According to United Nations data, the global population aged 65 and above will increase from 727 million in 2020 to 1 billion in 2030, accounting for 12% of the total population from 9.3%.

This demographic change has greatly increased medical demand and aggravated the shortage of human resources in the medical industry. It is estimated that by 2025, the shortage of registered nurses in the United States may reach 450,000, and the vacancies of general practitioners are expected to reach 1 million.

In this context, how can Hippocratic AI focusing on medical health solve this dilemma?

01.1 minute project overview

1. Project name: Hippocratic AI

2. Date of establishment: 2023

3. Product introduction:

Hippocratic Polaris, the core product of AI, is a large language model in the medical field with safety as the core. It provides patients with guidance on non-diagnostic topics such as dietary recommendations or drug dosage through audio communication methods such as phone calls.

4. Founding Team:

Munjal Shah: CEO, Co-Founder

Vishal Parikh: Chief Product Officer, Co-Founder

Meenesh Bhimani: Chief Medical Officer , co-founder

5. Financing situation:

In May 2023, Hippocratic AI completed a $50 million seed round of financing led by Andreessen Horowitz and General Catalyst;

In July 2023, Hippocratic AI partners with three medical systemsAnd raised US$15 million in funds;

In March 2024, Hippocratic AI completed a US$53 million Series A financing, co-led by Premji Invest and General Catalyst;< /p>

In September 2024, Hippocratic AI completed US$17 million in financing led by NVentures;

In January 2025, Hippocratic AI completed a $141 million Series B financing, led by the well-known venture capital firm Kleiner Perkins, with the company's valuation reaching $1.64 billion.

02. Use AI agents to reshape the future of medicine

As the global population ages, , medical demand continues to increase, and the shortage of medical staff becomes increasingly serious. However, as artificial intelligence begins to gain prominence, some are discovering that there may be areas of intersection between the two that can be bridged. Munjal Shah, CEO of Hippocratic AI, is one of them.

Around 2010, Munjal Shah, a computer science student at the University of California, San Diego, founded Andale and Like.com and began his exploration of neural networks and medical fields. The latter was later acquired by Google.

In 2014, Shah founded Health IQ, but eventually filed for bankruptcy. However, this did not discourage Shah. He embarked on the road of entrepreneurship again in 2023 and co-founded Hippocratic AI with a group of professionals from Johns Hopkins University, Stanford University, Google and NVIDIA to start a new journey.

Hippocratic is named after the "Hippocratic Oath" to demonstrate its commitment to medical ethics. Deep respect, especially for practicing the ancient and profound medical creed of "Do No Harm."

Since its inception, Hippocratic has rapidly grown into a unicorn in the field of medical AI, focusing on the development and deployment of AI agents. These agents can perform a variety of medical tasks, including preoperative preparation, chronic disease management, post-discharge follow-up, nutritional consultation, etc.

In addition to the original intention of reducing the administrative burden on medical staff, these AI agents can also ensure that patients receive timely care and support during emergencies such as natural disasters.

Hippocratic AI’s financing process is also worthy of attention.

After completing a $53 million Series A round of financing in March 2024, Hippocratic's valuation reached $500 million. Subsequently, the company raised another $17 million from NVIDIA's venture capital arm.

Just in January this year, Hippocratic AI raised another US$141 million, with its valuation soaring to US$1.64 billion, showing huge potential.

03. Vertical large model products

Hippocratic AI’s core product is Polaris, a A large language model (LLM) in the medical field with security at its core, capable of communicating with patients over the phone and handling various non-diagnostic tasks.

Polaris uses a system composed of multiple large language models with a total parameter of more than 1 trillion , each model works together as an agent.

The initial 1.0 version operates through a highly optimized dialogue management system, focusing on handling various dynamic factors through voice communication, including voice quality, pitch , speech rate, response length, interruption handling and communication delay.

Since the telephone is still the primary method of communication for medical services, the system is designed to naturally complete tasks such as appointment confirmation, preliminary examination or communication of laboratory results.

Polaris 2.0 will be released in 2024 and has significant performance improvements compared to 1.0:

Parameter and language support: The parameter size has increased from 1 trillion to 3 trillion, supporting 14 languages, including Spanish, French and Mandarin, while Polaris 1.0 only supports English.

Memory and contextual optimization: Personalized memory feature that remembers patients’ health history, preferences and goals to provide more personalized support.

Performance and accuracy: According to the 2024 Hippocratic AI study, the medical advice provided by Polaris 2.0 is more than 99% accurate, much higher than the U.S. registered nurse average of 81%.

Hippocratic AI’s AI agents are as safe as human clinicians and have completed hundreds of thousands of calls with patients

These AI agents support tailoring. Customized, clinicians can operate according to specific needs and do not require software programming knowledge. The process of creating an agent supports visual drag and drop methods and can usually be completed in less than an hour.

At the same time, if other customers of the platform use the AI ​​agent created by the doctor, the creator can also get a share, usually ranging from 5% to 70%, depending on the usage.

In addition, Hippocratic AI's products attach great importance to security testing and certification, using a three-step security testing method to ensure the safety and reliability of the AI ​​agent:

Phase 1: Tested by doctors and nurses to ensure the Agent completes all key checklist items.

Phase 2: Tested by more than 1,000 American registered nurses and more than 100 American registered doctors conducted conversation tests with AI as patients.

Phase 3: Involves more than 6,500 U.S. registered nurses, 500 registered physicians and the company's health system partners for a broader assessment and safety assessment.

In terms of application scenarios, Hippocratic’s AI agents have been expanded to multiple fields. For example, the AI ​​agent designed by maternal and infant mental health expert Kristina Dulaney can be used for postpartum depression screening; senior nurse Shawna AI agents designed by Butler help communities prepare for and respond to extreme heat waves and more in 2024. November, Hippocratic AI announced that its first patent was officially approved, which covers important innovations in the company’s Polaris secure large language model (LLM) system tailored for the medical field.

Last year, Hippocratic AI was named one of the most innovative generative AI startups of 2024 by CB Insights, and also ranked among the 2024 listed by The Medical Futurist. The annual list of the top 100 digital health and AI companies has been recognized by Bain & Company.

In terms of strategic cooperation, Hippocratic AI has reached cooperation with 23 medical systems, payers and pharmaceutical customers in 2024, and successfully provided services for patients in just 23 weeks. Among them, 16 customers have customized and launched AI agents.

Surprisingly, despite its many achievements, Hippocratic AI has been around for less than two years.

04. "AI Medical" has broad development prospects

Currently, the AI ​​medical industry is in a In the stage of rapid development, technology is constantly improving and application scenarios are constantly expanding. Some development trends may be foreseeable.

First of all, the integration of AI with technologies such as the Internet of Things, big data, and blockchain will be closer. For example, patient health data collected through IoT devices can be directly input into the AI ​​model for analysis and prediction, providing doctors with a more comprehensive diagnostic basis.

At the same time, blockchain technology can ensure the security and privacy of medical data and enhance patients' trust in AI medical care.

Secondly, with the help of AI’s powerful data analysis capabilities, the medical industry will be able to implement more personalized treatment plans.

Through comprehensive analysis of multi-dimensional data such as patients’ genetic information, medical history, and living habits, AI can tailor the most appropriate treatment plan for each patient. , improve treatment effects and reduce unnecessary waste of medical resources.

But at the same time, with the widespread application of medical AI, some related regulatory and ethical issues will become increasingly prominent. For example, how to ensure the safety and effectiveness of AI medical products,Protect patient privacy and rights, etc.

Looking at the entire industry, in addition to Hippocratic AI, there are also some companies in the "AI+ Medical achievements have been made.

For example, as a medical AI project under Google, DeepMind Health has achieved remarkable results in medical image analysis, disease prediction, etc. Its advantage lies in its strong technical strength and rich data resources.

In contrast, Hippocratic AI focuses more on non-diagnostic patient care tasks, interacting directly with patients through AI agent technology and providing auxiliary support to medical staff. .

IBM Watson Health is known for its powerful cognitive computing capabilities and has been widely used in drug research and development, medical data analysis and other fields.

The uniqueness of Hippocratic AI lies in its safety-centered design concept and its deep customization for medical scenarios, making it ideal for patient care and Be more competitive in medical process optimization.

Nabla focuses on optimizing the communication process between doctors and patients through AI technology, and its products mainly focus on clinical documentation and medical information management.

In comparison, Hippocratic AI’s business scope is broader, covering not only documentation, but also preoperative preparation, chronic disease management, remote patient monitoring, etc. This link provides medical institutions with one-stop AI solutions.

There are many other cases too numerous to mention. But what is certain is that the coordinated competition and common development of multiple companies will continuously provide innovation power for the AI ​​medical field and promote longer-term progress, while also providing more solid support for the transformation of the global medical system.