Artificial Intelligence
for Reproductive Medicine

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Oocytes Prediction / Classification

Accurate prediction for egg

Patient feedback in IVF cycles
and social egg freezing

Standardized scoring system to facilitate
research in improving egg quality

Available commercially

Embryo Predictions

Non-invasive assessment

Improving success rates per transfer

Decrease twins (single embryo transfer)

Healthier Pregnancy outcomes

Uterus Lining Classification

Prevent transferring embryos at non-ideal time

Improving success rates per transfer

Decrease twins (single embryo transfer)

Healthier Pregnancy outcomes

Quality control is critical for a successful IVF lab.
Artificial Intelligence will inevitably improve outcomes through automation, objective diagnostics and enhanced decision making – all of which are subject to inherent subjectivity, biases, and limitations when performed by a human.

For Clinicians

Doctor + AI = Best Possible Outcome

New tools to help clinicians and embryologists to personalize care and as a result improve outcomes.

For Patients

Everyone’s bodies are different and your personalized information is critical for your doctor to make the best individualized treatment plan for you. By having the option to get deeper information on not only your embryo but also your eggs, we’re armed with more information to give you options and make the right decisions for your care.

About Us

Change is inevitable. Progress is optional.

We have developed the first Artificial Intelligence software analysis tool to non-invasively evaluate oocytes (eggs), creating the only objective classification and prediction tool for an oocyte.

Insights yielded by our patented technology will be valuable to patients, clinicians, and researchers, and have numerous clinical applications including an enhanced non-invasive assessment tool for embryo quality and endometrial receptivity assessment.

We are seeking strategic partners to help us in our mission to build advanced diagnostic and predictive tools for reproductive medicine.

Dr. Dan Nayot
Medical Director
Diana V. Olusanmi
Rene Bharti
Alex Krivoi
Chief Technology Officer
Jim Meriano
Embryology Director

Board of advisers

Dr. Mitchell Rosen

Associate Professor, Reproductive Endocrinology and Infertility UCSF

James Lanthier
Louis Villalba

Senior Medical Device / Bio-Technology Executive

Dr. Haider Ali

Assistant Research Professor, Information Technology.
Computer Vision and knowledge based systems
Johns Hopkins

Ben Mulroney

Television Host
CTV, eTalk

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