The AI Podcast – Episode Summary

Episode: Lotus Health AI Doctor Raising $35M
Host: Jaden Schaefer
Date: February 4, 2026

Episode Overview

In this episode, Jaden Schaefer explores the breakthrough made by Lotus Health, a startup that has raised $35 million to build an AI-powered “doctor” offering free, 24/7 primary care services. The episode dives into what sets Lotus Health apart in the rapidly evolving AI healthcare landscape, analyzes the company’s operational and regulatory strategies, uncovers potential risks and incentives for investors, and reflects on the broader implications for AI-driven medicine.

Key Discussion Points & Insights

1. AI as the New First Stop for Health Questions (02:00–04:37)

• Behavioral Shift:

  • More people are using large language models (LLMs) like ChatGPT and Anthropic for initial health questions and self-diagnosis, moving away from traditional sources like WebMD.
  • Jaden shares personal anecdotes about using AI for his children's health needs.
    • “When my kids are sick, I don’t go to WebMD like I used to... WebMD always would tell me that either there's no problem or I was gonna die of cancer... ChatGPT seems to be doing a really great job.” [03:00]

• Benefits of AI Interactions:

  • AI tools help users clarify and articulate their symptoms and concerns, often asking follow-up questions a doctor might, but which patients sometimes forget in a rushed appointment.
  • Real-life examples where LLMs have given accurate, specialist-level advice after people struggled for years.
    • “There’s been a ton of really interesting cases where people... went to ChatGPT, listed out just everything, had a conversation and it finds kind of these specialized diagnoses which ended up being correct.” [04:15]

2. Lotus Health’s Vision & Origins (04:38–06:10)

• Founded by KJ Dhaliwal:

  • Previously sold the South Asian dating app D Mill for $50M in 2019.
  • Inspired by his childhood experience as a translator for his parents at doctor’s appointments—recognizing communication breakdowns in the US healthcare system.

• Founding Philosophy:

  • Sees LLMs not just as chatbots but as an opportunity to “rebuild primary care from the ground up.”
    • “He saw them less as this chatbot and more as an opportunity to kind of rebuild primary care from the ground up. This was, you know, kind of his vision.” [05:35]

• Platform Details:

  • Launched in May 2024.
  • Offers free, always-on, multilingual (50+ languages), AI-driven primary care.

3. Fundraising and Business Model (06:11–07:22)

• Recent Milestone:

  • $35M Series A led by CRV and Kleiner Perkins. Now at $41M raised total.

• Market Context:

  • Reflects broader adoption of AI for health (e.g., OpenAI Health, Anthropic Health).
  • Lotus Health inches beyond “conversational advice,” aiming for clinical outcomes.

• Unique Features:

  • Free to all users (differentiator).
  • Future monetization may include subscriptions or sponsored programs but is deprioritized for now to focus on refining the product and building trust.
    • “Their immediate goal is to basically refine the product, build trust and just get as many patients using it as possible.” [13:00]

4. How It Works: From Chat to Prescription (07:23–09:35)

• Clinical Functions of Lotus’ AI:

  • Provides diagnoses, writes prescriptions, orders labs, and refers to specialists (except for urgent, emergent, or physical-exam-required conditions).
    • “The AI model will be able to prescribe you, it's going to be able to do lab orders and refer you to specialists. Now, I know there's probably a ton of… compliance issues... but... this is basically everything you need a primary care doctor for.” [08:05]

• Operational and Compliance Structure:

  • Licensed to operate in all 50 states; holds malpractice insurance; HIPAA-compliant infrastructure.
  • Maintains full access to patient medical records.
  • Human-in-the-loop: Board-certified physicians from top universities review all AI-generated diagnoses, prescriptions, and lab orders before issuing to patients.
    • “They do always have a human in the loop... reviewing all of the final diagnosis, all of the prescriptions and all of the lab requests before anything is actually issued to a patient.” [09:00]

• Technology:

  • Built its own clinical reasoning model—combines up-to-date medical research with patient history for personalized care.

5. Regulatory & Practical Challenges (09:36–11:35)

• Scope and Limitations:

  • Not for urgent or hands-on care.
  • Redirects emergencies and cases needing physical exams to appropriate providers.
  • Aims to replace routine primary care only.

• Compliance Complexity:

  • US healthcare governance is a “patchwork” of state-level rules. Licensing for each state is arduous and a barrier for both human and digital healthcare.
    • “For in my own family I have an uncle that’s a doctor… getting the licenses in every state and board certification approval... there’s a lot that goes into just a doctor moving between states, sometimes months or years…” [10:25]

• Oversight:

  • Every automated clinical decision passes final human approval, minimizing risk but potentially capping scalability.

6. Investor Perspective & Market Potential (11:36–13:20)

• Investor Support:

  • CRV's general partner, Sara Gur, joins Lotus’ board; previously was early at DoorDash, Mercury, and Ring.
  • Belief that the pandemic-era telemedicine normalization opened doors for this care model.
    • “There are many challenges, but it's not SpaceX sending astronauts to the moon.” [11:55, attributed to Sara Gur]

• Efficiency and Workforce Impact:

  • Lotus claims it can handle 10x as many patients as a brick-and-mortar practice (even with manual review of each case); this number is defined by the review bottleneck, not the AI's speed.
    • “With the same amount of doctors on their app versus an actual office, they can 10x that, so they could hire a lot of doctors and basically get 10 times the output.” [12:30]

• Competitive Landscape:

  • Lotus isn't alone; other startups (e.g., Doctrine) are pursuing similar ideas. Lotus' key differentiator: free access.

7. Closing Reflection: The Future of AI-Driven Healthcare (13:21–14:40)

• Changing Patient Experience:

  • AI makes self-diagnosis and intake more accurate and formal.
  • Converts informal LLM “consultations” into real, actionable care with a streamlined path to prescriptions and labs.

• Vision for Care:

  • Combines AI efficiency with human oversight to maximize safety and accessibility.
    • “Mix it with a human and you have a human kind of overseeing everything, you can turn what people are already doing informally into something that looks and feels like real care.” [14:10]

• Impact on Healthcare System:

  • Potential to relieve pressure and burnout among doctors.
  • Promises faster, more affordable, and widespread access to primary care.

• Host’s Closing Sentiment:

  • Jaden expresses excitement for Lotus Health’s journey and promises future updates.

Memorable Quotes

• On LLMs in Medicine:

  “It helps you articulate and say what your concerns are going to be... There’s been a ton of really interesting cases where people... couldn’t diagnose or figure out what their issue were. And they went to ChatGPT...and it finds kind of these specialized diagnoses which ended up being correct.”
  — Jaden Schaefer [04:15]

• On Lotus Mission:

  “He saw them less as this chatbot and more as an opportunity to kind of rebuild primary care from the ground up.”
  — Jaden Schaefer recounting KJ Dhaliwal’s motivation [05:35]

• On the Human-in-the-Loop Safeguard:

  “AI is giving the advice, but the real doctors are actually signing off on it.”
  — Lotus Health CEO Dhaliwal (paraphrased by Jaden Schaefer) [09:25]

• Investor Confidence:

  “There are many challenges, but it's not SpaceX sending astronauts to the moon.”
  — Sara Gur, CRV general partner [11:55]

• Future Outlook:

  “Making this more formal and saying, look, you had the whole conversation, now just like get it reviewed by a doctor and you go get your prescription, I think is a very, very smart direction.”
  — Jaden Schaefer [14:30]

Timestamps for Key Segments

• 02:00 – 04:30: Rise of AI as primary health consult; user behaviors shifting
• 04:38 – 06:10: Lotus Health origin story and founding vision
• 06:11 – 07:22: Funding, scale, and positioning in a crowded field
• 07:23 – 09:35: AI workflow—diagnosis, prescriptions, human review process
• 09:36 – 11:35: Regulatory, licensing, and operational challenges
• 11:36 – 13:20: Investor rationale; efficiency claims; rivals; pricing strategy
• 13:21 – 14:40: System-level impact and podcast wrap-up

Tone & Style

The episode is accessible, anecdote-rich, and conversational, blending personal stories with analysis. Jaden expresses both skepticism and genuine excitement, weighing practical hurdles against the promise of transformative change in healthcare.