IVF is one of the most advanced technologies in modern medicine, and yet for many patients, it still feels like a black box. You wait, you hope, and you brace yourself for updates that can swing from excitement to heartbreak in a single phone call.

Daniella Gilboa has lived inside that black box for 15 years. As a clinical biologist and embryologist, she has worked in IVF labs, watched families wrestle with impossible choices, and seen how often patients are asked to make life-changing decisions without enough data or transparency. That gap is what led her to build AIVF, an AI-powered platform designed to make IVF more data-driven, more reliable, and more human.

In this episode of Lead with AI, host Dr. Tamara Nall speaks with Daniella about how AI-powered embryo ranking works inside IVF labs, how decision support tools can reduce uncertainty for patients, and why making IVF transparent may be just as important as improving success rates.

 The million-dollar IVF question   

In IVF, you can do everything “right” and still end up with uncertainty. After the injections, monitoring, and egg retrieval, you might have a handful of embryos, or none. Then comes the decision that determines what happens next: which embryo do you transfer?

For decades, that choice has typically relied on subjective embryo grading, where embryologists evaluate embryos visually and make a judgment call. Some patients add pre-implantation genetic testing (PGT), an invasive biopsy where cells are removed from a growing embryo and sent to a genetic lab. Both routes can be helpful, but neither fully solves the emotional reality of IVF: patients are often navigating a process filled with unknowns and waiting.

Daniella kept coming back to a simple belief. IVF should not depend on guesswork when so much is on the line. If IVF is driven by biology and data, then patients and clinicians deserve better tools to understand that data and make better decisions with it.

 AIVF is a flight simulator for the lab   

Daniella describes AIVF like a flight simulator for IVF. The platform lives inside the clinic, inside the lab, where the “magic” happens with eggs, sperm, and embryos. That matters because embryo selection is not an abstract decision. It happens in real time, under pressure, and the consequences are deeply personal.

AIVF analyzes embryo development using embryo video across the first five to six days of life, combined with lab data and known outcomes. The model learns patterns over large datasets and generates probability scores for each embryo. Instead of relying only on subjective grading, clinics can see an evidence-based number that supports decisions like which embryo to transfer and which embryos to freeze.

Just as important, AIVF is not positioned as AI replacing clinicians. It is a decision support tool designed to help doctors and embryologists make better calls with better information. The clinician still signs off, but the conversation shifts from “best guess” to “best supported decision.”

 The moment transparency becomes personal   

One of the most striking parts of Daniella’s vision is what it means for patients, not just clinics. IVF can feel like something happening behind a closed door, where the lab holds the information and the patient waits for updates. Even when the clinical team is excellent, the experience can still feel distant and opaque.

AIVF includes a patient-facing experience designed to open up that closed door. Daniella shared an image that stays with you: waking up at 4 a.m., opening an app, and seeing your embryos developing in real time, with scores attached. You are no longer only waiting to be told what is happening. You can see it, understand it, and ask better questions.

That shift is not a “nice-to-have.” For people who have felt powerless during IVF, transparency changes the emotional experience. It replaces helplessness with agency, and it gives patients a way to speak the same language as their clinicians.

 The stories that prove why it matters   

Technology becomes real when it changes an outcome. Daniella shared a story about a patient in Ireland who had been through multiple failed cycles and felt emotionally depleted. She still had frozen embryos from previous rounds, and she wanted clarity, not more guesswork.

Two embryos looked good visually, but when AIVF analyzed them, only one scored as likely viable. That embryo was transferred. She got pregnant. She gave birth. After so many failures, the patient told Daniella it suddenly became easy.

Another story raised the stakes even more. A patient had been told to consider egg donation after too many unsuccessful cycles. She asked for one more round. She had multiple embryos that looked acceptable, but AIVF helped identify the strongest candidates, the embryos with the best probability based on the model’s learning.

She transferred two and now has twin girls. Stories like these are not just emotional highlights. They show what decision support can do in high-stakes medicine: reduce uncertainty, support better choices, and give patients something IVF rarely offers clarity.

 AIVF does not change biology, but it changes the experience   

Daniella is direct about limitations. AIVF does not change biology. Age remains one of the most significant factors in fertility outcomes, and no algorithm can turn back the clock. Anyone promising that is selling fantasy.

What AIVF can change is what IVF feels like. It replaces the black box with usable information patients and clinicians can act on together. It transforms embryo selection from a purely subjective moment into a data-supported decision.

The clinician still signs off. The medical team remains responsible. But the decision is supported by probability scores informed by large-scale learning rather than a single snapshot or impression. That difference can change how patients cope with uncertainty and how clinics communicate choices with confidence.

 Ethics and trust in reproductive medicine   

When AI enters reproductive medicine, trust becomes the product. Daniella’s approach to ethics is grounded in the reality that fertility decisions are medical, emotional, and deeply personal. If patients do not trust the process, nothing else matters.

Her framework comes down to three principles. First, AI should augment humans, not replace them, especially in near-term medical practice. Second, AI must be explainable, not a mysterious score generator. If a clinician cannot interpret what the model is seeing, the tool is not ready for the clinic.

Third, success should be measured by human outcomes, not just model performance metrics. IVF is not a benchmark. It is families. If the outcomes do not improve in the real world, the model does not matter.

 The future Daniella is building   

Daniella’s vision goes beyond software. She wants AIVF to become the standard of care for IVF, and she imagines a future where AI-powered embryo ranking is simply how clinics operate. In that world, better embryo selection is not a luxury. It is expected.

She also sees the clinics themselves evolving. Her future includes AIVF-powered fertility clinics that expand access globally, so people do not have to give up on parenthood because IVF is not affordable or available. It is a vision rooted in democratization, not exclusivity.

Her boldest prediction is also the most futuristic: within a generation, IVF clinics will increasingly run with robotics and AI, scaling the infrastructure required for a world where IVF becomes far more common. The message is not meant to shock. It is meant to highlight what happens when reproductive care becomes something societies must scale, not something only a few can access.

 What you can do this week   

If you are currently in an IVF journey, Daniella’s advice is simple: ask better questions and demand clarity. Patients often feel pressure to be polite or quiet, especially in medical settings. Daniella’s view is the opposite. You are paying, you are investing emotionally, and you deserve to understand the process.

Ask questions like: How many embryos do I have? What are the chances for each one? Are you recommending biopsy, and why? If I do not want biopsy, what alternatives exist? If this cycle fails, what changes next time? These questions do not create conflict. They create better care.

And if you are not in the journey yet, both Daniella and Dr. Tamara Nall echoed the same message: plan earlier than you think. Egg freezing can be an insurance policy. You may never use it, but you will be grateful to have the option if life unfolds differently than you expected.

If you are navigating IVF, considering egg freezing, or curious what AI looks like when it delivers measurable impact in healthcare, this episode will change how you think about fertility, data, and the future of IVF.

Want to learn more about AIVF or find a clinic using AI-powered embryo ranking? Reach out to Daniella directly on LinkedIn, Instagram, or Facebook. For more on how AIVF works, visit the AIVF YouTube channel (@AIVFLtd5620) or email info@aivf.co.

 Quick answers   

What is AIVF?
AIVF is an AI-powered software platform used inside IVF labs that analyzes embryo development and generates probability scores to support embryo selection decisions.

It is designed to reduce uncertainty during IVF by giving clinicians and patients clearer information at the moment key decisions are made, like selecting which embryo to transfer or freeze.

Does AIVF replace doctors or embryologists?
No. Daniella describes it as decision support. Clinicians remain responsible for final decisions, with AI providing additional data to support those decisions.

The intent is to strengthen clinical judgment, not override it. AIVF is built to augment human expertise, not replace it.

Is AIVF an alternative to embryo biopsy and PGT?
Some patients use AIVF alongside PGT, and others use it when they prefer to avoid embryo biopsy. The decision depends on the patient, the clinic, and the clinical context.

Daniella’s broader point is that patients should understand why a clinic recommends biopsy, what the risks are, and what alternatives exist, then make an informed choice with their clinical team.

If you’re navigating IVF, considering egg freezing, or curious what AI looks like when it delivers measurable impact in healthcare, this conversation will change how you think about fertility, data, and the future of IVF.

Want to learn more about AIVF? Reach out to Daniella directly on LinkedIn, Instagram, or Facebook. For more on how AIVF works, visit the AIVF YouTube channel (@AIVFLtd5620) or email info@AIVF.co.    

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Follow Daniella Gilboa (Co-Founder & CEO, AIVF): LinkedIn: @Daniella-Gilboa | Twitter/X: @GilboaDaniella | Instagram: @Daniella_Gilboa | Facebook: Daniella.Gilboa.3 | Contact: info@AIVF.co

AIVF: LinkedIn: @AIVF | YouTube: @AIVFLtd5620 | Website: AIVF.co