Tamarin Health enables secure collaboration among health companies by utilizing encrypted data in use and cryptographic protocols, allowing for analysis across multi-party data sets without revealing raw data. This approach addresses privacy and intellectual property concerns, facilitating patient matching and insights that were previously unattainable.
Funding
$880K 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
Health companies face significant challenges in collaborating on data analysis due to privacy regulations, intellectual property concerns, and the risk of exposing sensitive raw data. Traditional methods of data sharing, such as copying and aggregating data, create security vulnerabilities and limit the scope of potential collaborations.
Solution
Tamarin Health enables secure and private collaboration among health companies by utilizing encrypted data in use and cryptographic protocols. This approach allows for analysis across multi-party data sets without revealing or sharing raw data, addressing key privacy and intellectual property concerns. The platform facilitates patient matching and enables insights that were previously unattainable due to data-sharing limitations. Collaborators can analyze data right where it lives, using their preferred tools, without the need for clunky VDI setups or the risk of exposing underlying data.
Target Audience
Tamarin Health targets health companies, including hospitals, research institutions, and pharmaceutical companies, seeking to collaborate on data analysis while maintaining data privacy and security.
Features
- Secure multi-party computation using encrypted data in use
- Patient matching across identifiable datasets without revealing patient identities
- Collaborative analysis without copying, sharing, or aggregating raw data
- Compatibility with existing data analysis tools and infrastructure
- Privacy-preserving capabilities that eliminate IP and security risks
- AI training on distributed datasets without exposing raw data