Shaping the Future of Healthcare and DeepTech with AI

Shahid Akhter, Consulting Editor, FEHealthcare, spoke to Hitesh Ganjoo, Founder & CEO, Iksha Labs, on how AI is driving a fundamental shift in healthcare and DeepTech—enabling patient-centric solutions, expanding market potential, overcoming adoption barriers, and building scalable innovations for the future.

 

When you look at the rise of AI today, how do you assess the market potential? Do traditional rules of measuring markets still apply in this space?

We used to ask traditional business questions like if there's enough space for everyone and how big the market is. However, I believe those traditional rules do not currently apply to AI. No one really knows the full potential yet. Companies like OpenAI talk about AGI, while others discuss ASI. What we are witnessing is not just a new technology but a fundamental transformation at every level. It’s not simply a matter of selling one solution to a hospital; rather, while we offer a solution, we are also proposing changes across multiple interactions. New segments and categories are emerging rapidly, and the boundaries between them are fading as one of the most transformative technologies in human history unfolds before us. An alternative approach would be to approach the market from a solution-first perspective.

When we approach hospitals, we find that most are unaware of the AI capabilities available today. This is eye-opening for us. Many players are working in this space, yet hospitals still don't know about these tools. For example, when we gave a demo to a hospital recently, they were surprised to learn that they could now automatically schedule appointments through a voice agent integrated with their system. This is a basic function from a technology perspective. There is a lot of distance to cover in terms of understanding capabilities, and it’s a journey we must take together.

 

Do you believe the AI market holds massive potential and will continue to expand rapidly in the future?

If you take radiology as an example, or even robotic surgery, each of these fields is a vast world. In radiology alone, the computational needs are different. For instance, consider MRIs. The MRI field is vast, and often only one area needs to be scanned in detail. People specialize in two or three subsets within the field, and that specialization opens new possibilities. Even doctors or AI professionals stumble upon new avenues unexpectedly and realize that there's a much larger path ahead. The opportunities appear endless. 

A market exists, but it depends on what you are focusing on. For example, we are currently collaborating with hospitals to improve patient experience; that alone is a billion-dollar opportunity. However, suppose the same doctor then asks if an AI agent can help analyze MRI scans. The answer is yes, and that opens a new market entirely. AI agents don’t have limited capabilities; they can adapt to multiple industries. So, the key point is that there is a large gap: we need to prioritize solutions rather than focus solely on technology.

 

Can an AI agent handle multiple roles for a doctor?

Yes. Currently, we are working with a doctor where the same AI agent is doing three tasks: handling all incoming patient queries (including phone calls), managing the calendar and previous patient history to suggest next steps for the doctor, and acting as a patient counsellor by sending reminders for follow-up care. The AI is performing the roles of an assistant, a receptionist, and a patient counsellor. The current capabilities are remarkable.

 

When did you start Iksha Labs, and what are its key focus areas within the DeepTech space?

This project is my second venture. My first venture started in 2013–14, focusing purely on healthcare and enabling professionals to keep up with the latest in their field. In healthcare, we saw doctors and hospitals struggling to adopt technology meaningfully. AI could directly improve patient experience, diagnosis, and workflows. Finance and insurance, on the other hand, are full of process inefficiencies where AI automation reduces costs and risks. We chose these sectors because the impact is immediate and measurable, providing strong opportunities to build trust and credibility.

Iksha Labs is a deep-tech solutions company, and our core strength is building intelligent AI agents and workflows. We focus on sectors such as healthcare, medical devices, finance, insurance, and robotics. We aim to solve complex and critical problems that traditional technology cannot address. By combining deep domain expertise with AI, computer vision, robotics, and advanced automation, we create scalable solutions that improve efficiency and transform industry operations.

 

How has the journey been so far with Iksha Labs?

The journey has been rewarding. One of our core principles was to build a bootstrap version first, to ensure product fit and that everything works smoothly. This approach paid off, as we have some trusted partners who have worked with us since the beginning and now trust us to handle their product end-to-end. For example, one of the fastest insurtech companies in the US has partnered with us for over five years. We have built their product from start to finish. Over the past four to five years, we have played a key role in developing an advanced image-guided surgical navigation system, initially for the Japanese market and now scaled globally. This technology is used by surgeons worldwide, and our expertise was essential for its success. Since then, our scope has only grown, powering innovations globally and developing our own in-house AI for organizations solving real-world problems. Through our journey, we have identified three major barriers to AI adoption: cost, trust, and compliance. We see these not as challenges, but as opportunities to address head-on.

 

Is it always possible to develop solutions locally, given the cost differences between domestic and imported technology?

It is not always possible if only the private sector is involved. Significant support from the government is essential. For example, the majority of any tech startup’s infrastructure costs—about 80%—are cloud expenses, often with companies like Amazon and Google. The government's cloud initiatives are positive steps, but awareness and adoption need to scale further so every company knows what's available.

 

How satisfied are you with the government’s support for startups, and what opportunities do you see for new entrants in this space?

It is not so much about handholding as it is about awareness. Startups often are unaware of the support systems in place. Many opportunities become apparent only after research and inquiry. Clearer and more predictable communication about these schemes, whether for funding or technology access, is necessary. For example, when we considered a collateral-free finance scheme for new technology, it was difficult to assess if we were truly eligible.

The support exists, but the information is often inconsistent. Clearer and more transparent processes would greatly help startups like ours to move faster. There's never been a better time than today to seize opportunities. Everywhere you look, especially in healthcare, AI has the potential to disrupt and improve every aspect of the system. Previously, our focus was solely on orthopedics and radiology; however, AI can now impact every aspect of the healthcare system. We are heading into an era of dramatic transformation. This is an opportunity for everyone. This kind of foundational shift happens once in a generation; the time to build is now.