Key Highlights:

• The announcement comes during the India AI Impact Summit, underscoring India’s push for sovereign AI infrastructure.
• Neysa.ai raises $1.2 billion, split evenly between equity and debt, in one of India’s largest early-stage tech fundraises.
• Blackstone leads the round, joined by Teachers’ Venture Growth, TVS Capital, 360 ONE Assets, and Nexus Venture Partners.
• Around 20,000 GPUs to be deployed in India, significantly expanding domestic AI compute capacity.

Indian artificial intelligence infrastructure startup Neysa.ai has raised $1.2 billion in a funding round led by Blackstone, marking one of the largest early-stage investments in India’s technology sector. The round includes $600 million in equity and $600 million in debt, with participation from Teachers’ Venture Growth, TVS Capital, 360 ONE Assets, and Nexus Venture Partners.

The timing is notable. The funding was announced during the India AI Impact Summit, an event of global scale where policymakers, international tech firms, and investors are debating how India should build its AI future. Neysa’s raise places infrastructure, not consumer apps, at the center of that conversation.

The capital will fund the deployment of roughly 20,000 graphics processing units across data centres in India. That expansion aims to address a key bottleneck in the country’s AI ecosystem: limited access to high-performance compute.

What does Neysa do, exactly?

Neysa operates in a part of the AI stack that rarely grabs headlines. It does not build chatbots, copilots, or consumer-facing AI tools. Instead, it focuses on the infrastructure layer that powers modern AI systems. At the core of its business is Velocis, a GPU-as-a-Service platform. Through Velocis, enterprises can rent high-performance computing resources on demand, much like cloud services, but optimized for AI workloads.

Training and running large AI models requires massive parallel computing power. This power usually comes from specialised chips, most commonly produced by Nvidia. These chips are expensive and often in short supply. Neysa addresses this by purchasing GPUs in bulk, installing them in domestic data centres, and offering access through its orchestration platform. Companies can train models, run inference, and scale capacity without owning or maintaining physical servers.

In practical terms, this means enterprises avoid large upfront capital expenditure. They also gain predictable performance and local data hosting, both critical for regulated industries.

Why are investors backing such a capital-heavy model?

Neysa was founded in 2023 by Sharad Sanghi and Anindya Das. Sanghi previously built Netmagic Solutions into a major managed hosting provider before it was acquired by NTT Communications in 2012. Das served as Netmagic’s chief technology officer.

That background matters. Investors see proven experience in building and operating large-scale infrastructure as essential for a business that requires billions in hardware investment.

The funding announcement makes this clear. Blackstone will partner with Sharad Sanghi to accelerate Neysa’s growth and scale-up plans. The firm has framed the investment as part of its broader strategy of backing foundational AI infrastructure.

Blackstone affiliates already hold stakes in global data centre and AI infrastructure platforms, including QTS, AirTrunk, CoreWeave, and Firmus. Neysa fits squarely into that portfolio.

Why is Neysa compared to AWS and Azure?

Neysa is increasingly described as a domestic alternative to global cloud providers such as Amazon Web Services and Microsoft Azure. The comparison is functional, not cosmetic.

Hyperscalers offer AI processing as part of broad cloud ecosystems. Neysa, by contrast, designs its platform specifically around GPU-intensive workloads. Velocis focuses on high-performance model training, large GPU cluster management, and scalable inference.

For Indian enterprises that require local data hosting, regulatory compliance, and dedicated AI performance, Neysa effectively functions as an AI-focused cloud provider. The difference is geographic and strategic. Neysa is built for India’s infrastructure constraints and policy environment.

This positioning becomes critical as enterprises move from experimentation to production-grade AI deployments.

Why does India need domestic AI compute?

India currently has an estimated 50,000 to 60,000 GPUs available for commercial AI workloads. That number is small relative to demand. Today, many Indian firms rely on overseas cloud providers to run AI models. For retail users, this setup causes little friction. For enterprises, it raises concerns around latency, data sovereignty, compliance, and long-term costs.

Hosting sensitive data abroad is especially problematic for sectors such as banking, telecom, healthcare, and government services. Regulations often require data residency. Performance requirements also favor low-latency, local infrastructure.

By deploying GPUs within India, Neysa positions itself as a “sovereign AI” provider. Its infrastructure allows enterprises to build and deploy AI systems without exporting sensitive data. This approach aligns closely with the goals of the IndiaAI Mission, which aims to expand domestic computing capacity and reduce reliance on foreign infrastructure.

What did Blackstone and Neysa say about the deal?

The official announcement includes unusually direct language about India’s AI ambitions.

Amit Dixit, Head of Asia Private Equity at Blackstone, said: “Over the past two decades, we have been committed to building businesses that build India, and this investment brings that to life. It reinforces Blackstone’s focus on backing the essential ‘picks and shovels’ of AI globally, including in India, a key market for Blackstone.”

Ganesh Mani, Senior Managing Director at Blackstone Private Equity, added: “Digital infrastructure is one of our highest conviction investment themes globally. This investment positions Neysa to play a meaningful role in advancing AI infrastructure in India and enables businesses and public institutions to deploy AI technologies more effectively as AI adoption accelerates.”

Sharad Sanghi, Co-Founder and CEO of Neysa, framed the funding in national terms: “India’s AI ambition requires production grade infrastructure built and operated at scale. Neysa is focused on delivering the execution layer of sovereign compute, and AI research enablement and adoption in alignment with the goals of IndiaAI Mission.”

What did Sanghi reveal at the India AI Impact Summit?

Speaking to The Hindu on the sidelines of the India AI Impact Summit, Sanghi emphasized why demand for local AI infrastructure is rising.

“Sovereignty, latency and compliance” are driving enterprise demand for locally installed AI infrastructure, he said. He noted that most AI inferencing still happens outside India. While that may be acceptable for consumer use, it creates discomfort for enterprises deploying large language models internally.

“Almost all the people who provide development platform want to set up increasing clusters in India,” Sanghi said. He added that tax incentives for data centres processing foreign data could position India as a regional AI hub.

On scale, Sanghi offered a striking projection: “We believe that today there are anywhere from 50 to 60,000 GPUs deployed in the country, and we believe in the next 2-3 years it will be 3 million, so it is going to be a 30-fold explosion.”

Who are Neysa’s competitors?

Neysa operates in a crowded but still immature market. Domestically, it competes with players such as Yotta Data Services and E2E Networks. Globally, hyperscalers remain formidable rivals due to scale and ecosystem depth.

However, Neysa’s differentiation lies in focus. It is not trying to be a general-purpose cloud. It is building an AI-first infrastructure stack designed around GPUs, orchestration software, and enterprise requirements. Its success will depend on hardware supply chains, utilisation rates, and the ability to deliver consistent performance at scale.

What does this funding mean for India’s AI future?

Neysa’s $1.2 billion raise is not just a startup story. It signals a shift in how AI development is being financed and localized in India.

Infrastructure, long seen as a constraint, is now attracting global capital. The timing, during the India AI Impact Summit, reinforces the message that AI sovereignty has moved from policy rhetoric to deployment.

If Neysa succeeds, it could reduce India’s dependence on foreign AI infrastructure. It could also lower barriers for enterprises and startups seeking to build production-grade AI systems locally. As India debates its role in the global AI economy, Neysa’s funding round offers a concrete answer — control the compute, and the ecosystem follows.