Larsen & Toubro has partnered with NVIDIA to build what is being described as India’s largest artificial intelligence infrastructure project. The announcement was made at the India AI Summit in February 2026 and has drawn wide attention from technology and industry leaders. The goal is to create a massive “AI factory” inside the country so that advanced computing power can be built, managed, and used within national borders.
This project supports the IndiaAI Mission, which focuses on developing strong local computing capacity. Instead of depending heavily on foreign data centers, India aims to create its own large-scale systems that can train and run advanced AI models securely.
The project is designed to grow in phases. Larsen & Toubro plans to expand its existing campus in Chennai to around 30 megawatts of AI computing capacity. In addition, a new 40 megawatt data center is planned in Mumbai. Over time, the total infrastructure could scale up to a gigawatt level, which would place it among the largest AI compute facilities in the region.
A gigawatt-scale AI center means extremely high computing power. Such facilities are needed to train large language models, power generative AI tools, and handle complex industrial data. The design will include advanced cooling systems, high-density racks, and powerful networking equipment.
Larsen & Toubro will take care of the engineering, building work, and day to day operations of the campus. The company has many years of experience in handling large projects in areas like energy, heavy industry, and technology parks.
NVIDIA will supply powerful graphics processing units, fast networking systems, storage tools, and AI software. These are important for running modern artificial intelligence systems smoothly. By bringing together strong construction skills and advanced computing technology, the partnership plans to deliver complete AI solutions in one place.
India’s digital economy is growing fast. Businesses, startups, and government departments are increasingly using artificial intelligence for language models, design tools, healthcare analysis, manufacturing automation, and financial services. These applications require strong computing systems that can process large amounts of data quickly.
There is also a growing need for data sovereignty. Many organizations prefer that sensitive information remain within the country. A large domestic AI center can provide lower latency, better security control, and more predictable performance compared to overseas servers.
The announcement comes at a time when several major Indian groups are committing billions of dollars to artificial intelligence and data infrastructure. Reports from the summit indicate that planned investments across sectors could reach hundreds of billions of dollars over the next decade.
Experts believe that local AI capacity will help reduce reliance on foreign cloud providers. It may also encourage global companies to run workloads in India. This can create jobs for engineers, data scientists, and infrastructure specialists.
Building such a large computing center is not easy. It needs steady electricity, good cooling systems, and fast internet connections. A gigawatt level facility uses a huge amount of power, so clean energy and a stable power grid are very important.
There can also be delays in getting advanced computer chips and other hardware. Skilled workers are needed to run and maintain these powerful systems. Good planning and proper management will be key to making the project successful.
If the project is completed as planned, the partnership between Larsen & Toubro and NVIDIA could greatly improve India’s position in the global AI space. A large AI factory like this would allow advanced AI models and business solutions to be developed and used inside the country on a big scale.
This project shows that engineering companies and global chip makers are now working together to meet the growing need for artificial intelligence. With strong government support and continued investment, India could become an important center for large AI computing in the next few years.