Fractal’s India Dilemma: The Missing Demand Engine In Enterprise AI

Fractal Analytics’ revenue is largely global in nature with US contributing the highest, despite India being its innovation hub over the past 25 years

Cofounder and group CEO Srikanth Velamakanni believes the scale of spending in US markets is simply much higher than India

Through its IndiaAI Mission mandate and a focus on LLMs, Fractal Analytics is doubling down on sovereign, large-scale AI model development in healthcare and beyond

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India’s artificial intelligence market is to reach a $126 Bn opportunity by 2030, with a potential GDP impact of $1.7 Tn by 2035. As per Inc42’s Bharat AI Startups Report, live AI use cases are growing particularly rapidly for enterprise use-cases, with enterprise AI is projected to grow from $11 Bn in 2025 to $71 Bn by 2030, roughly a 6.5x surge. 

This fundamental shift was equally evident at the India AI Impact Summit 2026, where enterprise presence was strong and the major AI tech giants all announced partnerships to propel this adoption even further. 

This has essentially flipped the script for existing AI-native companies like Fractal, where India is a secondary contributor to the revenue mix, and where the main focus remains the US market. 

Fractal Analytics, which went public earlier in February, has positioned itself as India’s first homegrown pure-play AI company to hit the stock markets. But the company’s growth story tells a more complicated truth about where its growth has come from. 

Nearly two-thirds of its revenue comes from North America. Europe contributes roughly a fifth. The Middle East and Australia are rising. India, despite being its largest innovation hub, is not a meaningful revenue driver.

The reason, according to cofounder and group CEO Srikanth Velamakanni, is simple: the scale of spending in US markets is simply much higher than India. “Most Indian companies are spending less than a few million dollars a year on AI. That is not enough as a source of revenue for Fractal Analytics,” he told Inc42 days after Fractal Analytics’ listing.

Contrasting this with the US, where the AI market is expected to expand from $54 Bn in 2024 to $319.32 Bn by 2032. For Fractal Analytics, which focuses on large enterprises with substantial AI budgets, even marginal performance improvements in such markets can translate into massive business impact.

As per its pre-IPO disclosure, Fractal’s net profit for H1 FY26 declined 2.7% to ₹70.9 Cr from ₹72.9 Cr in the corresponding period last year, on the back of higher tax outgo during the period under review. But operating revenue rose 19.8% to ₹1,559 Cr in H1 FY26 from ₹1,300.1 Cr in the year-ago period. 

Incidentally, the stock closed its first trading session at 6% below issue price, which shows that perhaps the Indian public market investors haven’t quite come to terms with the company’s revenue distribution and its potential to unlock domestic revenue. 

As of February 20, Fractal’s shares were trading at ₹860.50 as against the issue price of ₹900 at the upper band. 

US Vs India: The Spending Gap

This context shapes the company’s operating model. 

Fractal Analytics is built around what it calls Must Win Clients (MWCs), which include over 100 Fortune 500 companies, resulting in a concentrated revenue base. The top 10 clients contribute 54% of segment revenue. 

In FY25, the company reported a net revenue retention (NRR) of 121.3%, alongside 25.9% year-on-year revenue growth and a return to profitability. Healthcare and life sciences continues to be the primary growth engine, even as retail and CPG are expected to grow steadily. BFSI, the sector of focus when the company was founded, trails behind even as its share of revenue grows.

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This enterprise-focused strategy also explains the company’s geographic revenue mix. 

Today, while Indian enterprises are investing in AI, Velamakanni argues they are not investing at the level required to drive structural transformation. The hesitation, he says, is economic in nature. High capital costs and relatively cheaper labour have historically shaped India Inc.’s decision-making.

“Indian enterprises tend to choose what appears cheaper, that is people over capital,” Velamakanni said. 

Can GCCs Fill The Vacuum? 

That level of investment is not always meaningful for companies like Fractal Analytics, which have spent years and invested millions in R&D and their own AI models. The ROI has to be faster. “When you make even a small improvement in a large, scaled organisation, the impact can be massive because of the scale at which they operate. That is where both meaningful outcomes and meaningful revenues align,” he added.

As a result, Fractal Analytics’s India strategy is less about serving domestic enterprises directly and more about engaging with Global Capability Centres (GCCs) operating in the country. 

GCCs are company-owned offshore centres that handle core functions such as R&D, IT, engineering, and innovation. With over 1,800 centers, India is fast emerging as a major global hub for GCCs. Four years ago, as GCCs began evolving from cost-focused back offices into innovation and R&D hubs for multinational corporations, Fractal Analytics started working closely with them.

“Earlier GCCs were just back offices doing operations work. Now they are innovation and R&D centers for big companies,” Velamakanni noted. “This shift allows Fractal Analytics to solve high-value, global problems from India, even if the contract value originates overseas,” said Velamakanni.

“Earlier GCCs were just back offices doing operations work. Now they are innovation and R&D centers for big companies,” Velamakanni noted. “This shift allows Fractal Analytics to solve high-value, global problems from India, even if the contract value originates overseas,” said Velamakanni.

India As An Innovation Hub

As of March 2025, Fractal Analytics employs over 5,200 people in India, primarily across AI, engineering, and data science. 

“India’s talent pool is exceptional, and our entire R&D engine is based here. Access to deep, high-quality AI talent is Fractal Analytics’s secret sauce. Much of this capability remains under-recognised globally. In the US, hiring similar talent would mean competing directly with companies like OpenAI and Anthropic,” Velamakanni said. 

“In India, however, that depth of expertise is more accessible. We strongly believe that sustained advantage in AI comes from the quality and depth of talent and that is where India truly stands out.”

The Indian team at Fractal Analytics has given birth to a lot of intrapreneurs as well, who have gone on to build platform bets like Asper.ai and Analytics Vidhya, and previously incubated healthcare AI leader Qure.ai, as Inc42 covered in the pre-IPO deep-dive into the company, which detailed the 25-year journey and the key moments that shaped its current AI stack. 

Some businesses have been divested, for instance, the AI-for-investing platform, Theremin.ai, which operated under QI Capital. Others have been integrated into the Agentic AI platform from Fractal Analytics called Cogentiq, with several of its capabilities originally developed within these incubated startups.

Even as Fractal waits for the Indian enterprise market to mature and increase AI adoption, the market is key for the company’s plans to create a global AI company from India. 

For example, Fractal Analytics has been selected under the IndiaAI Mission to build the nation’s first Large Reasoning Model (LRM). This initiative aims to develop sovereign, specialised AI models for healthcare, STEM, and education with a 70 bn-parameter model expected this year. This is obviously a model that can be exported to other geographies and could become a first of its kind healthcare LLM that has India at its heart.   

The Next Phase For Enterprise AI

On the sidelines of the India AI Impact Summit 2026 this week, Fractal Analytics launched the next iteration of its healthcare reasoning model. Called Vaidya 2.0, this model will support healthcare related workflows such as emergency and patient assistance, as well as a symptom checker. 

“AI is becoming increasingly powerful and geopolitical, so we clearly need sovereign frontier models that we can keep within India’s control. At Fractal Analytics, we are building a large reasoning model for healthcare,” said Velamakanni.

Of course, this is just the beginning for Fractal. As the group CEO told us, it’s not just about building applications — deployment and usage matter just as much. When solutions are deployed at population scale, everything changes. “If we build a strong baseline healthcare model and roll it out across India, within a year or two we could have one of the best healthcare AI models in the world not just in benchmarks, but in real impact.”

And healthcare is just the beginning. 

In an earlier conversation with Inc42, cofounder and CEO Pranay Agrawal claimed enterprises looked for models that were services-based, and they had the patience to wait for new tech, but that’s changed now. Now companies need to show speed in adopting new tech. This is where Fractal’s Agentic AI route is expected to address some of the pain points, especially in terms of the productisation of services. 

For Fractal, which has seen over two decades of the Indian enterprise tech maturity cycle, the fundamental idea remains the same — deliver better outcomes for enterprises, but the mechanism has evolved and today everything hinges around AI. “True transformation requires AI to be deeply embedded at the core of every workflow,” Agrawal told us. 

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