Tech Data Partners with NVIDIA to Distribute AI Solutions in India

Tech Data Advanced Private Limited, a TD SYNNEX company, signed a new distribution agreement with NVIDIA on Wednesday to offer its data centre and enterprise AI solutions in India.

The partnership will give Indian businesses access to NVIDIA’s full-stack AI tools, including its advanced data centre GPUs, making it easier to adopt and deploy AI across different industries.

“Complementing NVIDIA’s advanced AI solutions with our homegrown offerings and a robust partner ecosystem, this collaboration will enable us to help Indian businesses bridge infrastructure gaps, scale AI initiatives, and maximise innovation across the IT ecosystem,” Sundaresan K, vice president and country general manager at Tech Data said.

NVIDIA’s platform includes a suite of tools and software that support developers in building AI-powered applications. Among these are the CUDA-X libraries, designed to speed up data processing and machine learning, and NVIDIA NIM microservices, which help developers build AI assistants and productivity plug-ins faster.

Tech Data plans to use its network of local partners to support customers, simplify AI adoption, and help bring NVIDIA’s solutions to market quickly. The company will also tap into recent partnerships, such as its collaboration with Dell’s AI Factory and several software vendors, to open up more opportunities for AI in India.

Tech Data already works with NVIDIA in Europe and North America. Expanding the partnership to India is part of its ongoing push to make AI more accessible through its Destination AI programme.

Meanwhile, at GTC 2025, NVIDIA unveiled two new personal AI supercomputers—the DGX Spark and DGX Station—designed to tackle demanding AI workloads. 

Powered by the NVIDIA Grace Blackwell platform, these systems are built to support AI developers, researchers, data scientists, and students in prototyping, fine-tuning, and running inference on large language models right from their desktops.

The models can be run locally or seamlessly deployed to any cloud platform.