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When Dr. Zaher Merhi started his fertility practice, he did what every other reproductive endocrinologist does: he followed the standard playbook. High-dose stimulation medications. Weeks of preliminary testing before a patient could even begin treatment. Protocols built around consistency, meaning what worked for the average patient was applied to every patient.
He was good at it. But he kept running into the same wall.
Women would come to him in their early 30s, healthy, motivated, with good ovarian reserve, and the system would swallow them whole. Four to eight weeks of intake testing before their first injection. Thousands of dollars in medication, much of it unused. Embryo assessments done by a technician eyeballing cells under a microscope twice a day, then putting the embryos back in an incubator and hoping for the best. They’d leave exhausted and $20,000 lighter, with outcomes that didn’t reflect how hard they had worked.
He kept thinking: there has to be a smarter way to do this.
The Problem With “One Size Fits All” Medicine
Photo Credit: Aurea
Fertility treatment, like most of medicine, was designed around averages. Clinical protocols are built from population-level data, then applied uniformly. The result is a system that works reasonably well for a theoretical average patient, but that theoretical patient doesn’t actually exist.
Every woman’s hormonal profile, her ovarian reserve, her response to medication, it’s distinct. And yet, most clinics start everyone at the same stimulation dose, adjust based on crude blood test markers, and select embryos using subjective visual assessment.
The pharmaceutical industry has no incentive to change this. More medication means more revenue. Longer treatment timelines mean more monitoring visits, more ultrasounds, more billable touchpoints. The incentives of the traditional fertility model are not always aligned with the patient’s best outcome.
Dr. Merhi didn’t want to run that kind of practice.
What AI Actually Changes (Not the Hype, The Reality)
In 2025, Dr. Merhi began exploring whether artificial intelligence tools could close some of these gaps. He is precise about this because “AI” in healthcare has become a marketing term that’s been stretched past its meaning.
The tools that changed how he practices are specific:
- Medication dosing algorithms. Before starting a patient on stimulation, Dr. Merhi runs her baseline hormone levels and ovarian reserve markers through a predictive model that recommends a starting dose tailored to her profile. This alone has reduced medication waste at his clinic by more than 70%. Patients aren’t over-stimulated. They’re not under-stimulated. They receive what their body actually needs.
- Continuous embryo monitoring. The EmbryoScope system keeps embryos in an uninterrupted culture environment while a time-lapse camera photographs them every ten minutes. An AI scoring model used at Aurea analyzes thousands of developmental parameters and assigns a probability score for each embryo reaching a viable blastocyst. Instead of a technician’s subjective opinion, there is a data model trained on hundreds of thousands of embryo development sequences.
- AI-assisted sperm selection. Aurea uses computer vision to analyze sperm morphology at a level no human eye can match. For couples dealing with male-factor infertility, this changes the calculus of ICSI entirely.
None of this replaces physician judgment. Every protocol Dr. Merhi runs, every decision he makes, is still his. What AI has done is give him information he didn’t previously have, and give it to him faster.
The Business Case Is the Patient Case
Photo Credit: Aurea
Here’s what he didn’t expect: building a more efficient clinical model didn’t just improve outcomes. It fundamentally changed the economics of fertility care.
When medication waste drops from 35% to under 10%, patients spend less. When you eliminate weeks of redundant preliminary testing and move patients from consultation to retrieval in approximately two weeks, you reduce the carrying cost of treatment. When embryo selection is more accurate, fewer transfer attempts are needed.
The traditional fertility clinic model profits from complexity. Dr. Merhi found that removing complexity, replacing subjective decisions with data-driven ones, actually made the business stronger, not weaker.
Every entrepreneur has at some point looked at a bloated, inefficient industry and asked: who is this designed for? That question is what led him to build something different.
His clinic, Aurea Fertility Center, is designed specifically for women under 40 with good ovarian reserve, the patients most likely to benefit from a streamlined, AI-optimized protocol. It is not the right fit for everyone. Complex cases, diminished ovarian reserve, advanced maternal age, significant male-factor, belong at a clinic built around that complexity. (That’s why there is a sister clinic for exactly those patients.) Knowing who you serve is the first principle of building anything that actually works.
What Entrepreneurs Can Learn From Fertility Medicine
Dr. Merhi has thought a lot about why healthcare, which has everything to gain from efficiency, has been so slow to adopt tools that other industries take for granted.
Part of it is regulatory caution, which is appropriate. Part of it is liability culture, which often isn’t. But a large part is simply institutional inertia: we do it this way because we’ve always done it this way.
Disruption in healthcare doesn’t come from ignoring the science. It comes from being honest about where subjective human judgment has been masquerading as evidence-based medicine, and replacing it with something better.
Dr. Merhi sees three principles from this experience that apply well beyond fertility care:
- Efficiency and quality are not in tension. The assumption that doing less (less medication, fewer testing steps, shorter timelines) means worse outcomes is almost always wrong. Waste is not the same as care. When you strip a process down to what actually moves the needle, outcomes improve because the signal isn’t buried in noise.
- Know your patient, or your customer, with specificity. Generic solutions serve generic needs. The moment he decided to build a clinic designed for one specific profile of patient, everything got sharper: the protocol, the pricing, the communication, the technology stack. Trying to serve everyone often means serving no one particularly well.
- Technology adoption requires explaining the “why” before the “what.” His patients are not data scientists. They don’t care that AI score uses a convolutional neural network. They care whether their embryo has a better chance. When he leads with the outcome, you’ll get a score that tells us which embryo to transfer, instead of the mechanism, the conversation changes. Entrepreneurs introducing new technology into conservative markets often make this mistake in reverse.
What He Still Doesn’t Know
Dr. Merhi is honest about the limits.
AI in reproductive medicine is still young. The models in use are trained on large datasets, but those datasets have their own biases and gaps. The tools available today will look primitive in ten years. He holds his clinical decisions with confidence and his technology assumptions with humility.
He also doesn’t know whether what he’s built can scale the way a software product scales. Medicine is still fundamentally a human endeavor. The physician-patient relationship, the trust, the judgment, the presence in the room when someone gets news they weren’t expecting, that doesn’t get replaced. Building a tech-forward clinic means threading a needle between efficiency and intimacy. He hasn’t fully figured out how to do that at volume.
What he does know is that the status quo wasn’t good enough. For his patients, the traditional model cost too much, took too long, and made too many decisions by gut when data was available. Changing that was worth the risk.
Dr. Zaher Merhi is a reproductive endocrinologist and the founder of Aurea Fertility. He has been featured in Forbes, The New York Times, and USA Today for his work in AI-integrated reproductive medicine. Aurea Fertility serves patients from across the United States and internationally via telemedicine at aureafertility.com.
When Dr. Zaher Merhi started his fertility practice, he did what every other reproductive endocrinologist does: he followed the standard playbook. High-dose stimulation medications. Weeks of preliminary testing before a patient could even begin treatment. Protocols built around consistency, meaning what worked for the average patient was applied to every patient.
He was good at it. But he kept running into the same wall.
Women would come to him in their early 30s, healthy, motivated, with good ovarian reserve, and the system would swallow them whole. Four to eight weeks of intake testing before their first injection. Thousands of dollars in medication, much of it unused. Embryo assessments done by a technician eyeballing cells under a microscope twice a day, then putting the embryos back in an incubator and hoping for the best. They’d leave exhausted and $20,000 lighter, with outcomes that didn’t reflect how hard they had worked.