Imaging Diagnostic System, the Colorectal Cancer Imaging Diagnostic System, and the Gastric Cancer Imaging Diagnostic System.

Second is the human-machine dialogue module that combines computer natural language recognition with novel cognitive reasoning computation—SMART DOCTOR by Jiejie Technology. This product can be understood as a localized version of IBM Watson.。

The second-generation product, SMART DOCTOR, is built on NLP natural language learning technology based on cognitive reasoning and computation. Leveraging Jiejie Technology’s extensive case resources, it has developed a disease ontology knowledge base, disease corpus, oncology treatment knowledge base, and diagnostic segmentation lexicon tailored to China’s national conditions and ethnic characteristics. By applying artificial intelligence technologies, it aims to create a localized Chinese counterpart to Watson—a robot capable of generating oncology treatment plans.

Today, the medical AI market has nearly 100 participants. Facing such intense competitive pressure, Shao Xuejie remains full of confidence. This is mainly due to the three major advantages of Jiejie Technology.

Unsupervised Learning: JieJie Technology is the first company in the industry to forgo encapsulated algorithms. The team, composed of renowned algorithm experts Feng Weijia, Wang Yanming, and Shao Xuejie, has achieved a significant breakthrough in image reconstruction using Restricted Boltzmann Machines. This advancement enables JieJie Technology to perform image processing via unsupervised learning without the need for data annotation. Furthermore, JieJie Technology leads the industry in the practical application of Generative Adversarial Networks (GANs), whereas most other companies in the sector still rely on supervised learning that requires image annotation.

Jiejie Technology's label-free machine learning technology has significantly shortened the R&D cycle, enabling coverage of a major disease type within just two months and thereby accumulating a substantial competitive advantage in the industry.

Data Acquisition: Jiejie Technology has established multi-center data source partnerships with the Chinese PLA General Hospital, Beijing Hospital, Beijing Friendship Hospital, Peking University Cancer Hospital, Aviation General Hospital, Beijing Tongren Hospital, Peking Union Medical College Hospital, Rocket Force General Hospital, and Shanghai East Hospital (Tongji University), as well as with the HQMS of the National Health and Family Planning Commission, the Occupational Disease Identification Center of the State Administration of Work Safety, and the Chinese Society of Clinical Oncology (CSCO). The company has acquired substantial datasets through research project initiatives, bilateral collaborations, and technology provisioning. Currently, its imaging database comprises hundreds of thousands of images, and its case database has accumulated over ten thousand records. For Jiejie Technology, the challenge does not lie in data acquisition; rather, data access constitutes a significant competitive advantage.

Market CapabilityShao Xuejie stated that JieJie Technology holds a natural advantage in the market. On one hand, the founding team possesses extensive medical expertise. On the other hand, leveraging relationships with investors, JieJie Technology has been able to rapidly establish connections with hospitals. Within just a few months, the company has secured cooperation agreements with over 100 hospitals, deploying its solutions on a research basis prior to obtaining CFDA certification. Additionally, negotiations are underway with another 200 hospitals. This pace of implementation is unmatched by other companies.

VCBeat learned that in September 2017, Jiejie Technology secured RMB 6 million in angel-round financing from a well-known pharmaceutical group.

Jiejie Technology is currently seeking its next round of financing.