Hanah Ecosystem
Hanah Ecosystem operates a privacy-first data exchange layer that connects women's health apps, clinical datasets, hospitals, and research partners through consent-based, governance-built infrastructure. The platform prepares de-identified product data mapped to clinical standards, enabling secure collaboration for research like their active PMS and PMDD study with a Dutch hospital.
- Artificial Intelligence
- Data & Analytics
- Digital Health
- Healthcare Technology
- Software Only
Funding
Founders
Product
Problem
Women's health data is fragmented across apps, clinics, studies, and institutions, limiting understanding and creating gaps for individuals, researchers, clinicians, and companies. This siloed landscape prevents responsible data collaboration and slows the generation of clinical evidence for conditions that disproportionately affect women.
Solution
Hanah Layer is a consent-driven data exchange platform that standardizes and connects women's health data across digital health companies, clinical systems, hospitals, and research partners. The platform prepares what a product already captures—consented, de-identified, and mapped to clinical standards—so every new collaboration runs over an existing connection rather than requiring a new project. Governance is configured once and applied to every request, with privacy, anonymization, permissions, and audit trails built into the infrastructure. This enables health apps to build evidence around their products, researchers to access real-world data, and organizations to collaborate securely without starting from scratch.
Target Audience
Primary customers are women's health and femtech applications seeking to generate clinical evidence, as well as hospitals, research institutions, and pharmaceutical companies that need access to consented, real-world women's health data for studies and collaboration.
Features
- Consent management with real-time enforcement—data sharing ceases immediately when a user withdraws consent
- Automated data preparation and mapping to clinical terminology standards for interoperability
- Privacy and anonymization technologies appropriate for sensitive health data, including encryption
- Centralized governance and permissions model applied consistently across all collaboration requests
- Study legibility and in-tenancy analysis capabilities supporting active research projects, such as the PMS and PMDD study with a Dutch hospital
- Secure exchange with full audit trail and GDPR-compliant processing (Articles 6 and 9)