Frekil —Scale AI for Medical Scans

Frekil envisions a future where the bottlenecks in medical image annotation are eradicated, accelerating breakthroughs in healthcare AI and life sciences. We exist to radically enhance the way medical imaging datasets are curated and labeled, enabling faster, more precise AI training and clinical validation.

Harnessing advanced artificial intelligence and machine learning, our platform transforms raw medical images into high-quality annotated datasets with unparalleled speed and accuracy. By integrating real-time quality controls and a collaborative, browser-based environment, we empower healthcare teams to deliver FDA-ready data, driving critical advancements in diagnostics, treatments, and medical research.

Our mission is to catalyze innovation in healthcare through technology that unlocks the full potential of medical imaging data. We are building an ecosystem where data annotation is seamless, scalable, and trusted, ultimately improving patient outcomes and advancing the future of medicine.

A Smart Solution to a Complex Problem

We've seen many AI companies tackle healthcare, but Frekil's approach caught our attention. Instead of trying to replace doctors with AI, they're focusing on something equally crucial but less glamorous: making medical image annotation dramatically faster and more accurate.

What's clever here is how they've identified a real bottleneck in healthcare AI development. Medical images need expert annotation before they can be used to train AI models or run clinical trials, and this process has traditionally been slow, expensive, and error-prone. Frekil's platform claims to speed this up by 10x - that's the kind of improvement that could actually move the needle in healthcare innovation.

The Platform's Secret Sauce

We're particularly impressed by Frekil's end-to-end approach. Their browser-based tools don't just make annotation faster; they've built in real-time quality control and consensus checks that ensure accuracy doesn't suffer for speed. For anyone who's worked with medical data, you'll know this balance is incredibly hard to strike.

The marketplace element is another smart touch. By connecting radiology chains with a global network of qualified annotators, they're creating a scalable solution that could handle everything from small research projects to massive clinical trials.

Where This Could Lead

While Frekil is still young (founded in 2025), we think they're onto something big. The FDA approval process for AI in healthcare isn't getting any simpler, and the demand for high-quality annotated medical data is only growing. If Frekil can deliver on their promises, they could become an essential platform for healthcare AI development.

That said, we'll be watching to see how they handle scaling challenges and maintain quality as their marketplace grows. Healthcare is notoriously complex, but Frekil's focused approach and clear value proposition make them one to watch in the YC X25 batch.