The Road to Real-World Impact: A Conversation with Dr. Khan Siddiqui, CEO of HOPPR
With the close of its Series A funding round, HOPPR is entering a pivotal new chapter — one focused not on invention, but on execution. In a conversation with HOPPR CEO and co-founder Dr. Khan Siddiqui, we discussed what this funding milestone enables, why timing matters, and what it really means to build AI that works in the real world.
Watch the full video above for the full interview.
CHICAGO, IL – July 8, 2025
From Vision to Execution: What made this the right moment to raise Series A funding?
“Funding is all about creating inflection points in a company’s journey,” Dr. Siddiqui says.
HOPPR’s early stages were focused on proving what many considered impossible: building large-scale foundation models for medical imaging to be served and fine-tuned within a developer platform, and with data contracts at scale. This means serving hundreds of thousands of images for multiple customers at a time with no performance issues.
To do this successfully, we needed a significant amount of funding to build the infrastructure, technology, and team to make it happen. Our funding enables us to secure data partnerships, train models across diverse conditions, and create a platform that supports rapid fine-tuning and deployment.
Now, with product-market fit validated and strong interest from health systems and channel partners, HOPPR is ready to execute on our vision.
What Does “Execution at Scale” Means for HOPPR?
HOPPR was started with the premise that building AI point solutions is probably obsolete. Paving the way for the future for HOPPR requires a single model that can actually assess multiple different conditions at the same time. Then, rapidly build and train a large set of models based on a large corpus of data, allowing for fine-tuning on smaller sets of data for specific tasks or use cases. Then, integrate the findings coming out of these models into existing systems and user interfaces.
“We didn’t want to build a third application that radiologists have to look at to understand what is happening. We want to enable their existing systems—PACS, RIS, EHRs—that require image-based results to become AI enabled.”
Executing this successfully on the technical side means running hundreds of thousands of models in parallel, performing inference on terabytes of imaging data, and delivering insights directly into systems that clinicians already use.
For Dr. Siddiqui, execution at scale is both a technical and a commercial imperative.
On the commercial side, it means focusing on channel partnerships and work with large enterprises who have scaled in volume and people who would use the solution as well as other partners with big deployments in health systems, hospitals, and radiology practices.
When one of your customers is responsible for 16% of global imaging volume, you need to be ready to deliver –– at that level, from day one. That is the meaning of execution at scale.
What Should We Expect from HOPPR in the Next Year?
An AI Development Platform for Medical Imaging Built for the Real World.
HOPPR’s approach to AI moves beyond point solutions. Instead of building one-off tools, the company is focused on creating a scalable foundation model platform—one that can adapt to new data, support application development for a wide range of clinical tasks, and be integrated into existing workflows.
At the core of this strategy is the ability to pre-train on large, diverse datasets and then fine-tune rapidly for specific conditions using smaller, localized data. That means faster deployment, greater flexibility, and real-world clinical relevance—without having to start from scratch each time.
What’s Next: Making It Available for Everyone
To date, HOPPR has worked closely with select early partners to refine and validate its approach. But now, the company is preparing to expand access more broadly.
“We’ve been working really hard to build something special. You’ll see some amazing things coming out—especially around RSNA. We’ll be making the platform available to everyone very soon.”
A Mission That Runs Deep
For Dr. Siddiqui, HOPPR’s mission is personal. He likes to solve problems while creating social impact at the same time.
“My wife is a radiologist. Many of my close friends are radiologists. Watching them burn out—that’s a huge motivator of what we are doing to AI-enable existing workflows and products rather than building another user interface, another application somebody has to look at, and why we want to partner in that manner.”
By focusing on AI that enhances, not replaces, clinical decision-making—and by integrating into the systems clinicians already use—HOPPR aims to reduce burnout, increase efficiency, and improve care at scale.
“We’re trying to create a fork in the history of radiology. That’s the kind of change we believe is possible.”
With funding secured, a foundation model platform ready, and clinical partnerships expanding, HOPPR is poised to show what AI can really do when built with purpose, scale, and usability in mind.
“Now it’s time to show what AI can do in the real world. And we’re just getting started.” - Dr Khan Siddiqui, MD, HOPPR Co-founder and CEO.
About HOPPR
HOPPR is the leading infrastructure platform for building, fine-tuning, and deploying AI foundation models and applications in medical imaging. Purpose-built for developers and PACs vendors, HOPPR offers secure tooling and access to curated data with known provenance, enabling the rapid development of clinically ready AI applications. With integrated quality management systems and support for marketing authorization, HOPPR bridges the gap between innovation and real-world deployment, helping transform diagnostic workflows and improve patient care globally. For more information, visit www.hoppr.ai.
