Fertility care is longitudinal, multi-actor, data fragmented, decision-sequencing heavy, emotionally & financially time-sensitive.  

And importantly: many fertility failures are not due to lack of knowledge.

They happen because:

• snapshot-thinking instead of longitudinal/trajectory thinking (trends),
• male/female factors are reviewed asymmetrically,
• couple dynamics & synchronization is missing (male and female are considered two isolated patients)
• signals are scattered (across lab reports, imaging, EMRs, treatment records, and patient-reported data),
• follow-ups are missed, timing drifts, repeat testing is forgotten,
• escalation logic is inconsistent (natural conception -> surgical correction / assisted reproduction techniques - IUI, ICSI, IVF etc.)
• nobody models “what happens next.”

Fertility journeys are becoming increasingly complex.

Clinicians must manually reconstruct timelines, identify missing investigations, review male and female factors, and make decisions. This process is time-consuming, cognitively demanding, and prone to overlooked data gaps.