Show Notes
You see the person responsible for your health for somewhere between 10 and 20 minutes, once or twice a year. Netflix gets three hours a day. One of those two relationships has enough data to know you. It is not the one keeping you alive.
Funding stage: Series A Plus. Lirio closed a Series A of just under $10 million led by Bill Hambrecht through Hambrecht Ducera Growth Ventures, then a $27 million Series B in September 2023, with total capital raised reported between roughly $59 million and $75 million, backed by Hambrecht Ducera Growth Ventures, Fine Day Ventures, Nixon Capital, Bon Secours Mercy Health, and Rochester Regional Health.
That asymmetry is the entire business case for Lirio, and Marten den Haring has been building against it since 2019. He is not a healthcare lifer. He is an economist by training, MSc and PhD, who spent 25 years shipping AI products for financial services, law enforcement, and national security: Oracle, OpenText, Chief Product Officer at Digital Reasoning in Nashville, then SVP Platform at Element AI in Montreal, the lab co-founded by Turing Award winner Yoshua Bengio. Six months into Canada, Nashville called him home, and Lirio was hiring.
He joined as Chief Product Officer in May 2019 to turn a Series A business plan into an actual product. The MVP went live around January 15, 2020. Do that math: six to eight weeks in the wild, and then the world closed. Lirio's product exists to drive people toward care. Care was shut, then reopened on 50 different state timetables into backlogs and staffing shortages, and nobody wanted more patient volume. Marten took the CEO chair in May 2021, in the middle of it, and describes 2021 through 2023 as a stretch where the team was openly asking whether product market fit simply was not there.
What flipped it was not healthcare. It was everything else. Consumers spent three years learning that they could get anything from their couch, and then brought that expectation to their care. Today Lirio delivers more than 400 million nudges a year and reports outcomes that are hard to argue with: nudges 4x more effective than standard health messaging, a 60% reactivation rate on patients lost for three or more years, 50% HbA1c improvement in under six months, and $4.4 million in direct margin added through targeted interventions.
The word “nudge” is doing a lot of work there, and Marten is careful about it. Ryan suggests it sounds like his wife on his fourth glass of wine. Marten's answer is the best line in the episode: if you want an automated version of your spouse, Lirio cannot help you. What Lirio actually does is treat every variable of a message as a decision, not the content alone: the channel, the hour, the frequency, the framing, and whether the right recipient is even the patient at all. Sometimes the highest leverage nudge goes to the daughter who manages her father's medications. And critically, Lirio does not ask anyone to download anything. Marten calls the platform headless: a brain that sits behind the CRM, the data warehouse, the marketing automation, and the engagement tools a health system already bought, and makes that existing stack work better.
The conversation lands, five days after launch, on ChatGPT Health. Marten's read is more generous than you would expect from a competitor. He thinks general purpose models genuinely help people find and apply knowledge, but he draws a hard line at memory and context, models will struggle to hold every prior interaction and every non-clinical detail that determines how you should communicate with a specific human. Then he offers the analogy that should worry everyone: in the mid 2000s, people had real privacy concerns about a rectangular search box called Google, and used it anyway, all day long, because it was convenient. We have a precedent. We know how this trade resolves.
On his own stack, Marten is direct about the tension every regulated founder is living. Lirio runs a comprehensive risk management framework, HITRUST CSF certification, SOC 2 Type II, and NIST, and it experiments with Cursor, OpenClaw, and frontier models inside that framework, because if you do not, the economics of building software stop working for you. His point is that guardrails are cultural before they are procedural: it is easy to make mistakes when nobody is looking, and in healthcare those mistakes have consequences.
Asked what he believes about the future that most people think is crazy, Marten notes that his worldview is less crazy than Elon Musk's, who had told The Economist five days earlier that humans likely lose control of AI within ten years. Marten's contrarian take: humans will still be in control in ten years, not by default, but because we will have seen what happens if we do not take charge. He does not want a world where a handful of people turn the rest of us into docile Labradors living at the pleasure of intelligent systems. He wants autonomy, relatedness, and human agency intact, and it is roughly where the episode turns into two guys negotiating for robot knees so Ryan can finally dunk a basketball.
Named Frameworks
The 8,760 Hour Gap
The strategic white space is not the appointment. It's everything around it.
- →A year contains 8,760 hours. Clinical contact accounts for well under one of them.
- →Play one: make the moments that exist count more. Play two: occupy the space between, where no communication was happening at all.
- →Play two is uncontested territory. Nobody was talking to the patient there, so there's no incumbent to displace.
- →Founder read: audit your own product for the interval nobody owns. That interval is usually where retention lives.
The Netflix Asymmetry
Data density determines personalization quality, and healthcare has the worst ratio in the consumer economy.
- →Netflix gets three hours a day of behavioral signal per subscriber. Healthcare gets 12 to 18 minutes, once or twice a year.
- →Netflix therefore knows what to recommend next. Your doctor doesn't know whether you took your pills yesterday.
- →The fix isn't more clinical time, which doesn't exist. The fix is generating signal in the gap.
- →Founder read: if your personalization is weak, you probably have a signal frequency problem, not a model problem.
The Four Dials Of A Nudge
A nudge is not a message. It's four independent decisions, and any one of them can kill the outcome.
- →Content and framing: a busy person needs it made easy, a skeptical person needs to understand why it matters.
- →Channel: a scheduling reminder works fine as a text. Visit prep instructions in a text get marked as spam.
- →Timing and frequency: time of day and outreach cadence change efficacy independent of everything else.
- →Founder read: most teams A/B test copy and leave three of the four dials on default.
The Headless Brain
Don't sell your customer more stuff. Make the stuff they already bought work.
- →Every health system has a tech stack: CRM, data warehouse, marketing automation, engagement tools.
- →A solution that requires new tools and new adoption is a solution that requires them to admit the last purchase failed.
- →Lirio integrates and orchestrates instead, acting as the brain behind existing outreach.
- →Founder read: "we make your current stack effective" outsells "we replace your current stack."
The Caregiver Extension
The person who needs to change the behavior is not always the person to nudge.
- →Cognitive decline makes direct medication reminders unreliable.
- →The relative on the care team is a viable, sometimes superior, intervention target.
- →Widening the definition of "user" from patient to care team unlocks populations the direct approach can't serve.
- →Founder read: in any product requiring follow-through, ask who else is already invested in the outcome.
The Convenience Privacy Trade
The historical precedent that predicts how AI health data plays out.
- →Mid 2000s: knowledge work began in a Google search box. People had documented privacy concerns and used it anyway, constantly, because it was convenient.
- →The trade resolved in favor of convenience every single time.
- →What's new: the interface is now conversational and embedded, which makes it easier to forget it's a tool whose inputs and outputs you should be scrutinizing.
- →Founder read: if your defensibility depends on users caring about privacy more than convenience, you don't have defensibility.
Founder Experiment
Run a Four Dial Nudge Test on your own funnel, fourteen days, no new tooling. Pick one binary, countable behavior a customer should take after leaving your product: completed onboarding step three, uploaded the first document, came back on day seven, booked the call. Get your real baseline over 14 days with your current outreach, most founders guess this number and are wrong by half. Then build four cells, changing one dial each, roughly 50 people minimum per cell: Cell A is your current message unchanged (control), Cell B swaps the channel, Cell C shifts the send time by at least four hours, and Cell D reframes the message for a different barrier. Add a fifth cell if you can, sending to someone adjacent who is already invested in the person's outcome, a manager, a teammate, a referrer. Measure completion at 14 days, not opens or clicks. If Cell D wins big, your copy was written for the wrong barrier. If B or C wins, your defaults were costing you conversions for free. If the caregiver cell wins, you've been talking to the wrong person entirely. Take the winning dial, hold it fixed, and re-test the next one. Four rounds in two months and you have a stacked nudge sequence instead of one guessed-at email.
Glossary
Precision Nudging
Lirio's trademarked approach: behavioral interventions personalized to an individual's specific barriers, delivered with optimized content, channel, timing, and frequency.
Large Behavior Model (LBM)
Lirio's proprietary model class. Structurally analogous to an LLM, but instead of predicting the next word from semantic data, it predicts the next behavior in a sequence from health behavior data.
n-of-1
A study design or personalization approach where the sample size is one: outreach optimized for a specific individual rather than a demographic segment that person resembles.
B2B2C
Selling to businesses that serve consumers. Lirio's customers are health systems, payers, retail pharmacies, and life sciences companies; the end beneficiary is the patient or member.
Headless platform
Software that provides logic and orchestration without owning the user interface. It sits behind the tools a customer already runs rather than adding another front end.
Gaps in care
Recommended care a patient hasn't received: overdue screenings, missed well visits, skipped vaccinations. Closing them is directly tied to reimbursement in US value-based arrangements.
A1C / HbA1c
A blood test reflecting average blood glucose over roughly two to three months. The primary control metric in diabetes management.
Agentic AI
AI systems that take multi-step action toward a goal rather than only generating a response. Lirio describes its platform as behavioral science plus agentic AI.
HITRUST
A security and privacy certification framework widely used in healthcare, separate from HIPAA. Lirio holds HITRUST CSF certification.
ChatGPT Health
OpenAI's health experience, launched to US users 18 and older on July 23, 2026, connecting Apple Health and supported medical records.
Q&A: What Founders Ask After This Episode
What does Lirio do?
Lirio is a healthcare personalization platform combining behavioral science and agentic AI to change patient and member health behavior. Its product, Precision Nudging, delivers individually personalized outreach that gets people to complete recommended care: screenings, vaccinations, medication adherence, and chronic condition management. Lirio sells B2B2C to health systems, health plans, retail pharmacies, and life sciences companies, and delivers more than 400 million nudges a year.
Who is Marten den Haring?
Marten den Haring is the CEO of Lirio. He holds an MSc and PhD in Economics and has more than 25 years of product and operations leadership across healthcare, financial services, law enforcement, and national security. Before Lirio he was SVP Platform at Element AI, Chief Product Officer at Digital Reasoning, and held executive roles at Oracle and OpenText. He joined Lirio as Chief Product Officer in May 2019, served as COO, and became CEO in May 2021.
What is a Large Behavior Model?
Lirio's model class for health behavior. Where a large language model ingests semantic data to predict the next word, an LBM ingests health behavior data to predict the next behavior in an individual's sequence, recommending the intervention most likely to move that specific person.
Why do patient reminders fail?
Because most reminders optimize one variable and ignore three. Content, channel, timing, and frequency all independently affect whether a message produces action. The framing also has to match the actual barrier: a person short on time needs the task made easy, while a person who doesn't understand the value needs education.
Is ChatGPT Health a competitor to healthcare AI startups?
Marten den Haring's position is that it's additive rather than directly competitive. General purpose models help people find knowledge and apply it to personal context. The limitations he identifies are persistent memory across prior interactions, the non-clinical context that shapes how you should communicate with a specific person, and integration into clinical workflows.
How do you build AI products in a regulated industry?
Marten's approach: a comprehensive risk management framework, certifications appropriate to every market (HITRUST, SOC 2 Type II, NIST, plus country-specific requirements), and explainability standards for machine learning models. You can't opt out of AI development tooling because the economics of building software no longer work without it, so the answer is to fit those tools inside existing compliance frameworks.
How do you sell software to hospitals that already have too much software?
Don't add to the stack. Health systems have already invested in CRMs, data warehouses, marketing automation, and engagement tools. Lirio positions as a headless platform that integrates with existing systems and orchestrates outreach through them, so the value proposition becomes "your existing investment now performs better."
What happens to a startup when its market shuts down?
Lirio's MVP launched around January 15, 2020 and got six to eight weeks of live operation before COVID closed the care settings its product drove people toward. The stall ran roughly 2021 into 2024, and the unlock came from outside healthcare: three years of consumers learning to expect digital-first everything created demand for exactly the digital engagement Lirio had built.
Will humans still be in control of AI in ten years?
Marten den Haring's contrarian prediction is yes, framed against Elon Musk's public prediction that humans likely lose control within ten years. Marten's view is that we'll see what happens if we fail to take charge and will resist a machine-driven world, preserving human autonomy and agency.
URLs Mentioned in the Episode
- Liriohttps://lirio.com/
- Marten den Haring's team page at Liriohttps://lirio.com/our-team/marten-den-haring/
- Ryan Estes on LinkedInhttps://www.linkedin.com/in/estesryan/
- AI for Foundershttps://aiforfounders.co
- Inbox Alchemyhttps://inboxalchemy.co





