Geen – AI layer for triage, care navigation and gender-sensitive health data

Geen is an AI layer (not a new platform) that sits on top of existing health, welfare and insurance systems to help people find the right route to care faster, while giving organisations better data to plan and evaluate services.

Technically, Geen combines:

• a GraphRAG-based triage engine that makes services, providers and care pathways machine-readable;

• a conversational copilot that can be embedded in existing portals (hospital portals, insurer portals, welfare platforms, municipal access points);

• analytics dashboards with disaggregated indicators (by gender, age, socio-economic profile, etc.) on time-to-care, service use and unmet needs.

Starting from everyday language (“I have had vertigo for weeks”, “I’m caring for a parent with dementia”), Geen suggests the most appropriate next step, prioritising public and in-network options and what is already funded (health systems, insurance, welfare). This reduces inappropriate referrals, missed appointments and delays in accessing care.

Within a UNITE project we are looking for partners such as:

• Hospitals, local health authorities, social care providers interested in piloting AI-supported triage and care navigation;

• Municipalities / regions working on integrated care, “home first” and community-based services;

• Welfare / insurance platforms that want to add an intelligent navigation layer to their existing portals;

• Universities and research centres focused on digital health, health equity, AI ethics and evaluation of impact;

• Civil society organisations / patient groups working on access, gender and vulnerable groups.

Geen can contribute to the consortium by:

• providing the AI triage and navigation layer (software, integration and configuration);

• co-designing local care pathways with partners and adapting the triage engine to different contexts;

• generating anonymised, disaggregated data for monitoring inequalities, evaluating pilots and informing policy;

• documenting methodologies and lessons learned for scaling AI-enabled care navigation in other European settings.

We are particularly interested in pilots that address equity, gender-sensitive care, chronic conditions and community-based services, and in collaborations that combine technical integration, service design and rigorous evaluation.