HOPPR provides a foundation model API for medical imaging that enables secure data handling and efficient model fine-tuning across various imaging modalities. This platform reduces the time and cost of AI development, facilitating faster prototyping and scalable applications in research and clinical settings.
Funding
$3M 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
Developing AI models for medical imaging is complex and costly, requiring secure data handling, extensive datasets across various modalities, and high-performance computing resources. Navigating data privacy regulations and minimizing the burden of IRB and PHI compliance further complicates the process.
Solution
HOPPR offers a foundation model API designed to streamline AI development in medical imaging. The platform provides secure data handling, model fine-tuning capabilities, and access to diverse datasets across modalities, anatomies, demographics, and geographies. By reducing the time and cost associated with AI development, HOPPR enables faster prototyping, hypothesis testing, and scalable applications for research and clinical settings. The platform also facilitates access to cutting-edge research, industry leaders, and multi-center collaborations.
Target Audience
HOPPR's primary users are researchers and developers in the medical imaging field who seek to accelerate AI model development while maintaining data security and regulatory compliance.
Features
- Foundation model API for various medical imaging modalities
- Secure data handling with anonymization and regulatory compliance
- Scalable, high-performance GPU environment for model training
- Access to diverse datasets across modalities, anatomies, demographics, and geographies
- Streamlined research with minimized IRB and PHI hurdles through access to de-identified data
- Integration with HOPPR’s labeling services and external services