Sify Announces Pay-Per-Use Model At Nvidia-Certified AI-Ready Data Centres In India

Sify Technologies Ltd. has announced the launch of a pay-per-use model to support the requirements for AI cloud services. This follows the recent expansion of Sify's portfolio of DGX-ready data centres, certified for up to 130 KW/rack capacity under Nvidia's DGX-Ready Data Centre programme.

Sify's latest hyperscale data centres in Chennai and Noida have now been certified by Nvidia, joining Sify's Navi Mumbai data centre that was certified in 2024. Sify will offer the colocation pricing programme at all three of these campus locations.

The hourly pricing model is inclusive of hosting, power and infrastructure costs. By pricing its services on an hourly basis, Sify is removing the entry-cost barrier and fixed-cost infrastructure risk, enabling its GPU Cloud partners to set up and respond quickly to the growing AI market.

Sify's converged ICT ecosystem will also offer services like global connectivity, premium IT infrastructure support and managed services. Initially, Sify will support the Nvidia H100, H200, B200, GB200 NVL72, and GB300 NVL72 platforms, including liquid-cooled variants.

"Sify already has the most extensive footprint of Nvidia-certified data centres and a network connectivity with the lowest latency to hyperscale clouds," said Sharad Agarwal, CEO of Sify Infinit Spaces Ltd., the data centre subsidiary of Sify Technologies. "Now, by introducing colocation pricing on an hourly basis, we aim to make it much faster and easier to deploy these platforms in India to support on-demand applications."

"Sify’s pay-per-use colocation model, built on Nvidia-certified platforms, is a timely innovation that removes traditional barriers to AI adoption," added Rajiv Ranjan, associate research director of IDC Asia Pacific. "By enabling global enterprises to tap into India's AI capabilities through scalable, high-performance infrastructure, Sify is well positioned to support domestic innovation and position India as a global hub for AI workloads and transformation."