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Lotus Health’s AI Doctor Offers Free Visits With $35M Funding

▼ Summary

– People are increasingly using LLMs like ChatGPT for health advice, and KJ Dhaliwal launched Lotus Health AI in May 2024 to provide free, 24/7 AI-driven primary care.
– Lotus facilitates actual medical care, including diagnosis and prescriptions, by using an AI model trained to ask doctor-like questions, but all outputs are reviewed by board-certified human doctors.
– The company is licensed in all 50 states and has raised $41 million, with investors believing telemedicine frameworks and AI advances help it navigate regulatory hurdles.
– Lotus claims it can handle ten times more patients than a traditional practice, addressing a doctor shortage, and currently differentiates itself by offering all services for free.
– The platform recognizes the limits of virtual care, directing patients to in-person care for urgent issues or physical exams, while its future business model may include subscriptions or sponsored content.

A significant shift is occurring as individuals increasingly turn to large language models for preliminary health guidance, finding these tools can offer surprisingly accurate medical information. Lotus Health AI is capitalizing on this trend by transforming those basic chats into a comprehensive, licensed medical service. Founded by KJ Dhaliwal and launched in May 2024, the platform operates as a free, around-the-clock primary care provider accessible in 50 languages. The startup recently secured a substantial $35 million Series A investment from firms like CRV and Kleiner Perkins, boosting its total funding to $41 million and signaling strong investor confidence in its AI-driven healthcare model.

The core concept moves beyond simple chatbot consultations. Lotus functions as a full-scale virtual medical practice, possessing the necessary licenses to operate across all 50 states, complete with malpractice insurance and HIPAA-compliant data systems. Its AI is engineered to replicate a physician’s diagnostic process, asking detailed questions based on a patient’s history and symptoms to formulate potential diagnoses, prescribe medications, and arrange specialist referrals.

Acknowledging the well-documented issue of AI “hallucinations,” the company has implemented a crucial safeguard. Every final diagnosis, lab order, and prescription is reviewed and approved by board-certified human doctors affiliated with prestigious institutions such as Stanford, Harvard, and UCSF. This hybrid model ensures AI efficiency is balanced with expert human oversight. The underlying technology synthesizes the latest clinical research with individual patient data to generate evidence-based treatment plans.

Dhaliwal emphasizes that the platform understands the boundaries of virtual care. For emergencies or situations requiring a physical exam, Lotus immediately directs patients to local urgent care facilities, emergency rooms, or in-person physicians. The ambition to delegate major aspects of healthcare to algorithms faces considerable regulatory complexity, including cross-state licensing rules for doctors. However, investors like CRV’s Saar Gur believe the foundational telemedicine frameworks built during the COVID-19 pandemic, coupled with recent AI advances, provide a viable path forward.

Gur, an early backer of companies like DoorDash and Ring, admits the venture is “a big swing” but is drawn to its potential to radically redesign primary care delivery. With a shortage of traditional doctors, Lotus aims to dramatically increase accessibility, claiming it can manage up to ten times the patient volume of a conventional practice. While competitors like Lightspeed-backed Doctronic exist, Lotus currently sets itself apart by offering its entire service without charge. Future monetization could involve subscriptions or sponsored content, but the present strategy is squarely focused on refining the technology and expanding its user base.

(Source: TechCrunch)

Topics

ai healthcare 95% telemedicine 85% primary care 80% startup funding 75% Regulatory Hurdles 70% AI Hallucinations 65% healthcare inefficiencies 60% evidence-based medicine 55% venture capital 50% business models 45%