Common questions, honestly answered.

Ashwam is a personal health platform built around each woman, not around population averages. It captures structured signal across the dimensions of daily life — body, mind, emotion, sleep, food, activity — and builds a longitudinal record that learns what is normal for her, specifically.

Where most health products compare a woman to other women — the population average that says, for example, that a "normal" cycle is 28 days — Ashwam compares her to herself. If your own cycle is typically 21 days, that is your normal. The platform is being built first for women in midlife, where existing health research has historically left the largest gaps.

Ashwam learns the patterns that are yours alone — when you sleep well and why, when you eat in ways that don't agree with you, when you feel bloated and what's happening around it. A short daily check-in, five minutes, across the dimensions Ashwam thinks with — body, mind, emotion, sleep, food, activity, and the social and environmental context that shapes them. Over weeks, then months, those answers form a baseline — your normal, not the average woman's normal.

Over the months and years, when that baseline shifts, Ashwam sees the change before it becomes a symptom you cannot ignore. It surfaces the right moments to ask better questions of your body — and to get the right test, the right consultation, at the right time. The longer you use it, the clearer it gets at telling apart the noise of a single bad day from a real biological change underneath.

Wearables read what your body is doing right now — your heart, your sleep, your activity — and compare you to a manufacturer's average score (readiness, stress score, biological age, and so on). Most metrics reset within a cycle, meaning the slow patterns of midlife biology never get to compound across years.

Ashwam treats wearables — and any sensor data — as one input, not the whole story. Lived experience is the foundation. Wearable signal enriches it. If you use more than one device — say, a watch and a ring — Ashwam reconciles their different methodologies into a single picture of you, alongside what you've shared in your daily check-ins.

Most women in the world do not have a wearable. If you do, Ashwam reads its signal in. If you do not, your lived experience alone is enough to build your baseline and act on what you see.

ChatGPT is a conversation. Ashwam is a record.

A general AI assistant responds when you ask it something. Ashwam observes your daily inputs and nudges you toward what is important to focus on, before you have thought to ask. The intelligence in ChatGPT lives in the moment of the conversation. Ashwam's intelligence lives in the structured, longitudinal record of your biological signal over time — a record that exists whether you ask it anything or not, purpose-built for the patterns of women in midlife.

In an ideal world you might use both. The purposes are completely different.

One more thing that matters clinically: a general AI cannot give your doctor an audit trail of why it produced any specific answer. Ashwam can. Every signal Ashwam surfaces is traceable to your own data — which is what makes it useful in a medical conversation, not just a personal one.

Nothing special. Ashwam is designed to be inclusive of every woman, not only the ones who can afford or have access to wearables and labs. The daily check-in alone — five minutes, across the dimensions of how you are doing — is enough to build your baseline and see your patterns over time.

To put it in scale: of roughly 4 billion women in the world, around 1.7–1.8 billion have smartphones. Roughly 225–285 million women globally own a wearable (Apple Watch, Fitbit, Garmin and similar, capable of basic women's-health features). Ashwam is built for the women the wearables industry has not reached, alongside the women it has.

And in the other direction: the longevity industry will tell you that you need hundreds of biomarkers from premium lab panels to take care of yourself. You do not. The signal in your own daily life — how you slept, what you ate, when you felt off — is enough to build a baseline and act on it.

If you wear a watch, Ashwam reads its signal in. If you choose to add lab results, they recalibrate your baseline. Each layer adds richness, but none is required. You can start today with nothing more than your phone and your honest five minutes.

Stats synthesised from the GSMA Mobile Gender Gap Report 2025, the IDC Worldwide Wearable Device Tracker, and corporate disclosures from Oura and Willow Innovations.

No. Ashwam the platform is built for every woman, across every starting point and every population.

The evidence programmes that will generate prediction models are sequenced with intent — and the first programme focuses on South Asian women, because they are among the most under-represented populations in existing women's health research. That sequencing decision is about where the research gap is largest, not about who the platform serves. From day one, Ashwam works for any woman who joins.

No. Ashwam is built for women in midlife — broadly the years across the perimenopausal transition and beyond. Many women start using Ashwam before they recognise themselves as perimenopausal, sometimes years earlier.

The longitudinal record is more valuable the earlier it begins, because perimenopausal change often shows up in patterns months before symptoms become unmistakable. If you are in your late 30s or any decade after, Ashwam is built with you in mind.

Yes. The platform launches publicly in December 2026, with rollout sequenced across countries in the months that follow.

The waitlist — the bar at the top of every page — captures your country, so we can let you know as Ashwam becomes available where you live — wherever that is.

Ashwam is built around female physiology — the perimenopausal transition, hormonal patterns, and the ways women's biology has historically been understudied. Its architecture, its questions, and its baselines are designed for women's bodies.

The platform is for anyone whose biology this serves, including transgender women and non-binary people whose bodies move through similar transitions. It is not built around male physiology, and would not produce useful patterns for it.

The Founding Circle is a hundred women using Ashwam, on rolling cohorts beginning July 2026.

The daily commitment is five minutes — the in-app check-in across the dimensions of how you are doing. The weekly commitment is one Circle, online, where we discuss what is working in the app, what is not, and what should be re-prioritised before public launch in December.

The Founding Circle is a validation cohort — testing what has been built — not a co-design body. The User Advisory Board, recruited from the Founding Circle after public launch, is the body that helps shape what comes next. More on the Founding Circle →

Yes. Founding Circle members have full access to the app at no cost during the beta.

Ongoing access at and after public launch will be communicated as the launch approaches and pricing is finalised. The Founding Circle commitment is your honest use of the app and participation in the weekly Circles — that is what is being asked, and what is being given back.

Ashwam is built by Shilpi Sharma, an exited founder from her last startup — Kvantum, an ML/AI platform for marketing measurement. She has built large-scale data systems across her career, most recently an intelligence platform reaching 115 million consumers in the US as Chief Strategy Officer at Yum Brands. Over the past year, Shilpi has built a small team of clinicians, engineers, designers and researchers across Australia, India and the United States.

The platform is self-funded at this stage. Ashwam is not building toward early venture-scale fundraising — it is building toward proof points first, evidence programmes second, and capital that follows the work.

Read the full thesis on North Star →

Shilpi's path to Ashwam started with her own body. During her post-COVID recovery, she went through a full diagnostic workup to rule out autoimmune conditions — and on that journey she came to understand a structural problem in women's health: the data underlying today's diagnostics comes overwhelmingly from white women, which means non-white women are often at a disadvantage when it comes to early detection of disease. The gap is in the data.

That realisation pulled her into women's health research starting in 2021. She also began investing in women's health companies through Portfolia, a Silicon Valley–based women's health fund.

And most recently, as a perimenopausal woman, she found the same problem in her own life. The existing tools for understanding what was happening to her were either built around a population average, or around a single moment in time. She had a watch and a ring to learn a bit about sleep and activity, but none of it was connecting her lived experience in any meaningful way to the rest of her measurement. She also found that her clinicians had every good intention. They just never had her data.

A physicist by education and a technologist by heart, Shilpi decided to build a platform that not only supports women right away but also fills the data gap in women's health for the most understudied populations — enabling researchers, academicians, and providers to work from real longitudinal evidence, not population averages.

She also believes that the women who build their baselines now will be able to inform their daughters about their biology in a much deeper way than our mothers were ever able to do for us.

Ashwam works with clinicians across endocrinology, gynaecology, and integrative medicine; with researchers in longitudinal cohort design; and with operators experienced in building consumer health products at scale.

The team is being kept deliberately small at this stage, and the advisors are chosen for the depth they bring to specific questions rather than for breadth. As Ashwam grows, the advisory structure will be made more visible.

You see your data. Ashwam sees the derived signal needed to compute your baseline and surface your patterns — never raw values where they are not needed.

Your data is not sold. It is not shared with advertisers, employers, insurers, or anyone else without your explicit, granular consent. If you choose to share your record with your care team — your GP, gynaecologist, nutritionist — that sharing happens on your terms, and you can revoke it at any time.

The full data architecture is described in the Ethos page.

Some of Ashwam's longer-term mission is generating the evidence base women's health has historically lacked — through prospective, consented, longitudinal cohorts.

No research programme is running yet, and no woman's data has been used for research. When one exists, participation will be opt-in, separate from using the app, and withdrawable at any time without affecting your access. Your data is never used for research without your specific consent for that specific programme.

The Ethos page describes the consent architecture in full.