‍Tell us about 5C’s technology and what makes it unique?

5C is a deep tech HealthTech company based in Bangalore. We’re building products at the intersection of AI and medical imaging. At our core, we believe AI can revolutionize both reactive diagnostics—such as identifying a fracture—as well as proactive diagnostics, including things like predicting dementia or metabolic risk.

What makes us distinct is our data foundation. We own the largest repository of annotated medical imaging data in the world. That means we’re not just building AI models—we’re training them on the most robust, diverse, and enriched dataset in the industry. Today, we report nearly 2% of all medical scans in India, and we’re only getting started.

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Can you walk us through how you built the foundation for 5C?

When we started in late 2017, most people were just beginning to explore convolutional neural networks for imaging purposes. The technology was promising, but I noticed a gap: models were being trained on tiny datasets—250 images, maybe. Yet real-world models need millions.

That was the weak signal I picked up on. Data wasn’t just important; it was going to be the moat. So for the first four to five years, we focused entirely on building our data infrastructure. We launched a teleradiology business to generate high-quality scan data and built the world’s largest medical image annotation team—soon to hit 100 full-time annotators. That gave us not only a massive volume of data, but deeply enriched, labeled datasets that could power truly robust AI.

And because we sit directly in the flow of clinical work, we can continuously validate and deploy our models. Our radiology AI product, Bionic, is now one of the most widely used in the world.

I remember Celesta Founding Partner Sriram telling me once that the “deep” in deep tech refers to the multiple layers of technology you need to build before value emerges. These layers are painful and non-revenue-generating at first. But once they’re built, they become your defensibility. That has been our strategy exactly. 

At 5C, we’ve built the data lake, the scalable annotation engine, the model training architecture, and the deployment layer—all integrated. It’s not fast or easy, but now we’re reaping the benefits of that foundation.

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What are the core problems you’re solving for users in the medical space?

The core issue is the growing imbalance between diagnostic demand and the supply of medical imaging specialists. Imaging volumes are exploding—driven by aging populations and rising chronic conditions. But the number of radiologists is growing only 3–4% per year. It’s not sustainable.

In India, for example, diagnostics are growing 16% year-over-year. In the U.S., burnout is rampant—over 20% of radiologists report feeling overwhelmed post-pandemic. This is where AI plays a transformative role. 

We believe 80% of the work for 80% of scans can be automated. That’s what we’re building toward: a unified radiology vision model that can automate high-volume, low-complexity scans and free up radiologists to focus on complex, high-value patient and diagnostic work.

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What is your vision for 5C in the long term?

Our mission is to be the medical imaging copilot for every professional, everywhere. Whether you’re using an edge device, a browser plugin, or a cloud PACS system, 5C will be there.

We’re building lightweight tools like a Chrome plugin that can instantly detect abnormalities in chest X-rays. We’re embedding our AI in RAM with device manufacturers. And we’re expanding across imaging modalities—X-ray, CT, MRI—and across use cases from reactive diagnostics to proactive health insights, including fracture detection to brain aging analysis. We are expanding globally to deliver this in emerging and developed markets alike.

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“The models aren’t the hard part—data is. That’s the moat. That’s what we spent years building before writing a single line of AI code.”

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What kind of market response are you seeing so far given the broader AI boom?

We’re seeing an incredible tailwind in clinical adoption. Today, we work with 600 radiologists, and 100% of them believe AI makes them better at their jobs. This is no longer a “man vs. machine” debate. It’s human + machine. AI is helping them achieve turnaround times of 300 seconds per X-ray. That kind of productivity boost is essential.

And that trust opens the door to powerful product-service business models where radiologists validate AI results. It’s a true synergy.

Regulatory is the biggest headwind right now. For example, the FDA hasn’t cleared a single AI-based software medical device in the U.S. this year. That’s a massive bottleneck.

How are you approaching global expansion with so much complexity and variety in regulatory systems?

Our approach is twofold. First, we segment markets based on whether they accept India’s regulatory approvals. For example, the Middle East, Malaysia, and the Philippines are markets where we can move quickly. For the U.S., we’re building a parallel motion around FDA clearance and go-to-market.

Second, we’re not just selling software—we’re operationalizing AI in radiology departments. We provide validated reports, not just AI results. That lets us deliver true teleradiology-as-a-service, with instant, on-demand quality. That’s a massive global opportunity.

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How did you personally get into this space?

I’m a computer science engineer by training. The idea for 5C came while working with the government of Karnataka. I’d visit hospitals and see expensive radiology machines sitting idle. The equipment was there—but there were no radiologists.

This coincided with the rise of advanced CNNs like ResNet. I experimented with models, but they were performing no better than random chance. That’s when it clicked: the models weren’t the problem—data was. That realization shaped everything that followed.

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As an early-stage founder, what does optimal investor support look like for you and 5C?

First and foremost—belief. As a founder, this is 100% of my life. For a VC, I’m a small percentage of a portfolio. That asymmetry is real, and what matters most is having investors who respect and empathize with that difference.

Second, helping founders find market expansion opportunities. Deep tech often looks like a niche at first. Great investors help you uncover the bigger play.

And third is crisis management. When things go wrong, who can you call? Who’s going to huddle with you to find solutions instead of saying “I told you so”? That’s when the real partnership shows.

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What keeps you motivated as a startup founder navigating all the highs and lows?

I try not to dwell on the rearview mirror. What keeps me going is having something to look forward to. A new product launch, a big customer, a new teammate. Even in the toughest moments, just knowing something exciting is around the corner helps me stay focused and motivated.

I once read about people who keep a lottery ticket in their wallet—not because they expect to win, but because it gives them hope. You need that optimism, that next milestone. That’s what sustains me.