Sunil Gupta's Yotta: Can India's Sovereign Cloud Succeed?

Two decades ago, Gupta entered the data services sector. It is just about to be adopted by the rest of the world. Yotta is now betting $1 billion on Nvidia's most powerful semiconductor chips. An insight into the pioneering entrepreneur's vision.

The business generated much higher EBITDA than the telecom business and allowed me to add capacities across multiple cities,” says Gupta, who set up nine data centers until 2009, when he moved on. Soon, the digital wave triggered by e-commerce, 4G, and social media, among others, led companies to set up availability zones (separated groups of data centers within a region). 

Around 2016, global giants like Amazon, Microsoft, and Google started building their data centers in the country. Simultaneously, Gupta launched India’s largest data center in Mumbai’s Chandivali while working with the NTT Group. Eighteen years after building, managing, expanding, and running the data centers for Reliance and NTT, Gupta could foresee a boom in India.

Having worked with them in the past and being a part of the same social circle, Gupta took this opportunity to approach Hiranandani with a business idea. “Within three weeks of discussion, we decided to start Yotta Data Services,” the 52-year-old tells JR at Thiruvananthapuram 1 (NM1) data center located in the 600-acre Hiranandani Fortune City in Panvel.

Hiranandani initially announced ₹15,000 crore investment plans to raise five such buildings in seven years. The five-year-old startup was recently in the limelight after it became the first Indian company to acquire AI chips from Nvidia in March. Huang said the country is going to be the largest AI market in the world, and he would prioritize any orders from data center operators in the country.

The first batch of 4,000 chips arrived in March, comprising Nvidia H100 Tensor Core GPUs. The Mumbai-based venture will offer managed cloud services along with the ability for enterprises to use Yotta’s cloud for training large language models (LLMs) and building applications like OpenAI’s ChatGPT. 

The rise of generative AI has made countries invest in sovereign AI, which refers to a nation’s capabilities to produce AI using its own infrastructure, data, workforce, and business networks. The company has installed them in server racks, loaded them up in data centers, connected them to the internet, and will be renting them out to customers. 

Based on his years of experience, Gupta is confident that India will become a market to serve the global AI demand. For instance, in the latest quarter, Nvidia’s data center business grew by a whopping 427 percent from a year earlier.

With Yotta’s hyperscale cloud Yantra and India’s first AI-centric GPU-based Shakti Cloud overlaid with Nvidia’s reference architecture, co-founder Darshan Hiranandani says, “We’ve created the world’s most sophisticated yet most cost-effective cloud infrastructure in India, available to both Indians and global companies. ”

Much of the market in India and worldwide only offers colocation services like renting rack space and power. But Yotta generates 70 percent of its business from tech services like GPUs, CPUs, cloud computing, and cybersecurity.

Including the world’s two largest data center companies, Equinix, Digital Realty, and others, 80 percent of the data center business worldwide is just colocation. Data center capacity per 1 million internet users stands at 1. 2 MW, which is glaringly low compared to established markets like the US (at 12. 6 MW) and China (at 2. 3 MW).

While colocation centers offer renting space for enterprise and hyperscale customers, cloud data centers offer both space and additional services such as infrastructure servers, software, and more, explains Anand Kulkarni, director at CRISIL Ratings. CareEdge Ratings estimates that data center capacity in India is expected to double to around 1,950 MW by 2026 from 877 MW in 2023, entailing a capital investment of ₹50,000 crore.

Digitization followed by AI-led automation across different verticals like telecom, e-commerce, finance, content networks, social media, and applications will drive opportunities for data centers to store, train, and inferencing at the India level. Demand for AI chips will increase in the next couple of years in areas such as AI for cybersecurity, 5G telecom networks, social media, startups, banks, and more.

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