The startup develops an artificial intelligence platform that utilizes big data analytics to prioritize embryos for transfer and select optimal sperm for injection in assisted reproductive technologies. This technology enhances the likelihood of successful pregnancies for patients by improving embryo selection and sperm quality assessment in clinics worldwide.
Funding
$13M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
In assisted reproductive technology (ART), the selection of viable embryos and optimal sperm is crucial for successful pregnancies, but traditional methods rely heavily on subjective visual assessments. These assessments can be inconsistent and may not capture subtle yet critical characteristics that influence developmental potential. This can lead to suboptimal selection, reducing the likelihood of successful implantation and live birth.
Solution
IVF 2.0 offers an AI-powered platform designed to enhance embryo and sperm selection in ART. The platform utilizes deep learning algorithms and computer vision to analyze vast amounts of data, identifying key parameters that are often undetectable by the human eye. By providing quantitative, objective assessments of embryo quality and sperm characteristics, IVF 2.0 aims to improve the accuracy and consistency of selection processes. The platform consists of two main products: ERICA, which prioritizes embryos based on euploidy potential, and SiD, which selects optimal sperm for intracytoplasmic sperm injection (ICSI) based on morphology, speed, and motility patterns.
Target Audience
The primary target audience includes IVF clinics and embryologists seeking to improve pregnancy success rates through more accurate and objective embryo and sperm selection.
Features
- ERICA: AI-driven embryo ranking based on euploidy training sets, eliminating the need for biopsy or media sampling
- ERICA: Deep learning AI that improves performance with continuous learning and adaptation
- ERICA: Processes 2.5 million parameters per embryo to estimate ploidy potential
- SiD: Real-time sperm selection based on morphology, speed, and motility patterns
- SiD: Identifies, tracks, and evaluates every sperm in the vision field in real-time
- SiD: Transforms qualitative sperm assessment into a quantitative assessment
- Both ERICA and SiD are compatible with existing lab equipment