Artificial intelligence systems are already common in IVF laboratories today, for real-time monitoring and selecting the best morphological embryos.

The Sperm Tracer AI system offers a revolutionary tool for training junior embryologists and standardizing the sperm selection process. By leveraging advanced machine learning algorithms, Sperm Tracer can analyze sperm morphology and motility with high precision, providing a consistent and objective assessment that is crucial for successful fertilization outcomes. This technology is an invaluable educational aid for junior embryologists, offering real-time feedback and detailed analysis that enhances their learning curve and competency in identifying high-quality sperm.

Moreover, the standardization provided by Sperm Tracer minimizes the variability and subjectivity inherent in manual sperm selection, ensuring that only the best candidates are chosen for fertilization. This uniformity is essential for high success rates in assisted reproductive technologies (ART). By integrating Sperm Tracer into the laboratory workflow, clinics can ensure that all embryologists, regardless of experience level, adhere to the same high standards of sperm selection, thereby improving overall outcomes and patient satisfaction.

ReproScientific’s Sperm Tracer also confronts several other significant issues. Each embryo carries 50% of the genetic information of an oocyte and 50% of a sperm. Every single sperm participating with 50% of the DNA cargo of the embryo, could play a detrimental role for the embryo itself and its quality. So, by increasing our ability to select high-quality sperm, we also improve the ability to get better embryos in our laboratories. This is highly seen in cases such as below:

  • Poor ovarian reserve
  • Multiple failed attempts
  • Unexplained infertility
  • Cases with few and or poor-quality eggs
  • Poor sperm quality
  • Previous low fertilization or poor-quality embryos

our technology can help patients achieve the goal of a long-awaited pregnancy.