AM Intelligence, backed by Greenko’s founders, plans to invest $8 billion to build a 1-gigawatt AI compute network. The company will launch its first 30-MW facility in Hyderabad by early 2027 using 9,000 NVIDIA systems. While this highlights significant capital spending in the AI infrastructure sector, the company is private and not listed on Indian stock exchanges.
AM Intelligence, a private Indian infrastructure firm founded by the team behind the Greenko Group, has announced a massive $8 billion investment roadmap to establish a 1-gigawatt (GW) AI compute portfolio. The company intends to serve the growing Compute-as-a-Service (CaaS) market, providing dedicated GPU clusters to developers and global cloud providers. The first phase involves a 30-MW compute hub in Hyderabad, which the company expects to be operational by early 2027.
To power this facility, the company has secured a binding order for 9,000 NVIDIA Vera Rubin systems. The project is designed with a heavy focus on high-density infrastructure, utilizing liquid-cooling technology to manage the extreme heat generated by these chips. The company stated that this approach aims to reduce water dependency and energy usage compared to traditional data center designs, which often struggle with the efficiency requirements of specialized AI training hardware.
Beyond the initial Hyderabad hub, the firm has outlined a strategy to scale its capacity across locations in Noida, Visakhapatnam, and Maharashtra, with further expansion plans targeting international markets in Malaysia, Finland, and the United States. A significant portion of this capacity is intended for global hyperscalers and cloud providers, with initial capacity already reportedly secured by a US-based client.
For Indian investors following the broader data center and AI theme, it is important to note that AM Intelligence is a private entity and is not listed on the NSE or BSE. As such, there is no direct way to invest in this specific company. However, the scale of this project serves as a sign of the massive capital expenditure occurring within the domestic digital infrastructure sector.
Investors should be aware of the substantial risks involved in such large-scale projects. Building and maintaining 1 GW of AI compute capacity requires enormous upfront spending, leading to high debt and financing requirements. Additionally, the company faces significant execution risks, including long supply chain backlogs for high-end NVIDIA GPU clusters, which are currently in extremely high demand globally. There are also broader industry concerns regarding the sustainability of the current AI infrastructure boom, as many projects in this space rely on aggressive financing and assume sustained high demand for computing power.
The most important updates to follow will be the actual commissioning timeline of the Hyderabad facility and whether the company can maintain its project execution speed in the face of tight global hardware supplies and high operational energy costs.