OvaVision offers an AI‑native hormone intelligence platform that uses smartphone‑based computer vision to read fertility tests, capturing over 1,000× more visual data than traditional light sensors. By learning features common across test designs, the system provides consistent, high‑resolution hormone insights regardless of brand or lighting conditions. The platform enables users to track hormone patterns more accurately and gain clearer fertility insights.
Funding
Funding not disclosed
Founders
Product
Problem
Current at‑home hormone test readers rely on 1970s‑era light sensors that capture only a few brightness measurements, requiring specific test strips, controlled lighting, and long processing times, which leads to inconsistent and low‑resolution hormone insights.
Solution
OvaVision offers an AI‑native platform that uses a smartphone camera and modern computer‑vision models to analyze the entire visual signal of any line‑based pregnancy test strip. By evaluating millions of pixels across the test line, the system extracts color gradients, edge patterns, and intensity distributions that are invisible to simple sensors. This approach provides consistent, high‑resolution β‑hCG readings across different brands and real‑world lighting conditions, delivering results in seconds without proprietary hardware. The software‑first design enables rapid addition of new hormone biomarkers through updates, extending the platform beyond β‑hCG to broader women’s health metrics.
Target Audience
Primary users are individuals and couples tracking early pregnancy or fertility‑related hormone patterns, including those undergoing IVF, IUI, medicated cycles, or natural conception attempts.
Features
- Smartphone‑based image capture that leverages millions of pixels for detailed analysis
- AI‑driven computer‑vision models trained on thousands of test images to interpret full test‑line patterns
- Brand‑agnostic compatibility with any standard line‑based pregnancy test strip
- Robust performance under varied lighting conditions without the need for controlled environments
- Instant result delivery within seconds, eliminating long processing delays
- Scalable software architecture allowing future expansion to additional hormone biomarkers