Alii provides an AI‑driven platform that continuously updates medical guidelines, protocols, and knowledge documents, turning them into interactive decision‑support tools for healthcare professionals. The system tailors evidence‑based information to individual patient contexts, enabling faster, more consistent choices across disciplines while facilitating collaborative care and clear communication.
Funding
$2.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Healthcare providers often struggle to keep clinical practice aligned with the latest medical guidelines, protocols, and real‑world experience, leading to inconsistent decision‑making, increased administrative burden, and potential treatment errors.
Solution
Alii delivers an AI‑driven platform that continuously ingests, harmonises, and updates medical knowledge from multiple disciplines into a single logical framework. The system translates this knowledge into interactive, patient‑specific decision‑support tools that are presented at the point of care. By integrating directly with electronic health records, Alii automatically retrieves and writes back relevant data, reducing manual entry and minimizing errors. The platform also makes the underlying reasoning transparent, enabling clinicians, nurses, and patients to understand and discuss treatment options together. Continuous learning from patient outcomes feeds back into the knowledge base, ensuring the system evolves with real‑world practice.
Target Audience
Primary users are hospitals, health systems, and multidisciplinary care teams—including physicians, nurses, and allied health professionals—who require up‑to‑date, evidence‑based guidance at the bedside.
Features
- AI‑powered aggregation and real‑time updating of guidelines, protocols, and practice experience across specialties
- Interactive decision‑support interface that tailors recommendations to individual patient characteristics and preferences
- Full EHR integration for automatic data extraction and result documentation, lowering administrative workload
- Transparent logic visualisation that shows the reasoning behind each recommendation to support shared decision‑making
- Multidisciplinary knowledge standardisation in a single language, facilitating coordinated care among clinicians
- Built‑in analytics that learn from outcomes and practice data to continuously refine and expand the knowledge base