top of page

Known adverse reactions

Drug interactions

Editor's comments

Clinical pathways

References to PubMed citations

Common and scientific names

All known uses

Evidence-based safety ratings

Evidence-based effectiveness ratings

Mechanism of action

Building the #1 natural-care dataset

Unali aims to build the first open-access, ontology-based database for Traditional, Complementary and Alternative Medicine (TCAM) products. The database includes:

Dataset includes:

Data Collection

Generating high-quality, ethically sourced data sets is crucial for enabling the use of next-generation AI technologies.

Products data

The foundation of our dataset is a relational representation of products in terms of characteristics and applications. We build it using keyword extraction and the use of triplet networks to derive semantically meaningful representations of text.

Behavioral data

The Unali user experience is designed to collect behavioral data. We use this data to build user cohorts to optimize our recommendations and gain insights into people’s interests and needs in the context of Traditional, Complementary and Alternative care.

Qualitative data

We provide users with fine-grained surveys to collect data on users' attitude towards natural care, their expectations before and satisfaction after treatments. Such data allows us to carry out comparisons with conventional medicine.

Clinical data

We integrate in our portal access to several million publications as recommended reads. We use a mixture of keyword and AI-built representations to categorize papers by keywords and link them to specific products.

Health equity

Data is a cornerstone for efforts to address disparities and advance health equity. Availability of high-quality, comprehensive data disaggregated by race/ethnicity is a prerequisite consideration included in building this dataset.


Our data pipeline ingests products, behavioral, qualitative and clinical data. The output is the first ever ontology-based TCAM database. It is designed to enable you to formulate and answer quantitative questions to monitor the performance of treatments, related products and more.

We welcome new collaborations. Limits are not placed on scientific questions or methods, and there is no requirement for co-authorship. Investigators interested in collaborations are invited to fill out a simple form that asks about the details of the collaboration. 

Scientific Research

Our mission is make natural care accessible to everyone. To that end, we are opening our dataset to Universities and in-residency students.

bottom of page