How an IIT Graduate Built Mednaath to Make Every Phone Call Intelligent and Inclusive
Nitish Kumar stood in a Korean office, unable to communicate. The IIT Ropar graduate had just moved to South Korea, leaving behind a successful career leading sales and marketing at Tata Motors. But now, in a foreign country where he couldn’t speak the language, he was experiencing something millions face daily—the crushing isolation of language barriers.
The problem wasn’t just personal. During his time at Tata Motors, Nitish had witnessed enterprises struggling with call intelligence and contact-center inefficiencies. Customer service teams drowned in high call volumes with no way to extract meaningful insights. Enterprises lost deals because they couldn’t communicate effectively across languages. Governments couldn’t serve diverse populations adequately.
Now in Korea, he saw the problem on steroids. Businesses wanted to go global but couldn’t handle multilingual customer support. Government services excluded non-Korean speakers. The existing solutions—human interpreters, clunky translation apps, or AI add-ons—were all inadequate. They were slow, expensive, unreliable, or couldn’t handle the real-time demands of phone conversations.
Nitish faced a daunting challenge: build AI-powered voice translation that worked at telecom scale, in real-time, with enterprise-grade reliability. He had to compete against tech giants with unlimited resources while solving technical problems that had stumped the industry for decades. Most people would have given up. Nitish decided to build Mednaath.
The Turning Point
The early days nearly broke him. Nitish and his team built their first prototypes with excitement, ready to revolutionize voice communication. They failed spectacularly.
The AI translations were clunky. The latency was unacceptable—conversations felt like talking through molasses. Worst of all, when they tried to integrate with legacy telecom systems used by enterprises and governments, everything fell apart. The systems couldn’t handle the load. The reliability was nowhere near what customers expected. Their prototypes worked in the lab but failed in the real world.
“We underestimated how difficult it would be to integrate AI seamlessly into legacy telecom systems,” Nitish recalls. “Our initial prototypes failed to deliver the low-latency and reliability customers expected, forcing us to rebuild our architecture from the ground up.”
The failure was devastating. They’d spent months building something that didn’t work. Investors were skeptical. The team was exhausted. But Nitish saw something others missed: the failure revealed exactly what needed to be fixed.
Instead of adding AI as an afterthought on top of existing systems, they needed to integrate it directly at the network level. They needed to build telecom-grade infrastructure from scratch—designed specifically for real-time AI translation and call intelligence. It meant starting over, but with a fundamentally better approach.
The breakthrough came when they achieved what seemed impossible: ultra-low latency translation with enterprise reliability, integrated directly into telecom networks. Conversations flowed naturally. The AI understood context, nuance, and industry-specific terminology. And remarkably, the platform could go live in a single day—no months-long implementations required.
The Strategy
Nitish’s strategy was deceptively ambitious: don’t just build another AI tool—rebuild the infrastructure of voice communication itself.
Deep Integration, Not Add-Ons
While competitors built AI services that sat on top of existing phone systems, Mednaath integrated directly at the network level. This deep integration delivered unmatched accuracy, ultra-low latency, and enterprise-grade scalability that traditional AI tools couldn’t match. Every phone call became intelligent by default, not as an optional feature.
Telecom-Grade Reliability at Scale
Mednaath didn’t just need to work—it needed to work with the same reliability enterprises expect from their phone systems. That meant 99.99% uptime, the ability to handle millions of simultaneous calls, and seamless integration with legacy infrastructure. Nitish built the platform like telecom infrastructure, not like a startup app.
Global by Design
From day one, Mednaath was built for a global audience. The platform now supports 150 languages with telecom-grade availability across the world. This wasn’t an afterthought—it was the core mission. Every enterprise, government, and individual should be able to communicate seamlessly, regardless of language.
Same-Day Deployment
While enterprise software typically takes months to implement, Mednaath could go live in a single day. This speed became a massive competitive advantage. Enterprises could test, validate, and scale without long procurement cycles or complex integrations.
Listen, Adapt, Iterate
Nitish embraced his own advice to founders: “Stay obsessed with solving a real problem, not with perfecting your original idea.” He listened deeply to users—enterprises struggling with multilingual customer support, governments trying to serve diverse populations, contact centers drowning in data. Each conversation shaped the product, making it more useful and more essential.
The Results
Today, Mednaath has achieved what once seemed impossible: real-time voice translation and call intelligence at global telecom scale.
The platform now supports 150 languages, making it one of the most comprehensive voice AI solutions in the world. Enterprises and governments use Mednaath to eliminate language barriers on phone calls, enhance productivity with call intelligence, and modernize operations through AI-powered contact-center solutions.
The impact is transformative. Customer service teams that once struggled with language barriers now serve global customers seamlessly. Government services that excluded non-native speakers now provide inclusive support. Contact centers extract actionable insights from every conversation, improving efficiency and customer experience.
What makes this achievement remarkable isn’t just the technology—it’s that Mednaath delivers telecom-grade reliability at scale. The platform handles millions of calls without breaking, maintains ultra-low latency that makes conversations feel natural, and integrates seamlessly with systems enterprises already use.
Nitish’s vision for the next 3-5 years is even more ambitious: “We aim to become the global standard for real-time voice intelligence by deeply integrating AI into telecom networks across every continent. We envision enabling truly barrier-free communication for billions of people—where every phone call, in any language, is instantly understood and enriched with actionable insights.”
He’s building infrastructure for the future—where intelligent voice communication becomes as universal and reliable as electricity. Where language is never a barrier. Where every conversation delivers insights that drive action.
