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At-scale AI Deployment

Enterprise AI Adoption

By integrating CARPL’s inferencing and orchestration capabilities into your PACS system, end users can leverage over 140 AI applications, enabling enhanced patient care, reduced turnaround times, and improved diagnostic accuracy. CARPL's secure enterprise imaging AI platform provides pre-deployment validation and post-deployment monitoring capabilities, ensuring AI systems perform optimally over time. With both cloud-based and on-premise deployments, CARPL offers adaptable solutions for varied clinical environments.

Want to AI-enable your practice through your existing PACS provider? Contact your local account manager or sales@carpl.ai to leverage the world's most secure and comprehensive radiology AI marketplace.

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User Perspectives

Our Ecosystem

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Testimonials

If you are going to use an AI application, you have to validate it on your data and your workflow. We have been working with CARPL to do that and it has been of great help. We have been doing head-to-head competitions where you have one AI application working against another 2 or 3 or however many you want, and in those comparisons, they're basically competing against each other. So instead of creating a true data-set, what we can do is just see any time one AI says something different than the other, making it much more efficient to utilize.We've seen it reduces ground truthing effort by about 80% which is phenomenal and allows validation at scale.

Nina Kottler, MD

Associate Chief Medical Officer, Clinical AI, Radiology Partners

RUBEE® AI powered by CARPL Platform enables a marketplace ecosystem that helps customers scale up and expand based on their clinical requirements. Besides the marketplace, AGFA HealthCare customers have the flexibility and option to benefit from RUBEE® AI Packages and RUBEE® Integrations depending on their unique AI requirements or choice of AI applications.

Anjum Ahmed, MD

Chief Medical Officer & Global Director of AI, AGFA HealthCare

Establishing a robust AI infrastructure with monitoring tools is key for safe, effective, and scalable AI adoption in radiology. While the current landscape is marked by an overwhelming array of AI-enabled point solutions, the future involves running multiple AI models, even for a single use case. DeepHealth’s partnership with CARPL.ai addresses this very need by creating a unique environment to dynamically run a combination of models and monitor performance and then continuously optimize the best models for specific tasks.

Sham Sokka, PhD

Chief Operating and Technology Officer, DeepHealth

Choosing the right AI solution was our biggest challenge. Many vendors promise monitoring capabilities, but transparency is often lacking. Calculating ROI was also difficult. CARPL helped us test and compare different AI options, leading to a well-informed and confident purchase decision.

While implementation success depends on the tool itself, pre-purchase testing and monitoring are crucial. CARPL excels in these areas, making it a very promising platform. Its value lies in guiding purchase decisions and ongoing monitoring. Ideally, CARPL would become an extension of our practice. The partnership with Philips is exciting, as it could be a perfect fit for Philips customers like us.

Bruno Rocha, MD

Medical Innovation Coordinator, Fleury

We at RadNet and DeepHealth were impressed by both, CARPL's technological and clinical prowess, which made us choose them as our AI platform partner. We are excited to work with them to accelerate the adoption of AI in radiology practices in the US and across the globe.

Howard G. Berger, MD

President and Chief Executive Officer, RadNet

AI pilots can be resource-intensive and expensive, from the decision to pilot through to setting up the necessary AI infrastructure. CARPL has been an exceptional partner in simplifying this process for us at Tan Tock Seng Hospital. Their system enabled us to validate multiple AI algorithms on a single platform, including chest X-ray AI and thyroid AI. CARPL's extensive AI marketplace covers most of our use cases, and their testing module easily generates performance summaries and key metrics like AUC. This has made our validation process both efficient and cost-effective. Their support has been invaluable, and we look forward to advancing our AI projects together.

Alvin Soon, MD

Head and Neck Radiologist, Tan Tock Seng Hospital

The integration of AI results into PACS will increase workflow efficiency and potentially reduce turnaround times for thoracic care. This empowers healthcare providers to make timely and informed decisions, thereby optimizing patient throughput. Thoracic treatment is just the starting point; we are committed to expanding this collaboration to encompass other clinical use cases.

Madhuri Sebastian

Business Lead for Radiology Informatics, Philips

CARPL’s visionary platform is a one-stop solution for all AI innovation requirements. Over the last few years, we have been able to access and test AI solutions on CARPL platform catering to specific clinical and operational needs and have leveraged it for clinical deployment of AI solution as well.

Osvaldo Landi Júnior, MD

Medical Innovation and Data Manager, FIDI

Using a validation platform such as CARPL will help to speed up the deployment of AI models into mainstream use, as well as enable the value of AI to be realized.

Charlene Liew, MD

Co-Chair, AI and Digital Committee, Changi General Hospital | Deputy Chief Medical Informatics Officer, Changi General Hospital | Director of Innovation, RADSC ACP, SingHealth

The recent statement on AI by the world's top radiology associations emphasizes the fact that there should be close collaboration between the developers and users of AI. It also brings to light the importance of validation, deployment and monitoring of AI while being used in clinical practice. I am happy that at RADICLE we already use CARPL for AI testing, deployment and monitoring which ensures that not only do we stick to these recommendations, but also go beyond them.

Leonardo Kayat Bittencourt, MD

Director of RADICLE and vice-chair of innovation, University Hospitals Department of Radiology

The process was made so efficient, that it took me only 20-35 seconds to ground-truth a study.

Kent Hutson, MD

Director of Innovation Clinical Operations, Radiology Partners

We are ecstatic to have clinically implemented AZmed's Rayvolve fracture detection tool through CARPL in our institution. The CARPL team has been extremely helpful, working with our team every step of the way to get this up and running. Further, our radiologists are excited to provide the best care possible for our patients with the integration of AI tools through CARPL.

Navid Faraji, MD

MSK radiology attending and associate program director of radiology residency, University Hospitals, Cleveland

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Unlock the potential of CARPL platform for optimizing radiology workflows

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