Why Jinxin.
Jinxin Fertility brings clinical experience and an international care network. Jinxin Technology works with clinicians to turn needs in care into AI tools that can be evaluated in practice.
Clinical teams and AI engineers, working together to support decisions, remember what patients share, and make medical records easier to manage.
Explore our workBy egg-retrieval cycles · Frost & Sullivan, 2026
Jinxin Fertility brings clinical experience and an international care network. Jinxin Technology works with clinicians to turn needs in care into AI tools that can be evaluated in practice.
From conversations across dialects to continuity of care, our work is rooted in China’s clinics. We aim to share this experience worldwide, developing medical AI together with local clinical teams.
Jinxin’s medical heritage began with a maternal and child health station in Chengdu. Today, Jinxin Fertility connects an international care network, while Jinxin Technology explores applied AI.

Chengdu’s Second District Maternal and Child Health Station is established.
Jinxin Fertility expands through HRC Fertility on the U.S. West Coast.
Jinxin Fertility lists on the Hong Kong Stock Exchange. Stock code: 01951.
IVF Co-pilot begins its clinical pilot at the Bisheng campus in Chengdu.³
Four projects at Jinxin Technology, shaped around clinical decisions, continuity of care, patient records and the information people find before a visit.
Behind every decision, someone is hoping.
An IVF treatment plan belongs to someone who has already invested time, money and hope.
At each decision point, clinicians bring together the patient’s history, current findings and their own experience.
IVF Co-pilot brings relevant clinical knowledge, experience from previous treatment cycles, and AI-assisted analysis into that workflow — helping doctors compare and review the information before them.
A clearer basis for decisions. With the clinician in charge.
Clinical pilot · Chengdu
The pilot is at Sichuan Jinxin Xinan Women & Children Hospital, Bisheng campus. The initial focus is stimulation planning and starting-medication assessment, bringing clinical knowledge, algorithms and local language models into the electronic medical record workflow.
Discuss clinical AI collaborationSome things should only have to be said once.
“Cost is something I need to consider.”
A patient should not have to find the courage to say this at every appointment.
Clinical Notes is designed to turn conversations into draft medical records, easing clinicians’ documentation workload. The aim is also to carry patients’ concerns into a nurse-led care workflow, with a named nurse responsible for follow-up.
Their concerns are remembered. Their next steps have someone responsible. And when they return, the conversation can continue from where it left off.
To be heard. To be remembered. To know who to turn to.
Local validation · Nurse-led care vision
Local transcription and structured summaries are being validated to support draft medical records for clinician review. The intended care workflow connects patient concerns and follow-up items to a named nurse, with context carried into later consultations.
Discuss continuity of careOne less thing to carry.
You can even take the records organized at Jinxin to another hospital.
IVF can be a long journey, spanning multiple treatment cycles.
With every cycle, the folder grows: test results, medication records, treatment reports. Every page carefully kept.
Before the next appointment, another evening spent piecing the story together.
Designed specifically for IVF, Digital Passport uses AI to organize records across cycles into one clear treatment history.
A little more room to focus on care.
Designed specifically for IVF care, the passport helps patients organize test results, medication records and treatment reports across cycles and appointments. Free and open to patients, it brings the records they provide into a clearer history they can take to Jinxin or another hospital.
Discuss patient-centred toolsTrust begins before the first visit.
Before they meet a clinician, a patient may already have asked AI where to turn.
What it says about a hospital — its people, its services, how to reach it — deserves careful attention.
GEO Observatory helps teams examine answers across AI platforms, trace the sources behind them, and identify missing or inconsistent information.
Help people find care, with information they can check.
In operation · JX-GEO
The workflow captures model responses and source references, supports comparison across repeated questions, and connects information gaps to review and follow-up. The aim is to improve the official information people can find and verify, while continuing to observe what AI platforms actually say.
Discuss evaluation and knowledge qualityLet’s explore medical AI together — through research, thoughtful evaluation and practical collaboration.