Chicago, Illinois – February 27, 2025

伊利诺伊州芝加哥 —— 2025年2月27日

; Healthcare desperately needs more clinicians, but can’t scale up fast enough. Traditional medical training demands thousands of hours of supervised, hands-on practice and struggles to prepare today’s workforce for modern challenges – especially the management of chronic diseases. Today,

；医疗保健行业迫切需要更多的临床医生，但无法快速扩大规模。传统的医学培训要求数千小时的监督下的实践操作，并且难以让当今的劳动力为现代挑战做好准备——尤其是慢性病的管理。如今，

SimCare AI

SimCare AI

announces $2 million in seed funding to rethink clinical training from first principles: using AI patients to bypass regulatory constraints and certify clinical skills with far fewer patient interactions.

宣布获得200万美元种子资金，用于从头开始重新思考临床培训：使用AI患者绕过监管限制，并通过更少的患者互动认证临床技能。

The funding round was led by Y Combinator and Drive Capital, with participation from Harper Court Ventures Fund, Singularity Capital, Triple S Ventures, Goodwater Capital, Asymmetry Ventures, Sand Hill North, and Transpose Platform.

本轮融资由Y Combinator和Drive Capital领投，Harper Court Ventures Fund、Singularity Capital、Triple S Ventures、Goodwater Capital、Asymmetry Ventures、Sand Hill North和Transpose Platform参与。

The story began with a problem: when founder Vrishank Saini failed a critical clinical communications exam and couldn’t afford the $9,000 tutor fee, he got together with Tigran Bdoyan and built an AI solution instead. The tool worked so well it attracted 2,500 users and reached $5,000 in monthly recurring revenue within three weeks.

故事始于一个问题：创始人弗里尚克·萨因在一次关键的临床通信考试中失败，且无法承担9000美元的辅导费用，于是他与提格兰·布多扬一起构建了一个AI解决方案。该工具效果非常好，三周内吸引了2500名用户，月经常性收入达到了5000美元。

After an initial rejection from Y Combinator’s S24 batch, Saini and his co-founder Bdoyan dropped out of college with no funding, moved to San Francisco, and – when told they couldn’t reapply to the same batch – created new email accounts and applied again. Y Combinator caught them but, impressed by their determination, gave them $500,000 to build SimCare AI..

在最初被Y Combinator的S24批次拒绝后，萨伊尼和他的联合创始人博伊扬退学且没有资金支持，搬到了旧金山，并且——当被告知不能重新申请同一批次时——他们创建了新的电子邮件账户再次申请。Y Combinator发现了他们的行为，但被他们的决心打动，给了他们50万美元来开发SimCare AI。

“We took a risk to prove our point,” said

“我们冒着风险来证明我们的观点，”

Vrishank Saini, CEO and Co-founder of SimCare AI

SimCare AI首席执行官兼联合创始人Vrishank Saini

. “By using AI patients, we’ve set a clinical benchmark for how training should be measured – efficient, reliable, and cost-effective. Current training methods excel at teaching acute conditions but fall short with chronic diseases that develop over months and years. A medication change today might not show its impact for months, and missed interventions might not reveal their consequences for years.

“通过使用AI患者，我们为如何衡量培训设定了一个临床基准——高效、可靠且经济实惠。目前的培训方法擅长教授急性病症，但在处理数月甚至数年发展的慢性疾病方面则显得不足。今天更改药物可能在数月内都不会显示出其影响，而错过的干预措施可能在数年后才会显现出后果。”

SimCare AI’s simulations compress these timelines dramatically, allowing clinicians to witness disease progression patterns that would traditionally take years to experience.”.

SimCare AI的模拟极大地压缩了这些时间线，使临床医生能够见证传统上需要数年才能经历的疾病进展模式。

The SimCare AI platform can be customized for different specialties and use cases, from residency programs preparing trainees for complex patient scenarios to social work programs practicing family interventions. Telehealth companies, for example, screen job applicants by testing their skills with SimCare AI patients, enabling faster and more cost-effective hiring.

SimCare AI 平台可以针对不同的专业和用例进行定制，从为复杂患者情景培训住院医师的项目，到练习家庭干预的社会工作项目。例如，远程医疗公司通过使用 SimCare AI 患者测试求职者的技能来筛选应聘者，从而实现更快、更经济高效的招聘。

The platform also supports their onboarding, training, upskilling, and remediation without the prolonged timelines and high expenses of traditional training. For healthcare organizations, being able to benchmark and predict performance of their workforce will offer employers an advantage. Currently, SimCare AI has already closed 30 pilots with institutions including the University of Pennsylvania..

该平台还支持他们的入职、培训、技能提升和补救措施，而无需传统培训的长时间和高费用。对于医疗保健组织而言，能够基准化并预测其员工的表现将为雇主提供优势。目前，SimCare AI已经与包括宾夕法尼亚大学在内的机构完成了30个试点项目。

The innovation comes at a crucial moment. As seasoned physicians leave the profession while less experienced clinicians backfill positions, the clinical experience gap is widening. Traditional training methods – role-playing, in-person evaluations, and one-on-one interviews – cost institutions hundreds of thousands of dollars annually in faculty time and administrative overhead, while still failing to provide comprehensive exposure to complex patient cases..

创新恰逢其时。随着经验丰富的医生离开这个行业，而经验较少的临床医生填补空缺，临床经验差距正在扩大。传统的培训方法——角色扮演、面对面评估和一对一访谈——每年耗费机构数十万美元的教职员工时间和行政开支，但仍然无法提供对复杂患者病例的全面接触。

Professor Emeritus of Medicine and Psychiatry, University of North Carolina

北卡罗来纳大学医学和精神病学荣誉教授

Douglas A. Drossman MD, President at DrossmanCare

道格拉斯·A·德罗斯曼医学博士，DrossmanCare总裁

commented: “I have been extremely impressed with our collaboration with SimCare AI. At DrossmanCare, in partnership with the Rome Foundation, we develop educational programs designed to enhance healthcare providers’ communication skills with patients. SimCare AI has seamlessly integrated our vast library of publications and videos on communication into an innovative program that allows providers to engage in advanced, simulated patient interviews with a virtual avatar.

评论道：“我们与SimCare AI的合作让我印象深刻。在DrossmanCare，我们与罗马基金会合作开发了旨在提高医疗保健提供者与患者沟通技巧的教育项目。SimCare AI将我们大量的关于沟通的出版物和视频无缝整合到一个创新项目中，让医疗提供者能够通过虚拟化身参与高级的、模拟的患者访谈。”

This approach enables providers to gain valuable insights into complex psychosocial issues through the use of sophisticated interview techniques. Additionally, the program provides real-time feedback, allowing providers to continuously refine their skills. I’ve never encountered a company with such a refined ability to replicate the nuances of a clinical encounter, offering a truly remarkable training experience.”.

这种方法使医生能够通过复杂的访谈技术获得关于复杂心理社会问题的宝贵见解。此外，该计划提供实时反馈，使医生能够不断提高技能。我从未遇到过一家能够如此细致地复制临床遭遇细节的公司，提供了真正卓越的培训体验。"

SimCare AI’s technology offers a radical solution: proving clinical competency with just 20 patient encounters instead of 200. The system’s sophisticated AI maps decision trees for each patient interaction, creating dynamic, realistic conversations that align with accreditation standards. This precision helps institutions track, assess, and verify student competencies according to regulatory requirements – allowing students and professionals to practice and be evaluated anytime, anywhere.

SimCare AI 的技术提供了一个彻底的解决方案：通过仅 20 次患者接触而非 200 次来证明临床能力。该系统的先进人工智能为每次患者互动绘制决策树，创建符合认证标准的动态、逼真的对话。这种精确性帮助机构根据监管要求跟踪、评估和验证学生的能力——使学生和专业人士能够随时随地进行练习和评估。

This standardized approach not only reduces faculty burden and costs but accelerates the pace at which new clinicians can enter the workforce..

这种标准化方法不仅减轻了教师的负担和成本，还加快了新临床医生进入职场的速度。

Molly Bonakdarpour, Partner at Drive Capital

莫莉·博纳卡达普尔，Drive Capital合伙人

, commented: “SimCare AI is addressing a clear need in healthcare training. In just four months, they’ve demonstrated strong early impact, delivering measurable ROI for customers. We’re impressed with their vision and execution and look forward to supporting their continued growth in AI-driven healthcare solutions.”.

“, 评论道：“SimCare AI 正在满足医疗培训中的一个明确需求。仅四个月的时间，他们就展示了强大的早期影响力，为客户带来了可衡量的投资回报率。他们的愿景和执行力给我们留下了深刻印象，我们期待支持他们在人工智能驱动的医疗解决方案领域的持续成长。””

The platform’s impact extends across the healthcare education landscape. While medical schools use SimCare AI to teach patient interactions and clinical reasoning, therapy programs employ it for counseling practice, and telehealth companies leverage it for hiring and upskilling. SimCare AI’s precision helps institutions track, assess, and verify student competencies according to regulatory requirements – a crucial feature for medical schools, nursing programs, and continuing medical education..

该平台的影响贯穿整个医疗教育领域。虽然医学院使用SimCare AI来教授患者互动和临床推理，但治疗项目用它来进行咨询实践，远程医疗公司则利用它进行招聘和技能提升。SimCare AI的精确性帮助机构根据监管要求跟踪、评估和验证学生的能力——这是对医学院、护理项目和继续医学教育来说都至关重要的功能。

Vrishank Saini

毛拉亚·萨因

added: “Looking ahead, SimCare AI plans to integrate more detailed clinical data – from transcripts to diagnostic workups – into its evaluation system. The company’s goal is to standardize clinical training and evaluation across healthcare, enabling competency to be measured quickly and reliably. For risk-bearing organizations, this provides a clear, consistent method to train clinicians in the specific skills that drive quality metrics.”.

补充道：“展望未来，SimCare AI计划将其评估系统整合更多详细的临床数据——从记录到诊断评估。该公司的目标是将临床培训和评估标准化，使得医疗领域的胜任能力能够快速且可靠地被衡量。对于承担风险的机构而言，这提供了一种明确且一致的方法，用于培训临床医生掌握推动质量指标的具体技能。”