Unboxing AI

Dr. Vidur Mahajan:
Good morning, good afternoon, good evening again—depending on where you are in the world. As I wait for my guest to turn on their camera, my name is Vidur and I’m the Chief Executive Officer at CARPL.ai. This is the Unboxing AI webinar series by CARPL—episode number, believe it or not, 53. We’ve been doing this for almost 53 weeks in a row.

Now, if you don’t know what the Unboxing AI webinar series is—well, how did you even get here? But seriously, each week at CARPL we invite a friend, collaborator, partner, customer—someone super smart—to share their views, discuss their challenges, and answer your questions.

Today, we are very lucky to have our dear friend Vijay Ramanathan with us. We’ll dive into his background shortly. And if you don’t know what CARPL is, we’re your friendly neighborhood AI platform, helping you connect with an entire ecosystem of amazing AI companies. Some help you auto-report scans, some triage stroke CTs, others read prostate MRIs—you name it. We bring this ecosystem of clinical radiology AI into your workflows through a single user interface, a single data channel, and a single procurement path—allowing you to build, test, deploy, and monitor all these solutions within your workflow.

With that, I’d like to welcome our guest today: Vijay Ramanathan. Vijay, thank you for joining—means a lot.

We recently announced our partnership with RamSoft, and Vijay is the CEO and Co-Founder of RamSoft. He co-founded RamSoft 30 years ago when he was just 17—or maybe even younger, Vijay, you look younger! He founded it with his father, Dr. Ram. That’s where the name RamSoft comes from. At the time, Vijay was pursuing his BSc in Computer Engineering at the University of Waterloo, where he and his brother—who I may say is much smarter than most of us—Shiva, created the first version of RamSoft. They didn’t even call it PACS back then, just “Medical Image Management Software.”

Today, he leads the vision for PowerServer—RamSoft’s flagship cloud-based RIS/PACS platform—among many other accomplishments. But the one I’m most fond of: Vijay attended his first RSNA at 17. Do they even let17-year-olds in?

Vijay Ramanathan:
Technically, the official RSNA rules require you to be 16. So yes, I was officially legal. My brother Shiva, during his first RSNA, actually had to bend the rules—he was 15 at the time and turned 16 during the event!

Dr. Vidur Mahajan:
That’s amazing. So both of you guys celebrate your birthdays during RSNA every year?

Vijay Ramanathan:
Exactly. Since my first RSNA at 17, the majority of my birthdays have been in Chicago at RSNA.

Dr. Vidur Mahajan:
Beautiful weather in Chicago, I must say! Also, just so everyone knows, Vijay’s birthday is on December 2nd. If you’re attending RSNA this year, you’re now obligated to wish him—and maybe even buy him a gift!

But seriously, take us back—what was RSNA like back in1994? Was informatics even a thing?

Vijay Ramanathan:
Radiology in 1994 was very different. PACS was a theoretical concept. The DICOM standard that we know today wasn’t formalized until 1998. So back then, you were working with software that predated DICOM. PACS was more a dream than a reality.

What we did have were early teleradiology software programs. And the internet? It technically existed, but no one really had access to it. We had CompuServe and America Online with dial-up connections.

RamSoft was one of the first companies—globally—not just in medical software—to launch a website. I manually wrote HTML as a teenager. There were no tools. Just me coding a website from scratch and putting it online.

Dr. Vidur Mahajan:
Wow. I got my first computer in ’96, internet in ’97—and we had to pay for both phone and data. If I got more than 1 kbps, I thought I was on fire. Two days to download a song!

Vijay Ramanathan:
Exactly. When we started, we were essentially doing frame grabbing—taking pictures of ultrasound or X-ray images. We used what we jokingly called “camera-on-a-stick.” A camera pointed at a lightbox where the film was displayed, and we’d save that image to a PC.

There was no CR back then. Though, in the ’80s, my father—Dr. Ram—was at Picker and led the team that developed the first mass-market digital chest X-ray machine. That equipment was installed in major hospitals all over the world.

But there was no way to extract images digitally—no DICOM. So we’d take pictures of screens. BMPs, JPGs—poor quality. But that’s all we had.

Dr. Vidur Mahajan:
That’s a fascinating origin. Let’s talk about resistance—what was it like trying to sell “PACS v0”? Were there naysayers? And how does that compare to AI today?

Vijay Ramanathan:
Absolutely—tons of resistance, all very justified. The biggest problem was lack of standards. DICOM came in 1998, but it took another five years for vendors to upgrade and for it to become useful in the field.

Radiologists didn’t trust PACS. A common concern was, “Who’s going to hang my films?” Radiologists were used to assistants prepping massive rotating lightboxes with 20–30 cases—including priors. PACS didn’t replicate that.

We had to develop hanging protocols, solve for priors still being on film, and get buy-in from private radiologists, outpatient centers, and ER teleradiologists—our early customers.

One thing we’ve always believed—thanks to my dad—is that healthcare should serve everyone. We don’t treat small customers any differently. Everyone deserves the same tools.

Dr. Vidur Mahajan:
And that carries over to AI. We need to democratize it—just like you did with PACS.

Vijay Ramanathan:
Exactly. AI must be available to everyone—not just big academic hospitals. If AI only helps Mass General, we’ve failed. Only when more than 50% of radiologists worldwide use AI can we say we’ve succeeded.

Dr. Vidur Mahajan:
Couldn’t agree more. And ironically, it’s often harder to convince specialists at academic centers. AI has more impact on general radiologists or ER physicians.

Vijay Ramanathan:
Right. AI is especially impactful in emergency settings—where the radiologist isn’t immediately available. That’s where it can shine.

Dr. Vidur Mahajan:
Let’s talk about PowerServer and OmegaAI. What’s the difference?

Vijay Ramanathan:
PowerServer is our flagship cloud-enabled RIS/PACS platform. It’s used by thousands of radiologists at hundreds of sites every day.

OmegaAI is our next-gen, fully cloud-native platform. It’s designed to evolve constantly. New features are instantly available to all users. And AI is the main reason we built it. AI changes fast—what’s good today is outdated in 3 months.

OmegaAI is our way of future-proofing the platform. We see most of our customers moving to it within the next few years.

Dr. Vidur Mahajan:
How do you address hesitancy from larger health systems about cloud and multi-tenancy?

Vijay Ramanathan:
Every tech transition has apprehension. From film to PACS. From on-premise to hosted. From single-tenant to multi-tenant cloud.

That’s our challenge to solve. We’ve been doing this for30 years. In a few years, people won’t even remember the challenge—they’ll just enjoy the benefits.

Dr. Vidur Mahajan:
Agreed. There’s a great question from the chat—from BS. They ask: unless equipment becomes democratized, how can AI reach everyone?

Vijay Ramanathan:
Great point. AI will help make equipment cheaper. Today, equipment differentiation lies in the embedded software. If we shift intelligence from equipment into the PACS—with AI as the brain—we can standardize, lower costs ,and make devices more accessible.

More vendors, lower costs, broader access. That’s what happened with DICOM. That’s where we’re going.

Dr. Vidur Mahajan:
So PACS becomes the smart layer. CARPL then becomes a window into the world’s AI.

Vijay Ramanathan:
Exactly. And with zero-click AI, radiologists just open a study, and AI insights are already there—visible when needed, invisible when not.

Dr. Vidur Mahajan:
Final question from Srinivas: Are your tools focused on specific body parts, like just chest?

Dr. Vidur Mahajan:
Great question. We’re an AI platform. Vijay’s team at RamSoft provides PACS. We integrate 175+ AI models from third parties—covering all kinds of body parts and specialties. It’s a platform within a platform—like inception.

Vijay Ramanathan:
And it’s all integrated into the workflow. Open a study in PowerServer or OmegaAI, and AI results just appear—no clicks required.

Dr. Vidur Mahajan:
Thank you, Vijay. And thank you to everyone who joined. This has been one of our most widely attended webinars. See you all next week. Vijay—means a lot.

Vijay Ramanathan:
Thank you, Vidur. Appreciate it.

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