Blackstone and co-investors announced Monday they will invest up to $600 million in equity in Indian AI infrastructure startup Neysa, giving Blackstone a majority stake, while Neysa plans to raise an additional $600 million in debt financing for a total $1.2 billion capital raise to deploy more than 20,000 GPUs across India and establish the country as a globally relevant AI compute destination.
The Mumbai-headquartered company, which provides GPU-based AI infrastructure to enterprises and government entities, will use the funding to scale large-scale GPU clusters including compute, networking, and storage infrastructure. Co-investors include Teachers' Venture Growth, TVS Capital, 360 ONE Asset, and Nexus Venture Partners.
India GPU Capacity Expected to Scale 30x
Ganesh Mani, a senior managing director at Blackstone Private Equity, said his firm estimates India currently has fewer than 60,000 GPUs deployed and expects the figure to scale nearly 30 times to more than 2 million GPUs in the coming years. The expansion is being driven by government demand, enterprises in regulated sectors like financial services and healthcare that need to keep data local, and AI developers building models within India.
"Digital infrastructure is one of our highest conviction investment themes globally," Mani said. "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."
The announcement coincides with the India AI Impact Summit in New Delhi, where global AI leaders including OpenAI CEO Sam Altman, Anthropic CEO Dario Amodei, and Alphabet CEO Sundar Pichai are gathering to discuss India's role in shaping global AI development.
Production-Grade Infrastructure for Sovereign Compute
Founded in 2023, Neysa designs and develops AI systems deployed and operated within India, providing purpose-built and cost-effective GPU-based AI infrastructure that enables enterprises and institutions to train, fine-tune, and deploy AI workloads. Customers span financial services, technology, healthcare, and public services sectors.
"India's AI ambition requires production-grade infrastructure built and operated at scale," said Sharad Sanghi, co-founder and CEO of Neysa. "Neysa is focused on delivering the execution layer of sovereign compute, AI research enablement, and adoption in alignment with the goals of the IndiaAI Mission. We seek to provide performance certainty and data assurance, enabling enterprises, hyperscalers, and global AI labs to deploy and scale reliable AI infrastructure in India."
Sanghi told TechCrunch the bulk of the new capital will be used to deploy large-scale GPU clusters, while a smaller portion will go toward research and development and building out Neysa's software platforms for orchestration, observability, and security. The company aims to more than triple its revenue next year as demand for AI workloads accelerates, with ambitions to expand beyond India over time.
Blackstone's AI Infrastructure Push
The investment builds on Blackstone's broader push into data center and AI infrastructure globally. The firm has previously invested in AI cloud providers CoreWeave and Firmus, with Firmus securing $10 billion from Blackstone earlier this month. Blackstone's portfolio also includes QTS, AirTrunk, and other digital infrastructure assets.
"Over the past two decades, we have been committed to building businesses that build India, and this investment brings that to life," said Amit Dixit, Head of Asia Private Equity at Blackstone. "It reinforces Blackstone's focus on backing the essential 'picks and shovels' of AI globally, including in India, a key market for Blackstone."
Founded in 2023, Neysa raised approximately $50 million in prior funding before the Blackstone-led round. The company employs 110 people across offices in Mumbai, Bengaluru, and Chennai. In April 2025, Neysa announced it was teaming up with NTT Data and the Telangana government to establish a 400MW GPU cluster comprising 25,000 GPUs, though GPU types were not specified.
Global AI labs, many of which count India among their largest user bases, are increasingly looking to deploy computing capacity closer to users to reduce latency and meet data localization requirements, driving demand for Indian AI infrastructure providers often referred to as "neo-clouds."
