According to United Nations data, the global population aged 65 and over will increase from 727 million in 2020 to 1 billion in 2030, and the proportion of the total population will increase from 9.3% to 12%.
This demographic change has greatly increased the demand for medical care 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 number of vacancies for general practitioners in the country is expected to reach 1 million.
Against this background, how can Hippocratic AI, which focuses on medical health, solve this dilemma?
01.1 minute project overview
1. Project name: Hippocratic AI
2. Establishment time: 2023
3. Product introduction:
Hippocratic AI's core product Polaris is a large language model in the medical field with security as its core. It provides patients with guidance on non-diagnostic topics such as dietary recommendations or drug dosages through audio communication methods such as telephone.
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 collaborated with three medical systems and raised US$15 million in funds;
In March 2024, Hippocratic AI completed a US$53 million Series A financing, led by Premji Invest and General Catalyst;
In September 2024, Hippocratic AI completed a US$17 million financing led by NVentures;
In January 2025, Hippocratic AI completed a US$141 million Series B financing, led by the famous venture capital firm Kleiner Perkins, and the company's valuation reached US$1.64 billion.
02.Reshaping the future of medicine with AI agents
As the global population ages, medical needs continue to increase, and the shortage of medical staff is becoming increasingly serious. However, as artificial intelligence gradually emerges, some people find that there may be an 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. In 2023, he embarked on the entrepreneurial road again 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 show its deep respect for medical ethics, especially the practice of "do no harm", an ancient and profound medical creed.
Since its founding, 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 counseling, 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 in emergency situations such as natural disasters.
Hippocratic AI's financing history is also worth paying attention to.
After completing a $53 million Series A financing in March 2024, Hippocratic was valued at $500 million. Subsequently, the company raised another $17 million from NVIDIA's venture capital arm.
Just in January of this year, Hippocratic AI raised another $141 million, and its valuation soared to $1.64 billion, with huge potential.
03.Vertical large model products
Hippocratic AI's core product is Polaris, a safety-focused large language model (LLM) in the medical field that can communicate with patients over the phone and handle various non-diagnostic tasks.
Polaris utilizes a system of multiple large language models with a total of more than 1 trillion parameters, each model working together as an agent.
Its initial 1.0 version operates through a highly optimized dialogue management system that focuses on handling various dynamic factors through voice communication, including voice quality, pitch, speech rate, response length, interruption handling, and communication delay.
Since the phone is still the primary mode of communication for healthcare services, the system is designed to naturally complete tasks such as appointment confirmation, preliminary examination or laboratory result communication.
Polaris 2.0 will be released in 2024 and has significant performance improvements over 1.0:
Parameter and language support: The parameter scale has increased from 1 trillion to 3 trillion, and 14 languages are supported, including Spanish, French and Mandarin, while Polaris 1.0 only supports English.
Memory and context optimization: It has a personalized memory function that remembers the patient's health history, preferences and goals to provide more personalized support.
Performance and Accuracy: According to a 2024 Hippocratic AI study, Polaris 2.0 provides medical advice with an accuracy rate of over 99%, far higher than the 81% average for registered nurses in the United States.
Hippocratic AI’s AI agents are as safe as human clinicians and have completed hundreds of thousands of calls with patients.
These AI agents can be customized, and clinicians can operate them according to specific needs without having software programming knowledge. The process of creating an agent supports visual drag-and-drop, and it usually takes less than an hour.
At the same time, if other customers on the platform use the AI agent created by the doctor, the creator can also get a share, which usually ranges from 5% to 70%, depending on usage.
In addition, Hippocratic AI's products pay great attention to safety testing and certification, and adopt a three-step safety testing method to ensure the safety and reliability of AI agents:
Phase I: Testing by doctors and nurses to ensure that the Agent completes all key checklist items.
Phase II: More than 1,000 US registered nurses and more than 100 US registered doctors as patients conduct dialogue tests with AI.
Phase III: Involving more than 6,500 US registered nurses, 500 registered doctors and the company's medical system partners for more extensive evaluation and safety assessment.
In terms of application scenarios, Hippocratic's AI agents have expanded to multiple fields. For example, the AI agent designed by maternal and child mental health expert Kristina Dulaney can be used for postpartum depression screening; the AI agent designed by senior nurse Shawna Butler helps communities prepare for and respond to extreme heat waves, etc.
In November 2024, Hippocratic AI announced that its first patent was officially approved, which covers the company's important innovations in the Polaris secure large language model (LLM) system tailored for the medical field.
Last year, Hippocratic AI was selected by CB Insights as one of the most innovative generative AI startups in 2024, and was also recognized by Bain & Company on The Medical Futurist’s list of 100 digital health and AI companies in 2024.
In terms of strategic partnerships, Hippocratic AI reached cooperation with 23 medical systems, payers and pharmaceutical customers in 2024, and successfully customized and launched AI agents for 16 of them in just 23 weeks.
Surprisingly, despite all the achievements, Hippocratic AI was founded less than two years ago.
04.“AI medical care” has broad development prospects
At present, the AI medical industry is in a stage of rapid development, with continuous technological progress and application scenarios expanding. Some development trends may be foreseeable.
First, 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 AI models for analysis and prediction, providing doctors with a more comprehensive basis for diagnosis.
At the same time, blockchain technology can ensure the security and privacy of medical data and enhance patients' trust in AI medical care.
Second, with the powerful data analysis capabilities of AI, the medical industry will be able to achieve 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 the privacy and rights of patients, etc.
Overlooking the entire industry, in addition to Hippocratic AI, there are also some companies that have made achievements in "AI+medical care".
For example, as a medical AI project under Google, DeepMind Health has achieved remarkable results in medical image analysis, disease prediction, etc., and its advantages lie in its strong technical strength and rich data resources.
In comparison, Hippocratic AI focuses more on non-diagnostic patient care tasks, interacting directly with patients through AI agent technology to provide auxiliary support to medical staff.
IBM Watson Health is known for its powerful cognitive computing capabilities and has a wide range of applications in drug development, medical data analysis and other fields.
The uniqueness of Hippocratic AI lies in its design concept with security as the core, and its deep customization for medical scenarios, making it more competitive in patient care and medical process optimization.
Nabla focuses on optimizing the communication process between doctors and patients through AI technology, and its products are mainly concentrated in clinical document recording and medical information management.
In comparison, Hippocratic AI has a wider business scope, which not only covers document records, but also includes preoperative preparation, chronic disease management, remote patient monitoring and other links, providing medical institutions with a one-stop AI solution.
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 innovative power for the AI medical field and promote more long-term progress, while providing more solid support for the transformation of the global medical system.
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