HHoppr.ai provides a generative AI platform focused on medical imaging. It gives developers access to diverse medical imaging data, pre-configured environments, and the latest AI/ML tools so they can build, train, and test medical imaging models. The platform works by offering ready-to-use datasets and infrastructure in a managed environment, helping researchers experiment and scale model training while maintaining privacy and regulatory compliance. What sets Hoppr.ai apart from competitors is its emphasis on medical imaging datasets combined with privacy safeguards and compliance-ready workflows, enabling safer and scalable AI development in healthcare. The company’s goal is to make it easier and more cost-effective to create healthcare AI solutions that can be used in real-world clinical settings.
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Company Size
11-50
Company Stage
Series A
Total Funding
$31.5M
Headquarters
Chicago, IL
Founded
2019
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HOPPR releases whole-body musculoskeletal X-ray Narrative Model. News | X-Ray | October 28, 2026 HOPPR FS MSK Whole-Body Narrative Model, now in beta release, generates draft report findings from up to three X-ray views per study, with customization and integration available through HOPPR Forward Deployed Services Oct. 28, 2026 - HOPPR has announced the beta release of the HOPPR FS MSK Whole-Body Narrative Model, a vision-language foundation model that generates draft findings text for musculoskeletal (MSK) radiographs. The model processes up to three views per study and provides a software component for developers building radiology reporting and image-based workflow applications. Through HOPPR Forward Deployed Services (FDS), HOPPR works with organizations to evaluate, customize, and integrate the model within their workflow. MSK radiography spans the body, from the cervical spine to the toes. The FS MSK Model was trained across the musculoskeletal system - including the spine, thorax and chest wall, upper extremity, and pelvis and lower extremity - giving developers one starting point for report drafting across anatomical regions. HOPPR trained the model on approximately 674,000 proprietary outpatient MSK studies, with the dataset balanced across body parts. The model focuses on describing abnormalities rather than normal anatomy. HOPPR evaluates the model against 26 MSK finding categories, including fracture, degenerative joint and spine changes, alignment, soft tissue, bone quality and lesions, and hardware. "Organizations shouldn't need a separate AI model for every bone and joint. Musculoskeletal imaging spans the whole body, and a single model trained across it gives developers a far stronger foundation to build on," said Khan Siddiqui, MD, co-founder and CEO of HOPPR. "The FS MSK Model offers one whole-body model for generating draft findings text, and our Forward Deployed Services team works with each customer to adapt it to their data and workflows." Whole-Body musculoskeletal X-ray Narrative Model. The FDS team brings together HOPPR machine learning scientists, software engineers, data scientists, and clinical experts who work alongside each organization. For the FS MSK Model, that work includes customizing the model with the customer's own data, designing the labeling workflows that support it, integrating the model into existing systems, and supporting validation testing in the customer's environment. HOPPR's secure infrastructure is HITRUST e1 certified and SOC 2 Type II attested, and operates under a Quality Management System. The model name, "FS," honors Dr. Florence Ada Stoney (1870-1932), widely credited as the first woman radiologist in the United Kingdom. Stoney established an X-ray department at the Elizabeth Garrett Anderson Hospital for Women in 1902 and later led the X-ray department at Fulham Military Hospital during World War I. "Dr. Stoney practiced radiology when the field was young and few doors were open to women," said Roger Boodoo, MD, Medical Director of AI at HOPPR. "Naming this model in her honor recognizes the people who helped build the discipline our work depends on." The FS MSK Whole-Body Narrative Model is a software component, not a medical device.
HOPPR, a Chicago company that builds AI for medical imaging, has released a beta of its FS MSK Whole-Body Narrative Model. The model drafts the findings section of musculoskeletal X-ray reports from up to three views per study. It was trained on about 674,000 proprietary outpatient studies covering the spine, thorax and chest wall, upper extremity, and pelvis and lower extremity. HOPPR evaluates it against 26 finding categories, including fracture, alignment, and hardware. Organizations can have the model customised and integrated into their workflows through HOPPR Forward Deployed Services. The beta is not cleared by the US Food and Drug Administration (FDA) and is not intended for diagnostic use.
HOPPR and CARPL.ai partner to give customers access to foundation models for building and fine-tuning radiology AI. Oct 07, 2026, 09:01 ET CUPERTINO, Calif., Oct. 7, 2026 /PRNewswire/ - CARPL.ai, the world's largest radiology AI marketplace and enterprise imaging AI platform, today announced a partnership with HOPPR, a company transforming how AI is developed for medical imaging. The collaboration gives healthcare providers access to HOPPR's foundation models to securely develop, fine-tune, and deploy custom radiology AI applications through the CARPL platform. Building these tailored models has traditionally required massive computational resources, large proprietary datasets, and significant technical overhead. This partnership removes those barriers. Radiology teams can now leverage HOPPR's advanced vision and language foundation models as a starting point. Using their own local imaging data or curated reference datasets, they can securely fine-tune applications such as automated report generation, ensuring outputs align with institutional terminology, reporting styles, and clinical requirements. The result is a seamless path from model training to deployment. These applications integrate directly into the CARPL platform, where healthcare providers can validate, deploy, and monitor them within their existing PACS infrastructure, without disrupting workflows. "As we help some of the world's largest radiology groups and academic medical centers adopt AI, a new need emerged - a need to build and fine-tune their own AI models, using their own data based on their own use case. This partnership will now fast-track that," said Vidur Mahajan, CEO at CARPL.ai. "HOPPR is quickly becoming the undisputed leader in the foundational AI space for radiology, and we are thrilled to offer them through our platform." "Accessing and curating millions of imaging studies to build AI models is time-consuming, expensive and difficult to scale. HOPPR's foundation models give radiologists and AI developers a starting point to build their own models using a fraction of the data they would otherwise need," said Dr. Khan Siddiqui, Co-Founder, Chairman & CEO at HOPPR. "Our partnership with CARPL connects that development process to clinical deployment, giving healthcare providers a single platform to procure, integrate, and use AI models built on HOPPR's platform." Looking ahead, CARPL.ai and HOPPR plan to expand capabilities across a wider variety of imaging modalities. The companies will also leverage CARPL's post-market surveillance tools to continuously monitor model performance, ensuring they remain accurate and consistent over time. About HOPPR Founded in 2019, HOPPR brings together experts in clinical radiology, AI development, and healthcare commercialization to advance the development of transparent and scalable AI for medical imaging. The HOPPR(R) AI Foundry is a secure development platform designed for building, fine-tuning, validating, and hosting AI models for medical imaging. The platform provides curated datasets, traceable development workflows, and secure infrastructure that support responsible AI development aligned with industry quality and regulatory standards. HOPPR(TM) AI Foundry holds SOC 2 Type II attestation and HITRUST e1 Certification and is HIPAA-compliant. HOPPR also offers Forward Deployed Services, embedding HOPPR's machine learning scientists, software engineers, data scientists, and clinical experts directly within your team to accelerate development at every stage. For more information, visit www.hoppr.ai. About CARPL.ai CARPL.ai is an end-to-end enterprise imaging AI platform, and the world's largest radiology AI marketplace offering 300+ applications from 100+ AI Partners. With regulatory clearances across multiple regions including the FDA, CE, ANVISA, TGA, and HSA, CARPL.ai enables radiologists and researchers to easily access, assess, and integrate radiology AI applications into their clinical practice. CARPL.ai provides a single user interface, a single data channel, and a single procurement channel for the testing, deployment, and monitoring of AI applications in clinical radiology workflows. The CARPL.ai platform is used by four out of the world's top five radiology groups, and integrates with leading PACS systems, including Philips, AGFA HealthCare, DeepHealth, Intelerad, RamSoft, and Paxera Health, ensuring seamless interoperability across imaging environments. Learn more at www.carpl.ai SOURCE HOPPR
HOPPR unveils new AI foundation model for Chest CT. The HOPPR EF Chest CT Narrative Model reportedly provides narrative language describing pertinent findings across pulmonary, upper abdominal, cardiac, mediastinal and soft tissue regions with processing of 3D chest CT volumes. Adding a fifth foundation model to its AI Foundry portfolio, HOPPR has introduced the HOPPR EF Chest CT Narrative Model. Trained on a large proprietary chest CT dataset drawn from multiple facilities, the offers narrative descriptions of chest CT findings across pulmonary, upper abdominal, cardiac, mediastinal and soft tissue regions with processing of 3D chest CT volumes. HOPPR added that the AI foundation model also includes coverage of conditions such as aortic injury, pneumothorax and pulmonary embolism. The company noted that theHOPPR EF Chest CT Narrative Model is available through HOPPR Forward Deployed Services that provide expertise in clinical workflow, machine learning and deployment support to facilitate development and customization of the foundation model to the needs of the radiology department or facility. "Chest CT is one of the most information-dense studies in radiology. Getting AI to work well across everything it captures - the lungs, the heart, the aorta - is a genuinely hard problem, and we are pleased with what this model can do," noted Khan Siddiqui, MD, the co-founder and CEO of HOPPR. "But the model is only part of what we are building. Our AI Foundry and Forward Deployed Services include secure infrastructure, curated data, and the clinical and technical expertise to help any organization move from a foundation model to a working application, regardless of where they are starting from. That is what makes this more than a model release."
HOPPR has launched its fifth foundation model, the HOPPR EF Chest CT Narrative Model, which processes 3D chest CT volumes and generates descriptive language covering pulmonary, cardiac, and other anatomical regions. The model was trained on a proprietary dataset from multiple US clinical sites, with deliberate inclusion of rare but serious conditions such as aortic injury and pulmonary embolism. The Chicago-based company's foundation model portfolio now spans three imaging modalities: chest X-ray, mammography, and chest CT. Models are available through HOPPR's AI Foundry platform alongside third-party models from NVIDIA, Google, Microsoft, and Stanford AIMI. The platform operates on HIPAA-ready infrastructure with SOC 2 Type II and HITRUST e1 certification. HOPPR Forward Deployed Services provides teams with clinical workflow expertise and machine learning support to adapt models to specific data and use cases.
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Industries
Company Size
11-50
Company Stage
Series A
Total Funding
$31.5M
Headquarters
Chicago, IL
Founded
2019
Find jobs on Simplify and start your career today
We update HOPPR's jobs every few hours, so check again soon!Browse all jobs