HOPPR Company Profile

Background

Overview

HOPPR is a technology company specializing in artificial intelligence (AI) solutions for medical imaging. Founded in 2019 and headquartered in Chicago, Illinois, HOPPR provides a secure platform that enables developers and medical imaging vendors to build, refine, and deploy AI applications tailored for the healthcare sector. The company's mission is to enhance diagnostic workflows and improve patient care by offering tools that ensure trust, traceability, and regulatory compliance in AI model development.

Mission and Vision

HOPPR's mission is to empower developers to create AI-driven medical imaging applications that improve care access, efficiency, and equity in healthcare. The company's vision is to revolutionize medical imaging by providing a secure and compliant infrastructure that accelerates the development and deployment of AI models, ultimately enhancing diagnostic accuracy and patient outcomes.

Industry Significance

In the rapidly evolving field of medical AI, HOPPR stands out by addressing critical challenges such as data provenance, model validation, and regulatory compliance. By offering a platform that integrates curated datasets, fine-tuning tools, and quality management systems, HOPPR facilitates the creation of high-performing, reliable AI models that are ready for clinical deployment.

Key Strategic Focus

Core Objectives

HOPPR aims to:

Provide a secure and compliant environment for developing AI models in medical imaging.

Offer tools and datasets that enable rapid fine-tuning and validation of AI models.

Support developers and medical imaging vendors in bringing AI applications to market efficiently and effectively.

Areas of Specialization

The company specializes in:

Developing foundation models for various medical imaging modalities.

Providing fine-tuning tools that allow customization of models for specific clinical applications.

Ensuring regulatory readiness through integrated quality management systems and traceability features.

Key Technologies Utilized

HOPPR employs:

Advanced machine learning algorithms tailored for medical imaging tasks.

Secure data management protocols to ensure data privacy and compliance.

Quality management systems that facilitate regulatory submissions and approvals.

Primary Markets Targeted

HOPPR primarily targets:

Medical imaging vendors seeking to integrate AI capabilities into their products.

Healthcare providers aiming to enhance diagnostic workflows with AI solutions.

Developers and researchers focused on creating AI applications for medical imaging.

Financials and Funding

Funding History

As of June 2025, HOPPR has secured a total of $31.5 million in funding. In June 2025, the company completed an oversubscribed Series A funding round led by Kivu Ventures and Greycroft, with participation from PSG Equity, Morningside Capital, Fortitude Ventures, and existing investor Health 2047.

Utilization of Capital

The funds from the Series A round are intended to:

Accelerate platform development.

Scale operations.

Expand foundation model capabilities.

Grow the team with top-tier engineering, AI, and compliance talent.

Pipeline Development

Key Pipeline Candidates

HOPPR is developing:

"Grace," a multimodal foundation model for medical imaging, designed to enhance image-to-image and text-to-image learning across various medical imaging modalities.

Stages of Development

The "Grace" model is in the development phase, with plans for fine-tuning and validation in collaboration with healthcare partners.

Target Conditions

The model aims to address a range of medical imaging applications, including radiology, cardiology, and other clinical domains.

Anticipated Milestones

HOPPR plans to unveil its latest innovations with commercial partners at the Radiological Society of North America (RSNA) 2024 conference.

Technological Platform and Innovation

Proprietary Technologies

HOPPR's platform includes:

A secure AI development environment optimized for medical imaging.

Foundation models designed for commercial use.

Fine-tuning tools that help teams build high-performing AI models.

Significant Scientific Methods

The company employs:

Advanced machine learning algorithms tailored for medical imaging tasks.

Quality management systems that facilitate regulatory submissions and approvals.

AI-Driven Capabilities

HOPPR's platform enables:

Rapid development of AI imaging applications.

Integration of AI models into clinical workflows.

Enhancement of diagnostic accuracy and operational efficiency.

Leadership Team

Key Executives

Dr. Khan M. Siddiqui: Co-Founder, Chairman & CEO. Dr. Siddiqui has a background in radiology and healthcare technology innovation, having served as Chief Medical Officer at Hyperfine and Chief Strategy Officer at Rad AI.

Dr. William Boonn: Chief Medical Officer. Dr. Boonn is a practicing cardiovascular radiologist at Penn Medicine and has over 20 years of leadership in radiology informatics and healthcare technology innovation.

Dr. Woojin Kim: Chief Strategy and Chief Medical Information Officer. Dr. Kim is a renowned musculoskeletal radiologist and an expert in imaging informatics and AI in healthcare.

Dr. Melanie Traughber: Chief Operating Officer. Dr. Traughber brings over 20 years of operational expertise in clinical research, medical imaging, and healthcare innovation.

Keith Corbin: Chief Financial Officer. With over 30 years of experience, Mr. Corbin has a proven ability to optimize financial performance and navigate complex business landscapes.

Competitor Profile

Market Insights and Dynamics

The medical AI imaging market is experiencing rapid growth, driven by increasing demand for diagnostic imaging and a shortage of radiologists. This creates a significant opportunity for AI solutions that can enhance diagnostic accuracy and operational efficiency.

Competitor Analysis

Key competitors in the medical AI imaging space include:

Viz.ai: Focuses on AI-powered healthcare solutions, particularly in the field of pulmonology.

DeepHealth: Specializes in AI-powered health informatics, offering solutions that enhance diagnostic workflows.

Strategic Collaborations and Partnerships

HOPPR has established strategic partnerships to strengthen its market position:

University of Miami’s NSF Center for Accelerated Real-Time Analytics (CARTA): Collaborating to develop standardized tools for evaluating AI models in healthcare, aiming to improve the accuracy and robustness of AI models used in clinical workflows.

Operational Insights

HOPPR differentiates itself by offering a secure and compliant platform tailored for medical imaging AI development, addressing critical challenges such as data provenance, model validation, and regulatory compliance. This focus positions HOPPR as a leader in the medical AI imaging space.

Strategic Opportunities and Future Directions

HOPPR plans to: