Wearable health apps weren't built for hormonal transitions. They collect great data. But the algorithms interpreting it were trained on populations that don't reflect what happens to sleep, HRV, and recovery during perimenopause.
The result: scores that don't match how you feel. Green across the board after a terrible night. "Low recovery" warnings when nothing is wrong. Metrics that miss the patterns that actually matter.
And even when the data is good, it's scattered. Sleep in one app. Cycle in another. Supplements in a spreadsheet. Lab results in a PDF somewhere. Nothing talks to anything else.
PeriClue brings it all into one place — sleep, recovery, activity, cycle, symptoms, nutrition, supplements, labs — and reads it through a lens grounded in perimenopause research, personal baselines, and cycle-phase context.
PeriClue is an iOS app that connects to your Apple Watch via Apple Health. No new hardware required — no ring, no band, no wearable subscription. It reads the same data your current watch collects. It just interprets it through a perimenopause-calibrated lens.
Instead of scoring your sleep on hours alone, it looks at how fragmented the night was. Instead of comparing your HRV to a population average, it tracks your own baseline and adjusts for where you are in your cycle. It connects things that other apps keep separate: sleep, recovery, activity, symptoms, supplements, cycle, nutrition, labs.
The idea was simple. I wanted one place that held everything and could actually tell me what it saw. Not a symptom log. Not another tracker with a different color scheme. Something that could look at three months of my data and surface what changed, what correlates, and what my provider might want to know.
I'm Anastasia, an independent developer. I'm not a doctor or a scientist. I'm someone who went looking for answers, found them in research papers and her own data, and built the tool she wished existed. I've since built a small team around it, with input from women going through the same thing and guidance from healthcare professionals who saw what was missing.
PeriClue was founded in 2025. The algorithms are grounded in peer-reviewed research (the SWAN cohort study, Penn Ovarian Aging Study, TREMIN longitudinal study, and others). Anthropic does not use your conversations to train its models. The data architecture is privacy-first by design, not by afterthought.
Health data is sensitive. PeriClue never sells data, never shares it with advertisers, and never uses it for anything other than generating personal health insights. AI conversations are processed by Anthropic and are never used to train its models. You can request full data deletion at any time.
Questions, feedback, or partnership inquiries: support@periclue.app